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NASA NTRS2019

Impact of GMI All-Sky Radiance Assimilation in the NASA GEOS Forecast System

The assimilation of cloud- and precipitation-affected ("all-sky") radiances has become an important focus of development at most numerical weather prediction centers. Efforts at the Global Modeling and Assimilation Office (GMAO) have focused on all-sky assimilation of GPM Microwave Imager (GMI) radiances, which became operational in the GEOS real-time production system in July 2018. Implementation of the all-sky capability required several upgrades to the GEOS hybrid 4D-EnVar assimilation infrastructure including the addition of control variables for cloud liquid, cloud ice, rain and snow, enhancements to the radiative transfer model, new hybrid background and observational error models, and modified quality control and bias correction procedures. This talk describes the impact of GMI all-sky radiance assimilation on GEOS analyses and forecasts as determined from examination of various metrics including statistics of background departures and analysis increments, forecast skill scores, and forecast sensitivity observation impact (FSOI) calculations. It is shown that in addition to the hydrometeors themselves, the initial wind, temperature and pressure fields all undergo significant dynamic adjustment in response to the analyzed cloud and precipitation features. Assimilation of GMI radiances leads to improved forecasts of lower tropospheric wind, temperature and humidity, especially in the tropics. The largest forecast improvements occur during the first 48 hours, with diminishing impact thereafter. However, combining GMI all-sky assimilation with improvements to the GEOS model physics as in the recent implementation of the real-time production system, extends these forecast improvements well in to the medium range. FSOI results based on a 24-hr moist global energy norm show that GMI radiances provide nearly uniform beneficial impact throughout the tropics, with more mixed impacts in the subtropics. While the overall impact of GMI is smaller than that of other, much more numerous microwave and hyperspectral infrared radiance types, its impact is among the largest of all radiance types on a per-observation basis.

Gelaro, Ron↗

NASA NTRS2019

Retrieval of Snow Freeboard of Antarctic Sea Ice Using Waveform Fitting of CryoSat-2 Returns

In this paper we develop a CryoSat-2 algorithm to retrieve the surface elevation of the air–snow interface over Antarctic sea ice. This algorithm utilizes a two-layer physical model that accounts for scattering from a snow layer atop sea ice as well as scattering from below the snow surface. The model produces waveforms that are fit to CryoSat-2 level 1B data through a bounded trust region least-squares fitting process. These fit waveforms are then used to track the air–snow interface and retrieve the surface elevation at each point along the CryoSat-2 ground track, from which the snow freeboard is computed. To validate this algorithm, we compare retrieved surface elevation measurements and snow surface radar return power levels with those from Operation IceBridge, which flew along a contemporaneous CryoSat-2 orbit in October 2011 and November 2012. Average elevation differences (standard deviations) along the flight lines (IceBridge Airborne Topographic Mapper, ATM – CryoSat-2) are found to be 0.016 cm (29.24 cm) in 2011 and 2.58 cm (26.65 cm) in 2012. The spatial distribution of monthly average pan-Antarctic snow freeboard found using this method is similar to what was observed from NASA's Ice, Cloud, and land Elevation Satellite (ICESat), where the difference (standard deviation) between October 2011–2017 CryoSat-2 mean snow freeboard and spring 2003–2007 mean freeboard from ICESat is 1.92 cm (9.23 cm). While our results suggest that this physical model and waveform fitting method can be used to retrieve snow freeboard from CryoSat-2, allowing for the potential to join laser and radar altimetry data records in the Antarctic, larger (∼30 cm) regional differences from ICESat and along-track differences from ATM do exist, suggesting the need for future improvements to the method. Snow–ice interface elevation retrieval is also explored as a potential to obtain snow depth measurements. However, it is found that this retrieval method often tracks a strong scattering layer within the snow layer instead of the actual snow–ice interface, leading to an overestimation of ice freeboard and an underestimation of snow depth in much of the Southern Ocean but with promising results in areas such as the East Antarctic sector.

