Assessment report for global and direct irradiance forecasts

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1 MACC-II Deliverable D_123.1 Assessment report for global and direct irradiance forecasts Date: 12/2013 Lead Beneficiary: DLR (#11) Nature: R Dissemination level: PP Grant agreement n

2 Work-package 123 (RAD, Operational satellite products) Deliverable D_123.1 Title Assessment report for global and direct irradiance forecasts Nature R Dissemination PP Lead Beneficiary DLR (#11) Date 12/2013 Status Final version Authors M. Schroedter-Homscheidt (DLR), Niels Killius (DLR), Gerhard Gesell (DLR) Approved by M. Schroedter-Homscheidt Contact This document has been produced in the context of the MACC-II project (Monitoring Atmospheric Composition and Climate - Interim Implementation). The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7 THEME [SPA ]) under grant agreement n All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability. For the avoidance of all doubts, the European Commission has no liability in respect of this document, which is merely representing the authors view. 2 / 41

3 Executive Summary / Abstract Solar surface irradiance forecasting is of major importance for the management of the solar energy capacities providing larger shares of our electricity supply due to the energy system transition process. Especially, applications from the grid management sector require intraday and day-ahead irradiance forecasts in hourly resolution. Photovoltaics and nonconcentrating solar thermal technologies require global irradiance forecasts, while all concentrating technologies both from the photovoltaic and the thermal sector require direct normal irradiance (DNI) forecasting. Nowadays numerical weather prediction schemes provide global irradiances - also named global horizontal irradiances (GHI) in solar energy applications -, but mostly no DNI forecasts. The European Centre for Medium-Range Weather Forecasts (ECMWF) has recently changed its output variable selection in order to include direct irradiances. Additionally, the MACC near-real time services provide daily analysis and forecasts of various parameters based e.g. on new aerosol properties. The operational ECMWF/IFS forecast system will profit on the medium term from the MACC aerosol forecasts. Therefore, within the MACC-II project specific experiment runs were performed allowing the assessment of the performance gain of potential future capabilities making use of new Copernicus based aerosol forecasts and/or the provision of hourly forecasts instead of three-hourly forecasts. A focus is laid on direct normal irradiance forecasts being needed by concentrating solar technologies and poorly evaluated so far. It was found that the inclusion of the new aerosol climatology in October 2003 improved both the GHI and DNI forecasts remarkably, while the change towards a new radiation scheme in 2007 had only minor and partly unfavourable impacts on the performance indicators. For GHI, larger RMSE values are found for broken/overcast conditions than for scattered cloud fields. For DNI, the findings are opposite with larger RMSE values for scattered clouds compared to overcast/broken cloud situations. The introduction of direct irradiances as an output parameter in the operational IFS version has not resulted in a general performance improvement compared to the widely used Skartveith and Olseth (1998) global to direct irradiance conversion scheme. Cloudy situations and especially thin ice cloud cases are forecasted much better, but large biases are introduced in clear sky cases. If applying the GEMS aerosol scheme, a major improvement especially in DNI biases is found for most stations. This is especially caused by cloud free cases being dominated by aerosol effects. 3 / 41

4 Table of Contents Preface Introduction Datasets ECMWF IFS GHI ECMWF IFS GHI2DNI ECMWF IFS DIR2DNI MACC-II fw53 GHI/DIR Ground-based observations Satellite-based cloud type information Methodology Research questions Evaluation parameters Results Evaluation of the ECMWF IFS GHI and GHI2DNI for several years Evaluation of ECMWF IFS DIR2DNI vs. the IFS GHI2DNI for the year Evaluation of ECMWF IFS GHI and DIR for 2012, 3hourly vs. explicit aerosols and hourly resolution Conclusions Acknowledgements / 41

5 Preface It has to be noted that broadband surface solar irradiance forecasts are not a part of the MACC-II service portfolio at the moment, while the UV irradiance forecast is part of the MACC-II services. This task and deliverable D123.1 is a research activity aiming at assessing the operational ECMWF s forecast capability in order to clarify the usefulness of such a product for the solar energy sector. It is taking into account the existing operational IFS version and experimental runs made in MACC-II on the basis of new aerosol data or with a higher temporally resolved output scheme (hourly instead of three-hourly). This will provide input for a future discussion of a possible extension of the Copernicus service - to be performed only later in the Copernicus operational phase. This discussion has to be done mainly internally at ECMWF. In parallel to the MACC-II UV irradiance forecast service, other irradiance s parameter forecasts as for global and direct irradiances could be included in Copernicus - but it could also be seen as part of the standard meteorological parameters being not covered by the Copernicus data policy. It was originally planned to assess the operational IFS forecast only - again, in order to define work plan items for a future project phase based on accuracies found and/or gaps/deficiencies identified. Nevertheless, the operational IFS forecast system will profit on the medium term from the MACC aerosol forecasts. Solar users will therefore use MACC results indirectly - independent about any discussion of including global and direct irradiance forecasts in the MACC portfolio under the Copernicus data policy. Therefore, within the MACC-II duration, the possibility was discussed with ECMWF and the AER team to include MACC and MACC-II results and further specific experiment runs in this assessment. This is scientifically very interesting and can provide a good feedback loop to AER. ECMWF therefore started additional runs and implemented additional output parameters for RAD - an activity not foreseen originally. This extension of the DoW turned out to provide difficulties in keeping the original schedule within RAD therefore this deliverable report is delayed with respect to the DoW. On the other hand, these later started AER runs cannot be seen as any delays within AER with respect to the DoW, as they have been introduced as additional work packages during the project s duration. 5 / 41

