Bidyut Bikash Goswami. , P. Mukhopadhyay. , Rahul Mahanta† ,B. N

Multiscale interaction with Topography and Extreme Rainfall Events in the North-East Indian region
Bidyut Bikash Goswami* , P. Mukhopadhyay*, Rahul Mahanta† ,B.N. Goswami* *Indian Institute of Tropical Meteorology, Pune, India. † Cotton College, Guwahati, Assam, India. Although there are different kinds of weather extremes – but we will confine ourselves with the extremes in rainfall JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, D12114, doi: /2009JD012275, 2010 23rd Silver Jubilee Award Lecture for the year th November 2011

23nd Silver Jubilee Award for the year 2010 17th November 2011
FACT FILE (Taken from Press releases of Munich Re, the world’s largest reinsurance firm ) Economic losses in the 1960s with losses in the 1990s and concluded that a significant portion of the increase in losses was due to a change in the frequency of extreme weather events. Altogether, a total of 950 natural catastrophes were recorded in 2010, nine-tenths of which were weather-related events like storms and floods. This total makes 2010 the year with the second-highest number of natural catastrophes since 1980 "Climate change presents a particular challenge to fast-growing emerging countries like India", says Torsten Jeworrek from Munich Re's Board of Management. 23nd Silver Jubilee Award for the year th November 2011

EXTREMES Rare Unexpected Severe SMALL IN NUMBER LARGE IN IMPACT Rare – from distribution point of view, i.e., something which is nowhere close to the normal conditions or the mean state. And hence we surely won’t expect them to occur in day-to-day life frequently. And obviously, even though we may get events which are rare and we do not expect them to frequently occur, but they should have that potential for devastation. 23nd Silver Jubilee Award for the year th November 2011

VERY LARGE 23nd Silver Jubilee Award for the year th November 2011

We need to know the extreme events well. (Spatio-temporal distribution and mechanism) There is a societal demand, apart from the question that “how the extreme events will respond to the changing climate?”, to know the extreme events well. 23nd Silver Jubilee Award for the year th November 2011

BUT … Hard to observe & even harder to predict. Challenges –
Observation (Where & When) Dynamical Model (Resolution, Parameterization) Statistical Model … still Resolution and hence Parameterization - always adds uncertainty to dynamical models. And in case an extreme – where the conditions are so very far from the mean state – the uncertainties are even worse. And with statistical models – it is hard to explore the physics behind. 23nd Silver Jubilee Award for the year th November 2011

Previous Studies Not many … Rakhecha and Soman (1994), Sinha Ray and Srivastava (2000), Sen Roy and Balling (2004) Goswami. et., al., 2006 : 1°x1° IMD gridded data , over central Indian region – increasing trend, due to warming climate (excludes the regions under the influence of local orography) Francis and Gadgil, 2006 : 30 stations along the west coast of India, most of the extreme events are associated with largescale organized convective activity - the northward propagating tropical convergence zone (TCZ). 23nd Silver Jubilee Award for the year th November 2011

Climatological mean summer monsoon rainfall (mm/day) Climatological mean variance of daily summer monsoon rain (mm2/day2) Goswami. et., al., 2006 23nd Silver Jubilee Award for the year th November 2011

Significance of the paper on focus: Focuses the North-East Indian region (NEI). Reveals the Origin. Proposes a Mechanism. Focuses NEI not simply because there are not many studies documenting convective activity over this region, but because of the fact that this study will bring out the role of inhomogeneous terrain. Nevertheless, the tremendous societal demand is always there. So far as the origin is concerned, the common notion is the extremes are dominantly related to the pre-monsoon nor’westers. This paper tries to verify the validity of this notion. Following the origin – we propose a Mechanism. This point, in particular, makes this work very special – because if we can get a clue about the mechanism behind this extremes … then its crucial … for modelers and forecasters … to avoid or at least to minimize the loss 23nd Silver Jubilee Award for the year th November 2011

DATA IMD 1°x1° gridded data : NO : poor representation of NEI. Daily rainfall data for 15 stations for 32 years ( ). Collected from IMD (NDC Pune, RMC Ghy). We have considered the period April to October (premonsoon thunderstorm season + extended rainy season), for the current study. IMD 1°x1° gridded dataset, European 40 years Reanalysis Data (ERA40), NASA/GEWEX Surface Radiation Budget (SRB) Release-3.0 TOA-OLR data (3hrly and daily). 23nd Silver Jubilee Award for the year th November 2011

The North-East Indian region
23nd Silver Jubilee Award for the year th November 2011

Taken from Krishnamurthy and Shukla, 2008 (Figure 1): Composite of OLR for active and break condition Points to keep in mind : Before jumping into analyzing the data Topographical features of NEI A weak out‐of‐phase relationship interannual time scale : Normand 1953, Shukla 1987 ; intraseasonal time scale : Annamalai and Slingo, 2001 ; interdecadal time scale : Goswami, 2005b NEI rainfall Climatology. [Rajeevan et al., 2006] 23nd Silver Jubilee Award for the year th November 2011

How do we define extreme rainfall events?
99 percentile [variability between station climatologies] For all stations – only one/two stations were seen For each station individually – Not really potentially devastating. Threshold ≥ 15 cm a day Threshold > 15 cm a day Needs to write So keeping in mind the above facts, we had to define the extremes now … first choice was to take the events exceeding the 99th percentile … but by this definition events from only a few stations dominated the list. So we changed the definition slightly … we took the event exceeding 99th percentile for each station individually … but by this definition relatively moderate events with low hydrological disaster potential also appeared as extremes. So finally we decided to define the extremes as the ones with intensity exceeding 15cm per day. 295 events for the period (April-October) 23nd Silver Jubilee Award for the year th November 2011

Is it the pre-monsoon norwesters ?

