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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

3D Continuous Forcing Dataset from 3D Constrained Variational Analysis at SGP

The continuous 3D large-scale forcing (VARANAL3D) data set derived from 3D constrained variational analysis (3DCVA) extends the conventional constrained variational analysis method by incorporating multiple sub-columns within the analysis domain. This advancement introduces spatial variability into the large-scale forcing fields, thereby enriching the data set’s applicability. The VARANAL3D data set spans from 2004 to 2018 and covers a region of 5˚×4.5˚ domain around the ARM SGP site. The analysis domain is divided into 10×9 sub-columns with 0.5˚ resolution. The 3D large-scale forcing data provides necessary variables to drive and evaluate single-column models (SCM), cloud-resolving models (CRM) ,and large-eddy simulations (LES), as well as information for testing model sensitivity to spatial variability of the large-scale forcing data, facilitating more rigorous testing and refinement of physical processes in SCM/CRM/LES.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

New Particle Formation Event Dataset at the Southern Great Plains (SGP) Observatory from 2018 to 2023

This data set contains observations of new particle formation (NPF) events collected at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory from 2018 to 2023. Measurements include particle number size distributions, radiance measurements, and associated meteorological variables from onsite instrumentation relevant for identifying and characterizing NPF events. Events were identified using standardized criteria and documented to support investigations of aerosol nucleation, growth dynamics, and their interactions with local atmospheric conditions. The data set provides a multi-year record that enables evaluation of seasonal and interannual variability in NPF occurrence and intensity at a mid-continental site. These data are intended to support studies of aerosol-cloud-climate interactions and model evaluation within both ARM and the broader atmospheric science community. More information can be found within the README_NPF_SGP_2018_2023.docx file.

event↗
DOE OSTI2025

NWB Sensors Infrared Cloud Imager Data Products from SGP

NWB Sensors is a company which has developed a commercially available Infrared Cloud Imager (ICI). For more information, consult the company's webpage, https://www.nwbsensors.com/infrared-cloud-imager. To validate the radiometric accuracy of the ICI, NWB Sensors deployed it to the ARM SGP User Facility in 2023. The primary motivation of this deployment was to perform an intercomparison between the ICI and the Atmospheric Emitted Radiance Interferometer (AERI). The AERI spectral radiance data product can be integrated across the response function of the ICI and directly compared to the zenith radiance observed by the ICI. In addition, the ICI uses proprietary models of the downwelling clear-sky radiance in its cloud processing algorithms. They are based on surface meteorology and precipitable water vapor (PWV). These models were validated by comparing their predicted radiances to those derived from radiative transfer models of the ARM radiosondes. Finally, PWV observations derived from the ICI's onboard GNSS-based PWV retrieval system were compared against those from the microwave radiometer. This dataset contains the ICI radiance and cloud data products.

Atmosphere↗
DOE OSTI2025

GreenSight WxHive Unmanned Aerial System (UAS) Atmospheric Profiling at the SGP Central Facility

The GreenSight WxHive is capable of flying multiple nanodrones simultaneously to provide spatiotemporal atmospheric sampling. During the WH2yMSIE campaign, the WxHive would fly up to 5 nanodrones at once, performing profiling within the planetary boundary layer over the ARM SGP Central Facility site. The measurements provided by the WxHive include latitude, longitude, altitude, pressure, temperature, humidity, and wind speed and direction. See the attached WeatherHive User Guide for more details about the instrument and measurements.

Air pressure↗
DOE OSTI2026

E3SMv3 ‘Nephele’ Perturbed Parameter Ensemble Value-Added Product for ENA, SGP, NSA, and Global Means

Processed output from the E3SMv3 Nephele perturbed parameter ensemble (PPE). This product contains global means of present-day (using 2010 aerosol forcings) and preindustrial (using 1850 aerosol forcings) monthly and daily global-mean quantities, as well as hourly mean quantities at the E3SMv3 model grid cell closest to the ENA, SGP, and NSA ARM sites. In this PPE, the E3SMv3 model was run for 27 months in an atmosphere-only configuration with free tropospheric winds nudged to reanalysis. Each ensemble member represents a unique combination of 25 model parameter values (in the microphysics, convective microphysics, and aerosol schemes) that were perturbed randomly and simultaneously. The E3SMv3 default configuration is included as member 0. See https://doi.org/10.22541/essoar.174907165.57104591/v1 (in review) for more information on the Nephele PPE and the perturbed parameters.

