Assessing variability and long-term trends in burned area by merging multiple satellite fire products

Long term, high quality estimates of burned area are needed for improving both prognostic and diagnostic fire emissions models and for assessing feedbacks between fire and the climate system. We developed global, monthly burned area estimates aggregated to 0.5° spatial resolution for the time period July 1996 through mid-2009 using four satellite data sets. From 2001ĝ€ "2009, our primary data source was 500-m burned area maps produced using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance imagery; more than 90% of the global area burned during this time period was mapped in this fashion. During times when the 500-m MODIS data were not available, we used a combination of local regression and regional regression trees developed over periods when burned area and Terra MODIS active fire data were available to indirectly estimate burned area. Cross-calibration with fire observations from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and the Along-Track Scanning Radiometer (ATSR) allowed the data set to be extended prior to the MODIS era. With our data set we estimated that the global annual area burned for the years 1997ĝ€ "2008 varied between 330 and 431 Mha, with the maximum occurring in 1998. We compared our data set to the recent GFED2, L3JRC, GLOBCARBON, and MODIS MCD45A1 global burned area products and found substantial differences in many regions. Lastly, we assessed the interannual variability and long-term trends in global burned area over the past 13 years. This burned area time series serves as the basis for the third version of the Global Fire Emissions Database (GFED3) estimates of trace gas and aerosol emissions.

Using fractal downscaling of satellite precipitation products for hydrometeorological applications

The objective of spatial downscaling strategies is to increase the information content of coarse datasets at smaller scales. In the case of quantitative precipitation estimation (QPE) for hydrological applications, the goal is to close the scale gap between the spatial resolution of coarse datasets (e.g., gridded satellite precipitation products at resolution L × L) and the high resolution (l × l; L»l) necessary to capture the spatial features that determine spatial variability of water flows and water stores in the landscape. In essence, the downscaling process consists of weaving subgrid-scale heterogeneity over a desired range of wavelengths in the original field. The defining question is, which properties, statistical and otherwise, of the target field (the known observable at the desired spatial resolution) should be matched, with the caveat that downscaling methods be as a general as possible and therefore ideally without case-specific constraints and/or calibration requirements? Here, the attention is focused on two simple fractal downscaling methods using iterated functions systems (IFS) and fractal Brownian surfaces (FBS) that meet this requirement. The two methods were applied to disaggregate spatially 27 summertime convective storms in the central United States during 2007 at three consecutive times (1800, 2100, and 0000 UTC, thus 81 fields overall) from the Tropical Rainfall Measuring Mission (TRMM) version 6 (V6) 3B42 precipitation product (~25-km grid spacing) to the same resolution as the NCEP stage IV products (~4-km grid spacing). Results from bilinear interpolation are used as the control. A fundamental distinction between IFS and FBS is that the latter implies a distribution of downscaled fields and thus an ensemble solution, whereas the former provides a single solution. The downscaling effectiveness is assessed using fractal measures (the spectral exponent β, fractal dimension D, Hurst coefficient H, and roughness amplitude R) and traditional operational scores statistics scores [false alarm rate (FR), probability of detection (PD), threat score (TS), and Heidke skill score (HSS)], as well as bias and the root-mean-square error (RMSE). The results show that both IFS and FBS fractal interpolation perform well with regard to operational skill scores, and they meet the additional requirement of generating structurally consistent fields. Furthermore, confidence intervals can be directly generated from the FBS ensemble. The results were used to diagnose errors relevant for hydrometeorological applications, in particular a spatial displacement with characteristic length of at least 50 km (2500 km2) in the location of peak rainfall intensities for the cases studied. © 2010 American Meteorological Society.

Rare variants create synthetic genome-wide associations.

Genome-wide association studies (GWAS) have now identified at least 2,000 common variants that appear associated with common diseases or related traits (http://www.genome.gov/gwastudies), hundreds of which have been convincingly replicated. It is generally thought that the associated markers reflect the effect of a nearby common (minor allele frequency >0.05) causal site, which is associated with the marker, leading to extensive resequencing efforts to find causal sites. We propose as an alternative explanation that variants much less common than the associated one may create "synthetic associations" by occurring, stochastically, more often in association with one of the alleles at the common site versus the other allele. Although synthetic associations are an obvious theoretical possibility, they have never been systematically explored as a possible explanation for GWAS findings. Here, we use simple computer simulations to show the conditions under which such synthetic associations will arise and how they may be recognized. We show that they are not only possible, but inevitable, and that under simple but reasonable genetic models, they are likely to account for or contribute to many of the recently identified signals reported in genome-wide association studies. We also illustrate the behavior of synthetic associations in real datasets by showing that rare causal mutations responsible for both hearing loss and sickle cell anemia create genome-wide significant synthetic associations, in the latter case extending over a 2.5-Mb interval encompassing scores of "blocks" of associated variants. In conclusion, uncommon or rare genetic variants can easily create synthetic associations that are credited to common variants, and this possibility requires careful consideration in the interpretation and follow up of GWAS signals.

Fate of products of degradation processes: consequences for climatic change.

The end products of atmospheric degradation are not only CO2 and H2O but also sulfate and nitrate depending on the chemical composition of the substances which are subject to degradation processes. Atmospheric degradation has thus a direct influence on the radiative balance of the earth not only due to formation of greenhouse gases but also of aerosols. Aerosols of a diameter of 0.1 to 2 micrometer, reflect short wave sunlight very efficiently leading to a radiative forcing which is estimated to be about -0.8 watt per m2 by IPCC. Aerosols also influence the radiative balance by way of cloud formation. If more aerosols are present, clouds are formed with more and smaller droplets and these clouds have a higher albedo and are more stable compared to clouds with larger droplets. Not only sulfate, but also nitrate and polar organic compounds, formed as intermediates in degradation processes, contribute to this direct and indirect aerosol effect. Estimates for the Netherlands indicate a direct effect of -4 watt m-2 and an indirect effect of as large as -5 watt m-2. About one third is caused by sulfates, one third by nitrates and last third by polar organic compounds. This large radiative forcing is obviously non-uniform and depends on local conditions.

Peptide interfacial biomaterials improve endothelial cell adhesion and spreading on synthetic polyglycolic acid materials.

Resorbable scaffolds such as polyglycolic acid (PGA) are employed in a number of clinical and tissue engineering applications owing to their desirable property of allowing remodeling to form native tissue over time. However, native PGA does not promote endothelial cell adhesion. Here we describe a novel treatment with hetero-bifunctional peptide linkers, termed "interfacial biomaterials" (IFBMs), which are used to alter the surface of PGA to provide appropriate biological cues. IFBMs couple an affinity peptide for the material with a biologically active peptide that promotes desired cellular responses. One such PGA affinity peptide was coupled to the integrin binding domain, Arg-Gly-Asp (RGD), to build a chemically synthesized bimodular 27 amino acid peptide that mediated interactions between PGA and integrin receptors on endothelial cells. Quartz crystal microbalance with dissipation monitoring (QCMD) was used to determine the association constant (K (A) 1 x 10(7) M(-1)) and surface thickness (~3.5 nm). Cell binding studies indicated that IFBM efficiently mediated adhesion, spreading, and cytoskeletal organization of endothelial cells on PGA in an integrin-dependent manner. We show that the IFBM peptide promotes a 200% increase in endothelial cell binding to PGA as well as 70-120% increase in cell spreading from 30 to 60 minutes after plating.