B. N. Goswami
& Prince K. Xavier
Centre for Atmospheric and Oceanic Sciences
Indian Institute of Science, Bangalore.

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.
Eastward shift of the Walker Circ.
With +ve ENSO
Decreased monsoon rainfall over India.
Increased subsidence over continental India.
Decreased low level divergence over the eastern
Equatorial IO.
Increased convection over the Equatorial IO.
Here, we discover, that ENSO can also induce decreased monsoon rainfall through another mechanism!

JJAS Composite of
Walker circulation
{(U,-ω) averaged
<5S-5N>} based on
11 El Ninos between
1950 and 2002
(composite of El Nino
SST (JJAS) is shown in the horizontal plane
(shaded))
JJAS Composite of
Monsoon Hadley
(MH) circulation
{(V,-ω) averaged
<70E-100E>} based on 11 El Ninos between 1950 and
2002

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
much before June 1 and over Kerala (MOK) take place
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 over Kerala and
‘Onset ’
‘Withdrawal’ from the southern tip (say 10N).
TCZ onset withdraw

Whatever controls the MOK and ‘withdrawal’ of Monsoon from southern tip of India (~10 o N) , 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
RR i
= R i
- R
Jan
Where, RR i is the relative pentad mean rainfall. This measured as specific pentad mean R i relative to winter mean R
Jan..
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
HOWI
:
Vertically integrated moisture transport
 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

During summer monsoon season, the circulation is characterized by
Low level, crossequatorial flow, southwesteries, westerly jet in Arabian sea
Tibetan anticyclone &
Upper level easterlies, monsoon easterly jet
 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 northsouth contrast of surface temperature but the meridional gradient of Tropospheric Heating!

Tropospheric temperature (TT, in o C) averaged over 200 hPa-
700 hPa (shaded) and
850 hPa winds. JJAS average.
TT ( in o C) averaged over
200 hPa- 700 hPa
(shaded) averaged between 70E-100E as a function of time and latitude.

Apparent Heat source Q
1 and apparent moisture sink Q
2
(5)
(6)

Meridional gradient of
TT is closely related to the meridional gradient of tropospheric heating.
From Li and Yanai, 1996, J.
Climate, 9, 358-375

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

The real ‘onset’ is followed by sustained northward propagation of TCZ.
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 mm 2 s -2 and P > 6 mm/day

JJAS Climatological mean vertical shear of zonal wind (U
200
– U
850
)
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
U
200
= 0
Onset  reversal of meridional gradient of TT around 10N

TT (contour and shaded) and
U
200
= 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,
Absolute zonal momentum
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, Brunt Vaisala frequency

850 hPa
‘Dynamic
Equator’
Climatological mean Absolute Vorticity (zeta
+ f) for JJA
, from NCEP Reanalysis

Streamlines of climatological mean (-ω,V) averaged between 60E-95E, over 10day 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)-Θ e
(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.
TT n
= TT in the north box
TT s
= TT in the south box
 TT = TT n
- TT s
Lat. Of absolute vorticity, η =0.
<50E-100E>
U
200
–U
15N>
850
<50E-100E,0-
PC1  black

SAM
EAM
WPM
Weaker meridional migration of the
TCZ in the EAM and WPM is due to weaker  TT and weaker U200 –
U850 in those regions.
 TT
U
200
– U
850
<respective lon.
Belts>

Using NCEP/NCAR reanalysis from 1950-2002 onset dates (OD), withdrawal dates (WD) and length of the rainy season (LRS = WD-OD) are calculated.
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  29 th May
Climatological mean WD  4 th October

Correlation between OD, WD, LRS and Other climate parameters a significance at 5% level b significance 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 response to El Nino Forcing
Tropospheric temperature (200 hPa – 700 hPa) anomalies during 1 May – 30 May simulated by CCM3 forced by El Nino Composite SST
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