{"id":428032,"date":"2026-02-26T15:07:39","date_gmt":"2026-02-26T14:07:39","guid":{"rendered":"https:\/\/climatescience.press\/?p=428032"},"modified":"2026-02-26T15:07:41","modified_gmt":"2026-02-26T14:07:41","slug":"claim-strongest-noreasters-are-getting-stronger-reality-low-confidence-and-fragile-trends","status":"publish","type":"post","link":"https:\/\/climatescience.press\/?p=428032","title":{"rendered":"Claim: Strongest Nor&#8217;easters Are Getting Stronger. Reality: Low Confidence and Fragile Trends"},"content":{"rendered":"<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" width=\"687\" height=\"1024\" data-attachment-id=\"428049\" data-permalink=\"https:\/\/climatescience.press\/?attachment_id=428049\" data-orig-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0-Noreasters1.jpg?fit=784%2C1168&amp;ssl=1\" data-orig-size=\"784,1168\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}\" data-image-title=\"0-Nor&amp;#8217;easters1\" data-image-description=\"\" data-image-caption=\"\" data-large-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0-Noreasters1.jpg?fit=687%2C1024&amp;ssl=1\" src=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0-Noreasters1.jpg?resize=687%2C1024&#038;ssl=1\" alt=\"\" class=\"wp-image-428049\" srcset=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0-Noreasters1.jpg?resize=687%2C1024&amp;ssl=1 687w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0-Noreasters1.jpg?resize=201%2C300&amp;ssl=1 201w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0-Noreasters1.jpg?resize=768%2C1144&amp;ssl=1 768w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0-Noreasters1.jpg?resize=640%2C953&amp;ssl=1 640w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0-Noreasters1.jpg?w=784&amp;ssl=1 784w\" sizes=\"auto, (max-width: 687px) 100vw, 687px\" \/><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The IPCC&#8217;s AR6 Working Group I Report, specifically Chapter 11 (&#8220;Weather and Climate Extreme Events in a Changing Climate&#8221;), provides a careful, consensus-based assessment of extratropical cyclones (ETCs), which include Nor&#8217;easters as a regional subset in the western North Atlantic.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AR6 explicitly states:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong><em>\u201cThere is low confidence in past changes of maximum wind speeds and other measures of dynamical intensity of extratropical cyclones.\u201d<\/em><\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Large natural variability (e.g., influenced by modes like the North Atlantic Oscillation).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Inhomogeneities and limitations in historical data and reanalyses (e.g., fewer observations pre-satellite era).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Lack of robust, consistent trends across datasets for dynamical intensity metrics like maximum winds or central pressure deepening rates.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AR6 assesses with medium confidence that future changes in overall ETC dynamical intensity (e.g., maximum wind speeds) &#8220;will be small&#8221;, though poleward shifts in storm tracks could lead to substantial regional changes in extreme wind speeds (increases in some areas, decreases in others).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">_________________________________________________________________________________________________________<\/p>\n\n\n\n<p class=\"has-large-font-size wp-block-paragraph\"><strong>Are the Strongest Nor&#8217;easters Getting Stronger? A Closer Look<\/strong><\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\"><br>From <a href=\"https:\/\/rogerpielkejr.substack.com\/p\/are-the-strongest-noreasters-getting\">The Honest Brocker<\/a><\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">by <a href=\"https:\/\/substack.com\/@rogerpielkejr\">Roger Pielke Jr.<\/a><\/p>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\"><strong>A case study in confidence inflation in climate science<\/strong><\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" width=\"720\" height=\"720\" data-attachment-id=\"428035\" data-permalink=\"https:\/\/climatescience.press\/?attachment_id=428035\" data-orig-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?fit=720%2C720&amp;ssl=1\" data-orig-size=\"720,720\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}\" data-image-title=\"image\" data-image-description=\"\" data-image-caption=\"\" data-large-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?fit=720%2C720&amp;ssl=1\" src=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=720%2C720&#038;ssl=1\" alt=\"\" class=\"wp-image-428035\" srcset=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?w=720&amp;ssl=1 720w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=300%2C300&amp;ssl=1 300w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=150%2C150&amp;ssl=1 150w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=640%2C640&amp;ssl=1 640w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=600%2C600&amp;ssl=1 600w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=400%2C400&amp;ssl=1 400w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=200%2C200&amp;ssl=1 200w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=450%2C450&amp;ssl=1 450w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=60%2C60&amp;ssl=1 60w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=550%2C550&amp;ssl=1 