 Hello, so should I start again and one more thing, the complex orthography, complex mean you can see this region has high mountains, large ocean body and from the south, the Sahara Desert. So it has a complex topography. So the complex topography also helps to generate the weather system during the winter season. So for example, the region sometimes triggers the development of storm center in itself and they feed on the moisture and gain energy from the Mediterranean Sea. So this is during winter season sometimes we have the Saharan cyclones which normally causes the dust events over Mediterranean region and eventually they can take place as the medicans, I mean to say the tropical cyclone like structure in the Mediterranean Sea. And from north, from north and northwest we have the cold air advection in the domain during the winter season and from south and southeast the Red Sea drop actually plays a role, major role over the East Mediterranean region and Middle East for the precipitation during the winter season. So all these features actually contributes to this region for the precipitation during the winter season. So the main rainfall mechanism in the Euro Mediterranean region actually comes from two ways. One is through thermo dynamical process. So in thermo dynamical process actually interaction between surface heating and atmosphere. So it gives the convective process originating on the warm sea and then due to the orographic structure it will give you, it can give sometimes the convection and then moisture. For example, when there is southerly or southerly flow or south-westernally flow in the Mediterranean from the south you will have the orographic lifting in the northern side of the Mediterranean Sea. So in this way the orographic lifting also helps in the development of the strong weather system but this is actually, we call this as thermo dynamical process. But during winter season the most dominant phenomena is the dynamical process. I mean the western disturbance. So the trajectories of westerly loads of troughs which actually comes through the North Atlantic Ocean, they actually provides the weather system through the western Mediterranean region and sometimes these systems go through the North but they generate, gives the secondary low pressure systems over the study domain. So mostly system I will discuss next. Most of the system actually dwells inside as a secondary system in the study domain. Another thing is Northern Hemisphere circulation patterns. For example, these patterns also contributes well to the precipitation during the winter season. The Scandinavian phenomena pattern we know and Eastern Atlantic-West Russian pattern also contribute other than the North Atron NEO. NEO is actually the big, we can say the major contributor to the precipitation over the Euro Mediterranean region and during the last few days we have a lot of discussion how positive NEO and negative NEO behaves and in which phase we can have more weather systems over the Euro Mediterranean region and during positive NEO most of the system actually goes through the North over the Northern Europe. So most favorable is for the precipitation of storm penetrating in the Mediterranean region is the negative NEO phenomenon. So frontal activity we can see here from the diagram, cold air advection actually comes from the North-West with the system and from the south we have warm air advection associated with the jet-subtractive jet-subtractive jet-subtractive actually helps for the warm air advection from south and south sea. So in this way the frontal system or winter season storms actually takes place over the Mediterranean region and this is the most dominating phenomena during the winter season. So what is the reason why I have selected the winter season? So this is the annual cycle you can see here, annual cycle precipitation in the steady domain and this is the seasonal cycle of precipitation in the steady domain. Here you can see during the winter season DGF has the highest value of precipitation objective. And so previously have been discussed many times and many people even Michael A1 also have discussed how ANZO has the impact over European precipitation. So it is actually a global phenomenon, it has become a global phenomenon. Everyone and most of the researchers have a lot of discussion how ANZO can generate the precipitation for different regions because as I mentioned in earlier from ANZO most climate signals or seasonal predictability even we can make some relationship with ANZO and we can have a best seasonal predictability for our own regions. So it actually helps us. So but in my study now I am going to make see how the atmospheric bridge I mean the storm centers has the relationship with ANZO and how they actually behave during the end in years of warm center and pacific ocean days. In my experimental setup I have used 6 hourly and sub N-carion as data set from 1948 to 2016 and for correlation purpose with ANZO I have used the global SST data set with resolution 1 degree which is available from 1991 to 2016 and to check how the storm frequency of storm cracks actually have the reflection in my study domain and what actually I have hypothesis for this study it actually has the impact or not. So for this I have used the global observed data set global precipitation climate product GPCP which is actually available from 1979 and methodology I have used the storm tracking scheme which is actually developed by Moray and Seymour in Melbourne University in 1991. So this is the state of the art now the storm tracking actual model or objective scheme by which you can identify the systems you can track them you can make your statistics. So this is actually very helpful tool and it is also sensitive to temporal resolution and even spatial resolution for example if you will use the daily data set in this model you will have the less storm centers but if you will use the 6 hourly for example you will have the system more system and even if you use the data 3 hourly then your storm centers will also increase but there are some other things. For example I first before this many people used this objective scheme for mean sea level pressure data set and even in 2016 we have published another paper over storm tracking we have used this scheme for 500 hectopascal to track those systems which have been affected to the precipitation over Saudi Arabia adjoining region but for this study we particularly we have made the optimization in this model and we have we have employed the data 200 hectopascal data set to track the large scale systems actually because at 200 hectopascal the systems has more longitudinal dimension so it has a large spread so we have employed you use the data 200 hectopascal in the scheme this scheme actually uses relationship basically how it identifies the basic mechanism in short how it identifies the system and how it will then track the system so identification the first step is the identification so this scheme actually first of all will prepare the geostrophic water city water city a greater