Podcasts about climate uncertainty

Amy MacIver is joined by Dr Peter Johnston, climate scientist at UCT’s Climate System Analysis Group (CSAG), to explore a question many listeners ask daily, “How accurate are our weather services, really?” With decades of experience in climate forecasting and climate risk, Dr Johnston explains why public scepticism is understandable—but often misplaced. See omnystudio.com/listener for privacy information.

Willkommen zu einer neuen Folge meines Podcasts! In dieser Episode begrüße ich den renommierten Experten Franz Josef Radermacher vor einem besonderen Gast an der Wand: Albert Einstein. Was hat Einstein mit Energie zu tun? Warum ist Energie die Grundlage menschlichen Wohlstands? Und wie gestalten wir eine nachhaltige Zukunft in einer global vernetzten Welt? Dieses Gespräch nimmt uns mit auf eine Reise durch die Geschichte der Energienutzung, die Herausforderungen der Energiewende und die geopolitischen Dimensionen, die oft übersehen werden. Prof. Radermacher ist Vorstand des Forschungsinstituts für anwendungsorientierte Wissensverarbeitung, stellv. Vorstandsvorsitzender von Global Energy Solutions e. V. (Ulm), emerit. Professor für Informatik, Universität Ulm, 2000 – 2018 Mitglied des Wissenschaftlichen Beirats beim Bundesministerium für Verkehr und digitale Infrastruktur (BMVI); er ist Ehrenpräsident des Ökosozialen Forum Europa, Wien, Mitglied des UN-Council of Engineers for the Energy Transition (CEET) sowie Mitglied des Club of Rome, Winterthur. Was hat Einstein mit diesem Gespräch zu tun? Wir beginnen mit der Frage, welche Rolle Energie in unserer Gesellschaft spielt sowie der Tatsache, dass vielen Menschen, vermutlich den meisten, nicht klar ist, was unsere Gesellschaft antreibt? So waren 2023 mehr als 81 Prozent des gesamten weltweiten Energieverbrauchs durch fossile Quellen gedeckt, und die Menge an fossilen Energieträgern wächst ständig. Wie hat Energie die Menschheit geprägt? Welche Energiequellen hatten wir früher und welchen Einfluss hatte die Veränderung der Energieträger auf unsere Gesellschaft und unseren Lebensstandard? Warum dominieren fossile Brennstoffe heute noch? Kann Energie Armut bekämpfen? Ist es Energie, die Wohlstand schafft? Warum sind zwei oft übersehene Parameter von so großer Bedeutung: Energiedichte und Platzbedarf?  Kernkraftwerke benötigen wenig Fläche im Vergleich zu Windrädern oder Photovoltaik:  »Da ist ja ein Faktor 100 dazwischen.« […] »Weil auch Fläche ein extrem knappes Gut ist, ist es problematisch, wenn man eine Energie mit ziemlich niedriger Dichte hat.« Gleichzeitig sind Energie und Emissionen, besonders Treibhausgase, globale Phänomene, die lokal nicht zu lösen sind. »Von 2004 bis 2023 haben die globalen Investitionen in Wind und Solar rund 4 Billionen Dollar ausgemacht, und trotzdem sind die fossilen Energieträger dreimal schneller gewachsen.“ Zudem: „In den großen Industrienationen […] eine Reduktion der CO2-Emissionen, aber gleichzeitig einen Zuwachs in Indien und China, der diese Reduktionen um das Faktor 5 überschattet.«, Robert Bryce Überrascht uns China? China hat mittlerweile die EU auch in den Pro-Kopf-Emissionen überholt. Was passiert, wenn Schwellenländer folgen? »An China kann man erkennen, was passiert, wenn ein armes Land versucht, Wohlstand aufzubauen. Und das geht bis heute nur mit fossilen Energieträgern.« Sind schnelle Lösungen gefährlich? Großinfrastruktur, Energiesysteme sind immer eine Frage von Jahrzehnten. Wenn wir versuchen, Dinge hier über das Knie zu brechen, ist die Wahrscheinlichkeit, dass Sie große und extrem teure Fehler machen, enorm. Außerdem stellt sich die Frage, welche Relevanz Europa überhaupt noch hat? Welche Maßnahmen gegen den Klimawandel könnten erfolgreich sein? Was wurde etwa in Baku beschlossen? Funktionieren Transferzahlungen? Warum scheitert eine Renewables Only Strategie zwangsläufig? »Die Idee, Renewables Only, ist ja eine von Deutschland immer wieder propagierte Idee.[… Es] ist nur eine Methode, [Entwicklungsländer] arm zu halten« Aber was ist die Alternative? Was ist Carbon Capture? Was ist die Rolle von Kernkraft? Welche Mischung verschiedener Verfahren ist sinnvoll? Zuletzt diskutieren wir über Strom vs. Moleküle und den All-Electric-Irrtum. Damit verbunden ist der Irrglaube, Wasserstoff könnte das Renable-Desaster lösen.  Welche geopolitischen Herausforderungen sind mit diesen Themen verknüpft? Ist Prof. Radermacher optimistisch — für Europa, die Welt? Was könnte man jungen Menschen empfehlen? Referenzen Andere Episoden Episode 109: Was ist Komplexität? Ein Gespräch mit Dr. Marco Wehr Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg Episode 95: Geopolitik und Militär, ein Gespräch mit Brigadier Prof. Walter Feichtinger Episode 94: Systemisches Denken und gesellschaftliche Verwundbarkeit, ein Gespräch mit Herbert Saurugg Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry Episode 81: Energie und Ressourcen, ein Gespräch mit Dr. Lars Schernikau Episode 73: Ökorealismus, ein Gespräch mit Björn Peters Episode 70: Future of Farming, a conversation with Padraic Flood Episode 62: Wirtschaft und Umwelt, ein Gespräch mit Prof. Hans-Werner Sinn Prof. Radermacher Forschungsinstitut für anwendungsorientierte Wissensverarbeitung/n Global Energy Solutions Prof. Radermacher im Vorstand der Global Energy Solutions All In: Energie und Wohlstand für eine wachsende Welt, Murmann (2024) Fachliche Referenzen Vaclav Smil, How the World Really Works, Penguin (2022) Vaclav Smil, Net Zero 2050, Fraser Institute (2024) Robert Bryce, The Energy Transition Isn't (2023) Robert Bryce, Numbers Don't Lie (2024)

In this episode, I had the privilege of speaking with John Ioannidis, a renowned scientist and meta-researcher whose groundbreaking work has shaped our understanding of scientific reliability and its societal implications. We dive into his influential 2005 paper, Why Most Published Research Findings Are False, explore the evolution of scientific challenges over the past two decades, and reflect on how science intersects with policy and public trust—especially in times of crisis like COVID-19. We begin with John taking us back to 2005, when he published his paper in PLOS Medicine. He explains how it emerged from decades of empirical evidence on biases and false positives in research, considering factors like study size, statistical power, and competition that can distort findings, and why building on shaky foundations wastes time and resources. “It was one effort to try to put together some possibilities, of calculating what are the chances that once we think we have come up with a scientific discovery with some statistical inference suggesting that we have a statistically significant result, how likely is that not to be so?” I propose a distinction between “honest” and “dishonest” scientific failures, and John refines this. What does failure really mean, and how can they be categorised? The discussion turns to the rise of fraud, with John revealing a startling shift: while fraud once required artistry, today's “paper mills” churn out fake studies at scale. We touch on cases like Jan-Hendrik Schön, who published prolifically in top journals before being exposed, and how modern hyper-productivity, such as a paper every five days, raises red flags yet often goes unchecked. “Perhaps an estimate for what is going on now is that it accounts for about 10%, not just 1%, because we have new ways of massive… outright fraud.” This leads to a broader question about science's efficiency. When we observe scientific output—papers, funding—grows exponentially but does breakthroughs lag? John is cautiously optimistic, acknowledging progress, but agrees efficiency isn't what it could be. We reference Max Perutz's recipe for success: “No politics, no committees, no reports, no referees, no interviews; just gifted, highly motivated people, picked by a few men of good judgement.” Could this be replicated in today's world or are we stuck in red tape? “It is true that the progress is not proportional to the massive increase in some of the other numbers.” We then pivot to nutrition, a field John describes as “messy.” How is it possible that with millions of papers, results are mosty based on shaky correlations rather than solid causal evidence? What are the reasons for this situation and what consequences does it have, e.g. in people trusting scientific results? “Most of these recommendations are built on thin air. They have no solid science behind them.” The pandemic looms large next. In 2020 Nassim Taleb and John Ioannidis had a dispute about the measures to be taken. What happened in March 2020 and onwards? Did we as society show paranoid overreactions, fuelled by clueless editorials and media hype? “I gave interviews where I said, that's fine. We don't know what we're facing with. It is okay to start with some very aggressive measures, but what we need is reliable evidence to be obtained as quickly as possible.” Was the medicine, metaphorically speaking, worse than the disease? How can society balance worst-case scenarios without paralysis. “We managed to kill far more by doing what we did.” Who is framing the public narrative of complex questions like climate change or a pandemic? Is it really science driven, based on the best knowledge we have? In recent years influential scientific magazines publish articles by staff writers that have a high impact on the public perception, but are not necessarily well grounded: “They know everything before we know anything.” The conversation grows personal as John shares the toll of the COVID era—death threats to him and his family—and mourns the loss of civil debate. He'd rather hear from critics than echo chambers, but the partisan “war” mindset drowned out reason. Can science recover its humility and openness? “I think very little of that happened. There was no willingness to see opponents as anything but enemies in a war.” Inspired by Gerd Gigerenzer, who will be a guest in this show very soon, we close on the pitfalls of hyper-complex models in science and policy. How can we handle decision making under radical uncertainty? Which type of models help, which can lead us astray? “I'm worried that complexity sometimes could be an alibi for confusion.” This conversation left me both inspired and unsettled. John's clarity on science's flaws, paired with his hope for reform, offers a roadmap, but the stakes are high. From nutrition to pandemics, shaky science shapes our lives, and rebuilding trust demands we embrace uncertainty, not dogma. His call for dialogue over destruction is a plea we should not ignore. Other Episodes Episode 116: Science and Politics, A Conversation with Prof. Jessica Weinkle Episode 112: Nullius in Verba — oder: Der Müll der Wissenschaft Episode 109: Was ist Komplexität? Ein Gespräch mit Dr. Marco Wehr Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg Episode 106: Wissenschaft als Ersatzreligion? Ein Gespräch mit  Manfred Glauninger Episode 103: Schwarze Schwäne in Extremistan; die Welt des Nassim Taleb, ein Gespräch mit Ralph Zlabinger Episode 94: Systemisches Denken und gesellschaftliche Verwundbarkeit, ein Gespräch mit Herbert Saurugg Episode 92: Wissen und Expertise Teil 2 Episode 90: Unintended Consequences (Unerwartete Folgen) Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry Episode 67: Wissenschaft, Hype und Realität — ein Gespräch mit Stephan Schleim References Prof. John Ioannidis at Stanford University  John P. A. Ioannidis, Why Most Published Research Findings Are False, PLOS Medicine (2005) John Ioannidis, A fiasco in the making? As the coronavirus pandemic takes hold, weare making decisions without reliable data (2020) John Ioannidis, The scientists who publish a paper every five days, Nature Comment (2018) Hanae Armitage, 5 Questions: John Ioannidis calls for more rigorous nutrition research (2018) John Ioannidis, How the Pandemic Is Changing Scientific Norms, Tablet Magazine (2021) John Ioannidis et al, Uncertainty and Inconsistency of COVID-19 Non-Pharmaceutical1Intervention Effects with Multiple Competitive Statistical Models (2025) John Ioannidis et al, Forecasting for COVID-19 has failed (2022) Gerd Gigerenzer, Transparent modeling of influenza incidence: Big data or asingle data point from psychological theory? (2022) Sabine Kleinert, Richard Horton, How should medical science change? Lancet Comment (2014) Max Perutz quotation taken from Geoffrey West, Scale, Weidenfeld & Nicolson (2017) John Ioannidis: Das Gewissen der Wissenschaft, Ö1 Dimensionen (2024)  

