Similarities and differences between three coexisting spaceborne radars in global rainfall and snowfall estimation

Tang, Guoqiang; Wen, Yixin; Gao, Jinyu; Long, Di; Ma, Yingzhao; Wan, Wei; Hong, Yang

doi:10.1002/2016wr019961

Cited by 51 publications

(42 citation statements)

References 42 publications

(82 reference statements)

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“…This matchup group is hereinafter referred to as Group 1. This relative large temporal difference is adopted to acquire adequate coincident events to support solid statistical analysis [29]. We also tried other time intervals ranging from 5 to 15 min.…”

Section: Methodsmentioning

confidence: 99%

“…The results applying the whole swath data are presented and discussed in Sections 3.1 and 3.2. Furthermore, since the TRMM PR scan pattern and GPM DPR normal scan pattern are very similar, we first selected the matchup pixels of all the DPR NS swath (referred to as DPR_NS) and TRMM PR swath within a time interval of 20 min and a space interval of two km same as those used in [29]. This matchup group is hereinafter referred to as Group 1.…”

Section: Methodsmentioning

confidence: 99%

“…When using ground-based instruments, such as the rain gauges and ground-based radars, to observe precipitation events, researchers often have difficulty obtaining sufficient data of good quality [29]. This is particularly true over remote mountainous regions and ocean due to the sparse distribution and uneven coverage of these observation instruments [29].…”

Section: Comparison Of Precipitation On Different Surface Typesmentioning

confidence: 99%

“…This is particularly true over remote mountainous regions and ocean due to the sparse distribution and uneven coverage of these observation instruments [29]. TRMM PR and GPM DPR have played an important role in providing precipitation estimates over the global oceans and remote regions.…”

Section: Comparison Of Precipitation On Different Surface Typesmentioning

confidence: 99%

“…In addition, since the specific methods adopted to adjust the attenuation have strong assumptions, they can have a profound effect on the quality of the final precipitation estimates. Combining sensors operating at other frequencies to obtain more detailed information to enhance the estimation of precipitation with different intensities and phases is an effective way to solve this problem [29]. Other efforts such as the constructing constellation of various instruments and platforms can make a great contribution as well.…”

mentioning

confidence: 99%

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Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

2017

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Spaceborne precipitation radars are powerful tools used to acquire adequate and highquality precipitation estimates with high spatial resolution for a variety of applications in hydrological research. The Global Precipitation Measurement (GPM) mission, which deployed the first spaceborne Ka-and Ku-dual frequency radar (DPR), was launched in February 2014 as the upgraded successor of the Tropical Rainfall Measuring Mission (TRMM). This study matches the swath data of TRMM PR and GPM DPR Level 2 products during their overlapping periods at the global scale to investigate their similarities and DPR's improvements concerning precipitation amount estimation and type classification of GPM DPR over TRMM PR. Results show that PR and DPR agree very well with each other in the global distribution of precipitation, while DPR improves the detectability of precipitation events significantly, particularly for light precipitation. The occurrences of total precipitation and the light precipitation (rain rates < 1 mm/h) detected by GPM DPR are~1.7 and~2.53 times more than that of PR. With regard to type classification, the dual-frequency (Ka/Ku) and single frequency (Ku) methods performed similarly. In both inner (the central 25 beams) and outer swaths (1-12 beams and 38-49 beams) of DPR, the results are consistent. GPM DPR improves precipitation type classification remarkably, reducing the misclassification of clouds and noise signals as precipitation type "other" from 10.14% of TRMM PR to 0.5%. Generally, GPM DPR exhibits the same type division for around 82.89% (71.02%) of stratiform (convective) precipitation events recognized by TRMM PR. With regard to the freezing level height and bright band (BB) height, both radars correspond with each other very well, contributing to the consistency in stratiform precipitation classification. Both heights show clear latitudinal dependence. Results in this study shall contribute to future development of spaceborne radar precipitation retrievals and benefit hydrological and meteorological research.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Comparison Of Precipitation On Different Surface Typesmentioning

confidence: 99%

Section: Comparison Of Precipitation On Different Surface Typesmentioning

confidence: 99%

mentioning

confidence: 99%

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Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

