The challenges of nowcasting convection over the ocean
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The Challenges of Nowcasting Convection over the Ocean. Huaqing Cai, Cathy Kessinger, Nancy Rehak, Daniel Megenhardt and Matthias Steiner National Center for Atmospheric Research Boulder, CO, USA Joint 2010 CWB weather Analysis and Forecasting and

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The Challenges of Nowcasting Convection over the Ocean

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The challenges of nowcasting convection over the ocean

The Challenges of Nowcasting Convection over the Ocean

Huaqing Cai, Cathy Kessinger, Nancy Rehak, Daniel Megenhardt and Matthias Steiner

National Center for Atmospheric Research

Boulder, CO, USA

Joint 2010 CWB weather Analysis and Forecasting

and

COAA 5th International Ocean-Atmosphere Conference

28-30 June, 2010

Central Weather Bureau, Taipei

ACKNOWLEDGMENTS

This study is supported by NASA ROSES and NASA ASAP program and in collaboration with NRL and MIT LL


Air france 447 0145 utc 1 june 2009

Air France 447 (0145 UTC 1 June 2009)

The wide-area view provided by real-time experimental Global Convection/Turbulence uplinks may have improved pilot situational awareness

Motivation: Air France 447

Longwave IR (0145 UTC)

Convection Diagnosis Oceanic (CDO)

0145 UTC

(approx.) Last ACARS message, 0214 UTC

+

(approx.) Last verbal contact, 0133 UTC

Cloud Top Height (0145 UTC)

(approx.) Last ACARS message, 0214 UTC

+

(approx.) Last verbal contact, 0133 UTC


Wx ahead uplink message valid 0130 utc 1 june 2009

“Wx Ahead” Uplink Message valid 0130 UTC 1 June 2009

/EXP CLOUD TOP FI AF447/AN NXXXAF 01 Jun 09

-- '/' Cloud tops 30,000 to 40,000 ft//////CCC/////

'C' Cloud tops above 40,000 ft///////////CC/////

*4.0N,30.0W/////////

*////////C//////////

//*//CC///CCC/////////

///*CCCC/C/CC//////////

////*CCCCCCC//C/////////

///CC*CCCCC///CC////////

///CCC*CCCCC/////////////

//CCCCC*CCCC//////////////

//CCCCCCC*CCC//////////////

/CCCCCCCCC*CCC///// /

//CCCCCCCCCC*CC///// // ///

//CCCCCCCCCCC*C///////// //////

/////CCCCCCCCCC*C// // // //////

//////CCCCCCCC//*/ // / //////

CC//////CCCCCCC//* /////////

CCC////////////// * /////////

/C//////////// *1.3N,31.4W ////

/////// */

*// /

/*/// //

/*/// /

/*//

/*//

*

// *

/// * //

// * ////

* /////

* //////

* /////

/// * ///

Pos Rpt / // * /

0133 // X 1.4S,32.8W //

Valid for // /

0130-0200z //

Pilot feedback at url: http://[site deleted]

30-39Kft

>40Kft

/=30-39Kft

C=>40Kft

Graphical view (EFB concept)

Text-based view for ACARS printer


The challenges of nowcasting convection over the ocean

Oceanic Diagnosis and Nowcasting System

CTop

CClass

GCD

Convective Nowcasting Oceanic (CNO-Titan) makes 1-hr and 2-hr nowcasts of storm location using an object tracker (Titan)

CNO-

Titan

Nowcast

CNO-

Gridded

Nowcast

CNO-Gridded produces gridded nowcasts that will more closely resemble storm structures

CNO-RF utilizes environmental and model-based inputs to better predict storm initiation and decay

[Cai et al. (2009)]

CNO-RF

Random

Forest

Nowcast

Convective Diagnosis Oceanic (CDO) identifies convective cells

With Growth/Decay

CDO

Interest

Without Growth/Decay

CDO

Binary

Product

With Growth/Decay


Cno based on titan dixon and wiener 1993

CNO Based on TITAN (Dixon and Wiener, 1993)

An Example of 1 Hr CNO-TITAN

TITAN for Radar Data

*1 hr nowcast of CDO valid at 1315 UTC on August 19, 2007 using TITAN technique is shown on the right; red lines on the right represent CDO = 2.5 verification.

