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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Remote sensing of atmospheric particulates: Technological innovation and physical limitations in applications to short-range weather prediction

Techniques for remote sensing of particles, from cloud droplet to hailstone size, using optical and microwave frequencies are reviewed. The inherent variability of atmospheric particulates is examined to delineate conditions when the signal can give information to be effectively utilized in a forecasting context. The physical limitations resulting from the phase, size, orientation and concentration variability of the particulates are assessed.

Curran, R. J.↗
NASA NTRS1991

Monolithic microwave integrated circuit water vapor radiometer

A proof of concept Monolithic Microwave Integrated Circuit (MMIC) Water Vapor Radiometer (WVR) is under development at the Jet Propulsion Laboratory (JPL). WVR's are used to remotely sense water vapor and cloud liquid water in the atmosphere and are valuable for meteorological applications as well as for determination of signal path delays due to water vapor in the atmosphere. The high cost and large size of existing WVR instruments motivate the development of miniature MMIC WVR's, which have great potential for low cost mass production. The miniaturization of WVR components allows large scale deployment of WVR's for Earth environment and meteorological applications. Small WVR's can also result in improved thermal stability, resulting in improved calibration stability. Described here is the design and fabrication of a 31.4 GHz MMIC radiometer as one channel of a thermally stable WVR as a means of assessing MMIC technology feasibility.

Sukamto, L. M.↗
NASA NTRS1996

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

Cirrus cloud radiative and physical characteristics are determined using a combination of ground based, aircraft, and satellite measurements taken as part of the First ISCCP Region Experiment (FIRE) cirrus intensive field observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center and top heights and the corresponding temperatures. Coincident GOES-4 4-km visible (0.65 micrometer) and 8-km infrared window (11.5 micrometer) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 062 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance , extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface-based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature wer ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperature and cloud thickness from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. the parameterization of visible reflectance in terms of cloud optical depth and clear sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous advanced very high resolution radiometer (AVHRR) data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloud pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study or cirrus cloud scattering processes and remote sensing techniques.

Minnis, Patrick↗
NASA NTRS1990

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

Cirrus cloud radiative and physical characteristics are determined using a combination of ground-based, aircraft, and satellite measurements taken as part of the FIRE Cirrus Intensive Field Observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center, and top heights and the corresponding temperatures. Coincident GOES 4-km visible (0.65 micro-m) and 8-km infrared window (11.5 micro-m) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 0.62 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance, extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface- based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature were ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperatures and cloud thicknesses from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. The parameterization of visible reflectance in terms of cloud optical depth and clear-sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous AVHRR data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloudy pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study of cirrus cloud scattering processes and remote sensing techniques.

Minnis, Patrick↗
NASA NTRS1996

Passive Microwave Remote Sensing of Rainfall Considering the Effects of Wind and Nonprecipitating Clouds

It has long been shown both in theory and in observation that emission from rain drops in a raining cloud results in upwelling brightness temperature above that caused by the sea surface alone. High brightness temperatures at microwave frequencies (e.g. 37 and 19 GHz) have usually been quantitatively associated with rainfall using physical or statistical models. By comparing concurrent special sensor microwave/imager and radar data, however, we noticed many cases where there is no appreciable rainfall in a field of view (FOV) which exhibits high brightness temperature (T(sub B)) at 37 and 19 GHz. On the basis of calculations and past literature it is shown that such high brightness temperatures can be caused by nonprecipitating clouds and by wind. The effect of the wind is to create wave and high-emissivity foam on the sea surface. A model is developed to relate T(sub B) to the fractional coverage of rain, f, within a FOV. The parameters of the model are calibrated by fitting the model to the observed brightness temperature and fractional rain coverage data. The critical parameter of the model, T(sub B min.), which is the threshold brightness temperature for the presence of rain, depends on the strength of the storm. The strength of the storm is characterized by the fraction of the FOVs within a large area that have T(sub B) higher than 240 K, which is readily obtainable from satellite data alone. The instantaneous FOV rain rate R can then be obtained through the f approximately R relationship which is empirically derived using radar data. An algorithm has been proposed based on the T(sub B) approximately f and f approximately R relationship. Application of the algorithm to TOGA-COARE and Darwin storms results in reasonable instantaneous FOV rain estimate. When averaged over the entire radar scan, a more accurate and unbiased areal rain estimate can be achieved.

