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S. E. Nicholson, B. Some, J. McCollum, E. Nelkin, D. Klotter, Y. Berte, B. M. Diallo, I. Gaye, G. Kpabeba, O. Ndiaye, J. N. Noukpozounkou, M. M. Tanu, A. Thiam, A. A. Toure, and A. K. Traore

Abstract

Gauge data from a West African network of 920 stations are used to assess Tropical Rainfall Measuring Mission (TRMM) satellite and blended rainfall products for 1998. In this study, mean fields, scattergrams, and latitudinal transects for the months of May–September and for the 5-month season are presented. Error statistics are also calculated. This study demonstrates that both the TRMM-adjusted Geostationary Observational Environmental Satellite precipitation index (AGPI) and TRMM-merged rainfall products show excellent agreement with gauge data over West Africa on monthly-to-seasonal timescales and 2.5° × 2.5° latitude/longitude space scales. The root-mean-square error of both is on the order of 0.6 mm day−1 at seasonal resolution and 1 mm day−1 at monthly resolution. The bias of the AGPI is only 0.2 mm day−1, whereas the TRMM-merged product shows no bias over West Africa. Performance at 1.0° × 1.0° latitude/longitude resolution is also excellent at the seasonal scale and good for the monthly scale. A comparison with standard rainfall products that predate TRMM shows that AGPI and the TRMM-merged product perform as well as, or better than, those products. The AGPI shows marked improvement when compared with the GPI, in reducing the bias and in the scatter of the estimates. The TRMM satellite-only products from the precipitation radar and the TRMM Microwave Imager do not perform well over West Africa. Both tend to overestimate gauge measurements.

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C. D. Hewitt, E. Allis, S. J. Mason, M. Muth, R. Pulwarty, J. Shumake-Guillemot, A. Bucher, M. Brunet, A. M. Fischer, A. M. Hama, R. K. Kolli, F. Lucio, O. Ndiaye, and B. Tapia

Abstract

There is growing awareness among governments, businesses, and the general public of risks arising from changes to our climate on time scales from months through to decades. Some climatic changes could be unprecedented in their harmful socioeconomic impacts, while others with adequate forewarning and planning could offer benefits. There is therefore a pressing need for decision-makers, including policy-makers, to have access to and to use high-quality, accessible, relevant, and credible climate information about the past, present, and future to help make better-informed decisions and policies. We refer to the provision and use of such information as climate services. Established programs of research and operational activities are improving observations and climate monitoring, our understanding of climate processes, climate variability and change, and predictions and projections of the future climate. Delivering climate information (including data and knowledge) in a way that is usable and useful for decision-makers has had less attention, and society has yet to optimally benefit from the available information. While weather services routinely help weather-sensitive decision-making, similar services for decisions on longer time scales are less well established. Many organizations are now actively developing climate services, and a growing number of decision-makers are keen to benefit from such services. This article describes progress made over the past decade developing, delivering, and using climate services, in particular from the worldwide effort galvanizing around the Global Framework for Climate Services under the coordination of UN agencies. The article highlights challenges in making further progress and proposes potential new directions to address such challenges.

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S. E. Nicholson, B. Some, J. McCollum, E. Nelkin, D. Klotter, Y. Berte, B. M. Diallo, I. Gaye, G. Kpabeba, O. Ndiaye, J. N. Noukpozounkou, M. M. Tanu, A. Thiam, A. A. Toure, and A. K. Traore

Abstract

Gauge data over North Africa are used to provide an assessment of satellite and blended rainfall products for 1988–94 and for 1998. A comparison is also made with the Global Precipitation Climatology Center (GPCC) gauge dataset. For the 1988–94 period, mean fields and latitudinal transects for the June–July–August season are presented, based on a 515-station gauge dataset, the GPCC gauge data, the Global Precipitation Climatology Project (GPCP) blended data, the infrared-based Geostationary Operational Environmental Satellite precipitation index (GPI), and the Special Sensor Microwave Imager (SSM/I) microwave estimates. Error calculations are also presented. The mean fields derived from the dense gauge network, the GPCC gauge-only analysis, and the GPCP are remarkably similar. The bias, with reference to the seasonal rainfall field based on the denser network, is about 3%–4% for either GPCC or GPCP. Agreement is relatively good, even in individual years. The rms error associated with these datasets is 12% for seasonal rainfall totals; thus, the error is largely random. In contrast, there are large systematic errors in the satellite-only analyses of GPI and SSM/I, with biases of 20% and 40% for the mean rain field as a whole and much larger biases in individual years. The rms errors are nearly 2 times as great. For 1998, a 920-station gauge dataset was available for a smaller section of West Africa. The comparison confirmed the superior performance of GPCP and demonstrated the lower level of performance of both GPCP and GPCC at the monthly scale as compared with the seasonal scale. Overall, the results of this study underscore the continued need for extensive gauge networks to describe adequately the large-scale precipitation field over Africa.

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