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Abstract A robust linear regression algorithm is applied to estimate 95% confidence intervals on the background wind associated with Madden–Julian oscillation (MJO) upper-tropospheric atmospheric circulation signals characterized by different phase speeds. Data reconstructed from the ERA5 to represent advection by the upper-tropospheric background flow and MJO-associated zonal wind anomalies, together with satellite outgoing longwave radiation anomalies, all in the equatorial plane, are regressed against advection data filtered for zonal wavenumber 2 and phase speeds of 3, 4, 5, and 7 m s −1 . The regressed advection by the background flow is then divided by the negative of the zonal gradient of regressed zonal wind across the central Indian Ocean base longitude at 80°E to estimate the associated background wind that leads to the given advection. The median estimates of background wind associated with these phase speeds are 13.4, 11.2, 10.5, and 10.3 m s −1 easterly. The differences between estimated values at neighboring speeds suggests that advection acts most strongly in slow MJO events, indicating that the slowest events happen to be slow because they experience stronger easterly advection by the upper-tropospheric background wind. Significance Statement The Madden–Julian oscillation (MJO) is the dominant subseasonal rainfall signal of the tropical atmosphere. This project shows that the background wind of the tropical atmosphere most especially slows down the slowest MJO events. Understanding what controls its speed might help scientists better predict events.
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Hydrometeor Storage and Advection Effects in DYNAMO Budget Analyses
Abstract The Dynamics of the Madden-Julian Oscillation (MJO) field campaign (DYNAMO) over the central Indian Ocean captured three strong MJO events during October-December 2011. Using the conventional budget approach of Yanai et al., surface rainfall P 0 is computed as a residual from the vertically integrated form of the moisture budget equation. This budget-derived P 0 is spatially averaged over the Gan Island NCAR S-PolKa radar domain and compared with rainfall estimates from the radar itself. To isolate the MJO signal, these rainfall time series are low-pass (LP) filtered and a three-MJO composite is created based on the time of maximum LP-filtered S-PolKa rainfall for each event. A comparison of the two composite rainfall estimates shows that the budget rainfall overestimates the radar rainfall by ∼ 15% in the MJO build-up stage and underestimates radar rainfall by ∼ 8% in the MJO decay stage. These rainfall differences suggest that hydrometeor (clouds and rain) storage and advection effects, which are neglected in the budget approach, are likely significant. Satellite and ground-based observations are used to investigate these hydrometeor storage and advection effects. While the findings are qualitatively consistent with expectations from theory, they fall short of explaining their full magnitude, suggesting even more refined experimental designs and measurements will be needed to adequately address this issue.
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- Award ID(s):
- 1853633
- PAR ID:
- 10349035
- Date Published:
- Journal Name:
- Journal of the Atmospheric Sciences
- ISSN:
- 0022-4928
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/JAS-D-21-0266.1