6 1. Introduction Solar surface irradiance forecasting is of major importance for the management of the solar energy capacities providing larger shares of our electricity supply due to the energy system transition process. Especially, applications from the grid management sector require intraday and day-ahead irradiance forecasts in hourly resolution. Photovoltaics and nonconcentrating solar thermal technologies require global irradiance forecasts, while all concentrating technologies both from the photovoltaic and the thermal sector require direct normal irradiance (DNI) forecasting. Nowadays numerical weather prediction schemes provide global irradiances - also named global horizontal irradiances (GHI) in solar energy applications -, but mostly no DNI forecasts. The European Centre for Medium-Range Weather Forecasts (ECMWF) has recently changed its output variable selection in order to include direct irradiances. Additionally, the MACC and MACC II (Modelling Atmospheric Composition and Climate, projects are establishing currently the core global and regional atmospheric environmental services delivered as a component of Europe s GMES (Global Monitoring for Environment and Security, named Copernicus recently) initiative. The MACC near-real time services provide daily analysis and forecasts of various parameters based e.g. on new aerosol properties. The operational ECMWF/IFS forecast system will profit on the medium term from the MACC aerosol forecasts. Therefore, within the MACC-II project specific experiment runs were performed allowing the assessment of the performance gain of potential future capabilities making use of new Copernicus based aerosol forecasts and/or the provision of hourly forecasts instead of three-hourly forecasts. Specific focus of this work is laid on the assessment of DNI forecasts. This parameter is of special interest for concentrating solar power and is not well evaluated so far, while global irradiance forecasts have been evaluated more thoroughly. Perez et al. (2013) assessed several global irradiance forecasts based on ECMWF, GFS, AEMet-HIRLAM, Skiron/GFS and WRF/GFS model runs and additional post-processing modules. Generally, the ECMWF-based forecast was performing very well or even best at most locations in Germany, Austria, Spain, and the ECMWF was performing better than the GFS-driven WRF model in all locations in Europe, the US and Canada. Mathiesen and Kleissl (2011) are showing that for the US ECMWF is the most accurate forecast in cloudy conditions, while GFS has the best clear sky accuracy. Having this finding in mind, the assessment of ECMWF s new aerosol capabilities is of special interest. There is a variety of other validation studies for global irradiance forecasts, but they typically deal either with the GFS model (Perez et al., 2010), Canada s GEM (Pelland et al., 2011), regional models like WRF (Lara-Fanego et al., 2012) or RAMS (Ronzio et al., 2013) or the Australian Limited Area Prediction System (LAPS, Gregory et al., 2012). There are only a few studies dealing with the accuracy assessment of direct irradiance forecasts derived from global numerical weather prediction models: Wittmann et al. (2008) show case studies of ECMWF day ahead forecast use for solar thermal power plant operations. For July 2003 they find relative RMSE values of 19% for global and 42% for direct irradiances at a power plant s location in Southern Spain. Breitkreuz et al. (2009) evaluate 6 / 41

7 the coupling of aerosol modeling with the WRF model resulting in an improvement of the day ahead clear sky forecast while the cloudy cases are less accurate than the ECMWF forecast. Lara-Fanego et al. (2012) evaluate a post-processing for WRF-model based GHI forecasts coupled to MODIS satellite retrievals for aerosols and ozone for Southern Spain. They report on relative RMSE values for the first, second and third day with only a slight increase from 61 to 62 and 63% (no night time values, hourly values). Marquez and Coimbra (2011) report on DNI forecasts made by the help of artificial neural networks as a postprocessing for numerical weather predictions provided by the US National Weather Service s (NWS) forecasting database. They find relative RMSE values between 37 and 40% for different models and for the day ahead, while the same day has relative RMSE values between 28 and 35% (no night time values, hourly values). Troccoli and Morcrette (2012) evaluate all three irradiance components of the ECMWF model for Australian stations, but provide results only on monthly averages. Kraas et al. (2013) evaluate the economic value of DNI day ahead forecasts based on a commercial MOS system for the Spanish electricity market conditions and provide relative RMSE values between 56 and 77 % for different years at a specific power plant site in Southern Spain. They report especially on the increasing relative mean bias error as a function of DNI variability over the day. Several authors worked on the assessment of forecast accuracy as a function of cloudiness, but most studies are restricted to the differentiation of cloud and cloud-free conditions (e.g. Lara-Fanego et al., 2012), the dependence on cloud coverage with systematic overestimations of about 100 W/m² in cloudy conditions (Lorenz, 2009) or parameters like cloud index or clear sky index (Mathiesen and Kleisl, 2011). Besides from these approaches, Ronzio et al. (2013) are the first to investigate forecast accuracy as a function of cloud types like cumuliform or stratiform clouds, height level of clouds, thin ice vs. other clouds and overlapping clouds as provided by the Satellite Application Facility on support to Nowcasting and Very Short-Range Forecasting (SAFNWC). A summary of forecasts, ground-based and satellite-based datasets used is given in section 2. Section 3 discusses the open research questions and the methodology applied, while section 4 provides results for several evaluation studies. 2. Datasets Several ECMWF based forecasts are under evaluation in this study. This includes (a) the operational Integrated Forecast System (IFS) with its different versions depending on the year and the forecast cycle used; (b) post-processing approaches to generate direct normal irradiances from the operational IFS; and (c) experimental runs generated in the MACC-II project with updated aerosols and hourly temporal resolution. 7 / 41

