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Anthony M. DeAngelis, Hailan Wang, Randal D. Koster, Siegfried D. Schubert, Yehui Chang, and Jelena Marshak

1. Introduction Droughts that develop on time scales of several weeks to a few months, known as flash droughts, have been receiving increased attention by the scientific community (e.g., Svoboda et al. 2002 ; Otkin et al. 2018 ; Pendergrass et al. 2020 ). Characterized by a lack of precipitation, enhanced evapotranspiration, and a rapid decline in soil moisture, flash droughts can disrupt agricultural production, deplete water resources, and impair natural ecosystems and vegetation ( Smith

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Christa D. Peters-Lidard, David M. Mocko, Lu Su, Dennis P. Lettenmaier, Pierre Gentine, and Michael Barlage

is adjusted based on local historical conditions as anomalies. As such, PDSI is not only sensitive to water supply deficit, but also to variability in atmospheric demand such as higher vapor pressure deficit. Computing PDSI is more involved than SPI or SPEI, as it requires the computation of a water budget. Similar to SPEI, it has been shown that the computation of PDSI is sensitive to the calculation of PET (e.g., Milly and Dunne 2016 ). Land surface model–based drought indicators Land surface

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Yaling Liu, Dongdong Chen, Soukayna Mouatadid, Xiaoliang Lu, Min Chen, Yu Cheng, Zhenghui Xie, Binghao Jia, Huan Wu, and Pierre Gentine

1. Introduction Soil moisture (SM) is an essential component of the Earth system. It affects the variability of the coupled energy (latent and sensible heat fluxes) and water fluxes (runoff and evapotranspiration) by modifying the partitioning of water and energy across the land–atmosphere interface ( Seneviratne et al. 2010 ). The effects of SM on evapotranspiration also impact temperature variability and may intrigue persistent heatwaves ( Fischer et al. 2007 ; Hirschi et al. 2011

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Keyhan Gavahi, Peyman Abbaszadeh, Hamid Moradkhani, Xiwu Zhan, and Christopher Hain

1. Introduction Climate extremes such as droughts and floods are becoming more severe and frequent, causing unprecedented threats to food and water security ( Hameed et al. 2019 ; Alipour et al. 2020 ; Rammig et al. 2020 ). Drought is a natural climate extreme occurring in virtually all climatic zones. Drought is considered to be a complex phenomenon classified into four major types including meteorological, agricultural, hydrological, and socioeconomic drought. Among these four types

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Shanshui Yuan, Steven M. Quiring, and Chen Zhao

). Wang et al. (2015) identified two main categories of drought indices: those that are purely based on statistical probability, such as the standardized precipitation index (SPI; McKee et al. 1993 ), and those that are based on a combination of a water balance model and statistical probability, such as the Palmer drought severity index (PDSI; Palmer 1965 ). The various drought indices do not always agree regarding the degree of dryness/wetness because each index is designed for a different purpose

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Yizhou Zhuang, Amir Erfanian, and Rong Fu

traditional definition for the Southwest usually just includes the states of Arizona and New Mexico, which only covers the southern part of the region defined here. c. Atmospheric moisture budget To derive individual moisture tendencies, we used the water vapor budget equation for a unit mass of air ( Yanai et al. 1973 ) as shown in Eq. (1) : (1) ∂ q ∂ t + ∇ ⋅ ( q v ) + ∂ ( q ω ) ∂ p = e − c , where t , q , and p stand for time, specific humidity, and pressure, respectively; v and ω are the

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Richard Seager, Jennifer Nakamura, and Mingfang Ting

precipitation, circulation, water vapor transports and SSTs. All onsets and terminations were associated with northerly and southerly flows, respectively, and associated anomalous moisture exports and imports. However, SNT also found that the flow anomalies occurred within a variety of hemispheric scale circulation anomaly patterns. SNT further found that these DO&Ts and driving circulation anomalies were not consistently related to SST anomalies that might provide predictability on seasonal time scales

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Kingtse C. Mo and Dennis P Lettenmaier

variables such as downward solar and longwave radiation, humidity, and wind using methods described by Bohn et al. (2013) . We used retrospective forcings from the near-real-time University of California, Los Angeles (UCLA) surface water monitor, which were derived from roughly 2400 index stations across the conterminous United States (CONUS) using procedures outlined in Wood and Lettenmaier (2006) . The 10-m wind speed was taken from the Climate Data Assimilation System (CDAS; Kalnay et al. 1996

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