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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Cloud Influence on ERA5 and AMPS Surface Downwelling Longwave Radiation Biases in West Antarctica

The surface downwelling longwave radiation component (LW?) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW? signal measured at the surface. In this study, we examine the LW? model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 reanalysis model relative to observations from the AWARE campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear sky conditions, ice cloud occurrences, and liquid-bearing cloud layer (LBCL) occurrences. The analysis results show a tendency (in both models at each site) to underestimate the LW? during clear sky conditions, high error variability (standard deviations > 20 W/m2) during any type of cloud occurrence, and negative LW? biases when LBCLs are observed (bias magnitudes > 15 W/m2 in tenuous LBCL cases; > 43 W/m2 in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid water-deficient atmosphere responsible for the identified LW? biases in both models is the result of excessive ice formation and growth, which could stem from model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.

Silber, Israel↗
DOE OSTI2019

Emergent Relationships Among Sea Ice, Longwave Radiation, and the Beaufort High Circulation Exposed Through Parameter Uncertainty Analysis

Using a perturbed parameter ensemble of a coupled climate model, emerging relationships are identified between sea ice area, net surface longwave radiation, and the atmospheric circulation over the Beaufort gyre. There is a strong positive correlation between sea ice area and the net longwave radiation over the ocean-ice surface during the melting season and a negative correlation during the freezing season. The mechanisms responsible for the longwave radiation balance at the surface are mainly driven by sea ice variations in the freezing season and by clouds in the melting season. A strong positive (negative) correlation is also found between the fall (summer) total sea ice area in the Arctic and the sea level pressure over the Beaufort High region. It is argued that as sea ice coverage is lost, static stability losses are severe in fall, resulting in enhanced evaporation, vertical motions, and weakening of the general large-scale anticyclonic circulation of the Beaufort High.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Three-Dimensional Surface Downwelling Longwave Radiation Clear-Sky Effects in the Upper Colorado River Basin

In complex terrain, non-parallel surfaces receive emitted radiation from adjacent surfaces. Qualitatively, where surface skin temperatures and lower tropospheric temperature and humidity are not uniform, the downwelling longwave radiation (DLR) will be determined not just by radiation from the atmosphere above a given location, but also by adjacent surface temperatures. We quantify this three-dimensional longwave radiative effect over the Upper Colorado River Basin in clear-sky conditions by calculating surface DLR with observed land-surface temperatures from ECOSTRESS. We find that this effect is due to terrain-subtended sky-view and represents ~22% of the surface longwave flux, rising to ~28% and ~24% in the East and Southeast of the Basin, respectively, and can be >50% in extreme cases. The common omission of this effect in atmospheric radiation models leads to an underestimation of DLR in complex terrain, especially at higher elevations, which has significant implications for mountainous ecohydrology simulations.

3-dimensional effects↗
DOE OSTI2019

Major improvements on the longwave radiative interactions between surface and clouds in the polar regions in atmospheric global circulation model

