Unraveling the Relationship Between Tropical Storms and Agricultural Drought

Abstract

Drought and tropical storm (TS) are associated with water deficit and surplus, respectively. Soil moisture is a key component in the hydrological cycle that plays an important role in monitoring drought and reflects the infiltrated or stored water due to TS rainfall. Therefore, soil moisture information can be used for the assessment of whether TS can ameliorate severe drought conditions. Here, we use downscaled 1 km Soil Moisture Active Passive data set generated at the Center for Complex Hydrosystems Research at the University of Alabama, and Hurricane Database 2nd generation to examine the coincidence of extreme events between agricultural droughts and Atlantic TS in the contiguous United States from 2015 to 2019. The Cumulative Distribution Function (CDF) matching approach is employed to correct the bias using the root zone soil moisture data provided by the North American Land Data Assimilation System Phase 2 (NLDAS‐2), and then weekly Standardized Soil Moisture Index is calculated for characterization of agricultural drought. As a result, we estimate the frequency of TS impacted regions in the US, the ratio of droughts ameliorated and exacerbated by TS, and the regions where TS highly affect the offset of drought. Our findings indicate detailed spatial information of the offset of drought conditions based on a high‐resolution data set and provide potential information in terms of mitigating drought and TS for the future.

A Multivariate Scaling System Is Essential to Characterize the Tropical Cyclones' Risk

“…Tropical cyclones (TCs) are among the most devastating natural disasters in the world. Despite the tremendous national governments' protection efforts, they still result in loss of lives and properties ( Karimiziarani et al., 2022; Klotzbach et al., 2018; Munoz et al., 2021; Sebastian et al., 2017; Song et al., 2022; Tennant & Gilmore, 2020). Tropical Cyclones are compound hazards, during which a combination of climate processes and hazards (i.e., torrential rainfall, intense winds, and abnormal surge) lead to significant societal impacts greater than the impacts each can produce in isolation (de Ruiter et al., 2020; Leonard et al., 2014; Zscheischler et al., 2018).…”

The Peer‐To‐Peer Type Propagation From Meteorological Drought to Soil Moisture Drought Occurs in Areas With Strong Land‐Atmosphere Interaction

“…Soil moisture is a key component of the hydrological cycle, which is often used in related research on soil drought. The occurrence mechanism and prediction of soil drought have achieved phased results (Song et al., 2022; Zarekarizi et al., 2021). Both usually happen at the same time, and future compound events are expected to be more frequent and extreme, which will severely limit the continent's ability to act as carbon sinks (Novick et al., 2016).…”

A Remote Sensing Driven Soil Moisture Estimator: Uncertain Downscaling With Geostatistically Based Use of Ancillary Data

“…Song et al. (2022) used downscaled 1 km SMAP data set generated at the Center for Complex Hydrosystems Research at the University of Alabama. Their findings indicate detailed spatial information on offsetting drought conditions based on a high‐resolution data set and provide potential details for mitigating drought.…”

“…Abbaszadeh et al (2020) use an ensemble-based Data Assimilation approach to explore the benefit of independently and jointly assimilating remotely sensed SMAP (Soil Moisture Active Passive) SM (at different spatial resolutions) and USGS streamflow observations to improve the accuracy and reliability of WRF-Hydro model predictions while accounting for uncertainties. Song et al (2022) used downscaled 1 km SMAP data set generated at the Center for Complex Hydrosystems Research at the University of Alabama. Their findings indicate detailed spatial information on offsetting drought conditions based on a high-resolution data set and provide potential details for mitigating drought.…”