Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2020WR029377 |
Data-driven worldwide quantification of large-scale hydroclimatic co-variation patterns and comparison with reanalysis and Earth System modeling | |
Navid Ghajarnia; Zahra Kalantari; Georgia Destouni | |
2021-09-21 | |
发表期刊 | Water Resources Research
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出版年 | 2021 |
英文摘要 | Large-scale co-variations of freshwater fluxes and storages on land can critically regulate the balance of green (evapotranspiration) and blue (runoff) water fluxes, and related land-atmosphere interactions and hydro-climatic hazards. Such large-scale co-variation patterns are not evident from smaller-scale hydrological studies that have been most common so far, and remain largely unknown for various regions and climates around the world. To contribute to bridging the large-scale knowledge gaps, we synthesize and decipher hydro-climatic data time series over the period 1980-2010 for 6405 catchments around the world. From observation-based data, we identify dominant large-scale linear co-variation patterns between monthly freshwater fluxes and soil moisture (SM) for different world parts and climates. These co-variation patterns are also compared with those obtained from reanalysis products and Earth System Models (ESMs). The observation-based datasets robustly show the strongest large-scale hydrological relationship to be that between SM and runoff (R), consistently across the study catchments and their different climate characteristics. This predominantly strongest co-variation between monthly SM and R is also the most misrepresented by ESMs and reanalysis products, followed by that between monthly precipitation and R. Comparison of observation-based and ESM results also shows that an ESM may perform well for individual monthly variables, but fail in representing the patterns of large-scale linear co-variations between them. Observation-based quantification of these patterns, and ESM and reanalysis improvements for their representation are essential for fundamental understanding, and more accurate and reliable modeling and projection of large-scale hydrological conditions and changes under ongoing global and regional change. This article is protected by copyright. All rights reserved. |
领域 | 资源环境 |
URL | 查看原文 |
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文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/338769 |
专题 | 资源环境科学 |
推荐引用方式 GB/T 7714 | Navid Ghajarnia,Zahra Kalantari,Georgia Destouni. Data-driven worldwide quantification of large-scale hydroclimatic co-variation patterns and comparison with reanalysis and Earth System modeling[J]. Water Resources Research,2021. |
APA | Navid Ghajarnia,Zahra Kalantari,&Georgia Destouni.(2021).Data-driven worldwide quantification of large-scale hydroclimatic co-variation patterns and comparison with reanalysis and Earth System modeling.Water Resources Research. |
MLA | Navid Ghajarnia,et al."Data-driven worldwide quantification of large-scale hydroclimatic co-variation patterns and comparison with reanalysis and Earth System modeling".Water Resources Research (2021). |
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