TY - JOUR
T1 - A new approach for assimilation of 2D radar precipitation in a high-resolution NWP model
AU - Korsholm, Ulrik Smith
AU - Petersen, Claus
AU - Sass, Bent Hansen
AU - Nielsen, Niels Woetmann
AU - Jensen, David Getreuer
AU - Olsen, Bjarke Tobias
AU - Gill, Rasphal
AU - Vedel, Henrik
PY - 2015
Y1 - 2015
N2 - A new approach for assimilation of 2D precipitation in numerical weather prediction models is presented and tested in a case with convective, heavy precipitation. In the scheme a nudging term is added to the horizontal velocity divergence tendency equation. In case of underproduction of precipitation, the strength of the nudging is proportional to the offset between observed and modelled precipitation, leading to increased moisture convergence. If the model over-predicts precipitation, the low level moisture source is reduced, and in-cloud moisture is nudged towards environmental values. The method was implemented in the Danish Meteorological Institute numerical weather prediction (DMI NWP) nowcasting system, running with hourly cycles, performing a surface analysis and 3D variational analysis for upper air assimilation at each cycle restart, followed by nudging assimilation of precipitation and then a free forecast. The precipitation fields are based on a 2D composite CAPPI (constant altitude plan position indicator) field made from observations with the DMI weather radars, and have a 10 min time resolution. The results obtained in this study indicate that the new method implies fast adjustment of the dynamical state of the model to facilitate precipitation release when the model precipitation intensity is too low. Removal of precipitation is shown to be of importance and the position of the model precipitation cells becomes skilful even at the smallest scales (∼3 km). Bias is reduced for low and extreme precipitation rates. In this meteorological case, the usage of the nudging procedure has been shown to improve the prediction of heavy precipitation substantially.
AB - A new approach for assimilation of 2D precipitation in numerical weather prediction models is presented and tested in a case with convective, heavy precipitation. In the scheme a nudging term is added to the horizontal velocity divergence tendency equation. In case of underproduction of precipitation, the strength of the nudging is proportional to the offset between observed and modelled precipitation, leading to increased moisture convergence. If the model over-predicts precipitation, the low level moisture source is reduced, and in-cloud moisture is nudged towards environmental values. The method was implemented in the Danish Meteorological Institute numerical weather prediction (DMI NWP) nowcasting system, running with hourly cycles, performing a surface analysis and 3D variational analysis for upper air assimilation at each cycle restart, followed by nudging assimilation of precipitation and then a free forecast. The precipitation fields are based on a 2D composite CAPPI (constant altitude plan position indicator) field made from observations with the DMI weather radars, and have a 10 min time resolution. The results obtained in this study indicate that the new method implies fast adjustment of the dynamical state of the model to facilitate precipitation release when the model precipitation intensity is too low. Removal of precipitation is shown to be of importance and the position of the model precipitation cells becomes skilful even at the smallest scales (∼3 km). Bias is reduced for low and extreme precipitation rates. In this meteorological case, the usage of the nudging procedure has been shown to improve the prediction of heavy precipitation substantially.
KW - NWP nowcasting
KW - Rapid update cycle
KW - Nudging
KW - Divergence
KW - Radar-derived precipitation
KW - NWP nowcasting
KW - Rapid update cycle
KW - Nudging
KW - Divergence
KW - Radar-derived precipitation
U2 - 10.1002/met.1466
DO - 10.1002/met.1466
M3 - Journal article
SN - 1350-4827
VL - 22
SP - 48
EP - 59
JO - Meteorological Applications
JF - Meteorological Applications
IS - 1
ER -