Uncertainties of GPM DPR Rain Estimates Caused by DSD Parameterizations

2014 ◽  
Vol 53 (11) ◽  
pp. 2524-2537 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini ◽  
Ali Tokay

AbstractA framework based on measured raindrop size distribution (DSD) data has been developed to assess uncertainties in DSD models employed in Ku- and Ka-band dual-wavelength radar retrievals. In this study, the rain rates and attenuation coefficients from DSD parameters derived by dual-wavelength algorithms are compared with those directly obtained from measured DSD spectra. The impact of the DSD gamma parameterizations on rain estimation from the Global Precipitation Measurement mission (GPM) Dual-Frequency Precipitation Radar (DPR) is examined for the cases of a fixed shape factor μ as well as for a constrained μ—that is, a μ–Λ relation (a relationship between the shape parameter and slope parameter Λ of the gamma DSD)—by using 11 Particle Size and Velocity (Parsivel) disdrometer measurements with a total number of about 50 000 one-minute spectra that were collected during the Iowa Flood Studies (IFloodS) experiment. It is found that the DPR-like dual-wavelength techniques provide fairly accurate estimates of rain rate and attenuation if a fixed-μ gamma DSD model is used, with the value of μ ranging from 3 to 6. Comparison of the results reveals that the retrieval errors from the μ–Λ relations are generally small, with biases of less than ±10%, and are comparable to the results from a fixed-μ gamma model with μ equal to 3 and 6. The DSD evaluation procedure is also applied to retrievals in which a lognormal DSD model is used.

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1260 ◽  
Author(s):  
Zuhang Wu ◽  
Yun Zhang ◽  
Lifeng Zhang ◽  
Xiaolong Hao ◽  
Hengchi Lei ◽  
...  

In this study, we evaluated the performance of rain-retrieval algorithms for the Version 6 Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR) products, against disdrometer observations and improved their retrieval algorithms by using a revised shape parameter µ derived from long-term Particle Size Velocity (Parsivel) disdrometer observations in Jianghuai region from 2014 to 2018. To obtain the optimized shape parameter, raindrop size distribution (DSD) characteristics of summer and winter seasons over Jianghuai region are analyzed, in terms of six rain rate classes and two rain categories (convective and stratiform). The results suggest that the GPM DPR may have better performance for winter rain than summer rain over Jianghuai region with biases of 40% (80%) in winter (summer). The retrieval errors of rain category-based µ (3–5%) were proved to be the smallest in comparison with rain rate-based µ (11–13%) or a constant µ (20–22%) in rain-retrieval algorithms, with a possible application to rainfall estimations over Jianghuai region. Empirical Dm–Ze and Nw–Dm relationships were also derived preliminarily to improve the GPM rainfall estimates over Jianghuai region.


2019 ◽  
Vol 36 (5) ◽  
pp. 883-902 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini

AbstractA physical evaluation of the rain profiling retrieval algorithms for the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory satellite is carried out by applying them to the hydrometeor profiles generated from measured raindrop size distributions (DSD). The DSD-simulated radar profiles are used as input to the algorithms, and their estimates of hydrometeors’ parameters are compared with the same quantities derived directly from the DSD data (or truth). The retrieval accuracy is assessed by the degree to which the estimates agree with the truth. To check the validity and robustness of the retrievals, the profiles are constructed for cases ranging from fully correlated (or uniform) to totally uncorrelated DSDs along the columns. Investigation into the sensitivity of the retrieval results to the model assumptions is made to characterize retrieval uncertainties and identify error sources. Comparisons between the single- and dual-wavelength algorithm performance are carried out with either a single- or dual-wavelength constraint of the path integral or differential path integral attenuation. The results suggest that the DPR dual-wavelength algorithm generally provides accurate range-profiled estimates of rainfall rate and mass-weighted diameter with the dual-wavelength estimates superior in accuracy to those from the single-wavelength retrievals.


2017 ◽  
Vol 18 (12) ◽  
pp. 3165-3179 ◽  
Author(s):  
Ali Tokay ◽  
Leo Pio D’Adderio ◽  
Federico Porcù ◽  
David B. Wolff ◽  
Walter A. Petersen

