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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Multidecadal Changes in Near-Global Cloud Cover and Estimated Cloud Cover Radiative Forcing

The first paper was Multidecadal changes in near-global cloud cover and estimated cloud cover radiative forcing, by J. R. Norris (2005, J. Geophys. Res. - Atmos., 110, D08206, doi: lO.l029/2004JD005600). This study examined variability in zonal mean surface-observed upper-level (combined midlevel and high-level) and low-level cloud cover over land during 1971-1 996 and over ocean during 1952-1997. These data were averaged from individual synoptic reports in the Extended Edited Cloud Report Archive (EECRA). Although substantial interdecadal variability is present in the time series, long-term decreases in upper-level cloud cover occur over land and ocean at low and middle latitudes in both hemispheres. Near-global upper-level cloud cover declined by 1.5%-sky-cover over land between 1971 and 1996 and by 1.3%-sky-cover over ocean between 1952 and 1997. Consistency between EECRA upper-level cloud cover anomalies and those from the International Satellite Cloud Climatology Project (ISCCP) during 1984-1 997 suggests the surface-observed trends are real. The reduction in surface-observed upper-level cloud cover between the 1980s and 1990s is also consistent with the decadal increase in all-sky outgoing longwave radiation reported by the Earth Radiation Budget Satellite (EMS). Discrepancies occur between time series of EECRA and ISCCP low-level cloud cover due to identified and probable artifacts in satellite and surface cloud data. Radiative effects of surface-observed cloud cover anomalies, called "cloud cover radiative forcing (CCRF) anomalies," are estimated based on a linear relationship to climatological cloud radiative forcing per unit cloud cover. Zonal mean estimated longwave CCRF has decreased over most of the globe. Estimated shortwave CCRF has become slightly stronger over northern midlatitude oceans and slightly weaker over northern midlatitude land areas. A long-term decline in the magnitude of estimated shortwave CCRF occurs over low-latitude land and ocean, but comparison with EMS all-sky reflected shortwave radiation during 1985-1997 suggests this decrease may be underestimated.

Norris, Joel↗
NASA NTRS2023

Impacts of Marine Surface Pressure Observations From A Spaceborne Differential Absorption Radar Investigated With an Observing System Simulation Experiment

A new instrument has been proposed for measuring surface air pressure over the marine surface with a combined active/passive scanning multi-channel differential absorption radar (DAR) to provide an estimate of the total atmospheric column oxygen content. A demonstrator instrument, the Microwave Barometric Radar and Sounder (MBARS), has been funded by the National Aeronautics and Space Administration (NASA) for airborne test missions. Here, a proof-of-concept study to evaluate the potential impact of spaceborne surface pressure data on numerical weather prediction is performed using the Goddard Modeling and Assimilation Office global observing system simulation experiment (OSSE) framework. This OSSE framework employs the Goddard Earth Observing System model and the hybrid 4D ensemble variational Gridpoint Statistical Interpolation data assimilation system. Multiple flight and scanning configurations of potential spaceborne orbits are examined. Swath width and observation spacing for the surface pressure data are varied to explore a range of sampling strategies. For wider swaths, the addition of surface pressures reduces the root mean square surface pressure analysis error by as much as 20% over some ocean regions. The forecast sensitivity observation impact tool estimates impacts on the Pacific Ocean basin boundary layer 24-hour forecast temperatures for spaceborne surface pressures on par with rawinsondes and aircraft, and greater impacts than the current network of ships and buoys. The largest forecast impacts are found in the southern hemisphere extratropics.

