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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

How Can TOLNet Help to Better Understand Tropospheric Ozone? A Satellite Perspective

Potential sources of a priori ozone (O3) profiles for use in Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite tropospheric O3 retrievals are evaluated with observations from multiple Tropospheric Ozone Lidar Network (TOLNet) systems in North America. An O3 profile climatology (tropopause-based O3 climatology (TB-Clim), currently proposed for use in the TEMPO O3 retrieval algorithm) derived from ozonesonde observations and O3 profiles from three separate models (operational Goddard Earth Observing System (GEOS-5) Forward Processing (FP) product, reanalysis product from Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), and the GEOS-Chem chemical transport model (CTM)) were: 1) evaluated with TOLNet measurements on various temporal scales (seasonally, daily, hourly) and 2) implemented as a priori information in theoretical TEMPO tropospheric O3 retrievals in order to determine how each a priori impacts the accuracy of retrieved tropospheric (0-10 km) and lowermost tropospheric (LMT, 0-2 km) O3 columns. We found that all sources of a priori O3 profiles evaluated in this study generally reproduced the vertical structure of summer-averaged observations. However, larger differences between the a priori profiles and lidar observations were observed when evaluating inter-daily and diurnal variability of tropospheric O3. The TB-Clim O3 profile climatology was unable to replicate observed inter-daily and diurnal variability of O3 while model products, in particular GEOS-Chem simulations, displayed more skill in reproducing these features. Due to the ability of models, primarily the CTM used in this study, on average to capture the inter-daily and diurnal variability of tropospheric and LMT O3 columns, using a priori profiles from CTM simulations resulted in TEMPO retrievals with the best statistical comparison with lidar observations. Furthermore, important from an air quality perspective, when high LMT O3 values were observed, using CTM a priori profiles resulted in TEMPO LMT O3 retrievals with the least bias. The application of time-specific (non-climatological) hourly/daily model predictions as the a priori profile in TEMPO O3 retrievals will be best suited when applying this data to study air quality or event-based processes as the standard retrieval algorithm will still need to use a climatology product. Follow-on studies to this work are currently being conducted to investigate the application of different CTM-predicted O3 climatology products in the standard TEMPO retrieval algorithm. Finally, similar methods to those used in this study can be easily applied by TEMPO data users to recalculate tropospheric O3 profiles provided from the standard retrieval using a different source of a priori.

Satellite↗
NASA NTRS2012

Variable Sampling Mapping

The performance of an optical system (for example, a telescope) is limited by the misalignments and manufacturing imperfections of the optical elements in the system. The impact of these misalignments and imperfections can be quantified by the phase variations imparted on light traveling through the system. Phase retrieval is a methodology for determining these variations. Phase retrieval uses images taken with the optical system and using a light source of known shape and characteristics. Unlike interferometric methods, which require an optical reference for comparison, and unlike Shack-Hartmann wavefront sensors that require special optical hardware at the optical system's exit pupil, phase retrieval is an in situ, image-based method for determining the phase variations of light at the system s exit pupil. Phase retrieval can be used both as an optical metrology tool (during fabrication of optical surfaces and assembly of optical systems) and as a sensor used in active, closed-loop control of an optical system, to optimize performance. One class of phase-retrieval algorithms is the iterative transform algorithm (ITA). ITAs estimate the phase variations by iteratively enforcing known constraints in the exit pupil and at the detector, determined from modeled or measured data. The Variable Sampling Mapping (VSM) technique is a new method for enforcing these constraints in ITAs. VSM is an open framework for addressing a wide range of issues that have previously been considered detrimental to high-accuracy phase retrieval, including undersampled images, broadband illumination, images taken at or near best focus, chromatic aberrations, jitter or vibration of the optical system or detector, and dead or noisy detector pixels. The VSM is a model-to-data mapping procedure. In VSM, fully sampled electric fields at multiple wavelengths are modeled inside the phase-retrieval algorithm, and then these fields are mapped to intensities on the light detector, using the properties of the detector and optical system, for comparison with measured data. Ultimately, this model-to-data mapping procedure enables a more robust and accurate way of incorporating the exit-pupil and image detector constraints, which are fundamental to the general class of ITA phase retrieval algorithms.

