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Aim: As climate change increases the frequency and severity of droughts in many regions, conservation during drought is becoming a major challenge for ecologists. Droughts are multidimensional climate events whose impacts may be moderated by changes in temperature, water availability or food availability, or some combination of these. Simultaneously, other stressors such as extensive anthropogenic landscape modification may synergize with drought. Useful observational models for guiding conservation decision‐making during drought require multidimensional, dynamic representations to disentangle possible drought impacts, and consequently, they will require large, highly resolved data sets. In this paper, we develop a two‐stage predictive framework for assessing how drought impacts vary with species, habitats and climate pathways. Location: Central Valley, California, USA. Methods: We used a two‐stage counterfactual analysis combining predictive linear mixed models and N‐mixture models to characterize the multidimensional impacts of drought on 66 bird species. We analysed counts from the eBird participatory science data set between 2010 and 2019 and produced species‐ and habitat‐specific estimates of the impact of drought on relative abundance. Results: We found that while fewer than a quarter (16/66) of species experienced abundance declines during drought, nearly half of all species (27/66) changed their habitat associations during drought. Among species that shifted their habitat associations, the use of natural habitats declined during drought while use of developed habitat and perennial agricultural habitat increased. Main Conclusions: Our findings suggest that birds take advantage of agricultural and developed land with artificial irrigation and heat‐buffering microhabitat structure, such as in orchards or parks, to buffer drought impacts. A working lands approach that promotes biodiversity and mitigates stressors across a human‐induced water gradient will be critical for conserving birds during drought. [ABSTRACT FROM AUTHOR]

The spatial heterogeneity related to complex topography in California demands high-resolution (< 5 km) modeling, but global convection-permitting climate models are computationally too expensive to run multi-decadal simulations. We developed a 3.25 km California climate modeling framework by leveraging regional mesh refinement (CARRM) using the U.S. Department of Energy (DOE)'s global Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) version 0. Four 5-year time periods (2015–2020, 2029–2034, 2044–2049, and 2094–2099) were simulated by nudging CARRM outside California to 1° coupled simulation of E3SMv1 under the Shared Socioeconomic Pathways (SSP)5-8.5 future scenario. The 3.25 km grid spacing adds considerable value to the prediction of the California climate changes, including more realistic high temperatures in the Central Valley and much improved spatial distributions of precipitation and snowpack in the Sierra Nevada and coastal stratocumulus. Under the SSP5-8.5 scenario, CARRM simulation predicts widespread warming of 6–10 °C over most of California, a 38 % increase in statewide average 30 d winter–spring precipitation, a near-complete loss of the alpine snowpack, and a sharp reduction in shortwave cloud radiative forcing associated with marine stratocumulus by the end of the 21st century. We note a climatological wet precipitation bias for the CARRM and discuss possible reasons. We conclude that SCREAM RRM is a technically feasible and scientifically valid tool for climate simulations in regions of interest, providing an excellent bridge to global convection-permitting simulations. [ABSTRACT FROM AUTHOR]

A three‐dimensional variably saturated flow model was developed for assessing future global water resources and parameterized for groundwater pumping. We applied this model to an actual watershed to verify its validity as an Earth System Model. For global applicability, the parameterization method for multi‐layered groundwater pumping was developed and verified through comparison with observations and MODFLOW results. The parameterization proposed in this study is applicable even when multiple groundwater pumping wells are present within one horizontal computational grid and when the well spans multiple vertical grids. This method can be applied at the global scale without parameters such as the well radius, for which data may be difficult to obtain. The parameterization recreated seasonal and annual variations in the observed values. Furthermore, the results were comparable to those of MODFLOW. However, the calculation results were overestimated relative to the observed values. This overestimation was likely to be due to active groundwater pumping in the Central Valley before the start of the unsteady‐state calculation. Therefore, the groundwater level at the beginning of the unsteady‐state calculation was calculated using observed values, improving reproducibility. Furthermore, as observed groundwater levels are unlikely to be available at the global scale, steady‐state calculations were conducted over 15 and 60 years considering groundwater pumping. However, the results were not as reproducible as those obtained using observed groundwater levels. These results suggest that the groundwater level set at the beginning of the calculation is important for global‐scale groundwater flow calculation. Plain Language Summary: Water resources are expected to become strained in the future due to climate change and population growth. The main focus of water resource assessments conducted to date has been on river water. Although groundwater is an important component of water resources, it has generally not been considered. This is largely due to the lack of groundwater models that can be applied at a global scale. Therefore, we developed a new groundwater model that was parameterized for groundwater pumping and validated in plains. The results of this study indicate that parameterization of groundwater pumping can produce reasonable results relative to observed values, and that the groundwater level set at the beginning of the calculation is important for the evaluation and prediction of global water resources. In particular, collection of observed groundwater levels or estimation of groundwater pumping are key steps toward more realistic prediction. Key Points: A three‐dimensional variably saturated flow model for use as an Earth System Model was developed and parameterized for groundwater pumpingThe validation results reproduced observations to some extent and were comparable to those of MODFLOW in the Central ValleyThe results show that setting the groundwater level at the beginning of the unsteady‐state simulation is important for global‐scale [ABSTRACT FROM AUTHOR]

