Decomposing observed radiative flux changes during the A-Train satellite era

Given decades-long measurements by CERES, it is understood that radiative fluxes at the top-of-atmopshere (TOA) and surface experience considerable monthly and inter-annual variations. This drives changes in global surface temperatures and the hydrological cycle, respectively. Measurements of the radiative fluxes alone do not provide much insight into the causes of this variability. However, by using the wide variety of collocated measurements from the A-Train constellation of satellites, it is possible to decompose these radiative responses into contributions from changes in individual radiatively-relevant climate variables to better understand governing processes. Using observation-based radiative kernels derived from CloudSat/CALIPSO measurements, we decompose net TOA and surface radiative flux anomalies into contributions from changes in temperature, water vapor, surface albedo, clouds and forcing terms, using measurements from a variety of instruments within the A-train constellation. We further decompose cloud radiative flux anomalies into contributions from individual cloud regimes, as defined by MODIS observations, and highlight the relative contributions of high and low cloud changes to net TOA and surface radiative fluxes overall.

This framework can be applied consistently to observations and model simulations. We therefore derive temperature-mediated radiative feedbacks from the observed radiative flux anomalies and compare them to short-term and long-term feedbacks in CMIP5 models to investigate potential emergent constrains on the TOA and surface energy budgets.