Qihang Li.↗
NASA NTRS2012

Heading Toward Launch with the Integrated Multi-Satellite Retrievals for GPM (IMERG)

The Day-l algorithm for computing combined precipitation estimates in GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). We plan for the period of record to encompass both the TRMM and GPM eras, and the coverage to extend to fully global as experience is gained in the difficult high-latitude environment. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in the three groups that are contributing expertise: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; 2) the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following cloud motion; and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures. In this talk we summarize the major building blocks and important design issues driven by user needs and practical data issues. One concept being pioneered by the IMERG team is that the code system should produce estimates for the same time period but at different latencies to support the requirements of different groups of users. Another user requirement is that all these runs must be reprocessed as new IMERG versions are introduced. IMERG's status at meeting time will be summarized, and the processing scenario in the transition from TRMM to GPM will be laid out. Initially, IMERG will be run with TRMM-based calibration, and then a conversion to a GPM-based calibration will be employed after the GPM sensor products are validated. A complete reprocessing will be computed, which will complete the transition from TMPA.

Huffman, George J.↗
NASA NTRS2014

MLS and CALIOP Cloud Ice Measurements in the Upper Troposphere: A Constraint from Microwave on Cloud Microphysics

This study examines the consistency and microphysics assumptions among satellite ice water content (IWC) retrievals in the upper troposphere with collocated A-Train radiances from Microwave Limb Sounder (MLS) and lidar backscatters from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). For the cases in which IWC values are small (less than 10mg m(exp-23)), the cloud ice retrievals are constrained by both MLS 240- and 640- GHz radiances and CALIOP 532-nm backscatter beta(532). From the observed relationships between MLS cloud-induced radiance T(sub cir) and the CALIOP backscatter integrated gamma532 along the MLS line of sight, an empirical linear relation between cloud ice and the lidar backscatter is found: IWC/beta532=0.58+/-0.11. This lidar cloud ice relation is required to satisfy the cloud ice emission signals simultaneously observed at microwave frequencies, in which ice permittivity is relatively well known. This empirical relationship also produces IWC values that agree well with the CALIOP, version 3.0, retrieval at values, less than 10mg m(exp-3). Because the microphysics assumption is critical in satellite cloud ice retrievals, the agreement found in the IWC-beta532 relationships increase fidelity of the assumptions used by the lidar and microwave techniques for upper-tropospheric clouds.

ice water content↗
NASA NTRS2014

Preface: Electromagnetic and Light Scattering by Nonspherical Particles XIV

The 14th Electromagnetic and Light Scattering Conference (ELS-XIV) was held at the Universit de Lille 1, Villeneuve d'Ascq, France on 17-21 June 2013. The conference was attended by 200 scientists from 26 countries. The scientific program included one plenary lecture, 12 invited reviews, 100 contributed oral talks, and 86 poster presentations. The program, the abstracts, and the slides of the oral presentations are available at the conference web site http:www-loa.univ-lille1.frELS-XIV. To highlight one of the traditional ELS themes, the ELS-XIV featured a special session on Remote sensing of aerosols and clouds using polarimetric observations. This session was sponsored and co-organized by the French space agency CNES and attracted representatives from nearly all research teams word-wide involved in the development and active use of space-borne, in situ, and ground-based polarimetric observations.

electromagnetic scattering↗
NASA NTRS2020

The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) airborne field campaign

In the fall of 2017, an airborne field campaign was conducted from the NASA Armstrong Flight Research Center in Palmdale, California, to advance the remote sensing of aerosols and clouds with multi-angle polarimeters (MAP) and lidars. The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign was jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON). Six instruments were deployed on the ER-2 high-altitude aircraft. Four were MAPs: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary EXploration (SPEX airborne), and the Research Scanning Polarimeter (RSP). The remainder were lidars, including the Cloud Physics Lidar (CPL) and the High Spectral Resolution Lidar 2 (HSRL-2). The southern California base of ACEPOL enabled observation of a wide variety of scene types, including urban, desert, forest, coastal ocean, and agricultural areas, with clear, cloudy, polluted, and pristine atmospheric conditions. Flights were performed in coordination with satellite overpasses and ground-based observations, including the Ground-based Multiangle SpectroPolarimetric Imager (GroundMSPI), sun photometers, and a surface reflectance spectrometer.

