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NASA NTRSDate not supplied

Spaceborne Remote Sensing of Hail: Retrievals, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in the most globally consistent way. Passive-microwave algorithms leverage the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. These retrievals are used to construct global climatologies of severe hail. The Bang and Cecil (2019) retrievals has been applied to several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and used to construct [near] global climatologies of severe hail. This retrieval, and others, have been tested using Global Precipitation Measurement (GPM) Ku-band precipitation radar, to assess their effectiveness and regional variability. A successful retrieval and climatology are those that correspond tightly to radar reflectivity and give minimal appearance of regional biases, especially with latitude. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. There are ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗

NASA NTRS2019

A Radar Investigation of Precipitation Properties During Discrepancies Between GOES-16 GLM and LMA Observed Flash Rates in the Skyline Alabama Supercell of 22 April 2017

Conclusions: GLM (Geostationary Lightning Mapper) flash rates were 2 to 5 times lower than LMA (Lightning Mapping Array) in an Alabama supercell that was tracked using a combination of GLM flash initiation density and VIL (Vertically Integrated Liquid); Since most lightning was initiating at 8-9 kilometers (and not at low levels) according to LMA, flash height does not appear to be a primary factor in low GLM flash rates; When (LMA-GLM) flash rate differences were largest, the LMA observed flash areas were relatively small (and vice versa); Flash size may be a primary factor in low GLM flash rates due to detectability and/or flash clustering issues with small flashes within the coarse 8 kilometers by 8 kilometers resolution; High cloud liquid water droplet concentrations were inferred indirectly from riming necessary for large radar MESH (Maximum Expected Size of Hail), VIL and hail/graupel volumes. High cloud water droplet concentrations in supercells may decrease GLM detection efficiency due to optical extinction of near IR (near Infrared) emitted by lightning as it moves through cloud; Despite large flash rate differences, GLM & LMA lightning jumps during robust supercell generally agreed with each other and radar trends in HID (Radar Reflectivity and Hydrometeor Identification), MESH and VIL.However, more LMA jumps (than GLM) in developing supercell and more GLM jumps (than LMA) in weak to decaying supercell. Future work: improve GLM tracking.

GLM↗

NASA NTRS1986

Radar glory from buried craters on icy moons

Three ice-covered moons of Jupiter, in comparison with rocky planets and earth's moon, produce radar echoes of astounding strengths and bizarre polarizations. Scattering from buried craters can explain these and other anomalous properties of the echoes. The role of such craters is analogous to that of the water droplets that create the apparition known as 'the glory', the optically bright region surrounding an observer's shadow on a cloud. Both situations involve the electromagnetic phenomenon of total internal reflection at a dielectric interface, operating in a geometry that strongly favors exact backscattering. Dim surface craters are transformed into bright glory holes by being buried under somewhat denser material, thereby increasing the intensity of their echoes by factors of hundreds. The dielectric interface thus formed at the crater walls nicely accounts for the unusual polarizations of the echoes.

Eshleman, Von R.↗

NASA NTRS2017

Microphysical Properties of Snow and Their Link to Ze-S Relations During BAECC 2014

This study uses snow events from the Biogenic Aerosols-Effects on Clouds and Climate (BAECC) 2014 campaign to investigate the connection between properties of snow and radar observations. The general hydrodynamic theory is applied to video-disdrometer measurements to retrieve masses of falling ice particles. Errors associated with the observation geometry and the measured particle size distribution (PSD) are addressed by devising a simple correction procedure. The value of the correction factor is determined by comparison of the retrieved precipitation accumulation with weighing-gauge measurements. Derived mass-dimensional relations are represented in the power-law form m = amDbm. It is shown that the retrieved prefactor am and exponent bm react to changes in prevailing microphysical processes. From the derived microphysical properties, event-specific relations between the equivalent reflectivity factor Ze and snowfall precipitation rate S (Ze = 5 azsSbzs ) are determined. For the studied events, the prefactor of the Ze-S relation varied between 53 and 782 and the exponent was in the range of 1.19-1.61. The dependence of the factors azs and bzs on the m(D) relation and PSD are investigated. The exponent of the Ze-S relation mainly depends on the exponent of the m(D) relation, whereas the prefactor azs depends on both the intercept parameterN0 of the PSDand the prefactors of them(D) andy(D) relations. Changes in azs for a given N0 are shown to be linked to changes in liquid water path, which can be considered to be a proxy for degree of riming.