Abstract A network of seven two-dimensional video disdrometers (2DVD), which were operated during the Midlatitude Continental Convective Clouds Experiment (MC3E) in northern Oklahoma, are employed to investigate the spatial variability of raindrop size distribution (DSD) within the footprint of the dual-frequency precipitation radar (DPR) on board the National Aeronautics and Space Administration’s Global Precipitation Measurement (GPM) mission core satellite. One-minute 2DVD DSD observations were interpolated uniformly to 13 points distributed within a nearly circular DPR footprint through an inverse distance weighting method. The presence of deep continental showers was a unique feature of the dataset resulting in a higher mean rain rate R with respect to previous studies. As a measure of spatial variability for the interpolated data, a three-parameter exponential function was applied to paired correlations of three parameters of normalized gamma DSD, R, reflectivity, and attenuation at Ka- and Ku-band frequencies of DPR (Z_Ka, Z_Ku, k_Ka, and k_Ku, respectively). The symmetry of the interpolated sites allowed quantifying the directional differences in correlations at the same distance. The correlation distances d0 of R, k_Ka, and k_Ku were approximately 10 km and were not sensitive to the choice of four rain thresholds used in this study. The d0 of Z_Ku, on the other hand, ranged from 29 to 20 km between different rain thresholds. The coefficient of variation (CV) remained less than 0.5 for most of the samples for a given physical parameter, but a CV of greater than 1.0 was also observed in noticeable samples, especially for the shape parameter and Z_Ku.


Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 39 ◽  
Author(s):  
Merhala Thurai ◽  
Viswanathan Bringi ◽  
Patrick Gatlin ◽  
Walter Petersen ◽  
Matthew Wingo

The raindrop size distribution (DSD) is fundamental for quantitative precipitation estimation (QPE) and in numerical modeling of microphysical processes. Conventional disdrometers cannot capture the small drop end, in particular the drizzle mode which controls collisional processes as well as evaporation. To overcome this limitation, the DSD measurements were made using (i) a high-resolution (50 microns) meteorological particle spectrometer to capture the small drop end, and (ii) a 2D video disdrometer for larger drops. Measurements were made in two climatically different regions, namely Greeley, Colorado, and Huntsville, Alabama. To model the DSDs, a formulation based on (a) double-moment normalization and (b) the generalized gamma (GG) model to describe the generic shape with two shape parameters was used. A total of 4550 three-minute DSDs were used to assess the size-resolved fidelity of this model by direct comparison with the measurements demonstrating the suitability of the GG distribution. The shape stability of the normalized DSD was demonstrated across different rain types and intensities. Finally, for a tropical storm case, the co-variabilities of the two main DSD parameters (normalized intercept and mass-weighted mean diameter) were compared with those derived from the dual-frequency precipitation radar onboard the global precipitation mission satellite.


Author(s):  
Mampi Sarkar ◽  
Paquita Zuidema ◽  
Virendra Ghate

AbstractPrecipitation is a key process within the shallow cloud lifecycle. The Cloud System Evolution in the Trades (CSET) campaign included the first deployment of a 94 GHz Doppler radar and 532 nm lidar. Despite a larger sampling volume, initial mean radar/lidar retrieved rain rates (Schwartz et al. 2019) based on the upward-pointing remote sensor datasets are systematically less than those measured by in-situ precipitation probes in the cumulus regime. Subsequent retrieval improvements produce rainrates that compare better to in-situ values, but still underestimate. Retrieved shallow cumulus drop sizes can remain too small and too few, with an overestimated shape parameter narrowing the raindrop size distribution too much. Three potential causes for the discrepancy are explored: the gamma functional fit to the dropsize distribution, attenuation by rain and cloud water, and an underaccounting of Mie dampening of the reflectivity. A truncated exponential fit may represent the dropsizes below a showering cumulus cloud more realistically, although further work would be needed to fully evaluate the impact of a different dropsize representation upon the retrieval. The rain attenuation is within the measurement uncertainty of the radar. Mie dampening of the reflectivity is shown to be significant, in contrast to previous stratocumulus campaigns with lighter rain rates, and may be difficult to constrain well with the remote measurements. An alternative approach combines an a priori determination of the dropsize distribution width based on the in-situ data with the mean radar Doppler velocity and reflectivity. This can produce realistic retrievals, although a more comprehensive assessment is needed to better characterize the retrieval errors.


2017 ◽  
Vol 56 (4) ◽  
pp. 877-896 ◽  
Author(s):  
Merhala Thurai ◽  
Patrick Gatlin ◽  
V. N. Bringi ◽  
Walter Petersen ◽  
Patrick Kennedy ◽  
...  

AbstractAnalysis of drop size distributions (DSD) measured by collocated Meteorological Particle Spectrometer (MPS) and a third-generation, low-profile, 2D-video disdrometer (2DVD) are presented. Two events from two different regions (Greeley, Colorado, and Huntsville, Alabama) are analyzed. While the MPS, with its 50-μm resolution, enabled measurements of small drops, typically for drop diameters below about 1.1 mm, the 2DVD provided accurate measurements for drop diameters above 0.7 mm. Drop concentrations in the 0.7–1.1-mm overlap region were found to be in excellent agreement between the two instruments. Examination of the combined spectra clearly reveals a drizzle mode and a precipitation mode. The combined spectra were analyzed in terms of the DSD parameters, namely, the normalized intercept parameter NW, the mass-weighted mean diameter Dm, and the standard deviation of mass spectrum σM. The inclusion of small drops significantly affected the NW and the ratio σM/Dm toward higher values relative to using the 2DVD-based spectra alone. For each of the two events, polarimetric radar data were used to characterize the variation of radar-measured reflectivity Zh and differential reflectivity Zdr with Dm from the combined spectra. In the Greeley event, this variation at S band was well captured for small values of Dm (<0.5 mm) where measured Zdr tended to 0 dB but Zh showed a noticeable decrease with decreasing Dm. For the Huntsville event, an overpass of the Global Precipitation Measurement mission Core Observatory satellite enabled comparison of satellite-based dual-frequency radar retrievals of Dm with ground-based DSD measurements. Small differences were found between the satellite-based radar retrievals and disdrometers.


