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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Transforming ESM Physical Parameterization Development Using Machine Learning Trained on Global Cloud-Resolving Models and Process Observations

ESMs robustly predict that 21st century greenhouse warming will slowly increase global mean precipitation, rapidly increase extreme precipitation, and increase subtropical drought. ESMs agree less about precipitation trends and extremes over particular land regions critical to human societies, e. g. in semi-arid regions such as California or the Sahel, or in wetter climates prone to monsoonal rainfall (e. g. southeast Asia) or to tropical cyclones and flooding from mesoscale convective systems (e. g. the southeastern U.S.) Deep convective parameterizations and poor representation of orography and complex vegetated land surfaces contribute to this inter-model spread; clouds, aerosols and sea-surface temperature biases are also key. Reducing regional precipitation projection uncertainty has enormous planning value for water supplies, land use, wildfire, hydropower, flood control, etc. IPCC-class ESMs are making painfully slow progress on this.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Regional climate change: consensus, discrepancies, and ways forward

Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Performance Evaluation of Weather@home2 Simulations over West African Region

Weather and climate forecasting, using climate models, have become essential tools and life-savers in the West African region; in spite of the fact that climate models do not fully comply with attributes of forecast qualities—RASAP: reliability, association, skill, accuracy, and precision. The objective of this paper is to quantitatively evaluate, in comparison to CRU and ERA5 datasets, the RASAP compliance-level of the weather@home2 modeling system (w@h2). Findings from some statistical evaluations show that, to a moderately significant extent, w@h2 model provides useful information during the monsoon seasons; skills to capture the Little Dry Season over the Guinea zone; predictive skills for the onset season; ability to reproduce all the annual characteristics of the surface maximum air temperature over the region; as well as skill to detect heat waves that usually ravage West Africa during the boreal spring. The model displays traces of attributes that are needed for seasonal climate predictions and applications. Deficiencies in the quantitative reproducibility point to the facts that the model does provide a reliability akin to that of regional climate models. This paper further furnishes a prospective user with information on whether the model might be “useful or not” for a particular application.

West Africa↗
DOE OSTI2025

Fire and Drought Affect Multiple Aspects of Diversity in a Migratory Bird Stopover Community

Drought and high-severity, stand-replacing wildfires can have substantial impacts on the composition of avian communities, including stop-over communities during migration. An inextricable link exists between drought and wildfire, each operating and impacting across different timescales. Many studies have found nonlinear avian abundance trends in breeding community time series data that include pre- and post-fire observations, describing an initial decrease in abundance followed by rapid increases that can attenuate over time. Here, we use a fall bird-banding dataset to evaluate shifts in a drought-impacted avian community following wildfire from taxonomic, functional, and phylogenetic perspectives. We looked at the community as a whole and also categorized birds as residents, migrants, and breeders to assess potential varying responses at the study site. We observed post-fire shifts in functional and phylogenetic diversity that corresponded to changes in vegetation. An influx of migratory insectivores post-fire drove much of the variation between pre- and post-fire avian communities and toward a more related, less phylogenetically dispersed community. A concurrent monsoon season drought was also associated with functional and phylogenetic diversity, highlighting the intertwined pulse press effects on avian communities. Overall, our results suggest that, although bird communities are immediately impacted by fire-driven resource changes, they can rebound over time, it is unclear how long-term drought may continue to shape the composition of these avian communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Farmers’ Perception of Climate Change and Its Impacts on Agriculture

Climate change and climate variability drive rapid glacier melt and snowpack loss, extreme precipitation and temperature events, and alteration of water availability in the Himalayas. There is increasing observational evidence of climate change impacts on water resource availability and agricultural productivity in the central Himalayan region. Here, we assess the farmers’ perception of climate change and its impacts on agriculture in western Nepal. We interviewed 554 households and conducted eight focus group discussions to collect farmers’ perceptions of temperature and rainfall characteristics, water availability, onset and duration of different seasons, and the impacts of such changes on their lives and livelihoods. Our results indicate that the farmers’ perceptions of rising annual and summer temperatures are consistent with observations. Perception, however, contradicts observed trends in winter temperature, as well as annual, monsoon, and winter precipitation. In addition, farmers are increasingly facing incidences of extreme events, including rainfall, floods, landslides, and droughts. These hazards often impact agricultural production, reducing household income and exacerbating the economic impacts on subsistence farmers. Integrated assessment of farmers’ perceptions and hydrometeorological observations is crucial to improving climate change impact assessment and informing the design of mitigation and adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Comparing Coarse-Resolution Land Surface Temperature Products over Western Australia

