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At least 343 records · Page 19

Scrutinizing entrainment and mass flux closures in shallow cumulus parameterizations using cloud-radar observations and large-eddy simulation (Final Report)

Representing warm, shallow clouds is a challenge for Global Climate Models, which leads to uncertainty in model projections of future climate. Our study was particularly concerned with how climate models represent the effects of shallow, non-precipitating cumulus clouds. Climate models must make certain assumptions when representing low clouds such as how much dry air from outside the cloud is mixed into the warm, moist cloud updraft. This process is called “entrainment” and tends to weaken the cloud updraft and dry out the cloud, compared to a theoretical cloud with no mixing. This project was a joint observational and modeling study to derive estimates of entrainment from field observations and use high-resolution modeling to evaluate the assumptions used in climate model representations of shallow cumulus. Our research took advantage of a wide variety of Department of Energy measurements from fixed climate-monitoring locations over the Southern Great Plains of the U.S. and the in the Eastern North Atlantic, along with short-term field projects (MAGIC, CAP–MBL, ACE–ENA). During the project, the PI maintained regular collaborations with Department of Energy Scientists at Brookhaven and Argonne National Laboratories. The project funded two students, who both obtained their M.S. in Atmospheric Science and are currently in the Atmospheric Science Ph.D. program. Both were lead authors on research papers funded by this grant.

54 ENVIRONMENTAL SCIENCES↗

Faster recovery of North Atlantic tropical cyclone-induced cold wakes in recent decades

Intense winds associated with tropical cyclones (TCs) generate surface ocean cooling in their wakes, which can persist for several weeks in their aftermath. While multi-decadal observations of the sea surface have shown a substantial warming of the ocean, long-term changes in cold wake recovery time remain largely unknown. Here we find a trend toward faster recovery of TC cold wakes in the Atlantic main development region (MDR) since 2001. This is due primarily to a decrease in the strength of the North Atlantic trade winds, which reduces evaporative cooling of the ocean. The faster damping of TC cold wakes has led to a significant increase in the intensification of subsequent TCs that encounter lingering wakes from prior TCs, with a magnitude that is about 9% of that from long-term warming of the ocean. Finally, earth system model simulations indicate that the observed decrease in the cold wake recovery time will likely continue into the future.

54 ENVIRONMENTAL SCIENCES↗

Interactions Between Clouds and Wind-Driven Surface Heat Exchanges over Land

Earth system model experiments show that increasing horizontal resolution fundamentally alters the simulated soil-moisture-precipitation feedback. Kilometer-scale simulations often produce weaker or even negative feedback compared to coarse-resolution models. A key difference of kilometer-scale models is that they resolve mesoscale secondary circulations, including boundary layer horizontal rolls and cellular structures, in addition to cold pools and downdrafts associated with convective precipitation. However, because the relevant processes occur on yet-smaller scales, these circulations are often poorly resolved. This project demonstrated that boundary layer secondary circulations significantly affect surface heat exchanges and wind gusts, and that current model parameterizations can misrepresent these processes at kilometer-scale resolution. Using DOE Atmospheric Radiation Measurement (ARM) observations and targeted experiments with the DOE Energy Exascale Earth System Model (E3SM), we identified physically unrealistic wind gust and surface flux responses to secondary circulations, diagnosed a systematic overestimation of wind shear in convective cold pools, and uncovered a multivariate relationship between land surface fluxes and the scales of updrafts that form shallow cumulus clouds. These findings provide observation-based recommendations for improving parameterizations of surface fluxes and wind gusts in high-resolution Earth system models, thereby reducing uncertainty in convective storm prediction and land-atmosphere feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic-scale atmospheric dynamics, their performance across timescales and under out-of-distribution forcing, such as +3K or +4K uniform-warming forcings, and the sources of biases remain elusive, to establish the model's reliability for Earth science. Here, we design three sets of experiments targeting synoptic-scale phenomena, interannual variability, and out-of-distribution uniform-warming forcings. We evaluate the Neural General Circulation Model (NeuralGCM), a hybrid model integrating a dynamical core with ML-based component, against observations and physics-based Earth system models (ESMs). At the synoptic scale, NeuralGCM captures the evolution and propagation of extratropical cyclones with performance comparable to ESMs. At the interannual scale, when forced by El Niño-Southern Oscillation sea surface temperature (SST) anomalies, NeuralGCM successfully reproduces associated teleconnection patterns but exhibits deficiencies in capturing nonlinear response. Under out-of-distribution uniform-warming forcings, NeuralGCM simulates similar responses in global-average temperature and precipitation and reproduces large-scale tropospheric circulation features similar to those in ESMs. Notable weaknesses include overestimating the tracks and spatial extent of extratropical cyclones, biases in the teleconnected wave train triggered by tropical SST anomalies, and differences in upper-level warming and stratospheric circulation responses to SST warming compared to physics-based ESMs. The causes of these weaknesses were explored. Despite the noted weaknesses, NeuralGCM reproduces responses across experiments reasonably and performs comparably to ESMs. By integrating a dynamical core with ML, NeuralGCM shows potential for developing ML-based ESMs.

