scholarly journals The Maritime Influence on Diurnal Temperature Range in the Chesapeake Bay Area

2013 ◽  
Vol 17 (21) ◽  
pp. 1-14 ◽  
Author(s):  
Kelsey Scheitlin
Keyword(s):  
Chesapeake Bay ◽  
Diurnal Temperature Range ◽  
Cloud Cover ◽  
Multiple Regression Model ◽  
Moist Air ◽  
Air Masses ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Bay Area ◽  
Weather Stations

Abstract This study analyzes the influence of the Atlantic Ocean and Chesapeake Bay on the diurnal temperature range (DTR) reported by nearby weather stations. Coastal locations reported the smallest DTRs and DTR fluctuations, and DTR increased with distance from the ocean. Month of the year and airmass type also proved to be significant predictors of DTR. All locations showed a bimodal annual DTR pattern with peaks during the transitional seasons and experienced the greatest DTR during dry and/or warm air masses. Proximity to the ocean had the largest (smallest) influence on DTR during dry (moist) air masses with extreme (moderate) temperatures. Seasonally, the proximity to the ocean had the strongest impact on DTR during early–middle spring. A multiple regression model using distance from water, month, and airmass type explains over 30% of DTR variability in the area (p < 0.01). Airmass type has the largest influence on DTR, and changes in both air mass and month impacted the DTR of continental locations more than coastal locations. Land use, cloud cover, and wind speed/direction are additional variables that could account for differences not explained by the model.

scholarly journals Spatiotemporal Analysis of Diurnal Temperature Range: Effect of Urbanization, Cloud Cover, Solar Radiation, and Precipitation

Climate ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 89 ◽  
Author(s):  
Andri Pyrgou ◽  
Mattheos Santamouris ◽  
Iro Livada
Keyword(s):  
Solar Radiation ◽  
Diurnal Temperature Range ◽  
Cloud Cover ◽  
Longwave Radiation ◽  
Ultraviolet B ◽  
Anthropogenic Sources ◽  
Daily Minimum Temperature ◽  
Urban Station ◽  
Diurnal Temperature ◽  
Temperature Range

High daily temperatures in the Mediterranean and Europe have been documented in observation and modeling studies. Long-term temperature data, from 1988 to 2017, from a suburban station and an urban station in Nicosia, Cyprus have been analyzed, and the diurnal temperature range (DTR) trend was investigated. The seasonal Mann–Kendall test revealed a decreasing DTR trend of −0.24 °C/decade at the urban station and −0.36 °C/decade at the suburban station, which were attributed to an increase in the daily minimum temperature. Variations in precipitation, longwave radiation, ultraviolet-A (UVA), ultraviolet-B (UVB), cloud cover, water vapor, and urbanization were used to assess their possible relationship with regional DTR. The clustering of daytime and night-time data showed a strong relationship between the DTR and observed cloud cover, net longwave radiation, and precipitation. Clouds associated with smaller shortwave and net longwave radiation reduce the DTR by decreasing the surface solar radiation, while atmospheric absolute humidity denotes an increased daytime surface evaporative cooling and higher absorption of the short and longwave radiation. The intra-cluster variation could be reduced, and the inter-cluster variance increased by the addition of other meteorological parameters and anthropogenic sources that affect DTR in order to develop a quantitative basis for assessing DTR variations.

scholarly journals Diurnal Temperature Range Variability due to Land Cover and Airmass Types in the Southeast

2010 ◽  
Vol 49 (5) ◽  
pp. 879-888 ◽  
Author(s):  
Kelsey N. Scheitlin ◽  
P. Grady Dixon
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Diurnal Temperature Range ◽  
Deciduous Forest ◽  
Mixed Forest ◽  
Evergreen Forest ◽  
Climatic Data ◽  
Air Masses ◽  
Diurnal Temperature ◽  
Temperature Range

Abstract This study examines the relationship between diurnal temperature range (DTR) and land use/land cover (LULC) in a portion of the Southeast. Temperature data for all synoptically weak days within a 10-yr period are gathered from the National Climatic Data Center for 144 weather stations. Each station is classified as one of the following LULC types: urban, agriculture, evergreen forest, deciduous forest, or mixed forest. A three-way analysis of variance and paired-sample t tests are used to test for significant DTR differences due to LULC, month, and airmass type. The LULC types display two clear groups according to their DTR, with agricultural and urban areas consistently experiencing the smallest DTRs, and the forest types experiencing greater DTRs. The dry air masses seem to enhance the DTR differences between vegetated LULC types by emphasizing the differences in evapotranspiration. Meanwhile, the high moisture content of moist air masses prohibits extensive evapotranspirational cooling in the vegetated areas. This lessens the DTR differences between vegetated LULC types, while enhancing the differences between vegetated land and urban areas. All of the LULC types exhibit an annual bimodal DTR pattern with peaks in April and October. Since both vegetated and nonvegetated areas experience the bimodal pattern, this may conflict with previous research that names seasonal changes in evapotranspiration as the most probable cause for the annual trend. These findings suggest that airmass type has a larger and more consistent influence on the DTR of an area than LULC type and therefore may play a role in causing the bimodal DTR pattern, altering DTR with the seasonal distribution of airmass occurrence.

