Improving the climate data management in the meteorological service of Angola: experience from SASSCAL
Rafael Posada
CORRESPONDING AUTHOR
Deutscher Wetterdienst, National Climate Monitoring, Frankfurter Str. 135, 63067 Offenbach, Germany
Domingos Nascimento
Instituto Nacional de Meteorologia e Geofisica (INAMET), Luanda, Angola
Francisco Osvaldo S. Neto
Instituto Nacional de Meteorologia e Geofisica (INAMET), Luanda, Angola
Jens Riede
Deutscher Wetterdienst, National Climate Monitoring, Frankfurter Str. 135, 63067 Offenbach, Germany
Frank Kaspar
Deutscher Wetterdienst, National Climate Monitoring, Frankfurter Str. 135, 63067 Offenbach, Germany
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F. Kaspar, J. Helmschrot, A. Mhanda, M. Butale, W. de Clercq, J. K. Kanyanga, F. O. S. Neto, S. Kruger, M. Castro Matsheka, G. Muche, T. Hillmann, K. Josenhans, R. Posada, J. Riede, M. Seely, C. Ribeiro, P. Kenabatho, R. Vogt, and N. Jürgens
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H. Gregow, P. Poli, H. M. Mäkelä, K. Jylhä, A. K. Kaiser-Weiss, A. Obregon, D. G. H. Tan, S. Kekki, and F. Kaspar
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F. Kaspar, B. Tinz, H. Mächel, and L. Gates
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Germany’s national meteorological service (Deutscher Wetterdienst, DWD) houses in Offenbach and Hamburg huge archives of historical handwritten journals of weather observations. They comprise not only observations from Germany, but also of the oceans and land stations in many parts of the world. DWD works on the digitisation and quality control of these archives. The paper presents the current status.
F. Kaspar, K. Zimmermann, and C. Polte-Rudolf
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Plant phenology is the study of periodically recurring patterns of growth and development of plants during the year. First plant phenological observations have been performed in Germany already in the 18th century. Today, Germany’s national meteorological service (Deutscher Wetterdienst, DWD) maintains a dense phenological observation network and a database with phenological observations.
F. Kaspar, G. Müller-Westermeier, E. Penda, H. Mächel, K. Zimmermann, A. Kaiser-Weiss, and T. Deutschländer
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K.-G. Karlsson, A. Riihelä, R. Müller, J. F. Meirink, J. Sedlar, M. Stengel, M. Lockhoff, J. Trentmann, F. Kaspar, R. Hollmann, and E. Wolters
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A. Riihelä, T. Manninen, V. Laine, K. Andersson, and F. Kaspar
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Cited articles
ACC: Final Declaration, Africa Climate Conference 2013, 15–18 October 2013, Arusha, Tansania, available at: http://www.wmo.int/amcomet/sites/default/files/field/doc/events/acc2013_final_declaration.pdf (last access: 17 February 2016), 2013.
Bauer, P., Thorpe, A., and Brunet, G.: The Quiet Revolution of Numerical Weather Prediction, Nature, 525, 47–55, 2015.
Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., Schamm, K., Schneider, U., and Ziese, M.: A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present, Earth Syst. Sci. Data, 5, 71–99, https://doi.org/10.5194/essd-5-71-2013, 2013.
Dabbish, L., Stuart, C., Tsay, J., and Herbsleb, J.: Social coding in GitHub: transparency and collaboration in an open software repository, in: Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work, ACM, 11–15 February 2012, Seattle, Washington, USA, 1277–1286, 2012.
GFCS: Annex to the Implementation Plan Of the Global Framework for Climate Services – Climate Services Information System Component, World Meteorological Organization, Geneva, Switzerland, 71 pp., 2014.
Hahn, C. J. and Warren, S. G.: Extended Edited Cloud Reports from Ships and Land Stations over Globe, 1952–1996 (2009 update), Carbon Dioxide Information Analysis Center Numerical Data Package NDP-026C, Carbon Dioxide Information Analysis Center Numerical, Tennessee, USA, 79 pp., 2009.
Hänsler, A.: Minutes – SASSCAL Thematic Workshop Climate, available at: http://www.sasscal.org/downloads/Minutes_SASSCAL-ClimateWorkshop_August2014_FINAL.pdf, (last access: 16 February 2016), 2014.
Kaspar, F., Helmschrot, J., Mhanda, A., Butale, M., de Clercq, W., Kanyanga, J. K., Neto, F. O. S., Kruger, S., Castro Matsheka, M., Muche, G., Hillmann, T., Josenhans, K., Posada, R., Riede, J., Seely, M., Ribeiro, C., Kenabatho, P., Vogt, R., and Jürgens, N.: The SASSCAL contribution to climate observation, climate data management and data rescue in Southern Africa, Adv. Sci. Res., 12, 171–177, https://doi.org/10.5194/asr-12-171-2015, 2015a.
