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At least 37 records · Page 2

High Resolution Observations of Drop Size Distribution for GPM Ground Validation

During the Mid-latitude Convective Cloud Experiment (MC3E), NASA's GPM GV Disdrometer and Radar Observations of Precipitation (DROP) Facility deployed an array of disdrometers and rain gauges in northern Oklahoma to sample, with high resolution, the drop size distribution (DSD) for use in development of precipitation retrieval algorithms for the GPM core satellite. The DROP Facility instruments deployed during MC3E consisted of 16 autonomous Parsivel units, 5 two-dimensional video disdrometers (2DVD), a vertical pointing K-band radar and 32 tipping bucket rain gauges. There were several rainfall events during MC3E in which rain drops exceeding 5 mm in diameter were recorded. During a convective rainfall event one of the 2DVDs measured a large rain drop of 8 mm in diameter falling from a convective cell under which several other disdrometers revealed a broad DSD spectrum across this cell and median drop diameter of 3.1 mm. The NPOL radar, which was scanning over the disdrometer array in high resolution RHI mode (every 40 sec), during a stratiform rainfall event revealed a 1 km thick bright band with locally thicker segments that produced rainfall rates of 6-10 mm/hr and indications of DSD modulations as enhanced concentrations of mid-sized rain drops (1.5-3.0 mm) descended below cloud base. These observations are key in characterizing the DSD variability within the 4 km footprint of the GPM Dual-wavelength Precipitation Radar that will provide a global map of precipitation as well as DSD.

Gatlin, Patrick N.↗

Estimating the Concentration of Large Raindrops from Polarimetric Radar and Disdrometer Observations

Estimation of rainfall integral parameters, including radar observables, and empirical relations between them are sensitive to the truncation of the drop size distribution (DSD), particularly at the large drop end. The sensitivity of rainfall integral parameters to the maximum drop diameter (D(sub max)) is exacerbated at C‐band since resonance effects are pronounced for large drops in excess of 5 mm diameter (D). Due to sampling limitations, it is often difficult to reliably estimate D(sub max) with disdrometers. The resulting uncertainties in D(sub max0 potentially increase errors in radar retrieval methods, particularly at C‐band, that rely on disdrometer observations for DSD input to radar models. In fact, D(sub max) is typically an assumed DSD parameter in the development of radar retrieval methods. Because of these very uncertainties, it is difficult to independently confirm disdrometer estimates of D(sub max) with polarimetric radar observations. A couple of approaches can be taken to reduce uncertainty in large drop measurement. Longer integration times can be used for the collection of larger disdrometer samples. However, integration periods must be consistent with a radar resolution volume (RRV) and the temporal and spatial scales of the physical processes affecting the DSD therein. Multiple co‐located disdrometers can be combined into a network to increase the sample size within a RRV. However, over a reasonable integration period, a single disdrometer sample volume is many orders of magnitudes less than a RRV so it is not practical to devise a network of disdrometers that has an equivalent volume to a typical RRV. Since knowledge of DSD heterogeneity and large drop occurrence in time and space is lacking, the specific accuracy or even general representativeness of disdrometer based D(sub max) and large drop concentration estimates within a RRV are currently unknown. To address this complex issue, we begin with a simpler question. Is the frequency of occurrence of large rain drops (D > 5 mm) in disdrometer observations, either stand alone or networked, generally representative and consistent with polarimetric radar observations? We first show from simulations that the concentration of large (D > 5 mm) rain drops (N(sub T5)) can be estimated from polarimetric observations of specific differential phase (K(sub dp)) and differential reflectivity (Z(sub dr)), N(sub T5)=F(K(sub dp),Z(sub dr)), or horizontal reflectivity (Z(sub h)) and Z(sub dr), N(sub T5)=(Z(sub h),Z(sub dr)). We assess the error associated with polarimetric retrieval of N(sub T5), including sensitivity to D(sub max) parameterization assumptions and measurement error in the radar simulations. Polarimetric measurements at S‐band and C‐band will then be used to retrieve estimates of N(sub T5) and compared to disdrometer estimates of N(sub T5). After careful consideration of retrieval error, we will check consistency between disdrometer and polarimetric radar estimates of N(sub T5) and the frequency of occurrence of large rain drops in a variety of precipitating regimes using data from NASA's Global Precipitation Measurement (GPM) Ground Validation (GV) program, including field campaigns such as MC3E (Oklahoma) and IFloodS (Iowa) and extended measurements over Huntsville, Alabama and NASA Wallops Flight Facility in coastal Virginia.

