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ABSTRACT:In August and September 2007 media and aid organizations reported on a severe flood in large parts of sub-Saharan Africa caused by a sequence of extreme rain events. However, the reporting was partly controversial and much was speculated about how unusual the flood event was. Here, we analyse various observational data sets in order to assess and to compare the spatio-temporal characteristics and intensity of the flood and the associated rain events. The return times are estimated from daily precipitation time series at fine spatial resolution, and the potential causes are disclosed in a global and regional context.Satellite data reveal that the flood was not large scale but confined to the main river basins in sub-Saharan West Africa. Nonetheless, abundant rainfall prevailed over large parts of Western Africa extending north into the Western Sahara, particularly during the second half of August and the beginning of September 2007. In detail, various precipitation data sets differ considerably in terms of the monthly anomalies, demonstrating the difficulty to delineate meteorological extreme events even at a sub-continental scale and during the most recent past. Return times typically range between 1 and 50 years with high spatial heterogeneity but amount to 1200 years in the regional mean over the Upper Volta Basin. Among the potential causes we identify a La Niña event in the tropical Pacific, anomalous heating in the tropical Atlantic coming along with a greater depth of the monsoonal westerlies, and enhanced activity of African easterly waves, both evident in 2-6 day zonal wind and outgoing longwave radiation variance anomalies.

Described herein is the first version release of monthly temperature holdings of a new Global Land Surface Meteorological Databank. Organized under the auspices of the International Surface Temperature Initiative (ISTI), an international group of scientists have spent three years collating and merging data from numerous sources to create a merged holding. This release in its recommended form consists of over 30 000 individual station records, some of which extend over the past 300 years. This article describes the sources, the chosen merge methodology, and the resulting databank characteristics. Several variants of the databank have also been released that reflect the structural uncertainty in merging datasets. Variants differ in, for example, the order in which sources are considered and the degree of congruence required in station geolocation for consideration as a merged or unique record. Also described is a version control protocol that will be applied in the event of updates. Future updates are envisaged with the addition of new data sources, and with changes in processing, where public feedback is always welcomed. Major updates, when necessary, will always be accompanied by a new journal paper. This databank release forms the foundation for the construction of new global land surface air temperature analyses by the global research community and their assessment by the ISTI's benchmarking and assessment working group.

Abstract. Germany's national meteorological service (Deutscher Wetterdienst, DWD) is the responsible authority for monitoring climate change in Germany. To fulfill this task it operates the National Climate Data Centre ("Nationales KlimaDatenZentrum, NKDZ"). The historical and current instrumental measurements and visual observations of DWD's station network are archived, quality-controlled and used to provide aggregated products, as for example daily and monthly means or climate normals. Gridded data are generated and used to derive time series of national and regional averages. Phenological observations and radiosonde data are also part of the data base. In recent years, additional historical data have been digitized to expand the data base. The products are used for informing the public, e.g. as an element of the German climate atlas (http://www.deutscher-klimaatlas.de). One major recent activity was the provision of information for the new climatological reference interval 1981–2010 and an updated climatological analysis based on the newly digitized data.

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