Results for “Sounder Data” — Page 33

NASA NTRS2019

Planetary Boundary Layer Height from AIRS, MERRA-2, and GPS Radio Occultation Data Products at NASA GES DISC, and Insights from Their Profiles Intercomparison

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides archive and distribution services for several data products in the Planetary Boundary Layer (PBL) category. As a new variable added to the Atmospheric Infrared Sounder (AIRS) Version 6 support product, the PBL height from AIRS is derived based on the gradients of the retrieved relative humidity profile, and provides the atmospheric pressure at the top of the PBL over the ocean. The GES DISC also hosts the Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) product generated by the Goddard Earth Observing System Model Version 5 (GEOS-5) data assimilation system. The PBL height from MERRA-2 is based on the total eddy diffusion coefficient of heat. The monthly PBL height has been made available in the Giovanni system (Giovanni is a Web-based application developed by the GES DISC providing a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data). Recently, the GES DISC began serving the global PBL height climatology product derived from the COSMIC/FORMOSAT-3 and TerraSAR-X Global Positioning System (GPS) radio occultation (RO) measurements from June 2006 to December 2015. In a previous study, we presented the monthly PBL height data from AIRS and MERRA-2 and demonstrated the GES DISC services which support data intercomparison, such as access, plotting, sub-setting, regridding, and generation of a multi-year monthly mean. We also provided intercomparison results, and found that different PBL height definitions contributed to significant differences of PBL height values between AIRS and MERRA-2. In this work, we present the 10-year seasonal climatologies from the AIRS, MERRA-2 and GPS-RO. We also used the cross section and vertical profile services in Giovanni to display and analyze the vertical atmosphere structure over regions where the PBL height derived from the AIRS and MERRA-2 are quite different. The examination of the AIRS and MERRA-2 three-dimensional data found that the relative humidity profiles had larger differences than the temperature profiles. The MERRA-2 gives more details than the AIRS for the vertical distribution of the humidity.

Ding, Feng↗

NASA NTRS2006

Processing EOS MLS Level-2 Data

A computer program performs level-2 processing of thermal-microwave-radiance data from observations of the limb of the Earth by the Earth Observing System (EOS) Microwave Limb Sounder (MLS). The purpose of the processing is to estimate the composition and temperature of the atmosphere versus altitude from .8 to .90 km. "Level-2" as used here is a specialists f term signifying both vertical profiles of geophysical parameters along the measurement track of the instrument and processing performed by this or other software to generate such profiles. Designed to be flexible, the program is controlled via a configuration file that defines all aspects of processing, including contents of state and measurement vectors, configurations of forward models, measurement and calibration data to be read, and the manner of inverting the models to obtain the desired estimates. The program can operate in a parallel form in which one instance of the program acts a master, coordinating the work of multiple slave instances on a cluster of computers, each slave operating on a portion of the data. Optionally, the configuration file can be made to instruct the software to produce files of simulated radiances based on state vectors formed from sets of geophysical data-product files taken as input.

