Foredrag

Mandagskollokvium: Climatology of total cloudiness in the Arctic: An intercomparison of satellite and surface observations and reanalyses

Monday 5 March, Alexander Chernokulsky will give the talk "Climatology of total cloudiness in the Arctic: An intercomparison of satellite and surface observations and reanalyses". See abstract below

Where: Auditorium, East Wing, Geophysical Institute

When: 5 March 2012, 11.15 - 12.00

Who: Alexander Chernokulsky

What: "Climatology of total cloudiness in the Arctic: An intercomparison of satellite and surface observations and reanalyses"

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Abstract:

The Arctic is a very sensitive region to the global climate change. An increase of air temperature is accompanied with changes in other climate variables; particularly with a decrease of the Arctic sea ice extent and cloud cover changes. The sensitivity of cloud radiative forcing is about 1 W/m2 per 1% of cloud cover in the Arctic. Thus, relatively a small percentage of changes in cloud cover or cloud properties could result in an anomalous climate forcing of several W/m2. Considering an importance of clouds in the Arctic, it is crucial to know exactly when and where clouds exist. However, the detection of clouds in the Arctic is intrinsically difficult.
We present here an intercomparison of the up-to-date climatologies of total cloudiness in the Arctic (north of 60° N) from satellite (APP-x, CERES, ISCCP, MODIS, PATMOS-x) and surface observations (EECRA) and 8 reanalyses (ERA-40, ERA-Interim, JRA-25, MERRA, NCEP/NCAR, NCEP/DOE, NCEP-CFSR, NOAA-CIRES 20CR).
The Arctic annual-mean total cloud fraction is about 0.70±0.03 according to different observational data. It is higher over the ocean (0.74±0.04) and less over land (0.67±0.03). Different observations for total cloud fraction are in a better agreement in summer than in winter and over the ocean than over land. An interannual variability is higher in winter than in summer according to all observations. The main cause of the discrepancies among observations is the difference in the cloud-detection algorithms, especially when clouds are detected over the ice/snow surface (during the whole year) or over the regions with the presence of strong low-tropospheric temperature inversions (mostly in winter). Generally, reanalyses are not in a close agreement with satellite and surface observations of cloudiness in the Arctic.