ALBERT

Description: Abstract

Description: Integrated water vapor above Iquique airport from March 2018 to March 2019 measured with Microwave radiometer HATPRO-FOGHAT. Retrieval is based on 20 Years of Radiosonde Data from Antofagasta. Radiosonde data has been preprocessed with a relative humidity threshold of 90% for cloud formation.

Description: Abstract

Description: Liquid water path above Iquique airport from March 2018 to March 2019 measured with Microwave radiometer HATPRO-FOGHAT. Retrieval is based on 20 Years of Radiosonde Data from Antofagasta. Radiosonde data has been preprocessed with a relative humidity threshold of 80% for cloud formation.

Description: Abstract

Description: Liquid water path above Iquique airport from March 2018 to March 2019 measured with Microwave radiometer HATPRO-FOGHAT. Retrieval is based on 20 Years of Radiosonde Data from Antofagasta. Radiosonde data has been preprocessed with a relative humidity threshold of 85% for cloud formation.

Description: Abstract

Description: Integrated water vapor above Iquique airport from March 2018 to March 2019 measured with Microwave radiometer HATPRO-FOGHAT. Retrieval is based on 20 Years of Radiosonde Data from Antofagasta. Radiosonde data has been preprocessed with a relative humidity threshold of 95% for cloud formation.

Description: Abstract

Description: Liquid water path above Iquique airport from March 2018 to March 2019 measured with Microwave radiometer HATPRO-FOGHAT. Retrieval is based on 20 Years of Radiosonde Data from Antofagasta. Radiosonde data has been preprocessed with a relative humidity threshold of 90% for cloud formation.

Description: Abstract

Description: Liquid water path above Iquique airport from March 2018 to March 2019 measured with Microwave radiometer HATPRO-FOGHAT. Retrieval is based on 20 Years of Radiosonde Data from Antofagasta. Radiosonde data has been preprocessed with a relative humidity threshold of 95% for cloud formation.

Description: Sea level pressure is a fundamental weather and climate element and the very basis of everyday weather maps. Daily sea level pressure distributions provide information on the influence of high and low pressure systems, air flow, weather activity, and, hence, synoptic conditions. Using sea level pressure distributions from the NCEP/NCAR Reanalysis 1 (Kalnay et al., 1996) and a simplified variant of the weather-typing scheme by Jenkinson and Collison (1977) atmospheric circulation over the North Sea has been classified as to pattern and intensity on a daily basis starting in 1948. A full account of the original weather-typing scheme can be found in Loewe et al. (2005), while the variant scheme has been detailed in Loewe et al. (2006). The analysis has been carried out on the original 16-point grid. Though formally valid at its central point (55°N, 5°E), results are representative of the North Sea region between 50°N-60°N and 0°E-10°E. The modified scheme allows for six weather types, namely four directional (NE=Northeast, SE, SW, NW) and two rotational types (C=cyclonic and A=anticyclonic). The strength of the atmospheric circulation is classified by way of a peak-over-threshold technique, employing re-calibrated thresholds for the gale index G* of 28.3, 36.6, and 44.6 hPa for gale (G), severe gale (SG), and very severe gale (VSG), respectively (Loewe et al., 2013). Technically, the set of weather-typing and gale-classification rules is implemented as a lean FORTRAN code (lwtnssim.f), internally known as "Simple Lamb weather-typing scheme for the North Sea v1". The processing run was done on a Linux server under Debian 10 (Buster). Both, weather types and gale days, form a catalogue of more than 70 annual calendars since 1948 that is presented and continuously updated to the present day at https://www.bsh.de/EN/DATA/Climate-and-Sea/Weather-and-Gales/weather-and-gales_node.html. This catalogue concisely documents synoptic conditions in the North Sea region. Possible benefits are manifold. Special events and episodes in regional-scale atmospheric circulation are easily looked up and traced. Beyond that, the dataset is well suited for frequency, trend, persistence, transition, and extreme-value statistics.

