An algorithm for determination of aerosol opticalthickness from AVHRR imagery over oceans

Summary The uncertainty in aerosol size distributions is a main source of errors in aerosol optical thickness determined from satellite measurements. To reduce the errors resulting from the uncertainty in aerosol size distributions, we have performed sensitivity analyses. It is found the errors resulting from the uncertainty in aerosol size distribution can be considerably reduced by using the Junge power law to approximate the aerosol size distribution in an actual atmosphere, if the exponent value is determined at the same time. An iterative algorithm is then developed for the simultaneous determination of aerosol optical thickness and the exponent of the Junge power law over ocean areas from the upwelling radiances measured in AVHRR visible and near infrared channels. A number of numerical experiments are carried out to investigate the validity of the Junge power law approximation by assuming the aerosol size distributions in an actual atmosphere are bimodal with different mode parameters, and by using the actual aerosol size distributions determined at several places by Kaufman et al. (1994). The results show that the errors in determined aerosol optical thickness resulting from the Junge power law approach are significantly reduced. The iterative algorithm is investigated further by comparing the aerosol optical thickness deduced from satellite measurement with that observed by a sun photometer. Received October 10, 2001 Revised December 28, 2001     

Insolation estimates for the LITFASS area derived from high resolution satellite data

Summary ?For the LITFASS-98 experiment, from June 1 until June 30, 1998, the spatially resolved insolation at surface could be computed from NOAA-14 AVHRR data applying the modular analysis scheme SESAT (Strahlungs- und Energiebilanzen aus Satellitendaten). The satellite inferred insolation for this period shows for clear-sky regions a good agreement with surface based observations with a rms error of 76 Wm⁻². For cloudy conditions the insolation is overestimated with respect to ground based observations, with a rms error between 83 and 118 Wm⁻², depending on the cloud optical thickness. This overestimation can be explained by the surface heterogeneity, leading to underestimated cloud optical thickness, and also by a fixed relative humidity below clouds (55%, dry atmosphere) and a fixed horizontal visibility (50 km, clear atmosphere). A detailed study of comparable scales in space and time, considering the different observation geometries and sampling intervals, shows that a 30 min ground based observation can be compared with a 8 × 8 km² mean by the satellite data. Received July 12, 2001; revised April 29, 2002; accepted June 7, 2002     

Using Remote Sensing to Assess Russian Forest Fire Carbon Emissions

Russian boreal forests are subject to frequent wildfires. The resulting combustion of large amounts of biomass not only transforms forest vegetation, but it also creates significant carbon emissions that total, according to some authors, from 35–94 Mt C per year. These carbon emissions from forest fires should be considered an important part of the forest ecosystem carbon balance and a significant influence on atmospheric trace gases. In this paper we discuss a new method to assess forest fire damage. This method is based on using multi-spectral high-resolution satellite images, large-scale aerial photography, and declassified images obtained from the space-borne national security systems. A normalized difference vegetation index (NDVI) difference image was produced from pre- and post-fire satellite images from SPOT/HRVIR and RESURS-O/MSU-E images. A close relationship was found between values of the NDVI difference image and forest damage level. High-resolution satellite data and large-scale aerial-photos were used to calibrate the NDVI-derived forest damage map. The method was used for mapping of forest fire extent and damage and for estimating carbon emissions from burned forest areas.     

Wind statistics for coastal stations in Cyprus

Summary ?A statistical analysis of wind speed and direction data for five selected meteorological stations at the Cyprus coast, is carried out in this study. Daily, monthly and annual variations of wind speed are established. The Weibull distribution statistics of the sites are also determined. In addition, an attempt is made to find the sea-breeze circulation effects in the same wind data. The wind statistics obtained are expected to serve as a validation test for wind energy applications, mainly along the southeastern coastline. Received April 5, 2001; revised February 13, 2002; accepted March 3, 2002     

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