Tropical Clouds and TOA Cloud Radiative Effects in the CMIP5 Models

This study investigates the CMIP5 AMIP simulations of three-dimensional cloud distribution and top-of-atmosphere (TOA) cloud radiative effects (CREs) in the tropics, with the focus on their climatology and climate variations associated with a leading natural climate variability – ENSO. The CMIP5 AMIP clouds are assessed using the ISCCP and CALIPSO satellite simulator output from the CFMIP Observation Simulator Package. The satellite observations used to evaluate the CMIP5 model simulations include the CERES EBAF TOA radiative fluxes, ISCCP cloud histogram of cloud top pressure and optical thickness, GOCCP cloud fraction, and AIRS relative humidity. To quantify the sensitivity of the cloud radiative effects to cloud fraction changes, a radiative transfer model is used to derive shortwave and longwave cloud radiative kernels for each tropical grid and each calendar month. Such cloud radiative kernels reveal the quantitative roles of cloud amount, optical thickness and height in contributing to the TOA CREs, and facilitate an in-depth quantitative comparison between the CMIP5 AMIP simulations and observations.

Results show that while the CMIP5 models simulate the tropical TOA CREs reasonably well, they are rather problematic in representing tropical clouds. The good simulations of the TOA CREs are often a result of compensating errors between different cloud processes. Climatologically, the CMIP5 models produce considerably less yet optically thicker clouds than the observed. The models particularly show strong underestimation of mid- and low-level clouds. While the tropical mean high-level clouds in the majority of the models are moderately less than that of the observed, the models consistently produce less high clouds over the Maritime continent and more high clouds over the western tropical Indian Ocean and subtropical Pacific trade cumulus regions. The reasonably good model simulations of the tropical mean TOA CREs are essentially a result of compensating errors over different tropical dynamical regimes and different cloud regimes. The model biases in climatology strongly affect the model simulations of climate variability. Taking ENSO as an example, the CMIP5 models consistently underestimate the TOA CRE anomalies over the Maritime Continent due to the notable model underestimation of high clouds there. In the central tropical Pacific, while the CMIP5 models simulate the TOA shortwave and longwave CRE anomalies fairly well, they are unfortunately a result of compensating errors between an underestimation of CRE changes from thin high clouds and an overestimation of CRE changes from medium and thick high clouds.