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At least 1,171 records · Page 65

Object-Based Evaluation of Dynamical and Statistical Downscaled Precipitation Products over CONUS

High-resolution precipitation data, generated through dynamical downscaling (DD) or statistical downscaling (SD) of global climate model output, provide critical information for regional climate assessment and adaptation planning. Most downscaling development and validation have focused on accurate gridscale precipitation construction and ignored the spatial structure of precipitation across model grids and at the event scale. However, many applications, e.g., hydrologic modeling and the analysis using the downscaled precipitation, require a reasonable representation of the spatial structure of precipitation within watersheds. Therefore, a set of standard metrics to evaluate the representation of the spatial structure of individual storms across diverse downscaled precipitation products is desired. To address this need, we conducted an object-based evaluation of precipitation in decades-long DD and SD products over the contiguous United States (CONUS). Specifically, we evaluate their ability to reproduce various features of precipitation objects in the observations: total volume, precipitation area, peak intensity, and spatial structure. Multiple metrics (bias, Perkins score, and nonparametric statistical tests) are used to quantify model performance. Our evaluation reveals notable variations in performance among individual products across different climate zones and seasons, as well as between extreme and nonextreme events. In general, most DD products exhibit balanced performance across the four precipitation object features, while SD products vary more significantly in their performance across products. Based on this comprehensive evaluation, we provide guidance on choosing downscaled products for specific regions, seasons, and precipitation object features. These findings and recommendations can inform precipitation-relevant modeling and analysis over CONUS, guide future downscaling technique developments, and provide actionable information for climate impact assessment and adaptation.

Downscaling↗

Object-Based Evaluation of Dynamical and Statistical Downscaled Precipitation Products over CONUS

High-resolution precipitation data, generated through dynamical downscaling (DD) or statistical downscaling (SD) of global climate model output, provide critical information for regional climate assessment and adaptation planning. Most downscaling development and validation have focused on accurate gridscale precipitation construction and ignored the spatial structure of precipitation across model grids and at the event scale. However, many applications, e.g., hydrologic modeling and the analysis using the downscaled precipitation, require a reasonable representation of the spatial structure of precipitation within watersheds. Therefore, a set of standard metrics to evaluate the representation of the spatial structure of individual storms across diverse downscaled precipitation products is desired. To address this need, we conducted an object-based evaluation of precipitation in decades-long DD and SD products over the contiguous United States (CONUS). Specifically, we evaluate their ability to reproduce various features of precipitation objects in the observations: total volume, precipitation area, peak intensity, and spatial structure. Multiple metrics (bias, Perkins score, and nonparametric statistical tests) are used to quantify model performance. Our evaluation reveals notable variations in performance among individual products across different climate zones and seasons, as well as between extreme and nonextreme events. In general, most DD products exhibit balanced performance across the four precipitation object features, while SD products vary more significantly in their performance across products. Based on this comprehensive evaluation, we provide guidance on choosing downscaled products for specific regions, seasons, and precipitation object features. These findings and recommendations can inform precipitation-relevant modeling and analysis over CONUS, guide future downscaling technique developments, and provide actionable information for climate impact assessment and adaptation.

Environmental sciences↗

Steady global surface warming from 1973 to 2022 but increased warming rate after 1990

The change in global mean surface temperature is a crucial and broadly used indicator of the evolution of climate change. Any decadal scale changes in warming rate are however obfuscated by internal variability. Here we show that the surface temperature increase through the recent La Nina influenced years (2022) is consistent with the 50-year trend of 0.18 °C/decade. We use an Earth System Model based tool to filter out modulations to the warming rate by sea-surface temperature patterns and find consistent warming rates in four major global temperature data series. However, we also find clear indications, in all observational series, of a step-up in warming rate since around 1990. CMIP6 models generally do not capture this observed combination of long-term warming rate and recent increase.