550w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-407.png?resize=50%2C50&amp;ssl=1 50w\" sizes=\"auto, (max-width: 720px) 100vw, 720px\" \/><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\"><em>UPDATE 2\/25: After publishing this piece I was asked to write a related column for&nbsp;<a href=\"https:\/\/www.thefp.com\/\">The Free Press<\/a>. You can read my column&nbsp;<a href=\"https:\/\/www.thefp.com\/p\/buried-by-snow-and-by-shaky-science\">here<\/a>&nbsp;(apologies for any paywalls). If you are visiting THB for the first time from that column, Welcome! \u2014 RP<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">As New England digs out from a historic blizzard, today\u2019s post takes a deep and technical dive into&nbsp;<a href=\"https:\/\/www.pnas.org\/doi\/10.1073\/pnas.2510029122\">recent research \u2014 Chen et al. 2025<\/a><a href=\"https:\/\/rogerpielkejr.substack.com\/p\/are-the-strongest-noreasters-getting#footnote-1-189012212\">1<\/a>&nbsp;\u2014 claiming that&nbsp;<a href=\"https:\/\/www.weather.gov\/safety\/winter-noreaster\">Nor\u2019easters<\/a>&nbsp;have become detectably more intense over recent decades. That research asserts,<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\">Our analysis of nor\u2019easter characteristics reveals that the strongest nor\u2019easters are becoming stronger . . .<\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">Taking advantage of AI tools, I have replicated and extended the analysis. As is far too common in high profile climate research, the top-line claims of the paper do not survive scrutiny. Public commentary by the paper\u2019s senior author and subsequent media reporting provide a case study in how uncertain and ambiguous findings are turned into strong claims expressed with absolute certainty.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Grab your coffee, settle in and let\u2019s take a deep dive. Last July, a paper in&nbsp;<em><a href=\"https:\/\/www.pnas.org\/doi\/10.1073\/pnas.2510029122\">PNAS<\/a><\/em>&nbsp;by Chen and colleagues was accompanied by widespread media coverage claiming that the new paper was the first and last word on trends in the intensification of nor\u2019easters. For example:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><em>Live Science<\/em>&nbsp;<a href=\"https:\/\/www.livescience.com\/planet-earth\/climate-change\/noreasters-have-become-20-percent-more-destructive-in-the-last-80-years-scientists-warn\">reported<\/a>&nbsp;that nor\u2019easters \u201chave become 20% more destructive in the last 80 years.\u201d<\/li>\n\n\n\n<li><em>Inside Climate News<\/em>&nbsp;<a href=\"https:\/\/insideclimatenews.org\/news\/14072025\/northeast-global-warming-impacts-noreasters\/\">declared<\/a>&nbsp;that \u201cthe strongest ones are clearly getting stronger.\u201d<\/li>\n\n\n\n<li>The Weather Network,&nbsp;<a href=\"https:\/\/www.theweathernetwork.com\/en\/news\/weather\/severe\/the-strongest-noreasters-are-getting-even-stronger-study-finds\">revisiting the study in December<\/a>, announced that nor\u2019easters are \u201cgrowing more intense and producing more rain and snow than ever before.\u201d<\/li>\n\n\n\n<li>The University of Pennsylvania\u2019s&nbsp;<a href=\"https:\/\/omnia.sas.upenn.edu\/story\/strongest-noreasters-getting-stronger-Michael-Mann\">press release<\/a>&nbsp;on the paper called its findings \u201cunquestionable.\u201d<\/li>\n\n\n\n<li>Michael E. Mann, the paper\u2019s senior author and a climate scientist at the University of Pennsylvania, in his accompanying&nbsp;<a href=\"https:\/\/michaelmann.net\/the-intensification-of-the-strongest-noreasters\/\">blog post<\/a>, stated that intensification \u201ccan now be seen in the observations.\u201d<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">A closer reading of the paper shows that none of the above claims are a true reflection of what the paper actually says, supported by a simple extension of its methods and analysis.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Note: This post is a first experiment fully implementing my new use of AI for quantitative research \u2013 see&nbsp;<a href=\"https:\/\/rogerpielkejr.substack.com\/p\/how-i-use-ai\">How I use AI<\/a>&nbsp;for more details. Today, I explore Chen et al., its supplementary materials, and the relevant ERA5 reanalysis literature. For readers interested in the quantitative details, please find more technical detail, data, and replication code for my analyses at the bottom of this post. Caveat lector!<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.weather.gov\/safety\/winter-noreaster\">Nor\u2019easters<\/a>&nbsp;are among the most consequential weather events affecting the densely populated U.S. East Coast, into New England and the Canadian maritime provinces. If the most intense storms have become detectibly more intense, and are expected to continue to do so, that has important implications for urban planning and decision making in other settings.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The bottom line: Chen et al. take on a worthwhile question but its headline claims, and those that followed publication, go meaningfully beyond what the data can currently support. Follow-on public discussion by its senior authors and in the media depart even further from what evidence and analysis can support. Worthwhile findings of uncertainty and ambiguity are transformed into unquestioned certainty in support of a narrative that everything is getting worse.