scholarly journals Variability and trend of diurnal temperature range in China and their relationship to total cloud cover and sunshine duration

2013 ◽  
Vol 31 (5) ◽  
pp. 795-804 ◽  
Author(s):  
X. Xia
Keyword(s):  
Diurnal Temperature Range ◽  
Cloud Cover ◽  
Sunshine Duration ◽  
Radiative Effect ◽  
Total Cloud Cover ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Clear Sky ◽  
Sky Conditions

Abstract. This study aims to investigate the effect of total cloud cover (TCC) and sunshine duration (SSD) in the variation of diurnal temperature range (DTR) in China during 1954–2009. As expected, the inter-annual variation of DTR was mainly determined by TCC. Analysis of trends of 30-year moving windows of DTR and TCC time series showed that TCC changes could account for that of DTR in some cases. However, TCC decreased during 1954–2009, which did not support DTR reduction across China. DTRs under sky conditions such as clear, cloudy and overcast showed nearly the same decreasing rate that completely accounted for the overall DTR reduction. Nevertheless, correlation between SSD and DTR was weak and not significant under clear sky conditions in which aerosol direct radiative effect should be dominant. Furthermore, 30–60% of DTR reduction was associated with DTR decrease under overcast conditions in south China. This implies that aerosol direct radiative effect appears not to be one of the main factors determining long-term changes in DTR in China.

scholarly journals U.S. Diurnal Temperature Range Variability and Regional Causal Mechanisms, 1901–2002

2012 ◽  
Vol 25 (20) ◽  
pp. 7216-7231 ◽  
Author(s):  
Ryan G. Lauritsen ◽  
Jeffrey C. Rogers
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Diurnal Temperature Range ◽  
Cloud Cover ◽  
The United States ◽  
Maximum Temperature ◽  
Climatic Research Unit ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Cover Soil

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.

scholarly journals Changes in total cloud cover over India based upon 1961-2007 surface observations

MAUSAM ◽  
2021 ◽  
Vol 61 (4) ◽  
pp. 455-468
Author(s):  
A. K. JASWAL
Keyword(s):  
Diurnal Temperature Range ◽  
Cloud Cover ◽  
Monsoon Season ◽  
Central India ◽  
Total Cloud Cover ◽  
Seasonal Trends ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Post Monsoon ◽  
Rainy Days

Based upon 172 well distributed surface meteorological stations over India, annual and seasonal trends in total cloud cover and associated climatic variables diurnal temperature range and rainy days are investigated for 1961-2007. The data analysis indicates a general decrease in total cloud cover over most parts of India during winter, summer and monsoon. On monthly scale, statistically significant decrease in total cloud cover has occurred during April (3% per decade), June to September (2% per decade) and December (5% per decade). Seasonally, the declining trends in total cloud cover are significant for summer and monsoon (2% per decade). Spatial analysis of trends suggests coherent decrease in total cloud cover over central India (all seasons) and south peninsula (except post monsoon).   All India averaged monthly, annual and seasonal trends in diurnal temperature range and rainy days are mixed and weak. Spatially, trends in diurnal temperature range are decreasing over north and increasing over south peninsula while trends in rainy days are decreasing over large number of stations during winter and monsoon and increasing in summer and post monsoon seasons. However, the sizes of the same trend regions show considerable variability between seasons. Monsoon season total cloud cover and Nino3.4 sea surface temperature anomalies are significantly negatively correlated over all regions of the country except northeast indicating a strong relationship between them.

scholarly journals An Empirical Study of Geographic and Seasonal Variations in Diurnal Temperature Range

2010 ◽  
Vol 23 (12) ◽  
pp. 3205-3221 ◽  
Author(s):  
Lawrence S. Jackson ◽  
Piers M. Forster
Keyword(s):  
Soil Moisture ◽  
Seasonal Variation ◽  
Solar Radiation ◽  
Land Surface ◽  
Diurnal Temperature Range ◽  
Cloud Cover ◽  
Longwave Radiation ◽  
Explanatory Variables ◽  
Diurnal Temperature ◽  
Temperature Range

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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