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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Model estimates of dissolved organic carbon, runoff, snowmelt, and snow water equivalent from 1981-2010 across the western Arctic

This dataset contains estimates of dissolved organic carbon (DOC) yield (mg C m-2), runoff (mm day-1), snow water equivalent (SWE, mm day-1), and snowmelt (mm day-1) from a simulation of the Permafrost Water Balance Model (PWBM v4). The simulation effectively quantifies snowpack accumulation and melt, runoff, and DOC leaching, and broadly capture the seasonal cycle in DOC concentration and mass loadings. Daily air temperature, precipitation, and wind speed data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) were used for meteorological forcings. The model outputs are organized by grid and day of the month in gzipped ASCII text files contained within each archived ZIP file. No special software is required to work with these data. The basin and domain information files are also ASCII text. The gridded estimates are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and leachate DOC concentrations and loadings across parts of the western Arctic. A manuscript describing the data and associated analysis has been accepted for publication in Journal of Geophysical Research - Biogeosciences (Rawlins et al., 2021).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Space-Based Remote Sensing of Atmospheric Aerosols: The Multi-Angle Spectro-Polarimetric Frontier

The review of optical instrumentation, forward modeling, and inverse problem solution for the polarimetric aerosol remote sensing from space is presented. The special emphasis is given to the description of current airborne and satellite imaging polarimeters and also to modern satellite aerosol retrieval algorithms based on the measurements of the Stokes vector of reflected solar light as detected on a satellite. Various underlying surface reflectance models are discussed and evaluated.

polarimetry↗
DOE OSTI2021

The three-dimensional construction of leaves is coordinated with water use efficiency in conifers

Conifers prevail in the canopies of many terrestrial biomes, holding a great ecological and economic importance globally. Current increases in temperature and aridity are imposing high transpirational demands and resulting in conifer mortality. Therefore, identifying leaf structural determinants of water use efficiency is essential for predicting physiological impacts due to environmental variation. Here, using synchrotron-generated microtomography imaging, we extracted leaf volumetric anatomy and stomatal traits in 34 species across conifers with a special focus on Pinus , the richest conifer genus. We show that intrinsic water use efficiency (WUE i ) is positively driven by leaf vein volume. Needle-like leaves of Pinus , as opposed to flat leaves or flattened needles of other genera, showed lower mesophyll porosity, decreasing the relative mesophyll volume. This led to increased ratios of stomatal pore number per mesophyll or intercellular airspace volume, which emerged as powerful explanatory variables, predicting both stomatal conductance and WUE i . Our results clarify how the three-dimensional organisation of tissues within the leaf has a direct impact on plant water use and carbon uptake. By identifying a suite of structural traits that influence important physiological functions, our findings can help to understand how conifers may respond to the pressures exerted by climate change.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Overview of the SPARC Reanalysis Intercomparison Project (S-RIP) during 2013-2020

The Stratosphere-troposphere Processes And their Role in Climate (SPARC) project is one of the four core projects of the World Climate Research Programme (WCRP). Researchers interested in SPARC use global atmospheric reanalysis products to understand a wide range of processes and variability in the atmosphere, to validate chemistry climate models, and to investigate and identify climate change. The SPARC Reanalysis Intercomparison Project (S-RIP) was initiated in 2011 and officially started in 2013 to conduct a coordinated intercomparison of all major global atmospheric reanalysis data sets. The S-RIP has been aiming at writing up an assessment report in the SPARC report series (to be published by the end of 2020) (1) on overall quality of temperature, winds, ozone, and water vapor data, (2) on more process- and region-oriented evaluation of the Brewer–Dobson circulation, extratropical stratosphere-troposphere coupling, extratropical upper troposphere and lower stratosphere, the tropical tropopause layer, the quasi-biennial oscillation, polar processes, and the upper stratosphere and lower mesosphere, and (3) with a coordinated description of the reanalysis systems. We also have an inter-journal special issue on "The SPARC Reanalysis Intercomparison Project (S-RIP)" in Atmospheric Chemistry and Physics (ACP) and Earth System Science Data (ESSD). In the presentation, we will discuss key findings and recommendations as well as the evaluation of this rst phase of the S-RIP activity.

