Coupling of Vegetation Growing Season Anomalies and Fire Activity with Hemispheric and Regional-Scale Climate Patterns in Central and East Siberia

Abstract

An 18-yr time series of the fraction of absorbed photosynthetically active radiation (fAPAR) taken in by the green parts of vegetation data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) instrument series was analyzed for interannual variations in the start, peak, end, and length of the season of vegetation photosynthetic activity in central and east Siberia. Variations in these indicators of seasonality can give important information on interactions between the biosphere and atmosphere. A second-order local moving window regression model called the "camelback method" was developed to determine the dates of phenological events at subcontinental scale. The algorithm was validated by comparing the estimated dates to phenological field observations. Using spatial correlations with temperature and precipitation data and climatic oscillation indices, two geographically distinct mechanisms in the system of climatic controls of the biosphere in Siberia are postulated: central Siberia is controlled by an "Arctic Oscillation-temperature mechanism," while east Siberia is controlled by an "El Niño-precipitation mechanism." While the analysis of data from 1982 to 1991 indicates a slight increase in the length of the growing season for some land-cover types due to an earlier beginning of the growing season, the overall trend from 1982 to 1999 is toward a slightly shorter season for some land-cover types caused by an earlier end of season. The Arctic Oscillation tended toward a more positive phase in the 1980s leading to enhanced high pressure system prevalence but toward a less positive phase in the 1990s. The results suggest that the two mechanisms also control the fire regimes in central and east Siberia. Several extreme fire years in central Siberia were associated with a highly positive Arctic Oscillation phase, while several years with high fire damage in east Siberia occurred in El Niño years. An analysis of remote sensing data of forest fire partially supports this hypothesis.

Interdisciplinary approaches: towards new statistical methods for phenological studies

“…The different spatio-temporal statistical methods discussed were grouped into the following categories: (1) thresholds (Zhou et al 2003;Delbart et al 2005;Karlsen et al 2006Karlsen et al , 2007; (2) derivatives (Baltzer et al 2007); (3) smoothing algorithms (e.g. moving average models) (Reed et al 1994), discrete Fourier analysis (Moody and Johnson 2001), Principal component analysis (Eastman and Fulk 1993;Hall-Beyer 2003); and (4) fitted models (logistic models) (Zhang et al 2004), Gaussian models or lower order Fourier estimates (Jönsson and Eklundh 2004), quadratic models with accumulated growing degree days Henebry 2004a, b, 2008).…”

Effects of climate variability on savannah fire regimes in West Africa

“…Other studies have shown the relationships between climate indexes and fire activities in southeastern Asia, Central and South America, and the boreal regions of Eurasia and North America (van der Werf et al, 2004(van der Werf et al, , 2006Westerling et al, 2006). Boreal fires have been linked to ENSO, NAO, AO (Arctic Oscillation), PDO (Pacific Decadal Oscillation) and the AMO (Skinner et al, 2006;Balzter et al, 2007;Le Goff et al, 2007;Beverly et al, 2011).…”

Satellite Observations of El Niño Impacts on Eurasian Spring Vegetation Greenness during the Period 1982–2015

“…For example, Buermann et al [111] indicated that the warm event ENSO signal was manifested as warmer and greener conditions in North America, Far East Asia, and to some extent central Europe, while the positive phase AO signal featured enhanced warm and green conditions over large regions in Europe and Asian Russia for the period 1982-1998. Balzter et al [112] suggested that the AO and El Niño controlled the forest fire regimes in Central and East Siberia: several extreme fire years in Central Siberia were associated with a highly positive AO phase while several years with high fire damage in East Siberia occurred in El Niño years. Gong and Ho [113] implied that the large-scale circulation was essential for understanding the regional response of vegetation to global climate change; taking nine circulation indices and time lags into account, a large portion (71%) of the satellite-sensed variance in NDVI could be explained.…”