Smith, Jeffrey, S.↗
NASA NTRS1982

HIRS-AMTS satellite sounding system test - Theoretical and empirical vertical resolving power

The present investigation is concerned with the vertical resolving power of satellite-borne temperature sounding instruments. Information is presented on the capabilities of the High Resolution Infrared Radiation Sounder (HIRS) and a proposed sounding instrument called the Advanced Moisture and Temperature Sounder (AMTS). Two quite different methods for assessing the vertical resolving power of satellite sounders are discussed. The first is the theoretical method of Conrath (1972) which was patterned after the work of Backus and Gilbert (1968) The Backus-Gilbert-Conrath (BGC) approach includes a formalism for deriving a retrieval algorithm for optimizing the vertical resolving power. However, a retrieval algorithm constructed in the BGC optimal fashion is not necessarily optimal as far as actual temperature retrievals are concerned. Thus, an independent criterion for vertical resolving power is discussed. The criterion is based on actual retrievals of signal structure in the temperature field.

Thompson, O. E.↗
NASA NTRS2019

Microphysical Retrievals from Simultaneous Measurements by Airborne and Ground Radars during OLYMPEX

The OLYMPEX field campaign took place over the Olympic Peninsula of Washington during winter 2015-2016. During the intensive observing period, several aircraft flights obtained multi-frequency airborne radar measurements at X-, Ku-, Ka, and W-band from radars aboard the ER-2 and DC-8 aircraft. In addition, ground radars at S- and X-band performed RHI scans under the aircraft ground tracks. These coincident datasets provide a wealth of complementary information about the hydrometeor particle sizes, shapes, and orientations.In order to synthesize these measurements and test the robustness of scattering models, an optimal estimation retrieval based upon a Hitschfeld-Bordan profiling algorithm has been developed. This algorithm retrieves profiles of the particle size distribution parameters Nw and Dm, and, in the ice phase, relative proportions of aggregate, pristine, and rimed particles, using scattering models with different size-density and size-aspect ratio relationships. Under this formulation, only the pristine particles are horizontally aligned and capable of producing non-zero ZDR and KDP.From the nadir-looking airborne multifrequency radars, we find that aggregates may be readily distinguished from rimed and pristine particles owing to their uniqueness in triple-frequency space. However, rimed and pristine particles occupy a similar region in this space and thus polarimetric measurements greatly enhance their identification in our retrieval framework. With these capabilities we will present analyses of three-dimensional hydrometeor mapping obtained during various OLYMPEX cases. Some features retrieved in these cases include a layer of enhanced aggregation about 2km above the melting layer, hypothesized to be maintained by orographic uplift. This layer is often situated above a layer of denser, aligned particles. Regions of riming and supercooled liquid water beneath generating cells are also identified by our retrieval algorithm. Comparisons to in-situ observations and evaluation of scattering models will be presented.

Munchak, S. Joseph↗
NASA NTRS2023

Single-Scattering Properties of Ellipsoidal Dust Aerosols Constrained By Measured Dust Shape Distributions

Most global aerosol models approximate dust as spherical particles, whereas most remote sensing retrieval algorithms approximate dust as spheroidal particles with a shape distribution that conflicts with measurements. These inconsistent and inaccurate shape assumptions generate biases in dust single-scattering properties. Here, we obtain dust single-scattering properties by approximating dust as triaxial ellipsoidal particles with observationally constrained shape distributions. We find that, relative to the ellipsoidal dust optics obtained here, the spherical dust optics used in most aerosol models underestimate dust single-scattering albedo, mass extinction efficiency, and asymmetry parameter for almost all dust sizes in both the shortwave and longwave spectra. We further find that the ellipsoidal dust optics are in substantially better agreement with observations of the scattering matrix and linear depolarization ratio than the spheroidal dust optics used in most retrieval algorithms. However, relative to observations, the ellipsoidal dust optics overestimate the lidar ratio by underestimating the backscattering intensity by a factor of ∼2. This occurs largely because the computational method used to simulate ellipsoidal dust optics (i.e., the improved geometric optics method) underestimates the backscattering intensity by a factor of ∼2 relative to other computational methods (e.g., the physical geometric optics method). We conclude that the ellipsoidal dust optics with observationally constrained shape distributions can help improve global aerosol models and possibly remote sensing retrieval algorithms that do not use the backscattering signal.

