000			03258nab a22003497a 4500
999			_c63797 _d63789
001			63797
003			MX-TxCIM
005			20230203154318.0
008			190416s2021 xxu|||p|o|||| 00| 0 eng d
022			_a1525-755X
022			_a1525-7541 (Online)
024	8		_ahttps://doi.org/10.1175/JHM-D-20-0287.1
040			_aMX-TxCIM
041			_aeng
100	1		_8001710725 _aMontes, C. _gSustainable Intensification Program _gSustainable Agrifood Systems _910999
245	1	0	_aIntense precipitation events during the monsoon season in Bangladesh as captured by satellite-based products
260			_aUSA : _bAMS, _c2021.
500			_aPeer review
500			_aOpen Access
520			_aExtreme precipitation events are a serious threat to societal well-being over rainy areas such as Bangladesh. The reliability of studies of extreme events depends on data quality and their spatial and temporal distribution, although these subjects remain with knowledge gaps in many countries. This work focuses on the analysis of four satellite-based precipitation products for monitoring intense rainfall events: the Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS), the PERSIANN–Climate Data Record (PERSIANN-CDR), the Integrated Multisatellite Retrievals (IMERG), and the CPC morphing technique (CMORPH). Five indices of intense rainfall were considered for the period 2000–19 and a set of 31 rain gauges for evaluation. The number and amount of precipitation associated with intense rainfall events are systematically underestimated or overestimated throughout the country. While random errors are higher over the wetter and higher-elevation northeastern and southeastern parts of Bangladesh, biases are more homogeneous. CHIRPS, PERSIANN-CDR, and IMERG perform similar for capturing total seasonal rainfall, but variability is better represented by CHIRPS and IMERG. Better results were obtained by IMERG, followed by PERSIANN-CDR and CHIRPS, in terms of climatological intensity indices based on percentiles, although the three products exhibited systematic errors. IMERG and CMORPH systematically overestimate the occurrence of intense precipitation events. IMERG showed the best performance representing events over a value of 20 mm day−1; CMORPH exhibited random and systematic errors strongly associated with a poor representation of interannual variability in seasonal total rainfall. The results suggest that the datasets have different potential uses and such differences should be considered in future applications regarding extreme rainfall events and risk assessment in Bangladesh.
546			_aText in English
650		7	_2AGROVOC _98181 _aExtreme weather events
650		7	_2AGROVOC _912655 _aSatellite observation
650		7	_2AGROVOC _99386 _aPrecipitation
651		7	_2AGROVOC _91424 _aBangladesh
700	1		_913044 _aAcharya, N.
700	1		_913046 _aHassan, S.M.Q.
700	1		_aKrupnik, T.J. _gSustainable Intensification Program _gSustainable Agrifood Systems _8INT3222 _9906
773	0		_dUSA : AMS, 2021. _gv. 22, no. 6, p. 1405-1419 _tJournal of Hydrometeorology _x1525-755X
856	4		_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/21533
942			_2ddc _cJA _n0