von Lerber, Annakaisa↗

NASA NTRSDate not supplied

Detecting Hail from Space: Algorithms, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global climatologies of severe hail using several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the late 1980’s using the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We developed a passive-microwave algorithm that corresponds tightly to radar reflectivity and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗

NASA NTRS1990

Doppler radar imaging of spherical planetary surfaces

This paper describes a technique for using echo power-spectra for making radar images of spherical planetary targets. In developing the Doppler-radar imaging system, the target's reflectivity distribution is expanded in a truncated spherical harmonic series; the distribution of echo power in rotational phase and the Doppler frequency are obtained in form of a system of linear equations which express the echo spectra as functions of the series coefficients. To estimate the coefficients from an observed phase-Doppler distribution, the inversion is cast as a least-squares problem, and is solved using singular value decompositions, yielding a linear imaging system which can be fully characterized by its impulse response as a function of latitude. Simulations were designed and used to explore the capabilities of Doppler radar imaging, and the sensitivity of imaging to such factors as subradar altitude coverage and signal-to-noise ratio was investigated.

Hudson, R. Scott↗

NASA NTRSDate not supplied

Spaceborne Passive-Microwave Hail Detection: Global Climatologies, Validation, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D. Bang↗

NASA NTRS1983

Planetary geodesy

The current known geodetic parameters of the planets and their moons are reviewed. A 3:2 spin-orbit resonance has been calculated for Mercury, a planet for which previous mass estimates are suggested to be inaccurate by 30 pct. The Pioneer Venus Orbiter data indicated a Venus diameter of 6051 km, a geoid surface highly-correlated with the surface topography, and regional gravity anomalies. Reflective mirrors on the surface and data from the Lunar Orbiter 4 have produced values for the principal polar moment of inertia homogeneity factor, the earth-moon mass ratio, a fifth degree and order spherical harmonic gravity model, the lunar acceleration, and the lunar potential Love number. The Mars gravity field is now estimated up to 12th degree and order spherical harmonics from Mariner 9 and Viking Orbiters 1 and 2, which also obtained new topographical data. New gravity fields and mass are being calculated for the Jovian and Saturnian moons. The outer planets' radii and rotational periods have recently been revised to greater accuracy. New data will be forthcoming from the Space Telescope and the planned Venus Radar Mapper.

Sjogren, W. L.↗

NASA NTRS1990

Enhanced frequency spectra of winds at the mesoscale based on radar profiler observations

Frequency spectra of horizontal winds in the troposphere and stratosphere, over a range of periods and frequencies, have been studied by means of two radar profilers, located at Plattenville, Colorado, and Poker Flat, Alaska, to determine if the spectra deviations from a consistent power law behavior can be verified in a statistical sense. At Plattenville, the spectrum of both zonal and meridional winds in the troposphere is found to obey a low-frequency regime at periods longer than a few hours and a high-frequency regime at periods less than 1/2 hour. The energy levels in the high-frequency regime are enhanced over those obtained by extrapolation of the low-frequency regime by a factor of 4. At Poker Flat, a similar pattern is found in the stratosphere, and the magnitude of the enhancement factor is 1.7. It is suggested that the enhanced amplitudes reflect the effects of upward-propagating gravity waves launched by the flow over a rough terrain, and that they influence the dynamics of the large-scale circulation to a great extent.

Nastrom, G. D.↗

NASA NTRS1998

Total Lightning and Radar Storm Characteristics Associated with Severe Storms in Central Florida