8 Fig. 2.1 describes the temporal availability of the different forecasts together with the availability of BSRN (Baseline Surface Radiation Network) and the DLR-PSA ground stations. 1 Fig. 2.1 Data availability of ground stations (BSRN, DLR-PSA) and model experiments 2.1 ECMWF IFS GHI The operational ECMWF Integrated Forecast System (IFS) provides ECMWF s standard forecast including GHI forecasts in a 3-hourly resolution ( IFS GHI ). The parameter SSRD (solar surface radiation) is the 3-hourly irradiation sum of the previous 3 hours. Several radiation schemes have been used during the different years (ECMWF, 2013): Since 2 nd May 1989 (cycle 32) the radiation was modelled based on Fouquart and Bonnel (1980) as described in Morcrette (1991 and 2002). Since 5 th June 2007 (cycle 32r2) a new radiation scheme RRTM-SW (McRad, Morcrette et al., 2008a and 2008b) is applied on the T399 grid (0.45 ) and interpolated to a domain-averaged radiation in the T799 grid box 1 Other experiments of the MACC project cannot be used as e.g. the MACC reanalysis (GEMS aerosol scheme, fbov experiment code) or the MACC NRT run (GEMS aerosol scheme, fnyp experiment code) both due to a missing radiation output. At the time of this report, there has been no MACC-GLOMAP aerosol code being included in any experiment run together with an AOD generation module, yet. 8 / 41

9 (ECMWF,2009). It is based on the McICA (Monte Carlo Independent Column Approximation) scheme. Finally, since 18 th May 2011 (cycle Cy37r2) direct irradiance has been included in the output parameters. The operational IFS provides the following spatial resolution: 0.5 spatial grid before Feb 2006; an increased T799 (0.25 ) spatial resolution since Feb 2006 (cycle 30r1), and finally a T1279 (0.15 ) spatial resolution since 26 Jan 2010 (cycle 36r1). Aerosols in the IFS are based on a monthly mean climatology following Tegen et al. (1997). An hourly temporal forecast resolution is needed following the requirements of the dayahead and intraday electricity markets being relevant for the grid integration of solar power. The temporal interpolation from the original 3-hourly irradiation sum towards an hourly global irradiance forecast is performed following Breitkreuz (2008): Due to the strong nonlinear behavior of irradiances during the day, the explicit interpolation of irradiances is not recommended. Instead of irradiances, the clear sky index being defined as the ratio of the global irradiance divided by the clear sky global irradiance is used. Applying a clear sky model (Hoyer-Klick et al., 2010) the clear sky index is calculated for the irradiation sum provided every third hour in the IFS forecast. The clear sky index is then interpolated linearly for each minute and averaged to hourly values. Finally, by using the clear sky model again, the global irradiance is calculated in hourly averaged resolution. The clear sky model inputs are based on the MACC-II reanalysis for aerosols, water vapour and ozone for 2012 cases shown here, and on MATCH aerosols (Schroedter-Homscheidt et al., ) for the multi-annual assessment in section 4.1 as the MACC-II reanalysis is only available from 2006 onwards. 2.2 ECMWF IFS GHI2DNI Even before any direct or direct normal irradiance is derived, an interpolation from 3-hourly GHI sums to hourly GHI values is performed as described in section 2.1. An empirical conversion is used to derive direct irradiance values following the approach of Skartveith and Olseth (1998). These are finally transferred to the hourly averaged DNI values - named IFS GHI2DNI furtheron - by using the cosine of the sun zenith angle. Being based on the forecast as described in section 2.1, the underlying aerosols are also the standard IFS monthly mean climatology following Tegen et al. (1997). Also, the spatial resolution is the same as described in section ECMWF IFS DIR2DNI Starting with 18 th May 2011 (cycle Cy37r2) the ECMWF IFS was extended to provide clearsky and total-sky direct fluxes at the surface as additional parameters this dataset is named IFS DIR2DNI in the following sections. The radiation scheme has not been changed compared to the description in section 2.1, but the output variable list has been extended. The 3-hourly direct irradiation is also interpolated to hourly averaged irradiances (see section 2.1 and 2.2) and also for this dataset, the aerosols in the IFS are based on the monthly mean climatology following Tegen et al. (1997). 2.4 MACC-II fw53 GHI/DIR The fw53 experiment provides forecasts for a period from 1 st December 2011 onwards until 31th December These forecasts are starting every day at 00 UTC with a forecast length of 48 hours. This experiment provides hourly forecast resolution instead of the 9 / 41