2017

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Observed radiative cooling over the Tibetan Plateau for the past three decades driven by snow cover‐induced surface albedo anomaly

et al. 2017

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Seasonal snow cover on the Tibetan Plateau (TP) is a sensitive indicator of climate change. Unlike the decreasing snow cover extent and associated weakening of radiative cooling effects for the Northern Hemisphere during recent decades reported by previous studies, snow cover variability over the TP and its impact on the energy budget remain largely unknown. We defined the snow cover‐induced radiative forcing (SnRF) as the instantaneous perturbation to Earth's shortwave radiation at the top of the atmosphere (TOA) induced by the presence of snow cover. Here using satellite observations and a radiative kernel approach, we found slightly enhanced SnRF, i.e., a radiative cooling effect on the TP during the past three decades (1982–2014). However, this cooling effect weakened during 2001–2014 because of reduced snow cover at a rate of −0.61% decade−1 and land surface albedo at a rate of −0.72% decade−1. Changes in snow cover fraction are highly correlated with anomalies in land surface albedo (as) over the TP both spatially and temporally. Moreover, the SnRF is closely related to the direct observation of TOA shortwave flux anomalies (R2 = 0.54, p = 0.004) over the TP during 2001–2014. Despite the insignificant interannual variability in SnRF, its intra‐annual variability has intensified driven mostly by enhanced SnRF during the snow accumulation season but weakened SnRF during the melt season, indicating greater energy release during the transition between accumulation and melt seasons. This may pose a great challenge to snow meltwater use and flood prediction for transboundary rivers originating from the TP, such as the Brahmaputra River basin.

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The Global Precipitation Measurement (GPM) mission's scientific achievements and societal contributions: reviewing four years of advanced rain and snow observations

Skofronick-Jackson

Kirschbaum

Petersen

et al. 2018

Quart J Royal Meteoro Soc

133

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Precipitation represents a life‐critical energy and hydrologic exchange between the Earth's atmosphere and its surface. As such, knowledge of where, when and how much rain and snow falls is essential for scientific research and societal applications. Building on the 17‐year success of the Tropical Rainfall Measurement Mission (TRMM), the Global Precipitation Measurement (GPM) Core Observatory (GPM‐CO) is the first US National Aeronautical and Space Administration (NASA) satellite mission specifically designed with sensors to observe the structure and intensities of both rain and falling snow. The GPM‐CO has proved to be a worthy successor to TRMM, extending and improving high‐quality active and passive microwave observations across all times of day. The GPM‐CO launched in early 2014, is a joint mission between NASA and the Japanese Aerospace Exploration Agency (JAXA), with sensors that include the NASA‐provided GPM Microwave Imager and the JAXA‐provided Dual‐frequency Precipitation Radar. These sensors were devised with high accuracy standards enabling them to be used as a reference for inter‐calibrating a constellation of partner satellite data. These inter‐calibrated partner satellite retrievals are used with infrared data to produce merged precipitation estimates at temporal scales of 30 min and spatial scales of 0.1° × 0.1°. Precipitation estimates from the GPM‐CO and partner constellation satellites, provided in near real time and later reprocessed with all ancillary data, are an indispensable source of precipitation data for operational and scientific users. Advances have been made using GPM data, primarily in improving sensor calibration, retrieval algorithms, and ground validation measurements, and used to further our understanding of the characteristics of liquid and frozen precipitation and the science of water and hydrological cycles for climate/weather forecasting. These advances have extended to societal benefits related to water resources, operational numerical weather prediction, hurricane monitoring, prediction, and disaster response, extremes, and disease.

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Similarities and differences between three coexisting spaceborne radars in global rainfall and snowfall estimation

Cited by 51 publications

References 42 publications

Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

Observed radiative cooling over the Tibetan Plateau for the past three decades driven by snow cover‐induced surface albedo anomaly

The Global Precipitation Measurement (GPM) mission's scientific achievements and societal contributions: reviewing four years of advanced rain and snow observations

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