Todays guest is Jessica Weinkle, Associate Professor of Public Policy at the University of North Carolina Wilmington, and Senior Fellow at The Breakthrough Institute.  In this episode we explore a range of topics and we start with the question: What is ecomodernism, and how does The Breakthrough Institute and Jessica interpret it?  “It's not a movement of can'ts” Why are environmentalists selective about technology acceptance? Why do we assess  ecological impact through bodies like the IPCC and frameworks like Planetary Boundaries? Are simplified indicators of complex systems genuinely helpful or misleading?  Is contemporary science more about appearances than substance, and do scientific journals serve more and more as advocacy platforms than fact-finding missions? How much should activism and science intersect? To what extent do our beliefs influence science, and vice versa, especially when financial interests are at play in fields like climate science? Can we trust scientific integrity when narratives are tailored for publication, like in the case of Patrick Brown? What responsibilities do experts have when consulting in political spheres, and should they present options or advocate for specific actions?  How has research publishing turned into big business, and what does this mean for the pursuit of truth?  “Experts should always say: here are your options A, B, C...; not: I think you should do A” How does modeling shape global affairs? When we use models for decision-making, are we taking them too literally, or should we focus on their broader implications?  “To take a model literally is not to take it seriously […] the models are useful to give us some ideas, but the specificity is not where we should focus.” What's the connection between scenario building, modeling, and risk management?  “There is an institutional and professional incentive to make big claims, to draw attention. […] That's what we get rewarded for. […] It does create an incentive to push ideas that are not necessarily the most helpful ideas for addressing public problems.” How does the public venue affect scientists, and does the incentive to make bold claims for attention come at the cost of practical solutions? What lessons should we have learned from cases like Jan Hendrik Schön, and why haven't we?  “There is an underappreciation for the extent to which scholarly publishing is a business, a big media business. It's not just all good moral virtue around skill and enlightenment. It's money, fame and fortune.” Finally, are narratives about future scenarios fueling climate anxiety, and how should we address this in science communication and policy-making? “There is a freedom in uncertainty and there is also an opportunity to create decisions that are more robust to an unpredictable future. The more that we say we are certain ... the more vulnerable we become to the uncertainty that we are pretending is not there.” Other Episodes Episode 109: Was ist Komplexität? Ein Gespräch mit Dr. Marco Wehr Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg Episode 90: Unintended Consequences (Unerwartete Folgen) Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry Episode 79: Escape from Model Land, a Conversation with Dr. Erica Thompson Episode 76: Existentielle Risiken Episode 74: Apocalype Always Episode 70: Future of Farming, a conversation with Padraic Flood Episode 68: Modelle und Realität, ein Gespräch mit Dr. Andreas Windisch Episode 60: Wissenschaft und Umwelt — Teil 2 Episode 59: Wissenschaft und Umwelt — Teil 1 References Jessica Weinkle Jessica on Substack Jessica at The Breakthrough Institute Jessica at the Department of Public and International Affairs (UNCW) The Breakthrough Journal Planetary Boundaries (Stockholm Resilience Centre) Patrick T. Brown, I Left Out the Full Truth to Get My Climate Change Paper Published, The FP (2023) Roger Pielke Jr., What the media won't tell you about . . . hurricanes (2022) Roger Pielke Jr., "When scientific integrity is undermined in pursuit of financial and political gain" (2023) Many other excellent articles Roger Pielke on his Substack The Honest Broker Jessica Weinkle, Model me this (2024) Jessica Weinkle, How Planetary Boundaries Captured Science, Health, and Finance (2024) Jessica Weinkle, Bias. Undisclosed conflicts of interest are a serious problem in the climate change literature (2025) Marcia McNutt, The beyond-two-degree inferno, Science Editorial (2015) Scientific American editor quits after anti-Trump comments, Unherd (2024) Erica Thompson, Escape from Model Land, Basic Books (2022)  

In part one of Red Eye Radio with Gary McNamara and Eric Harley, the guys begin by discussing climate change and the uncertainty displayed in tragic fails such as the lack of water in the LA wildfires. Also more confusion from the radical transgenders..this time from Australia regarding the inclusion of "male lesbians", Biden's overuse of his "pardoning pen", analyzing the Hitler salute, the return of Trump's late night tweets, the left adopts an aggressive narrative, international tariffs and much more. For more talk on the issues that matter to you, listen on radio stations across America Monday-Friday 12am-5am CT (1am-6am ET and 10pm-3am PT), download the RED EYE RADIO SHOW app, asking your smart speaker, or listening at RedEyeRadioShow.com. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Join our Mailing List - https://www.mapitforward.coffee/mailinglistIntroduction to Regenerative Coffee Farming is now Available On-Demand at https://ondemand.mapitforward.coffee for as little as $10. Why not grab a gift card for your team, suppliers or favorite coffee human******************************Welcome to the 2nd episode of a five-part series on The Daily Coffee Pro by Map It Forward Podcast, hosted by Map It Forward founder, Lee Safar.Our guest on the podcast in this series is Alejandro Cadena, CEO of Caravela Coffee - a globally recognized green coffee exporter out of Latin America and an importer into consuming regions around the world.In this discussion, Alejandro and Lee discuss the definitive nature of the year ahead, 2025. This series explores what we should expect, how we got here, and why this is a year that is unlike any other in the history of the coffee industry.The episodes in this series are:1. Change Is Coming For The Coffee Industry in 2025 - https://youtu.be/R7YGoGxes2w2. The Major Forces At Play in The Coffee Industry in 2025 - https://youtu.be/gmllrkmAI_k3. What To Expect from 2025 In Coffee - https://youtu.be/NqU-ZHRMago4. Stakeholder Collaboration in the Coffee Supply Chain - https://youtu.be/5QP-UJgs-Ks5. Predictions for 2025 in Coffee - https://youtu.be/UG8XgyCtx5AIn this episode of The Daily Coffee Pro by Map It Forward, host Lee Safar discusses the critical role of risk management in the coffee industry with guest Alejandro Cadena from Caravela. They explore the major forces expected to impact the coffee industry in 2025, including climate change, political uncertainty, and logistical challenges. The conversation underscores the importance of managing supply and price risks rather than focusing on uncontrollable variables. Additionally, the episode highlights the need for sustainable business practices, collaborative partnerships, and the significance of understanding the industry's financial models. Tune in to gain insights into how to navigate the unpredictable future of coffee production and stay ahead in the market.00:00 Managing Risks in the Coffee Industry00:49 Exciting News: Regenerative Coffee Farming Workshops02:10 Introduction to the Podcast and New Year Wishes02:48 Discussion with Alejandro Cadena: Forces Shaping 2025 in Coffee03:33 Climate Uncertainty and Its Impact on Coffee06:45 Political Uncertainty and Coffee Trade10:37 Logistical Challenges in Coffee Supply Chain12:36 The Importance of Managing Risks in Coffee17:53 The Reality of Coffee Business Economics22:54 Future of Coffee: Pricing and Business Models32:54 Conclusion and Next Episode Teaser Connect with Alejandro and Caravela Coffee here:https://caravela.coffee/enhttps://www.instagram.com/caravelacoffeehttps://www.linkedin.com/in/alejandro-c-74241a/••••••••••••••••••••••••••••••••

Join our Mailing List - https://www.mapitforward.coffee/mailinglistIntroduction to Regenerative Coffee Farming is now Available On-Demand at https://ondemand.mapitforward.coffee for as little as $10. Why not grab a gift card for your team, suppliers or favorite coffee human******************************Welcome to the 2nd episode of a five-part series on The Daily Coffee Pro by Map It Forward Podcast, hosted by Map It Forward founder, Lee Safar.Our guest on the podcast in this series is Alejandro Cadena, CEO of Caravela Coffee - a globally recognized green coffee exporter out of Latin America and an importer into consuming regions around the world.In this discussion, Alejandro and Lee discuss the definitive nature of the year ahead, 2025. This series explores what we should expect, how we got here, and why this is a year that is unlike any other in the history of the coffee industry.The episodes in this series are:1. Change Is Coming For The Coffee Industry in 2025 - https://youtu.be/R7YGoGxes2w2. The Major Forces At Play in The Coffee Industry in 2025 - https://youtu.be/gmllrkmAI_k3. What To Expect from 2025 In Coffee - https://youtu.be/NqU-ZHRMago4. Stakeholder Collaboration in the Coffee Supply Chain - https://youtu.be/5QP-UJgs-Ks5. Predictions for 2025 in Coffee - https://youtu.be/UG8XgyCtx5AIn this episode of The Daily Coffee Pro by Map It Forward, host Lee Safar discusses the critical role of risk management in the coffee industry with guest Alejandro Cadena from Caravela. They explore the major forces expected to impact the coffee industry in 2025, including climate change, political uncertainty, and logistical challenges. The conversation underscores the importance of managing supply and price risks rather than focusing on uncontrollable variables. Additionally, the episode highlights the need for sustainable business practices, collaborative partnerships, and the significance of understanding the industry's financial models. Tune in to gain insights into how to navigate the unpredictable future of coffee production and stay ahead in the market.00:00 Managing Risks in the Coffee Industry00:49 Exciting News: Regenerative Coffee Farming Workshops02:10 Introduction to the Podcast and New Year Wishes02:48 Discussion with Alejandro Cadena: Forces Shaping 2025 in Coffee03:33 Climate Uncertainty and Its Impact on Coffee06:45 Political Uncertainty and Coffee Trade10:37 Logistical Challenges in Coffee Supply Chain12:36 The Importance of Managing Risks in Coffee17:53 The Reality of Coffee Business Economics22:54 Future of Coffee: Pricing and Business Models32:54 Conclusion and Next Episode Teaser Connect with Alejandro and Caravela Coffee here:https://caravela.coffee/enhttps://www.instagram.com/caravelacoffeehttps://www.linkedin.com/in/alejandro-c-74241a/••••••••••••••••••••••••••••••••Support this podcast by supporting our Patreon:https://bit.ly/MIFPatreonThe Daily Coffee Pro by Map It Forward Podcast Host: Lee Safarhttps://www.mapitforward.coffeehttps://www.instagram.com/mapitforward.coffeehttps://www.instagram.com/leesafar••••••••••••••••••••••••••••••••