Carey, Lawrence D.↗

Statistical Analysis of Instantaneous Frequency Scaling Factor as Derived from Optical Disdrometer Measurements at V/W Bands

Since October 2015, NASA Glenn Research Center (GRC) and the Air Force Research Laboratory (AFRL) have collaboratively operated an RF terrestrial link in Albuquerque, New Mexico to characterize atmospheric propagation phenomena at 72 and 84 GHz. The W/V-band Terrestrial Link Experiment (WTLE) consists of coherent transmitters at each frequency on the crest of the Sandia Mountains and a corresponding pair of receivers in south Albuquerque. The beacon receivers provide a direct measurement of the link attenuation, while concurrent weather instrumentation provides a measurement of the atmospheric conditions. Among the available weather instruments is an optical disdrometer which yields an optical measurement of rain rate, as well as droplet size and velocity distributions (DSD, DVD). In particular, the DSD can be used to derive an instantaneous scaling factor (ISF) by which the measured data at one frequency can be scaled to another - for example, scaling the 72 GHz to an expected 84 GHz timeseries. Given the availability of both the DSD prediction and the directly observed 84 GHz attenuation, WTLE is thus uniquely able assess DSD-derived instantaneous frequency scaling at the V/W-bands. Previous work along these lines has investigated the DSD-derived ISF at Ka and Q-band (20 GHz to 40 GHz) using a satellite beacon receiver experiment in Milan, Italy. This work will expand the investigation to terrestrial links in the V/W-bands, where the frequency scaling factor is lower and where the link is also much more sensitive to attenuation by rain, clouds, and other atmospheric effects.

Radio Transmission↗

Statistical Analysis of Instantaneous Frequency Scaling Factor as Derived from Optical Disdrometer Measurements at VW Bands

Since October 2015, NASA Glenn Research Center (GRC) and the Air Force Research Laboratory (AFRL) have collaboratively operated an RF terrestrial link in Albuquerque, New Mexico to characterize atmospheric propagation phenomena at 72 and 84 GHz. The WV-band Terrestrial Link Experiment (WTLE) consists of coherent transmitters at each frequency on the crest of the Sandia Mountains and a corresponding pair of receivers in south Albuquerque. The beacon receivers provide a direct measurement of the link attenuation, while concurrent weather instrumentation provides a measurement of the atmospheric conditions.Among the available weather instruments is an optical disdrometer which yields an optical measurement of rain rate, as well as droplet size and velocity distributions (DSD, DVD). In particular, the DSD can be used to derive an instantaneous scaling factor (ISF) by which the measured data at one frequency can be scaled to another for example, scaling the 72 GHz to an expected 84 GHz timeseries. Given the availability of both the DSD prediction and the directly observed 84 GHz attenuation, WTLE is thus uniquely able assess DSD-derived instantaneous frequency scaling at the VW-bands. Previous work along these lines has investigated the DSD-derived ISF at Ka and Q-band (20 GHz to 40 GHz) using a satellite beacon receiver experiment in Milan, Italy [1-3]. This work will expand the investigation to terrestrial links in the VW-bands, where the frequency scaling factor is lower and where the link is also much more sensitive to attenuation by rain, clouds, and other atmospheric effects.

