Arctic sea-ice loss is projected to lead to more frequent strong El Niño events

Nature Portfolio (Springer Nature) | August 23rd, 2022

Arctic sea ice has decreased substantially and is projected to reach a seasonally ice-free state in the coming decades. Little is known about whether dwindling Arctic sea

Arctic sea ice has decreased substantially and is projected to reach a seasonally ice-free state in the coming decades. Little is known about whether dwindling Arctic sea ice is capable of influencing the occurrence of strong El Niño, a prominentmode of climate variability with global impacts. Based on time slice coupled model experiments, here we show that no significant change in the occurrence of strong El Niño is found in response to moderate Arctic sea-ice loss that is consistent with satellite observations to date. However, as the ice loss continues and the Arctic becomes seasonally ice-free, the frequency of strong El Niño events increases bymore than one third, as defined by gradientbased indices that remove mean tropical Pacific warming induced by the seasonally ice-free Arctic. By comparing our time slice experiments with greenhouse warming experiments, we conclude that at least 37–48% of the increase of strong El Niño near the end of the 21st century is associated specifically with Arctic sea-ice loss. Further separation of Arctic sea-ice loss and greenhouse gas forcing only experiments implies that the seasonally ice-free Arctic might play a key role in driving significantly more frequent strong El Niño events.

Are Atmospheric Models Too Cold in the Mountains? The State of Science and Insights from the SAIL Field Campaign

American Meteorological Society (AMS) | July 16th, 2024

ARTMIP-early start comparison of atmospheric river detection tools: how many atmospheric rivers hit northern California’s Russian River watershed?

Climate Dynamics (Springer) | September 10th, 2018

Many atmospheric river detection tools (ARDTs) have now been developed. However, their relative performance is not well documented. This paper compares a diverse set of A

Many atmospheric river detection tools (ARDTs) have now been developed. However, their relative performance is not well documented. This paper compares a diverse set of ARDTs by applying them to a single location where a unique 12-year-long time-series from an atmospheric river observatory at Bodega Bay, California is available. The study quantifies the sensitivity of the diagnosed number, duration, and intensity of ARs at this location to the choice of ARDT, and to the choice of reanalysis data set. The ARDTs compared here represent a range of methods that vary in their use of different variables, fixed vs. percentile-based thresholds, geometric shape requirements, Eulerian vs. Lagrangian approaches, and reanalyses. The ARDTs were evaluated first using the datasets documented in their initial publication, which found an average annual count of 19 ± 7. Applying the ARDTs to the same reanalysis dataset yields an average annual count of 19 ± 4. Applying a single ARDT to three reanalyses of varying grid sizes (0.5°, 1.0°–2.5°) showed little sensitivity to the choice of reanalysis. While the annual average AR event count varied by about a factor of two (10–25 per year) depending on the ARDT, average AR duration and maximum intensity varied by less than ± 10%, i.e., 24 ± 2 h duration; 458 ± 44 kg m− 1 s− 1maximum IVT. ARDTs that use a much higher threshold for integrated vapor transport were compared separately, and yielded just 1–2 ARs annually on average. Generally, ARDTs that include either more stringent geometric criteria or higher thresholds identified the fewest AR events.

Assessing and communicating the impacts of climate change on the Southern California coast

California Natural Resources Agency (CNRA) | August 27th, 2018

 Over the course of this and the next century, the combination of rising sea levels, severe storms, and coastal erosion will threaten the sustainability of coastal commu

 Over the course of this and the next century, the combination of rising sea levels, severe storms, and coastal erosion will threaten the sustainability of coastal communities, development, and ecosystems as we currently know them. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies for projected increased levels of coastal flooding and erosion, coastal managers need user-friendly planning tools based on the best available climate and coastal science. In anticipation of these climate change impacts, many communities are in the early stages of climate change adaptation planning but lack the scientific information and tools to adequately address the potential impacts. In collaboration with leading scientists worldwide, the USGS designed the Coastal Storm Modeling System (CoSMoS) to assess the coastal impacts of climate change for the California coast, including the combination of sea level rise, storms, and coastal change. In this project, we directly address the needs of coastal resource managers in Southern California by integrating a vast range of global climate change projections and translate that information using sophisticated physical process models into planning-scale physical, ecological, and economic exposure, shoreline change, and impact assessments, all delivered in two simple, user-friendly, online tools. Our results show that by the end of the 21st century, over 250,000 residents and nearly $40 billion in building value across Southern California could be exposed to coastal flooding from storms, sea level rise, and coastal change. Results for the other major population center in California (the greater San Francisco Bay Area) are also available but not explicitly discussed in this report. Together, CoSMoS has now assessed the exposure of 95% of the 26 million coastal residents of the State (17 million in Southern California) 

Assessing Regional Strategies to Cope with Drought, Climate, and Environmental Flow Policy Impacts for a Sustainable Water Supply: A Case Study of the Bay Area

American Chemical Society (ACS) | December 27th, 2024

Assessing risk of groundwater pollution exposure from sea level rise in California

Publisher not available | June 12th, 2025

Sea level rise (SLR) will cause a groundwater table rise in coastal aquifers, and this can trigger exposure to toxic chemicals via direct contact with contaminated water

