Using retrieved cloud properties to investigate their radiative impact

The cloud climate feedback has long been recognised as one of the greatest sources of uncertainty of future climate predictions. In order to narrow this uncertainty models should be evaluated in terms of cloud properties and their radiative sensitivity to those properties. Over recent years methods have been developed to retrieve cloud properties (ice and liquid water content), therefore allowing this evaluation. This thesis focuses on model validation by using retrieved cloud property information, from active remote sensing instruments at Lindenberg in Germany, as input to a radiative transfer scheme. The radiative budget of the atmosphere is simulated and can be used as a tool to assess model cloud representation and its radiative response to cloud properties. First, the radiation scheme is assessed under cloud-free conditions. The clear sky top of atmosphere (TOA) radiation budget can be modelled with an average difference of 15 W m -2 in the shortwave (SW) and 5 W m -2 in the longwave (LW) of observations. The surface radiative ftuxes are simulated with an average difference of 30 W m -2 in the SW and 12 W m-2 in the LW. After testing the sensitivity of the radiation simulations to cloud property retrieval errors, the radiation budget in the presence of cloud is calculated. Cloudy sky simulations agree with observations with an average difference of 10 W m-2 at the TOA in both the SW and LW, and at the surface, 1 W m -2 in the SW and 6 W m -2 in the LW, although the variability is larger than this indicates. A positive bias is found in the OLR simulations which is partly attributed to un-observed thin ice clouds, which consist of small particles that are beyond the sensitivity of the radar. Simulations show that these clouds reduce the OLR by -4 W m -2 , explaining a portion of this discrepancy. The cloud property data and the radiative simulations are used to assess the cloud representation, and cloud radiative response, in the ECMWF model. The temperature dependant parameterisation of mixed phase clouds is compared with observations and found to be unrealistic. The radiative impact of this error reduces the magnitude of the SW and LW simulated radiative effect by approximately 20%.EThOS - Electronic Theses Online ServiceGBUnited Kingdo