Summary for policymakers Technical summary 1. The climate system - an overview 2. Observed climate variability and change 3. The carbon cycle and atmospheric CO2 4. Atmospheric chemistry and greenhouse gases 5. Aerosols, their direct and indirect effects 6. Radiative forcing of climate change 7. Physical climate processes and feedbacks 8. Model evaluation 9. Projections of future climate change 10. Regional climate simulation - evaluation and projections 11. Changes in sea level 12. Detection of climate change and attribution of causes 13. Climate scenario development 14. Advancing our understanding Glossary Index Appendix.

Climate change 2001: the scientific basis

[1] We use the Total Ozone Mapping Spectrometer (TOMS) sensor on the Nimbus 7 satellite to map the global distribution of major atmospheric dust sources with the goal of identifying common environmental characteristics The largest and most persistent sources are located in the Northern Hemisphere, mainly in a broad “dust belt” that extends from the west coast of North Africa, over the Middle East, Central and South Asia, to China There is remarkably little large-scale dust activity outside this region In particular, the Southern Hemisphere is devoid of major dust activity Dust sources, regardless of size or strength, can usually be associated with topographical lows located in arid regions with annual rainfall under 200–250 mm Although the source regions themselves are arid or hyperarid, the action of water is evident from the presence of ephemeral streams, rivers, lakes, and playas Most major sources have been intermittently flooded through the Quaternary as evidenced by deep alluvial deposits Many sources are associated with areas where human impacts are well documented, eg, the Caspian and Aral Seas, Tigris-Euphrates River Basin, southwestern North America, and the loess lands in China Nonetheless, the largest and most active sources are located in truly remote areas where there is little or no human activity Thus, on a global scale, dust mobilization appears to be dominated by natural sources Dust activity is extremely sensitive to many environmental parameters The identification of major sources will enable us to focus on critical regions and to characterize emission rates in response to environmental conditions With such knowledge we will be better able to improve global dust models and to assess the effects of climate change on emissions in the future It will also facilitate the interpretation of the paleoclimate record based on dust contained in ocean sediments and ice cores

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2000RG000095

Environmental characterization of global sources of atmospheric soil dust identified with the nimbus 7 total ozone mapping spectrometer (toms) absorbing aerosol product

Studies of ecosystem processes on the Jornada Experimental Range in southern New Mexico suggest that longterm grazing of semiarid grasslands leads to an increase in the spatial and temporal heterogeneity of water, nitrogen, and other soil resources. Heterogeneity of soil resources promotes invasion by desert shrubs, which leads to a further localization of soil resources under shrub canopies. In the barren area between shrubs, soil fertility is lost by erosion and gaseous emissions. This positive feedback leads to the desertification of formerly productive land in southern New Mexico and in other regions, such as the Sahel. Future desertification is likely to be exacerbated by global climate warming and to cause significant changes in global biogeochemical cycles.

https://science.sciencemag.org/content/sci/247/4946/1043.full.pdf

Biological Feedbacks in Global Desertification

The global distribution of dust aerosol is simulated with the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. In this model all topographic lows with bare ground surface are assumed to have accumulated sediments which are potential dust sources. The uplifting of dust particles is expressed as a function of surface wind speed and wetness. The GOCART model is driven by the assimilated meteorological fields from the Goddard Earth Observing System Data Assimilation System (GEOS DAS) which facilitates direct comparison with observations. The model includes seven size classes of mineral dust ranging from 0.1–6 μm radius. The total annual emission is estimated to be between 1604 and 1960 Tg yr−1 in a 5-year simulation. The model has been evaluated by comparing simulation results with ground-based measurements and satellite data. The evaluation has been performed by comparing surface concentrations, vertical distributions, deposition rates, optical thickness, and size distributions. The comparisons show that the model results generally agree with the observations without the necessity of invoking any contribution from anthropogenic disturbances to soils. However, the model overpredicts the transport of dust from the Asian sources to the North Pacific. This discrepancy is attributed to an overestimate of small particle emission from the Asian sources.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2000JD000053