global warming↗

Steric Sea Level Rise and Relationships with Model Drift and Water Mass Representation in GFDL CM4 and ESM4

Abstract Density-driven steric seawater changes are a leading-order contributor to global mean sea level rise. However, intermodel differences in the magnitude and spatial patterns of steric sea level rise exist at regional scales and often emerge during the spinup and preindustrial control integrations of climate models. Steric sea level results from an eddy-permitting climate model, GFDL CM4, are compared with a lower-resolution counterpart, GFDL-ESM4. The results from both models are examined through basin-scale heat budgets and watermass analysis, and we compare the patterns of ocean heat uptake, redistribution, and sea level differ in ocean-only [i.e., Ocean Model Intercomparison Project (OMIP)] and coupled climate configurations. After correcting for model drift, both GFDL CM4 and GFDL-ESM4 simulate nearly equivalent ocean heat content change and global sea level rise during the historical period. However, the GFDL CM4 model exhibits as much as a 40% increase in surface ocean heat uptake in the Southern Ocean and subsequent increases in horizontal export to other ocean basins after bias correction. The results suggest regional differences in the processes governing Southern Ocean heat export, such as the formation of Antarctic Intermediate Water (AAIW), Subpolar Mode Water (SPMW), and gyre transport between the two models, and that sea level changes in these models cannot be fully bias-corrected. Since the process-level differences between the two models are evident in the preindustrial control simulations of both models, these results suggest that the control simulations are important for identifying and correcting sea level–related model biases.

Krasting, John P. [a NOAA/OAR/Geophysical Fluid Dy↗

Discrepant trends in global land-surface and air temperatures controlled by vegetation biophysical feedbacks

Satellite-based land surface temperature (Ts) with continuous global coverage is increasingly used as a complementary measure for air temperature (Ta), yet whether they observe similar temporal trends remains unknown. Here, we systematically analyzed the trend of the difference between satellite-based Ts and station-based Ta (Ts–Ta) over 2003–2022. We found the global land warming rate inffered from Ts was on average 42.6% slower than that from Ta (Ts–Ta trend: -0.011 °C yr -1 , p = 0.06) during daytime of summer. This slower Ts-based warming was attributed to recent Earth greening, which effectively cooled canopy surface through enhancing evapotranspiration and turbulent heat transfer. However, Ts showed faster warming than Ta during summer nighttime (0.015 °C yr -1 , p < 0.01), winter daytime (0.0069 °C yr -1 , p = 0.08) and winter nighttime (0.0042 °C yr -1 , p = 0.16), when vegetation activity is limited by temperature and solar radiation. Our results indicate potential biases in assessments of atmospheric warming and the vegetation-air temperature feedbacks using satellite-observed surface temperature proxies.

54 ENVIRONMENTAL SCIENCES↗

Air‐Ice‐Ocean Coupling During a Strong Mid‐Winter Cyclone: Observing Coupled Dynamic Interactions Across Scales

Abstract Arctic cyclones are key drivers of sea ice and ocean variability. During the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, joint observations of the coupled air‐ice‐ocean system were collected at multiple spatial scales. Here, we present observations of a strong mid‐winter cyclone that impacted the MOSAiC site as it drifted in the central Arctic pack ice. The sea ice dynamical response showed spatial structure at the scale of the evolving and translating cyclonic wind field. Internal ice stress and ocean stress play significant roles, resulting in timing offsets between the atmospheric forcing and the ice response and post‐cyclone inertial ringing in the ice and ocean. Ice motion in response to the wind field then forces the upper ocean currents through frictional drag. The strongest impacts to the sea ice and ocean from the passing cyclone occur as a result of the surface impacts of a strong atmospheric low‐level jet (LLJ) behind the trailing cold front and changing wind directions between the warm‐sector LLJ and post cold‐frontal LLJ. Impacts of the cyclone are prolonged through the coupled ice‐ocean inertial response. Local impacts of the approximately 120 km wide LLJ occur over a 12 hr period or less and at scales of a kilometer to a few tens of kilometers, meaning that these impacts occur at combined smaller spatial scales and faster time scales than most satellite observations and coupled Earth system models can resolve.

