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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Upper Blue Nile Basin Water Budget from a Multi-Model Perspective

Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.

Rainfall↗
NASA NTRS2010

NASA-Modified Precipitation Products to Improve EPA Nonpoint Source Water Quality Modeling for the Chesapeake Bay

The Environmental Protection Agency (EPA) has estimated that over 20,000 water bodies within the United States do not meet water quality standards. Ninety percent of the impairments are typically caused by nonpoint sources. One of the regulations in the Clean Water Act of 1972 requires States to monitor the Total Maximum Daily Load (TMDL), or the amount of pollution that can be carried by a water body before it is determined to be "polluted", for any watershed in the U.S.. In response to this mandate, the EPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a Decision Support Tool (DST) for assessing pollution and to guide the decision making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program -- Fortran (HSPF), computes daily stream flow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA modified/NOAA precipitation data. Using these data within HSPF, stream flow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better stream flow statistics and, ultimately, in improved water quality assessment.

Nigro, Joseph↗
NASA NTRS1982

Crop weather models of corn and soybeans for Agrophysical Units (APU's) in Iowa using monthly meteorological predictors

Models based on multiple regression were developed to estimate corn and soybean yield from weather data for agrophysical units (APU) in Iowa. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for crop reporting districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU's were selected to be more homogeneous with respect crop to production than the CRDs. The APU models are quite similar to the CRD models, similar explained variation and number of predictor variables. The APU models are to be independently evaluated and compared to the previously evaluated CRD models. That comparison should indicate the preferred model area for this application, i.e., APU or CRD.

Leduc, S.↗
NASA NTRS2012

Use NU-WRF and GCE Model to Simulate the Precipitation Processes During MC3E Campaign

One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF

Tao, Wei-Kuo↗
NASA NTRS2002

Urban Surface Radiative Energy Budgets Determined Using Aircraft Scanner Data

It is estimated that by the year 2025, 80% of the world's population will live in cities. The extent of these urban areas across the world can be seen in an image of city lights from the Defense Meteorological Satellite Program. In many areas of North America and Europe, it is difficult to separate individual cities because of the dramatic growth and sprawl of urbanized areas. This conversion of the natural landscape vegetation into man-made urban structures such as roads and buildings drastically alter the regional surface energy budgets, hydrology, precipitation patterns, and meteorology. One of the earliest recognized and measured phenomena of urbanization is the urban heat island (UHI) which was reported as early as 1833 for London and 1862 for Paris. The urban heat island results from the energy that is absorbed by man-made materials during the day and is released at night resulting in the heating of the air within the urban area. The magnitude of the air temperature difference between the urban and surrounding countryside is highly dependent on the structure of the urban area, amount of solar immolation received during the day, and atmospheric conditions during the night. These night time air temperature differences can be in the range of 2 to 5 C. or greater. Although day time air temperature differences between urban areas and the countryside exists during the day, atmospheric mixing and stability reduce the magnitude. This phenomena is not limited to large urban areas, but also occurs in smaller metropolitan areas. The UHI has significant impacts on the urban air quality, meteorology, energy use, and human health. The UPI can be mitigated through increasing the amount of vegetation and modification of urban surfaces using high albedo materials for roofs and paved surfaces. To understand why the urban heat island phenomenon exists it is useful to define the surface in terms of the surface energy budget. Surface temperature and albedo is a major component of the surface energy budget. Knowledge of it is important in any attempt to describe the radiative and mass fluxes which occur at the surface. Use of energy terms in modeling surface energy budgets allows the direct comparison of various land surfaces encountered in a urban landscape, from vegetated (forest and herbaceous) to non-vegetated (bare soil, roads, and buildings). These terms are also easily measured using remote sensing from aircraft or satellite platforms allowing one to examine the spacial variability. The partitioning of energy budget terms depends on the surface type. In natural landscapes, the partitioning is dependent on canopy biomass, leaf area index, aerodynamic roughness, and moisture status, all of which are influenced by the development stage of the ecosystem. In urban landscapes, coverage by man-made materials substantially alters the surface face energy budget. The remotely sensed data obtained from aircraft and satellites, when properly calibrated allows the measurement of important terms in the radiative surface energy budget a urban landscape scale.