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What Chen et al. did and what they found<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Chen et al. use&nbsp;<a href=\"https:\/\/doi.org\/10.1002\/qj.3803\">ERA5<\/a>&nbsp;\u2014 the European Centre for Medium-Range Weather Forecasts\u2019 global&nbsp;<em>reanalysis&nbsp;<\/em>\u2014 to construct a historical record of<em>&nbsp;<\/em>nor\u2019easters<em>&nbsp;<\/em>from 1940 to 2025. A nor\u2019easter is a powerful, large-scale low-pressure storm system, called an&nbsp;<a href=\"https:\/\/marrella.aos.wisc.edu\/ExtratropicalCyclones_Martin_2024.pdf\">extratropical cyclone (ETC)<\/a>, that forms along the east coast of North America, characterized by winds blowing from the northeast (giving such storms their common name), often accompanied by heavy rain or snow.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A&nbsp;<em>reanalysis<\/em>&nbsp;can be understood as a retrospective weather forecast: historical weather observations \u2014 from sources such as weather balloons, ships, land stations, and eventually satellites \u2014 are fed into a numerical weather model to reconstruct the historical state of the global atmosphere.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Ideally, the result is a consistent, gridded dataset of weather variables covering the entire planet, filling in gaps where direct observations were never made. ERA5 is the most widely used reanalysis in climate research. As we will see, going back further in time, reanalysis quality is far from uniform, and the creators of such datasets warn about its use for long-term trend analyses.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Using the ERA5 reanalysis, Chen et al. identify 900 storms from 1940 to 2024<a href=\"https:\/\/rogerpielkejr.substack.com\/p\/are-the-strongest-noreasters-getting#footnote-2-189012212\">2<\/a>&nbsp;that meet their criteria for an ETC. With this time series they apply a statistical technique called&nbsp;<em>quantile regression<\/em>&nbsp;to explore whether the intensity of the strongest ETCs has changed over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Quantile regression allows for a focus on extremes rather than just averages, enabling quantification of whether, for instance, the intensity of the top 10%, top 5%, or top 1% of storms have detectably changed over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Chen et al. report that from 1940\u20132025 record, the peak wind speeds of the most intense nor\u2019easters \u2014 those in the top 1% (that is, about 9 storms) \u2014 increased by approximately 6%, from ~31 m\/s (~69 mph) at the start of the record to ~33 m\/s (~74 mph) by its end. The trend for the top quarter of storms (75th percentile and above) is similar in magnitude.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The authors then apply a damage-scaling relationship to translate this wind speed increase into a headline impact figure: asserting that economic loss potential is proportional to the cube of wind speed. They assert that a 6% increase in peak winds implies a ~20% increase in destructive power (see&nbsp;<a href=\"https:\/\/doi.org\/10.1098\/rsta.2007.2086\">Pielke 2007<\/a>&nbsp;for a discussion of the sensitivity of damage estimates to assumptions about wind-damage scaling exponents).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The math is straightforward. Whether the underlying 6% increase in peak wind speed trend is real and \u201cunquestionable,\u201d however, does not stand up to scrutiny.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The paper also includes a very useful supplementary analysis: It includes a test of whether the results of 1940-2024 hold up when restricted to the era when data from satellites was systematically available (1979\u20132024). The satellite era is the period when global weather observations, and thus global reanalysis, became far more comprehensive and reliable, as described in a recent overview \u2014&nbsp;<a href=\"https:\/\/doi.org\/10.1002\/qj.4803\">The ERA5 global reanalysis from 1940 to 2022<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The supplementary analysis to Chen et al. includes information that dramatically undercuts the headline findings that were picked up and amplified by the media.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What the PNAS Supplementary Analysis to Chen et al. actually shows<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A close look at the supplementary analysis reveals results that depart from the paper\u2019s headline results.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Specifically, the satellite-era analysis (1979-2024) does show nominally significant trends \u2014 but they are concentrated in the 60th to 78th percentile range of storm intensity, not at the extreme tail, as claimed in the main body of the text.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For the very strongest storms (95th and 99th percentiles) that Mann\u2019s post-publication&nbsp;<a href=\"https:\/\/michaelmann.net\/the-intensification-of-the-strongest-noreasters\/\">blog post<\/a>&nbsp;emphasizes, the satellite-era statistical significance does not reach conventional thresholds of significance. That means that the paper\u2019s headline \u2014 the strongest storms getting stronger \u2014 is least well supported in the most trustworthy portion of the dataset of the satellite observational era.