ALBERT

Description: The Arctic is especially vulnerable to the long-term transport of aerosols and other pollutants because aerosols can affect the albedo of the surface by deposition on snow and ice. However, aerosol observations for this area are sparse and hence there is considerable uncertainty in the knowledge on the properties of the Arctic aerosol. Arctic aerosol observations are needed to fill this gap because these are among the basic and most important parameters for researching the Arctic environment. Atmospheric remote sensing using satellites offers us an opportunity to describe the aerosol distribution in terms of both local, regional and global coverage. However, AOD retrieval over a bright surface remains a difficult task because it is hard to separate and explicitly describe the contribution of the observed signal reflected by the variable surface and back scattering by the semi-transparent aerosols, especially with a large solar or sensor zenith angle. In this paper, an approach using a synergetic approach with Moderate Resolution Imaging Spectroradiometer (MODIS) data based on prior knowledge is presented. The detailed analysis of the model demonstrates that it is suitable for Arctic region AOD retrieval. Six AERONET stations at high latitude (Andenes, Barrow, Ittoqqortoormiit, OPAL, Thule, and Tiksi) were used for validation, and the correlation coefficient between retrieved AODs and AERONET AODs was 0.75 and the retrieval absolute error is approximately 0.1, while the relative error is 20% (at some stations with clear skies as low as 10% was found). Furthermore, the Russian wildfires that occurred in late July of 2010 and their effect on the Arctic environment is presented; Satellite retrieved AODs in the Arctic increased to 1.0 during 1 August and 15 August 2010, even 2.0, during the burning phase, and subsequently returned to normal values (lower than 0.1), which was fully in line with the AERONET observations. This indicates that the fire plumes were transported to the Arctic region.

Description: Nine years of daily aerosol optical depth (AOD) measurements have been derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data using the Synergetic Retrieval of Aerosol Properties (SRAP) method over China for the period from August 2002 to August 2011, comprising AODs at 470, 550, and 660 nm. Then, the variation over China over the nine years was determined from the derived AOD data. Preliminary daily results show the agreement between the Aerosol Robotic Network (AERONET) AOD data and the derived AOD data. From 1219 daily collocations, representing mutually cloud-free conditions, we find that more than 54% of SRAP-MODIS retrieved AOD values comparing with AERONET-observed values within an expected error envelop of 20%. From 222 monthly averaged collocations, representing mutually cloud-free conditions, we find that more than 63% of SRAP-MODIS retrieved AOD values comparing with AERONET-observed values within an expected error envelop of 15% and more than 70% within an expected error envelop of 20%. In addition, the long-term SRAP AOD dataset has been implemented in analysing case studies involving dust storms, haze and the characteristics of AOD variation over China over the past nine years. It was found that areas in China with high AOD values generally appear in the Inner Mongolia, the North China Plain, Tarim Basin, the Sichuan Basin, the Tibetan Plateau and the middle and lower reaches of the Yangtze River and area with low AOD values generally appear in the Fujian Province, the Yungui Plateau, and northeast plain. The seasonal averaged AOD results indicate that AOD values generally reach their maximum in spring and their minimum in winter. The yearly mean and monthly mean SRAP AOD were also used to study the spatial and temporal aerosol distributions over China. The results indicate that the AOD over China exhibited no obvious change. Monthly averaged AOD in August in Beijing experienced one decreasing processes from 2006 to 2010, especially after 2007. The monthly mean AOD decreased from 0.46 in 2007 to 0.29 in 2010. SRAP AODs were used to study one haze case and dust case. Combining AOD data from the SRAP AOD dataset and HYSPLIT model can forecast the transport of haze. SRAP AOD data are also sensitive enough to reflect the occurrence and intensity of dust weather. Thus, the SRAP AOD dataset can be used to precisely reflect the spatial distribution, concentration distribution and transmission path of dust.