scholarly journals A Robust Error-Based Rain Estimation Method for Polarimetric Radar. Part II: Case Study

2012 ◽  
Vol 51 (9) ◽  
pp. 1702-1713 ◽  
Author(s):  
Acacia S. Pepler ◽  
Peter T. May
Keyword(s):  
Estimation Method ◽  
Heavy Rain ◽  
Rain Gauge ◽  
Polarimetric Radar ◽  
Composite Methods ◽  
A New Technique ◽  
Rain Events ◽  
Radar Part ◽  
Rain Rates

AbstractRainfall estimation using polarimetric radar involves the combination of a number of estimators with differing error characteristics to optimize rainfall estimates at all rain rates. In Part I of this paper, a new technique for such combinations was proposed that weights algorithms by the inverse of their theoretical errors. In this paper, the derived algorithms are validated using the “CP2” polarimetric radar in Queensland, Australia, and a collocated rain gauge network for two heavy-rain events during November 2008 and a larger statistical analysis that is based on data from between 2007 and 2009. Use of a weighted combination of polarimetric algorithms offers some improvement over composite methods that are based on decision-tree logic, particularly at moderate to high rain rates and during severe-thunderstorm events.

scholarly journals A Robust Error-Based Rain Estimation Method for Polarimetric Radar. Part I: Development of a Method

2011 ◽  
Vol 50 (10) ◽  
pp. 2092-2103 ◽  
Author(s):  
Acacia S. Pepler ◽  
Peter T. May ◽  
Merhala Thurai
Keyword(s):  
Decision Tree ◽  
Estimation Method ◽  
Radar Data ◽  
Estimation Accuracy ◽  
Polarimetric Radar ◽  
Modest Improvement ◽  
Naturally Occurring ◽  
Composite Methods ◽  
Radar Part ◽  
Rain Rates

AbstractThe algorithms used to estimate rainfall from polarimetric radar variables show significant variance in error characteristics over the range of naturally occurring rain rates. As a consequence, to improve rainfall estimation accuracy using polarimetric radar, it is necessary to optimally combine a number of different algorithms. In this study, a new composite method is proposed that weights the algorithms by the inverse of their theoretical error. A number of approaches are discussed and are investigated using simulated radar data calculated from disdrometer measurements. The resultant algorithms show modest improvement over composite methods based on decision-tree logic—in particular, at rain rates above 20 mm h−1.

scholarly journals Comparison of Radar-Based Hail Detection Using Single- and Dual-Polarization

2019 ◽  
Vol 11 (12) ◽  
pp. 1436 ◽  
Author(s):  
Skripniková ◽  
Řezáčová
Keyword(s):  
Comparative Analysis ◽  
Heavy Rain ◽  
Radar Data ◽  
Severe Weather ◽  
Detection Methods ◽  
Polarimetric Radar ◽  
Dual Polarization ◽  
Rain Events ◽  
Single Polarization ◽  
Strong Agreement

The comparative analysis of radar-based hail detection methods presented here, uses C-band polarimetric radar data from Czech territory for 5 stormy days in May and June 2016. The 27 hail events were selected from hail reports of the European Severe Weather Database (ESWD) along with 21 heavy rain events. The hail detection results compared in this study were obtained using a criterion, which is based on single-polarization radar data and a technique, which uses dual-polarization radar data. Both techniques successfully detected large hail events in a similar way and showed a strong agreement. The hail detection, as applied to heavy rain events, indicated a weak enhancement of the number of false detected hail pixels via the dual-polarization hydrometeor classification. We also examined the performance of hail size detection from radar data using both single- and dual-polarization methods. Both the methods recognized events with large hail but could not select the reported events with maximum hail size (diameter above 4 cm).

scholarly journals Comparisons of Instantaneous TRMM Ground Validation and Satellite Rain-Rate Estimates at Different Spatial Scales

2008 ◽  
Vol 47 (8) ◽  
pp. 2215-2237 ◽  
Author(s):  
David B. Wolff ◽  
Brad L. Fisher
Keyword(s):  
Rain Rate ◽  
Spatial Scales ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Global Ocean ◽  
Ground Validation ◽  
Microwave Imager ◽  
Rain Events ◽  
Trmm Microwave Imager ◽  
Rain Rates

