 Thanks Chairman. Good afternoon ladies and gentlemen. Thanks the organizers of this workshop for inviting me to this very exciting workshop. So here I'm going to talk about a coupled decadal skill IRC interaction theory. The actually the night and nail AMO, AMO, coupled mode and impact. I'm from the College of Global Change and Earth Systems Science Beijing Normal University. Firstly, I would like to acknowledge my co-stars here Dr. Chengsun and Professor Fei-Fei Jin from the University of Hawaii. So in this talk I would like to discuss three questions. The first one is a delayed oscillator model for the cognitive periodic multi-decadal variation of the NAO. And this is a time series of NAO index clearly showing multi-decadal variation of the NAO and the recent decadal awakening. Actually there are some many studies to show that some factors for you know such kind of multi-decadal variability such as article CS and you know warming of into Pacific warm pool and greenhouse scarcity increase. However, you know the the mechanics of the called a 60-year cycle of a NAO is still elusive. So here is a reconstructed NAO index in the past three centuries and according to wavelet analysis you have a very significant cause a 60-year cycle here and also this recent decadal awakening of a NAO can be explained by this kind of called a 60 year cycle. You know due to the observation data of the NAO index is very short. We may employ you know the numerical model to study the relevant to mechanism related to the called a 60-year cycle of a NAO. And here is you know the NAO index in red line and the AMO index blue line the low pass field NAO index black lines in you know carbon model and car CCSM4 and according to the you know spectral wavelet spectrum analysis you have you know for both a NAO and AMO very significant cause a 60-year cycle and such kind of a cycle is reasonably well simulated by this model implying this model can be maybe available to study the relevant you know a mechanism related to the called a 60-year cycle. So here we employ the per simple oscillation pattern analysis POP to review dominant patterns of SAT anomaly modicator variability over you know North Atlantic region. So the leading mode you know the real part and you know imaginary part of POP patterns you know the homogenous pattern AMO signal and you know medial triple pattern which is called North Atlantic or triple net. So according to the time series of you know real and imaginary parts suggested the oscillatory sequence of these POPs from you know the positive net to a positive AMO and negative net phase follows. So the lead lag correlation between the NAO and AMO and NAO and net suggests you know the net is in phase with NAO and NAO leads you know AMO by around 15 years while AMO may have negative feedback on NAO. So here we hypothesis three possible mechanism in voting to this called a 60-year cycle. The first one is directly effect of the night on the NAO. So here's the you know coupled modes you know the RC coupled mode in this you know CCM4 model you know for the you know the atmospheric you know C level pressure response to AMO the homogenous pattern however you know to night you have the NAO you know signal here. So if you run you know a GCM speed model to say C level pressure response to you know AMO and net pattern only net can trigger such kind of NAO structure. So that means you know NAO come from this meridional mode of SAT over North Atlantic Ocean. So a physical processes for this you know net on NAO. So net contributed in the surface heat flux anomalies and leads to very strong gradient in air temperature and then you have very strong eddy growth rate. Then a storm track intensity increase and also the storm track shifts to the northward. According to the wave floor interaction theory you may have the positive NAO phase here. The west list should be accelerated. Second process is NAO forcing on the AMO. So actually this today several speakers already mentioned this point and Thomas and Nor already gave some you know results about the you know the forcing of NAO on AMO. Actually there is a substantial modeling evidence that NAO release wind stress anomaly can lead to multi-degradable variations of the AMO which in turn produce the SAT pattern of the AMO. So here we employ the mom file model to say boss AMO can the upper surface temperature response to NAO signal. NAO type driving forcing. The R panel shows you know transient response of the AMO in the lower panel panels are you know transient response of upper surface temperature. So as time increases the AMO intensity increase probably after 10 years go to study state and if you look at the special pattern over the North Atlantic Ocean you have very robust AMO structure. So if we employ the carbon model CSM4 simulation here you know NAO release you know the AMO by around 15 years and the positive you know NAO can produce can strengthen AMO then you have the you know since AMO is in face with AMO you have a positive AMO face and vice versa. So the third process is an active feedback of AMO on net because you have you know intensification of clockwise heat transport from the AMO. The AMO you know shows you know the very strong bird clinic structure and over the in the upper surface you have the homogeneous pattern here. Due to this AMO the positive signal could be propagated from lower latitude into the lower high latitude and in the deep ocean the negative goes to the southward and also over the high latitude the signals go to downward and after around 15 to 18 years this structure could become in a bar tropical structure and you have a negative North Atlantic triple face here. So here's a theoretical explanation for the time delay. Since you know advection caused by AMO plays a very important role in the SST evolution from the positive AMO to negative net. So the theory according to scale analysis the theoretical time delay is around 16 years very close to the you know time lag of the night and relative to the AMO. So now here is you know the schematic diagram to show the relevant mechanism through this called a 60 year cycle of an AO. So actually a positive net can produce a positive an AO and the positive AO forces the enhancement of the AMO and leads to the positive AMO phase and enhance the you know AMO continuously affect the heat transport and then after around 15 years the positive AMO can produce a negative and nice phase and then you have a negative an AO and then finish this cycle around call this 60 year cycle. So based on this kind of a mechanism we build a delayed oscillator decay oscillator model for an AO model digital variability. So here is the equation. So according to normal mode analysis for frequency and a growth rate yes and you have the if we we have the you know the result for growth rate and the frequency which are closer to the observation. If we integrate this you know equation the numerical solution shows that very clearly causes a 60 year cycle. So this model may be available for explaining called a 60 year cycle of an AO of this carbon mode. So here the we this carbon mode may have very important impacts you know on the multi-decay of variability of a global mean surface temperature. So if we take a look at the detuned you know nothing hemisphere temperature here very clearly multi-decay of variability and the lead lag correlation between the NaO index and detuned the nothing hemisphere temperature so that the NaO leads not detuned an HT by around 15 or 16 years. And here's the correlation map between SST and NaO index 16 years earlier showing very robust you know structure similar to the AM pattern. So based on the husband model we can input the NaO index into this kind of equation to get the the temperature contributed by NaO. You have the in blue line and the green line is you know AMO related to nothing hemisphere temperature. Both are very close to each other. And based on this mechanism we can you know build a certain kind of annual based prediction model. Here's you know hand the cost to show the very good performance of this model and in the future we may made this kind of prediction and in the next decade we the temperature will fall slightly. I think this result is inconsistent with the normal result. Also this kind of decadal carbon mode has very important effects on the southern hemisphere climate. Here's an example and in the last three decades you have very drought over the Australia eastern Australia. And this is the red line is sub-topical eastern Australia rainfall index and the blue line is NaO index. And the light correlation shows that NaO leaves you know this rainfall by around 15 years. And such kind of based on the you know the mechanism of the carbon mode the NaO can produce you know trigger the AMO circulation here. The later can modulate to the southern ocean you know warming and cooling and you know in fact the wisely circulation and in fact the Australia climate. And also we can set up such kind of a statistical model to make a prediction. The speed period shows a very good you know result and in the future the rainfall over Australia may go in up which is a good news for Australian people. I think if we it is right. So come to conclusions in this study we proposed a coupled decadal scale IRC interaction theory the NaO AMO AMO carbon mode. And we build a delayed decadal oscillator model for exploring the CODE 60 year cycle of NaO. And the such kind of mode you know this decadal NaO temperature multi-decadal variability. And it's a very important decelerator of an energy multi-decadal warming or cooling and more important maybe an important factor of heretics. Also such kind of decadal mode also exerts an influence on southern hemisphere climate especially the Australian rainfall variation. That's all. Thank you for your attention.