Greenbelt, MD, United States
Greenbelt, MD, United States

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Huang S.,ASRC Federal Inuteq | Dahal D.,Stinger Ghaffarian Technologies SGT Inc | Dahal D.,Eros | Liu H.,Washington State University | And 6 more authors.
Canadian Journal of Forest Research | Year: 2015

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.Weused 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. © 2015, National Research Council of Canada. All rights reserved.

Zhu Q.,Nanjing University | Zhu Q.,University of Quebec at Montréal | Jiang H.,Nanjing University | Jiang H.,Zhejiang Agriculture And forestry University | And 7 more authors.
Global and Planetary Change | Year: 2012

Investigating the relationship between factors (climate change, atmospheric CO 2 concentrations enrichment, and vegetation structure) and hydrological processes is important for understanding and predicting the interaction between the hydrosphere and biosphere. The Integrated Biosphere Simulator (IBIS) was used to evaluate the effects of climate change, rising CO 2, and vegetation structure on hydrological processes in China at the end of the 21st century. Seven simulations were implemented using the assemblage of the IPCC climate and CO 2 concentration scenarios, SRES A2 and SRES B1. Analysis results suggest that (1) climate change will have increasing effects on runoff, evapotranspiration (ET), transpiration (T), and transpiration ratio (transpiration/evapotranspiration, T/E) in most hydrological regions of China except in the southernmost regions; (2) elevated CO 2 concentrations will have increasing effects on runoff at the national scale, but at the hydrological region scale, the physiology effects induced by elevated CO 2 concentration will depend on the vegetation types, climate conditions, and geographical background information with noticeable decreasing effects shown in the arid Inland region of China; (3) leaf area index (LAI) compensation effect and stomatal closure effect are the dominant factors on runoff in the arid Inland region and southern moist hydrological regions, respectively; (4) the magnitudes of climate change (especially the changing precipitation pattern) effects on the water cycle are much larger than those of the elevated CO 2 concentration effects; however, increasing CO 2 concentration will be one of the most important modifiers to the water cycle; (5) the water resource condition will be improved in northern China but depressed in southernmost China under the IPCC climate change scenarios, SRES A2 and SRES B1. © 2011 Elsevier B.V.

Chander G.,Stinger Ghaffarian Technologies SGT Inc. | Haque M.O.,Stinger Ghaffarian Technologies SGT Inc. | Micijevic E.,Stinger Ghaffarian Technologies SGT Inc. | Barsi J.A.,Science Systems And Applications Inc.
IEEE Transactions on Geoscience and Remote Sensing | Year: 2010

From the Landsat program's inception in 1972 to the present, the Earth science user community has been benefiting from a historical record of remotely sensed data. The multispectral data from the Landsat 5 (L5) Thematic Mapper (TM) sensor provide the backbone for this extensive archive. Historically, the radiometric calibration procedure for the L5 TM imagery used the detectors' response to the internal calibrator (IC) on a scene-by-scene basis to determine the gain and offset for each detector. The IC system degraded with time, causing radiometric calibration errors up to 20%. In May 2003, the L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center through the National Landsat Archive Production System (NLAPS) were updated to use a lifetime lookup-table (LUT) gain model to radiometrically calibrate TM data instead of using scene-specific IC gains. Further modification of the gain model was performed in 2007. The L5 TM data processed using IC prior to the calibration update do not benefit from the recent calibration revisions. A procedure has been developed to give users the ability to recalibrate their existing level-1 products. The best recalibration results are obtained if the work-order report that was included in the original standard data product delivery is available. However, if users do not have the original work-order report, the IC trends can be used for recalibration. The IC trends were generated using the radiometric gain trends recorded in the NLAPS database. This paper provides the details of the recalibration procedure for the following: 1) data processed using IC where users have the work-order file; 2) data processed using IC where users do not have the work-order file; 3) data processed using prelaunch calibration parameters; and 4) data processed using the previous version of the LUT (e.g., LUT03) that was released before April 2, 2007. © 2009 IEEE.

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