Snyder, W. Van↗

NASA NTRS2018

An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral Sensors

The intercalibration between a broadband and a hyperspectral satellite Earth observation system requires the convolution of the hyperspectral data with the spectral response functions (SRFs) of the corresponding broadband channels. There are two potential issues associated with the convolution procedure. First, the finite resolution of a hyperspectral spectrum, that is, the deviation from the highly accurate line-by-line monochromatic radiances, will contribute to convolution errors. The magnitude of the errors depends on the spectral resolution and the SRF shape of the hyperspectral instrument. This type of the convolution error has not been well recognized, and there is a lack of corresponding discussion in most published papers. Although it is small as compared with the instrument accuracy of existing hyperspectral sounders, the error is deemed to be signicant when it is compared with the stringent calibration requirement imposed by future climate missions like the Climate Absolute Radiance and Refractivity Observatory (CLARREO). Second, some broadband channels are insufficiently covered by the hyperspectral data, causing spectral gaps that lead to convolution errors. Although several methods have been developed to fill the spectral gaps and hence compensate for the second type of convolution error, the correction accuracy may still need improvement especially when a large spectral gap needs to be lled. This paper presents a methodology to accurately quantify and compensate for both types of convolution errors. This methodology utilizes the available hyperspectral information to correct the scene-dependent convolution errors due to either the limited spectral resolution or spectral gaps. We use simulations to characterize the intercalibration errors between the Moderate resolution Imaging Spectroradiometer (MODIS) and current operational infrared sounders. We demonstrate that convolution errors can be effectively removed to meet the highly accurate intersatellite calibration requirement proposed by the Climate Absolute Radiance and Refractivity Observatory. Our methodology is also validated using real satellite data for the intercalibration between Aqua MODIS and Aqua Atmospheric Infrared Sounders (AIRS). Our study demonstrates that the accurate characterization and correction for the convolution errors greatly reduces the scene-dependent and spectrally dependent errors, being critical to the consistency check between Infrared Atmospheric Sounding Interferometer (IASI) and AIRS using the double-difference method. The convolution correction also facilitates the evaluation for other intercalibration errors (e.g., the drift of MODIS SRFs). Our derived SRF shift values from MODIS-AIRS (after convolution error corrections) and from MODIS-IASI intercalibration are consistent with each other. We further extend the methodology to study the calibration of a broadband channel which is either completely or largely uncovered bya hyperspectral measurement.The large spectral gap-filling methodology is validated by demonstrating the accurate prediction of the MODIS radiance of band 29 using the Cross-track Infrared Sounder spectra, with the real IASI spectral data being used as the reference.

Correction Method↗

NASA NTRS2008

Accurate Satellite-Derived Estimates of Tropospheric Ozone Radiative Forcing

Estimates of the radiative forcing due to anthropogenically-produced tropospheric O3 are derived primarily from models. Here, we use tropospheric ozone and cloud data from several instruments in the A-train constellation of satellites as well as information from the GEOS-5 Data Assimilation System to accurately estimate the instantaneous radiative forcing from tropospheric O3 for January and July 2005. We improve upon previous estimates of tropospheric ozone mixing ratios from a residual approach using the NASA Earth Observing System (EOS) Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) by incorporating cloud pressure information from OMI. Since we cannot distinguish between natural and anthropogenic sources with the satellite data, our estimates reflect the total forcing due to tropospheric O3. We focus specifically on the magnitude and spatial structure of the cloud effect on both the shortand long-wave radiative forcing. The estimates presented here can be used to validate present day O3 radiative forcing produced by models.

Joiner, Joanna↗

NASA NTRS1995

Short-range precipitation forecasts using assimilation of simulated satellite water vapor profiles and column cloud liquid water amounts

These observing system simulation experiments investigate the assimilation of satellite-observed water vapor and cloud liquid water data in the initialization of a limited-area primitive equations model with the goal of improving short-range precipitation forecasts. The assimilation procedure presented includes two aspects: specification of an initial cloud liquid water vertical distribution and diabatic initialization. The satellite data is simulated for the next generation of polar-orbiting satellite instruments, the Advanced Microwave Sounding Unit (AMSU) and the High-Resolution Infrared Sounder (HIRS), which are scheduled to be launched on the NOAA-K satellite in the mid-1990s. Based on cloud-top height and total column cloud liquid water amounts simulated for satellite data a diagnostic method is used to specify an initial cloud water vertical distribution and to modify the initial moisture distribution in cloudy areas. Using a diabatic initialization procedure, the associated latent heating profiles are directly assimilated into the numerical model. The initial heating is estimated by time averaging the latent heat release from convective and large-scale condensation during the early forecast stage after insertion of satellite-observed temperature, water vapor, and cloud water formation. The assimilation of satellite-observed moisture and cloud water, together withy three-mode diabatic initialization, significantly alleviates the model precipitation spinup problem, especially in the first 3 h of the forecast. Experimental forecasts indicate that the impact of satellite-observed temperature and water vapor profiles and cloud water alone in the initialization procedure shortens the spinup time for precipitation rates by 1-2 h and for regeneration of the areal coverage by 3 h. The diabatic initialization further reduces the precipitation spinup time (compared to adiabatic initialization) by 1 h.

