Survey of data assimilation methods for convective-scale numerical weather prediction at operational centres

Nils Gustafsson1 Tijana Janjic ́2 Christoph Schraff3 Daniel Leuenberger4 Martin Weissmann5 Hendrik Reich5 Pierre Brousseau6 Thibaut Montmerle6 Eric Wattrelot6 Antonín Bucˇánek7 Máté Mile8 Rafiq Hamdi9 Magnus Lindskog1 Jan Barkmeijer10 Mats Dahlbom11 Bruce Macpherson12 Sue Ballard12 Gordon Inverarity12 Jacob Carley13 Curtis Alexander14 David Dowell14 Shun Liu13 Yasutaka Ikuta15 Tadashi Fujita15

Data assimilation (DA) methods for convective-scale numerical weather prediction at operational centres are surveyed. The operational methods include variational methods (3D-Var and 4D-Var), ensemble methods (LETKF) and hybrids between variational and ensemble methods (3DEnVar and 4DEnVar). At several operational centres, other assimilation algorithms, like latent heat nudging, are additionally applied to improve the model initial state, with emphasis on convective scales. It is demonstrated that the quality of forecasts based on initial data from convective-scale DA is significantly better than the quality of forecasts from simple downscaling of larger-scale initial data. However, the duration of positive impact depends on the weather situation, the size of the computational domain and the data that are assimilated. Furthermore it is shown that more advanced methods applied at convec- tive scales provide improvements over simpler methods. This motivates continued research and development in convective-scale DA.

Challenges in research and development for improvements of convective-scale DA are also reviewed and discussed. The difficulty of handling the wide range of spa- tial and temporal scales makes development of multi-scale assimilation methods and space–time covariance localization techniques important. Improved utilization of observations is also important. In order to extract more information from exist- ing observing systems of convective-scale phenomena (e.g. weather radar data and satellite image data), it is necessary to provide improved statistical descriptions of the observation errors associated with these observations.

KEYWORDS

convective-scale, data assimilation, numerical weather prediction

Bibliographic data

Nils Gustafsson1 Tijana Janjic ́2 Christoph Schraff3 Daniel Leuenberger4 Martin Weissmann5 Hendrik Reich5 Pierre Brousseau6 Thibaut Montmerle6 Eric Wattrelot6 Antonín Bucˇánek7 Máté Mile8 Rafiq Hamdi9 Magnus Lindskog1 Jan Barkmeijer10 Mats Dahlbom11 Bruce Macpherson12 Sue Ballard12 Gordon Inverarity12 Jacob Carley13 Curtis Alexander14 David Dowell14 Shun Liu13 Yasutaka Ikuta15 Tadashi Fujita15. Survey of data assimilation methods for convective-scale numerical weather prediction at operational centres
Journal: Quarterly Journal of the Royal Meteorological Society,, Volume: 144, Year: 2018, First page: 1218, Last page: 1256, doi: 10.1002/qj.3179