Mathematics – Logic
Scientific paper
Dec 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004agufm.p14a..02w&link_type=abstract
American Geophysical Union, Fall Meeting 2004, abstract #P14A-02
Mathematics
Logic
3322 Land/Atmosphere Interactions, 1815 Erosion And Sedimentation, 1610 Atmosphere (0315, 0325), 1640 Remote Sensing, 0305 Aerosols And Particles (0345, 4801)
Scientific paper
Mineral aerosols are an important component of the Earth's climate system and potentially a major forcing mechanism for climate change. Monitoring aeolian dust dynamics and improving our understanding of the major environmental controls influencing dust storm occurrence is therefore a key scientific challenge. Meteorological records are regularly used to calculate wind erosion indices for modelling conditions conducive to dust storm occurrence and remote sensing (e.g. TOMS) is increasingly being used as a method for monitoring regional atmospheric aerosol loading. Given that direct measurements of dust concentrations and deposition rates are very limited in number, very few studies have investigated the associations between wind erosion indices, satellite monitoring of aerosol loadings and actual dust flux. In this paper we report the findings of a study aiming to validate correlations between measured dust deposition, meteorological conditions and TOMS aerosol index in the region adjacent to the southern shore of the Aral Sea. Monthly measurements of dust deposition were collected from May 2000 to May 2001 at 7 sites in Karakalpakstan. Daily meteorological data from these sites were used to calculate a climatic index of wind erosion parameterised using a variety of measures of available soil moisture (P-E, mean rainfall, number of rain days) and a range of measures of wind erosivity (mean wind speed, dimensionless vector units, frequency over threshold). Additionally, monthly N7 TOMS and EP TOMS AI data were extracted for a coincident period for 3 areas covering the SW, S and SE regions adjacent to the Aral Sea. Regression analysis was used to identify relationships between direct measurements of dust deposition, various adaptations of the wind erosion index and the TOMS AI data. Findings from the study indicate strong negative (and exponential) relationships between rates of dust deposition flux and various measures of soil moisture availability at the annual and monthly temporal scale. Surprisingly, relationships between dust flux and all measures of wind power were poor. These results suggest that the occurrence of dust storms in the region is strongly controlled by seasonally changing surface erodibility parameters (surface crusting, vegetation growth, damp sediment) rather than erosivity factors. Time lags associated with the dynamics of these erodibility parameters resulted in only weak associations between dust flux and environmental controls over time periods less than one month and discussion highlights the complex role of such surface characteristics in modelling of dust emissions. Particularly strong associations between TOMS AI and dust flux were found suggesting that at temporal scales greater than one month satellite monitoring can provide a useful tool for describing regional dust occurrence.
Bryant Robert G.
Hubbard Richard
O'Hara S. L.
Weaver Corinne M.
Wegerdt J.
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