Meteorology & Atmospheric Sciences↗

Improving the Capabilities and Computational Efficiency of the RTE+RRTMGP Radiation Code (Final Report)

This report details progress on the RTE+RRTMGP radiation codes made during the period of performance. RTE+RRTMGP is a set of codes for computing radiative fluxes in planetary atmospheres. RRTMGP uses a k-distribution to provide an optical description (absorption and possibly Rayleigh optical depth) of the gaseous atmosphere, along with the relevant source functions, on a pre-determined spectral grid given temperatures, pressures, and gas concentration. RTE computes fluxes given spectrally-resolved optical descriptions and source functions. Spectrally-resolved fluxes are summarized (“reduced”) via a user extensible class. The initial release of the code and the design choices are described in Pincus et al. 2019; the codes are available on Github. Although RRTMGP was based on current (at the time) empirical spectroscopic data, RTE and RRTMGP were developed in large part to modernize software practices. The design focused on flexibility broadly interpreted: by separating code from data and allowing data to drive computation; in coupling to the host model (e.g. the coupling of clouds to radiative fluxes is user-controlled); with respect to programming languages (computational tasks are accessed via widely-compatible C interfaces); and with respect to hardware (the codes run on a range of CPU and GPU architectures). The code also puts an emphasis on modularity and clarity. RTE+RRTMGP v1.0 was released in September 20219. This award supported the evolution of the RTE+RRTMGP code base to support greater flexibility, accuracy, and efficiency.

54 ENVIRONMENTAL SCIENCES↗

Characterization of Root Zone Soil Moisture and Herpetofaunal Biodiversity in the Southern Great Plains

(1) Goal: The scientific objective to the proposed research is to develop a proto-type downscaled (<1 km) version of the root-zone soil moisture product called SoilMERGE or SMERGE. This objective is linked as root zone soil moisture is a critical climate variable that has a more direct influence on plant growth than precipitation. Therefore, the developed downscaled version of SMERGE can be used as input into biodiversity informatic techniques (i.e., maximum entropy modeling) Development of downscaled SMERGE will be facilitated by Department of Energy (DOE) resources specifically data from the DOE Atmospheric Radiation Measurement (ARM) facility and modeling platforms such as the Energy Exascale Earth System Model (E3SM).

54 ENVIRONMENTAL SCIENCES↗

Partial Support for the Federal Committee for Meteorological Services and Supporting Research

An interagency collaboration initiated between Navy, Air Force and NOAA and expanded to DOE, NASA, and NSF in 2012, for coordination of research to operations of a National earth system analysis and prediction capability. The goal of ESPC is to meet broad but specific agency requirements for an earth system analysis and prediction framework to support one-day to decadal global prediction at appropriate horizontal and vertical resolution; including the atmosphere, ocean, land, cryosphere, and space.

54 ENVIRONMENTAL SCIENCES↗

Subsets of geostationary satellite data over international observing network sites for studying the diurnal dynamics of energy, carbon, and water cycles

The latest generation of geostationary satellites provide Earth observations similar to widely used polar-orbiting sensors but at intervals as frequently as every 5–10 min, making them ideal for studying the diurnal dynamics of land–atmosphere interactions. The NASA Earth Exchange (NEX) group created the GeoNEX datasets by collating data from several geostationary platforms, including GOES-16/17/18, Himawari-8/9, and GK-2A, and placing them on a common grid to facilitate use by the Earth science community. Here, we document the GeoNEX Coincident Ground Observations (GeCGO) dataset for terrestrial ecosystem studies and provide examples for its use. Currently, GeCGO provides GOES-16 Advanced Baseline Imager (ABI) data over a 10 km × 10 km area surrounding 1586 network sites across the Americas. GeCGO makes it easy to compare the time series of geostationary data with the diurnal ground observations, including carbon/water fluxes and aerosol optical depth, and is extensible to other regions. We also develop GeoNEXTools to facilitate analyses that require both GeoNEX data and other NASA satellite data. The objectives of this paper are to introduce GeCGO and GeoNEXTools and demonstrate their applications. First, we describe the details of GeCGO and GeoNEXTools. Second, we explain how GeCGO can be integrated with other satellite data. Finally, we showcase comparisons between GeCGO and observations from three ground-based networks. GeCGO is available at https://doi.org/10.25966/y5pe-xp41 (Hashimoto et al., 2025).