This paper examines the three dimensional characteristics of lightning flashes and severe storms observed in Central Florida during 1997-1998. The lightning time history of severe and tornadic storms were captured during the on-going ground validation campaign supporting the Lightning Imaging Sensor (LIS) experiment on the Tropical Rainfall Measuring Mission (TRMM). The ground validation campaign is a collaborative experiment that began in 1997 and involves scientists at the Global Hydrology and Climate Center, MIT/Lincoln Laboratories, and the NWS Forecast Office at Melbourne, FL. Lightning signatures that may provide potential early warning of severe storms are being evaluated by the forecasters at the NWS/MLB office. Severe storms with extreme flash rates sometimes exceeding 300 per minute and accompanying rapid increases in flash rate prior to the onset of the severe weather (hall, damaging winds, tornadoes) have been reported by Hodanish et al. and Williams et al. (1998-this conference). We examine the co-evolving changes in storm structure (mass, echo top, shear, latent heat release) and kinematics associated with these extreme and rapid flash rate changes over time. The flash frequency and density are compared with the three dimensional radar reflectivity structure of the storm to help interpret the possible mechanisms producing the extreme and rapidly increasing flash rates. For two tornadic storms examined thus far, we find the burst of lightning is associated with the development of upper level rotation in the storm. In one case, the lightning burst follows the formation of a bounded weak echo region (BWER). The flash rates diminish with time as the rotation develops to the ground in conjunction with the decent of the reflectivity core. Our initial findings suggest the dramatic increase of flash rates is associated with a sudden and dramatic increase in storm updraft intensity which we hypothesize is stretching vertical vorticity as well as enhancing the development of the mixed phase region of the storm. We discuss the importance of these factors in producing both the observed extreme flash rates and the severe weather that follows in these storms and others to be presented.

Goodman, Steven J↗

NASA NTRS2008

Understanding Ice Supersaturation, Particle Growth, and Number Concentration in Cirrus Clouds

Many factors control the ice supersaturation and microphysical properties in cirrus clouds. We explore the effects of dynamic forcing, ice nucleation mechanisms, and ice crystal growth rate on the evolution and distribution of water vapor and cloud properties in nighttime cirrus clouds using a one-dimensional cloud model with bin microphysics and remote sensing measurements obtained at the Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility located near Lamont, OK. We forced the model using both large-scale vertical ascent and, for the first time, mean mesoscale velocity derived from radar Doppler velocity measurements. Both heterogeneous and homogeneous nucleation processes are explored, where a classical theory heterogeneous scheme is compared with empirical representations. We evaluated model simulations by examining both bulk cloud properties and distributions of measured radar reflectivity, lidar extinction, and water vapor profiles, as well as retrieved cloud microphysical properties. Our results suggest that mesoscale variability is the primary mechanism needed to reproduce observed quantities. Model sensitivity to the ice growth rate is also investigated. The most realistic simulations as compared with observations are forced using mesoscale waves, include fast ice crystal growth, and initiate ice by either homogeneous or heterogeneous nucleation. Simulated ice crystal number concentrations (tens to hundreds particles per liter) are typically two orders of magnitude smaller than previously published results based on aircraft measurements in cirrus clouds, although higher concentrations are possible in isolated pockets within the nucleation zone.

Comstock, Jennifer M.↗

NASA NTRS2009

Anvil Clouds of Tropical Mesoscale Convective Systems in Monsoon Regions

The anvil clouds of tropical mesoscale convective systems (MCSs) in West Africa, the Maritime Continent and the Bay of Bengal have been examined with TRMM and CloudSat satellite data and ARM ground-based radar observations. The anvils spreading out from the precipitating cores of MCSs are subdivided into thick, medium and thin portions. The thick portions of anvils show distinct differences from one climatological regime to another. In their upper portions, the thick anvils of West Africa MCSs have a broad, flat histogram of reflectivity, and a maximum of reflectivity in their lower portions. The reflectivity histogram of the Bay of Bengal thick anvils has a sharply peaked distribution of reflectivity at all altitudes with modal values that increase monotonically downward. The reflectivity histogram of the Maritime Continent thick anvils is intermediate between that of the West Africa and Bay of Bengal anvils, consistent with the fact this region comprises a mix of land and ocean influences. It is suggested that the difference between the statistics of the continental and oceanic anvils is related to some combination of two factors: (1) the West African anvils tend to be closely tied to the convective regions of MCSs while the oceanic anvils are more likely to be extending outward from large stratiform precipitation areas of MCSs, and (2) the West African MCSs result from greater buoyancy, so that the convective cells are more likely to produce graupel particles and detrain them into anvils

Cetrone, J.↗

NASA NTRSDate not supplied

A Neural Network Parametrization of Volumetric Cloud Fraction Profiles Using Satellite Observations and MERRA-2 Reanalysis Meteorological Data

