b. n. goswami & prince k. xavier centre for atmospheric and oceanic sciences

B. N. GoswamiB. N. Goswami& Prince K. Xavier& Prince K. Xavier

Centre for Atmospheric and Oceanic SciencesCentre for Atmospheric and Oceanic Sciences

Indian Institute of Science, Bangalore.Indian Institute of Science, Bangalore.

ENSO Control on Indian Summer ENSO Control on Indian Summer Monsoon Through Length ofMonsoon Through Length of the Rainythe Rainy

Season (LRS)Season (LRS)

Shall present:

1)A new mechanism, not recognized so far, through which ENSO induces decreased precipitation over Indian monsoon region during northern summer.

2)An objective method of delineating the Indian Summer Monsoon Rainy Season.

Interannual variation of All India monsoon (JJAS) rainfall (AIR) between 1871-2002.

Changing ENSO-Monsoon Relationship

(a) 21-year sliding window correlation between AIR and Nino3 SST, (b) lead-lag correlation between AIR and Nino3

SST during the period 1871- 1971 and 1980-2000.

How does ENSO induces decreased Indian summer monsoon Prec.?

Current paradigm:

Large scale circulation changes associated with ENSO introduces inhibition for organized convection over Indian region.

Here, we discover, that ENSO can also induce decreased monsoon rainfall through another mechanism!

Eastward shift of the Walker Circ. With +ve ENSO

Decreased low level divergence over the eastern Equatorial IO.

Increased convection over the Equatorial IO.

Increased subsidence over continental India.

Decreased monsoon rainfall over India.

JJAS Composite of Walker circulation {(U,-ω) averaged <5S-5N>} based on 11 El Ninos between 1950 and 2002

JJAS Composite of Monsoon Hadley (MH) circulation {(V,-ω) averaged <70E-100E>} based on 11 El Ninos between 1950 and 2002

(composite of El Nino SST (JJAS) is shown in the horizontal plane (shaded))

Implicit in all these is an assumption (blindly!) that the ‘Indian summer monsoon season’ is of fixed duration!

The ‘Indian summer monsoon’ is a physical phenomenon driven by large scale heating gradients that vary in intensity and duration from year to year. Therefore, the actual length of the physical monsoon season may vary from year to year.

Thus, there is another degree of freedom , namely the length of the rainy season (LRS) that may influence the ENSO-Monsoon relationship.

There is great need for an objective definition to delineate the Indian summer monsoon SEASON.

Daily GPCP Precipitation averaged over <70E-90E, 8N-30N> from May 1 till 30 October

•Many monsoon ‘Onset’ over Kerala (MOK) take place much before June 1 and ‘Withdrawal’ from Kerala also takes place after September 30.

•Monsoon rain from spells before June 1 and after Sept. 30 are traditionally not included in the Seasonal mean (JJAS) rainfall!

•Could influence the interannual variability of Indian summer monsoon rainfall!

•All teleconnections studied so far with JJAS rainfall (e.g. ENSO-monsoon, monsoon-snow etc) may be completely misleading of physical relationships!

Define Indian summer monsoon rainy season

Traditionally the Indian summer monsoon season is defined as between June 1 and September 30 (for convenience!).

What really delineates the Indian Summer Monsoon (rainy) Season?

Physically, the rainy season is delineated by Monsoon ‘Onset’ over Kerala and ‘Withdrawal’ from the southern tip (say 10N).

onset

withdraw

TCZ

Whatever controls the MOK and ‘withdrawal’ of Monsoon from southern tip of India (~10oN) , therefore, determines the length of the Indian summer monsoon season or the Length of the Raining Season (LRS).

Thus, if we can agree upon an objective definition of MOK and withdrawal of monsoon from the southern tip, we can define LRS or the Monsoon Season.

Can we use existing definitions of MOK and withdrawal?

Almost all existing definitions of MOK or withdrawal are not physically based and require a ‘magic’ threshold on precipitation and/or low level wind shear! Unsatisfactory.

To our knowledge, nobody has attempted to define the Monsoon Season objectively using the physical driving that determine the onset and withdrawal!

Summary of some past definitions:

Ananthakrishnan et al. (1968, J. Climatol. 8, 283-296; 1983, Curr. Sci. 52, 155-164)

Precipitation based for MOK . Transition to sustained heavy rainfall. Based on 70+ raingauge stations over Kerala. Onset is the date when transition from light to heavy rainfall takes place that is sustained for more than 5 days above a threshold of 10 mm/day.

