In this paper I will characterize land cover change and, address types of land use change and discuss the impacts that they have on climate. While there are a




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НазваниеIn this paper I will characterize land cover change and, address types of land use change and discuss the impacts that they have on climate. While there are a
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Marcus D Williams


Introduction


In this paper I will characterize land cover change and, address types of land use change and discuss the impacts that they have on climate. While there are a multitude of types of land use change, the three in particular that I will focus on are Urbanization, Agricultural expansion, and deforestation. I will also give my personal opinion on studies stating that changes in albedo influence long term climate patterns.


To start of the discussion, I will frame the importance of the issue from a personal standpoint. As part of my thesis research I am hoping to characterize multi-decadal temperature trends in the South Eastern United States, or more specifically Florida, Georgia, Alabama, and the Carolinas. As seen in figure 1 there is a pronounced warm period in the 1920’s through the 1950’s, and a pronounced cool period in the decades of the 1960’s through the 1990’s. Can knowledge of this variability lead to longer horizon predictability in agriculture, water resources, and energy planning? When viewing this type of variability there are several scientific questions that arise. The question of importance to the topic of this paper is, are there any anthropogenic influences. Is this variability a result of human interaction with the land surface, or is the signal part of the natural variability of the climate.

1) Land-Cover

Land cover refers to everything covering the land surface, including vegetation, bare soil, buildings and infrastructure, inland bodies of water, and wetlands. Land cover influences climate and weather at local to global scales; they can have direct impacts on climate by affecting the composition of the atmosphere and the exchange of energy between continents and the atmosphere. Worldwide changes to forest, farmlands, waterways and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Land cover classification from MODIS (fig.2) estimates that there are about eighteen types of land cover. Some studies suggest that without the influence of humans (fig.3) the number of land cover types would be reduced down to about seven. A large aspect of the human influence comes from the increase in the spatial extent of croplands (fig.4), pastures, and rangelands (fig.5).


2) Urbanization

Urbanization is one of the extreme cases of land-use change. Although currently only 1.2% of the Earth’s land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in the near future. Currently about 45% of the worlds population live in cities. It is estimated that by the year 2025, 60% of the world’s population will live in cities (UNFP 1999). Modification of the landscape through urbanization alters the natural channeling of energy through the atmospheric, land and water systems. Recent studies (Elvidge et al. 2004) indicated that the density of the impervious surface area (ISA) for the conterminous United States is 112 610 km sq. This is roughly equal to the size of the state of Ohio. The interactions of urban surfaces with the atmosphere are governed by surface heat fluxes. Urbanization drastically modifies the distribution of the fluxes through changes in the physical characteristics of the surface. Reduced evaporation changes the radiative fluxes and near surface flow because of the complicated geometry of streets and tall buildings, and anthropogenic heat. You should see and increase in outgoing IR, decreased latent heat flux, increased heat storage, and the introduction of an anthropogenic heat source. The impact of urbanization is quite apparent when analyzing a time series of the average time series of maximum and minimum temperatures in Atlanta, GA. From 1960 to 2000 the population of the city of Atlanta had an increase in population from 1.5 million to slightly over 4 million people. During this period there was approximately a 3-5°C increase in the average maximum and minimum temperature. The phenomenon that occurred in Atlanta is commonly referred to as the Urban Heat Island (UHI). This phenomenon was investigated by Dousset in 2003. Dousset used multiple satellite sensors to analyze the physical processes that determine energy fluxes and their interaction with the urban surfaces through the investigation of the summertime microclimate of Los Angeles and Paris for a period of two years. Dousset found that downtown business and industrial districts can generate a heat island larger that 7°C. This point is best illustrated with the analysis of the %Built density versus land surface temperature (fig. 6) and the NDVI versus land surface temperature (fig.7). The %built density and LST both displayed a positive correlation. As the %built increased so did the LST. There was a negative correlation between the LST and NDVI. Both findings show that and increase in ISA causes an increase in temperature.

