Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle
In this study, we developed a suite of spatially and temporally scalable Water Cycle Indicators (WCI) to examine the long-term changes in water cycle variability and demonstrated their use over the contiguous US (CONUS) during 1979–2013 using the MERRA reanalysis product. The WCI indicators consist...
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doaj-8d828b15a51f4c34868467f1f281ef1c2020-11-24T23:06:02ZengHindawi LimitedAdvances in Meteorology1687-93091687-93172016-01-01201610.1155/2016/54817315481731Developing and Demonstrating Climate Indicators for Monitoring the Changing Water CycleXia Feng0Paul Houser1Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA 22030, USADepartment of Geography and Geoinformation Science, George Mason University, Fairfax, VA 22030, USAIn this study, we developed a suite of spatially and temporally scalable Water Cycle Indicators (WCI) to examine the long-term changes in water cycle variability and demonstrated their use over the contiguous US (CONUS) during 1979–2013 using the MERRA reanalysis product. The WCI indicators consist of six water balance variables monitoring the mean conditions and extreme aspects of the changing water cycle. The variables include precipitation (P), evaporation (E), runoff (R), terrestrial water storage (dS/dt), moisture convergence flux (C), and atmospheric moisture content (dW/dt). Means are determined as the daily total value, while extremes include wet and dry extremes, defined as the upper and lower 10th percentile of daily distribution. Trends are assessed for annual and seasonal indicators at several different spatial scales. Our results indicate that significant changes have occurred in most of the indicators, and these changes are geographically and seasonally dependent. There are more upward trends than downward trends in all eighteen annual indicators averaged over the CONUS. The spatial correlations between the annual trends in means and extremes are statistically significant across the country and are stronger for P, E, R, and C compared to dS/dt and dW/dt.http://dx.doi.org/10.1155/2016/5481731 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xia Feng Paul Houser |
spellingShingle |
Xia Feng Paul Houser Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle Advances in Meteorology |
author_facet |
Xia Feng Paul Houser |
author_sort |
Xia Feng |
title |
Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle |
title_short |
Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle |
title_full |
Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle |
title_fullStr |
Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle |
title_full_unstemmed |
Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle |
title_sort |
developing and demonstrating climate indicators for monitoring the changing water cycle |
publisher |
Hindawi Limited |
series |
Advances in Meteorology |
issn |
1687-9309 1687-9317 |
publishDate |
2016-01-01 |
description |
In this study, we developed a suite of spatially and temporally scalable Water Cycle Indicators (WCI) to examine the long-term changes in water cycle variability and demonstrated their use over the contiguous US (CONUS) during 1979–2013 using the MERRA reanalysis product. The WCI indicators consist of six water balance variables monitoring the mean conditions and extreme aspects of the changing water cycle. The variables include precipitation (P), evaporation (E), runoff (R), terrestrial water storage (dS/dt), moisture convergence flux (C), and atmospheric moisture content (dW/dt). Means are determined as the daily total value, while extremes include wet and dry extremes, defined as the upper and lower 10th percentile of daily distribution. Trends are assessed for annual and seasonal indicators at several different spatial scales. Our results indicate that significant changes have occurred in most of the indicators, and these changes are geographically and seasonally dependent. There are more upward trends than downward trends in all eighteen annual indicators averaged over the CONUS. The spatial correlations between the annual trends in means and extremes are statistically significant across the country and are stronger for P, E, R, and C compared to dS/dt and dW/dt. |
url |
http://dx.doi.org/10.1155/2016/5481731 |
work_keys_str_mv |
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