MOK by IMD

Rainfall criterion like Ananthakrishnan et al. but combined with subjective judgment of forecasters. This includes increase in K.E of the Low Level Jet (LLJ) , low level westerly shear etc.

Wang and LinHO 2002, J. Climate, 15, 386-398

Again introduces a rainfall threshold but introduces the seasonality

RRi = Ri - RJan

Where, RRi is the relative pentad mean rainfall. This measured as specific pentad mean Ri relative to winter mean RJan..

The threshold used is 5 mm/day. They show that this criterion may be useful in defining the ‘onset’ and ‘withdrawal’ of monsoon over south as well as east Asia.

Wang and LinHo 2002, J.Climate, 15, 386-398

withdrawal from s. India is too late! Not appropriate for defining ISM season. Because, the rainfall criterion can not distinguish summer and winter monsoon rainfall.

Fasullo and Webster, 2003, J.Climate, 16, 3200-3211

Vertically integrated moisture transport

HOWI:

withdrawal too early! Again can not be used to define ISM season.

He et al. 2003, J. Meteorol. Soc. Japan, 81, 1201-1223.

Define monsoon ‘onset’ in terms of change in sign of meridional gradient of upper tropospheric temperature (200 hPa-500 hPa)

Reg.B <17.5N-25.5N,70-80E>

Probably the most physically based definition.

All these definitions (except that of He et al. 2003) are based on some criterion related to rainfall and not based on the physical processes that drive the MOK and ‘withdrawal’.

Here, we propose to define the rainy season based on the physical process that drives the Indian summer monsoon.

To do this we have to start with asking…

What drives the Indian summer monsoon?

Long term mean

JJA precipitation

and

DJF precipitation

Wet summer-dry winter

Major character of monsoon

Low level, cross-equatorial flow, south-westeries, westerly jet in Arabian sea

Tibetan anticyclone & Upper level easterlies, monsoon easterly jet

During summer monsoon season, the circulation is characterized by

Deep baroclinic vertical structure

Annual Evolution of the Indian monsoon. Precipitation averaged over 70E-90E (shaded) and KE of the 850 hPa LLJ (50E-65E, 5N-15N) from observations.

KE of LLJ Onset

The classical land-sea contrast theory is inadequate!

Courtesy : JS

Courtesy : JS

What drives Indian summer monsoon is not north-south contrast of surface temperature but the meridional gradient of Tropospheric Heating!

Tropospheric temperature (TT, in oC) averaged over 200 hPa- 700 hPa (shaded) and 850 hPa winds. JJAS average.

TT (in oC) averaged over 200 hPa- 700 hPa (shaded) averaged between 70E-100E as a function of time and latitude.

(5)

(6)

Apparent Heat source Q1 and apparent moisture sink Q2

Meridional gradient of TT is closely related to the meridional gradient of tropospheric heating.

From Li and Yanai, 1996, J. Climate, 9, 358-375

Annual evolution of rainfall over the monsoon region. Climatological mean daily precipitation averaged over 70E-100E.

Annual evolution of TT (200 hPa -700 hPa) over the monsoon region. Climatological mean daily TT averaged over 70E-100E.

‘Onset’ and ‘withdrawal’ are also controlled by the heating gradient

Time-latitude section of CMAP anomalies (unfiltered) averaged over 70E-90E. Only +ve anomalies >2m/day is plotted. C.I. is 2 mm/day.

Northward propagation of spells

Dashed line K.E of 850 hPa winds averaged over the LLJ (55E-65E,5N-15N)

ONSET K.E >100 mm2s-2 and P > 6 mm/day

The real ‘onset’ is followed by sustained northward propagation of TCZ.

JJAS Climatological mean vertical shear of zonal wind (U200

–

U850

)

Large easterly shear is crucial for northward propagation of the TCZ (Jiang et.al. 2003)

TT (contour and shaded)

Onset reversal of meridional gradient of TT around 10N

TT (contour and shaded)

Onset reversal of meridional gradient of TT around 10N

TT (contour and shaded) and

U200

= 0

Onset reversal of meridional gradient of TT around 10N

TT (contour and shaded) and

U200

= 0

Onset reversal of meridional gradient of TT around 10N

Another element of the onset puzzle:

Sharpness of the ‘Onset’!

