QPE/QPF) Crowne Plaza Manila Galleria, Quezon City, Philippines 27-30 March 2012

A Training Course on Quantitative Precipitation Estimation/Forecasting (QPE/QPF) Crowne Plaza Manila Galleria, Quezon City, Philippines 27-30 March 2012

Frequently used QPF techniques and developments Extrapolation, Climatology, Similarity

Kuo-Chen Lu Central Weather Bureau, Chinese Taipei

Training Course on QPE/QPF Manila 2012 1 contents

 Introduction  Philosophy  Synoptic forcing  Frontal system  Development of forecast guide  Typhoon  Climatology approach

 Rain gauge and Grid base  Dynamic model approach

 Development of forecast guide

Training Course on QPE/QPF Manila 2012 2 philosophy

 QPF : is the expected amount of melted precipitation accumulated over a specified time period over a specified area.  Amount: Maximum value, or the mean value ?  Time period : Hourly, Daily or, A Storm lifespan.  Specified Area : A rain gauge, a river basin, A township, A high risk area.  How they evaluate QPF ?  What’s the reporter said on the newspaper ?  They evaluated the QPF is based on the rain gauges. So the forecaster should forecast the value to meet the reporter need, that is based on the rain gauges. Besides, they show the maximum value first.  What’s the type of QPF that the user need ?  The type of the value should be in the range or in probability.  Daily or hourly, the spatial resolution and the duration of request.

Training Course on QPE/QPF Manila 2012 3 Forecasting QPF

 Must determine  Where  When  How Much rainfall will occur area.  Must understand the processes that determine the size, scale and intensity of an area of precipitation  (synoptic, mesoscale, and even microscale meteorology)  Must ..Possess Good Pattern Recognition Skills and understand what gives the pattern the potential to produce significant rainfall  Must Possess a working Knowledge of  Local Climatology  Understand numerical models  especially model biases and why they occur

Training Course on QPE/QPF Manila 2012 4 Subjectively QPF

 Analyze situation looking at the synoptic and mesoscale environment. (use the current data and model output to assess situation  Does the environment favor high rainfall rates.  Use model guidance as a first guess but understand model limitations and biases.  Based on model output, radar and satellite imagery and conventional upper air data, try to figure out where rainfall will be most intense for the longest period. This is where the heaviest rainfall will occur.  Modify model guidance based on your understanding of the physics that determines how much rainfall will fall.  Calibrate forecasts through verification. Verification is very important for manual and computer generated forecast. But how do you verify a forecast.

Training Course on QPE/QPF Manila 2012 5 Philosophy Synoptic Checking Large Scale checking on a specific area, with regard to the itemized synoptic forcing. Dynamic guidance Numerical Model may perform well on synoptic forecast, but not on the convective scale, especially on the heavy rain fall. It is worth to evaluate the synoptic forcing by NWP. Decision Making A check list of synoptic forcing by the NWP might help us to expect when and where the heavy rain will occur. Training Course on QPE/QPF Manila 2012 6 Synoptic Checking of Frontal System

1. Surface front 2. Low level horizontal wind shear 3. Sub synoptic system 4. Moist Field 5. Low level Jet 6. Cold tongue 7. Pressure depression 8. Upper level diference 9. Instibility Composited chart 0000 UTC June 1, 2000

Training Course on QPE/QPF Manila 2012 7 Terrential Rainfall Check list Table for 12 48 hrs during the Mei-Yu Season

Initial time Year______Mon.______Day______Hr.______Z NWP: WRF JMA

Items of check list OBJ 12H r 24Hr 36Hr 48Hr remark

1. Surface front location within 20 N 28 N 118 E 124 E ( ) ( ) ( ) ( ) ( )

Taipei near 100Km or passed 200Km ( ) ( ) ( ) ( ) ( ) KuoHsung near 200Km ( ) ( ) ( ) ( ) ( )

2. Horizontal wind shear 22 N 28 N 114 E 127 E

850/700hPa ( ) ( ) ( ) ( ) ( )