SPECTRAL-RESOLUTION LIDAR↗
NASA NTRS2021

Modeling the Radiative Effect on Microphysics in Cirrus Clouds Against Satellite Observations

The radiative effect on microphysics (REM) plays an important role in the dew/frost formation near the surface. How REM impacts cirrus clouds is investigated in this study, using bin microphysical model simulations and coincident data of the CloudSat and Global Precipitation Measurement (GPM) satellites. REM affects ice crystal spectrum with two types: radiative cooling and warming. Radiative cooling, as predicted by the bin-model simulations, favors the formation of horizontally oriented ice crystals (HOICs), but radiative warming does not. Hence, a test of REM can be transformed to a test of HOICs, because HOICs can be measured by the microwave polarization observations of the GPM Microwave Imager (GMI) at 166 GHz. To analyze the GMI data for their HOIC distribution, clouds are sorted into four groups with different optical depth and altitude, based on the radiative cooling/warming ratio (or eta) computed with satellite-retrieved ice water content. Their HOIC distributions (e.g., the midlevel thick clouds have more HOICs than the high-level ones) agree well with those predicted by the bin-model simulations. The general agreement between the GMI observations and bin-model simulations suggests that REM is common in cirrus clouds and impacts cirrus clouds significantly.

clouds↗
NASA NTRSDate not supplied

A Census of Severe Weather as Observed From Aqua: Visible/IR and Passive-Microwave Perspectives of Severe Convection

Severe weather phenomena represent the extreme upper end of the spectrum of convection and precipitation and tend to be highly localized and relatively rare compared to the rest of the distribution, but they can cause damage and loss disproportionate to their scale and frequency. Fortunately, severe convection exhibits distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Leveraging these signatures individually has become a long-established practice to detect, analyze and establish climatologies of severe thunderstorms, especially in instances where traditional ground-based data may be unavailable. Spaceborne visible/IR and passive-microwave approaches are not without their pitfalls, however: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together and assess the extent to which these datasets can be combined to improve severe thunderstorm detection. We pair AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis in six different geographical regimes throughout the Aqua domain. We present a census of potentially severe convective storms and their environments as seen by multiple instruments simultaneously, investigating how MODIS and AMSR-E signatures may be used together to diagnose storm properties and processes, and how the interrelationships between the signatures varies seasonally and geographically. Using statistical machine learning analysis, we aim to quantify the optimal MODIS and AMSR-E parameter sets for discriminating severe from non-severe storm cells and assess what improvement (if any) in detection results from combining the IR, visible, and microwave datasets.

Sarah Bang↗
NASA NTRSDate not supplied

Challenges in Remote-Sensing of Hail: Examining the Performance and Biases of Satellite Hail Retrievals Using Aqua MODIS Visible/IR and AMSR-E Passive-Microwave Observations

Hail poses threats to myriad aspects of human life and society, infrastructure, and agriculture. Scientifically, hail can often cause large errors in precipitation retrieval and estimation, posing challenges to establishing the current climatology of severe storms and their future trend in a changing Earth system. Fortunately, hailstorms exhibit distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Approaches that leverage these signatures, however, are not without their pitfalls,: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. Large horizontal areas of smaller scatterers may also meaningfully lower the brightness temperatures, especially if they are able to occupy large portions of the footprint. Radiative transfer simulations show that low frequencies such as 19- and 37-GHz can be scattered to extremely low brightness temperatures by high concentrations of smaller (graupel-sized) ice scatterers, especially in larger features that are more likely to occupy the footprint, which may cause climatologies to overestimate the frequency severe hail. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together, pairing AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis over CONUS, and then explore the performance and challenges of the algorithm when we expand outside the United States into six different geographical regimes throughout the Aqua domain.