Model atmospheric temperature↗
NASA NTRS2001

Sunphotometric Measurement of Columnar H2O and Aerosol Optical Depth During the 3rd Water Vapor IOP in Fall 2000 at the SGP ARM Site

We conducted ground-based measurements with the Ames Airborne Tracking 6-channel Sunphotometer (AATS-6) during the 3rd Water Vapor IOP (WVIOP3), September 18 - October 8, 2000 at the SGP ARM site. For this deployment our primary result was columnar water vapor (CWV) obtained from continuous solar transmittance measurements in the 0.94-micron band. In addition, we simultaneously measured aerosol optical depth (AOD) at 380, 450, 525, 864 and 1020 nm. During the IOP, preliminary results of CWV and AOD were displayed in real-time. The result files were made available to other investigators by noon of the next day. During WVIOP3 those data were shown on the daily intercomparison plots on the IOP web-site. Our preliminary results for CWV fell within the spread of values obtained from other techniques. After conclusion of WVIOP3, AATS-6 was shipped directly to Mauna Loa, Hawaii for post-mission calibration. The updated calibration, a cloud screening technique for AOD, along with other mostly cosmetic changes were applied to the WVIOP3 data set and released as version 0.1. The resulting changes in CWV are small, the changes in AOD and Angstrom parameter are more noticeable. Data version 0.1 was successfully submitted to the ARM External Data Center. In the poster we will show data examples for both CWV and AOD. We will also compare our CWV results with those obtained from a GPS (Global Positioning System) slant path method.

Schmid, B↗
NASA NTRS2003

Validation of the Archived CERES Surface and Atmosphere Radiation Budget (SARB) at SGP

The CERES Surface and Atmosphere Radiation Budget (SARB) product (Charlock et al, 2002) includes the vertical profile of broadband SW, broadband LW, and 8-12 micron window (WN) fluxes; upwelling and downwelling at TOA, 70 hPa, 200 hPa, 500 hPa, and the surface; and for all-sky and clear-sky conditions. We test the archived CERES TRMM record of SARB for January-August 1998 and focus on discrepancies with ground-based measurements at SGP. The CERES SARB is generated by a highly modified Fu-Liou radiative transfer code (Fu and Liou, 1993). The most critical inputs for this application are cloud optical properties (fractional area, optical depth, particle size and phase, height of top, and estimate of geometrical thickness Minnis et al., 2002) from the narrowband VIRS imager. Numerous VIRS pixels (approx. 2km resolution at nadir) are matched to each of the large (approx. 20km) CERES broadband footprints (Wielicki et al, 1996). Other inputs include temperature and humidity from ECMWF (Rabier et al, 1998) , NCEP ozone profiles from SBUV and TOVS (Yang et al, 2001), aerosol optical thickness (AOT) from the Model for Atmospheric Transport and Chemistry (MATCH) aerosol assimilation (Collins et al., 2001) or alternately from the VIRS imager (Ignatov and Stowe, 2000). VIRS AOT is available for clear and partly cloudy ocean footprints during daylight; and only when viewing geometry renders a contribution from sunglint as unlikely. For other footprints, AOT is taken from MATCH. AOT is apportioned into fractions of dust (Tegan and Lacis, 1996), sea salt, sulfate, dust, soluble organic, insoluble organic, and soot (Hess et al., 1996) using the 6-hourly MATCH output. Tuned fluxes are retrieved by adjusting inputs to nudge computed TOA fluxes toward CERES observations (Rose et al, 1997). In clear conditions, the fields of humidity, surface skin temperature, surface albedo and AOT are adjusted to produce a closer match of computed and observed fluxes at TOA. When CERES footprints have clouds, the cloud optical thickness, fractional area within the footprint, and temperature of cloud top are adjusted by the tuning algorithm. Both tuned and untuned fluxes are archived, as are the respective adjustments to any parameters at the surface or within the atmosphere.

Charlock, Thomas P.↗
NASA NTRS2007

Improvements to GOES Twilight Cloud Detection over the ARM SGP

The current ARM satellite cloud products derived from Geostationary Operational Environmental Satellite (GOES) data provide continuous coverage of many cloud properties over the ARM Southern Great Plains domain. However, discontinuities occur during daylight near the terminator, a time period referred to here as twilight. This poster presentation will demonstrate the improvements in cloud detection provided by the improved cloud mask algorithm as well as validation of retrieved cloud properties using surface observations from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) site.

