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Tellus A: Dynamic Meteorology and Oceanography Volume 61, 2009 - Issue 2

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Original Articles

Doppler radar radial winds in HIRLAM. Part II: optimizing the super-observation processing

K. SalonenFinnish Meteorological Institute, P.O. Box 503, FI-00101, Helsinki, FinlandCorrespondence[email protected]

H. JärvinenFinnish Meteorological Institute, P.O. Box 503, FI-00101, Helsinki, Finland

G. HaaseSwedish Meteorological and Hydrological Institute, Norrköping, Sweden

S. NiemeläFinnish Meteorological Institute, P.O. Box 503, FI-00101, Helsinki, Finland

R. EresmaaFinnish Meteorological Institute, P.O. Box 503, FI-00101, Helsinki, Finland

Pages 288-295 | Received 05 Nov 2007, Accepted 05 Nov 2007, Published online: 15 Dec 2016

Cite this article
https://doi.org/10.1111/j.1600-0870.2008.00381.x

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Jian Yin, Wei Han, Zhiqiu Gao & Haiqin Chen. (2021) Assimilation of Doppler radar radial wind data in the GRAPES mesoscale model with observation error covariances tuning. Quarterly Journal of the Royal Meteorological Society 147:737, pages 2087-2102.
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Jianing Feng, Yihong Duan, Qilin Wan, Hao Hu & Zhaoxia Pu. (2020) Improved Prediction of Landfalling Tropical Cyclone in China Based on Assimilation of Radar Radial Winds with New Super-Observation Processing. Weather and Forecasting 35:6, pages 2523-2539.
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J. A. Waller, E. Bauernschubert, S. L. Dance, N. K. Nichols, R. Potthast & D. Simonin. (2019) Observation Error Statistics for Doppler Radar Radial Wind Superobservations Assimilated into the DWD COSMO-KENDA System. Monthly Weather Review 147:9, pages 3351-3364.
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Karoliina Hämäläinen, Elena Saltikoff, Otto Hyvärinen, Ville Vakkari & Sami Niemelä. (2019) Assessment of Probabilistic Wind Forecasts at 100 m Above Ground Level Using Doppler Lidar and Weather Radar Wind Profiles. Monthly Weather Review 148:3, pages 1321-1334.
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J. A. Waller, D. Simonin, S. L. Dance, N. K. Nichols & S. P. Ballard. (2016) Diagnosing Observation Error Correlations for Doppler Radar Radial Winds in the Met Office UKV Model Using Observation-Minus-Background and Observation-Minus-Analysis Statistics. Monthly Weather Review 144:10, pages 3533-3551.
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Qin Xu, Li Wei, Kang Nai, Shun Liu, Robert M. Rabin & Qingyun Zhao. (2015) A Radar Wind Analysis System for Nowcast Applications. Advances in Meteorology 2015, pages 1-13.
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Heiner Lange & George C. Craig. (2014) The Impact of Data Assimilation Length Scales on Analysis and Prediction of Convective Storms. Monthly Weather Review 142:10, pages 3781-3808.
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D. Simonin, S. P. Ballard & Z. Li. (2014) Doppler radar radial wind assimilation using an hourly cycling 3D-Var with a 1.5 km resolution version of the Met Office Unified Model for nowcasting. Quarterly Journal of the Royal Meteorological Society 140:684, pages 2298-2314.
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S. de Haan. (2013) Assimilation of GNSS ZTD and radar radial velocity for the benefit of very-short-range regional weather forecasts. Quarterly Journal of the Royal Meteorological Society 139:677, pages 2097-2107.
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Martin Ridal, Magnus Lindskog, Nils Gustafsson & Günther Haase. (2011) Optimized advection of radar reflectivities. Atmospheric Research 100:2-3, pages 213-225.
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Kirsti Salonen, Günther Haase, Reima Eresmaa, Harri Hohti & Heikki Järvinen. (2011) Towards the operational use of Doppler radar radial winds in HIRLAM. Atmospheric Research 100:2-3, pages 190-200.
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S. J. Rennie, S. L. Dance, A. J. Illingworth, S. P. Ballard & D. Simonin. (2011) 3D-Var Assimilation of Insect-Derived Doppler Radar Radial Winds in Convective Cases Using a High-Resolution Model. Monthly Weather Review 139:4, pages 1148-1163.
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A. Rossa, G. Haase, C. Keil, P. Alberoni, S. Ballard, J. Bech, U. Germann, M. Pfeifer & K. Salonen. (2010) Propagation of uncertainty from observing systems into NWP: COST-731 Working Group 1. Atmospheric Science Letters 11:2, pages 145-152.
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Doppler radar radial winds in HIRLAM. Part II: optimizing the super-observation processing

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Doppler radar radial winds in HIRLAM. Part II: optimizing the super-observation processing

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