3. Sub synoptic South of Taiwan or east of 114 E surface/850hPa Meso-low ( ) ( ) ( ) ( ) ( ) 700/500hPa Short wave trough ( ) ( ) ( ) ( ) ( )

4. Moist fields 850hPa Td 15 ( ) ( ) ( ) ( ) ( )

850hPa e axi cross Taiwan ( ) ( ) ( ) ( ) ( ) 700hPa T-Td 3 ( ) ( ) ( ) ( ) ( )

5. Low level Jet 18 N 26 N 115 E 125 E surface 10 20kts southwestly wind 850hPa 25kts southwestly wind ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 700hPa 30kts southwestly wind ( ) ( ) ( ) ( ) ( ) 850hPa 10kts south southwestly within north of ( ) ( ) ( ) ( ) ( ) South China Sea 15 N

6. Thermal Fields 850hPa cold tongue/warm tongue arount the wind shear ( ) ( ) ( ) ( ) ( ) 700hPa cold tongue/warm tongue arount the wind shear ( ) ( ) ( ) ( ) ( )

7. Pressure depression (around Taiwan) Surface pressure P 24hr -3hPa 850hPa H 24hr -15gpm ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) Sea level pressure 1005hPa ( ) ( ) ( ) ( ) ( ) Low pressure around Hai-Nan Low Pressure ( ) ( ) ( ) ( ) ( ) 1004hPa

8. Upper level wind difluence

300/200hPa angle of difluence 45 ( ) ( ) ( ) ( ) ( )

9. Stability Total Index 40 ( ) ( ) ( ) ( ) ( ) K-Index 35 ( ) ( ) ( ) ( ) ( )

Summary Yes ( ) 22

Training Course on QPE/QPF Manila 2012 8 Terrential Rainfall Check list Table for 12 48 hrs during the Mei-Yu Season

Initial time Year______Mon.______Day______Hr.______Z NWP: WRF JMA

Items of check list OBJ 12H r 24Hr 36Hr 48Hr remark

1. Surface front location within 20 N 28 N 118 E 124 E ( ) ( ) ( ) ( ) ( )

Taipei near 100Km or passed 200Km ( ) ( ) ( ) ( ) ( ) KuoHsung near 200Km ( ) ( ) ( ) ( ) ( )

2. Horizontal wind shear 22 N 28 N 114 E 127 E

850/700hPa ( ) ( ) ( ) ( ) ( )

3. Sub synoptic South of Taiwan or east of 114 E surface/850hPa Meso-low ( ) ( ) ( ) ( ) ( ) 700/500hPa Short wave trough ( ) ( ) ( ) ( ) ( )

4. Moist fields 850hPa Td 15 ( ) ( ) ( ) ( ) ( )

850hPa e axi cross Taiwan ( ) ( ) ( ) ( ) ( ) 700hPa T-Td 3 ( ) ( ) ( ) ( ) ( )

Items of check list OBJ 12H r 24Hr 36Hr 48Hr remark

6. Thermal Fields 850hPa cold tongue/warm tongue arount the wind shear ( ) ( ) ( ) ( ) ( ) 700hPa cold tongue/warm tongue arount the wind shear ( ) ( ) ( ) ( ) ( )

7. Pressure depression (around Taiwan) Surface pressure P 24 hr -3hPa 850hPa H 24 hr -15gpm ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) Sea level pressure 1005hPa ( ) ( ) ( ) ( ) ( ) Low pressure around Hai-Nan Low Pressure ( ) ( ) ( ) ( ) ( ) 1004hPa

8. Upper level wind difluence

300/200hPa angle of difluence 45 ( ) ( ) ( ) ( ) ( )