Description: preindustrial Control experiment to be used in VolMIP analyses. The piControl experiment is the CMIP6-DECK piControl experiment described in Eyring et al. (2016). piControl provides initial climate states that are sampled to start most of VolMIP experiments (Zanchettin et al., 2016). The dataset contains monthly values of selected variables spatially averaged over four regions. These are the full globe (GL), the Northern Hemisphere extratropics (30°-90°N, NH), the tropics (30°S-30°N, TR), and the Southern Hemisphere (30°-90°S, hereafter SH). The considered variables have the following cmor names: hfls, hfss, pr, rlds, rldscs, rlus, rlut, rlutcs, rsds, rsdscs, rsdt, rsus, rsut, rsutcs, tas. Additionally, the climate indices NAO and Nino34 are part of the dataset. Considered models are CanESM5, IPSL-CM6A-LR, GISS-E2.1-G, MIROC-ES2L, MPI-ESM1.2-LR (named MPI-ESM-LR in the files of this dataset) and UKESM1. Considered experiments are piControl and volc-pinatubo-full, with initial date and final date as specified for each model in Zanchettin et al. (2021). Different realizations are considered for the participating models depending on availability.

Description: Idealized volcanic-forcing coupled climate model experiment using the 1991 Pinatubo forcing as used in the CMIP6 historical simulations. It is a Tier 1 (mandatory) VolMIP experiment based on a large ensemble of short-term “Pinatubo” climate simulations aimed at accurately estimating simulated responses to volcanic forcing that may be comparable to the amplitude of internal interannual climate variability. Initialization is based on equally distributed predefined states of ENSO (cold/neutral/warm states) and of the North Atlantic Oscillation (NAO, negative/neutral/positive states). Sampling of an eastern phase of the Quasi-Biennial Oscillation (QBO), as observed after the 1991 Pinatubo eruption, is preferred for those models that spontaneously generate such mode of stratospheric variability. VIRF diagnostics must be calculated for this experiment for the whole integration and for all ensemble members, as these are required for the “volc-pinatubo-strat”/“surf” experiments. A minimum length of integration of 3 years is requested. Details about the experiment are provided by Zanchettin et al. (2016). The dataset contains monthly values of selected variables spatially averaged over four regions. These are the full globe (GL), the Northern Hemisphere extratropics (30°-90°N, NH), the tropics (30°S-30°N, TR), and the Southern Hemisphere (30°-90°S, hereafter SH). The considered variables have the following cmor names: hfls, hfss, pr, rlds, rldscs, rlus, rlut, rlutcs, rsds, rsdscs, rsdt, rsus, rsut, rsutcs, tas. Additionally, the climate indices NAO and Nino34 are part of the dataset. Considered models are CanESM5, IPSL-CM6A-LR, GISS-E2.1-G, MIROC-ES2L, MPI-ESM1.2-LR (named MPI-ESM-LR in the files of this dataset) and UKESM1. Considered experiments are piControl and volc-pinatubo-full, with initial date and final date as specified for each model in Zanchettin et al. (2021). Different realizations are considered for the participating models depending on availability.

Description: The Bias Corrected CESMv1 data for mid-century (2041-2050) for RCP8.5 emission scenario at coarser resolution has been downscaled to 10km resolution over India using the Weather Research and Forecasting (WRF) model. The climate variables included are 2m Temperature (t2m), relative humidity (rh), wind speed (wspd), total precipitation (prec), mean surface shortwave flux (sw), top-of-atmosphere outgoing longwave radiation (lw), mean surface latent (lhf) and sensible (shf) heat fluxes along with the latitude, longitude, and time information. The dataset covers the Indian National Territory region at a 369 x 369 grid. The data is available at three temporal resolutions: Daily TS, Monthly TS, and Monthly Climatology. The dataset has been structured into a total of 30 files (10 variables x 3 temporal resolutions) packed in self-explanatory NetCDF format. The daily, monthly, and monthly climatology files contain 369x369x3650, 369x369x30, and 369x369x12 data points, respectively. The entire dataset is about 30 GB in size. The precipitation files in the older version contained hourly accumulated values for every day. This version contains the correct daily accumulated, monthly accumulated and monthly climatology precipitation data.

