CGD's Dr. Natalie Mahowald

Abstract

Changes in desert area due to humans have important implications from a local, regional to global level. Here I focus on the latter in order to better understand estimated changes in desert dust aerosols and the associated iron deposition into oceans. Using 17 model simulations from the World Climate Research Programme's Coupled Model Intercomparison Project phase 3 multi-model dataset and the BIOME4 equilibrium vegetation model, I estimate changes in desert dust source areas due to climate change and carbon dioxide fertilization. If I assume no carbon dioxide fertilization, the mean of the model predictions is that desert areas expand from the 1880s to the 2080s, due to increased aridity. If I allow for carbon dioxide fertilization, the desert areas become smaller. Thus better understanding carbon dioxide fertilization is important for predicting desert response to climate. There is substantial spread in the model simulation predictions for regional and global averages.

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Global trends in visibility: implications for dust sources, Atmospheric Chemistry and Physics, 7, 3309-3337, 2007. N. M. Mahowald, J. A. Ballantine, and J. Feddema.

Abstract

There is a large uncertainty in the relative roles of human land use, climate change and carbon dioxide fertilization in changing desert dust source strength over the past 100 years, and the overall sign of human impacts on dust is not known. We used visibility data from meteorological stations in dusty regions to assess the anthropogenic impact on long term trends in desert dust emissions. We did this by looking at time series of visibility derived variables and their correlations with precipitation, drought, winds, land use and grazing. Visibility data are available at thousands of stations globally from 1900 to the present, but we focused on 357 stations with more than 30 years of data in regions where mineral aerosols play a dominant role in visibility observations. We evaluated the 1974 to 2003 time period because most of these stations have reliable records only during this time. We first evaluated the visibility data against AERONET aerosol optical depth data, and found that only in dusty regions are the two moderately correlated. Correlation coefficients between visibility-derived variables and AERONET optical depths indicate a moderate correlation (0.47), consistent with capturing about 20% of the variability in optical depths. Two visibility-derived variables appear to compare the best with AERONET observations: the fraction of observations with visibility less than 5 km (VIS5) and the surface extinction (EXT). Regional trends show that in many dusty places, VIS5 and EXT are statistically significantly correlated with the Palmer drought severity index (based on precipitation and temperature) or surface wind speeds, consistent with dust temporal variability being largely driven by meteorology. This is especially true for North African and Chinese dust sources, but less true in the Middle East, Australia or South America, where there are not consistent patterns in the correlations. Climate indices such as El Nino or the North Atlantic Oscillation are not correlated with visibility-derived variables in this analysis. There are few stations where visibility measures are correlated with cultivation or grazing estimates on a temporal basis, although this may be a function of the very coarse temporal resolution of the land use datasets. On the other hand, spatial analysis of the visibility data suggests that natural topographic lows are not correlated with VIS5 or EXT, but land use is correlated at a moderate level. This analysis is consistent with land use being important in some regions, but meteorology driving interannual variability during 1974-2003.

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Cynthia D. Nevison¹, Natalie M. Mahowald¹, Scott C. Doney², Ivan D. Lima², Guido R. van der Werf³, James T. Randerson⁴, David F. Baker¹, Prasad Kasibhatla⁵ and Galen A. McKinley⁶, 2007. Contribution of Ocean, Fossil Fuel, Land Biosphere and Biomass Burning Carbon Fluxes to Seasonal and Interannual Variability in Atmospheric CO2. Accepted in Journal of Geophysical Research, Biogeochemistry.

Abstract

The seasonal and interannual variability in atmospheric carbon dioxide (CO2) concentrations is simulated using best available model estimates of surface carbon fluxes and a tracer transport model that incorporates interannual variability (IAV) in transport. The atmospheric CO2 variability resulting from these surface fluxes is compared to observations from 89 GLOBALVIEW monitoring stations. At northern hemisphere stations, the model is generally able to capture the observed seasonal cycle in atmospheric CO2, which is dominated by the land tracer. The ocean tracer has a seasonal amplitude only ~10%, on average, of and tends to be out of phase with the observed cycle at these stations. Model and observed CO2 growth anomalies are moderately well correlated in the northern hemisphere (R ~0.4-0.8), but the correlation is less significant in the southern hemisphere (R < 0.6). Land dominates IAV in the northern hemisphere, and biomass burning in particular can account for most of the strong positive CO2 growth anomaly observed during the 1997-1998 ENSO event. The signals in atmospheric CO2 from the terrestrial biosphere extend throughout the southern hemisphere, but oceanic fluxes also exert a strong influence there, accounting for roughly half of the variability at many extratropical stations. However, the modeled ocean tracer is generally uncorrelated to observations from 1979-2004, even in the southern hemisphere, with one exception during the weak El Nino/post-Pinatubo period of the early 1990s. The model suggests that the ocean may have accounted for 20-25% of the slowdown in the atmospheric CO2 growth rate observed during that time.