9. Stability Total Index 40 ( ) ( ) ( ) ( ) ( ) K-Index 35 ( ) ( ) ( ) ( ) ( )

Summary Yes ( ) 22

Heavy raainfall

(50mm < PQF <130mm a day) resuilts Terrential Rainfall

Training(QPF Course >= on 130mm QPE/QPF a day)Manila 2012 10

EX: Surface Fronts  20°N～28°N，118°E～124°E ( x ) Taipei near 100Km or passed 200Km ( x ) KuoHsung near 200Km ( - )

Training Course on QPE/QPF Manila 2012 11 EX: Low level Jet（18°N～26°N，115°E～125°E）

surface 10～20kts southwestly wind 850hPa ＞25kts southwestly wind 700hPa ＞30kts southwestly wind

Training Course on QPE/QPF Manila 2012 12 Composited chart 0000 UTC June 14, 1997

QPE 15 items selected

Training Course on QPE/QPF Manila 2012 13 Composited chart 0000 UTC May 18, 1998

QPE 9 items selected

Training Course on QPE/QPF Manila 2012 14 Composited chart 0000 UTC May 19, 1999

QPE 11 items selected

Training Course on QPE/QPF Manila 2012 15 Composited chart 0000 UTC June 12, 2000

QPE 15 items selected

Training Course on QPE/QPF Manila 2012 16 Distribution of the number of items for the synoptic forecing

15.0% 14.3% 13.9%

12.0% percentage

9.0% 8.3% 7.8% 7.8% 7.4% 6.5% 百分比 6.0% 5.7% 5.7% 5.7% Rare events 4.3%

3.9%

3.0% 2.6% 2.6% 1.7% 1.3% 0.4% 0.0% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Number項目數 of items

Training Course on QPE/QPF Manila 2012 17 Distribution of the number of items for the frequency of heavy rainfall

100% 2500

90% Blue 大雨發生頻率bar : freq. of

80% heavy發生總雨量 rain 2000 black line the is total rain fall for stations every

70%

frequency heavyrain 60% 1500

50%

1000

40% 總雨量值發生大雨頻率

30%

20% 500

10%

0% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Number勾選因子數目 of items

Training Course on QPE/QPF Manila 2012 18 the correlation among the synoptic items

Pressure Upper Synopic Level Sub Moist Low Thermo Average Front Depressio level Instability items Shear System Fields Level Jet Fields of items n difluence Average 17% 8% 6% 23% 14% 7% 4% 4% 17% 5.7 Rain 16% 8% 7% 22% 15% 6% 3% 4% 19% 4.1 Heavy 19% 7% 6% 24% 12% 8% 5% 4% 15% 8.6 rain Terrenti 20% 6% 6% 23% 13% 6% 6% 5% 15% 10.6 al Rain Correlat ion 0.55 0.35 0.26 0.60 0.31 0.29 0.25 0.35 0.31 0.65 Coef.

Training Course on QPE/QPF Manila 2012 19 Verificaion of the number of synoptic items (forecast v.s. Analyis )

21 21

18 12 hrs 18 24 hrs 十二二 15 十 15 小四時 12 小 12 預時測 9 預 9 項測目 6 項 6 數目 3 數 3

0 0 3 6 9 12 15 18 21 0 0 3 6 9 12 15 18 21 客觀分析項目數客觀分析項目數 21 36 hrs 21 t s a c e r o F 18 18 48hrs 三四十十 15 15 六八小小 12 12 時時預預 9 9 測測項項 6 6 目目

數數 3 3

0 0 0 3 6 9 12 15 18 21 0 3 6 9 12 15 18 21 客觀分析項目數客觀分析項目數 a n a lTraining ys i sCourse on QPE/QPF Manila 2012 20 Verificaion for differenct valied time

Training Course on QPE/QPF Manila 2012 21 Summary of Frontal System

 There are good relation between the rain event and Synoptic forcing, if the forcing can be quantitatively define.   Find an appropriated way to use NWP can help the forecast of heavy rain event subjectively.

Training Course on QPE/QPF Manila 2012 22 Development of Computer Interface

Training Course on QPE/QPF Manila 2012 23 Historical data base of QPE

Training Course on QPE/QPF Manila 2012 24 Samples of difference combinaiton of synoptic items.

