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NASA NTRS1998

Upper tropospheric water vapor: A field campaign of two Raman lidars, Airborne hygrometers, and Radiosondes

Water vapor in the atmosphere plays an important role in radiative transfer and the process of radiative balance so critical for understanding global change. It is the principal ingredient in cloud formation, one of the most difficult atmospheric processes to model, and the most variable component of the Earth-atmosphere albedo. And as a free molecule, it is the most active infrared absorber and emitter, thus, the most important greenhouse gas. The radiative impact of water vapor is important at all levels of the atmosphere. Even though moisture decreases by several orders-of-magnitude from the Earth's surface to the tropopause, recent research has shown that, from a radiative standpoint, a small percentage change in water vapor at any level is nearly equivalent. Therefore accurate and precise measurements of this important atmospheric constituent are needed at all levels to evaluate the full radiative impact. The need for improved measurements in the upper troposphere is particularly important because of the generally hostile (very dry and cold) conditions encountered. Because of the importance of water vapor to the understanding of radiative transfer, the Department of Energy's Atmospheric Radiation Measurements (ARM) program initiated a series of measurement campaigns at the Cloud And Radiation Testbed (CART) site in Oklahoma, especially focused on atmospheric water vapor. Three water vapor intensive observation period (water vapor IOP) campaigns were planned. Two of the water vapor IOP campaigns have been completed: the first IOP was held during the fall of 1996 with a focus on boundary layer water vapor measurements, and the second was conducted during the fall of 1997 with a focus on both boundary layer moisture e and moisture in the upper troposphere. This paper presents a review of the intercomparisons of water vapor measurements in the upper troposphere aquired during the second water vapor IOP. Data to be presented include water vapor measurements ements from: two Raman Lidars, the NASA Goddard Scanning Raman Lidar (SRL) and the CART Raman Lidar (CARL), a number of Vaisala radiosondes launched during the IOP campaign, and a dew point hygrometer flown on the University of North Dakota Cessna Citation Aircraft.

Melfi, S. Harvey↗
NASA NTRS1998

Assimilation of Goes-Derived Skin Temperature Tendencies into Mesoscale Models to Improve Forecasts of near Surface Air Temperature and Mixing Ratio

A technique has been developed for assimilating GOES-FR skin temperature tendencies into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature chance closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts (0-48 h) is that it does not require a complex land-surface formulation within the atmospheric model. As a result, the need to specify poorly known soil and vegetative characteristics is eliminated. The GOES assimilation technique has been incorporated into the PSU/NCAR MM5. Results will be presented to demonstrate the ability of the assimilation scheme to improve short- term (0-48h) simulations of near-surface air temperature and mixing ratio during the warm season for several selected cases which exhibit a variety of atmospheric and land-surface conditions. In addition, validation of terms in the simulated surface energy budget will be presented using in situ data collected at the Southern Great Plains (SGP) Cloud And Radiation Testbed (CART) site as part of the Atmospheric Radiation Measurements Program (ARM).

Lapenta, William M.↗
NASA NTRS2000

Continuous Water Vapor Profiles from Operational Ground-Based Active and Passive Remote Sensors

The Atmospheric Radiation Measurement program's Southern Great Plains Cloud and Radiation Testbed site central facility near Lamont, Oklahoma, offers unique operational water vapor profiling capabilities, including active and passive remote sensors as well as traditional in situ radiosonde measurements. Remote sensing technologies include an automated Raman lidar and an automated Atmospheric Emitted Radiance Interferometer (AERI), which are able to retrieve water vapor profiles operationally through the lower troposphere throughout the diurnal cycle. Comparisons of these two water vapor remote sensing methods to each other and to radiosondes over an 8-month period are presented and discussed, highlighting the accuracy and limitations of each method. Additionally, the AERI is able to retrieve profiles of temperature while the Raman lidar is able to retrieve aerosol extinction profiles operationally. These data, coupled with hourly wind profiles from a 915-MHz wind profiler, provide complete specification of the state of the atmosphere in noncloudy skies. Several case studies illustrate the utility of these high temporal resolution measurements in the characterization of mesoscale features within a 3-day time period in which passage of a dryline, warm air advection, and cold front occurred.

