# Presentation: 502466

## Quantitative PrecipitationEstimation by WSR-88D Radar

- Dan Berkowitz
- Applications Branch
- Radar Operations Center

## WSR-88D Radar QPE 

- Where we were
- Where we are now
- Where we are going

## Steps in Radar Rainfall Estimation

- Reflectivity is sampled for an unblocked volume in space by scanning at selected elevation angles.
- Ground clutter contamination is reduced or eliminated.
- An equation relating reflectivity to rainfall rate is applied.
- Accumulations are made from each volume scan and added to the previous amounts.
- Adjustments can be made to account for a bias – overestimate or underestimate compared with rain gauges.
- Products are created and distributed to users.

## History of Major Changes in PPS

- 1991:  First system deployment (using sectorized occultation data)
- 1998:  **Terrain-based** occultation data and additional **rainfall rate relationships**
- 2004:  Build 5 software with **Enhanced**** ****Preprocessing** (EPRE) and new ***(high vertical resolution)*** volume coverage pattern (VCP)

## Objectives in Hybrid Scan Construction

- Original (Sectorized) Hybrid Scan --
-    The objective is to **utilize reflectivity measurements**** from as close to 1-km altitude above radar level as possible** while minimizing the likelihood of ground clutter and data loss due to terrain blockages (i.e., 1 km beam clearance).
- Terrain-based Hybrid Scan --
-    The objective is to **use reflectivity** **from the lowest unblocked and “uncontaminated” elevation angle **(i.e., 1 _*meter*_ beam clearance).

## Construction of Hybrid Scan Reflectivity

- Generic hybrid scan construction from bottom four slices and USGS DEM terrain
- Rings at 11, 19, and 27 nm
- Terrain-based hybrid scan construction from bottom four slices and NIMA DTED terrain data
- Elimination of most ring discontinuities
- Beam blockage algorithm (BBA) starting in 2004 using NIMA and SRTM DTED data

## Terrain-based Hybrid Scan (NE cross-section at Eureka, CA)

## Original Hybrid Scan

**Notes:**
Eureka CA (KBHX) Storm Total Precipitation (STP) product for 2/21/96 shows the anomalous concentric rings caused by 1000 meter optimum height (above radar) rule used to create the old Hybrid Scan data files.

## Terrain-based Hybrid Scan

**Notes:**
KBHX STP for 2/21/96 using the “terrain-based” Hybrid Scan data file.  The anomalous rings have been eliminated.

## Terrain and Blockage Map Quality

- From 1991-1998 **USGS (NAD 27) “native DEM” data** – Resolution was 3 arc-seconds, roughly 90 meters (1:250,000-scale), but with poor geolocation of some radar sites and with vertical accuracy inadequate for blockage determination (called “occultation data”).  The algorithm for map generation was poor.
- Starting 1998 **NIMA DTED-1 (NAD 83)** – These were better and more complete data than USGS DEM data.  An improved blockage map generation algorithm was used.
- Starting 2005 **SRTM-1 DTED-2 (WGS 84 datum)** – These data have a resolution of 1 arc-second, roughly 30 meters (1:24,000-scale) to be used _**within 50 km**_ of each radar where it is available (i.e., not for sites above 60° N latitude)

## Resolution of Digital Terrain Elevation Data(blue boxes = 3 arc-sec; red boxes = 1 arc-sec)

## Clutter Mitigation

**Clutter suppression of ground return in **_**base data**_ using near zero velocity (notch widths)
- Ignoring AP-contaminated lowest elevation in PPS by use of the “tilt test”
- Tilt test replaced in 2004 by Radar Echo Classifier AP Detection Algorithm (REC-APDA) on a bin-by-bin basis (Build 5 software)
**Clutter suppression of ground return in **_**base data**_ using Gaussian Model Adaptive Processing (GMAP) with ORDA

## Ground Returns (Ground Clutter)

**NP** = Normal Propagation ground returns *(identified in a clutter bypass map)*
**AP** = Anomalous Propagation ground returns *(typically causing “contamination” of RPG products and often handled by operator-selected clutter suppression regions)*(Note that _**at**_** **_**least**_** **_**one**_ volume scan will pass before an operator sees AP ground returns and “rectifies” them with clutter regions.  A much greater period of time is likely to pass before an operator returns to bypass map only.)

