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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-29
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-29
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model evaluation paper 23 Apr 2019

Model evaluation paper | 23 Apr 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

Evaluation of WRF-DART (ARW v.3.9.1.1 and DART manhattan release) multi-phase cloud water path assimilation for short-term solar irradiance forecasting in a tropical environment

Frederik Kurzrock1,2, Hannah Nguyen2, Jerome Sauer2, Fabrice Chane Ming3, Sylvain Cros2, William L. Smith Jr.4, Patrick Minnis4, Rabindra Palikonda4, Thomas A. Jones5, Caroline Lallemand2, Laurent Linguet6, and Gilles Lajoie1 Frederik Kurzrock et al.
  • 1Institut de Recherche pour le Développement (IRD), UMR 228 ESPACE-DEV, Université de La Réunion, Saint-Denis, LaRéunion, France
  • 2Reuniwatt SAS, Sainte Clotilde, La Réunion, France
  • 3Laboratoire de l’Atmosphère et des Cyclones, UMR8105, UMR CNRS - Météo-France - Université, Université de LaRéunion, La Réunion, France
  • 4Climate Science Branch (E302), NASA Langley Research Center, Hampton, Virginia, USA
  • 5Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma, USA
  • 6Institut de Recherche pour le Développement (IRD), UMR 228 ESPACE-DEV, Université de Guyane, Cayenne, Guyane, France

Abstract. Numerical weather prediction models tend to underestimate cloud presence and therefore often overestimate global horizontal irradiance (GHI). The assimilation of cloud water path (CWP) retrievals from geostationary satellites using an ensemble Kalman filter (EnKF) led to improved short-term GHI forecasts of the Weather Research and Forecasting (WRF) model in mid-latitudes in case studies. An evaluation of the method under tropical conditions and a quantification of this improvement for study periods of more than a few days is still missing. This paper focuses on the assimilation of CWP retrievals in three phases (ice, supercooled, and liquid) in a 6-hourly cycling procedure, and on the impact of this method on short-term forecasts of GHI for Reunion Island, a tropical island in the South-West Indian Ocean. The multi-layer gridded cloud properties of NASA Langley's Satellite ClOud and Radiation Property retrieval System (SatCORPS) are assimilated using the EnKF of the Data Assimilation Research Testbed (DART) manhattan release (revision 12002) and the advanced research WRF (ARW) v3.9.1.1. The ability of the method to improve cloud analyses and GHI forecasts is demonstrated and a comparison using independent radiosoundings shows a reduction of specific humidity bias in the WRF analyses, especially in the low and mid troposphere. Ground-based GHI observations at 12 sites on Reunion Island are used to quantify the impact of CWP DA. Over a total of 44 days during austral summer time, when averaged over all sites, CWP data assimilation has a positive impact on GHI forecasts for all lead times between 5 and 14 hours. Root Mean Squared Error and Mean Absolute Error are reduced by 4 % and 3 % respectively.

Frederik Kurzrock et al.
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Status: open (until 25 Jun 2019)
Status: open (until 25 Jun 2019)
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Frederik Kurzrock et al.
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