Satellite-derived land surface temperature (LST) has commonly been used to monitor global temperature changes. The MODIS MYD11A2 product is the most common coarse-resolution product used for this purpose. An updated MODIS product (MYD21A2) and new VIIRS (VNP21A2) product have also recently become available. This study analyses eight-day, quality-controlled, LST imagery over Western Australia (WA) for the three products for an urban and a non-urban area for the years 2013, 2016, and 2019. An analysis of the data indicates that (i) the averaged daytime LST difference between the three products for Perth city over the three years was 1.32 °C, while at night it was 0.89 °C; (ii) the averaged daytime difference over the Kimberley region was 7.02 °C with a night average difference of 2.39 °C; and (iii) both the MYD21A2 and VNP21A2 products still appear to record anomalous monthly LST values, particularly in the humid Kimberley monsoonal months. The overall objective of the National Aeronautics and Space Administration (NASA) is to ensure that the LST values of the two satellite system products are comparable, so evidence of LST value differences will require further investigation, especially if the older product is to be replaced by the newer systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Atmospheric teleconnection processes linking winter air stagnation and haze extremes in China with regional Arctic sea ice decline

Abstract. Recent studies suggested significant impacts of boreal cryosphere changes on wintertime air stagnation and haze pollution extremes in China. However, the underlying mechanisms of such a teleconnection relationship remains unclear. Here we use the Whole Atmosphere Community Climate Model (WACCM) to investigate dynamic processes leading to atmospheric circulation and air stagnation responses to Arctic sea ice changes. We conduct four climate sensitivity experiments by perturbing sea ice concentrations (SIC) and corresponding sea surface temperature (SST) in autumn and early winter over the whole Arctic and three subregions in the climate model. The results indicate distinct responses in circulation patterns and regional ventilation to the region-specific Arctic changes, with the largest increase of both the probability (by 132 %) and the intensity (by 30 %) of monthly air stagnation extremes being found in the experiment driven by SIC and SST changes over the Pacific sector of the Arctic (the East Siberian and Chukchi seas). The increased air stagnation extremes are mainly driven by an amplified planetary-scale atmospheric teleconnection pattern that resembles the negative phase of the Eurasian (EU) pattern. Dynamical diagnostics suggest that convergence of transient eddy forcing in the vicinity of Scandinavia in winter is largely responsible for the amplification of the teleconnection pattern. Transient eddy vorticity fluxes dominate the transient eddy forcing and produce a barotropic anticyclonic anomaly near Scandinavia and wave train propagation across Eurasia to the downstream regions in East Asia. The piecewise potential vorticity inversion analysis reveals that this long-range atmospheric teleconnection of Arctic origin takes place primarily via the middle and upper troposphere. The anomalous ridge over East Asia in the middle and upper troposphere worsens regional ventilation conditions by weakening monsoon northwesterlies and enhancing temperature inversions near the surface, leading to more and stronger air stagnation and pollution extremes over eastern China in winter. Ensemble projections based on state-of-the-art climate models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) corroborate this teleconnection relationship between high-latitude environmental changes and midlatitude weather extremes, though the tendency and magnitude vary considerably among each participating model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Exploring dimethyl sulfide (DMS) oxidation and implications for global aerosol radiative forcing

