Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño–Southern Oscillation (ENSO)

Henchiri, Malak; Igbawua, Tertsea; Javed, Tehseen; Bai, Yun; Zhang, Sha; Essifi, Bouajila; Ujoh, Fanan; Zhang, Jiahua

doi:10.3390/rs13234730

Cited by 18 publications

(8 citation statements)

References 72 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This agrees with Henchiri et al. (2021), who reported the same over North and West Africa. The lowest severity (1.0) was observed in January 2010, with an interarrival period of 17 months.…”

Section: Resultssupporting

confidence: 93%

“…Over Africa, the maximum severity (33.6) was observed between January 1983 and June 1984 (18-month duration), with an interarrival period of 19 months. This agrees with Henchiri et al (2021), who reported the same over North and West Africa. The lowest severity (1.0) was observed in January 2010, with an interarrival period of 17 months.…”

Section: Drought Severity Intensity and Interarrival Periodsupporting

confidence: 93%

See 1 more Smart Citation

Multivariate Drought Monitoring, Propagation, and Projection Using Bias‐Corrected General Circulation Models

et al. 2023

View full text Add to dashboard Cite

Understanding how droughts are characterized, propagated, and projected, particularly multivariate droughts, is necessary to explain the variability and changes in drought characteristics. This study aims to understand multimodel global drought monitoring, propagation, and projection by utilizing a multivariate standardized drought index (MSDI) during the historical (1959–2014) and future (2045–2100) periods under two socioeconomic pathways SSPs (370 and 585), derived from the bias‐corrected Coupled Model Intercomparison Project Phase 6 (CMIP6). Based on the energy metrics, the multivariate bias correction method outperformed other techniques in correcting the biases in the CMIP6 drought representation. The drought indicators demonstrate distinct categories for meteorological, hydrological, and multivariate droughts. There were significant high cross correlations between Heatwave Total Length (HWTL) and MSDI in Africa and South America for all lagged times. Europe and North America generally saw the maximum MSDI drought duration (228 months) during the historical period. For future projections, Africa recorded the maximum drought duration (197 months), while Europe witnessed the minimum drought duration for SSP 370 (171 months), and North America (149 months) for SSP 585. Furthermore, during the historical period in tropical Africa, the propagation of meteorological to hydrological drought was slower during the wet months than during the dry months. Under the SSP 370 future projection, there was a shift in the long period of meteorological‐hydrological propagation from the middle and late wet months to the beginning of the wet months in tropical Africa. Therefore, tracking and projecting drought characteristics is vital for understanding the risk of drought‐related consequences.

show abstract

Section: Resultssupporting

confidence: 93%

Section: Drought Severity Intensity and Interarrival Periodsupporting

confidence: 93%

Multivariate Drought Monitoring, Propagation, and Projection Using Bias‐Corrected General Circulation Models

et al. 2023

View full text Add to dashboard Cite

show abstract

“…A comprehensive assessment of droughts is required, which includes a realistic representation of the water available in soils, drought propagation, feedback from vegetation cover, and human influence during these events (Henchiri et al 2021 ).…”

Section: Resultsmentioning

confidence: 99%

A state-of-the-art examination of disaster management in Sierra Leone: the implementation drawbacks, research gaps, advances, and prospects

Turay

Gbetuwa

2022

Geoenviron Disasters

View full text Add to dashboard Cite

Unfolding events have shown that Sierra Leone is enduring various disasters at a worrying rate. While progress is being made in disaster management, activities that degrade the fragile ecosystem, exacerbated by climate change, poverty, and bad governance, remain growing concerns. Amid these concerns, there is inadequate information to take appropriate actions. The authors wish to provide a solution by examining 35 publications from various scholarly and grey literature and raw data sources, following a critical review process designed to expose the implementation drawbacks, research gaps, advances, and prospects in disaster management in Sierra Leone. The study results show that lapses in data management, fewer professionals, and inefficiencies in communication are the most pressing considerations for improving disaster management in the country. Inadequate funds to implement management plans remain pervasive. Following these findings, we recommend that all first responders be routinely exposed to international tabletop exercises and simulated disaster response training to help them build their capacities and learn from other countries. Students in the relevant disciplines should be encouraged to participate in these exercises to facilitate early learning. Also, management initiatives should consider gender equity, the situations of the disabled, and other vulnerable groups at all levels of planning and implementation of activities. Future studies should assess the influence of social media on disaster management research and practice in the country.

show abstract

“…For these areas to be used for calibration and validation purposes, and to ensure optimal SMC conditions, the months with minimum rainfall are used. According to [30], the average rainfall in the western and eastern areas of the Sahara Desert, along the 20 • N parallel, is practically null. Similar areas can also be identified in the Arabic peninsula [31]).…”

Section: Location Country From Coordinates To Coordinatesmentioning

confidence: 99%

Calibration and Validation of CYGNSS Reflectivity through Wetlands’ and Deserts’ Dielectric Permittivity

et al. 2022

View full text Add to dashboard Cite

The reflection of Global Navigation Satellite Systems (GNSS) signals, namely GNSS-Reflectometry (GNSS-R), has recently proven to be able to monitor land surface properties in the microwave spectrum, at a global scale, and with very low revisiting time. Moreover, this new technique has numerous additional advantages, including low cost, low power consumption, lightweight and small payloads, and near real-time massive data availability, as compared to conventional monostatic microwave remote sensing. However, the GNSS-R surface reflectivity values estimated through the bistatic radar equation, and the Fresnel coefficients have shown a lack of coincidence with real surface reflectivity data, mostly due to calibration issues. Previous studies have attempted to avoid this matter with direct regression methods between uncalibrated GNSS-R reflectivity data and external soil moisture content (SMC) products. However, calibration of GNSS-R reflectivity used in traditional inversion models is still a challenge, such as those to estimate SMC, freeze/thaw, or biomass. In this paper, a successful procedure for GNSS-R reflectivity calibration is established using data from the CYGNSS (Cyclone GNSS) constellation. The scale and bias parameters are estimated from the theoretical dielectric properties of water and dry sand, which are well-known and empirically validated values. We employ four calibration areas that provide maximum range limits of reflectivity, such as deserts and wetlands. The CYGNSS scale factor and the bias parameter resulted in a = 3.77 and b = 0.018, respectively. The derived scale and bias parameters are applied to the CYGNSS dataset, and the retrieved SMC values through the Fresnel reflection coefficients are in excellent agreement with the Soil Moisture Active Passive (SMAP) SMC product. Then, the SMAP SMC is used as a reference true value, and provides a standard linear regression with an R-square coefficient of 0.803, a root mean square error (RMSE) of 0.084, and a Pearson’s correlation coefficient of 0.896.

show abstract

Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño–Southern Oscillation (ENSO)

Cited by 18 publications

References 72 publications

Multivariate Drought Monitoring, Propagation, and Projection Using Bias‐Corrected General Circulation Models

Multivariate Drought Monitoring, Propagation, and Projection Using Bias‐Corrected General Circulation Models

A state-of-the-art examination of disaster management in Sierra Leone: the implementation drawbacks, research gaps, advances, and prospects

Calibration and Validation of CYGNSS Reflectivity through Wetlands’ and Deserts’ Dielectric Permittivity

Contact Info

Product

Resources

About