# Presentation: 670674

## GFE Diurnal Temperature TrendSmart Tool

- Chris Sohl – Norman OK

## The Motivation...

- Grids appear very accurate and detailed, but...
- Important forecasts occasionally have large errors

- _10PM ASOS Temps_
- SPS	82
- OKC	79
- HBR	78
- GAG	77

**Notes:**
Here’s how we traditionally create forecasts.  Weather models produce guidance for meteorologists at local offices and national centers.  Forecasters at our national centers generate a variety of graphical products, and experts at each local office type text products and weather element forecasts for specific locations.  With this process, the NWS and our partners and customers are wedded to fixed product formats and schedules.  Also, even if our forecasters understand the details of a weather event at higher resolution (in space and time), they are unable to express the full content of this information to the public in words.

## The Motivation...

**The Motivation...**

**Notes:**
Here’s how we traditionally create forecasts.  Weather models produce guidance for meteorologists at local offices and national centers.  Forecasters at our national centers generate a variety of graphical products, and experts at each local office type text products and weather element forecasts for specific locations.  With this process, the NWS and our partners and customers are wedded to fixed product formats and schedules.  Also, even if our forecasters understand the details of a weather event at higher resolution (in space and time), they are unable to express the full content of this information to the public in words.

## The Motivation...

- Linear interpolation has saw tooth appearance
- Cubic spline interpolation shifts the time of Max and Min temperatures
- Both methods too slow to warm temps in the day and cool in the evening

## Slide 5

## The Motivation...

- Computed typical temperature changes at certain intervals of the day and adjusted those grids accordingly before interpolating
- Thus, why not develop an interpolation algorithm that performs this operation?

## Methodology 

- Used 8 years of 5 minute data for two Mesonet sites in Oklahoma
- Determined the average ratio (f) of the Min. to Max. temperature at each hour
- Diurnal temperature curves derived for each month
- Result:  **DiurnalTfromMaxTMinT**

## Methodology 

**        ****#     J   F   M   A   M   J   J   A   S   O   N   D   GMT**
**        ****f=[[ 68, 81, 86, 89, 87, 89, 89, 86, 80, 69, 62, 61], # 0**
**           ****[ 53, 62, 65, 72, 72, 75, 75, 69, 57, 51, 50, 50], # 1**
**           ****[ 44, 50, 53, 54, 53, 55, 55, 50, 45, 41, 42, 40], # 2**
**           ****[ 37, 42, 44, 44, 42, 43, 42, 40, 37, 35, 35, 34], # 3**
**           ****[ 31, 36, 36, 36, 34, 35, 34, 33, 30, 30, 30, 29], # 4**
**           ****[ 26, 31, 30, 30, 27, 28, 28, 27, 24, 25, 25, 25], # 5**
**           ****[ 21, 25, 24, 25, 21, 22, 22, 22, 20, 20, 20, 21], # 6**
**           ****[ 17, 20, 18, 20, 16, 16, 17, 19, 16, 17, 16, 18], # 7**
**           ****[ 13, 16, 15, 15, 12, 11, 13, 14, 12, 14, 13, 15], # 8**
**           ****[ 10, 12, 11, 10,  7,  8,  8, 10,  9, 11, 10, 11], # 9**
**           ****[  7,  9,  7,  6,  3,  3,  4,  6,  5,  7,  7,  7], # 10**
**           ****[  5,  5,  3,  3,  0,  0,  1,  2,  2,  4,  5,  5], # 11**
**           ****[  2,  2,  1,  0,  0,  1,  0,  0,  0,  1,  1,  1], # 12**
**           ****[  0,  0,  0,  6, 12, 15, 13, 10,  3,  0,  0,  0], # 13**
**           ****[  1,  2, 12, 24, 28, 31, 29, 28, 21, 16,  7,  1], # 14**
**           ****[ 15, 20, 30, 41, 44, 47, 46, 46, 41, 37, 26, 19], # 15**
**           ****[ 36, 41, 48, 56, 59, 60, 60, 62, 58, 56, 47, 40], # 16**
**           ****[ 56, 59, 63, 69, 71, 72, 74, 76, 72, 71, 65, 60], # 17**
**           ****[ 73, 75, 75, 81, 80, 81, 84, 86, 83, 83, 80, 77], # 18**
**           ****[ 86, 87, 87, 89, 89, 89, 92, 94, 91, 92, 91, 89], # 19**
**           ****[ 96, 96, 94, 96, 95, 95, 97, 97, 97, 97, 97, 97], # 20**
**           ****[100,100, 98,100, 98,100,100,100,100,100,100,100], # 21**
**           ****[ 98,100,100,100,100,100,100,100, 98, 98, 97, 97], # 22**
**           ****[ 89, 96, 96, 97, 96, 96, 96, 95, 94, 91, 85, 84]] # 23**
**        ****#     J   F   M   A   M   J   J   A   S   O   N   D**

- Python “f-table”

## “f-table” 

## Features of DiurnalTfromMaxTMinT

- “f-table”  used on Fcst MaxT and MinT to compute the hourly T that climatologically is the warmest or coldest for that time of year
- Diurnal curves factor in “average” wind, cloud cover and humidity

## Tool Limitations

- Not for periods with a non-standard diurnal temperature trace (i.e. falling temps during the day or warming at night)
- Periods with non-standard trace can be deselected

## Advantages

- An improved interpolation scheme over existing linear or cubic spline interpolation methods
- Tool  based on meteorology (climatology) rather than a strictly mathematical derivation

## Advantages

- Provides better ‘first guess’ temperature trend which can be easily modified with the temporal tool
- Especially useful for days 3 through 7

## Applying the Tool

- MaxT and MinT grids edited
- Smart Tool applied to those periods where a standard diurnal trace exists

## Slide 15

## Adjustments to diurnal curve easily made in the 

**Adjustments to diurnal curve easily made in the **
**     ****temporal editor**
**(EX: faster than normal cooling during evening**
**     ****hours on a calm, clear night)**

## Examples of:   

**Examples of:   **
** ****Non-standard diurnal trace**
** ****Inverted ‘sharkfin’ shape of the climatological trace**

## Max/Min points on curve in temporal editor are not

**Max/Min points on curve in temporal editor are not**
**      ****adjusted**
**Can adjust temporal curve for smaller edit area **
**      ****subset**

## Credits

- Cheryl Sharpe – Concept; Statistical
-                               Analysis of Climate Data
- Steve Nelson –  Smart Tool Coding
- Oklahoma Climatological Survey –    Provided climate data