performance of wrf (arw) over river basins in odisha, india during flood season 2014

IJIRST –International Journal for Innovative Research in Science & Technology| Volume 2 | Issue 06 | November 2015 ISSN (online): 2349-6010

All rights reserved by www.ijirst.org 83

Performance of WRF (ARW) over River Basins in

Odisha, India During Flood Season 2014

Sumant Kr. Diwakar Dr. (Mrs.) Surinder Kaur

India Meteorological Department, New Delhi, India India Meteorological Department, New Delhi, India

Dr. Ashok Kumar Das Anuradha Agarwala

India Meteorological Department, New Delhi, India Faculty of Mathematical Sciences, Department of Statistics,

Delhi University

Abstract

Operational Weather Research & Forecasting – Advanced Research WRF in short WRF (ARW) 9 km x 9 km Model (IMD)

based rainfall forecast of India Meteorological Department (IMD) is utilized to compute rainfall forecast over River basins in

Odisha during Flood season 2014. The performance of the WRF Model at the sub-basin level is studied in detail. It is observed

that the IMD’s WRF (ARW) day1, day2, day3 correct forecast range lies in between 31-47 %, 37-43%, and 28-47% respectively

during the flood season 2014.

Keywords: GIS; WRF (ARW); IMD; Flood 2014; Odisha

_______________________________________________________________________________________________________

I. INTRODUCTION

Forecast during the monsoon season river sub-basin wise in India is difficult task for meteorologist to give rainfall forecast

where the country have large spatial and temporal variations. India Meteorological Department (IMD) through its Flood

Meteorological Offices (FMO) is issuing Quantitative Precipitation Forecast (QPF) sub-basin wise for all Flood prone river

basins in India (IMD, 1994). There are 10 FMOs all over India spread in the flood prone river basins and FMO Bhubaneswar,

Odisha is one of them. The Categories in which QPF are issued are as follows

Rainfall (in mm) 0 1-10 11-25 26-50 51-100 >100

Odisha is an Indian state on the subcontinent’s east coast, by the Bay of Bengal. It is located between the parallels of 17.49’ N

and 22.34’ N Latitudes and meridians of 81.27’ E and 87.29’ E Longitudes. It is surrounded by the Indian states of West Benga l

to the north-east and in the east, Jharkhand to the north, Chhattisgarh to the west and north-west and Andhra Pradesh to the

south. Bhubaneswar is the capital of Odisha.

Odisha is the 9th

largest state by area in India and the 11th

largest by population. Odisha has a coastline about 480 km long.

The narrow, level coastal strip including the Mahanadi river delta supports the bulk of the population. On the basis of

homogeneity, continuity and physiographical characteristics, Odisha has been divided into five major morphological regions.

The Odisha Coastal Plain in the east, the Middle Mountainous and Highlands Region, the Central Plateaus, the western rolling

uplands and the major flood plains.

River System A.

The river system of Odisha comprises the Mahanadi, Brahmani, Baitarani, Subarnarekha, Vamasadhara, Burhabalanga,

Rushikulya, Nagavali, Indravati, Kolab, Bahuda, Jambhira and other tributaries and distributaries. Table – 1

Major Rivers in Odisha with Catchment Area (Sq. Km)

Sl. No. Name of the Major River Basin Catchment Area (Sq. Km.)

% to Geographical area of State Total Area Within Odisha

1. Mahanadi 141134 65628 42.15

2. Brahmani 39116 22516 14.46

3. Baitarani 14218 13482 8.66

4. Kolab 20427 10300 6.61

5. Rushikulya 8963 8963 5.76

6. Vamsadhara 11377 8960 5.75

7. Indravati 41700 7400 4.75

8. Burhabalanga & Jambhira 6691 6354 4.08

9. Nagavali 9275 4500 2.89

10. Subarnarekha 19277 2983 1.92

11. Bahuda 1118 890 0.57

Performance of WRF (ARW) over River Basins in Odisha, India During Flood Season 2014 (IJIRST/ Volume 2 / Issue 06/ 015)


Fig. 1: Location map of study Area

FMOs mainly using the synoptic analogue model to do the same which was developed by each FMO for the area of their

jurisdiction. But nowadays most of the countries tilted towards Numerical Weather Prediction (NWP) models as NWP methods

have achieved better skills and are playing important role in rainfall forecasting. Rainfall prediction skill of NWP model is still

not adequate to address satisfactorily detailed aspects of Indian Summer Monsoon. This is because of large spatial and temporal

variability of rainfall and some inherent limitations of NWP models. In-spite of these limitations rainfall forecast of NWP

models are estimated for its utilization in various fields such as in flood forecasting, water management, planning etc.