Yost, c. R.↗
NASA NTRS2005

A Climatology of Midlatitude Continental Clouds from the ARM SGP Site: Low-Level Cloud Macrophysical, Microphysical, and Radiative Properties - Part I

A record of single-layer and overcast low cloud (stratus) properties has been generated using approximately 4000 hours of data collected from January 1997 to December 2002 at the Atmospheric Radiation Measurement (ARM) Southern Great Plains Central Facility (SCF). The cloud properties include liquid-phase and liquid-dominant, mixed-phase, low cloud macrophysical, microphysical, and radiative properties including cloud-base and -top heights and temperatures, and cloud physical thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding; cloud liquid water path (LWP) and content (LWC), and cloud-droplet effective radius (r(sub e)) and number concentration (N) derived from the macrophysical properties and radiometer data; and cloud optical depth (tau), effective solar transmission (gamma), and cloud/top-of-atmosphere albedos (R(sub cldy)/R(sub TOA)) derived from Eppley precision spectral pyranometer measurements. The cloud properties were analyzed in terms of their seasonal, monthly, and hourly variations. In general, more stratus clouds occur during winter and spring than in summer. Cloud-layer altitudes and physical thicknesses were higher and greater in summer than in winter with averaged physical thicknesses of 0.85 km and 0.73 km for day and night, respectively. The seasonal variations of LWP, LWC, N. tau, R(sub cldy), and R(sub TOA) basically follow the same pattern with maxima and minima during winter and summer, respectively. There is no significant variation in mean r(sub e), however, despite a summertime peak in aerosol loading, Although a considerable degree of variability exists, the 6-yr average values of LWP, LWC, r(sub e), N, tau, gamma, R(sub cldy) and R(sub TOA) are 150 gm(exp -2) (138), 0.245 gm(exp -3) (0.268), 8.7 micrometers (8.5), 213 cm(exp -3) (238), 26.8 (24.8), 0.331, 0.672, 0.563 for daytime (nighttime). A new conceptual model of midlatitude continental low clouds at the ARM SGP site has been developed from this study. The low stratus cloud amount monotonically increases from midnight to early morning (0930 LT), and remains large until around local noon, then declines until 1930 LT when it levels off for the remainder of the night. In the morning, the stratus cloud layer is low, warm, and thick with less LWC, while in the afternoon it is high, cold, and thin with more LWC. Future parts of this series will consider other cloud types and cloud radiative forcing at the ARM SCF.

Dong, Xiquan↗
NASA NTRS2006

A Climatology of Midlatitude Continental Clouds from the ARM SGP Site: Cloud Fraction and Surface Radiative Forcing - Part II

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of cloud fraction and radiative forcing between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layered low (0-3 km), middle (3-6 km), and high clouds (more than 6 km) using ARM SCG ground-based paired lidar-radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties of approximately 10 Wm(exp -2). The annual averages of total, and single-layered low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total and low cloud amounts peak during January and February and reach a minimum during July and August, high clouds occur more frequently than other types of clouds with a peak in summer. The average annual downwelling surface SW fluxes for total and low clouds (151 and 138 Wm(exp-2), respectively) are less than those under middle and high clouds (188 and 201 Wm(exp -2), respectively), but the downwelling LW fluxes (349 and 356 Wm(exp -2)) underneath total and low clouds are greater than those from middle and high clouds (337 and 333 Wm(exp -2)). Low clouds produce the largest LW warming (55 Wm(exp -2) and SW cooling (-91 Wm(exp -2)) effects with maximum and minimum absolute values in spring and summer, respectively. High clouds have the smallest LW warming (17 Wm(exp -2)) and SW cooling (-37 Wm(exp -2)) effects at the surface. All-sky SW CRF decreases and LW CRF increases with increasing cloud fraction with mean slopes of -0.984 and 0.616 Wm(exp -2)%(exp -1), respectively. Over the entire diurnal cycle, clouds deplete the amount of surface insolation more than they add to the downwelling LW flux. The calculated CRFs do not appear to be significantly affected by uncertainties in data sampling and clear-sky screening. Traditionally, cloud radiative forcing includes, not only the radiative impact of the hydrometeors, but also the changes in the environment. Taken together over the ARM SCF, changes in humidity and surface albedo between clear and cloudy conditions offset approximately 20% of the NET radiative forcing caused by the cloud hydrometeors alone. Variations in water vapor, on average, account for 10% and 83% of the SW and LW CRFs, respectively, in total cloud cover conditions. The error analysis further reveals that the cloud hydrometeors dominate the SW CRF, while water vapor changes are most important for LW flux changes in cloudy skies. Similar studies over other locales are encouraged where water and surface albedo changes from clear to cloudy conditions may be much different than observed over the ARM SCF.