Abstract This study provides a comprehensive intercomparison of instantaneous rain rates observed by the two rain sensors aboard the Tropical Rainfall Measuring Mission (TRMM) satellite with ground data from two regional sites established for long-term ground validation: Kwajalein Atoll and Melbourne, Florida. The satellite rain algorithms utilize remote observations of precipitation collected by the TRMM Microwave Imager (TMI) and the Precipitation Radar (PR) aboard the TRMM satellite. Three standard level II rain products are generated from operational applications of the TMI, PR, and combined (COM) rain algorithms using rain information collected from the TMI and the PR along the orbital track of the TRMM satellite. In the first part of the study, 0.5° × 0.5° instantaneous rain rates obtained from the TRMM 3G68 product were analyzed and compared to instantaneous Ground Validation (GV) program rain rates gridded at a scale of 0.5° × 0.5°. In the second part of the study, TMI, PR, COM, and GV rain rates were spatiotemporally matched and averaged at the scale of the TMI footprint (∼150 km2). This study covered a 6-yr period (1999–2004) and consisted of over 50 000 footprints for each GV site. In the first analysis, the results showed that all of the respective rain-rate estimates agree well, with some exceptions. The more salient differences were associated with heavy rain events in which one or more of the algorithms failed to properly retrieve these extreme events. Also, it appears that there is a preferred mode of precipitation for TMI rain rates at or near 2 mm h−1 over the ocean. This mode was noted over ocean areas of Kwajalein and Melbourne and has been observed in TRMM tropical–global ocean areas as well.

scholarly journals Preliminary evaluation of polarimetric parameters from a new dual-polarization C-band weather radar in an alpine region

2010 ◽  
Vol 25 ◽  
pp. 111-117 ◽  
Author(s):  
H. Paulitsch ◽  
F. Teschl ◽  
W. L. Randeu
Keyword(s):  
Attenuation Correction ◽  
Rain Rate ◽  
Weather Radar ◽  
Heavy Rain ◽  
Rain Gauge ◽  
Preliminary Evaluation ◽  
Dual Polarization ◽  
Horizontal Polarization ◽  
Rain Rates ◽  
Differential Reflectivity

Abstract. The first operational weather radar with dual polarization capabilities was recently installed in Austria. The use of polarimetric radar variables rises several expectations: an increased accuracy of the rain rate estimation compared to standard Z-R relationships, a reliable use of attenuation correction methods, and finally hydrometeor classification. In this study the polarimetric variables of precipitation events are investigated and the operational quality of the parameters is discussed. For the new weather radar also several polarimetric rain rate estimators, which are based on the horizontal polarization radar reflectivity, ZH, the differential reflectivity, ZDR, and the specific differential propagation phase shift, KDP, have been tested. The rain rate estimators are further combined with an attenuation correction scheme. A comparison between radar and rain gauge indicates that ZDR based rain rate algorithms show an improvement over the traditional Z-R estimate. KDP based estimates do not provide reliable results, mainly due to the fact, that the observed KDP parameters are quite noisy. Furthermore the observed rain rates are moderate, where KDP is less significant than in heavy rain.

scholarly journals A TRMM-Calibrated infrared technique for rainfall estimation: application on rain events over eastern Mediterranean

2006 ◽  
Vol 7 ◽  
pp. 181-188 ◽  
Author(s):  
H. Feidas ◽  
G. Kokolatos ◽  
A. Negri ◽  
M. Manyin ◽  
N. Chrysoulakis
Keyword(s):  
Eastern Mediterranean ◽  
Regional Scale ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Tropical Areas ◽  
Trmm Precipitation ◽  
Remote Sensing Techniques ◽  
Rain Events ◽  
Rain Rates ◽  
Rain Gauge Network

Abstract. The aim is to evaluate the use of a satellite infrared (IR) technique for estimating rainfall over the eastern Mediterranean. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the Eastern Mediterranean for four rain events during the six month period of October 2004 to March 2005. Estimates from this technique are verified over a rain gauge network for different time scales. Results show that PR observations can be applied to improve IR-based techniques significantly in the conditions of a regional scale area by selecting adequate calibration areas and periods. They reveal, however, the limitations of infrared remote sensing techniques, originally developed for tropical areas, when applied to precipitation retrievals in mid-latitudes.

scholarly journals Thailand Daily Rainfall and Comparison with TRMM Products

2008 ◽  
Vol 9 (2) ◽  
pp. 256-266 ◽  
Author(s):  
Roongroj Chokngamwong ◽  
Long S. Chiu
Keyword(s):  
Daily Rainfall ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Absolute Difference ◽  
Rain Event ◽  
Critical Success ◽  
Global Precipitation Climatology Centre ◽  
Temporal And Spatial ◽  
Rain Events ◽  
Rain Rates

