Causes of accelerated High-Tide Flooding in the U.S. since 1950

Nature Portfolio (Springer Nature) | December 15th, 2023

Causes of the 2011‐14 California Drought

American Meteorological Society (AMS) | September 15th, 2015

The causes of the California drought during November–April winters of 2011/12–2013/14 are analyzed using observations and ensemble simulations with seven atmo

The causes of the California drought during November–April winters of 2011/12–2013/14 are analyzed using observations and ensemble simulations with seven atmosphere models forced by observed SSTs. Historically, dry California winters are most commonly associated with a ridge off the west coast but no obvious SST forcing. Wet winters are most commonly associated with a trough off the west coast and an El Niño event. These attributes of dry and wet winters are captured by many of the seven models. According to the models, SST forcing can explain up to a third of California winter precipitation variance. SST forcing was key to sustaining a high pressure ridge over the west coast and suppressing precipitation during the three winters. In 2011/12 this was a response to a La Niña event, whereas in 2012/13 and 2013/14 it appears related to a warm west–cool east tropical Pacific SST pattern. All models contain a mode of variability linking such tropical Pacific SST anomalies to a wave train with a ridge off the North American west coast. This mode explains less variance than ENSO and Pacific decadal variability, and its importance in 2012/13 and 2013/14 was unusual. The models from phase 5 of CMIP (CMIP5) project rising greenhouse gases to cause changes in California all-winter precipitation that are very small compared to recent drought anomalies. However, a long-term warming trend likely contributed to surface moisture deficits during the drought. As such, the precipitation deficit during the drought was dominated by natural variability, a conclusion framed by discussion of differences between observed and modeled tropical SST trends.

Causes of the Extreme Dry Conditions over California During Early 2013

American Meteorological Society (AMS) | September 30th, 2014

The state of California experienced extreme dry conditions during early 2013. In particular, January and February received 28% and 15%, respectively, of their nor

The state of California experienced extreme dry conditions during early 2013. In particular, January and February received 28% and 15%, respectively, of their normal monthly rainfall. When January and February are combined, January/ February 2013 is ranked as the driest of the period 1895–2014. Such large precipitation deficits exerted enormous stress on water resources in an already high water-demand region. Thus, it is of practical importance to investigate the causes of this extreme climate event so as to assess its predictability. *Chapter 3, Explaining Extreme Events of 2013 from a Climate Perspective, Bull. Amer. Meteor. Soc., 95 (9)

Central Coast Summary Report - California's Fourth Climate Change Assessment

California Energy Commission (CEC) | September 28th, 2018

The Central Coast Region is notable for its extensive natural ecosystems, many of which will be impacted by climate change. Hardwood forests, scrublands, and herbaceous

The Central Coast Region is notable for its extensive natural ecosystems, many of which will be impacted by climate change. Hardwood forests, scrublands, and herbaceous grasslands comprise most of its land cover, with significantly less intensive agriculture and small-to medium-sized cities in the region. There is a strong demand for development in rural areas and agriculture is being developed on lands formerly supporting grazing or natural vegetation. The region continues to reflect an economic and social disconnect between prosperous coastal communities and agricultural areas with many low-income farm workers, inequalities that may result in disadvantaged groups suffering disproportionately from the impacts of climate change. The counties included in this report are Santa Barbara, San Luis Obispo, Monterey, San Benito, and Santa Cruz, with some information for the northern part of Ventura County.

Changes in Winter Atmospheric Rivers along the North American West Coast in CMIP5 Climate Models

American Meteorological Society (AMS) | April 1st, 2014

Most extreme precipitation events that occur along the North American west coast are associated with winter atmospheric river (AR) events. Global climate models h

Most extreme precipitation events that occur along the North American west coast are associated with winter atmospheric river (AR) events. Global climate models have sufficient resolution to simulate synoptic features associated with AR events, such as high values of vertically integrated water vapor transport (IVT) approaching the coast. From phase 5 of the Coupled Model Intercomparison Project (CMIP5), 10 simulations are used to identify changes in ARs impacting the west coast of North America between historical (1970–99) and end-of-century (2070–99) runs, using representative concentration pathway (RCP) 8.5. The most extreme ARs are identified in both time periods by the 99th percentile of IVT days along a north–south transect offshore of the coast. Integrated water vapor (IWV) and IVT are predicted to increase, while lower- tropospheric winds change little. Winter mean precipitation along the west coast increases by 11%–18% [from 4% to 6% (8C)21], while precipitation on extreme IVT days increases by 15%–39% [from 5% to 19% (8C)21]. The frequency of IVT days above the historical 99th percentile threshold increases as much as 290% by the end of this century.