Operationally the WRF (ARW) 9 x 9 Km2 rainfall forecast is made available to Hydromet division by NWP division at New

Delhi and rainfall forecast estimation sub-basin wise for River basins is done by the Hydromet division at New Delhi using the

available data. Then this estimation forecast is uploaded in IMD website (www.imd.gov.in) operationally during flood season

2014 as an additional tool for issuing QPF for their sub-basins. This input in turn will be utilized in the flood forecasting purpose.

The main aim of this paper is to study the performance of WRF rainfall forecast during heavy rainfall events in the flood

season 2014 over river basins under Flood Meteorological Office, Bhubaneswar of IMD. The Figure 1 showing the location of

river sub basin map of the study Area.

Fig. 2: Rain-gauge Network



II. Methodology

Sub basin wise rainfall forecast estimation for basins lying over the state of Odisha from operational WRF (9kmX9km) gridded

rainfall forecast is computed during the flood season. The meso-scale forecast system WRF (ARW) with 3DVAR data

assimilation is being operated daily twice, at 9 km horizontal resolutions with 38 Eta levels in the vertical and the integration and

with the outer model domain covers the area between lat. 25°S to 45°N long 40°E to 120°E for the forecast up to 3 days using

initial and boundary conditions from the IMD GFS-574/L64 (horizontal resolution over the tropics~22km)

(http://202.54.31.51/bias/aboutus.php). Following are the Physics options set to operational run of WRF viz. mp_physics-

WSM3(3), ra_lw_physics-rrtm scheme(1), ra_sw_physics- Dudhia scheme(1), bl_pbl_physics-YSU(1), cu_physics-GD

scheme(3). WRF (9kmx9km) gridded rainfall forecast data which is in netcdf format is averaged for each sub basins using

NCAR Command Language (NCL). Observed areal rainfall is computed by taking the average of station rainfall values lying in

each sub-basin. The correlation between the sub basin wise observed rainfall and the WRF model rainfall forecast rainfall (mm)

table is prepared for flood season 2014 and shown in Table 4. Daily rainfall bar graph over the basin areas is also prepared

during the Heavy Rainfall events over FMO Bhubaneswar to identify the dates in which the heavy rainfall occurred.

The performance of categorical QPF (0, 1-10 mm, 11-25 mm, 26-50 mm, 51-100 mm, > 100 mm) issued for sub basins is

verified from 6X6 categorically for different skill scores viz. Percentage of Correct (PC), Heidke Skill Score (HSS), Critical

Success Index (CSI) which is shown in Table 3 month-wise separately during Flood dates.

It is to be noted that due to technical issues the WRF Model did not run on 13 Aug, 14 Aug, 15 Aug and 4 Sep 2014, so

outputs are not available.

III. RESULTS AND DISCUSSION

The Rain-gauge network for real time reception of rainfall data in the basins over the Odisha during the flood season 2014 is

shown in figure 2. The total number of stations for real time rainfall data reception is 195. The summer monsoon rainfall over

Odisha occurs mostly due to monsoon depression, Low Pressure Systems (LPS) developing over the Bay of Bengal and moving

along the monsoon trough.

The dates of floods during the year 2014 are shown in the table below: Table – 2

Flood dates of 2014 in Odisha

Sl. No. Year Flood Dates

1.

2014

July 19-22 & July 27-30

2. Aug 01-17

3. Sep 01-09

July 2014 (Flood Period Are 19.07.2014 to 22.07.2014 & 27.07.2014 to 30.07.2014) A.

Synoptic Situation during the Flood Dates 1)

The Synoptic situation on 20.07.2014, a low pressure area (LOPAR) was formed over North Bay of Bengal and adjoining areas

of Gangetic West Bengal and Odisha with associated cyclonic circulation extends up to Mid tropospheric level. It was rapidly

concentrated into a Depression on 21st July 2014 over North Eastern parts of Odisha and adjoining areas of Gangetic West

Bengal about 50 km east of Baripada. On 22.07.2014, it was moved over North Chhattisgarh and neighborhood about 50 km

Southeast of Pendra. During this period, the axis of monsoon trough on mean sea level was passed through Ganganagar, Aligarh,

Fatehpur, Daltonganj, Midnapur and thence Southeast wards to East Central Bay of Bengal across North-west Bay of Bengal.



