# Presentation: 533293

## Experiments of Hurricane Initialization with Airborne Doppler Radar Data for the Advanced-research Hurricane WRF (AHW) Model

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

**Experiments of Hurricane Initialization with Airborne Doppler Radar Data for the Advanced-research Hurricane WRF (AHW) Model**

- Qingnong Xiao1, Xiaoyan Zhang1, Christopher Davis1, John Tuttle1, Greg Holland1, and Patrick J. Fitzpatrick2
- 1*ESSL/MMM, National Center for Atmospheric Research, Boulder, Colorado*
- 2*Northern Gulf Institute, The Mississippi State University, Stennis Space Center, Mississippi*

## Outline

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Motivations
- Airborne Doppler radar data
- WRF 3DVAR data assimilation
- Experiments and results
- Hurricane Jeanne (2004)
- Hurricanes Katrina and Rita (2005)
- Statistical verification
- Summary and conclusions

## Outline

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Motivations
- Airborne Doppler radar data
- WRF 3DVAR data assimilation
- Experiments and results
- Hurricane Jeanne (2004)
- Hurricanes Katrina and Rita (2005)
- Statistical verification
- Summary and conclusions

## AHW previous results

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- WRF ARW improved track and intensity over official forecast beyond 36 h.
- Short-term forecasts (< 2 days) show a rather poor skills in WRF ARW, due to model spin-up problem.
- An improved hurricane initialization, using advanced data assimilation technique, can augment the skills of short-term forecasts.

- WRF hurricane forecast in 2005 (Orange), Davis et al. 2008

## Motivations

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Airborne Doppler radar data provide high resolution wind and hydrometeor structure of  hurricane vortex, and have a great potential for improved hurricane initialization.
- An improved hurricane initialization, using advanced data assimilation technique, can augment the skills of short-term forecasts, especially the hurricane intensity forecasts.

## Outline

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Motivations
- Airborne Doppler radar data
- WRF 3DVAR data assimilation
- Experiments and results
- Hurricane Jeanne (2004)
- Hurricanes Katrina and Rita (2005)
- Statistical verification
- Summary and conclusions

## Flight track for Hurricane Jeanne (2004)

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- NOAA 43

- NOAA 42

- Airborne Doppler radar observations

## Horizontal wind field and radar reflectivity at 2.5 km AMSL for Hurricanes a) Jeanne at ~1800 UTC 24 Sep 2004, b) Katrina at ~1800 UTC 27 Aug 2005 and c) Rita at ~1800 UTC 20 Sep 2005. 

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Horizontal wind field and radar reflectivity at 2.5 km AMSL for Hurricanes a) Jeanne at ~1800 UTC 24 Sep 2004, b) Katrina at ~1800 UTC 27 Aug 2005 and c) Rita at ~1800 UTC 20 Sep 2005.

## Outline

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Motivations
- Airborne Doppler radar data
- WRF 3DVAR data assimilation
- Experiments and results
- Hurricane Jeanne (2004)
- Hurricanes Katrina and Rita (2005)
- Statistical verification
- Summary and conclusions

## WRF-Var data assimilation system

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

**Background constraint**** ****(****J****b****)**

**Observation constraint**** ****(****J****o****)**

**x****b**** **: model **background** (former information)
**H(x)** : **observation operator** (simulating observations from model)
**[y – H(x)]** : **innovation** vector (new information)
- Minimum of the cost function **J(x),** (**analysis**) updates the background with new information from observations.

- 9h

- 12h

- 15h

- Assimilation window

*J**b*

*J**o*

*J**o*

*J**o*

- obs

- obs

- obs

*Analysis*

- xa

*Background*

- corrected forecast

- former forecast

- With hypotheses, the analysis estimates the true state of the atmosphere (in terms of max likelihood).

**Notes:**
Data assimilation:  The process of combining observations and short-range forecasts to obtain an initial condition for NWP 
is called (atmospheric) data assimilation.  
Variational data assimilation: The data assimilation process is through an iterative procedure to solve the variational optimization 
problem (least-squares problem) - Maximum likelihood estimation for the Truth

## WRF-Var Capabilities

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- WRF-Var is an advanced data assimilation system based on the variational technique.
- It includes WRF 3D-Var, 4D-Var, and ensemble/variational hybrid (En3D-Var, En4D-Var).

- It can assimilate all observational data, including satellite and radar data.
- It is robust, and facilitates research and real-time applications.

