Chairpersons: Frank Kaspar, Deborah Niermann
The focus topic of this year's EMS meeting emphasizes the role of transdisciplinary consortia and collaborations - such as the German Hans Ertel Centre for Weather Research (HErZ). The development process of a regional reanalysis in Germany has relied strongly on such a cooperative approach with the site of this year's meeting - University of Bonn - together with the University of Cologne and Germany’s national meteorological service (DWD) contributing to this success in particular.
The development of a regional reanalysis based began approx. 12 years ago as a fundamental research activity within the Hans Ertel Centre for Weather Research (HErZ) at the meteorological institutes of the Universities of Bonn and Cologne. Based on the numerical weather prediction model COSMO of DWD (Deutscher Wetterdienst), regional reanalysis datasets have been developed with grid spacing of up to 2 km (Bollmeyer et al., 2015; Wahl et al., 2017). This activity was based on research funding provided by DWD and was conducted in close cooperation with DWD. Later, DWD included the reanalysis in its climate service portfolio and began working on its further development. The cooperation with European partners, esp. some national weather services, within the EU-FP7-project UERRA provided the opportunity to compare the quality of the COSMO-reanalysis with other products (Kaiser-Weiss et al., 2019). Today, COSMO reanalyses are an established product of the DWD and have been widely used in applications on European and national German levels. The COSMO reanalysis datasets are publicly available and provide spatio-temporal consistent data of atmospheric parameters covering both near-surface conditions and vertical profiles. A second generation of the COSMO reanalysis is currently in production and a reanalysis with DWD’s new modeling system ICON is being prepared. Product evaluation is carried out in various collaborative projects, e.g. with focus on meteorological risk estimates or energy applications (Kaspar et al., 2019).
The dataset is used to support our partner agency BSH (Federal Maritime and Hydrographic Agency) in their tasks related to the expansion of wind farms within the German Exclusive Economic Zone (EEZ), as we will discuss in further presentations. Given the high relevance of high-quality weather information in the field of energy meteorology, cooperation with the Institute of Energy Economics at the University of Cologne (EWI) was also intensified in the current phase of the HErZ. The spatial and temporal resolution also provides opportunities to assess details of extreme events in various parameters, as it is done, for example, in the ClimXtreme research network, a cooperative activity of 35 research institutions coordinated by the University of Bonn. Through such cooperation with universities, the reanalysis has also been used in a number of theses.
References:
How to cite: Kaspar, F. and Keller, J.: Development of Regional Reanalyses in Germany: 12 years of cross-community cooperation, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-683, https://doi.org/10.5194/ems2022-683, 2022.
Reanalyses are enjoying an ever-increasing number of users and interest groups, especially due to steadily increasing spatial and temporal resolutions. However, new applications also require a comprehensive quality assessment of the used data set, taking into account different time scales, parameters, and regions. Within the framework of the joint BMBF project ClimXtreme (https://www.climxtreme.net/), we evaluate the quality of DWD’s current reanalysis product COSMO-REA6 and its follow-up product R6G2 (COSMO-REA6 Generation 2) concerning the representation of extreme events like heat waves, windstorms and heavy precipitation.
Reanalyses enable a comprehensive assessment of extreme events and their relevant processes. Here we are aiming at an evaluation approach of extreme wind events and comparisons for mean near surface wind speed, analyzing sub-daily, daily and seasonal patterns, as well as regional differences. The comparisons (using station measurements and gridded observations as reference as well as known reanalyses such as ERA5 as benchmark) also integrate brand new data from the Copernicus European Regional Re-Analysis (CERRA). Both regional reanalyses, CERRA and R6G2 are available for the complete EURO-CORDEX domain, at an almost similar spatial resolution of 5.5 km for CERRA and about 6 km for R6G2. The evaluation here, concentrate on the German region and current events from the years 2018, like winter storm Friederike.
For evaluation the platform MAVIS (Meteorological Analysis and Visualization System), based on Freva (http://doi.org/10.5334/jors.253) is used. Freva is a scientific software framework supporting scientific cooperation on high performance computing environments, equipped with a standardized model database, a programming interface and a history of evaluations.
