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At least 19 records

The Wasatch Environmental Observatory: A mountain to urban research network in the semi‐arid western US

Abstract The 2085 km 2 Jordan River Basin, and its seven sub‐catchments draining the Central Wasatch Range immediately east of Salt Lake City, UT, are home to an array of hydrologic, atmospheric, climatic and chemical research infrastructure that collectively forms the Wasatch Environmental Observatory (WEO). WEO is geographically nested within a wildland to urban land‐use gradient and built upon a strong foundation of over a century of discharge and climate records. A 2200 m gradient in elevation results in variable precipitation, temperature and vegetation patterns. Soil and subsurface structure reflect systematic variation in geology from granitic, intrusive to mixed sedimentary clastic across headwater catchments, all draining to the alluvial or colluvial sediments of the former Lake Bonneville. Winter snowfall and spring snowmelt control annual hydroclimate, rapid population growth dominates geographic change in lower elevations and urban gas and particle emissions contribute to episodes of severe air pollution in this closed‐basin. Long‐term hydroclimate observations across this diverse landscape provide the foundation for an expanding network of infrastructure in both montane and urban landscapes. Current infrastructure supports both basic and applied research in atmospheric chemistry, biogeochemistry, climate, ecology, hydrology, meteorology, resource management and urban redesign that is augmented through strong partnerships with cooperating agencies. These features allow WEO to serve as a unique natural laboratory for addressing research questions facing seasonally snow‐covered, semi‐arid regions in a rapidly changing world and an excellent facility for providing student education and research training.

Follstad Shah, Jennifer J.↗

Extension of Large Fire Emissions From Summer to Autumn and Its Drivers in the Western US

Abstract Burned areas in the western US have increased ten‐fold since 1980s, which are attributable to multiple factors, including increasing heat, changing precipitation patterns, and extended drought. To better understand how these factors contribute to large fire emissions (gridded monthly fire emissions >95th percentile of all the fire emissions in the western US; 0.009 Gg/month), we build a machine learning model to predict fire emissions (PM 2.5 ) over the western US at 0.25° resolution, interpreted using explainable artificial intelligence (XAI). From the predictor contributions derived from XAI, we conduct k‐means clustering analysis to identify four clusters of predictor variables representing different drivers of large fire emissions. The four clusters feature the contributions of fuel load (Cluster 1) and different levels of dryness (Cluster 2–4), controlled by fuel moisture, drought condition, and fire‐favorable large‐scale meteorological patterns featuring high temperature, high pressure, and low relative humidity. In the past two decades, large fire emissions peak in summer. However, large fire emissions increased significantly in September and October in 2010–2020 relative to 2000–2009, extending the peak large fire emissions from summer to autumn. The larger enhancements of large fire emissions during autumn compared to summer are contributed by decreased fuel moisture, along with more frequent concurrent fire‐favorable large‐scale meteorological patterns and drought. These results highlight fuel drying as a common driver supported by multiple drivers, such as warmer temperature and more frequent synoptic patterns favorable for fires, in increasing the autumn risk of large fire emissions across the western US.

54 ENVIRONMENTAL SCIENCES↗

Western US Tropospheric Ozone: An Assessment of Vertical and Seasonal Variations over California and Nevada

In the rural western US free-tropospheric O3 has risen in recent years as a result of rising Asian emissions, deep stratospheric intrusions and more frequent wildfires. This increasing O3 trend combined with the high surface elevation of much of the western US, which aids mixing between boundary layer and free-troposphere, pose challenges in attaining the more stringent O3 National Ambient Air Quality Standard (NAAQS) at many western US rural surface sites. As such, the ability to identify various sources and transport mechanisms that contribute towards surface O3 is increasingly important. This paper analyzes vertical profiles of O3 from the Alpha Jet Atmospheric eXperiment (AJAX) over California and Nevada, ozonesondes from Trinidad Head, CA and tropospheric ozone profiles from the differential absorption lidar (DIAL) at the JPL Table Mountain Facility, CA. Surface O3 from the US EPA Clean air Status and Trends Network (CASNET) are used to discuss surface trends. GEOS-Chem determines the trends in regional O3 and assess the contributions of various sources on surface O3. And Realtime Air Quality Modeling System (RAQMS) is used to forecast and interpret free-tropospheric observations. Specifically we will address the following questions: What are the effects of the lowered NAAQS? Do we observe elevated O3 during 2012 at surface sites reported in previous studies? And if so, what are the causes? How variable is free-tropospheric O3 over California and Nevada? How frequently do we observe high O3 lamina in the free troposphere and what are the surface impacts?