## WRF-Var Flow Chart

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- NCEP
- Analysis

**WRF-Var**
**(3/4D-Var or**
**En-Var)**

**Observation**
**Preprocessor**

**Background**
**Error**
**Calculation**

***B***

- Forecast

***x******b***

***x******a***

***y******o***

- WPS

- WRF
- REAL

**TC Vortex**
**Relocation**

**Regular**
**Obs**

**Satellite**
**Obs**

**Radar**
**Obs**

**TC Bogus**
**Obs**

- Verification
- and
- Statistics

- Cycling

## Outline

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Motivations
- Airborne Doppler radar data
- WRF 3DVAR data assimilation
- Experiments and results
- Hurricane Jeanne (2004)
- Hurricanes Katrina and Rita (2005)
- Statistical verification
- Summary and conclusions

## Track

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Intensity

## Jeanne (2004): Hurricane initialization 

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Jeanne (2004): Hurricane initialization

- GTS+RADR

- GTS only

- NO DA

## H-Windfrom NOAA/HRD

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- H-Windfrom NOAA/HRD

## Vertical structure

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- GTS+RADR

- GTS only

## 300 hPa analytical increments of wind vector (maximum vector represents 29.7 ms-1) and temperature (isolines with contour interval of 0.2K, the negative value dashed)

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- 300 hPa analytical increments of wind vector (maximum vector represents 29.7 ms-1) and temperature (isolines with contour interval of 0.2K, the negative value dashed)

- GTS+RADR

- GTS only

## 24-h forecasts of SLP (thick solid isolines), and surface (10-m) wind vector and speed (shadings with thin isolines) for Hurricane Jeanne at 1800 UTC 25 Sep 2004 

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- 24-h forecasts of SLP (thick solid isolines), and surface (10-m) wind vector and speed (shadings with thin isolines) for Hurricane Jeanne at 1800 UTC 25 Sep 2004

- GTS+RADR

- GTS only

## Vertical cross-sections of equivalent potential temperature and horizontal wind speed (shading with the scale on the upper right) at 1800 UTC 25 Sep 2004 (24-h forecast)

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- GTS+RADR

- GTS only

## Hurricane forecast (reflectivity)

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- 24-hr

- 36-hr

- GTS                plus radar wind       plus reflectivity

## The reflectivity (dBZ) image from WSR–88D from Melbourne, Florida at 0232 UTC 26 Sep 2004

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

## Hurricane track

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Black: Observation
- Red: NO-DA
- Blue: GTS-DA
- Green: GTS + ADR wind DA
- Cyan: GTS _ ADR wind and reflectivity DA

## Hurricane intensity

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Black: Observation
- Red: NO-DA
- Blue: GTS-DA

- Green: GTS + ADR wind DA
- Cyan: GTS _ ADR wind and reflectivity DA

## WRF 3DVAR analysis for Hurricane Katrina (2005)

**Best Track:     948mb**
**GFS Analysis: 985mb**
**GTSRV          : 979mb**

**before**

**after**

- SLP & Wind at 850mb

## 48-h Track Forecast for Katrina (2005)

## 48-h Intensity Forecast for Katrina (2005)

## 48-h Track Forecast for Hurricane Rita (2005)

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

**Notes:**
Replot the track

## 48-h Intensity Forecast for Rita (2005)

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

## Average mean absolute errors for the three hurricanes a) track, b) CSLP, and c) MSW

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Average mean absolute errors for the three hurricanes a) track, b) CSLP, and c) MSW

## Summary and Conclusions

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL

- Airborne Doppler radar data have a more detailed hurricane inner-core structure. Assimilation of the data results in a better vortex initialization.
- Both the intensity and track forecast are improved after assimilating airborne Doppler radar wind data. The intensity forecast benefits more than track from airborne Doppler radar data assimilation.
- The benefits of airborne Doppler data assimilation are somewhat smaller for the stronger, rapidly intensifying hurricanes of Katrina and Rita (2005) than for Jeanne (2004).
- In terms of WRF 3D-Var for airborne Doppler data assimilation, some limitations also exist.
- A specific background error covariance for hurricanes should be developed.
- Reflectivity assimilation in WRF 3D-Var uses warm-rain process to bridge rainwater with other model variables in the analysis.
- Observation error statistics for aircraft radar data are only crudely represented at present.
- WRF 3D-Var does not take into account the time differences but instead ingests data at one instant in time.

## Thank you!

- 63rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL