Loading in 5 sec....

A STATISTICAL COMPARISON OF AMPS 10-KM AND 3.3-KM DOMAINSPowerPoint Presentation

A STATISTICAL COMPARISON OF AMPS 10-KM AND 3.3-KM DOMAINS

- By
**elu** - Follow User

- 123 Views
- Uploaded on

Download Presentation
## PowerPoint Slideshow about ' A STATISTICAL COMPARISON OF AMPS 10-KM AND 3.3-KM DOMAINS' - elu

**An Image/Link below is provided (as is) to download presentation**

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

### A STATISTICAL COMPARISON OF AMPS 10-KM AND 3.3-KM DOMAINS

Michael G. Duda, Kevin W. Manning,

and Jordan G. Powers

Mesoscale and Microscale Meteorology Division, NCAR

AMPS Users’ Workshop 2004

June 8-10, 2004

Introduction

- Purpose:
- Demonstrate the usefulness of statistical significance testing in comparing biases of two domains
- Determine where biases at McMurdo Station are significantly different in the 3.3-km and 10-km AMPS domains
- Examine a 7 day period beginning 12Z Nov. 27, 2003 when McMurdo Station was affected by a snowstorm

- Methodology:
- Use hypothesis testing to identify statistically significant differences in mean bias
- Consider only differences that are statistically significant

Why Consider Statistical Significance?

- Mean bias curves do not indicate the variance in the biases
- Some differences between curves are not as relevant

Hypothesis Testing

- Consider biases to be from a hypothetical population (assumed to be normally distributed)
- Let d = x3.3 – x10
- x3.3 and x10 are biases in 3.3-km and 10-km domains at a given time

- Perform one-sample Student’s t test
- H0: d=0
- Reject H0 with 95% confidence if t t
- Test statistic:

Hypothesis Testing Example

Circled pressure levels will be examined in the next two slides

Example: 150 hPa Temperature

- For this data we can reject the null hypothesis at the 5 percent level
- This means we reject the hypothesis that the means of the 3.3-km and 10-km bias populations are the same

differences between curves

Example: 850 hPa Temperature

- For this data we cannot reject the null hypothesis at the 5 percent level
- This means we cannot reject the hypothesis that the 3.3-km and 10-km bias populations have the same mean

differences between curves

Comparison Results: Temperature

- Statistically significant differences
- Surface: 3.3-km grid has warm bias while 10-km grid has a cool bias at hours 24, 36
- 925 hPa: 3.3-km grid has warm bias while 10-km grid has a cool bias at hours 24, 36
- 300 hPa: 3.3-km grid has larger warm bias than 10-km grid

- No statistically significant differences
- At hours 24 and 36, no significant differences in MAE at any level

Comparison Results: Wind U-Component

- Statistically significant differences
- Surface: 3.3-km grid has lower positive bias than 10-km grid at forecast hours 12, 24, 36
- 850 hPa: 3.3-km grid has larger negative bias at forecast hours 12, 24, 36
- 500 hPa: 3.3-km grid has smaller bias, but MAEs of both grids are similarly large

- Differences at other levels are not statistically significant

Summary

- Use a Student’s t test (at 5 percent level) to perform statistical significance testing on difference between 3.3-km and 10-km biases
- Identify statistically significant differences on model bias v. pressure plots for McMurdo
- Consider only statistically significant differences between mean biases to improve objectivity
- Apparently large differences in mean bias may be statistically insignificant and misleading

Hypothesis Testing Example

* Biases at these pressure levels will be examined in the following slides

*

*

Example: 400 hPa Wind V-Component

For this data we do not reject the null hypothesis at the 95 percent level

differences between curves

Example: 925 hPa Wind V-Component

For this data we do reject the null hypothesis at the 95 percent level

differences between curves

Download Presentation

Connecting to Server..