Kaspar, F., Tinz, B., Mächel, H., and Gates, L.: Data rescue of national and international meteorological observations at Deutscher Wetterdienst, Adv. Sci. Res., 12, 57–61, https://doi.org/10.5194/asr-12-57-2015, 2015b.
Lawrimore, J. H., Menne, M. J., Gleason, B. E., Williams, C. N., Wuertz, D. B., Vose, R. S., and Rennie, J.: An overview of the Global Historical Climatology Network monthly mean temperature data set, version 3, J. Geophys. Res., 116, D19121, https://doi.org/10.1029/2011JD016187, 2011a.
Lawrimore J. H., Menne M. J., Gleason, B. E., Williams, C. N., Wuertz, D. B., Vose, R. S., and Rennie, J.: Global Historical Climatology Network – Monthly (GHCN-M), Version 3.2, NOAA National Centers for Environmental Information, https://doi.org/10.7289/V5X34VDR, 2011b.
Menne, M. J., Durre, I., Korzeniewski, B., McNeal, S., Thomas, K., Yin, X, Anthony, S., Ray, R., Vose, R. S., Gleason, B. E., and Houston,T. G.: Global Historical Climatology Network – Daily (GHCN-Daily), Version 3.20, NOAA National Climatic Data Center, Asheville, USA, https://doi.org/10.7289/V5D21VHZ, 2012a.
Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E., and Houston, T. G.: An Overview of the Global Historical Climatology Network-Daily Database, J. Atmos. Ocean. Tech., 29, 897–910, https://doi.org/10.1175/JTECH-D-11-00103.1, 2012b.
Niang, I., Ruppel, O. C., Abdrabo, M. A., Essel, A., Lennard, C., Padgham, J., and Urquhart, P.: Africa, in: Climate Change 2014: Impacts, Adaptation, and Vulnerability, Part B: Regional Aspects, Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change edited by: Barros, V. R., Field, C. B., Dokken, D. J., Mastrandrea, M. D., Mach, K. J., Bilir, T. E., Chatterjee, M., Ebi, K. L., Estrada, Y. O., Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N., MacCracken, S., Mastrandrea, P. R., and White, L. L., Cambridge University Press, Cambridge, UK and New York, NY, USA, 1199–1265, 2014.
Peterson, T. C. and Vose, R. S.: An overview of the Global Historical Climatology Network temperature database, B. Am. Meteorol. Soc., 78, 2837–2849, 1997a.
Peterson, T. C. and Vose, R. S.: Global Historical Climatology Network – Monthly (GHCN-M), Version 2, NOAA National Centers for Environmental Information, https://doi.org/10.7289/V5X34VDR, 1997b.
R Core Team: R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org/, last access: 20 October 2015.
Stuber, D., Mhanda, A., and Lefebvre, C.: Climate Data Management Systems: status of implementation in developing countries, Clim. Res., 47, 13–20, 2011.
Thorne, P. W., Willett, K. M., Allan, R. J., Bojinski, S., Christy, J. R., Fox, N., Gilbert, S., Jolliffe, I., Kennedy, J. J., Kent, E., Tank, A. K., Lawrimore, J., Parker, D. E., Rayner, N., Simmons, A., Song, L., Stott, P. A., and Trewin, B.: Guiding the Creation of A Comprehensive Surface Temperature Resource for Twenty-First-Century Climate Science, B. Am. Meteorol. Soc., 92, ES40–ES47, https://doi.org/10.1175/2011BAMS3124.1, 2011.
WMO: WMO-No. 100: Guide to Climatological Practices, World Meteorological Organization, Geneva, Switzerland, 117 pp., 2011.
WMO: WMO-No. 1131: Climate Data Management System Specifications. World Meteorological Organization, Geneva, Switzerland, 170 pp., 2014.
Short summary
To respond to the challenges of climate change, Angola, Botswana, Germany, Namibia, South Africa and Zambia have initiated the regional competence centre SASSCAL. As part of the initiative, Deutscher Wetterdienst (DWD) cooperates with the meteorological services of Angola, Botswana and Zambia to improve the management of climate data. First results of the cooperation between DWD and the Angolan Meteorological Services (INAMET) are presented in order to provide hints for comparable activities.
To respond to the challenges of climate change, Angola, Botswana, Germany, Namibia, South Africa...