Clouds play a crucial role in regulating the hydrologic cycle and Earth's radiative energy budget, yet they are often poorly represented in global climate models (GCMs). This study applies deep machine learning techniques to develop a physical parameterization of volumetric cloud fraction (VCF), the fraction of a 3-D grid volume occupied by clouds using satellite lidar-radar measurements. The neural network (NN) captures the complicated relationships between observed VCF profiles and collocated meteorological variables from MERRA-2 reanalysis data. Our results show that the NN model, particularly a sequence-to-sequence long short-term memory (LSTM) network with a sixfactor loss function, effectively learns the underlying cloud physical processes. The NN model outperforms MERRA-2 reanalysis in representing low-level clouds in tropical and subtropical regions and low- and middle-level clouds over midlatitude storm-track regions, and also improves VCF histograms. These improvements are reflected in the vertical distributions of zonally, meridionally, and globally averaged VCFs, geographic distributions of low-, middle-, and high-level clouds, and seasonal variations in monthly-mean VCF. Furthermore, the NN predictions effectively capture the El Niño-Southern Oscillation (ENSO) effects and other interannual variations. The NN parameterization is further evaluated through a sensitivity analysis, in which a single predictor is perturbed at a time. This reveals that relative humidity (RH) is the dominant factor influencing variations in globally averaged VCF at low and middle altitudes, followed by temperature. At higher altitudes, temperature becomes the primary driver of VCF through its effect on RH. Changes in wind components had minimal impact on globally averaged VCF.

Shan Zeng↗

NASA NTRS2002

Observations and Parameterizations of Particle Size Distributions in Deep Tropical Cirrus and Stratiform Precipitation Clouds: Results from In-Situ Observations in TRMM Field Campaigns

In this study, we report on the evolution of particle size distributions (PSDs) and habits as measured during slow, Lagrangian-type spiral descents through deep subtropical and tropical cloud layers in Florida, Brazil, and Kwajalein, Marshall Islands, most of which were precipitating. The objective of the flight patterns was to learn more about how the PSDs evolved in the vertical and to obtain information of the vertical structure of microphysical properties. New instrumentation yielding better information on the concentrations of particles in the size (D) range between 0.2 and 2 cm, as well as improved particle imagery, produced more comprehensive observations for tropical stratiform precipitation regions and anvils than have been available previously. Collocated radar observations provided additional information on the vertical structure of the cloud layers sampled. Most of the spirals began at cloud top, with temperatures (T) as low as -50 C, and ended at cloud base or below the melting layer (ML). The PSDs broadened from cloud top towards cloud base, with the largest particles increasing in size from several millimeters at cloud top to one centimeter or larger towards cloud base. Some continued growth was noted in the upper part of the ML. Concentrations of particles less than 1 mm in size decreased with decreasing height. The result was a consistent change in the PSDs in the vertical. Similarly, systematic changes in the size dependence of the particle cross-sectional area was noted with decreasing height. Aggregation-as ascertained from both the changes in the PSDs and evolution of particle habits as observed in high detail with the cloud particle imager (CPI) probe-was responsible for these trends. The PSDs were generally well-represented by gamma distributions of the form N = N0 gamma D microns e- lambda gamma D that were fitted to the PSDs over 1-km horizontal intervals throughout the spirals. The intercept (N0 gamma), slope (lambda gamma), and dispersion (microns) values were derived for each PSD. Exponential curves (N = N0e- lambdaD; micron = 0) were also fitted to the distributions. The lambda gamma values for given spirals varied systematically with temperature as did the values of lambda (exponential), and the data generally conformed to values found in previous studies involving exponential fits to size distributions in mid-latitude frontal and cirrus layers. Considerable variability often noted in the PSD properties during the loops of individual spirals was manifested primarily in large changes in N0 gamma and N0, but micron, lambda gamma and lambda remained fairly stable. Temperature is not found to be the sole factor controlling lambda gamma or lambda but is a primary one. Direct relationships were found between lambda gamma and N0 gamma or lambda gamma and micron for the gamma distributions and lambda and N0 for the exponential. The latter relationship was not found as distinctly in earlier studies; observed PSDs in this study had better fidelity with less scatter. The micron values changed monotonically with T over the range of temperatures and were directly related to N0 gamma or lambda gamma, thereby reducing the number of variables in the PSD functional equation to two. In the upper part of the ML, N0 and lambda continued to decrease, and in the lower part these values began to increase as the largest particles melted. We developed general expressions relating various bulk microphysical, radar, and radiative transfer-related variables to N0 gamma and lambda gamma, useful for both tropical and mid-latitude clouds. These relationships facilitate the specification of a number of bulk properties in cloud and climate models. The results presented in this paper apply best to temperatures between 0 and -40 C, for which the measured radar reflectivities fall in the range of 0 to 25 dBZe.

