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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Decomposition of Sources of Errors in Seasonal Streamflow Forecasting over the U.S. Sunbelt

Seasonal streamflow forecasts, contingent on climate information, can be utilized to ensure water supply for multiple uses including municipal demands, hydroelectric power generation, and for planning agricultural operations. However, uncertainties in the streamflow forecasts pose significant challenges in their utilization in real-time operations. In this study, we systematically decompose various sources of errors in developing seasonal streamflow forecasts from two Land Surface Models (LSMs) (Noah3.2 and CLM2), which are forced with downscaled and disaggregated climate forecasts. In particular, the study quantifies the relative contributions of the sources of errors from LSMs, climate forecasts, and downscaling/disaggregation techniques in developing seasonal streamflow forecast. For this purpose, three month ahead seasonal precipitation forecasts from the ECHAM4.5 general circulation model (GCM) were statistically downscaled from 2.8deg to 1/8deg spatial resolution using principal component regression (PCR) and then temporally disaggregated from monthly to daily time step using kernel-nearest neighbor (K-NN) approach. For other climatic forcings, excluding precipitation, we considered the North American Land Data Assimilation System version 2 (NLDAS-2) hourly climatology over the years 1979 to 2010. Then the selected LSMs were forced with precipitation forecasts and NLDAS-2 hourly climatology to develop retrospective seasonal streamflow forecasts over a period of 20 years (1991-2010). Finally, the performance of LSMs in forecasting streamflow under different schemes was analyzed to quantify the relative contribution of various sources of errors in developing seasonal streamflow forecast. Our results indicate that the most dominant source of errors during winter and fall seasons is the errors due to ECHAM4.5 precipitation forecasts, while temporal disaggregation scheme contributes to maximum errors during summer season.

Decomposition↗
NASA NTRS2017

The Regional Influence of the Arctic Oscillation and Arctic Dipole on the Wintertime Arctic Surface Radiation Budget and Sea Ice Growth

An analysis of 2000-2015 monthly Clouds and the Earth's Radiant Energy System-Energy Balanced and Filled (CERES-EBAF) and Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA2) data reveals statistically significant fall and wintertime relationships between Arctic surface longwave (LW) radiative flux anomalies and the Arctic Oscillation (AO) and Arctic Dipole (AD). Signifying a substantial regional imprint, a negative AD index corresponds with positive downwelling clear-sky LW flux anomalies (greater than10W m(exp -2)) north of western Eurasia (0 deg E-120 deg E) and reduced sea ice growth in the Barents and Kara Seas in November-February. Conversely, a positive AO index coincides with negative clear-sky LW flux anomalies and minimal sea ice growth change in October-November across the Arctic. Increased (decreased) atmospheric temperature and water vapor coincide with the largest positive (negative) clear-sky flux anomalies. Positive surface LW cloud radiative effect anomalies also accompany the negative AD index in December-February. The results highlight a potential pathway by which Arctic atmospheric variability influences the regional surface radiation budget over areas of Arctic sea ice growth.

