Abstract
The performance of 20 models from the Atmospheric Model Intercomparison Project (AMIP) was evaluated concerning surface radiation over the tropical oceans (30° S–30° N) from 1979 to 2000. The model ensemble mean of the net surface shortwave radiation (QSW) was underestimated compared to the International Satellite Cloud Climatology Project (ISCCP) data by 4 W m−2. On the other hand, net longwave radiation (QLW) was overestimated by 4 W m−2, leading to an underestimation of the net surface radiation (Qrad) by 8 W m−2. The most prominent bias in the Qrad appears to be over regions of low-level clouds in the off-equatorial eastern Pacific, eastern Atlantic, and the south-eastern Indian Ocean. The root means squared error of QLW was larger than that of QSW in 17 out of 20 AMIP models. Overestimation of the total cloud cover and atmospheric humidity contributed to the underestimation of Qrad. In general, models with higher horizontal resolutions performed slightly better than those with coarser horizontal resolutions, although some systematic bias persists in all models and in all seasons, in particular, in regions of low-level clouds for QLW, and high-level clouds for QSW. The ensemble mean performed better than most models, but two high-resolution models (GFDL-HIRAM-C180 and GFDL-HIRAM-C360) outperform the model ensemble.
Highlights
The spatio-temporal distribution of surface energy plays an essential role in determining the weather and climate on our planet (e.g., [1])
We provide an assessment of 20 atmospheric global climate models (AGCMs) participating in the Atmospheric
In the absence of cloud cover information at high, mid, and low-levels from the Atmospheric Model Intercomparison Project (AMIP) simulations, we only show how the bias in QLW and QSW varies with the bias in total cloud cover
Summary
The spatio-temporal distribution of surface energy plays an essential role in determining the weather and climate on our planet (e.g., [1]). We evaluate AMIP models concerning their ability to capture surface radiative fluxes compared to the satellite and in situ observations over the tropical oceans. The global models with coarse horizontal resolutions may not capture the convection and clouds over the tropical oceans This is expected to lead to bias in the surface radiation that is influenced by the atmospheric as well as surface properties. In addition to the ISCCP data, we analyzed observations of surface radiative fluxes from moored buoys (Figure 1) that include the Tropical Atmosphere Ocean (TAO) array (63 buoys) in the Pacific, the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) array (18 buoys) in the Atlantic, and the Research Moored Array for African-Asian-Australian.
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