Associated with an instability.

Hypothesis:

Symmetric intertial instability is responsible for it.

(Krishnakumar V. and Lau K.M. , 1998, J. Met. Soc. Japan, 76, 363-383

Krishnakumar V. and Lau K. M. , 1997, Tellus, 49A, 228-245,

Tomas and Webster 1997, QJRMS, 123, 1445-1482)

(also see Review conditional symmetric instability by Schultz & Schumacher, MWR, 1999)

If perturbation is in slantwise path (rather than vertical or horizontal), if the mean wind is in x-direction and in thermal wind balance, stability of such motion depends on relative slope of potential temperature Θ-surface and M surface. The resulting circulation is symmetric when viewed along dir. Basic flow.

Condition for dry inertial instability is given by:

Where,

In terms of Ertel’s potential vorticity P (Charney, 1973), the condition is;

Where,

In terms of Richardson No. Ri ,the condition is equivalent to

Where,

Absolute zonal momentum

Brunt Vaisala frequency

Climatological mean Absolute Vorticity (zeta + f) for JJA , from NCEP Reanalysis

‘Dynamic Equator’

850 hPa

Streamlines of climatological mean (-ω,V) averaged between 60E-95E, over 10-day periods from mid-April to mid-June.

To note:

1.Northward movement of deep upward motion (TCZ), rapid between last week of May and first week of June.

2.The barrier of massive descending motion is overcome at the time ‘Onset’.

3.The shallow meridional circulation during pre-onset takes north warm moist air near the surface and brings south dry air above PBL

Precip. Averaged

Over 70E-100E,10N-30N

Latitude of absolute vorticity =0, averaged over 70E-100E

Potential Convective instability index (Θ

e

(700)-Θe (1000))

Events that lead to the Indian summer monsoon ‘Onset’ (MOK)

Surface heating (land-ocean contrast) during pre-monsoon season produces cross-equatorial flow near the surface but is capped by subsidence and a southward flow above the PBL.

Builds up potential convective instability, but can not be realized.

When tropospheric heating gradient changes sign, primarily due to the influence of the Tibetan Plateau heating, cross equatorial flow

and a large scale cyclonic vorticity above the PBL is set up.

Zero absolute vorticity line at 850 hPa moves north to about 5N and conditions for dry symmetric inertial instability as well as

conditional moist inertial instability is established.

Dry inertial instability overcomes the inhibition of subsidence, moist inertial instability takes over and explosive organized

convection takes place.

Onset has arrived!

First EOF of climatological mean TT (shaded). Zero contour around 10N delineates boundary between the heat ‘source’ in north from the heat ‘sink’ in the south.

TTn = TT in the north boxTTs = TT in the south box

TT = TTn - TTs

Lat. Of absolute vorticity, η =0.

<50E-100E>U200 –U850 <50E-100E,0-15N>

PC1 black

TT

U200 – U850

<respective lon. Belts>

SAM

EAMWPM

Weaker meridional migration of the TCZ in the EAM and WPM is due to weaker TT and weaker U200 – U850 in those regions.

Statistics of Onset dates (OD), withdrawal dates (WD) and length of the rainy season (LRS) in Julian days from

NCEP/NCAR reanalysis between 1950-2002.

Climatological mean OD 29th May

Climatological mean WD 4th October

Using NCEP/NCAR reanalysis from 1950-2002 onset dates (OD), withdrawal dates (WD) and length of the rainy season (LRS = WD-OD) are calculated.

Correlation between OD, WD, LRS and Other climate parameters

asignificance at 5% level

bsignificance at 1% level

Correlation between OD, WD,LRS and Nino4 SST anomalies of each month from NCEP/NCAR reanalysis (NC) as well as ERA.

Actual dates of OD, WD and LRS from NC and ERA from 1950 onwards. (in Julian days)

Actual dates of OD, WD and LRS from NC and ERA from 1950 onwards. (in Julian days)

Composite P from CMAP during Onset (OD) based on deltaTT

Composite of Prec.

(a)3 pentad before OD-OD Prec.

(b)2 pentad before OD- OD Prec.

(c) 1 pentad before OD- OD Prec.

(d) on OD Prec.

(e)1 pentad after OD- OD Prec.

(f) 2 pentad after OD- OD Prec.

(g)3 pentad after OD- OD Prec.