Training Course on QPE/QPF Manila 2012 25 THE FLOW CHART OF SUBJECTIVE QPF

Interface for

Environment Environment Historical Synoptic Synoptic Database similarity Checking Analysis ＋ NWP

Fine tune

Rainfall Decision Database Making

Training Course on QPE/QPF Manila 2012 26 Philosophy Climatology guidance --- for day 3, day 4 forecast Large Uncertainty for the track and the structure of Typhoon Dynamic guidance --- for day2 and day 0 forecast High resolution model (WRF Ensemble) is available Similarity or analogue --- for the day 1 and day 0 Radar echo and QPE is available for calibration

Training Course on QPE/QPF Manila 2012 27 The mechanism of typhoon precipitation

1. convergence of typhoon circulation (radius Spiral band dependent),

2. Terrain slope lifting of typhoon circulation (location Inner rain ban dependent), Topographic lifting 3. convections within eye wall Eye Wall and rain bands (transient)

4. interactions with environmental flows (e.g. NE or SW monsoon).

Training Course on QPE/QPF Manila 2012 28 The terrain slope lifting (topographically locked) – key of typhoon rainfall climatology model

Training Course on QPE/QPF Manila 2012 29 Training Course on QPE/QPF Manila 2012 30 Training Course on QPE/QPF Manila 2012 31 Collection of Historical case for climatological QPF model. Locations of 371 rain gauges

CWB: 340 ; WRB: 8 ; Reservoir: 23

To study the rainfall characteristics in Taiwan during typhoon period, we analyzed all hourly rainfall data taken at 371 rain gauges for 91 typhoons in 1989~2007. Training Course on QPE/QPF Manila 2012 32 115 120 125 130 135 140 35 35

30 30 Typhoon Nielson (1985) 08/23

25 08/24 08/21 25 08/19 08/22 08/20

20 08/18 20 33 Training Course on QPE/QPF Manila 2012

115 120 125 130 135 140 120 125 130 135 140

30 30

10/03 Typhoon Longwang (2005) 10/02 25 25 09/29 09/30 09/27

10/01 09/28 20 20 34 Training Course on QPE/QPF Manila 2012 09/26

15 15

120 125 130 135 140 110 115 120 125 130 135

30 30

Typhoon Dujan (2003) 25 25 09/03

09/01 09/02 08/31 20 20 35 Training Course on QPE/QPF Manila 2012

08/30 15 15 110 115 120 125 130 135 Climatology by Track Type

The track pattern is the key point for the topographic block of rainfall

Training Course on QPE/QPF Manila 2012 36 Training Course on QPE/QPF Manila 2012 37 Track Type 1, Moving Westward, and passed the sea of Northern Taiwan

Average rainfall on the 25 Synoptic weather sites around Taiwan Training Course on QPE/QPF Manila 2012 38 Track Type 2, Moving Westward and Landing on Taiwan

Average rainfall on the 25 Synoptic weather sites around

Training Course on QPE/QPF ManilaTaiwan 2012 39 Track Type 6,7 Moving Northward and passed Eastern/Western sea of Taiwan

Training Course on QPE/QPF Manila 2012 40 Collection of Historical case for climatological QPF model. Locations of 371 rain gauges

CWB: 340 ; WRB: 8 ; Reservoir: 23

Maximum Data counts

Taipei (4669 Mean Standard 2) deviation The rainfalls at a station 0.5o x 0.5o grid box (e.g. 46692, Taipei) were averaged15 mm/h when the typhoon 50 mm/h centers were located within each 0.5o x 0.5o grid box (256 grid boxes) to represent Use Barnes (1973) scheme the climatology at that box. to interpolate to 0.1o x 0.1o → Typhoon rainfall climatology map