Turner, D. D.↗
NASA NTRS2003

Measurement of Low Amounts of Precipitable Water Vapor Using Ground-Based Millimeterwave Radiometry

Extremely dry conditions characterized by amounts of precipitable water vapor (PWV) as as 1-2 mm commonly occur in high-latitude regions during the winter months. While such atmospheres carry only a few percent of the latent heat energy compared to tropical atmospheres, the effects of low vapor amounts on the polar radiation budget - both directly through modulation of longwave radiation and indirectly through the formation of clouds - are considerable. Accurate measurements of precipitable water vapor (PWV) during such dry conditions are needed to improve polar radiation models for use in understanding and predicting change in the climatically sensitive polar regions. To this end, the strong water vapor absorption at 183.310 GHz provides a unique means of measuring low amounts of PWV. Weighting function analysis, forward model calculations based upon a 7-year radiosonde dataset, and retrieval simulations consistently predict that radiometric measurements made using several millimeter-wavelength (MMW) channels near the 183 GHz line, together with established microwave (MW) measurements at the 22.235 GHz water vapor line and -3 1 GHz atmospheric absorption window can be used to determine within 5% uncertainty the full range of PWV expected in the Arctic. This unique collective capability stands in spite of accuracy limitations stemming from uncertainties due to the sensitivity of the vertical distribution of temperature and water vapor at MMW channels. In this study the potential of MMW radiometry using the 183 GHz line for measuring low amounts of PWV is demonstrated both theoretically and experimentally. The study uses data obtained during March 1999 as part of an experiment conducted at the Department of Energy s Cloud and Radiation Testbed (CART) near Barrow, Alaska. Several radiometers from both NOAA and NASA were deployed during the experiment to provide the first combined MMW and MW ground-based data set during dry arctic conditions. Single-channel retrievals of PWV were performed using the MW and MMW data. Discrepancies in the retrieved values were found to be consistent with differences observed between measured brightness temperatures (TBs) and forward-modeled TBs based on concurrent radiosonde profiles. These discrepancies are greater than can be explained by measurement error alone and are attributed to absorption model uncertainty. We discuss here the measurements, retrieval technique, and line model discrepancies along with difficulties and potential of MMW/MW PWV measurement.

Racette, Paul E.↗
NASA NTRS2011

Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Roman, Miguel O.↗
NASA NTRS2012

Variability in Surface BRDF at Different Spatial Scales (30m-500m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Roman, Miguel O.↗
NASA NTRS1995

Data management and scientific integration within the Atmospheric Radiation Measurement Program

The Atmospheric Radiation Measurement (ARM) Program has been developed by the U.S. Department of Energy with the goal to improve the predictive capabilities of General Circulation Models (GCM's) in their treatment of clouds and radiative transfer effects. To achieve this goal, three experimental testbeds were designed for the deployment of instruments that will collect atmospheric data used to drive the GCM's. Each site, known as a Cloud and Radiation Testbed (CART), consists of a highly available, redundant data system for the collection of data from a variety of instrumentation. The first CART site was deployed in April 1992 in the Southern Great Plains (SGP), Lamont, Oklahoma, with the other two sites to follow in September 1995 in the Tropical Western Pacific and in 1997 on the North Slope of Alaska. Approximately 400 MB of data are transferred per day via the Internet from the SGP site to the ARM Experiment Center at Pacific Northwest Laboratory in Richland, Washington. The Experiment Center is central to the ARM data path and provides for the collection, processing, analysis, and delivery of ARM data. Data are received from the CART sites from a variety of instrumentation, observational systems, amd external data sources. The Experiment Center processes these data streams on a continuous basis to provide derived data products to the ARM Science Team in near real-time while providing a three-month running archive of data. A primary requirement of the ARM Program is to preserve and protect all data produced or acquired. This function is performed at Oak Ridge National Laboratory where leading edge technology is employed for the long-term storage of ARM data. The ARM Archive provides access to data for participation outside of the ARM Program. The ARM Program involves a collaborative effort by teams from various DOE National Laboratories, providing multi-disciplinary areas of expertise. This paper will discuss the collaborative methods in which the ARM teams translate the scientific goals of the Program into data products. By combining atmospheric scientists, systems engineers, and software engineers, the ARM Program has successfully designed and developed an environment where advances in understanding the parameterizations of GCM's can be made.