*Advantages of TITAN: computationally efficient; capability of addressing growth/decay.

*Disadvantages of TITAN: polygons can only roughly represent storm shapes; tends to over-forecasting


The challenges of nowcasting convection over the ocean

TITAN Motion

Vectors at t0

Gridded 0 hr TITAN

Motion Vectors

Gridded 2 hr TITAN

Motion Vectors

Gridded 1 hr TITAN

Motion Vectors

Merged with GFS Winds Closest in Time

Merged with GFS Winds Closest in Time

Merged with GFS Winds Closest in Time

Temporal & Spatial

Smoothing

Temporal & Spatial

Smoothing

Temporal & Spatial

Smoothing

15-60 min

Motion Vectors

75-120 min

Motion Vectors

135-180 min

Motion Vectors

15-60 min Forecasts

by Advecting Original

Satellite Data at t0

75-120 min Forecasts

by Advecting 60 min

Nowcasts

135-180 min Forecasts

by Advecting 120 min

Nowcasts

CNO Based on Modified TITAN---- Gridded Forecast

1-3 Hr CNO-Gridded Forecast Flow Chart

An Example of 1 Hr CNO-Gridded Forecast

*Advantages of CNO-Gridded: realistic looking storms; low bias.

*Disadvantages of CNO-Gridded: could be computationally expensive; no explicit growth/decay capability


The challenges of nowcasting convection over the ocean

CNO Based on Random Forest Statistical Analysis and Data Fusion

  • The random forest technique produces an ensemble of decision trees from labeled training instances

    • during training, RF generates estimates of predictor importance

    • RF trees “vote” on classification of new data points, comprising a nonlinear empirical model that provides both deterministic predictions and probabilistic information

Data pt.

Data pt.

Data pt.

Data pt.

Data pt.

Tree 2

Tree 3

Tree 100

Tree 1

Tree 4

Vote: 0

Vote: 0

Vote: 0

Vote: 1

Vote: 1

=> 40 votes for “0”, 60 votes for “1”; consensus category “1”

*Slide courtesy of John Williams and Dave Ahijevych


An example of cno rf forecast compared with cno titan 1 hr

CNO-RF

An Example of CNO-RF Forecast Compared with CNO-TITAN ( 1 hr)

B

Hurricane Dean

A

C

*1 hr forecasts valid at

1315 UTC on August 19,

2007 for both techniques; Red lines represent

CDO = 2.5 verification

*Advantages of random forest technique: more realistic

looking storms; taking into account of storm environment to address storm growth/decay.

*As a relatively new, novel technique for nowcasting, its potential needs to be fully explored

D

CNO-TITAN

B

CNO

Hurricane Dean

A

C

D


Statistical evaluation of the three nowcasting techniques

Statistical Evaluation of the Three Nowcasting Techniques

CSI

BIAS

  • 5 days of data from Aug 19-23, 2007 over the Gulf of Mexico domain are used to calculate the statistics with a grid size of ~ 5 km and CDO threshold of 2.5

  • All three techniques show skill over persistence

  • RF and gridded forecast perform best at 1 hr lead time

  • TITAN is the best at 2-3 hr lead time

  • Gridded forecast is the best for 4-6 hr lead time


Relative skill comparisons of three nowcasting techniques versus persistence

Relative Skill Comparisons of Three Nowcasting Techniques versus Persistence

  • Gridded and RF nowcasts ~10 % better than persistence at 1 hr lead time

  • TITAN is the best for 2 and 3 hr lead time (~20-30% improvement)

  • Gridded nowcasts the best for 4,5 and 6 hr lead time (~ 15-25% improvement)