Radio Attenuation↗

Observing the Full Spectrum of the Rain Drop Size Distribution

GPM DSD retrievals exhibit inconsistencies between GV, DPR and Combined algorithm retrievals. Development of positive bias in convective Dm rain DSD noted, and strongest in KuPR retrieval. Associated epsilons are too low and result in markedly reduced convective rain rates (a current issue in the retrievals). Source may be NUBF. Issues with the large end of the DSD not withstanding, on the small end of the DSD, combined MPS and 2DVD measurements fit with generalized gamma functions exhibit strong potential for representing the entire spectrum of the DSD and subsequently the whole rain rate spectrum.

Hydrology↗

Measurements of Rainfall Rate, Drop Size Distribution, and Variability at Middle and Higher Latitudes: Application to the Combined DPR-GMI Algorithm

The Global Precipitation Measurement mission is a major U.S.–Japan joint mission to understand the physics of the Earth’s global precipitation as a key component of its weather, climate, and hydrological systems. The core satellite carries a dual-precipitation radar and an advanced microwave imager which provide measurements to retrieve the drop size distribution (DSD) and rain rates using a Combined Radar-Radiometer Algorithm (CORRA). Our objective is to validate key assumptions and parameterizations in CORRA and enable improved estimation of precipitation products, especially in the middle-to-higher latitudes in both hemispheres. The DSD parameters and statistical relationships between DSD parameters and radar measurements are a central part of the rainfall retrieval algorithm, which is complicated by regimes where DSD measurements are abysmally sparse (over the open ocean). In view of this, we have assembled optical disdrometer datasets gathered by research vessels, ground stations, and aircrafts to simulate radar observables and validate the scattering lookup tables used in CORRA. The joint use of all DSD datasets spans a large range of drop concentrations and characteristic drop diameters. The scaling normalization of DSDs defines an intercept parameter N(W), which normalizes the concentrations, and a scaling diameter D(m), which compresses or stretches the diameter coordinate axis. A major finding of this study is that a single relationship between N(W) and D(m), on average, unifies all datasets included, from stratocumulus to heavier rainfall regimes. A comparison with the N(W)–D(m) relation used as a constraint in versions 6 and 7 of CORRA highlights the scope for improvement of rainfall retrievals for small drops (D(m) < 1 mm) and large drops (D(m) > 2 mm). The normalized specific attenuation–reflectivity relationships used in the combined algorithm are also found to match well the equivalent relationships derived using DSDs from the three datasets, suggesting that the currently assumed lookup tables are not a major source of uncertainty in the combined algorithm rainfall estimates.

Viswanathan Bringi↗

Dual-parameter radar rainfall measurement from space - A test result from an aircraft experiment

An aircraft experiment has been conducted with a dual-frequency (X/Ka-bands) radar to test various rainfall retrieval methods from space. The authors test a method to derive raindrop size distribution (DSD) parameters from the combination of a radar reflectivity profile and a path-integrated attenuation derived from surface return, which may be available from most spaceborne radars. The estimated DSD parameters are reasonable in that the values generally fall within the range of commonly measured ones and that shifts in DSD parameters appear to be correlated with changes in storm type. The validity of the estimation result is also demonstrated by a consistency check using the Ka-band reflectivity profile which is independent of the DSD estimation process. Although errors may occur in the cases of nonuniform beam filling, these test results indicate the feasibility of the dual-parameter radar measurement from space in achieving a better accuracy in quantitative rainfall remote measurements.

