000			03464nab a22003617a 4500
999			_c62011 _d62003
001			62011
003			MX-TxCIM
005			20240826224818.0
008			200602s2020 ne ||||| |||| 00| 0 eng d
022			_a2212-0947
024	8		_ahttps://doi.org/10.1016/j.wace.2020.100263
040			_aMX-TxCIM
041			_aeng
100	1		_913713 _aAdeme, D.
245	1	0	_aClimate trends and variability at adaptation scale : _bpatterns and perceptions in an agricultural region of the Ethiopian Highlands
260			_aAmsterdam (Netherlands) : _bElsevier, _c2020.
500			_aPeer review
500			_aOpen Access
520			_aAnalysis of climate variability and trends frequently takes place at large scale. For agricultural applications, however, highly localized climate conditions can be critically important. This certainly applies to tropical highland regions, where dissected topography and convectively dominated precipitation processes can lead to strong variability in both mean climate conditions and year-to-year climate variability. This study examines recent climate variability and trends (1981–2016) on Choke Mountain, located in the western Ethiopian Highlands. Through analysis of precipitation and temperature records at monitored locations, we explore observed variability in climate patterns and trends across sites and seasons. The lens for our spatial analysis is the agroecosystem (AES), defined on the basis of prevailing climate and cropping systems, which currently serve as the foundation for climate adaptation planning in the region. We find that interannual temperature variability is greatest in the hottest, driest AES, and is most pronounced in the dry season. All AES warmed significantly in all seasons over the analysis period, but the magnitude of trend was greatest in high elevation AES. Precipitation variability was also large across AES, with largest interannual variability found in the dry season. This season is frequently excluded in climate analyses, but it is a critical harvest time and irrigation period. Trends in rainfall anomaly and precipitation concentration index are less clear, but there is a tendency towards drying and increasing irregularity of rainfall. Interestingly, we find little association between the El Niño Southern Oscillation (ENSO) and temperature or precipitation variability at our study sites. This suggests that even though ENSO is a widely recognized driver of large-scale rainfall variability in the region, its impacts are highly spatially variable. This has implications for applying ENSO-based precipitation outlooks to agricultural management decisions. Farmer interviews reveal that local perceptions of climate variability and trends are generally consistent with the objective observations.
546			_aText in English
650		7	_2AGROVOC _95511 _aClimate change adaptation
650		7	_2AGROVOC _95507 _aTrends
650		0	_aAnalysis _gAGROVOC _927824
651		7	_2AGROVOC _92025 _aEthiopia
700	1		_913714 _aZiatchik, B.F.
700	1		_aFantaye, K.T. _gSocioeconomics Program _gSustainable Agrifood Systems _8INT3458 _9956
700	1		_9427 _aBelay Simane
700	1		_913715 _aAlemayehu, G.
700	1		_913716 _aAdgo, E.
773	0		_dAmsterdam (Netherlands) : Elsevier, 2020. _gv. 29, art. 100263 _tWeather and Climate Extremes _x2212-0947
856	4		_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/20888
942			_2ddc _cJA _n0