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In the paper, the authors emphasize a sensitivity analysis that starts their analysis in 1950 rather than 1940 \u2014 trimming just a single decade from the pre-satellite period. But even in this alternative analysis, statistical significance almost completely disappears across the distribution, as you can see in the image below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" width=\"723\" height=\"395\" data-attachment-id=\"428036\" data-permalink=\"https:\/\/climatescience.press\/?attachment_id=428036\" data-orig-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?fit=1721%2C941&amp;ssl=1\" data-orig-size=\"1721,941\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}\" data-image-title=\"0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941\" data-image-description=\"\" data-image-caption=\"\" data-large-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?fit=723%2C395&amp;ssl=1\" src=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?resize=723%2C395&#038;ssl=1\" alt=\"\" class=\"wp-image-428036\" srcset=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?resize=1024%2C560&amp;ssl=1 1024w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?resize=300%2C164&amp;ssl=1 300w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?resize=768%2C420&amp;ssl=1 768w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?resize=1536%2C840&amp;ssl=1 1536w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?resize=640%2C350&amp;ssl=1 640w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?resize=1200%2C656&amp;ssl=1 1200w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?w=1721&amp;ssl=1 1721w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0eda214a9-fd72-4514-8e71-db4c33b5810d_1721x941.png?w=1446&amp;ssl=1 1446w\" sizes=\"auto, (max-width: 723px) 100vw, 723px\" \/><figcaption class=\"wp-element-caption\">Disappearing significance. Top panel, From Figure 4 in main text. Bottom panel, From figure S3 in SI. Annotations added by me.<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">The sensitivity analysis clearly indicates that one decade of early, sparse data is doing an enormous amount of work in generating the headline result. This inconvenient information is reported in the supplementary material but not discussed in the paper, in the university press release, or the senior author\u2019s blog post on the paper. But that is just the start of problems with the headline results<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The ERA5 Problem<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">As a model-based reconstruction of the atmosphere that incorporates historical weather observations, ERA5&nbsp;<a href=\"https:\/\/rmets.onlinelibrary.wiley.com\/doi\/10.1002\/qj.4803\">does not incorporate a uniform observational record<\/a>&nbsp;over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The number and quality of those observations has changed dramatically over time. For instance, in 1940, ERA5 was working with roughly&nbsp;<a href=\"https:\/\/doi.org\/10.1002\/qj.4803\">17,000 global observations per day<\/a>, almost entirely from land stations and ships, with virtually no coverage over the open ocean. By 2022, that number had grown to&nbsp;<a href=\"https:\/\/doi.org\/10.1002\/qj.4803\">25 million observations per day<\/a>, with global satellite coverage providing near-complete atmospheric profiles worldwide. The&nbsp;<a href=\"https:\/\/doi.org\/10.1002\/qj.4174\">preliminary back-extension to 1950<\/a>&nbsp;was released with explicit caveats about uncertainties and cautions about its use in research.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Logically, any reanalysis that is data-sparse over the ocean over the 1940s to 70s and data-rich from 1979 onward will tend to show apparent improvement in storm intensity over time, partly reflecting improved data coverage rather than real changes in storm behavior.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Independent validation studies confirm that&nbsp;<a href=\"https:\/\/doi.org\/10.1080\/21664250.2023.2301181\">ERA5 systematically underestimates wind speeds within extratropical cyclone centers, with elevated errors near the storm core and in the Gulf Stream region<\/a>&nbsp;where nor\u2019easters intensify most explosively. Other research suggests that&nbsp;<a href=\"https:\/\/doi.org\/10.1002\/joc.8339\">biases in intensity estimates of the top 5% most extreme ETCs may be a negative bias of ~10%, with ERA5 performance deteriorating further for local extreme values within storms<\/a>&nbsp;\u2014 the events at the focus of Chen et al..<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Chen et al. does not engage with any of this literature.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To put these uncertainties in concrete terms: The paper\u2019s headline finding is a ~6% increase in peak wind speeds over 85 years, corresponding to a trend of roughly 0.2 m\/s per decade at the 99th percentile. ERA5\u2019s known negative bias for extreme extratropical cyclone winds is ~10% \u2014 and that bias is not constant over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Again logically, because ERA5 is data-sparse over the western Atlantic in the early decades and data-rich after 1979, the reanalysis almost certainly underestimates early-record wind speeds more severely than late-record ones. That means that any improvement in observational coverage from 1940 to 2025 could generate a spurious apparent trend of comparable magnitude to the claimed signal detected in Chen et al..