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Groundwater is a major source of water in the western US. However, there are limited recharge estimates available in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US. Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01-15% for Mosaic, 3.2-42% for Noah, and 6.7-31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge rates in data limited regions.

Expanding networks of all-weather, high-time-resolution GPS networks with surface meteorology throughout the southwestern United States and Mexico offers opportunities for improved understanding of the North American monsoon convection and forecasting of organized convective events and associated hazards.

We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed for the equation (i.e., minimum and maximum daily temperature, specific humidity, wind speed, incoming shortwave radiation, and pressure) were obtained from the North American–CORDEX initiative. We used dynamically downscaled projections of three CMIP5 GCMs for RCP8.5 emission scenarios (i.e., HadGEM2-ES, MPI-ESM-LR, and GFDL-ESM2M), and each was dynamically downscaled to ~25 km by two RCMs (i.e., WRF and regCM4). All terrestrial annual PET projections showed a statistically significant increase when comparing the historical period (1986–2005) to future projections (2020–2039 and 2040–2059). The regional spatial average of the six GCM-RCM combinations projected an increase in the annual PET of about +4% and +8% for 2020–2039 and 2040–2059, respectively. The projected average 20-year annual changes over the study area range for the two projection periods were +1.4%–+8.7% and +3%–+14.2%, respectively. The projected annual PET increase trends are consistent across the entire region and for the six GCM-RCM combinations. Higher annual changes are projected in the northeast part of the region, while smaller changes are projected along the pacific coast. The main drivers for the increase are the projected warming and increase in the vapor pressure deficit. The projected changes in PET, which represent the changes in the atmospheric evaporative demand, are substantial and likely to impact vegetation and the hydrometeorological regime in the area. Quantitative assessments of the projected PET changes provided by this study should be considered in upcoming studies to develop resilience plans and adaptation strategies for mitigating the projected future changes. [ABSTRACT FROM AUTHOR]

Precipitation in the Southern Plains of the United States is relatively well depicted by the Community Earth System Model (CESM). However, despite its ability to capture seasonal mean precipitation anomalies, CESM consistently underestimates extreme pluvial and drought events, rendering it an insufficient tool for extending simulation lead times for exceptional events, such as the abnormally dry May 2011, which helped drive Texas into its worst period of drought in more than a century, and the abnormally wet May 2015, which led to widespread flooding in that state. Ensemble‐based regional climate experiments are completed for the two extreme years using Weather Research and Forecasting model (WRF) and downscaled from CESM. WRF simulations are at convection‐permitting grid resolution for improved physical representation of simulated precipitation over the Southern Great Plains. By integrating convection‐permitting models (CPMs) into each individual member of a CESM ocean data assimilation ensemble, this study demonstrates that high‐resolution dynamical downscaling can improve model skillfulness at capturing these two events and is thus a potentially useful tool for forecasting extremely high and extremely low precipitation events at subseasonal or even seasonal lead times. Plain Language Summary: The Community Earth System Model (CESM) has reasonable climatological representation over the Southern Plains region of the United States, but it is still a challenge for CESM to capture the extreme events like severe floods and drought. In this study, we applied a regional climate modeling approach onto CESM at a model resolution capable of resolving convection for selected record‐breaking wet and dry years in Texas. Results indicate our modeling approach can improve CESM's capability to simulate both wet and dry extremes and the modeling system skill is reasonable using CESM simulations initialized weeks before the events' occurrence. Different sources of upper atmospheric zonal winds may lead to abnormally wet or dry seasonal precipitation in Texas. Key Points: Dynamical downscaling could improve the performance of fully coupled low resolution climate model in simulating climate conditions over landConsistent improvements from convective‐permitting modeling in the depiction of precipitation for extreme Texas flood and drought yearsImproved regional circulation pattern depiction, combined with convective‐permitting modeling, leads to enhanced precipitation simulation [ABSTRACT FROM AUTHOR]

Existing studies on the impacts of climate change on groundwater recharge are either global or basin/location-specific. The global studies lack the specificity to inform decision making, while the local studies do little to clarify potential changes over large regions (major river basins, states, or groups of states), a scale often important in the development of water policy. An analysis of the potential impact of climate change on groundwater recharge across the western United States (west of 100° longitude) is presented synthesizing existing studies and applying current knowledge of recharge processes and amounts. Eight representative aquifers located across the region were evaluated. For each aquifer published recharge budget components were converted into four standard recharge mechanisms: diffuse, focused, irrigation, and mountain-systems recharge. Future changes in individual recharge mechanisms and total recharge were then estimated for each aquifer. Model-based studies of projected climate-change effects on recharge were available and utilized for half of the aquifers. For the remainder, forecasted changes in temperature and precipitation were logically propagated through each recharge mechanism producing qualitative estimates of direction of changes in recharge only (not magnitude). Several key patterns emerge from the analysis. First, the available estimates indicate average declines of 10-20% in total recharge across the southern aquifers, but with a wide range of uncertainty that includes no change. Second, the northern set of aquifers will likely incur little change to slight increases in total recharge. Third, mountain system recharge is expected to decline across much of the region due to decreased snowpack, with that impact lessening with higher elevation and latitude. Factors contributing the greatest uncertainty in the estimates include: (1) limited studies quantitatively coupling climate projections to recharge estimation methods using detailed, process-based numerical models; (2) a generally poor understanding of hydrologic flowpaths and processes in mountain systems; (3) difficulty predicting the response of focused recharge to potential changes in the frequency and intensity of extreme precipitation events; and (4) unconstrained feedbacks between climate, irrigation practices, and recharge in highly developed aquifer systems.

In this study, two classifications of 20 Weather Types (WTs) were used to identify large-scale and synoptic-scale patterns over the Middle Americas region (MAR) that comprises Mexico, intra-American seas, Central America, and northern South America. The Self-Organizing Maps (SOM) method was used to detect both classifications using standardized Mean Sea-Level Pressure (MSLP) anomalies from the ERA-Interim (ERA-I) reanalysis and the Community Earth System Model-Large Ensemble (CESM-LE) in the historical period and its future projection under an RCP8.5 scenario. The WTs obtained with the CESM-LE in the historical period were assigned to each day of the future projection. Averages of the days belonging to each WT of the historical period were compared between both classifications (ERA-I and CESM-LE) employing seasonal and monthly frequencies of occurrence, correspondence in days of occurrence, Pearson's spatial correlation, and position changes of high-pressure semi-permanent centers such as the North Atlantic Subtropical High (NASH) and the North Pacific High (NPH). From precipitation and MSLP, it was observed that WTs obtained with CESM-LE showed a marked seasonality in their temporal distribution, mainly in the wet period (May–October), similar to the ERA-I classification. Three characteristic phenomena of MAR were the North American Monsoon System (NAMS), the Mid-Summer Drought (MSD), and the Caribbean Low-Level Jet (CLLJ). The CESM-LE adequately represented these phenomena in the historical period compared with ERA-I. Regarding the future projection, the CESM-LE ensemble showed that the spatial patterns were very similar in the historical period. However, differences in precipitation between August and September decreased. To assess the effect of internal climate variability of the CESM-LE, we analyzed the spatial average of precipitation in two regions: NAMS and MSD, for the 34 members of the ensemble in the future projection. In the CLLJ region, differences between the historical and the future projection in terms of averages of the zonal-wind component and precipitation were less than 1 %. This analysis showed that the SOM technique detected the signal of climate change on a regional scale without being affected by the internal global variability of the model. Therefore, SOM emerged as a useful tool for the analysis of numerical experiments such as CESM-LE. [ABSTRACT FROM AUTHOR]