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1. Pervasive alterations to snow-dominated ecosystem functions under climate change

   https://doi.org/10.1073/pnas.2202393119  

   Wieder, William R.; Kennedy, Daniel; Lehner, Flavio; Musselman, Keith N.; Rodgers, Keith B.; Rosenbloom, Nan; Simpson, Isla R.; Yamaguchi, Ryohei (July 2022, Proceedings of the National Academy of Sciences)

   Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. Our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change. 

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2. California’s 2023 snow deluge: Contextualizing an extreme snow year against future climate change

   https://doi.org/10.1073/pnas.2320600121  

   Marshall, Adrienne M.; Abatzoglou, John T.; Rahimi, Stefan; Lettenmaier, Dennis P.; Hall, Alex (May 2024, Proceedings of the National Academy of Sciences)

   The increasing prevalence of low snow conditions in a warming climate has attracted substantial attention in recent years, but a focus exclusively on low snow leaves high snow years relatively underexplored. However, these large snow years are hydrologically and economically important in regions where snow is critical for water resources. Here, we introduce the term “snow deluge” and use anomalously high snowpack in California’s Sierra Nevada during the 2023 water year as a case study. Snow monitoring sites across the state had a median 41 y return interval for April 1 snow water equivalent (SWE). Similarly, a process-based snow model showed a 54 y return interval for statewide April 1 SWE (90% CI: 38 to 109 y). While snow droughts can result from either warm or dry conditions, snow deluges require both cool and wet conditions. Relative to the last century, cool-season temperature and precipitation during California’s 2023 snow deluge were both moderately anomalous, while temperature was highly anomalous relative to recent climatology. Downscaled climate models in the Shared Socioeconomic Pathway-370 scenario indicate that California snow deluges—which we define as the 20 y April 1 SWE event—are projected to decline with climate change (58% decline by late century), although less so than median snow years (73% decline by late century). This pattern occurs across the western United States. Changes to snow deluge, and discrepancies between snow deluge and median snow year changes, could impact water resources and ecosystems. Understanding these changes is therefore critical to appropriate climate adaptation. 

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3. Assessing the Influence of a Bias Correction Method on Future Climate Scenarios Using SWAT as an Impact Model Indicator

   https://doi.org/10.3390/w15040750  

   Brighenti, Tássia Mattos; Gassman, Philip W.; Gutowski, William J.; Thompson, Janette R. (February 2023, Water)

   In this study, we evaluate the implications of a bias correction method on a combination of Global/Regional Climate Models (GCM and RCM) for simulating precipitation and, subsequently, streamflow, surface runoff, and water yield in the Soil and Water Assessment Tool (SWAT). The study area is the Des Moines River Basin, U.S.A. The climate projections are two RCMs driven by two GCMs for historical simulations (1981–2005) and future projections (2030–2050). Bias correction improves historical precipitation for annual volumes, seasonality, spatial distribution, and mean error. Simulated monthly historical streamflow was compared across 26 monitoring stations with mostly satisfactory results for percent bias (Pbias). There were no changes in annual trends for future scenarios except for raw WRF models. Seasonal variability remained the same; however, most models predicted an increase in monthly precipitation from January to March and a reduction for June and July. Meanwhile, the bias-corrected models showed changes in prediction signals. In some cases, raw models projected an increase in surface runoff and water yield, but the bias-corrected models projected a reduction in these variables. This suggests the bias correction may be larger than the climate-change signal and indicates the procedure is not a small correction but a major factor. 

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4. The Mesoscale Response to Global Warming over the Pacific Northwest Evaluated Using a Regional Climate Model Ensemble

   https://doi.org/10.1175/JCLI-D-21-0061.1  

   Mass, Clifford F.; Salathé, Eric P; Steed, Richard; Baars, Jeffrey (March 2022, Journal of Climate)

   Abstract This paper describes the downscaling of an ensemble of 12 general circulation models (GCMs) using the Weather Research and Forecasting (WRF) Model at 12-km grid spacing over the period 1970–2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. The 1 April snowpack declines are large over the lower-to-middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCMs producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the twenty-first century. Significance Statement This paper provides a unique high-resolution view of projected climate change over the Pacific Northwest and does so using an ensemble of regional climate models, affording a look at the uncertainties in local impacts of global warming. The paper examines regional meteorological processes influenced by global warming and provides guidance for adaptation and preparation. 

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5. Projected Changes to Streamflow and Stream Temperature in Central Texas: How Much Will the River Flow?

   https://doi.org/10.1175/EI-D-22-0021.1  

   Wootten, Adrienne M.; Martin, Elinor; Randklev, Charles R.; Smith, Ryan (January 2023, Earth Interactions)

   Abstract Riverine ecosystems are dependent in large part on the climate of the region, and climate change is expected to alter climatic factors of interest, such as precipitation, temperature, and evapotranspiration. In central Texas, precipitation is expected to decrease while temperature increases as the climate changes. Drought and flooding events are also expected to increase in the region, which will also affect streamflow and stream temperature in riverine ecosystems. Numerous studies have assessed the potential impacts of climate change on riverine species. This study examines the projected climate changes, determines potential changes in streamflow and stream temperature for river basins in central Texas, and assesses the appropriate uses of climate projections for riverine species impact assessments, using the Texas fatmucket ( Lampsilis bracteata ) as a case study. Previously established regression methods were used to produce projections of streamflow and stream temperature. This study finds that streamflow is projected to decrease and stream temperature is projected to increase. Using thermal tolerance thresholds previously determined for the Lampsilis bracteata , this study also finds that the lethal temperature events for the Lampsilis bracteata will increase. This study makes several recommendations on the use of downscaled climate projections for impact assessments for riverine species such as the Lampsilis bracteata . 

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