SASCOF-MEETING PUNE APRIL 2014

P Goswami and K C Gouda

CSIR Centre for Mathematical and Computer Simulation (C-MMACS) , Bangalore-37

CSIR C-MMACS Long-Range, High-Resolution Forecasting of Monsoon

First Outlook (Based on March 15 Forecast)

Approach and Methodology

Goswami and Gouda, MWR MWR 2009

Goswami and Gouda, MWR 2010 Goswami, Mallick and Gouda 2012 JGR

C-MMACS Long-range forecasting of monsoon: Approach

Forecast skill depends on several components •Optimization of Model Configuration for maximum skill in monsoon forecasting

•Ensemble methodology for long-range forecasting )monsoon ensemble)

•Conceptual basis and methodology for advance (~ 30 days) forecasting of DOM

•Climatological SST to minimize error due to incompatible (observed/predicted) SST

•Multi-scale evaluation: Regional, cyclone, ERE: Towards seamless prediction

Ensemble Methodology for Long-range Forecasting

Ensemble methodology for short-range forecasting is not necessarily suitable/optimal for long-range forecasting A natural choice of ensemble members for long-range forecasting states on different days The choice of states for ensemble should be guided by physical and dynamical reasoning (ISO over the monsoon region) A “Monsoon Ensemble” (Goswami and Gouda, 2011, Mon Wea Rev) provides consistently better forecast for inter annual variability Size of the Ensemble: Saturates at 6 based on 24 year hindcasts

Novel Methodology: The Monsoon Ensemble

The Monsoon Ensemble

Preparation of initial conditions is a critical component of dynamical forecasting; C-MMACS developed the concept and the algorithm for Monsoon Ensemble. Inter annual variability in all India seasonal (JJA) rainfall anomaly (as % of respective mean). Use of monsoon ensemble results in better agreement (top panel) with the observed (IMD) anomalies than with conventional method (bottom panel). Goswami and Gouda, Mon Wea Rev., 2011

DOM is identified based on a set of objective Criteria (Goswami & Gouda, Mon Wea Rev.,2010)

: 3day uniform Pre-onset Persistence : 5day uniform Post-onset Persistence : Area Coverage 30-50% over Kerala :Rain threshold 10mm/day (model)

Advance Forecasting of Date of Onset of Monsoon

Basic Premise •Large TRANSITIONS are predictable (large signal-to-noise ratio)

•An optimized GCM configuration provides skill in forecasting transition

•A single variable (rainfall) can be used to identify DOM based on dynamical dependence of various variables in a model (wind, humidity, temperature, ..)

• The objective criteria are identified based on calibration with observation (IMD)

Climatological SST

•SST, through lower boundary forcings, is expected to play critical roles in monsoon dynamics (already emphasized in many works) • The significant interannual variability of SST is likely to impact monsoon inter annual variability (already emphasized in many works)

•It is thus extremely important to prescribe SST for monsoon forecasting carefully: this is an issues less explored.

• In a forecasting framework, it is important to ensure compatibility for proper balance; the model atmosphere and SST need to be in dynamical balance

• Observed SST may not be in dynamical balance with the model atmosphere (it is in perfect balance with the observed atmosphere!)

• In a coupled model, there is balance between the model SST and the model atmosphere (after spin up) ; however, this does not guarantee skill

• We consider climatological SST to minimize error due to incompatible SST

Broad Methodology

• Variable-Resolution GCM • In-house Multi-grid Ensemble Methodology • Multi-lead Monsoon ensemble • Monsoon-specific model calibration and validation

Scope

• High resolution (~50 KM) over Indian region • Long lead (6-3 months) • Multiple Scenarios (Probability and Reliability) • Advance Onset Forecast • Early (March) and Late (April/May) Outlook

C-MMACS Experimental Forecast of Monsoon

The Variable-Resolution GCM

MODEL: LMDZ 3.3 with variable Resolution GCM Resolution : 192X144 grid points (~80Km X ~60 Km) High resolution (~50 KM) over Indian region Vertical Level : 19 Zoom Factor : 2.0 Convective Parameterization : Tidtke Radiation Parameterization : ECMWF Land Surface Process : Dynamic Lower Boundary conditions SST: AMIP monthly Climatology Orography : USGS Vegetation: NCEP Climatology Sea Ice : NCEP Climatology Initial Condition NCEP Daily Fields on 2.5X2.5 degree grid

Past Performance

Seasonal Rainfall Anomaly

Region (Coverage) June-August June July August

CM IMD CM IMD CM IMD CM IMD

All-India Continental land

N N D E N N

E N

North-India (72-84 oE,

24-30 o

N)