58 GEOSCIENCES↗

Contributions to Polar Amplification in CMIP5 and CMIP6 Models

As a step towards understanding the fundamental drivers of polar climate change, we evaluate contributions to polar warming and its seasonal and hemispheric asymmetries in Coupled Model Intercomparison Project phase 6 (CMIP6) as compared with CMIP5. CMIP6 models broadly capture the observed pattern of surface- and winter-dominated Arctic warming that has outpaced both tropical and Antarctic warming in recent decades. For both CMIP5 and CMIP6, CO 2 quadrupling experiments reveal that the lapse-rate and surface albedo feedbacks contribute most to stronger warming in the Arctic than the tropics or Antarctic. The relative strength of the polar surface albedo feedback in comparison to the lapse-rate feedback is sensitive to the choice of radiative kernel, and the albedo feedback contributes most to intermodel spread in polar warming at both poles. By separately calculating moist and dry atmospheric heat transport, we show that increased poleward moisture transport is another important driver of Arctic amplification and the largest contributor to projected Antarctic warming. Seasonal ocean heat storage and winter-amplified temperature feedbacks contribute most to the winter peak in warming in the Arctic and a weaker winter peak in the Antarctic. In comparison with CMIP5, stronger polar warming in CMIP6 results from a larger surface albedo feedback at both poles, combined with less-negative cloud feedbacks in the Arctic and increased poleward moisture transport in the Antarctic. However, normalizing by the global-mean surface warming yields a similar degree of Arctic amplification and only slightly increased Antarctic amplification in CMIP6 compared to CMIP5.

54 ENVIRONMENTAL SCIENCES↗

Data and script associated with “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest”

This data package contains the data and code to use and run the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model (WT-WRF-Hydro) with the Sequential Precipitation Input Tagging (SPIT) framework. It is associated with the publication “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest” published in Scientific Reports (Butler et al., 2026; https://doi.org/10.1038/s41598-026-46539-1). We use the Continental U.S. (CONUSII; Rasmussen et al., 2021) dataset to force the model with an historical climate (2006–2013) and a future climate (2086–2093) with a representative carbon pathway (RCP) 8.5 scenario. We use the model to calculate water transit times in five headwater catchments within the U.S. Pacific Northwest. We also show key hydrologic and environmental variables that affect water transit times and changes in the future. Finally, we use observed data to validate the model such as stream water isotopes, snowpack characteristics, and stream discharge. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package consists of 11 folders: (1) "Figures" contains the exported figures used in the manuscript; (2) "Model_Isotope_Date" contains the WT-WRF-Hydro isotope date used in model validation; (3) “Model_Outputs_Future” contains the WT-WRF-Hydro future climate outputs; (4) “Model_Outputs_Historical” contains the WT-WRF-Hydro historical climate outputs; (5) “Model_Outputs_Weights_Areas” contains the WT-WRF-Hydro weights per catchment used to calculate water transit times and isotopes in stream water; (6) “MODIS_data_scripts” contains data used to validate snow conditions in the study area; (7) “Observed_Flow_Data” contains the observed streamflow data used in model validation; (8) “Observed_Isotope_Data” contains the observed stream water isotope data used in model validation; (9) “Scripts” contains the Python scripts used to general results and the figures; (10) “Statistic_Outputs” contains the water transit time statistical outputs reported in this manuscript; (11) “Validation_SNOTEL” contains the SNOTEL data used in model validation. The files in this data package have the following file extensions: .tif, .txt, .csv, .pdf, .py, .jpg, and .png.

American River↗

On the Effect of Historical SST Patterns on Radiative Feedback

Here, we investigate the dependence of radiative feedback on the pattern of sea-surface temperature (SST) change in fourteen Atmospheric General Circulation Models (AGCMs) forced with observed variations in SST and sea-ice over the historical record from 1871 to near-present. We find that over 1871-1980, the Earth warmed with feedbacks largely consistent and strongly correlated with long term climate sensitivity feedbacks (diagnosed from corresponding atmosphere-ocean GCM abrupt 4xCO2 simulations). Post 1980 however, the Earth warmed with unusual trends in tropical Pacific SSTs (enhanced warming in the west, cooling in the east) and cooling in the Southern Ocean that drove climate feedback to be uncorrelated with – and indicating much lower climate sensitivity than – that expected for long-term CO 2 increase. We show that these conclusions are not strongly dependent on the AMIP II SST dataset used to force the AGCMs, though the magnitude of feedback post 1980 is generally smaller in nine AGCMs forced with alternative HadISST1 SST boundary conditions. We quantify a ‘pattern effect’ (defined as the difference between historical and longterm CO 2 feedback) equal to 0.48 ± 0.47 [5-95%] W m -2 K -1 for the time-period 1871-2010 when the AGCMs are forced with HadISST1 SSTs, or 0.70 ± 0.47 [5-95%] W m -2 K -1 when forced with AMIP II SSTs. Assessed changes in the Earth’s historical energy budget agree with the AGCM feedback estimates. Furthermore satellite observations of changes in top-of-atmosphere radiative fluxes since 1985 suggest that the pattern effect was particularly strong over recent decades but may be waning post 2014.