Hegyi, Bradley M.↗
NASA NTRS2018

File Specification for M2AMIP Products: Version Number - 1.0

The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is an atmospheric reanalysis computed with the Goddard Earth Observing (EOS) System, Version 5.12.4 (GEOS) data assimilation system (Gelaro et al., 2017). To supplement the reanalysis, the GEOS General Circulation Model (GCM) used in MERRA-2 has been used to generate a 10-member ensemble of simulations, configured following the convention of the Atmospheric Model Intercomparison Project (AMIP; Gates et al., 1992). Each ensemble member was initialized using meteorological fields from a different date in November 1979. The AMIP simulations used the sea-surface temperature (SST) and sea-ice boundary conditions that were used in MERRA-2 (Bosilovich et al., 2016). This 10-member ensemble of AMIP simulations, denoted M2AMIP, is available for download in a group of self-describing files, which are documented in this office note. All data collections are provided on the same horizontal grid as MERRA-2. This grid has 576 points in the longitudinal direction and 361 points in the latitudinal direction, corresponding to a resolution of 0.625 degrees by 0.5 degrees. Although data collections are available at this grid, all fields are computed on a cubed-sphere grid with an approximate resolution of 50 km by 50 km and are then spatially interpolated to the latitude-longitude grid. There are no changes in the vertical grids used: variables are provided on either the native vertical grid of 72 model layers, or interpolated to 42 standard pressure levels. Unlike MERRA, no data collections are available at the vertical layer edges. More details on the grid are provided in Section 4. MERRA-2 introduced observation-based precipitation forcing for the land surface parameterization and the corresponding variable PRECTOTCORR in the MERRA-2 FLX (surface turbulent fluxes and related quantities) and LFO (land-surface forcing) collections (see Section 6; Reichle et al., 2017). While this variable is still available for M2AMIP, there was no observation-based forcing, making the value identical to the model derived precipitation, PRECTOT. Similarly, without data assimilation, the values for the analysis increments, D*DTANA, in the tendency and vertically integrated file collections are zero. The M2AMIP data are available for download online through the NASA Center for Climate Simulation (NCCS) DataPortal (https://portal.nccs.nasa.gov/datashare/gmao_m2amip/). Data are arranged in subdirectories based on ensemble member, followed by year and month. Control files that are compatible with the Grid Analysis and Display System (GrADS) are available in the ctl_daily and ctl_monthly directories for the hourly, three hourly, and monthly mean data. Control files for the monthly mean diurnal cycle can be found in the ctl_diurnal subdirectory within the directory for each individual ensemble member.

M2AMIP↗
NASA NTRS2020

Evaluation of long-term Northern Hemisphere snow water equivalent products

Nine gridded Northern Hemisphere snow water equivalent (SWE) products were evaluated as part of the European Space Agency (ESA) Satellite Snow Product Intercomparison and Evaluation Exercise (SnowPEx). Three categories of datasets were assessed: (1) those utilizing some form of reanalysis (the NASA Global Land Data Assimilation System version 2 – GLDAS-2; the European Centre for Medium-Range Weather Forecasts (ECMWF) interim land surface reanalysis – ERA-Interim/Land and ERA5; the NASA Modern-Era Retrospective Analysis for Research and Applications version 1 (MERRA) and version 2 (MERRA-2); the Crocus snow model driven by ERA-Interim meteorology – Crocus); (2) passive microwave remote sensing combined with daily surface snow depth observations (ESA GlobSnow v2.0); and (3) stand-alone passive microwave retrievals (NASA AMSR-E SWE versions 1.0 and 2.0) which do not utilize surface snow observations. Evaluation included validation against independent snow course measurements from Russia, Finland, and Canada and product intercomparison through the calculation of spatial and temporal correlations in SWE anomalies. The stand-alone passive microwave SWE products (AMSR-E v1.0 and v2.0 SWE) exhibit low spatial and temporal correlations to other products and RMSE nearly double the best performing product. Constraining passive microwave retrievals with surface observations (GlobSnow) provides performance comparable to the reanalysis-based products; RMSE over Finland and Russia for all but the AMSR-E products is ∼50 mm or less, with the exception of ERA-Interim/Land over Russia. Using a seven-dataset ensemble that excluded the stand-alone passive microwave products reduced the RMSE by 10 mm (20 %) and increased the correlation from 0.67 to 0.78 compared to any individual product. The overall performance of the best multiproduct combinations is still at the margins of acceptable uncertainty for scientific and operational requirements; only through combined and integrated improvements in remote sensing, modeling, and observations will real progress in SWE product development be achieved.

Northern Hemisphere snow water equivalent (SWE) pr↗
NASA NTRSDate not supplied

Evaluating the SAGE III/ISS Version 5.2 Water Vapor Retrieval in the Presence of Aerosol Loading

The Stratospheric Aerosol and Gas Experiment operating on the International Space Station (SAGE III/ISS) is an occultation instrument that retrieves aerosol extinction and ozone, water vapor, and other trace gas concentrations. Water vapor in the stratosphere plays a role in ozone depletion and global temperature regulation making it an important species to monitor. The SAGE III/ISS instrument provides high quality, vertically resolved profiles of water vapor throughout the stratosphere and upper troposphere. In previous versions of SAGE water vapor products, a dry bias was noted in comparison to other satellite retrievals in the presence of elevated aerosol optical depth. Several updates for the version 5.2 water vapor algorithm will be presented and compared with previous versions of the data and other satellite products during different periods of aerosol loading.