How to cite: Niermann, D., Spangehl, T., Borsche, M., Kaspar, F., and Schimanke, S.: Assessment of new DWD and Copernicus regional reanalysis products R6G2 and CERRA with focus on near surface wind speed , EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-435, https://doi.org/10.5194/ems2022-435, 2022.
The German energy transition demands the increasing usage of renewable energy resources. Following current plans of the German government, the proportion of renewable energy in total electricity needs shall rise to more than 80 percent until 2030 and reach 100 percent in 2035. One important contribution to reach these goals is the increased setting up of wind farms within the German Exclusive Economic Zone (EEZ). Here, the effective usage of the available space and the economic and environmental planning require knowledge on the meteorological and climatological conditions. A crucial factor is the spatial and temporal variability of the wind over the North Sea and Baltic Sea. Additional insight is gained by the representation of the atmospheric boundary layer.
Global and regional atmospheric reanalyses provide detailed information of the wind speed and wind direction at hub heights of modern wind turbines. In order to facilitate offshore wind farm tenders, Deutscher Wetterdienst (DWD, Germany’s national meteorological service) provides reanalysis data and quality assessments to Bundesamt für Seeschifffahrt und Hydrographie (BSH, Federal Maritime and Hydrographic Agency). Currently, the regional reanalysis COSMO-REA6, maintained by DWD, is used besides the global reanalysis ERA5, produced by the European Centre for Medium-Range Weather Forecasts (ECMWF).
At present, new reanalyses and derived products become available. One example is the Copernicus European Regional Re-Analysis (deterministic system, CERRA-DET and ensemble of data assimilations, CERRA-EDA). Moreover, a successor of COSMO-REA6, R6G2 (COSMO-REA6 Generation 2), is currently produced by DWD. Furthermore, a convection-resolving climate simulation for Germany with COSMO-CLM, as a regional downscaling of ERA5, was recently produced by DWD.
The quality of the reanalysis data for offshore wind energy application is assessed on the basis of a consistent evaluation approach. Different types of observations are used as reference. In-situ measurements of the wind speed and wind direction at heights between 30 m and 100 m are available from FINO (Research platforms in the North Sea and Baltic Sea, https://www.fino-offshore.de/en/index.html). Moreover, near surface wind speed and wind direction, retrieved from ASCAT scatterometers onboard METOP-A and METOP-B satellites, are used (satellite data provided by CMEMS, Copernicus Marine Environment Monitoring Service). Results are presented for the 100 m wind speed and wind direction at FINO1 and near surface wind fields over the North Sea. Uncertainties of the different products are addressed by carefully intercomparing the reanalyses.
How to cite: Spangehl, T., Borsche, M., Niermann, D., Kaspar, F., Schimanke, S., Brienen, S., Möller, T., and Brast, M.: Intercomparing the quality of recent reanalyses for offshore wind farm planning, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-331, https://doi.org/10.5194/ems2022-331, 2022.
Improving the representation of lower boundary layer winds and temperatures in weather forecasting is still a major task, despite the increase in the spatial resolution. As applications strongly rely on high-quality data from weather and climate models, systematic errors and biases in relevant areas, e.g., boundary layer wind speed or near-surface temperatures, degrade the quality of such applications. In this regard, new observing systems can provide information to enhance the model state representation through data assimilation. Smartphones are widely used and are already equipped with build-in sensors, e.g., for air pressure, thus providing a potentially valuable source of meteorological information. We further see wind power data obtained as wind turbine power output as potential implicit measurements for boundary layer wind speeds. Through the FAIR project, examplary data from smartphopnes is provided by the University Duisburg-Essen and for wind power data from the industry partners BayWa r.e. In this study, we aim to assimilate these observations into the operational NWP model ICON-LAM to assess the potential benefit with respect to NWP and future regional reanalyses. A new forward operator was developed for the LETKF scheme to assimilate wind power output. To investigate the benefit of assimilating wind power and air pressure data from smartphones tuning experiments have been performed. The sensitivity of various parameter settings, such as horizontal localization scale, and appropriate observation error estimation using the Desroziers metric is tested. The simulation results are evaluated and compared against independent observations for different synoptical situations and they indicate a potential for improvement.