Kozu, Toshiaki↗

Tests of Radar Rainfall Retrieval Algorithms

The NASA/JPL Airborne Rain Mapping Radar (ARMAR) operates at 14 GHz. ARMAR flew on the NASA DC-8 aircraft during Tropical Ocean Global Atmosphere (TOGA) Coupled Ocean Atmosphere Response Experiment (COARE), collecting data in oceanic mesoscale convective systems, similar to those now being observed by the Tropical Rainfall Measuring Mission (TRMM) satellite, which includes a 14-GHz precipitation radar. Several algorithms for retrieving rain rate from downward looking radars are in existence. These can be categorized as deterministic and stochastic. Deterministic algorithms use the path integrated attenuation (PIA), measured by the surface reference technique, as a constraint. One deterministic algorithm corrects the attenuation-rainfall (k-R) relation, while another corrects the reflectivity rainfall (ZR) relation. Stochastic algorithms apply an Extended Kalman Filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. We find that the stochastic algorithm with PIA is the most robust algorithm with regard to incorrect assumptions about the drop-size distribution (DSD). The deterministic algorithm that uses the PIA to adjust the Z-R relation is also fairly robust and produces rain rates similar to the stochastic algorithm that uses the PIA. The deterministic algorithm that adjusts only the k-R relation and the stochastic radar-only algorithm are more sensitive to assumptions about the DSD. It is likely that they underestimate convective rainfall, especially if the DSD is erroneously assumed to be appropriate for stratiform rain conditions. The underestimation is illustrated in the diagram. The algorithm labeled D IS initially assumes a DSD that is appropriate for stratiform. rain, while the rain is most likely convective. The PIA constraint causes the k-R relation to be adjusted, resulting in a much lower rain rate than the other algorithms. Additional information is contained in the original.

Durden, Stephen L.↗

To What Extent Can Raindrop Size Be Determined by a Multiple-Frequency Radar?

In this paper, an analytical treatment of the atmospheric remote sensing problem of determining the raindrop size distribution (DSD) with a spaceborne multifrequency microwave nadir-looking radar system is presented. It is typically assumed that with two radar measurements at different frequencies one ought to be able to calculate two state variables of the DSD: a bulk quantity, such as the rain rate, and a distribution shape parameter. To determine if this nonlinear problem can indeed be solved, the DSD is modeled as a Gamma distribution and quadratic approximations to the corresponding radar-rain relations are used to examine the invertibility of the resulting system of equations in the case of two as well as three radar frequencies. From the investigation, it is found that for regions of DSD state space multiple solutions exist for two or even three different frequency radar measurements. This should not be surprising given the nonlinear coupled nature of the problem.

rain characteristics↗

Drop Axis Ratio Distributions in Stratiform and Convective Rain

A fully calibrated low profile 2D video disdrometer (2DVD) has been recording many different rainfall events in Northern Alabama (USA) since June 2007. An earlier publication reported drop shapes and axis ratio distributions determined for some of the events. For one of the cases examined, a noticeable shift in the 3.5 - 3.75 mm drop axis ratio distribution was noted. In this paper, we extend the earlier work by separating the 2DVD measurements into stratiform and convective rain. The separation is made possible by using the minute-by-minute drop size distribution (DSD) measured by the 2DVD. The 1-minute DSDs are fitted to a gamma distribution, and using a simple indexing technique which involves two of the fitted parameters, periods of convective and stratiform rain are separated for a given event. The output of the DSD indexing technique is qualitatively confirmed by comparing with simultaneous time series observations from a co-located UHF profiler which continuously records height profiles of reflectivity, Doppler mean and spectral width, all of which enable the identification of bright-band periods and, furthermore, periods of moderate and deep convection. Excellent consistency is found between the output of the DSD-based separation method and the profiler observations. Next, we utilize the output of DSD index-based separation method to flag the periods of severe convection for a given event. Drop axis ratios during the flagged periods are derived and compared with those during stratiform rain periods. Five cases have been considered. Axis ratio distributions do not show appreciable differences between stratiform and convective periods for four of the cases. The fifth case (the same case as reported earlier) shows a shift in the 3.5 - 3.75 mm drop axis ratios during a prolonged period of convection. The contoured shapes for these drops determined from the 2DVD camera data indicate the possibility of non-axisymmetric oscillations, compared with the contoured images for other events which fit well to our reference drop shapes. For all of above cases, observations from a C-band polarimetric radar - situated 15 km away are examined. The variations between the co-polar radar reflectivity and the differential reflectivity as well as the specific differential phase are compared with the 2DVD data based scattering calculations for the 5 events. The implications will be discussed.