tropospheric↗

Comparing Potential Recharge Estimates From Three Land Surface Models Across the Western US

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.

groundwater↗

Large Scale Deformation of the Western US Cordillera

Destructive earthquakes occur throughout the western US Cordillera (WUSC), not just within the San Andreas fault zone. But because we do not understand the present-day large-scale deformations of the crust throughout the WUSC, our ability to assess the potential for seismic hazards in this region remains severely limited. To address this problem, we are using a large collection of Global Positioning System (GPS) networks which spans the WUSC to precisely quantify present-day large-scale crustal deformations in a single uniform reference frame. Our work can roughly be divided into an analysis of the GPS observations to infer the deformation field across and within the entire plate boundary zone and an investigation of the implications of this deformation field regarding plate boundary dynamics.

Bennett, Richard A.↗

The Role of Wind Speed in Prolonging Large Fire Durations in the Western US

Abstract The duration of large wildfires in the western US has increased significantly from 1992 to 2020 in the two fire seasons, by 0.76 days yr −1 in summer and 0.55 days yr −1 in fall. The factors driving the trend and variability were analyzed using multiple linear regression models. Our analysis identified the maximum daily wind speed during large fires, which has also increased during the study period, as the primary predictor for the large fire duration. Despite the observed rise in maximum wind speed specifically during large fires, there are no corresponding trends in the average daily mean wind speed throughout the fire seasons. The mechanisms underlying the increase in maximum wind speed during large fires remain unclear and warrant further investigation, as they may pose growing challenges for fire control.

54 ENVIRONMENTAL SCIENCES↗

CERF: IM3 Projected Western US Power Plant Locations

Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

CERF↗

Modeling the Water Systems of the Western US to Support Climate‐Resilient Electricity System Planning

Abstract Electricity and water systems in the Western US (WUS) are closely connected, with hydropower comprising 20% of total annual WUS generation, and electricity related to water comprising about 7% of total WUS electricity use. Because of these interdependencies, the threat of climate change to WUS resources will likely have compounding electricity impacts on the Western Interconnect grid. This study describes a WUS‐wide water system model with a particular emphasis on estimating climate impacts on hydropower generation and water‐related electricity use, which can be linked with a grid expansion model to support climate‐resilient electricity planning. The water system model combines climatically‐driven physical hydrology and management of both water supply and demand allocation, and is applied to an ensemble of 15 climate scenarios out to 2050. Model results show decreasing streamflow in key basins of the WUS under most scenarios. Annual water‐related electricity use increases up to 4%, and by up to 6% during the summer months, driven by growing agricultural demands met increasingly through a shift toward energy‐intensive groundwater to replace declining surface water. Total annual hydropower generation changes by +5% to −20% by mid‐century but declines in most scenarios, with decreases in summer generation by up to nearly −30%. Water‐related electricity use increases tend to coincide with hydropower generation declines, annually and seasonally, demonstrating the importance of concurrently evaluating the climate signal on both water‐for‐energy and energy‐for‐water to inform planning for grid reliability and decarbonization goals.