Sources and distributions of dust aerosols simulated with the GOCART model

Changes in climate extremes and their impacts on the natural physical environment: An overview of the IPCC SREX report

A theory is developed to describe the dependence upon roughness density of the threshold friction velocity ratio Rt, the ratio of the threshold friction velocity of an erodible surface without roughness to that of the surface with nonerodible roughness present The roughness density is quantified by the frontal area index λ The prediction is Rt = (1 − mσλ)−½(1 + mβλ)−½, where β is the ratio of the drag coefficient of an isolated roughness element on the surface to the drag coefficient of the substrate surface itself; σ is the basal-to-frontal area ratio of the roughness elements; and m (< 1) is a parameter accounting for differences between the average substrate surface stress and the maximum stress on the surface at any one point The prediction is well verified by four independent data sets

The effect of roughness elements on wind erosion threshold

A model for the estimation of total dust production for the United States is discussed. Its primary use will be in the inventory of alkaline elements for use in acid/base balance studies of atmospheric precipitation by the National Acid Precipitation Assessment Program (NAPAP). The model is a summation of the expected dust production caused by wind erosion for individual sampling units of the detailed soil and land use inventory of the National Resources Inventory, compiled by the U.S. Department of Agriculture. The model is based on a dust emission function derived theoretically and verified by experiment. An extremely important parameter is the threshold velocity for dust production; this parameter is dependent on effects of vegetative residue, roughness of the soil, live standing plants, soil texture and the effect of atmospheric precipitation. Experimentation has supplied values of this parameter for the calculation. Wind data used in the model were obtained from the Wind Energy Resource Information System (WERIS). The model was calibrated with dust emission data for the area, including the panhandles of Texas and Oklahoma.

Modeling dust emission caused by wind erosion

Desert soils mostly from the Mojave Desert were tested for threshold friction velocity (the friction velocity above which soil erosion takes place) with an open-bottomed portable wind tunnel. Several geomorphological settings were chosen to be representative of much of the surface of the Mojave Desert, for example, playas, alluvial fans, and aeolian features. Variables which increase threshold velocity are decreasing proportion of sand, increasing size of dry aggregates of the soil, and increasing fraction of the soil mass larger than 1 mm. Threshold velocity increases with different types of soil surfaces in the following order: disturbed soils (except disturbed heavy clay soils), sand dunes, alluvial and aeolian sand deposits, disturbed playa soils, skirts of playas, playa centers, and desert pavement (alluvial deposits). 21 references, 5 figures, 6 tables.

Threshold velocities for input of soil particles into the air by desert soils

https://jornada.nmsu.edu/bibliography/06-010.pdf

Multi-scale controls on and consequences of aeolian processes in landscape change in arid and semi-arid environments

A physical model was developed to explain threshold friction velocities u*t for particles of the size 60–120 μm lying on a rough surface in loose soils for semiarid and arid parts of the United States. The model corrected for the effect of momentum absorption by the nonerodible roughness. For loose or disturbed soils the most important parameter that controls u*t is the aerodynamic roughness height z0. For physical crusts damaged by wind the size of erodible crust pieces is important along with the roughness. The presence of cyanobacteriallichen soil crusts roughens the surface, and the biological fibrous growth aggregates soil particles. Only undisturbed sandy soils and disturbed soils of all types would be expected to be erodible in normal wind storms. Therefore disturbance of soils by both cattle and humans is very important in predicting wind erosion as confirmed by our measurements.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/97JD01303

Dale A. Gillette

Papers

The effect of roughness elements on wind erosion threshold

Modeling dust emission caused by wind erosion

Threshold velocities for input of soil particles into the air by desert soils

Multi-scale controls on and consequences of aeolian processes in landscape change in arid and semi-arid environments

Factors controlling threshold friction velocity in semiarid and arid areas of the United States