scholarly journals Effects of Clouds, Soil Moisture, Precipitation, and Water Vapor on Diurnal Temperature Range

1999 ◽  
Vol 12 (8) ◽  
pp. 2451-2473 ◽  
Author(s):  
Aiguo Dai ◽  
Kevin E. Trenberth ◽  
Thomas R. Karl
2012 ◽  
Vol 25 (20) ◽  
pp. 7216-7231 ◽  
Author(s):  
Ryan G. Lauritsen ◽  
Jeffrey C. Rogers

Abstract Long-term (1901–2002) diurnal temperature range (DTR) data are evaluated to examine their spatial and temporal variability across the United States; the early century origin of the DTR declines; and the relative regional contributions to DTR variability among cloud cover, precipitation, soil moisture, and atmosphere/ocean teleconnections. Rotated principal component analysis (RPCA) of the Climatic Research Unit (CRU) Time Series (TS) 2.1 dataset identifies five regions of unique spatial U.S. DTR variability. RPCA creates regional orthogonal indices of cloud cover, soil moisture, precipitation, and the teleconnections used subsequently in stepwise multiple linear regression to examine their regional impact on DTR, maximum temperature (Tmax), and minimum temperature (Tmin). The southwestern United States has the smallest DTR and cloud cover trends as both Tmax and Tmin increase over the century. The Tmin increases are the primary influence on DTR trend in other regions, except in the south-central United States, where downward Tmax trend largely affects its DTR decline. The Tmax and DTR tend to both exhibit simultaneous decadal variations during unusually wet and dry periods in response to cloud cover, soil moisture, and precipitation variability. The widely reported post-1950 DTR decline began regionally at various times ranging from around 1910 to the 1950s. Cloud cover alone accounts for up to 63.2% of regional annual DTR variability, with cloud cover trends driving DTR in northern states. Cloud cover, soil moisture, precipitation, and atmospheric/oceanic teleconnection indices account for up to 80.0% of regional variance over 1901–2002 (75.4% in detrended data), although the latter only account for small portions of this variability.


2010 ◽  
Vol 23 (12) ◽  
pp. 3205-3221 ◽  
Author(s):  
Lawrence S. Jackson ◽  
Piers M. Forster

Abstract The diurnal temperature range (DTR) of surface air over land varies geographically and seasonally. The authors have investigated these variations using generalized additive models (GAMs), a nonlinear regression methodology. With DTR as the response variable, meteorological and land surface parameters were treated as explanatory variables. Regression curves related the deviation of DTR from its mean value to values of the meteorological and land surface variables. Cloud cover, soil moisture, distance inland, solar radiation, and elevation were combined as explanatory variables in an ensemble of 84 GAM models that used data grouped into seven vegetation types and 12 months. The ensemble explained 80% of the geographical and seasonal variation in DTR. Vegetation type and cloud cover exhibited the strongest relationships with DTR. Shortwave radiation, distance inland, and elevation were positively correlated with DTR, whereas cloud cover and soil moisture were negatively correlated. A separate analysis of the surface energy budget showed that changes in net longwave radiation represented the effects of solar and hydrological variation on DTR. It is found that vegetation and its associated climate is important for DTR variation in addition to the climatic influence of cloud cover, soil moisture, and solar radiation. It is also found that surface net longwave radiation is a powerful diagnostic of DTR variation, explaining over 95% of the seasonal variation of DTR in tropical regions.


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