Changing impacts of Alaska-Aleutian subduction zone tsunamis in California under future sea-level rise

Nature Portfolio (Springer Nature) | December 8th, 2021

The amplification of coastal hazards such as distant-source tsunamis under future relative sea-level rise (RSLR) is poorly constrained. In southern California, the Alaska

The amplification of coastal hazards such as distant-source tsunamis under future relative sea-level rise (RSLR) is poorly constrained. In southern California, the Alaska-Aleutian subduction zone has been identified as an earthquake source region of particular concern for a worst-case scenario distant-source tsunami. Here, we explore how RSLR over the next century will influence future maximum nearshore tsunami heights (MNTH) at the Ports of Los Angeles and Long Beach. Earthquake and tsunami modeling combined with local probabilistic RSLR projections show the increased potential for more frequent, relatively low magnitude earthquakes to produce distant-source tsunamis that exceed historically observed MNTH. By 2100, under RSLR projections for a high-emissions representative concentration pathway (RCP8.5), the earthquake magnitude required to produce >1 m MNTH falls from ~Mw9.1 (required today) to Mw8.0, a magnitude that is ~6.7 times more frequent along the Alaska-Aleutian subduction zone.

Chapter 12: Sea Level Rise, Climate Science Special Report, Fourth National Climate Assessment

U.S. Global Change Research Program | November 1st, 2017

Sea level rise is closely linked to increasing global temperatures. Thus, even as uncertainties remain about just how much sea level may rise this century, it is virtu

Sea level rise is closely linked to increasing global temperatures. Thus, even as uncertainties remain about just how much sea level may rise this century, it is virtually certain that sea level rise this century and beyond will pose a growing challenge to coastal communities, infrastructure, and ecosystems from increased (permanent) inundation, more frequent and extreme coastal flooding, erosion of coastal landforms, and saltwater intrusion within coastal rivers and aquifers. Assessment of vulnerability to rising sea levels requires consideration of physical causes, historical evidence, and projections. A risk-based perspective on sea level rise points to the need for emphasis on how changing sea levels alter the coastal zone and interact with coastal flood risk at local scales.

Characterizing storm-induced coastal change hazards along the United States West Coast

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

Traditional methods to assess the probability of storm-induced erosion and flooding from extreme water levels have limited use along the U.S. West Coast where swell domin

Traditional methods to assess the probability of storm-induced erosion and flooding from extreme water levels have limited use along the U.S. West Coast where swell dominates erosion and storm surge is limited. This effort presents methodology to assess the probability of erosion and flooding for the U.S. West Coast from extreme total water levels (TWLs), but the approach is applicable to coastal settings worldwide. TWLs were derived from 61 years of wave and water level data at shore-perpendicular transects every 100-m along open coast shorelines. At each location, wave data from the Global Ocean Waves model were downscaled to the nearshore and used to empirically calculate wave run-up. Tides were simulated using the Oregon State University’s tidal data inversion model and non-tidal residuals were calculated from sea-surface temperature and pressure anomalies. Wave run-up was combined with still water levels to generate hourly TWL estimates and extreme TWLs for multiple return periods. Extremes were compared to onshore morphology to determine erosion hazards and define the probability of collision, overwash, and inundation.

Characterizing the spatial scales of extreme daily precipitation in the United States

American Meteorological Society (AMS) | October 1st, 2018

The spatial extent of an extreme precipitation event can be important for a basin’s hydrologic response and subsequent flood risk, and may yield insights into underlyi

The spatial extent of an extreme precipitation event can be important for a basin’s hydrologic response and subsequent flood risk, and may yield insights into underlying atmospheric processes. Using a relaxed movingneighborhood approach, we develop indicator semivariograms based on precipitation records from the Global Historical Climatology Network–Daily (GHCN-D) station network to directly quantify the climatological length scales of extreme daily precipitation over the United States during 1965–2014. We find that the length scales of extreme (90th percentile) daily precipitation events vary both regionally and seasonally. Over the eastern half of the United States, daily extreme precipitation length scales reach 400 km during the winter months, but are approximately half as large during the summer months. The Northwest region, on the other hand, exhibits little seasonal variation, with extreme precipitation length scales of approximately 150 km throughout the year. By leveraging in situ station measurements, our study avoids some of the uncertainties associated with satellite or interpolated precipitation data, and provides the longest climatological assessment of length scales of extreme daily precipitation over the United States to date. Although the length scales that we calculate can be sensitive to station density, neighborhood size, and neighborhood relaxation, we find that the interregional and inter-seasonal differences in length scales are relatively robust. Our method could be extended to quantify changes in the spatial extent of extreme daily precipitation in the recent past, and to investigate the underlying causes of any changes that are detected.

Characterizing uncertain sea-level rise projections to support investment decisions

PLOS | February 17th, 2018

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regardi

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea- level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.