Confronting Arctic Troposphere, Clouds, and Surface Energy Budget Representations in Regional Climate Models with Observations
Six state-of-the-art regional climate models (RCMs) are evaluated in comparison to observations from the Arctic Clouds during Summer Experiment (ACSE) field campaign from July to October 2014. The results indicate that the differences in the RCMs in the surface energy balance are a result of the individual RCMs treatment of cloud and cloud-radiative interactions. Differences in radiative and turbulent fluxes were found to be relatively larger but are the result of invoking compensating errors.
The results of this study provide one of the first analyses in diagnosing the state of atmospheric modeling of the Arctic in over a decade, providing a continuing benchmark as to the evolution and progress in atmospheric modeling of the Arctic spanning multiple decades. The coordinated effort of individual RCM groups for this study will also provide the framework for future larger studies using observations of the Arctic climate system from the current year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The combined effort of the observations and the evaluation of RCMs will provide for the development and refinement of future modeling capabilities resulting in a better understanding and prediction of the Arctic climate system.
A coordinated regional climate model (RCM) evaluation and intercomparison project based on observations from a July–October 2014 trans‐Arctic Ocean field experiment (ACSE‐Arctic Clouds during Summer Experiment) has been completed. Six state‐of‐the‐art RCMs were constrained with common reanalysis lateral boundary forcing and upper troposphere nudging techniques to explore how the RCMs represented the evolution of the surface energy budget (SEB) and their relation to cloud properties. The results indicate that the main reasons for the modeled differences in the SEB components are a direct consequence of the RCM treatment of cloud and cloud‐radiative interactions. The RCMs could be separated into groups by their overestimation or underestimation of cloud liquid. While radiative and turbulent heat flux errors were relatively large, they often invoke compensating errors. In addition, having the surface sea‐ice concentrations constrained by the reanalysis or satellite observations limited how errors in the modeled radiative fluxes could affect the SEB and ultimately the surface evolution and its coupling with lower tropospheric mixing and cloud properties. Many of these results are consistent with RCM biases reported in studies over a decade ago. One of the six models was a fully coupled ocean‐ice‐atmosphere model. Despite the biases in overestimating cloud liquid, and associated SEB errors due to too optically thick clouds, its simulations were useful in understanding how the fully coupled system is forced by, and responds to, the SEB evolution. Moving forward, it is recommended that the development of RCM studies need to consider the fully coupled climate system.