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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

The Relationships Between the Trends of Mean and Extreme Precipitation

This study provides a better understanding of the relationships between the trends of mean and extreme precipitation in two observed precipitation data sets: the Climate Prediction Center Unified daily precipitation data set and the Global Precipitation Climatology Program (GPCP) pentad data set. The study employs three kinds of definitions of extreme precipitation: (1) percentile, (2) standard deviation and (3) generalize extreme value (GEV) distribution analysis for extreme events based on local statistics. Relationship between trends in the mean and extreme precipitation is identified with a novel metric, i.e. area aggregated matching ratio (AAMR) computed on regional and global scales. Generally, more (less) extreme events are likely to occur in regions with a positive (negative) mean trend. The match between the mean and extreme trends deteriorates for increasingly heavy precipitation events. The AAMR is higher in regions with negative mean trends than in regions with positive mean trends, suggesting a higher likelihood of severe dry events, compared with heavy rain events in a warming climate. AAMR is found to be higher in tropics and oceans than in the extratropics and land regions, reflecting a higher degree of randomness and more important dynamical rather than thermodynamical contributions of extreme events in the latter regions.

global warming↗
NASA NTRS2013

Data Assimilation of AIRS Water Vapor Profiles: Impact on Precipitation Forecasts for Atmospheric River Cases Affecting the Western of the United States

Atmospheric rivers are transient, narrow regions in the atmosphere responsible for the transport of large amounts of water vapor. These phenomena can have a large impact on precipitation. In particular, they can be responsible for intense rain events on the western coast of North America during the winter season. This paper focuses on attempts to improve forecasts of heavy precipitation events in the Western US due to atmospheric rivers. Profiles of water vapor derived from from Atmospheric Infrared Sounder (AIRS) observations are combined with GFS forecasts by a three-dimensional variational data assimilation in the Gridpoint Statistical Interpolation (GSI). Weather Research and Forecasting (WRF) forecasts initialized from the combined field are compared to forecasts initialized from the GFS forecast only for 3 test cases in the winter of 2011. Results will be presented showing the impact of the AIRS profile data on water vapor and temperature fields, and on the resultant precipitation forecasts.

Blankenship, Clay↗
DOE OSTI2021

Enhancing Resilience of Urban Systems Against Climate-Induced Floods Using Advanced Data-Driven and Computing Techniques: A Driver-Pressure-State-Impact-Response (DPSIR) Framework

Focal Area: This white paper proposes advanced data-driven and computing techniques to improve the predictability of extreme climate events (precipitation) and focuses on comprehending their impact dynamics to enhance resilience of urban systems. Science Challenge: In urban systems, climate change has presented significant challenges related to accurate spatiotemporal prediction of extreme climate events (heavy precipitation) and their impacts, i.e. flooding. The occurrence of extreme climate events and their compounding repercussions on the built environment make urban systems increasingly more vulnerable. The interactions between extreme climate events, urban systems, and the corresponding impacts are irregular, non-linear, and dynamic, making it difficult to standardize resilience. As it stands, the management of complex urban systems is affected by uncertainties related to the nature of short- and long-term consequences caused by extreme events.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

Tao, Wei-Kuo↗
DOE OSTI2023

Moisture Sources of Precipitation in the Great Lakes Region: Climatology and Recent Changes

Abstract Given the critical role of precipitation on hydroclimate, we quantified the contributions of moisture source regions to precipitation in the Great Lakes Region (GLR) using multiple reanalysis data sets. Results show that the Great Plains (GPs) and the GLR itself are the primary sources of moisture. The moisture sources for the double peaks in the GLR precipitation that occur in June and September are identified, which is caused by a shift in the peak timing of moisture contribution from the GLR and GPs. In particular, moisture from the GPs contributes more to the heavy precipitation, while moisture from the GLR contributes more to the light precipitation. We also found a statistically significant ( p < 0.05) increasing trend in the moisture contribution from the mid‐Pacific, caused by an intensified zonal moisture transport from the mid‐Pacific through changes in atmospheric circulation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Operational Performance of Sensor Systems Used to Determine Atmospheric Boundary Layer Properties as Part of the NASA Aircraft Vortex Spacing System Project

