Global estimation of burned area using MODIS active fire observations

We present a method for estimating monthly burned area globally at 1° spatial resolution using Terra MODIS data and ancillary vegetation cover information. Using regression trees constructed for 14 different global regions, MODIS active fire observations were calibrated to burned area estimates derived from 500-m MODIS imagery based on the assumption that burned area is proportional to counts of fire pixels. Unlike earlier methods, we allow the constant of proportionality to vary as a function of tree and herbaceous vegetation cover, and the mean size of monthly cumulative fire-pixel clusters. In areas undergoing active deforestation, we implemented a subsequent correction based on tree cover information and a simple measure of fire persistence. Regions showing good agreement between predicted and observed burned area included Boreal Asia, Central Asia, Europe, and Temperate North America, where the estimates produced by the regression trees were relatively accurate and precise. Poorest agreement was found for southern-hemisphere South America, where predicted values of burned area are both inaccurate and imprecise; this is most likely a consequence of multiple factors that include extremely persistent cloud cover, and lower quality of the 500-m burned area maps used for calibration. Application of our approach to the nine remaining regions yielded comparatively accurate, but less precise, estimates of monthly burned area. We applied the regional regression trees to the entire archive of Terra MODIS fire data to produce a monthly global burned area data set spanning late 2000 through mid-2005. Annual totals derived from this approach showed good agreement with independent annual estimates available for nine Canadian provinces, the United States, and Russia. With our data set we estimate the global annual burned area for the years 2001-2004 to vary between 2.97 million and 3.74 million km², with the maximum occurring in 2001. These coarse-resolution burned area estimates may serve as a useful interim product until long-term burned area data sets from multiple sensors and retrieval approaches become available

To What Extent Can Vegetation Mitigate Greenhouse Warming? A Modeling Approach

Climate models participating in the IPCC Fourth Assessment Report indicate that under a 2xCO2 environment, runoff would increase faster than precipitation overland. However, observations over large U.S watersheds indicate otherwise. This inconsistency suggests that there may be important feedbacks between climate and land surface unaccounted for in the present generation of models. We postulate that the increase in precipitation associated with the increase in CO2 is also increasing vegetation density, which may already be feeding back onto climate. Including this feedback in a climate model simulation resulted in precipitation and runoff trends consistent with observations and reduced the warming by 0.6OC overland. This unaccounted for missing water may be linked to about 10% of the missing land carbon sink. A recent compilation of outputs from 19 coupled atmosphere-ocean general circulation models used in the IPCC Fourth Assessment Report (AR4) shows projected increases in air temperature, precipitation and river discharge for 24 major rivers in the world in response to doubling CO2 by the end of the century (1). The ensemble mean from these models also indicates that, compared to their respective baselines overland, the global mean of the runoff change would increase faster (8.9% per year) than that of the precipitation (5% per year). We analyze century-scale observed annual runoff time-series (1901-2002) over 9 hydrological units covering large regions of the Eastern United States (Fig.1) compiled by the United States Geological Survey (USGS)(2). These regions were selected because they are the most forested; the least water-limited and are not under extensive irrigation. We compare these time-series to similar time-series of observed annual precipitation anomalies spanning the period 1900-1995 (3). Both time-series exhibit a positive longterm trend (Fig. 2); however, in contrast to the analysis of (I), these historic data records show that the rate of precipitation increase is 5.5 % per year, roughly double the rate of runoff increase of 3.1 % per year

Time-dependent inversion estimates of global biomass-burning CO emissions using Measurement of Pollution in the Troposphere (MOPITT) measurements

We present an inverse-modeling analysis of CO emissions using column CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT) instrument and a global chemical transport model (GEOS-CHEM). We first focus on the information content of MOPITT CO column retrievals in terms of constraining CO emissions associated with biomass burning and fossil fuel/biofuel use. Our analysis shows that seasonal variation of biomass-burning CO emissions in Africa, South America, and Southeast Asia can be characterized using monthly mean MOPITT CO columns. For the fossil fuel/biofuel source category the derived monthly mean emission estimates are noisy even when the error statistics are accurately known, precluding a characterization of seasonal variations of regional CO emissions for this source category. The derived estimate of CO emissions from biomass burning in southern Africa during the June-July 2000 period is significantly higher than the prior estimate (prior, 34 Tg; posterior, 13 Tg). We also estimate that emissions are higher relative to the prior estimate in northern Africa during December 2000 to January 2001 and lower relative to the prior estimate in Central America and Oceania/Indonesia during April-May and September-October 2000, respectively. While these adjustments provide better agreement of the model with MOPITT CO column fields and with independent measurements of surface CO from National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostics Laboratory at background sites in the Northern Hemisphere, some systematic differences between modeled and measured CO fields persist, including model overestimation of background surface CO in the Southern Hemisphere. Characterizing and accounting for underlying biases in the measurement model system are needed to improve the robustness of the top-down estimate. Copyright 2006 by the American Geophysical Union

Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling

Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activity, and deforestation rates to estimate emissions for the Brazilian state of Mato Grosso during 2001–2005. Our model of DEforestation CArbon Fluxes (DECAF) runs at 250-m spatial resolution with a monthly time step to capture spatial and temporal heterogeneity in fire dynamics in our study area within the ''arc of deforestation'', the southern and eastern fringe of the Amazon tropical forest where agricultural expansion is most concentrated. Fire emissions estimates from our modelling framework were on average 90 Tg C year<sup>−1</sup>, mostly stemming from fires associated with deforestation (74%) with smaller contributions from fires from conversions of Cerrado or pastures to cropland (19%) and pasture fires (7%). In terms of carbon dynamics, about 80% of the aboveground living biomass and litter was combusted when forests were converted to pasture, and 89% when converted to cropland because of the highly mechanized nature of the deforestation process in Mato Grosso. The trajectory of land use change from forest to other land uses often takes more than one year, and part of the biomass that was not burned in the dry season following deforestation burned in consecutive years. This led to a partial decoupling of annual deforestation rates and fire emissions, and lowered interannual variability in fire emissions. Interannual variability in the region was somewhat dampened as well because annual emissions from fires following deforestation and from maintenance fires did not covary, although the effect was small due to the minor contribution of maintenance fires. Our results demonstrate how the DECAF model can be used to model deforestation fire emissions at relatively high spatial and temporal resolutions. Detailed model output is suitable for policy applications concerned with annual emissions estimates distributed among post-clearing land uses and science applications in combination with atmospheric emissions modelling to provide constrained global deforestation fire emissions estimates. DECAF currently estimates emissions from fire; future efforts can incorporate other aspects of net carbon emissions from deforestation including soil respiration and regrowth

Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009)

New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 Pg C year⁻¹ with significant interannual variability during 1997–2001 (2.8 Pg C year⁻¹ in 1998 and 1.6 Pg C year⁻¹ in 2001). Globally, emissions during 2002–2007 were relatively constant (around 2.1 Pg C year⁻¹) before declining in 2008 (1.7 Pg C year⁻¹) and 2009 (1.5 Pg C year⁻¹) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002–2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001–2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH₄, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year⁻¹. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series

Measurements of CO2 exchange over a woodland savanna (Cerrado Sensu stricto) in southeast Brasil

The technique of eddy correlation was used to measure the net ecosystem exchange over a woodland savanna (Cerrado Sensu stricto) site (Gleba Pé de Gigante) in southeast Brazil. The data set included measurements of climatological variables and soil respiration using static soil chambers. Data were collected during the period from 10 October 2000 to 30 March 2002. Measured soil respiration showed average values of 4.8 molCO2 m-2s-1 year round. Its seasonal differences varied from 2 to 8 molCO2 m-2s-1 (Q10 = 4.9) during the dry (April to August) and wet season, respectively, and was concurrent with soil temperature and moisture variability. The net ecosystem CO2 flux (NEE) variability is controlled by solar radiation, temperature and air humidity on diel course. Seasonally, soil moisture plays a strong role by inducing litterfall, reducing canopy photosynthetic activity and soil respiration. The net sign of NEE is negative (sink) in the wet season and early dry season, with rates around -25 kgC ha-1day-1, and values as low as 40 kgC ha-1day-1. NEE was positive (source) during most of the dry season, and changed into negative at the onset of rainy season. At critical times of soil moisture stress during the late dry season, the ecosystem experienced photosynthesis during daytime, although the net sign is positive (emission). Concurrent with dry season, the values appeared progressively positive from 5 to as much as 50 kgC ha-1day-1. The annual NEE sum appeared to be nearly in balance, or more exactly a small sink, equal to 0.1 0.3 tC ha-1yr-1, which we regard possibly as a realistic one, giving the constraining conditions imposed to the turbulent flux calculation, and favourable hypothesis of succession stages, climatic variability and CO2 fertilization

Effects of temperature at constant air dew point on leaf carboxylation efficiency and CO 2 compensation point of different leaf types

The effect of temperature on photosynthesis at constant water-vapor pressure in the air was investigated using two sclerophyll species, Arbutus unedo and Quercus suber , and one mesophytic species, Spinacia oleracea . Photosynthesis and transpiration were measured over a range of temperatures, 20–39° C. The external concentration of CO 2 was varied from 340 μbar to near CO 2 compensation. The initial slope (carboxylation efficiency, CE) of the photosynthetic response to intercellular CO 2 concentration, the CO 2 compensation point (Γ), and the extrapolated rate of CO 2 released into CO 2 -free air ( R i ) were calculated. At an external CO 2 concentration of 320–340 μbar CO 2 , photosynthesis decreased with temperature in all species. The effect of temperature on Γ was similar in all species. While CE in S. oleracea changed little with temperature, CE decreased by 50% in Q. suber as temperature increased from 25 to 34° C. Arbutus unedo also exhibited a decrease in CE at higher temperatures but not as marked as Q. suber . The absolut value of R i increased with temperature in S. oleracea , while changing little or decreasing in the sclerophylls. Variations in Γ and R i of the sclerophyll species are not consistent with greater increase of respiration with temperature in the light in these species compared with S. oleracea .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47470/1/425_2004_Article_BF00397389.pd

Heterogeneous surface fluxes and their effects on the SGP CART site

The treatment of subgrid-scale variations of surface properties and the resultant spatial variations of sensible and latent heat fluxes has received increasing attention in recent years. Mesoscale numerical simulations of highly idealized conditions, in which strong flux contrasts exist between adjacent surfaces, have shown that under some circumstances the secondary circulations induced by land-use differences can significantly affect the properties of the planetary boundary layer (PBL) and the region of the atmosphere above the PBL. At the Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site, the fluxes from different land-surface types are not expected to differ as dramatically as those found in idealized simulations. Although the corresponding effects on the atmosphere should thus be less dramatic, they are still potentially important. From an ARM perspective, in tests of single column models (SCMs) it would be useful to understand the effects of the lower boundary conditions on model performance. We describe here our initial efforts to characterize the variable surface fluxes over the CART site and to assess their effects on the PBL that are important for the performance of SCMs