Abstract. Aerosol indirect radiative forcing (IRF), which characterizes how aerosols alter cloud formation and properties, is very sensitive to the preindustrial (PI) aerosol burden. Dimethyl sulfide (DMS), emitted from the ocean, is a dominant natural precursor of non-sea-salt sulfate in the PI and pristine present-day (PD) atmospheres. Here we revisit the atmospheric oxidation chemistry of DMS, particularly under pristine conditions, and its impact on aerosol IRF. Based on previous laboratory studies, we expand the simplified DMS oxidation scheme used in the Community Atmospheric Model version 6 with chemistry (CAM6-chem) to capture the OH-addition pathway and the H-abstraction pathway and the associated isomerization branch. These additional oxidation channels of DMS produce several stable intermediate compounds, e.g., methanesulfonic acid (MSA) and hydroperoxymethyl thioformate (HPMTF), delay the formation of sulfate, and, hence, alter the spatial distribution of sulfate aerosol and radiative impacts. The expanded scheme improves the agreement between modeled and observed concentrations of DMS, MSA, HPMTF, and sulfate over most marine regions, based on the NASA Atmospheric Tomography (ATom), the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), and the Variability of the American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) measurements. We find that the global HPMTF burden and the burden of sulfate produced from DMS oxidation are relatively insensitive to the assumed isomerization rate, but the burden of HPMTF is very sensitive to a potential additional cloud loss. We find that global sulfate burden under PI and PD emissions increase to 412 Gg S (+29 %) and 582 Gg S (+8.8 %), respectively, compared to the standard simplified DMS oxidation scheme. The resulting annual mean global PD direct radiative effect of DMS-derived sulfate alone is −0.11 W m−2. The enhanced PI sulfate produced via the gas-phase chemistry updates alone dampens the aerosol IRF as anticipated (−2.2 W m−2 in standard versus −1.7 W m−2, with updated gas-phase chemistry). However, high clouds in the tropics and low clouds in the Southern Ocean appear particularly sensitive to the additional aqueous-phase pathways, counteracting this change (−2.3 W m−2). This study confirms the sensitivity of aerosol IRF to the PI aerosol loading and the need to better understand the processes controlling aerosol formation in the PI atmosphere and the cloud response to these changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Warm-phase microphysical evolution in large-eddy simulations of tropical cumulus congestus: evaluating drop size distribution evolution using polarimetry retrievals, in situ measurements, and a thermal-based framework

Owing to uncertainties in convective microphysics processes, improving parameterizations in Earth system models (ESMs) can benefit from observationally constrained cases suitable for scaling between cloud-resolving models and ESMs. We propose a benchmark large-eddy simulation (LES) cumulus congestus case study from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP 2 Ex) for evaluating and improving ESMs in single-column model (SCM) mode. We seek observational constraints using novel polarimetric retrievals and in situ cloud microphysics measurements. Simulations using bulk and bin microphysics initialized with observed aerosol profiles are compared to cloud-top retrievals of cloud droplet effective radius (R eff ), effective variance (ν eff ), and number concentration (N d ) from the airborne Research Scanning Polarimeter (RSP). Both schemes reproduce characteristics of cloud-top N d and R eff that increase and decrease with altitude, respectively. Cloud-top N d is low-biased relative to RSP retrievals in both schemes, potentially due to limitations in both simulations and retrieval assumptions. Cloud-top R eff is low-biased in the bulk scheme but reasonably reproduced by the bin scheme. Profiles of N d and R eff are sensitive to the collision–coalescence process and the vertical variation in aerosol size distribution. Comparison of simulated and in situ droplet size distributions (DSDs) shows that, to first order, integrated moments are always sensitive to sizes < ~ 30 µm and can also be sensitive to larger sizes if the DSDs are sufficiently broad, with implications for the assumed maximum observed size retrieved by the RSP. The bin scheme captures the observed extended tail of the DSD, while the bulk scheme is unable to due to parametric constraints. Differences in expected relationships between in situ measurements of cloud cores and cloud-top retrievals by RSP demonstrate difficulty in constraining well the case presented herein. Finally, a thermal-tracking framework demonstrates that the dilution of N d throughout a thermal's lifetime is heavily determined by collision–coalescence and the height-varying aerosol distribution and that, in the absence of these, the impact of entrainment on diluting N d is largely offset by secondary activation. Implications for evaluating warm-phase convective microphysics schemes in ESMs and translating results for use on global, space-based polarimetry platforms are discussed.