Training Course on QPE/QPF Manila 2012 42 Climatology Approach

66 1o x 1o Mean rainfall rate

Training Course on QPE/QPF Manila 2012 43 Climatology

29 31 Approach

26 47 55 57

36 68 66 66

1o x 1o Mean rainfall rate Training Course on QPE/QPF Manila 2012 44 Climatology

29 31 37 29 Approach

26 47 55 57

36 68 66 66

54 79 103 59

36 29 55 80 1o x 1o Mean

9 23 65 59 rainfall rate Training Course on QPE/QPF Manila 2012 45 Rainfall estimated based on climatology rainfall forecast and CWB 120-h track forecast 2009080603UTC

2009080612UTC

Training Course on QPE/QPF Manila 2012 From Lee et al 46 Rainfall estimated based on climatology rainfall forecast and CWB 120-h track forecast 2009080700UTC

2009080712UTC

Training Course on QPE/QPF Manila 2012 47 Model can provide hourly and cumulative rainfalls when integrating along the typhoon track.

Observed 26.9mm481.8 25 443.5450 21.3mm 400 20 350 300 15 Seth (1994) 250 10 200 150 5 100 1.009 50

0 0

1008 08 1008 10 1008 12 1008 14 1008 16 1008 18 1008 20 1008 22 1008 24 1008 02 1009 04 1009 06 1009 08 1009 10 1009 12 1009 14 1009 16 1009 18 1009 20 1009 22 1009 24 1009 02 1010 04 1010 06 1010 08 1010 10 1010 12 1010 14 1010 16 1010 18 1010 20 1010

Training Course on QPE/QPF Manila 2012 48 46693 Lynn (1987) 200 175 3 hr rainfall

150 (mm)

125

100

0 2300 2312 2400 2412 2500 2512 2600

Training Course on QPE/QPF Manila 2012 49 Climatology model underestimated seriously where the interactions taking place ( Lynn, 1987).

Observations Rainfall (blue) vs. model results (red)

Taitong station Chu-tze-hu station

Training Course on QPE/QPF Manila 2012 50 Summary of Climatology Model

 Motivation  For a given typhoon, the distribution and amount of rainfall over Taiwan is highly correlated to the relation between typhoon position and Taiwan island, it is so called topographic locking.  It is workable to provide a statistical based rainfall estimate according to a given typhoon track forecast

 Weakness  The limited historical typhoon cases  Difficult to resolve the case dependent variability of environmental situation and mesoscale precipitation structure.

Lee et al. 2006 51 Training Course on QPE/QPF Manila 2012 52 Numerical model forecast  Strength  If track forecast is OK, the model QPF is worth to be a guidance  Is able to represent the interaction between the environment and typhoon circulation  Depend on case, has the potential to capture the mesoscale precipitation process  Weakness  Uncertainty to the track forecast  Official track forecast still better than the model forecast  Uncertainty from the initial condition and the model physical process  Limitation to the model resolution  Hard to configure a model that performs THE BEST all the time

How to maximally take advantage of the strength and well handle the uncertainty of the weakness from the model QPF?

Training Course on QPE/QPF Manila 2012 53 What can we do to extract the useful model TY QPF information from ensemble forecasts? Training Course on QPE/QPF Manila 2012 54 • Select the model QPF cases from ensemble members according to the prior estimate of the typhoon position, then produce the composite rain map and probability products based on the selected samples. • Maximally use the ensemble QPF based on the optimal track forecast • More members are required to provide the enough spread of the forecast typhoons. • “Realtime” is not a critical issue, so that can join all the model resources from Taiwan community, e.g. the ensemble typhoon forecast experiment conducted by TTFRI in 2010. • Climatology Model ensemble typhoon QPF (ETQPF) • Using the near-realtime ensemble typhoons instead of the real typhoons. Training Course on QPE/QPF Manila 2012 55 OBS

Examples of the member QPFs with similar typhoon location Training Course on QPE/QPF Manila 2012 56 Observation

Ty Megi (2010)

Strong interaction between the typhoon circulation and north-east wind Training Course on QPE/QPF Manila Ensemble2012 based Typhoon QPF 57 Ty Fanapi (2010)