Motivations: One of the most important tasks in the study of physical and socioeconomic aspects of climate change is the simulation of polar climate and how it changes in response to global warming. One import component of the polar energy budget (and thus of polar climate) is the radiative interaction between surface and clouds. As of today, the vast majority of state-of-the-art global climate models (GCMs), including all three US flagship GCMs (NCAR CESM, GFDL CM3, and GISS E2-H/E2-R), still assume constant surface emissivity overall spectral bands in their longwave radiation treatment. Similarly, a majority of state-of-the-art GCMs assume non-scattering clouds in the longwave spectrum, including both the NCAR CESM and GFDL CM3. The issues of ignoring spectral variation in surface emissivity and scattering by clouds manifest themselves in the far-infrared (IR) over the polar continents because (1) there is so little water vapor in such areas that surface far-IR emission can reach clouds; and (2) the imaginary part of the refractive index of ice has a local minimum over 350-550 cm-1, which implies possible strong scattering effects over this spectral region both within and between the snow surface and ice clouds. Our sensitivity studies using CloudSat-retrieved hydrometeor profiles over the high-elevation Antarctic continent show that, in winter, an appropriate inclusion of snow surface spectral emissivity and ice cloud scattering in radiative transfer calculations can noticeably reduce the monthly-mean surface net downward far-IR flux and net atmospheric far-IR emission over the entire region. For the far-IR alone, the magnitude of these effects is ~1Wm-2 or even larger. Projection Objectives: We propose to carry out the following studies: (1) Develop or update schemes that can be used in the CESM to compute the optical properties of the snow surface and ice clouds consistently across the longwave and the shortwave spectrum; (2) Modify the longwave radiation scheme in the CESM such that it can incorporate surface spectral emissivity and scattering of clouds; (3) Validate schemes developed for (1) and (2) against measurements or benchmark models; (4) Evaluate the effects of these new treatments on the simulated polar energy budget and climate by the CESM. Technical Approaches:1.Use a detailed snowpack radiative transfer model to simulate spectrally resolved emissivity of snow surfaces as a function of snow effective radius. The model will be validated against available high spectral-resolution measurements of snow spectral emissivity (ASTER spectra library v2.0). Currently the CESM prognoses vertically-resolved snow effective radius, and snow shortwave albedo is parameterized based on snow effective radius. Our treatment of snow spectral emissivity here will be consistent with the treatment of snow albedo in the shortwave and seamlessly connected with the snow physical module in the CESM. 2. Update the parameterization of ice cloud optical properties in the CESM, for both longwave and shortwave, based on the latest ice-cloud scattering database developed by co-I Prof. Yang. 3. Modify RRTMG_LW, the current longwave radiation scheme in the CESM, to include the surface spectral emissivity and the scattering of clouds in the longwave calculation. Validate modified scheme against a line-by-line radiative transfer model with multiple scattering capability (LBLRTM/CHARTS). 4. Implement products from Steps 1-3 into the CESM and conduct simulations to evaluate their effects on the simulated polar climate and energy budget. These runs will be compared to control runs and evaluated using routine model-observation diagnostics, including data from the ARM NSA (North Slope of Alaska) site. Moreover, a novel aspect in this step is that we will evaluate the simulated longwave band-by-band fluxes and cloud radiative effect against observational counterparts over both polar continents, using a product recently derived by the lead PI Prof. Huang from collocated AIRS and CERES satellite observations from 2002 to 2013. Benefits and outcomes: This project will significantly improve the longwave radiation scheme in the CESM and its successors and provide more realistic treatment of radiative interactions between polar surfaces and clouds. In the future, it will also be straightforward to extend this framework to include spectral emissivity of all surface types. This is responsive to identified DoE Earth System Modeling Science Drivers to improve the performance of the fully coupled climate system modeling and to help address questions on how rapid changes in cryospheric systems interact with the climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Enhanced Cloud Top Longwave Radiative Cooling Due To the Effect of Horizontal Radiative Transfer in the Stratocumulus to Trade Cumulus Transition Regime

Abstract Recent studies develop the SPeedy Algorithm for Radiative TrAnsfer through CloUd Sides (SPARTACUS) to handle the influence of horizontal RT on vertical radiative fluxes within an atmospheric column. The present study applies SPARTACUS to large eddy simulation (LES)‐generated cloud fields across the stratocumulus to trade cumulus transition (STCT) regime with coarse and fine vertical resolutions. The results show that, as the vertical resolution increases, radiation simulations show increasingly stronger cloud‐top longwave (LW) radiative cooling. Consequently, the sharp radiative heating gradient across the cloud layer in the LES‐like resolution simulations cannot be resolved with the coarse resolution simulations. Including the horizontal RT typically enhances cloud LW radiative cooling rate by less than 10% for all the cloud fields but more significantly in the cloud fields during the STCT. The enhanced cloud LW radiative cooling also occurs in the lower cloud layer in the decoupled cumulus cloud regime.

Geology↗
DOE OSTI2017

Impact of Multiple Scattering on Longwave Radiative Transfer Involving Clouds

Abstract General circulation models (GCMs) are extensively used to estimate the influence of clouds on the global energy budget and other aspects of climate. Because radiative transfer computations involved in GCMs are costly, it is typical to consider only absorption but not scattering by clouds in longwave (LW) spectral bands. In this study, the flux and heating rate biases due to neglecting the scattering of LW radiation by clouds are quantified by using advanced cloud optical property models, and satellite data from Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Clouds and the Earth's Radiant Energy System (CERES), and Moderate Resolution Imaging Spectrometer (MODIS) merged products (CCCM). From the products, information about the atmosphere and clouds (microphysical and buck optical properties, and top and base heights) is used to simulate fluxes and heating rates. One‐year global simulations for 2010 show that the LW scattering decreases top‐of‐atmosphere (TOA) upward flux and increases surface downward flux by 2.6 and 1.2 W/m 2 , respectively, or approximately 10% and 5% of the TOA and surface LW cloud radiative effect, respectively. Regional TOA upward flux biases are as much as 5% of global averaged outgoing longwave radiation (OLR). LW scattering causes approximately 0.018 K/d cooling at the tropopause and about 0.028 K/d heating at the surface. Furthermore, over 40% of the total OLR bias for ice clouds is observed in 350–500 cm −1 . Overall, the radiative effects associated with neglecting LW scattering are comparable to the counterpart due to doubling atmospheric CO 2 under clear‐sky conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Major improvements on the longwave radiative interactions between surface and clouds in the Polar Regions in atmospheric global circulation model (GCM). Final Project Report