Description: The global climate model system MPI-ESM-LR was applied to create an ensemble of 30 members for the historical period 1950-2005 and a continuation of the simulations for the RCP8.5 period 2006-2099. Additionally, a pre-industrial control run was performed for 1950-2099 with atmospheric pCO2 of 1850. All members were subsequently directly regionalized using the regionally coupled MPIOM-REMO climate model system consisting of the global ocean model MPIOM focused with its horizontal resolution on the North Sea and the regional atmospheric model REMO over the EURO CORDEX22 region (euro-cordex.net), which was fully coupled with MPIOM in this region. For extreme value analyses, certain variables were stored with hourly time step. Here, global sea surface height and regional (EURO CORDEX22) u and v wind components at 10 m above ground are available. Further data can be requested from the authors.

Description: In this study, the first gridded hydroclimate dataset in eastern China (EC) during the last millennium was generated. This hydroclimate dataset mainly consisted of two components. The first section was created by interpolating drought/flood grades from 1500 to 2000 using the angular distance weight method. Sampling error estimates were employed to assess the effects of the interpolated dataset. The second section for the hydroclimate dataset during 960-1500 was generated by constructing best subset regression models using selected tree-ring chronologies in the United States/northwestern China through atmospheric teleconnection. The validation parameters of the calibration equations were also derived, including the adjusted R2, predicted R2, RE, and CE. This dataset includes three files named Hydr_EC.mat (43KB), Val_Par.mat (4KB), and SEE.mat (1KB), respectively. In detail, Hydro-EC is the hydroclimate in eastern China during the last millennium; Val-Par and SEE are the dataset’s validation results.

Description: Abstract

Description: This dataset summarizes the following physicochemical parameters assessed for 32 soil samples sieved to 〈2 mm from 16 shallow soil profiles, which were sampled in two depth intervals (0–15 and 15–30 cm): CIELAB soil colour, spectrophotometric redness index, electrical conductivity, soil pH, contents of organic carbon, organic phosphorus and total phosphorus, proportion of organic phosphorus in total phosphorus, calcium carbonate content, geochemical proxies for (de)calcification and (de)salinization, and contents of total and poorly crystalline pedogenic iron oxides. Constituting a soil chronosequence at the south-central coast of the Atacama Desert, four shallow soil profiles were sampled from each of the four morphostratigraphic units of the coastal alluvial fan Paposo (25.03°S/70.47°W). Results are stored in a .csv table.

Description: Abstract

Description: This dataset contains proportions of grain size classes, the median grain size, and the differential grain size distribution for the size fraction 40–311 nm of 32 soil samples sieved to 〈2 mm from 16 shallow soil profiles, which were sampled in two depth intervals (0–15 and 15–30 cm). Constituting a soil chronosequence at the south-central coast of the Atacama Desert, four shallow soil profiles were sampled from each of the four morphostratigraphic units of the coastal alluvial fan Paposo (25.03°S/70.47°W). Particle size measurements were conducted using laser diffraction analysis. Results are stored in a .csv table.

Description: The hydrodynamic model TRIM-NP in a barotropic mode is used to simulate the strong storm tide in March 1906 forced by ECMWF ERA-20C and CERA-20C ensemble of coupled climate reanalyses (https://www.ecmwf.int). The model area covers the region of 20W to 30E and 42N to 65N with a spatial resolution of 12.8x12.8 km for grid 1. At the lateral boundaries of grid 1, the water level is calculated with tide model FES2004. TRIM-NP calculates one way nested with higher resolution the North Sea (with 6.4km, grid2), southern North Sea (with 3.2km, grid3) and the German Bight (with 1.6km, grid4). In this data bank, the datasets are available hourly for grid 2 and grid 4. Please contact the authors for grid 1 and grid 3.

Description: The hydrodynamic model TRIM-NP in a barotropic mode is used to simulate the strong storm tide in March 1906 forced by NOAA-CIRES-DOE Twentieth Century Reanalysis (20CR) version 2c and 3. datasets (https://portal.nersc.gov/project/20C_Reanalysis/). The model area covers the region of 20W to 30E and 42N to 65N with a spatial resolution of 12.8x12.8 km for grid 1. At the lateral boundaries of grid 1, the water level is calculated with tide model FES2004. TRIM-NP calculates one way nested with higher resolution the North Sea (with 6.4km, grid2), southern North Sea (with 3.2km, grid3) and the German Bight (with 1.6km, grid4). In this data bank, the datasets are available hourly for grid 2 and grid 4. Please contact the authors for grid 1 and grid 3.

