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Boreal fires can cool the climate; however, this conclusion came from individual fires and may not represent the whole story. We hypothesize that the climatic impact of boreal fires depends on local landscape heterogeneity such as burn severity, prefire vegetation type, and soil properties. To test this hypothesis, spatially explicit emission of greenhouse gases (GHGs) and aerosols and their resulting radiative forcing are required as an important and necessary component towards a full assessment. In this study, we integrated remote sensing (Landsat and MODIS) and models (carbon consumption model, emission factors model, and radiative forcing model) to calculate the carbon consumption, GHGs and aerosol emissions, and their radiative forcing of 2001-2010 fires at 30 m resolution in the Yukon River Basin of Alaska. Total carbon consumption showed significant spatial variation, with a mean of 2,615 g C m and a standard deviation of 2,589 g C m. The carbon consumption led to different amounts of GHGs and aerosol emissions, ranging from 593.26 Tg (CO) to 0.16 Tg (NO). When converted to equivalent CO based on global warming potential metric, the maximum 20 years equivalent CO was black carbon (713.77 Tg), and the lowest 20 years equivalent CO was organic carbon (−583.13 Tg). The resulting radiative forcing also showed significant spatial variation: CO, CH, and NO can cause a 20-year mean radiative forcing of 7.41 W m with a standard deviation of 2.87 W m. This emission forcing heterogeneity indicates that different boreal fires have different climatic impacts. When considering the spatial variation of other forcings, such as surface shortwave forcing, we may conclude that some boreal fires, especially boreal deciduous fires, can warm the climate. [ABSTRACT FROM AUTHOR]

The albedo change caused by fires and the subsequent succession is spatially heterogeneous, leading to the need to assess the spatiotemporal variation of surface shortwave forcing (SSF) as a component to quantify the climate impacts of high-latitude fires. We used an image reconstruction approach to compare postfire albedo with the albedo assuming that no fires had occurred. Combining the fire-caused albedo change from the 2001-2010 fires in interior Alaska and the monthly surface incoming solar radiation, we examined the spatiotemporal variation of SSF in the early successional stage of approximately 10 years. Our results showed that although postfire albedo generally increased in fall, winter, and spring, some burned areas could show an albedo decrease during these seasons. In summer, the albedo increased for several years and then declined again. The spring SSF distribution did not show a latitudinal decrease from south to north as previously reported. The results also indicated that although the SSF is usually largely negative in the early successional years, it may not be significant during the first postfire year. The annual 2005-2010 SSF for the 2004 fire scars was -1.30, -4.40, -3.31, -4.00, -3.42, and -2.47 W·m−2, respectively. The integrated annual SSF map showed significant spatial variation, with a mean of -3.15 W·m−2, a standard deviation of 3.26 watts per square metre (W·m−2), and 16% of burned areas having positive SSF. Our results suggest that boreal deciduous fires would be less positive for climate change than boreal evergreen fires. Future research is needed to comprehensively investigate the spatiotemporal radiative and nonradiative forcings to determine the effect of boreal fires on the climate. [ABSTRACT FROM AUTHOR]

Abstract: In interior Alaska, wildfires change gross primary production (GPP) after the initial disturbance. The impact of fires on GPP is spatially heterogeneous, which is difficult to evaluate by limited point-based comparisons or is insufficient to assess by satellite vegetation index. The direct prefire and postfire comparison is widely used, but the recovery identification may become biased due to interannual climate variability. The objective of this study is to propose a method to quantify the spatially explicit GPP change caused by fires and succession. We collected three Landsat images acquired on 13 July 2004, 5 August 2004, and 6 September 2004 to examine the GPP recovery of burned area from 1987 to 2004. A prefire Landsat image acquired in 1986 was used to reconstruct satellite images assuming that the fires of 1987–2004 had not occurred. We used a light-use efficiency model to estimate the GPP. This model was driven by maximum light-use efficiency (Emax) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). We applied this model to two scenarios (i.e., an actual postfire scenario and an assuming-no-fire scenario), where the changes in Emax and FPAR were taken into account. The changes in Emax were represented by the change in land cover of evergreen needleleaf forest, deciduous broadleaf forest, and shrub/grass mixed, whose Emax was determined from three fire chronosequence flux towers as 1.1556, 1.3336, and 0.5098gC/MJ PAR. The changes in FPAR were inferred from NDVI change between the actual postfire NDVI and the reconstructed NDVI. After GPP quantification for July, August, and September 2004, we calculated the difference between the two scenarios in absolute and percent GPP changes. Our results showed rapid recovery of GPP post-fire with a 24% recovery immediately after burning and 43% one year later. For the fire scars with an age range of 2–17years, the recovery rate ranged from 54% to 95%. In addition to the averaging, our approach further revealed the spatial heterogeneity of fire impact on GPP, allowing one to examine the spatially explicit GPP change caused by fires. [Copyright &y& Elsevier]

ABSTRACT The estimation of ice/snow accumulation is of great significance in quantifying the mass balance of ice sheets and variation in water resources. Improving the accuracy and reducing uncertainty has been a challenge for the estimation of annual accumulation over the Greenland ice sheet. In this study, we kriged and analyzed the spatial pattern of accumulation based on an observation data series including 315 points used in a recent research, plus 101 ice cores and snow pits and newly compiled 23 coastal weather station data. The estimated annual accumulation over the Greenland ice sheet is 31.2 g cm−2 yr−1, with a standard error of 0.9 g cm−2 yr−1. The main differences between the improved map developed in this study and the recently published accumulation maps are in the coastal areas, especially southeast and southwest regions. The analysis of accumulations versus elevation reveals the distribution patterns of accumulation over the Greenland ice sheet. [ABSTRACT FROM AUTHOR]