Masatomo Fujiwara↗
NASA NTRSDate not supplied

All-sky Microwave Radiance Assimilation in The GEOS Atmospheric Reanalysis for The Early 21st Century (GEOS-21C)

The Goddard Earth Observing System (GEOS) is used for weather, climate, and air quality forecasts and producing reanalysis datasets. Its atmospheric data assimilation system (ADAS) is a hybrid–4DEnVar system. Various satellite radiance, atmospheric motion vector (winds), aircraft, and convectional data are assimilated by this system to produce global atmospheric states. Satellite data assimilation within GEOS ADAS is enhanced by considering correlated observational errors among infrared radiance observations and assimilating new microwave radiance data in all-sky conditions since the release of the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). These new microwave radiance data include brightness temperature measurements made by the Global Precipitation Mission (GPM) microwave imager (GMI) and Advanced Microwave Scanning Radiometer 2 / Global Change Observation Mission 1st – Water (AMSR2/GCOM-W). Historical microwave radiance data made by various Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) aboard the Aqua satellite are tested within the all-sky microwave radiance assimilation framework in the preparation of the GEOS enhanced Atmospheric Reanalysis for the early 21st century (GEOS-21C). Assimilation of these data in all-sky conditions enhances use of other satellite data and improves GEOS analysis and forecast. In this talk, we will present the procedures of to assimilate microwave radiance data in all-sky conditions and their impact on atmospheric analysis in the preparation of GEOS-21C.

Jianjun Jin↗
NASA NTRS2008

Nowcasting in the GPM Era

The Global Precipitation Measurement (GPM) Mission is an international satellite mission to unify and advance global precipitation measurements from a constellation of dedicated and operational microwave sensors. The GPM concept centers on the deployment of a Core Spacecraft in a non-Sun-synchronous orbit at 65deg inclination carrying a dual-frequency precipitation radar (DPR) and a multi-frequency passive microwave radiometer (GMI) with high-frequency capabilities to serve as a precipitation physics observatory and calibration standard for the constellation radiometers. The baseline GPM constellation is envisioned to comprise conical-scanning microwave imagers (e.g., GMI, SSMIS, AMSR, MIS, MADRAS, GPM-Brazil) augmented with cross-track microwave temperaturelhumidity sounders (e.g., MHS, ATMS) over land. In addition to the Core Satellite, the GPM Mission will contribute a second GMI to be flown in a low-inclination (approx.40deg) non-Sun-synchronous orbit to improve near real-time monitoring of hurricanes. GPM is a science mission with integrated applications goals aimed at (1) advancing the knowledge of the global waterlenergy cycle variability and freshwater availability and (2) improving weather, climate, and hydrological prediction capabilities through more accurate and frequent measurements of global precipitation. The GPM Mission is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA), with opportunities for additional partners in satellite constellation and ground validation activities. Within the framework of the inter-governmental Group ob Earth Observations (GEO) and Global Earth Observation System of Systems (GEOSS), GPM has been identified as a cornerstone for the Precipitation Constellation (PC) being developed under the auspices of Committee of Earth Observation Satellites (CEOS). The GPM Core Observatory is scheduled for launch in 201 3, followed by the launch of the GPM Low-Inclination Observatory in 2014. An overview of the GPM mission status, measurement capabilities, ground validation plans, and anticipated contributions to scientific research and societal applications with a special emphasis on nowcasting will be presented.

Hou, Arthur Y.↗
NASA NTRS2008

Nowcasting in the GPM Era

The Global Precipitation Measurement (GPM) Mission is an international satellite mission to unify and advance global precipitation measurements from a constellation of dedicated and operational microwave sensors. The GPM concept centers on the deployment of a Core Spacecraft in a non-Sun-synchronous orbit at 65' inclination carrying a dual-frequency precipitation radar (DPR) and a multi-frequency passive microwave radiometer (GMI) with high-frequency capabilities to serve as a precipitation physics observatory and calibration standard for the constellation radiometers. The baseline GPM constellation is envisioned to comprise conical-scanning microwave imagers (e.g., GMI, SSMIS, AMSR, MIS, MADRAS, GPM-Brazil) augmented with cross-track microwave temperaturelhumidity sounders (e.g., MHS, ATMS) over land. In addition to the Core Satellite, the GPM Mission will contribute a second GMI to be flown in a low-inclination (-40') non-Sun-synchronous orbit to improve near real-time monitoring of hurricanes. GPM is a science mission with integrated applications goals aimed at (1) advancing the knowledge of the global waterlenergy cycle variability and freshwater availability and (2) improving weather, climate, and hydrological prediction capabilities through more accurate and frequent measurements of global precipitation. The GPM Mission is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA), with opportunities for additional partners in satellite constellation and ground validation activities. Within the framework of the inter-governmental Group ob Earth Observations (GEO) and Global Earth Observation System of Systems (GEOSS), GPM has been identified as a cornerstone for the Precipitation Constellation (PC) being developed under the auspices of Committee of Earth Observation Satellites (CEOS). The GPM Core Observatory is scheduled for launch in 201 3, followed by the launch of the GPM Low-Inclination Observatory in 2014. An overview of the GPM mission status, measurement capabilities, ground validation plans, and anticipated contributions to scientific research and societal applications with a special emphasis on nowcasting will be presented.

