.png){kind=icon}
返回
Addressing rainfall data selection uncertainty using connections between rainfall and streamflow
.png){kind=icon}
OA
AI
DOI：10.1038/s41598-017-00128-5.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Studies of the hydroclimate at regional scales rely on spatial rainfall data products, derived from remotely-sensed (RS) and in-situ (IS, rain gauge) observations. Because regional rainfall cannot be directly measured, spatial data products are biased. These biases pose a source of uncertainty in environmental analyses, attributable to the choices made by data-users in selecting a representation of rainfall. We use the rainforest-savanna transition region in Brazil to show differences in the statistics describing rainfall across nine RS and interpolated-IS daily rainfall datasets covering the period of 1998-2013. These differences propagate into estimates of temporal trends in monthly rainfall and descriptive hydroclimate indices. Rainfall trends from different datasets are inconsistent at river basin scales, and the magnitude of index differences is comparable to the estimated bias in global climate model projections. To address this uncertainty, we evaluate the correspondence of different rainfall datasets with streamflow from 89 river basins. We demonstrate that direct empirical comparisons between rainfall and streamflow provide a method for evaluating rainfall dataset performance across multiple areal (basin) units. These results highlight the need for users of rainfall datasets to quantify this data selection uncertainty problem, and either justify data use choices, or report the uncertainty in derived results.
Keyword:
PRECIPITATION ANALYSIS TMPA
CLIMATE-CHANGE
GLOBAL PRECIPITATION
WATER-BALANCE
AMAZON BASIN
RIVER
DEFORESTATION
INFORMATION
VARIABILITY
DEPENDENCE
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.9
论文数:
27.9W
被引数:
83.5W
机构
引用论文
Cropping frequency and area response to climate variability can exceed yield response.png)
NATURE CLIMATE CHANGE
NATURE CLIMATE CHANGEIF27.1
PREAI
分享收藏分享收藏分享收藏The use of the aridity index to assess climate change effect on annual runoffJOURNAL OF HYDROLOGY
JOURNAL OF HYDROLOGYIF6.3
PREAI
分享收藏The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scalesTRMM多卫星降水分析 (TMPA): 精细尺度的准全球，多年，组合传感器降水估计OAAI
OAAI分享收藏
查看更多内容