Hashimoto, Hirofumi [NASA Ames Research Center (AR↗

Evaluating and Improving Convective Parameterization for GCMs Using ARM Observations. Final report

This technical report summarizes the achievements during the project period funded by the Atmospheric System Research (ASR) program. The general goal of the project is to improve the representation of atmospheric deep convection in global climate models. By using DOE Atmospheric Radiation Measurement (ARM) program observations and a hierarchy of models from cloud-resolving to global climate models, we evaluated and improved many aspects of convection parameterization schemes, such as the trigger function for convection and closure condition to determine the amount of convection. We also incorporated the stochasticity of convection into a convection scheme. These improvements, when implemented into the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) and the DOE Exascale Energy Earth System Model (E3SM), led to improved simulation of precipitation characteristics, including precipitation intensity, Intertropical Convergence Zone, and Madden-Julian oscillation. The project also improved the representation of microphysical processes in convective clouds. It enables the interaction of cloud microphysics with aerosols in weather and climate models.

54 ENVIRONMENTAL SCIENCES↗

North Slope Alaska and Tethered Balloon Systems: ARM Facilities Monthly Status Update

In support of the DOE Office of Science, Sandia National Labs is one of nine national laboratories which oversees the Atmospheric Radiation Measurement (ARM) Program. The Sandia ARM team has an obligation to fulfill its mission to provide the nation with data to improve the understanding of climate processes and the representation of those processes in climate models. Sandia’s ARM team’s ability to provide detailed and accurate descriptions of the Earth’s atmosphere in diverse climate regimes assists the DOE in development of sustainable solutions to the nation’s energy and environmental challenges. Sandia Labs manages ARM atmospheric facilities along the North Slope of Alaska (NSA) at Utqiagvik as well as the Tethered Balloon System (TBS). Activities conducted at NSA and with the TBS aide in data collection for the ARM data archive. An overview of these activities for the month of December follows.

54 ENVIRONMENTAL SCIENCES↗

Elevated-Mn ChemCam targets illuminating Mn redox cycling and diagenesis in the Bradbury Rise, Gale Crater, Mars

Manganese plays a crucial role as a paleo-environmental and geological indicator due to its sensitivity to redox potential and pH variations in the environment. On Earth, the association between the rise of atmospheric oxygen during the Great Oxidation Event and the presence of Mn in the sedimentary rock record underscores its significance. Here, in this study, we reexamined ChemCam targets from the first 600 sols of the Mars Science Laboratory mission, focusing on identifying instances of above-average Mn within these targets. These elevated-Mn targets were categorized into distinct geologic classes, revealing a pattern linking heightened Mn levels with diagenetically altered materials, such as calcium-sulfate veins and concretions, as well as clay minerals within the same targets, indicating a compelling relationship between Mn enrichment and diagenetic processes. High concentrations of Mn were observed in chemically altered targets, suggesting the occurrence of multiple fluid events: the first to alter the material and the second to deposit Mn. The observed patterns suggest multiple diagenetic events and redox cycling that facilitated the deposition and transport of Mn subsequent to the initial dissolution of basaltic materials. This research sheds light on the complexity of martian diagenetic processes and their implications for the planet’s environmental evolution.

58 GEOSCIENCES↗

Global Impacts of Marine Methanethiol Emissions and Chemistry in the Atmosphere

Oceanic emissions of dimethyl sulfide (DMS) have long been known to influence aerosol particle composition, cloud condensation nuclei (CCN) concentration, and Earth’s radiative budget. However, the impact of oceanic emissions of methanethiol (MeSH), a sulfur compound produced by the same oceanic precursor as DMS, has been relatively less explored. The gas-phase oxidation of MeSH has a higher effective yield of SO 2 and a shorter oxidative lifetime compared to DMS, highlighting the relevance of this pathway for the modeled representation of particle formation, growth, and CCN abundance in the marine atmosphere. Here, we use the global chemical transport model GEOS-Chem to explore possible scenarios representative of specific environmental conditions and MeSH emission schemes based on previous experimental studies. We further implement and test previously reported chemical mechanisms for MeSH oxidation, along with additional improvements, highlighting key uncertainties and sensitivities for regional and global sulfur budgets. We place our results in the context of recent modeling updates to DMS chemistry and cloud processing, which further impact SO 2 production in the marine atmosphere in parallel with MeSH oxidation. Within the overall marine sulfur budget, our findings highlight that MeSH plays a significant role in SO 2 production in the marine atmosphere, contributing to regional surface layer concentration increases of up to 40–60%. These results point to the importance of MeSH for efforts aimed at improving the modeled representation of sulfur spatiotemporal patterns relevant to air quality predictions and climate impact assessments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The GFDL‐CM4X Climate Model Hierarchy, Part II: Case Studies

