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NASA NTRSDate not supplied

Enhancing Radiative Transfer Models for Optimized Assimilation of Microwave and Radar Observations

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.

Isaac Moradi↗
NASA NTRSDate not supplied

Optimizing Assimilation of Microwave and Radar Observations in the NWP Models

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.

Isaac Moradi↗
NASA NTRSDate not supplied

Assimilation of Spaceborne Microwave and Radar Observations

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.

Isaac Moradi↗
NASA NTRSDate not supplied

Hyperspectral Sounder Products: SiFSAP and ClimFiSP

Infrared hyperspectral sounders have demonstrated to provide very high value information for a range of weather and climate applications. Traditional retrieval algorithms of hyperspectral sounders use the ‘cloud clearing’ methodology in the retrieval process due to the lack of means to account for cloud scattering effect. The corresponding Level-2 data products are therefore limited by two major factors: the degradation of spatial resolution as compared with the native resolution of the instruments and the lack of ‘radiance closure’ that is critically needed for climate trend studies. The single field-of-view (FOV) sounder atmospheric products (SiFSAP) algorithm has been developed to supplement existing operational products. The SiFSAP algorithm uses the principal component based radiative transfer model (PCRTM) that is ultra-fast and has been extensively validated for the cloud scattering simulation capability. The cloud properties are physically retrieved along with profiles of temperature, moisture, and trace gases of interest, surface properties simultaneously by fitting single FOV spectral measurements. Therefore, SiFSAP ensure the radiometric consistency between the retrieved geophysical properties and the top-of-atmosphere (TOA) spectral measurements. This presentation provides a general introduction of SiFSAP and details about the physical retrieval algorithm. Also introduced here is a derivative data product of SiFSAP, the climate fingerprinting Sounder Products (ClimFiSP). ClimFiSP include the space-time averaged properties of key climate variables that are derived from the space-time averaged radiances via the spectral fingerprinting scheme. The spectral fingerprinting method allows a low latency data update on ClimFiSP following any potential calibration update on satellite measurements. ClimFiSP also include the rigorously defined uncertainty characterization for trends or anomalies of climate variables, being critical for the construction of long-term climate data record. Both SiFSAP and ClimFiSP will be available to users through NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC).

Wan Wu↗
NASA NTRS1992

Multiple scattering lidar returns from stratus clouds

Multiple scattering lidar returns from stratus clouds were measured using a multi-field-of-view (MFOV) lidar operating at 1.054 microns. The detector consists of four concentric silicon photodiodes which define half-angle fields of view (FOV) of 3.8, 12.5, 25 and 38.5 mrad. The central FOV receives the conventional lidar signal, while the outer FOV's receive only multiply scattered contributions. The ratios of the signals in the outer FOV's to the signal in the central FOV is an indication of the lateral spreading of the scattered component of the laser pulse as it propagates through the cloud. MFOV lidar returns from stratus clouds measured between October 1991 and March 1992 can be divided into two distinct types, those with large multiple scattering ratios and those with small ratios. An example of each type of return is shown. Both measurements were made at an elevation angle of 45 degrees. Clouds with small multiple scattering signals probably have a high concentration of much larger particles on the order of hundreds of micrometers in size. This is a typical size range for suspended ice crystals or precipitations. Stratus clouds often have a high concentration of ice crystals even when there is no precipitation. Large ice crystals would give smaller signals in the outer FOV's because much of the scattered intensity is contained in a narrow diffraction peak with an angular width on the order of milliradians. The result is that for a given extinction, many more orders of scattering are required for the laser pulse to spread out. So far we have not been able to do simulations of MFOV lidar returns from ice crystal clouds because of uncertainties about the phase function of the crystals, particularly the magnitude of the backscatter peak at 180 degrees. On two occasions, MFOV lidar returns measured just prior to snowfall, showed a striking vertical profile. An example is shown. From 900 to 1300m, the multiply scattered signals are negligible compared to the return in the central FOV. Abruptly, at 1300m strong signals begin in the outer FOVs. These results could be explained by the presence of a cloud layer composed of water droplets at a range of 1300m (or 900m above ground) with snow precipitations forming at the bottom of the cloud. By measuring the polarization ratio of lidar signals, Pal and Carswell have observed snow precipitating from a cloud layer composed of water droplets. Based on these results, we believe that analysis of multiple scattering lidar returns can yield important information on the phase of cloud particles.

