Anthropogenic influence on climate over the Southeast US

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1 Anthropogenic influence on climate over the Southeast US Vasu Misra Dept. of Earth, Ocean, and Atmospheric Science & Center for Ocean-Atmospheric Prediction Studies & Florida Climate Institute 1

2 Acknowledgments J. P. Michael R. Boyles E. Chassignet M. Griffin J. J. O Brien 2

3 Kinds of Anthropic influence on climate Increasing green house gas concentration (CO 2, CH 4, SO X, H 2 O, NO X, 0 3 )5 3

4 Land cover Irrigation Urbanization Land cover can change albedo, bowen ratio, roughness Irrigation can change bowen ratio, heat capacity and conductivity of the soil That s not the northern lights! It s a new strip mall. Urbanization: heat capacity and conductivity of paving and building material, albedo changes can influence climate 4

5 Illustration of Urban Heat Island The photo like view of Atlanta region Land surface temperature: densely vegetated area is cooler (in yellow) than the urban areas (in red) Courtesy: NASA Earth Observatory 5

6 Data sets used I Daily data of T min, T max from 327 NWS cooperative station network from NCDC T max and T min are chosen as trends in them represent different physical process; T min is measured when the boundary layer is typically shallow while T max represents a thicker layer of atmospheric behavior. Only 285 retained as rest had five or more consecutive years of missing data missing The missing data was filled by doing our best to avoid mixing urban and rural stations detrended, removed seasonal cycle and chose the surrounding stations within a 50 mile radius that had a correlation with the reference station of over 0.6 6

7 Objective The question we are trying to answer is how does land cover and use affect observed temperature trends in the southeast US? 7

8 Data sets used II Land cover data: Population interaction zones for Agriculture (PIZA) developed by the US Department of Agriculture Economic Research Service. PIZA uses four category system based on interaction of the urban population with agriculture with 1 being negligible and 4 being high interaction. PIZA is available at 5km grid resolution and based on data for year

9 Data sets used III Irrigation data: From global maps of area equipped for irrigation at 5 minute resolution obtained from United Nations FAO through its AQUASTAT global water and agriculture information system The digital global maps were developed by combining irrigation statistics with geospatial information on the position and extent of irrigation 9

10 Methodology Trends were computed using Ensemble Empirical Mode Decomposition (EEMD) It is probably one of the most unambiguous ways of finding trend and other temporal variations in a given time series Of the 285 stations, 123 failed to show statistically significant trends in T max, in T min or in both. Results shown in the following slides only show the significant trends. 10

T min trends in 0 F per century StrongER warming trends in urban areas of Florida, Georgia, Alabama, South Carolina Trends in North Carolina seem to be rather insensitive to urbanization Red is urban

11 T min trends in 0 F per century StrongER warming trends in urban areas of Florida, Georgia, Alabama, South Carolina Trends in North Carolina seem to be rather insensitive to urbanization Red is urban (PIZA=4); Green is rural (PIZA=1) Resolution of PIZA sometimes insufficient to resolve the location of temperature measurement site: E.g. Tallahassee Trends laid on PIZA [Population Interaction Zones for Agriculture from USDA-Economic Research Service 2005] 11

12 The significance of the slope of the linear fit is tested using the Monte Carlo technique 12

T max trends in 0 F per century WeakER warming (or even cooling) trends in rural areas of Florida, Georgia, Alabama, South Carolina Trends of T max in North

13 T max trends in 0 F per century WeakER warming (or even cooling) trends in rural areas of Florida, Georgia, Alabama, South Carolina Trends of T max in North Carolina seem to be more sensitive to urbanization Trends laid on PIZA [Population Interaction Zones for Agriculture from USDA-Economic Research Service 2005] 13

14 The significance of the slope of the linear fit is tested using the Monte Carlo technique 14

15 T max trends in 0 F per century Since Tmax is measured during the day, the weaker (or cooling) trends in rural areas suggest influence of irrigation. Irrigation reduces Bowen ratio North Carolina has relatively less irrigated land Trends laid on irrigation data (land equipped for irrigation) based on UN FAO AQUASTAT 15

16 T min trends in 0 F per century Irrigation by way of wetting the soil raises the heat capacity and heat conductivity of the soil and under light wind conditions can lead to warming of the surface temperatures. 16

17 17

18 Restating the objectives The question we are trying to answer is how does land cover and use affect observed temperature trends in the southeast US? This objective was reframed to ask what gives rise to spatial heterogeneity in the temperature trends? More specifically, What is (Veg) T t? And (Irr) T t? 18

19 Conclusions The temperature trends in the Southeast US is affected by land cover and land use (Veg) T t 0 (Irr) T t 0 The data supports theory: Urbanization raise the warming trends in T min. Irrigation reduces the warming trends in T max and increase warming trends in T min. North Carolina is the northernmost state of our definition of the Southeast US. We speculate that it could be overwhelmed by the global warming signal or with a combination of some other large-scale low frequency variations. 19

th Conf on Hydrology, 85 th AMS Annual Meeting, 9-13 Jan, 2005, San Diego, CA., USA.

4.12 19th Conf on Hydrology, 85 th AMS Annual Meeting, 9-13 Jan, 5, San Diego, CA., USA. IMPACT OF DEFORESTATION ON THE PROPOSED MESOAMERICAN BIOLOGICAL CORRIDOR IN CENTRAL AMERICA Ronald M Welch 1, Deepak