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Z. M. Subin, W. J. Riley, J. Jin, D. S. Christianson, M. S. Torn, and L. M. Kueppers

Abstract

A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California’s climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California’s climate was assessed by comparing simulations by WRF3–CLM3.5 and WRF3–Noah to observations from 1982 to 1991.

Using WRF3–CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1). The land-cover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario.

Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of −0.7° to +1°C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.2°–1.2°C reductions in summer daily-mean 2-m air temperature and 2.0°–3.7°C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those projected under climate change this century, projections of climate and vegetation change in this region need to consider these climate–vegetation interactions.

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Christian Seiler and Arnold F. Moene

Abstract

Spatial estimates of actual evapotranspiration are useful for calculating the water balance of river basins, quantifying hydrological services provided by ecosystems, and assessing the hydrological impacts of land-use practices. To provide this information, the authors estimate actual evapotranspiration in central Bolivia with a remote sensing algorithm [Surface Energy Balance Algorithms for Land (SEBAL)]. SEBAL was adapted for the effects of topography (particularly for elevation, slope, and aspect) and atmospheric properties on incoming solar radiation. Instantaneous fluxes are converted to daily and annual fluxes using reference evapotranspiration. The required input data consist of meteorological data and satellite data. Results show more evapotranspiration for humid regions and less evapotranspiration for dry regions and deforested land. Actual evapotranspiration estimates are compared with annual precipitation measurements from 27 meteorological observations. In case annual actual evapotranspiration is estimated correctly, it must be lower than the precipitation measurements. This is the case for 23 stations. The remaining four stations are all located at higher altitudes (>2700 m). Unfortunately, no actual evapotranspiration measurements are available for additional validation purposes.

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David Montenegro Lapola, Ruediger Schaldach, Joseph Alcamo, Alberte Bondeau, Siwa Msangi, Joerg A. Priess, Rafaella Silvestrini, and Britaldo Silveira Soares-Filho

Abstract

Climate change scenarios vary considerably over the Amazon region, with an extreme scenario projecting a dangerous (from the human perspective) increase of 3.8°C in temperature and 30% reduction in precipitation by 2050. The impacts of such climate change on Amazonian land-use dynamics, agricultural production, and deforestation rates are still to be determined. In this study, the authors make a first attempt to assess these impacts through a systemic approach, using a spatially explicit modeling framework to project crop yield and land-use/land-cover changes in the Brazilian Amazon by 2050. The results show that, without any adaptation, climate change may exert a critical impact on the yields of crops commonly cultivated in the Amazon (e.g., soybean yields are reduced by 44% in the worst-case scenario). Therefore, following baseline projections on crop and livestock production, a scenario of severe regional climate change would cause additional deforestation of 181 000 km2 (+20%) in the Amazon and 240 000 km2 (+273%) in the Cerrado compared to a scenario of moderate climate change. Putting an end to deforestation in the Brazilian Amazon forest by 2020 (and of the Cerrado by 2025) would require either a reduction of 26%–40% in livestock production until 2050 or a doubling of average livestock density from 0.74 to 1.46 head per hectare. These results suggest that (i) climate change can affect land use in ways not previously explored, such as the reduction of yields entailing further deforestation, and (ii) there is a need for an integrated/multidisciplinary plan for adaptation to climate change in the Amazon.

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John Risley, Hamid Moradkhani, Lauren Hay, and Steve Markstrom

Abstract

In an earlier global climate-change study, air temperature and precipitation data for the entire twenty-first century simulated from five general circulation models were used as input to precalibrated watershed models for 14 selected basins across the United States. Simulated daily streamflow and energy output from the watershed models were used to compute a range of statistics. With a side-by-side comparison of the statistical analyses for the 14 basins, regional climatic and hydrologic trends over the twenty-first century could be qualitatively identified. Low-flow statistics (95% exceedance, 7-day mean annual minimum, and summer mean monthly streamflow) decreased for almost all basins. Annual maximum daily streamflow also decreased in all the basins, except for all four basins in California and the Pacific Northwest. An analysis of the supply of available energy and water for the basins indicated that ratios of evaporation to precipitation and potential evapotranspiration to precipitation for most of the basins will increase. Probability density functions (PDFs) were developed to assess the uncertainty and multimodality in the impact of climate change on mean annual streamflow variability. Kolmogorov–Smirnov tests showed significant differences between the beginning and ending twenty-first-century PDFs for most of the basins, with the exception of four basins that are located in the western United States. Almost none of the basin PDFs were normally distributed, and two basins in the upper Midwest had PDFs that were extremely dispersed and skewed.