Abstract Daily rainfall data collected from more than 100 gauges over Thailand for the period 1993–2002 are used to study the climatology and spatial and temporal characteristics of Thailand rainfall variations. Comparison of the Thailand gauge (TG) data binned at 1° × 1° with the Global Precipitation Climatology Centre (GPCC) monitoring product shows a small bias (1.11%), and the differences can be reconciled in terms of the increased number of stations in the TG dataset. Comparison of daily TG with Tropical Rainfall Measuring Mission (TRMM) version 6 (V6) 3B42 rain estimates shows improvements over version 5 (V5) in terms of bias and mean absolute difference (MAD). The V5 is computed from the adjusted Geostationary Operational Environmental Satellite (GOES) precipitation index (AGPI) and V6 is computed using the TRMM Multisatellite Precipitation Analysis (TMPA) algorithm. The V6 histogram is much closer to that of TG than V5 in terms of rain fraction and conditional rain rates. Scatterplots show that both versions of the satellite products are deficient in capturing heavy rain events. In terms of detecting rain events, a critical success index (CSI) shows no difference between V6 and V5 3B42. The CSI for V6 is higher for the rainy season than the dry season. These results are generally insensitive to rain-rate threshold and averaging periods. The temporal and spatial autocorrelation of daily rain rates for TG, V6, and V5 3B42 are computed. Autocorrelation function analyses show improved temporal and spatial autocorrelations for V6 compared to TG over V5 with e-folding times of 1, 1, and 2 days, and isotropic spatial decorrelation distances of 1.14°, 1.87°, and 3.61° for TG, V6, and V5, respectively. Rain event statistics show that the V6 3B42 overestimates the rain event durations and underestimates the rain event separations and the event conditional rain rates when compared to TG. This study points to the need to further improve the 3B42 algorithm to lower the false detection rate and improve the estimation of heavy rainfall events.

scholarly journals Skilful precipitation nowcasting using deep generative models of radar

Nature ◽  
2021 ◽  
Vol 597 (7878) ◽  
pp. 672-677
Author(s):  
Suman Ravuri ◽  
Karel Lenc ◽  
Matthew Willson ◽  
Dmitry Kangin ◽  
Remi Lam ◽  
...  
Keyword(s):  
Poor Performance ◽  
Heavy Rain ◽  
Generative Models ◽  
Generative Model ◽  
Alternative Methods ◽  
Systematic Evaluation ◽  
Lead Times ◽  
Physical Constraints ◽  
Rain Events ◽  
Rain Rates

AbstractPrecipitation nowcasting, the high-resolution forecasting of precipitation up to two hours ahead, supports the real-world socioeconomic needs of many sectors reliant on weather-dependent decision-making1,2. State-of-the-art operational nowcasting methods typically advect precipitation fields with radar-based wind estimates, and struggle to capture important non-linear events such as convective initiations3,4. Recently introduced deep learning methods use radar to directly predict future rain rates, free of physical constraints5,6. While they accurately predict low-intensity rainfall, their operational utility is limited because their lack of constraints produces blurry nowcasts at longer lead times, yielding poor performance on rarer medium-to-heavy rain events. Here we present a deep generative model for the probabilistic nowcasting of precipitation from radar that addresses these challenges. Using statistical, economic and cognitive measures, we show that our method provides improved forecast quality, forecast consistency and forecast value. Our model produces realistic and spatiotemporally consistent predictions over regions up to 1,536 km × 1,280 km and with lead times from 5–90 min ahead. Using a systematic evaluation by more than 50 expert meteorologists, we show that our generative model ranked first for its accuracy and usefulness in 89% of cases against two competitive methods. When verified quantitatively, these nowcasts are skillful without resorting to blurring. We show that generative nowcasting can provide probabilistic predictions that improve forecast value and support operational utility, and at resolutions and lead times where alternative methods struggle.

scholarly journals A Bayesian technique for conditioning radar precipitation estimates to rain-gauge measurements

2001 ◽  
Vol 5 (2) ◽  
pp. 187-199 ◽  
Author(s):  
E. Todini
Keyword(s):  
Kalman Filtering ◽  
Rain Gauge ◽  
Theoretical Development ◽  
Block Kriging ◽  
Signal Ratio ◽  
Rain Gauges ◽  
Precipitation Estimates ◽  
Meteorological Radar ◽  
A New Technique