1. Summary of Work and Accomplishments in Year 1 (01/15/2015-01/14/2016). We developed new ice cloud parameterizations based on state-of-the-art MODIS Collection 6 (MC6) ice particle model. Features of the model include the consideration of surface roughness of ice crystals and spectral consistency in cloud property retrievals. Using more than 14,000 particle size distributions (PSDs) from in-situ measurements and the latest ice particle single-scattering property library, our parameterizations provide band-averaged bulk-scattering properties. According to statistics of fittings, the parameterization schemes represent the band-averaged bulk-scattering properties very well. Compared to the ice particle model developed by Fu (1998), flux simulations with the MC6 particle model result in larger upward flux at the top of the atmosphere (TOA) and smaller at the surface for typical cirrus clouds. In the assessment of the effect of longwave light scattering, our results also support the conclusions of previous studies. The error in flux calculations reaches about 10 W/m 2 when a cirrus cloud is thin and its particle size is small. 2. Summary of Work and Accomplishments in Year 2 (01/15/2016-01/14/2017) Clouds are a major modulator of the global radiation budgets. However, representations of clouds in general circulation models (GCMs) neglect many important processes, particularly those related to ice clouds. One major uncertainty source is the radiative transfer scheme in GCMs. To reduce the computational burden in most GCMs, absorption is the only radiative transfer process considered in longwave spectral bands. Recently, a state-of-the-art MC6 ice model has been available, which provides spectral consistency in ice cloud retrievals. With an advanced light scattering library for ice particles, we performed sensitivity studies of the potential impacts on the climate including light scattering for MC6 model and other 11 ice cloud models. Specifically, we modified RRTMG_LW (the GCM version of Longwave Rapid Radiative Transfer Model), a radiative transfer module widely used in GCMs and numerical prediction models, to identify flux simulation differences with and without considering light scattering processes. The simulations with light scattering come from a rigorous radiative solver, DISORT (Discrete Ordinates Radiative Transfer Program for a Multi-Layered Plane-Parallel Medium), are used as benchmarks. The results show that the weighted annual mean biases of RRTMG_LW for the upward flux at the top of the atmosphere, the downward flux at the surface, and the net flux into the atmosphere are about 0.8 ± 0.3, -0.1 ± 0.05, and -0.7 ± 0.3 W m-2, respectively. According to the different the ice crystal shapes, the weighted annual mean bias for heating rate is about -0.006 ± 0.02 to 0.04 K/day. 3. Summary of Work and Accomplishments in Year 3 (01/15/2017-01/14/2018) Since absorption dominates optical properties of clouds in the longwave (LW) spectrum, most of general circulation models (GCMs) only take absorption properties of clouds into account in the radiative transfer modules in order to reduce computational costs. To quantify the biases of excluding LW scattering when clouds exist, we simulated fluxes and heating rates by using satellite data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectrometer (MODIS) merged products (CCCM) in 2010. In annual global average, neglecting LW scattering causes overestimation by 2.6 W/m 2 for the top-of-atmosphere (TOA) upward fluxes and underestimation by 1.2 W/m 2 for surface downward fluxes. In particular, regional extreme biases are approximately 12 W/m 2 for TOA upward fluxes and are approximately -3.6 W/m 2 for surface downward fluxes, or are approximately 5% of the global averaged outgoing longwave radiation (OLR) and 1% of the global averaged surface downward fluxes, respectively. In terms of heating rates, on average, LW scattering heats the whole atmosphere column by 0.0045 K/day, heats the cloud layers by 0.0420 K/day, heats the surface by 0.028 K/day, and cools the tropopause by 0.018 K/day.

58 GEOSCIENCES↗
DOE OSTI2024

Broadband and filter radiometers at Ross Island, Antarctica: detection of cloud ice phase versus liquid water influences on shortwave and longwave radiation

Abstract. Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015–2016 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Increasing wintertime cloud opacity increases surface longwave radiation at a long-term Arctic observatory

As the Arctic warms, winter clouds are known and expected to change. Yet the extent to which these cloud changes amplify or dampen warming (cloud feedback) remains uncertain. This uncertainty results from systemic difficulties in modeling and observing Arctic low clouds. Surface-based observations avoid many of these difficulties. Here, we use two decades of surface-based observations (1998–2023) to constrain and explain longwave flux change during winter. We find that longwave flux into the surface is increasing and that this increase cannot be explained by direct impacts of temperature and greenhouse gases alone. Only when increasing cloud radiative effect (0.96 ± 0.64 W/m 2 /K) is considered can increasing longwave flux be explained. Cloud radiative effect increases due to increasing cloud opacity, which is driven equally by ice-only and mixed-phase clouds. The direct observational constraint from this work suggests that increasing cloud opacity drives increasing net surface radiation on Alaska’s North Slope during winter.