10 standard 3-hourly temporal resolution; includes both global and direct irradiance parameters; and includes the GEMS aerosol scheme (Morcrette et al., 2009) as implemented in the MACC reanalysis instead of the standard IFS aerosol climatology. The fw53 experiment takes its meteorology and aerosols from the MACC reanalysis (fbov experiment) and provides irradiance forecasts at a TL255 L60 (0.7 ) resolution which is slightly less spatially resolved than the radiation scheme being applied in the IFS on the T399 (0.45 ) grid. 2.5 Ground-based observations In this study, the focus is laid on the verification of DNI forecasts therefore, only groundbased observations providing the direct and the global component are of interest. Additionally, direct irradiance measurements are highly sensitive to daily cleaning of the sensors and a rigorous data quality control. Therefore, the study focuses on measurements from the Baseline Surface Radiation Network (BSRN, Ohmura et al., 1998) being a part of the World Climate Research Programme (WCRP). BSRN stations provide ground-based datasets of GHI, DNI and the diffuse hemispherical irradiance (DHI) component in a 1-min temporal resolution. The quality control procedures are described in a report of Long and Dutton (2012). Only years with a data coverage over all seasons have been taken into account. Additionally, DLR provides 1-min measurements made with a CH1 Kipp & Zonen pyrheliometer at the Plataforma Solar de Almeria site in Southern Spain. This data has been quality controlled following the recommendations of the MESOR project (Beyer et al., 2008) which is an extension to the BSRN quality control standards with special focus on the solar energy sector. In this study we use the stations given in Tab. 1. All measurements have been averaged to hourly time series. Table. 2.1 Data availability of BSRN and DLR/PSA ground stations Name ID Code Lat. ( ) Lon ( ) Elev (m) Period DLR/PSA 1 PSA Cabauw (BSRN) 2 CAB Camborne (BSRN) 3 CAM Carpentras (BSRN) 4 CAR Cener (BSRN) 5 CEN Izana (BSRN) 6 IZA Lerwick (BSRN) 7 LER Lindenberg (BSRN) 8 LIN Palaiseau (BSRN) 9 PAL Payerne (BSRN) 10 PAY Sede Boquer (BSRN) 11 SBO Tamanrasset (BSRN) 12 TAM Toravere (BSRN) 13 TOR Satellite-based cloud type information The APOLLO (AVHRR Processing scheme Over clouds, Land and Ocean; Kriebel, Saunders, and Gesell, 1989; Kriebel et al., 2003) algorithm was originally developed to exploit data from the AVHRR sensors aboard the polar orbiting series of NOAA satellites, in order to estimate the properties of clouds. It has been adapted to process images of the SEVIRI (Spinning Enhanced Visible and Infrared Imager) instrument aboard the series of Meteosat 10 / 41

11 Second Generation satellites (APOLLO/SEV). APOLLO/SEV provides quantities related to clouds for each pixel (3 km at nadir) and every 15 min. Among these quantities, are a mask with values being cloud-free or cloudy, cloud optical depth and the level of the cloud, low, medium, high, with additionally a thin cloud type class. Cloud types are derived according to the top temperature and the layer boundaries are set to 700 hpa and 400 hpa with the associated temperatures taken from standard atmospheres. The thin clouds layer exclusively contains thin pure ice phase clouds with no thick clouds underneath. In a further post-processing several hourly cloud information parameters are created: If all 4 MSG slots inside an hour from minutes 15, 30, 45 of the actual and 00 of the following hour are cloud free, the hourly cloud mask is set to cloud free, otherwise the mask is set as cloudy. The same is done if all slots have the type thin ice cloud then the hourly cloud type is set to thin ice cloud. All other cases are treated as water/mixed phase cloud types. Additionally to the single pixel results, the surrounding 49x49 pixel window are evaluated in order to understand the medium scale cloud situation and to discriminate between overcast/broken, scattered and isolated cloud fields. If the cloud fraction in the window is above 50%, a broken or overcast situation is assumed. If the window s cloud fraction is between 10 and 50%, a scattered cloud situation is specified. In case of a window cloud fraction below 10%, a further parameter is used: In case the number of cloud elements inside the window is above 5, the situation is still described as scattered, while otherwise, a situation with few, isolated clouds and being close to a cloud free case is assumed. 3. Methodology 3.1 Research questions The following research questions will be discussed below: a) Evaluation of the ECMWF IFS GHI and GHI2DNI for several years allowing the comparison of different radiation schemes applied in the operational IFS over the recent years. This evaluation is extended towards different cloud situations discriminating optically thin cirrus clouds from optically thick water/mixed phase clouds as well as overcast/broken and scattered cloud conditions. b) Evaluation of ECMWF IFS DIR vs. the IFS GHI2DNI for the year 2012 allowing the assessment of the new output parameter direct irradiance compared to the previously needed empirical GHI2DNI conversion scheme. c) Evaluation of ECMWF s fw53 DIR and GHI providing experiment for the year 2012 versus the standard ECMWF IFS DIR and GHI forecast. This allows the assessment of the GEMS aerosol scheme and the value of hourly forecast resolution. 3.2 Evaluation parameters Statistical parameters for the comparison of hourly values include biases, root mean square error (RMSE), and linear correlation coefficients following the definitions in Beyer et al. (2008) and Hoyer-Klick et al. (2010). Especially, RMSE is seen as the most important statistical metric for the application of electricity grid management issues. This is reflecting the fact that in this application area small errors are of less importance compared to large errors affecting the electricity grid s security. The skill score is therefore also based on the RMSD and defined as the ratio: 11 / 41