Hou, Arthur Y.↗
NASA NTRS2018

The Best Educational Tool for Interdisciplinary Earth Science Giovanni

Accessing and using NASA Earth science data has commonly presented a challenge to many educators and students, due to issues such as heterogeneous data formats, complex data structures, large volumes of data storage, special programming requirements, and diverse analytical software options that often require a significant investment in time and resources, especially for novices. By facilitating data access and evaluation, as well as promoting open access to create a more level playing field for non-funded scientists, NASA Earth observation data can be more readily used for scientific discovery and societal benefits. To advance this goal, the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) developed the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni). To date, Giovanni has assisted researchers around the world publish over 1300 peer-reviewed papers in a wide range of Earth science disciplines. In this presentation, we will demonstrate how easy it is to use Giovanni for the rapid creation of many different analyses of both weather and climate events.

interdisciplinary↗
NASA NTRSDate not supplied

Particle Size Distribution Parameters from SAGE III/ISS Extinction Spectra

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on the relative abundance of different sized particles within the sample volume, often referred to as the particle size distribution (PSD). If the PSD is accurately known then other key modeling parameters (e.g., surface area density and effective radius) can be derived. Historically, occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts routinely failed to account for measurement uncertainty and lacked a rigorous estimate of the inferred PSD uncertainty. We carried out a series of simulations to evaluate the accuracy of these inferences and, for every valid SAGE III/ISS extinction spectrum, determined the range of PSD parameters that fell withing the bounds of the extinction error bars. Special application of this method was applied to estimate the impact of the 2022 Hunga Tonga eruption had on particle size distributions.

Travis N Knepp↗
NASA NTRS1996

On the search for extant life on Mars

Proposals for continuing the search for extant life on Mars are primarily predicated on the assumption that specialized environmental niches that could support a biota may exist on the planet. Before attempting any critical tests for extant organisms, either in situ or on returned samples, it is imperative to determine whether any such sites actually exist. If, through remote sensing and landed instrumentation, sites of potential biological interest are discovered and characterized, biological tests can then more effectively be planned to elicit the presence of organisms that are adapted to living in these particular environments.

NASA Discipline Exobiology↗
NASA NTRS2006

Water Vapor Sensors Go Sky-High to Assure Aircraft Safety

JPL used a special tunable diode laser, which NASA scientists could tune to different wavelengths, like a radio being tuned to different frequencies, to accurately target specific molecules and detect small traces of gas. This tunable diode laser was designed to emit near-infrared light at wavelengths absorbed by the gas or gases being detected. The light energy being absorbed by the target gas is related to the molecules present. This is usually measured in parts per million or parts per billion. Multiple measurements are made every second, making the system quick to respond to variations in the target gas. NASA scientists developed this technology as part of the 1999 Mars Polar Lander mission to explore the possibility of life-giving elements on Mars. NASA has since used the tunable diode laser-based gas sensor on aircraft and on balloons to successfully study weather and climate, global warming, emissions from aircraft, and numerous other areas where chemical gas analysis is needed. SpectraSensors, Inc., was formed in 1999 as a spinoff company of JPL, to commercialize tunable diode laser-based analyzers for industrial gas-sensing applications (Spinoff 2000). Now, the San Dimas, California-based firm has come back to the market with a new product featuring the NASA-developed instrument for atmospheric monitoring. This instrument is now helping aircraft avoid hazardous weather conditions and enabling the National Weather Service to provide more accurate weather forecasts.

Source record↗
NASA NTRS2000

Improving Global Reanalyses and Short Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a "1+1"D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the "1+1"D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+lD scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSM/I rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Hou, Arthur Y.↗
NASA NTRS2006