Description: Source code of the Max Planck Institute Earth System Model (MPI-ESM1.2) adopted to the project PRIMAVERA for the comparison of four different ocean vertical mixing schemes.

Description: ICON 2.5 km simulations over the tropical Atlantic ([65W:15E],[10S:20N] for the months of December 2013 (NARVAL1 : 30 days) and August 2016 (NARVAL2 : 30 days). The grid spacing, computed as the square root of the triangular grid cells, amounts to 2.5 km. In the vertical, a stretched vertical coordinate is used with 75 layers, whereby 12 layers are located in the first kilometer. The simulations are conducted for the months of December 2013 and July 2016. They are started every day at 00 UTC from the analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) and integrated for 36 hours. Boundary data are taken from the ECMWF forecasts and updated every 3 hours. At the bottom boundary, the Sea Surface Temperature (SST) is taken from the ECMWF analysis. It is kept fixed at its initial value during the 36-h integration period. The simulations were conducted using the ICOsahedral Non-hydrostatic (ICON) model (Zängl et al., 2015). Given the horizontal grid spacing, no convective parameterization is employed and convection is explicitly resolved by the bulk microphysics scheme that predicts cloud water, rain, snow, ice and graupel (Baldauf et al., 2011). The parameterizations for gravity wave drag and subgrid-scale orography are also switched off, otherwise the model employs the same parameterizations as the operational model version in use at the German Weather Service (DWD), see Zängl et al. (2015) and Klocke et al. (2017) for further details.

Description: ICON 2.5 km simulations over the tropical Atlantic ([65W:15E],[10S:20N] for the months of December 2013 (NARVAL1 : 30 days) and August 2016 (NARVAL2 : 30 days). The grid spacing, computed as the square root of the triangular grid cells, amounts to 2.5 km. In the vertical, a stretched vertical coordinate is used with 75 layers, whereby 12 layers are located in the first kilometer. The simulations are conducted for the months of December 2013 and July 2016. They are started every day at 00 UTC from the analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) and integrated for 36 hours. Boundary data are taken from the ECMWF forecasts and updated every 3 hours. At the bottom boundary, the Sea Surface Temperature (SST) is taken from the ECMWF analysis. It is kept fixed at its initial value during the 36-h integration period. The simulations were conducted using the ICOsahedral Non-hydrostatic (ICON) model (Zängl et al., 2015). Given the horizontal grid spacing, no convective parameterization is employed and convection is explicitly resolved by the bulk microphysics scheme that predicts cloud water, rain, snow, ice and graupel (Baldauf et al., 2011). The parameterizations for gravity wave drag and subgrid-scale orography are also switched off, otherwise the model employs the same parameterizations as the operational model version in use at the German Weather Service (DWD), see Zängl et al. (2015) and Klocke et al. (2017) for further details.

Description: HadCRU_MLE_v1.0 is a dataset of monthly gridded surface temperatures for the Earth during the instrumental period (since 1850). The name ‘HadCRU_MLE_v1.0’ reflects the dataset’s use of maximum likelihood estimation and observational data primarily from the Met Office Hadley Centre and the Climate Research Unit of the University of East Anglia. Source datasets used to create HadCRU_MLE_v1.0 include land surface air temperature anomalies of HadCRUT4, sea surface temperature anomalies of HadSST4, sea ice coverage of HadISST2, the surface temperature climatology of Jones et al. (1999), the sea surface temperature climatology of HadSST3, land mask data of OSTIA, surface elevation data of GMTED2010, and climate model output of CCSM4 for a pre-industrial control scenario. HadCRU_MLE_v1.0 was generated using information from the Met Office Hadley Centre, the Climate Research Unit of the University of East Anglia, the E.U. Copernicus Marine Service, the U.S. Geological Survey, and the University Corporation of Atmospheric Research. The primary motivation to develop HadCRU_MLE_v1.0 was to correct for two biases that may exist in global instrumental temperature datasets. The first bias is an amplification bias caused by not adequately accounting for the tendency of different regions of the planet to warm at different rates. The second bias is a sea ice bias caused by not adequately accounting for changes in sea ice coverage during the instrumental period. Corrections to these biases increased the estimate of global mean surface temperature change during the instrumental period. The new dataset has improvements compared to the Cowtan and Way version 2 dataset, including an improved statistical foundation for estimating model parameters, taking advantage of temporal correlations of observations, taking advantage of correlations between land and sea observations, and accounting for more sources of uncertainty. To properly correct for amplification bias, HadCRU_MLE_v1.0 incorporates the behaviour of the El Niño Southern Oscillation. HadCRU_MLE_v1.0 includes mean surface temperature anomalies for each month from 1850 to 2018 and for each 5° latitude by 5° longitude grid cell. Future versions of HadCRU_MLE may become available to extend the temporal coverage beyond 2018. The maximum likelihood estimation approach allows for the estimated field of surface temperature anomalies to be temporally and spatially complete for the entire instrumental period and for the entire surface of the Earth. A 5° by 5° gridded 1961-1990 temperature climatology for HadCRU_MLE_v1.0 is available, although caution is advised when interpreting this temperature climatology since the source datasets used for temperature climatologies do not correspond perfectly with the source datasets used for temperature anomalies. Other information of HadCRU_MLE_v1.0 is available, including the estimated local amplification factors, the magnitude of the corrections for sea ice bias, and the impact of the El Niño Southern Oscillation on surface temperature anomalies.