In the face of climate uncertainty, growers wonder which grape varieties will flourish in their regions in the future, or if any will grow there at all. Joel Harms, Ph.D. student in the Department of Bioresource Engineering at McGill University in Australia is using artificial intelligence to simulate the potential to grow pinot noire in different regions of the world that are currently considered too cool. The project mapped 1,300 varieties to 16 different points of climate data including temperature, precipitation, and growing degree days. The findings could play a crucial role in identifying the winegrowing regions of tomorrow. Resources:         207: Managing Catastrophic Loss in Vineyards: Lessons from Cyclone Gabrielle in New Zealand Cal-Adapt Development of a generative AI-based model for guiding grape variety selection under contemporary climate dynamics Generative AI for Climate-Adaptive Viticulture Development Joel Harms Google Scholar Page Mapping Global of the Potential for Pinot Noir Cultivation under Climate Uncertainty using Generative AI University of Adelaide Wine Economics Research Center Vineyard Team Programs: Juan Nevarez Memorial Scholarship - Donate SIP Certified – Show your care for the people and planet   Sustainable Ag Expo – The premiere winegrowing event of the year Vineyard Team – Become a Member Get More Subscribe wherever you listen so you never miss an episode on the latest science and research with the Sustainable Winegrowing Podcast. Since 1994, Vineyard Team has been your resource for workshops and field demonstrations, research, and events dedicated to the stewardship of our natural resources. Learn more at www.vineyardteam.org.   Transcript [00:00:00] Beth Vukmanic: In the face of climate uncertainty, growers wonder which grape varieties will flourish in their regions in the future, or if any, will grow there at all. [00:00:13] Welcome to Sustainable Wine Growing with the Vineyard Team, where we bring you the latest in science and research for the wine industry. I'm Beth Vukmanic, Executive Director. [00:00:23] In today's podcast, Craig McMillan, Critical Resource Manager at Niner Wine Estates, with longtime SIP certified vineyard and the first ever SIP certified winery. Speaks with Joel Harms, PhD student in the Department of Bioresource Engineering at McGill University in Australia. [00:00:42] Joel is using artificial intelligence to simulate the potential to grow Pinot Noir in different regions of the world that are currently considered too cool. [00:00:52] The project mapped 1, 300 varieties to 16 different points of climate data. including temperature, precipitation, and growing degree days. The findings could play a critical role in identifying the wine growing regions of tomorrow. [00:01:07] Want to be more connected with the viticulture industry but don't know where to start? Become a member of the Vineyard Team. Get access to the latest science based practices, experts, growers, and wine industry tools through both infield and online education so that you can grow your business. Visit vineyardteam. org and choose grower or business to join the community today. Now let's listen in. [00:01:34] Craig Macmillan: Our guest today is Joel Harms. He's a PhD student in the Department of Bioresources Engineering at McGill University. And today we're going to talk about mapping global future potential for Pinot Noir cultivation under climate uncertainty using generative AI. [00:01:51] Bye. Bye. This is a really interesting topic. I came across an abstract from a recent ASEV meeting and I was like, I just have to know more about this. This just sounds too interesting. But welcome to the podcast, Joel. [00:02:04] Joel Harms: Okay. Thank you very much. Thank you for having me. [00:02:06] Craig Macmillan: What got you interested in this topic in terms of this wine grape region? Stuff. [00:02:12] Joel Harms: I think it was more about I wanted to build models that are useful, I guess, broadly useful in vineyard management and like establishing new vineyards and like kind of covering some of the base problems. Initially, my thought was, how can we. see which grape varieties are alike. [00:02:32] How can we like make a representation of them in like a latent space. But then I found out , if I do that, that's, you know, somewhat useful, but if I take that just a step further, I could just connect it with climate data already. And then we would have a model that could, be used for prediction and it would be so I guess. How do I say like broad or general enough so that you could apply it in any environment. So like any climate can be used to predict any grape suitability matrix, which is quite nice. And so then I thought, no, let's do it. Let's try that. [00:03:11] Craig Macmillan: So your colleagues and yourself did some simulations, as we just mentioned specifically around Pinot Noir and the potential to grow it in different parts of the world that currently are considered too cool. Tell us exactly how you went about this. [00:03:25] Joel Harms: The abstract is kind of a case study on one application of, These models that we built. So we built very general grape variety recommender systems based on climate. And so we wanted to show a cool application globally. This can be applied to find regions that will be too hot in the future. [00:03:43] So we built the AI models first starting from looking at where grapes are grown and tying that together with what climate is there regionally. Unfortunately, you know, we can't use like very precise climate data because we don't have the exact location of each grape variety in each region. [00:04:02] Craig Macmillan: hmm. Yep. [00:04:03] Joel Harms: Yeah. So therefore, we use larger climate data. So like at 50 kilometer resolution, which is still helpful to, I think, gather overall trends, not so much, you know, to plan an individual vineyard probably, but just to see like in which areas maybe there would be. in the future interesting vineyard sites. [00:04:23] Just like kind of as like a pre guidance sort of model. And then we, tested it. We tried to validate this model and then we presented a first case study with Pinot Noir because we were presenting in Oregon at the ASEV conference. So I figured, you know, might as well do Pinot Noir if we're already in Oregon. [00:04:43] Craig Macmillan: Can you explain to me the artificial intelligence piece of this? I mean, you hear about it and you know, kind of what different types of AI do. I don't think a lot of people realize that, you know, that's a very general concept and people have designed particular tools for particular reasons. [00:05:01] So, in this case, what exactly was the AI component? What's inside the box, basically? How does it work? [00:05:07] Joel Harms: First off, I guess to explain for listeners , cause AI does get thrown around a lot and it's hard to know what that actually means. So when we're talking about AI, it's usually we're tying some sort of input data to some sort of output data. And we're teaching a very complicated mathematical function to map one to the other. [00:05:25] So like kind of a correlation. But it's not a simple correlation. That's why we need these models and that's why they're pretty fancy. [00:05:31] So in our case, we're using an AI that was inspired from the community of medical science, where similar models were used to connect, for example, the ECG measurements of a heart with like scans of the heart. [00:05:50] And then Trying to tie both of those datas together and to reconstruct them again to see if, like, you could find correlations between those and maybe if one of them is missing, you could, , predict what it would look like. And so, since this is a very similar problem, , and we have similar input data in the sense of, we have grapes, which grapes are grown where, and we have what is the climate there, roughly. [00:06:13] So we can tie that together and try to connect both of those types of data and then get an output of both of those types of data so that we can go from grapes to climate and climate to grapes in the same model. So we have these , you could say like four models. that are tied together at the center. So input grapes, input climate, then in the center where they get tied together and then output grapes, output climate. And so we train it to, reconstruct it from this combined space where we like, Scrunch it down, which is what the autoencoder does. [00:06:48] Craig Macmillan: So if, if I understand correctly, what we're talking about is , we know that we have the data and we know where wine grapes are grown, different types for different climates. Then we have the climate data in terms of how things may change over time. And then we're creating a prediction of. How those climates change, and then translate that into what we already know about wine grapes. [00:07:09] Joel Harms: Sort of. Yeah. But in our model for training, we just use the existing ones. So historical climate data and historical grape variety data. Once we have that model trained, we just apply it for new climates that come from like other climate models. So we don't do the climate modeling ourselves, but we extract that information and feed that into it and get the grape varieties output. [00:07:31] Craig Macmillan: So you look specifically, at least reported on areas that currently are considered too cold for growing a high quality pinot noir or growing wine grapes in general. What did you find out? What Parts of the world might be the new leading Pinot Noir regions. [00:07:46] Joel Harms: . So that depends a little bit on the exact scenario and how much the climate is supposed to warm. We have like two scenarios is what we looked at. We looked at a 8. 5 scenario and a 2. 6 scenario and going by the 8. 5 scenario, some of the regions that are improving are for example, Western China. And also Southern California, actually, and Quebec, , like Southern California is in Santa Barbara. I guess that's technically Central Coast, [00:08:17] Craig Macmillan: Yeah, well, that's interesting There's a lot of Pinot Noir in Santa Barbara County in the in the coastal zones Any other regions that popped up? [00:08:26] Joel Harms: Yeah, a lot of Australia seems to be doing better and like Northern France, [00:08:31] Craig Macmillan: Yeah pushing it to the north. Did England pop up? [00:08:35] Joel Harms: England, yes, but England seems to like stay the same in compared to historical. So not like as if it's improving, at least like from this, like rough map that we made. What we want to do is do it a bit more finely. The, this prediction, because we currently just used regions where wine is already grown, but then try to like interpolate just for calculation efficiency. Outward. So like our maps are created not only by the model itself, because that would be too calculation intensive. So for the, for the sake of simplicity, we did it like this, but we're still writing the final paper. So, you know, don't invest just yet, wait a little bit and then, [00:09:17] Craig Macmillan: I was gonna bring that up. Where should I put my money? [00:09:19] Joel Harms: Exactly. So don't do that yet. Wait for the final paper and then we will double check everything over. Oh yeah. Arkansas was one that was improving too. Very interestingly. Yeah. [00:09:28] Craig Macmillan: I was kind of surprised because having talked to guests, many guests from, you know, New York, from Texas, from people who consult in the Southwest Northern California, which can get quite warm. What we've talked about is the question of it getting too hot to grow quality wine grapes. [00:09:49] You know, wine grapes will grow to tolerate quite high temperatures. So, for instance, the San Joaquin Valley in California, produces a lot of wine grapes. They're not considered to be very high quality compared to coastal zones. So the vines do great and produce good crops and all of that. So there's concern that areas that have been kind of in the sweet spot, kind of in the, we call it the Goldilocks phenomenon where climate, soil, time, everything just all kind of fits together. [00:10:12] It sounds like this idea would be applicable to predicting what areas might become too warm for high quality wine [00:10:19] Joel Harms: Yes. Yes. It's definitely the case. Yes. And in our maps. You can see both at the same time because it sees like relative change, positive, relative change to, to negative. Some areas that look like they're not going to do so well in the future or less good in the future, even though they're like really good right now is like Oregon, unfortunately. [00:10:39] And the Azores or Northern Spain, even in Eastern Europe, a lot of areas. Seem to be warming up like in Romania at the coast. Not necessarily just the warming up part, but also because we consider 16 different climate variables, it could be the warming up part, but it could also be, you know, like the precipitation changing things like that, you know. [00:10:59] Craig Macmillan: You said 16 variables, we talked, you got temperature, you got precipitation, what, what are some of the others? [00:11:04] Joel Harms: Yeah, we got the growing degree days, the winter index, we got the Huggins index, we have radiation. Diurnal temperature range, the annual average temperature, for the precipitation, we have it like a three different scales, in the harvest month over the growing season and also throughout the whole year same for the temperature. And then we have the, growing indexes [00:11:26] Craig Macmillan: do you have plans to do this kind of thing again? Or publish additional papers from the work you've already done, because I think, it sounds like you've got a lot of interesting findings, [00:11:35] Joel Harms: Oh yeah. Yeah. The results only came in like right before the conference. We're still analyzing everything, writing everything. So the first thing that's coming up is a paper just on , how did we build the model and like all the validations and does it make sense with like expert classifications of how experts classify suitability for grapevines and things like that in the past to see if. That lines up as it should yeah, and then after that we'll publish some of these predictions and what we can learn from these and more detailed than how we did it right now where, most of it's like interpolated because we couldn't predict for every location, so like we predicted for some locations and interpolated. Just for computational efficiency, I guess, but you know, we're, we're getting there. Unfortunately, academia is quite you know, a slow profession. takes a lot of time. [00:12:24] Craig Macmillan: Yes, yes it does. And then getting it published takes a lot of time with reviews and whatnot. And so I just want to put a time stamp on this. This is being recorded in October of 2024. So, Give it some months, at least several, several, several, several. But it's exciting. This stuff's coming out. It'll be in, be in the literature. That's really, really great. [00:12:43] Joel Harms: And soon what we're trying to do is also release like a tool or something that, you know, where people can input their location and we can, our climate data, like call out the climate data and see what, what some of the predictions would be. Yeah. [00:12:57] Craig Macmillan: Oh, that's neat. [00:12:59] Joel Harms: I might've done that for Niner Vineyards just now to see, to see what, what's a suitable there, but only the current ones. [00:13:08] So I mean, it's kind of is exactly what you're growing. [00:13:10] Craig Macmillan: Funny. You should mention that. There is a a website called CalAdapt that allows you to put in some ranges and some variables specific to your location, you put your location in, and then there's a number of different models that you can run. Some are very conservative, some are not in terms of what the predictions are for climate change globally. [00:13:31] And then gives you a nice report on what the average temperature change might be in degrees Fahrenheit or Celsius also takes a stab at precipitation, although I talked to somebody who was connected to that and they said the precipitation is always kind of questionable. And also looks at things like heat waves, how many heat waves days over 100 or days over 95, you might expect because those can be quite fluctuating. [00:13:55] damaging. Even, even though vines can tolerate heat, if they're not acclimated, getting these big stretches of over a hundred, for instance, can be kind of stressful. I did that and kind of looked at it myself and thought, huh, I wonder if we had better, more, um, detailed information, what that might look like. [00:14:12] Another tool that was mentioned that you used was a deep coupled auto incoder networks. What are those? [00:14:18] Joel Harms: So that was what I described earlier, like these component models , where we have a. The encoder and decoder part, the input part is the , encoder and the output part is the decoder. And in the middle of these we have a latent space and then the coupled part means that we're having multiple of these that share their latent space. [00:14:38] So that's , where we're tying them together so that we can input either climate or grapes and get as outputs either climates or grapes. So it's like very, very flexible in that way and so I quite like that. And it turns out it does better than even some more traditional approaches where you just feed in climate and get out grapes like from a neural network or something like that. [00:14:59] Just like a neural network, because we have technically like four neural networks and all of them have three layers. So that's three layers or more. And so that's what makes them deep. [00:15:08] Craig Macmillan: Got it. [00:15:09] Is this your primary work as a PhD student? [00:15:13] Joel Harms: Well, as a PhD student, I'm still working on modeling. But not so much with grapevines, unfortunately. I'm looking at still climate models. How can we adapt for example, now we're looking more at the Caribbean. There's flooding issues. Particularly in Guyana. And so we're trying to, you know, help maybe the government to plan land use better in order to avoid, you know, critical areas being flooded, agricultural land being flooded and these type of things. [00:15:41] So it's more looking at flooding modeling, there's definitely some overlap in that sort of work, it's definitely still like in the area of using data science to help decision making which is the overall theme of this work. [00:15:55] Craig Macmillan: Yeah, and that was something that also came up in my little mini project was the potential for massive storms and also the potential for drought. Which, wasn't part of your work at this stage. Is that something that you would be able to find a way of including in your modeling that might give you some idea of how things might change? [00:16:15] And it's specifically what I'm thinking of is Cyclone Gabriel, I believe it was called, Gabriella just devastated parts of New Zealand. And raised a lot of concern about how, you know, when we were in these coastal zones, we go, Oh, yes, it's mild. It's great. But we're right near the ocean. [00:16:33] Right. And in October between 24, we've seen a very active hurricane season in the Caribbean and on the East coast and the Gulf. Do you think there's potential for this kind of thing to give us more of a heads up about what might be coming our way in terms of massive storm events? Cause that might affect how and what I do. [00:16:52] Joel Harms: I guess this wouldn't depend really on the grape variety itself. That would be more like a citing issue, right? Like where do you plant? [00:16:58] That's what we're looking at now with the like flooding mapping if there is a storm, where does the water collect? Which roads are cut off? Or, I mean, I guess in the case of vineyards, you could look at like, what would be the likely damage would there be now saltwater maybe even if you're depending on where you are. That's definitely something to look at. [00:17:17] All you need is sufficient, like past data points. So you can calibrate your models and then. You know, look at different future scenarios and what will be important to for the future is to look at what's kind of the certainty of these predictions, right? Like, what are your error margins? What's your confidence interval? [00:17:33] Because that might drastically alter your decisions. If it says, oh, it's probably not going to be too bad, but you're very uncertain about that, then you're probably going to take some more precautions than, you know, not because usually now we have A lot of models where their prediction is very, like is deterministic. [00:17:50] So they say, this is how it will be. And it's hard to tell where, you know, where those margins are of error, which is something to look at in the future for sure. [00:18:01] Craig Macmillan: Yeah, that is a challenge in the the model that I did for a Paso Robles vineyard Precipitation didn't really change very much which I was surprised by so it wasn't gonna become like a drought area completely but the potential ranged from five inches of rain a year to 60 inches of rain a year, which is why I was asking about these massive storms. [00:18:21] Maybe our averages, continuous to what we have now, but it may be a bunch of craziness year to year around that. And I think that is interesting and useful to know. So you prepare for it. [00:18:34] Joel Harms: that's something people are looking at, I think cause you can use some models to calculate sort of new climate indices. To see like from daily data train, like new climate indices to see these big storm events and things like that, and maybe incorporate that. That could help, , maybe with that sort of analysis of where even if it's the same average, the index is different because it measures something else. [00:18:59] Yes, I wouldn't know what they're called, but yes, I believe this already exists and is being improved. . [00:19:05] Craig Macmillan: Yeah. Yeah. With your experience so far, what do you see? Because everybody's talking about this. It's like the future in a world of artificial intelligence and this and that. In this particular area where you're, you're tying one set of variables to climate variables and also to historical weather. [00:19:23] In the big picture, beyond just wine grapes, but in the big picture, any topic, where do you see this kind of work going? You touched on it a little bit, when you close your eyes and open your mind what does the future look like? What, kind of tools are we going to have and what kind of things are we going to be able to find out? [00:19:38] Joel Harms: Yeah, that's interesting. I think it, it really depends on the data we have available and it looks like we'll have more and more data available. [00:19:47] So better disease models, location specific disease models to plan spray schedules better and things like that, they seem to be coming. I think I've seen parts of that already from some companies rolling out. [00:20:00] It's all about kind of the creatively using the data that you have available, because a lot of like my data, for example, that I used for this. This isn't necessarily new data, right? This comes from the University of Adelaide who collects where, which grape varieties are grown all over the world. [00:20:17] And then just historical, climate data. It's not very new, but just to put these together in a meaningful way with AI, that's going to be the challenge. And then also to test, is this reliable or not? Because you could theoretically predict almost anything, but then you need to check, is it just correlation? [00:20:39] Am I taking all the important variables into account? And we're developing AI very, very fast. But maybe we need to spend a bit more time, you know, trying to validate it, trying to see how robust it is, which is a major challenge, especially with these complicated models, because, I heard about this example. [00:20:57] Where in the past, for some self driving cars, their AI that recognized stop signs could be tricked if there was a sticker on the stop sign, and it would ignore the stop sign. Even though there's not a big difference, but you can't test for, you know, all of these cases, what might happen. And that's kind of the same for, , what we are doing. [00:21:17] So improving the testing, that would be, I think, a major A major goal to make sure it's robust and reliable or that it tells you how, how certain it is, you know, then at least you can deal with it, you know, and not just make a decision off of that. Yeah, [00:21:29] Craig Macmillan: Yeah. What the level of uncertainty is. That's always the getcha. [00:21:33] Joel Harms: yes, [00:21:34] Craig Macmillan: That's always the hard part. If you had one thing that you would tell growers on this topic, what would it be? Mm [00:21:43] Joel Harms: Specifically for my models, it would be to take the current results with a grain of salt. And then to sort of use this to, narrow down like a selection of grapes and to still run tests and things like that. Cause it's regional data, right? It's not going to tell you exactly what you should grow in your location. [00:22:02] Cause it's, you know, the weather data is based on four to 50 kilometers around you. You know, that's where we're like assembling the data from. [00:22:10] Craig Macmillan: that a 50 kilometer quadrant? [00:22:12] Joel Harms: yes. Yeah. [00:22:13] Craig Macmillan: Yep. Okay. Gotcha. [00:22:14] Joel Harms: Yes, exactly. So this tool is mainly used or useful if you use it to like pre select some varieties so you can see what might be good, you know, and then decide for yourself what you want. [00:22:27] The take home message is like, it's not supposed to take away grape growing experts and things like that, or replace them in any way, but it's supposed to like support it because. There's so many grape varieties and if climate regions or like regions where we're growing grapes are changing, where the climate is changing, we want to get the best choice. [00:22:47] And so we should probably look at all of them, all of our available options and see what we can do. It will narrow it down for you. And then, you know, you'll still have to see what works exactly for you. What wine do you want to produce? I mean, it doesn't take that into account, right? It just gives you what probably would grow well here. [00:23:03] Craig Macmillan: . [00:23:03] Yeah, then I think that there's going to be a future also in bringing in some either hybrid varieties or varieties that are not terribly well known. I've talked to people from Texas and from Michigan Pennsylvania, where the traditional vinifera only varieties don't do pretty well. Terribly well, often because of cold hardiness because of cold winters, they don't handle it, but there's hybrids that do great and make interesting wine. [00:23:27] And I think that would be an interesting thing to include in a model or if it came out kind of like the winner was something we don't normally [00:23:33] Joel Harms: Right. Usually we have a lot of hybrids in this because we have 1, 300 varieties. [00:23:39] Craig Macmillan: wow. Oh, I didn't realize that. [00:23:41] Joel Harms: so I think we have most of the. commercially used grape varieties, like in all aspects. [00:23:48] Craig Macmillan: yeah, probably, probably. [00:23:49] Joel Harms: Yeah. So it's quite, quite far ranging. We only excluded some where it was never more than 1 percent of any region, because then like our model couldn't really learn what this grape variety needs. [00:24:00] Right. Because it's like too small, even in the largest region where it we cut those out. So, cause else we would have 1700. But then like the 1300 that actually get used commercially at a significant scale. Those we have. The model is actually built like we have a suitability index. [00:24:18] But we're still trying to, , fine adjust so that we can rank not just what's popular and like how much will grow. Cause then you'll always get, you know, the top, the top 10 will look very similar for any region. But then through the suitability index, we actually get a lot of these smaller varieties that would fit very well also ranked in the top 10 or in the top 50 of varieties. [00:24:41] Craig Macmillan: They've mentioned fine tuning the model at this point. Is this particular project or this particular model, is this gonna continue on into the future? It sounds you have ideas for improvements. Is this number one gonna continue on into the future and is there gonna come a point when This will be available for the industry, industries internationally to do their own trials. [00:25:03] Joel Harms: Yes, I think so. So I think when we're publishing the paper latest at that point, we'll have the tool set up where people can try it out, put in, in their location. And I guess we're publishing the methodology. So you could build like a version of this yourself. It's not too crazy. Probably code will be published too. [00:25:24] So, you know, you could build this yourself if you wanted to, or you could just use the models we have trained already. Okay. And just apply them to your case. That's what the tool is for. . Right now it's like all code based. So like, it's not, not so easy where you just, drop your pin, like where you're at and then it gives you some predictions, , that's what we're aiming for. [00:25:44] Craig Macmillan: Fantastic. So our guest today has been Joel Harms. He is a PhD student in the Department of Bioresource Engineering at McGill. University. Thanks so much for being on the podcast. This is really fascinating. I'm really looking forward to how this work progresses. And I think it's very eyeopening for us. [00:26:01] Again, you know, one of the things I thought was fascinating is I've had all these conversations about areas that would no longer be suitable, but a flip on it and say, well, areas that might be suitable in the future. I hadn't thought of that. [00:26:12] Joel Harms: Why not? You [00:26:13] Craig Macmillan: why not? You know, that's, that's, that's a very interesting question, and it applies to other crops as well. [00:26:18] I just had never really thought about it like that. You know, maybe you can grow oranges in Iowa at some point. [00:26:23] Joel Harms: That, that would be nice. I guess. [00:26:25] Craig Macmillan: maybe [00:26:26] Joel Harms: maybe see. [00:26:28] Craig Macmillan: we'll see. We'll see. You never know. Anyway, Joel, thanks for being on the podcast. I appreciate it. [00:26:33] Beth Vukmanic: Thank you for listening. Today's podcast was brought to you by Cal West Rain. Since 1989, Cal West Rain has served growers on California's Central Coast and the San Joaquin Valley. As a locally owned, full line irrigation and pump company, they offer design and construction experience in all types of low volume irrigation systems, whether they're for vines, trees, or row crops. [00:27:03] In addition, CalWestRain offers a full range of pumps and pump services, plus expertise in automation systems, filtration systems, electrical service, maintenance and repairs, equipment rental, and a fully stocked parts department. Learn more at CalWestRain. com. [00:27:23] Make sure you check out the show notes for links to Joel, his research articles, plus sustainable wine growing podcast episode 207. Managing Catastrophic Loss in Vineyards, Lessons from Cyclone Gabriel in New Zealand. If you liked this show, do us a big favor by sharing it with a friend, subscribing, and leaving us a review. [00:27:44] You can find all of the podcasts at vineyardteam.org/podcast, and you can reach us at podcast at vineyardteam.org. Until next time, this is Sustainable Wine Growing with the Vineyard Team.   Nearly perfect transcription by Descript