Ongoing (2014-16) drought in the state of California has played a major role in the depletion of groundwater. Within California's Central Valley, home to one of the world's most productive agricultural regions, drought and increased groundwater depletion occurs almost hand in hand, but this relationship appears to have changed over the last decade. Data derived from 497 wells have revealed a continued depletion of groundwater lasting a full year after drought, a phenomenon that was not observed in earlier records before the twenty-first century. Possible causes include 1) lengthening of drought associated with amplification in the 4-6-yr drought and El Niño frequency since the late 1990s and 2) intensification of drought and increased pumping that enhances depletion. Altogether, the implication is that current groundwater storage in the Central Valley will likely continue to diminish even further in 2016, regardless of the drought status. [ABSTRACT FROM AUTHOR]

California Central Valley (CCV) heat waves are grouped into two types based on the temporal and spatial evolution of the large-scale meteorological patterns (LSMPs) prior to onset. The k-means clustering of key features in the anomalous temperature and zonal wind identifies the two groups. Composite analyses show different evolution prior to developing a similar ridge-trough-ridge pattern spanning the North Pacific at the onset of CCV hot spells. Backward trajectories show adiabatic heating of air enhanced by anomalous sinking plus horizontal advection as the main mechanisms to create hot lower-tropospheric air just off the Northern California coast, although the paths differ between clusters. The first cluster develops the ridge at the west coast on the day before onset, consistent with wave activity flux traveling across the North Pacific. Air parcels that arrive at the maximum temperature anomaly (just off the Northern California coast) tend to travel a long distance across the Pacific from the west. The second cluster has the ridge in place for several days prior to extreme CCV heat, but this ridge is located farther north, with heat anomaly over the northwestern United States. This ridge expands south as air parcels at midtropospheric levels descend from the northwest while lower-level parcels over land tend to bring hot air from directions ranging from the hot area to the northeast to the desert areas to the southeast. These two types reveal unexpected dynamical complexity, hint at different remote associations, and expand the assessment needed of climate models' simulations of these heat waves. [ABSTRACT FROM AUTHOR]

In this study, the Weather Research and Forecasting (WRF) model was applied to dynamically downscale the Parallel Climate Model (PCM) projection for the climate change impact on regional meteorological conditions in California. Comparisons were made for meteorological fields that strongly influence regional air quality between the current (2000--06) and future (2047--53) downscaling results to infer potential air pollution changes in California. Changes in both the meteorological fields and the implied future air quality vary by region and season. Analyses showed that the normalized number of stagnation days (NNSD) integrating all stagnation events, during which most of the air pollution episodes occur, in California's San Joaquin Valley (SJV) will increase and the intensity of stagnation will be stronger in the future for the two main air pollution seasons (i.e., summer and winter). Increases in surface wind and planetary boundary layer height (PBLH) were observed for the coastal part of Los Angeles County (LAC) during summer, suggesting stronger ventilation in this region. Contrary situations were seen in other parts of the South Coast Air Basin (SoCAB) and SJV. Although a surface wind change was not evident in SJV during winter, there was a significant PBLH decrease. Climatechangeinduced variations in surface wind and PBLH were only statistically significant in coastal SoCAB and the southern portion of SJV relative to the corresponding interannual variability; changes in temperature are significant throughout the regions studied. The sea breeze along the coast of California plays an important role in the state's climate and air quality, especially during summertime owing to the stronger intensity compared to wintertime. Analysis of the land--sea temperature contrast and the southwesterly wind along the California coastline indicated that the summertime sea breeze will be stronger in the Central Valley (CV) but weaker for the SoCAB region in the future. [ABSTRACT FROM AUTHOR]

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The study explores the potential changes in water year types and hydrological droughts as well as runoff, based on which the former two metrics are calculated in the Central Valley of California, United States, in the 21st century. The latest operative projections from four representative climate models under two greenhouse-gas emission scenarios are employed for this purpose. The study shows that the temporal distribution of annual runoff is expected to change in terms of shifting more volume to the wet season (October–March) from the snowmelt season (April–July). Increases in wet season runoff volume are more noticeable under the higher (versus lower) emission scenario, while decreases in snowmelt season runoff are generally more significant under the lower (versus higher) emission scenario. In comparison, changes in the water year types are more influenced by climate models rather than emission scenarios. When comparing two regions in the Central Valley, the rain-dominated Sacramento River region is projected to experience more wet years and less critical years than the snow-dominated San Joaquin River region due to their hydroclimatic and geographic differences. Hydrological droughts in the snowmelt season and wet season mostly exhibit upward and downward trends, respectively. However, the uncertainty in the direction of the trend on annual and multi-year scales tends to be climate-model dependent. Overall, this study highlights non-stationarity and long-term uncertainty in these study metrics. They need to be considered when developing adaptive water resources management strategies, some of which are discussed in the study. [ABSTRACT FROM AUTHOR]