Fons, Steven W.↗

DOE OSTI2024

Bulk cloud microphysical properties as seen from numerical simulation and remote sensing products: case study of a hailstorm event over the La Plata Basin

Hailstorms develop over the La Plata Basin, in south-eastern South America, more often during later winter and early austral spring, between September and October. These systems have significant socioeconomic impacts over the region. Thus, a better understanding of how atmospheric drivers modulate the formation of hailstorms is important to improve the forecast of such phenomena. In this study, we selected a hailstorm event observed over the eastern La Plata Basin during 14–15 July 2016 to evaluate the performance of the Brazilian developments on the Regional Atmospheric Modelling System (BRAMS) model. The ability of the model in simulating cloud microphysical properties was evaluated by comparing simulations driven by different global forcings against in situ and remote sensing observations. The model results showed good skill in capturing the basic characteristics of the thunderstorm, particularly in terms of the spatial distribution of hydrometeors. The simulated spatial distribution of hail covers locations where hail fall was reported. The BRAMS simulations suggest that, despite relatively low values of the convective available potential energy (CAPE) (700–1000 J kg -1 ), environments with strong 0–8-km bulk shear (60–70 kt, ~30.9–36.0 m s –1 ) can promote the formation of ice clouds and hail fall over the eastern La Plata Basin. To be more conclusive, however, further research is needed to understand how different combinations of CAPE and shear affect hail formation over the region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) (Final Campaign Report)

The Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) campaign was conducted at the National Oceanic and Atmospheric Administration’s (NOAA) Barrow Atmospheric Baseline Observatory (71.3230° N, 156.6114° W, “BRW” hereafter), next to the Atmospheric Radiation Measurement (ARM) user facility NSA site and ~ 6 km northeast of the town of Utqiaġvik. The location of the NSA site is shown in Figure 1. Our observing period began in October 2021 and continued until May 2024. This campaign was funded by the U.S. Department of Energy (DOE) Office of Science Early Career Research Program through grant number DE-SC001879. This grant contains funding for three ARM field campaigns. The previous field campaigns were performed at ARM’s Southern Great Plains atmospheric observatory in Oklahoma (SGP; 36.6073° N, 97.4876° W) and the ARM’s Eastern North Atlantic atmospheric observatory on Graciosa Island, Azores (ENA; 39.0916° N, 28.0257° W). The ExINP-NSA campaign aims included: • Determining the number concentration of ice-nucleating particles (n INPs ) active at temperatures spanning the range of heterogeneous freezing processes (from ≈−30 °C to 0 °C) using a combination of online and offline measurements, • Determining whether local meteorological conditions and/or synoptic scale air mass transport impact INP abundance and/or ice nucleation efficiency, • Examining if the physicochemical properties of INPs relate to aerosol chemistry, and • Assessing if there is a similarity in INP properties across three ARM sites Multi-seasonal datasets of INP abundance in the NSA region were delivered from this campaign. This campaign also allowed researchers to perform a comprehensive analysis of atmospheric INPs based on long- term ground-based measurements in the Alaskan Arctic. Our data and results from the ExINP-NSA campaign will help refine current earth system models. One of the stated goals of ARM is to advance aerosol-cloud ice interaction, which will be a direct result of this campaign. Current earth system models poorly represent INPs, and the 15-minute time resolution data over several seasons generated during this campaign will provide an invaluable resource, especially combined with the datasets generated during two previous ARM ExINP campaigns. These datasets will allow for a greater understanding of ice nucleation processes as they may (or may not) relate to local meteorological processes and aerosol chemistry and will eventually help further the understanding of the Earth’s atmospheric processes and energy balance.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2014

NASA Glenn Icing Research Tunnel: 2014 Cloud Calibration

The results of the December 2013 to February 2014 Icing Research Tunnel full icing cloud calibration are being presented to the SAE AC-9C committee, as represented in the 2014 cloud calibration report. The calibration steps included establishing a uniform cloud and conducting drop size and liquid water content calibrations. The goal of the calibration was to develop a uniform cloud, and to generate a transfer function from the inputs of air speed, spray bar atomizing air pressure and water pressure to the outputs of median volumetric drop diameter and liquid water content. This was done for both 14 CFR Parts 25 and 29, Appendix C (typical icing) and soon-to-be released Appendix O (supercooled large drop) conditions.

