Examining the relationship of El Niño to weather patterns in Alaska shows wide climate variances that depend on the teleconnection between the tropics and the northern latitudes. However, the weather patterns exhibited in Alaska during and just after moderate to strong El Niño episodes are generally consistent: above normal temperature and precipitation along the Alaskan coast, and above normal temperature and below normal precipitation in the interior, especially through the winter. The warm, dry conditions in the Alaskan interior increase summer wildfire potential. Statistics on the area burned since 1940 show that 15 out of 17 of the biggest fire years occurred during a moderate to strong El Niño episode. These 15 years account for nearly 63% of the total area burned over the last 58 years. Evidence points to increased dry thunderstorms and associated lightning activity during an El Niño episode; the percentage of total area burned by lightning caused fires during five episodes increased from a normal of less than 40% to a high of about 96%.

Advanced Very High Resolution Radiometer (AVHRR) satellite data were acquired and composited into twice-a-month periods from 1 May 1991 to 15 October 1991 in order to map vegetation characteristics of the Alaskan landscape. Unique spatial and temporal qualities of the AVHRR data provide information that leads to a better understanding of regional biophysical characteristics of vegetation communities and patterns. These data provided synoptic views of the landscape and depicted phenological diversity, temporal vegetation phenology (green-up, peak of green, and senescence), photosynthetic activity, and regional landscape patterns. Products generated from the data included a phenological class map, phenological composite maps (onset, peak, and duration), and photosynthetic activity maps (mean and maximum greenness). The time-series data provide opportunities to study phenological processes at small landscape scales over time periods of weeks, months, and years. Regional patterns identified on some of the maps are unique to specific areas; others correspond to biophysical or ecoregional boundaries. The data provide new insights to landscape processes, ecology, and landscape physiognomy that allow scientists to look at landscapes in ways that were previously difficult to achieve.

Summary Data from a sparse network of climate stations in Alaska were interpolated to provide 1‐km resolution maps of mean monthly temperature and precipitation–‐variables that are required at high spatial resolution for input into regional models of ecological processes and resource management. The interpolation model is based on thin‐plate smoothing splines, which uses the spatial data along with a digital elevation model to incorporate local topography. The model provides maps that are consistent with regional climatology and with patterns recognized by experienced weather forecasters. The broad patterns of Alaskan climate are well represented and include latitudinal and altitudinal trends in temperature and precipitation and gradients in continentality. Variations within these broad patterns reflect both the weakening and reduction in frequency of low‐pressure centres in their eastward movement across southern Alaska during the summer, and the shift of the storm tracks into central and northern Alaska in late summer. Not surprisingly, apparent artifacts of the interpolated climate occur primarily in regions with few or no stations. The interpolation model did not accurately represent low‐level winter temperature inversions that occur within large valleys and basins. Along with well‐recognized climate patterns, the model captures local topographic effects that would not be depicted using standard interpolation techniques. This suggests that similar procedures could be used to generate high‐ resolution maps for other high‐latitude regions with a sparse density of data.

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ABSTRACT. Maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada, produced by Oregon State University's Spatial Climate Analysis Service (SCAS) and the Alaska Geospatial Data Clearinghouse (AGDC), were analyzed. Because both sets of maps are generally available and in use by the community, there is a need to document differences between the processes and input data sets used by the two groups to produce their respective set of maps and to identify similarities and differences between the two sets of maps and possible reasons for the differences. These differences do not affect the observed large-scale patterns of seasonal and annual variability. Alaska is divided into interior and coastal zones, with consistent but different variability, separated by a transition region. The transition region has high interannual variability but low long-term mean variability. Both data sets support the four major ecosystems and ecosystem transition zone identified in our earlier work. Differences between the two sets of maps do occur, however, on the regional scale; they reflect differences in physiographic domains and in the treatment of these domains by the two groups (AGDC, SCAS). These differences also provide guidance for an improved observational network for Alaska. On the basis of validation with independent in situ data, we conclude that the data set produced by SCAS provides the best spatial coverage of Alaskan long-term mean monthly surface temperature and precipitation currently available.