Bertrand, Leah [Univ. of Colorado, Boulder, CO (Un↗
DOE OSTI2026

Dust semi-direct effects: low-level cloud response to free-tropospheric dust-induced longwave radiation over the North Atlantic Ocean

Aerosol semi-direct effect is the adjustment of the radiative budget due to the cloud response to radiation absorption. Although dust accounts for about a third of aerosols' shortwave absorption, our understanding of its semi-direct effect often relies on traditional shortwave-focused mechanisms previously established for biomass-burning aerosols, and implications of dust longwave absorption on clouds have yet to be explored. Here, we assess the low-level cloud cover (LLCC) response to changes in properties and characteristics of the free-tropospheric dust layer over the North Atlantic Ocean (May–August, 2007–2017). We find that, consistent with previous studies, LLCC typically responds positively (increases in clouds) to an overlying dust layer. However, this response weakens with increasing dust optical depth (DOD), dust geometric thickness (DGT), and dust-layer base height (DBH). Specifically, we find that the LLCC response weakens by 4.3 ± 1.04 % and 1.6 ± 0.65 %, respectively, for a one-standard-deviation increase in DOD and DGT, and a smaller response to DBH (0.19 ± 0.45 %). We also find that the weakened LLCC response is primarily due to enhanced dust-induced longwave-dominated cloud-top warming, which counteracts the mean cloud-top cooling by as much as 19 % (mean of 9 %). Sensitivity analysis further indicates that the variability in dust properties, influenced by dust size distribution and refractive index, dominates the changes in dust-induced cloud-top warming, rather than variabilities in cloud properties or thermodynamic profiles. Our result adds to the traditional understanding of LLCC enhancement through shortwave-driven atmospheric stability, often associated with aerosol semi-direct effects, and highlights the role of dust-induced cloud-top longwave warming in dust semi-direct effects.

Pandey, Satyendra K. [Univ. of California, Merced,↗
DOE OSTI2025

Meteorological Variables and Energy Fluxes at the Pumphouse Site, Crested Butte, CO 2017-2019

This data contains output from the pumphouse eddy covariance tower that includes shortwave radiation, longwave radiation, net radiation, air temperature, relative humidity, as well as sensible, latent, and ground heat fluxes. Also included is calculated evapotranspiration from the latent heat flux and the latent heat of vaporization. All data are on a daily timestep and displayed in Mountain Time. The data has been processed, and Quality Assurance / Quality Control (QA/QC) was done, but any daily gaps in the data have not been filled in. This research was funded by the Department of Energy and performed as part of the Watershed Function Scientific Focus Area. This research aimed to constrain evapotranspiration in a high-elevation catchment.The dataset includes one comma-separated values (CSV) data file (EddyCovariance_MeteorlogicalVariables_CrestedButtePumphouse.csv). Additionally, three metadata CSV files are included: (1) location metadata file (locations.csv), which contains location metadata and coordinates; (2) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and (3) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Meteorological, reference evapotranspiration and estimated transpiration data, July 2020-Dec 2021, Slate River Floodplain, Crested Butte, Colorado

This data package includes a time series of meteorological data (air temperature, relative humidity, barometric pressure, precipitation, wind speed, soil heat flux, incoming shortwave radiation, incoming longwave radiation, outgoing shortwave radiation and outgoing longwave radiation) from the Slate River floodplain outside Crested Butte, Colorado, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The package also includes reference evapotranspiration calculated via the Penman-Monteith equation and an estimate of willow (Salix spp.) evapotranspiration using the method of Irmak et al., J. Hydrology, 2013. Due to two malfunctioning sensors (incoming shortwave radiation from Oct 2020-May 2021 and incoming longwave radiation from May 2021-March 2022), observed net radiation and calculated evapotranspiration are only included from July-October 2020. However, users may be able to extend calculated evapotranspiration using estimates of these two parameters from other sources. Both sensors have been replaced and data beyond 2021 be uploaded to this repository when it is available.Within the data package, "FLMD.csv" describes file-level metadata and "dd.csv" defines column headers and universal terms across the dataset. The data package includes 3 "*data.csv" files, two for meteorological data for 2020 and 2021 and one for reference evapotranspiration and transpiration data from 2020 ("SLT_OBJ2_PenmanMonteith_2020_data.csv"). Each "*data.csv" file of meteorological data has a corresponding "*_InstallationMethods.csv" file that describes the location, sensor model, sensor serial number and other metadata corresponding to each measured parameter. We also include a Jupyter notebook ("PenmanMonteithET_Calculations.ipynb") that details the assumptions and equations used to calculate daily and hourly reference evapotranspiration and daily willow transpiration from raw meteorological data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Projections of Hourly Meteorology by Balancing Authority Based on the IM3/HyperFACETS Thermodynamic Global Warming (TGW) Simulations