How to cite: Kelbch, A., Valmassoi, A., and Keller, J.: Assessing the potential of assimilating wind turbine power output and smartphone data for future reanalysis, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-247, https://doi.org/10.5194/ems2022-247, 2022.
Irrigation, predominantly carried out in southern Europe, has a considerable impact on the state of the atmosphere, but is not yet included in numerical models used for producing reanalyses. A common approach to correct the soil moisture (and, thus, also lower boundary condition in the atmospheric model) is to alter the soil moisture field to fit 2m temperature observations in a data assimilation scheme. In this way, water is added to or removed from the soil in the form of assimilation increments. This raises the question whether this assimilation process also recognizes soil moisture changes from irrigation and adjusts the model state accordingly.
To answer this question, we analyze the effects in the Po valley in northern Italy – a region where irrigated fields are the predominant land use. Here we compare three years in the late irrigation period July and August with each other, one particular rainy year, one drought year with irrigation and one drought year when irrigation was prohibited by law.
For this purpose we conduct a spatial analysis of the soil moisture increments in the neighbourhood of assimilated stations with respect to irrigation and precipitation bias. The resulting findings are then interpreted in terms of their spatial relation to other stations and their values of irrigation and precipitation bias.
The results indicate that the assimilation process is able to compensate for the deviations caused by irrigation. However, the effictiveness of this process also depends on the spatio-temporal density of observations. Since the vast majority of observing sites are located in non-irrigated areas, considerable model deviations in soil moisture and corresponding atmospheric parameters are still expected to be present in irrigated areas.
How to cite: Rosell, C., Valmassoi, A., Keller, J., and Friederichs, P.: Irrigation nudging in COSMO-REA6, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-507, https://doi.org/10.5194/ems2022-507, 2022.
In this work, we aim to include a computationally inexpensive enhanced urban and land surface representation in a reanalyses framework. First, we update the land use representation used in the ICON-LAM numerical weather prediction by employing the 100m CORINE data set with three urban land use classes instead of the older 300m GLOBCOVER with only one urban category. Then, we include an energetic surface modification for complex urban fabric as an increase in the heat capacity and area sensible heat flux.
Further, we use the Copernicus Land Surface Temperature (LST) satellite product available at 5-km 1-hour resolution in the context of data assimilation to correct surface temperatures. Specifically, we investigate the sensitivity on parameter settings within the LETKF-KENDA data assimilation scheme, i.e., horizontal localization length, adaptive inflation, coarsening factor, thinning, and different observational errors.
The latter two are of particular importance since we deal with spatially dense data, whose errors are spatially correlated. Thus, we include the observation error correlation in the KENDA scheme and compare the results to the standard version.
The results show that the LST assimilation improves the land temperature biases drastically, e.g. down from over 7K to 2.5K for the Berlin area. At the same time, it also seems to cause a degradation in 2-meter temperature biases. However, this effect seems to be related to their model equivalent calculation (especially during daytime) rather than the observation impact itself. The analysis increments do not exhibit a similar behavior across various cities in the Central European area.
The urban correction improves the 2-meter temperature representation, especially in the morning hours. We do not find the combined changes in surface temperatures due to LST assimilation and urban correction to drastically alter the Urban Heat Island representation for the two case study cities (Berlin and Cologne).
How to cite: Valmassoi, A. and Keller, J. D.: Improving the urban surface representation in high-resolution reanalyses frameworks, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-426, https://doi.org/10.5194/ems2022-426, 2022.
Chairpersons: Frank Kaspar, Deborah Niermann
The Copernicus European regional reanalysis (https://climate.copernicus.eu/regional-reanalysis-europe) was produced as part of the Copernicus Climate Change Service (C3S). The presentation will introduce the service and its main objectives as well as it will give an overview on available data. Data quality will be demonstrated by comparison with ERA5 and other gridded datasets.