Hutt, D. L.↗
NASA NTRS2018

Impact of the Ozone Monitoring Instrument Row Anomaly on the Long-Term Record of Aerosol Products

Since about three years after the launch the Ozone Monitoring Instrument (OMI) on the EOS-Aura satellite, the sensor's viewing capability has been affected by what is believed to be an internal obstruction that has reduced OMI's spatial coverage. It currently affects about half of the instrument's 60 viewing positions. In this work we carry out an analysis to assess the effect of the reduced spatial coverage on the monthly average values of retrieved aerosol optical depth (AOD), single scattering albedo (SSA) and the UV Aerosol Index (UVAI) using the 2005-2007 three-year period prior to the onset of the row anomaly. Regional monthly average values calculated using viewing positions 1 through 30 were compared to similarly obtained values using positions 31 through 60, with the expectation of finding close agreement between the two calculations. As expected, mean monthly values of AOD and SSA obtained with these two scattering-angle dependent subsets of OMI observations agreed over regions where carbonaceous or sulphate aerosol particles are the predominant aerosol type. However, over arid regions, where desert dust is the main aerosol type, significant differences between the two sets of calculated regional mean values of AOD were observed. As it turned out, the difference in retrieved desert dust AOD between the scattering-angle dependent observation subsets was due to the incorrect representation of desert dust scattering phase function. A sensitivity analysis using radiative transfer calculations demonstrated that the source of the observed AOD bias was the spherical shape assumption of desert dust particles. A similar analysis in terms of UVAI yielded large differences in the monthly mean values for the two sets of calculations over cloudy regions. On the contrary, in arid regions with minimum cloud presence, the resulting UVAI monthly average values for the two sets of observations were in very close agreement. The discrepancy under cloudy conditions was found to be caused by the parameterization of clouds as opaque Lambertian reflectors. When properly accounting for cloud scattering effects using Mie theory, the observed UVAI angular bias was significantly reduced. The analysis discussed here has uncovered important algorithmic deficiencies associated with the model representation of the angular dependence of scattering effects of desert dust aerosols and cloud droplets. The resulting improvements in the handling of desert dust and cloud scattering have been incorporated in an improved version of the OMAERUV algorithm.

Atmospheric Chemistry↗
NASA NTRS1990

Optical and morphological properties of Cirrus clouds determined by the high spectral resolution lidar during FIRE

Cirrus clouds reflect incoming solar radiation and trap outgoing terrestrial radiation; therefore, accurate estimation of the global energy balance depends upon knowledge of the optical and physical properties of these clouds. Scattering and absorption by cirrus clouds affect measurements made by many satellite-borne and ground based remote sensors. Scattering of ambient light by the cloud, and thermal emissions from the cloud can increase measurement background noise. Multiple scattering processes can adversely affect the divergence of optical beams propagating through these clouds. Determination of the optical thickness and the vertical and horizontal extent of cirrus clouds is necessary to the evaluation of all of these effects. Lidar can be an effective tool for investigating these properties. During the FIRE cirrus IFO in Oct. to Nov. 1986, the High Spectral Resolution Lidar (HSRL) was operated from a rooftop site on the campus of the University of Wisconsin at Madison, Wisconsin. Approximately 124 hours of fall season data were acquired under a variety of cloud optical thickness conditions. Since the IFO, the HSRL data set was expanded by more than 63.5 hours of additional data acquired during all seasons. Measurements are presented for the range in optical thickness and backscattering phase function of the cirrus clouds, as well as contour maps of extinction corrected backscatter cross sections indicating cloud morphology. Color enhanced images of range-time indicator (RTI) displays a variety of cirrus clouds with approximately 30 sec time resolution are presented. The importance of extinction correction on the interpretation of cloud height and structure from lidar observations of optically thick cirrus are demonstrated.

Grund, Christian John↗
NASA NTRS2023

CLASS Observation of Polarized Cloud Emission at Millimeter Wavelengths

The dynamic atmosphere imposes challenges to ground-based cosmic microwave background observation, especially for measurements on large angular scales. The hydrometeors in the atmosphere, mostly in the form of clouds, scatter the ambient thermal radiation and are known to be the main linearly polarized source in the atmosphere. This scattering-induced polarization is significantly enhanced for ice clouds due to the alignment of ice crystals under gravity, which are also the most common clouds seen at the millimeter-astronomy sites at high altitudes. This work presents a multifrequency study of cloud polarization observed by the Cosmology Large Angular Scale Surveyor experiment on Cerro Toco in the Atacama Desert of northern Chile, from 2016–2022, at the frequency bands centered around 40, 90, 150, and 220 GHz. Using a machine-learning-assisted cloud classifier, we made connections between the transient polarized emission found in all four frequencies with the clouds imaged by monitoring cameras at the observing site. The polarization angles of the cloud events are found to be mostly 90° from the local meridian, which is consistent with the presence of horizontally aligned ice crystals. The90 and 150 GHz polarization data are consistent with a power law with a spectral index of 3.90±0.06, while an excess/deficit of polarization amplitude is found at 40/220 GHz compared with a Rayleigh scattering spectrum. These results are consistent with Rayleigh-scattering-dominated cloud polarization, with possible effects from supercooled water absorption and/or Mie scattering from a population of large cloud particles that contribute to the220 GHz polarization.

