G.J. Collatz

Combining satellite data and biogeochemical models to estimate global effects of human-induced land cover change on carbon emissions and primary productivity

This study uses a global terrestrial carbon cycle model (the Carnegie-Ames-Stanford Approach (CASA) model), a satellite-derived map of existing vegetation, and global maps of natural vegetation to estimate the effects of human-induced land cover change on carbon emissions to the atmosphere and net primary production. We derived two maps approximating global land cover that would exist for current climate in the absence of human disturbance of the landscape, using a procedure that minimizes disagreements between maps of existing and natural vegetation that represent artifacts in the data. Similarly, we simulated monthly fields of the Normalized Difference Vegetation Index, required as input to CASA, for the undisturbed land cover case. Model results estimate total carbon losses from human-induced land cover changes of 182 and 199 Pg for the two simulations, compared with an estimate of 124 Pg for total flux between 1850 and 1990 [Houghton, 1999], suggesting that land cover change prior to 1850 accounted for approximately one-third of total carbon emissions from land use change. Estimates of global carbon loss from the two independent methods, the modeling approach used in this paper and the accounting approach of Houghton [1999], are comparable taking into account carbon losses from agricultural expansion prior to 1850 estimated at 48–57 Pg. However, estimates of regional carbon losses vary considerably, notably in temperate midlatitudes where our estimates indicate higher cumulative carbon loss. Overall, land cover changes reduced global annual net primary productivity (NPP) by approximately 5%, with large regional variations. High-input agriculture in North America and Europe display higher annual NPP than the natural vegetation that would exist in the absence of cropland. However, NPP has been depleted in localized areas in South Asia and Africa by up to 90%. These results provide initial crude estimates, limited by the spatial resolution of the data sets used as input to the model and by the lack of information about transient changes in land cover. The results suggest that a modeling approach can be used to estimate spatially-explicit effects of land cover change on biosphere-atmosphere interactions.

Climate regulation of fire emissions and deforestation in equatorial Asia

Drainage of peatlands and deforestation have led to large-scale fires in equatorial Asia, affecting regional air quality and global concentrations of greenhouse gases. Here we used several sources of satellite data with biogeochemical and atmospheric modeling to better understand and constrain fire emissions from Indonesia, Malaysia, and Papua New Guinea during 2000–2006. We found that average fire emissions from this region [128 ± 51 (1σ) Tg carbon (C) year−1, T = 1012] were comparable to fossil fuel emissions. In Borneo, carbon emissions from fires were highly variable, fluxes during the moderate 2006 El Niño more than 30 times greater than those during the 2000 La Niña (and with a 2000–2006 mean of 74 ± 33 Tg C yr−1). Higher rates of forest loss and larger areas of peatland becoming vulnerable to fire in drought years caused a strong nonlinear relation between drought and fire emissions in southern Borneo. Fire emissions from Sumatra showed a positive linear trend, increasing at a rate of 8 Tg C year−2 (approximately doubling during 2000–2006). These results highlight the importance of including deforestation in future climate agreements. They also imply that land manager responses to expected shifts in tropical precipitation may critically determine the strength of climate–carbon cycle feedbacks during the 21st century.

Daily and 3‐hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003–2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

A human-driven decline in global burned area

Burn less, baby, burn less Humans have, and always have had, a major impact on wildfire activity, which is expected to increase in our warming world. Andela et al. use satellite data to show that, unexpectedly, global burned area declined by ∼25% over the past 18 years, despite the influence of climate. The decrease has been largest in savannas and grasslands because of agricultural expansion and intensification. The decline of burned area has consequences for predictions of future changes to the atmosphere, vegetation, and the terrestrial carbon sink. Science, this issue p. 1356 Global burned area has declined by ~25% over the past 18 years. Fire is an essential Earth system process that alters ecosystem and atmospheric composition. Here we assessed long-term fire trends using multiple satellite data sets. We found that global burned area declined by 24.3 ± 8.8% over the past 18 years. The estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas. Agricultural expansion and intensification were primary drivers of declining fire activity. Fewer and smaller fires reduced aerosol concentrations, modified vegetation structure, and increased the magnitude of the terrestrial carbon sink. Fire models were unable to reproduce the pattern and magnitude of observed declines, suggesting that they may overestimate fire emissions in future projections. Using economic and demographic variables, we developed a conceptual model for predicting fire in human-dominated landscapes.

Long-term trends and interannual variability of forest, savanna and agricultural fires in South America

Background: Landscape fires in South America have considerable impacts on ecosystems, air quality and the climate system. We examined long-term trends and interannual variability of forest, savanna and agricultural fires for the continent during 2001–2012 using multiple satellite-derived fire products. Results: The annual number of active fires in tropical forests increased significantly during 2001–2005. Several satellite-derived metrics, including fire persistence, indicated that this trend was mostly driven by deforestation. Fires between 2005 and 2012 had a small decreasing trend and large year-to-year changes that were associated with climate extremes. Fires in savannas and evergreen forests increased in parallel during drought events in 2005, 2007 and 2010, suggesting similar regional climate controls on fire behavior. Deforestation fire intensity (the number of fires per unit of deforested area) increased significantly within the Brazilian Amazon in areas with small-scale deforestation. Conclusion: Fires associated with forest degradation are becoming an increasingly important component of the fire regime and associated carbon emissions.

