Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle

Xia Feng,Paul Houser

doi:10.1155/2016/5481731

Abstract

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 forP,E,R, andCcompared todS/dtanddW/dt.

Highlights

The Intergovernmental Panel on Climate Change (IPCC) stated in its Fifth Assessment Report (AR5) that the global mean surface temperature has increased by about 0.85∘C over the twentieth century and this increase is likely due to the enhancement of the greenhouse effect [1]
The Climate Extremes Index (CEI) is composed of five components measuring the fraction area of the contiguous US (CONUS) that experiences extremes outside the 90th/10th percentile in the maximum and minimum temperature, extreme 1-day precipitation, wet/dry days, and the Palmer Drought Severity Index (PDSI)
The water cycle related variables are obtained from the Modern Era Retrospective-Analysis for Research and Applications (MERRA [18]), a state-of-the-art reanalysis that provides the multiyear estimates of atmospheric conditions and land surface fields

Summary

Introduction

The Intergovernmental Panel on Climate Change (IPCC) stated in its Fifth Assessment Report (AR5) that the global mean surface temperature has increased by about 0.85∘C over the twentieth century and this increase is likely due to the enhancement of the greenhouse effect [1]. Because of the central importance of water in the Earth system, any changes in mean, variability, and extremes of water cycle would have profound impact on our society and environment. Tools for monitoring climate variability and change have been developed primarily through the use of indicators. Indicators usually are measurements or calculations that represent the important features of the status and trend of climate system and are often used to guide both research and decisions [10]. Karl et al [11] introduced a combined Climate Extremes Index (CEI) to quantify observed changes in multiple types of climate extremes within the contiguous US (CONUS). The CEI is composed of five components measuring the fraction area of the CONUS that experiences extremes outside the 90th/10th percentile in the maximum and minimum temperature, extreme 1-day precipitation, wet/dry days, and the Palmer Drought Severity Index (PDSI). The USDM utilizes a unique classification system from D0–D4 representing 30th, 20th, 10th, 5th, and 2nd percentile to measure the strength

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Conclusion