13 HYDRO ENERGY↗

Connections Between Mean North Pacific Circulation and Western US Precipitation Extremes in a Warming Climate

Abstract Extreme precipitation has widespread impacts over the western US (WUS), which are expected to be exacerbated in the future given thermodynamically driven increases in atmospheric moisture and shifts in atmospheric circulation patterns. However, internal climate variability complicates how these factors affect future projections of precipitation changes. In this study, we investigate late 21st‐century changes in mean‐state responses over the North Pacific Ocean and associated WUS precipitation extremes using the Multi‐Model Large Ensemble Archive, which is a recent and valuable resource to disentangle the effects of model structural differences from internal variability. We found that inter‐model differences in precipitation extremes over the WUS are large: from south to north (here, from California to Washington), models show different levels of increases for both the frequency and intensity of heavy precipitation. In general, the Pacific Northwest sees a more consistent signal than California. We show that wet‐season mean circulation influences extreme precipitation, by using a decomposition of the relative contributions of thermodynamic (atmospheric humidity) and dynamic (large‐scale circulation) driven changes. The thermodynamic contribution dominates, however, the dynamic contribution varies with latitude and differs substantially between model ensembles. Inter‐model differences affect the spread in not only the magnitude, but also the sign of the dynamic contribution. This implies that mean circulation changes contribute to uncertainty in quantifying the regional structure of concentrated moisture flux and future extreme events. This result highlights the need to more accurately constrain projected North Pacific coupled circulation changes to narrow the spread in projections of future precipitation extremes.

54 ENVIRONMENTAL SCIENCES↗

Natural Variability Has Concealed Increases in Western US Flood Hazard Since the 1970s

Flood hazard across the western United States (US) has generally shown decreasing trends in recent decades. This region's extreme streamflow is highly influenced by natural variability, which could either mask or amplify anthropogenic streamflow trends. Here, in this study, we utilize a technique known as dynamical adjustment to assess historical (1970–2020) annual maximum 1-day streamflow (Qx1d) from unregulated basins across the western US with and without the impact of natural variability. After removing natural variability, the fraction of basins with a positive (>5%) trend in Qx1d shifts from 25% to 53%. Basins with increasing (decreasing) Qx1d trends after dynamical adjustment exhibit weak (strong) drying, and furthermore are associated with intensifying precipitation extremes and/or large decreases in snowpack. Increasing flood hazard will likely emerge for such basins as the current phase of natural decadal variability shifts, and anthropogenic signals continue to intensify.

54 ENVIRONMENTAL SCIENCES↗

Variable wildfire impacts on the seasonal water temperatures of western US streams: A retrospective study

Recent increases in the burn area and severity of wildfires in the western US have raised concerns about the impact on stream water temperature–a key determinant of cold-water fish habitats. However, the effect on seasonal water temperatures of concern, including winter and summer, are not fully understood. In this study, we assessed the impact of wildfire burns at Boulder Creek (Oregon), Elk Creek (Oregon), and Gibbon River (Wyoming) watersheds on the downstream winter and summer water temperatures for the first three post-fire years. To obtain results independent of the choice of the analytical method, we evaluated the consequence of each burn using three different statistical approaches that utilize local water temperature data. Our results from the three approaches indicated that the response of water temperatures to wildfire burns varied across seasons and sites. Wildfire burns were associated with a median increase of up to 0.56°C (Standard Error; S.E. < 0.23°C) in the summer mean water temperatures (MWT) and 62 degree-day Celsius (DDC; S.E. < 20.7 DDC) in the summer accumulated degree days (ADD) for the three subsequent years across studied stream sites. Interestingly, these burns also corresponded to a median decrease of up to 0.49°C (S.E. < 0.45°C) in the winter MWT and 39 DDC (S.E. < 40.5 DDC) in the winter ADD for the same period across sites. Wildfire effects on the downstream water temperatures diminished with increasing site distance from the burn perimeter. Our analyses demonstrated that analytical methods that utilize local watershed data could be applied to evaluate fire effects on downstream water temperatures.

54 ENVIRONMENTAL SCIENCES↗

Wildfires increasingly impact western US fluvial networks

Wildfires are increasing globally in frequency, severity, and extent, but their impact on fluvial networks, and the resources they provide, remains unclear. We combine remote sensing of burn perimeter and severity, in-situ water quality monitoring, and longitudinal modeling to create the first large-scale, long-term estimates of stream+river length impacted by wildfire for the western US. We find that wildfires directly impact ~6% of the total stream+river length between 1984 and 2014, increasing at a rate of 342 km/year. When longitudinal propagation of water quality impacts is included, we estimate that wildfires affect ~11% of the total stream+river length. Our results indicate that wildfire activity is one of the largest drivers of aquatic impairment, though it is not routinely reported by regulatory agencies, as wildfire impacts on fluvial networks remain unconstrained. We identify key actions to address this knowledge gap and better understand the growing threat to fluvial networks, water security, and public health risks.

