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Benjamin L. Lamptey

Abstract

Two monthly gridded precipitation datasets of the Global Precipitation Climatology Project (GPCP; the multisatellite product) and the Global Precipitation Climatology Centre (GPCC) Variability Analysis of Surface Climate Observations (VASClimO; rain gauge data) are compared for a 22-yr period, from January 1979 to December 2000, over land areas (i.e., latitudes 4°–20°N and longitudes 18°W–15°E). The two datasets are consistent with respect to the spatial distribution of the annual and seasonal rainfall climatology over the domain and along latitudinal bands. However, the satellite generally overestimates rainfall. The inability of the GPCC data to capture the bimodal rainfall pattern along the Guinea coast (i.e., south of latitude 8°N) is an artifact of the interpolation of the rain gauge data. For interannual variability, the gridded multisatellite and gridded gauge datasets agree on the sign of the anomaly 15 out of the 22 yr (68% of the time) for region 1 (between longitude 5° and 18°W and north of latitude 8°N) and 18 out of the 22 yr (82% of the time) for region 2 (between longitude 5°W and 15°E and north of latitude 8°N). The datasets agreed on the sign of the anomaly 14 out of the 22 yr (64% of the time) over the Guinea Coast. The magnitudes of the anomaly are very different in all years. Most of the years during which the two datasets did not agree on the sign of the anomaly were years with El Niño events. The ratio of the seasonal root-mean-square differences to the seasonal mean rainfall range between 0.24 and 2.60. The Kendall’s tau statistic indicated statistically significant trends in both datasets, separately.

Full access
Benjamin L. Lamptey
,
Rajul E. Pandya
,
Thomas T. Warner
,
Rebecca Boger
,
Roelof T. Bruintjes
,
Paul A. Kucera
,
Arlene Laing
,
Mitchell W. Moncrieff
,
Mohan K. Ramamurthy
,
Timothy C. Spangler
, and
Marianne Weingroff

Abstract

No Abstract available.

Full access
Graeme Stephens
,
Jan Polcher
,
Xubin Zeng
,
Peter van Oevelen
,
Germán Poveda
,
Michael Bosilovich
,
Myoung-Hwan Ahn
,
Gianpaolo Balsamo
,
Qingyun Duan
,
Gabriele Hegerl
,
Christian Jakob
,
Benjamin Lamptey
,
Ruby Leung
,
Maria Piles
,
Zhongbo Su
,
Paul Dirmeyer
,
Kirsten L. Findell
,
Anne Verhoef
,
Michael Ek
,
Tristan L’Ecuyer
,
Rémy Roca
,
Ali Nazemi
,
Francina Dominguez
,
Daniel Klocke
, and
Sandrine Bony

Abstract

The Global Energy and Water Cycle Exchanges (GEWEX) project was created more than 30 years ago within the framework of the World Climate Research Programme (WCRP). The aim of this initiative was to address major gaps in our understanding of Earth’s energy and water cycles given a lack of information about the basic fluxes and associated reservoirs of these cycles. GEWEX sought to acquire and set standards for climatological data on variables essential for quantifying water and energy fluxes and for closing budgets at the regional and global scales. In so doing, GEWEX activities led to a greatly improved understanding of processes and our ability to predict them. Such understanding was viewed then, as it remains today, essential for advancing weather and climate prediction from global to regional scales. GEWEX has also demonstrated over time the importance of a wider engagement of different communities and the necessity of international collaboration for making progress on understanding and on the monitoring of the changes in the energy and water cycles under ever increasing human pressures. This paper reflects on the first 30 years of evolution and progress that has occurred within GEWEX. This evolution is presented in terms of three main phases of activity. Progress toward the main goals of GEWEX is highlighted by calling out a few achievements from each phase. A vision of the path forward for the coming decade, including the goals of GEWEX for the future, are also described.

Open 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