The CAUSES project: Clouds Above the United States and Errors at the Surface

 

Author

Cyril Julien Morcrette — Met Office - UK

Category

General topics – Clouds

Description

This project aims to understand and reduce the causes of climate-model warm surface temperature biases over the American Midwest. This will be achieved by evaluating a number of climate models that exhibit the bias using a common approach, which is based on comparison with observations collected in the Southern Great Plains (SGP). Previous work has shown that the surface temperature biases seen in a number of climate models when looking at multi-year simulations are already present within just a few days of simulation. As a result our experimental protocol consists of 3 main experiments. The first experiment uses climate models to mimic a weather forecasting system by producing hindcasts starting from atmospheric analyses. We focus on the spring and summer of 2011 and start a new forecast every 24 hours from April to August. Each forecast is 5 days long. The model column nearest to SGP is then compared to observations. We relate the growth in the surface temperature error to errors in the simulation of the surface radiation and then to the cloud cover and the cloud type. The second experiment consists of simulations starting on the first day of each month of the first half of 2011 and running until the end of August 2011. The third experiment is based on using the climate models to produce 10-year long atmosphere-only simulations. By combining these three experiments we will investigate how those errors first appear, on time-scales of just a few days, and then how they evolve on time-scales of weeks to months. Throughout this project, we will use observations collected at and around the SGP site. So far participants running 10 different model configurations have submitted data to be analysed as part of the project. This poster will summarise progress so far and present some highlight results from the models taking part. These include: CAM5, HadGEM3, ECMWF-IFS, LMDZ, AROME, ARPEGE, CanCM4, CAM5-IPHOC and WRF-with-CAM5-physics using two different land surface models.