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The Diurnal Temperature Smart Tool What is it and why the need for it? What is it and why the need for it? How is it implemented? How is it implemented?

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Presentation on theme: "The Diurnal Temperature Smart Tool What is it and why the need for it? What is it and why the need for it? How is it implemented? How is it implemented?"— Presentation transcript:

1 The Diurnal Temperature Smart Tool What is it and why the need for it? What is it and why the need for it? How is it implemented? How is it implemented? What are the results? What are the results? Angie Enyedi National Weather Service Jacksonville, FL

2 What is it? An interpolation method of hourly temperatures between forecast maximum and minimum temperatures in the new graphical forecast produced by the NWS, the Interactive Forecast Preparation System (IFPS).

3 The default interpolation methods in the Graphical Forecast Editor (GFE) were either the Cubic Spline or the Linear Interpolation Methods. The default interpolation methods in the Graphical Forecast Editor (GFE) were either the Cubic Spline or the Linear Interpolation Methods. These methods were used during the implementation stage of IFPS. These methods were used during the implementation stage of IFPS. Initial Interpolation Techniques

4 Both fail to represent abrupt temperature falls after sunset and temperature rises after sunrise. Both fail to represent abrupt temperature falls after sunset and temperature rises after sunrise. Both have unrepresentative peaks (linear) and plateaus (cubic spline) when the daily max or min temperature is achieved. Both have unrepresentative peaks (linear) and plateaus (cubic spline) when the daily max or min temperature is achieved.

5 We need an interpolation tool that accounts for monthly differences in radiational cooling and insolation between the times of daily minimum and maximum temperatures! ANSWER: The Diurnal Temperature Tool

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7 Cubic LinearDiurnal MAE (  F) 4.7 3.4 1.1 Mean Absolute Error

8 How the Tool was Implemented at JAX 1. Stratifying the Data 7 years of hourly ASOS observations were stratified by month then by hour for site JAX (Jacksonville, FL). 7 years of hourly ASOS observations were stratified by month then by hour for site JAX (Jacksonville, FL). Archived data was obtained from NCDC. Archived data was obtained from NCDC. Date/Time (Z) Actual Temp Apr 1, 1995 0200Z 55 Apr 2, 1995 0200Z53 ….etc… Apr 30, 2001 0200Z 66

9 2. Averaging the Data For Example: T hour for 01 April = 60.30 T hour for 02 April = 59.46 T hour for 03 April = 58.59 All temps in a particular hour in a given month were avearged to get an average T hour. All Temps for that hour summed, then divided by total number of entries to get T hour. Average T hour for 02Z in April = 59.56

10 3. Calculating the ratio, f Temperatures from 00Z-23Z were converted to a range between 5-95% based on the difference between the T max and T min each month. Note: f for T max = 95 f for T min = 5 f for T min = 5 This was done to reduce the warm and cold bias. (T hour -T min ) T max -T min + 5 = f 90

11 4. Smart Tool references the “f” Table The f table is referenced by the diurnal temperature smart tool when it calculates hourly temperatures (T hour ) between the forecast daily minimum and maximum temperatures. The f table is referenced by the diurnal temperature smart tool when it calculates hourly temperatures (T hour ) between the forecast daily minimum and maximum temperatures. Tool will warm & cool temperatures based on monthly diurnal climatological trends. Tool will warm & cool temperatures based on monthly diurnal climatological trends. F Table for April 00Z 5812Z 12 01Z 4513Z 33 02Z 38 14Z 53 03Z 3315Z 68 04Z 27 16Z 78 05Z 2317Z 85 06Z 2018Z 91 07Z 1619Z 94 08Z 1220Z 95 09Z 921Z 92 10Z 722Z 86 11Z 523Z 75

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13 Note the seasonal variation of the approximate time of the daily max and min temperature. Note the seasonal variation of the approximate time of the daily max and min temperature. Note the seasonal variation of temperature decrease (increase) after sunset (sunrise). Note the seasonal variation of temperature decrease (increase) after sunset (sunrise).

14 Cubic LinearDiurnal MAE (  F) 6.4 3.8 1.7 Mean Absolute Error

15 Cubic LinearDiurnal MAE (  F) 4.4 3.1 1.8 Mean Absolute Error

16 Cubic LinearDiurnal MAE (  F) 5.1 3.1 0.8 Mean Absolute Error

17 Results of the Diurnal Temperature Interpolation Method Data suggests that the diurnal temperature interpolation method better represents monthly radiational cooling & insolation trends when compared to the linear and cubic spline methods.

18 Benefits of the Diurnal Temperature Interpolation Tool Best represents abrupt diurnal temperature rises and falls when compared to the cubic spline and linear interpolation techniques. Best represents abrupt diurnal temperature rises and falls when compared to the cubic spline and linear interpolation techniques. Has representative increases and decreases when the daily max or min temperature is achieved. Has representative increases and decreases when the daily max or min temperature is achieved. Can be customized for each month (and various sites across the country) accounting for differences in radiational warming & cooling. Can be customized for each month (and various sites across the country) accounting for differences in radiational warming & cooling.

19 Short Comings of the Diurnal Temperature Smart Tool Only customized for site JAX in our forecast area. The tool is run over our entire grid space and may not represent radiational cooling or insolation trends at sites further inland nor those close to the coast. Only customized for site JAX in our forecast area. The tool is run over our entire grid space and may not represent radiational cooling or insolation trends at sites further inland nor those close to the coast. Does not represent sensible heat influences from convection or latent heat influence from ground moisture. Does not represent sensible heat influences from convection or latent heat influence from ground moisture. Does not account for atypical warming/cooling such as warm air advection at night or cold air advection during the day. Does not account for atypical warming/cooling such as warm air advection at night or cold air advection during the day.

20 Taking the Diurnal Smart Tool a Step Further… Data could be further stratified based on cloud cover, for example: Diurnal temperature smart tool could be created for sunny/mostly sunny, partly cloudy, and clouldy/mostly cloudy days in GFE.

21 Credits & Where to Get the Tool Cheryl Sharpe and Steve Nelson (NWS) Created the original Diurnal Temperature Smart Tool Jason Hess IFPS Focal Point NWS Jacksonville, FL The Diurnal Temperature Smart Tool is available for download into IFPS at the Smart Tool Repository Website.

22 Thank You! Questions and/or Comments? Angie Enyedi Forecaster NWS Jacksonville, Climate F.P. angela.enyedi@noaa.gov


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