<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This does not mean the asserted trend detected by Chen et al. is necessarily an artifact of observational system and coverage changes. But it does mean the reanalysis data cannot currently be used to distinguish a real trend from a measurement artifact. That itself is an important and worthwhile finding, even if not ready made for climate headlines.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That brings us to the importance of rigorous standards for detection and attribution, as established by the Intergovernmental Panel on Climate Change (IPCC).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Chen et al. in context of the IPCC framework for detection and attribution<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Whether ETCs have increased in intensity on climate timescales is ultimately a&nbsp;<a href=\"https:\/\/www.ipcc.ch\/report\/ar6\/wg1\/chapter\/chapter-10\/\">detection and attribution<\/a>&nbsp;question: Has a change in the statistics of ETCs been detected in nor\u2019easter intensity? If so, then we next ask about attribution: Can a detected change be attributed to human or natural factors, or perhaps both?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Achieving detection and\/or attribution requires a robust evidence base, including: multiple independent datasets, multiple methods, often reinforced by earth system model simulations that can reproduce the observed change through known mechanisms.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Let\u2019s review what AR6 actually says about extratropical cyclones. On past changes,&nbsp;<a href=\"https:\/\/www.ipcc.ch\/report\/ar6\/wg1\/chapter\/chapter-11\/\">AR6 Chapter 11<\/a>&nbsp;is explicit:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\">\u201cThere is&nbsp;<em>low confidence<\/em>&nbsp;in past changes of maximum wind speeds and other measures of dynamical intensity of extratropical cyclones.\u201d<\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">For projections, AR6 is carefully hedged, stating with medium confidence that for future changes in overall ETC intensity, \u201cin the future, these changes will be small,\u201d but their location and tracks may also change, along with other nuances.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The AR6 also evaluates&nbsp;<a href=\"https:\/\/www.ipcc.ch\/report\/ar6\/wg1\/chapter\/chapter-12\/\">time-of-emergence<\/a>&nbsp;for ETC wind extremes.&nbsp;<a href=\"https:\/\/rogerpielkejr.substack.com\/p\/its-later-than-you-think\">Time of emergence<\/a>&nbsp;is the point at which a change in a particular weather or climate variable over decades or longer becomes large enough relative to climate variability to be robustly detectable in observations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For extratropical cyclone wind speeds, AR6 concludes that this threshold has not yet been crossed, and does not expect it to be crossed any time soon (the strongest claim the IPCC makes is with medium confidence, i.e., 50-50 or \u201cas likely as not\u201d) even under the most extreme and implausible climate scenario available for projections.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In plain language: even if ETCs are becoming more intense, the IPCC AR6 concludes the noise of natural variability will obscure that signal throughout this century. Logically, that means that the IPCC expects any such signal to be small in the context of variability, and not detectible in 2026.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To complete this discussion, I\u2019ll review what would be needed for a robust detection claim:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>The detected signal must be distinguishable from internal variability.<\/strong>&nbsp;The satellite-era trend in ETC intensity is small relative to year-to-year variability, even over that 46-year period \u2014 Hence the low statistical significance.<a href=\"https:\/\/rogerpielkejr.substack.com\/p\/are-the-strongest-noreasters-getting#footnote-3-189012212\">3<\/a>&nbsp;Large-scale climate modes operating on decadal timescales \u2014 such as the&nbsp;<a href=\"https:\/\/www.ncei.noaa.gov\/access\/monitoring\/nao\/\">North Atlantic Oscillation<\/a>,&nbsp;<a href=\"https:\/\/psl.noaa.gov\/data\/timeseries\/AMO\/\">Atlantic Multidecadal Oscillation<\/a>, and&nbsp;<a href=\"https:\/\/psl.noaa.gov\/pdo\/\">Pacific Decadal Oscillation<\/a>&nbsp;\u2014 produce changes in extratropical storm activity that are distinct from long-term forcing. The 46-year satellite record is short compared to these modes, making it difficult to distinguish a forced trend from internal variability.<\/li>\n\n\n\n<li><strong>Any detected signal must be robust across methods and datasets.<\/strong>&nbsp;Chen et al.\u2019s supplementary material shows that the result is sensitive to start date (e.g., near-null from 1950, as shown above), to statistical method (e.g., the sensitivity analysis in the Chen et al. supplementary material indicates that&nbsp;<a href=\"https:\/\/en.wikipedia.org\/wiki\/Kendall_rank_correlation_coefficient\">Mann-Kendall<\/a>&nbsp;significance concentrates in the 62nd\u201385th percentile, not the extreme tail), and to storm radius choice.