On the Cause of the 1930s Dust Bowl

Science

Volumn 303, Issue 5665, 2004, Pages 1855-1859

  Schubert, Siegfried D ^a   Suarez, Max J ^a   Pegion, Philip J ^a,b   Koster, Randal D ^a   Bacmeister, Julio T ^a,c  

^a NASA GODDARD SPACE FLIGHT CENTER   (United States)

^b SAIC FREDERICK INC   (United States)

^c UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DUST; STORMS;

DUST STORMS; SEA SURFACE TEMPERATURE (SST);

DROUGHT;

AIR-SEA INTERACTION; DESERTIFICATION; DROUGHT; DUST; SEA SURFACE TEMPERATURE;

ARTICLE; ATMOSPHERIC DISPERSION; DROUGHT; DUST; HISTORY; METEOROLOGY; MODEL; OCEANOGRAPHY; PRECIPITATION; PRIORITY JOURNAL; SEA SURFACE TEMPERATURE; TROPICS; TROPOSPHERE;

GREAT PLAINS; NORTH AMERICA;

EID: 1642382215     PISSN: 00368075     EISSN: None     Source Type: Journal    
DOI: 10.1126/science.1095048     Document Type: Article

References (29)

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2. The "Dust Bowl" was loosely defined to be the region encompassing the western third of Kansas, southeastern Colorado, the Oklahoma Panhandle, the northern two-thirds of the Texas Panhandle, and northeastern New Mexico.
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14. The model was run with a 3° latitude by 3.75° longitude horizontal grid as compared with the 2° latitude by 2.5° longitude grid used in the earlier study (11). The resolution change was made for computational efficiency and does not appear to have much impact on the model's basic climatology or its variability.
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18. Mexico experienced somewhat above-normal precipitation during the 1930s. This may have been due, in part, to a number of hurricanes that made landfall over Mexico, especially during 1933 and 1936. The coarse resolution of the model runs precludes the simulation of hurricanes; this may account for some of the unrealistic dry conditions simulated by the model over Mexico.
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21. The SST anomalies used to force the model were computed separately for each calendar month as the sum of a mean annual cycle (computed for the period 1902 to 1999) and the SST anomaly field for that calendar month. In Fig. 2, we show only the time-averaged anomalies.
22. Materials and methods are available as supporting material on Science Online.
23. It should be noted that current AGCMs (including this model) tend to have difficulty simulating warm-season continental rainfall. In the Great Plains, this is primarily due to a poor representation of nighttime precipitation and appears to be strongly tied to deficiencies in how the models represent convective rain. The good comparison with observations shown in Fig. 5 indicates that despite any such deficiencies in the warm season precipitation climatology, the NSIPP model produces a realistic annual cycle in the response to the SST forcing.
24. It can be argued that precipitation deficits during summer are the result of anomalies that are "remembered" from the previous spring and winter. In these calculations, any such memory of the previous season's condition would come from the land surface. The Fixed Beta run suggests, that at most, such an impact would account for 50% of the summer precipitation deficit. Furthermore, the lack of substantial ensemble mean precipitation deficits over the continental. United States during the spring and winter seasons (not shown) suggests that the impact of the land is primarily a contemporaneous feedback and not the result of memory of the previous season's anomalies. We note that the observations do show substantial precipitation deficits to the north and east of the core region during spring, but similar anomalies are also obtained for some of the individual model runs, suggesting that the observed precipitation anomalies in the spring may not have been forced by SST anomalies.
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29. This work was supported by the NASA Earth Science Enterprise's Global Modeling and Analysis Program and the NASA Seasonal-to-Interannual Prediction Project.