data set from which it can create the which actually sorry which actually comes from the Laplacian of geopretential height this relation so Laplacian of geopretential height is also can be considered as the intensity of the storm centers okay so the positive values of the Laplacian of geopretential height indicates the intensity of the storm center so the model first of all will identify the low pressure system then it will search for the positive value of Laplacian of geopretential height if both conditions will be fulfilled then it will say this is a low pressure system otherwise it will neglect but for for these things we have to give some threshold values so these threshold values come from the climatological analysis of of these characteristics so I will not go into detail how so I just started for this sensitivity test I just took the one of the event from 23rd to 30th January 2009 first it was wrapped over the 20 question and this event already has been discussed in the laborato paper study there is a whole there is a study which actually they have made the whole discussion related to this event so the purpose for us to take this as a case study is that we have to serve check first that our storm tracking model is working well or not so for this we have made the sensitivity test and we have took the threshold values when we reached at a step that this is exactly the same system where from it was started and it has some proper end-up and there is no contradiction between the observation I mean I mean re-analysis and storm tracked and the storm tracked trajectory then we said okay so the model is storm tracking objective scheme is working well we can make our long period analysis so due to this event it cost the human casualties and the Euro-media training region as a whole some suffered about six billion dollars and more it was the most costly event of the 21st century and this was declared as the most deadliest system of the hundred year history of the Euro-media training region so it cost heavy rainfall, flash floods over the central and even over the eastern parts of the Euro-media training region this is the system which is identified by the storm tracking model so I just took only two of the time steps to describe how it actually had worked so the system on 12 UTC 27th January is identified by the model over Gulf of Geneva okay so it was actually started on for identified in this study domain on 26 at this position but just for the explanation I just added these two pictures so this is the cloud spectrum of that of that day so we can see how it is it coincides with the synoptic map at 200 hectopascal so this is a second one is for 20th January and this is the cloud spectrum of 20th January taken from the European map set this is the precipitation of the same day so you can see here how upper air system actually generates the precipitation because as I mentioned before this is the winter season storm center this is the characteristic and this is a frontal system so it will generate it will it can generate the precipitation at the surface but for example sometime we have a low pressure system at the surface but we have no precipitation because upper is it's not sporty there is no drop for example at 500 or 200 but when there is a drop or a low pressure system at 200 hectopascal in this study domain then definitely we will have precipitation at the surface so the storm centers it was actually named first when it was in the Atlantic Ocean it was named as the strong class and when it was entered in the Euro Mediterranean region it was named as the strong class too so the system actually started from here on 26 January and it ends up over the western Black Sea on 30th January 2009 so the Genesis region of this storm center was Gulf of Geneva and the Lysus region was the Black Sea so here this is a subset subset of the storm tracks for 10 years from 2000 to 2010 actually it shows the picture where the storm center actually comes during the winter season so the source region major source region is is the Mediterranean region itself most 60% systems originate dwells in the Mediterranean region 20% systems comes through the Atlantic Ocean 15% of the systems come through the Northern Europe North Northwestern and Northern Europe and 5% system actually retrieved back to the through the Mediterranean region from Central Asia due to the Central Asian blocking during the winter season so solid here the blue dots actually shows the gents point of the storm center and red points shows the Lysus where it actually finished the Lysus points of the storm center so we can see clearly see how the storm train storm center actually comes in this in the study now this is a climatology of the storm storm tracks for 67 years from 1950 up to 2060 sorry 16 and this is a precipitation rainfall climatology over the study domain so we can see here the storm center maximum and even in our previous presentation from last few days I have observed there are actually three storm tracks maximum during the winter season one over Pacific Ocean second over Atlantic Ocean and third over Mediterranean region there are three storm max storm centers when the northern hemisphere actually so the climatology in normally from calculation I observed that an average of 50 storm centers every winter season passes through this through the study domain okay and the precipitation pattern also helps us the how actually it happened because mostly precipitation you will see will happen during near to the water body if sometime the storm center is very strong over the northern northern Europe for example but there is very less precipitation because of the source of moisture is it's not near to the center but it helps here even if trough can also generate the heavy precipitation at this region so we have selected only two things we just selected the storm centers and even trough with certain criteria we have we have defined in the in the storm tracking model so this is the climatology for some tracking and this is climatology for a precipitation now our main goal objective so Euro Mediterranean storm tracks frequency time series actually I have selected the index of the storm frequency in the study domain and then I have correlated with the ANSO phenomena you know 3.4 region so in the start when I just take the simultaneous correlation I found the correlation value was not so high it was just 0.17 so there was no reason to describe the interseasonal relationship between ANSO and the storm tracks in the storm track index over the Euro Mediterranean region then I just try to check the interdicado relationship so I took the laminar sliding correlation and again there are some time there was the graph it shows the positive value sometime negative value so there was no point to decide is it interdicado relationship is available or not then finally we have decided to take a multi-dicado relationship for this I took that 21 year slide the correlation between the storm track frequency index and you know 3.4 SST index then we found a relationship here so it