54 ENVIRONMENTAL SCIENCES↗

Training the next generation of researchers in exploring cloud dynamics and microphysics using millimeter-wavelength radars

Millimeter-wavelength radars, with their ability to collect observations and high spatiotemporal resolution, have become cornerstone instruments for investigating cloud and precipitation microphysics and dynamics in the last two decades. Since the1990s the US Department of Energy Atmospheric Radiation Measurement (ARM) program has invested in mm-wavelength radar technology progressively adding scanning capability, additional frequencies and polarimetric capability. In addition, atmospheric observatories including those technologies have been operated overseas. Those technologies have enhanced our understanding of cloud and precipitation processes. Only a few universities operate those instruments and use them for educational purposes. The central role of mm- wavelength radars and their role will be further highlighted in the next decade. NASA and other international space agencies are planning to launch millimeter-wavelength (i.e., Ku, Ka, W, G- bands) Doppler radar in space to improve our understanding of cloud and precipitation formation, evolution and their impacts on global climate.

54 ENVIRONMENTAL SCIENCES↗

Estimating the Impacts of Increasing Temperatures and the Efficacy of Climate Adaptation Strategies in Urban Microclimates with Deep Learning

As urbanization and climate change progress, understanding and addressing urban heat becomes a priority for climate adaptation efforts. High temperatures concentrated in the urban core can drive increased risk of heat-related death and illness as well as increased energy demand for cooling. However, modeling the urban microclimate is an ongoing field of research typically burdened by an imprecise description of the built environment, incomplete observational records, significant computational cost, and a lack of high-resolution estimates of the impacts of increasing temperatures. Here, we present computationally efficient machine learning methods that can improve the accuracy of urban temperature estimates when compared to historical reanalysis data. These models are applied to a neighborhood in Los Angeles, and we compare the energy benefits of heat mitigation strategies to the impacts of climate change. We find that cooling demand is likely to increase substantially through midcentury, but engineered high-albedo surfaces could lessen this increase by more than 50 %. The corresponding increase in winter gas heating offsets the summer cooling benefit in the current climate, but total annual energy use from combined heating and cooling with electric heat pumps benefits from the engineered heat mitigation strategies under both current and future climates.

54 ENVIRONMENTAL SCIENCES↗

Estimating Individual Tree Mortality in the Sierra Nevada Using Lidar and Multispectral Reflectance Data

Widespread tree mortality events occur during periods of severe drought in temperate conifer forests and are expected to become more frequent in many areas due to climate change. Improved mapping of individual tree mortality is needed to identify risk factors and design effective conservation strategies. In this study, we used National Ecological Observatory Network (NEON) lidar and multispectral reflectance airborne observations to map individual tree mortality over a 160 km 2 area during and after the 2012–2016 drought for two sites in California's Sierra National Forest. We used NEON lidar to derive tree locations and crown perimeters and multispectral data to map tree mortality for more than 1 million trees. We found that 25.4% of the trees in our study area died between 2013 and 2017, with considerably higher mortality at the lower-elevation Soaproot Saddle site. Between 2017 and 2019, an additional 2.0%–2.8% of the trees died each year. Two wildfires in 2020 and 2021 increased tree mortality within burned area perimeters by 49%–89% between 2019 and 2021. Consistent with previous work, we found that tree mortality risk increased as a function of tree height. Tree mortality was positively associated with distance from rivers, trees per hectare, and decreasing slope at the lower elevation site. In contrast, increasing slope was positively associated with tree mortality at the higher elevation site. Our approach and dataset provide a means to study the combined effects of drought and wildfire on tree mortality and may improve projections of forest resilience under a changing climate.

