The SASSCAL contribution to climate observation, climate data management and data rescue in Southern Africa

Abstract

Abstract.A major task of the newly established "Southern African Science Service Centre for Climate Change and Adaptive Land Management" (SASSCAL; www.sasscal.org) and its partners is to provide science-based environmental information and knowledge which includes the provision of consistent and reliable climate data for Southern Africa. Hence, SASSCAL, in close cooperation with the national weather authorities of Angola, Botswana, Germany and Zambia as well as partner institutions in Namibia and South Africa, supports the extension of the regional meteorological observation network and the improvement of the climate archives at national level. With the ongoing rehabilitation of existing weather stations and the new installation of fully automated weather stations (AWS), altogether 105 AWS currently provide a set of climate variables at 15, 30 and 60 min intervals respectively. These records are made available through the SASSCAL WeatherNet, an online platform providing near-real time data as well as various statistics and graphics, all in open access. This effort is complemented by the harmonization and improvement of climate data management concepts at the national weather authorities, capacity building activities and an extension of the data bases with historical climate data which are still available from different sources. These activities are performed through cooperation between regional and German institutions and will provide important information for climate service related activities.

Uncertainty of Rainfall Products: Impact on Modelling Household Nutrition from Rain-Fed Agriculture in Southern Africa

“…However, this problem is not necessarily caused by a lack of infrastructural development. The Angolan civil war from 1975 to 2002 [40], for instance, coincides temporally with a massive drop in the availability of meteorological station records compared to the late 1960s when the country already enjoyed good station coverage [41]. The current distribution of meteorological stations within the Cuvelai-Basin is heterogeneous.…”

Improving the climate data management in the meteorological service of Angola: experience from SASSCAL

“…As described in Kaspar et al (2015a), it has an intuitive Graphical User Interface with a key-entry module, quality control procedures and data import options which allow the import of data from various sources, including data from automatic weather stations. The software is currently based largely on the data base management system (DBMS) Microsoft ® Access © and Microsoft Visual Basic 6 ® , but modifications to the software, and a switch to open-source database systems are currently in preparation.…”

“…However, the lack of adequate data and observation systems in Africa seriously hinders the ability of scientists to assess the past and current state of the climate in the region (ACC, 2013). This also applies to parts of Southern Africa, where the knowledge on climate variability is limited because of the low availability of historic and present-day ground-based observations (Niang et al, 2014) To contribute to reduce this lack of data, the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) initiative supports, among others, activities focused on the installation and reparation of Automatic Weather Stations (AWS) within the SASSCAL region: Angola, Botswana, Namibia, South Africa and Zambia (Kaspar et al, 2015a). The current 1 AWS Network of SASSCAL comprises 132 AWSs.…”

Evaluation of gridding procedures for air temperature over Southern Africa

“…As part of the SASSCAL initiative (Southern African Science Service Center for Climate Change and Adaptive Land Management), 148 automatic weather stations (AWS) have been installed since 2013 to improve this situation (Kaspar et al, 2015;Posada et al, 2016). Most of them have been installed in Angola, Botswana, Namibia and Zambia and few of them in South Africa, and cover an area of approximately 3.4 million km 2 .…”

“…Here, we have used observational data from the SASSCAL AWS Network (Kaspar et al, 2015) and evaluated the quality of several temperature interpolation methods for Southern Africa to fill some of the identified data gaps. For evaluation purposes a dataset of monthly mean minimum and maximum temperatures with a resolution of 0.22 • was produced covering the period between September 2014 and August 2016.…”