drop size↗

NASA NTRS2003

Modeling Aerosol Nucleation

The goal of this work has been to understand how nitric acid condenses on cirrus ice cloud particles by analyzing data obtained during the SAGE III Ozone Loss and Validation Experiment (SOLVE) research mission based out of Kiruna, Sweden. Ms. Gamblin simultaneously analyzed gas phase nitric acid data along with particulate NO, data, particulate, vapor and gas-phase water data from several different instruments, particle size data, which included surface area and volume measurements, ozone concentration data as well as temperature, pressure and GPS coordinates of the sampled air parcel. All parameters where held constant with only one allowed to vary in order to determine what controls the extent to which nitric acid will condensation on ice. In addition, this data was compared to theoretical values of nitric acid condensation on ice based upon recent laboratory data. Comparison of these two data sets shows the field data does not agree with what is expected in the laboratory at comparable temperatures and nitric acid pressures. The most significant difference is that surface coverages in the atmosphere were found to be elevated relative to surface coverages measured in the laboratory. The results of this study were accepted for publication by Geophysical Research Letters.

Toon, Owen B.↗

NASA NTRS1992

Does UV instrumentation effectively measure ozone abundance?

Measurements of O3 on Mars provide significant information about the chemistry and composition of the atmosphere, including long-term changes. The most extensive and accurate data were inferred from the Mariner 9 UV spectrometer experiment. Mars O3 shows strong seasonal and latitudinal variation, with column abundances ranging from 0.2 microns at equatorial latitudes to 60 microns over the northern winter polar latitudes (1 micron-atm is a column abundance of 2.689 x 10(exp 15) molecules cm(exp-2)). The Mariner 9 UV spectrometer scanned from 2100 to 3500 Angstroms in one of its two spectral channels every 3 seconds with a spectral resolution of 15 Angstroms and an effective field-of-view of approximately 300 km(exp 2). Measurements were made for almost half a Martian year, with winter and spring in the Northern Hemisphere and summer and fall in the Southern Hemisphere. The detectability limit of the spectrometer was approximately 3 microns of ozone. The UV spectrometer on Mariner 9 was incapable of penetrating the dust during dust storms; the single-scattering albedo and phase function of airborne dust and cloud ice are not known to the degree required to extract the small UV signal reflected up from near the surface. The reflectance spectroscopy technique would also have difficulty detecting the total column abundance of O3 in cases where large dust abundances exist together with the polar hood, especially at high latitudes where large solar zenith angles magnify those optical depths; yet these cases would contain the maximum O3, based on theoretical results. It is quite possible that the maximum O3 column abundance observed by Mariner 9 of 60 microns is common. In fact, larger quantities may exist in some of the colder areas with optically thick clouds and dust. As the Viking period often had more atmospheric dust loading than did that of Mariner 9, the reflectance spectroscopy technique may even have been incapable of detecting the entire O3 column abundance during much of the Mars year that Viking observed, particularly at high latitudes.

Lindner, Bernhard Lee↗

NASA NTRS2003

Latent Heating Retrieval from TRMM Observations Using a Simplified Thermodynamic Model

A procedure for the retrieval of hydrometeor latent heating from TRMM active and passive observations is presented. The procedure is based on current methods for estimating multiple-species hydrometeor profiles from TRMM observations. The species include: cloud water, cloud ice, rain, and graupel (or snow). A three-dimensional wind field is prescribed based on the retrieved hydrometeor profiles, and, assuming a steady-state, the sources and sinks in the hydrometeor conservation equations are determined. Then, the momentum and thermodynamic equations, in which the heating and cooling are derived from the hydrometeor sources and sinks, are integrated one step forward in time. The hydrometeor sources and sinks are reevaluated based on the new wind field, and the momentum and thermodynamic equations are integrated one more step. The reevalution-integration process is repeated until a steady state is reached. The procedure is tested using cloud model simulations. Cloud-model derived fields are used to synthesize TRMM observations, from which hydrometeor profiles are derived. The procedure is applied to the retrieved hydrometeor profiles, and the latent heating estimates are compared to the actual latent heating produced by the cloud model. Examples of procedure's applications to real TRMM data are also provided.