Dust↗
NASA NTRSDate not supplied

PyroCbs from Australia Fires and its Impact Using Satellite Observations from CrIS and TROPOMI and Reanalysis Data

Pyrocumulonimbus (pyroCb) clouds are thunder clouds created by intense heat from the Earth’s surface. They are formed similarly to cumulonimbus clouds, but the intense heat that results in the vigorous updraft comes from fire, either large wildfires or volcanic eruptions. Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles to the atmosphere, particularly during the pyroCb outbreak that occurred in southeast Australia between 29 December 2019 and 4 January 2020. It was estimated that at least 18 pyroCbs were generated during this episode, and some of them injected ice, smoke, and biomass burning gases above the local tropopause. An unprecedented abundance of H2O and CO in the stratosphere, and the displacement of background ozone (O3) and N2O from rapid ascent of air from the troposphere and lower stratosphere were found from satellite observations. Some other studies also found that the fire emissions and their long-range transport resulted in stratospheric aerosol, temperature, and O3 anomalies after the 2020 Australian bushfires and altered the Antarctic ozone and vortex, posing great impact to local air quality and climate change. Further study on the atmospheric thermodynamic status of atmosphere associated with these pyroCbs, and the change of the cloud properties and trace gases during this unprecedented Australia fires will be made using a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP). SiFSAP was developed by NASA using the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1, and will soon be available to the public at NASA DAAC. Since this product has a spatial resolution of 15 km at nadir, which is better than most global weather and climate models and other current operational sounding products, a process-oriented analysis of the dynamic transport of CO and fire plumes during this unprecedented fire disasters will be made in this study. Based on a Principal Component Radiative Transfer Model (PCRTM) and an optimized estimation retrieval algorithm, a simultaneously retrieval is made using the whole spectral information measured by CrIS, and the derived SiFSAP include temperature, water vapor, trace gases (such as O3, CO2, CO, CH4 and N2O), cloud properties and surface properties. Use of ATMS together with CrIS allows SiFSAP to get accurate retrieval products under thick pyroCb conditions, and an algorithm to detect pyroCb based on the hyperspectral infrared sounder spectrum from CrIS will be developed and verified. In addition to SiFSAP sounding products, other products like CO, O3, NO2 from TROPOMI, O3 from OMPS will be used for retrospective analysis. The wind fields from the NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize the transport, and the SiFSAP temperature and water vapor profiles within and around pyroCbs will be compared with MERRA-2 and ERA5 products.

Xiaozhen (Shawn) Xiong↗
NASA NTRS2008

Inter-comparison between AIRS and IASI through Retrieved Parameters

A State-of-the-art retrieval algorithm dealing with all-weather conditions has been applied to satellite/aircraft instruments retrieving cloud/surface and atmospheric conditions. High quality retrievals have been achieved from IASI data. Surface, cloud, and atmospheric structure and variation are well captured by IASI measurements and/or retrievals. The same retrieval algorithm is also applied to AIRS for retrieval inter-comparison. Both AIRS and IASI have a similar FOV size but AIRS has a higher horizontal resolution. AIRS data can be interpolated to IASI horizontal resolution for inter-comparison at the same geophysical locations, however a temporal variation between AIRS and IASI observations need to be considered. JAIVEx has employed aircraft to obtain the atmospheric variation filling the temporal gap between two satellites. First results show that both AIRS and IASI have a very similar vertical resolving power, atmospheric conditions are well captured by both instruments, and radiances are well calibrated. AIRS data shown in retrievals (e.g., surface emissivity and moisture) have a relatively higher noise level. Since the this type of retrieval is very sensitive to its radiance quality, retrieval products inter-comparison is an effective way to identify/compare their radiance quality, in terms of a combination of spectral resolution and noise level, and to assess instrument performance. Additional validation analyses are needed to provide more-definitive conclusions.