Gracio, Deborah K.↗
NASA NTRS1997

Cirrus Cloud Radiative and Microphysical Properties from Ground Observations and In Situ Measurements During FIRE 1991 and Their Application to Exhibit Problems in Cirrus Solar Radiative Transfer Modeling

Measurements from the FIRE 1991 cirrus cloud field experiment in the central United States are presented and analyzed. The first part focuses on cirrus microphysical properties. Aircraft 2D-probe in situ data at different cloud altitudes were evaluated for cirrus cases on four different days. Also presented are simultaneous data samples from balloonborne videosondes. Only these balloonsondes could detect the smaller crystals. Their data suggest (at least for midlatitude altitudes below 10 km) that ice crystals smaller than 15 microns in size are rare and that small ice crystals not detected by 2D-probe measurements are radiatively of minor importance, as overlooked 2D-probe crystals account for about 10% of the total extinction. The second part focuses on the link between cirrus cloud properties and radiation. With cloud macrophysical properties from surface remote sensing added to the microphysical data and additional radiation measurements at the surface, testbeds for radiative transfer models were created. To focus on scattering processes, model evaluations were limited to the solar radiative transfer by comparing calculated and measured transmissions of sunlight at the surface. Comparisons under cloud-free conditions already reveal a model bias of about +45 W/sq m for the hemispheric solar downward broadband flux. This discrepancy, which is (at least in part) difficult to explain, has to be accounted for in comparisons involving clouds. Comparisons under cirrus cloud conditions identify as the major obstacle in cirrus solar radiative transfer modeling the inability of one-dimensional radiative transfer models to account for horizontal inhomogeneities. The successful incorporation of multidimensional radiative transfer effects will depend not only on better models but critically on the ability to measure and to define characteristic inhomogeneity scales of cloud fields. The relative minor error related to the microphysical treatment is in part a reflection of the improved understanding on solar scattering on ice crystals over the last decade and of the available wealth on ice-crystal size and shape data for this study. In absence of this information, uncertainties from microphysical cirrus model assumptions will remain high.

Kinne, Stefan↗
NASA NTRS2015

RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

parameterization↗
NASA NTRS2021

Land-Atmosphere Coupling at the U.S. Southern Great Plains: A Comparison on Local Convective Regimes Between ARM Observations, Reanalysis, and Climate Model Simulations

Using the 9-yr warm-season observations at the Atmospheric Radiation Measurement Southern Great Plains site, we assess the land-atmosphere (L-A) coupling in North American Regional Reanalysis (NARR) and two climate models: hindcasts with the Community Atmosphere Model version 5.1 by Cloud-Associated Parameterizations Testbed (CAM5-CAPT) and nudged runs with the Energy Exascale Earth System Model Atmosphere Model version 1 Regionally Refined Model (EAMv1-RRM). We focus on three local convective regimes and diagnose model behaviors using the Local Coupling metrics (Santanello et al. 2018). NARR agrees well with observations except a slightly warmer and drier surface with higher downwelling shortwave radiation and lower evaporative fraction. On clear-sky days, it shows warmer and drier early-morning conditions in both models with significant underestimates in surface evaporation by EAMv1-RRM. On the majority of the ARM-observed shallow cumulus days, there is no or little low-level clouds in either model. When captured in models, the simulated shallow cumulus shows much less cloud fraction and lower cloud bases than observed. On the days with late-afternoon deep convection, models tend to present a stable early-morning lower atmosphere more frequently than the observations, suggesting that the deep convection is triggered more often by elevated instabilities. Generally, CAM5-CAPT can reproduce the local L-A coupling processes to some extent due to the constrained early-morning conditions and large-scale winds. EAMv1-RRM exhibits large precipitation deficits and warm and dry biases towards mid-to-late summers, which may be an amplification through a positive L-A feedback among initial atmosphere and land states, convection triggering and large-scale circulations.

land-atmosphere↗
NASA NTRS2018

Active and Passive Radiative Transfer Modeling of the Olympic Mountains Experiment