Grecu, Mircea↗

NASA NTRS1978

A cloud physics radiometer

The paper describes the design features and capabilities of a seven-channel cloud physics radiometer (CPR) for remote sensing of cloud properties. The CPR channel characteristics and functions are tabulated and diagrammed. Each of the first three channels utilizes a photo-multipler detector, with the high-voltage power supply integrated with the tube into a single unit. In operation a heater is used to keep the optics temperature at or above 273 K and this temperature is constantly monitored. The last four channel detectors and filters are all cooled to the temperature of liquid nitrogen. The inclined scanning mirror rotates at a rate of 3.48 rps. Registration pulses are triggered and recorded as the mirror enters and leaves the + or -45 deg earth observation region. The ice-cloud, water cloud, snow discriminator detector has worked quite well in general. Interesting radiometer data have been obtained and their analysis is under way. The combination of the CPR and the Cloud Lidar System will make possible sophisticated remote sensing cloud studies.

Kyle, H. L.↗

NASA NTRS2002

Towards a Multisensor Approach to Improve on Current TRMM Retrievals of Clouds and Precipitation

The Tropical Rainfall Measuring Mission (TRMM) was designed to measure tropical rainfall and its variation from a low inclination orbiting satellite. The TRMM payload was carefully chosen to overcome a number of limitations of past satellite observing systems. This payload is predicated on the combination of active and passive observations from the TRMM Precipitation Radar (PR) and TRMM Microwave Imager (TMI) and Visible and Infrared Scanner (VIRS). Our research over the past three years has been devoted to the challenge of developing the most effective way of combining complementary information from these sensors to provide the most consistent estimate of precipitation. We have approached this problem from three directions. The first was to carry out preliminary analysis of passive microwave and infrared data from the TMI and VIRS instruments to understand the character of clear and cloudy skies in the basis defined by polarization and brightness temperature differences. Using this information as a foundation, the properties of two retrieval algorithms were analyzed, one for retrieving ice clouds from VIRS that was developed in parallel with this project and the other for rainfall from the TMI. Finally, the knowledge gleaned from each of these studies, coupled with ancillary data from NWP models and a broadband radiative transfer model, was used to create and algorithm for synthesizing the principal components of the Earth's energy budget from the basic building blocks of the atmosphere, gases, clouds, and precipitation. Principal results from each of these areas of research and their role in the TRMM and climate communities are summarized.

Stephens, Graeme L.↗

NASA NTRS2014

A Range Correction for Icesat and Its Potential Impact on Ice-sheet Mass Balance Studies

We report on a previously undocumented range error in NASA's Ice, Cloud and land Elevation Satellite (ICESat) that degrades elevation precision and introduces a small but significant elevation trend over the ICESat mission period. This range error (the Gaussian-Centroid or 'G-C'offset) varies on a shot-to-shot basis and exhibits increasing scatter when laser transmit energies fall below 20 mJ. Although the G-C offset is uncorrelated over periods less than1 day, it evolves over the life of each of ICESat's three lasers in a series of ramps and jumps that give rise to spurious elevation trends of −0.92 to −1.90 cm yr(exp −1), depending on the time period considered. Using ICESat data over the Ross and Filchner-Ronne ice shelves we show that (1) the G-C offset introduces significant biases in ice-shelf mass balance estimates, and (2) the mass balance bias can vary between regions because of different temporal samplings of ICESat.We can reproduce the effect of the G-C offset over these two ice shelves by fitting trends to sample-weighted mean G-C offsets for each campaign, suggesting that it may not be necessary to fully repeat earlier ICESat studies to determine the impact of the G-C offset on ice-sheet mass balance estimates.

mass balance↗

NASA NTRS2008

Characterization of MJO-Related Upper Tropospheric Hydrological Processes using MLS

This study quantifies Madden-Julian Oscillation (MJO)- related hydrological variability in the upper troposphere/ lower stratosphere (UT/LS) using Aura Microwave Limb Sounder (MLS) cloud ice water content (IWC) and water vapor (H2O). In a composite of six boreal-winter MJO events, the UT/LS IWC anomaly is strongly positively correlated with the convection (TRMM rainfall) anomaly. IWC anomalies range from +/-2 mg/cu m at 215 hPa to +/-0.08 mg/cu m at 100 hPa. The UT/LS H2O anomaly has an eastward-tilting structure similar to the previous-documented temperature structure, but the H2O maximum lags the temperature maximum by about a week. The H2O anomaly is positively correlated with the convection anomaly in the UT (261 hPa) and LS (68 hPa) but negatively correlated with the convection anomaly near the tropopause (100 hPa). This analysis provides a multi-parameter construct useful in validating and improving the parameterization of convection, clouds and cloud microphysics in MJO modeling.