Luvall, Jeffrey C.↗
DOE OSTI2025

CROCUS Forward Scatter Disdrometer Data at Argonne National Laboratory Prairie Site

The Vaisala FD70 is a multi-parameter present weather and visibility sensor designed to measure precipitation type, intensity, and visibility with high accuracy in diverse environmental conditions. It uses a combination of forward-scatter measurement and optical disdrometer technologies to detect drop size, fall speeds, and optical properties, enabling the classification of various precipitation types such as rain, snow, sleet, and freezing rain along is visibility estimates. The FD70 provides quantitative estimates of liquid-equivalent precipitation rate and meteorological optical range (MOR), supporting applications in meteorological research, aviation, and road weather monitoring. These measurements are collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20 acre prairie site at Argonne National Lab, located in Lemont, IL. Data is available in netcdf format. Each file contains one second interval data, for approximately 24 hrs each day. File naming convention includes the project (CROCUS), location (ATMOS), instrument name, data level (raw, a1), and date (year, month, day).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Crop weather models of barley and spring wheat yield for agrophysical units in North Dakota

Models based on multiple regression were developed to estimate barley yield and spring wheat yield from weather data for Agrophysical units(APU) in North Dakota. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for Crop Reporting Districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU models show sight improvements in some of the statistics of the models, e.g., explained variation. These models are to be independently evaluated and compared to the previously evaluated CRD models. The comparison will indicate the preferred model area for this application, i.e., APU or CRD.

Leduc, S.↗
NASA NTRS1993

Remote sensing for oceanography, hydrology and agriculture; Proceedings of Symposia A5, A3 and A9 of the COSPAR 29th Plenary Meeting, Washington, Aug. 28-Sept. 5, 1992

New results from satellite studies of the ocean and radar mapping of the earth are presented. Atttention is given to data from the ERS-1 satellite. Synthetic aperture radar mapping of land surface features and sea ice, radar backscatter measurements, and orbit altitude measurements are discussed. The use of remote sensing in hydrology, soil moisture determination, precipitation measurement, agricultural meteorology, and crop growth estimation is reviewed.

Gower, J. F. R.↗
NASA NTRS1994

Possible Halo Depictions in the Prehistoric Rock Art of Utah

In western American rock art the concentric circle symbol, which is widely regarded as a sun symbol, is ubiquitous. We provide evidence from Archaic and Fremont Indian rock art sites in northwestern Utah that at least one depiction was motivated by an observation of a complex halo display. Cirrus cloud optical displays are linked in both folklore and meteorology to precipitation-producing weather situations, which, in combination with an abundance of weather-related rock art symbolism, indicate that such images reflected the ceremonial concerns of the indigenous cultures for ensuring adequate precipitation. As has been shown to be the case with rock art rainbows, conventionalization of the halo image may have resulted in simple patterns that lacked recognizable details of atmospheric optical phenomena. However, in one case in which an Archaic-style petroglyph (probably 1500 yr or more old) satisfactorily reproduced a complicated halo display that contained parhelia and tangent arcs, sufficient geometric information is rendered to indicate a solar elevation angle of approx. 40 deg. at the time of observation.