Heymsfield, Andrew J.↗

NASA NTRS2000

On Utilization of NEXRAD Scan Strategy Information to Infer Discrepancies Associated With Radar and Rain Gauge Surface Volumetric Rainfall Accumulations

To evaluate the Tropical Rainfall Measuring Mission (TRMM) monthly Ground Validation (GV) rain map, 42 quality controlled tipping bucket rain gauge data (1 minute interpolated rain rates) were utilized. We have compared the gauge data to the surface volumetric rainfall accumulation of NEXRAD reflectivity field, (converting to rain rates using a 0.5 dB resolution smooth Z-R table). The comparison was carried out from data collected at Melbourne, Florida during the month of July 98. GV operational level 3 (L3 monthly) accumulation algorithm was used to obtain surface volumetric accumulations for the radar. The gauge records were accumulated using the 1 minute interpolated rain rates while the radar Volume Scan (VOS) intervals remain less than or equal to 75 minutes. The correlation coefficient for the radar and gauge totals for the monthly time-scale remain at 0.93, however, a large difference was noted between the gauge and radar derived rain accumulation when the radar data interval is either 9 minute, or 10 minute. This difference in radar and gauge accumulation is being explained in terms of the radar scan strategy information. The discrepancy in terms of the Volume Coverage Pattern (VCP) of the NEXRAD is being reported where VCP mode is ascertained using the radar tilt angle information. Hourly radar and gauge accumulations have been computed using the present operational L3 method supplemented with a threshold period of +/- 5 minutes (based on a sensitivity analysis). These radar and gauge accumulations are subsequently improved using a radar hourly scan weighting factor (taking ratio of the radar scan frequency within a time bin to the 7436 total radar scans for the month). This GV procedure is further being improved by introducing a spatial smoothing method to yield reasonable bulk radar to gauge ratio for the hourly and daily scales.

Roy, Biswadev↗

NASA NTRSDate not supplied

Do Better Satellite Precipitation Algorithms Improve Landslide Hazard Assessment?

Satellites make it possible to estimate precipitation in near real time. Given the challenges of achieving global coverage by other means, these data are used widely. However, few systems for landslide hazard assessment rely on satellite precipitation estimates. This could be due in part to perceptions of accuracy, although latency, spatial resolution, and other factors may also be important. We test whether recent changes to data streams from the Global Precipitation Measurement mission (GPM) have improved its potential for use in landslide prediction. Specifically, we examine data produced by the Integrated Multi-satellitERetrievals for the GPM (IMERG) algorithm, which was upgraded to version 7 this year. IMERG relies upon other algorithms, including the Goddard Profiling Algorithm (GPROF) and the GPM Combined Radar-Radiometer Algorithm (CORRA). Many changes have been made during the switch from IMERG version 6 to version 7. These include upgrading CORRA and GPROF to version 7, to improve the accuracy of precipitation in frozen, mountainous, and coastal areas. The measured intensity of some storms has been enhanced with a new algorithm, the Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood. Combined with many others, these changes to IMERG should improve its utility for landslide hazard assessment in a variety of contexts. To test this idea, we retrain the global Landslide Hazard Assessment for Situational Awareness (LHASA) model twice—first with data from IMERG version 6B and second with 7B. Since current daily rainfall is the most important variable in determining outcomes predicted by LHASA, it should reflect changes made to that input. First, we grid the landslides at a daily, thirty-arcsecond resolution. This serves as the response variable. At each of these sites current and antecedent rainfall are extracted, along with antecedent snow mass and soil moisture, slope, and PGA. In addition, one million grid cells are selected at random points to represent conditions under which landslides (probably) do not occur. After merging these data, we hold back 20% of the dataset for validation purposes and train a machine-learning model with the rest. We assess both the model’s overall ability to identify landslides and its ability to predict specific large landslide disasters.