3) Agricultural expansion

Croplands and pastures have become one of the largest terrestrial biomes on the planet occupying 40% of the land surface. Prior to agricultural settlement in the mid-19th-Century, grasslands comprised 300 million hectares of central North America, 21% of which (61.5 million ha) was short-grass steppe. More than half of cropland expansion between 1980 and 2000 occurred at the expense of natural forests. In the US the effects of agricultural expansion are region specific. This has to do with the type on land cover change that occoured. In Florida marsh and wet prairie were replaced with croplands (fig.8). This resulted in a warming trend in the max and min temps in the city of Belle Glade, FL. This trend was representative of most of the area south of Lake Okeechobee. The opposite happened in the Mid-Western United States. Adegoke et al. investigated the effects of irrigation in the Great Plains (Nebraska) by comparing temperature and dewpoint. Over the last 5 decades, the total acreage under irrigation in the U.S. high plains increased from 3 million to 20 million .Used RAMS model with LEAF-2 land atmosphere feedback scheme. RAMS simulations forced by 4 Land surface scenarios covering a 15 day period (July 1-15). Model simulations showed cooling and increases in vapor and LHF to the atmosphere Correlations between observations and simulations ranged from .83-.92. Results from the study showed that as much as a 3°C cooling occurred between natural vegetation and irrigated crop land cover scenarios. Both of these results where in agreement with the results found from Easterling et al. 1997. His study found that there was a warming trend in the minimum temperature, cooling trend in the maximum temperature, resulting in a decrease in the diurnal temperature range.

4) Deforestation

Deforestation is the process of clearing forests, by cutting down, clearing, or damaging the forests themselves, for various economic and political reasons. These reasons range from the need for increased land for agriculture and grazing, to the profitability of the extracted resources. Regardless of the perceived short-term benefits derived from deforestation, it is harmful both ecologically, as well as long-term economically. There is a need to explore the extent of this harmfulness and the effects on the environment caused by deforestation. In model simulations the warming effects of carbon release where off set by the biophysical feedbacks in Temperate and Boreal forest. Deforestation in the Tropical forest results in warming everywhere. The dominance of the greenhouse effects in the tropics was the reason for the warming. Food and Agriculture Organization estimates that 53,000 square miles of tropical rainforest where destroyed each year during the 1980’s.With about 21,000 square miles per year of deforestation occurring in the Amazon Basin. The large scale change in land cover type has lead to observed differences in albedo, evaporation, surface fluxes, and temperature. The pasture areas had a higher surface albedo, which modified the surface fluxes, leading to higher temperatures in the pasture area as opposed to the forest areas. Deforestation also has adverse effects on the hydrological cycle. Deforestation can affect soil erosion and infiltration rates, which would alter the river discharge in surrounding river basins. Gash and Nobre conducted an investigation of the effects of deforestation on the discharge of the Tocantins River. The study compared a period of little deforestation to a period of heavy deforestation. The two periods experienced relatively the same amount of precipitation but period two had greater discharge and less evapotranspiration (fig.9). This indicates that period two had a less protected surface. Deforestation alters the natural water cycle through reduced interception, reduced infiltration rate, reduced tree root strength, and increased raindrop impact. All these things act to increase erosion.

5) Are you convinced?

The question arises of how convincing are the studies that suggest albedo changes influence climate. It is clear that changes in albedo can affect the partitioning of energy and cause changes in the atmosphere. Are these changes large enough to matter in climate? The short answer is yes, but evidence only supports short time-scale processes and not climate. Mesoscale models only capture responses on a short time scale. There is also a problem with the model simulations greatly outweigh the observational studies. Although these model simulations provide great case study examples, there is no overlap between observational evidence and modeling evidence. Also the station density needs to be considered for some of the model simulations. Areas where the largest impacts are predicted to occur have the lowest station densities, so there is little data to validate model simulations. For example, above 50°N, 53% of the grids have no station data. Also the case study scenarios are often unrealistic. Model simulations often simulate unrealistic surface perturbations. Although the extent of land use change is increasing, the abrupt nature used in simulations is not the observed pattern. Another glaring omission is the lack of ocean influence. Ocean-atmosphere feedbacks are important in the mean state and evolution of the climate. 4/5 of the earth surface is water, with some of the dominant modes of variability coming from ocean-atmosphere coupled phenomena (ENSO,MJO,NAO ). Many of the studies fail to mention how these dominant modes of variability could be influencing their results. Also most climate models fail to produce correct simulations of ENSO, MJO and other forms of ocean-atmosphere variability, so is it safe to say these same problems aren’t manifested in their simulations. The last issue of concern is the station data that is being used in model simulations. USHCN is considered to be a “high quality” observing network. Further analysis of HCN station data shows that the temperature instruments that are used in HCN are often too close to local influences on the micro climate. These local influences on the micro climate are not representative of the larger mesoscale environment. During a survey of site quality rating of approximately 800 HCN stations, 69% of all surveyed stations had a warm bias of at least 2°C. Other biases in temperature observations can be introduced by station moves, changes in observation times, equipment changes, and changes in station elevation. HCN employs a bias correction, but there are significant uncertainties introduced from each step of the homogenization adjustments.