Stanford, McKenna Wallace [Columbia Univ., New Yor↗
DOE OSTI2023

Assessing carbon storage capacity and saturation across six central US grasslands using data–model integration

Abstract. Future global changes will impact carbon (C) fluxes and pools in most terrestrial ecosystems and the feedback of terrestrial carbon cycling to atmospheric CO2. Determining the vulnerability of C in ecosystems to future environmental change is thus vital for targeted land management and policy. The C capacity of an ecosystem is a function of its C inputs (e.g., net primary productivity – NPP) and how long C remains in the system before being respired back to the atmosphere. The proportion of C capacity currently stored by an ecosystem (i.e., its C saturation) provides information about the potential for long-term C pools to be altered by environmental and land management regimes. We estimated C capacity, C saturation, NPP, and ecosystem C residence time in six US grasslands spanning temperature and precipitation gradients by integrating high temporal resolution C pool and flux data with a process-based C model. As expected, NPP across grasslands was strongly correlated with mean annual precipitation (MAP), yet C residence time was not related to MAP or mean annual temperature (MAT). We link soil temperature, soil moisture, and inherent C turnover rates (potentially due to microbial function and tissue quality) as determinants of carbon residence time. Overall, we found that intermediates between extremes in moisture and temperature had low C saturation, indicating that C in these grasslands may trend upwards and be buffered against global change impacts. Hot and dry grasslands had greatest C saturation due to both small C inputs through NPP and high C turnover rates during soil moisture conditions favorable for microbial activity. Additionally, leaching of soil C during monsoon events may lead to C loss. C saturation was also high in tallgrass prairie due to frequent fire that reduced inputs of aboveground plant material. Accordingly, we suggest that both hot, dry ecosystems and those frequently disturbed should be subject to careful land management and policy decisions to prevent losses of C stored in these systems.

58 GEOSCIENCES↗
DOE OSTI2021

Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya

The sensitive ecosystem of the central Himalayan (CH) region, which is experiencing enhanced stress from anthropogenic forcing, requires adequate atmospheric observations and an improved representation of the Himalaya in the models. However, the accuracy of atmospheric models remains limited in this region due to highly complex mountainous topography. This article delineates the effects of spatial resolution on the modeled meteorology and dynamics over the CH by utilizing the Weather Research and Forecasting (WRF) model extensively evaluated against the Ganges Valley Aerosol Experiment (GVAX) observations during the summer monsoon. The WRF simulation is performed over a domain (d01) encompassing northern India at 15 km x 15 km resolution and two nests (d02 at 5 km x 5 km and d03 at 1 km x 1 km) centered over the CH, with boundary conditions from the respective parent domains. WRF simulations reveal higher variability in meteorology, e.g., relative humidity (RH = 70.3%-96.1%) and wind speed (WS = 1.1-4.2m s(-1)), compared to the ERA-Interim reanalysis (RH D 80.0%-85.0%, WS D 1.2-2.3m s(-1)) over northern India owing to the higher resolution. WRF-simulated temporal evolution of meteorological variables is found to agree with balloon-borne measurements, with stronger correlations aloft (r = 0.44-0.92) than those in the lower troposphere (r = 0.18-0.48). The model overestimates temperature (warm bias by 2.8 degrees C) and underestimates RH (dry bias by 6.4 %) at the surface in d01. Model results show a significant improvement in d03 (P = 827.6 hPa, T = 19.8 degrees C, RH = 92.3 %), closer to the GVAX observations (P = 801.4 hPa, T = 19.5 degrees C, RH = 94.7 %). Interpolating the output from the coarser domains (d01, d02) to the altitude of the station reduces the biases in pressure and temperature; however, it suppresses the diurnal variations, highlighting the importance of well-resolved terrain (d03). Temporal variations in near-surface P, T, and RH are also reproduced by WRF in d03 to an extent (r>0:5). A sensitivity simulation incorporating the feedback from the nested domain demonstrates the improvement in simulated P, T, and RH over the CH. Our study shows that the WRF model setup at finer spatial resolution can significantly reduce the biases in simulated meteorology, and such an improved representation of the CH can be adopted through domain feedback into regional-scale simulations. Interestingly, WRF simulates a dominant easterly wind component at 1 km x 1 km resolution (d03), which is missing in the coarse simulations; however, the frequency of southeasterlies remains underestimated. The model simulation implementing a highresolution (3 s) topography input (SRTM) improved the prediction of wind directions; nevertheless, further improvements are required to better reproduce the observed local-scale dynamics over the CH.