<a href=\"https:\/\/rogerpielkejr.substack.com\/p\/are-the-strongest-noreasters-getting#footnote-4-189012212\">4<\/a>&nbsp;The paper uses no independent reanalysis \u2014&nbsp;<a href=\"https:\/\/www.data.jma.go.jp\/jra\/html\/JRA-55\/index_en.html\">JRA-55<\/a>,&nbsp;<a href=\"https:\/\/gmao.gsfc.nasa.gov\/gmao-products\/merra-2\/\">MERRA-2<\/a>, or the&nbsp;<a href=\"https:\/\/psl.noaa.gov\/data\/20thC_Rean\/\">20th Century Reanalysis<\/a>&nbsp;\u2014 to assess the robustness of the findings, which are based solely on ERA5.<\/li>\n\n\n\n<li><strong>For attribution claims, any detected signal must be consistent with model-based attribution.<\/strong>&nbsp;The paper offers a hypothesized physical mechanism for intensifying nor\u2019easters (warming Atlantic sea surface temperatures feeding nor\u2019easter intensification) but provides no model-based attribution analysis. The data presented and statistical analysis are not suggestive that any such attribution analysis is even appropriate. Attribution claims of Chen et al. are entirely speculative.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Taken together, these factors would, in my view, lead to a&nbsp;<em>low confidence<\/em>&nbsp;finding by IPCC standards. That is very different from \u201cour study demonstrates that this [trend in intensity] can now be seen in the observations.\u201d<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>From Research to Spin<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Chen et al. does not discuss that the results are sensitive to start-date choice, that the satellite-era robustness check concentrates significance in the middle of the distribution rather than the extreme tail, or that the analysis leaves natural decadal variability and ERA5\u2019s temporal inhomogeneities unaddressed.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Following publication, Mann presents the marginal (at best) findings as a demonstration of established fact, invokes a wind-speed-cubed adjustment to the small findings to generate impressive-sounding numbers related to real-world damage, and omits the contradictory evidence included in the paper\u2019s supplementary material.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Other than that, how was the play Mrs. Lincoln?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The over-hyping of results and shedding of uncertainty and complexity is a pattern we often see in high-profile climate research and chronicled in detail over the years here at THB. Loose standards of scientific quality may help to generate breathless headlines but does not serve improved scientific understandings or public confidence in climate science.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Postscript: Methods and Replication Files<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>For readers who want to go deeper, below is the technical summary underlying the discussion above. My analysis draws on the paper\u2019s published figures, the supplementary material, and independent analysis of the ERA5 validation literature. I use Claude for the data extraction and coding. An Excel file with data and Python file with code can be found below.<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Table 1: Trend slopes and nominal p-values by analysis window<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The table below shows the estimated trend in nor\u2019easter peak wind speed (in meters per second per decade) at five points in the intensity distribution (quantiles), across five different choices of analysis start date. Results marked [SI] come directly from the authors\u2019 own supplementary figures; results marked [est] are estimated by scaling statistical power from the full-record result and are less reliable.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" width=\"723\" height=\"489\" data-attachment-id=\"428039\" data-permalink=\"https:\/\/climatescience.press\/?attachment_id=428039\" data-orig-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-408.png?fit=1066%2C721&amp;ssl=1\" data-orig-size=\"1066,721\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}\" data-image-title=\"image\" data-image-description=\"\" data-image-caption=\"\" data-large-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-408.png?fit=723%2C489&amp;ssl=1\" src=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-408.png?resize=723%2C489&#038;ssl=1\" alt=\"\" class=\"wp-image-428039\" srcset=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-408.png?resize=1024%2C693&amp;ssl=1 1024w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-408.png?resize=300%2C203&amp;ssl=1 300w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-408.png?resize=768%2C519&amp;ssl=1 768w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-408.png?resize=640%2C433&amp;ssl=1 640w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-408.png?w=1066&amp;ssl=1 1066w\" sizes=\"auto, (max-width: 723px) 100vw, 723px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Table 2: Effective p-values after accounting for ERA5 systematic bias (at the 95th percentile)<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nominal p-values assume the data are unbiased. ERA5\u2019s improving observational coverage over time introduces a systematic bias that can masquerade as a real trend \u2014 particularly in the pre-satellite period. The table below adjusts for this, drawing on published ERA5 validation studies (<a href=\"https:\/\/doi.org\/10.1002\/qj.4803\">Soci et al. 2024<\/a>;&nbsp;<a href=\"https:\/\/doi.org\/10.1002\/qj.4174\">Bell et al. 2021<\/a>;&nbsp;<a href=\"https:\/\/doi.org\/10.1080\/21664250.2023.2301181\">Lodise et al. 2024<\/a>).