The Copernicus European Regional ReAnalysis (CERRA) is produced with a setup of the HARMONIE-ALADIN model system including a 3D-Var data assimilation scheme for upper air observations and an OI-scheme for surface observations. The model domain covers entire Europe at a horizontal resolution of 5.5 km. The system provides eight analyses per day – at 0 UTC, 3 UTC, 6 UTC, … and 21 UTC. Between the analyses, data are available with hourly resolution from the forecast model. More than fifty parameters are available on various level types including surface parameters and data up to 1 hPa. Data are available for the period September 1984 – June 2021 through Copernicus Climate Data Store (CDS).
In addition to CERRA, the service produced a reanalysis with an ensemble of data assimilation (EDA) system, called CERRA-EDA. CERRA-EDA consists of 10 members and is produced with a horizontal resolution of 11 km. Uncertainty information from the ensemble system is used as a flow depending part of the B-matrix for CERRA. Another product of the service is CERRA-Land. CERRA-Land provides daily precipitation analyses as well as parameters from the surface/soil model SURFEX, which is driven with CERRA data.
In the presentation, the production chain will be illustrated and the availability of data will be clarified. The focus will be on CERRA. The quality of the regional reanalysis will be demonstrated in comparison to the global reanalysis ERA5. For instance, investigations of the winter storm Gudrun (January 2005, southern Sweden) will be presented.
How to cite: Schimanke, S., Isaksson, L., Edvinsson, L., Ridal, M., Hopsch, S., Dahlgren, P., Bazile, E., Le Moigne, P., and Verrelle, A.: Copernicus European regional reanalysis, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-335, https://doi.org/10.5194/ems2022-335, 2022.
Within the UERRA project (2014-2017) a surface re-analysis at 5.5km resolution has been produced over Europe for the period 1961-2015 (UERRA D2.8 https://www.uerra.eu) with the so-called MESCAN-SURFEX system. During the Copernicus Climate Change Service C3S_322_lot1 contract (2018-2021), the period 2016-2019 has been produced with exactly the same system.
Since the data are available on the Climate Data Store, several impact studies or local comparisons have been published for different types of applications: precipitation studies (Bezak et al., 2020 and 2021), temperature studies (Chervenkov et al., 2021, Hofer and Horak, 2020) or for snow indicators (Morin et al., 2021). User feedback, depending of the variables and/or the study area, can be very positive or highlight some questions or some weaknesses of the product. In May 2020, a user shows some “curious” trends for the temperature of 3 European cities (Budapest, Riga and Warsaw). After several months of investigation, the problem was fixed and it was decided to re-run the surface analysis MESCAN and the off-line land surface model SURFEX for the period 1961-2019 to produce version 2 of this re-analysis, named UERRA-Land2.
After a brief description of the problem discovered in May 2020, the modification of the surface analysis will be explained and the impact on several variables such as temperature and snow depth will be presented. A comparison with ERA5-Land and the added value of the regional re-analysis UERRA-Land2 will be discussed.
The UERRA-Land2 dataset is now available on demand at Météo-France and hopefully soon on the Climate Data Store.
How to cite: Bazile, E., Verrelle, A., Glinton, M., and Le Moigne, P.: A new version of the European surface reanalysis UERRA-Land2 at 5.5km for the period 1961-2019, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-578, https://doi.org/10.5194/ems2022-578, 2022.