N.C. Privé↗
NASA NTRS2008

The South American Land Data Assimilation System (SALDAS) 5-Year Retrospective Atmospheric Forcing Datasets

The definition and derivation of a 5-year, 0.125deg, 3-hourly atmospheric forcing dataset for the South America continent is described which is appropriate for use in a Land Data Assimilation System and which, because of the limited surface observational networks available in this region, uses remotely sensed data merged with surface observations as the basis for the precipitation and downward shortwave radiation fields. The quality of this data set is evaluated against available surface observations. There are regional difference in the biases for all variables in the dataset, with biases in precipitation of the order 0-1 mm/day and RMSE of 5-15 mm/day, biases in surface solar radiation of the order 10 W/sq m and RMSE of 20 W/sq m, positive biases in temperature typically between 0 and 4 K, depending on region, and positive biases in specific humidity around 2-3 g/Kg in tropical regions and negative biases around 1-2 g/Kg further south.

deGoncalves, Luis Gustavo G.↗
NASA NTRSDate not supplied

Impact of COVID-19 Restrictions on Atmospheric Concentrations of O3 and NO2 Across the Globe

We use a machine learning algorithm combining information from the NASA GEOS composition forecast (GEOS-CF) model and surface observations of nitrogen dioxide (NO2) and ozone (O3) at more than 5,000 observation sites to assess the impact of COVID-19 restrictions on surface air quality in 46 countries. Our methodology removes the compounding impacts of meteorology, seasonality and atmospheric chemistry on air pollution, thus allowing for a quantitative estimate of the change in surface air quality following COVID-19 containment measures. Compared to GEOS-CF model predictions that do not include emission reductions related to COVID-19 restrictions, surface observations show a drop in surface NO2 of up to 60% after the implementation of lockdowns. Average NO2 concentrations between February 2020 to June 2020 were 18% lower than business as usual. The earliest and strongest declines are observed over China, followed by Europe and the US. While NO2 concentrations over China recovered within 2 months, the recovery has been slower over Europe and the US. The impact of COVID-19 restrictions on O3 is complicated by non-linear atmospheric chemistry. Locally, O3 can show a short-term increase of up to 50% as a result of the decrease in NO2, which leads to a reduction in night time titration. However, this effect is offset by a decrease in photochemical production during the day. Our results indicate that these two competing processes resulted in a net zero change in average surface ozone during the first 5 months of the pandemic. The results also indicate that the reduced photochemical production becomes increasingly important over time. Our analysis is based on surface observations and model simulations available in near real-time, and we will present an up-to-date view of the short and medium-term impacts of COVID-19 restrictions on air quality around the world.

COVID-19↗
NASA NTRSDate not supplied

TPSAS-NF1676L-11678-DND

Cloud vertical profiles retrieved from CALIPSO and CloudSat data provide additional information that greatly improves the estimate of atmospheric radiative heating rates and potentially improves the estimate of the global surface radiation budget. To utilize CALIPSO and CloudSat cloud vertical profiles, we combined their profiles and generated merged profiles. Weused the merged cloud profiles and MODIS derived cloud profiles by the CERES cloud algorithm in irradiance computations. In this study, the improvement of the irradiance by CALIPSO and CloudSat derived merged cloud vertical profiles is evaluated by comparing modeled irradiances with and without merged cloud profiles. Because of lower cloud base heights provided by the merged profiles compared with cloud base heights derived from an empirical formula using the MODIS derived cloud top height and optical thickness, the global annual mean surface longwave downward irradiance increases approximately by 7 Wm-2. While CALIPSO version 3 data have not been incorporated in the irradiance computation and the effect of the new CALIPSO data needs to be assessed, a comparison with surface observations suggests an improvement of surface downward longwave irradiance computations. The surface downward longwave irradiance computed with CALIPSO and CloudSat merged clouds agrees better with surface observations than the irradiance computed with MODIS only does. The bias difference over ARM SGP sites with 2 years of data decreases from -5 W m-2to -2 Wm-2, and it decreases from -9 Wm-2to no bias over polar validation sites. The result suggests that CALIPSO CloudSat derived merged clouds significantly improve surface longwave irradiance estimates once they are combined with MODIS derived cloud properties and with temperature and humidity profiles from reanalysis.

