How much of this is new policies vs just crazy inflation since 2020? fred.stlouisfed.org/series/CAUCS...
20.08.2025 06:32 β π 0 π 0 π¬ 1 π 0@climatequant.bsky.social
Climate, Extreme Weather, Engineering, Statistics, Public Policy πππ§ππ https://www.djrasmussen.co/
How much of this is new policies vs just crazy inflation since 2020? fred.stlouisfed.org/series/CAUCS...
20.08.2025 06:32 β π 0 π 0 π¬ 1 π 0Many ultra-high-net-worth individuals are drawn to the exclusivity and aesthetic of waterfront property, regardless of the climate risks. The ability to self-insure and pay in cash removes many of the typical financial constraints or regulatory hurdles that would otherwise deter such investments.
06.08.2025 23:46 β π 0 π 0 π¬ 1 π 0Yes. Could be representativeness issues (grid vs point) or other assimilation or model biases. Gridded products β in situ observations. I developed a dataset to deal with these issues: essopenarchive.org/doi/full/10....
29.07.2025 18:24 β π 1 π 0 π¬ 1 π 0Rx burns may have public health benefits, but because those benefits are delayed, theyβre often heavily discounted. That can make them harder to justify in the near term, despite potential long-term payoff
15.07.2025 17:30 β π 1 π 1 π¬ 0 π 0New online Wildfire Mitigation Plan Database from PNNL. Over 400 wildfire mitigation plans from 170 utilities across 19 U.S. states. Useful to understand, compare, and improve strategies for managing wildfire risks to power infrastructure.
www.pnnl.gov/publications...
Glad this issue is getting attention! But isn't this what trend preserving approaches like Cannon et al. (2015) are supposed to help with? LOCA's bias correction may not be trend preserving (not sure)
02.07.2025 05:51 β π 1 π 0 π¬ 1 π 0Iβm an independent climate risk researcher working at the intersection of climate science, infrastructure, and decision-making. I focus on hazard modeling, risk quantification, and integrating social science into climate resilience. More on my work & publications: www.djrasmussen.co (12/12)
17.04.2025 15:55 β π 1 π 0 π¬ 0 π 0Our preliminary estimates are consistent with FEMAβs elevationsβbut are based on 70 years of observations, not modeled storms. They also avoid potentially problematic EV fitting assumptions (e.g., MLE) and include full uncertainty estimates (see: ascmo.copernicus.org/articles/11/...) (11/12)
17.04.2025 15:55 β π 0 π 0 π¬ 1 π 0More work is coming. Weβre expanding this framework (again led by Joao Morim) to develop fully probabilistic estimates of storm surge extremes for the U.S. and select territories (10/12)
17.04.2025 15:55 β π 1 π 0 π¬ 1 π 0π Article: rdcu.be/eh8gu (9/12)
17.04.2025 15:55 β π 2 π 0 π¬ 1 π 0Regardless of attribution, our findings have implications for infrastructure design. Planners and engineers with long horizons should consider storminess w/ sea-level rise. The now-revoked Federal Flood Risk Management Standard (FFRMS) is still a useful reference (8/12) www.fema.gov/sites/defaul...
17.04.2025 15:55 β π 0 π 0 π¬ 1 π 0Though modest in magnitude, Iβd argue these trends matter. Itβs possible that internal climate variability and anthropogenic forcing are exerting opposing influencesβpartially masking the full signal. Disentangling these drivers requires large ensemble simulations (7/12)
17.04.2025 15:55 β π 3 π 0 π¬ 1 π 0We do not directly attribute these changes to anthropogenic climate forcing, but they are consistent with known shifts in sea surface temperatures (SSTs) and mean sea level, both of which are projected to continue rising. (6/12)
17.04.2025 15:55 β π 0 π 0 π¬ 1 π 0These trends have accelerated in several regions since 1975. In hotspotsβespecially the Gulf and Southeast Atlantic coastsβstorm surge extremes are increasing at rates comparable to or exceeding MSL rise. (5/12)
17.04.2025 15:55 β π 0 π 0 π¬ 1 π 0The result: we find robust, spatially coherent trends in storm surge extremes along 70% of the U.S. coastlineβcontradicting the longstanding view that such regional trends in storminess donβt exist.
In some areas, the magnitude of these trends rivals contributors to regional sea-level rise. (4/12)
We use a spatio-temporal Bayesian hierarchical model to combine 70 years of tide gauge data across the U.S. This framework accounts for spatial dependence across sites and quantifies uncertainty in the estimated trends. (3/12)
17.04.2025 15:55 β π 0 π 0 π¬ 1 π 0Previous studies using tide gauges have identified storm surge trends at a few U.S. locationsβbut the results have been inconsistent. No robust evidence of regionally coherent trends have emerged. (2/12)
17.04.2025 15:55 β π 0 π 0 π¬ 1 π 0Rising mean sea levels are clearly driving more frequent coastal flooding. But what about changes in storminess? Thatβs been harder to assess, due to limitations in how storm surge is measured. Our new study in Nature Climate Change (led by Joao Morim) addresses this. π§΅ (1/12)
17.04.2025 15:55 β π 4 π 0 π¬ 1 π 0Been wondering about home value growth. JP Morgan mentioned it, but itβs often left out of the insurance gap convo. Home values have nearly tripled in some places since early 2010s. How could premiums possibly keep up? Lots of factors at play but feels like more attention is needed on this.
15.04.2025 18:02 β π 1 π 0 π¬ 0 π 0Interesting read, thanks! Home values have nearly tripled in some markets since 2012 (eg., Calif). How significant is the gap between rising asset values and the rate at which premiums have increased?
14.04.2025 18:51 β π 0 π 0 π¬ 0 π 0Absolutely. And yes, humility goes a long way to win folks over, especially those that are also modelers. Nuance just doesnt get the same amount of clicks
21.02.2025 16:45 β π 1 π 0 π¬ 0 π 0Risk is not hazard but itβs great marketing for selling data. They (and others) seem to have found a niche conflating increases in property insurance premiums (largely a result of socioeconomic factors) with changes in hazard frequency and intensity.
21.02.2025 15:46 β π 1 π 0 π¬ 1 π 0