Is it the altitude ? 23nd Silver Jubilee Award for the year th November 2011

More rainy days – more extremes ?

Strategic Location of the Stations

Is there any trend ? Fig. 4(A), Goswami et al, 2006, showing percentiles of seasonal rainfall. 23nd Silver Jubilee Award for the year th November 2011

Information at hand : Events are decreasing Heavy rain favors some specific locations. ? Why is it so 23nd Silver Jubilee Award for the year th November 2011

Is the NEI region becoming convectively stable ?
Convective Available Potential Energy (CAPE) : It is measure of the amount of energy available for convection. More CAPE, more convective instability Convective Inhibition Energy (CINE) : It is measure of the amount of energy that will prevent free convection. Conceptually, it is the opposite of CAPE. Mani et al, 2009 : Central India region is becoming convectively unstable Interdecadal mode of variability (quasi periodic, yr) of the Indian summer monsoon (Goswami, 2005b). 23nd Silver Jubilee Award for the year th November 2011

The frequency of occurrence of the extreme rainfall events over NEI is decreasing as a result of the region becoming increasingly convectively stable under the influence of the interdecadal mode of variability of the Indian summer monsoon. 23nd Silver Jubilee Award for the year th November 2011

? ORIGIN 23nd Silver Jubilee Award for the year th November 2011

Lets have a look at the actual events carefully
6/29 26/33 23nd Silver Jubilee Award for the year th November 2011 60/65

Organization of convection Lag composite of OLR anomalies (Wm-2) with respect 00 hours of the day of the extreme events at PGT. size of about 400 km persists for almost 2 days larger zonal scale compared to meridional scale We took the SRB OLR 3hrly data and averaged the anomaly at 00hr of the event day, which is the 00 hr composite. Likewise we constructed composites from -24hr to +24 hr reference to the event hour. What we see is mesoscale structures persisting for at least two days. 23nd Silver Jubilee Award for the year th November 2011

This plot shows 0 hr composite for all the stations (with at least 5 events). So what this persisting mesoscale structures indicate is, these are associated with the large scale circulation … and this large scale convection during the summer monsoon is none other than the ITCZ, propagating northward. So then the question arises is how this northward propagating ITCZ is triggering the extreme events??? Mesoscale organization of deep convection embedded in the northward-eastward migrating TCZ 23nd Silver Jubilee Award for the year th November 2011

Lat-Time plot of composite of OLR anomalies (Wm-2) averaged between plus-minus 2 longitudes about the exact location. gravity waves southward propagating with phase speed between 9 and 10 ms−1 gravity waves due to interaction of TCZ with mountains Strong updrafts associated with the gravity wave seem to be responsible. Longitude Southward T=4 Northward T=3 Time (Hours)  T=2 T=1 T=0 Latitude S N Let this red longitude be the event longitude … we averaged the anomaly for plus-minus two longitudes about the event longitude. 23nd Silver Jubilee Award for the year th November 2011

These oscillations are gravity waves …
Grabowski and Moncrieff [2001]: Hierarchical organization of the tropical deep convection can be explained only by convectively generated gravity waves. Jiang and Smith [2003] ; Mapes [2003], Houze [2004] ; Webster[2002] and Zuidema[2003]: Observed during JASMINE Mapes [2003] 23nd Silver Jubilee Award for the year th November 2011

Lag Composite of daily mean composite of OLR anomalies (Wm-2) for the days on which the extreme events occurred over a much larger domain indicating the large scale organization. The location of NEI region is shown by a box in the figure. 23nd Silver Jubilee Award for the year th November 2011

All stations show similar largescale organization except two. The association is not random. 23nd Silver Jubilee Award for the year th November 2011

Which phase of ISO ?? First, to visualize the different phases of ISO: An ISO index is defined [20–90 day filtered rainfall anomaly -> averaged over Central India (72°E–86°E, 15°N–25°N) -> normalized by its own standard deviation] ISO index > 1.5 => peak active condition Lag Composites of OLR anomalies corresponding to +-20 days of peak active days are constructed. These represent the evolution of convection with different typical phases of the monsoon ISO. 23nd Silver Jubilee Award for the year th November 2011

6-stations resembles to peak minus 12 days
1-station resembles to peak minus 3 days 1-station resembles to peak 23nd Silver Jubilee Award for the year th November 2011

Findings Centered on peak monsoon season. Large‐scale monsoon circulation favors the genesis of intense rainfall events Shows a decreasing trend over time. Because of the special topographic features, the monsoon circulation also drives long rainy spells over the NEI region. A possible hypothesis 23nd Silver Jubilee Award for the year th November 2011

Interaction with topography Mesoscale organizations
Hypothesis Gravity wave Deep convection Interaction with topography Mesoscale organizations A certain phase of TCZ 23nd Silver Jubilee Award for the year th November 2011

Concluding remark Any model that attempts to simulate or predict these events must have the correct representation of summer monsoon intraseasonal oscillations and topography. 23nd Silver Jubilee Award for the year th November 2011

Future scope Need to verify the hypothesis proposed in this work with the help of a model High resolution data (in space and time) to see the evolution of the extremes in better detail. 23nd Silver Jubilee Award for the year th November 2011

Thank you 23nd Silver Jubilee Award for the year th November 2011

Bidyut Bikash Goswami. , P. Mukhopadhyay. , Rahul Mahanta† ,B. N

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Bidyut Bikash Goswami. , P. Mukhopadhyay. , Rahul Mahanta† ,B. N

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