Wednesday, November 14, 2012

New paper shows models significantly underestimate cooling from clouds

A new paper published in Geophysical Research Letters compares satellite observations of clouds to the predictions of five climate models and finds that all models significantly underestimate total cloud cover and low cloud amount [each underestimated by up to 13%]. Other research has shown that total cloud cover and low clouds act to cool the climate. Thus, the models predict excessive warming due to significant underestimates of cloud cover.

As Dr. Roy Spencer points out in his book
"The most obvious way for warming to be caused naturally is for small, natural fluctuations in the circulation patterns of the atmosphere and ocean to result in a 1% or 2% decrease in global cloud cover. Clouds are the Earth’s sunshade, and if cloud cover changes for any reason, you have global warming — or global cooling."

Key Points
  • To evaluate the cloud vertical structure of models using CALIPSO satellite
  • Five GCMs underestimate the total cloud cover at all latitudes except in Arctic
  • Discrepancies are more pronounced in tropics and poles, and over continents
G. Cesana
Laboratoire de Météorologie Dynamique (LMD/IPSL), Université Pierre et Marie Curie, Paris, France
H. Chepfer
Laboratoire de Météorologie Dynamique (LMD/IPSL), Université Pierre et Marie Curie, Paris, France
The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite provides robust and global direct measurements of the cloud vertical structure. The GCM-Oriented CALIPSO Cloud Product is used to evaluate the simulated clouds in five climate models using a lidar simulator. The total cloud cover is underestimated in all models (51% to 62% vs. 64% in observations) except in the Arctic. Continental cloud covers (at low, mid, high altitudes) are highly variable depending on the model. In the tropics, the top of deep convective clouds varies between 14 and 18 km in the models versus 16 km in the observations, and all models underestimate the low cloud amount (16% to 25%) compared to observations (29%). In the Arctic, the modeled low cloud amounts (37% to 57%) are slightly biased compared to observations (44%), and the models do not reproduce the observed seasonal variation.