Aeolian Research

The file contains the dune age and depth data used in the calulation of the Accumulation intensity values for the analysis of Asian dune accumulation. Data are extracted form the publically available INQUA dune Atlas database at https://www.dri.edu/inquadunesatlas Date are those included in the database on publication in 2016 and refered to in Lancaster et al. (2016) In each tab: Column 1 gives the age code in the database (from which original sources can be identified) Column 2 is blank Column 3 gives the sampling depth, in m allowing individual age sampling points ina profile/section/core to be related to each other Column 4 gives the published age (OSL or TL) in years Column 5 giuves the associated 1 sigma age error Data are grouped according to samplelocation, ie a cluster of ages from a section/profile/core ina dune are grouped together Blank rows separate sites These data were then analysed using the AI numerial model in Thomas and Bailey (2017) References Lancaster, N., Wolfe, S., Thomas, D.S.G., and 12 other.s 2016. The INQUA Dunes Atlas chronologic database. Quat. Int. 410, 3-10. Thomas DSG, Bailey RM 2017 Is there evidence for global-scale forcing of Southern Hemisphere Quaternary desert dune accumulation? A quantitative method for testing hypotheses of dune system development. Earth Surf. Proc. Landf. 42, 2280-94.

The full distributions of Generalized Likelihood Uncertainty Estimate (GLUE) modelling used in Behrooz et al (submitted, Aeolian Research, 2018)

This is a repository for data from the following source paper (which was formerly hosted on our central web site): Livingstone, I., Bristow, C., Bryant, R.G., Bullard, J., White, K., Wiggs, G.F., Baas, A.C., Bateman, M.D. and Thomas, D.S., 2010. The Namib Sand Sea digital database of aeolian dunes and key forcing variables. Aeolian Research, 2(2-3), pp.93-104. https://doi.org/10.1016/j.aeolia.2010.08.001 In the zip file are the following resources, as well as a copy of the above paper: All data files can be easily interrogated in QGIS, ArcGIS or ArcPro 1. Digital elevation models 1.1 SRTM DEM [*.img] 1.2 ASTER GDEM [*.img] 1.3 Individual ASTER DEM tiles 2. Remote sensing imagery 2.1 Landsat 5 TM mosaic [*.img] 2.2 Individual ASTER image tiles 3. Vegetation index data 3.1 PAL NDVI data 3.2 GIMMS NDVI data 4. Quaternary dune age database 5. Map of dune types 6. Ancillary map data 6.1 Administrative boundaries 6.2 Drainage basin catchments 6.3 Mean annual rainfall 6.4 Potential annual average evaporation 6.5 Average daily maximum temperature for the hottest month 6.6 Average daily minimum temperature for the coldest month 6.7 Annual average number of days with rain 6.8 Rainfall for October–March as a percentage of the annual average 6.9 Average deviation of rainfall as percentage of the annual average 7. Wind data 7.1 ERA-40 data 8. Bibliographic database

This is a repository for data from the following source paper (which was formerly hosted on our central web site): Livingstone, I., Bristow, C., Bryant, R.G., Bullard, J., White, K., Wiggs, G.F., Baas, A.C., Bateman, M.D. and Thomas, D.S., 2010. The Namib Sand Sea digital database of aeolian dunes and key forcing variables. Aeolian Research, 2(2-3), pp.93-104. https://doi.org/10.1016/j.aeolia.2010.08.001 In the zip file are the following resources, as well as a copy of the above paper: All data files can be easily interrogated in QGIS, ArcGIS or ArcPro 1. Digital elevation models 1.1 SRTM DEM [*.img] 1.2 ASTER GDEM [*.img] 1.3 Individual ASTER DEM tiles 2. Remote sensing imagery 2.1 Landsat 5 TM mosaic [*.img] 2.2 Individual ASTER image tiles 3. Vegetation index data 3.1 PAL NDVI data 3.2 GIMMS NDVI data 4. Quaternary dune age database 5. Map of dune types 6. Ancillary map data 6.1 Administrative boundaries 6.2 Drainage basin catchments 6.3 Mean annual rainfall 6.4 Potential annual average evaporation 6.5 Average daily maximum temperature for the hottest month 6.6 Average daily minimum temperature for the coldest month 6.7 Annual average number of days with rain 6.8 Rainfall for October–March as a percentage of the annual average 6.9 Average deviation of rainfall as percentage of the annual average 7. Wind data 7.1 ERA-40 data 8. Bibliographic database