Heute wieder eine Episode in der ich kurz über eine Thema der Wissenschaftspraxis reflektieren möchte, den meisten Zuhörern wahrscheinlich nicht klar ist, dessen Konsequenzen sich auch mir noch nicht völlig erschließen, ich freue mich also auf Emails und Kommentare. Das Thema ist wenig erbaulich, ist aber ein Puzzlestein, der gut in das Bild passt, das wir in einigen früheren Episoden schon angesprochen haben. Die Qualität des wissenschaftlichen Publikationswesens scheint sich im Sturzflug zu befinden und dies seit vielen Jahren. Die deutsche Physikerin Sabine Hossenfeldern sagt leicht polemisch: »Scientific Process is slowing down and most of what gets published in academia is now bullshit.« Was erleben wir in den letzten Jahrzehnten und warum hat mich eine persönliche Beobachtung zu dieser Episode gebracht? Warum ist das Motto der 1660 gegründeten Royal Society heute aktueller als je zuvor. »Nullius in Verba« Referenzen Andere Episoden Episode 106: Wissenschaft als Ersatzreligion? Ein Gespräch mit Manfred Glauninger Episode 104: Aus Quantität wird Qualität Episode 91: Die Heidi-Klum-Universität, ein Gespräch mit Prof. Ehrmann und Prof. Sommer Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry Episode 84: (Epistemische) Krisen? Ein Gespräch mit Jan David Zimmermann Episode 79: Escape from Model Land, a Conversation with Dr. Erica Thompson Episode 71: Stagnation oder Fortschritt — eine Reflexion an der Geschichte eines Lebens Episode 68: Modelle und Realität, ein Gespräch mit Dr. Andreas Windisch Episode 47: Große Worte Episode 41: Intellektuelle Bescheidenheit: Was wir von Bertrand Russel und der Eugenik lernen können Episode 39: Follow the Science? Fachliche Referenzen Report of the Investigation Committee on the Possibility of Scientific Misconduct in the Work of Hendrik Schön And Coauthors Publikationen von Jan Hendrik Schön (Google Scholar) John Ioannidis, Das Gewissen der Wissenschaft, Ö1 Dimensionen (2024) John Ioannidis, The scientists who publish a paper every five days, Nature Comment (2018) John P. A. Ioannidis, Why Most Published Research Findings Are False (2005) Jesse Singal, Quick Fix, Picador (2022) Erica Thompson, Escape from Model Land, Basic Books (2022) Sabine Hossenfelder, Lost in Math: How Beauty Leads Physics Astray (2020) Beall's List Jeffrey Beall Sabine Hossenfelder, Science is in trouble and it worries me (2024)