Composite of 850 hPa winds

(a)3 pentad before OD-OD winds

(b)2 pentad before OD- OD winds

(c) 1 pentad before OD- OD winds

(d) on OD winds

(e)1 pentad after OD- OD winds

(f) 2 pentad after OD- OD winds

(g)3 pentad after OD- OD winds

Correlation between

(a) OD and TT during 15May-15June

(b) WD and TT during 15Sep-15Oct.

(c) LRS and TT during 15Sep.-15Oct.

(a)Normalized Time series of LRS and JJAS Nino4 SSTA

(b) 21-year sliding window correlation between LRS and JJAS Nino4 SST

Correlation between LRS and JJAS SST elsewhere

Correlation between JJAS Nino3 SST and JJAS SST elsewhere

Interannual variability of LRS is strongly coupled to the ENSO SST Mode

How does the ENSO SST controls the LRS?

During positive ENSO phase (El Nino), SST results in positive P anom over central and eastern Pacific and negative P anom over western Pacific and maritime continent.

Atmospheric response to this tropical heating anomaly results in negative TT anomaly to the north and positive TT anomaly to the south over the south Asian monsoon region during northern summer

Results in delayed Onset and early Withdrawal, reduced LRS. Reduced seasonal rainfall!

El Nino minus La Nina Composite of TT (shaded) and P (contour) anomalies during 15May-30May

El Nino minus La Nina Composite of TT (shaded) and P (contour) anomalies during 15Sep.-30Sep.

EL Nino and La Nina Composite of TT and Ushear

Composite SST anomalies (JJAS)

El Nino

La Nina

From SU, NEELIN, AND MEYERSON, 2003, J. Climate, 16, 1183

Atmospheric response to EL Nino SST produces decreased meridional gradient of TT over the Indian region.

Tropospheric temperature (200 hPa – 700 hPa) anomalies during 1 May – 30 May simulated by CCM3 forced by El Nino Composite SST

Tropospheric Temperature response to El Nino Forcing

Atmospheric response to EL Nino SST produces decreased meridional gradient of TT over the Indian region.

Time series of JJAS Nino3 SST (blue) and LRS (yellow). Trend in the two time series are shown.

Even on decadal time scale a consistent relationship is seen. The increasing trend of Nino3 SST is associated with a decreasing trend of the LRS.

JJAS AIR & Nino3 SST

LRS & Nino4 SST

How do we reconcile these two apparently contradictory results?

Part of the problem is due to restricting the season to JJAS in defining AIR!

We claim that if the ‘actual’ monsoon season rainfall is taken each year, the decreasing AIR-Nino3 SST relationship would disappear!

To test this hypothesis, we would need to reconstruct AIR using LRS. Daily AIR data for long period is needed. Pending this, we test the hypothesis using NCEP Reanalysis precipitation.

Construct AIR (P ave <70-100E, 10-30N) with JJAS and LRS.

21-year moving window correlation between JJAS Nino3 SST , JJAS NCEP reanalysis precipitation averaged <70E-100E,10N-30N> and NCEP reanalysis precipitation averaged <70E-100E,10N-30N> averaged over LRS of each year from 1950 to 2002.

Recall that the total seasonal rainfall is not only affected by LRS but it can also be influenced by the PDF of the rains spells. This part is governed by ‘internal dynamics’.

Therefore, the total seasonal rainfall and ENSO SST can still have slightly different relationship that that with LRS and ENSO SST due to the contribution of ‘internal dynamics’.

Conclusions:

A physically based method has been described to define the Indian summer monsoon rainy reason.

A robust mechanism through which ENSO influence Indian summer monsoon rainfall is discovered. El Nino (La Nina) reduce (increase) monsoon season rainfall by shrinking (expanding) the rainy season thus encompassing more or less rain spells.

In contrast to JJAS AIR & Nino3 (or Nino4) SST relationship, the LRS & Nino3 (or Nino4) SST relationship has remained steady over the years.

We believe that the primary mechanism through which ENSO influence Indian monsoon rainfall is through LRS which has remained strong. The apparent weakening ENSO-monsoon relationship based on JJAS AIR is likely to be largely due to ‘fixed season’ rainfall in AIR.

Strong need to reconstruct AIR based on LRS and re-examination of all teleconnections are indicated.

Thanks to :

Feby Jose

M.S. Madhusoodanan

Composite SST anomalies

El Nino

La Nina