Abstract
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 midlatitudes 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 are 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 Réunion Island, a tropical island in the southwest Indian Ocean. The multilayer 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 middle troposphere. Ground-based GHI observations at 12 sites on Réunion Island are used to quantify the impact of CWP DA. Over a total of 44 d during austral summertime, when averaged over all sites, CWP data assimilation has a positive impact on GHI forecasts for all lead times between 5 and 14 h. Root mean square error and mean absolute error are reduced by 4 % and 3 %, respectively.
Highlights
The ongoing global transition from conventional to renewable energy is accompanied by an expected increase in installed photovoltaic (PV) capacity (Schmela et al, 2018)
The root mean square error (RMSE) for water path (WP) at different altitudes during all cycling periods listed in Table 1 is calculated and shown in Fig. 3 in which the impact of the three-phased cloud water path (CWP) assimilation can be seen
The difference between the first guesses and the analyses is a measure of the impact of the respective phase on the analysis, and it can be seen that ice water path (IWP) has the greatest impact and liquid water path (LWP) has the lowest impact
Summary
The ongoing global transition from conventional to renewable energy is accompanied by an expected increase in installed photovoltaic (PV) capacity (Schmela et al, 2018). As an intermittent source of energy, PV requires solar irradiance forecasts in order to ensure grid stability and to enable an extensive feed-in of solar power into the electricity grids (Diagne et al, 2013). It is challenging to forecast global horizontal irradiance (GHI) in these regions. F. Kurzrock et al.: WRF-DART CWP DA in the tropics nion Island, which is located in the southwest Indian Ocean (SWIO) (Fig. 1). Kurzrock et al.: WRF-DART CWP DA in the tropics nion Island, which is located in the southwest Indian Ocean (SWIO) (Fig. 1) In this region, enhanced convection often causes large diurnal variability in solar irradiance (Badosa et al, 2013). Solar irradiance forecast errors are especially pronounced in the austral summer season (December–February) when convection is strong compared to winter (Badosa et al, 2015). The specific topography of Réunion Island, with an elevation of up to 3069 m, results in an interplay of both breeze-induced clouds and orographic clouds due to the predominant southeasterly trade winds, which are often extremely unpredictable
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