Singh, Jaydeep↗
DOE OSTI2021

TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets

TempestExtremes (TE) is a multifaceted framework for feature detection, tracking, and scientific analysis of regional or global Earth system datasets on either rectilinear or unstructured/native grids. Version 2.1 of the TE framework now provides extensive support for examining both nodal (i.e., pointwise) and areal features, including tropical and extratropical cyclones, monsoonal lows and depressions, atmospheric rivers, atmospheric blocking, precipitation clusters, and heat waves. Available operations include nodal and areal thresholding, calculations of quantities related to nodal features such as accumulated cyclone energy and azimuthal wind profiles, filtering data based on the characteristics of nodal features, and stereographic compositing. This paper describes the core algorithms (kernels) that have been added to the TE framework since version 1.0, including algorithms for editing pointwise trajectory files, composition of fields around nodal features, generation of areal masks via thresholding and nodal features, and tracking of areal features in time. Several examples are provided of how these kernels can be combined to produce composite algorithms for evaluating and understanding common atmospheric features and their underlying processes. These examples include analyzing the fraction of precipitation from tropical cyclones, compositing meteorological fields around extratropical cyclones, calculating fractional contribution to poleward vapor transport from atmospheric rivers, and building a climatology of atmospheric blocks.

58 GEOSCIENCES↗
DOE OSTI2024

An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1

Abstract. The interaction between clouds and radiation is a key process within the climate system, and assessing the impacts of that interaction provides valuable insights into both the present-day climate and future projections. Many modeling experiments have been designed over the years to probe the impact of the cloud radiative effect (CRE) on the climate, including those that seek to disrupt the mean CRE effect and those that only disrupt the covariance of the CRE with the circulation. Seven such experimental designs have been added to the Energy Exascale Earth System Model version 1 (E3SMv1) of the US Department of Energy. These experiments include both the first and second iterations of the Clouds On/Off Klimate Intercomparison Experiment (COOKIE) experimental design, as well as the cloud-locking method. This paper documents the code changes necessary to implement such experiments and also provides detailed instructions for how to run them. Analyses across experiment types provide valuable insights and confirm the findings of prior studies, including the role of cloud radiative heating toward intensifying the monsoon, intensifying rain rates, and poleward expansion of the general circulation owing to cloud feedbacks.

Harrop, Bryce E. (ORCID:0000000339524525)↗
DOE OSTI2024

Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3

Systematic, routine, and comprehensive evaluation of Earth system models (ESMs) facilitates benchmarking improvement across model generations and identifying the strengths and weaknesses of different model configurations. By gauging the consistency between models and observations, this endeavor is becoming increasingly necessary to objectively synthesize the thousands of simulations contributed to the Coupled Model Intercomparison Project (CMIP) to date. The Program for Climate Model Diagnosis and Intercomparison (PCMDI) Metrics Package (PMP) is an open-source Python software package that provides quick-look objective comparisons of ESMs with one another and with observations. The comparisons include metrics of large- to global-scale climatologies, tropical inter-annual and intra-seasonal variability modes such as the El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO), extratropical modes of variability, regional monsoons, cloud radiative feedbacks, and high-frequency characteristics of simulated precipitation, including its extremes. The PMP comparison results are produced using all model simulations contributed to CMIP6 and earlier CMIP phases. An important objective of the PMP is to document the performance of ESMs participating in the recent phases of CMIP, together with providing version-controlled information for all datasets, software packages, and analysis codes being used in the evaluation process. Among other purposes, this also enables modeling groups to assess performance changes during the ESM development cycle in the context of the error distribution of the multi-model ensemble. Quantitative model evaluation provided by the PMP can assist modelers in their development priorities. In this paper, we provide an overview of the PMP, including its latest capabilities, and discuss its future direction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Effect of elevation, season and accelerated snowmelt on biogeochemical processes during isolated conifer needle litter decomposition