  • Overall, gridded technique seems to be the best performer


Examples of 1 hr gridded forecast over the gulf of mexico domain

Examples of 1 hr Gridded Forecast over the Gulf of Mexico Domain

1 HR

D

Issue time: 1215 UTC 2009/09/05

Valid time: 1315 UTC 2009/09/05

C

B

A

*White lines are CDO=2.5 verification, satellite data available every 30 min


The challenges of nowcasting convection over the ocean

Examples of 3 hr Gridded Forecast over the Gulf of Mexico Domain

3 HR

Issue time: 1215 UTC 2009/09/05

Valid time: 1515 UTC 2009/09/05

D

C

B

A

*White lines are CDO=2.5 verification, satellite data available every 30 min


The challenges of nowcasting convection over the ocean

Examples of 6 hr Gridded Forecast over the Gulf of Mexico Domain

6 HR

Issue time: 1215 UTC 2009/09/05

Valid time: 1815 UTC 2009/09/05

D

C

B

A

*White lines are CDO=2.5 verification, satellite data available every 30 min


Examples of 3 hr cdo forecasts based on cno gridded technique in the west pacific domain

Examples of 3 hr CDO Forecasts Based on CNO-Gridded Technique in the West Pacific Domain

3 HR

Issue time: 2100 UTC 2009/12/28

Valid time: 0000 UTC 2009/12/29

A

D

C

B

*White lines are CDO=1.5 verification; Cloud class is not used in CDO

*Satellite data are available every 3 hrs


The challenges of nowcasting convection over the ocean

Examples of 3 hr CDO Forecasts Based on CNO-Gridded Technique in the West Pacific Domain

3 HR

Issue time: 0000 UTC 2009/12/29

Valid time: 0300 UTC 2009/12/29

A

D

C

B

*White lines are CDO=1.5 verification; Cloud class is not used in CDO

*Satellite data are available every 3 hrs


The challenges of nowcasting convection over the ocean

Examples of 3 hr CDO Forecasts Based on CNO-Gridded Technique in the West Pacific Domain

3 HR

Issue time: 0300 UTC 2009/12/29

Valid time: 0600 UTC 2009/12/29

A

D

C

B

*White lines are CDO=1.5 verification; Cloud class is not used in CDO

*Satellite data are available every 3 hrs


Summary statistics of cno gridded forecasts

Summary Statistics of CNO-Gridded Forecasts

The black squares are statistics from Aug 19-22, 2007

What are the GFS model scores for oceanic convection???

  • 30 days of data from Sep 1-30, 2009 over the Gulf of Mexico domain are used to calculate the statistics with a grid size of ~ 5 km and CDO threshold of 2.5

  • The results showed here could serve as benchmark performance of extrapolation-based nowcasting techniques for oceanic convection

  • Similar verification for model forecasts need to be done so that a comparison of convective forecasting skills between model and extrapolation can be obtained


Summary and future work

Summary and Future Work

  • The challenges of nowcasting convection over the ocean at the current stage are caused by the lack of 1) high spatial and temporal resolution data; 2) the best way to identify convection over the ocean; and 3) the best way to blend observation-based extrapolating nowcasts with model-based convective forecasts.

  • The nowcasting products need to be uplinked to transoceanic aircraft for situational awareness.

  • Three nowcasting techniques (CNO-TITAN, CNO-Gridded and CNO-Random Forest) for oceanic convection forecasting in the 1-6 hr time frame are implemented, tested and compared in the Gulf of Mexico domain

  • Based on the overall performance statistics, CNO-Gridded forecasts for 1-8 hr are implemented in the Gulf of Mexico and Pacific domain in the realtime Oceanic Diagnosis and Nowcasting System.

  • The summary statistical performance of CNO-Gridded extrapolating technique could serve as benchmark for future blending work of GFS model and extrapolating for oceanic convection in 1-8 hr time frame.


Thanks for your attention questions and comments

Thanks for Your Attention!Questions and Comments?


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