# Presentation: 502362

## Data Quality Assurance Algorithm

**James Evans**
**NEXRAD TAC**
**22 MAY 2002**

## Key FAA Systems that Benefitfrom Improved NEXRAD Algorithms

- Integrated Terminal Weather System

- Weather And Radar Processor

- Corridor Integrated Weather System

- Medium Intensity Airport Weather System

## Why a Data Quality Assurance Algorithm?

**NEXRAD reflectivity data susceptible to**
**Artifacts (bull’s-eyes, sun strobes, AGC malfunctions)**
**Clutter (AP- anomalous propagation)**
**Operational effectiveness of reflectivity products compromised by contaminants**
**Especially as used by non-meteorologist ATC personnel**
**FAA needs maximum removal of contaminants from reflectivity products to achieve goals**
**Increased safety**
**Reduced convective weather delays**
**Solution:  An algorithm that removes contaminants through  both artifact detection (AD) and AP detection**

## Data Quality Assurance Algorithm

## Artifacts not limited to “bull’s-eye” patterns
Wedges/spikes/strobes
Other circular patterns (starbursts)

Typical sources
WSR-88D equipment failure
Loss of AGC attenuation
Loss of AGC control
Any other type of receiver failure
Interference
FAA and DOD radars
Aircraft
Ground based, wireless, cable TV, and other transmitter transmissions
Solar

Many characterized by a radial constant power function signature

**Wedges/spikes/strobes**
**Other circular patterns (starbursts)**
**Typical sources**
**WSR-88D equipment failure**
**Loss of AGC attenuation**
**Loss of AGC control**
**Any other type of receiver failure**
**Interference**
**FAA and DOD radars**
**Aircraft**
**Ground based, wireless, cable TV, and other transmitter transmissions**
**Solar**
**Many characterized by a radial constant power function signature**

**WSR-88D Artifacts**

## More Artifact Examples

- March 21, 2000
- 1450 UTC
- Jackson, MS

- March 22, 2000
- 1513 UTC
- San Diego, CA
- Beale, CA

- May 5, 2000
- 1524 UTC
- Beale, CA

**More Artifact Examples**

## DQA Algorithm Flow – AD Removal

- Source:  Logic based on Unisys’ WARP artifact detection design document.
- MIT/LL modified for application to all tilts in volume and added exclusion checks.

## Ground Cluttera/k/a Anomalous Propagation (AP)

**NWS meteorologists use clutter filters to remove ground clutter that is “always” present near the radar**
**When a temperature inversion causes air at surface to be colder than air aloft, beams are bent toward the ground and AP clutter is encountered unexpectedly**
**Night time/early morning in clear weather**
**After a thunderstorm passes near a radar site**
**NWS generally does not use clutter filters to get rid of AP**

## More AP Examples

- Fort Worth
- 100197
- 1538 UTC
- AP embedded with cells to north

- Memphis
- 042096
- 1259 UTC
- AP to north and west post squall line passage

## DQA Algorithm Flow – AP Removal

## Enhanced DQA AP Edit vs. Build 1.2 AP Edit

**Goal**
**Both maximize ****AP**** removal with minimal impact on “****weather****”**
**Versions**
**Enhanced AP Edit is original LL AP Edit logic**
**ORPG Build 1.2 is sibling of above (from pre-ORPG) now with modified adaptation parameters**
**Method**
**Both use removal by region**
**Different reflectivity and Doppler adaptation parameter values**
**removal by extension**
**1D radial “blooming” similar**
**2D extension significantly differ**
**Limitation**
**Both require all 3 radar moments**
**Potential future DQA upgrade to include REC input and/or Princeton U. dBZ texture logic to mitigate**

## Method

**Removal by region**
**low dBZ**** in any region prioritized over ****AP**** rules**
**OMIT ALL**** - all gates in region are ****AP**
**ACCEPT IF**** - all gates in region are ****AP**** unless proven “****weather****”**
**REJECT IF**** - all gates in region are “****weather****” unless proven ****AP**
**ACCEPT ALL**** - all gates in region are “****weather****”**
**Removal by extension**
**clutter bloom (1D neighbor extension)**
**order statistics filtering (2D neighborhood window extension)**
**LL version uses a scatter filter**
**ORPG Build 1.2 uses a median filter with adaptation parameters set to simulate a pseudo-scatter filter result**
**Critical Difference**
**The LL scatter filter technique is superior to the ORPG Build 1.2 pseudo-scatter filter method for AP removal and not over smoothing the data**

## Regions along Radial for AP Editing

- Contiguous range gates along a radial are grouped into regions as
- a function of elevation angle (tilt), distance from radar, and altitude
- caps.  With processing performed on individual radials, the regions
- along a radial essentially are as follows:

## AP Edit Version Flow Summary

- Removal by Extension

- Clutter Bloom logic similar
- Doppler and reflectivity adaptation parameters differ

- Order Statistic Filters –
- Scatter Filter Used
- Median Filter Not Used

- Removal by Extension

- Order Statistic Filters –
- Scatter Filter Not Available
- Median Filter Used as Pseudo-scatter filter

**DQA AP EDIT**

**ORPG BUILD 1.2**

## DQA benefits HRVIL product – Sun strobe

## DQA benefits HRVIL product – Bull`s-eye

## DQA Algorithm and ORPG Builds

**Build 3 version currently in testing prior to hand-off to the ROC this July**
**High Resolution VIL algorithm retooled to use DQA input for Build 3 (also soon in testing)**
**March 2003 begins operational release cycle **
**DQA output will be available to any NEXRAD algorithm**
**Possible future DQA-edited comprefl product(s) to supercede current AP-edited comprefl products**