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Regional Modeling of Antarctic Clouds Keith M. Hines 1 and David H. Bromwich 1,2 1 Polar Meteorology Group Byrd Polar Research Center The Ohio State University.

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Presentation on theme: "Regional Modeling of Antarctic Clouds Keith M. Hines 1 and David H. Bromwich 1,2 1 Polar Meteorology Group Byrd Polar Research Center The Ohio State University."— Presentation transcript:

1 Regional Modeling of Antarctic Clouds Keith M. Hines 1 and David H. Bromwich 1,2 1 Polar Meteorology Group Byrd Polar Research Center The Ohio State University 2 Atmospheric Sciences Program Department of Geography The Ohio State University

2 Issues for Mesoscale Modeling of Antarctic Clouds Limited observations for comparison/inspiration/verification Low aerosol concentrations Clear-sky precipitation/diamond dust Thin ice clouds Ice cloud physics less well understood than liquid cloud physics Non-spherical ice particles Are the more frequent Arctic field programs relevant for the Antarctic? How can we make use of more advanced (two-moment) cloud microphysical parameterizations? How can we make use of remote sensing? Synergy with ice core studies

3 Arctic Studies with Cloud Component SHEBA/FIRE/ARM (1998) M-PACE (October 2004) ISDAC (IPY) ASCOS (IPY) STAR (IPY) What about the Antarctic?

4 AMPS studies and Antarctic Clouds

5 AMPS Cloud Forecast Evaluation (Fogt and Bromwich 2008) December 2003 – February 2005 Polar MM5 30 km basic horizontal resolution for Antarctica Reisner Single-Moment Microphysics Look at Relative Humidity and Cloud Fraction

6 McMurdo South Pole correlation bias Relative Humidity WRT ICE

7 Predicted vs. Observed Relative Humidity at 700 hPa, 400 hPa and 250 hPa Overforecast of Relative Humidity Increases with Height in the Troposphere

8 Estimated Cloud Fraction for explicit moisture schemes that predict cloud mixing ratio (g m -3 ) CF = Σ [ A LIQ CLWP + A ICE CIWP ] ( Fogt and Bromwich 2008) Old: A LIQ = 0.100 ; A ICE = 0.0735 New: A LIQ = 0.075 ; A ICE = 0.1700 (Better matches Lubin’s (1994) absorption coefficient for Antarctic clouds) (CCM2 mid-latitude)

9 Compare Simulated to Observed Cloud Fraction at 3 Sites

10 deficit excess deficit Original Modified formula Percent matches by cloud category partly cloudy clear overcast

11 CF = Σ [ A LIQ CLWP + A ICE CIWP ] PWRF

12 Pseudosatellite Regions

13 Pseudosatellite Product AMPS MODIS Figure shows: High clouds in (1) well captured and demonstrated in (2). Excessive clouds in Ross Sea (3) Low clouds over Ross Ice Shelf are not captured. Overall, statistical testing shows the product better captures high clouds than low clouds 1200 UTC 21 Jan 2006

14 AMPS Cloud Forecast Evaluation (Nicolas and Bromwich 2010) October 2003 ; 2006-2007 Polar MM5 30 / 20 km basic horizontal resolution for Antarctica Reisner Single-Moment Microphysics Look at Cloud Frequency and Precipitation vs. Satellite Remote Sensing,

15 ICESat GLAS Lidar AMPS Cloud Frequency October 2003 AMPS Cloud Fraction

16 CALIPSO/CALIOP Lidar Cloud Frequency AMPS Cloud Frequency October 2007 – October 2006

17 Issues for Mesoscale Modeling of Antarctic Clouds Limited observations for comparison/inspiration/verification Low aerosol concentrations Clear-sky precipitation/diamond dust Thin ice clouds Ice cloud physics less well understood than liquid cloud physics Non-spherical ice particles Synergy between Arctic and Antarctic observational and modeling studies? How can we make use of more advanced (two-moment) cloud microphysical parameterizations? How can we make use of remote sensing? Synergy with ice core studies


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