## Ground Clutter Mitigation – Legacy RDA

- RDA

- ORPG

**Clutter filtering:**  NP Clutter Bypass Map and/or clutter regions (low, medium, or high velocity notch width suppression)

- Zh, V, W

- (***often*** with AP ground returns)

- Products

- I & Q

- 1. **R**adar **E**cho **C**lassifier (REC) **AP** **D**etection **A**lgorithm

- 2. **E**nhanced Precip.
**Pre**processing (EPRE)

- 3.  **H**ybrid **S**can **R**efl. (HSR) used in PPS, SAA, & RCM

## Ground Clutter Mitigation – Initial ORDA

- ORDA

- ORPG

**Clutter filtering (GMAP):**  NP Clutter Map and/or clutter regions

- Zh, V, W

- Products

- I & Q

- 1. Radar Echo Classifier (**REC**) **AP** **D**etection **A**lgorithm

- 2. Enhanced Precip.
- Preprocessing (**EPRE**)

- 3.  Hybrid Scan Refl. (**HSR**) used in PPS, SAA, & RCM

- (***often*** with AP ground returns)

## Ground Clutter Mitigation –        Proposed ORDA-based AP Detection

- ORDA

- ORPG

**1.  NP Clutter filtering (GMAP)**

- Zh, V, W

- Products

- I & Q

- 1. Radar Echo Classifier (**REC**) **AP** **D**etection **A**lgorithm

- 3. Enhanced Precip.
- Preprocessing (**EPRE**)

- 4.  Hybrid Scan Refl. (**HSR**) used in PPS, SAA, & RCM

- 2.  **REC** **P**recip.
**D**etection **A**lgorithm

**2.**  **C**lutter **F**ilter **D**ecision **S**upport         (for AP)

**3.  AP Clutter filtering (GMAP)**

- (Nearly all AP
- ground return
- is removed, as
- needed, in real
- time.)

## CFDS Methodology and Example

- CFDS will automate GMAP application in AP conditions
- Fuzzy logic used to discriminate AP clutter from precipitation
- GMAP applied only to gates with AP clutter
- Precipitation is not filtered and, therefore, is not biased (unless weather spectrum is
-      (narrow and centered at 0m/s velocity)
- Clutter filtering is done in *real time.*
- Example: KJIM squall line (assume NP clutter is AP clutter)

- Reflectivity – No GMAP

- Velocity – No GMAP

## CFDS Specifies Where GMAP is Applied

- Clutter flag specifies GMAP application
- Near-zero precipitation return is not clutter filtered and no bias is introduced
- NP clutter is removed and underlying signal recovered

- Reflectivity – CFDS turns GMAP on/off

- Velocity – CFDS turns GMAP on/off

## What if GMAP is Applied Everywhere?

- Example shown for comparison purposes only
- Shows the bias that is introduced when precipitation is clutter filtered
- CFDS will automate the clutter filter application decision and remove the human from this decision loop
- Result: much improved moment estimates and data quality

- Reflectivity – GMAP applied at all gates

- Velocity – GMAP applied at all gates

## Ground Clutter Mitigation – Dual Polarization (Proposed)

- ORDA

- ORPG

- Zh, Zv, ZDR, V, W, ρhv, KDP, ΦDP

- Products

- I & Q

**1.  NP Clutter filtering (GMAP)**

**2. ** **CFDS includes dual pol. variables** (for AP)

**3.  AP Clutter filtering (GMAP)**

**1.  Hydrometeor Classification Algorithm (HCA) **

**2.  Enhanced Precip. **
**Preprocessing (EPRE v2)**

**3.  Hybrid Scan DP moments used in Dual Pol. PPS, SAA, & RCM**

- (AP ground return
- is removed in real
- time.)

