Mahmoud Osman
Johns Hopkins University;Cairo University | Research Scientist
| Subject Areas: | Drought monitoring and prediction, Hydroclimatology, Weather and climate extremes |
Recent Activity
ABSTRACT:
We present a global dataset of flash drought events, meticulously compiled using the Soil Moisture Volatility Index (SMVI), a cutting-edge tool initially applied within the United States. This dataset marks a significant expansion of the SMVI methodology to a global context, offering an essential resource for comprehensively understanding and predicting rapidly evolving drought phenomena. Characterized by detailed information on the onset, duration, and severity of each event, the dataset covers a wide array of climatic zones, thus providing a diverse and inclusive global perspective. A key feature of this dataset is the integration of atmospheric variables, which sheds light on the meteorological factors driving and influencing flash droughts. Such integration allows for an in-depth exploration of the complex interplay between soil moisture and atmospheric conditions, enhancing our understanding of drought dynamics.
ABSTRACT:
We present a global dataset of flash drought events, meticulously compiled using the Soil Moisture Volatility Index (SMVI), a cutting-edge tool initially applied within the United States. This dataset marks a significant expansion of the SMVI methodology to a global context, offering an essential resource for comprehensively understanding and predicting rapidly evolving drought phenomena. Characterized by detailed information on the onset, duration, and severity of each event, the dataset covers a wide array of climatic zones, thus providing a diverse and inclusive global perspective. A key feature of this dataset is the integration of atmospheric variables, which sheds light on the meteorological factors driving and influencing flash droughts. Such integration allows for an in-depth exploration of the complex interplay between soil moisture and atmospheric conditions, enhancing our understanding of drought dynamics.
ABSTRACT:
We present a global dataset of flash drought events, meticulously compiled using the Soil Moisture Volatility Index (SMVI), a cutting-edge tool initially applied within the United States. This dataset marks a significant expansion of the SMVI methodology to a global context, offering an essential resource for comprehensively understanding and predicting rapidly evolving drought phenomena. Characterized by detailed information on the onset, duration, and severity of each event, the dataset covers a wide array of climatic zones, thus providing a diverse and inclusive global perspective. A key feature of this dataset is the integration of atmospheric variables, which sheds light on the meteorological factors driving and influencing flash droughts. Such integration allows for an in-depth exploration of the complex interplay between soil moisture and atmospheric conditions, enhancing our understanding of drought dynamics.
ABSTRACT:
We present a global dataset of flash drought events, meticulously compiled using the Soil Moisture Volatility Index (SMVI), a cutting-edge tool initially applied within the United States. This dataset marks a significant expansion of the SMVI methodology to a global context, offering an essential resource for comprehensively understanding and predicting rapidly evolving drought phenomena. Characterized by detailed information on the onset, duration, and severity of each event, the dataset covers a wide array of climatic zones, thus providing a diverse and inclusive global perspective. A key feature of this dataset is the integration of atmospheric variables, which sheds light on the meteorological factors driving and influencing flash droughts. Such integration allows for an in-depth exploration of the complex interplay between soil moisture and atmospheric conditions, enhancing our understanding of drought dynamics.
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Created: Dec. 20, 2023, 3:03 a.m.
Authors: Osman, Mahmoud · Benjamin Zaitchik · Jason Otkin · Martha Anderson
ABSTRACT:
We present a global dataset of flash drought events, meticulously compiled using the Soil Moisture Volatility Index (SMVI), a cutting-edge tool initially applied within the United States. This dataset marks a significant expansion of the SMVI methodology to a global context, offering an essential resource for comprehensively understanding and predicting rapidly evolving drought phenomena. Characterized by detailed information on the onset, duration, and severity of each event, the dataset covers a wide array of climatic zones, thus providing a diverse and inclusive global perspective. A key feature of this dataset is the integration of atmospheric variables, which sheds light on the meteorological factors driving and influencing flash droughts. Such integration allows for an in-depth exploration of the complex interplay between soil moisture and atmospheric conditions, enhancing our understanding of drought dynamics.
Created: Feb. 21, 2024, 4:33 p.m.
Authors: Osman, Mahmoud · Benjamin Zaitchik · Jason Otkin · Martha Anderson
ABSTRACT:
We present a global dataset of flash drought events, meticulously compiled using the Soil Moisture Volatility Index (SMVI), a cutting-edge tool initially applied within the United States. This dataset marks a significant expansion of the SMVI methodology to a global context, offering an essential resource for comprehensively understanding and predicting rapidly evolving drought phenomena. Characterized by detailed information on the onset, duration, and severity of each event, the dataset covers a wide array of climatic zones, thus providing a diverse and inclusive global perspective. A key feature of this dataset is the integration of atmospheric variables, which sheds light on the meteorological factors driving and influencing flash droughts. Such integration allows for an in-depth exploration of the complex interplay between soil moisture and atmospheric conditions, enhancing our understanding of drought dynamics.
Created: Feb. 25, 2024, 4:19 a.m.
Authors: Osman, Mahmoud · Benjamin Zaitchik · Jason Otkin · Martha Anderson
ABSTRACT:
We present a global dataset of flash drought events, meticulously compiled using the Soil Moisture Volatility Index (SMVI), a cutting-edge tool initially applied within the United States. This dataset marks a significant expansion of the SMVI methodology to a global context, offering an essential resource for comprehensively understanding and predicting rapidly evolving drought phenomena. Characterized by detailed information on the onset, duration, and severity of each event, the dataset covers a wide array of climatic zones, thus providing a diverse and inclusive global perspective. A key feature of this dataset is the integration of atmospheric variables, which sheds light on the meteorological factors driving and influencing flash droughts. Such integration allows for an in-depth exploration of the complex interplay between soil moisture and atmospheric conditions, enhancing our understanding of drought dynamics.
Created: June 5, 2024, 8:19 a.m.
Authors: Osman, Mahmoud · Benjamin Zaitchik · Jason Otkin · Martha Anderson · Talebpour, Mahdad
ABSTRACT:
We present a global dataset of flash drought events, meticulously compiled using the Soil Moisture Volatility Index (SMVI), a cutting-edge tool initially applied within the United States. This dataset marks a significant expansion of the SMVI methodology to a global context, offering an essential resource for comprehensively understanding and predicting rapidly evolving drought phenomena. Characterized by detailed information on the onset, duration, and severity of each event, the dataset covers a wide array of climatic zones, thus providing a diverse and inclusive global perspective. A key feature of this dataset is the integration of atmospheric variables, which sheds light on the meteorological factors driving and influencing flash droughts. Such integration allows for an in-depth exploration of the complex interplay between soil moisture and atmospheric conditions, enhancing our understanding of drought dynamics.