Global Climate Change I
Presiding: S Burr, Cornell University; R Davis, California Institute of Technology
GC34A-01 15:30h
Micromorphology and Trace Metal Content as Indicators of Bleaching in Skeletons of Modern and Holocene Corals
Morphology and trace metal content of scleractinian corals have previously been used as proxies for past environmental conditions, but no proxy for the health of ancient corals currently exists. Skeletal material associated with bleached and non-bleached tissue from Recent Porites divaricata and Montastrea franksii were analyzed with SEM and ICPAES. Both morphology and trace metal content differed between skeletal material associated with bleached and non-bleached tissue in P. divaricata. SEM analysis showed skeletal corallites associated with unbleached tissue had well-defined septal and columellar denticles. Skeletal corallites associated with bleached tissue had weakly-defined denticles, many appearing rudimentary. SEM analysis was inconclusive for morphological differences between samples known to have been bleached and non-bleached in M. franksii. Significantly higher trace metal/Ca ratios were found with ICPAES for Ag, As, Cd, and Co between skeletal material associated with bleached than with non-bleached tissue in P. divaricata, and Ag, As, P, and Zn between skeletal material associated with bleached than with non-bleached tissue in M. franksii. The presence of these differences suggested the processes of skeletogenesis and the uptake and deposition of trace metals in the scleractinian skeleton were affected by bleaching. Mid-Holocene (~5,000 ybp) Porites sp. were tested to determine if such indicators of bleaching might be observed in the fossil record. Skeletal morphology and trace metal content differ between Recent bleached and non-bleached Porites divaricata from Punta Cana, Dominican Republic, trace metal content differs between bleached and non-bleached Montastrea franksii from Looe Key, FL. It is possible that these indicators allow the recognition of coral bleaching in the fossil record
GC34A-02 16:00h
Proxy Measures of 4-Year Differences in Cloud Radiative Forcing Using MISR Data from the Terra Satellite
The MISR instrument on the Terra satellite has functioned almost flawlessly since its launch in December 1999. While many of its products relating to cloud properties and top-of-atmosphere radiative fluxes are still being refined, consistently (re)processed products based on data measured in 2000 and 2004 can now be compared to examine potential trends in spectral albedo and cloud-top heights. These measures can even be interpreted as proxies of trends in cloud radiative forcing. Here we present the 4-year differences obtained so far on a seasonal, regional, and global basis. Of particular initial interest is an assessment of MISR's sensitivity to trend detection, given its careful approach to radiometric calibration, relevant to albedo trends, and to its use of purely geometric (stereo) techniques to detect trends in cloud-top heights. Preliminary analysis indicates a sampling sensitivity of approximately ~0.002 and ~25 m in the global, monthly, 4-year difference of spectral albedo and cloud-top height, respectively. By minimizing the uncertainties due to sampling sensitivity, it is then possible to examine trends due to other factors, including residual calibration uncertainty, as well as apparent secular, periodic and episodic changes in the climate system. While MISR makes no direct measurements of the longwave effect of clouds, changes in their height may be used as a proxy for this, noting that a height change of +200 m is roughly equivalent to an albedo reduction of 0.01 in terms of its global mean significance. Thus, comparison on this basis also provides indicators of trends in net cloud radiative forcing. So far, we note that many of the 4-year anomalies in albedo and height appear to have compensating effects, whereby higher clouds are associated with larger albedos.
GC34A-03 16:30h
Improved Semi-Arid Vegetation Type Differentiation at Community Level Using MISR Multi-Angular and Multi-Spectral Observations and SVM algorithms
Mapping accurately community types is one of main challenges for monitoring semi-arid grasslands with remote sensing. Multi-angle approach has been proved useful for mapping vegetation types in desert. Multi-angle Imaging SpectroRadiometer (MISR) Global Mode provides 275 meters spatial resolution 4 spectral bands (blue, green, red and near-infrared) observations at nadir, and red band 8 multi-angular observations (26.1, 45.6, 60.0 and 70.5 degrees from the vertical both forward and afterward of nadir). And MISR 233 orbit paths make up each 16-day global repeat cycle. In this paper, support vector machine (SVM)-based algorithms are used to classify vegetation types at community level in New Mexico desert. Besides the original MISR observations, the k parameter at red band, which is derived from RPV BRDF model, and structural scattering index, which is derived from volumetric weight at near-infrared band and geometric weight at red band of a linear semi-empirical kernel-driven BRDF model (RossThick-LiSparse-Reciprocal model), are introduced into the SVM algorithms as additional information dimensions. The k parameter is capable to expose surface cover heterogeneity at the sub-pixel scale resolution, and the structural scattering index represents the vegetation structural information in the pixel. So the two additional parameters can bring new information to the SVM classification. In order to get the structural scattering index, MISR 1100 meters spatial resolution near-infrared multi-angle observations are resampled to 275 meters pixel so that the volumetric weight at near-infrared band of the linear semi-empirical kernel-driven BRDF model can be obtained at same spatial resolution of geometric weight at red band. Preliminary results based on part data have showed that 72.9 precent or more accuracy can be expected.
GC34A-04 16:45h
Global Water Resources Under Future Changes: Toward an Improved Estimation
Global water resources availability in the 21st century is going to be an important concern. Despite its international recognition, however, until now there are very limited global estimates of water resources, which considered the geographical linkage between water supply and demand, defined by runoff and its passage through river network. The available studies are again insufficient due to reasons like different approaches in defining water scarcity, simply based on annual average figures without considering the inter-annual or seasonal variability, absence of the inclusion of virtual water trading, etc. In this study, global water resources under future climate change associated with several socio-economic factors were estimated varying over both temporal and spatial scale. Global runoff data was derived from several land surface models under the GSWP2 (Global Soil Wetness Project) project, which was further processed through TRIP (Total Runoff Integrated Pathways) river routing model to produce a 0.5x0.5 degree grid based figure. Water abstraction was estimated for the same spatial resolution for three sectors as domestic, industrial and agriculture. GCM outputs from CCSR and MRI were collected to predict the runoff changes. Socio-economic factors like population and GDP growth, affected mostly the demand part. Instead of simply looking at annual figures, monthly figures for both supply and demand was considered. For an average year, such a seasonal variability can affect the crop yield significantly. In other case, inter-annual variability of runoff can cause for an absolute drought condition. To account for vulnerabilities of a region to future changes, both inter-annual and seasonal effects were thus considered. At present, the study assumed the future agricultural water uses to be unchanged under climatic changes. In this connection, EPIC model is underway to use for estimating future agricultural water demand under climatic changes on a monthly basis. From the estimation of present stress level (withdrawal to resource ratio), the months between January to May was found to have the highest number of population above water stress level, while the months between June to August having lower population in stress. The regions suffering from high seasonal variability are those of Asian monsoon zone, south-central Africa and central-east part of South America. Inter-annual variability, on the other hand, is dominant mostly along the Middle-east or Sahara regions and the western part of South America and Latin America. Virtual water trading among countries was estimated on per capita basis. It shows that many Middle east countries are able to compensate their water stress significantly through virtual water trading. The overall effect of climate change on lowering of river runoff mostly affected Europe, southern part of China and Latin America. India or Central Africa have better runoff availability under changing climate, but still subject to a higher water stress because of socio-economic factors like high population growth and expected increase in rate of water uses. Decrease in population as well as saturation level of maximum water uses along most European countries, on the contrary, relaxed the pressure of lowering river runoff, causing no significant change in future stress.