Zhou, Daniel K.↗
NASA NTRS2008

Assimilation of Atmospheric InfraRed Sounder (AIRS) Profiles using WRF-Var

The Weather Research and Forecasting (WRF) model contains a three-dimensional variational (3DVAR) assimilation system (WRF-Var), which allows a user to join data from multiple sources into one coherent analysis. WRF-Var combines observations with a background field traditionally generated using a previous model forecast through minimization of a cost function. In data sparse regions, remotely-sensed observations may be able to improve analyses and produce improved forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The combined AIRS/AMSU system provides radiance measurements used as input to a sophisticated retrieval scheme which has been shown to produce temperature profiles with an accuracy of 1 K over 1 km layers and humidity profiles with accuracy of 15% in 2 km layers in both clear and partly cloudy conditions. The retrieval algorithm also provides estimates of the accuracy of the retrieved values at each pressure level, allowing the user to select profiles based on the required error tolerances of the application. The purpose of this paper is to describe a procedure to optimally assimilate high-resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type using gen_be and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics in the WRF-Var. The AIRS thermodynamic profiles are obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators are used to select the highest quality temperature and moisture data for each profile location and pressure level. Analyses are run to produce quasi-real-time regional weather forecasts over the continental U.S. The preliminary assessment of the impact of the AIRS profiles will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes.

Zavodsky, Brad↗
NASA NTRS1995

(abstract) Using an Inversion Algorithm to Retrieve Parameters and Monitor Changes over Forested Areas from SAR Data

In this work, the application of an inversion algorithm based on a nonlinear opimization technique to retrieve forest parameters from multifrequency polarimetric SAR data is discussed. The approach discussed here allows for retrieving and monitoring changes in forest parameters in a quantative and systematic fashion using SAR data. The parameters to be inverted directly from the data are the electromagnetic scattering properties of the forest components such as their dielectric constants and size characteristics. Once these are known, attributes such as canopy moisture content can be obtained, which are useful in the ecosystem models.

forest canopy SAR data algorithm radar scattering ↗
NASA NTRSDate not supplied

The PolCube CubeSat Polarimeter for Earth Science

PolCube is a 12U CubeSat + polarimeter instrument designed by NASA Langley and the Korea Astronomy and Space Science Institute (KASI) for Earth Science. PolCube is based on the PolCam polarimeter onboard the Korean Pathfinder Lunar Observatory (KPLO) that launched in August 2022. The objective of the PolCube instrument is to retrieve detailed fine-mode (pollution and smoke) and coarse-mode (sea-salt and dust) aerosol properties over the ocean for a range of light to heavy aerosol loadings using its polarimetric-imaging capability at multiple angles and wavelengths from 410 − 865 nm. An additional objective is to discriminate aerosols from thin clouds. We quantify the performance of aerosol and ocean remote sensing products from the PolCube polarimeter instrument using the Microphysical Aerosol Properties from Polarimetry (MAPP) remote sensing retrieval algorithm. PolCube’s accurate and high-resolution aerosol-retrieval products will provide unique spatial and temporal coverage of the Earth that can be used synergistically with other instruments, such as the PACE (Plankton, Aerosols, Clouds and Ecosystems) and GEMS (Geostationary Environmental Monitoring Spectrometer) mission to improve air-quality forecasting. We present the PolCube-MAPP retrieval algorithm, which used optimal estimation and artificial intelligence, as well as multiple powerful inherent optical property look-up-tables for the Earth’s aerosol, cloud, and hydrosol particles. We estimate that PolCube can retrieve total aerosol optical depth at 555 nm (AOD555) within ±0.068, fine-mode AOD555 within ±0.078, and fine-mode single-scattering albedo within ±0.036, where all uncertainties are expressed as one standard deviation (1σ).

Snorre Stamnes↗
NASA NTRS2009

Efficient Method for Analyzing Hyperspectral Remote Sensing Data

The current and next generation satellite infrared sensors such as AIRS, IASI, CrIS, and CLARREO all have one thing in common: large number of spectral channels. In order to fully utilize the information content of these sensors, a large number of Radiative Transfer (RT) calculations through the inhomogeneous atmosphere are needed. It is also computationally intensive to invert atmospheric and surface properties using all the channels. Usually, only subsets of channels are used to perform physical inversions for atmospheric profiles. We will explore ways to speed up RT calculations and inversions and test the algorithms using data from the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument. We will describe a retrieval algorithm using a Principal Component-based Radiative Transfer Model (PCRTM) for generating atmospheric temperature/moisture/ozone profiles and surface properties. The retrieval algorithm performs both the radiative transfer calculations and inversions in the Principal Component (PC) domain. The inversion algorithm is based on a non-linear Levenberg- Marquardt method with climatology covariance matrices and a priori information as constraints. One advantage of this approach is that it uses all information content from the ultraspectral data so that the retrieval is less sensitive to instrument noise and eliminates the need for selecting a sub-set of the channels. We will also use data collected during the Joint Airborne IASI Validation Experiment (JAIVEx) field campaign to validate the algorithm and IASI retrievals.

