Evaluation of clouds in climate and forecasting models using CloudSat and Calipso data.

点击翻译按钮获取中文摘要

Climate change is one of the great challenges facing the world today. There is compelling evidence that the inexorable increase in 'greenhouse gases' (particularly carbon dioxide) due to human activity is having a warming effect on climate. However, it is very difficult to determine just how much average global surface temperature will rise in future in response to a particular increase in greenhouse gas concentration, and in fact the forecasts vary by a factor of three. One of the major problems stems from clouds. Everyday experience tells us the profound effect the presence of a cloud has on the amount of the sun's energy that reaches the ground, and similarly the fact that cloudy nights tend to be warmer than clear is because the infrared energy emitted by the surface is then nearly balanced by the energy emitted back towards it by the cloud. Exactly the same processes act on large scales, and to calculate surface temperature with any skill we need to know accurately how cloud is distributed around the globe, including its detailed properties such as average droplet size. There are two main difficulties. Firstly, the computer simulations used to predict climate split the atmosphere into large grid-boxes (typically 200 km across and up to 1 km deep), with often only two numbers being used to describe the cloud in each box (e.g. the amount of cloud and the mass of cloud water). This is clearly very crude. Secondly, the information available to test the simulated clouds is from imagers carried on satellites, which cannot see very far into a cloud to determine how it is arranged vertically or to detect one cloud layer beneath another. In this project we will make use of exciting new data from two satellites to be launched by NASA in May 2005. 'CloudSat' carries a cloud radar that works by continually sending short pulses of radio waves downwards. Clouds scatter some of these waves back to the radar, and by timing how long the echo takes to be returned and by measuring its strength, we can calculate the height of the cloud and how much water it contains. As CloudSat orbits the earth it will for the first time be able to infer cloud properties at each height in the atmosphere. The second satellite 'Calipso' carries a lidar and works on the same principle but using light rather than radio waves. The key aspect to this project is to combine the radar and lidar to learn more about the nature of the clouds. The fact that radar is more sensitive to the large cloud particles while lidar is more sensitive to the small means that we can estimate important cloud properties such as the size of ice crystals in cirrus and the rate of drizzle falling from low altitude water clouds (which is important for determining how long the cloud will persist). Between 0 and -40°C, clouds can contain both small liquid droplets and large ice crystals; our results from ground-based lidar show that these clouds are particularly badly simulated by computer models, but with radar and lidar the two components can be easily distinguished and their properties estimated. We will then use all the cloud properties extracted from around a year of global observations to test the clouds in two of the world's best computer models, the Met Office climate model and the ECMWF forecast model. This will be used to highlight problems with the models, and address them by developing new ways to simulate clouds and testing them again against the new observations. Of particular interest will be schemes shortly to be introduced in both models to represent the horizontal cloud structure in a large model grid-box which we will test around the globe for the first time. The resulting improvements in simulated clouds should give us more confidence in predictions of climate change.