E N E E N N

D N

South- India (75-78oE,

8-12oN)

N N

N E N N

N N

Central-India (72-84oE,

20-28oN)

D N D E D E N N

North east India

(92-96oE,

24-30oN)

N D N D N D N D

North west (68-75oE,

24-30oN)

D N D E D N D E

Regional Category Forecast: 2013

D [Deficit; RA < -20%], N [Normal; -20%<RA<20%; E [Exccess; RA>20%]

Region (Coverage) June-August June July August

CM IMD CM IMD CM IMD CM IMD

All-India Continental land

N N D D D D E N

North-India (72-84 oE,

24-30 oN)

N N D D D D E N

South- India (75-78oE,

8-12oN)

N N D D E N E E

Central-India (72-84oE,

20-28oN)

N N N D D D E E

North east India

(92-96oE,

24-30oN)

N D N N N N E N

North west (68-75oE,

24-30oN)

D N D D D D N N

Regional Category Forecast 2012

D [Deficit; RA < -20%], N [Normal; -20%<RA<20%; E [Exccess; RA>20%]

Performance of DOM forecast (2007-2013)

Year Actual Onset

Date

C-MMACS

Forecast Onset

Date

Error

(Days)

2007 May 28 May 26 2

2008 May 31 May 28 3

2009 May 23 May 23 0

2010 May 31 May 29 2

2011 May 29 June 03 5

2012 June 05 June 05 0

2013 June 01 May 31 1

Average error in prediction of date of onset

Uncertainty as per 24 year hindcasts (MWR, 2009)

2 Days

2 Days

Monsoon 2014: El Nino Scenario

ENSO: Current Status and Forecast

• ENSO-neutral (average) conditions continue across the equatorial Pacific, but significant warming both in the western and far eastern regions

• The Climate Prediction Center (CPC) has indicated about a 50% chance of El Niño (warm) conditions developing this summer and/or fall

• There is likely impact on Indian Monsoon 2014

http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/lanina/enso_evolution-status-fcsts-web.pdf

Tropical Pacific Ocean SSTs (top) and Anomalies (bottom)

Courtesy: http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/enso_update/sstanim.shtml

Tropical Pacific Ocean SSTs are above average in the western and far eastern regions

Courtesy: http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/enso_update/sstweek_c.gif

C-MMACS First Outlook 2014

Seasonal (JJA) Rainfall Anomaly for Monsoon 2014

Standard Scenario El-nino Scenario

Rainfall Anomaly for JUNE 2014

Standard Scenario El-nino Scenario

Rainfall Anomaly for JULY 2014

Standard Scenario El-nino Scenario

Rainfall Anomaly for AUGUST 2014

Standard Scenario El-nino Scenario

Region (Coverage) June-August June July August

ST EL

ST EL ST EL ST EL

All-India Continental N D D S N N N N

North-India (72-84 o

E, 24-30

oN)

N D D D N N N D

South- India (75-78oE,

8-12oN)

N D N D N N E N

Central-India (72-84oE,

20-28oN)

D D D S N D N N

North east (92-96oE,

24-30oN)

N N S D E D N N

North west (68-75oE,

24-30oN)

E D D D E N E D

Regional Category Forecast

D [Deficit; RA < -20%], N [Normal; -20%<RA<20%; E [Exccess; RA>20%]

ST: Standard SST scenario; EL: El-nino Scenario

Forecast of Date of Onset of Monsoon 2014

Area-average (75-77oE, 8-12oN) daily rainfall over Kerala during May 01 to June 30, 2014 from C-MMACS first outlook for 2014.

Predicted Date of Onset 2014 Monsoon : June 12 2014 Date of Generation of Forecast: 15th March 2014

Thank You

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J F M A M J J A S O N D J F M A M J J A S O N D

SOI

Month

SOI* values from the top "analog years" compared with the current period (2013-14)

2013-14

1967-68

1962-63

1956-57

*For SOI explanation see: http://oregon.gov/ODA/NRD/docs/pdf/forecast_method.pdf

ENSO Indices

El Niño

La Niña

(1967-68; 1962-63; 1956-57)

ENSO-Neutral

ENSO Predictive Models Computer models predict ENSO-neutral through spring 2014

Courtesy: http://iri.columbia.edu/climate/ENSO/currentinfo/SST_table.html

La Niña

El Niño

Model forecasts favor ENSO-neutral conditions through spring 2014; followed by possible El Niño development.

ENSO-neutral