Evaluation of Interannual Variability of Cloud Liquid Water Path in Climate Models Using a Multidecadal Record of Passive Microwave Observations

Cloud Liquid Water Path (CLWP) is an important variable affected by changes in the climate system. The nature of its changes within a changing climate, and the connection of these changes to cloud-climate feedbacks, however, are not well-understood at present. The Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) climatology, an updated version of the University of Wisconsin (UWisc) CLWP dataset, seamlessly blends observations from many different passive microwave sensors over the past 26 years in order to create a robust, long-term record of CLWP. With this dataset, we are able to observe trends and interannual variability in CLWP with some degree of statistical significance. Present day climate models (those comprising the CMIP3 and CMIP5 collections) aim to accurately represent cloud feedbacks and, directly related to this, capture interannual variability in several different cloud variables including CLWP. In this work, we present the long-term evolution of CLWP in a few characteristic regions around the globe using the MAC-LWP dataset, and compare it to the simulated evolution of CLWP in the CMIP3 and CMIP5 models. The extent to which present-day GCM's accurately portray interannual and long-term CLWP changes will be discussed.