Performance evaluation of radar and satellite rainfalls for Typhoon Morakot over Taiwan: Are remote-sensing products ready for gauge denial scenario of extreme events?

Evaluation of Version-7 TRMM Multi-Satellite Precipitation Analysis Product during the Beijing Extreme Heavy Rainfall Event of 21 July 2012

“…All the above statistics are computed pixel by pixel. Compared with rain gauge observations, the number of hits (A), false alarms (B), and misses (C) can be computed, and then statistic metrics POD, FAR and CSI can be computed with A, B, and C. More detail is available in [1]. Figure 2 shows the daily-accumulated rainfall (00:00 UTC on 21 July 2012 to 00:00 UTC on 22 July 2012).…”

“…Typhoon Morakot in Taiwan in August 2009 [1][2][3], severe floods in Pakistan in 2010 [4] and in Beijing in July 2012 [5,6], and Hurricane Sandy [7] in northeast U.S. in October 2012 have shown that the precipitation system tends to develop into heavier storms with a longer dry period between two precipitation events [8]. On 21 July 2012, a 60-year return period extreme storm hit Beijing and adjacent regions, triggering flash floods in the urban area and landslides in the mountainous region.…”

“…The real time product 3B42RT of V7 (covering the period of 1998-present) was also available in October 2012. The accurate measurement of precipitation would greatly benefit the detection and warning of severe storms, flash flooding and landslides [1,15]. Therefore, it is a key task for NASA's missions to improve the satellite's performance in measuring precipitation in order to advance our understanding of Earth's water and energy cycle and improve the forecast of extreme events that cause natural hazards and disasters [16][17][18].…”

“…We assumed that rain gauge measurements represent the precipitation truth within the corresponding pixel of satellite data. This kind of assumption is a common way to evaluate remote sensing products and has been widely applied by the remote sensing community [1,[27][28][29][30][31]. Considering that the TRMM products to be evaluated have the same spatio-temporal resolution, to better address the differences for these TRMM products, the uncertainty analysis associated with the NUBF effect has not been included in the current study.…”

Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean

“…1-10 km and 5-60 min), distributed, regional, or even global rainfall estimates. These datasets allow for capturing dynamics and variability of rainfall extremes at scales that cannot be represented by rain gauges (Amitai et al, 2011;Chen et al, 2013;Marra et al, 2016;Panziera et al, 2016;Tapiador et al, 2012) and permit one to overcome the issues related to the conversion of point to areal information. Given the quantitative uncertainty related to remote sensing precipitation products (Berne and Krajewski, 2013;Mei et al, 2016;Stampoulis et al, 2013) and their limited records, unable to provide adequate samples of the climatology, the possibility of using such datasets for rainfall frequency analysis has only recently started to be explored.…”