There has been a renewed interest in the application of remote sensor technology to operational aviation and airport-related activities such as Aircraft Vortex Spacing System (AVOSS). Radio Acoustic Sounding Systems (RASS), Doppler-acoustic sodars, Ultrahigh Frequencies (UHF) profilers and lidars have many advantages in measuring wind and temperature profiles in the lower atmospheric boundary layer since they can operate more or less continuously and unattended; however, there are limitations in their operational use at airports. For example, profilers deteriorate (limited altitude coverage or missing) in moderate or greater rain and can be affected by airplane targets in their field of view. Sodars can handle precipitation better but are affected by the high noise environments of airports and strong winds. Morning temperature inversions typically limit performance of RASS, sodars and profilers. Fog affects sonic anemometers. Lidars can have difficulties in clouds, fog or heavy precipitation. Despite their limitations these sensors have proven useful to provide wind and temperature profiles for AVOSS. Capabilities and limitations of these and other sensors used in the AVOSS program are discussed, parameter settings for the sensor systems are documented, and recommendations are made for the most cost-effective group of sensors for the future. The potential use of specially tuned dynamic forecast models and measurements from landing and departing aircraft are addressed.

Zak, J. Allen↗
NASA NTRS1999

Multi-Scale Interactions Associated with the Monsoon Onset Over South China Sea and Adjacent Regions during SCSMEX-98

Using data collected during The South China Sea Monsoon Experiment (SCSMEX) (1998) as well as from the TRMM Microwave-Imager (TMI) and precipitation radar (PR), we have studied the multi-scale interactions (meso-synoptic-intraseasonal) associated with monsoon onset over South China Sea (SCS) and its subsequent evolution. Results show that the monsoon onset (defined by development of steady wind direction and heavy precipitation) over the northern SCS occurred around May 15 -17. Prevailing southerlies and southwesterlies developed over the central SCS after May 20. Shortly after, monsoon convection developed over the whole SCS region around May 23-27. The entire onset process appeared to be delayed by about a week to 10 days compared with climatology. During late spring of 1998, mid-latitude frontal systems were particularly active. These systems strongly impacted the northern SCS convection and may have been instrumental in triggering the onset of the SCS monsoon. The Tropical Oceans and Global Atmosphere (TOGA) and Bureau of Meteorology Research Centre (BMRC) radar showed a wide variety of convective systems over the Intensive Flux Array, from frontal bands to shear-banded structure, deep convection, pop-corn type shallow convection, slow moving "fine lines" to water spout. Analysis of SSM/I wind and moisture data suggested that the delayed convective activity over the SCS may be linked to the weakened northward propagation of monsoon rain band, hence contributing to a persistence of the rainband south of the Yangtze River and the disastrous flood that occurred over this region during mid to late June, 1998.

Lau, William K. M.↗
NASA NTRS2022

Precipitation over the U.S. Coastal Land/Water Using Gauge-Corrected Multi-Radar/Multi-Sensor System and Three Satellite Products

The weather and climate over the coastal regions have received increasing attention because of substantial population growth, the rising sea level, and extreme weather. Satellite remote sensing provides global precipitation estimates (including coastal land/ocean). While these datasets have been extensively evaluated over land, they have rarely been assessed over coastal ocean. As precipitation radars cover both coastal land and ocean, we used the Multi-Radar/Multi-Sensor System (MRMS) gauge-corrected precipitation product from 2018 to 2020 to evaluate three widely used satellite-based precipitation products over the U.S. coastal land versus the ocean (and the water over the Great Lakes). These products included the Integrated Multi-satellite Retrievals for GPM (IMERG), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Climate Prediction Center Morphing technique (CMORPH). The MRMS data showed a precipitation climatology difference between the coastal land and the ocean that was higher in the winter and lower in the summer and autumn. IMERG and CMORPH performed best over land and water, respectively, while PERSIANN was the most consistent in its performance over land versus water. Heavy precipitation was overestimated by the three products, with larger overestimates over water than over land. These results were not affected by the MRMS uncertainties due to the gauge correction or by the use of different versions.

coastal precipitation↗
NASA NTRS2003

Regional-Scale Modeling at NASA Goddard Space Flight Center

Over the past decade, the Goddard Mesoscale Modeling and Dynamics Group has used a popular regional scale model, MM5, to study precipitation processes. Our group is making contributions to the MM5 by incorporating the following physical and numerical packages: improved Goddard cloud processes, a land processes model (Parameterization for Land-Atmosphere-Cloud Exchange - PLACE), efficient but sophisticated radiative processes, conservation of hydrometeor mass (water budget), four-dimensional data assimilation for rainfall, and better computational methods for trace gas transport. At NASA Goddard, the MM5 has been used to study: (1) the impact of initial conditions, assimilation of satellite-derived rainfall, and cumulus parameterizations on rapidly intensifying oceanic cyclones, hurricanes and typhoons, (2) the dynamic and thermodynamic processes associated with the development of narrow cold frontal rainbands, (3) regional climate and water cycles, (4) the impact of vertical transport by clouds and lightning on trace gas distributiodproduction associated with South and North American mesoscale convective systems, (5) the development of a westerly wind burst (WWB) that occurred during the TOGA COARE and the diurnal variation of precipitation in the tropics, (6) a Florida sea breeze convective event and a Mid-US flood event using a sophisticated land surface model, (7) the influence of soil heterogeneity on land surface energy balance in the southwest GCIP region, (8) explicit simulations (with 1.33 to 4 km horizontal resolution) of hurricanes Bob (1991) and Bonnie (1998), (9) a heavy precipitation event over Taiwan, and (10) to make real time forecasts for a major NASA field program. In this paper, the modifications and simulated cases will be described and discussed.