Increased drought and temperatures associated with climate change have implications for ecosystem stress with risk for enhanced carbon release in sensitive biomes. Litter decomposition is a key component of biogeochemical cycling in terrestrial ecosystems, but questions remain regarding the local response of decomposition processes to climate change. This is particularly complex in mountain ecosystems where the variable nature of the slope, aspect, soil type, and snowmelt dynamics play a role. Hence, the goal of this study was to determine the role of elevation, soil type, seasonal shifts in soil moisture, and snowmelt timing on litter decomposition processes. Experimental plots containing replicate deployments of harvested lodgepole and spruce needle litter alongside needle-free controls were established in open meadows at three elevations ranging from 2,800–3,500 m in Crested Butte, Colorado. Soil biogeochemistry variables including gas flux, porewater chemistry, and microbial ecology were monitored over three climatically variable years that shifted from high monsoon rains to drought. Results indicated that elevation and soil type influenced baseline soil biogeochemical indicators; however, needle mass loss and chemical composition were consistent across the 700 m elevation gradient. Rates of gas flux were analogously consistent across a 300 m elevation gradient. The additional variable of early snowmelt by 2–3 weeks had little impact on needle chemistry, microbial composition and gas flux; however, it did result in increased dissolved organic carbon in lodgepole porewater collections suggesting a potential for aqueous export. In contrast to elevation, needle presence and seasonal variability of soil moisture and temperature both played significant roles in soil carbon fluxes. Furthermore, during a pronounced period of lower moisture and higher temperatures, bacterial community diversity increased across elevation with new members supplanting more dominant taxa. Microbial ecological resilience was demonstrated with a return to pre-drought structure and abundance after snowmelt rewetting the following year. These results show similar decomposition processes across a 700 m elevation gradient and reveal the sensitivity but resilience of soil microbial ecology to low moisture conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Modeling of Precipitation over Africa: Progress, Challenges, and Prospects

In recent years, there has been an increasing need for climate information across diverse sectors of society. This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change. Likewise, this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa. By leveraging a large volume of climate model outputs, numerous studies have investigated the model representation of African precipitation as well as underlying physical processes. These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies. This paper provides a review of the progress in precipitation simulation over Africa in state-of-the-science climate models and discusses the major issues and challenges that remain.

CMIP6↗
DOE OSTI2024

A late glacial paleoenvironmental and climate record from the Sierra de Juarez, Baja California

Ciénegas are desert wetlands that are strongly correlated with the stability of the hydrologic cycle in arid landscapes. However, these environments are particularly vulnerable to climate change, drought, water diversion, and fire suppression which all have contributed to the degradation of ciénegas along the U.S.-Mexican borderlands. Therefore, identifying the timing of precipitation patterns in this region is of particular interest because of its relationship to many ecological responses of the landscape such as groundwater recharge and fire. Here, we present the first-ever fire paleoenvironmental record from Ciénega Chimeneas, a ciénega complex in the Sierra de Juárez of Baja California. We explore how changes in the amount and seasonality of moisture affected ciénega complexes and fire activity from across the southwestern North American region over the past 45,000 years. Further, our record suggests that during the late glacial period, 41,000–21,000 cal yr BP, the increase of Larrea and Quercus indicate an increase in summer precipitation. Subsequently, when summer precipitation increased, pollen preservation and pollen accumulation rates (PAR) also increased. Increased vegetation allowed for increased fire activity during the late glacial period. Regionally, most of the comparison sites also indicated wet conditions during the full glacial period. However, around 21,000 cal yr BP, effective moisture decreased resulting in a dramatic change in the vegetation assemblage. Specifically, the summer wet taxa disappeared, while pollen preservation and PAR decreased, suggesting a dry period until ~14,000 cal yr BP. Little fire activity is recorded after 21,000 cal yr BP, likely due to the absence of fuels. At ~14,000 cal yr BP, Larrea and Quercus reappear suggesting increased summer precipitation. However, the appearance of Cyperaceae and increases in grasses suggest increased winter precipitation. We suggest that the combination of summer wet and winterwet taxa ~14,000 cal yr BP represents an increase in ENSO conditions, while the summer moisture controls remained relatively constant.

54 ENVIRONMENTAL SCIENCES↗