## Near or Deep Convection Volume Coverage Patterns

- VCP11

- VCP12 – starting 2004

- Near or Deep Convection Volume Coverage Patterns

**Notes:**
Note, original PPS requires legacy VCPs have the same lowest 4 tilts (0.5, 1.5, 2.4, 3.35).  
Build 5 (2004) PPS can use any VCP.  VCP 12 maintains a constant height difference between elevation angles and scans more often.

## PPS Adaptable Parametersin Enhanced Preprocessing (EPRE)

## PPS Adaptable Parametersin Enhanced Preprocessing (EPRE)

**CLUTTHRESH** (refer to CLR product)
**RAINZ** (dBZ threshold)
**RAINA** (area threshold)
**NEXZONE** (number of exclusion zones)
- Wind farms
- Highways
- Plumes

## Supplementary Precipitation Data (SPD)

**VOLUME COVERAGE PATTERN = 21    MODE = A     TIME CONT: PASSED**
**                                                                                **
**          ****GAGE BIAS APPLIED               -      NO**
**               ****BIAS ESTIMATE              -     0.34**
**               ****EFFECTIVE # G/R PAIRS      -    11.38**
**               ****MEMORY SPAN (HOURS)        -     5.00**
**               ****DATE/TIME LAST BIAS UPDATE - 06/24/05 20:26**
**  ****TOTAL NO. OF BLOCKAGE BINS REJECTED     -        0**
**               ****CLUTTER BINS REJECTED      -    41281**
**               ****FINAL BINS SMOOTHED        -        0**
**   ****HYBRID SCAN PERCENT BINS FILLED        -    99.86**
**               ****HIGHEST ELEV. USED (DEG)   -     9.90**
**               **_**TOTAL RAIN AREA (KM**2)**_**  - ****15210.94**
**                                                                                **
**        ****MISSING PERIOD: 06/24/05 16:06 06/24/05 17:27**

## Human Computer Interface (HCI) for Build 8 RPG

## Build 8 Precipitation Status Window

## Converting Reflectivity to Rainfall Rate

- Default WSR-88D Convective Relationship
- (Z=300R1.4)
- Additional Relationships (late 1990s) Optimized for Different Weather Situations
- Tropical Convective (Rosenfeld) Z=250R1.2
- General Stratiform (Marshall-Palmer) Z=200R1.6
- Winter/Cool Stratiform & Orographic – East (Z=130R2.0)
- Winter/Cool Stratiform & Orographic – West (Z=75R2.0)

**Notes:**
Convective: 	Summer deep convection and other non-tropical convection

Tropical-Rosenfeld:  Tropical convective systems

Marshall-Palmer:  General stratiform precipitation

Cool Stratiform:  Winter stratiform precipitation and orographic precipitation (East and West of continental divide)

## Maximum Precip. Rate Allowed (MXPRA) a.k.a. “hail cap”

| Climate/regime
 | MXPRA Value
 |
| --- | --- |
| Arid - High Plains Spring
 | 75 mm/hr (~3 in/hr)
 |
| Central Plains Spring, High Plains Summer
 | 100 mm/hr (~4 in/hr)
 |
| Central Plains Summer, Gulf Coast Spring
 | 125 mm/hr (~5 in/hr)
 |
| Tropical - Gulf Coast Summer
 | 150 mm/hr (~6 in/hr)
 |