54 ENVIRONMENTAL SCIENCES↗

Optimization of the light detection system of the ICARUS detector

The Short Baseline Neutrino (SBN) Program at Fermilab is designed to investigate short-baseline neutrino oscillations and test the hypothesis of sterile neutrinos, motivated by several experimental anomalies observed over the past decades. Within this program, the ICARUS experiment plays a key role. It employs the world’s largest Liquid Argon Time Projection Chamber (LArTPC) and serves as the farthest and most sensitive SBN detector for studying muon and electron neutrino oscillations. A crucial subsystem of the ICARUS detector is the Light Detection System (LDS), which captures the prompt scintillation light produced by neutrino interactions in the 600-ton active liquid Argon volume. This system provides precise timing information that is essential for event reconstruction, the trigger system, and cosmic background rejection. The LDS is composed of 360 Hamamatsu R5912-MOD 8-inch photomultiplier tubes (PMTs), operating under cryogenic conditions ($\sim 87 \ K$) inside the detector’s cryostats. During the detector’s operation at FNAL, a degradation in PMT gain has been observed, attributed to aging under low-temperature conditions. In collaboration with ICARUS teams from INFN Pavia and Catania, I developed an experimental setup to study the temperature-dependent behavior of the PMTs, performing gain measurements both at room temperature and down to $-70°C$ using a climatic chamber at INFN Catania. The results indicate that while the PMTs maintain stable gain at room temperature, a significant and permanent gain reduction occurs at low temperatures. Although $-70°C$ is still warmer than liquid Argon temperatures, the findings clearly demonstrate a gain-dependent performance degradation. The thesis also discusses mitigation strategies implemented in the ICARUS detector to address this issue and presents a simplified model to describe and simulate the observed behavior.

Saia, Clara [Catania U.] (ORCID:0009000464102417)↗

Fifty Years of Research on the Madden-Julian Oscillation: Recent Progress, Challenges, and Perspectives

The Madden-Julian Oscillation (MJO), first discovered by Madden and Julian in 1971, is a prominent tropical phenomenon with a typical period of 30–60 days and featured by a large-scale envelope of cloud clusters and rain systems moving eastward along the equator. The MJO significantly influences not only intense tropical rainstorms, such as hurricanes, but also extreme weather over the middle to high latitudes. Skillful prediction of the MJO several weeks ahead, therefore, will be greatly valuable for disaster mitigation purposes. However, many present-day climate models have great difficulty in realistically simulating the MJO for reasons that are not well understood. This article provides a comprehensive review of the recent progress in the observational, modeling, and theoretical study of the MJO, with a particular focus on the most recent decade. Several future research directions are also suggested to further advance our understanding and prediction capability of the MJO.

54 ENVIRONMENTAL SCIENCES↗

Slope-Aspect Induced Climate Differences Influence How Water Is Exchanged Between the Land and Atmosphere

Cross-slope climate differences in the midlatitudes are ecologically important, and impact vegetation-mediated water balance between the earth surface and the atmosphere. We made high-resolution in situ observations of air temperature, relative humidity, soil moisture, insolation, and sap velocity observations on 14 Pacific madrone trees (Arbutus menziesii) spanning adjacent north and south slopes at the University of California's Angelo Coast Range Reserve. To understand the cross-slope response of sap velocity, a proxy for transpiration, to microclimate, we modeled the sap velocity on each slope using a transpiration model driven by ambient environment and parameterized with a Markov Chain Monte Carlo parameter estimation process. The results show that trees on opposing slopes do not follow a shared pattern of physiological response to transpiration drivers. This means that the observed sap velocity differences are not due entirely to observed microclimate differences, but also due to population-level physiological differences, which indicates acclimation to inhabited microclimate. While our present data set and analytical tools do not identify mechanisms of acclimation, we speculate that differing proportions of sun-adapted and shade-adapted leaves, differences in stomatal regulation, and cross-slope root zone moisture differences could explain some of the observed and modeled differences.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses

Abstract Lateral subsurface flow plays an essential role in sustaining the terrestrial ecosystem, but it is not explicitly represented in most Earth System Models. In this study, we implemented an explicit lateral saturated flow model into the E3SM land model (ELM). The model explicitly describes lateral flow in the saturated zone by representing, for each model grid, an idealized hillslope consisting of five hydrologically connected soil columns. We conducted three model experiments driven by 0.125° atmospheric forcing data during 1980–2015 over California using models of the default ELM, a modified version of ELM to enhance infiltration, and the model with the lateral saturated flow model. The simulated runoff, evapotranspiration, and terrestrial water storage anomaly (TWSA) from the three simulations were evaluated against available observations, and the model explicitly representing lateral flow performs best. The new model produces greater gridcell‐averaged evapotranspiration especially over the mountainous regions with moderate relief and seasonally dry climates. Most importantly, it improves the modeled seasonal variations, interannual variabilities, and the recent decadal decline of TWSA. Many of these improvements can be attributed to the enhanced ecosystem resilience to droughts as demonstrated by transpiration increases caused by lateral flow. Model sensitivity experiments suggest that subsurface runoff is most sensitive to the ratio between horizontal and vertical saturated hydraulic conductivity, followed by hillslope planforms (convergent, divergent, and uniform), number of columns, and lower boundary conditions. Future work should effectively characterize hillslopes in global models and explore the long‐term influences of lateral water movement on modeled biogeochemical cycle.

