climate

Change in Annual Average Temperature (°F) from 1950 to 2006
The source of observed temperature data was 176 weather stations measuring daily maximum and minimum temperatures during 1950-2006 in and around Wisconsin, from the National Weather Service’s Cooperative Observer Program. This data was interpolated to an 8-km grid (Serbin & Kucharik, 2009. Daily average temperature was estimated by averaging the daily maximum and minimum temperatures. Trends in annual temperature were estimated using the slopes of linear regression fits for the entire 1950-2006 time series.

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Change in Annual Average Precipitation (inches) from 1950 to 2006
The source of observed temperature data was 176 weather stations measuring daily maximum temperatures during 1950-2006 in and around Wisconsin, from the National Weather Service’s Cooperative Observer Program.  This data was interpolated to an 8-km grid (Serbin & Kucharik, 2009).  Trends in the frequency of daily high temperatures exceeding 90°F were estimated using the slopes of linear regression fits for the entire 1950-2006 time series.

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Projected Change in Annual, Spring, Summer, Autumn, and Winter Average Temperature (°F) from 1980 to 2055
The climate output that was analyzed was produced by fourteen global climate models from the Coupled Model Intercomparison Project Phase 3 (CMIP3), a critical source of data to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Results are based on the A1B emission scenario, which is considered a mid-line scenario for both carbon dioxide emissions and economic growth, with carbon dioxide levels in the atmosphere rising from 390 ppmv (parts per million by volume) at present to 550 ppmv by the mid-2050s. The coarse climate projections were downscaled to a 0.1° latitude x 0.1 °longitude grid over Wisconsin and debiased against observed temperature and precipitation from station observations within the National Weather Service’s Cooperative Observer Program. By interpolating and debiasing probability distribution functions and their attributes, a realistic representation of the variance and extremes of temperature and precipitation was achieved, in addition to a realistic representation of the means of both variables. In computing the projected change in annual average temperature, the difference in mean temperature between 2046-2065 and 1961-2000 was computed. For the seasons, March-May was used for spring, June-August for summer, September-November for autumn, and December-February for winter.

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Projected Change in Winter Average Precipitation (inches) from 1980 to 2055
The climate output that was analyzed was produced by fourteen global climate models from the Coupled Model Intercomparison Project Phase 3 (CMIP3), a critical source of data to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4).  Results are based on the A1B emission scenario, which is considered a mid-line scenario for both carbon dioxide emissions and economic growth, with carbon dioxide levels in the atmosphere rising from 390 ppmv (parts per million by volume) at present to 550 ppmv by the mid-2050s.  The coarse climate projections were downscaled to a 0.1° latitude x 0.1° longitude grid over Wisconsin and debiased against observed temperature and precipitation from station observations within the National Weather Service’s Cooperative Observer Program.  By interpolating and debiasing probability distribution functions and their attributes, a realistic representation of the variance and extremes of temperature and precipitation was achieved, in addition to a realistic representation of the means of both variables.  In computing the projected change in wintertime precipitation, the difference in mean December-February precipitation between 2046-2065 and 1961-2000 was computed.

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Projected Change in the Frequency of 2” Precipitation Events (days/decade) from 1980 to 2055
The climate output that was analyzed was produced by fourteen global climate models from the Coupled Model Intercomparison Project Phase 3 (CMIP3), a critical source of data to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Results are based on the A1B emission scenario, which is considered a mid-line scenario for both carbon dioxide emissions and economic growth, with carbon dioxide levels in the atmosphere rising from 390 ppmv (parts per million by volume) at present to 550 ppmv by the mid-2050s.  The coarse climate projections were downscaled to a 0.1° latitude x 0.1° longitude grid over Wisconsin and debiased against observed temperature and precipitation from station observations within the National Weather Service’s Cooperative Observer Program.  By interpolating and debiasing probability distribution functions and their attributes, a realistic representation of the variance and extremes of temperature and precipitation was achieved, in addition to a realistic representation of the means of both variables.  The projected change in the frequency of 2-inch (or more) precipitation days is computed as the difference in the number of such wet days per year during 2046-2065 and 1961-2000.  Results are based on the time-mean cumulative distribution function and the frequency of exceeding the 2-inch precipitation threshold, using the full array of realizations of the small-scale atmospheric state for a given large-scale circulation pattern.

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Projected Change in the Frequency of 90°F Days per Year from 1980 to 2055
The climate output that was analyzed was produced by fourteen global climate models from the Coupled Model Intercomparison Project Phase 3 (CMIP3), a critical source of data to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Results are based on the A1B emission scenario, which is considered a mid-line scenario for both carbon dioxide emissions and economic growth, with carbon dioxide levels in the atmosphere rising from 390 ppmv (parts per million by volume) at present to 550 ppmv by the mid-2050s. The coarse climate projections were downscaled to a 0.1° latitude x 0.1° longitude grid over Wisconsin and debiased against observed temperature and precipitation from station observations within the National Weather Service’s Cooperative Observer Program. By interpolating and debiasing probability distribution functions and their attributes, a realistic representation of the variance and extremes of temperature and precipitation was achieved, in addition to a realistic representation of the means of both variables. The projected change in the frequency of 90°F days is computed as the difference in the number of such hot days per year during 2046-2065 and 1961-2000. Results are based on the time-mean cumulative distribution function and the frequency of exceeding the 90°F high-temperature threshold, using the full array of realizations of the small-scale atmospheric state for a given large-scale circulation pattern.

 

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