M Heitz↗
NASA NTRS2021

Accuracy Assessment of Global Internal-Tide Models Using Satellite Altimetry Models Using Satellite Altimetry

Altimeter measurements are corrected for several geophysical parameters in order to access ocean signals of interest, like mesoscale or sub-mesoscale variability. The ocean tide is one of the most critical corrections due to the amplitude of the tidal elevations and to the aliasing phenomena of high-frequency signals into the lower-frequency band, but the internal-tide signatures at the ocean surface are not yet corrected globally. Internal tides can have a signature of several centimeters at the surface with wavelengths of about 50–250 km for the first mode and even smaller scales for higher-order modes. The goals of the upcoming Surface Water Ocean Topography (SWOT) mission and other high-resolution ocean measurements make the correction of these small-scale signals a challenge, as the correction of all tidal variability becomes mandatory to access accurate measurements of other oceanic signals. In this context, several scientific teams are working on the development of new internal-tide models, taking advantage of the very long altimeter time series now available, which represent an unprecedented and valuable global ocean database. The internal-tide models presented here focus on the coherent internal-tide signal and they are of three types: empirical models based upon analysis of existing altimeter missions, an assimilative model and a three-dimensional hydrodynamic model. A detailed comparison and validation of these internal-tide models is proposed using existing satellite altimeter databases. The analysis focuses on the four main tidal constituents: M2, K1, O1 and S2. The validation process is based on a statistical analysis of multi-mission altimetry including Jason-2 and Cryosphere Satellite-2 data. The results show a significant altimeter variance reduction when using internal-tide corrections in all ocean regions where internal tides are generating or propagating. A complementary spectral analysis also gives some estimation of the performance of each model as a function of wavelength and some insight into the residual non-stationary part of internal tides in the different regions of interest. This work led to the implementation of a new internal-tide correction (ZARON'one) in the next geophysical data records version-F (GDR-F) standards.

Loren Carrere↗
NASA NTRS2021

Deep Space Observations of Terrestrial Glitter

Deep space climate observatory (DSCOVR) spacecraft drifts about the Lagrangian point ≈1.4–1.6 × 106 km from Earth, where its Earth polychromatic imaging camera (EPIC) observes the sun-lit face of the Earth every 1 to 2 hours. At any instance, there is a preferred (specular) spot on the globe, where a glint may be observed by EPIC. While monitoring reflectance at these spots (terrestrial glitter), we observe occasional intense glints originating from neither ocean surface nor cloud ice and we argue that mountain lakes high in the Andes are among the causes. We also examine time-averaged reflectance at the spots and find it exceeding that of neighbors, with the excess monotonically increasing with separation distance. This specular excess is found in all channels and is more pronounced in the latest and best-calibrated version of EPIC data, thus opening the possibility of testing geometric calibration by monitoring distant glitter.

DSCOVR↗
NASA NTRS2023

The Gmao Hybrid 4d-Envar Observing System Simulation Experiment Framework.

This work describes the extension of the Global Modeling and Assimilation Office (GMAO) Observing System Simulation Experiment (OSSE) framework to use a hybrid 4D-EnVar scheme instead of 3D-Var. The original 3D-Var and hybrid 4D-EnVar OSSEs use the same version of the data assimilation system (DAS) so that a direct comparison is possible in terms of the validation with respect to their corresponding real cases. Rather than quantifying the differences between the two data assimilation methodologies, a short inter-comparison of upgrading from a 3D- to a 4D-OSSE is provided to highlight aspects where this change matters to the OSSE community and to identify features of data assimilation that can only be explored in a four-dimensional OSSE framework. A short validation of the hybrid 4D-EnVar OSSE shows that conclusions from previous assessments of the 3D-Var OSSE in its ability to mimic the behavior of the real system still hold with the same caveats. Furthermore, some aspects of the ensemble configuration and behavior are discussed along with forecast sensitivity to observation impacts (FSOI). Estimates of error standard deviations are shown to be smaller in the hybrid 4D-EnVar OSSE but with little impact on the character of the error. A discussion on future work directions focuses on exploring the four-dimensional aspect such as the error distribution within the assimilation window or four-dimensional handling of high-temporal density observations.

