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Accurate solar irradiance data are not only of particular importance for the assessment of the radiative forcing of the climate system, but also absolutely necessary for efficient planning and operation of solar energy systems. Within the European project Heliosat-3, a new type of solar irradiance scheme is developed. This new type will be based on radiative transfer models (RTM) using atmospheric parameter information retrieved from the Meteosat Second Generation (MSG) satellite (clouds, ozone, water vapour) and the ERS-2/ENVISAT satellites (aerosols, ozone).This paper focuses on the description of the clear-sky module of the new scheme, especially on the integrated use of a radiative transfer model. The linkage of the clear-sky module with the cloud module is also briefly described in order to point out the benefits of the integrated RTM use for the all-sky situations. The integrated use of an RTM within the new Solar Irradiance Scheme SOLIS is applied by introducing a new fitting function called the modified Lambert -Beer (MLB) relation. Consequently, the modified Lambert -Beer relation and its role for an integrated RTM use are discussed. Comparisons of the calculated clear-sky irradiances with ground-based measurements and the current clear-sky module demonstrate the advantages and benefits of SOLIS. Since SOLIS can provide spectrally resolved irradiance data, it can be used for different applications. Beside improved information for the planning of solar energy systems, the calculation of photosynthetic active radiation, UV index, and illuminance is possible. D

Accurate solar surface irradiance data is a prerequisite for an efficient planning and operation of solar energy systems. Further, it is essential for climate monitoring and analysis. Recently, the demand on information about spectrally resolved solar surface irradiance has grown. As surface measurements are rare, satellite derived information with high accuracy might fill this gap. This paper describes a new approach for the retrieval of spectrally resolved solar surface irradiance from satellite data. The method combines a eigenvector-hybrid look-up table approach for the clear sky case with satellite derived cloud transmission (Heliosat method). The eigenvector LUT approach is already used to retrieve the broadband solar surface irradiance of data sets provided by the Climate Monitoring Satellite Application Facility (CM-SAF). This paper describes the extension of this approach to wavelength bands and the combination with spectrally resolved cloud transmission values derived with radiative transfer corrections of the broadband cloud transmission. Thus, the new approach is based on radiative transfer modeling and enables the use of extended information about the atmospheric state, among others, to resolve the effect of water vapor and ozone absorption bands. The method is validated with spectrally resolved measurements from two sites in Europe and by comparison with radiative transfer calculations. The validation results demonstrate the ability of the method to retrieve accurate spectrally resolved irradiance from satellites. The accuracy is in the range of the uncertainty of surface Remote Sens. 2012, 4 623 measurements, with exception of the UV and NIR (≥ 1200 nm) part of the spectrum, where higher deviations occur.

Downward long and short wave incoming irradiances play a key role in the radiation budget at the earth surface. The monitoring of those parameters is essential for the understanding of the basic mechanisms involved in climate change, such as the greenhouse effect, the global dimming, the change in cloud cover and precipitations, etc. The use of geostationary satellite observations becomes crucial, since they allow the retrieval of irradiance at the surface, with the best spatial and temporal coverage. Three of Eumetsat decentralized Satellite Application Facilities (SAFs) are retrieving on an operational basis the surface solar and the downward long wave radiation from Meteosat images. This study presents a common validation of these SAFs radiation products against ground data from 8 stations covering four months representative of the annual declination variation. The overall conclusion is that the products of the different facilities are comparable in terms of bias and standard deviation. The surface solar irradiance is retrieved with a standard deviation of 80-100 (W m-2) and negligible bias, and the downward long wave irradiance with a standard deviation of 25 (W m-2) with a slight site-dependent bias

