# Presentation: 236759

## Precipitation Error Characterizationover the Global Oceans

- 16 June 2004

**Notes:**
Background color 0, 8, 126

## Oceanic Precipitation League

- Yuter, Wood, Horn - University of Washington
- Wilheit - Texas A & M University
- Sobel - Columbia University
- Kingsmill – University of Colorado
- Foufoula-Georgiou – University of Minnesota
- Chandrasekar – Colorado State University
- Braun – NASA Goddard Space Flight Center

**Notes:**
Reverse alphabetical order

## 3-Pronged Approach

- Bridge analysis of observations and refinements of algorithms
- GV site routine products
- Focused measurements for physical validation
- Global error characterization product

**Notes:**
3-pronged approach. physical validation using GV site and field project data, comparisons between GV and satellite, Satellite relative comparisons.

## Potential Oceanic GV Supersites

## Error CharacterizationDevelopment Challenges

- Has not been done before
- User expectations vague
- Difficult to define requirements

**Notes:**
No prescient. Practical requirements

## Prototype Advantages

- End-to-end skeleton working early
- Test drive and refine concepts
- Frequent feedback from users
- Functionality added incrementally

## Prototype Global Oceanic Error Characterization

- Input: TRMM TMI and PR (Vers. 5)
- 1B11, 1C21, 2A12, 2A23, 2A25
- Oceanic rain certain pixels
- Grids of ~2000 x 2000 km2 oceanic area
- Daily product based on accumulated statistics for previous 30 days
- Compare
- Probability distributions
- Statistical variables

**Notes:**
Basic info on prototype 

## Slide 8

## Global Error Product Will Address:

- How different?
- Relative error statistics
- Why Different?
- Diagnostic information
- Target User Groups
- Forecasters
- Algorithm Refinement
- Data Assimiliation

## GSFC PPS

- Satellite Error
- Characterization

- GV Precip
-  Characterization

- GV Routine
- Products

- Focused
- Measurements

- OPL Viewer

- Daily 1 day &
- accum 30 day
- products

- Distilled Info

- GPM Orbit
- Products

- GV Data Processing

- End User

- Info for
- Data Assim.

- Models

## Prototype Will Compare

- Spatial scales:
- PR and TMI native resolutions
- PR rescaled to TMI 10 GHz scale (30 x 60 km2)
- Data types:
- Surface Rainrate (Rsfc)
- Vertically-Integrated Precipitable                    Liquid Water Content
- Emission Tb
- Rainy Area

**Notes:**
Rescale PR to common resolution of TMI

## Conditional Rsfc PR– TMI

**Notes:**
Show how this 30 day average varies when change 1 day at a time.

## Conditional Rsfc PR– TMI

-  48

- 13

**Notes:**
Show how this 30 day average varies when change 1 day at a time.

## Tropical West Pacific near Kwajalein

**Notes:**
Skewness is departure from asymmetry relative to normal, positive is skewed to the right. Kurtosis is degree of peakedness relative to a normal distribution (is positive for more peaked and negative for less peaked than normal).

## Kwajalein GV radar 

- Kwajalein GV radar
- 37,388,868 4 km2 pixels

- Number of Pixels

- Log10(R)

## South Central Pacific

**Notes:**
Skewness is departure from asymmetry relative to normal, positive is skewed to the right. Kurtosis is degree of peakedness relative to a normal distribution (is positive for more peaked and negative for less peaked than normal).

## PR pixels rescaled to TMI 10 GHz scale

- % Rainy Area of 30 km x 60 km pixels

## % Rainy area of 10 GHz scale pixels

## Need Feedback

## Conclusions

- Global Error Characterization Prototype Skeleton Working
- PR vs TMI Rsfc Bias Varies Regionally and Temporally
- Differences between PR and TMI
- Rain/No Rain Screening
- Min Rsfc Threshold
- Can Impact Level 3 Products
- Rainy Area of TMI 10 GHz scale pixels
- Regional Variations
- Strongly Skewed to Small %

## The End

## TMI Swath (872 km)

- PR Swath (245 km)

- EFOVs

- Along-track axis

- EFOV

- IFOV end

- IFOV start

- Satellite subpt 15 km
- between swaths

**Notes:**
Need all post-boost values.

## Slide 23

## PR Rainy Pixel Rsfc Mean

## TMI Rainy Pixel Rsfc Mean

## PR-rescaled Rsfc Average