Description: The hydrodynamic model TRIM-NP in a barotropic mode is used to simulate the strong storm tide in March 1906 forced by reconstructed weather data by the Deutsche Wetterdienst (DWD) and Helmholtz-Zentrum Geesthacht. From georeferenced historical station data, pressure maps are drawn, digitised, and wind speed calculated from them. The model area covers the region of 20W to 30E and 42N to 65N with a spatial resolution of 12.8x12.8 km for grid 1. At the lateral boundaries of grid 1, the water level is calculated with tide model FES2004. TRIM-NP calculates one way nested with higher resolution the North Sea (with 6.4km, grid2), southern North Sea (with 3.2km, grid3) and the German Bight (with 1.6km, grid4). In this data bank, the datasets are available hourly for grid 2 and grid 4. Please contact the authors for grid 1 and grid 3. The datasets are visualised https://doi.org/10.5446/49529 or https://www.dkrz.de/projects-and-partners/projects/focus/stormtide1906. In additional experiments, the tides at the lateral boundaries are shifted backwards (up to minus six hours) or forward (up to plus six hours) in time to calculate the peak of the storm tide. The atmospheric forcing is not changed. Only the water levels from grid4 of this experiment are stored.

Description: Abstract

Description: Classification of the state of the atmospheric boundary layer at Diego Aracena Aitport, Iquique, Chile. Profiles of vertical and horizontal wind speed and backscatter coefficient (measured with a Doppler Wind Lidar) as well as thermal stratification at the surface (Thermo-Hygrometers at ~1m and ~2m height) are used to identify height regions without and with turbulence, clouds and precipitation . In a second step the sources of this turbulence are identified (clouds, surface heating or wind shear). For details of the method see Manninen, A., T. Marke, E. O'Connor, and M. Tuononen, 2018: Atmospheric boundary layer classification with Doppler lidar, J. Geophys. Res. , 123, DOI:10.1029/2017JD028169. For daily plots see: http://tiny.cc/iqq_cn_bl_class

Description: Ensemble of MPI-ESM1-2-HR CMIP6 historical simulations without solar and ozone variability (i.e., set to the year 1850). The simulations are performed within the BMBF project "Solar contribution to climate change on decadal to centennial timescales" (SOLCHECK) of the "Role of the middle atmosphere in climate" (ROMIC II: https://romic2.iap-kborn.de/en/romic/strategy). The experimental setup is identical to the MPI-ESM1-2-HR historical CMIP6 simulations except for the solar and ozone variability. Please refrain from using the following variables since their computations where either erroneous or do not comply with the CMIP6 protocol: Eyr_fracLut, 6hrPlevPt_sfcWind, Amon_mc, CFday_mc, CFmon_dmc, CFmon_smc, CFmon_mcd, CFmon_mcu, Omon_o2sat, Oyr_o2sat, Omon_uo, Omon_umo, Omon_hfx Omon_tauuo Technical details: Ensemble run on bullx B700 Mistral at DKRZ