Earth's clouds↗
NASA NTRS1998

Satellite Estimation of Spectral Surface UV Irradiance: Effect of Horizontally Homogeneous Clouds - 2

The local variability of UV irradiance at the Earth's surface is mostly caused by clouds in addition to the seasonal variability. Parametric representations of radiative transfer RT calculations are presented for the convenient solution of the transmission T of ultraviolet radiation through plane parallel clouds over a surface with reflectivity R(sub s). The calculations are intended for use with the Total Ozone Mapping Spectrometer (TOMS) measured radiances to obtain the calculated Lambert equivalent scene reflectivity R for scenes with and without clouds. The purpose is to extend the theoretical analysis of the estimation of UV irradiance from satellite data for a cloudy atmosphere. Results are presented for a range of cloud optical depths and solar zenith angles for the cases of clouds over a low reflectivity surface R(sub s) less than 0.1, over a snow or ice surface R(sub s) greater than 0.3, and for transmission through a non-conservative scattering cloud with single scattering albedo omega(sub 0) = 0.999. The key finding for conservative scattering is that the cloud-transmission function C(sub T), the ratio of cloudy-to clear-sky transmission, is roughly C(sub T) = 1 - R(sub c) with an error of less than 20% for nearly overhead sun and snow-free surfaces. For TOMS estimates of UV irradiance in the presence of both snow and clouds, independent information about snow albedo is needed for conservative cloud scattering. For non-conservative scattering with R(sub s) greater than 0.5 (snow) the satellite measured scene reflectance cannot be used to estimate surface irradiance. The cloud transmission function has been applied to the calculation of UV irradiance at the Earth's surface and compared with ground-based measurements.

Krothov, N.↗
NASA NTRS1974

Multiple scattering in cloud layers; some results

Theoretical methods are discussed for calculating radiative effects of aerosols. Experimental determination is emphasized for relevant aerosol parameters on a global basis to arrive at realistic estimates of heating and cooling. Internal radiation fields in very thin and very thick slabs are reviewed. Phase functions, polarization, emission by internal sources, and path length distribution are also considered.

Vandehulst, H. C.↗
NASA NTRS1991

Properties of dust and clouds in the Mars atmosphere: Analysis of Viking IRTM emission phase function sequences

An analysis of emission-phase-function (EPF) observations from the Viking Orbiter Infrared Thermal Mapper (IRTM) yields a wide variety of results regarding dust and cloud scattering in the Mars atmosphere and atmospheric-corrected albedos for the surface of Mars. A multiple scattering radiative transfer model incorporating a bidirectional phase function for the surface and atmospheric scattering by dust and clouds is used to derive surface albedos and dust and ice optical properties and optical depths for these various conditions on Mars.

Clancy, R. T.↗
NASA NTRS1992

Electromagnetic scattering in clouds

Techniques used to explain the nature of the optical effects of clouds on the light produced by lightning include a Monte Carlo simulation, an equivalent medium approach, and methods based on Boltzmann transport theory. A cuboidal cloud has been considered using transform methods and a diffusion approximation. Many simplifying assumptions have been used by authors to make this problem tractable. In this report, the cloud will have a spherical shape and its interior will consist of a uniform distribution of identical spherical water droplets. The source will be modeled as a Hertz dipole, electric or magnetic, inside or outside the cloud. An impulsive source is used. Superposition may be employed to obtain a sinusoid within an envelope which describes a lightning event. The problem is investigated by transforming to the frequency domain, obtaining Green's functions, and then using the Cagniard-DeHoop method to symbolically recover the time domain solution.

Solakiewicz, Richard↗
NASA NTRS1995

Lidar measurements of boundary layers, aerosol scattering and clouds during project FIFE

A detailed account of progress achieved under this grant funding is contained in five journal papers. The titles of these papers are: The calculation of area-averaged vertical profiles of the horizontal wind velocity using volume imaging lidar data; Volume imaging lidar observation of the convective structure surrounding the flight path of an instrumented aircraft; Convective boundary layer mean depths, cloud base altitudes, cloud top altitudes, cloud coverages, and cloud shadows obtained from Volume Imaging Lidar data; An accuracy analysis of the wind profiles calculated from Volume Imaging Lidar data; and Calculation of divergence and vertical motion from volume-imaging lidar data. Copies of these papers form the body of this report.

Eloranta, Edwin W.↗