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Jianjun Ge

Abstract

Land-use and land-cover change has been recognized as a key component in global climate change. In the boreal forest ecosystem, fires often cause significant changes in vegetation structure and surface biophysical characteristics, which in turn dramatically change energy and water balances of land surface. Several studies have characterized fire-induced changes in surface energy balance in boreal ecosystem based on site observations. This study provides satellite-observed impacts of a large fire on surface climate in Alaska’s boreal forest. A land surface temperature (LST) product from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) is used as the primary data. Five years after fire, surface temperature over the burned area increased by an average of 2.0°C in the May–August period. The increase reached a maximum of 3.2°C in the year immediately following the fire. The warm anomaly decreased slightly after the second year but remained until the fifth year of the study. These changes in surface temperature may directly affect surface net radiation and thus partition of surface available energy. By documenting continuous and synoptic surface temperature changes over multiple years, this paper demonstrates the value of Earth Observing System (EOS) observations for land–climate interaction research. The observed characteristics of surface temperature change as well as changes in key surface biophysical parameters such as albedo and leaf area index (LAI) can be used in the next generation of climate models to improve the representation of large-scale ecosystem disturbances.

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Laure M. Montandon, Souleymane Fall, Roger A. Pielke Sr., and Dev Niyogi

Abstract

The Global Historical Climate Network version 2 (GHCNv.2) surface temperature dataset is widely used for reconstructions such as the global average surface temperature (GAST) anomaly. Because land use and land cover (LULC) affect temperatures, it is important to examine the spatial distribution and the LULC representation of GHCNv.2 stations. Here, nightlight imagery, two LULC datasets, and a population and cropland historical reconstruction are used to estimate the present and historical worldwide occurrence of LULC types and the number of GHCNv.2 stations within each. Results show that the GHCNv.2 station locations are biased toward urban and cropland (>50% stations versus 18.4% of the world’s land) and past century reclaimed cropland areas (35% stations versus 3.4% land). However, widely occurring LULC such as open shrubland, bare, snow/ice, and evergreen broadleaf forests are underrepresented (14% stations versus 48.1% land), as well as nonurban areas that have remained uncultivated in the past century (14.2% stations versus 43.2% land). Results from the temperature trends over the different landscapes confirm that the temperature trends are different for different LULC and that the GHCNv.2 stations network might be missing on long-term larger positive trends. This opens the possibility that the temperature increases of Earth’s land surface in the last century would be higher than what the GHCNv.2-based GAST analyses report.

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Brandon J. Vogt

Abstract

This study applied remotely sensed cloud-to-ground (CG) lightning strike location data, a digital elevation model (DEM), and a geographic information system (GIS) to characterize negative polarity peak current CG lightning Earth attachment behavior. It explored the propensity for (i) flashes to favor topographic highpoint attachment and (ii) striking distance (a near-Earth attachment force) to increase with peak current. On a 16 000 km2 10-m DEM covering a section of southeast and south-central Colorado, a GIS extraction method identified approximately 5000 hilltop and outcrop highpoints containing at least 15 m of vertical gain in a 300-m radius neighborhood with a minimum horizontal separation of 600 m. Flashes with peak currents ranging from −20 to −119 kiloamps (kA), collected between February 2005 and May 2009, were subdivided into 10 kA classes and mapped on this modified DEM. Buffers of 100-, 200-, and 300-m radii created around each highpoint were used to assess the hypothesis that striking distance increases with higher negative peak current. Point-in-polygon counts compared actual CG strike totals to random point totals received inside buffers. CG strikes favored topographic highpoints by as much as 5.0% when compared to random points. Chi-square goodness-of-fit tests further corroborated that actual CG strikes at highpoints were generated by a more nonrandom process. A positive trend between striking distance and peak current was also observed. Although this correlation has been characterized in controlled settings, this study is the first to document this physical process at real-world landscape scales over multiple years.