Description: LARSIM (LARSIM=LArge Area Runoff Simulation Model BW= Baden-Wuerttemberg) is described in "Freiburger Schriften zur Hydrologie", Band 22. 2006 (Ludwig, K.; Bremicker, M.: The water Balance Model LARSIM) The calculated results from LARSIM for the gauges Murg at Rotenfels and Kinzig at Schwaibach were handed over. The results are calcultaed in operational mode of the flood forecasting centre Karlsruhe (HVZ). The forecasts were corrected with ARIMA (0,1,0), i.e. the forecasted discharges were shifted with a constant amount, so, that the first forecast value attaches directly to the last measured value. During low water periods, the forecast is adapted to the average value of the last 24 h of the measured values. The forecasts were calculated for 72 hours. The runs driven by the DWD forecast LMK takes the LMK (new name: COSMO-DE) for the first 21 hours and then the LME-forecast. The runs called LME take only the LME (new name: COSMO-EU) forecast into accuont. For the period up to the forecast time measured values were used. The model uses precipitation, temperature, wind velocity, dew point or rel. humidity and the solar radiation. The measurement network uses the stations of the German Weatherservice DWD, the stations of the federal state Baden-Wuerttemberg (called "LUBW Luft" and "LUBW Ombro") and stations of third parties. The measurement network is very dense, but the equipement of the different stations may be dissimilar. You can see the network of the precipitation stations at http://www.hvz.baden-wuerttemberg.de/ -〉 Niederschlag -〉 Stationskarte. The forecasts were performed by the Flood Forecasting Centre Karlsruhe (HVZ) with its operational model "Oberrheinzf" (for Oberrheinzufluesse = tributaries of the river Rhine). The HVZ is part of the "Landesanstalt fuer Umwelt, Messungen und Naturschutz Baden-Wuerttemberg" (LUBW)". The model covers the region: 7°42' / 48°04' und 8°33' / 49°02'

Description: Reflectivity and radial velocity of Karlsruhe C-Band Doppler Radar located at Forschungszentrum Karlsruhe. Volume data in polar coordinates are delivered. Two scans have been performed: 1. 14 Elevation volume scan of reflectivity and radial velocity starting at 0.4 deg elevation up to 30 deg elevation, 120 km range, 500 m resolution, dual PRF (pulse repetition frequency; 1153 Hz/864 Hz): reflectivity and radial velocity. 2. 14 Elevation volume scan as 1, but only single PRF: reflectivity. The data is provided in two different data sets: reflectivity (ca. every 5 min; data from both scan modi) and radial_velocity (every 10 min; data from 1st scan mode).

Description: Profiles of the 35 GHz cloud radar MIRA36-S at COPS-Supersite Hornisgrinde. Containing reflectivity, radial Doppler velocity, spectral width and LDR (linear depolarisation ratio). Different scan modi are possible during one day. See more information on measurement times/scan modi in entry "cops_suph_cradar_info_1". Data available from 01.06.2007 to 06.08.2007 and 24.08.2007 to 31.08.2007.

Description: The Sodar/RASS device installed at Fussbach consisted of a DSDPA.90/64-Sodar and a DSDR3x7-1290MHz-RASS extension by METEK GmbH. It operated with an averaging period of 10 min. The minimum measurement height was 40 m and the maximum measurement height 700 m with a step width of 20 m in between.

Description: The 9 m profile mast run by University of Bayreuth continuously measured profiles of the wind speed, the air temperature and the water vapor pressure above a corn field with a sampling frequency of 1 Hz averaged to 1 min values within the data logger. Six cup anemometers and five psychrometers have been mounted in different heights. After a check for plausibility the 1 min values have been averaged to 30 min intervals, which are provided in this data set. The following instruments have been installed for the parameters given below: - wind speed: F460 cup anemometer (Climatronics Corp.) - temperature and water vapor pressure: electrically aspirated psychrometer (Frankenberger) The water vapor pressure has been calculated from the measured dry and moist thermometer temperatures of the psychrometer according to Sprung's psychrometer formula.

Description: Lidar data of 2mu Doppler Lidar run by FZK/IMK-TRO at COPS-Supersite Hornisgrinde. The windtracer is a commercial Doppler Lidar from LMCT. It can be operated in scanning and slant path mode. The data is direct output of the Real Time Lidar Data Processing Unit containing UTC, scanner position, rangegates and measured line_of_sight_velocity, signal to noise ratio (SNR), and aerosol backscatter signal derived from SNR. The wind profile is calculated automatically using VAD algorithm for 10 minutes intervals. No manual quality control is applied.

