The study tests and further develops a previously presented method for adjusting initial clouds in the HARMONIE mesoscale numerical weather prediction (NWP) model. The method uses satellite-observed cloud properties from the Nowcasting and very short range forecasting Satellite Application Facility (NWCSAF) together with ground-based synoptic stations (SYNOP) observations, adjusting the humidity profile of the model based on the available cloud information with the overall aim to improve the forecast, in particular as regards clouds and solar radiation. A reference setup of the HARMONIE model is used as a baseline against which the cloud initialization experiments are compared. All HARMONIE experiments are run for July 2016, with a model run starting at 06Z each day. The HARMONIE outputs are compared with cloud fraction and solar radiation observations from groundbased stations, while satellite cloud observations are also used for inspecting the behaviour of the forecasts. The performance of other generally used verification parameters is also studied. The results as regards clouds are encouraging. Symmetrical extremal dependence index (SEDI) skill scores show improvement in initial cloud conditions in 84% and 74% of the cases, when evaluated for cloud-free (0-1 octas) and cloudy conditions (7-8 octas), respectively. The improvement lasts 2-4 hr into the forecast. Other parameters, however, show somewhat degraded skill as compared with the reference model run, while for solar radiation, the cloud initialization scheme exhibits somewhat ambiguous results. The distribution of solar radiation values is improved for relatively sunny conditions, while at the other end of the distribution, the cloud initialization scheme produces too many cases with relatively strongly attenuated radiation.

Abstract. Weather forecasts from ensemble prediction systems (EPS) are improved by statistical models trained on past EPS forecasts and their atmospheric observations. Recently these corrections have moved from being univariate to multivariate. The focus has been on (quasi-)horizontal atmospheric variables. This paper extends the correction methods to EPS forecasts of vertical profiles in two steps. First univariate distributional regression methods correct the probability distributions separately at each vertical level. In the second step copula coupling re-installs the dependence among neighboring levels by using the rank order structure of the EPS forecasts. The method is applied to EPS data from the European Centre for Medium-Range Weather Forecasts (ECMWF) at model levels interpolated to four locations in Germany, from which radiosondes are released to measure profiles of temperature and other variables four times a day. A winter case study and a summer case study, respectively, exemplify that univariate postprocessing fails to preserve stable layers, which are crucial for many atmospheric processes. Quantile resampling and a resampling that preserves the relative distance between individual EPS members improve the calibration of the raw forecasts of the temperature profiles as shown by rank histograms. They also improve the multivariate metrics of energy score and variogram score and retain the stable layers. Improvements take place over all times of the day and all seasons. They are largest within the atmospheric boundary layer and for shorter lead times.

Accurate irradiance forecasts are needed for the growing solar energy industry also in Northern Europe. We have compared irradiance forecasts from an operational numerical weather prediction (NWP) model, a satellite‐based model, and persistence models. We aim to determine whether operational NWP models are suitable for forecasting irradiance at the high latitudes, and how their accuracy compares to the satellite‐based model. We have included all members and the ensemble average of the MetCoOp ensemble prediction system (MEPS), the MetCoOp‐Nowcasting (MNWC) system, the satellite‐based Solis‐Heliosat model, and two persistence models. The comparison is made as a point comparison against in situ irradiance observations in Finland and Sweden, for intra‐day forecasts with hourly and 15‐min output and the full forecast of MEPS with hourly output. In addition, we show two energy market case studies. We find the operational NWP models to be very suitable for irradiance forecasting in the area, up to the full horizon of the forecasts. Solis‐Heliosat errors grow with lead time, while the NWP model errors are largest in the beginning, settling to smaller values after the first hours. Solis‐Heliosat has more accuracy for the first 2–3 h of the forecast, after which NWP models produce better forecasts. However, during morning periods Solis‐Heliosat is found to have limited accuracy, while conversely, MNWC performs better in the morning than in the afternoon. The energy market case study highlights the same results: NWP models do well with forecasting irradiance in Fennoscandia, but the optimal selection of forecast model depends on the required forecast horizon and time.

<p>With the increase of solar power use, the need for solar irradiance forecasts is also increasing. Solar power is a naturally fluctuating energy source, which makes solar irradiance forecasts necessary for e.g. grid integration and management. Both the use of solar energy and the need for forecasts are present also in the Nordic countries, where the sub-Arctic latitude brings its own challenges.</p><p>Various methods exist for forecasting solar irradiance. Numerical Weather Prediction (NWP) models have been found superior for forecasting for the following days, while satellite-based models are found suitable for the first few hours of the forecast. The satellite-based model Solis-Heliosat has been found to perform well also in the high latitudes. The current operational NWP models in Finland, however, have not been yet extensively validated for this purpose.</p><p>To determine the suitability of the operational NWP models for forecasting solar irradiance in the Nordic countries, we have comparatively validated the MetCoOp Ensemble Model (MEPS), and the MetCoOp Nowcasting Model (MNWC) against in situ irradiance measurements at several stations in Finland and Sweden. We have also included the Solis-Heliosat model in the study, to improve our understanding on the differences and the relative accuracy between the NWP and satellite-based models. As a benchmark, two persistence models are included. The comparison is made for one summer, including all model runs and all MEPS ensemble members, with both hourly and 15 minute output depending on the model.</p><p>The results show all models to somewhat under predict irradiance. MEPS shows very good performance in the full length of the forecast, while Solis-Heliosat is better in the first 2-3 hours of the forecast. Solis-Heliosat has some difficulty with the forecasts starting in the morning, whereas MNWC slightly struggles in the afternoon.</p><p>Overall we find the NWP models very suitable for forecasting solar irradiance in Finland and Sweden, particularly with the full forecast horizon of MEPS, and the 15-minute time step of MNWC. Nevertheless, Solis-Heliosat brings further value to the beginning of the forecast.</p><p>Kallio‐Myers, V., Riihelä, A., Schoenach, D., Gregow, E., Carlund, T., & Lindfors, A. V. (2022). Comparison of irradiance forecasts from operational NWP model and satellite‐based estimates over Fennoscandia. <em>Meteorological Applications</em>, <em>29</em>(2), e2051.</p><p> </p>