Forcing and Responses of the Surface Energy Budget at Summit, Greenland

Energy exchange at the Greenland Ice Sheet surface governs surface temperature variability, a factor critical for representing increasing surface melt extent, which portends a rise in global sea level. A comprehensive set of cloud, tropospheric, near-surface and sub-surface measurements at Summit Station is utilized to determine the driving forces and subsequent responses of the surface energy budget (SEB). This budget includes radiative, turbulent, and ground heat fluxes, and ultimately controls the evolution of surface temperature. At Summit Station, clouds radiatively warm the surface in all months with an annual average cloud radiative forcing value of 33 W m−2, largely driven by the occurrence of liquid-bearing clouds. The magnitude of the surface temperature response is dependent on how turbulent and ground heat fluxes modulate changes to radiative forcing. Relationships between forcing terms and responding surface fluxes show that changes in the upwelling longwave radiation compensate for 65–85% (50– 60%) of the total change in radiative forcing in the winter (summer). The ground heat flux is the second largest response term (16% annually), especially during winter. Throughout the annual cycle, the sensible heat flux response is comparatively constant (9%) and latent heat flux response is only 1.5%, becoming more of a factor in modulating surface temperature responses during the summer. Combining annual cycles of these responses with cloud radiative forcing results, clouds warm the surface by an estimated 7.8◦C annually. A reanalysis product (ERA-I), operational model (CFSv2), and climate model (CESM) are evaluated utilizing the comprehensive set of SEB observations and process-based relationships. Annually, surface temperatures in each model are warmer than observed with overall poor representation of the coldest surface temperatures. Process-based relationships between different SEB flux terms offer insight into how well a modeling framework represents physical processes and the ability to distinguish errors in forcing versus those in physical representation. Such relationships convey that all three models underestimate the response of surface temperatures to changes in radiative forcing. These results provide a method to expose model deficiencies and indicate the importance of representing surface, sub-surface and boundary-layer processes when portraying cloud impacts on surface temperature variability