气候变化领域集成服务门户(CCPortal): Evaluation of multiple climate data sources for managing environmental resources in East Africa

CCPortal

DOI	10.5194/hess-22-4547-2018
	Evaluation of multiple climate data sources for managing environmental resources in East Africa
	Gebrechorkos S.H.; Hülsmann S.; Bernhofer C.
发表日期	2018
ISSN	1027-5606
起始页码	4547
结束页码	4564
卷号	22 期号:8
英文摘要	Managing environmental resources under conditions of climate change and extreme climate events remains among the most challenging research tasks in the field of sustainable development. A particular challenge in many regions such as East Africa is often the lack of sufficiently long-term and spatially representative observed climate data. To overcome this data challenge we used a combination of accessible data sources based on station data, earth observations by remote sensing, and regional climate models. The accuracy of the Africa Rainfall Climatology version 2.0 (ARC2), Climate Hazards Group InfraRed Precipitation (CHIRP), CHIRP with Station data (CHIRPS), Observational-Reanalysis Hybrid (ORH), and regional climate models (RCMs) are evaluated against station data obtained from the respective national weather services and international databases. We did so by performing a comparison in three ways: Point to pixel, point to area grid cell average, and stations' average to area grid cell average over 21 regions of East Africa: 17 in Ethiopia, 2 in Kenya, and 2 in Tanzania. We found that the latter method provides better correlation and significantly reduces biases and errors. The correlations were analysed at daily, dekadal (10 days), and monthly resolution for rainfall and maximum and minimum temperature (Tmax and Tmin) covering the period of 1983-2005. At a daily timescale, CHIRPS, followed by ARC2 and CHIRP, is the best performing rainfall product compared to ORH, individual RCMs (I-RCM), and RCMs' mean (RCMs). CHIRPS captures the daily rainfall characteristics well, such as average daily rainfall, amount of wet periods, and total rainfall. Compared to CHIRPS, ARC2 showed higher underestimation of the total (-30%) and daily (-14%) rainfall. CHIRP, on the other hand, showed higher underestimation of the average daily rainfall (-53%) and duration of dry periods (-29%). Overall, the evaluation revealed that in terms of multiple statistical measures used on daily, dekadal, and monthly timescales, CHIRPS, CHIRP, and ARC2 are the best performing rainfall products, while ORH, I-RCM, and RCMs are the worst performing products. For Tmax and Tmin, ORH was identified as the most suitable product compared to I-RCM and RCMs. Our results indicate that CHIRPS (rainfall) and ORH (Tmax and Tmin), with higher spatial resolution, should be the preferential data sources to be used for climate change and hydrological studies in areas of East Africa where station data are not accessible. © Author(s) 2018.
语种	英语
scopus关键词	Chirp modulation; Climate models; Earth (planet); Rain; Remote sensing; Soil moisture; Sustainable development; Earth observations; Environmental resources; International database; Maximum and minimum temperatures; National Weather Services; Rainfall climatologies; Regional climate models; Statistical measures; Climate change; climate change; climate modeling; data set; pixel; rainfall; regional climate; remote sensing; resource management; satellite data; spatial resolution; sustainable development; temperature effect; East Africa; Ethiopia; Kenya; Tanzania
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159931
作者单位	Gebrechorkos, S.H., United Nations University, Institute for Integrated Management of Material Fluxes and of Resources (UNU-FLORES), Dresden, 01067, Germany, Faculty of Environmental Sciences, Institute of Hydrology and Meteorology, Technische Universität Dresden, Dresden, 01062, Germany; Hülsmann, S., United Nations University, Institute for Integrated Management of Material Fluxes and of Resources (UNU-FLORES), Dresden, 01067, Germany; Bernhofer, C., Faculty of Environmental Sciences, Institute of Hydrology and Meteorology, Technische Universität Dresden, Dresden, 01062, Germany
推荐引用方式 GB/T 7714	Gebrechorkos S.H.,Hülsmann S.,Bernhofer C.. Evaluation of multiple climate data sources for managing environmental resources in East Africa[J],2018,22(8).
APA	Gebrechorkos S.H.,Hülsmann S.,&Bernhofer C..(2018).Evaluation of multiple climate data sources for managing environmental resources in East Africa.Hydrology and Earth System Sciences,22(8).
MLA	Gebrechorkos S.H.,et al."Evaluation of multiple climate data sources for managing environmental resources in East Africa".Hydrology and Earth System Sciences 22.8(2018).