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Fourth Study Conference on BALTEX Scala Cinema Gudhjem

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1<br />

0.8<br />

0.6<br />

0.4<br />

0.2<br />

GO(CLD-M)<br />

ERA40<br />

SMHI<br />

0 100 200 300 400<br />

Time (Julian day)<br />

Figure 3. A comparis<strong>on</strong> between ERA40 (black line) and<br />

SMHI 1 0 x1 0 (blue line) total cloudiness above Eastern<br />

Gotland Basin). Daily means averaged over a 30-years<br />

period.<br />

0.35<br />

0.3<br />

0.25<br />

0.2<br />

0.15<br />

0.1<br />

GO(CLD-STD)<br />

ERA40<br />

SMHI<br />

0 100 200 300 400<br />

Time (Julian day)<br />

Figure 4. A comparis<strong>on</strong> between ERA40 (black line) and<br />

SMHI 1 0 x1 0 (blue line) total cloudiness above Eastern<br />

Gotland Basin). Daily standard deviati<strong>on</strong> averaged over a<br />

30-years period.<br />

5. Baltic Sea modelling<br />

In Figure 5, the modelling of sea ice is examined using the<br />

PROBE-Baltic (Omstedt and Axell, 2003) model forced<br />

with the two different meteorological data sets. The<br />

agreements are good between the two data sets. However<br />

both calculati<strong>on</strong>s over estimate ice during mild winters. This<br />

indicates that the two data sets have a bias towards land<br />

influence, which makes Baltic Sea winter c<strong>on</strong>diti<strong>on</strong>s over<br />

sea slightly too cold.<br />

- 79 -<br />

Figure 5. Annual maximum ice extent in the Baltic Sea:<br />

A comparis<strong>on</strong> between observed (green line) and<br />

modelled data using ERA40 forcing (black line) and<br />

SMHI 1 0 x1 0 forcing (blue line).<br />

6. Discussi<strong>on</strong><br />

Several aspects of the two different data sets will be<br />

discussed during the c<strong>on</strong>ference. In general there is a good<br />

agreement between the two data sets. The ERA40 data<br />

offer much more variables for investigati<strong>on</strong>s compared to<br />

the SMHI 1 0 x1 0 data set. However, the SMHI 1 0 x1 0 data is<br />

c<strong>on</strong>tinuously up dated and could therefore work as a<br />

complement to ERA40 from 2001 and <strong>on</strong>wards. The<br />

precipitati<strong>on</strong> data over the Baltic Sea seems, however, too<br />

low in the ERA40 data.<br />

References<br />

Karlss<strong>on</strong>, K.-G., (2003). A 10 year cloud climatology over<br />

Scandinavia derived from NOAA Advanced Very<br />

High Resoluti<strong>on</strong> Radiometer imagery. Internati<strong>on</strong>al<br />

Journal of Climatology, 23, 1023-1044.<br />

Omstedt, A. and L., Axell (2003). Modeling the variati<strong>on</strong>s<br />

of salinity and temperature in the large Gulfs of the<br />

Baltic Sea. C<strong>on</strong>tinental Shelf Research, 23, 265-294<br />

Rutgerss<strong>on</strong>, A., Bumke, K., Clemens, M., Foltescu, V.,<br />

Lindau, R., Michels<strong>on</strong>, D., Omstedt , A., (2001).<br />

Precipitati<strong>on</strong> Estimates over the Baltic Sea: Present<br />

State of the Art, Nordic Hydrology, 32(4), 285-314.<br />

Omstedt, A., Meuller, L., and L., Nyberg (1997) Interannual,<br />

seas<strong>on</strong>al and regi<strong>on</strong>al variati<strong>on</strong>s of precipitati<strong>on</strong> and<br />

evaporati<strong>on</strong> over the Baltic Sea. Ambio, 26, No. 8, 484-<br />

492.

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