Wu, Xiaohua↗

NASA NTRS2012

Geophysical Information from Advanced Sounder Infrared Spectral Radiance

Advanced satellite sensors are tasked with improving global observations of the Earth's atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Satisfying this type of improvement for inferred geophysical information from these observations requires optimal usage of data from current systems as well as enhancements to future sensors. This presentation addresses the information content present in infrared spectral radiance from advanced atmospheric sounders with an emphasis on knowledge of thermodynamic state and trace species. Results of trade-off studies conducted to evaluate the impact of spectral resolution, spectral coverage, instrument noise, and a priori knowledge on remote sensing system information content will be discussed. A focus is placed on information achievable from the Atmospheric InfraRed Sounder (AIRS) on the NASA EOS Aqua satellite in orbit since 2002, the Infrared Atmospheric Sounding Interferometer (IASI) aboard MetOp-A since 2006, and the Cross-track Infrared Sounder (CrIS) instrument aboard the NPP and JPSS series of satellites which began 28 October 2011.

Larar, Allen M.↗

NASA NTRSDate not supplied

Latest Development in Radiative Transfer Models and Retrieval Algorithms Using Principal Components

The radiative transfer model (RTMs) has a wide range of applications in satellite remote sensing and atmospheric radiation applications. However, millions of line-by-line (LBL) radiative transfer calculations at fine monochromatic frequencies are needed in order to properly calculate spectral contributions of water vapor and trace gases in the atmosphere in infrared and solar spectral regions. Therefore, fast and accurate RTMs are needed to efficiently process large amount of satellite data. A Principal Component-based Radiative Transfer Model (PCRTM) was first developed in 2004 at NASA Langley Research Centre to fulfil this need. By using PC-compression, one can reduce the data dimension significantly while maintaining original information content. The PCRTM can directly compute PC-scores and their derivatives with respect to retrieved parameters. The PCRTM can simulate the top-of-atmosphere (TOA) radiance or reflectance spectra from 0.250 µm (400000 cm-1) to 2000 µm (50 cm-1) with several orders of magnitude faster speed as compared to a LBL RTM. It is also extremely accurate compared to LBL RTM benchmarks (0.03 K RMS error in IR and 0.05% in solar). The PCRTM model has been developed for hyperspectral sensors such as AIRS, CrIS, IASI, NAST-I, SHIS, FIRST, and CLARREO-IR in thermal IR spectral region and CLARREO-Solar, CPF, TEMPO, EMIT, OMI, and SCIAMACHY in solar spectral region. The PCRTM accuracy has been demonstrated via RTM intercomparisons and with real satellite observations from AIRS, CrIS, IASI, SCHIAMACHY, and EMIT etc. In this presentation, we will describe two PCRTM-based inversion algorithms to retrieve atmospheric temperature, water vapor, and trace gas profiles, as well as cloud and surface properties from hyperspectral sounders such as AIRS, CrIS, IASI, and NAST-I. The first one is called Single Fieldof-view Sounder Atmospheric Product (SiFSAP) algorithm. It provides L2 products with 9-times higher area spatial resolution as compared to current cloud-clearing sounder algorithms. The SiFSAP L2 and L3 products are available at NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access. The second inversion algorithm is called Climate Fingerprinting Atmospheric Product (ClimFiSP) algorithm. It is designed to produce high quality climate products (trends, anomalies, daily, and monthly profiles of temperature, water vapor, traces, clouds, and surface properties) from multiple satellite sensors such AIRS on Aqua and CrIS on multiple satellites. This product will be available at NASA GES DISC later this year. The PCRTMbased high fidelity simulators for CLARREO and CPF have been used for sensor performance trade studies, algorithm development, and inter-satellite calibrations. We have also used PCRTM generated TOA radiance spectra to train an AI-based algorithm and successfully retrieved cloud properties from EMIT solar hyperspectral imagers.

