Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019JD030804 |
Bias Correction of High-Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments | |
Bannister, Daniel1,2; Orr, Andrew1; Jain, Sanjay K.3; Holman, Ian P.4; Momblanch, Andrea4; Phillips, Tony1; Adeloyes, Adebayo J.5; Snapir, Boris4; Waine, Toby W.4; Hosking, J. Scott1; Allen-Sader, Clare1 | |
2019-12-26 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
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ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2019 |
卷号 | 124期号:24页码:14220-14239 |
文章类型 | Article |
语种 | 英语 |
国家 | England; India; Scotland |
英文摘要 | The need to provide accurate estimates of precipitation over catchments in the Hindu Kush, Karakoram, and Himalaya mountain ranges for hydrological and water resource systems assessments is widely recognized, as is identifying precipitation extremes for assessing hydro-meteorological hazards. Here, we investigate the ability of bias-corrected Weather Research and Forecasting model output at 5-km grid spacing to reproduce the spatiotemporal variability of precipitation for the Beas and Sutlej river basins in the Himalaya, measured by 44 stations spread over the period 1980 to 2012. For the Sutlej basin, we find that the raw (uncorrected) model output generally underestimated annual, monthly, and (particularly low-intensity) daily precipitation amounts. For the Beas basin, the model performance was better, although biases still existed. It is speculated that the cause of the dry bias over the Sutlej basin is a failure of the model to represent an early-morning maximum in precipitation during the monsoon period, which is related to excessive precipitation falling upwind. However, applying a nonlinear bias-correction method to the model output resulted in much better results, which were superior to precipitation estimates from reanalysis and two gridded datasets. These findings highlight the difficulty in using current gridded datasets as input for hydrological modeling in Himalayan catchments, suggesting that bias-corrected high-resolution regional climate model output is in fact necessary. Moreover, precipitation extremes over the Beas and Sutlej basins were considerably underrepresented in the gridded datasets, suggesting that bias-corrected regional climate model output is also necessary for hydro-meteorological risk assessments in Himalayan catchments. |
英文关键词 | Regional climate modelling Himalaya Precipitation bias-correction Extreme precipitation |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000504438600001 |
WOS关键词 | KOSHI RIVER-BASIN ; HIGH-ALTITUDE ; SATELLITE RAINFALL ; CLOUD MICROPHYSICS ; WESTERN HIMALAYA ; TIBETAN PLATEAU ; WATER-RESOURCES ; GLACIER ; IMPACT ; SIMULATIONS |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/225979 |
专题 | 环境与发展全球科技态势 |
作者单位 | 1.British Antarctic Survey, Cambridge, England; 2.Satavia Ltd, Cambridge, England; 3.Natl Inst Hydrol, Roorkee, Uttar Pradesh, India; 4.Cranfield Univ, Cranfield Water Sci Inst, Cranfield, Beds, England; 5.Heriot Watt Univ, Inst Infrastruct & Environm, Edinburgh, Midlothian, Scotland |
推荐引用方式 GB/T 7714 | Bannister, Daniel,Orr, Andrew,Jain, Sanjay K.,et al. Bias Correction of High-Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2019,124(24):14220-14239. |
APA | Bannister, Daniel.,Orr, Andrew.,Jain, Sanjay K..,Holman, Ian P..,Momblanch, Andrea.,...&Allen-Sader, Clare.(2019).Bias Correction of High-Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,124(24),14220-14239. |
MLA | Bannister, Daniel,et al."Bias Correction of High-Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 124.24(2019):14220-14239. |
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