Atmospheric Infrared Sounder (AIRS)↗

NASA NTRS2020

A Machine Learning-Based Cloud Detection and Thermodynamic Phase Classification Algorithm using Passive Spectral Observations

We trained two Random Forest (RF) machine-learning models for cloud mask and cloud thermodynamic phase detection using spectral observations from VIIRS on Suomi NPP (SNPP). Observations from CALIOP were carefully selected to provide reference labels. The two RF models were trained for all-day and daytime-only conditions using a 4-year collocated VIIRS/CALIOP dataset from 2013 to 2016. Due to the orbit difference, the collocated CALIOP and SNPP VIIRS training samples cover a broad viewing zenith angle range, which is a great benefit to overall model performance. The all-day model uses 3 VIIRS infrared (IR) bands (8.6,11, and 12 μm) and the daytime model uses 5 Near-IR (NIR) and Shortwave-IR (SWIR) bands (0.86, 1.24, 1.38, 1.64 and 2.25 μm) together with the 3 IR bands to detect clear, liquid water, and ice cloud pixels. Up to 7 surface types, namely, ocean/water, forest, cropland, grassland, snow/ice, barren/desert, and shrubland, were considered separately to enhance performance for both models. Detection of cloudy pixels and thermodynamic phase with the two RF models were compared against collocated CALIOP products from 2017. It is shown that, with a conservative screening process that excludes the most challenging cloudy pixels for passive remote sensing, the two RF models have high accuracy rates in comparison with the CALIOP reference for both cloud detection and thermodynamic phase. Other existing SNPP VIIRS and Aqua MODIS cloud mask and phase products are also evaluated, with results showing that the two RF models and the MODIS MYD06 optical property phase product are the top 3 algorithms with respect to lidar observations during the daytime. During the nighttime, the RF all-day model works best for both cloud detection and phase, in particular for pixels over snow/ice surfaces. The present RF models can be extended to other similar passive instruments if training samples can be collected from CALIOP or other lidars. However, the quality of reference labels and potential sampling issues that may impact model performance would need further attention.

cloud detection↗

NASA NTRS2006

Potential Nighttime Contamination of CERES Clear-sky Field of View by Optically Thin Cirrus during the CRYSTAL-FACE Campaign

We investigate the outgoing broadband longwave (LW, 5 to approx. 200 microns) and window (WIN, 8 to approx. 12 microns) channel radiances at the top of atmosphere (TOA) under clear-sky conditions, using data acquired by the Cloud and the Earth s Radiant Energy System (CERES) and Moderate-Resolution Imaging Spectroradiometer (MODIS) instruments onboard the NASA Terra satellite platform. In this study, detailed analyses are performed on the CERES Single Scanner Footprint TOA/Surface Fluxes and Clouds product to understand the radiative effect of thin cirrus. The data are acquired over the Florida area during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers Florida Area Cirrus Experiment (CRYSTAL-FACE) field program. Of particular interest is the anisotropy associated with the radiation field. Measured CERES broadband radiances are compared to those obtained from rigorous radiative transfer simulations. Analysis of results from this comparison indicates that the simulated radiances tend to be larger than their measured counterparts, with differences ranging from 2.1% to 8.3% for the LW band and from 1.7% to 10.6% for the WIN band. The averaged difference in radiance is approximately 4% for both the LW and WIN channels. A potential cause for the differences could be the presence of thin cirrus (i.e., optically thin ice clouds with visible optical thicknesses smaller than approximately 0.3). The detection and quantitative analysis of these thin cirrus clouds are challenging even with sophisticated multispectral instruments. While large differences in radiance between the CERES observations and the theoretical calculations are found, the corresponding difference in the anisotropic factors is very small (0.2%). Furthermore, sensitivity studies show that the influence due to a 1 K bias of the surface temperature on the errors of the LW and WIN channel radiances is of the same order as that associated with a 2% bias of the surface emissivity. The LW and WIN errors associated with a 5% bias of water vapor amount in the lower atmosphere in conjunction with a 50% bias of water vapor amount in the upper atmosphere is similar to that of a 1 K bias of the vertical temperature profile. Even with the uncertainties considered for these various factors, the simulated LW and WIN radiances are still larger than the observed radiances if thin cirrus clouds are excluded.