Tao, W.-K.↗
DOE OSTI2025

Data for Myers-Pigg et al. (2026), "Short-term coastal forest responses to a hurricane-scale freshwater and saltwater flooding experiment"

Coastal upland forests are exposed to intensifying precipitation regimes and sea level rise, increasing tree mortality and transforming these coastal forests into wetland ecosystems. Despite these well-known risks, the differing degrees to which hydrological, biogeochemical, and biological components of upland forests respond to novel salinity exposure is relatively unknown. The Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment decouples two distinct disturbances associated with hydrological extremes: (1) flooding from heavy precipitation and (2) exposure to saline conditions from storm surge. This dataset includes data reported in Myers-Pigg et al. (2025), which analyzed data from the first TEMPEST flooding treatment in 2022. This includes: - Colored dissolved organic matter in porewaters - Soil temperature and oxygen - Groundwater temperature and chemistry - Dissolved organic carbon concentrations in porewaters - Soil-to-atmosphere CH4 and CO2 fluxes - Soil temperature, water content, and electrical conductivity - Root-influenced CH4 and CO2 flux - Tree sap flow velocity - The R analytical code and documentation about the computational environmental in which it was run (the "sessionInfo.txt" file) All data files are plain-text comma separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Daily Precipitation Frequency Distributions Impacts on Land-Surface Simulations of CONUS

Many precipitation-driven data products from land data assimilation systems support assessments of droughts, floods, and other societally-relevant land-surface processes.The accumulated precipitation used as input to these products has a significant impacton water budgets; however, the effects of daily distribution of precipitation on theseproducts are not well known. A comparison of the Integrated Multi-satellite Retrievalsfor GPM (IMERG) and Climate Hazards Group InfraRed Precipitation with Stationsversion 2 (CHIRPS2) rainfall products over the continentalUnited States (CONUS) wasperformed to quantify the impacts of the daily distributionof precipitation on biases anderrors in soil moisture, runoff, and evapotranspiration (ET). Since the total accumulatedprecipitation between the IMERG and CHIRPS product differed, a third precipitationproduct, CHIRPS-to-IMERG (CHtoIM), was produced that usedCHIRPS2 accumulatedprecipitation totals and the daily precipitation frequency distribution of IMERG. Thisnew product supported a controlled analysis of the impact ofprecipitation frequencydistribution on simulated hydrological fields. The CHtoIM had higher occurrences ofprecipitation in the 0–5 mm day−1range, with a lower occurrence of dry days, whichdecreased soil moisture and surface runoff in the land-surface model. The surface soillayer had a tendency to reach saturation more often in the CHIRPS2 simulations, wherethe number of moderate to heavy precipitation days (>5mm day−1) was increased. Usingthe blended CHtoIM product as input reduced errors in surface soil moisture by 5–15%when compared to Soil Moisture Active/Passive (SMAP) data.Similarly, ET errors werealso slightly decreased (∼2%) when compared to SSEBop data. Moderate changes indaily precipitation distributions had a quantifiable impact on soil moisture, runoff, andET. These changes usually improved the model when compared to other modeled andobservational datasets, but the magnitude of the improvements varied by region andtime of year.

Daniel P Sarmiento↗
DOE OSTI2024

DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models With 3D Diffusion Models

Earth system models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low-cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low-cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio-temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

A Strong Atmospheric River Responsible for the 2019 Record Floods in the Middle East

