Observed impact of snow cover on the heat balance and the rise of continental spring temperatures

Science

Volumn 263, Issue 5144, 1994, Pages 198-200

  Groisman, Pavel Ya ^a,b   Karl, Thomas R ^b   Knight, Richard W ^b  

^a STATE HYDROLOGICAL INSTITUTE   (Russian Federation)

^b NATIONAL CLIMATIC DATA CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC THERMODYNAMICS; ENVIRONMENTAL IMPACT; GREENHOUSE EFFECT; HEAT RADIATION; MATHEMATICAL MODELS; SNOW;

ATMOSPHERIC RADIATIVE BALANCE; CONTINENTAL SPRING TEMPERATURES; EARTH RADIATION BUDGET; GLOBAL WARMING; NORTHERN HEMISPHERE SNOW COVER; PLANETARY ALBEDO; SURFACE AIR TEMPERATURE;

CLIMATOLOGY;

HEAT BALANCE; SNOW COVER; SPRING TEMPERATURE;

EID: 0028058226     PISSN: 00368075     EISSN: None     Source Type: Journal    
DOI: 10.1126/science.263.5144.198     Document Type: Article

References (23)

1. Climate-related variables can be loosely classified into three categories: forcings, feedbacks, and responses. The climate is forced by those conditions that directly affect other climate elements, the response variables. Changes in a response variable can sometimes affect other climate-related elements, providing feedback effects. In this sense, changes in snow cover force changes in the hemispheric radiative balance. Snow cover is often regarded as a feedback variable because changes in temperature affect snow cover, which then has a feedback effect on temperature.
2. 2 at low latitudes. Each grid cell contains one bit of information for every week, indicating the absence or presence of snow cover. For each grid cell, the weekly snow cover was integrated over monthly and seasonal time scales.
3. 2 at low latitudes. Each grid cell contains one bit of information for every week, indicating the absence or presence of snow cover. For each grid cell, the weekly snow cover was integrated over monthly and seasonal time scales.
4. 2 at low latitudes. Each grid cell contains one bit of information for every week, indicating the absence or presence of snow cover. For each grid cell, the weekly snow cover was integrated over monthly and seasonal time scales.
5. 2 at low latitudes. Each grid cell contains one bit of information for every week, indicating the absence or presence of snow cover. For each grid cell, the weekly snow cover was integrated over monthly and seasonal time scales.
6. 2 at low latitudes. Each grid cell contains one bit of information for every week, indicating the absence or presence of snow cover. For each grid cell, the weekly snow cover was integrated over monthly and seasonal time scales.
7. Monthly temperatures (1972 to 1992) were selected from two archives: the Global Historical Climatology Network [R. S. Vose et al., Environ. Sci. Div. Publ. No. 3912 (Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, TN, 1992)] and surface data from 376 Chinese stations, compiled by W. Wan-Lin and transferred to the U.S. National Climatic Data Center in the framework of a Bilateral Data Exchange between the Peoples Republic of China and the United States. A total of 1543 stations were used.
8. The ERBE monthly values of clear-sky and total radiative fluxes were used from the scanners with narrow field of view (albedo and outgoing infrared radiation). These data are gridded at a resolution of 2.5° and are available for November 1984 through December 1988 [B. R. Barkstrom, Bull. Am. Meteorol. Soc. 65, 1170 (1984); B. R. Barkstrom et al., ibid. 70, 1254 (1989)].
9. The ERBE monthly values of clear-sky and total radiative fluxes were used from the scanners with narrow field of view (albedo and outgoing infrared radiation). These data are gridded at a resolution of 2.5° and are available for November 1984 through December 1988 [B. R. Barkstrom, Bull. Am. Meteorol. Soc. 65, 1170 (1984); B. R. Barkstrom et al., ibid. 70, 1254 (1989)].
10. Digital maps of the global distribution of total cloud cover (11) span from 1971 to 1981. We found that the spatial and temporal variations of the cloud cover are not correlated with variations of snow cover over the NEL. When snow is on the ground, clouds tend to have a small mean effect on the radiation fields at the TOA because both are cold and bright [H. L. Kyle et al., Bull. Am. Meteorol. Soc. 74, 815 (1993)]. For these reasons, we averaged the cloud cover over the 11-year period and used the averages in subsequent analyses.
11. D. A. Robinson and K. F. Dewey, Geophys. Res. Lett. 17, 1557 (1990).
12. Other variables were added to the list of independent variables in a multiple linear-regression equation. This included the solar zenith angle and the temperature (which varies in the range of ±0.5°C). The estimates of ∂α/∂S and ∂OLR/∂S are not significantly changed when any of these factors are incorporated into the equation.
13. The mean value of C is close to 0.6 and does not change with temperature.
14. We ignored the variations of the snow cover over sea ice and over Greenland.
15. A. Henderson-Sellers and P. J. Robinson, Contemporary Climatology (Longman Scientific, Harlow, United Kingdom, 1986).
16. S. G. Warren et al., NCAR Tech. Note 273 STR (National Center for Atmospheric Research, Boulder, CO, 1986).
17. R. D. Cess et al., J. Geophys. Res. 97, 20421 (1992).
18. We grouped the data according to surface air temperature to estimate ∂OLR/∂S and found that under all-sky conditions, this temperature is a poor surrogate for other factors (besides snow cover) affecting OLR.
19. The numbers should be reduced by a factor of 0.21 or 0.55 if integrated over the Northern Hemisphere or the Northern Hemisphere land areas, respectively.
20. We believe that Eq. 4 (and therefore Fig. 3A and Table 2) provides better estimates and definition of the snow cover feedback of the radiative balance, whereas Eq. 5 provides less accurate results, especially for ∂OLR/∂S in all-sky conditions.
21. V. Ramanathan, B. R. Barkstrom, E. F. Harrison, Phys. Today 42, 22 (May 1989).
22. P. D. Jones and K. R. Briffa, Holocene 2, 165 (1992).
23. Supported by the NOAA Office of Global Programs and a Department of Energy Office of Environmental Effects/NOAA National Climatic Data Center Interagency Agreement.