Nocturnal low-Level Jets (NLLJ) are maxima in the vertical profile of the horizontal wind speed in the lowest hundreds of meters of the troposphere. NLLJ impacts have been noted in many research fields and applications, e.g., air traffic, forest fire propagation, aerosol transport, and wind power production. The present study assesses NLLJs in ERA5 reanalysis of ECMWF in comparison to the predecessor product ERA-Interim and a novel observational dataset for Lindenberg (Germany) developed by DWD. The observational reference data is a composite of measurements for the years 2014 to 2018 from a meteorological tower limited to levels below 100 m a.g.l. and from a Doppler Wind Lidar for data above 100 m. The NLLJs are evaluated in three (six) hourly data from ERA5 (ERA-Interim) against the observations by applying an automated detection algorithm for NLLJs. Specifically, the NLLJ frequency of occurrence, core height and wind speed are statistically analysed and compared. The results for 2014 so far show an improvement in the NLLJ occurrence in the most recent reanalysis, with probability of detection (POD) of 49% (33%) and false alarm rate (FAR) of 27% (42%) for ERA5 (ERA-Interim). Both ERA5 and ERA-Interim qualitatively reproduce the month-to-month differences in the NLLJ numbers. We see also an improvement of the NLLJ core wind speed in ERA5 compared to ERA-Interim, with mean differences of +0.5 m/s (+1.6 m/s) for ERA5 (ERA-Interim) relative to the composite data. The core of NLLJs is too high in both reanalyses, with mean differences of 63m (27m) for ERA5 (ERA-Interim). Furthermore, we compared ERA5 against the composite data for all five available years. The POD and FAR are similar to 2014, with no clear period of the year with a better performance. The year with the best reproduction of NLLJs was 2018, with a POD of 52% and FAR of 27%, and March was the best month, with POD 67% of and FAR of 27%. The mean wind speed difference in the NLLJ core assessed across all years was only 0.01 m/s lower in the ERA5 re-analyses compared to the observation, while the mean core height was overestimated by 69 m. Taken together, we see an improvement of the wind profile and the representation of NLLJs in ERA5 compared to ERA-Interim, although further work is needed for representing the NLLJ heights and frequency of occurrence with a higher precision. Ongoing work includes the development of a better understanding of the spatiotemporal differences in the occurrence and properties of NLLJs in Europe and beyond.
How to cite: Weide Luiz, E. and Fiedler, S.: Assessment of nocturnal low-level jets in ERA5 and ERA-Interim reanalysis , EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-94, https://doi.org/10.5194/ems2022-94, 2022.
Wavelet transforms allow for the decomposition of precipitation fields over a broad range of spatial scales. The wavelet coefficients obtained from the decomposition of daily global precipitation fields can be used to study the spatial characteristics of the model simulated field over multiple spatial scales, in addition to diagnosing the effective model resolution. At a given spatial scale, the variability of the corresponding wavelet coefficients is proportional to the amount of “details” needed to pass from the representation of the precipitation field at that scale to the representation with respect to the next -finer- scale. The greater the variability, the greater the details required, and the greater the energy associated with that specific spatial scale. If we consider a sequence of daily precipitation fields over several years, we can construct the energy spectrum of global precipitation and analyse its evolution with climate change. We also propose utilising wavelets in future downscaling activity.
We have applied a 2D Haar wavelet transform to the ERA5 global daily precipitation fields for the period from 1950 to 2020. Then, we have studied the variability of the daily wavelet coefficients for the different spatial scales. If we compare the two normal periods, 1961-1990 and 1991-2020, it can be seen that for the most recent period there is a shift of the maximum of the energy spectrum towards smaller scales. The shift is more pronounced in the tropics. If we consider the time series of the energies, there is an increase in the energies for most of the spatial scales after 1985. The growth rates among the scales are different, though, and precipitation at the Meso-beta scale and the lower part of the synoptic scale (up to around 440 km) has become more important in the total wavelet energy balance of daily precipitation. The wavelet analysis enables us to detect a change in the scale structure of the global daily precipitation patterns with climate change.
The results presented here are part of the work described in detail in the scientific article:
How to cite: Lussana, C., Casati, B., Benestad, R. E., Lutz, J., Dobler, A., Landgren, O., Haugen, J. E., Mezghani, A., and Parding, K. M.: Wavelet transform applied to ERA5 global daily precipitation fields to assess changes in the rainfall patterns, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-181, https://doi.org/10.5194/ems2022-181, 2022.