Atmospheric rivers (ARs) cause some of the weather-related disasters around the world. While many studies have shown the contribution of ARs to precipitation in the coastal regions such as western Europe and the U.S. West Coast, little is known about their mechanisms and impacts on flooding in the Middle East. This study shows that an AR was responsible for the record floods during March 2019 across the Middle East. Iran in particular was hit hardest with the floods that left a death toll of at least 76 and an early estimate of $2.5 billion (U.S. dollars) damage to its infrastructures. The heavy precipitation produced by this AR made the 2018/19 rainy season the wettest in the past four decades. By contrast, the prior year (2017/18) was the driest over the same period. This is a compelling example of rapid dry-to-wet transitions that may enhance the chance of landslides and impose challenges to water resources management. The AR originated in the Atlantic Ocean and propagated across North Africa and the Arabian Peninsula before its final landfall over the Zagros Mountains. On its nearly 9000 km journey, the AR received additional moisture from the Mediterranean, Red, and Arabian Seas, and the Persian Gulf. Moisture transport by this AR during 24-25 March 2019 is estimated at more than 150times the aggregated discharge of the four major rivers in the region, that is, the Tigris, Euphrates, Karun, and Karkheh. Anomalously warm sea surface temperatures in all surrounding basins and coincidence of a midlatitude system and a subtropical jet provided the necessary ingredients for formation of this strong AR. This work underlines the fact that the impacts of rain-producing ARs are not limited to the coastal regions. Such ARs can travel very long distances away from the oceans and affect remote arid and semi-arid regions like the Middle East. This study examined an individual AR, though one associated with record floods. However, it attempts to draw attention to the need for more AR-related research over the Middle East.

Atmospheric Rivers↗
DOE OSTI2023

Environmental Controls on MCS Lifetime Rainfall Over Tropical Oceans

Abstract Mesoscale convective systems (MCSs) contribute a majority of rainfall over tropical oceans. However, our understanding of the environmental controls on tropical oceanic MCS precipitation remains incomplete. Using 20‐year of satellite observations, reanalysis data, and MCS tracking, we found that MCSs initiating in a mesoscale environment with enhanced lower‐free‐tropospheric moisture, warmer middle troposphere, stronger low‐level ascent, and stronger deep‐layer (surface‐400 hPa) wind shear tend to produce more precipitation during their lifetimes. While most of these environmental factors are correlated with one another, the deep‐layer shear is not. A rapid pickup in MCS lifetime rainfall is found when the lower‐free‐tropospheric specific humidity exceeds 10 g kg −1 . This nonlinearity is mostly dominated by the nonlinear increase in MCS area. On the other hand, both MCS area and rain rate increase quasi‐linearly with the deep‐layer shear. The increase in rain rate is related to the enhancement of heavy precipitating convective activity with deep‐layer shear.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling

Abstract During the last four decades, global warming has statistically significant intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio, and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150‐year dynamical downscaling data set at convection‐permitting resolution, this study introduces a framework to construct the projected future intensity‐duration‐frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub‐daily and multi‐day duration utilizing hourly in situ observations as well as quantile‐based statistical techniques in bias‐correction and return levels selection. The assumption of non‐stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980–2022, future projected IDF curves for 2058–2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 15% and 25%, respectively, across 74 stations, considering both annual and seasonal timescales. Future projections suggest that extreme precipitation events may become more severe across six investigated return periods, with longer return periods showing a greater increase. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high‐resolution input data set. Plain Language Summary This study investigates the evolving nature of extreme precipitation events in the Midwestern United States under a changing climate. By leveraging a high‐resolution dynamical downscaling data set, we construct projected intensity‐duration‐frequency (IDF) curves for future extreme rainfall events. These curves serve as vital tools for infrastructure planning and water resource management. Our analysis reveals a significant increase in both the intensity and frequency of extreme precipitation events in the region. Future projected IDF curves for the late century indicate an average intensity increase of approximately 15%–25% compared to historical values. Moreover, the frequency of such events is expected to double. Spatial heterogeneity in future trends is observed across different stations within the Midwest, highlighting the importance of high‐resolution modeling in capturing localized climate variability. These findings underscore the urgent need for climate adaptation strategies to mitigate the increasing risks associated with extreme precipitation events in the region. Key Points This study introduces a workflow to construct future intensity‐duration‐frequency (IDF) curves over the Midwest United States using a new convection‐permitting modeling data set The current IDF construction workflow reproduces well the historical observed IDF 30 curves in summer months with median relative errors of 2.4% among 74 stations and 6 investigated durations The projected IDF curves show diverse future trends of extreme precipitation across stations, with intensity increases of approximately 15% and 25% under RCP4.5 and RCP8.5 climate scenarios, respectively, and a doubling of frequency on average

Nguyen, Trung↗
NASA NTRS2013

Impact of AIRS Thermodynamic Profiles on Precipitation Forecasts for Atmospheric River Cases Affecting the Western United States

This project is a collaborative activity between the NASA Short-term Prediction Research and Transition (SPoRT) Center and the NOAA Hydrometeorology Testbed (HMT) to evaluate a SPoRT Advanced Infrared Sounding Radiometer (AIRS: Aumann et al. 2003) enhanced moisture analysis product. We test the impact of assimilating AIRS temperature and humidity profiles above clouds and in partly cloudy regions, using the three-dimensional variational Gridpoint Statistical Interpolation (GSI) data assimilation (DA) system (Developmental Testbed Center 2012) to produce a new analysis. Forecasts of the Weather Research and Forecasting (WRF) model initialized from the new analysis are compared to control forecasts without the additional AIRS data. We focus on some cases where atmospheric rivers caused heavy precipitation on the US West Coast. We verify the forecasts by comparison with dropsondes and the Cooperative Institute for Research in the Atmosphere (CIRA) Blended Total Precipitable Water product.