A panel at the WSIA Annual Marketplace in San Diego said private insurers are assessing their appetite for flood risk due to changing climate conditions and increased frequency of severe storms.

Eifrige Hörer des Podcasts werden bemerken, dass es bereits eine Episode zum Thema gab, nämlich Episode 10 mit dem Titel »Komplizierte Komplexität« aus dem Jahr 2019. Es lohnt sich auch, diese nochmals nachzuhören, aber nach fünf Jahren ist es an der Zeit, hier ein Update zu machen. Ganz besonders auch deshalb, weil ich wieder einen hervorragenden Gesprächspartner zum Thema virtuell einladen durfte, Dr. Marco Wehr. Dr. Marco Wehr ist Physiker und promovierter Wissenschaftstheoretiker. Als vielfach ausgezeichneter Autor und Redner beschäftigt er sich mit Fragen der Vorhersehbarkeit, der Rolle des Körpers für das Denken und der Beziehung von Gehirn und Computer. Marco Wehr ist Gründer und Leiter des Philosophischen Labors in Tübingen. Sein neues Buch »Komplexe neue Welt« ist natürlich eine der Grundlagen für dieses Gespräch. Es ist unlängst zum Wissensbuch des Jahres 2024 vorgeschlagen worden. Link zum Buch natürlich wie immer in den Shownotes. Marco beschäftigt sich auch mit der Frage der Modellierung, und sein aktuelles Vortrags-Format für 2025 heißt folgerichtig: »Die Macht mathematischer Modelle«. Wir beginnen mit der Frage, was der Unterschied zwischen komplexen und komplizierten Systemen oder Fragestellungen ist, zumal diese beiden Begriffe umgangssprachlich oft synonym verwendet werden. Was kann man in dieser Hinsicht von Mandelbrot-Fraktalen lernen? Welche Systeme der Welt sind irreduzibel? “Can one predict what will happen? No, there's what I call computational irreducibility: in effect the passage of time corresponds to an irreducible computation that we have to run to know how it will turn out.”, Stephen Wolfram Wie kann man feststellen, ob man ein kompliziertes oder komplexes Problem vor sich hat? Was sind »Inseln der Propheten«? Gibt es eine kognitive Täuschung in den Naturwissenschaften? Der US-amerikanische Wissenschaftsforscher John Ioannidis hält Menschen (und besonders auch Wissenschafter), die glauben, zu viel zu wissen, für eine große Gefahr. Schon der bedeutende Philosoph des 20. Jahrhunderts, Karl Popper, hat dies sehr deutlich ausgedrückt: »Jeder Intellektuelle hat eine ganz spezielle Verantwortung. Er hat das Privileg und die Gelegenheit, zu studieren. Dafür schuldet er es seinen Mitmenschen (oder der Gesellschaft), die Erkenntnisse seines Studiums in der einfachsten und klarsten und bescheidensten Form darzustellen. Das Schlimmste – eine Sünde gegen den heiligen Geist – ist, wenn die Intellektuellen es versuchen, sich ihren Mitmenschen gegenüber als große Propheten aufzuspielen und sie mit orakelnden Philosophien zu beeindrucken. Wer's nicht einfach und klar sagen kann, der soll schweigen und weiterarbeiten, bis er's klar sagen kann.«  Dann sprechen wir über den Laplacesche Dämon und was man von ihm über die Welt und die Entstehung der Wahrscheinlichkeitsrechnung lernen kann?  Wie hat Urbain Le Verrier den Neptun vorhergesagt?  »Ich möchte, dass man das, was man weiß, und das, was man nicht weiß, deutlich voneinander unterscheidet.« Wie erkennt man einen Experten und wer repräsentiert Wissenschaft? Was sind Rückkopplung und Resonanz und warum ist es so entscheidend, diese Phänomene in komplexen Systemen zu verstehen? Wo sind die Grenzen eines Modells? Gibt es eine saubere Trennung zwischen Beobachter und Modell? Was sind Signaturen komplexer oder chaotischer Systeme? Begehen wir in der heutigen wissenschaftlichen Praxis zu häufig den Fehler »im Licht zu suchen«, statt dort, wo es sinnvoll wäre — besonders in den Bereichen, die man im weiteren Sinne als Data-Science bezeichnet? Man kann versuchen, die Welt zu verstehen, oder die lösbaren Probleme der Welt herauszupicken und daraus falsche Schlüsse über die Welt zu ziehen. Was ist die stoische Landkarte, wie kann und diese weiterhelfen? Hypothese ist immer vor der Empirie und damit bekommen begründete Vorannahmen eine wichtige Rolle im wissenschaftlichen Prozess.  Dazu kommt, dass es nie nur ein Modell gibt, das zu bestimmten Daten »passt«, dies wird auch als Duhem-Quine Hypothese bezeichnet. Was bedeutet dies am Beispiel der Klimamodellierung oder Wirtschaftsmodellen? Kann man die Inseln des Wissens von den Inseln des Unwissens unterscheiden? Welche Rolle spielen Vulkane und andere Naturkatastrophen? Warum ist die Energiewende in Deutschland schiefgegangen? »Am deutschen Wesen soll die Welt genesen...« Die Welt lernt in der Tat von Deutschland, aber wohl eher am Versagen Deutschlands. Das mag gut für die Welt sein, ist aber schlecht für Deutschland. Wie ist das dazu gekommen? Was sind »intellektuelle Insulaner«? Was sind Komplexitätsfallen – natürliche vs. künstliche — heute haben wir es mit beiden zu tun und einer Mischung/Interaktion von beiden? Noch kritischer sind hybride Komplexitätsfallen oder Komplexitätsmonster — wie kommen diese zustande? Was versteht man unter emergenten Effekten? Was sind existenzielle Risiken, und warum ist ein Fokus auf »Klima« kontraproduktiv — Carrington-Event als Beispiel. “There are no solutions, only tradeoffs”, Thomas Sowell Wie gehen wir als Individuen mit radikaler Unsicherheit in komplexen Systemen um? »We control nothing, but we influence everything«, Brian Klaas Was ist die richtige Balance zwischen Sicherheit und Unsicherheit? Ist diese erreichbar? »Die meisten Menschen wollen nicht in einer total vorhersagbaren Welt leben, auch wenn sie das behaupten.« Wie kommen wir als Gesellschaft wieder aus den zahlreichen schweren Problemen heraus, in denen wir uns in den letzten Jahren verstrickt haben? Offene Diskussion scheint das wesentlichste zu sein. Kontroverse steht im Zentrum von Wissenschaft und daraus folgt offener und kritischer gesellschaftlicher Diskurs.  Referenzen Andere Episoden Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg Episode 106: Wissenschaft als Ersatzreligion? Ein Gespräch mit Manfred Glauninger Episode 99: Entkopplung, Kopplung, Rückkopplung Episode 96: Ist der heutigen Welt nur mehr mit Komödie beizukommen? Ein Gespräch mit Vince Ebert Episode 94: Systemisches Denken und gesellschaftliche Verwundbarkeit, ein Gespräch mit Herbert Saurugg Episode 92: Wissen und Expertise Teil 2 Episode 90: Unintended Consequences (Unerwartete Folgen) Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry Episode 85: Naturalismus — was weiß Wissenschaft? Episode 80: Wissen, Expertise und Prognose, eine Reflexion Episode 79: Escape from Model Land, a Conversation with Dr. Erica Thompson Episode 76: Existentielle Risiken Episode 72: Scheitern an komplexen Problemen? Wissenschaft, Sprache und Gesellschaft — Ein Gespräch mit Jan David Zimmermann Episode 69: Complexity in Software Episode 68: Modelle und Realität, ein Gespräch mit Dr. Andreas Windisch Episode 36: Energiewende und Kernkraft, ein Gespräch mit Anna Veronika Wendland Episode 10: Komplizierte Komplexität Dr. Marco Wehr Marco Wehr auf LinkedIn Philosophisches Labor in Tübingen Marco Wehr, Komplexe neue Welt und wie wir lernen, damit klarzukommen, Galiani Berlin (2024) Fachliche Referenzen Steven Wolfram, How to Think Computationally about AI, the Universe and Everything (2023) Daphne Hruby, John Ioannidis: Das Gewissen der Wissenschaft, Ö1 Dimensionen (2024) Karl Popper, Auf der Suche nach einer besseren Welt (1987) Underdetermination of Scientific Theory, Stanford Encyclopedia of Philosophy (2023) Franz Josef Radermacher, Global Energy Solutions Thomas Sowell, A Conflict of Visions: Ideological Origins of Political Struggles (1987) Brian Klaas, Fluke: Chance, Chaos, and Why Everything We Do Matters, John Murray (2024)