54 ENVIRONMENTAL SCIENCES↗

Thermal acclimation of stem respiration implies a weaker carbon-climate feedback

The efflux of carbon dioxide (CO2) from woody stems, a proxy for stem respiration, is a critical carbon flux from ecosystems to the atmosphere, which increases with temperature on short timescales. However, plants acclimate their respiratory response to temperature on longer timescales, potentially weakening the carbon-climate feedback. The magnitude of this acclimation is uncertain despite its importance for predicting future climate change. We develop an optimality-based theory dynamically linking stem respiration with leaf water supply to predict its thermal acclimation. We show that the theory accurately reproduces observations of spatial and seasonal change. We estimate the global value for current annual stem CO2 efflux as 27.4 ± 5.9 PgC. By 2100, incorporating thermal acclimation reduces projected stem respiration without considering acclimation by 24 to 46%, thus reducing land ecosystem carbon emissions.

Zhang, Han↗

Urban Heat Island Effects to Air and Water Quality in the Augusta Metropolitan Area

The Urban Heat Island (UHI) is the longest-known anthropogenic impact on weather and climate. Urbanization in the 21st century has led to an amplification in UHI effects, which poses environmental concerns as well as public health risks. While the UHI is often observed in larger metropolitan areas, it is less studied in smaller or moderately-sized cities that are still developing. The population of the Augusta Metropolitan Area (AMA) has increased over 10% in the last decade. Because of increasing urban sprawl in conjunction with overall increased anthropogenic warming, it is critical to define Augusta’s UHI impact and model how it could change in the future.

Wermter, Joseph E.↗

Laminar burning speed measurements for hydrogen enhanced natural gas in a spherical chamber

This work presents laminar burning speed measurements for natural gas and hydrogen enhanced natural gas in gas-turbine conditions using a spherical combustion chamber at an initial temperature and pressure of 296 K and 10 atm, respectively. Natural gas and hydrogen fuels were prepared and mixed with a synthetic air mixture comprised of oxygen, nitrogen, and helium. The experimental data collected during 10 atm ignition was used to predict the LBS at elevated pressures (30 bar) to approach gas-turbine operating conditions. A significant enhancing effect of combustion pressure on LBS was observed, as well as H2 dilution. This work provides fundamental combustion data relevant to sustainable fuels to reduce economic dependence on carbon-based fossil fuels and reduce anthropogenic climate effects through 2050.

Yovino, Louis↗

Exploring the elevated water vapor signal associated with the free tropospheric biomass burning plume over the southeast Atlantic Ocean

In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol-cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6-7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments. Using reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and specialized WRF-Chem simulations, we trace the plume-vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper tropospheric air and then is subjected to conditions of strong westward advection, namely the southern African easterly jet (AEJ-S). Our analysis indicates that air masses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ~5-6 km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (~6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) back trajectories support this interpretation. This work thus gives insights into the conditions and processes which cause water vapor to covary with plume strength. Better understanding of this relationship, including how it varies spatially and temporally, is important to accurately quantify direct, semi-direct, and indirect aerosol effects over this region.

54 ENVIRONMENTAL SCIENCES↗

Convectively Induced Secondary Circulations and Wind‐Driven Heat Fluxes in the Surface Energy Balance Over Land

Increased resolution has enabled kilometer-scale weather and climate models to partially resolve secondary circulations, including horizontal convective rolls (HCRs) and cold pool gust fronts. Although these circulations are ubiquitous in convective boundary layers over land, their impacts on the surface energy balance are largely unknown. Doppler lidar and surface observations were combined with DOE E3SM land model experiments, revealing increased surface winds (5 m/s) and heat fluxes (50 W/m 2 ) in convergent branches of HCRs. Larger wind-driven flux responses (up to 150 W/m 2 ) were found along gust fronts. Surface energy balance shifts to accommodate wind-driven fluxes, reducing ground heat conduction and longwave cooling. Our findings from the US Southern Great Plains are broadly relevant to modeling convective boundary layers. In particular, widely used subgrid wind gust parameterizations were found to be physically inconsistent with resolved secondary circulations and could worsen climate prediction biases at kilometer-scales.

54 ENVIRONMENTAL SCIENCES↗