Zavodsky, Bradley T.↗
DOE OSTI2024

Coastal-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) Science Plan

Understanding the mechanisms governing the urban atmospheric environment is critical for informing urban populations regarding the impacts of climate change and associated mitigation and adaptation measures. Earth system (climate and weather) models have not yet been adapted to provide accurate predictions of climate and weather variability within cities, nor do they provide well-tested representations of the impacts of urban systems on the atmospheric environment. These limitations are largely due to limited field data available for testing and development of these models. We will deploy the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s first Mobile Facility (AMF1) to the mid-Atlantic region surrounding the city of Baltimore for the Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE). This deployment will create a four-node regional atmospheric observatory network including Baltimore and its three primary surrounding environments – rural, urban, and bay. CoURAGE investigators will study the interactions among the Earth’s surface, the atmospheric boundary layer, aerosols and atmospheric composition, clouds, radiation, and precipitation at each site, and examine how the spatial gradients across the region interact to create the climate conditions in Baltimore. This study will determine the degree to which Baltimore’s atmospheric environment depends on interactive feedbacks in the atmospheric system and the degree to which conditions in Baltimore depend on the surrounding environment. Some topics of interest include how urban land management exacerbates heat waves, the impact of regional mesoscale winds (nocturnal jet, bay breeze) on urban air pollution and cloud cover, and the impact of the urban heat island and aerosol production on heavy precipitation events. Understanding this integrated coast-urban-rural system quantitatively and with good accuracy and precision is critical to informing climate adaptation and mitigation efforts in the city of Baltimore. The understanding gained should be applicable to many similar coastal, mid-latitude urban centers. Another important objective of CoURAGE is to improve the representation of the climate of coastal cities in Earth systems models (ESMs). CoURAGE investigators will use the observations to test current ESMs, identify weaknesses and work towards improved simulations of this complex environment. The ARM core facility will be deployed in the city of Baltimore, complementing the Baltimore Social-Environmental Collaborative (BSEC), a DOE urban integrated field laboratory (UIFL). Ancillary sites will be deployed to rural Maryland northwest of Baltimore, and to the southern end of Kent Island within Chesapeake Bay. The fourth node will be a long-term atmospheric observatory operated in Beltsville, Maryland by Howard University and the Maryland Department of the Environment. Measurements will be conducted for one year, starting in December of 2024. There will be two intensive operational periods (IOPs), one in summer and one in winter, when the ancillary sites will be enhanced with additional balloon launches, tethered balloon system (TBS) operation, and added atmospheric composition measurements.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Numerical Simulations of TRMM LBA, TOGA, COARE, GATE, ARM and PRESTORM Convective Systems: Sensitivity tests on Microphysical Processes

The 3D Goddard Cumulus Ensemble (GCE) model was utilized to examine the behavior and response of simulated deep tropical cloud systems that occurred over the west Pacific warm pool region, the Atlantic ocean and the central United States. The periods chosen for simulation were convectively active periods during TOGA-COARE (February 22 1993, December 11-17, 1992; December 19-28, February 9-13, 1993), GATE (September 4, 1974), LBA (January 26 and February 23, 1998), ARM (1997 IOP) and PRESTORM (June 11, 1985). We will examine differences in the microphysics for both warm rain and ice processes (evaporation /sublimation and condensation/ deposition), Q1 (Temperature), Q2 (Water vapor) and Q3 (momentum both U and V) budgets for these three convective events from different large-scale environments. The contribution of stratiform precipitation and its relationship to the vertical shear of the large-scale horizontal wind will also be examined. New improvements to the GCE model (i.e., microphysics: 4ICE two moments and 3ICE one moment; advection schemes) as well as their sensitivity to the model results will be discussed. Preliminary results indicated that various microphysical schemes could have a major impact on stratiform formation as well as the size of convective systems. However, they do not change the major characteristics of the convective systems, such as: arc shape, strong rotational circulation on both ends of system, heavy precipitation along the leading edge of systems.

Tao, W.-K.↗