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| Titel |
Evaluation of the SMAP model-simulated snow internal physical properties at
Sapporo, Japan from 2005 to 2015 |
| VerfasserIn |
Masashi Niwano, Teruo Aoki, Katsuyuki Kuchiki, Sumito Matoba, Yuji Kodama, Tomonori Tanikawa |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250133038
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| Publikation (Nr.) |
 EGU/EGU2016-13606.pdf |
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| Zusammenfassung |
| Temporal evolution of snow internal physical properties such as grain size, density,
temperature, and water content are controlled by changes in meteorological conditions. On
the other hand, in a snow covered area, surface atmospheric conditions are modulated in
response to variations of snow albedo, which is affected by (optically equivalent) snow grain
size as well as mass concentration of snow impurities such as black carbon and dust.
Therefore, it is necessary for snowpack models incorporated in climate models to simulate
realistic snow internal physical properties to perform accurate future climate prediction
especially in the cryosphere.
In this study, we evaluated snow internal physical properties at Sapporo (43˚ 05’N, 141˚
21’E, 15 m a.s.l.), Japan from 2005 to 2015 simulated with a 1-D multilayered physical
snowpack model SMAP (Snow Metamorphism and Albedo Process). The model was driven
by quality controlled 30-min averaged data for air temperature, relative humidity, wind speed,
surface pressure, snow depth, downward and upward shortwave radiant flux, downward
longwave radiant flux, and ground surface soil heat flux. Simulation results were
compared against the data obtained from snow pit works performed twice a week at
Sapporo.
First of all, the model-simulated column integrated SWE (snow water equivalent) were
compared against in-situ measurements (273 data were available during the 10 winters). The
results show that the model tends to underestimate SWE (mean error; ME was –19 mm);
however, root mean square error (RMSE) was 34 mm, and these scores are better than those
for simulations driven by not snow depth but precipitation (ME was less than –25 mm
and RMSE was more than 40 mm). It suggests that the correction technique for
precipitation measurements considering catch efficiency of a rain gauge is still
insufficient. Next, the model-simulated profiles for snow density and snow temperature
were compared against in-situ measurements. For this purpose, total 1688 and 2562
measurement data have been used for the former and the latter comparisons, respectively.
The SMAP model tends to underestimate snow density (ME = –51 kg m−3) and
overestimate snow temperature (ME = 0.42 oC); however, RMSE for both properties
were sufficiently small (88 kg m−3and 1.62 oC, respectively). In order to permit
higher precision of the model, it would be necessary to develop physically based
schemes for new snow density and effective thermal conductivity of the snowpack. |
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