Sassen, Kenneth↗
NASA NTRS2008

The NASA Energy and Water Cycle Extreme (NEWSE) Integration Project

Skillful predictions of water and energy cycle extremes (flood and drought) are elusive. To better understand the mechanisms responsible for water and energy extremes, and to make decisive progress in predicting these extremes, the collaborative NASA Energy and Water cycle Extremes (NEWSE) Integration Project, is studying these extremes in the U.S. Southern Great Plains (SGP) during 2006-2007, including their relationships with continental and global scale processes, and assessment of their predictability on multiple space and time scales. It is our hypothesis that an integrative analysis of observed extremes which reflects the current understanding of the role of SST and soil moisture variability influences on atmospheric heating and forcing of planetary waves, incorporating recently available global and regional hydro- meteorological datasets (i.e., precipitation, water vapor, clouds, etc.) in conjunction with advances in data assimilation, can lead to new insights into the factors that lead to persistent drought and flooding. We will show initial results of this project, whose goals are to provide an improved definition, attribution and prediction on sub-seasonal to interannual time scales, improved understanding of the mechanisms of decadal drought and its predictability, including the impacts of SST variability and deep soil moisture variability, and improved monitoring/attributions, with transition to applications; a bridging of the gap between hydrological forecasts and stakeholders (utilization of probabilistic forecasts, education, forecast interpretation for different sectors, assessment of uncertainties for different sectors, etc.).

House, P. R.↗
NASA NTRS2011

Urban Heat Islands

It is estimated that by the year 2025, 80% of the world's population will live in cities. This conversion of the natural landscape vegetation into man-made urban structures such as roads and buildings drastically alter the regional surface energy budgets, hydrology, precipitation patterns, and meteorology. Research studies from many cities have documented these effects range from decreases in air quality, increased energy consumption and alteration of regional climate to direct effects on human health.

Luvall, Jeffrey C.↗
NASA NTRS2024

Effective Visualization of Radar Data for Users Impacted By Color Vision Deficiency

Color Vision Deficiency (CVD) is a decreased ability to discern between particular colors. Eight percent of genetic males and half a percent of genetic females have some form of CVD, with many in the radar community falling into this group. When presenting data on a two-dimensional plane, it is common to use colors to represent values via a colormap. Colormap choice in the radar community is influenced by the ability to highlight scientifically interesting features in data, institutional choices, and domain dominance of legacy colormaps. The problem with these current colormaps is that many do not project well for those with CVD (i.e., green next to red). In working with the CVD community to address this problem, multiple colormaps for moments such as equivalent reflectivity factor and Doppler velocity were created for users with forms of CVD such as deuteranomaly, protanomaly, protanopia, and deuteranopia using Python tools such as colorspacious and viscm. We show how these colormaps can improve interpretability for four cases: a mesoscale convective system, a pyrocumulonimbus storm, a wintertime mid-latitude cyclone, and widespread storms with a large bird migration. These new radar equivalent reflectivity factor, Doppler velocity, and polarization colormaps are designed to highlight rain, frozen precipitation, non-meteorological targets, velocity-based items, be perceptually uniform, and visually friendly for those with CVD.

Zachary Sherman↗
DOE OSTI2025

Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling

This dataset contains (a) a script “R_met_integrated_for_modeling.R”, and (b) associated input CSV files: 3 CSV files per location to create a 5-variable integrated meteorological dataset file (air temperature, precipitation, wind speed, relative humidity, and solar radiation) for 19 meteorological stations and 1 location within Trail Creek from the modeling team within the East River Community Observatory as part of the Watershed Function Scientific Focus Area (SFA). As meteorological forcings varied across the watershed, a high-frequency database is needed to ensure consistency in the data analysis and modeling. We evaluated several data sources, including gridded meteorological products and field data from meteorological stations. We determined that our modeling efforts required multiple data sources to meet all their needs. As output, this dataset contains (c) a single CSV data file (*_1981-2022.csv) for each location (20 CSV output files total) containing hourly time series data for 1981 to 2022 and (d) five PNG files of time series and density plots for each variable per location (100 PNG files). Detailed location metadata is contained within the Integrated_Met_Database_Locations.csv file for each point location included within this dataset, obtained from Varadharajan et al., 2023 doi:10.15485/1660962. This dataset also includes (e) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and (f) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Review the (g) ReadMe_Integrated_Met_Database.pdf file for additional details on the script, methods, and structure of the dataset.The script integrates Northwest Alliance for Computational Science and Engineering’s PRISM gridded data product, National Oceanic and Atmospheric Administration’s NCEP-NCAR Reanalysis 1 gridded data product (through the `RCNEP` R package, Kemp et al., doi:10.32614/CRAN.package.RNCEP), and analytical-based calculations. Further, this script downscales the input data into hourly frequency, which is necessary for the modeling efforts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