PCRTM↗

NASA NTRS2019

Learning from GES DISC's MLS and OMI Data Users: Metrics Matter

It has been over 15 years since Aura research satellite launched in 2004 to observe the Earth's ozone layer, air quality, and climate from four different instruments - the High Resolution Dynamics Limb Sounder (HIRDLS), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Tropospheric Emission Spectrometer (TES). Observations from the Aura mission have established a concrete understanding of the changing chemistry of our atmosphere.The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the official archive and distribution center for the HIRDLS, MLS, and OMI instruments. This presentation will report metrics of data usage and services on these instruments. Key to GES DISC's mission to provide better data support is gaining a better understanding of our users' needs and behaviors as they discover, access and utilize these data. We will summarize the users' needs from these instruments based on user inquiry information collected over the Aura mission lifetime and present findings from this ensemble metrics.

Metrics↗

NASA NTRSDate not supplied

Deriving Climate Change Signal from Hyperspectral Sounders Using Spectral Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric temperature, water vapor and trace gas vertical profiles. We have developed a radiometrically consistent spectral fingerprinting method to derive climate change signals from Aqua AIRS/AMSU and S-NPP CrIS/ATMS data. The climate variables include temperature and water vapor profiles, cloud, trace gases, and surface skin temperature. The radiative kernels obtained via a single field of view physical retrieval algorithm under all-sky conditions. A key component to this work is a Principal Component-based Radiative Transfer Model (PCRTM). It is 4 orders of magnitude faster than a line-by-line radiative transfer model while keeping a similar accuracy (0.03 K RMS errors with close to zero bias). The PCRTM includes multiple scattering of clouds and non-thermodynamics equilibrium of CO2 in the RT calculations. Instead of quantifying the radiometric differences between AIRS/AMSU and CrIS/ATMS measurements directly using Simultaneous Nadir Overpass (SNO) or Double Difference Technique (DDT), we use the radiometric consistent fingerprinting scheme to derive two sets of space-time averaged anomalies from the Level 1 data of AIRS/AMSU and CrIS/ATMS. The derived anomalies in geophysical space will form a long-term, stable, and continuous climate data record. We can further infer the causes of any offset or drift by studying the differences between two overlapping data sets. For example, the offset in surface skin temperature anomaly time series will most likely caused by the Blackbody temperature calibration errors of the sounder instruments.

climate↗

NASA NTRSDate not supplied

GEOS Constituent Data Assimilation beyond Aura MLS: Assimilating NASA SAGE III/ISS profiles of stratospheric water vapor

Water vapor in the lower stratosphere is an important trace gas for atmospheric chemistry and radiative budget with direct impact on climate. During the last quarter of the 20th century, the Stratospheric Aerosol and Gas Experiment (SAGE) missions were crucial in monitoring the stratospheric ozone loss and the subsequent recovery as well as trends in water vapor linked to surface temperature trends. The SAGE III instrument aboard the International Space Station (ISS) continues the SAGE mission record, with high vertical resolution profiles of water vapor (and other constituents) since mid-2017. The NASA GEOS Earth system model has the capability to assimilate multi-constituents from ground and space-based instruments using the GEOS Constituent Data Assimilation System (CoDAS). Reanalysis products of stratospheric water vapor without data constraints are historically poor, and two recent reanalyses which assimilated stratospheric constituents observed by the Microwave Limb Sounder (MLS) improve the representation of stratospheric composition, including water vapor, when compared against independent observations. The MLS instrument is on NASA's Aura satellite which is expected to be decommissioned in the coming years. Here we demonstrate that while the number of solar occultation observations a day from SAGE III/ISS is about 1 % of the total number of profiles observed globally by MLS, the chemical timescales of water vapor in the lower stratosphere are long enough that the SAGE III/ISS data can provide a useful constraint on the assimilated product. Analyzed water vapor fields from assimilating only SAGE III/ISS water vapor profiles agree well with independent stratospheric observations, including when compared against the frost-point hygrometers at the three NOAA stations. Over the five-year period from 2017 through 2022, the analyzed water vapor using SAGE III/ISS captures many of the features seen with the assimilation of MLS observations. Note, this ability is reduced over regions where the SAGE III/ISS instrument provides infrequent or no observations (associated with the orbit of the ISS), as highlighted in the case study period following the eruption of the tropical underwater volcano Hunga Tonga in early 2022. Nevertheless, there is a clear benefit to the assimilation of stratospheric water vapor from SAGE III/ISS observations, allowing us to continue to monitor stratospheric composition for climate assessments following the impending loss of Aura.