Thurai, M.↗

Assessing Dual-Polarization Radar Estimates of Extreme Rainfall During Hurricane Harvey

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on August 25, 2017 before exiting the state as a tropical storm on August 29, 2017. Left in its wake was historic flooding, with some locations measuring more than 60 inches of rain over a five-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar data set to retrieve daily and event-total precipitation estimates for the period August 25-29, 2017. The KHGX precipitation estimates were then compared to the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed Drop Size Distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value of α=0.015 and β=0.600 and β=0.625 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.

David B Wolff↗

Assessing Dual-Polarization Radar Estimates of Extreme Rainfall During Hurricane Harvey

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on 25 August 2017 before exiting the state as a tropical storm on 29 August 2017. Left in its wake was historic flooding, with some locations measuring more than 60 in. (150 cm) of rain over a 5-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar dataset to retrieve daily and event-total precipitation estimates for the period 25–29 August2017. The KHGX precipitation estimates were then compared with the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed drop size distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value ofa50.015 andb50.600 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.

David Billings Wolff↗

Can Remotely Sensed Snow Disappearance Explain Seasonal Water Supply?

Understanding the relationship between remotely sensed snow disappearance and seasonal water supply may become vital in coming years to supplement limited ground based, in situ measurements of snow in a changing climate. For the period 2001–2019, we investigated the relationship between satellite derived Day of Snow Disappearance (DSD)—the date at which snow has completely disappeared—and the seasonal water supply, i.e., the April—July total streamflow volume, for 15 snow dominated basins across the western U.S. A Monte Carlo framework was applied, using linear regression models to evaluate the predictive skill—defined here as a model’s ability to accurately predict seasonal flow volumes—of varied predictors, including DSD and in situ snow water equivalent (SWE), across a range of spring forecast dates. In all basins there is a statistically significant relationship between mean DSD and seasonal water supply (p ≤ 0.05), with mean DSD explaining roughly half of the variance. Satellite-based model skill improves later in the forecast season, surpassing the skill of in-situ-based (SWE) models in skill in 10 of the 15 basins by the latest forecast date. We found little to no correlation between model error and basin characteristics such as elevation and the ratio of snow water equivalent to total precipitation. Despite a relatively short data record, this exploratory analysis shows promise for improving seasonal water supply prediction, in particular for snow dominated basins lacking in situ observations.

snow remote sensing↗

A potential method for the estimation of drop size distribution from a dual-wavelength airborne radar

In order to investigate the role of the drop size distribution (DSD) from a dual-wavelength airborne radar and to recover profiled rain rates, a procedure is described for the purpose of estimating the DSD. The method differs from previous approaches in that it provides 2n + 1 parameters of the profiled DSD (where n is the number of range gates) and it uses a recursive procedure beginning at the range gate near the surface progressing backwards toward the storm top. The method is argued to be useful both as a diagnostic tool and as a means by which more detailed information on the vertical structure of the precipitation can be obtained.

Meneghini, R.↗

Structural Damage Prediction and Analysis for Hypervelocity Impact. UDRI Light Gas Gun Test Data Summaries

The HEX bumper was originally developed for use with the Defensive Shields Demonstration (DSD) Program. The University of Dayton Research Institute was a subcontractor to the Martin Marietta Astronautics Group in Denver Colorado at the time the HEX bumper was designed for use on the DSD Program. The design originated at the University and was essentially made available to interested parties. All HEX bumpers used in the DSD Program were fabricated at the University by rolling sheet stock through a special set of rollers. Two pieces of 3003-H14 aluminum sheet were rolled to produce the bumpers evaluated in Shots 4-1302 and 4-1304. A brief summary of the results of these tests is given in below. Contact prints of the multiple-exposure, orthogonal view radiographs of the debris clouds produced by the tests are attached. A sketch of the HEX bumper design is also attached.

