Richard Mueller
Deutscher Wetterdienst
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Featured researches published by Richard Mueller.
Remote Sensing | 2012
Richard Mueller; Tanja Behrendt; Annette Hammer; Axel Kemper
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 measurements, with exception of the UV and NIR ( ≥ 1200 nm) part of the spectrum, where higher deviations occur.
Journal of Applied Meteorology and Climatology | 2013
Uwe Pfeifroth; Richard Mueller; Bodo Ahrens
AbstractGlobal 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. ...
Remote Sensing | 2011
Richard Mueller; Jörg Trentmann; Christine Träger-Chatterjee; Rebekka Posselt; Reto Stöckli
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 (1983–2005) 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 satellite-observed effective cloud albedo and derived solar surface irradiance as essential climate variables for climate monitoring and analysis.
Theoretical and Applied Climatology | 2014
Isaac Moradi; Richard Mueller; Richard Perez
Solar radiation is an important variable for studies related to solar energy applications, meteorology, climatology, hydrology, and agricultural meteorology. However, solar radiation is not routinely measured at meteorological stations; therefore, it is often required to estimate it using other techniques such as retrieving from satellite data or estimating using other geophysical variables. Over the years, many models have been developed to estimate solar radiation from other geophysical variables such as temperature, rainfall, and sunshine duration. The aim of this study was to evaluate six of these models using data measured at four independent worldwide networks. The dataset included 13 stations from Australia, 25 stations from Germany, 12 stations from Saudi Arabia, and 48 stations from the USA. The models require either sunshine duration hours (Ångstrom) or daily range of air temperature (Bristow and Campbell, Donatelli and Bellocchi, Donatelli and Campbell, Hargreaves, and Hargreaves and Samani) as input. According to the statistical parameters, Ångstrom and Bristow and Campbell indicated a better performance than the other models. The bias and root mean square error for the Ångstrom model were less than 0.25 MJ m2 day−1 and 2.25 MJ m2 day−1, respectively, and the correlation coefficient was always greater than 95 %. Statistical analysis using Student’s t test indicated that the residuals for Ångstrom, Bristow and Campbell, Hargreaves, and Hargreaves and Samani are not statistically significant at the 5 % level. In other words, the estimated values by these models are statistically consistent with the measured data. Overall, given the simplicity and performance, the Ångstrom model is the best choice for estimating solar radiation when sunshine duration measurements are available; otherwise, Bristow and Campbell can be used to estimate solar radiation using daily range of air temperature.
Remote Sensing of Environment | 2004
Richard Mueller; K.F. Dagestad; Pierre Ineichen; Marion Schroedter-Homscheidt; Sylvain Cros; Dominique Dumortier; R. Kuhlemann; Jan Asle Olseth; G. Piernavieja; Christian Reise; Lucien Wald; Detlev Heinemann
Remote Sensing of Environment | 2012
Rebekka Posselt; Richard Mueller; Reto Stockli; Jörg Trentmann
Remote Sensing | 2011
Rebekka Posselt; Richard Mueller; Reto Stöckli; Jörg Trentmann
Solar Energy | 2009
Isaac Moradi; Richard Mueller; Bohloul Alijani; Gholam Ali Kamali
Remote Sensing of Environment | 2014
Rebekka Posselt; Richard Mueller; Jörg Trentmann; Reto Stockli; Mark A. Liniger
Solar Energy | 2006
Marco Girodo; Richard Mueller; Detlev Heinemann