Data assimilation↗
NASA NTRSDate not supplied

Quantitative Assessment of the HLS Surface Reflectance Consistency

The Harmonized Landsat and Sentinel-2 (HLS) project produces compatible surface reflectance (SR) from observations acquired by Landsat-8/9 OLI and Sentinel-2A/2B MSI. The HLS harmonization procedures include atmosphere correction, cloud masking, view angle normalization, and bandpass adjustment. The objective of this study is to quantitatively assess the reflectance consistency between Landsat and Sentinel-2 within the Version 2 HLS data. We collected 545 pairs of same-day Landsat/Sentinel-2 images across the globe to represent a wide range of vegetation types and climate regimes. The mean absolute difference (MAD) in reflectance between Landat and Sentinel-2 was calculated as a consistency indicator for each harmonization step. The MAD generally increased after the atmosphere correction, and then greatly decreased after the BRDF and bandpass adjustments, to smaller than the top-of-atmosphere MAD values. The MAD ranged from 0.0048 to 0.0093 for the six common spectral bands (blue, green, red, NIR, SWIR1, and SWIR2) in the final products, only slightly greater than the difference between Landsat and Sentinel-2 calibrations.. An evaluation on a few commonly used vegetation indices also showed good agreement between Landsat and Sentinel-2 reflectance. All these evaluations demonstrate that the HLS project produces a consistent SR dataset from Landsat-OLI and Sentinel-MSI, which will be a valuable resource for a wide range of remote sensing applications.

Qiang Zhou↗
NASA NTRS2017

Version 3 of the SMAP Level 4 Soil Moisture Product

The NASA Soil Moisture Active Passive (SMAP) Level 4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root zone (0-100 cm) soil moisture as well as related land surface states and fluxes from 31 March 2015 to present with a latency of 2.5 days. The ensemble-based L4_SM algorithm is a variant of the Goddard Earth Observing System version 5 (GEOS-5) land data assimilation system and ingests SMAP L-band (1.4 GHz) Level 1 brightness temperature observations into the Catchment land surface model. The soil moisture analysis is non-local (spatially distributed), performs downscaling from the 36-km resolution of the observations to that of the model, and respects the relative uncertainties of the modeled and observed brightness temperatures. Prior to assimilation, a climatological rescaling is applied to the assimilated brightness temperatures using a 6 year record of SMOS observations. A new feature in Version 3 of the L4_SM data product is the use of 2 years of SMAP observations for rescaling where SMOS observations are not available because of radio frequency interference, which expands the impact of SMAP observations on the L4_SM estimates into large regions of northern Africa and Asia. This presentation investigates the performance and data assimilation diagnostics of the Version 3 L4_SM data product. The L4_SM soil moisture estimates meet the 0.04 m3m3 (unbiased) RMSE requirement. We further demonstrate that there is little bias in the soil moisture analysis. Finally, we illustrate where the assimilation system overestimates or underestimates the actual errors in the system.

GEOS-↗
NASA NTRS1993

Federal Communications Commission (FCC) Transponder Loading Data Conversion Software. User's guide and software maintenance manual, version 1.2

This volume contains the complete software system documentation for the Federal Communications Commission (FCC) Transponder Loading Data Conversion Software (FIX-FCC). This software was written to facilitate the formatting and conversion of FCC Transponder Occupancy (Loading) Data before it is loaded into the NASA Geosynchronous Satellite Orbital Statistics Database System (GSOSTATS). The information that FCC supplies NASA is in report form and must be converted into a form readable by the database management software used in the GSOSTATS application. Both the User's Guide and Software Maintenance Manual are contained in this document. This volume of documentation passed an independent quality assurance review and certification by the Product Assurance and Security Office of the Planning Research Corporation (PRC). The manuals were reviewed for format, content, and readability. The Software Management and Assurance Program (SMAP) life cycle and documentation standards were used in the development of this document. Accordingly, these standards were used in the review. Refer to the System/Software Test/Product Assurance Report for the Geosynchronous Satellite Orbital Statistics Database System (GSOSTATS) for additional information.