Source record↗

Comparison of Radar Rainfall Retrieval Algorithms in Convective Rain During TOGA COARE

The authors compare deterministic and stochastic rain-rate retrieval algorithms by applying them to 14-GHz nadir-looking airborne radar reflectivity profiles acquired in tropical convective rain during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment, The deterministic algorithms both use the path-integrated attenuation (PIA), measured by the surface reference technique, as a constraint. One deterministic algorithm corrects the k-R relation, while the second corrects the Z-R relation. The stochastic algorithms are based on applying an extended Kalman filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. The authors find that the stochastic algorithm, which uses the PIA, is the most robust algorithm with regard to incorrect assumptions about the drop size distribution (DSD). The deterministic algorithm that uses the PIA to adjust the Z-R relation is also fairly robust and produces rain rates similar to the stochastic algorithm that uses the PIA, The deterministic algorithm that adjusts only the k-R relation and the stochastic radar-only algorithm are more sensitive to assumptions about the DSD. It is likely that they underestimate convective rainfall, especially if the DSD is erroneously assumed to be appropriate for stratiform rain conditions.

Durden, Stephen L.↗

Phase Transition in Dusty Plasmas: A Microphysical Description

Dust grains immersed in plasma discharges acquire a large negative charge and settle into a dust cloud at the edge of the sheath. In this region, the plasma ions stream toward the electrode at a velocity u approx. cs=(T(sub e)/m(sub i))(exp 1/2). Experimentally at sufficiently high gas pressure P, the random kinetic energy of the grains is damped by gas friction, and the grains are strongly coupled and self-organize into a crystalline configuration. For lower pressures despite the dissipation of grain kinetic energy to gas friction, the dust grains reach a steady-state kinetic temperature T(sub d) which is much larger than the temperature of any other component in the plasma. T(sub d) is so large that the dust acts like a fluid. We have used the dynamically shielded dust (DSD) model to simulate these physical processes. We find that the known experimental features are nicely reproduced in the simulations, and that additional features are revealed. In the figure we plot the variation of T(sub d) as P is continuously varied in a DSD code run. A marked difference is evident between the critical pressure P(sub m) for the melting transition as P is decreased, and the critical pressure P(sub c) for the condensation transition as P is increased. For P(sub m) is less than P is less than P(sub c), mixed phase states are seen. This hysteresis occurs because the instability which triggers melting is different from the instability that heats the dust in the fluid phase and inhibits freezing. At low pressure, the dust is subject to a two-stream instability with the ions. This instability is responsible for the high temperature of the dust at low pressure. The basic physics underlying the melting transition has been elucidated in a series of papers. We are developing a first-principles analytic approach to the melting transition, which embodies the same physics that is present in the DSD code.

Joyce, Glenn↗

Retrieval of Hydrometeor Drop Size Distributions from TRMM Field Campaign Profiler Doppler Velocity Spectra Observations

Consistent with the original proposal and work plan, this project focused on estimating the raindrop size distributions (DSDs) retrieved from vertically pointing Doppler radar profilers and analyzing the relationship of the retrieved DSDs with the dynamics of the precipitation processes. The first phase of this project focused on developing the model to retrieve the DSD from the observed Doppler velocity spectra. The second phase used this model to perform DSD retrievals from the profiler observations made during the TRMM Ground Validation Field Campaigns of TEFLUN-B, TRMM-LBA, and KWAJEX. The third phase of this project established collaborations with scientists involved with each field campaign in order to validate the profiler DSD estimates and to enable the profiler retrievals to be used in their research. Through these collaborations, the retrieved DSDs were placed into context with the dynamical processes of the observed precipitating cloud systems.

Williams, Christopher R.↗