D.J. Rasmussen
@climatequant.bsky.social
Nice! I’d also love to see some more local or regional examples, since those tend to be especially useful for adaptation decision-making.
December 6, 2025 at 9:17 PM
Nice! I’d also love to see some more local or regional examples, since those tend to be especially useful for adaptation decision-making.
I work in industry, and I see this all the time. e.g. professional services firms often prioritize soft skills in hiring, which means many “climate scientist” roles end up filled by people who don’t fully understand the data or methods they’re working with.
December 5, 2025 at 6:43 PM
I work in industry, and I see this all the time. e.g. professional services firms often prioritize soft skills in hiring, which means many “climate scientist” roles end up filled by people who don’t fully understand the data or methods they’re working with.
Yeah. I never see evaluation of the alignment of observed local/ regional trends with near-term climate model projections. Dunn et al. 2020/2024 is helpful. Models are awesome but we should consider diverse pieces of evidence when making million dollar decisions. Not just do what NASA-NEX data says.
December 4, 2025 at 7:03 PM
Yeah. I never see evaluation of the alignment of observed local/ regional trends with near-term climate model projections. Dunn et al. 2020/2024 is helpful. Models are awesome but we should consider diverse pieces of evidence when making million dollar decisions. Not just do what NASA-NEX data says.
"There is not a lot of agreement on what best practices would even look like (even from domain experts deeply enmeshed in this stuff who really do know what they're talking about)."
Yes! Really comes down to specific use cases (e.g., "changes in 1% AEP rainfall" or "number of 'wet' days")
Yes! Really comes down to specific use cases (e.g., "changes in 1% AEP rainfall" or "number of 'wet' days")
December 4, 2025 at 6:56 PM
"There is not a lot of agreement on what best practices would even look like (even from domain experts deeply enmeshed in this stuff who really do know what they're talking about)."
Yes! Really comes down to specific use cases (e.g., "changes in 1% AEP rainfall" or "number of 'wet' days")
Yes! Really comes down to specific use cases (e.g., "changes in 1% AEP rainfall" or "number of 'wet' days")
Yes. Using these data off the shelf will under-sample extremes.
An entirely different approach is needed for wet tails.
The training data don't work well (Livneh, Metsim, ERA5+WRF). Pierce et al. 2021 helped, but it needs to be obs-based, spatial extreme value (e.g. the Atlases).
An entirely different approach is needed for wet tails.
The training data don't work well (Livneh, Metsim, ERA5+WRF). Pierce et al. 2021 helped, but it needs to be obs-based, spatial extreme value (e.g. the Atlases).
December 4, 2025 at 6:52 PM
Yes. Using these data off the shelf will under-sample extremes.
An entirely different approach is needed for wet tails.
The training data don't work well (Livneh, Metsim, ERA5+WRF). Pierce et al. 2021 helped, but it needs to be obs-based, spatial extreme value (e.g. the Atlases).
An entirely different approach is needed for wet tails.
The training data don't work well (Livneh, Metsim, ERA5+WRF). Pierce et al. 2021 helped, but it needs to be obs-based, spatial extreme value (e.g. the Atlases).
I think govt involvement is also about liability. There are better private-sector flood maps out there, but what CEO is going to expose their company to litigation when people don't like the publicly shown scores? FEMA deals with LOMAs day and night, and they have sovereign immunity.
December 3, 2025 at 7:41 PM
I think govt involvement is also about liability. There are better private-sector flood maps out there, but what CEO is going to expose their company to litigation when people don't like the publicly shown scores? FEMA deals with LOMAs day and night, and they have sovereign immunity.
How much of this is new policies vs just crazy inflation since 2020? fred.stlouisfed.org/series/CAUCS...
Zillow Home Value Index (ZHVI) for All Homes Including Single-Family Residences, Condos, and CO-OPs in California
Zillow Home Value Index (ZHVI) for All Homes Including Single-Family Residences, Condos, and CO-OPs in California
fred.stlouisfed.org
August 20, 2025 at 6:32 AM
How much of this is new policies vs just crazy inflation since 2020? fred.stlouisfed.org/series/CAUCS...