Saharan dust was collected using subsurface sediment traps mooried in the tropical North Atlantic Ocean in 2012-2013, and by shipboard aerosol collection during three trans-Atlantic research cruises in 2005, 2012 and 2015. The samples were analysed for radiogenic Strontium (Sr), Neodymium (Nd), and Hafnium (Hf) isotopes, rare earth element (REE; La-Lu) abundances and particle size. In addition, soil sediments from Mauritania, a potential source area, were analysed.

The particle sizes of Saharan dust in marine sediment core records have been used frequently as a proxy for trade-wind speed. However, there are still large uncertainties with respect to the seasonality of the particle sizes of deposited Saharan dust off northwestern Africa and the factors influencing this seasonality. We investigated a three-year time-series of grain-size data from two sediment-trap moorings off Cape Blanc, Mauritania and compared them to observed wind-speed and precipitation as well as satellite images. Our results indicate a clear seasonality in the grain-size distributions: during summer the modal grain sizes were generally larger and the sorting was generally less pronounced compared to the winter season. Gravitational settling was the major deposition process during winter. We conclude that the following two mechanisms control the modal grain size of the collected dust during summer: (1) wet deposition causes increased deposition fluxes resulting in coarser modal grain sizes and (2) the development of cold fronts favors the emission and transport of coarse particles off Cape Blanc. Individual dust-storm events throughout the year could be recognized in the traps as anomalously coarse-grained samples. During winter and spring, intense cyclonic dust-storm events in the dust-source region explained the enhanced emission and transport of a larger component of coarse particles off Cape Blanc. The outcome of our study provides important implications for climate modellers and paleo-climatologists.

Changes in the emission, transport and deposition of aeolian dust have profound effects on regional climate, so that characterizing the lifecycle of dust in observations and improving the representation of dust in global climate models is necessary. A fundamental aspect of characterizing the dust cycle is quantifying surface dust fluxes, yet no spatially explicit estimates of this flux exist for the World's major source regions. Here we present a novel technique for creating a map of the annual mean emitted dust flux for North Africa based on retrievals of dust storm frequency from the Meteosat Second Generation Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the relationship between dust storm frequency and emitted mass flux derived from the output of five models that simulate dust. Our results suggest that 64 (±16)% of all dust emitted from North Africa is from the Bodélé depression, and that 13 (±3)% of the North African dust flux is from a depression lying in the lee of the Aïr and Hoggar Mountains, making this area the second most important region of emission within North Africa.

Previous investigations showed that the Orlovat loess-paleosol section, northern Serbia, is characterized by irregularities in sedimentological properties, magnetic susceptibility and color of the sediment. Here, we applied granulometric analysis and X-ray fluorescence (XRF) analyses to study how the sedimentation at the Orlovat site was conditioned by specific geomorphological or climatic conditions. Grain-size analysis is an established method and one of the most frequently used paleoenvironmental proxies of loess deposits, and is complemented here with high resolution XRF analysis on sand-free samples to obtain a more detailed insight into paleoenvironmental conditions and weathering during the past ~160 ka. The geomorphological conditions of the surrounding area and variations in wind speed over time are of great importance for a better understanding of loess-paleosol deposits. The Orlovat section was exposed to special depositional conditions, which differ from other sections studied in the Carpathian Basin. Sand was delivered during interglacials, most probably from the Deliblato Sands by the southeast Kosava wind. This study highlights the importance of an integrated sedimentological approach for reliable paleoenvironmental reconstruction.