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Assessing the inherent uncertainties in satellite data products is a challenging task. Different technical approaches have been developed in the Earth Observation (EO) communities to address the validation problem which results in a large variety of methods as well as terminology. This paper reviews state‐of‐the‐art methods of satellite validation and documents their similarities and differences. First, the overall validation objectives and terminologies are specified, followed by a generic mathematical formulation of the validation problem. Metrics currently used as well as more advanced EO validation approaches are introduced thereafter. An outlook on the applicability and requirements of current EO validation approaches and targets is given.

together with an initialization procedure and a model evaluation system. This paper 31 summarizes the lessons learned from MiKlip so far; some are purely scientific, others concern 32 strategies and structures of research that targets future operational use. 33Three prediction-system generations have been constructed, characterized by 34 alternative initialization strategies; the later generations show a marked improvement in 35 hindcast skill for surface temperature. Hindcast skill is also identified for multi-year-mean 36European summer surface temperatures, extra-tropical cyclone tracks, the Quasi-Biennial 37Oscillation, and ocean carbon uptake, among others. Regionalization maintains or slightly 38 enhances the skill in European surface temperature inherited from the global model and also 39 displays hindcast skill for wind-energy output. A new volcano code package permits rapid 40 modification of the predictions in response to a future eruption. 41MiKlip has demonstrated the efficacy of subjecting a single global prediction system 42 to a major research effort. The benefits of this strategy include the rapid cycling through the 43 prediction-system generations, the development of a sophisticated evaluation package usable 44 by all MiKlip researchers, and regional applications of the global predictions. Open research 45 questions include the optimal balance between model resolution and ensemble size, the 46 appropriate method for constructing a prediction ensemble, and the decision between full-47 field and anomaly initialization. 48

Abstract. This paper describes the new First Guess Daily product of the Global Precipitation Climatology Centre (GPCC). The new product gives an estimate of the global daily precipitation gridded at a spatial resolution of 1• latitude by 1 • longitude. It is based on rain gauge data reported in near-real time via the Global Telecommunication System (GTS) and available about three to five days after the end of each observation month. In addition to the gridded daily precipitation totals in mm day −1 , the standard deviation in mm day −1 , the kriging interpolation error in % and the number of measurements per grid cell are also encoded into the monthly netCDF product file and provided for all months since January 2009. Prior to their interpolation, the measured precipitation values undergo a preliminary automatic quality control. For the calculation of the areal mean of the grid, anomalies are interpolated with ordinary block kriging. This approach allows for a near-real-time release. Therefore, the purely GTS-based data processing lacks an intensive quality control as well as a high data density and is denoted as First Guess. The daily data set is referenced under doi:10.5676/DWD_GPCC/FG_D_100. Two further products, the Full Data Daily and a merged satellite-gauge product, are currently under development at Deutscher Wetterdienst (DWD). These additional products will not be available in near-real time, but based on significantly more and strictly quality controlled observations. All GPCC products are provided free of charge via the GPCC webpage: ftp://ftp-anon.dwd.de/pub/data/gpcc/html/download_gate.html.

[1] Airborne measurements of the ratio of spectral upward and downward irradiances (so-called spectral albedo) are used to derive the areal spectral surface albedo in the wavelength range from 330 to 1670 nm. The data were collected over different sea and land surfaces in cloudless atmospheric conditions during three field campaigns. Measurements from the Albedometer (developed at IfT) and the NASA Solar Spectral Flux Radiometer (SSFR) are employed. Spectral radiative transfer calculations show that atmospheric scattering and absorption within the layer beneath the flight level considerably contribute to the airborne albedo measurements reported here, even for low flight altitudes (0.2-0.5 km). To remove this atmospheric masking, a nonlinear extrapolation of the airborne albedo measurements to the ground is performed. The nonlinearity is due to the vertically inhomogeneous distribution of the particle microphysical properties. This fact underlines the importance of aerosol profile measurements for the proper correction of atmospheric masking. Examples of the extrapolated areal spectral surface albedos are discussed in terms of their solar zenith angle dependence, their small-scale, and general variability. Finally, typical areal spectral surface albedos for different sea and land surfaces, as derived from the three measurement campaigns, are supplied in parameterized form for use in radiative transfer applications.

The Global Energy and Water Cycle Exchanges project (GEWEX) water vapor assessment’s (G-VAP) main objective is to analyze and explain strengths and weaknesses of satellite-based data records of water vapor through intercomparisons and comparisons with ground-based data. G-VAP results from the intercomparison of six total column water vapor (TCWV) data records are presented. Prior to the intercomparison, the data records were regridded to a common regular grid of 2° × 2° longitude–latitude. All data records cover a common period from 1988 to 2008. The intercomparison is complemented by an analysis of trend estimates, which was applied as a tool to identify issues in the data records. It was observed that the trends over global ice-free oceans are generally different among the different data records. Most of these differences are statistically significant. Distinct spatial features are evident in maps of differences in trend estimates, which largely coincide with maxima in standard deviations from the ensemble mean. The penalized maximal F test has been applied to global ice-free ocean and selected land regional anomaly time series, revealing differences in trends to be largely caused by breakpoints in the different data records. The time, magnitude, and number of breakpoints typically differ from region to region and between data records. These breakpoints often coincide with changes in observing systems used for the different data records. The TCWV data records have also been compared with data from a radiosonde archive. For example, at Lindenberg, Germany, and at Yichang, China, such breakpoints are not observed, providing further evidence for the regional imprint of changes in the observing system.