1 / 46

Aquaplanet simulations of the MJO: Wind-evaporation feedback and horizontal moisture advection

Aquaplanet simulations of the MJO: Wind-evaporation feedback and horizontal moisture advection. Eric D. Maloney, Walter Hannah Department of Atmospheric Science Colorado State University Adam Sobel Columbia University.

gelsey
Télécharger la présentation

Aquaplanet simulations of the MJO: Wind-evaporation feedback and horizontal moisture advection

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Aquaplanet simulations of the MJO: Wind-evaporation feedback and horizontal moisture advection Eric D. Maloney, Walter Hannah Department of Atmospheric Science Colorado State University Adam Sobel Columbia University Funded by: NSF Climate and Large-Scale Dynamics Program, NOAA Climate Program Office, CMMAP

  2. The Madden-Julian Oscillation (MJO) • Salient features: • Convectively coupled disturbance that propagates eastward across the Tropics • 5-10 m s-1 propagation speed in the Indian and west Pacific, where MJO convective variability is strongly coupled to the large-scale flow. • Simple baroclinic wind structure, with 850 hPa and 200 hPa wind perturbations 180o out of phase • Characteristic timescales of 30-90 days. Madden and Julian 1972

  3. Theory: Moisture Modes and Wind-Induced Surface Heat Exchange (WISHE) Moisture modes: • A moisture mode is a balanced disturbance in which the large-scale dynamics are regulated by the weak temperature gradient approximation (e.g. Sobel et al. 2001; Majda and Klein 2003; Raymond and Fuchs 2007, 2009; Sugiyama 2009) • Properties are strongly regulated by local interactions between convection and tropospheric moisture • Essential dynamics of the mode involve processes that control the tropical moisture field, including latent heat flux and horizontal advection WISHE: • Early models of WISHE: Mean easterly flow and enhancement of surface fluxes to the east of convection supported disturbance amplitude and eastward propagation (Neelin et al. 1987, Emanuel 1987) • Increasing evidence exists that some form of WISHE may be importance for MJO maintenance and possibly propagation, although it must operate in a state of basic state westerlies, unlike the early linear models (e.g. Sobel et al. 2009)

  4. SST Boundary Condition for Our Primary Simulation • Resembles the observed mean December-April SST, but with the meridional SST gradient poleward of 10o reduced to ¼ of observed. • Modified version of NCAR CAM3 • T42 horizontal resolution (2.8o x 2.8o), and 26 vertical levels • Perpetual March 21 insolation and ozone • 16-year simulation

  5. Unfiltered Precipitation and Winds vs. Longitude 5 m/s Even in unfiltered data, many salient features of the MJO apparent, including 5 m s-1 eastward propagation, and a period of 40-60 days.

  6. Wavenumber-Frequency Spectra (Precip) Observations Model 90 days 30 days 90 days 30 days A strong spectral peak exists in the model at same zonal wavenumber and frequency as observations.

  7. Mean Wind and Precipitation Variance Variance units: mm2 day-2 Intraseasonal variance peaks in regions of mean westerly flow at low-levels. Variance is stronger than observed.

  8. Composite Precipitation and U850 (Unfiltered)

  9. Precipitation is an increasing and strongly non-linear function of saturation fraction of the troposphere (e.g. compare to Bretherton et al. 2004)

  10. Composite PW Anomalies PW Units: mm Column precipitable water anomalies are sizeable, and in phase with precipitation anomalies, as would be expected given the strong relationship between saturation fraction and precipitation. Precipitation contour interval 4 mm day-1.

  11. dPW/dt in quadrature with precipitation signal. Precipitation contour 4 mm day-1.

  12. Intraseasonal Vertically-Integrated MSE Budget • Horizontal advection is the leading term and is (nearly) in quadrature with PW and precipitation in the intraseasonal MSE budget • Latent heat flux slightly lags precipitation, and has a positive covariance with precipitation • 80-90% of MSE tendency due to latent heat component • Vertical advection causes anomalous MSE export during enhanced precipitation, although is overcompensated by LH and LW anomalies Precip LW LH+SH e.g. Neelin and Held (1987)

  13. Composite Vertically-Integrated Moisture Budget • Horizontal advection is (nearly) in quadrature with precipitation (and PW) and in phase with the humidity tendency. • Surface evaporation slightly lags the precipitation anomalies, with a strong positive covariance

  14. Composite Zonal Advection (Phase 5) • = 50-day mean, = deviation from 50-day mean • Eastward zonal advection of moisture anomalies is supported by

  15. Total • At time of peak moistening in the model, total zonal winds are on the order of 5 m s-1. • That is helping to regulate eastward propagation in the model might be testable by changing the SST boundary condition in the model in order to reduce the basic state westerly flow in the model. • Meridional advection appears to act more as a damping mechanism on moisture anomalies, mainly through U850 Precip

  16. Sensitivity Tests • Set surface fluxes at climatological mean to test influence of WISHE • Use SST distribution with reduced zonal gradient to test influence of reduced zonal advection through reduction in

  17. Control Versus No-WISHE Comparison Control No-WISHE • WISHE appears to destabilize the MJO in the model. 30-90 day, zonal wavenumber 1-3 variance decreases dramatically without WISHE active • Small spatial scale precipitation variability that moves slowly east is still apparent in the model

