www.sciencemag.org/cgi/content/full/1117368/DC1
Supporting Online Material for
Role of Land-Surface Changes in Arctic Summer Warming
F. S. Chapin III,1* M. Sturm,2 M. C. Serreze,3 J. P. McFadden,4 J. R. Key,5 A. H. Lloyd,6A. D. McGuire,7 T. S. Rupp,8 A. H. Lynch,9 J. P. Schimel,10 J. Beringer,9 W. L. Chapman,11 H. E. Epstein,12 E. S. Euskirchen,1 L. D. Hinzman,13 G. Jia,14 C.-L. Ping,15 K.
D. Tape,1 C. D. C. Thompson,1 D. A. Walker,1 J. M. Welker16 *To whom correspondence should be addressed. E-mail: [email protected]
Published 22 September 2005 on Science Express DOI: 10.1126/science.1117368
This PDF file includes:
Methods References
Supporting on-line material
Role of Terrestrial Ecosystem Changes in Arctic Summer Warming Chapin et al.
Detailed methods
Surface map of air temperature trends
We extended the Chapman and Walsh (1) dataset of summer air temperature maps (1961-1990) to 2004. Briefly, a dataset of surface air temperature was developed by the Climate
Research Unit of the University of East Anglia (2) by consolidating monthly air temperatures from land surface stations and monthly sea surface temperatures from the Comprehensive Ocean-Atmosphere Dataset. This dataset has been updated annually. We used the best-fit linear trends of June-August temperatures over the 1961-2004 period for all grid cells poleward of 40˚N for which no more than 20% of the monthly values were missing. The grid-cell trends were then objectively analyzed using a spatial weighting technique with a 400-km radius of influence (3). We then compared spatial patterns of surface air temperature with those from 1961-1990 (1) and 1966-1995 (4). We also present the temporal trend in surface air temperature for the Alaskan terrestrial domain from 1930-2004.
Alaska surface, cloud, and radiation properties from space
From the pan-arctic dataset of Wang and Key (5) we extracted data for summer (June-August) in the Alaskan terrestrial Arctic for surface, cloud, and radiation properties collected from the extended Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder
(APP-x) project for the period 1982-1999 (6). These properties include cloud fraction, cloud optical depth, and surface radiation components (allwave, longwave, and shortwave forcing) for all summer days to evaluate the effect of clouds on trends in the radiation budget seen from space. We also analyzed surface skin temperature and surface broadband albedo for clear-sky days to evaluate the impact of changes in land-surface properties and radiation components in the absence of clouds. We performed trend analysis of cloud, surface and radiation parameters with least-squares fit regression.
Change in season length
We synthesized all published long-term records of change in date of spring snowmelt (or other proxies, such as date of leaf out or date of surface soil thaw) for arctic Alaska. We also included 1972-2000 values for arctic Alaska from the pan-arctic dataset of Dye (7) and unpublished data from surface measurements at Imnavait Creek in the foothills of the Brooks Range, 1985-2005 (http://www.uaf.edu/water/projects/NorthSlope/imnavait/basin/basin.html).
Vegetation change
Using a satellite-based vegetation map (8), we estimated the linear extent of tundra-forest ecotone in arctic Alaska (the North Slope, Seward Peninsula and southwest Alaska and
subdivided this ecotone into upland and lowland portions. Based on tree-ring analysis of stand-ages across these ecotones (9), we estimate that forests expand at 2.55 km [50 yr]-1 in lowlands and 0.1 km [50 yr]-1 in uplands (9). When these estimates are applied to the entire forest-tundra ecotone, we calculate that 11,600 km2 (2.3% of the treeless area) has been converted from tundra to forest in the past 50 years. This is equivalent to 0.5% of the treeless area decade-1.
Vegetation and season-length effects on energy budget
We updated the synthesis by Eugster et al. (10) of published research on pre-snowmelt and summer energy budget parameters in boreal conifer, arctic shrub tundra, and arctic tussock tundra (upland tundra without tall shrubs) by including recently published studies from Alaska (11-13). From these data we estimated mean values of albedo, net radiation (as a % of incoming shortwave), and heat flux to the atmosphere (sensible + latent heat flux). For a given vegetation type, we compared pre- to post-snowmelt energy budgets to estimate the effect of increased season length on atmospheric heating. By comparing summer energy budgets of shrubless tundra, shrub tundra, and forest, we estimated the effect of vegetation change on atmospheric heating. Based on our estimates of average change per decade in season length and areal extent of vegetation, we calculated the decadal change in atmospheric heating due to increased length of growing season and vegetation change (Tables 1 and 2).
References
1. W. L. Chapman, J. E. Walsh, Bulletin of the American Meteorological Society 74, 33 (1993).
2. P. D. Jones et al., Journal of Climate and Applied Meteorology 25, 161 (1986). 3. G. P. Cressman, Monthly Weather Review 87, 367 (1959).
4. M. C. Serreze et al., Climatic Change 46, 159 (2000). 5. X. J. Wang, J. R. Key, Science 299, 1725 (2003).
6. W. Meier, J. A. Maslanik, J. R. Key, C. W. Fowler, Earth Interactions 1, available online at http://earthinteractions.org (1997).
7. D. G. Dye, Hydrological Processes 16, 3065 (2002).
8. M. D. Fleming, paper presented at the 1996 Alaska Surveying and Mapping Conference, Anchorage, Alaska 1996.
9. A. H. Lloyd, Ecology (In press).
10. W. Eugster et al., Global Change Biology 6 (Suppl. 1), 84 (2000).
11. J. Beringer, I. Chapin, F. S., C. D. C. Thompson, A. D. McGuire, Agricultural and Forest Meteorology 168, doi:10.1016/j.agrformet.2005.05.006 (2005).
12. H. P. Liu, J. T. Randerson, J. Lindfors, I. Chapin, F. S., Journal of Geophysical Research - Atmospheres 110, D13101, doi:10.1029/2004JD005158 (2005).