White, Cary B.↗
NASA NTRS2018

Identifying and Forecasting Potential Biophysical Risk Areas within a Tropical Mangrove Ecosystem Using Multi-Sensor Data

Mangroves are one of the most productive ecosystems known for provisioning of various ecosystem goods and services. They help in sequestering large amounts of carbon, protecting coastline against erosion, and reducing impacts of natural disasters such as hurricanes. Bhitarkanika Wildlife Sanctuary in Odisha harbors the second largest mangrove ecosystem in India. This study used Terra, Landsat and Sentinel-1 satellite data for spatio-temporal monitoring of mangrove forest within Bhitarkanika Wildlife Sanctuary between 2000 and 2016. Three biophysical parameters were used to assess mangrove ecosystem health: leaf chlorophyll (CHL), Leaf Area Index (LAI), and Gross Primary Productivity (GPP). A long-term analysis of meteorological data such as precipitation and temperature was performed to determine an association between these parameters and mangrove biophysical characteristics. The correlation between meteorological parameters and mangrove biophysical characteristics enabled forecasting of mangrove health and productivity for year 2050 by incorporating IPCC projected climate data. A historical analysis of land cover maps was also performed using Landsat 5 and 8 data to determine changes in mangrove area estimates in years 1995, 2004 and 2017. There was a decrease in dense mangrove extent with an increase in open mangroves and agricultural area. Despite conservation efforts, the current extent of dense mangrove is projected to decrease up to 10% by the year 2050. All three biophysical characteristics including GPP, LAI and CHL, are projected to experience a net decrease of 7.7%, 20.83% and 25.96% respectively by 2050 compared to the mean annual value in 2016. This study will help the Forest Department, Government of Odisha in managing and taking appropriate decisions for conserving and sustaining the remaining mangrove forest under the changing climate and developmental activities.

Shanti Shrestha↗
NASA NTRS2005

The Tropical Convective Spectrum: Archetypal Vertical Structures - Part 1

A taxonomy of tropical convective and stratiform vertical structures is constructed through cluster analysis of 3 yr of Tropical Rainfall Measuring Mission (TRMM) "warm-season" (surface temperature greater than 10 C) precipitation radar (PR) vertical profiles, their surface rainfall, and associated radar-based classifiers (convective/ stratiform and brightband existence). Twenty-five archetypal profile types are identified, including nine convective types, eight stratiform types, two mixed types, and six anvil/fragment types (nonprecipitating anvils and sheared deep convective profiles). These profile types are then hierarchically clustered into 10 similar families, which can be further combined, providing an objective and physical reduction of the highly multivariate PR data space that retains vertical structure information. The taxonomy allows for description of any storm or local convective spectrum by the profile types or families. The analysis provides a quasi-independent corroboration of the TRMM 2A23 convective/ stratiform classification. The global frequency of occurrence and contribution to rainfall for the profile types are presented, demonstrating primary rainfall contribution by midlevel glaciated convection (27%) and similar depth decaying/stratiform stages (28%-31%). Profiles of these types exhibit similar 37- and 85-GHz passive microwave brightness temperatures but differ greatly in their frequency of occurrence and mean rain rates, underscoring the importance to passive microwave rain retrieval of convective/stratiform discrimination by other means, such as polarization or texture techniques, or incorporation of lightning observations. Close correspondence is found between deep convective profile frequency and annualized lightning production, and pixel-level lightning occurrence likelihood directly tracks the estimated mean ice water path within profile types.

Precipitation radar↗