Description: The files contain vertical profiles of absolute humidity and backscatter signals at 820 nm measured with the Water Vapor Differential Absorption Lidar of University of Hohenheim (UHOH DIAL) during COPS 2007. The UHOH DIAL was located at Hornisgrinde (COPS Supersite H) with other instruments. The backscatter signals are offline backscatter data multiplied with range squared in arbitrary units. These data show aerosols and clouds above the lidar. The temporal and spatial resolution of these data is 10 s and 15 m, respectively. For the humidity data (in g/m**-3) of this release, the temporal and spatial resolution is the same but with a 150-m-long weighting function. Data with higher resolution, data of higher altitudes, or data of measurement days which are not published within this release are available on request. See pdf summary in entry 'cops_suph_rlidar_info_1' for further information.

Description: The research aircraft DO-128, call sign D-IBUF, of the IFF (TU Braunschweig) measures numerous meteorological and chemical variables to get a better understanding of the atmospheric processes which cause the development of precipitation. The aircraft starts from the Baden Airpark and flys among different flight pattern which are described in the flight protocols. The meteorological variables are static pressure and dynamic pressure at the nose boom, surface temperature, humidity mixing ratio by a lyman-alpha sensor, dewpoint temperature by a dewpoint-mirror, relative humidity by an aerodata-humicap, air temperature by a PT-100 sensor, vertical and horizontal wind components by a five-hole probe and GPS, turbulence (100 Hz), shortwave (pyranometer) and longwave (pyrgeometer) radiance in upper und lower half space. The chemical variables are mole fractions of ozone, carbon dioxide, carbon monoxide, nitrogen dioxide, nitrogen monoxide and nitric oxides (NOx). There are also a few variables for the position and the velocity of the aircraft stored in the data file. Additionally to the measurements by the aircraft, up to 30 drop-sondes can be dropped out of the aircraft. By using these sondes, vertical profiles of temperature, pressure, humidity and wind can be detected (see also the meta data describing the drop-sonde data). Special events are also marked in the data files by the event counter (e.g. dropping times of the drop-sondes, marks concerning the flight patterns etc.). The specific action or flight manoeuvre indicated by the event_number can be identified in the flight protocol.

Description: The energy balance station run by University of Bonn measured high-frequency (10 Hz) eddy-covariance raw data with a CSAT3 (Campbell Scientific, Inc.) sonic anemometer and a LI-7500 (LI-COR Biosciences) hygrometer above the target land use type meadow. The measuring set-up was continuously running during the entire COPS measurement period in order to provide a complete time series of the turbulent fluxes of momentum, sensible and latent heat as well as carbon dioxide. Post-processing was performed using the software package TK2 (developed by the Department of Micrometeorology, University of Bayreuth) which produces quality assured turbulent flux data with an averaging interval of 30 min. The documentation and instruction manual of TK2 (see entry cops_nebt_ubt_info_1) and additional references about the applied flux corrections and post-field data quality control (see entry cops_nebt_ubt_info_2) as well as a document about the general handling of the flux data can be found in supplementary pdf-files within the energy balance and turbulence network (NEBT) experiment of the data base. The turbulent flux data in this data set are flagged according to their quality and checked for an impact of possible internal boundary layers. Additionally, the flux contribution from the target land use type intended to be observed to the total flux measured was calculated applying footprint modeling. Information and references about the internal boundary layer evaluation procedure and the footprint analysis are also given in additional info pdf-files. Pictures of the footprint climatology of the station as related to the land use and to the spatial distribution of the quality flags are included in the corresponding additional info pdf-file.

Description: The files contain vertical profiles of temperature and particle backscatter coefficient at 355 nm measured with the Rotational Raman Lidar of University of Hohenheim (UHOH RRL) during COPS 2007. The UHOH RRL was located at Hornisgrinde (COPS Supersite H) with other instruments. The temporal resolution of the particle-backscatter-coefficient data is 10 s in June 2007 and 13 s in July and August 2007, respectively. The spatial resolution is 37.5 m. For the temperature data of this release, the temporal and spatial resolution of the data is 5 minutes and 37.5 m, respectively. Missing values were added for data containing clouds and exceeding statistical measurement uncertainties of 2 K. Scanning data, data with higher resolution, data of higher altitudes, or data of measurement days which are not published within this release are available on request. See pdf summary in entry 'cops_suph_rlidar_info_1' for further information.

Description: The two energy balance station run by Meteo-France/CNRM measured high-frequency (20 Hz) eddy-covariance raw data with a Solent-HS (Gill Instruments Ltd.) sonic anemometer and a LI-7500 (LI-COR Biosciences) hygrometer above the target land use type corn. The measuring set-up was continuously running during July 2007 in order to provide turbulent flux data of momentum, sensible and latent heat as well as carbon dioxide. Post-processing was performed using the software package TK2 (developed by the Department of Micrometeorology, University of Bayreuth) which produces quality assured turbulent flux data with an averaging interval of 30 min. The documentation and instruction manual of TK2 (see entry cops_nebt_ubt_info_1) and additional references about the applied flux corrections and post-field data quality control (see entry cops_nebt_ubt_info_2) as well as a document about the general handling of the flux data can be found in supplementary pdf-files within the energy balance and turbulence network (NEBT) experiment of the data base. The turbulent flux data in this data set are flagged according to their quality and checked for an impact of possible internal boundary layers. Additionally, the flux contribution from the target land use type intended to be observed to the total flux measured was calculated applying footprint modeling. Information and references about the internal boundary layer evaluation procedure and the footprint analysis are also given in additional info pdf-files. Pictures of the footprint climatology of the station as related to the land use and to the spatial distribution of the quality flags are included in the additional info pdf-file corresponding to the individual station.

Description: The energy balance stations run by University of Bayreuth continuously measured radiation and soil parameters over different land types with a sampling frequency of 1 Hz averaged to 1 min values within the data logger. After a check for plausibility the 1 min values have been averaged to 30 min intervals, which are provided in this data set. The instrumentation was different on each location. The following was measured depending on the station: - soil heat flux - soil temperature - volumetric soil water content - longwave radiation components - shortwave radiation components - tipping bucket rain gauge measurements The ground heat flux including the heat storage in the upper soil layer was determined from the measured soil heat flux, soil temperatures and volumetric soil water contents according to the 'simple measurement' (SM) method according to Liebethal and Foken (2007).

Description: The hydrological model DIMOSOP was run by University of Brescia with three different atmospheric forcings and different runoff forecast times. For more information on the model please contact the originator. Basins: Brenta at Bassano, Avisio at Stramentizzo, Noce at S.Giustina, Sarca at Maso Gobbo, Chiese at Lago Idro, Mella at Stocchetta, Oglio at Sarnico, Chiese at Malga Bissina, Lago d Arno, Lago d Avio, Cismon at Corlo, Toce at Candoglia, Rio del Sabbione at Sabbione, Gries at Morasco, T.Roni at Toggia, Rio d Arbola at Codelago, Melezzo at Masera, Bogna at Pontecaddo, Toce at Pontemaglio, Anza at Piedimulera, Isorno at Pontetto, Diveria at Crevoladossola, Ovesca at Villadossola, Anza at Ceppo Morelli, Diga Antrona, Ciampere at Avino, Ovesca at Alpe Cavalli, Devero at Agaro, Lago Busin, Lago Vannino, Taro at Pontetaro, Taro at S.Secondo, Cismon at Corlo

Description: Hydrological forecasts with hydrological model LARSIM (LARSIM=LArge Area Runoof Simulation Model, BY=Bavaria, Conceptual RR-model. Forecast depth: 72 hours.) for rivers Iller and Lech (DE) driven by numerical weather prediction models LME, GME, GFS. The runs were performed by "Wasserwirtschaftsamt Kempten" (WWA-KE).

Description: The goal of the experiment is to drive FEST, a rainfall-runoff distributed model with continuous soil moisture account, with ensemble forecasts from COSMO-LEPS (CLEPS) and with forecasts from ISACMOL2. The application domain is the Toce-Ticino and Maggia watershed. Hydrograph simulations and alerts are provided for Candoglia (Toce), Solduno (Maggia) and Bellinzona (Ticino). The runs were provided by Politecnico di Milano (PoliMi), Italy.