Controls of dust emissions by vegetation and topographic depressions: An evaluation using dust storm frequency data

Abstract

[1] The degree to which dust emissions are controlled by vegetation cover and geomorphic setting (specifically closed topographic depressions) was investigated using dust storm frequency (DSF) data based on visibility measurements from >2400 meteorological stations worldwide. Comparisons with distributions of vegetation types suggest that DSF is highest in desert/bare ground (median: 60-80 d/yr) and shrubland (median: 20-30 d/yr) regions, and comparatively low in grassland regions (median: 2 -4 d/yr). Average DSF is inversely correlated with leaf area index (an index of vegetation density) and net primary productivity. In nonforested regions, DSF increases as the fraction of closed topographic depressions increases, likely due to the accumulation of fine sediments in these areas. These findings support the importance of incorporating vegetation and geomorphic setting as explicit controls on emissions in global dust cycle models.

Global trends in visibility: implications for dust sources

“…However, interpreting the dust storm frequency dataset used in Engelstaedter et al (2003) as blowing dust or sand makes this dataset consistent with the results of this and other previous studies which analyzed data at particular stations (e.g. N'Tchayi Mbourou et al, 1997).…”

“…4 and Table 4), we obtain no statistically significant correlations with either topographic lows or human land use variables. However, if we use the dust storm frequency dataset described in Engelstaedter et al (2003) i. j. of I. Tegen and S. Engelstaedter), we obtain similar results to those obtained in that study (Fig. 4 and Table 4) -the dustiness in this dataset is correlated with natural dry lake beds, and not with land use proxies.…”

“…4 and Table 4) -the dustiness in this dataset is correlated with natural dry lake beds, and not with land use proxies. In doing this comparison, we realized that the dust storm frequency dataset used in Engelstaedter, et al (2003) represents the number of days with blowing dust or sand per year (and is not derived from the visibility data, but from the atmospheric phenomenon dataset), not the fraction of days with visibility less than 1km. The original description of the datasets was unclear.…”

Long-term variability of dust events in Iceland (1949–2011)

“…The long-term dust variability studies based on meteorological observations present up to 90 year old records from North America, Africa, Asia and Australia (N'TchayiMbourou et al, 1997;Qian et al, 2002;Natsagdorj et al, 2003;Ekström et al, 2004;Jamalizadeh et al, 2008;Steenburgh et al, 2012). Engelstaedter et al (2003) reported high dust activity at many weather stations located in high-latitude regions. Cold climate regions are represented by long-term dust frequency in Northeast (NE) Iceland (Dagsson-Waldhauserova et al, 2013).…”

“…Detailed and longterm studies on wind erosion variability can potentially explain the climatological and environmental changes in the past. Periodical dust occurrences can affect ecosystem fertility and spatial and temporal distribution of animal and vegetation species similarly to climate variations (Fields et al, 2010). Oceanic ecosystems receive high amounts of nutrient rich dust spread over large areas where deserts occur near the sea .…”