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IOGOOS: November 4-9, 2002 peter j. webster: georgia institute of technology Variability of the Indian Ocean monsoon system on timescales of weeks to years.

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Presentation on theme: "IOGOOS: November 4-9, 2002 peter j. webster: georgia institute of technology Variability of the Indian Ocean monsoon system on timescales of weeks to years."— Presentation transcript:

1 IOGOOS: November 4-9, 2002 peter j. webster: georgia institute of technology Variability of the Indian Ocean monsoon system on timescales of weeks to years

2 IOGOOS: November 4-9, 2002 Outline: Brief description of coupled phenomena Weather Intraseasonal varaibility Interannual variability Regulation Predictability

3 IOGOOS: November 4-9, 2002

4 resource

5 IOGOOS: November 4-9, 2002 and hazard………

6 IOGOOS: November 4-9, 2002 description

7 IOGOOS: November 4-9, 2002 mean august and january precipitation

8 IOGOOS: November 4-9, 2002

9 Annual cycle of convection (OLR) in the Indian Ocean-South Asia region

10 IOGOOS: November 4-9, 2002 annual cycle of surface winds over Indian Ocean and South Asia

11 IOGOOS: November 4-9, 2002

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13 Monsoon regions are the largest region where precipitation exceeds evaporation. This excess water must come from somewhere …

14 IOGOOS: November 4-9, 2002 …….which defines the scale of the monsoon. The monsoon is intrinsically inter-hemispheric with the winter hemisphere being the source of moisture

15 IOGOOS: November 4-9, 2002 Monsoon tied to both zonal & meridional land-sea contrasts

16 IOGOOS: November 4-9, 2002 To a large degree the system seems “well behaved” and appears to act as a large scale sea-breeze system. But there are surprises and issues that are difficult to understand

17 IOGOOS: November 4-9, 2002 Time Scales of Monsoon Variability Interannual variability: Variations on the annual cycle of the monsoon generated by SST/land surface variations in PO and IO. Monsoon Weather: Monsoon lows and depressions, tropical cyclones (hurricanes) and etc. Produce short-lived local flooding (or drought), erosion, high winds and etc. Intraseasonal Variability: “Envelopes”: or clusters of weather events producing day droughts or flood periods. Arguably most important but also most difficult to forecast

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20 Persistence of SST over 6-month period North Indian Ocean shows strong persistence (I.e., if you know the SST now, you know it 6 months from now). Much more persistent than in Pacific Ocean which contains springtime “persistence barrier: Inference: predictability exists in Indian Ocean.

21 IOGOOS: November 4-9, 2002 El Nino influences Indian Ocean Changes SST, sea surface slope and regions of maximum precipitation El Nino influences Indian Ocean Changes SST, sea surface slope and regions of maximum precipitation But we are uncertain how this influence is manifested and large amounts of variance are unexplained

22 IOGOOS: November 4-9, 2002 Relationship Between Indian Monsoon Rainfall and ENSO El Nino La Nina

23 IOGOOS: November 4-9, 2002 Decadal Changes in Monsoon-ENSO Relationships Correlations over 125 years average about -0.6 but there are long periods where the correlation drops to very small numbers.

24 IOGOOS: November 4-9, 2002 also……….. Four near normal years show very different precipitation patterns. ENSO offers only “broad-brush” prediction of rainfall over India. Does rainfall over India define a strong or weak monsoon? Are fine “fine brush” forecasts possible?

25 IOGOOS: November 4-9, 2002 Other modes of variability? are there other modes of variability besides El Nino? Is there predictability in the these modes? Are these phenmena independent of El Nino? Is there a basic building block of variability in the Indian Ocean/monsoon regime? Can understanding these phenomena help design n observing array in the Indian Ocean? are there other modes of variability besides El Nino? Is there predictability in the these modes? Are these phenmena independent of El Nino? Is there a basic building block of variability in the Indian Ocean/monsoon regime? Can understanding these phenomena help design n observing array in the Indian Ocean?

26 IOGOOS: November 4-9, 2002 Indian Ocean SST and All-India Rainfall

27 IOGOOS: November 4-9, 2002 Indian Ocean Zonal Mode or Dipole “Recently” discovered mode of variability following period (earlier evidence exists, though) Exhibits strong coupled characteristics between ocean and atmosphere Appears linked to ENSO and to vigor of monsoon Strongly tied to annual cycle as is El Nino in Pacific Ocean Strongly tied to climate variability especially equinoctial “short rains” in East Africa Vigorous for decades and occasionally takes a statistical vacation “Recently” discovered mode of variability following period (earlier evidence exists, though) Exhibits strong coupled characteristics between ocean and atmosphere Appears linked to ENSO and to vigor of monsoon Strongly tied to annual cycle as is El Nino in Pacific Ocean Strongly tied to climate variability especially equinoctial “short rains” in East Africa Vigorous for decades and occasionally takes a statistical vacation

28 IOGOOS: November 4-9, 2002 most unusual events in 1997

29 IOGOOS: November 4-9, 2002

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31 Coupled mechanism for the Indian Ocean Zonal Mode Webster et al. (1999)