Fig. 3: Daily Average Rainfall (mm) from 11 to 22 & 27 to 31 July 2014

On dated 27th

July 2014, a low pressure area (LOPAR) has formed over North West Bay of Bengal and neighborhood with

associated upper air cyclonic circulation extending up to Mid-Tropospheric level and continued up to dated 28th

July 2014. On

29th

July 2014, it was concentrated into a Well-Marked Low pressure area over the same region with associated upper air

cyclonic circulation extending up to Mid-Tropospheric level and continued up to 30th July 2014 over the same region. During the

period, the axis of monsoon trough on mean sea level passed through Anupgarh, Jaipur, Ambikapur, Sambalpur, centre of the

system and thence Southeast wards to East Central Bay of Bengal extending up to 1.5 km above sea level.

August 2014 (Flood period 03.08.2014 to 16.08.2014) B.


Monsoon was active on 03.08.14 and vigorous from 04.08.14 to 05.08.14 over Odisha. On 03.08.14, a low pressure area

(LOPAR) was formed over North Bay of Bengal and neighborhood with associated upper air cyclonic circulation extending up

to Mid-tropospheric level and became Well Marked Low pressure area over the same region in the evening.

On 04.08.14 it was intensified into a Depression over Gangetic West Bengal and neighborhood close to Midnapur and it became

Deep Depression in the same evening over Jharkhand and neighborhood.

On 05.08.14, it was moved over North Chhattisgarh, adjoining Jharkhand and East Madhya Pradesh about 100 km East-south-

east of Ambikapur. It was weakened into a Depression on 06.08.14 and further weakened into a Well-Marked Low (WML)

Pressure on 07.08.14 over North-West Madhya Pradesh and neighborhood. Under the influence of the cyclonic circulation over

North- Bay of Bengal and neighborhood on 08.08.14, a low pressure area was formed on 09.08.14 over the same region with

associated upper air cyclonic circulation extended up to Mid-Tropospheric level. It shifted over North Eastern part of Jharkhand

and neighborhood on 10.08.14 and then shifted over Southern parts of Bihar and neighborhood on 11.08.14 and it merged with

the monsoon trough on 12.08.14. However, associated upper air cyclonic circulation lied over East Uttar Pradesh and

neighborhood extending up to 4.5 KM above sea level and became less marked on 13.08.14.

Another upper air cyclonic circulation was over East Bihar and neighborhood extending up to Mid-tropospheric level on

13.08.14 shifted over Sub-Himalayan West Bengal and Sikkim and adjoining Bihar embedded with the trough on 14.08.14 and

continued up to 15.08.14. The axis of monsoon trough on mean sea level was present from Rajasthan to EC Bay of Bengal across

UP, Jharkhand GWB and Odisha from 03.08.2014 to 08.08.2014 and was from UP to East Central Bay of Bengal across Bihar,

Jharkhand and West Bengal from 09.08.2014 to 16.08.2014.



Fig. 4: Daily Average Rainfall (mm) from 1 to 8 & 9 to 17 August 2014

September 2014 (Flood period 05.09.2014 to 08.09.2014) C.


South west monsoon was vigorous from 05.09.14 to 07.09.14 over Odisha. A Well-Marked Low (WML) pressure area over

North West Rajasthan and adjoining areas of Haryana and Punjab on 05.09.14 and became a low pressure area over Punjab and

adjoining Rajasthan and Haryana with associated cyclonic circulation extends up to 3.1 km above sea level on 06.09.14 and was

less marked on 07.09.14.

Another Low Pressure Area (LOPAR) was formed over North Bay of Bengal off West Bengal-Bangladesh coast on 05.09.14

with associated cyclonic circulation extends up to Mid Tropospheric level and it became WML over northwest Bay of Bengal

and adjoining Odisha-West Bengal coasts on 06.09.14 and shifted over Odisha and adjoining Chhattisgarh on 07.09.14 and on

08.09.14, it was over Southeast Madhya Pradesh and adjoining North Maharashtra with associated cyclonic circulation extends

up to Mid Tropospheric Level. The axis of monsoon trough on mean sea level was from West Rajasthan to East Central Bay of

Bengal across Uttar Pradesh, Bihar, Jharkhand, Odisha and North West Bay of Bengal throughout the period.

Fig. 5: Daily Average Rainfall (mm) from 1 to 9 to September 2014



Comparison of Observed Rainfall with WRF Model Output on selected flood dates D.