Lee, Yong-Keun↗

NASA NTRS1998

Results from the Mars Global Surveyor Thermal Emission Spectrometer

The Thermal Emission Spectrometer spectra of low albedo surface materials suggests that a four to one mixture of pyroxene to plagioclase, together with about a 35 percent dust component provides the best fit to the spectrum. Qualitative upper limits can be placed on the concentration of carbonates (<10 percent), olivine (<10 percent), clay minerals (<20 percent), and quartz (<5 percent) in the limited regions observed. Limb observations in the northern hemisphere reveal low-lying dust hazes and detached water-ice clouds at altitudes up to 55 kilometers. At an aerocentric longitude of 224 degrees a major dust storm developed in the Noachis Terra region. The south polar cap retreat was similar to that observed by Viking.

unmanned↗

NASA NTRS2019

Characterizing the System Impulse Response Function from Photon-Counting LiDAR Data

NASA's Multiple Altimeter Beam Experimental LiDAR (MABEL) is an aircraft-based photon-counting laser altimeter designed as a simulator to test measurement techniques and algorithms for Advanced Topographic Laser Altimeter System (ATLAS), the sole instrument on NASA's Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. By measuring the time of flight, pointing angle, and absolute position for individual photons, ICESat-2 provides detailed elevation measurements of earth's surface. Calculating accurate and precise elevations requires an understanding of how photons interact with surfaces, and characterization of the photon distribution after returning from surfaces. Neither MABEL nor ATLAS records the transmitted laser pulse shape, relying instead on aggregating several pulses worth of photons, often using histograms, to characterize the pulse shape. In this paper, we assess the limitations of using histograms and propose a more robust method to describe MABEL's system impulse-response function using an exponentially modified Gaussian distribution. We also provide standard error estimates for the arithmetic mean and standard deviation calculations, and for exponentially modified Gaussian parameters using a Monte Carlo sensitivity analysis. We apply this method to photon returns from a sea ice lead and from a dry salt lake bed as case studies for estimating the standard error associated with sample size for the arithmetic mean and standard deviation, and for the exponentially modified Gaussian parameters. We use these standard errors to calculate the minimum number of photons required to find both Gaussian and exponentially modified Gaussian distribution parameters within 3 cm of their parent population values.

photoncounting↗

NASA NTRSDate not supplied

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral instruments produce high-resolution and information-dense radiance spectra, thus offering the opportunity to reduce uncertainties in retrieval products. An optimal estimation-based cirrus cloud optical and microphysical product retrieval is under development for the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Earth Surface Mineral Dust Source Investigation (EMIT) instruments, and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder). The spectral coverage of all three instruments includes the ultraviolet, visible, and near-infrared. In this study a very fast radiative transfer model, the Principal Component-based Radiative Transfer Model in the solar spectral region (PCRTM-Solar), is used for forward modeling computations. This will reduce the computational burden in the forward radiance and Jacobian calculations as the cost function is minimized, enabling the entire AVIRIS, EMIT, and CLARREO-Pathfinder spectral range to be used in the optimal estimation framework. Using the entire spectrum will maximize the information content, resulting in a more robust and more accurate retrieval. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water. Preliminary results will be shown.

Jeffrey Mast↗

DOE OSTI2021

Triple-frequency radar retrieval of microphysical properties of snow

Abstract. An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterised by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment For Future Precipitation Mission. During this campaign, in situ microphysical probes were mounted on the same aeroplane as the radars. This nearly perfectly co-located dataset of the remote and in situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content (IWC) and mean mass-weighted diameters obtaining root-mean-square errors of 0.13 and 0.15, respectively, for log 10IWC and log 10Dm. The retrieval of the degree of riming is more challenging, and only the algorithm that uses Doppler information obtains results that are highly correlated with the in situ data.

54 ENVIRONMENTAL SCIENCES↗