Spatial Modeling of Climatic Parameter Fluctuation Mapping Temperature Variation in the Bermejo Basin from 1901 to 2000
Temperature variation maps were produced following an approach based on the following guidelines to assess climate change effects on anthropic and (semi)natural ecosystems:
The method presented here focuses on step 6 and part of steps 7 and 8 of the guidelines. This method (Figure 1) is applied to the production of maps showing annual mean air temperature variation in the argentinian sector of Bermejo Basin from 1901 to 2000.
- Define major climatic variables that condition the existence of (semi)natural and anthropic ecosystems;
- Compile statistical data of selected climatic variables of stations within and close to the study area;
- Analyze historic trends, fluctuation and extreme values for each selected parameter;
- Compile cartographic and descriptive information about ecosystems to be assessed;
- Obtain satellite imagery or aerial photos of one or more dates at a suitable spatial resolution to map ecosystems and their variation areas;
- Model the spatial and temporal variations of selected climatic parameters;
- Quantify the magnitude of climatic parameter variations for each ecosystem;
- Map ecosystem areas where climatic parameter values are lying out of their original distribution ranges to identify potential impact areas;
- Build up alternative spatial scenarios showing expected climatic parameters variations and their potential impacts on ecosystems;
- Define potential implications of changes in ecosystems distribution.
Figure 1: Method for Mapping Temperature Variation and Thermal Zones Shift Using a Geographic Information System and Linking it to Thematic Maps for further Analysis
The method starts by building up a tabular database from long-term climatic data and producing a digital elevation model (DEM) from topographic data using GIS capabilities. Then, regression analysis between air temperature and elevation are carried out and lapse rates derived. Lapse rates are validated/adjusted from instantaneous soil temperature readings at different elevations, at the depth(s) showing the best correlation with mean air temperature. Data from secondary stations have also to be used for this purpose.
Air temperatures at sea level are estimated for different periods for each meteorological station applying the obtained lapse rates, and the differences between these estimates and the ordinates (constant terms) obtained from the regression formulas are derived. Air temperature differences at sea level obtained for each station are interpolated to the rest of the area using GIS capabilities. For this, the area is assumed to be flat and at sea level during this step. Simultaneously, preliminary air temperature maps are obtained for the different periods by the straight application of the regression formulas to the DEM.
Final air temperature maps are obtained for different periods by adding the values contained on the two previous maps: air temperature differences at sea level and air temperatures derived from lapse rates, as proposed by De Fina and Sabella (1959) and De Fina (1992). Final temperature maps are used to calculate temperature variation between two periods by subtracting the values obtained for the last period to the values obtained for the first.
Simultaneously, estimated temperature values for each period are grouped into ranges most closely linked to (agro)ecological zones boundaries, and the obtained temperature differences for each couple of consecutive periods are also grouped into ranges. All maps obtained in the GIS environment until this step present a raster format, with individual values stored in individual square cells.