This dataset contains 40 years (1980-2019) of historical hourly meteorology and 80 years (2020-2099) of projected hourly meteorology for 54 Balancing Authorities (BAs) in the conterminous United States. Details about the scenarios and variables included in this dataset are in the readme.pdf file. This dataset is derived from the IM3/HyperFACETS Thermodynamic Global Warming (TGW) simulations (https://doi.org/10.57931/1885756). More details on the TGW approach can be found at: https://tgw-data.msdlive.org/. If you use this dataset please also cite the raw TGW dataset (Jones, A. D., Rastogi, D., Vahmani, P., Stansfield, A., Reed, K., Thurber, T., Ullrich, P., & Rice, J. S. (2022). IM3/HyperFACETS Thermodynamic Global Warming (TGW) Simulation Datasets (v1.0.0) [Data set]. MSD-LIVE Data Repository. https://doi.org/10.57931/1885756). To go from the TGW data to these BA-level aggregated data we first averaged the raw gridded data by county in the United States. That intermediate data step is also stored in MSD-LIVE (https://doi.org/10.57931/1960548). We then population-weight the county-level hourly data in order to create population-weighted meteorology time series for each BA. Historical populations are from the United States Census Bureau and the evolving future populations are based on Shared Socioeconomic Pathways (SSPs) 3 and 5. The four climate scenarios crossed with the two SSPs yield eight different future projections for each BA: rcp45cooler_ssp3, rcp45cooler_ssp5, rcp45hotter_ssp3, rcp45hotter_ssp5, rcp85cooler_ssp3, rcp85cooler_ssp5, rcp85hotterssp3, rcp85hotterssp5. For the historical period and each of the eight future scenarios the dataset has hourly estimates of the population-weighted average of five meteorological variables: Temperature, specific humidity, shortwave radiation, longwave radiation, and wind speed. All times are in Coordinated Universal Time (UTC). The code to go from the raw TGW data to county-level and then BA-level projections is available at: https://github.com/IMMM-SFA/im3components/tree/main/im3components/wrf_to_tell.

Balancing Authority↗
DOE OSTI2023

Projections of Hourly Meteorology by County Based on the IM3/HyperFACETS Thermodynamic Global Warming (TGW) Simulations

This dataset contains 40 years (1980-2019) of historical hourly meteorology and 80 years (2020-2099) of projected hourly meteorology for each county in the conterminous United States. Details about the scenarios and variables included in this dataset are in the readme.pdf file. This dataset is derived from the IM3/HyperFACETS Thermodynamic Global Warming (TGW) simulations (https://doi.org/10.57931/1885756). More details on the TGW approach can be found at: https://tgw-data.msdlive.org/. If you use this dataset please also cite the raw TGW dataset (Jones, A. D., Rastogi, D., Vahmani, P., Stansfield, A., Reed, K., Thurber, T., Ullrich, P., & Rice, J. S. (2022). IM3/HyperFACETS Thermodynamic Global Warming (TGW) Simulation Datasets (v1.0.0) [Data set]. MSD-LIVE Data Repository. https://doi.org/10.57931/1885756). The four future climate scenarios in the TGW data are: rcp45cooler, rcp45hotter, rcp85cooler, and rcp85hotter. For the historical period and each of the four future scenarios the dataset has hourly estimates of the spatial-average of six meteorological variables for each county: Temperature, specific humidity, shortwave radiation, longwave radiation, and the U (east-west) and V (north-south) components of the wind speed. Times for each file are in the filename and all times are in Coordinated Universal Time (UTC). Counties are identified by their Federal Information Processing Standard (FIPS) code. The mapping between counties and FIPS codes is provided in the state_and_county_fips_codes.csv file. The code to go from the raw TGW data to county-level projections is available at: https://github.com/IMMM-SFA/im3components/tree/main/im3components/wrf_to_tell.

County↗