The U.S. Drought Monitor map released Thursday morning looked the same as it did last week, when University of Minnesota soil scientist Jeff Strock said recent snow and rain brought relief to farmers who will be planting soon.“The vast majority of that moisture is actually getting into the ground and really starting to wet up that top 4 to 6 inches of soil that has been really pretty dry, given that we've had very little snowfall and moisture over the course of the winter,” he said.In the long term, though, farmers will continue to deal with uncertainty caused by climate change. Minnesota Climate Adaptation Partnership Director Heidi Roop met with farming representatives in St. Cloud Tuesday to talk through the research on future climate conditions in the state — and what they mean for agriculture. She joined MPR News Cathy Wurzer with takeaways from the meeting.

Dr. Judith Curry is a climatologist and author. She was a member of National Research Council's Climate Research Committee and published over a hundred scientific papers.  Her latest book “Climate Uncertainty and Risk” discusses the risks and response to current and future climate issues. We discuss the book, climate hypocrisy, propaganda, worst case scenarios and more. 0:00:00 - Intro 0:00:14 - Dr. Judith Curry's Background 0:06:25 - Politics, Labels & Transparency 0:12:10 - Use of Fossil Fuels & Alternate Energy 0:18:45 - Issues in Africa 0:20:30 - Facing Political Reality of Energy Policies 0:23:05 - History of Climate Propaganda 0:24:35 - Climate Hypocrisy  0:28:10 - Climate Models & Population Growth 0:32:40 - Problems with Electric Cars 0:34:40 - United Nations & Biggest Polluters 0:36:55 - Agriculture,  Best Diet For Climate & Policy 0:41:05 - Climate Predictions & Worst Case Scenarios 0:44:00 - Volcanic Cooling 0:48:00 - Traditional Environmentalism, Soil & Farming 0:52:28 - Solar Variations & Possible Cooling 0:54:05 - Sea Levels Rising & Misdirected Blame 0:57:20 - California, Rolling Blackouts & Nuclear Power 1:02:57 - Outro Dr. Judith Curry website:https://judithcurry.com/Chuck Shute link tree:https://linktr.ee/chuck_shuteSupport the showThanks for Listening & Shute for the Moon!

In episode 43 of Healthy & Awake Podcast, titled "Climate Uncertainty & Risk w/ Dr. Judith Curry," we delve into the nuanced conversation of climate change, striking a balance between concern and pragmatism. Our distinguished guest, Dr. Judith Curry, brings her extensive experience as President and co-founder of the Climate Forecast Applications Network and Professor Emerita at the Georgia Institute of Technology, to dissect climate alarmism, draw parallels between societal responses to climate issues and the COVID-19 pandemic, and discuss actionable steps individuals can take to contribute to environmental sustainability. Throughout the conversation, we explore Dr. Curry's perspectives on technology's role in addressing climate change, including her take on electric vehicles, underpinned by her expertise in climate dynamics, extreme weather events, and risk science. Join us for this enlightening dialogue that transcends mainstream narratives and offers critical insights into navigating the complexities of climate change and environmental stewardship. Twitter: @curryjaBlog: Climate Etc. judithcurry.comClimate Forecast Applications Network (CFAN): www.cfanclimate.netBook: Climate Uncertainty and Risk __________________________________________________________________

In Episode 80 habe ich mich schon einmal mit dem Thema Wissen und Expertise auseinandergesetzt, damals eher mit dem Fokus auf die Frage wie gut (oder schlecht) Prognosen in der Realität sind, und woran das liegen könnte. In dieser Episode versuche ich einige weitere Gedanken zu entwerfen und ersuche explizit um Feedback, was Sie davon halten. Ich diskutiere einige Ideen zu den Fragen: Wo steckt in einer Gesellschaft Wissen, wo steckt Expertise Gibt es Grenzen der Expertise (in komplexen Systemen) Wie kann sich das Verhältnis von Expertise zu Wissen über die Zeit verändern In welchem Verhältnis stehen diese beiden Begriffe generell zueinander Das Ganze natürlich wieder mit zahlreichen Beispielen. Referenzen Andere Episoden Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry Episode 80: Wissen, Expertise und Prognose, eine Reflexion Episode 79: Escape from Model Land, a Conversation with Dr. Erica Thompson Episode 72: Scheitern an komplexen Problemen? Wissenschaft, Sprache und Gesellschaft — Ein Gespräch mit Jan David Zimmermann Episode 68: Modelle und Realität, ein Gespräch mit Dr. Andreas Windisch Episode 41: Intellektuelle Bescheidenheit: Was wir von Bertrand Russel und der Eugenik lernen können Episode 39: Follow the Science? Episode 37: Probleme und Lösungen Episode 27: Wicked Problems Episode 25: Entscheiden unter Unsicherheit Episode 17: Kooperation Fachliche Referenzen Dieter Macek: Eine Gesamtgenealogie der griechisch-mediterranen Mythologie Thomas Sowell, Intellectuals and Society, Basic Books (2012) Matt Ridley, How Innovation Works, Fourth Estate (2020) Aspirin & Salizylsäure Nobelpreis zur Acetylsalicylsäure: Sir John Robert Vane (1982) Calvin Coolidge The Medical Context of Calvin Jr.'s Untimely Death (Coolidge Foundation)

Im heutigen Podcast werde ich einige unterhaltsame aber auch ernsthafte Geschichten erzählen, zu einem Thema, das ich in verschiedenen anderen Episoden schon angesprochen habe: »Unintended Consequences — Unerwartete Folgen« In dieser Episode wird es also weniger um eine tiefe Analyse der Gründe für unerwartete Folgen bestimmter Maßnahmen gehen, sondern es soll vielmehr die Breite und Tragweite der Problematik anschaulich gemacht werden. Dies trifft sowohl auf die Fälle zu, wo die unerwünschten Folgen negativer als auch positiver Natur sind. In der Episode spreche ich Beispiele aus der Chemie, der Ökologie, Politik und Wissenschaft an. Es ist auch das erste Mal, dass mit Barbara Streisand eine Schauspielerin und Sängerin thematisiert wird, oder besser gesagt, ihre Villa am Strand! Welche Rolle spielen simple und komplexe Systeme, oder Probleme mit engem oder weitem Kontext? Was können wir tun, um schwerwiegende unerwünschte Folgen zu vermeiden und positive zu begünstigen? “All history is the history of unintended consequences.”, T. J. Jackson Lears Referenzen Andere Episoden Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry Episode 80: Wissen, Expertise und Prognose, eine Reflexion Episode 76: Existentielle Risiken Episode 72: Scheitern an komplexen Problemen? Wissenschaft, Sprache und Gesellschaft — Ein Gespräch mit Jan David Zimmermann Episode 69: Complexity in Software Episode 37: Probleme und Lösungen Episode 27: Wicked Problems Episode 25: Entscheiden unter Unsicherheit Episode 23: Frozen Accidents Episode 10: Komplizierte Komplexität Fachliche Referenzen Rory Sutherland, Alchemy, Virgin Digital (2019) Los Angeles Times, Unintended consequences of conserving water: leaky pipes, less revenue, bad odors (2015) Rachel Carson, Silent Spring, Penguin Classic (1962) Bloomberg, Tree Planting Program in Mexico may Encourage Deforestation (2021) Tokunaga, E., Yamamoto, T., Ito, E. et al. Understanding the Thalidomide Chirality in Biological Processes by the Self-disproportionation of Enantiomers. Sci Rep 8, 17131 Barbara Streisand Estate (Photo): Copyright (C) 2002 Kenneth & Gabrielle Adelman, California Coastal Records Project Thomas Sowell, Intellectuals and Society, Basic Books (2012) Vaclav Smil, Invention and Innovation: A Brief History of Hype and Failure, MIT Press (2023) Reason TV, Great Moments in Unintended Consequences (YouTube Playlist) Niall Ferguson on Regulation (YouTube), Zitat T. J. Jackson Lears

In the News with Mike Dakkakwww.itnshow.comClimate scientist Judith Curry joins ITN to discuss some of the more popular myths pushed by climate change activists.Buy Judith's book Climate Uncertainty and Risk: Rethinking Our Response Subscribe to Judith's blog at https://judithcurry.com.Follow Judith on Twitter at https://twitter.com/curryja.