K. Emma Knowland↗

NASA NTRSDate not supplied

GEOS Constituent Data Assimilation Beyond Aura MLS: Assimilating NASA SAGE III/ISS Profiles of Stratospheric Water Vapor

Water vapor in the lower stratosphere is an important trace gas for atmospheric chemistry and radiative budget with direct impact on climate. During the last quarter of the 20th century, the Stratospheric Aerosol and Gas Experiment (SAGE) missions were crucial in monitoring the stratospheric ozone loss and the subsequent recovery as well as trends in water vapor linked to surface temperature trends. The SAGE III instrument aboard the International Space Station (ISS) continues the SAGE mission record, with high vertical resolution profiles of water vapor (and other constituents) since mid-2017. The NASA GEOS Earth system model has the capability to assimilate multi-constituents from ground and space-based instruments using the GEOS Constituent Data Assimilation System (CoDAS). Reanalysis products of stratospheric water vapor without data constraints are historically poor, and two recent reanalyses which assimilated stratospheric constituents observed by the Microwave Limb Sounder (MLS) improve the representation of stratospheric composition, including water vapor, when compared against independent observations. The MLS instrument is on NASA's Aura satellite which is expected to be decommissioned in the coming years. Here we demonstrate that while the number of solar occultation observations a day from SAGE III/ISS is about 1 % of the total number of profiles observed globally by MLS, the chemical timescales of water vapor in the lower stratosphere are long enough that the SAGE III/ISS data can provide a useful constraint on the assimilated product. Analyzed water vapor fields from assimilating only SAGE III/ISS water vapor profiles agree well with independent stratospheric observations, including when compared against the frost-point hygrometers at the three NOAA stations. Over the five-year period from 2017 through 2022, the analyzed water vapor using SAGE III/ISS captures many of the features seen with the assimilation of MLS observations. Note, this ability is reduced over regions where the SAGE III/ISS instrument provides infrequent or no observations (associated with the orbit of the ISS), as highlighted in the case study period following the eruption of the tropical underwater volcano Hunga Tonga in early 2022. Nevertheless, there is a clear benefit to the assimilation of stratospheric water vapor from SAGE III/ISS observations, allowing us to continue to monitor stratospheric composition for climate assessments following the impending loss of Aura.

K. Emma Knowland↗

NASA NTRSDate not supplied

GEOS Constituent Data Assimilation Beyond Aura MLS: Assimilating NASA SAGE III/ISS Profiles of Stratospheric Water Vapor

Water vapor in the lower stratosphere is an important trace gas for atmospheric chemistry and radiative budget with direct impact on climate. During the last quarter of the 20th century, the Stratospheric Aerosol and Gas Experiment (SAGE) missions were crucial in monitoring the stratospheric ozone loss and the subsequent recovery as well as trends in water vapor linked to surface temperature trends. The SAGE III instrument aboard the International Space Station (ISS) continues the SAGE mission record, with high vertical resolution profiles of water vapor (and other constituents) since mid-2017. The NASA GEOS Earth system model has the capability to assimilate multi-constituents from ground and space-based instruments using the GEOS Constituent Data Assimilation System (CoDAS). Reanalysis products of stratospheric water vapor without data constraints are historically poor, and two recent reanalyses which assimilated stratospheric constituents observed by the Microwave Limb Sounder (MLS) improve the representation of stratospheric composition, including water vapor, when compared against independent observations. The MLS instrument is on NASA's Aura satellite which is expected to be decommissioned in the coming years. Here we demonstrate that while the number of solar occultation observations a day from SAGE III/ISS is about 1 % of the total number of profiles observed globally by MLS, the chemical timescales of water vapor in the lower stratosphere are long enough that the SAGE III/ISS data can provide a useful constraint on the assimilated product. Analyzed water vapor fields from assimilating only SAGE III/ISS water vapor profiles agree well with independent stratospheric observations, including when compared against the frost-point hygrometers at the three NOAA stations. Over the five-year period from 2017 through 2022, the analyzed water vapor using SAGE III/ISS captures many of the features seen with the assimilation of MLS observations. Note, this ability is reduced over regions where the SAGE III/ISS instrument provides infrequent or no observations (associated with the orbit of the ISS), as highlighted in the case study period following the eruption of the tropical underwater volcano Hunga Tonga in early 2022. Nevertheless, there is a clear benefit to the assimilation of stratospheric water vapor from SAGE III/ISS observations, allowing us to continue to monitor stratospheric composition for climate assessments following the impending loss of Aura.