<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" width=\"723\" height=\"487\" data-attachment-id=\"428041\" data-permalink=\"https:\/\/climatescience.press\/?attachment_id=428041\" data-orig-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-409.png?fit=1087%2C732&amp;ssl=1\" data-orig-size=\"1087,732\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}\" data-image-title=\"image\" data-image-description=\"\" data-image-caption=\"\" data-large-file=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-409.png?fit=723%2C487&amp;ssl=1\" src=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-409.png?resize=723%2C487&#038;ssl=1\" alt=\"\" class=\"wp-image-428041\" srcset=\"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-409.png?resize=1024%2C690&amp;ssl=1 1024w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-409.png?resize=300%2C202&amp;ssl=1 300w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-409.png?resize=768%2C517&amp;ssl=1 768w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-409.png?resize=640%2C431&amp;ssl=1 640w, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/image-409.png?w=1087&amp;ssl=1 1087w\" sizes=\"auto, (max-width: 723px) 100vw, 723px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>A note on methods<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The trend slopes in Table 1 were derived by digitizing the quantile regression trend lines from the paper\u2019s Figure 4A and fitting linear regressions to subsets of each line corresponding to the analysis windows shown. The p-value estimates for windows not directly reported by the authors were scaled from the published full-record p-values using the ratio of statistical power (which scales with the square root of n(n\u00b2\u22121)\/12 for rank-based tests). The ERA5 systematic bias ranges in Table 2 are conservative estimates based on the published validation literature cited above; they represent plausible bounds rather than precise measurements. The satellite-era and 1950-start p-values in Table 1 are taken directly from the authors\u2019 supplementary Figures S2 and S3 respectively and do not rely on scaling.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Further Research and Publication Invitation<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">I do not intend to carry this analysis forward to peer-reviewed publication, though I do think it is well on its way in that direction. If any atmospheric scientist (at any level) is interested in carrying this analysis forward, I invite you to do so. I ask only that (a) you let me know, and (b) as research ethics require, you include me as a co-author \u2014 no ghost authorship here.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/rogerpielkejr.substack.com\/p\/are-the-strongest-noreasters-getting#footnote-anchor-1-189012212\">1<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The authors, all from the University of Pennsylvania, are: Kevin Chen, Xueke Li, Mackenzie M. Weaver, Shannon A. Christiansen, Annabelle L. Horton, and Michael E. Mann.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/rogerpielkejr.substack.com\/p\/are-the-strongest-noreasters-getting#footnote-anchor-2-189012212\">2<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The paper claims throughout that its data spans 2025. This is obviously an error or typo as the data presented go through 2024 (and the paper was submitted in April 2025, obviously well before 2025 data would have been available). This post accurately describes the time period covered in the analysis.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/rogerpielkejr.substack.com\/p\/are-the-strongest-noreasters-getting#footnote-anchor-3-189012212\">3<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Technical point, which is largely irrelevant given the other issues: Chen et al. do not correct for serial autocorrelation in the storm record, which would reduce the effective sample size and push p-values upward. A more sophisticated analyses would consider such details.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/rogerpielkejr.substack.com\/p\/are-the-strongest-noreasters-getting#footnote-anchor-4-189012212\">4<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The primary analysis of Chen et al. uses a 750-km effective radius to define the wind field around each storm, and the supplementary material also explores results at 500 km and 1,000 km. The authors acknowledge that results \u201cvary somewhat\u201d with this alternative methodological choice, but do not discuss the details of the considerable variations. The paper\u2019s abstract and Mann\u2019s blog post also make strong claims about precipitation trends, but these receive far less analytical scrutiny than the wind speed results and are not the focus of thr paper or this post.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u201cThere is low confidence in past changes of maximum wind speeds and other measures of dynamical intensity of extratropical cyclones.\u201d  <\/p>\n<p>AR6 assesses with medium confidence that future changes in overall ETC dynamical intensity (e.g., maximum wind speeds) &#8220;will be small&#8221;, though poleward shifts in storm tracks could lead to substantial regional changes in extreme wind speeds (increases in some areas, decreases in others).