12 skill score = (RMSD ECMWF RMSD 2d_pers ) RMSD 2d_pers The persistence approach in this case is mostly a two-day persistence. This is a specific feature required by the day-ahead electricity market as realised today e.g. in Spain: Typically, any day-ahead forecast has to be provided to the market operator during the late morning hours. This restricts the persistence to the values obtained on the previous day as the best estimate for tomorrow without using any weather forecast. In order to generate results being comparable against other studies, we also include the standard one-day persistence in the results. This also reflects the expectation that other electricity markets will be organised with closure times allowing the usage of standard persistence as poor man s forecast. All parameters are available for each forecast hour up to 48 hours, but only daytime values are evaluated following the MESOR standard (Beyer et al., 2008). All results are derived at the location of ground-based observations using the nearest neighbouring ECMWF grid point. 4 Results 4.1 Evaluation of the ECMWF IFS GHI and GHI2DNI for several years First of all, a time series of basic statistics over the different years and IFS model versions is performed versus the two day persistence (Fig. 4.1 to 4.3 for GHI, 4.4 to 4.6 for DNI). Generally, the change in the radiation scheme in 2007 does not result in a major improvement of statistical parameters. For Tamanrasset a negative bias in GHI is even increased, while for other stations the positive GHI bias remains similar. For DNI, the bias of most stations is even increasing after There is no improvement visible in the RMSE at the GHI and other statistical parameters do also not indicate a major improvement in DNI based on the radiation code change in Only a slight improvement at many stations in the linear correlation coefficient of DNI might be seen. Fig. 4.1 supports the finding of several authors being reviewed in Mathiesen et al. (2013) and summarized in the statement that regardless of the model, global irradiance NWP forecasts are generally positively biased. Here, the same is found for all years later than 2005 and with exception of the station Tamanrasset. 12 / 41

13 Fig. 4.1 Day ahead hourly GHI forecast verification annual absolute and relative bias (line) based on daytime values only and together with the two-day persistence in dotted lines. For the DNI annual biases, the year 2003 is very eye-catching with low biases up to 250 W/m² for Sede Boquer, DLR/PSA, Tamanrasset, Carpentras, Payerne, Lindenberg, Toravere, and Camborne (ordered from largest to smaller values). Also, in the GHI verification, a strong underestimation with biases of up to -80 W/m² are found. A deeper insight in monthly resolved statistics shows very low DNI bias values for months before October 2003 for these stations (Fig. 4.7 for Sede Boquer). The visual interpretation of hourly time series 13 / 41

14 reveals that especially in clear sky days the maximum DNI value is underestimated systematically. Referring to ECMWF (2013), the new IFS model cycle 26r3 was introduced on 7 th October 2003 including a new aerosol climatology in the full model. Having in mind that Sede Boquer, DLR/PSA and Tamanrasset are the stations being most affected by aerosols, it is not surprising that this change occurs. Obviously, the change towards cycle 26r3 was positive for the IFS s verification results. For Tamanrasset, mostly clear sky cases are underestimated a result pointing into the direction of deficiencies in the aerosol climatology. Both, for GHI and DNI the station Izana shows large negative biases for all years. It has to be noted that Izana is a mountainous station, while the ECMWF forecast is valid as an average for a 0.15 x 0.15 grid box having a much smaller averaged elevation than the Izana observatory. Therefore, an underestimation can be expected for this station. Also for both, GHI and DNI at the station Lerwick low correlation coefficients and large relative RMSE values are found for all years. A visual interpretation reveals that cloudy days are often forecasted as typical clear sky days. Partly, those days show a reduced GHI, but still larger than the observations. Also, Camborne has large positive biases for 2004 to Also here, visual interpretation of time series reveals that cloudy cases with low and medium height clouds are often forecasted as cloud free. The station Payerne besides Lerwick and Camborne shows a rather low correlation coefficient. Visual interpretation shows that often clear sky days are forecasted as cloudy, while cloudy days are forecasted as clear sky. While other stations show discrepancies in situations with quickly varying irradiance values, Payerne is a station with many complete forecast failures of the overall situation in a day. In case of solar technologies with thermal or battery storages, this error characteristic is very important as the overall daily sum of irradiation is also badly forecasted in such conditions. 14 / 41

15 Fig. 4.2 Day ahead hourly GHI forecast verification annual absolute and relative RMSE (line) based on daytime values only and together with the two-day persistence in dotted lines. Fig. 4.3 Day ahead hourly GHI forecast verification annual correlation coefficients (line) based on daytime values only and together with the two-day persistence in dotted lines. 15 / 41

16 Fig. 4.4 Day ahead hourly DNI forecast verification annual correlation coefficients (line) based on daytime values only and together with the two-day persistence in dotted lines. 16 / 41

17 Fig. 4.5 Day ahead hourly DNI forecast verification annual absolute and relative bias (line) based on daytime values only and together with the two-day persistence in dotted lines. 17 / 41

18 Fig. 4.6 Day ahead hourly DNI forecast verification annual absolute and relative RMSE (line) based on daytime values only and together with the two-day persistence in dotted lines. 18 / 41

19 Fig. 4.7 Day ahead hourly DNI forecast verification monthly resolved absolute bias for the stations Sede Boquer for 2003, 2004, and 2005 (top, middle, bottom) based on daytime values only and together with the two-day persistence in dotted lines. Overall, Fig. 4.1 to 4.6 are showing two-day persistence forecasts as reference as discussed above and reflecting nowadays electricity market requirements. Generally, it can be noted, that the bias of the two-day persistence approach is much smaller compared to the ECMWF forecast bias, but both RMSE and correlation coefficients are much worse than the ECMWF forecast. So, overall, ECMWF has a positive forecast skill for all stations and both GHI and DNI if generated as a conversion from GHI to DNI. 19 / 41

20 Fig. 4.8 Day ahead (lines) and day 0 (dotted) hourly GHI forecast verification annual absolute and relative bias - based on daytime values only. 20 / 41

21 Fig. 4.9 Day ahead (lines) and day 0 (dotted) hourly GHI forecast verification annual absolute and relative RMSE - based on daytime values only. Besides nowadays electricity market requirements for day ahead forecasting, the day zero forecast verification is also of interest. This is motivated both by other electricity market designs which allow the use of day zero forecasts and the requirements of power plant operators and electricity grid operators for day zero forecasts. Therefore, the verification of day ahead versus the actual day ( day zero ) is shown in Fig. 4.8 to 4.13 lines indicate the results for the day ahead verification results, while dotted lines give the results for the day zero verification. 21 / 41