32 IOGOOS: November 4-9, 2002 Composite growth of the positive phase of IOZM (i)

33 IOGOOS: November 4-9, 2002 Composite growth of the positive phase of IOZM (ii)

34 IOGOOS: November 4-9, 2002 Composite growth of the negative phase of IOZM (i)

35 IOGOOS: November 4-9, 2002 Composite growth of the negative phase of IOZM (ii)

36 IOGOOS: November 4-9, 2002 Indian Ocean Zonal Mode: Inherent mode of Indian Ocean invoked by outside perturbations including ENSO Indian Ocean Zonal Mode: Inherent mode of Indian Ocean invoked by outside perturbations including ENSO Time series of E-W SST gradient frequency spectra

37 IOGOOS: November 4-9, 2002

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40 Sea-level variations associated with IOZM: Positive phase: warm SST WIO, low SSH EIO Negative phase: warm SST EIO, high SSH EIO Sea-level variations associated with IOZM: Positive phase: warm SST WIO, low SSH EIO Negative phase: warm SST EIO, high SSH EIO

41 IOGOOS: November 4-9, 2002 Intraseasonal variability in Indian Ocean Predominant feature of IO system Arguably the most important time scale for prediction (variability on day scales far larger than interannual Possess features very similar to interannual variability Shows great robustness in behavior, effect and duration A chaotic instability? Predictability? Is intraseasonal variability a coupled ocean- atmosphere phenomenon?

42 IOGOOS: November 4-9, 2002 Intraseasonal Modes: Impact on Rainfall Intraseasonal variability imposes a distinct form to precipitation. Histograms of precipitation, shown for 9 years show distinct wet periods with lulls in between. Lower diagram shows the distinct spatial character Precipitation histograms in central India

43 IOGOOS: November 4-9, 2002 Pattern of Intraseasonal Modes

44 IOGOOS: November 4-9, 2002

45 Temporal evolution of MISO along 90E: 1995 Active phases of the monsoon commence near the equator and propagate northward (and southward) across South Asia. commence active phase northward propagation Active phase

46 IOGOOS: November 4-9, 2002 Latitude-time section of OLR along 90E: 1988

47 IOGOOS: November 4-9, 2002 Sequence of Monsoon Intraseasonal Variability Sequence shows the evolution of the “average” MISO over a 30-day period

48 IOGOOS: November 4-9, 2002 Composite wind stress during intraseasonal oscillation

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50 0° 10ºN 20ºN 20ºS 10ºS Composite zonally & vertically heat flux during intraseasonal oscillation day latitude -0.7PW +0.5PW

51 IOGOOS: November 4-9, 2002 Can we use composite structures to forecast ISO? Intraseasonal oscillations almost absent from numerical models, coupled or otherwise. Empirical forecasts possible if ISO is resilient and reproducible Following scheme uses 6 features of ISO and makes 25 day forecasts

52 IOGOOS: November 4-9, 2002 (pentads) Example of 25 day empirical forecast for 1999 Ganges Valley precipitation

53 IOGOOS: November 4-9, 2002 Ganges Valley 25-day forecasts

54 IOGOOS: November 4-9, 2002 Ganges Valley 25-day forecasts

55 IOGOOS: November 4-9, 2002 The coupled ocean- atmosphere system in the Indian Ocean

56 IOGOOS: November 4-9, 2002

57 Heat budget of the North Indian Ocean Heat budget comprises of change in heat storage, flux into system surface and transport across equator Annual mean small southward transport (-0.25 PW) Annual cycle between -2PW and -2 PW, opposite to atmospheric heat flux and wind Heat transferred by ocean from summer to winter hemisphere indicating regulation o by negative feedbacks

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60 Heat Storage Components Change in heat storage can be broken down into two parts due to: changes in temp (H.dT/dt) changes in thickness (T dH/dt) Through these two processes we can understand the actual physics that determine the annual cycle of upper ocean temperature

61 IOGOOS: November 4-9, 2002

62 Interannual variability of ocean heat transport There is a large interannual variability in IO ocean transport Also, large intraseasonal variability associated with atmospheric component of ISO Note that heat transport is seamless at equator. Can Ekman transport account for that? Probably not!

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64 Differences between IO meridional heat flux as function of ENSO

65 IOGOOS: November 4-9, 2002 Differences between IO meridional heat flux as function of monsoon strength

66 IOGOOS: November 4-9, 2002 Details of heat transport at equator and 10S Wave and boundary heat transport? Ekman and boundary transport?

67 IOGOOS: November 4-9, 2002 Cross-equatorial heat transport for 1987 and 1988

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69 Ocean transport and monsoon strength weak monsoonstrong monsoon weak southward ocean heat transport strong southward heat transport anom warms NIOanom cools NIO

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71 Strong and weak monsoons invoke different upwelling effects creating SST gradients. Then ……. Impact of anomalous monsoon seasons

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74 Some important points The monsoon is a coupled system The system possesses great predictability Probabilistic forecasts on all time scales are possible But, there is insufficient data for initialization All ideas presented here are fanciful and will remain so until substantiated with solid data


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