Retrieving cloud fraction in the field-of-view of a high-spectral resolution infrared radiometer

The combination of radiance from both clear and cloudy regions of sky within the instrument's field of view (FOV) adds significant uncertainty to retrievals of atmospheric state profiles and cloud microphysical properties from infrared spectroradiometers. In this letter, we use observations of radiance from both the 8-13 and 3-5 /spl mu/m bands to retrieve estimates of the cloud fraction in the instrument's FOV, as well as microphysical cloud properties, from high-spectral-resolution infrared radiometers. Cloud fraction derived from imagers as well as high-time-resolution observations show good agreement and high correlation with our derived cloud fraction values. This is shown for both ground-based and aircraft-based observations. We also demonstrate that the use of the additional information in the 3-5 /spl mu/m band extends the dynamic range and accuracy of microphysical properties that can be retrieved from infrared radiance data.     

Combined Digital Photogrammetry and Time-of-Flight Laser Scanning for Monitoring Cliff Evolution

Although cliffs form approximately 75% of the world's coastline, the understanding of the processes through which they evolve remains limited because of a lack of quantitative data on the morphological changes they undergo. In this paper the combination of terrestrial time-of-flight laser scanning with high-resolution digital photogrammetry is examined to generate high-quality data-sets pertaining to the geomorphic processes governing cliff development. The study was undertaken on a section of hard rock cliffs in North Yorkshire, UK, which has been monitored over a 12-month period. High-density, laser-scanned point clouds have been used to produce an accurate representation of these complex surfaces, free from the optical variations that degrade photographic data. These data-sets have been combined with high-resolution photographic monitoring, resampled with the fixed accuracies of the terrestrial laser survey, to generate a new approach to recording the volumetric changes in complex coastal cliffs. This has led to significant improvements in the understanding of the activity patterns of coastal cliffs.     

Effects of detailed soil spatial information on watershed modeling across different model scales

Hydro-ecological modelers often use spatial variation of soil information derived from conventional soil surveys in simulation of hydro-ecological processes over watersheds at mesoscale (10–100 km²). Conventional soil surveys are not designed to provide the same level of spatial detail as terrain and vegetation inputs derived from digital terrain analysis and remote sensing techniques. Soil property layers derived from conventional soil surveys are often incompatible with detailed terrain and remotely sensed data due to their difference in scales. The objective of this research is to examine the effect of scale incompatibility between soil information and the detailed digital terrain data and remotely sensed information by comparing simulations of watershed processes based on the conventional soil map and those simulations based on detailed soil information across different simulation scales. The detailed soil spatial information was derived using a GIS (geographical information system), expert knowledge, and fuzzy logic based predictive mapping approach (Soil Land Inference Model, SoLIM). The Regional Hydro-Ecological Simulation System (RHESSys) is used to simulate two watershed processes: net photosynthesis and stream flow. The difference between simulation based on the conventional soil map and that based on the detailed predictive soil map at a given simulation scale is perceived to be the effect of scale incompatibility between conventional soil data and the rest of the (more detailed) data layers at that scale. Two modeling approaches were taken in this study: the lumped parameter approach and the distributed parameter approach. The results over two small watersheds indicate that the effect does not necessarily always increase or decrease as the simulation scale becomes finer or coarser. For a given watershed there seems to be a fixed scale at which the effect is consistently low for the simulated processes with both the lumped parameter approach and the distributed parameter approach.     