22 Biases in GHI seem to be rather similar, with smaller differences in both directions for some years and stations. The GHI s RMSE of day zero is systematically below the RMSE of the day ahead as expected. For Sede Boquer and Tamanrasset the relative RMSE of day zero is nearly the same than the day ahead or smaller by few percent only. For other stations differences of up to 10% are reached. For DNI biases the same is found - small variations in both directions for some years and stations, but no clear trend. The DNI s RMSE of day zero is systematically below the day ahead s RMSE, but the differences are smaller than for the GHI case. Differences in relative RMSEs up to 5% are found for most years and stations. Fig Day ahead (lines) and day 0 (dotted) hourly GHI forecast verification annual correlation coefficients - based on daytime values only. 22 / 41

23 Fig Day ahead (lines) and day 0 (dotted) hourly DNI forecast verification annual absolute and relative bias - based on daytime values only. 23 / 41

24 Fig Day ahead (lines) and day 0 (dotted) hourly DNI forecast verification annual absolute and relative RMSE - based on daytime values only. 24 / 41

25 Fig Day ahead (lines) and day 0 (dotted) hourly DNI forecast verification annual correlation coefficients - based on daytime values only. Based on APOLLO cloud types a discrimination between cloud free, thin ice clouds and other cloud cases can be made. Fig give the result for the year 2010 the year with the most recent radiation scheme being in place and the most ground stations available. As we have not seen any dedicated differences between the years 2008 to 2012 in the above analysis, we focus on a single year from now on. The result is presented as a target plot following ideas as introduced by Jolliff et al. (2009) and currently being widely adapted in the air quality community. It sets bias and centred root mean square errors (CRMSE) in relation to each other. The CRMSE is the standard-deviation of the differences between the reference and the modelled AOD dataset. A movement towards the centre of this plot can be interpreted as an overall improvement in RMSE. In case the forecasted amplitude as described by the standard deviation σ mod of all modelled values is less than the observed amplitude at the station (as described by the standard deviation σ obs of all observed values) the sign on the horizontal axis is chosen as negative. Cloud free situations tend to have small, but negative biases in the GHI with exception of the station Izana, which is probably due to the mountainous location of the ground station compared to the area averaged forecast value. Also, Tamanrasset shows a larger negative bias for cloud free situations. Several stations show low biases around zero (Toravere, Payerne, Cabauw, Carpentras, Cener) also for the thin ice cloud cases, while other stations as DLR/PSA, Sede Boquer, and Tamanrasset show large positive biases for thin ice clouds. For all stations, the biases are large for the water and mixed phase cloud conditions. This is partly in line with the findings of Ronzio et al., 2013 who found the worst GHI forecast performance for mid and high level thick clouds for three Italian stations and all forecasts being assessed (IFS/ECMWF, GFS/NCEP, LAMI, RAMS) in Doing the same analysis for 2011, we find this behaviour for all stations, but Toravere and Sede Boquer, where the 25 / 41

26 RMSE for thin ice clouds is slightly larger than for other clouds. For most stations, the forcasted amplitude is below the observed amplitude of values, resulting in symbols being located on the left hand side of the target plot. Thin ice clouds for the DLR/PSA station and water/mixed-phase clouds for Toravere and Sede Boquer are the only cases where the forecasted amplitude is higher than the observed amplitude. For DNI, cloud free situations are characterized by low biases, but still large RMSE values being represented by the fact that no symbol is close to the centre of the target plot 8Fig. 4.15). Izana is an exemption as discussed previously. Besides Payerne and Izana, all other stations show the largest RMSE values for thin ice clouds. Biases are also highest for thin ice clouds at the stations Carpentras, Cener, DLR/PSA, Sede Boquer, and Tamanrasset. For Cabauw, the biases of both cloud classes are similar, while for Payerne and Toravere the water/mixed-phase class is biased more. Forecasted values do generally not include circumsolar irradiances as they treat the sun as a point source. Compared to the BSRN network this would result in an underestimation of DNI but obviously, the forecast tends to overestimate the DNI in thin ice cloud conditions. Therefore, it is more likely, that such thin ice clouds are not forecasted and therefore, DNI is forecasted as high clear sky cases. The visual interpretation of time series supports this, as frequently cases with typical clear sky DNI patterns in the forecast occur, while the observed DNI is varying around 30 to 70 % values of the typical clear sky DNI. There is no clear finding about the modelled amplitude versus the observed amplitude for the different cloud classes. It can be noted that for most stations (besides Payerne and Izana) the two cloud classes are not on the same half of the plot indicating differences in the modelled amplitude of the two cloud classes, but the results are heterogeneous for all stations. Some thin ice cloud symbols can be found in the right half of the target plot, others on the left half. The same applies for water/mixed phase clouds. 26 / 41