Xi, B.↗
NASA NTRS2006

Observational Evidence of Changes in Water Vapor, Clouds, and Radiation at the ARM SGP Site

Characterizing water vapor and cloud effects on the surface radiation budget is critical for understanding the current climate because water vapor is the most important greenhouse gas in the atmosphere and clouds are one of the largest sources of uncertainty in predicting potential future climate change. Several studies have shown that insolation over land declined until 1990 then increased until the present. Using 8 years of data collected at the ARM Southern Great Plains (SGP) surface site, we found that the insolation increased from 1997 to 2000, but significantly decreased from 2001 to 2004, changes that exactly mirror the variation in the second-order fit of cloud fraction. Under clear-sky conditions, the rates of water vapor, insolation and downwelling longwave (LW) flux are -0.166 cm/yr, 0.48 Wm(exp -2)/yr, and -1.16 Wm(exp -2)/yr, respectively, indicating that water vapor changes are more important for LW flux than for insolation.

Dong, Xiquan↗
NASA NTRS2010

A Comparison of MERRA and NARR Reanalysis Datasets with the DOE ARM SGP Continuous Forcing data

In this study, the atmospheric state, precipitation, cloud fraction, and radiative fluxes from Modern Era Retrospective-analysis for Research and Applications (MERRA) and North American Regional Reanalysis (NARR) are collected and compared with the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) continuous forcing during the period 1999-2001. For the atmospheric state, the three datasets have excellent agreement for the horizontal wind components and air temperature. NARR and ARM have generally good agreement for humidity, except for several biases in the PBL and in the upper troposphere. MERRA, on the other hand, suffers from a year-round negative bias in humidity except for the month of June. For the vertical pressure velocity, significant differences exist with the largest biases occurring during the spring upwelling and summer downwelling periods. Although NARR and MERRA share many resemblances to each other, ARM outperforms these reanalyses in terms of correlation with cloud fraction. Because the ARM forcing is constrained by observed precipitation that gives the adequate mass, heat, and moisture budgets, much of the precipitation (specifically during the late spring/early summer) is caused by smaller-scale forcing that is not captured by the reanalyses. Both NARR and MERRA capture the seasonal variation of CF observed by ARM radar-lidar and GOES with high correlations (0.92-0.78), but having negative biases of 14% and 3%, respectively. Compared to the ARM observations, MERRA shows a better agreement for both SW and LW fluxes except for LW-down (due to a negative bias in water vapor), NARR has significant positive bias for SW-down and negative bias for LW-down under clear- and all-sky conditions . The NARR biases result from a combination of too few clouds and a lack of sufficient extinction by aerosols and water vapor in the atmospheric column. The results presented here represent only one location for a limited time period, and more comparisons at different locations and longer time period are needed.

Kennedy, Aaron D.↗
NASA NTRS2010

A 10-Year Climatology of Cloud Cover and Vertical Distribution Derived from Both Surface and GOES Observations Over the DOE ARM SGP Site

Analysis of a decade of ARM radar-lidar and GOES observations at the SGP site reveal that 0.5 and 4-hr averages of the surface cloud fraction correspond closely to 0.5deg and 2.5deg averages of GOES cloudiness, respectively. The long-term averaged surface and GOES cloud fractions agree to within 0.5%. Cloud frequency increases and cloud amount decreases as the temporal and spatial averaging scales increase. Clouds occurred most often during winter and spring. Single-layered clouds account for 61.5% of the total cloud frequency. There are distinct bimodal vertical distributions of clouds with a lower peak around 1 km and an upper one that varies from 7.5 to 10.8 km between winter and summer, respectively. The frequency of occurrence for nighttime GOES high-cloud tops agree well with the surface observations, but are underestimated during the day.