In this episode of Faithful Politics, hosts Will Wright and Josh Burtram engage in an insightful discussion with Dr. Judith Curry, a distinguished climatologist. They delve into the complexities of climate science, examining the interplay between human-induced changes and natural climate processes. Dr. Curry addresses the challenges in understanding climate science and critiques the politicization and alarmist perspectives often associated with the climate debate.The conversation also explores the implications of climate policies, emphasizing the importance of adopting pragmatic and well-rounded approaches. Dr. Curry advocates for a more nuanced and inclusive discourse on climate change, highlighting the significance of considering diverse viewpoints and scientific uncertainties in shaping effective environmental strategies.Learn more about our guest by going to her website: https://judithcurry.com/Buy her book, "Climate Uncertainty & Risk" https://anthempress.com/climate-uncertainty-and-risk-hbGuest Bio:Judith A. Curry is an American climatologist and former chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology. Her research interests include hurricanes, remote sensing, atmospheric modeling, polar climates, air-sea interactions, climate models, and the use of unmanned aerial vehicles for atmospheric research. She was a member of the National Research Council'sClimate Research Committee, published over a hundred scientific papers, and co-edited several major works. Curry retired from academia in 2017 at age 63, coinciding with her public climate change skepticism.Support the showTo learn more about the show, contact our hosts, or recommend future guests, click on the links below: Website: https://www.faithfulpoliticspodcast.com/ Faithful Host: Josh@faithfulpoliticspodcast.com Political Host: Will@faithfulpoliticspodcast.com Twitter: @FaithfulPolitik Instagram: faithful_politics Facebook: FaithfulPoliticsPodcast LinkedIn: faithfulpolitics

About this conversation: Dr Judith Curry is the President and co-founder of the Climate Forecast Applications Network (CFAN).  She is Professor Emerita at the Georgia Institute of Technology, where she served as Chair of Earth and Atmospheric Sciences for 13 years. Her expertise is in climate dynamics, extreme weather, and prediction/predictability. Judith is a Fellow of the American Meteorological Society, the American Association for the Advancement of Science, and the American Geophysical Union. Following an influential career in academic research and administration, Judith founded CFAN to translate cutting-edge weather and climate research into forecast products and services that support the management of weather and climate risk for public and private sector decision-makers. Judith is a leading global thinker on climate change. She is frequently called upon to give U.S. Congressional testimony and serve as an expert witness on matters related to weather and climate. Her influential blog Climate Etc. addresses leading-edge and controversial topics about climate change and the science-policy interface. Her new book is Climate Uncertainty and Risk - Rethinking the climate change problem, the risks we are facing, and how we can respond. The conversation explores the biases in climate change research and the impact on funding and career advancement. It delves into the history and ethics of science, highlighting the presence of personal motives and professional rivalry. The need for a broader intellectual and moral foundation in scientific education is discussed, emphasizing the importance of ethics and philosophy. The conversation also addresses the power politics involved in science and medicine, leading to a lack of trust in these fields. This is a fascinating conversation and I hope you enjoy it. Links Website Climate Forecast Applications Network Website Website Judith Curry Website Twitter/X Judith Curry X account Book Climate Uncertainty and Risk IMPORTANT NOTICE Following my cancellation for standing up for medical ethics and freedom, my surgical career has been ruined. I am now totally dependent on the support of my listeners, YOU. If you value my podcasts, please support the show so that I can continue to speak up by choosing one or both of the following options - ⁠Buy me a coffee⁠ If you want to make a one-off donation. Join my Substack To access additional content, you can upgrade to paid from just £5.50 a month Doc Malik Merch Store⁠ Check out my amazing freedom merch To sponsor the Doc Malik Podcast contact us at ⁠hello@docmalik.com⁠  About Doc Malik: Orthopaedic surgeon Ahmad Malik is on a journey of discovery when it comes to health and wellness. Through honest conversations with captivating individuals, Ahmad explores an array of topics that profoundly impact our well-being and health. You can follow us on social media, we are on the following platforms: ⁠Twitter Ahmad⁠ | ⁠Twitter Podcast⁠ | ⁠Instagram Ahmad⁠ | ⁠Instagram Podcast

Professor of Atmospheric Science Judith Curry explains all! Her book is "Climate Uncertainty and Risk" - widely available and a superb read! NOTE: My extensive research and interviewing / video/sound editing, business travel and much more does require support - please consider helping if you can with monthly donation to support me directly, or one-off payment: https://www.paypal.com/donate?hosted_button_id=69ZSTYXBMCN3W - alternatively join up with my Patreon - exclusive Vlogs/content and monthly zoom meetings with the second tier upwards: https://www.patreon.com/IvorCummins

I recently read the book "Climate Uncertainty and risk" written by Dr. Judith Curry, who is  one of the leading US climate scientists but also an important heterodox thinker. I loved her book, not only because of her take on climate change, but also because she covers a lot of essential topics that are applicable in other complex problems as well. Judith Curry is president of Climate Forecast Applications Network (CFAN).  Previously, she was professor and chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology and professor at the University of Colorado-Boulder in the department of aerospace engineering sciences program in the atmospheric and oceanic sciences and environmental studies program. Dr Curry published more than 200 reviewed scientific articles and gave 13 testimonials at US congressional hearings. In our conversation we discuss about the state of climate and climate science. What role does uncertainty play in assessing climate change and climate risk? Why urgency in measures might be a disaster. What role do carbon emissions play and can wind and solar energy help in mitigating climate change? What role does or should nuclear energy play? Do many prominent environmentalists hate nuclear even more than climate change? However, uncertainty cuts both ways, what does this mean in terms of climate, tipping points, systemic attractors, regime shifts?  What role do natural effects play in climate change, like volcanoes (think of the year without summer)? How can we reduce vulnerability and why does deindustrialization and becoming poorer as a society not seem to be a clever way to handle complex risks? At the moment it rather seems that we are crippling our economy without reducing the footprint on the planet while at the same time reducing our resilience. “There are no solutions, only tradeoffs.”, Thomas Sowell What does resilience mean on a societal level and what can we do to achieve it? How is resilience connected to global existential risks? "At that point we are making the environment worse, and doing nothing for the climate and we are messing up our economy over this crazy net zero stuff." Is energy transition on the scale some countries attempt to do it, a risk far greater than risks related to climate change in the 21st century? What are wicked problems (showing complexity, uncertainty and ambiguity)? Why do predict than act approaches (which work for tame problems) not work on wicked problems? "Climate change is the mother of all wicked problems." What is the utility of models in general and climate specifically? “This is exactly what models are for—to serve as working hypotheses for further research.”, Ludwig von Bertalanffy How do climate models work? What is a scenario and how can scenarios be of use in assessing climate change?  Why did we see such a heatwave this summer and autumn? What are likely reasons and what does the hot summer and August of this year tell us about anthropogenic climate change and the next decades? How to deal with extreme risks that are unlikely, like a Carrington Event? What are microgrids and how could the help making a society more resilient? What is the difference and utility of caution, precaution and the precautionary principle? Why is the precautionary principle problematic and how could a proactionary principle helt? What are principles of robust decision making? How do incrementalism and local decision making contribute? Is the seed — select — amplify (Meyer, Davis) idea and antifragility connected? Why do we see deep quality problems and politicisation in science? How is gate keeping of major institutions abused to stop critical discussion, including top journals like Nature and Science? Why did cancel culture blossom in academia and create a toxic intellectual environment? "The whole incentive system has become completely perverse." Careerism, ideology or money? Which is harming science the most? “Big Science may destroy great science, and the publication explosion may kill ideas. Ideas, which are only too rare, may become submerged in the flood.”, Karl Popper Should we separate science and activism or is a scientist ethically required to become an activist under certain conditions?  "Once you became a political activist, it is game over for your credibility as a  scientist." However, being a scientist and activist for a politically popular topic is currently highly rewarded. Can people handle complexity or should we simplify complex topics to easy to understand soundbites? And if so, who does the simplifying? Should we hide the scientific debate or even cancel it, to be able to send a simple message? "In the old days, disagreement was the spice of academic debate and life. Now we are out to cancel our opponents." References Judith Curry Website and Blog of Dr. Judith Curry CV Judith Curry, Climate, Uncertainty and Risk, Anthem Press (2023) Judith Curry, Klima: Unsicherheit und Risiko (2023) Other Episodes Modeling Episode 79: Escape from Model Land, a Conversation with Dr. Erica Thompson Episode 68: Modelle und Realität, ein Gespräch mit Dr. Andreas Windisch Episode 53: Data Science und Machine Learning, Hype und Realität — Teil 1 Existential Threats Episode 76: Existentielle Risiken Episode 74: Apocalype Always Episode 45: Mit »Reboot« oder Rebellion aus der Krise? Episode 42: Gesellschaftliche Verwundbarkeit, ein Blick hinter die Kulissen: Gespräch mit Herbert Saurugg Complex problems Episode 72: Scheitern an komplexen Problemen? Wissenschaft, Sprache und Gesellschaft — Ein Gespräch mit Jan David Zimmermann Episode 69: Complexity in Software Episode 37: Probleme und Lösungen Episode 80: Wissen, Expertise und Prognose, eine Reflexion Episode 27: Wicked Problems Episode 25: Entscheiden unter Unsicherheit Episode 23: Frozen Accidents Science, Quality and Stagnation Episode 67: Wissenschaft, Hype und Realität — ein Gespräch mit Stephan Schleim Episode 65: Getting Nothing Done — Teil 2 Episode 64: Getting Nothing Done — Teil 1 Episode 28: Jochen Hörisch: Für eine (denk)anstössige Universität! Episode 18: Gespräch mit Andreas Windisch: Physik, Fortschritt oder Stagnation Episode 16: Innovation und Fortschritt oder Stagnation? Other Reference Guinevere Glasfurd, The Year Without Summer: 1816 - one event, six lives, a world changed, Two Roads (2020) Thomas Sowell, Intellectuals and Society, Basic Books (2012) Christopher Meyer, Stan Davis, It's Alive: The Coming Convergence of Information, Biology and Business, Texere Publishing (2003) Björn Lomborg, False Alarm: How Climate Change Panic Costs Us Trillions, Hurts the Poor, and Fails to Fix the Planet, Basic Books (2020) Roger Pielke Jr. on Substack Carrington Event: Lloyds, Solar Storm Risk to the North American Electric Grid (2013) John Ioannidis, How the Pandemic Is Changing Scientific Norms (2021) Karl Popper, The Myth of the Framework: In Defence of Science and Rationality, Routledge (2014)

In this episode, Dennis Prager interviews Judith Curry about her new book, "Climate Uncertainty and Risk," challenging the consensus on human-induced climate change. They discuss the controversy around the 97% consensus claim, the lack of clear evidence for an existential threat from warming, and the risks associated with the transition to wind and solar energy. 

The charge that Elon Musk is an antisemite is ridiculous. It's made by leftists to smear the multi-billionaire. The reason why the left hates him is because he has made X a platform for free speech. They can't forgive him for that… High school students in Brooklyn march and shout antisemitic slogans... America first should not mean America only.  Dennis continues the theme with which he ended the first hour. America first should not mean America only. Unfortunately, to many conservatives it does. This is wrong and counter-productive. Dennis explains… A high school in northern California flies a Palestinian flag.  Dennis talks to Judith Curry, former chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology. Her new book is Climate Uncertainty and Risk: Rethinking Our Response.Thanks for listening to the Daily Dennis Prager Podcast. To hear the entire three hours of my radio show as a podcast, commercial-free every single day, become a member of Pragertopia. You'll also get access to 15 years' worth of archives, as well as daily show prep. Subscribe today at Pragertopia dot com.See omnystudio.com/listener for privacy information.

This week Ed and Lee spend time with Judith Curry, Ph.D. (@CurryJA), Professor Emeritus at Georgia Tech's School of Earth and Atmospheric Sciences.  She has decades a climate scientist and provides some context for the current climate hysteria.  You can find her blog HERE.  Her most recent book "Climate Uncertainty and Risk: Rethinking Our Response" is available HERE.Email us at Comments@LetsThinkPodcast.comTwitter: @LetsThinkPodca2Gettr:  @LetsThinkPodInstagram:  LetsThinkAboutThatPodcast

https://www.youtube.com/watch?v=4rfVhsOCs4w #2023 #art #music #movies #poetry #poem #photooftheday #volcano #news #weather #climate #horse #monkeys #puppy #fyp #love #instagood #onelove #eyes #getyoked #horsie #gotmilk #book #shecomin #getready

Judith A. Curry is a climatologist, the founder of Climate Forecast Applications Network, and the author of a new book: Climate Uncertainty and Risk: Rethinking Our Response. In her third appearance on the podcast (the last was December 27, 2022) Curry talks about her new book, the “oversimplified analysis” of climate that's being used by legacy media and policymakers, censorship, the importance of Twitter, and why we need to see the global climate as a “complex, chaotic, non-linear system.” (Recorded August 18, 2023.)

