1. Snow parametrisations in COSMO-RU: analysis of winter-spring forecasts 2009-2010 COLOBOC Workshop. Moscow, 6 September 2010

2. Basic characteristics of New snow scheme  Multilayerness  Radiation is described explicitly  Description of snow compaction by metamorphism and gravity  Phase transition of liquid water in snow cover  Description of water percolation with its next freezing and release of heat COLOBOC Workshop. Moscow, 6 September 2010

3. Methods and data  Comparison 2 versions model COSMO- Ru: “new” (with New snow scheme in TERRA) and “old” (previous snow scheme in TERRA)  Integration period – 78h (from 00 UTC)  Data: - station measurements - decade measurements of snow survey on Roshydromet’s stations COLOBOC Workshop. Moscow, 6 September 2010

4. Research region: European part of Russia north centre south

5. Snow characteristics: SWE and snow depth (1.12.09-28.02.10) Medvegegorsk : SWE – measurements and 72h forecasts north 91 mm95 mm 83 mm COLOBOC Workshop. Moscow, 6 September 2010

6. Snow characteristics: SWE and snow depth (1.12.09-28.02.10) north 16 mm 18 mm Medvegegorsk : SWE – measurements and 72h forecasts without mistakes COLOBOC Workshop. Moscow, 6 September 2010

7. Snow characteristics: SWE and snow depth (1.12.09-28.02.10) centre 70 mm 81mm 108mm Inza : SWE – measurements and 72h forecasts COLOBOC Workshop. Moscow, 6 September 2010

8. Snow characteristics: SWE and snow depth (1.12.09-28.02.10) centre 0 0 37mm Inza : SWE – measurements and 72h forecasts without mistakes COLOBOC Workshop. Moscow, 6 September 2010

9. Snow characteristics: SWE and snow depth (1.12.09-28.02.10) south Harabaly : SWE – measurements and 72h forecasts COLOBOC Workshop. Moscow, 6 September 2010

10. Snow characteristics: SWE and snow depth (1.12.09-28.02.10) south Harabaly : SWE – measurements and 72h forecasts without mistakes COLOBOC Workshop. Moscow, 6 September 2010

11. Snow characteristics: SWE and snow depth (1.12.09-28.02.10) stationnewold Verhnyaya Toyma0,890,94 Krasnoborsk0,880,95 Lalsk0,900,92 Medvegegorsk0,920,96 Pinega0,920,94 Correlation coefficients for snow depth according station data and 72h forecasts stationnewold Blagodarniy0,840,85 Verhniy Baskunchak0,550,42 Modok0,870,72 Nalchik0,770,65 Prohladnaya0,860,78 Harabaly0,890,84 north south stationnewoldstationnewold Anna0,810,84Kolomna0,920,94 Bologoe0,930,94Michurinsk0,900,96 Buzuluk0,93 Mogga0,900,95 Buy0,870,92Morshansk0,940,96 Vetluga0,850,94Poniri0,850,90 Gotnya0,810,86Radishevo0,96 Dmitrov0,940,95Rybinsk0,920,97 Inza0,95 Rilsk0,830,86 Kamishin0,860,94Spas-Demensk0,920,95 Karabulak0,910,90Urupinsk0,750,77 Karachev0,910,97Frolovo0,780,69 centre

12. 00С00С 00С00С 00С00С Snow depth north centre south

13. T2m (11.03.-29.03.09) Kursk Moscow night KurskMoscow day COLOBOC Workshop. Moscow, 6 September 2010

14. T2m (29.03.10)

15. Snow fractional cover - ice covered part of grid element - SWE - parameter

16. Differences between forecasts with “standard” cf=0.015m and cf=0.05m Day 1Day 2 Snow depth T2m

17. T2m (29.03.10). Experiments if then

18. T2m (29.03.10). Experiments Smolensk Kursk Kaluga

19. Snow fractional cover. Experiments If hsnow>0.3mthen cf_snow=0.01m

20. region date decemberjanuaryfebruary 1020315101520253151015202528 north 170 197 199 201 196 centre 137198 197 209 210 217230240244251 south 105 136 184 195229308 Snow density for field, kg/m 3 region date decemberjanuaryfebruary 1020315101520253151015202528 north 193 178 193 197 203 195 centre 85 158 195251188214216249248 Snow characteristics: snow density (1.12.09-28.02.10) Snow density for forest

21. Conclusions - SWE Forecasts are considerably overestimated by two versions of model COSMO-Ru. The cause is an inaccuracy of SWE initial data, though snow depth initial data is quite correct. Needed: correction of the forming algorithm of SWE initial data using improved values of snow density - Snow density varies during the period of snow cover existing in time scale and in each region (from north to south). It also have some differences between field and forest. So SWE calculation may take into consideration regional features of snow density. - During snow accumulation period New snow scheme tends to overestimate snow depth after snowfalls. So, in New snow scheme Recommendation: to do the correction of the computing algorithm of fresh snow density in New scheme - During snow melting period New snow scheme reproduce more realistically: - time dependence of SWE; - T2m at night (due to using New snow scheme there is the improvement of T2m forecast by 1,5-2 C). It is connected with New snow scheme’s description of freezing daily melted water and following release of heat. - During snow melting period the biggest mistakes of T2m forecasts were in vast regions for two versions (till 10 C), connected with equating to 0 C surface temperature of cell with snow. - Modifications with the snow fractional cover algorithm allowed to reduce the region area with mistaken temperature. Recommendation: to improve the algorithm of taking into account surfaces without snow during snow melting periods.

22. Thank you for your attention! COLOBOC Workshop. Moscow, 6 September 2010