ISLSCP Initiative II global data sets: Surface boundary conditions and atmospheric forcings for land-atmosphere studies

[1] We report herein the publication and evaluation of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II global interdisciplinary data record. The record consists of 52 data sets, with a common series in the 10-year period 1985 to 1996. Selected data series extend well beyond this period. All series are coregistered to a common grid and gap-filled for continuity using uniform procedures. We describe briefly the individual data sets within the collection; provide user guidance; and contrast, compare and evaluate those data sets containing similar parameters (land cover, NDVI, albedo, precipitation and near-surface meteorology). We also describe the process used to develop the Initiative II collection which involved a broad international scientific community focused on addressing a well-defined set of carbon, water and energy cycle questions within the context of a specific set of analysis tools. The communities that drove the definition of the Initiative II collection were investigators within the international scientific communities of the Global Energy and Water cycle Experiment, GEWEX, program (http://www.gewex.org/); the International Geosphere/Biosphere Program IGBP (http://www.igbp.kva.se); and the U.S. Global Change Research Program, USGCRP (http://www.usgcrp.gov/). Finally, we report usage statistics based on access and download of files from the ISLSCP Initiative II collection available at http://www.daac.ornl.gov.

Global Fire Emissions Database, Version 4.1 (GFEDv4)

This dataset provides global estimates of monthly burned area, monthly emissions and fractional contributions of different fire types, daily or 3-hourly fields to scale the monthly emissions to higher temporal resolutions, and data for monthly biosphere fluxes. The data are at 0.25-degree latitude by 0.25-degree longitude spatial resolution and are available from June 1995 through 2016, depending on the dataset. Emissions data are available for carbon (C), dry matter (DM), carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), hydrogen (H2), nitrous oxide (N2O), nitrogen oxides (NOx), non-methane hydrocarbons (NMHC), organic carbon (OC), black carbon (BC), particulate matter less than 2.5 microns (PM2.5), total particulate matter (TPM), and sulfur dioxide (SO2) among others. These data are yearly totals by region, globally, and by fire source for each region.

Assessing the magnitude of CO2 flux uncertainty in atmospheric CO2 records using products from NASA's Carbon Monitoring Flux Pilot Project

NASAs Carbon Monitoring System Flux Pilot Project (FPP) was designed to better understand contemporary carbon fluxes by bringing together state-of-the art models with remote sensing data sets. Here we report on simulations using NASAs Goddard Earth Observing System Model, version 5 (GEOS-5) which was used to evaluate the consistency of two different sets of observationally informed land and ocean fluxes with atmospheric CO2 records. Despite the observation inputs, the average difference in annual terrestrial biosphere flux between the two land (NASA Ames Carnegie-Ames-Stanford-Approach (CASA) and CASA-Global Fire Emissions Database version 3 (GFED)) models is 1.7 Pg C for 2009–2010. Ocean models (NASAs Ocean Biogeochemical Model (NOBM) and Estimating the Circulation and Climate of the Ocean Phase II (ECCO2)-Darwin) differ by 35% in their global estimates of carbon flux with particularly strong disagreement in high latitudes. Based upon combinations of terrestrial and ocean fluxes, GEOS-5 reasonably simulated the seasonal cycle observed at Northern Hemisphere surface sites and by the Greenhouse gases Observing SATellite (GOSAT) while the model struggled to simulate the seasonal cycle at Southern Hemisphere surface locations. Though GEOS-5 was able to reasonably reproduce the patterns of XCO2 observed by GOSAT, it struggled to reproduce these aspects of Atmospheric Infrared Sounder observations. Despite large differences between land and ocean flux estimates, resulting differences in atmospheric mixing ratio were small, typically less than 5 ppm at the surface and 3 ppm in the XCO2 column. A statistical analysis based on the variability of observations shows that flux differences of these magnitudes are difficult to distinguish from inherent measurement variability, regardless of the measurement platform.

ISLSCP II MODIS (Collection 4) IGBP Land Cover, 2000-2001

The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the information content of MODIS data in the spectral, temporal, spatial, and directional domains. These are global land cover classifications (dominant type, classification confidence and fractional cover) generated using a full year of MODerate Resolution Imaging Spectroradiometer (MODIS) data covering the period from October 2000 to October 2001. These products describe the geographic distribution of the 17 land cover classification scheme proposed by the International Geosphere-Biosphere Programme (IGBP).

ISLSCP II UNH/GRDC Composite Monthly Runoff

The University of New Hampshire (UNH)/Global Runoff Data Centre (GRDC) composite runoff data combines simulated water balance model runoff estimates derived from climate forcing with monitored river discharge. It can be viewed as a data assimilation applied in a water balance model context (conceptually similar to the commonly used 4DDA techniques used in meteorological modeling). Such a data assimilation scheme preserves the spatial specificity of the water balance calculations while constrained by the more accurate discharge measurement. There are 11 data files in this data set and 1 changemap file which shows the differences between the ISLSCP II land/water mask and the original data set.