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Emmanuel M. Attua and Joshua B. Fisher

Abstract

Urban land-cover change is increasing dramatically in most developing nations. In Africa and in the New Juaben municipality of Ghana in particular, political stability and active socioeconomic progress has pushed the urban frontier into the countryside at the expense of the natural ecosystems at ever-increasing rates. Using Landsat satellite imagery from 1985 to 2003, the study found that the urban core expanded by 10% and the peri-urban areas expanded by 25% over the period. Projecting forward to 2015, it is expected that urban infrastructure will constitute 70% of the total land area in the municipality. Giving way to urban expansion were losses in open woodlands (19%), tree fallow (9%), croplands (4%), and grass fallow (3%), with further declines expected for 2015. Major drivers of land-cover changes are attributed to demographic changes and past microeconomic policies, particularly the Structural Adjustment Programme (SAP); the Economic Recovery Programme (ERP); and, more recently, the Ghana Poverty Reduction Strategy (GPRS). Pluralistic land administration, complications in the land tenure systems, institutional inefficiencies, and lack of capacity in land administration were also key drivers of land-cover changes in the New Juaben municipality. Policy recommendations are presented to address the associated challenges.

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Scott R. Loarie, David B. Lobell, Gregory P. Asner, and Christopher B. Field

Abstract

Albedo is an important factor affecting global climate, but uncertainty in the sources and magnitudes of albedo change has led to simplistic treatments of albedo in climate models. Here, the authors examine nine years (2000–08) of historical 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) albedo estimates across South America to advance understanding of the magnitude and sources of large-scale albedo changes. The authors use the magnitude of albedo change from the arc of deforestation along the southeastern edge of the Brazilian Amazon (+2.8%) as a benchmark for comparison. Large albedo increases (>+2.8%) were 2.2 times more prevalent than similar decreases throughout South America. Changes in surface water drove most large albedo changes that were not caused by vegetative cover change. Decreased surface water in the Santa Fe and Buenos Aires regions of Argentina was responsible for albedo increases exceeding that of the arc of deforestation in magnitude and extent. Although variations in the natural flooding regimes were likely the dominant mechanism driving changes in surface water, it is possible that human manipulations through dams and other agriculture infrastructure contributed. This study demonstrates the substantial role that land-cover and surface water change can play in continental-scale albedo trends and suggests ways to better incorporate these processes into global climate models.

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Silvia Merino-de-Miguel, Federico González-Alonso, Margarita Huesca, Dolors Armenteras, and Carol Franco

Abstract

Satellite-based strategies for burned area mapping may rely on two types of remotely sensed data: postfire reflectance images and active fire detection. This study uses both methods in a synergistic way. In particular, burned area mapping is carried out using MCD43B4 [Moderate Resolution Imaging Spectrometer (MODIS); Terra + Aqua nadir bidirectional reflectance distribution function (BRDF); adjusted reflectance 16-day L3 global 1-km sinusoidal grid V005 (SIN)] postfire datasets and MODIS active fire products. The developed methodology was tested in Colombia, an area not covered by any known MODIS ground antenna, using data from 2004. The resulting burned area map was validated using a high-spatial-resolution Landsat-7 Enhanced Thematic Mapper Plus (ETM+) image and compared to two global burned area products: L3JRC (terrestrial ecosystem monitoring global burnt area product) and MCD45A1 (MODIS Terra + Aqua burned area monthly global 500-m SIN grid V005). The results showed that this method would be of great interest at regional to national scales because it proved to be quick, accurate, and cost effective.

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