Cloud properties and the Earth's radiation budget are defined as essential climate variables by the Global Climate Observing System (GCOS). The cloud albedo is a measure for the portion of solar radiation reflected back to space by clouds. This information is essential for the analysis and interpretation of the Earth's radiation budget and the solar surface irradiance. We present and discuss a method for the production of the effective cloud albedo and the solar surface irradiance based on the visible channel (0.45-1 µm) on-board of the Meteosat satellites. This method includes a newly developed self-calibration approach and has been used to generate a 23-year long continuous and validated climate data record of the effective cloud albedo and the solar surface irradiance. Using this climate data record we demonstrate the ability of the method to generate the two essential climate variables in high accuracy and homogeneity. Further on, we discuss the role of the cloud albedo within climate monitoring and analysis. We found trends with opposite sign in the observed effective cloud albedo resulting in positive trends in the solar surface irradiance over ocean and partly negative trends over land. Ground measurements are scarce over the ocean and thus satellite-derived effective cloud albedo and solar surface irradiance constitutes a unique observational data source. Within this scope it has to be considered that the ocean is the main energy reservoir of the Earth, which emphasises the role of Remote Sens. 2011, 3 2306 satellite-observed effective cloud albedo and derived solar surface irradiance as essential climate variables for climate monitoring and analysis.

Solar surface irradiance (SIS) is an essential variable in the radiation budget of the Earth. Climate data records (CDR's) of SIS are required for climate monitoring, for climate model evaluation and for solar energy applications. A 23 year long continuous and validated SIS CDR based on the visible channel (0.45-1 µm) of the MVIRI instruments onboard the first generation of Meteosat satellites has recently been generated using a climate version of the well established Heliosat method. This version of the Heliosat method includes a newly developed self-calibration algorithm and an improved algorithm to determine the clear sky reflection. The climate Heliosat version is also applied to the visible narrow-band channels of SEVIRI onboard the Meteosat Second Generation Satellites (2004-present). The respective channels are observing the Earth in the wavelength region at about 0.6 µm and 0.8 µm. SIS values of the overlapping time period are used to analyse whether a homogeneous extension of the MVIRI CDR is possible with the SEVIRI narrowband channels. It is demonstrated that the spectral differences between the used visible channels leads to significant differences in the solar surface irradiance in specific regions. Especially, over vegetated areas the reflectance exhibits a high spectral dependency resulting in large differences in the retrieved SIS. The applied self-calibration method alone is not able to compensate the spectral differences of the channels. Furthermore, the extended range of the input values (satellite counts) enhances the cloud detection of the SEVIRI instruments resulting in lower values for SIS, on average. Our findings have implications Remote Sens. 2011, 3 1030 for the application of the Heliosat method to data from other geostationary satellites (e.g., GOES, GMS). They demonstrate the need for a careful analysis of the effect of spectral and technological differences in visible channels on the retrieved solar irradiance.

Global precipitation monitoring is essential for understanding the earth’s water and energy cycle. Therefore, usage of satellite-based precipitation data is necessary where in situ data are rare. In addition, atmospheric-model-based reanalysis data feature global data coverage and offer a full catalog of atmospheric variables including precipitation. In this study, two model-based reanalysis products, the interim reanalysis by the European Centre for Medium-Range Weather Forecasts (ERA-Interim) and NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA), as well as two satellite-based datasets obtained by the Global Precipitation Climatology Centre (GPCP) and Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) are evaluated. The evaluation is based on monthly precipitation in the tropical Pacific Ocean during the time period 1989–2005. Rain-gauge atoll station data provided by the Pacific Rainfall Database (PACRAIN) are used as ground-based reference. It is shown that the analyzed precipitation datasets offer temporal correlations ranging from 0.7 to 0.8 for absolute amounts and from 0.6 to 0.75 for monthly anomalies. Average monthly deviations are in the range of 20%–30%. GPCP offers the highest correlation and lowest monthly deviations with reference to PACRAIN station data. The HOAPS precipitation data perform in the range of the reanalysis precipitation datasets. In high native spatial resolution, HOAPS reveals deficiencies owing to its relatively sparse temporal coverage. This result emphasizes that temporal coverage is critical for controlling the performance of precipitation monitoring. Both reanalysis products show similar systematic behaviors in overestimating small and medium precipitation amounts and underestimating high amounts.