Transcript enso-lrs - CAOS - Indian Institute of Science

ENSO Control on Indian Summer Monsoon
Through Length of the Rainy Season (LRS)
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.
Decreased low
level divergence
over the eastern
Equatorial IO.
Increased
subsidence over
continental India.
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, 8N30N> 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).
withdraw
onset
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
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 oC)
averaged over 200 hPa700 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.
Apparent Heat source Q1 and apparent moisture sink Q2
(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 70E100E.
Annual evolution of TT
(200 hPa -700 hPa)
over the monsoon
region. Climatological
mean daily TT
averaged over 70E100E.
The real ‘onset’ is followed by sustained northward propagation of TCZ.
Time-latitude section
of CMAP anomalies
(unfiltered)
averaged over 70E90E. 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,5N15N)
ONSET  K.E >100
mm2s-2 and P > 6
mm/day
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:
Absolute zonal
momentum
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,
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 70E100E,10N-30N
Latitude of
absolute vorticity
=0, averaged over
70E-100E
Potential Convective
instability index (Θe
(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 box
TTs = TT in the south box
TT = TTn - TTs
Lat. Of absolute vorticity, η =0.
<50E-100E>
U200 –U850 <50E-100E,015N>
PC1  black
EAM
WPM
SAM
Weaker
meridional
migration of the
TCZ in the EAM
and WPM is due to
weaker TT and
weaker U200 –
U850 in those
regions.
TT
U200 – U850
<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  29th May
Climatological mean WD 4th October
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 of Prec.
(a) 3 pentad before ODOD Prec.
(b) 2 pentad before ODOD Prec.
(c) 1 pentad before ODOD Prec.
(d) on OD Prec.
(e) 1 pentad after ODOD Prec.
(f) 2 pentad after ODOD Prec.
(g) 3 pentad after ODOD Prec.
Composite P from CMAP during
Onset (OD) based on deltaTT
Composite of 850 hPa
winds
(a) 3 pentad before ODOD winds
(b) 2 pentad before ODOD winds
(c) 1 pentad before ODOD winds
(d) on OD winds
(e) 1 pentad after ODOD winds
(f) 2 pentad after ODOD winds
(g) 3 pentad after ODOD winds
Correlation between
(a) OD and TT during 15May15June
(b) WD and TT during 15Sep15Oct.
(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 15May30May
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