Fibonacci Grids

Recent years have seen a resurgence of interest in a variety of non-standard computational grids for global numerical prediction. The motivation has been to reduce problems associated with the converging meridians and the polar singularities of conventional regular latitude-longitude grids. A further impetus has come from the adoption of massively parallel computers, for which it is necessary to distribute work equitably across the processors; this is more practicable for some non-standard grids. Desirable attributes of a grid for high-order spatial finite differencing are: (i) geometrical regularity; (ii) a homogeneous and approximately isotropic spatial resolution; (iii) a low proportion of the grid points where the numerical procedures require special customization (such as near coordinate singularities or grid edges). One family of grid arrangements which, to our knowledge, has never before been applied to numerical weather prediction, but which appears to offer several technical advantages, are what we shall refer to as "Fibonacci grids". They can be thought of as mathematically ideal generalizations of the patterns occurring naturally in the spiral arrangements of seeds and fruit found in sunflower heads and pineapples (to give two of the many botanical examples). These grids possess virtually uniform and highly isotropic resolution, with an equal area for each grid point. There are only two compact singular regions on a sphere that require customized numerics. We demonstrate the practicality of these grids in shallow water simulations, and discuss the prospects for efficiently using these frameworks in three-dimensional semi-implicit and semi-Lagrangian weather prediction or climate models.

Swinbank, Richard↗
NASA NTRS1998

Surface-Wind Anomalies in North-Atlantic and North Pacific from SSM/I Observations: Influence on Temperature of Adjoining Land Regions

Surface winds over the oceans are derived from Special Sensor Microwave Imager (SSM/I) measurements, assigning direction by Variational Analysis Method (VAM). Validations by comparison with other measurements indicate highly-satisfactory data quality. Providing global coverage from 1988, the dataset is a convenient source for surface-wind climatology. In this study, the interannual variability of zonal winds is analyzed concentrating on the westerlies in North Atlantic and North Pacific, above 30 N. Interannual differences in the westerlies exceeding 10 m sec (exp -1) are observed over large regions, often accompanied by changes of the same magnitude in the easterlies below 30 N. We concentrate on February/March, since elevated temperatures, by advancing snow-melt, can produce early spring. The extremely strong westerlies in 1997 observed in these months over North Atlantic (and also North Pacific) apparently contributed to large surface-temperature anomalies in western Europe, on the order of +3 C above the climatic monthly average for England and France. At these latitudes strong positive anomalies extended in a ring around the globe. We formulated an Index of South westerlies for the North Atlantic, which can serve as an indicator for day-by-day advection effects into Europe. In comparing 1997 and 1998 with the previous years, we establish significant correlations with the temperature anomalies (one to five days later, depending on the region, and on the season). This variability of the ocean-surface winds and of the temperature anomalies on land may be related to the El Nino/La Nina oscillations. Such large temperature fluctuations over large areas, whatever the cause, can be regarded as noise in attempts to assess long-term trends in global temperature.

Otterman, Joseph↗
NASA NTRS1999

Improving Global Reanalyses and Short-Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a 1+1D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the 1+1D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSW rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Hou, Arthur Y.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10737-DND

The Clouds and the Earth's Radiant Energy System (CERES) project provides the community a quality climate TOA and surface fluxes and cloud properties and are key elements in evaluating the ability of climate models to predict both past and future climate states. One important aspect of successful climate monitoring is satellite calibration. The CERES instantaneous broadband calibration radiance stability is 0.1% per year, whereas the accuracy of the longwave (LW) and shortwave (SW) is better than 0.5% and 1% respectively. CERES uses the 3-hourly GEO fluxes and clouds to provide diurnally averaged daily and monthly TOA flux means from the CERES measurements onboard the Terra (10:30 AM local equator crossing time) and Aqua (13:30 PM) sun-synchronous satellites. The GEO radiances are calibrated against MODIS as a reference to provide consistent GEO retrieved cloud properties and derived broadband fluxes. These fluxes are then carefully normalized against the well-calibrated CERES fluxes to ensure climate quality fluxes, free of GEO artifacts. With the upcoming release of Edition3 products, CERES has just recalibrated all the CERES instruments to ensure that both Terra and Aqua fluxes are on the same radiometric scale and the removal of all known instrument trends. CERES will also recalibrate all GEO satellites using the entire GEO time record. CERES employs collocated, coincident ray-matched GEO/MODIS radiances as its primary technique, calibrating GEO radiances beginning in the year 2000. The advantage of the ray-matching technique is that it provides a full dynamic range of radiances to check the linearity of the GEO visible instrument. CERES uses deep convective clouds and invariant desert sites to validate the primary technique. All three methods can assess the stability of the GEO visible instrument. Examples of the CERES GEO calibration techniques and validation efforts will be shown at the conference. Special emphasis will be given to the newly incorporated desert site methodology.

R. Bhatt↗
NASA NTRS2004

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special but not exclusive look at the latest earth observing mission, Aura.

King, Michael D.↗
NASA NTRS2005

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by whch scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special look at the latest earth observing mission, Aura.

King, Michael D.↗