Many 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.
August 6, 2025 at 11:46 PM
Many 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.
Yes. Could be representativeness issues (grid vs point) or other assimilation or model biases. Gridded products ≠ in situ observations. I developed a dataset to deal with these issues: essopenarchive.org/doi/full/10....
Multivariate Bias Correction of ERA5 Using in-situ Observations for Planning and Engineering
Climate risk analyses for infrastructure are typically performed using a point-based frame of reference. However, the atmospheric data that informs these decisions often comes from gridded products su...
essopenarchive.org
July 29, 2025 at 6:25 PM
Yes. Could be representativeness issues (grid vs point) or other assimilation or model biases. Gridded products ≠ in situ observations. I developed a dataset to deal with these issues: essopenarchive.org/doi/full/10....
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)
July 2, 2025 at 5:51 AM
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)
I’m 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)
April 17, 2025 at 3:55 PM
I’m 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)
Our preliminary estimates are consistent with FEMA’s elevations—but 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)
https://ascmo.copernicus.org/articles/11/1/2025/).
April 17, 2025 at 3:55 PM
Our preliminary estimates are consistent with FEMA’s elevations—but 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)
More work is coming. We’re 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)
April 17, 2025 at 3:55 PM
More work is coming. We’re 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)
📄 Article: rdcu.be/eh8gu (9/12)
Observations reveal changing coastal storm extremes around the United States
Nature Climate Change - Coastal communities are at risk from extreme coastal storms. This study leverages US tide gauge data from 1950–2020 to show that likelihood estimates of storm surge...
rdcu.be
April 17, 2025 at 3:55 PM
📄 Article: rdcu.be/eh8gu (9/12)
Regardless 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...
www.fema.gov
April 17, 2025 at 3:55 PM
Regardless 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...
Though modest in magnitude, I’d argue these trends matter. It’s possible that internal climate variability and anthropogenic forcing are exerting opposing influences—partially masking the full signal. Disentangling these drivers requires large ensemble simulations (7/12)
April 17, 2025 at 3:55 PM
Though modest in magnitude, I’d argue these trends matter. It’s possible that internal climate variability and anthropogenic forcing are exerting opposing influences—partially masking the full signal. Disentangling these drivers requires large ensemble simulations (7/12)
We 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)
April 17, 2025 at 3:55 PM
We 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)
These trends have accelerated in several regions since 1975. In hotspots—especially the Gulf and Southeast Atlantic coasts—storm surge extremes are increasing at rates comparable to or exceeding MSL rise. (5/12)
April 17, 2025 at 3:55 PM
These trends have accelerated in several regions since 1975. In hotspots—especially the Gulf and Southeast Atlantic coasts—storm surge extremes are increasing at rates comparable to or exceeding MSL rise. (5/12)
The result: we find robust, spatially coherent trends in storm surge extremes along 70% of the U.S. coastline—contradicting the longstanding view that such regional trends in storminess don’t exist.
In some areas, the magnitude of these trends rivals contributors to regional sea-level rise. (4/12)
In some areas, the magnitude of these trends rivals contributors to regional sea-level rise. (4/12)
April 17, 2025 at 3:55 PM
The result: we find robust, spatially coherent trends in storm surge extremes along 70% of the U.S. coastline—contradicting the longstanding view that such regional trends in storminess don’t exist.
In some areas, the magnitude of these trends rivals contributors to regional sea-level rise. (4/12)
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)
April 17, 2025 at 3:55 PM
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)
Previous studies using tide gauges have identified storm surge trends at a few U.S. locations—but the results have been inconsistent. No robust evidence of regionally coherent trends have emerged. (2/12)
April 17, 2025 at 3:55 PM
Previous studies using tide gauges have identified storm surge trends at a few U.S. locations—but the results have been inconsistent. No robust evidence of regionally coherent trends have emerged. (2/12)