Fig. 6: Comparison of 21st July 2015 Observed Rainfall with WRF Model Output



Basin-Wise Comparison of Observed Rainfall with WRF Model Output for Some Dates E.


Fig. 9: Comparison of 10th Aug. 2015 Observed Rainfall with WRF Model Output



Fig. 10: Comparison of 7th Sep. 2015 Observed Rainfall with WRF Model Output

The performance of categorical QPF issued for river sub basins under FMO Bhubaneswar is verified by computing different

skill scores from 6 x 6 contingency table categorically viz., HSS, CSI, PC .There are no similar or nearby values found in PCs

from Day-1 to Day-3 for all the four events. Also some time PC value for day-2 forecast values is better than day-1, even PC

values decreases form day-3 to day-1. Therefore, rainfall forecast of WRF model during the events showed irregular behavior.

However, day-1 PC values lie between 31% to maximum 47%; day-2 PC values lie between 37% to 47% and day-3 PC values

lie between 28% to 47%.

Critical Success Index is decreasing for higher category of rainfall, which also stands that heavy rainfall events are not

correctly forecasted as compared to lower rainfall categories by the model. The HSS values are very low for all the events, even

low negative values are found. These stand that forecast accuracy is very low, even chance forecast is present. Table – 3

WRF Skill Scores of FMO Bhubaneswar for Flood season, 2014

WRF Skill Scores for FMO Bhubaneswar , 11 July - 31 July , 2014

Skill Score PC HSS CSI1 (0) CSI2 (1-10) CSI3 (11-25) CSI4 (26-50) CSI5 (51-100) CSI6 (>100)

Day-1 31.03 0.00 0.00 0.33 0.14 0.05 0.00 0.00

Day-2 37.24 0.06 0.05 0.33 0.22 0.13 0.00 0.00

Day-3 41.38 0.13 0.00 0.36 0.29 0.15 0.00 0.00

WRF Skill Scores for FMO Bhubaneswar , 1 August - 17 August , 2014


Day-1 46.51 0.05 0.00 0.46 0.19 0.00 0.00 0.00

Day-2 43.02 -0.03 0.00 0.41 0.15 0.00 0.00 0.00

Day-3 46.81 -0.01 0.00 0.51 0.06 0.00 0.00 0.00

WRF Skill Scores for FMO Bhubaneswar , 1 Sept -9 Sept , 2014


Day-1 43.08 0.16 0.00 0.34 0.27 0.24 0.00 -

Day-2 40.00 0.10 0.00 0.28 0.29 0.17 0.00 -

Day-3 27.69 -0.10 0.00 0.13 0.27 0.05 0.00 -

Table – 4

Correlation between WRF Model Output and Observed Rainfall

Correlation of Day1 Correlation of Day2 Correlation of Day3

Flood dates

Sub-basin

June

(20-

30)

July

(11-31)

Aug

(1-17)

Sep

(1-9)

June

(20-30)

July

(11-31)

Aug

(1-17)

Sep

(1-9)

June

(20-30)

July

(11-31)

Aug

(1-17)

Sep

(1-9)



Baitarani 0.33 0.46 0.00 0.64 0.21 0.28 0.75 0.45 -0.06 -0.06 0.46 -0.45

Brahmani 0.69 0.59 -0.04 0.70 0.85 0.34 0.47 0.78 0.42 0.11 0.70 -0.17

Burhabalanga 0.44 0.55 0.33 0.67 0.22 0.40 0.77 0.51 0.01 0.08 0.70 0.38

Lower Mahanadi 0.64 0.41 -0.40 0.61 0.70 -0.01 0.54 0.25 -0.02 0.21 -0.35 -0.33

Rushikulya 0.01 0.16 -0.02 0.40 0.23 -0.19 0.23 0.36 -0.20 -0.24 0.05 0.39

Subarnarekha 0.52 0.38 0.36 0.89 0.68 0.41 0.49 0.35 0.75 0.18 0.95 -0.25

Upper Mahanadi 0.88 0.65 0.02 0.06 0.71 0.34 0.17 0.31 0.35 0.36 0.42 -0.48

Vamsadhara -0.24 -0.25 -0.17 0.13 0.59 -0.10 -0.30 0.28 -0.23 -0.32 -0.42 0.00

Negative

Relation No Relation

Positive

Relation

The correlation table-4 clearly shows that there is mostly positive correlation between WRF model rainfall forecast and

observed rainfall which means that model prediction and observed rainfall have similar pattern. The WRF model forecast is

highly correlated with sub basin wise average observed rainfall for the sub-basins Subarnarekha, Burhabalanga, Upper Mahanadi

in most of the cases. However, very low or negative correlations are also found in many cases. Even few cases of no correlations

i.e. 0 values are also observed during the period.