In this episode, I speak with Dr. Judith Curry, a leading climatologist and global thinker on climate change and public policy discourse with numerous recognitions and awards. In our discussion, we talk about different climate-related narratives, the current state of scientific inquiry in the field, the politicisation of science in policymaking, her experience of US congressional testimonies, and her personal journey and story. What I really liked about our discussion was her message of hope, especially for young people, which is also reflected in her latest book "Climate Uncertainty and Risk: Rethinking Our Response". Notes: Curry, J., 2023. Climate Uncertainty and Risk: Rethinking Our Response. Anthem Press. Curry, J.A. and Webster, P.J., 2011. Climate science and the uncertainty monster. Bulletin of the American Meteorological Society, 92(12), pp.1667-1682. https://www.budget.senate.gov/download/testimony-curry

Judith Curry joins us to chat about Climate Uncertainty and Risk and the commons sense solutions to our global warming and climate change. We chat about climategate and how she became skeptical of the narrative and realized this was not a workable solution.   We chat about C02 and if it actually creates warming, the forecast models, propaganda from the alarmists, what happened to Tim Ball, dismissing the grand solar maximum, why this new 'heat index' is in the media now, the heat measuring stations and the issue with them, forecast models, net zero and the problem with rapid transition.   In the second half we chat about India and China, wind and solar, LNG, electrifying Africa, fixing poverty vs supposed climate change solutions, localized risk management and solutions, nuclear, new technologies, problems with getting wind and solar approved in USA, and NASA. Are chemtrails real? Does geoengineering and weather modification have an impact? Will carbon taxing work? What about ESG? What about climate tech and informatech?   We also talk about group think, politics in science, risk perception, covid and climate change, Agenda 21 and Agenda 2030, letting the markets take care of some of this and will there be an expertise crisis?   Climate Etc. is hosted by Judith Curry.  "Climate Uncertainty and Risk: Rethinking Our Response" is her latest book.   Judith is President (co-owner) of Climate Forecast Applications Network (CFAN).  Previously, I was Professor and Chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology.     Climate Etc. is hosted by Judith and  provides a forum for climate researchers, academics and technical experts from other fields, citizen scientists, and the interested public to engage in a discussion on topics related to climate science and the science-policy interface.   You are free to share or remix anything from Climate Etc., following the guidelines of Creative Commons.   https://www.amazon.com/Climate-Uncertainty-Risk-Environment-Sustainability/dp/1839989254/ref=sr_1_1?crid=15Y0HOH78PS0T&keywords=judith+curry&qid=1690338749&sprefix=judith+curry%2Caps%2C127&sr=8-1   https://judithcurry.com/about/   To gain access to the second half of show and our Plus feed for audio and podcast please clink the link http://www.grimericaoutlawed.ca/support.   For second half of video (when applicable and audio) go to our Substack and Subscribe. https://grimericaoutlawed.substack.com/ or to our Locals  https://grimericaoutlawed.locals.com/   If you would rather watch: https://rokfin.com/stream/37135 https://grimericaoutlawed.locals.com/post/4338434/judith-curry-climate-uncertainty-and-risk-reclaiming-our-response https://rumble.com/v32ll7k-judith-curry-climate-uncertainty-and-risk-rethinking-our-response.html   Help support the show, because we can't do it without ya. If you value this content with 0 ads, 0 sponsorships, 0 breaks, 0 portals and links to corporate websites, please assist. Many hours of unlimited content for free. Thanks for listening!!   Support the show directly: https://grimerica.ca/support-2/ Our Audiobook Site: www.adultbrain.ca Our Audiobook Youtube Channel:  https://www.youtube.com/@adultbrainaudiobookpublishing/videos Grimerica Media Youtube Channel: https://www.youtube.com/@grimerica/featured Darren's book www.acanadianshame.ca Check out our next trip/conference/meetup - Contact at the Cabin www.contactatthecabin.com Other affiliated shows: www.grimerica.ca The OG Grimerica Show www.Rokfin.com/Grimerica Our channel on free speech Rokfin Join the chat / hangout with a bunch of fellow Grimericans  Https://t.me.grimerica https://www.guilded.gg/chat/b7af7266-771d-427f-978c-872a7962a6c2?messageId=c1e1c7cd-c6e9-4eaf-abc9-e6ec0be89ff3   Get your Magic Mushrooms delivered from: Champignon Magique  Mushroom Spores, Spore Syringes, Best Spore Syringes,Grow Mushrooms Spores Lab Get Psychedelics online Leave a review on iTunes and/or Stitcher: https://itunes.apple.com/ca/podcast/grimerica-outlawed http://www.stitcher.com/podcast/grimerica-outlawed Sign up for our newsletter http://www.grimerica.ca/news SPAM Graham = and send him your synchronicities, feedback, strange experiences and psychedelic trip reports!! graham@grimerica.com InstaGRAM https://www.instagram.com/the_grimerica_show_podcast/  Purchase swag, with partial proceeds donated to the show www.grimerica.ca/swag Send us a postcard or letter http://www.grimerica.ca/contact/ ART - Napolean Duheme's site http://www.lostbreadcomic.com/  MUSIC Tru Northperception, Felix's Site sirfelix.bandcamp.com

In her book, Climate Uncertainty and Risk, Dr. Judith Curry describes how the climate science community has been captured by certain points of view concerning society and the desire for consensus, undermining its pursuit of objective facts. Climate change claims are fraught with uncertainty, only to be shrouded in secrecy for those who seek real-world data. The result is a society that bases it's policy decisions of improper, and often incorrect, scientific assertions, rather than advancing human wellbeing.

In her book, Climate Uncertainty and Risk, Dr. Judith Curry describes how the climate science community has been captured by certain points of view concerning society and the desire for consensus, undermining its pursuit of objective facts. Climate change claims are fraught with uncertainty, only to be shrouded in secrecy for those who seek real-world data. The result is a society that bases it's policy decisions of improper, and often incorrect, scientific assertions, rather than advancing human wellbeing.

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Recently, respected climatologist Dr. Judith Curry published a new book, "Climate Uncertainty and Risk: Rethinking Our Response." This book helps us rethink the climate change problem, the risks we are facing, and how we can respond to these challenges. Understanding the deep uncertainty surrounding the climate change problem helps us to better assess what the proper course of action our society should take. This book shows how uncertainty and disagreement can be part of the decision-making process. It provides a road map for formulating pragmatic solutions.Tune in to the show for a review by the Dr. Curry herself. We'll also take a look at some of the silliest climate news of the week!

Recently, respected climatologist Dr. Judith Curry published a new book, "Climate Uncertainty and Risk: Rethinking Our Response." This book helps us rethink the climate change problem, the risks we are facing, and how we can respond to these challenges. Understanding the deep uncertainty surrounding the climate change problem helps us to better assess what the proper course of action our society should take. This book shows how uncertainty and disagreement can be part of the decision-making process. It provides a road map for formulating pragmatic solutions.Tune in to the show for a review by the Dr. Curry herself. We'll also take a look at some of the silliest climate news of the week!

Professor Judith A. Curry discusses her new book, "Climate Uncertainty and Risk." The conversation delves into the inadequacy of global climate models in predicting regional climate change and extreme weather events. Professor Curry sheds light on the inappropriate use of climate model output in shaping public policy decisions. The discussion also explores the complex nature of climate change, the underestimation of volcanic activity in climate modeling, and the limitations of cost-benefit analysis in policy formulation.Get Professor Curry's Book here - https://amzn.to/3NnNObqVisit my NEW Website! https://openmindspodcast.com/Check out my Instagram/Tik Tok for daily posts: Instagram @openmindspodTiktok @openmindspodcast

Joe Selvaggi talks with climate expert Dr. Judith Curry about the insights contained in her newly released book, Climate Uncertainty and Risk: Rethinking our Response, in which she tracks the evolution of climate science from model development, to political weapon, to an emerging view that the best response to a changing climate is to build […]

Joe Selvaggi talks with climate expert Dr. Judith Curry about the insights contained in her newly released book, Climate Uncertainty and Risk: Rethinking our Response, in which she tracks the evolution of climate science from model development, to political weapon, to an emerging view that the best response to a changing climate is to build resiliency.

Join us in this enlightening episode as we delve into the complex world of climate science and policy with renowned climate scientist, Dr. Judith Curry. In a candid and thought-provoking interview, Dr. Curry shares her unique perspective on the ongoing climate change debate, offering insights that challenge conventional narratives and encourage a deeper understanding of this critical global issue. As a former professor and chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology, Dr. Curry brings a wealth of knowledge and experience to the table. We explore the nuances of climate modeling, the role of natural variability in shaping our climate, and the challenges of separating scientific inquiry from political agendas. With her fearless approach to questioning established consensus, she urges listeners to think critically and consider the uncertainties that exist in our understanding of Earth's complex climate system. Everything can and should be questioned! Judith's new book: Climate Uncertainty and Risk: Rethinking Our Response is out now! You can also listen in to other interviews she has done such as: The Jordan B Peterson Podcast: The Models Are OK, the Predictions Are Wrong | Dr. Judith Curryyoutube.comhttps://www.youtube.com › watch BizNewsTv: dissident climatologist Dr Judith Curry on climate changeyoutube.comhttps://www.youtube.com › watch Don't forget to subscribe and leave us a review to help spread the word. Stay tuned for more captivating interviews with experts and thought leaders shaping our world. Find Judith here: https://judithcurry.com https://twitter.com/curryja Order her new book here: https://www.amazon.com/Climate-Uncertainty-Risk-Environment-Sustainability/dp/1839989254/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=1686064283&sr=8-1 - Make sure to follow us on instagram and subscribe on YouTube and Spotify to not miss any new episodes! https://www.instagram.com/paintmymindpodcast/ https://www.youtube.com/@paintmymindpodcast

Current debates over climate change are focused almost entirely on reducing emissions - which is something we should do - but we also need to answer the question, how should we be adapting? MIT's Robert Pindyck shares what we know and don't know and how we can adapt given the enormous climate uncertainty.

Nick talks to climatologist Dr. Judith Curry, the former chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology. Her research interests have included hurricanes, atmospheric modeling, air-sea interactions, and a variety of other areas in climate science. She runs Climate, Etc., an online blog focused on climate science. She is also writing a new book called, “Climate Uncertainty & Risk,” which she described towards the end of the podcast. They discuss: how Earth's climate has changed over time and how climate scientists measure this; what computer models are used for in climate science and what their strengths & weaknesses are; tropical storms and severe weather events; CO2, methane, and other greenhouse gasses; different forms of energy, such as oil, natural gas, solar, wind, and nuclear; how she thinks about the tradeoffs between different energy sources in terms of their abundance, environmental impact, costs, and other factors; the politicization of climate science and why certain branches of science are especially prone to it.Support M&M:Sign up for the weekly Mind & Matter newsletter[https://mindandmatter.substack.com/?sort=top]The Amino Co., shop science-back amino acids supplements. Use code ‘MIND' to save 30%.[aminoco.com/MIND]Follow Nick's work through Linktree:[https://linktr.ee/trikomes]Organize your digital highlights & notes w/ Readwise (2 months free w/ sub)[https://readwise.io/nickjikomes/]Learn more about our podcast sponsor, Dosist[https://dosist.com]Support the show

Some farmers and crop consultants are asking questions about what crops should really be planted and where.