Thomas A Stanley↗

NASA NTRS2008

Reducing Surface Clutter in Cloud Profiling Radar Data

An algorithm has been devised to reduce ground clutter in the data products of the CloudSat Cloud Profiling Radar (CPR), which is a nadir-looking radar instrument, in orbit around the Earth, that measures power backscattered by clouds as a function of distance from the instrument. Ground clutter contaminates the CPR data in the lowest 1 km of the atmospheric profile, heretofore making it impossible to use CPR data to satisfy the scientific interest in studying clouds and light rainfall at low altitude. The algorithm is based partly on the fact that the CloudSat orbit is such that the geodetic altitude of the CPR varies continuously over a range of approximately 25 km. As the geodetic altitude changes, the radar timing parameters are changed at intervals defined by flight software in order to keep the troposphere inside a data-collection time window. However, within each interval, the surface of the Earth continuously "scans through" (that is, it moves across) a few range bins of the data time window. For each radar profile, only few samples [one for every range-bin increment ((Delta)r = 240 m)] of the surface-clutter signature are available around the range bin in which the peak of surface return is observed, but samples in consecutive radar profiles are offset slightly (by amounts much less than (Delta)r) with respect to each other according to the relative change in geodetic altitude. As a consequence, in a case in which the surface area under examination is homogenous (e.g., an ocean surface), a sequence of consecutive radar profiles of the surface in that area contains samples of the surface response with range resolution (Delta)p much finer than the range-bin increment ((Delta)p << r). Once the high-resolution surface response has thus become available, the profile of surface clutter can be accurately estimated by use of a conventional maximum-correlation scheme: A translated and scaled version of the high-resolution surface response is fitted to the observed low-resolution profile. The translation and scaling factors that optimize the fit in a maximum-correlation sense represent (1) the true position of the surface relative to the sampled surface peak and (2) the magnitude of the surface backscatter. The performance of this algorithm has been tested on CloudSat data acquired over an ocean surface. A preliminary analysis of the test data showed a surface-clutter-rejection ratio over flat surfaces of >10 dB and a reduction of the contaminated altitude over ocean from about 1 km to about 0.5 km (over the ocean). The algorithm has been embedded in CloudSat L1B processing as of Release 04 (July 2007), and the estimated flat surface clutter is removed in L2B-GEOPROF product from the observed profile of reflectivity (see CloudSat product documentation for details and performance at http://www.cloudsat.cira.colostate.edu/ dataSpecs.php?prodid=1).

Tanelli, Simone↗

NASA NTRS2013

Forward-Looking IED Detector Ground Penetrating Radar

There have been many developments of mine or metal detectors based on ground penetrating radar techniques, usually in hand-held or rover-mounted devices. In most mine or metal detector applications, conditions are in a stationary mode and detection speed is not an important factor. A novel, forward-looking, stepped-frequency ground penetrating radar (GPR) has been developed with a capability to detect improvised explosive devices (IEDs) at vehicular speeds of 15 to 20 mph (24 to 32 km/h), 10 to 20 m ahead of the vehicle, to ensure adequate time for response. The GPR system employs two horn antennas (1.7 to 2.6 GHz, 20 dBi) as transmit and receive. The detector system features a user-friendly instantaneous display on a laptop PC and is a low-power-consumption (3 W) compact system with minimal impact on vehicle operations. In practice, the whole GPR system and a laptop PC can be powered by plugging into a cigarette lighter of a vehicle. The stepped-frequency continuous-wave (CW) radar scans frequency from 1.7 to 2.6 GHz in 1,000 steps of 0.9 MHz, with the full frequency scan in 60 ms. The GPR uses a bi-static configuration with one horn antenna used as a transmitter and the other used as a receiver so that isolation between transmitter and receiver is improved. Since the horn antennas (20 dBi) are mounted on the roof of a vehicle at a shallow inclination angle (15 to 25 with respect to horizontal), there is a first-order reduction in ground reflection so that a significant amount of the total reflected power received by the GPR comes from the scattering of RF energy off of buried objects. The stepped-frequency technique works by transmitting a tone at a particular frequency, while the received signal is mixed with the transmitted tone. As a result, the output of the mixer produces a signal that indicates the strength of the received signal and the extent to which it is in phase or out of phase with the transmitted tone. By taking measurements of the phase relationship between the transmitted and received signals over a wide frequency range, an interference pattern is produced showing all target reflections. When a Fourier transform is performed on this pattern, the result is a time-domain representation of targets. Among the advantages of this technique over impulse radar is the ability to transmit and receive much more total energy, and to use non-damped, highly focused horn antennas. The novelty of the IED detector GPR has been achieved by miniaturization of GPR electronics (single electronics board, 10x5x2 cm), low power consumption (3 W), faster signal processing capability, and minimal impact on vehicle operations.

Kim, Soon Sam↗