Spatial representativeness of ground‐based solar radiation measurements

The validation of gridded surface solar radiation (SSR) data often relies on the comparison with ground‐based in situ measurements. This poses the question on how representative a point measurement is for a larger‐scale surrounding. We use high‐resolution (0.03°) SSR data from the Satellite Application Facility on Climate Monitoring (CM SAF) to study the subgrid spatial variability in all‐sky SSR over Europe and the spatial representativeness of 143 surface sites with homogeneous records for their site‐centered larger surroundings varying in size from 0.25° to 3°, as well as with respect to a given standard grid of 1° resolution. These analyses are done on a climatological annual and monthly mean basis over the period 2001–2005. The spatial variability of the CM SAF data set itself agrees very well with surface measurements in Europe, justifying its use for the present study. The annual mean subgrid variability in the 1° standard grid over European land is on average 1.6% (2.4 W m−2), with maximum of up to 10% in Northern Spain. The annual mean representation error of point values at 143 surface sites with respect to their 1° surrounding is on average 2% (3 W m−2). For larger surroundings of 3°, the representation error increases to 3% (4.8 W m−2). The monthly mean representation error at the surface sites with respect to the 1° standard grid is on average 3.7% (4 W m−2). This error is reduced when site‐specific correction factors are applied or when multiple sites are available in the same grid cell, i.e., three more sites reduce the error by 50%.

[1]  John E. Hay,et al.  An assessment of the mesoscale variability of solar radiation at the earth's surface , 1984 .

[2]  H. Guillard,et al.  A method for the determination of the global solar radiation from meteorological satellite data , 1986 .

[3]  B. Efron.  Better Bootstrap Confidence Intervals , 1987 .

[4]  L. Alados-Arboledas,et al.  Local-Scale Variability of Solar Radiation in a Mountainous Region , 1995 .

[5]  Martin Wild,et al.  Validation of general circulation model radiative fluxes using surface observations , 1995 .

[6]  C. H. Whitlock,et al.  Assessment of the global monthly mean surface insolation estimated from satellite measurements using global energy balance archive data , 1995 .

[7]  Charles N. Long,et al.  Surface measurements of solar irradiance: A study of the spatial correlation between simultaneous measurements at separated sites , 1995 .

[8]  H. Beyer,et al.  Modifications of the Heliosat procedure for irradiance estimates from satellite images , 1996 .

[9]  B. Barkstrom,et al.  Clouds and the Earth's Radiant Energy System (CERES): An Earth Observing System Experiment , 1996 .

[10]  D. W. Nelson,et al.  Optimal Measurement of Surface Shortwave Irradiance Using Current Instrumentation , 1997 .

[11]  Tim P. Barnett,et al.  On the Space–Time Scales of the Surface Solar Radiation Field , 1998 .

[12]  J. Morcrette,et al.  The disposition of radiative energy in the global climate system: GCM-calculated versus observational estimates , 1998 .

[13]  Martin Wild,et al.  Means and Trends of Shortwave Irradiance at the Surface Estimated from Global Energy Balance Archive Data. , 1998 .

[14]  B. McArthur,et al.  Baseline surface radiation network (BSRN/WCRP) New precision radiometry for climate research , 1998 .

[15]  A. Ohmura,et al.  The Global Energy Balance Archive , 1999 .

[16]  R. Perez,et al.  Effective Accuracy of Satellite-Derived Hourly Irradiances , 1999 .

[17]  C. Long,et al.  Identification of clear skies from broadband pyranometer measurements and calculation of downwelling shortwave cloud effects , 2000 .

[18]  Chris A. Glasbey,et al.  Spatio-temporal variability of solar energy across a region: a statistical modelling approach , 2001 .

[19]  J. Schmetz,et al.  AN INTRODUCTION TO METEOSAT SECOND GENERATION (MSG) , 2002 .

[20]  J. Barnard,et al.  A Simple Empirical Equation to Calculate Cloud Optical Thickness Using Shortwave Broadband Measurements , 2004 .