was it is clear from here we can see before 1980s before 1985 the relationship is negative but it is not significant after 1985 the correlation becomes positive and it is significant so I after that after this relation I decided to split my analysis in two parts the first period from 1950 to 1979 and the second period from 1987 up to 2016 so in this way we can see because it the the split of the periods based on sliding correlation graph so here we can see when I took the Samuel simultaneous correlation before after this period between and so index and the storm frequency index I found the correlation was minus 0.24 which is not significant but when I took this correlation for from 1987 to 2016 between storm track frequency below so the correlation value comes positive and it is actually significant the most significant thing is that the difference of the two correlations first period and second period is significant and the departure value is 0.64 but for storm intensity the right one shows that it was it was having a positive relationship with and so even in the first period and even in the recent period but it the difference of the two is not so much high so our focus was over this stage how the storm frequency relationship is has been changed this is for example the special correlation between and so index and storm intensity over the study domain we can see positive relationship with the with the storm intensities and this is in the recent period from 1987 this correlation between and so and storm intensity further enhanced so vice versa just take the correlation with the storm frequency index with the SSD and it is clear from this relation you can see in the first reference period from 1950 to 1979 the correlation was with central and eastern Pacific Ocean SSD was negative but it is it was not it is not significant but the recent period from 1987 to 2016 the correlation surprisingly was positive and it is significant at 95% swear I have used student detest so later on I have correlated and so index with the 200 hectopascal geopotential height in two different periods based on our sliding correlation graph so I found during the previous period the jet stream you can say the sub-tropical jet stream path was more northward in the study domain so the situation was not favorable for the storm stumps enters to enter in the study domain but in recent period you can see here as in in the previous lectures Dr. Davis Frost also mentioned and I also have take the reference from his study we can see the blocking which normally prevails over Atlantic Ocean it actually shifts further eastward and little southward over the Mediterranean or southwest Mediterranean region so it actually helps to stumps enters to enter from the west western side in the Euro Mediterranean region but major change happened over the eastern Euro Mediterranean region where the anomaly value anomalies values become negative and the sub-tropical jet the second component actually during winter season there are two components of sub-tropical jet stream which prevails one over North Atlantic Ocean second over Middle East so this jet stream over Middle East also shifts southwards during the warm years and it eventually helps to dwell to take place how to do that the more stumps enters over East Mediterranean and your eastern Euro Mediterranean region so the numblest warming as from the previous study so I have observed the they mentioned the numblest warming in central and eastern Pacific Ocean during the MSO events causes an equator equator word shift of sub-tropical jet because stumps enters always move along the northern part of the subtropical jet so if sub-tropical jet will shift southward then eventually the stumps enter will also shift to southward and this is actually benefit you can say have the benefit for the stumps enters during the early New Year's to goes through the Mediterranean Western Mediterranean region so same pattern also reflected over in the at the 10000 hectopascal we can see here how that's it when I took the I have to their correlation between and so index and 1000 hectopascal geopotential height I found the same change is also reflecting at the surface during the two periods so recent period is most favorable for the storm activity in the Euro Mediterranean region so this hypothesis finally I took the I have to the stumps composite and so composite of stumps frequency this figure shows so we can see here during the early New Year's we can we will see we can have we have more stumps frequency activity over over the study domain and at the same time the precipitation composite and so composite for precipitation also reflecting the almost little bit same pattern in the study domain so stumps activity at 200 hectopascal for example there is stumps enter it always give precipitation in southern and south eastern part of its center so it is considered now just few days before in my lab I just try to check because before this I just took the composite for the recent period from 1987 to 2016 and there was no information for me because GPC data set was available from I think 1979 so now I just check from the CPC from our lab during these days so I found the same confirm the same change even in CPC data set so you can see here the press only no composite during the first period from 1950 to 1997 there is a negative anomaly actually now negative anomalies are dominating but in recent period doing the El Nino composite shows the positive signal with precipitation so it is clear they are doing winter season if there is a El Nino phenomena I mean the VAM SSD in the center and Eastern Pacific Ocean we will have we can have more precipitation over Euro-media training area so this one the data set is different this is GPC the other one is CPC I just actually to try to confirm that the CPC because before the sidebars have no CPC data set so I just tried two days before to show the CPC also showing the same signal or not yes sir this is this is the answer comforted yes I also I also it is just for the my satisfaction I because I found a new data set with me in the lab so I just try to see the same change is also reflecting in this data set or not or it is just the artifact of the data set so it can be done by using the you are right we can also use the observational data set to verify these things for example station data set it is available for recent period especially so we can check this so conclusion of my study about the multi-decadal changes clearly shows a phase shift of the and so impact over Euro Mediterranean storm tracks frequency and so associated significant changes are noted in the upper and lower troposphere in recent period with respect to the earlier period these changes may largely influence the storm activity and storm intensity which consequently affects the precipitation nominees over the Euro Mediterranean region and the last and most important these findings can have more important implications in Euro Mediterranean seasonal predictability this is our study which we have published from this study and that's it