Seiji Kato↗
NASA NTRS1991

Analysis of a general circulation model simulation of the atmospheric response to the observed sea surface temperature anomalies of January and February 1983

A new version of the Goddard Laboratory for Atmospheres GCM is utilized to simulate the influence of an observed sea surface temperature anomaly on rainfall and atmospheric circulation. The model can reproduce many essential features of the observed tropical rainfall and circulation anomalies during January-February 1983. Particularly, the model simulates realistic patterns of tropical anomalies of sea level pressure, 200 mb geopotential heights, and horizontal winds at the 200 and 850 mb levels. The model-simulated tropical precipitation anomaly patterns appear realistic, although the precipitation is rather excessive and the atmosphere is too energetic.

Sud, Y. C.↗
NASA NTRS1989

The Kelvin-Helmholtz instability at the magnetopause and inner boundary layer surface

Observations by the vector electron spectrometer on the ISEE 1 spacecraft are used to directly check the incompressible hydromagnetic stability condition given by Hasegawa (1975), which indicates how stability is influenced by the velocity shear, density ratio, magnetic field, and the direction of the wave vector of the unstable wave mode. The magnetopause is generally found to be stable, by a large margin. In contrast, many cases of marginal stability or instability are found across density transitions in, and at the inner edge of, the boundary layer for wave vectors in plausible directions. It thus appears that the Kelvin-Helmholtz instability is of importance at the inner edge of the magnetospheric boundary layer, as predicted by MHP theory.

Ogilvie, Keith W.↗
NASA NTRSDate not supplied

Update on Earth Skin Temperature Monitoring From 16 Years of IASI Satellite Observations

Surface parameters such as emissivity and skin temperature have been retrieved from IASI measurements of last 16 years. Monthly and spatially gridded surface skin temperature is produced to show the phenomena of its natural variability, which is also reflected in the surface emissivity and/or soil moisture content derived from the same time series of measurements. The anomalies of surface skin temperature are used to estimate its trend. The IASI global surface skin temperature trend is comparable with the NASA GISTEMP5 global surface air temperature trend. The trend of IASI global surface skin temperature reports that an approximate 0.027 K/yr. increase has evolved during 2007–2023. Attention has been given to the arctic region where an average warming rate is near 3 times higher than the global average. In some arctic regions, the rapid warming rate has reached 0.2-0.3 K/yr. which is about 10 times higher than the global average. Geophysical distribution of the surface temperature trend in the arctic region is emphasized and reported.

Global warming↗
NASA NTRS2018

Impact of Aquarius and SMAP Sea Surface Salinity Observations on Seasonal Predictions of the 2015 El Nino

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts for the big 2015 El Nino event. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP (Soil Moisture Active Passive Mission), allows a unique opportunity to compare and contrast forecasts generated with the benefit of these two satellite SSS observation types. Four distinct experiments are presented that include 1) freely evolving model SSS (i.e. no satellite SSS), relaxation to 2) climatological SSS (i.e. WOA13 SSS), 3) Aquarius, and 4) SMAP initialization. Coupled hindcasts are then generated from these initial conditions for March 2015. These forecasts are then validated against observations and evaluated with respect to the observed El Nino development.

Hackert, E.↗
NASA NTRS2018

Impact of Aquarius and SMAP Sea Surface Salinity Observations on Seasonal Predictions of the 2015 El Nino

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts for the big 2015 El Nino event. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast coupled forecasts generated with the benefit of these two satellite SSS observation types. Four distinct experiments are presented that include 1) freely evolving model SSS (i.e. no satellite SSS), relaxation to 2) climatological SSS (i.e. WOA13 (World Ocean Atlas 2013) SSS), 3) Aquarius and 4) SMAP initialization. Coupled hindcasts are generated from these initial conditions for March 2015. These forecasts are then validated against observations and evaluated with respect to the observed El Nino development.