54 ENVIRONMENTAL SCIENCES↗

A Multi-Satellite Framework to Rapidly Evaluate Extreme Biosphere Cascades: The Western US 2021 Drought and Heatwave

The increasing frequency and intensity of climate extremes and complex ecosystem responses motivate the need for integrated observational studies at low-latency to determine biosphere responses and carbon-climate feedbacks. Here, we develop a satellite-based rapid attribution workflow and demonstrate its use at a 1–2-month latency to attribute drivers of the carbon cycle feedbacks during the 2020-2021 Western US drought and heatwave. In the first half of 2021, concurrent negative photosynthesis anomalies and large positive column CO 2 anomalies were detected with satellites. Using a simple atmospheric mass balance approach, we estimate a surface carbon efflux anomaly of 132 TgC in June 2021, a magnitude corroborated 28 independently with a dynamic global vegetation model. Integrated satellite observations of hydrologic processes, representing the soil-plant-atmosphere continuum (SPAC), show that these surface carbon flux anomalies are largely due to substantial reductions in photosynthesis because of a spatially widespread moisture-deficit propagation through the SPAC between 2020 and 2021. A causal model indicates deep soil moisture stores partially drove photosynthesis, maintaining its values in 2020 and driving its declines throughout 2021. The causal model also suggests legacy effects may have amplified photosynthesis deficits in 2021 beyond the direct effects of environmental forcing. The integrated, observation framework presented here provides a valuable first assessment of a biosphere extreme response and an independent testbed for improving drought propagation and mechanisms in models. The rapid identification of extreme carbon anomalies and hotspots can also aid mitigation and adaptation decisions.

Causal model↗

Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method

More frequent and widespread large fires are occurring in the western United States (US), yet reliable methods for predicting these fires, particularly with extended lead times and a high spatial resolution, remain challenging. In this study, we proposed an interpretable and accurate hybrid machine learning (ML) model, that explicitly represented the controls of fuel flammability, fuel availability, and human suppression effects on fires. The model demonstrated notable accuracy with a F 1 -score of 0.846 ± 0.012, surpassing process-driven fire danger indices and four commonly used ML models by up to 40% and 9%, respectively. More importantly, the ML model showed remarkably higher interpretability relative to other ML models. Specifically, by demystifying the “black box” of each ML model using the explainable AI techniques, we identified substantial structural differences across ML fire models, even among those with similar accuracy. The relationships between fires and their drivers, identified by our model, were aligned closer with established fire physical principles. The ML structural discrepancy led to diverse fire predictions and our model predictions exhibited greater consistency with actual fire occurrence. With the highly interpretable and accurate model, we revealed the strong compound effects from multiple climate variables related to evaporative demand, energy release component, temperature, and wind speed, on the dynamics of large fires and megafires in the western US. Our findings highlight the importance of assessing the structural integrity of models in addition to their accuracy. They also underscore the critical need to address the rise in compound climate extremes linked to large wildfires.

54 ENVIRONMENTAL SCIENCES↗

EOSDIS Terra Data Sampler #1: Western US Wildfires 2000

This CD-ROM contains sample data in HDF-EOS format from the instruments on board the Earth Observing System (EOS) Terra satellite: (1) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER); (2) Clouds and the Earth's Radiant Energy System (CERES); (3) Multi-angle Imaging Spectroradiometer (MISR); and (4) Moderate Resolution Imaging Spectroradiometer (MODIS). Data from the Measurements of Pollution in the Troposphere (MOPITT) instrument were not available for distribution (as of October 17, 2000). The remotely sensed, coincident data for the Western US wildfires were acquired August 30, 2000. This CD-ROM provides information about the Terra mission, instruments, data, and viewing tools. It also provides the Collage tool for viewing data, and links to Web sites containing other digital data processing software. Full granules of the data on this CD-ROM and other EOS Data and Information System (EOSDIS) data products are available from the NASA Distributed Active Archive Centers (DAACs).

