Assessment of BSRN radiation records for the computation of monthly means

Roesch, Andreas; Wild, Martin; Ohmura, Atsumu; Dutton, Ellsworth G; Long, Charles; Zhang, Taiping

doi:10.5194/amt-4-339-2011

Cited by 157 publications

(92 citation statements)

References 18 publications

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“…Following the recommendations of Roesch et al (2011), only the BSRN measurements were kept which obey the following constraints: Roesch et al (2011) note a percentage of missing data of 4 % for global irradiance and 13 % for direct irradiance for all studied BSRN data.…”

Section: Bsrn Data For Validationmentioning

confidence: 99%

McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions

et al. 2013

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A new fast clear-sky model called McClear was developed to estimate the downwelling shortwave direct and global irradiances received at ground level under clear skies. It is a fully physical model replacing empirical relations or simpler models used before. It exploits the recent results on aerosol properties, and total column content in water vapour and ozone produced by the MACC project (Monitoring Atmosphere Composition and Climate). It accurately reproduces the irradiance computed by the libRadtran reference radiative transfer model with a computational speed approximately 10⁵ times greater by adopting the abaci, or look-up table, approach combined with interpolation functions. It is therefore suited for geostationary satellite retrievals or numerical weather prediction schemes with many pixels or grid points, respectively. McClear irradiances were compared to 1 min measurements made in clear-sky conditions at several stations within the Baseline Surface Radiation Network in various climates. The bias for global irradiance comprises between −6 and 25 W m⁻². The RMSE ranges from 20 W m⁻² (3% of the mean observed irradiance) to 36 W m⁻² (5%) and the correlation coefficient ranges between 0.95 and 0.99. The bias for the direct irradiance comprises between −48 and +33 W m⁻². The root mean square error (RMSE) ranges from 33 W m⁻² (5%) to 64 W m⁻² (10%). The correlation coefficient ranges between 0.84 and 0.98. This work demonstrates the quality of the McClear model combined with MACC products, and indirectly the quality of the aerosol properties modelled by the MACC reanalysis

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Section: Bsrn Data For Validationmentioning

confidence: 99%

McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions

et al. 2013

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“…The quality of the downwelling shortwave (SW) and longwave (LW) fluxes is tested following the recommendation of the Baseline Surface Radiation Network (BSRN; test version 2.0; Roesch et al, 2011). Additional semi-automatic controls were developed and applied to SW irradiances in order to reject data collected when the sun tracker failed (used for the direct and diffuse SW radiation measurements) and to remove values that are inconsistent between measured global SW fluxes and global SW fluxes calculated from direct and diffuse measured ones.…”

Section: Specific Computation For Advanced Meteorological Variablesmentioning

confidence: 99%

ReOBS: a new approach to synthesize long-term multi-variable dataset and application to the SIRTA supersite

Chiriaco

Dupont

Badosa

et al. 2018

Earth Syst. Sci. Data

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Abstract.A scientific approach is presented to aggregate and harmonize a set of 60 geophysical variables at hourly timescale over a decade, and to allow multiannual and multi-variable studies combining atmospheric dynamics and thermodynamics, radiation, clouds and aerosols from ground-based observations. Many datasets from ground-based observations are currently in use worldwide. They are very valuable because they contain complete and precise information due to their spatio-temporal co-localization over more than a decade. These datasets, in particular the synergy between different type of observations, are under-used because of their complexity and diversity due to calibration, quality control, treatment, format, temporal averaging, metadata, etc. Two main results are presented in this article: (1) a set of methods available for the community to robustly and reliably process ground-based data at an hourly timescale over a decade is described and (2) a single netCDF file is provided based on the SIRTA supersite observations. This file contains approximately 60 geophysical variables (atmospheric and in ground) hourly averaged over a decade for the longest variables. The netCDF file is available and easy to use for the community. In this article, observations are "re-analyzed". The prefix "re" refers to six main steps: calibration, quality control, treatment, hourly averaging, homogenization of the formats and associated metadata, as well as expertise on more than a decade of observations. In contrast, previous studies (i) took only some of these six steps into account for each variable, (ii) did not aggregate all variables together in a single file and (iii) did not offer an hourly resolution for about 60 variables over a decade (for the longest variables). The approach described in this article can be applied to different supersites and to additional variables. The main implication of this work is that complex atmospheric observations are made readily available for scientists who are non-experts in measurements. The dataset from SIRTA observations can be downloaded at http://sirta.ipsl.fr/reobs.html (last access: April 2017) (Downloads tab, no password required) under https://doi

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“…To ensure a high quality of the reference data set, only those BSRN measurements that pass the limit tests are considered in the calculation of the daily and monthly averages. To derive monthly-and daily-averaged values from the surface measurements, the method M7 proposed by [66] was employed to reduce the impact of missing values. The uncertainty of the derived monthly means is on average ±8 W/m 2 [28].…”

Section: Reference Data For Validationmentioning

confidence: 99%

Digging the METEOSAT Treasure—3 Decades of Solar Surface Radiation

et al. 2015

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Solar surface radiation data of high quality is essential for the appropriate monitoring and analysis of the Earth's radiation budget and the climate system. Further, they are crucial for the efficient planning and operation of solar energy systems. However, well maintained surface measurements are rare in many regions of the world and over the oceans. There, satellite derived information is the exclusive observational source. This emphasizes the important role of satellite based surface radiation data. Within this scope, the new satellite based CM-SAF SARAH (Solar surfAce RAdiation Heliosat) data record is discussed as well as the retrieval method used. The SARAH data are retrieved with the sophisticated SPECMAGIC method, which is based on radiative transfer modeling. The resulting climate data of solar surface irradiance, direct irradiance (horizontal and direct normal) and clear sky irradiance are covering 3 decades. The SARAH data set is validated with surface measurements of the Baseline Surface Radiation Network (BSRN) and of the Global Energy and Balance Archive (GEBA). Comparison with BSRN data is performed in order to estimate the accuracy and precision of the monthly and daily means of solar surface irradiance.The SARAH solar surface irradiance shows a bias of 1.

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Assessment of BSRN radiation records for the computation of monthly means

Cited by 157 publications

References 18 publications

McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions

McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions

ReOBS: a new approach to synthesize long-term multi-variable dataset and application to the SIRTA supersite

Digging the METEOSAT Treasure—3 Decades of Solar Surface Radiation

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