Kovach, R.↗
NASA NTRS1990

Simulations of winter blocking episodes using observed sea surface temperatures

The formation of major Northern Hemisphere blockings during January 1979 is studied in numerical simulations of the global atmosphere with a sea surface temperature (SST) field updated with observations during the model integration. Both the standard 4 x 5 degrees latitude-longitude and high-resolution 2 x 2.5 degrees versions of the Goddard Laboratory for Atmospheres general circulation models (GCMs) are employed. The SST field is provided by a blend analysis of in situ and satellite-retrieved data. The simulations by the high-resolution GCM with a realistic SST field of the ocean surface are shown to be capable of producing two successive realistic major blockings in the Pacific and Atlantic through a one-month period. The skill in predicting the blocking formation as obtained in the simulations is due to improved skill in forecasting of ultralog waves. Although the results are encouraging, only one initial state is involved in this series of simulations; therefore, the results should not be generalized yet at this stage of investigation.

Kung, Ernest C.↗
DOE OSTI2024

The influence of cloud cover on the reliability of satellite-based solar resource data

Satellite-based solar resource data are often developed and validated by using binary cloudiness categories: clear sky or overcast cloudy sky. To investigate the reliability of solar resource data in partially cloudy conditions, we estimate cloud fraction using two distinct algorithms: a physical retrieval model using surface observed global horizontal irradiance (GHI) and direct normal irradiance (DNI) and a temporal average of cloud mask data estimated by the observed DNI. Our analysis reveals a significant presence of scattered clouds, broken clouds, and mismatches between satellite- and surface-based cloud data at 17 surface sites across the contiguous United States, though confidently clear and cloudy conditions collectively account for more than 70 % of the data. Solar radiation is computed using the National Solar Radiation Database (NSRDB) algorithm and validated using surface observations. Here, our findings suggest that, in the presence of scattered clouds, NSRDB data for clear-sky conditions can be subject to significant overestimation. In cloudy-sky conditions classified by satellite data, DNI computed by the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) can be underestimated when limited clouds are detected by surface observations. The bias observed in several cloudiness categories indicates that the NSRDB is exceptionally accurate in confidently clear conditions. However, clear-sky conditions with scattered clouds and mismatched cloud data contribute significantly to the overall uncertainties in the NSRDB. Therefore, future improvements in solar resource data should involve development and implementation of satellite-derived cloud fraction and should consider a novel radiative transfer model accounting for amplified cloud reflection. The evaluation within cloudiness categories also provides a physical rationale for the superior performance of FARMS-DNI compared to the Direct Insolation Simulation Code (DISC) in both cloudy-sky and all-sky conditions.

14 SOLAR ENERGY↗
NASA NTRS2020

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the NASA/GMAO Seasonal Forecast System

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts. Assimilation of SSS improves the mixed layer depth (MLD) and modulates the Kelvin waves associated with ENSO. In column 2, the initialization differences between experiments that assimilate SSS minus those withholding SSS assimilation are presented. Column 3 shows examples of forecasts generated for the different phases of ENSO assimilating the different satellite SSS. In general, for all phases of ENSO, SSS assimilation improves forecasts. The far right column compares ensemble means for assimilation of individual and combined SMOS, Aquarius, and SMAP SSS forecasts. Finally, the latest forecasts are presented comparing assimilation versus no- assimilation of satellite SSS for single forecasts over the last year.

Hackert, E.↗
NASA NTRS2019

Impact of Aquarius and SMAP Satellite Sea Surface Salinity Observations on Coupled El Niño/Southern Oscillation Forecasts

This study demonstrates the positive impact of including gridded Aquarius and SMAP sea surface salinity (SSS) into initialization of coupled forecasts for the tropical Indo-Pacific. An experiment that assimilates conventional ocean observations serves as the control. In a separate experiment, Aquarius and SMAP satellite SSS are additionally assimilated into the control initialization. Analysis of the initialization differences with the control indicates that SSS assimilation causes a freshening and shallowing of the mixed layer depth (MLD) near the equator and enhanced Kelvin wave amplitude. For each month from September 2011 to September 2018, 12 month coupled ENSO forecasts are initialized from both the control and satellite SSS assimilation experiments. The experiment assimilating Aquarius and SMAP SSS significantly outperforms the control relative to observed NINO3.4 sea surface temperature anomalies. This work highlights the importance of inclusion of satellite SSS for improving the initialization ENSO coupled forecasts.