Perkins, Dorothy C.↗

Further adoption of conservation tillage can increase maize yields in the western US Corn Belt

Conservation tillage can reduce soil erosion, increase soil health, and decrease labor and fuel input costs. Despite these benefits, potential yield impacts remain an important concern for farmers considering adoption. Previous research suggests that conservation tillage is likely to have the largest yield benefits in more arid conditions, but a lack of field-level analyses across climatic, management and soil conditions limits confidence in such predictions. Satellite imagery provides the opportunity to monitor agricultural lands at sub-field resolution across large spatial scales and wide environmental gradients. Here we investigate the maize yield impacts of conservation tillage in the semi-arid western US Corn Belt, using sub-field resolution datasets on tillage practices and crop yields derived from satellite data spanning four states (Nebraska, Kansas, South Dakota, and North Dakota) between 2008 and 2020. On these datasets, we estimate heterogenous yield outcomes for several thousand maize fields across gradients in climate, soil quality and irrigation status by using a causal forests analysis, an adaptation of the random forests machine-learning algorithm for causal inference on observational data. We find that long-term adoption of conservation tillage increased rainfed maize yields by an average of 9.9% in the region. Impacts on irrigated yields were small and not statistically significant. These results, along with an analysis of variables related to greater than average yield benefits, indicate that improved water infiltration and retention are the primary reasons for conservation tillage benefits. Despite yield benefits, many fields estimated to see increased yields under long term low till have not adopted the practice. Therefore, we identify specific counties likely to benefit most from increased levels of adoption. Our results strengthen the understanding of the impacts of conservation agriculture on crop yields and help define environments and counties most likely to benefit from conservation tillage.

54 ENVIRONMENTAL SCIENCES↗

Mechanisms of crustal deformation in the western US

The deformation processes in the western United States were studied, considering both deterministic models and random or statistical models. The role of the intracrustal delamination and mechanisms of crustal thinning were also examined. The application of fractal techniques to understand how the crust is deforming was studied in complex regions. Work continued on the development of a fractal based model for deformation in the western United States. Fractal studies were also extended to the study of topography and the geoid.

Turcotte, Donald L.↗

The Influence of Land‐Surface Conditions on the 2020–2021 Western US Drought

Abstract In summer 2021, 90% of the western United States (WUS) experienced drought, with over half of the region facing extreme or exceptional conditions, leading to water scarcity, crop loss, ecological degradation, and significant socio‐economic consequences. Beyond the established influence of oceanic forcing and internal atmospheric variability, this study highlights the importance of land‐surface conditions in the development of the 2020–2021 WUS drought, using observational data analysis and novel numerical simulations. Our results demonstrate that the soil moisture state preceding a meteorological drought, due to its intrinsic memory, is a critical factor in the development of soil droughts. Specifically, wet soil conditions can delay the transition from meteorological to soil droughts by several months or even nullify the effects of La Niña‐driven meteorological droughts, while drier conditions can exacerbate these impacts, leading to more severe soil droughts. For the same reason, soil droughts can persist well beyond the end of meteorological droughts. Our numerical experiments suggest a relatively weak soil moisture‐precipitation coupling during this drought period, corroborating the primary contributions of the ocean and atmosphere to this meteorological drought. Additionally, drought‐induced vegetation losses can mitigate soil droughts by reducing evapotranspiration and slowing the depletion of soil moisture. This study highlights the importance of soil moisture and vegetation conditions in seasonal‐to‐interannual drought predictions. Findings from this study have implications for regions like the WUS, which are experiencing anthropogenically‐driven soil aridification and vegetation greening, suggesting that future soil droughts in these areas may develop more rapidly, become more severe, and persist longer.

Jiang, Yelin [Lamont‐Doherty Earth Observatory Col↗