Sea level rise (SLR) will cause a groundwater table rise in coastal aquifers, and this can trigger exposure to toxic chemicals via direct contact with contaminated water or through vapor intrusion. This study presents deep learning- and explainable artificial intelligence (XAI) models to assess risk of polluted groundwater exposure due to SLR in California. Our method quantifies risk based on (1) SLR-related groundwater rise projections and (2) a prioritization of 2296 hazardous sites according to a geochemical indexing algorithm applied to groundwater data from the California State Water Resources Control Board. Our results indicate that nearly half a million people in California may be potentially exposed to marginal or poor groundwater by the end of the century. We show that feature collinearity renders numerous indicators on socioeconomics, demography, health and environment as dependent- and thus insignificant risk predictors. Our XAI models furthermore indicate that features on total population and features related to demographics (households of color and low income) and pollution source (proximity to wastewater dischargers) exert strongest controls on risk. However performance differences between randomly- and spatially cross-validated models highlight generalization challenges due to spatial autocorrelation. While the former model yields better results for California-specific analysis, only the latter model should be applied for unbiased risk assessments in other coastal regions.

Assessing the climate‐scale variability of atmospheric rivers affecting western North America

American Geophysical Union (AGU) | August 3rd, 2017

We have created a new seven‐decade‐long catalog of atmospheric river behavior land‐falling upon the west coast of North America. The catalog has been validated agai

We have created a new seven‐decade‐long catalog of atmospheric river behavior land‐falling upon the west coast of North America. The catalog has been validated against independent precipitation observations to ensure that the atmospheric rivers represented therein are associated with extreme orographic precipitation. Our results clearly delineate a prominent role for atmospheric rivers in California's hydroclimate. Atmospheric river variability has been particularly important in the recent California drought as well as its most recent lapse. We also detect a long‐term increasing trend in water vapor transport impinging on the west coast of North America associated with atmospheric rivers and overall wintertime water vapor transport associated with climate warming. Our results, moreover, suggest that potential predictability of seasonal behavior of atmospheric rivers may hinge on sources of climatic variability somewhat different from that of total water vapor transport.

Assessing the Effects of Climate Change on Middle Rio Grande Surface Water Supplies Using a Simple Water Balance Reservoir Model

American Meteorological Society (AMS) | August 12th, 2022

The middle Rio Grande is a vital source of water for irrigation in the region. Climate change is impacting regional hydrology and is likely to put additional stress on a

The middle Rio Grande is a vital source of water for irrigation in the region. Climate change is impacting regional hydrology and is likely to put additional stress on a water supply that is already stretched thin. To gain insight on the hydrologic effects of climate change on reservoir storage, a simple water balance model was used to simulate the Elephant Butte–Caballo Reservoir system (southern New Mexico). The water balance model was forced by hydrologic inputs generated by 97 climate simulations derived from CMIP5 global climate models, coupled to a surface hydrologic model. Results suggest that the percentage of years that reservoir releases satisfy agricultural water rights allocations over the next 50 years (2021–70) will decrease relative to the past 50 years (1971–2020). The modeling also projects an increase in multiyear drought events that hinder reservoir management strategies to maintain high storage levels. In most cases, changes in reservoir inflows from distant upstream snowmelt is projected to have a greater influence on reservoir storage and water availability downstream of the reservoirs than will changes in local evaporation and precipitation from the reservoir surfaces.

Assumptions and Estimates for California Water Plan Update 2023 (Draft)

California Department of Water Resources (DWR) | October 14th, 2022

The draft Assumptions and Estimates for California Water Plan Update 2023 (draft A&E Report) describes key assumptions and estimates, data and data sources; improvements

The draft Assumptions and Estimates for California Water Plan Update 2023 (draft A&E Report) describes key assumptions and estimates, data and data sources; improvements to analytical tools, methods, and approaches; and the supporting documents and companion State plans being used to prepare California Water Plan Update 2023 (Update 2023), State government’s strategic plan for managing and developing water resources for sustainability and resilience. The draft A&E Report cites the statutory requirements for the California Water Plan (Water Plan), key legislative and policy drivers, assumptions, and estimates related to water data portfolios, future scenarios, water accounting, watershed resilience planning, and equity in water resource management. Also discussed are resource management strategies, the alignment of integrated watershed programs and plans, and integration and alignment of State plans.

Asymmetric emergence of low-to-no snow in the midlatitudes of the American Cordillera

Nature Portfolio (Springer Nature) | November 14th, 2022

Societies and ecosystems within and downstream of mountains rely on seasonal snowmelt to satisfy their water demands. Anthropogenic climate change has reduced mountain sn

Societies and ecosystems within and downstream of mountains rely on seasonal snowmelt to satisfy their water demands. Anthropogenic climate change has reduced mountain snowpacks worldwide, altering snowmelt magnitude and timing. Here the global warming level leading to widespread and persistent mountain snowpack decline, termed low-to-no snow, is estimated for the world’s most latitudinally contiguous mountain range, the American Cordillera. We show that a combination of dynamical, thermodynamical and hypsometric factors results in an asymmetric emergence of low-to-no-snow conditions within the midlatitudes of the American Cordillera. Low-to-no-snow emergence occurs approximately 20 years earlier in the southern hemisphere, at a third of the local warming level, and coincides with runoff efficiency declines (8% average) in both dry and wet years. The prevention of a low-to-no-snow future in either hemisphere requires the level of global warming to be held to, at most, +2.5 °C.