Liu, Xu↗
NASA NTRS2001

[Limb Scattering Data Analysis]

The primary purpose of this grant was to support analysis of the limb scattering data taken during the 1997 flight of the SOLSE (Shuttle Ozone Limb Sounding Experiment) and LORE (Limb Ozone Retrieval Experiment) instruments. Work was done to assess the performance of the retrieval algorithms for cloudy and clear sky cases in preparation for a poster presentation. The nadir-viewing data were also compared to coincident GOME (Global Ozone Monitoring Experiment) data and to radiative transfer calculations. An algorithm similar to the TOMS (Total Ozone Mapping Spectrometer) ozone retrieval algorithm was developed to infer the ozone column amount from the SOLSE nadir data. Comparison with coincident TOMS ozone column data confirmed that column ozone could be derived successfully from SOLSE nadir radiances, and also revealed significant changes in the SOLSE wavelength resolution and absolute radiometric calibration that were subsequently confirmed by comparing the post-flight instrument characterization to the pre-flight characterization, indicating a potentially useful method for monitoring instrument behavior in-flight.

Loughman, Robert↗
NASA NTRS2017

Simulation of the Ozone Monitoring Instrument Aerosol Index Using the NASA Goddard Earth Observing System Aerosol Reanalysis Products

We provide an analysis of the commonly used Ozone Monitoring Instrument (OMI) aerosol index (AI) product for qualitative detection of the presence and loading of absorbing aerosols. In our analysis, simulated top-of-atmosphere (TOA) radiances are produced at the OMI footprints from a model atmosphere and aerosol profile provided by the NASA Goddard Earth Observing System (GEOS-5) Modern-Era Retrospective Analysis for Research and Applications aerosol reanalysis (MERRAero). Having established the credibility of the MERRAero simulation of the OMI AI in a previous paper we describe updates in the approach and aerosol optical property assumptions. The OMI TOA radiances are computed in cloud-free conditions from the MERRAero atmospheric state, and the AI is calculated. The simulated TOA radiances are fed to the OMI aerosol retrieval algorithms, and its retrieved AI (OMAERUV AI) is compared to the MERRAero calculated AI. Two main sources of discrepancy are discussed: one pertaining the OMI algorithm assumptions of the surface pressure, which are generally different from what the actual surface pressure of an observation is, and the other related to simplifying assumptions in the molecular atmosphere radiative transfer used in the OMI algorithms. Surface pressure assumptions lead to systematic biases in the OMAERUV AI, particularly over the oceans. Simplifications in the molecular radiative transfer lead to biases particularly in regions of topography intermediate to surface pressures of 600hPa and 1013.25hPa. Generally, the errors in the OMI AI due to these considerations are less than 0.2 in magnitude, though larger errors are possible, particularly over land. We recommend that future versions of the OMI algorithms use surface pressures from readily available atmospheric analyses combined with high-spatial resolution topographic maps and include more surface pressure nodal points in their radiative transfer lookup tables.

remote sensing↗
NASA NTRS2013

Aerosol Airmass Type Mapping Over the Urban Mexico City Region From Space-based Multi-angle Imaging

Using Multi-angle Imaging SpectroRadiometer (MISR) and sub-orbital measurements from the 2006 INTEX-B/MILAGRO field campaign, in this study we explore MISR's ability to map different aerosol air mass types over the Mexico City metropolitan area. The aerosol air mass distinctions are based on shape, size and single scattering albedo retrievals from the MISR Research Aerosol Retrieval algorithm. In this region, the research algorithm identifies dust-dominated aerosol mixtures based on non-spherical particle shape, whereas spherical biomass burning and urban pollution particles are distinguished by particle size. Two distinct aerosol air mass types based on retrieved particle microphysical properties, and four spatially distributed aerosol air masses, are identified in the MISR data on 6 March 2006. The aerosol air mass type identification results are supported by coincident, airborne high-spectral-resolution lidar (HSRL) measurements. Aerosol optical depth (AOD) gradients are also consistent between the MISR and sub-orbital measurements, but particles having single-scattering albedo of approx. 0.7 at 558 nm must be included in the retrieval algorithm to produce good absolute AOD comparisons over pollution-dominated aerosol air masses. The MISR standard V22 AOD product, at 17.6 km resolution, captures the observed AOD gradients qualitatively, but retrievals at this coarse spatial scale and with limited spherical absorbing particle options underestimate AOD and do not retrieve particle properties adequately over this complex urban region. However, we demonstrate how AOD and aerosol type mapping can be accomplished with MISR data over complex urban regions, provided the retrieval is performed at sufficiently high spatial resolution, and with a rich enough set of aerosol components and mixtures.