[21]  Alexander P. Trishchenko,et al.  Natural variability and sampling errors in solar radiation measurements for model validation over the Atmospheric Radiation Measurement Southern Great Plains region , 2005 .

[22]  C. Long,et al.  From Dimming to Brightening: Decadal Changes in Solar Radiation at Earth's Surface , 2005, Science.

[23]  Despina Hatzidimitriou,et al.  Global distribution of Earth's surface shortwave radiation budget , 2005, Atmospheric Chemistry and Physics.

[24]  Martin Wild,et al.  Solar radiation budgets in atmospheric model intercomparisons from a surface perspective , 2005 .

[25]  E. Dutton,et al.  Do Satellites Detect Trends in Surface Solar Radiation? , 2004, Science.

[26]  Krista Gaustad,et al.  Estimation of fractional sky cover from broadband shortwave radiometer measurements , 2006 .

[27]  Robert S. Stone,et al.  Decadal variations in surface solar irradiance as observed in a globally remote network , 2006 .

[28]  D. Turner,et al.  A method for continuous estimation of clear‐sky downwelling longwave radiative flux developed using ARM surface measurements , 2008 .

[29]  R. Roebeling,et al.  Operational climate monitoring from space: the EUMETSAT Satellite Application Facility on Climate Monitoring (CM-SAF) , 2008 .

[30]  Alejandro Bodas-Salcedo,et al.  Evaluation of the Surface Radiation Budget in the Atmospheric Component of the Hadley Centre Global Environmental Model (HadGEM1) , 2008 .

[31]  E. Kassianov,et al.  Development and Evaluation of a Simple Algorithm to Find Cloud Optical Depth with Emphasis on Thin Ice Clouds , 2008 .

[32]  Bruce A. Wielicki,et al.  Surface insolation trends from satellite and ground measurements: Comparisons and challenges , 2009 .

[33]  Gert König-Langlo,et al.  Global dimming and brightening: An update beyond 2000 , 2009 .

[34]  Taiping Zhang,et al.  Assessment of BSRN radiation records for the computation of monthly means , 2010 .

[35]  Charles N. Long,et al.  Exploiting diurnal variations to evaluate the ISCCP-FD flux calculations and radiative-flux-analysis-processed surface observations from BSRN, ARM, and SURFRAD , 2010 .

[36]  Richard Müller,et al.  The Role of the Effective Cloud Albedo for Climate Monitoring and Analysis , 2011, Remote. Sens..

[37]  Martin Wild,et al.  Assessment of global dimming and brightening in IPCC-AR4/CMIP3 models and ERA40 , 2011 .

[38]  V. Ramaswamy,et al.  Analysis of the biases in the downward shortwave surface flux in the GFDL CM2.1 general circulation model , 2011 .

[39]  T. Andrews,et al.  An update on Earth's energy balance in light of the latest global observations , 2012 .

[40]  Sunny Sun-Mack,et al.  Uncertainty Estimate of Surface Irradiances Computed with MODIS-, CALIPSO-, and CloudSat-Derived Cloud and Aerosol Properties , 2012, Surveys in Geophysics.

[41]  M. Journée,et al.  Sensitivity to spatio-temporal resolution of satellite-derived daily surface solar irradiation , 2012 .

[42]  C. Schär,et al.  The global energy balance from a surface perspective , 2013, Climate Dynamics.

[43]  Jörg Trentmann,et al.  Remote sensing of solar surface radiation for climate monitoring — the CM-SAF retrieval in international comparison , 2012 .

[44]  Taiping Zhang,et al.  The validation of the GEWEX SRB surface shortwave flux data products using BSRN measurements: A systematic quality control, production and application approach , 2013 .

[45]  M. Wild,et al.  Testing the homogeneity of short-term surface solar radiation series in Europe , 2013 .

[46]  Martin Wild,et al.  Validation and stability assessment of the monthly mean CM SAF surface solar radiation dataset over Europe against a homogenized surface dataset (1983–2005) , 2013 .