Mallasch, Paul G.↗
DOE OSTI2024

Cracked Gridline Wear Out Follows a Power Law

Cracks can form in Silicon solar cells in photovoltaic modules due to mechanical stresses arising from various extrinsic factors like handling and weather. While the immediate performance degradation may be minor, continuous loading overtime will degrade module performance. One probable reason is gridline surface wear across the cracked silicon with increased cyclic loading. In this work we propose a method to correlate gridline wear to module electrical degradation. We begin by conducting cyclic four-point bending tests on laminated silicon solar cells with a single crack and 22 intact gridlines for 10,000 cycles. We measure the progressive change in resistance during each loading cycle. We correlate it to a length scale called critical crack opening displacement (CCOD) that signifies failure of individual gridlines. By employing Weibull analysis, we determine the characteristic CCOD for all cycles and fit this data to a modified version of a wear power law. We observe that this i ts the data well. We also propose to study the effect of individual parameters in the power law equation and extend the equation to include material properties.

bending↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-Snf Sherman Barn

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Snf Sherman Barn. This is the FLUXNET version of the carbon flux data for the site US-Snf Sherman Barn produced by applying the standard ONEFlux (1F) software. Site Description - The Sherman Barn is pasture site on Sherman Island, that is managed by the California Department of Water Resources (DWR). A flux tower equipped to analyze energy, H2O, CO2, and CH4 fluxes was installed on June, 2018

Kusak, Kuno↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-Myb Mayberry Wetland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Myb Mayberry Wetland. This is the FLUXNET version of the carbon flux data for the site US-Myb Mayberry Wetland produced by applying the standard ONEFlux (1F) software. Site Description - The Mayberry Wetland site is a 300-acre restored wetland on Sherman Island, north of Mayberry Slough, that is on the property of Mayberry Farms and managed by the California Department of Water Resources and Ducks Unlimited. During Summer 2010, the site was restored from a pepperweed and annual grassland pasture to a wetland through a project managed by Bryan Brock (bpbrock@water.ca.gov). A flux tower equipped to analyze energy, H2O, CO2, and CH4 fluxes was installed on October 14, 2010. At the time of installation, flooding of the site had only recently begun after extensive reconstruction of the wetland bathymetry conducted during the summer. Although some small patches of tules remain within the site, the site is a patchwork of deep and shallow open water with some remaining vegetation. Currently, there is an intention to flood-to-kill the current pepperweed and upland grasses and let the wetland plants propagate naturally, so no additional plant manipulation will occur.

Matthes, Jaclyn Hatala↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-Ro1 Rosemount- G21

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ro1 Rosemount- G21. This is the FLUXNET version of the carbon flux data for the site US-Ro1 Rosemount- G21 produced by applying the standard ONEFlux (1F) software. Site Description - This tower is located in a farm field farmed in accordance with the dominant farming practice in the region: a corn/soybean rotation with chisel plow tillage in the fall following corn harvest and in the spring following soybeans.

Baker, John↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-Ro4 Rosemount Prairie

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ro4 Rosemount Prairie. This is the FLUXNET version of the carbon flux data for the site US-Ro4 Rosemount Prairie produced by applying the standard ONEFlux (1F) software. Site Description - This tower is located in restored prairie in a former agricultural area. Dominant species include Andropogon gerardii, Sorghastrum nutans and Elymus canadensis

Baker, John↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-Tw2 Twitchell Corn

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Tw2 Twitchell Corn. This is the FLUXNET version of the carbon flux data for the site US-Tw2 Twitchell Corn produced by applying the standard ONEFlux (1F) software. Site Description - The Twitchell Corn site is a corn field on peat soil. The tower was installed on May 17, 2012 and was equipped to analyze energy, H2O and CO2 fluxes. The field was planted in early May 2012 and harvested in early November 2012. The field was fallow during the non-growing season. The variety of corn used was ES-7477 hybrid corn commercialized by Eureka seeds. Beginning 2013-05-09 this site was converted to wetland. The tower was moved 540m ESE to avoid earth moving in the construction. The site is near US-Tw1, US-Tw3 and US-Twt sites.

Sturtevant, Cove↗