aerosol optical depth↗
NASA NTRS2010

GPM Microwave Imager Engineering Model Results

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument is being developed by Ball Aerospace and Technology Corporation (BATC) for the GPM program at NASA Goddard. The Global Precipitation Measurement (GPM) mission is an international effort managed by the National Aeronautics and Space Administration (NASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and more frequent precipitation measurements. The GPM Microwave Imager (GMI) will be used to make calibrated, radiometric measurements from space at multiple microwave frequencies and polarizations. GMI will be placed on the GPM Core Spacecraft together with the Dualfrequency Precipitation Radar (DPR). The DPR is two-frequency precipitation measurement radar, which will operate in the Ku-band and Ka-band of the microwave spectrum. The Core Spacecraft will make radiometric and radar measurements of clouds and precipitation and will be the central element ofGPM's space segment. The data products from GPM will provide information concerning global precipitation on a frequent, near-global basis to meteorologists and scientists making weather forecasts and performing research on the global energy and water cycle, precipitation, hydrology, and related disciplines. In addition, radiometric measurements from GMI and radar measurements from the DPR will be used together to develop a retrieval transfer standard for the purpose of calibrating precipitation retrieval algorithms. This calibration standard will establish a reference against which other retrieval algorithms using only microwave radiometers (and without the benefit of the DPR) on other satellites in the GPM constellation will be compared.

Newell, David↗
NASA NTRS2010

GPM Microwave Imager Design, Predicted Performance and Status

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument is being developed by Ball Aerospace and Technology Corporation (BATC) for the GPM program at NASA Goddard. The Global Precipitation Measurement (GPM) mission is an international effort managed by the National Aeronautics and Space Administration (t.JASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and more frequent precipitation measurements. The GPM Microwave Imager (GMI) will be used to make calibrated, radiometric measurements from space at multiple microwave frequencies and polarizations. GMI will be placed on the GPM Core Spacecraft together with the Dual-frequency Precipitation Radar (DPR). The DPR is two-frequency precipitation measurement radar, which will operate in the Ku-band and Ka-band of the microwave spectrum. The Core Spacecraft will make radiometric and radar measurements of clouds and precipitation and will be the central element of GPM's space segment. The data products from GPM will provide information concerning global precipitation on a frequent, near-global basis to meteorologists and scientists making weather forecasts and performing research on the global energy and water cycle, precipitation, hydrology, and related disciplines. In addition, radiometric measurements from GMI and radar measurements from the DPR will be used together to develop a retrieval transfer standard for the purpose of calibrating precipitation retrieval algorithms. This calibration standard will establish a reference against which other retrieval algorithms using only microwave radiometers (and without the benefit of the DPR) on other satellites in the GPM constellation will be compared.

Krimchansky, Sergey↗
NASA NTRS1990

An algorithm for retrieving water vapor profiles in clear and cloudy atmospheres from 183 GHz radiometric measurements - Simulation studies

The latent heat represented by atmospheric water vapor is extremely important to the energetics of the earth system. Future satellites (NOAA and DMSP) will carry microwave radiometers designed to measure the profile of water vapor globally. The problem of retrieving water vapor from the measurements is highly nonlinear even in clear atmospheres and the addition of clouds only makes it more so. In this paper, an algorithm with several novel features, which will retrieve water vapor profiles from microwave radiometric measurements even in the presence of clouds, is developed. Simulations with this algorithm show a vertical resolution on the order of 3 km and that clouds are well handled in many, but not all, circumstances. The most surprising result is that clouds can actually improve the vertical resolution of the retrieval.

Wilheit, Thomas T.↗
NASA NTRS2007

Cloudy Sounding and Cloud-Top Height Retrieval From AIRS Alone Single Field-of-View Radiance Measurements

High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single field-of-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud top pressure (CTP) and cloud optical thickness (COT) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Center of Medium range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from 38 high-spectral infrared (IR) sounder instruments.

Weisz, Elisabeth↗