27 Fig Day ahead hourly GHI forecast verification separated into classes cloud free (diamond), thin ice clouds (+) and other water/mixed phase clouds (*). Fig Day ahead hourly DNI forecast verification separated into classes cloud free (diamond), thin ice clouds (+) and other water/mixed phase clouds (*). Based on APOLLO cloud masks, also a distinction between overcast/broken clouds and scattered clouds is made. Fig and 4.17 show all those cases with a water/mixed phase cloud as the ground station s pixel and broken/overcast (crosses) or scattered (stars) cloud conditions in the surroundings. For GHI, several stations (DLR/PSA, Carpentras, Sede Boquer, Tamanrasset, and Toravere) show larger RMSE for broken/overcast conditions than for scattered cloud situations this is not obvious and against many expectations of having scattered cloud fields (as e.g. cumulus clouds) as the reason for large RMSE values at stations. Cabauw and Cener have similar RMSE values for both classes, while for Izana, and Payerne the RMSE of the scattered cloud situations is larger. For all stations with exception of Payerne, the bias is smaller for scattered cloud conditions. For DNI, the situation is different scattered clouds result in larger RMSE values for all stations besides Tamanrasset and Sede Boquer. For Payerne and Izana broken/overcast clouds show smaller biases and for Sede Boquer there is no difference. But for all other stations, the scattered cloud situations have smaller biases pointing to the fact that the larger RMSE is driven by a larger scatter between forecasts and observations as expected for scattered cloud fields. 27 / 41

28 Fig Day ahead hourly GHI forecast verification separated into classes overcast/broken (+) and scattered clouds (*). Fig Day ahead hourly DNI forecast verification separated into classes overcast/broken (+) and scattered clouds (*). 28 / 41

29 For several stations a different behavior in the forecasted amplitude of both GHI and DNI values versus the observed amplitude is found for the two cloud classes resulting in one station s mark in the target plot on the one side and the other mark on the other side of the target plot. For GHI, the stations DLR_PSA, Carpentras, and Tamanrasset have larger forecasted amplitudes than observed, while for Cabauw the forecasted amplitudes are smaller than observed. For DNI, the stations DLR/PSA, Carpentras, Cener, Sede Boquer, Tamanrasset, and Toravere show the same effect broken/overcast conditions have larger forecasted amplitudes than observed, while scattered clouds have smaller forecasted amplitudes than observed. Actually, finding that scattered clouds have smaller forecasted amplitudes is not surprising, but the fact that broken/overcast clouds have larger forecasted amplitudes than observed is not obvious. 4.2 Evaluation of ECMWF IFS DIR2DNI vs. the IFS GHI2DNI for the year 2012 The empirical transformation from GHI to DNI based on Skartveith and Olseth (1998) has been discussed frequently as being derived from the station Bergen only, being perhaps only valid for the northern regions etc. Therefore, the announcement of having direct irradiances as explicit model output parameter was very much welcomed by the solar energy community needing DNI especially. Fig Day ahead hourly DNI forecast verification for two day persistence (+) and different approaches GHI2DNI (*) and DIR2DNI (diamond). 29 / 41

30 Fig provides the comparison of both day ahead approaches vs. the two day persistence for the seven stations available in A clear shift of the bias is seen. The GHI2DNI approach results in mainly positive biases (with exception of Toravere), but the use of the DIR2DNI also results in biases, only with the opposite sign. For some stations the bias is reduced (Cener, DLR/PSA, Tamanrasset), but for others it is even worse in absolute values (Cabauw, Carpentras, Izana, Toravere). The RMSE is reduced for Tamanrasset, but increased for all other stations. The same effect is found for the day zero the RMSE values are generally smaller on day zero, but the bias shifting remains the same. A further analysis reveals that cloudy cases are forecasted much better by the DIR2DNI approach, but large biases are introduced in clear sky cases (Fig 4.19 to 4.21). For all stations the biases are negative for the DIR2DNI approach and being larger in their absolute value for the clear sky cases. For thin ice cloud cases a strong reduction in biases and RMSE is found for all stations besides Cabauw and Toravere. For water/mixed phase clouds also a reduction in biases and RMSE is found for all stations besides Toravere - for Toravere the RMSE is also reduced, but the bias turns from a small positive to a slightly larger negative bias. Fig Day ahead hourly DNI forecast verification in cloud free cases for GHI2DNI (+) and DIR2DNI (*) approaches. 30 / 41

31 Fig Day ahead hourly DNI forecast verification in water/mixed phase cloud cases for GHI2DNI (+) and DIR2DNI (*) approaches. Fig Day ahead hourly DNI forecast verification in thin ice cloud cases for GHI2DNI (+) and DIR2DNI (*) approaches. 31 / 41

32 4.3 Evaluation of ECMWF IFS GHI and DIR for 2012, 3hourly vs. explicit aerosols and hourly resolution In the previous chapter the standard ECMWF IFS model runs have been assessed. Now we look into an experimental run ( fw53 ) using an explicit aerosol modelling scheme (GEMS) instead of an aerosol climatology and providing hourly output. For GHI, there are only small changes between the two runs with exception of Izana showing a large increase in RMSE (Fig. 4.22). The other stations also show a slight increase in RMSE for the hourly run. Biases are slightly reduced for Carpentras and Cener, but slightly increased for DLR/PSA, Cabauw, Izana, Sede Boquer, and Tamanrasset. For the day zero all findings are the same just with slightly reduced RMSE values. The assessment of cloud free cases shows a remarkable increase in both biases and RMSE for all stations in the fw53 run (Fig 4.23). It is not decidable whether this is an effect of the aerosol modelling (as being in clear sky) or whether a cloudy situation with lower GHI values is forecasted too often. For water/mixed phase clouds the biases and/or RMSE are larger for the fw53 run (Fig. 4.24), while for thin ice clouds the biases generally are reduced (besides for Izana) and the RMSE is slightly increased in most stations (Fig. 4.25). Fig Day ahead hourly GHI forecast verification for IFS GHI (+) and fw53 (*) approaches. 32 / 41