K. Emma Knowland↗

NASA NTRS2020

Validation of Carbon Trace Gas Profile Retrievals from the NOAA-Unique Combined Atmospheric Processing System for the Cross-Track Infrared Sounder

This paper provides an overview of the validation of National Oceanic and Atmospheric Administration (NOAA) operational retrievals of atmospheric carbon trace gas profiles, specifically carbon monoxide (CO), methane (CH4) and carbon dioxide (CO2), from the NOAA-Unique Combined Atmospheric Processing System (NUCAPS), a NOAA enterprise algorithm that retrieves atmospheric profile environmental data records (EDRs) under global non-precipitating (clear to partly cloudy) conditions. Vertical information about atmospheric trace gases is obtained from the Cross-track Infrared Sounder (CrIS), an infrared Fourier transform spectrometer that measures high resolution Earth radiance spectra from NOAA operational low earth orbit (LEO) satellites, including the Suomi National Polar-orbiting Partnership (SNPP) and follow-on Joint Polar Satellite System (JPSS) series beginning with NOAA-20. The NUCAPS CO, CH4, and CO2 profile EDRs are rigorously validated in this paper using well-established independent truth datasets, namely total column data from ground-based Total Carbon Column Observing Network (TCCON) sites, and in situ vertical profile data obtained from aircraft and balloon platforms via the NASA Atmospheric Tomography (ATom) mission and NOAA AirCore sampler, respectively. Statistical analyses using these datasets demonstrate that the NUCAPS carbon gas profile EDRs generally meet JPSS Level 1 global performance requirements, with the absolute accuracy and precision of CO 5% and 15%, respectively, in layers where CrIS has vertical sensitivity; CH4 and CO2 product accuracies are both found to be within ±1%, with precisions of ≈1.5% and ⪅0.5%, respectively, throughout the tropospheric column.

satellite cal/val; error analysis; greenhouse gase↗

NASA NTRS2001

U.S. Participation in the Mars Express Mission

NASA will provide the antenna and RF subsystem to the MARSIS radar sounder. There are 11 U.S. Co-Investigators for the science investigations, and navigation and data archiving support are also provided. ASPERA-3 receives NASA Discovery Program funding. Additional information is contained in the original extended abstract.

Morrison, A. D.↗

NASA NTRS2012

Comparison of Gravity Wave Temperature Variances from Ray-Based Spectral Parameterization of Convective Gravity Wave Drag with AIRS Observations

The realism of ray-based spectral parameterization of convective gravity wave drag, which considers the updated moving speed of the convective source and multiple wave propagation directions, is tested against the Atmospheric Infrared Sounder (AIRS) onboard the Aqua satellite. Offline parameterization calculations are performed using the global reanalysis data for January and July 2005, and gravity wave temperature variances (GWTVs) are calculated at z = 2.5 hPa (unfiltered GWTV). AIRS-filtered GWTV, which is directly compared with AIRS, is calculated by applying the AIRS visibility function to the unfiltered GWTV. A comparison between the parameterization calculations and AIRS observations shows that the spatial distribution of the AIRS-filtered GWTV agrees well with that of the AIRS GWTV. However, the magnitude of the AIRS-filtered GWTV is smaller than that of the AIRS GWTV. When an additional cloud top gravity wave momentum flux spectrum with longer horizontal wavelength components that were obtained from the mesoscale simulations is included in the parameterization, both the magnitude and spatial distribution of the AIRS-filtered GWTVs from the parameterization are in good agreement with those of the AIRS GWTVs. The AIRS GWTV can be reproduced reasonably well by the parameterization not only with multiple wave propagation directions but also with two wave propagation directions of 45 degrees (northeast-southwest) and 135 degrees (northwest-southeast), which are optimally chosen for computational efficiency.

