%0 Journal Article %1 apurv2019evaluation %A Apurv, Tushar %A Cai, Ximing %D 2019 %J Water Resources Research %K droughts, extremes, statistics %N 0 %R 10.1029/2018WR024047 %T Evaluation of the Stationarity Assumption for Meteorological Drought Risk Estimation at the Multidecadal Scale in Contiguous United States %U https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018WR024047 %V 0 %X Abstract In this study, we analyze the nonstationarity in meteorological droughts at the multidecadal scale in different parts of the contiguous United States during 1901–2017. We develop metrics to compare the drought risk calculated under the assumptions of stationarity and nonstationarity and identify their spatial and temporal patterns. By analyzing the variability of drought risk in the past and exploring its ongoing patterns, we evaluate in which regions of the contiguous United States the assumption of stationarity can be safely used for drought risk planning and management. We find statistically significant interdecadal changes in the probability distribution functions of drought severity in parts of the Northwest, upper Midwest, the Northeast, eastern parts of Great Plains and in parts of Arizona, New Mexico, Utah, and Nevada in the Southwest. In these regions, the nonstationary risk has been significantly higher than the stationary estimate of risk in the past, which shows that the assumption of stationarity can lead to the underestimation of drought risk in these regions. The multidecadal drought risk shows low variability in California, parts of northern and western Great Plains, Ohio Valley, and in the Southeast, since the statistical properties of droughts have not changed significantly in these regions during 1901–2017. However, the meteorological drought risk has increased in California and the Southeast in the recent decades due to the influence of global warming and hence the assumption of stationarity for risk estimation may lead to underestimation of drought risk in future in these regions if this effect of global warming persists.

@article{apurv2019evaluation, abstract = {Abstract In this study, we analyze the nonstationarity in meteorological droughts at the multidecadal scale in different parts of the contiguous United States during 1901–2017. We develop metrics to compare the drought risk calculated under the assumptions of stationarity and nonstationarity and identify their spatial and temporal patterns. By analyzing the variability of drought risk in the past and exploring its ongoing patterns, we evaluate in which regions of the contiguous United States the assumption of stationarity can be safely used for drought risk planning and management. We find statistically significant interdecadal changes in the probability distribution functions of drought severity in parts of the Northwest, upper Midwest, the Northeast, eastern parts of Great Plains and in parts of Arizona, New Mexico, Utah, and Nevada in the Southwest. In these regions, the nonstationary risk has been significantly higher than the stationary estimate of risk in the past, which shows that the assumption of stationarity can lead to the underestimation of drought risk in these regions. The multidecadal drought risk shows low variability in California, parts of northern and western Great Plains, Ohio Valley, and in the Southeast, since the statistical properties of droughts have not changed significantly in these regions during 1901–2017. However, the meteorological drought risk has increased in California and the Southeast in the recent decades due to the influence of global warming and hence the assumption of stationarity for risk estimation may lead to underestimation of drought risk in future in these regions if this effect of global warming persists.}, added-at = {2019-07-04T13:08:11.000+0200}, author = {Apurv, Tushar and Cai, Ximing}, biburl = {https://www.bibsonomy.org/bibtex/2e27e0d5e911701e9fd660d5b65d7ebb1/rutgerdankers}, doi = {10.1029/2018WR024047}, eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018WR024047}, interhash = {c7f60001305d5319f9a97b6b35a97b54}, intrahash = {e27e0d5e911701e9fd660d5b65d7ebb1}, journal = {Water Resources Research}, keywords = {droughts, extremes, statistics}, number = 0, timestamp = {2019-07-04T13:08:11.000+0200}, title = {Evaluation of the Stationarity Assumption for Meteorological Drought Risk Estimation at the Multidecadal Scale in Contiguous United States}, url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018WR024047}, volume = 0, year = 2019 }