33 Fig Day ahead hourly GHI forecast verification for cloud free cases of IFS GHI (+) and fw53 (*) approaches. Fig Day ahead hourly GHI forecast verification for water/mixed phase cases of IFS GHI (+) and fw53 (*) approaches. 33 / 41

34 Fig Day ahead hourly GHI forecast verification for thin ice cloud cases of IFS GHI (+) and fw53 (*) approaches. For all stations but Izana and Tamanrasset, day ahead forecasted DNI biases are reduced remarkably towards very small values (Fig. 4.26), while RMSEs are slightly better or slightly worse. For Tamanrasset a positive bias is introduced, being very similar to the GHI2DNI version. For Izana both bias and RMSE increase remarkably. For the day zero all findings are the same again, just with slightly reduced RMSE values. A strong bias reduction is found in the cloud free cases of fw53 (Fig. 4.27) for all stations besides Izana. The introduction of an explicit aerosol modelling seems to be very successful. On the other hand the RMSE for all cases is not reduced (Fig. 4.26) as one could have expected from a higher temporal resolution. For both cloud classes (thin ice clouds and water/mixed phase clouds) the RMSE and bias values are increasing (besides the Toravere station, Fig 4.28 and 4.29). This probably reflects the effect that a higher temporally resolved cloud information does not reduce the scatter as hoped for but very often just enhances the scatter in the forecast. This has been previously discussed in studies on mesoscale numerical weather predictions (e.g. Girodo, 2006). 34 / 41

35 Fig Day ahead hourly DNI forecast verification for DIR2DNI (+) and fw53 (*) approaches. Fig Day ahead hourly DNI forecast verification for cloud free cases of DIR2DNI (+) and fw53 (*) approaches. 35 / 41

36 Fig Day ahead hourly DNI forecast verification for water/mixed phase cases of DIR2DNI (+) and fw53 (*) approaches. Fig Day ahead hourly DNI forecast verification for thin ice cloud cases of DIR2DNI (+) and fw53 (*) approaches. 36 / 41

37 5 Conclusions This study assesses the performance of solar surface irradiance forecasts as provided by the ECWMF s IFS operational system and additional experimental runs with enhanced aerosol representation and temporal resolution. A focus is laid on direct normal irradiance forecasts being needed by concentrating solar technologies and poorly evaluated so far. Nevertheless, global irradiance forecasts are also evaluated having non-concentrating photovoltaic technologies in mind. Satellite-based cloud type information allow the assessment of performances in different cloud conditions in a direct manner - without needing any inverse assumption about which irradiance patterns are reflecting which cloud conditions. It was found that the inclusion of the new aerosol climatology in October 2003 improved both the GHI and DNI forecasts remarkably, while the change towards a new radiation scheme in 2007 had only minor and partly unfavourable impacts on the performance indicators. Following Morcrette et al. (2008) the change towards the McRad scheme was motivated mainly by improvements in the radiative heating rate vertical profiles and therefore the cloud/radiation interaction. Impacts of McRad have been assessed by monitoring the behaviour of meteorological parameters as geopotential, temperature, humidity, horizontal wind and vertical velocity in different heights, longwave cloud forcing as seen from satellites, or sea surface temperatures; but not against ground based surface irradiance measurements as in this study. In the study, we evaluate both two- and one-day persistence forecasts as reference. Twoday persistence forecasts are partly used as reference due to timelines in nowadays electricity grid markets. Nevertheless, results are given for both in order to ensure the comparability to other studies. Cloud free situations show small, but negative biases in GHI, while positive biases are larger for water and mixed phase clouds compared to thin ice clouds. For DNI, cloud free situations show low biases, but still large RMSE values. Largest bias and RMSE values are found for thin ice clouds which are most likely not being forecasted in all cases. For GHI, larger RMSE values are found for broken/overcast conditions than for scattered cloud fields. For DNI, the findings are opposite with larger RMSE values for scattered clouds compared to overcast/broken cloud situations. The introduction of direct irradiances as an output parameter in the operational IFS version has not resulted in a general performance improvement compared to the widely used Skartveith and Olseth (1998) global to direct irradiance conversion scheme. Cloudy situations and especially thin ice cloud cases are forecasted much better, but large biases are introduced in clear sky cases. If applying the GEMS aerosol scheme in an experimental IFS run in hourly temporal resolution, a major improvement especially in DNI biases is found for most stations. DNI biases are strongly reduced especially in cloud free cases being dominated by aerosol 37 / 41

38 effects. On the other hand, the RMSE for all cases is not reduced and for both cloud classes RMSE and biases are increasing. For GHI, there are only small overall changes, but towards larger RMSE values. It is assumed that the improvements in aerosols are only visible in the DNI and cloud free cases, while the hourly resolution results in a generally larger scatter in the all sky conditions similar effects have been discussed by Girodo (2006) for the use of both temporally and spatially better resolved meso-scale modeling compared to ECMWF forecasts. Overall, the coupling of the operational ECMWF IFS with an aerosol scheme as the GEMS scheme used nowadays in the MACC reanalysis or any other further enhanced aerosol scheme is highly recommended. Only with this addition, the use of direct irradiance forecasts as the new model output parameter can be recommended as performing better than nowaday s state of the art global to direct irradiance transformation. 6 Acknowledgements We thank the numerous operators of the BSRN network stations and the World Radiation Monitoring Center (WRMC) for providing their measurements. Additionally, we thank our colleague S. Wilbert for providing PSA measurements. 38 / 41

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