Xi, Baike↗
NASA NTRS2013

Evaluation of Precipitation Simulated by Seven SCMs against the ARM Observations at the SGP Site

This study evaluates the performances of seven single-column models (SCMs) by comparing simulated surface precipitation with observations at the Atmospheric Radiation Measurement Program Southern Great Plains (SGP) site from January 1999 to December 2001. Results show that although most SCMs can reproduce the observed precipitation reasonably well, there are significant and interesting differences in their details. In the cold season, the model-observation differences in the frequency and mean intensity of rain events tend to compensate each other for most SCMs. In the warm season, most SCMs produce more rain events in daytime than in nighttime, whereas the observations have more rain events in nighttime. The mean intensities of rain events in these SCMs are much stronger in daytime, but weaker in nighttime, than the observations. The higher frequency of rain events during warm-season daytime in most SCMs is related to the fact that most SCMs produce a spurious precipitation peak around the regime of weak vertical motions but rich in moisture content. The models also show distinct biases between nighttime and daytime in simulating significant rain events. In nighttime, all the SCMs have a lower frequency of moderate-to-strong rain events than the observations for both seasons. In daytime, most SCMs have a higher frequency of moderate-to-strong rain events than the observations, especially in the warm season. Further analysis reveals distinct meteorological backgrounds for large underestimation and overestimation events. The former occur in the strong ascending regimes with negative low-level horizontal heat and moisture advection, whereas the latter occur in the weak or moderate ascending regimes with positive low-level horizontal heat and moisture advection.

Model comparison↗
NASA NTRS2017

RFI Mitigation and Testing Employed at GGAO for NASA's Space Geodesy Project (SGP)

Radio Frequency Interference (RFI) Mitigation at Goddard Geophysical and Astronomical Observatory (GGAO) has been addressed in three different ways by NASA's Space Geodesy Project (SGP); masks, blockers, and filters. All of these techniques will be employed at the GGAO, to mitigate the RFI consequences to the Very Long Baseline Interferometer.

Hilliard, Lawrence M.↗
NASA NTRS2017

RFI Mitigation and Testing Employed at GGAO for NASA's Space Geodesy Project (SGP)

Radio Frequency Interference (RFI) Mitigation at Goddard Geophysical and Astronomical Observatory (GGAO) has been addressed in three different ways by NASA's Space Geodesy Project (SGP); masks, blockers, and filters. All of these techniques will be employed at the GGAO, to mitigate the RFI consequences to the Very Long Baseline Interferometer.

Hilliard, L. M.↗
DOE OSTI2026

The Spatial and Temporal Variability of the Clear Convective Boundary Layer at the ARM SGP Supersite

The convective boundary layer (CBL), also known as the mixing layer, constitutes the critical lower segment of the atmosphere that significantly influences daily human activities. The growing demand for precise weather forecasts is driven by the requirements of agriculture, transportation, and routine societal functions. Here, to enhance understanding of the CBL, this study investigates the spatiotemporal variability in the CBL and its controlling factors using four-year Doppler lidar, surface flux, and profiling measurements at five ARM Southern Great Plains sites within a 100 km radius. This investigation utilizes data collected exclusively under clear-sky conditions or scattered low-cloud conditions. Results reveal significant spatial differences in CBL evolutions. Daily mixing layer heights (MLHs) vary up to 1 km (30% of the mean) in late afternoon. There is a clear east–west contrast: western sites (C1, E32, E37) exhibit higher summer MLH (1.9–2.1 km) and vertical velocity variances (1.0–1.2 m 2 s −2 ) than eastern sites (1.6–1.8 km), reversing in winter. Temporally, the MLH peaks at 70% of the sunrise–sunset interval, the lagging heat flux (HF) peaks at 50%; and the seasonal MLH maxima lag the HF by approximately one month, influenced by nighttime PBL (planetary boundary layer) properties. The HF and lower tropospheric stability are the main factors of influence for the CBL, but site-specific dependencies highlight the critical roles of local factors, underscoring the need for including them in CBL modeling.

ARM SGP site↗
DOE OSTI2023

Direct measurement of small particle growth and aging at SGP

Atmospheric aerosols influence climate directly by scattering and absorbing solar radiation and indirectly through their influence on the reflectivity and lifetime of clouds. But that influence is limited to only those particles large enough to efficiently interact with solar radiation (diameter, D p ≳ 100 nm) and/or to form cloud droplets at typical atmospheric supersaturations (D p ≳ 50 nm). Many cloud condensation nuclei (CCN) originate as ~1 nm nucleated particles that must grow to those threshold sizes before being lost to coagulation with larger particles. Though there is consensus that new particle formation and growth contributes significantly to total CCN concentrations, different groups using different models and assumptions have arrived at diverse estimates.

54 ENVIRONMENTAL SCIENCES↗