Research And Application Of A New Cloud-Radiative Scheme In Climate Models

Clouds play an important role in the atmospheric radiative transfer. However, there is stillgreat uncertainty in cloud-radiative transfer process within traditional climate models,primarily due to the low spatial resolution and lack of precise sub-grid cloud structure. As thefast development of climate models, cloud-radiative process becomes more and more abottleneck to the model development. So, it is of great importance to describe sub-grid cloudstructures and their radiative effects more realistically. In this thesis, a new cloud-radiativeframework, named McICA, is introduced into the National Climate Center's Global ClimateModel, called BCC_AGCM2.0.1. The McICA framework is suitable for improving therepresentation of sub-grid cloud-radiative process because it has the ability to achieve morerealistic sub-grid cloud structures, as well as keeps the radiative calculation precise withoutsignificantly increasing the CPU time. Unfortunately, one drawback of the McICA frameworkis it will introduce some random noise, which may degrade the modeled climate.The impact of McICA noise on the modeled climate and impact of replacing the oldcloud-radiative scheme with the new one are studied in this thesis. In addition, potential waysof better representing cloud overlap structures and decrease biases in modeled total cloudfractions are studied with data from a global high-resolution cloud resolving model. The mainconclusions are as follows:1. There is a minor perturbation of modeled climate within McICA samples, and themodeled climate fields are impacted very little by McICA noise, with global mean bias atthe order of0.01%compared to the reference ICA results. Good agreement betweenMcICA and ICA results is also illustrated from zonal mean, vertical, and domaindistributions of variables. So, it's highly reliable to use the McICAcloud-radiation schemein BCC_AGCM2.0.1to do climate researches. Because random noises have little impacton the modeling, the modeling ability of BCC_AGCM2.0.1still depends on its physicalparameterization and dynamic framework improvements.2. The introduction of McICA framework in BCC_AGCM2.0.1leads to a greatimprovement in clear-sky and cloudy-sky TOA radiative budget of the Earth-atmospheresystem, with the OLR bias reduced from about6.5W/m2to2.8W/m2, and the TOA netshortwave flux bias reduced from about5.9W/m2to3.7W/m2. The use of a new cloud vertical overlap assumption results in a sharp decrease in total cloud fraction from about8%to only1.4%. The cold bias in troposphere is somewhat corrected by the new scheme,and at the same time the bias of specific humidity in the tropics is reduced by about1/3.With the improvement in temperature and specific humidity in the low-latitude area, themodeled tropical convective movements are also more realistic. The global distributionand seasonal variation of surface temperature, sea surface pressure and precipitation arecomparable between the new and old scheme.3. A set of climatological cloud overlap parameter (decorrelation depth) data or aparameterized relationship between cloud overlap parameter and other meteorologicalvariables can be used to represent the spacialy different characters of cloud overlap andreduce biases in the modeled total cloud fraction. These provide two alternatives toimprove the modeling of cloud fractions and radiation within the McICA cloud-raditionframework.