A 30-year Copernicus Arctic Regional Reanalysis (CARRA) for the period of 1991-2021 has recently been finalized within the framework of the Copernicus Climate Change Service (C3S), which is a service implemented by ECMWF on behalf of the European Commission. The reanalysis is performed on European Arctic regions covering Greenland, Iceland, Barents Sea, Svalbard and Northern Scandinavia, with a 2.5 km grid resolution reanalysis based on the HARMONIE-AROME NWP system. A near-real time extension service of the reanalysis, CARRA-Timely Updates is now being set up with a targeted monthly update with a 2-month delay. In addition, plans are under discussion to set up a system for the next generation of a CARRA reanalysis which will cover the whole pan-Arctic region with similar resolution for a somewhat further extended reanalysis time period. These efforts are led by MET Norway with the other Nordic and the French national meteorological services as partners. Due to the Arctic climate warming being on average faster than the rest of the globe, there is enhanced user focus on change processes in this area. Through the Copernicus Climate Data Store (CDS), the CARRA dataset is now available for the climate research community. In this presentation we will focus on how the data set verifies and compares to other data sets. We demonstrate how the Arctic reanalysis adds value versus the global reanalysis ERA5 both statistically and for special weather events. This value addition is obtained both by using a higher-resolution model and by using fine-scale regional input data not used in the global system.
How to cite: Schyberg, H., Yang, X., Støylen, E., Dahlgren, P., S. Madsen, M., Køltzow, M., and Olesen, M.: Evolution of the Copernicus Arctic Regional Reanalysis, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-535, https://doi.org/10.5194/ems2022-535, 2022.
The Copernicus Climate Change Service of the European Commission aims to produce and deliver a land regional reanalysis for Europe covering the period from 1984 to the present at a horizontal resolution of 5.5 km.
The need for precipitation and surface variables at an ever-increasing spatial and temporal resolution is a recurrent demand. These variables allow, among other things, to address water resource management issues and to conduct climate change impact studies. Regional surface reanalyses are a way to reconstruct these variables for past periods covering several years using state-of-the-art models.
CERRA-Land (Copernicus European Regional Re-Analysis) is a regional land surface reanalysis dataset that describes the evolution of soil moisture, soil temperature and the snowpack. CERRA-Land is the result of a single stand alone integration of the SURFEX V8.1 land surface model driven by meteorological forcing from the CERRA atmospheric reanalysis and an offline analysis of daily accumulated surface precipitation using an optimal interpolation between an initial estimate (first guess) based on CERRA predicted precipitation and in situ rain gauges. The 2-meter temperature and relative humidity forcing data come from the CERRA surface analysis and the shortwave and longwave downwelling radiation, the 10-meter wind speed, and surface pressure come from the CERRA forecast outputs.
The CERRA-Land system uses the tiling approach where each grid-box of the model is divided into three different fractions: urban, lake and natural. For the nature fraction, the soil is discretized into 14 layers to accurately describe the water and energy transfers between the surface and the deep soil.
The quality of CERRA-Land is assessed by comparisons to ground-based observations, such as snow depth, 2-meter temperature, downwelling shortwave radiation and independent rainfall stations. A comparison with ERA5-Land will be done and the added value of the regional dataset will be discussed. The entire CERRA-Land dataset from 1984 to present is now available in the MARS database at ECMWF and will be available through the Copernicus Climate Data Store.
How to cite: Verrelle, A., Michael, G., Eric, B., and Le Moigne, P.: Strengths and weaknesses of the new CERRA-Land surface reanalysis at 5.5 km resolution over Europe, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-279, https://doi.org/10.5194/ems2022-279, 2022.
PERUN/Reanalysis (PERRea) is a product based on the ALADIN system, which shares its model code with the global NWP systems ARPEGE/IFS. It is the first step towards the regional climate simulations within the CMIP6 framework.
PERRea is being calculated for the period 1989–2019 on the domain covering Central Europe and its surroundings, with the horizontal mesh size 2.3km and 87 vertical levels. It provides not only the consistent 3D information about regional weather and climate on hourly footing, but its verification against the measurements and the driving ERA5 reanalysis quantifies accuracy of underlying ALADIN configuration, intended for simulations of future climate.