Sensor forward models are an important tool for interpreting remote sensing observations of geophysical phenomena. By implementing a three-dimensional framework, we can simulate and analyze observations from various sensors on disparate platforms. To demonstrate our model framework, we simulate observations from the Olympic Mountains Experiment (OLYMPEX). The use of cloud model simulations allows us to understand sensor response to cloud ice, falling snow, and other processes and features, and the application of model tools to observations allows us to quantify precipitation.MIIST 3D Forward ModelThe Multi-Instrument Inverse Solver Testbed(MIIST) uses the Atmospheric Radiative TransferSimulator (ARTS) for solving the vector radiativetransfer (RT) equation in up to three spatialdimensions within a spherical geometry• Gas absorptiono Line-by-line calculationso Fast transmittance tables• Hydrometeor scattering solverso Discrete ordinateo RT4 (Evans, 1D)o Radar Single Scattering (1D or 3D)o Monte Carlo (3D)Scattering TablesHigh-fidelity hydrometeor scatteringtables are necessary for accurateand consistent forward modeling ofmulti-frequency observations• Requires full Stokes matriceso And absorption vector• Randomly oriented particleso Discrete Dipole Approximationo Characteristic Basis Function Method(coming soon)• Horizontally-oriented plateso Invariant Imbedding T-matrix MethodCloud Resolving SimulationsCloud resolving simulations (e.g.,NU-WRF) supply output consistentwith ARTS needs• Atmospheric Informationo Temperatureo Pressure / heighto Water vapor• Hydrometeor Profileso ARTS architecture ripe for explicit binmicrophysics• Examples use Morrison 2M schemeThe Olympic Mountains Experiment (OLYMPEX)Validation for GPM of mid-latitudefrontal systems approaching nearcoastalmountains from the ocean• Large collection of ground-based andairborne sensorso Radarso Radiometerso In situ• Contemporaneous with RADEXo Two sets of radar at same frequenciesRadiometer Simulation (3 km NUWRF, 20151203, 15:00)2018.12.14 7Simulate 166 GHz polarizationdifference• Corresponds to the presence of aligned icecrystals• Look at trends for both simulations andobservations• Simulations can tolerate lower resolutiono Larger domainSimulations from Observations: OLYMPEXSimulate sensor response usinggeophysical retrievals as input• Single frequency radar retrievals• Multiple scattering enhancementapparent at W band• Spatially dependent phenomenonModeling Application: 1D Retrievals03 December 2015• DC-8 and ER-2 flightso Focus on APR-3 (DC-8)• Citationo Stacked microphysics legso Qualitative comparisonso Range of frozen habitso Presence of supercooledliquid cloudsResults• Retrievals match probeso Good qualitative match• Bands of increasedreflectivity correspond tolarge Dm and highaggregate fraction• Significant amounts ofsupercooled liquid water

Adams, Ian S.↗
NASA NTRS2005

Principal Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Sensors: Theoretical Concept - Part I

Modern infrared satellite sensors such as Atmospheric Infrared Sounder (AIRS), Cosmic Ray Isotope Spectrometer (CrIS), Thermal Emission Spectrometer (TES), Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, super fast radiative transfer models are needed. This paper presents a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the Principal Component-based Radiative Transfer Model (PCRTM) predicts the Principal Component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from properties of PC scores and instrument line shape functions. The PCRTM is very accurate and flexible. Due to its high speed and compressed spectral information format, it has great potential for super fast one-dimensional physical retrievals and for Numerical Weather Prediction (NWP) large volume radiance data assimilation applications. The model has been successfully developed for the National Polar-orbiting Operational Environmental Satellite System Airborne Sounder Testbed - Interferometer (NAST-I) and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.

Liu, Xu↗
NASA NTRS2005

Thermodynamic and cloud parameter retrieval using infrared spectral data

High-resolution infrared radiance spectra obtained from near nadir observations provide atmospheric, surface, and cloud property information. A fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The retrieval algorithm is presented along with its application to recent field experiment data from the NPOESS Airborne Sounding Testbed - Interferometer (NAST-I). The retrieval accuracy dependence on cloud properties is discussed. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with an accuracy of approximately 1.0 km. Preliminary NAST-I retrieval results from the recent Atlantic-THORPEX Regional Campaign (ATReC) are presented and compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL).

Zhou, Daniel K.↗
NASA NTRS2003

Extraction of Profile Information from Cloud Contaminated Radiances

Clouds act to reduce the signal level and may produce noise dependence on the complexity of the cloud properties and the manner in which they are treated in the profile retrieval process. There are essentially three ways to extract profile information from cloud contaminated radiances: (1) cloud-clearing using spatially adjacent cloud contaminated radiance measurements, (2) retrieval based upon the assumption of opaque cloud conditions, and (3) retrieval or radiance assimilation using a physically correct cloud radiative transfer model which accounts for the absorption and scattering of the radiance observed. Cloud clearing extracts the radiance arising from the clear air portion of partly clouded fields of view permitting soundings to the surface or the assimilation of radiances as in the clear field of view case. However, the accuracy of the clear air radiance signal depends upon the cloud height and optical property uniformity across the two fields of view used in the cloud clearing process. The assumption of opaque clouds within the field of view permits relatively accurate profiles to be retrieved down to near cloud top levels, the accuracy near the cloud top level being dependent upon the actual microphysical properties of the cloud. The use of a physically correct cloud radiative transfer model enables accurate retrievals down to cloud top levels and below semi-transparent cloud layers (e.g., cirrus). It should also be possible to assimilate cloudy radiances directly into the model given a physically correct cloud radiative transfer model using geometric and microphysical cloud parameters retrieved from the radiance spectra as initial cloud variables in the radiance assimilation process. This presentation reviews the above three ways to extract profile information from cloud contaminated radiances. NPOESS Airborne Sounder Testbed-Interferometer radiance spectra and Aqua satellite AIRS radiance spectra are used to illustrate how cloudy radiances can be used in the profile retrieval process.