convective gravity wave drag↗

NASA NTRSDate not supplied

Satellite Data Assimilation in the GEOS Atmospheric Data Assimilation System

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. The GEOS ADAS is enhanced by considering correlated observational errors among infrared radiance observations and assimilating new microwave radiance data in all-sky conditions. Historical microwave radiance data are tested within the all-sky microwave radiance assimilation framework and show beneficial effect in the preparation of the next GEOS reanalysis product. In this seminar, I will present the procedures of to assimilate microwave radiance data in all-sky conditions in the GEOS-ADAS. I will also discuss our efforts to update GEOS ADAS by assimilating more satellite data such as geostationary infrared observations and new observations made by the Advanced Technology Microwave Sounder (ATMS) aboard NOAA 21 polar orbit satellite.

Jianjun Jin↗

NASA NTRS1992

Science Goals and Mission Objectives of Nasa's Laser Atmospheric Wind Sounder Program

Knowledge of the global wind field is widely recognized as fundamental to advancing our understanding and prediction of the total Earth system. Yet, because wind profiles are primarily measured by land-based rawinsondes, the oceanic areas (covering three quarters of the Earth's surface) and many regions of the less developed southern hemisphere land areas are poorly observed. The gap between our requirements for wind data and their availability continues to widen. For example, as faster computers become available to model the atmosphere with ever increasing resolution and sophistication, our ability to model the atmosphere will be hampered by a lack of data, particularly wind profiles. In order to address this important deficiency in wind observations, NASA plans to construct the Laser Atmospheric Wind Sounder (LAWS) instrument, with deployment tentatively scheduled between 2002 and 2005 as part of NASA's Earth Observing System (EOS) mission. Addressed here is the importance of wind measurements for advancing our understanding and prediction of the total Earth System. The current characteristics of the LAWS instrument under study are also summarized.

Baker, Wayman E.↗

NASA NTRS2012

The Advanced Technology Microwave Sounder (ATMS): First Year On-Orbit

The Advanced Technology Microwave Sounder (ATMS) is a new satellite microwave sounding sensor designed to provide operational weather agencies with atmospheric temperature and moisture profile information for global weather forecasting and climate applications. A TMS will continue the microwave sounding capabilities first provided by its predecessors, the Microwave Sounding Unit (MSU) and Advanced Microwave Sounding Unit (AMSU). The first flight unit was launched a year ago in October, 2011 aboard the Suomi-National Polar-Orbiting Partnership (S-NPP) satellite, part of the new Joint Polar-Orbiting Satellite System (JPSS). Microwave soundings by themselves are the highest-impact input data used by Numerical Weather Prediction models; and A TMS, when combined with the Cross-track Infrared Sounder (CrIS), forms the Cross-track Infrared and Microwave Sounding Suite (CrIMSS). The microwave soundings help meet sounding requirements under cloudy sky conditions and provide key profile information near the surface. ATMS was designed & built by Aerojet Corporation in Azusa, California, (now Northrop Grumman Electronic Systems). It has 22 channels spanning 23-183 GHz, closely following the channel set of the MSU, AMSU-AI/2, AMSU-B, Microwave Humidity Sounder (MHS), and Humidity Sounder for Brazil (HSB). It continues their cross-track scanning geometry, but for the first time, provides Nyquist sample spacing. All this is accomplished with approximately V. the volume, Y, the mass, and Y, the power of the three AMSUs. A description will be given of its performance from its first year of operation as determined by post-launch calibration activities. These activities include radiometric calibration using the on-board warm targets and cold space views, and geolocation determination. Example imagery and zooms of specific weather events will be shown. The second ATMS flight model is currently under construction and planned for launch on the "Jl" satellite of the JPSS program in approximately 2016. Additional units are expected on the J2 and 13 satellites, as well as potentially on future European METOP satellites.

Kim, Edward J.↗