## G/R Mean Field Bias Table (in SPD product)

| MEMORY SPAN
(HOURS) | EFFECTIVE NO.
G-R PAIRS | AVG. GAGE
VALUE (MM) | AVG. RADAR
VALUE (MM) | MEAN FIELD
BIAS |
| --- | --- | --- | --- | --- |
| 0.001  | 1.000  | 1.016  | 1.372  | 0.740  |
| 1.000  | 1.769  | 0.695  | 1.260  | 0.552  |
| 2.000  | 3.144  | 0.693  | 1.729  | 0.401  |
| 3.001  | 5.558  | 0.831  | 2.370  | 0.350  |
| 4.998  | 11.377  | 1.026  | 3.053  | 0.336  |
| 10.004 | 22.779  | 1.210  | 3.576  | 0.338  |
| 168.006   | 338.968  | 2.584  | 4.296  | 0.601  |

**    ****LAST BIAS UPDATE TIME:  06/24/05 20:26           BIAS APPLIED ?   NO**

## Legacy PPS with Sectorized HSR

## 2004:  Build 5 PPS with Terrain-Based HSR (unlimited angles)

## Evolution of Radar Rainfall Rate Calculation

_**Horizontal Polarization:**_
**R(Z****h****)** for all drop size distributions (with adaptable coefficient and exponent for specific weather regimes)

_**Dual Polarization:**_
**R(Z****h****)** okay for reference to past but underestimates in small droplet rain (low ZDR) and overestimates in large drop rainfall (high ZDR); highly vulnerable to hail contamination
**R(K****DP****)** okay for cool season stratiform (esp. with bright band) but not good for long ranges or very light rain
**R(K****DP****,Z****DR****)** okay for areal rainfall estimation and high rainfall rates
**R(Z,Z****DR****)** okay for low rainfall rates
**R(Z,K****DP****,Z****DR****) ***“synthetic algorithm”*** **good for warm season convection and best overall

## Dual Polarization Weather Radar (by end of this decade)

- Combined radar moments will lead to a Hydrometeor Classification Algorithm (HCA) **to distinguish hail, heavy rain, snow, birds, insects, etc.**
- Rate relationship depends upon HCA.

## Slide 34

## Uncertainties in Radar Precip. Estimation (abbreviated list)

- Complete or partial beam blockage
- Beam propagation path – height of sample
- Mixed precipitation types **(hail, rain, and/or snow)**
- Beam not filled with precipitation
- Evaporation near the ground
- Detection of non-meteorological targets (**ground, birds, bugs, **etc.)
- Displacement of radar sample relative to a ground location (rain gauge) due to wind shear
**Methods of integrating** radar with rain gauge and satellite data

## CNRFC 24-Hour Precipitation 17 Dec 2002

- Radar Only

- Gauge Only

## CNRFC 24-Hour Precipitation 17 Dec 2002

- Radar Only

- Gauge Bias-Corrected Radar

## CNRFC 24-Hour Precipitation 17 Dec 2002

- Gauge Bias-Corrected Hydroestimator

## Summary

**Blockages** and **ground clutter contamination** are reduced.
- EPRE provides flexibility to use new VCPs.
**Multi-sensor mosaics** enable River Forecast Centers and other radar data users to get better areal rainfall estimates.
- Changes in the near future will reduce uncertainties and help discriminate meteorological from non-meteorological targets.

## Dealing With Uncertainty

- “As we know, there are known knowns.  There are things we know we know.
- We also know there are known unknowns.  That is to say, we know there are some things we do not know.
- But there are also unknown unknowns, the ones we don’t know we don’t know.”
- -- Donald Rumsfeld (2004)

## Questions?

*Questions?*

## Snow Accumulation Algorithm Products

**OSW**, #144: One-Hour Snow Accumulation (Water Equiv.)
**OSD**, #145: One-Hour Snow Accumulation (Depth)
**SSW**, #146: Storm Total Snow Accumulation (Water Equiv.)
**SSD**, #147: Storm Total Snow Accumulation (Depth)
**USW**, #150: User Selectable Snow Accumulation (Water Equiv.)
**USD**, #151: User Selectable Snow Accumulation (Depth)