Articles | Volume 12, issue 2
https://doi.org/10.5194/gmd-12-805-2019
https://doi.org/10.5194/gmd-12-805-2019
Model experiment description paper
 | 
21 Feb 2019
Model experiment description paper |  | 21 Feb 2019

A benchmark for testing the accuracy and computational cost of shortwave top-of-atmosphere reflectance calculations in clear-sky aerosol-laden atmospheres

Jeronimo Escribano, Alessio Bozzo, Philippe Dubuisson, Johannes Flemming, Robin J. Hogan, Laurent C.-Labonnote, and Olivier Boucher

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Cited articles

Barlakas, V.: A New Three–Dimensional Vector Radiative Transfer Model and Applications to Saharan Dust Fields, PhD thesis, University of Leipzig, 108 pp., 2016. a
Barlakas, V., Macke, A., and Wendisch, M.: SPARTA – Solver for Polarized Atmospheric Radiative Transfer Applications: Introduction and application to Saharan dust fields, J. Quant. Spectrosc. Ra., 178, 77–92, https://doi.org/10.1016/j.jqsrt.2016.02.019, 2016. a
Benedetti, A., Reid, J. S., Knippertz, P., Marsham, J. H., Di Giuseppe, F., Rémy, S., Basart, S., Boucher, O., Brooks, I. M., Menut, L., Mona, L., Laj, P., Pappalardo, G., Wiedensohler, A., Baklanov, A., Brooks, M., Colarco, P. R., Cuevas, E., da Silva, A., Escribano, J., Flemming, J., Huneeus, N., Jorba, O., Kazadzis, S., Kinne, S., Popp, T., Quinn, P. K., Sekiyama, T. T., Tanaka, T., and Terradellas, E.: Status and future of numerical atmospheric aerosol prediction with a focus on data requirements, Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, 2018. a, b
Bocquet, M., Elbern, H., Eskes, H., Hirtl, M., Žabkar, R., Carmichael, G. R., Flemming, J., Inness, A., Pagowski, M., Pérez Camaño, J. L., Saide, P. E., San Jose, R., Sofiev, M., Vira, J., Baklanov, A., Carnevale, C., Grell, G., and Seigneur, C.: Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models, Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, 2015. a
Bodhaine, B. A., Wood, N. B., Dutton, E. G., and Slusser, J. R.: On Rayleigh optical depth calculations, J. Atmos. Ocean. Tech., 16, 1854–1861, https://doi.org/10.1175/1520-0426(1999)016<1854:ORODC>2.0.CO;2, 1999. a
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Accurate shortwave radiance computations are becoming increasingly important for some applications in atmospheric composition. In this work we propose a benchmark protocol and dataset to asses the accuracy and computing runtime of radiance calculations of radiative transfer models. It is applied to four models, showing the potential of this benchmark to evaluate the model performance under a variety of atmospheric conditions, viewing geometries, aerosol loading, and optical properties.