Abstract. The paper introduces a new technique based upon the use of block-Kriging and of Kalman filtering to combine, optimally in a Bayesian sense, areal precipitation fields estimated from meteorological radar to point measurements of precipitation such as are provided by a network of rain-gauges. The theoretical development is followed by a numerical example, in which an error field with a large bias and a noise to signal ratio of 30% is added to a known random field, to demonstrate the potentiality of the proposed algorithm. The results analysed on a sample of 1000 realisations, show that the final estimates are totally unbiased and the noise variance reduced substantially. Moreover, a case study on the upper Reno river in Italy demonstrates the improvements in rainfall spatial distribution obtainable by means of the proposed radar conditioning technique. Keywords: Rainfall, meteorological radar, Bayesian technique, block-Kriging, Kalman filtering

scholarly journals The Catastrophic Flash-Flood Event of 8–9 September 2002 in the Gard Region, France: A First Case Study for the Cévennes–Vivarais Mediterranean Hydrometeorological Observatory

2005 ◽  
Vol 6 (1) ◽  
pp. 34-52 ◽  
Author(s):  
Guy Delrieu ◽  
John Nicol ◽  
Eddy Yates ◽  
Pierre-Emmanuel Kirstetter ◽  
Jean-Dominique Creutin ◽  
...  
Keyword(s):  
Extreme Event ◽  
Flash Flood ◽  
Rain Gauge ◽  
Primary Objective ◽  
Economic Damage ◽  
Rain Event ◽  
First Case ◽  
Research Initiative ◽  
Rain Events

Abstract The Cévennes–Vivarais Mediterranean Hydrometeorological Observatory (OHM-CV) is a research initiative aimed at improving the understanding and modeling of the Mediterranean intense rain events that frequently result in devastating flash floods in southern France. A primary objective is to bring together the skills of meteorologists and hydrologists, modelers and instrumentalists, researchers and practitioners, to cope with these rather unpredictable events. In line with previously published flash-flood monographs, the present paper aims at documenting the 8–9 September 2002 catastrophic event, which resulted in 24 casualties and an economic damage evaluated at 1.2 billion euros (i.e., about 1 billion U.S. dollars) in the Gard region, France. A description of the synoptic meteorological situation is first given and shows that no particular precursor indicated the imminence of such an extreme event. Then, radar and rain gauge analyses are used to assess the magnitude of the rain event, which was particularly remarkable for its spatial extent with rain amounts greater than 200 mm in 24 h over 5500 km2. The maximum values of 600–700 mm observed locally are among the highest daily records in the region. The preliminary results of the postevent hydrological investigation show that the hydrologic response of the upstream watersheds of the Gard and Vidourle Rivers is consistent with the marked space–time structure of the rain event. It is noteworthy that peak specific discharges were very high over most of the affected areas (5–10 m3 s−1 km−2) and reached locally extraordinary values of more than 20 m3 s−1 km−2. A preliminary analysis indicates contrasting hydrological behaviors that seem to be related to geomorphological factors, notably the influence of karst in part of the region. An overview of the ongoing meteorological and hydrological research projects devoted to this case study within the OHM-CV is finally presented.

scholarly journals High-Frequency Single-Board Doppler Minisodar for Precipitation Measurements. Part I: Rainfall and Hail

2005 ◽  
Vol 22 (4) ◽  
pp. 421-432
Author(s):  
Shixuan Pang ◽  
Hartmut Graßl
Keyword(s):  
High Frequency ◽  
Digital Signal ◽  
Rain Gauge ◽  
Refractive Indices ◽  
Subsequent Paper ◽  
Doppler Sodar ◽  
The Mean ◽  
Rain Events ◽  
Rain Rates ◽  
Good Agreement

Abstract A high-frequency Doppler sodar for precipitation measurements has been developed. Such a Doppler sodar (6–20 kHz) can almost always measure precipitation and turbulence spectra simultaneously. Therefore, the mean vertical wind and spectral broadening effects can be directly removed. As the acoustic refractive indices for ice and liquid water are almost the same, the acoustic retrieval of precipitation can also be applied to rain with small hail (e.g., diameter D < 10 mm) or large hail, but for the latter, neglecting the effects of different orientations and shapes of hailstones. The authors’ single-board minisodar is based on the digital signal processing (DSP) technique. The first prototype has been continuously operated at a coastal weather station since 25 October 2002. For stratiform rain events, the minisodar showed good agreement with a Joss–Waldvogel disdrometer and an optical rain gauge. However, for convective heavy showers, the minisodar always observed higher rain rates. The continuous, nonattended automatic operation of the minisodar has shown its capability for all kinds of precipitation measurements. The retrieval of precipitation rates for snow and graupel will be provided in a subsequent paper.

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