Hackert, Eric C.↗
NASA NTRS2018

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GEOS GMAO S2S Forecast System

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts. Assimilation of SSS improves the mixed layer depth (MLD) and modulates the Kelvin waves associated with ENSO. In column 2, the initialization differences between experiments that assimilate SSS minus those withholding SSS assimilation are presented. Column 3 shows examples of forecasts generated for the different phases of ENSO. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast coupled forecasts generated with the benefit of these two satellite SSS observation types. The far right column compares assimilation of Aquarius, SMAP and combined Aquaries and SMAP on forecasts for the 2015 El Nino.

ENSO↗
DOE OSTI2019

Aerosol Observing System Surface Meteorology (AOSMET) Instrument Handbook

The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Aerosol Observing System (AOS) surface meteorology instrument is an ancillary sensor that provides temperature, relative humidity, pressure, wind speed and direction, and precipitation data relevant to the AOS. It consists of a Vaisala WXT520 Weather Transmitter mounted on top of the AOS aerosol inlet, at a height of approximately 10 meters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Monthly Mean In Situ Surface Flux Observations Paired with Satellite-Derived and Reanalysis-Based Flux Data for the Great Lakes Region, 2001–2020

Surface radiative and turbulent heat fluxes over the Great Lakes strongly influence regional hydrological and meteorological processes, and their accurate representation is critical for numerical weather prediction and coupled atmosphere–lake modeling. However, direct flux observations are spatially sparse across the region, so gridded reanalysis and satellite-derived products are often used for climatological analyses and model evaluation despite differences in their flux representations. This dataset provides processed, quality-controlled, monthly mean surface flux observations from the Great Lakes Evaporation Network (GLEN), AmeriFlux, and the National Data Buoy Center, paired with spatiotemporally matched flux estimates from two reanalysis products, the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA5) and the Modern Era Reanalysis for Research and Applications, version 2 (MERRA-2), and two satellite-derived products, the Clouds and Earth's Radiant Energy Systems Energy Balanced and Filled (CERES-EBAF) and the Cloud, Albedo and Surface Radiation dataset from AVHRR data - Edition 3 (CLARA-A3). The dataset includes sixteen observational stations with variable temporal coverage within 2001–2020. For each station, a CSV file contains monthly time series of available flux variables, including surface downwelling shortwave radiation (SW), surface downwelling longwave radiation (LW), sensible heat (SH) flux, and latent heat flux (LH), alongside matched gridded product values where available. Columns in the CSV file correspond to different variables sourced from each dataset, with column titles structured as "{dataset}_{variable}". Columns with relevant metadata are also provided in each CSV file, including station latitude and longitude, monthly timestamps, and the name of the sourced observational data. These files are structured for direct use in common analysis tools, including Microsoft Excel, Python pandas, and Python matplotlib. This dataset supports climatological analysis of the Great Lakes regional surface energy budget, evaluation of satellite-derived and reanalysis-based flux products, and development or validation of flux representations in numerical weather prediction and coupled atmosphere–lake models.

Great Lakes↗
DOE OSTI2025

NCAR-RAL Surface Hydrometeorological Observation Network Data for LASSO-CACTI Overview Paper

This data set contains the 15 minute resolution surface meteorology and soils data from the 15 NCAR/RAL weather stations that were operated around central Argentina during the RELAMPAGO (Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations) Extended Observing Period (EOP). Data providence, citation, and acknowledgement This ARM data set is a copy of v1.0 of the NCAR data set obtained in June 2024 from https://doi.org/10.26023/KW8Z-F2WX-H0Y. The citation for the original data source is: Gochis, D., et al. 2019. NCAR-RAL Surface Hydrometeorological Observation Network Data. Version 1.0. UCAR/NCAR - Earth Observing Laboratory. https://doi.org/10.26023/KW8Z-F2WX-H0Y Accessed June 2024. In addition to the citation reference and any other acknowledgements, please acknowledge NCAR/EOL in your publications with text such as: “Data provided by NCAR/EOL under the sponsorship of the National Science Foundation. https://data.eol.ucar.edu/”

air temperature↗