Climatology Observations ETQPF 12-hr accumulated rainfall official track : 2010/09/18 00Z valid time from 09/18 12Z Training Course on QPE/QPF Manila 2012 to 09/1958 00Z Ty Fanapi (2010)

Climatology Station Obs ETQPFs 12-hr accumulated rainfall official track : 2010/09/18 06Z valid time from 09/18 18Z Training Course on QPE/QPF Manila 2012 to 09/1959 06Z Ty Fanapi (2010)

Climatology Station Obs ETQPFs 12-hr accumulated rainfall official track : 2010/09/18 06Z valid time from 09/19 06Z Training Course on QPE/QPF Manila 2012 to 09/1960 18Z Ty Fanapi (2010)

Climatology Station Obs ETQPFs 12-hr accumulated rainfall official track : 2010/09/18 12Z valid time from 09/18 12Z Training Course on QPE/QPF Manila 2012 to 09/1961 00Z Ty Fanapi (2010)

Climatology Station Obs ETQPFs 12-hr accumulated rainfall official track : 2010/09/18 12Z valid time from 09/19 00Z Training Course on QPE/QPF Manila 2012 to 09/1962 12Z Observation

Better estimate of the typhoon track Better QPF

Training Course on QPE/QPF Manila 2012 63 Systematic errors of ETQPF based on the best track

Megi (O-F) Fanapi (O-F)

Over prediction over mountain range

Under prediction: Smooth out due to the composite process Training Course on QPE/QPF Manila 2012 64 How to promote the ETQPF performance in advance? How to include the uncertainty of the track forecast?

• Improve the ensemble prediction system. • Develop a Human–Machine Interaction information system to maximally handle the forecast uncertainty and perform the risk assessment for decision making.

Training Course on QPE/QPF Manila 2012 65 • Apply certain criterion to filter out the undesired model forecast based on • The selection radius, model ID, model resolution, initial time, forecast time, rainfall intensity, typhoon strength, moving speed, vertical shear, …

To optimally estimate the typhoon QPF

Training Course on QPE/QPF Manila 2012 66 ETQPFs

A user friendly GUI interface to manually modify the forecast typhoon track

To include the uncertainty of the track forecast

Training Course on QPE/QPF Manila 2012 67 Optimal ETQPF guide

Track improve

1. Best track 2. CWB official track 3. WRF ensemble track 4. Man Machine Mix

Training Course on QPE/QPF Manila 2012 68 ETQPF based on the track uncertanity

Training Course on QPE/QPF Manila 2012 69 ETQPF Summary  An Ensemble based Typhoon QPF (ETQPF) technique is able to provide trustable model QPF products over Taiwan island.  Ensemble mean, standard deviation, probabilistic QPF products based on the prior estimate of the typhoon track forecast from official or ensemble forecast.  A Human–Machine Interaction information system (ETQPFs) has been implemented to maximally handle the forecast uncertainty and perform the risk assessment for decision making.  Taking the advantage of information technology is essential and has great potential to well handle the forecast guidance with large uncertainty.

Training Course on QPE/QPF Manila 2012 70 The track of Typhoon ( location and speed) The Structure ( Intensity and Size) The Mesoscale convection ( Instability )

Training Course on QPE/QPF Manila 2012 71 There’s always something you don’t know

Blue line is Forecast Track.

Red line is traced by radar. It took longer and closer than Synoptic view.’

Nowcasting is crucial.

Training Course on QPE/QPF Manila 2012 72 QPF is highly depend on QPE for two purposes, one is for climatological, one is for the calibration.

Both climatology and dynamic model are necessary for the approach of QPF.

QPF is strongly depend on the process of Man Machine Mix for two reasons, one is that guidance is too complicated, the other one is that the it need perform in precisely and efficiently.

Training Course on QPE/QPF Manila 2012 73 Training Course on QPE/QPF Manila 2012 74