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Cornelia Klein
,
Francis Nkrumah
,
Christopher M. Taylor
, and
Elijah A. Adefisan

Abstract

Mesoscale convective systems (MCSs) are the major source of extreme rainfall over land in the tropics and are expected to intensify with global warming. In the Sahel, changes in surface temperature gradients and associated changes in wind shear have been found to be important for MCS intensification in recent decades. Here we extend that analysis to southern West Africa (SWA) by combining 34 years of cloud-top temperatures with rainfall and reanalysis data. We identify clear trends in intense MCSs since 1983 and their associated atmospheric drivers. We also find a marked annual cycle in the drivers, linked to changes in the convective regime during the progression of the West African monsoon. Before the peak of the first rainy season, we identify a shear regime where increased temperature gradients play a crucial role for MCS intensity trends. From June onward, SWA moves into a less unstable, moist regime during which MCS trends are mainly linked to frequency increase and may be more influenced by total column water vapor. However, during both seasons we find that MCSs with the most intense convection occur in an environment with stronger wind shear, increased low-level humidity, and drier midlevels. Comparing the sensitivity of MCS intensity and peak rainfall to low-level moisture and wind shear conditions preceding events, we find a dominant role for wind shear. We conclude that MCS trends are directly linked to a strengthening of two distinct convective regimes that cause the seasonal change of SWA MCS characteristics. However, the convective environment that ultimately produces the most intense MCSs remains the same.

Open access
Christopher J. White
,
Daniela I. V. Domeisen
,
Nachiketa Acharya
,
Elijah A. Adefisan
,
Michael L. Anderson
,
Stella Aura
,
Ahmed A. Balogun
,
Douglas Bertram
,
Sonia Bluhm
,
David J. Brayshaw
,
Jethro Browell
,
Dominik Büeler
,
Andrew Charlton-Perez
,
Xandre Chourio
,
Isadora Christel
,
Caio A. S. Coelho
,
Michael J. DeFlorio
,
Luca Delle Monache
,
Francesca Di Giuseppe
,
Ana María García-Solórzano
,
Peter B. Gibson
,
Lisa Goddard
,
Carmen González Romero
,
Richard J. Graham
,
Robert M. Graham
,
Christian M. Grams
,
Alan Halford
,
W. T. Katty Huang
,
Kjeld Jensen
,
Mary Kilavi
,
Kamoru A. Lawal
,
Robert W. Lee
,
David MacLeod
,
Andrea Manrique-Suñén
,
Eduardo S. P. R. Martins
,
Carolyn J. Maxwell
,
William J. Merryfield
,
Ángel G. Muñoz
,
Eniola Olaniyan
,
George Otieno
,
John A. Oyedepo
,
Lluís Palma
,
Ilias G. Pechlivanidis
,
Diego Pons
,
F. Martin Ralph
,
Dirceu S. Reis Jr.
,
Tomas A. Remenyi
,
James S. Risbey
,
Donald J. C. Robertson
,
Andrew W. Robertson
,
Stefan Smith
,
Albert Soret
,
Ting Sun
,
Martin C. Todd
,
Carly R. Tozer
,
Francisco C. Vasconcelos Jr.
,
Ilaria Vigo
,
Duane E. Waliser
,
Fredrik Wetterhall
, and
Robert G. Wilson

Abstract

The subseasonal-to-seasonal (S2S) predictive time scale, encompassing lead times ranging from 2 weeks to a season, is at the frontier of forecasting science. Forecasts on this time scale provide opportunities for enhanced application-focused capabilities to complement existing weather and climate services and products. There is, however, a “knowledge–value” gap, where a lack of evidence and awareness of the potential socioeconomic benefits of S2S forecasts limits their wider uptake. To address this gap, here we present the first global community effort at summarizing relevant applications of S2S forecasts to guide further decision-making and support the continued development of S2S forecasts and related services. Focusing on 12 sectoral case studies spanning public health, agriculture, water resource management, renewable energy and utilities, and emergency management and response, we draw on recent advancements to explore their application and utility. These case studies mark a significant step forward in moving from potential to actual S2S forecasting applications. We show that by placing user needs at the forefront of S2S forecast development—demonstrating both skill and utility across sectors—this dialogue can be used to help promote and accelerate the awareness, value, and cogeneration of S2S forecasts. We also highlight that while S2S forecasts are increasingly gaining interest among users, incorporating probabilistic S2S forecasts into existing decision-making operations is not trivial. Nevertheless, S2S forecasting represents a significant opportunity to generate useful, usable, and actionable forecast applications for and with users that will increasingly unlock the potential of this forecasting time scale.

Full access
Douglas J. Parker
,
Alan M. Blyth
,
Steven J. Woolnough
,
Andrew J. Dougill
,
Caroline L. Bain
,
Estelle de Coning
,
Mariane Diop-Kane
,
Andre Kamga Foamouhoue
,
Benjamin Lamptey
,
Ousmane Ndiaye
,
Paolo Ruti
,
Elijah A. Adefisan
,
Leonard K. Amekudzi
,
Philip Antwi-Agyei
,
Cathryn E. Birch
,
Carlo Cafaro
,
Hamish Carr
,
Benard Chanzu
,
Samantha J. Clarke
,
Helen Coskeran
,
Sylvester K. Danuor
,
Felipe M. de Andrade
,
Kone Diakaria
,
Cheikh Dione
,
Cheikh Abdoulahat Diop
,
Jennifer K. Fletcher
,
Amadou T. Gaye
,
James L. Groves
,
Masilin Gudoshava
,
Andrew J. Hartley
,
Linda C. Hirons
,
Ishiyaku Ibrahim
,
Tamora D. James
,
Kamoru A. Lawal
,
John H. Marsham
,
J. N. Mutemi
,
Emmanuel Chilekwu Okogbue
,
Eniola Olaniyan
,
J. B. Omotosho
,
Joseph Portuphy
,
Alexander J. Roberts
,
Juliane Schwendike
,
Zewdu T. Segele
,
Thorwald H. M. Stein
,
Andrea L. Taylor
,
Christopher M. Taylor
,
Tanya A. Warnaars
,
Stuart Webster
,
Beth J. Woodhams
, and
Lorraine Youds

Abstract

Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics, and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The Global Challenges Research Fund (GCRF) African Science for Weather Information and Forecasting Techniques (SWIFT) project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement, and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps. Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training, modeling and operational prediction, and communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather forecasting “Testbeds”—the first of their kind in Africa—which have been used to bring new evaluation tools, research insights, user perspectives, and communications pathways into a semioperational forecasting environment.

Open access