Check dam positioning by prioritization of micro-watersheds using SYI model and morphometric analysis — Remote sensing and GIS perspective

Sediment Yield Index (SYI) model and results of morphometric analysis have been used to prioritize watersheds and to locate sites for checkdam positioning in Tarafeni watershed in Midnapur district. West Bengal. Various thematic maps such as land use/land cover, slope, drainage, soil etc. were prepared from 1RS ID LISS III digital data, SOI toposheets of 1:50,000 scale and other reference maps. Morphometric parameters such as bifurcation ratio (R_b). drainage density (D_d), texture ratio (T), length of overland flow (L_o), stream frequency (F_u), compactness coefficient (C_c), circularity ratio (R_c), elongation ratio (E_r), shape factor (B_s) and form factor (R_f) were computed. Automated demarcation of prioritization of micro-watersheds was done by using GIS overlaying technique by assigning weight factors to all the identified features in each thematic map and ranks were assigned to the morphometric parameters. Five categories of priority viz., very high, high, medium, low and very low, were given to all the watersheds in both the methods. Sixty-two micro-watersheds using SYI method and twenty-three micro-watersheds using morphometric have been prioritized as very high priority. Final priority map was prepared by considering the commonly occurred very high-prioritized micro-watersheds in both SYI model and morphometric analysis. Twenty-four suitable sites were identified for check dam construction in 21 highly prioritized watersheds. It is proved that integrated study of SYI model and morphometric analysis yield good result in prioritization of watersheds.     

A 500 hPa synoptic wildland fire climatology for large Canadian forest fires, 1959–1996

Summary In Canada, the average annual area of burned forest has increased from around 1 million ha in the 1970’s to over 2.5 million ha in the 1990’s. A previous study has identified the link between anomalous mid-tropospheric circulation at 500 hPa over northern North America and wildland fire severity activity in various large regions of Canada over the entire May to August fire season. In this study, a northern North American study region of the hemispheric gridded 5° latitude by 10° longitude 500 hPa dataset is identified and analysed from 1959 to 1996 for a sequence of six monthly periods through the fire season, beginning in April and ending in September. Synoptic types, or modes of upper air behavior, are determined objectively by the eigenvector method employing K-means cluster analysis. Monthly burned areas from the Canadian Large Fire Database (LFDB) for the same period, 1959 to 1996, are analysed in conjunction with the classified monthly 500 hPa synoptic types. Relationships between common monthly patterns of anomalous upper flow and spatial patterns of large fire occurrence are examined at the ecozone level. Average occurrence of a monthly synoptic type associated with very large area burned is approximately 18% of the years from 1959 to 1996. The largest areas burned during the main fire (May to August) season occur in the western Boreal and Taiga ecozones – the Taiga Plains, Taiga Shield, Boreal West Shield and Boreal Plains. Monthly burned areas are also analysed temporally in conjunction with a calculated monthly zonal index (Zi_m) for two separate areas defined to cover western and eastern Canada. In both western and eastern Canada, high area burned is associated with synoptic types with mid-tropospheric ridging in the proximity of the affected region and low Zi_m with weak westerlies and strong meridional flow over western Canada. Received April 3, 2001 Revised July 13, 2001     

Aerosol characterization and optical thickness retrievalsusing GOME and METEOSAT satellite data

Summary ?Retrievals of atmospheric aerosol optical thickness are highly dependent on the choice of the class describing the aerosol properties leading to significant errors while using classes available in the literature. High spectral resolution measurements from GOME (Global Ozone Monitoring Experiment) between the ultraviolet and the near infrared can be used for an accurate characterization of the aerosol optical properties. The radiometer MVIRI (METEOSAT Visible and Infrared Imager) on board the geostationary satellite METEOSAT, while being equipped only with broadband VIS channel, ensures an adequate half-hourly monitoring of the atmospheric conditions over a large portion of the Earth. The present algorithm is based on a combination of data from both sensors for the retrieval of the aerosol optical thickness at the reference wavelength of 0.55 μm (AOT). A case of a desert dust outbreak from the African continent over the Atlantic Ocean is examined. AOT values obtained using a priori fixed classes taken from the literature are compared with those retrieved with this algorithm using the GOME-derived classes. Systematic differences of the order of a few tenths on average are found which remain significant also after considering the measurement errors. This represents a novelty introduced by the synergetic use of both sensors. Received March 13, 2002