<\/p>\n","protected":false},"author":121246920,"featured_media":428051,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","_crdt_document":"","advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[1],"tags":[691834437,691819140,691841642,691840378],"class_list":{"0":"post-428032","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","6":"hentry","7":"category-uncategorized","8":"tag-climate-research","9":"tag-climate-science","10":"tag-noreasters","11":"tag-pnas-study","13":"fallback-thumbnail"},"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/02\/0Screenshot-2026-02-26-150339.png?fit=1093%2C947&ssl=1","jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paxLW1-1NlK","jetpack-related-posts":[{"id":373519,"url":"https:\/\/climatescience.press\/?p=373519","url_meta":{"origin":428032,"position":0},"title":"Rolling Stone: President Trump Falsely Claims Global Warming is Good","author":"uwe.roland.gross","date":"03\/04\/2025","format":false,"excerpt":"But, but, devastating storms\u2026","rel":"","context":"In \"Climate change\"","block_context":{"text":"Climate change","link":"https:\/\/climatescience.press\/?tag=climate-change"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/04\/0lomborg-climate-deaths-chart.webp?fit=1200%2C924&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/04\/0lomborg-climate-deaths-chart.webp?fit=1200%2C924&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/04\/0lomborg-climate-deaths-chart.webp?fit=1200%2C924&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/04\/0lomborg-climate-deaths-chart.webp?fit=1200%2C924&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/04\/0lomborg-climate-deaths-chart.webp?fit=1200%2C924&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":279281,"url":"https:\/\/climatescience.press\/?p=279281","url_meta":{"origin":428032,"position":1},"title":"Hurricane Daniel and the Medicanes: A Dive into Science","author":"uwe.roland.gross","date":"18\/09\/2023","format":false,"excerpt":"The media\u2019s recent fascination with Hurricane Daniel and the phenomenon of \u201cMedicanes\u201d has sparked a flurry of discussions, with many attributing these rare supercharged Mediterranean storms to anthropogenic climate change. But before jumping to conclusions, it\u2019s essential to delve into the science and understand the broader context.","rel":"","context":"In \"Climate change\"","block_context":{"text":"Climate change","link":"https:\/\/climatescience.press\/?tag=climate-change"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/0Screenshot-2023-09-18-114028.png?fit=1194%2C679&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/0Screenshot-2023-09-18-114028.png?fit=1194%2C679&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/0Screenshot-2023-09-18-114028.png?fit=1194%2C679&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/0Screenshot-2023-09-18-114028.png?fit=1194%2C679&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/0Screenshot-2023-09-18-114028.png?fit=1194%2C679&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":310369,"url":"https:\/\/climatescience.press\/?p=310369","url_meta":{"origin":428032,"position":2},"title":"Is climate change to blame for the atmospheric rivers impacting California? 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One could say spotting his name in a paper about \u201cintensification of the strongest nor\u2019easters\u201d is like\u2026","rel":"","context":"In \"Climate fearmongering\"","block_context":{"text":"Climate fearmongering","link":"https:\/\/climatescience.press\/?tag=climate-fearmongering"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/07\/0pnas.2510029122fig02.jpg?fit=1200%2C713&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/07\/0pnas.2510029122fig02.jpg?fit=1200%2C713&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/07\/0pnas.2510029122fig02.jpg?fit=1200%2C713&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/07\/0pnas.2510029122fig02.jpg?fit=1200%2C713&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/07\/0pnas.2510029122fig02.jpg?fit=1200%2C713&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":290894,"url":"https:\/\/climatescience.press\/?p=290894","url_meta":{"origin":428032,"position":4},"title":"Why Tropical Storms Appear To Be More\u00a0Frequent","author":"uwe.roland.gross","date":"11\/12\/2023","format":false,"excerpt":"The \u201cNormal\u201d is based on the 1991-2020 climatology, so is clearly grossly underestimated and a worthless measure.","rel":"","context":"In \"BBC\"","block_context":{"text":"BBC","link":"https:\/\/climatescience.press\/?tag=bbc"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-252.png?fit=1200%2C800&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-252.png?fit=1200%2C800&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-252.png?fit=1200%2C800&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-252.png?fit=1200%2C800&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-252.png?fit=1200%2C800&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":293667,"url":"https:\/\/climatescience.press\/?p=293667","url_meta":{"origin":428032,"position":5},"title":"No Trends In Extratropical Cyclones \u2013\u00a0IPCC","author":"uwe.roland.gross","date":"03\/01\/2024","format":false,"excerpt":"We constantly hear that storms are getting worse because of global warming. 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