Rain rate estimation from nadir-looking TOPEX/POSEIDON microwave radiometer (TMR) for correction of radar altimetric measurements

1999 ◽  
Vol 37 (5) ◽  
pp. 2556-2568 ◽  
Author(s):  
A.K. Varma ◽  
R.M. Gairola ◽  
C.M. Kishtawal ◽  
P.C. Pandey ◽  
K.P. Singh
Keyword(s):  
Rain Rate ◽  
Microwave Radiometer ◽  
Rate Estimation ◽  
Altimetric Measurements

scholarly journals Physical Retrieval of Rain Rate from Ground-Based Microwave Radiometry

2021 ◽  
Vol 13 (11) ◽  
pp. 2217
Author(s):  
Wenyue Wang ◽  
Klemens Hocke ◽  
Christian Mätzler
Keyword(s):  
Rain Rate ◽  
Radiative Transfer Equation ◽  
Microwave Radiometer ◽  
Rain Gauge ◽  
Reanalysis Data ◽  
Retrieval Method ◽  
Rain Gauge Data ◽  
Rate Estimation ◽  
Gauge Data ◽  
Microwave Radiometers

Because of its clear physical meaning, physical methods are more often used for space-borne microwave radiometers to retrieve the rain rate, but they are rarely used for ground-based microwave radiometers that are very sensitive to rainfall. In this article, an opacity physical retrieval method is implemented to retrieve the rain rate (denoted as Opa-RR) using ground-based microwave radiometer data (21.4 and 31.5 GHz) of the tropospheric water radiometer (TROWARA) at Bern, Switzerland from 2005 to 2019. The Opa-RR firstly establishes a direct connection between the rain rate and the enhanced atmospheric opacity during rain, then iteratively adjusts the rain effective temperature to determine the rain opacity, based on the radiative transfer equation, and finally estimates the rain rate. These estimations are compared with the available simultaneous rain rate derived from rain gauge data and reanalysis data (ERA5). The results and the intercomparison demonstrate that during moderate rains and at the 31 GHz channel, the Opa-RR method was close to the actual situation and capable of the rain rate estimation. In addition, the Opa-RR method can well derive the changes in cumulative rain over time (day, month, and year), and the monthly rain rate estimation is superior, with the rain gauge validated R2 and the root-mean-square error value of 0.77 and 22.46 mm/month, respectively. Compared with ERA5, Opa-RR at 31GHz achieves a competitive performance.

scholarly journals Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

2008 ◽  
Vol 25 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Jianxin Wang ◽  
Brad L. Fisher ◽  
David B. Wolff
Keyword(s):  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Radar Reflectivity ◽  
Time Shift ◽  
Estimation Errors ◽  
Rate Estimation ◽  
Reflectivity Data ◽  
Rain Rates ◽  
Event Definition

Abstract This paper describes the cubic spline–based operational system for the generation of the Tropical Rainfall Measuring Mission (TRMM) 1-min rain-rate product 2A-56 from tipping-bucket (TB) gauge measurements. A simulated TB gauge from a Joss–Waldvogel disdrometer is employed to evaluate the errors of the TB rain-rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When 1-min rain rates are averaged over 4–7-min intervals or longer, the errors dramatically reduce. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-min rain rates higher and lower than 3 mm h−1, respectively. These errors decrease to 5% and 14% when rain rates are used at the 7-min scale. The radar reflectivity–rain-rate distributions drawn from the large amount of 7-min rain rates and radar reflectivity data are mostly insensitive to the event definition. The time shift due to inaccurate clocks can also cause rain-rate estimation errors, which increase with the shifted time length. Finally, some recommendations are proposed for possible improvements of rainfall measurements and rain-rate estimations.

Rain rate estimation by simplified method using UHF wind profiler measurement at KMITL

2000 ◽  
Author(s):  
Chaiwat Somboonlarp ◽  
Nipha Leelaruji ◽  
Narong Hemmakorn ◽  
Apinan Manyanon ◽  
Yuichi Ohno
Keyword(s):  
Rain Rate ◽  
Wind Profiler ◽  
Rate Estimation ◽  
Simplified Method ◽  
Uhf Wind Profiler

Application of X- and S-band radars for rain rate estimation over an urban area

1997 ◽  
Vol 22 (3-4) ◽  
pp. 259-264 ◽  
Author(s):  
R. Uijlenhoet ◽  
J.N.M. Stricker ◽  
H.W.J. Russchenberg
Keyword(s):  
Urban Area ◽  
Rain Rate ◽  
Rate Estimation

scholarly journals Rain‐rate estimation algorithm using signal attenuation of Ka‐band cloud radar

2019 ◽  
Vol 27 (1) ◽  
Author(s):  
Su‐Bin Oh ◽  
Pavlos Kollias ◽  
Jeong‐Soon Lee ◽  
Seung‐Woo Lee ◽  
Yong Hee Lee ◽  
...  
Keyword(s):  
Rain Rate ◽  
Estimation Algorithm ◽  
Signal Attenuation ◽  
Ka Band ◽  
Rate Estimation ◽  
Cloud Radar

scholarly journals Satellite Microwave Surface Observations in Tropical Cyclones

2010 ◽  
Vol 138 (2) ◽  
pp. 421-437 ◽  
Author(s):  
Yves Quilfen ◽  
Bertrand Chapron ◽  
Jean Tournadre
Keyword(s):  
Wind Speed ◽  
Tropical Cyclones ◽  
Rain Rate ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Surface Wind Speed ◽  
Microwave Measurements ◽  
Dual Frequency

Abstract Sea surface estimates of local winds, waves, and rain-rate conditions are crucial to complement infrared/visible satellite images in estimating the strength of tropical cyclones (TCs). Satellite measurements at microwave frequencies are thus key elements of present and future observing systems. Available for more than 20 years, passive microwave measurements are very valuable but still suffer from insufficient resolution and poor wind vector retrievals in the rainy conditions encountered in and around tropical cyclones. Scatterometer and synthetic aperture radar active microwave measurements performed at the C and Ku band on board the European Remote Sensing (ERS), the Meteorological Operational (MetOp), the Quick Scatterometer (QuikSCAT), the Environmental Satellite (Envisat), and RadarSat satellites can also be used to map the surface wind field in storms. Their accuracy is limited in the case of heavy rain and possible saturation of the microwave signals is reported. Altimeter dual-frequency measurements have also been shown to provide along-track information related to surface wind speed, wave height, and vertically integrated rain rate at about 6-km resolution. Although limited for operational use by their dimensional sampling, the dual-frequency capability makes altimeters a unique satellite-borne sensor to perform measurements of key surface parameters in a consistent way. To illustrate this capability two Jason-1 altimeter passes over Hurricanes Isabel and Wilma are examined. The area of maximum TC intensity, as described by the National Hurricane Center and by the altimeter, is compared for these two cases. Altimeter surface wind speed and rainfall-rate observations are further compared with measurements performed by other remote sensors, namely, the Tropical Rainfall Measuring Mission instruments and the airborne Stepped Frequency Microwave Radiometer.

scholarly journals Ceilometer-Based Rain-Rate Estimation: A Case-Study Comparison With S-Band Radar and Disdrometer Retrievals in the Context of VORTEX-SE

2020 ◽  
Vol 58 (12) ◽  
pp. 8268-8284
Author(s):  
Francesc Rocadenbosch ◽  
Ruben Barragan ◽  
Stephen J. Frasier ◽  
Joseph Waldinger ◽  
David D. Turner ◽  
...  
Keyword(s):  
Rain Rate ◽  
Rate Estimation
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