1. Comparison on Cloud and radiation properties at Barrow between ARM/NSA measurements and GCM outputs Qun Miao and Zhien Wang University of Wyoming 1. Introduction 2. Data 4. Conclusions Arctic region has drawn lots attention due to its rapid changes during the past decades and potentially large impacts on global climate, less understanding in the interactive feedback processes, and also relatively poor representations in models. Arctic clouds are among the most difficult variables for model simulations. One of the reasons is that Arctic clouds are very difficult to validate. In this study, we utilize ground-based radar and lidar combined cloud properties at the ARM/NSA site since 1998 to compare with the simulations of four selected IPCC climate models. Together with radiation measurements at the ARM/NSA site, the dataset provides us an opportunity to examine model simulated cloud vertical structure and cloud radiative forcing. Model simulations Four climate models: NCAR CCSM3.0, GFDL CM2.0, GISS ModelE, UKMO-HadCM3 Four climate models: NCAR CCSM3.0, GFDL CM2.0, GISS ModelE, UKMO-HadCM3 Climate of the 20th Century and committed climate change experiments Period: 01/1990 to 12/2010 https://esg.llnl.gov:8443/index.jsp Period: 01/1990 to 12/2010 https://esg.llnl.gov:8443/index.jsphttps://esg.llnl.gov:8443/index.jsp Ground-based measurements at Barrow, AK: : Combined MMCR and MPL cloud boundaries 05/1998 to 02/2005 Combined MMCR and MPL cloud boundaries 05/1998 to 02/2005 MWR liquid water path 01/1998 to 10/2007 MWR liquid water path 01/1998 to 10/2007 SKYRAD downwelling longwave (LW) radiation 02/1998 to 02/2008 SKYRAD downwelling longwave (LW) radiation 02/1998 to 02/2008 GNDRAD upwelling LW radiation 04/1998 to 02/2008 GNDRAD upwelling LW radiation 04/1998 to 02/2008 Large discrepancies of cloud occurrence between model simulations and observations exist at Barrow, in both the seasonal trend and magnitude.Large discrepancies of cloud occurrence between model simulations and observations exist at Barrow, in both the seasonal trend and magnitude. Large LWP magnitude differences are present (up to 150 W/m 2 ). GFDL and UKMO underestimate while CCSM and GISS overestimate LWP. Large LWP magnitude differences are present (up to 150 W/m 2 ). GFDL and UKMO underestimate while CCSM and GISS overestimate LWP. Models simulate the seasonal cycle of surface upwelling/downwelling LW radiations well.Models simulate the seasonal cycle of surface upwelling/downwelling LW radiations well. Significant biases of downwelling LW cloud forcing are exist in some models.Significant biases of downwelling LW cloud forcing are exist in some models. Contacts: Qun Miao – miao@uwyo.edu Zhien Wang – zwang@uwyo.edu 3a. Cloud occurrence Simulations: 01/1990 to 12/2010 Observations: 05/1998 to 02/2005 3b. Cloud liquid water path Observations: 01/1998 to 10/2007 Models simulate LWP seasonal cycle well, but with a large difference in magnitude. GFDL and HadCM3 are very close to the observations in the cold season, but underestimate it in the warm season. CCSM and GISS overestimate LWP (up to 150 g/m 2 ). No model simulates the observed seasonal cycle of cloud occurrences well, especially for low clouds. For most months, CCSM and UKMO underestimate, GFDL and GISS overestimate total cloud occurrence. The seasonal cycle of total clouds is mainly determined by low clouds. The models simulate less middle level clouds than the observations. STD NSA Observations CCSM GFDLUKMO 2-5 km < 2 km > 5 km 3c. Surface LW radiation and LW downwelling Cloud Forcing (CF) 3d. LWP vs LW Cloud forcing Models simulate the annual cycles of surface LW radiation well, but simulations reach their peaks about one month earlier than the observations. There is about 20-30 W/m 2 difference in magnitude. CCSM overestimates LW cloud forcing by about 20 W/m 2 ; GFDL simulations are very close to observations; HadCM3 underestimates it by 5-10 W/m 2. The differences between model simulated and observed LWP-cloud forcing relation indicate that model simulated cloud vertical structure and microphysical properties are different from observations. 3. Results