Smith, W. L.↗
NASA NTRS2008

Current Sounding Capability From Satellite Meteorological Observation With Ultraspectral Infrared Instruments

Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. The intent of the measurement of tropospheric thermodynamic state and trace abundances is the initialization of climate models and the monitoring of air quality. The NPOESS Airborne Sounder Testbed-Interferometer (NAST-I), designed to support the development of future satellite temperature and moisture sounders, aboard high altitude aircraft has been collecting data throughout many field campaigns. An advanced retrieval algorithm developed with NAST-I is now applied to satellite data collected with the Atmospheric InfraRed Sounder (AIRS) on the Aqua satellite launched on 4 May 2002 and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite launched on October 19, 2006. These instruments possess an ultra-spectral resolution, for example, both IASI and NAST-I have ~0.25 cm-1 and a spectral coverage from 645 to 2760 cm-1. The retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error less than 1 km). Retrievals of atmospheric soundings, surface properties, and cloud microphysical properties with the AIRS and IASI observations are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed? Interferometer (NAST I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the AIRS and IASI are investigated. These advanced satellite ultraspectral infrared instruments are now playing an important role in satellite meteorological observation for numerical weather prediction.

Zhou, Daniel K.↗
NASA NTRS1996

SUCCESS Studies of the Impact of Aircraft on Cirrus Clouds

During April of 1996 NASA will sponsor the SUCCESS project to better understand the impact of subsonic aircraft on the Earth's radiation budget. We plan to better determine the radiative properties of cirrus clouds and of contrails so that satellite observations can better determine their impact on Earth's radiation budget. We hope to determine how cirrus clouds form, whether the exhaust from subsonic aircraft presently affects the formation of cirrus clouds, and if the exhaust does affect the clouds whether the changes induced are of climatological significance. We seek to pave the way for future studies by developing and testing several new instruments. We also plan to better determine the characteristics of gaseous and particulate exhaust products from subsonic aircraft and their evolution in the region near the aircraft. In order to achieve our experimental objectives we plan to use the DC-8 aircraft as an in situ sampling platform. It will carry a wide variety of gaseous, particulate, radiative, and meteorological instruments. We will also use a T-39 aircraft primarily to sample the exhaust from other aircraft. It will carry a suite of instruments to measure particles and gases. We will employ an ER-2 aircraft as a remote sensing platform. The ER-2 will act as a surrogate satellite so that remote sensing observations can be related to the in situ parameters measured by the DC-8 and T-39. The mission strategy calls for a 5 week deployment beginning on April 8, 1996, and ending on May 10, 1996. During this time all three aircraft will be based in Salina, Kansas. A series of flights, averaging one every other day during this period, will be made mainly near the Department of Energy's Climate and Radiation Testbed site (CART) located in Northern Oklahoma, and Southern Kansas. During this same time period an extensive set of ground based measurements will be made by the DOE, which will also be operating several aircraft in the area to better understand the radiative properties of the atmosphere. Additional flights will be made over the Rocky Mountains, to investigate wave clouds. Flights will also be made over the Gulf of Mexico to utilize an oceanic background for remote sensing measurements. The results of this mission will be presented in this talk.

Toon, Owen B.↗
NASA NTRS2018

Three-Dimensional Sensor Forward Modeling of Clouds and Precipitation in the Multi-Instrument Inverse Solver Testbed (MIIST)

Sensor forward models are an essential tool for interpreting remote sensing observations and performing quantitative estimates of geophysical parameters. Our three-dimensional forward modeling and retrieval framework allows us to perform detailed analyses of NASA field campaign datasets for a deeper understanding of the remote sensing of clouds and precipitation. This presentation details the componenets of this radiative transfer model used to simulate active (radar) and passive (microwave radiometer) observations, and we give some relevant examples based on both model precipitation systems and actual observations.

Adams, Ian S.↗
NASA NTRS2008

High Vertically Resolved Atmospheric State Revealed with IASI Single FOV Retrievals under All-weather Conditions

The Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite was launched on October 19, 2006. The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25 cm(exp -1) and a spectral coverage from 645 to 2760 cm(exp -1). Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated to benefit future NPOESS operation.

Zhou, Daniel K.↗