  18. Effect of Reduced Basic State Westerlies Control 90 days 30 days • The space time-spectrum of precipitation still indicates a concentrated spectral peak, but now it occurs near 100 day period rather than 40-50 days. • Propagation speed is 2.5 m s-1 rather than 4-5 m s-1, which is the approximate total eastward zonal wind at peak moistening as well. • Supports the role of in eastward propagation Reduced Zonal Gradient

  19. Lag-Regression Plot vs. 141oE Wind Reduced Zonal Gradient Control • Propagation speed slowed from 4-5 m s-1 to about 2.5 m s-1 in going to the simulation with reduced zonal gradient and reduced westerlies. • Supports the role of in eastward propagation

  20. Conclusions • An MJO in an aquaplanet GCM simulation is analyzed that shows some characteristics of a moisture mode • The model MJO is destabilized by wind-evaporation feedback, and appears to propagate eastward through advection of anomalous humidity by the sum of perturbation winds and mean westerly flow • At the phase of peak moistening, the total zonal wind at 850 hPa is 5 m s-1, approximately the same as the propagation speed of the intraseasonal disturbances • A zonally-symmetric aquaplanet does not support a robust MJO

  21. Open Questions/Future Work • Why is the MJO in a simulation with realistic meridional temperature gradients so unlocalized in frequency? • What initiates the MJO in this model? • Can the horizontal advection mechanism in this model be even more convincingly proven (e.g. by manipulating moisture advection?) • Importance of cloud-radiative feedbacks?

  22. Thanks!

  23. Extra Slides

  24. Theory: Wind-Induced Surface Heat Exchange (WISHE) • Early models of WISHE: Mean easterly flow and enhancement of surface fluxes to the east of convection supported eastward propagation (Neelin et al. 1987, Emanuel 1987) • Increasing evidence exists that some form of WISHE may be importance for MJO maintenance and possibly propagation, although it must operate in a state of basic state westerlies, unlike the early linear models (e.g. Sobel et al. 2009) Araligidad (2007)

  25. Motivation for Studying the MJO: Impacts(e.g. Tropical Cyclones) Enhanced MJO Precip Suppressed MJO Precip Higgins and Shi (2001) Maloney and Hartmann (2000)

  26. We Worked Hard to Get a Reasonable MJO in this Model Minimum entrainment Precipitation efficiency

  27. Theory: Moisture Modes and the MSE Budget • A moisture mode instability can result if large-scale divergent motions associated with convection import MSE into the column (e.g. Raymond et al. 2009, negative gross moist stability) • Alternatively, export by divergent motions can be positive, but MSE sources such as latent heat flux and cloud-radiative feedbacks overcompensate to produce MSE increases as a result of convection. • Such instability is manifest for WTG as strong positive moisture-convection feedbacks • The later view appears most relevant to the simulated MJO we analyze here Peters and Bretherton (2006)

  28. SST Distributions Used “Realistic” SST Zonally Symmetric Quarter Meridional Gradient

  29. Wavenumber-Frequency Spectra (U850) Observations Model 30 days 90 days 90 days 30 days A concentrated model peak also occurs in zonal wind, although variance too strong compared to observed.

  30. GCM Unfiltered Precipitation vs. Longitude 60 d 5 m/s 40 d 50 d

  31. Wavenumber-Frequency Spectra (U850) Observations “Realistic” SST Zonally Symmetric Quarter Gradient

  32. Composite Precipitation and U850 (Unfiltered) From Wheeler and Hendon (2004)

  33. Precip U850 (Notice reversed time axis) Westerly wind maximum lags precipitation maximum by about 5 days (1 MJO phase). Note the approximate 5 m s-1 total wind at Phases 4 and 5. Composited using the method of Wheeler and Hendon (2004)

  34. Composite Humidity Anomalies Unlike popular hypothesis in the literature, no initial and gradually deepening low-level precursor humidity signal in the lower troposphere precedes MJO convection.

  35. Lag Composites Results

  36. Composite Horizontal Advection (MSE) Zonal Meridional

  37. Composite U-Wind, T Contour=0.4 K Contour=1 m s-1 (Notice reversed time axis)

  38. Mean Wind (Vertical Profile)

  39. Intraseasonal Precipitable Water Budget • Precipitation and the vertical advection (convergence) terms largely are equal and opposite • Anomalous vertical moisture advection is negative at the time of peak moistening • Horizontal advection is (nearly) in quadrature with precipitation, consistent with its role suggested in the MSE budget E Precip

  40. Composite Meridional Advection (Phase 5) • Meridional advection tends to be a damping influence on anomalies. The term is prominent, acting somewhat like a diffusion in the presence of strong moisture gradients

  41. Total Total

  42. GCM Unfiltered U850 vs. Longitude Control No-WISHE

  43. Unfiltered Precipitation vs. Longitude,Control Versus No-WISHE Control Reduced Zonal Gradient • Get the sense right away that eastward propagation is slower when the basic state westerlies are changed, supporting the role of in eastward advection.

  44. Lag-Regression Plot vs. 141oE Wind Reduced Zonal Gradient Control • Propagation speed slowed from 4-5 m s-1 to about 2.5 m s-1 in going to the simulation with reduced zonal gradient and reduced westerlies. • Supports the role of in eastward propagation

  45. Precipitation Variance and Mean Wind

  46. Mean Wind and Precip

More Related