In order to guarantee reliable operation at convection permitting scales, PERRea employs ALADIN non-hydrostatic dynamical kernel combined with the so-called ALARO-1 physics. Its main highlights are: 1) self-switching-off convection parameterization with microphysical calculations sandwiched between updraft and downdraft computation, seeing joint output from subgrid and resolved condensation, 2) turbulence scheme incorporating the moist effects and using two prognostic energies, and 3) broadband radiation scheme enabling full cloud-radiation interaction. As for data assimilation component, PERRea analyses the soil properties using the optimal interpolation of SYNOP screen level temperature and humidity measurements. The upper air analysis combines the large scales from driving ERA5 reanalysis with the small scales from the previous high-resolution short range forecast. Their optimal combination is ensured via digital filter blending technique.
In this contribution, comparison of the PERRea with different reference datasets is presented for the period 1990–1999 over the full domain. Daily, monthly and seasonal precipitation, 2m temperature, 10m wind speed and surface solar radiation were selected for the comparison. Validation sets include ERA5 (the driving reanalysis of PERRea), station data from ECA&D dataset and E-OBS v23.0 (gridded station data over Europe) in 0.1° resolution.
The preliminary results show generally good agreement between PERRea and the two reference datasets, ERA5 and E-OBS. A weak systematic overestimation of precipitation in PERRea in selected regions with respect to ERA5 may indicate a difficulties in simulation of dry spells. The comparison of 2m temperature in PERRea against E-OBS shows insufficient diurnal amplitude especially in summer; whilst maximum daily temperature is underestimated in Central Europe, the minimum temperature is overestimated by more than 3 °C.
This research is supported by the Technology Agency of the Czech Republic Czech Technology Agency, under the SS02030040 project.
How to cite: Pokorna, L., Sokol, Z., Belda, M., Brozkova, R., Trojakova, A., and Bobotova, G.: PERUN/Reanalys – the high resolution reanalysis for central Europe driven by ERA 5, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-70, https://doi.org/10.5194/ems2022-70, 2022.
We compare Earth's surface energy balance components (monthly mean radiation and energy fluxes) from the ERA5-Land reanalysis with their measured equivalents from FLUXNET stations in the period 2001-2018. The comparison (FLUXNET station vs. the nearest grid point of ERA5-Land) is focused on Central European sites with an elevation under 1000 m above sea level during the summer half of the year (April - September) that roughly corresponds to the growing season in Central Europe. FLUXNET stations are further divided into four groups according to biomes (and surface types) that they represent: grass, crop, forest or wetland. We put special emphasis on the turbulent heat fluxes: sensible (H) and latent heat (LE) heat flux and their relative share in a form of evaporative fraction (EF, a ratio of latent heat flux, LE, to the sum of both turbulent fluxes, H + LE).
There's a perfect fit between monthly FLUXNET observations and ERA5-Land data in case of some radiation fluxes: incoming shortwave (SWin) or outgoing longwave (LWout) radiation. Incoming longwave radiation (LWin) is underestimated by ERA5-Land, while the score of reflected shortwave radiation (SWout) is mixed.
Latent heat flux (LE) is overestimated by the reanalysis, while sensible heat flux (H) is lower in the reanalysis than in FLUXNET observations. This leads to overestimation of the evaporative fraction (EF) by ERA5-Land in the growing season, with monthly values of EF being mostly between 0.7 - 0.9. On the other hand, FLUXNET's EF values range from 0.2 to 1.0. When focused on individual biomes, the best fit between ERA5-Land and FLUXNET is seen for grass. The shape of "half-annual" (Apr - Sep) cycle is also well captured for grass locations. In other major biomes (cropland or forest) we see not only disagreement in terms of absolute values of H and LE fluxes (or EF) but in the shape of "half-annual" cycle too. There's no significant decline of EF in summer for cropland locations in ERA5-Land. The magnitude of a steady EF increase in forest sites of FLUXNET is weaker in ERA5-Land.
Acknowledgement: "SustES - Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797)”.
How to cite: Skalak, P., Fischer, M., Orság, M., and Trnka, M.: Monthly surface energy fluxes in ERA5-Land reanalysis: a comparison with FLUXNET observations., EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-662, https://doi.org/10.5194/ems2022-662, 2022.