This may be due to the large variation of rainfall in spatial as well as temporal distribution and inherent limitation of NWP

model.

IV. CONCLUSION

The heavy rainfall events are generally underestimated by WRF model rainfall during the study period. Critical Success Index is

decreasing for higher category of rainfall, which also stands that heavy rainfall events are not correctly forecasted by the model.

Low HSS value confirms that the WRF model rainfall forecast is not accurately predicted the heavy rainfall events. This may be

due to large spatial and temporal variability of rainfall and some inherent limitations of NWP models.

There are no similar or nearby values found in PCs from Day-1 to Day-3 for all the four events. Also some time PC value for

day-2 forecast values is better than day-1, even PC values decreases form day-3 to day-1. However, day-1 PC values lie between

31% to maximum 47%, day-2 PC values lie between 37% to 47% and day-3 PC values lie between 28% to 47%. Therefore,

rainfall forecast of WRF model during the events is showed irregular performance.

There is mostly positive correlation between WRF model rainfall and observed rainfall shows that model prediction and

observed rainfall have similar rainfall distribution over river basins. The WRF model forecast is highly correlated with sub basin

wise average observed rainfall for the sub-basins Subarnarekha, Burhabalanga, Upper Mahanadi in most of the cases. However,

very low or negative correlations are also found in some cases. Even few no correlations (i.e. 0 values) are also observed during

the period.

REFERENCES

[1] Manual of Hydrometeorology (Revised), 2010, India Meteorological Deptt.

[2] Harihara Ayyar, P.S. and Tripathi, N. 1973 Indian J. of Met. Geophysics, Vol. 24, 3, pp.279-282. [3] Ashok Kumar Das, Surinder Kaur, Mausam, 2013, Vol.64,4 pp. 625-644 IMD

[4] Roy Bhowmik, S. K. and Durai, V. R., 2008, “Multimodel Ensemble Forecasting of rainfall over Indian Monsoon region”, Atmosfera., 21, 3, 225-239

[5] Mukherjee, K., Surinder Kaur, and Mehra, A.K. Mausam, 1991, Vol.42, 1, pp. 29-32 India Meteorological Deptt. [6] Manual on estimation of probable maximum precipitation (PMP) No. 1045, 2009, WMO

[7] Mukherjee, K., SurinderKaur, and Mehra, A.K. Mausam, 1991, Vol.42, 1, pp. 29-32 India Meteorological Deptt.

[8] Manual on estimation of probable maximum precipitation (PMP) No. 1045, 2009, WMO [9] M Valipour et al, Comparison of the ARMA, ARIMA and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam

reservoir,Journal of Hydrology, Vol. 476,7 pp-433-441

[10] Vikramaditya Mandal, Utpal K. De, and Biplab K. Basu, 2007: Precipitation Forecast Verification of the Indian Summer Monsoon with Intercomparison of Three Diverse Regions.Wea. Forecasting, 22, 428–443

[11] Ashwini Ranade, A. K. Mitra,Nityanand Singh, Swati Basu. (2014) A verification of spatio-temporal monsoon rainfall variability across Indian region

using NWP model output.Meteorology and Atmospheric Physics 125:1-2, 43-61. [12] Dan Singh, M. R. Bhutiyani, Tule Ram. (2014) Station-based verification of qualitative and quantitative MM5 precipitation forecasts over Northwest

Himalaya (NWH). Meteorology and Atmospheric Physics 125, 107-118

[13] Krishnamurti TN, Gnansheelan C, Chakraborty A (2007) Prediction of diurnal change using multimodel super ensemble Part I: precipitation. Mon Weather Rev 135:3613–3632

[14] V. R. Durai, S. K. Roy Bhowmik. (2014) Prediction of Indian summer monsoon in short to medium range time scale with high resolution global forecast

system (GFS) T574 and T382. Climate Dynamics 42, 1527-1551 [15] Joshi, M. K., Rai, A., and Pandey, A.: Validation of TMPA and GPCP 1DD against the ground truth rain-gauge data for Indian region, Int. J. Climatol.,

online first, doi:10.1002/joc.3612 2012.

performance of wrf (arw) over river basins in odisha, india during flood season 2014

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