This paper is Part II of a two‐part paper that documents the Climate Model version 4X (CM4X) hierarchy of coupled climate models developed at the Geophysical Fluid Dynamics Laboratory. Part I of this paper is presented in Griffies et al. (2025a, https://doi.org/10.1029/2024MS004861 ). Here we present a suite of case studies that examine ocean and sea ice features that are targeted for further research, which include sea level, eastern boundary upwelling, Arctic and Southern Ocean sea ice, Southern Ocean circulation, and North Atlantic circulation. The case studies are based on experiments that follow the protocol of version 6 from the Coupled Model Intercomparison Project. The analysis reveals a systematic improvement in the simulation fidelity of CM4X relative to its CM4.0 predecessor, as well as an improvement when refining the ocean/sea ice horizontal grid spacing from the 0.25° of CM4X‐p25 to the 0.125° of CM4X‐p125. Even so, there remain many outstanding biases, thus pointing to the need for further grid refinements, enhancements to numerical methods, and/or advances in parameterizations, each of which target long‐standing model biases and limitations.

54 ENVIRONMENTAL SCIENCES↗

A U.S. scientific community review of carbon cycle science gaps and opportunities to better support earth system science and carbon management

Greenhouse gas (GHG) emissions continue to grow, while natural carbon reservoirs are becoming increasingly vulnerable to anthropogenic pressures, climate extremes, and disturbance. These changes are impacting humans, ecosystems, and natural resources worldwide. Tracking and mitigating GHG emissions require a pivot to operational monitoring of regional carbon flux and stock changes. The current GHG observing system is addressing needs at two distinct scales: 1) Local scale (< 1 km), related to anthropogenic point source emissions, and 2) global scales (> 1000 km), related to land and ocean carbon sinks. More focus on intermediate (10–1000 km) scales is needed to more effectively monitor progress in reducing carbon emissions, enhancing removals, and maintaining sinks. Representatives from carbon cycle biomass and flux communities across United States government agencies and academic institutions met in September 2024 to discuss the rationale and scientific context for more effectively implementing an operational system for GHG monitoring in support of urban and national carbon management needs. To guide development of this system, we propose a multi-tiered global spaceborne observing framework for carbon flux and stock, prioritizing: 1) frequent GHG partial columns for carbon emissions and removals; 2) continuous time series and data fusion of biomass from Lidar and Synthetic Aperture Radar (SAR) for carbon stocks, and 3) expanded coverage of tropical, high latitude, and oceanic regions to monitor carbon cycle tipping points and feedbacks. This system should be complemented by expanded surface and airborne networks for oceanic and terrestrial/aquatic ecosystems for calibration, ground truthing, and study of under-sampled regions.

54 ENVIRONMENTAL SCIENCES↗

Emergence of seasonal delay of tropical rainfall during 1979–2019

Fundamental to Earth’s climate, tropical rainfall marks a dominant annual cycle characterized by its amplitude and phase, representing the range between wet and dry seasons and their onset timing, respectively. Under global warming, previous studies revealed enhanced amplitude of rainfall annual cycle over ocean and delayed phase over land in the tropics, underpinned by solid theories. It is unclear however whether these changes have already emerged in the observational records. Here, we report a robust delay of 3.02 and 3.43 days over the northern tropical land and Sahel respectively during 1979-2018 based on five observation datasets. Furthermore, most of the delay is captured by multiple ensemble simulations driven by external forcings, with greenhouse gases (GHG) more important over the northern tropical land and anthropogenic aerosols (AER) more important over the Sahel. Both GHG and AER delay the annual cycle of regional precipitation similarly by producing a moister and more ocean-like atmosphere, thus increasing its lag in response to seasonal solar forcing. Our findings provide new evidence of the human footprints on Earth’s hydrological cycle at continental and regional scales. As GHG and AER continue to increase and decrease respectively, these seasonal delays will be further amplified in the future.

54 ENVIRONMENTAL SCIENCES↗