2016 ◽  
Vol 33 (4) ◽  
pp. 653-667 ◽  
Author(s):  
Atsushi Hamada ◽  
Yukari N. Takayabu

AbstractThis paper demonstrates the impact of the enhancement in detectability by the dual-frequency precipitation radar (DPR) on board the Global Precipitation Measurement (GPM) core observatory. By setting two minimum detectable reflectivities—12 and 18 dBZ—artificially to 6 months of GPM DPR measurements, the precipitation occurrence and volume increase by ~21.1% and ~1.9%, respectively, between 40°S and 40°N.GPM DPR is found to be able to detect light precipitation, which mainly consists of two distinct types. One type is shallow precipitation, which is most significant for convective precipitation over eastern parts of subtropical oceans, where deep convection is typically suppressed. The other type is probably associated with lower parts of anvil clouds associated with organized precipitation systems.While these echoes have lower reflectivities than the official value of the minimum detectable reflectivity, they are found to mostly consist of true precipitation signals, suggesting that the official value may be too conservative for some sort of meteorological analyses. These results are expected to further the understanding of both global energy and water budgets and the diabatic heating distribution.


2016 ◽  
Vol 33 (8) ◽  
pp. 1779-1792 ◽  
Author(s):  
Xinxin Xie ◽  
Raquel Evaristo ◽  
Silke Troemel ◽  
Pablo Saavedra ◽  
Clemens Simmer ◽  
...  

AbstractThis study analyzes radar observations of evaporation in rain and investigates its impact on surface rainfall and atmospheric cooling rates. A 1D model is used to examine the impact of raindrop evaporation on the evolution of the initial raindrop size distribution (DSD), the resulting reflectivity (Z), and differential reflectivity (ZDR) and surface rain rates. Raindrop evaporation leads to a decrease of Z and an increase of ZDR toward the surface because of the depletion of small raindrops that evaporate first and thus enhance the mean raindrop size. The latter effect, however, can be reduced because of the increasing temperature toward the surface and may even lead to a decrease of ZDR toward the surface. Two events with significant rain evaporation, observed simultaneously by a polarimetric X-band radar and a K-band Micro Rain Radar (MRR), offer quite detailed insight into the evaporation process. During the first event, which exhibits an initial ZDR > 1.5 dB in the upper rain column, raindrops undergo relatively weak evaporation as deduced from the decrease of the small raindrop fraction observed by the MRR. The second event is characterized by a lower initial ZDR < 0.5 dB with all raindrops evaporating before reaching the ground. A retrieval scheme for estimating the evaporation-related cooling rate and surface precipitation from polarimetric radar observations below the bright band is derived based on MRR observations. The algorithm is then used to simulate polarimetric X-band radar observations, which might mitigate uncertainties in the surface rainfall retrievals due to evaporation at far distances from the radars and in the case of beam blocking.


Author(s):  
Yang Gao ◽  
Tongwen Wu ◽  
Jun Wang ◽  
Shihao Tang

AbstractThe Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) mission core satellite provides the new-generation global observation of rain since 2014. The main objective of this paper is to evaluate the suitability and limitation of GPM-DPR level-2 products over China. The DPR rain rate products are compared with rain gauge data during the summers of five years (2014-2018). The ground observation network is composed of more than 50000 rain gauges. The DPR precipitation products for all scans (DPR_NS, DPR_MS and DPR_HS) generally underestimate rain rates. However, DPR_MS agrees better with gauge estimates than DPR_NS and DPR_HS, yielding the lowest mean error, systematic deviation, and the highest Pearson correlation coefficient. In addition, all three swath types show obvious overestimation over gauge estimates between 0.5 to 1 mm/h and underestimation when gauge estimates are larger than 1 mm/h. The DPR_HS and DPR_MS agree better with gauge estimates below and above 2.5 mm/h, respectively. A deeper investigation was carried out to analyze the variation of DPR_MS’s performance with respect to terrains over China. An obvious underestimation, relative to gauge estimates, occurs in Tibetan Plateau while a slight overestimation occurs in North China Plain. Furthermore, our comprehensive analysis suggests that in Sichuan Basin, the DPR_MS exhibit the best agreement with gauge estimates.


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