6) Summary

It has been shown that for a wide range of land cover change types including urbanization, agricultural expansion, and deforestation there are various impacts on the local climate. These impacts include, but are not limited too, changes in the minimum and maximum temperature, increased or decreased precipitation, and alterations in the hydrological cycle. Since these land cover changes are taking place on a global spatial scale it is becoming of increasing importance to understand their influence on climate. Observational and modeling studies suggest that these types of land surface change influence the local areas in the short-term, but no substantial evidence has been presented verifying long term climate change. The most important step that can be taken in examining this problem is introducing more realistic modeling simulations and take a careful eye in picking the data sets used in your analysis, as some data can introduce biases that can skew simulation results.

References

Adegoke, J.O et al., 2002. Imapct on Midsummer Surface Fluxes and Temperature under Dry Synoptic conditions: A Regional Atmospheric Model Study of the U.S High Plains. Monthly Weather Review., 131, 556-564


Bala, G., K Calderia, M. Wickett, T.J. Phillips, D.B. Lobell, C.Delire, A Mirin., 2007. Combined climate and carbon-cycle effects of large-scale deforestation., PNAS., 104, 6550-6555


Bonan, G. B. 2002. Ecological Climatology: Concepts and Applications. Cambridge University Press, 678 pp


Boucher, O., Myhre, G., and Myhre, A., 2004. Direct Human influence on atmospheric water vapour and climate. Clim. Dyn., 22, 597-603


Chase, T.N et al., 2001. Relative climatic effects of landcover change and elevated carbon dioxide combined with aerosols: A comparison of model results and observations. Jour. Of Geophysical Research. 106, 31685-31691


Chase, T. N., Pielke, R. A., Kittel, T. G. F., Baron, J. S. and Stohlgren, T. J. 1999. Potential impacts on Colorado Rocky Mountain weather due to land use changes on the adjacent Great Plains. J. Geophys. Res.-Atmos., 104, 16673–16690

Costa, M. H., Botta, A., and Cardille, J. 2003. A.: Effects of large-scale changes in land cover on the discharge of the Tocantins River, Southeastern Amazonia, J. Hydrol., 283(1–4), 206–217,


Costa, M. H. and Foley, J. A. 2000. Combined effects of deforestation and doubled atmosphericCO2 concentrations on the climate of Amazonia. J. Climate, 13, 18–34


Cotton, W. R. and Pielke, R. A. Sr. 2007. Human impacts on weather and climate. Cambridge University Press, 2nd Edition, 330 pp


Crutzen, P.J., 2004. New Directions: The growing urban heat and pollution “island” effect-impact on chemistry and climate. Atmospheric Environment. 38, 3539-3540


Dousset, B. and Gourmelon, F., 2003. Satellite multi-sensor data analysis of urban surface temperatures and land cover. ISPRS Journal of Photogrammy & Remote Sensing. 58, 43-54


Easterling, D.R. et al., 1997. Maximun and minimum Temperature Trends for the Globe. Science. Science. 277, 364-366


Feddema, J. J., Oleson, K. W., Bonan, G. B., Mearns, L. O., Buja, L. E. and co-authors. 2005. The importance of landcover change in simulating future climates. Science, 310, 1674–1678.

Foley, J.A. et al. 2005. Global Consequences of Land Use. Science, 309, 570-574


Gash, J.H.C, Nobre, C.A., 1997. Climatic Effects of Amazonian Deforestation: Some Results from ABRACOS. Am. Bull. AMS. 78, 823-830


Hale, R. C., K. P. Gallo, T. W. Owen, and T. R. Loveland (2006), Land use/land cover change effects on temperature trends at U.S. Climate Normals Stations, Geophys. Res. Lett., 33, L11703, doi:10.1029/2006GL026358


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Figure 1: Annual Statewide mean temperature in °F for the state of Alabama




Figure 2: Land cover classification from MODIS




Figure 3: Potential natural vegetation without the influence of humans




Figure 4: Percentage of land cover composed of croplands (1990)




Figure 5: Percentage of land cover composed of pastures and rangelands (1990)




Figure 6: Land Surface Temperature versus %Built density for Paris




Figure 7: Land Surface Temperature versus NDVI for Paris




Figure 8: Pre-1900 and 1993 land cover types for the Florida peninsula




Figure 9: River discharge in the Tocantins River basin for period 1 (1949-1968) and period 2 (1979-1998)

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