Sarah D Bang↗
NASA NTRS2018

A13H-2546: Intercomparison of biomass burning aerosol properties from in-situ and remote-sensing instruments in ORACLES-2016

The magnitude of the cumulative effects of aerosols, both directly and on cloud properties, remains the biggest source of uncertainty in our understanding of anthropogenic radiative forcing on the climate. The magnitude of aerosol effects in any given region will depend on not just the aerosol concentration, but also on the characteristics of the aerosol under consideration. The NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign was conducted in 2016-2018 over three deployments in the Southeast Atlantic Ocean (SEA), with the goal of making observations of seasonal biomass burning (BB) smoke plumes overlying persistent stratocumulus cloud decks. During the first ORACLES deployment (September 2016), two NASA aircraft (a P-3 and an ER-2) were flown with a suite of aerosol, cloud, radiation, and meteorological instruments for remote-sensing and in-situ observations. In ORACLES, data collected by eight different instrument teams are used to derive aerosol properties over this region by independent methods. Here we present a comparison of results from the different instrument retrievals with a focus on the measures of aerosol absorption. We focus on specific cases with near-coincident measurements from in-situ (PSAP or PTI for aerosol absorption combined with a nephelometer for aerosol scattering) and remote sensing (4STAR, AirMSPI, RSP, and SSFR) instruments from coordinated flights between the two aircraft. We use the single scattering albedo (SSA), a measure of the relative absorption versus total extinction by aerosols, as the main comparable property between the various remote sensing and in-situ methods. For the remote sensing instruments, we see general good agreement in the total aerosol loading (aerosol optical depth, AOD), though see some differences in the absorbing component (AAOD). We report values for the retrieved aerosol parameters measured in the ORACLES flights and comment upon the observed variability between different instruments. Finally, we discuss these ORACLES results in the context of previous measurements of BB aerosol over the SEA.

Kristina Pistone↗
NASA NTRS1990

Comparison of satellite based cloud retrieval methods for cirrus and stratocumulus

One difficulty in using satellite remote sensing data is the spatial variability of cloud properties on scales smaller than most meteorological satellite fields of view (approx. 4 to 8 km). The variation is examined of satellite derived cloud cover as a function of the satellite sensor spatial resolution for seven cloud cover retrieval methods: (1) Reflectance threshold; (2) Temperature threshold; (3) ISCCP; (4) HBTM (Hybrid Bispectral Threshold Method); (5) NCLE; (6) Spatial coherence; and (7) Functional Box Counting. The first two methods are simple single spectral thresholds which specify a satellite pixel as cloud filled if the measured reflectance is greater than the threshold, or if the measured equivalent blackbody temperature is less than the threshold. The next three methods are bispectral, using one visible wavelength window channel and one thermal infrared wavelength window. The final two algorithms rely on the spatial variability within the cloud field to determine cloud cover. Spatial coherence assumes only that the cloud field occurs in a single layer and that the clouds are optically thick in the infrared window. LANDSAT Thematic Mapper (TM) data is used to test the spatial resolution dependence of the cloud algorithms. The ISCCP bispectral threshold applied to the full resolution data is used as the reference or truth cloud cover, after which the retrieval methods are applied to the spatial resolutions. Studies of the fraction of pixels in the scene at cloud edge, and of the profile of reflectance and temperature near cloud edges indicate an uncertainty in the reference cloud fraction of 1 to 5 percent.

Parker, Lindsay↗
NASA NTRS2011

Visualizing Airborne and Satellite Imagery

Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

Bierwirth, Victoria A.↗
NASA NTRS2003

Light Scattering by Gaussian Particles: A Solution with Finite-Difference Time Domain Technique

The understanding of single-scattering properties of complex ice crystals has significance in atmospheric radiative transfer and remote-sensing applications. In this work, light scattering by irregularly shaped Gaussian ice crystals is studied with the finite-difference time-domain (FDTD) technique. For given sample particle shapes and size parameters in the resonance region, the scattering phase matrices and asymmetry factors are calculated. It is found that the deformation of the particle surface can significantly smooth the scattering phase functions and slightly reduce the asymmetry factors. The polarization properties of irregular ice crystals are also significantly different from those of spherical cloud particles. These FDTD results could provide a reference for approximate light-scattering models developed for irregular particle shapes and can have potential applications in developing a much simpler practical light scattering model for ice clouds angular-distribution models and for remote sensing of ice clouds and aerosols using polarized light. (copyright) 2003 Elsevier Science Ltd. All rights reserved.

Sun, W.↗