The Cloud Population and Onset of the Madden-Julian Oscillation over the Indian Ocean during dynamo-amie
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- APPENDIX A Sensitivity of quantities derived for “rainy” and “dry” periods to precipitation threshold
- APPENDIX B Testing statistical significance for echo-top PDFs
- 9. References
- Phase Dates
8. Conclusions This study is unique because never before has a powerful S-band radar system such as S-PolKa been located and operated continuously for several months where MJO-related convection is known to first appear before propagating eastward. The DYNAMO/AMIE radar operation in the central-equatorial Indian Ocean documented the cloud population over a 3.5 5-month period with the S-PolKa dual-wavelength, dual-polarized scanning radar system nearly co-located with 3-hourly rawinsondes. Three distinct one- to two-week long large-scale convective events (LCEs) occurred at Addu during the IOP. Although clouds of all depths were present during active and suppressed periods, the variability in convection associated with the MJO was dominated by the variability in the areal coverage by cloud systems exhibiting deep precipitating stratiform areas, as has been noted previously by Zuluaga and Houze [2013], and Barnes and Houze [2013]. Large cloud echo clusters and MCSs containing large areas of stratiform precipitation contributed over one-third of the total precipitation of the cloud populations occurring during LCEs, while suppressed periods featured isolated convective cells and some echo clusters with small amounts of stratiform precipitation. Since the stratiform components of the cloud systems originate as convective cores, the increased stratiform rain during LCEs indicates a temporary maximum in the upward mass flux of water within deep convection during active MJO periods. Whether this transport was due simply to the greater number of convective cores present or occurred because stronger updrafts transport more water vertically remains to be determined, but is not important when considering the net latent heat release, which depends only on the net vertical transport. The greater proportion of stratiform rain during LCEs thus implies [Houze, 1982, 1989] that the heating profile is more top-heavy (i.e. has a maximum in the upper troposphere) during rainy portions of LCEs. Several observations indicate that the cloud population and humidity field change relatively suddenly rapidly near the beginning of an LCE. The areal coverage of stratiform precipitation increases rapidly over about 3-7 days as the primary type of convection making up the cloud population shifts from isolated convective clouds and large medium-sized precipitating clusters to large MCSs. A rapid increase in the modal distribution of convective cloud echo-top height from 5-6 km to 8 km closely corresponds in time to humidity increases in the portion of the troposphere lying above 850 hPa that occur a week or less prior to the increase in modal echo-top height, if prior at all. No direct positive feedback is shown indicated between moistening and this sudden vertical growth of convection. (Little variation is observed in humidity occurs below 850 hPa; a warm, moist marine boundary layer is observed at all times.) These results directly contradict the proposed timescale for the "discharge-recharge" mechanism for MJO onset, which describes the vertical build-up of moist static energy as occurring gradually over 10 to 20 days. We have shown that rResults supporting consistent with this the timescale for the "discharge-recharge" hypothesis could be obtained when by compositing our results over all three LCEs because sharp changes in humidity and the convective cloud population were would be smoothed out. We could not produce resultsResults supporting the 10-20 day timescale of “discharge-recharge” do not arise when examining individual casesrealizations. No gradual “recharging” of humidity or convective depth is actually observed. This paper highlights the importance of investigating MJO onset on a case study basis. We also have documented the relationship between the build-up of humidity through the depth ofin the troposphere and the associated build-up of convection. When filtered for 20-60 day variability, humidity appears to increase a couple of days before convective areal coverage increases. Stratiform echoes are observed a couple more days later, followed by moistening of the upper troposphere. However, the time scale for changes in humidity and convection prior to MJO onset is shown by this study to be less than 10 days. The filtered time series lose information about high-frequency events and sharp changes in either field that are critical in describing how MJO onset occurs during each individual LCE. When we do not filter for the 20-60 day variability, several results from this study suggest that clouds moisten the lower troposphere prior to a build up in convective echo-top associated with MJO onset:
Additionally, we show evidence that stratiform and anvil elements contribute to moistening in the upper troposphere because
Nonetheless, weWe cannot draw any conclusions about the effects of low- and mid-level moisture on the eventual increase in convective echo-top and the onset of a LCE associated with development of an MJO. We note that dDuring one LCE, increases in lower-tropospheric humidity occurred at the same time as convective depth increased. Also, a quick look at the smoothed, unfiltered time series of humidity (Fig. 8b) shows that mid-level moistening occurreds before, after, and concurrently with, the observed rapid build-up of convective echo-tops associated with LCE1, LCE2, and LCE3 respectively. Additionally, we have not explored potential effects of large-scale convergence or /advection of moisture into the region prior to convective build-up [e.g. Maloney, 2009], which could also contribute to the increase in low-level moisture, though we have shown that humidity anomalies dido not appear to precede anomalies in convective areal coverage in the cases considered here. We have also briefly shown that changes in the upper-level zonal wind and temperature anomalies occur on the same frequency as the MJO events occur. ThusThis concurrence indicates that, upper-level dynamics may have an impact on widespread, organized convection convection—a topic that needs to be explored in a future study. Our current description of convection related to the MJO is not intended to fully explain the mechanisms responsible for onset and propagation of convection but rather provide some detail on the relationship between convection and tropospheric humidity leading up to MJO onset. While the DYNAMO/AMIE data analyzed herein do not support the "discharge-recharge" hypothesis, we have also not yet explained definitively why clouds generally grow taller in the three to seven days prior to MJO onset. Also, the current analysis only examines humidity and convection within a small sample domain located within a much larger area in which MJO onset occurs. The vast DYNAMO/AMIE dataset includes not only instrumentation used in this paper, but also an entire array of precipitation and cloud radars over the Indian Ocean and tropical west Pacific that provide information on variability of the cloud population in other regions. Use of a broader set of deployed instruments, reanalysis, and satellite data should provide more understanding of the three-dimensional processes, potentially including upper tropospheric dynamics, involved in MJO onset. Future numerical simulations of cloud systems can also be anchored to the observational dataset and provide insight on the relative roles of various processes that control the intraseasonal variability in tropospheric moisture and convection. Such experiments will yield detailed water budgets that describe the transfer of water between convective clouds and their anvils, which as act agents for moistening the troposphere, and between clouds and the surrounding environment. APPENDIX A Sensitivity of quantities derived for “rainy” and “dry” periods to precipitation threshold The selection of a rainfall threshold to separate “rainy” and “dry” periods during an active LCE is a somewhat subjective process. If the threshold is too low (i.e. 0 mm), then an insufficient amount of the time series will be classified as a dry period to make any meaningful statistical comparison of echo-top PDFs during rainy and dry periods. If the threshold is too high, then dry periods are biased by times when a significant amount of rainfall is falling over some portion of the radar domain. An hourly domain-averaged precipitation estimate of 0.25 mm (or 6 mm day-1) typically occurs during the beginning or end of a short-term (1- to 2-day long) precipitation event (Fig. 2), and the precipitation echo during such times is classified either by many isolated convective echo clusters or stratiform in some part of the radar domain. Thus, any threshold above 0.25 mm is likely too high. Figure A1 shows two panels: They are duplicates of Figs. 6c and 9, except using a rainfall threshold of 0.25 mm. The peak of the PDF for rainy periods in Fig. A1a is at the same location as that in Fig. 6c, though the probability is about 0.01 higher. The PDF for dry periods in Fig A1a is shifted upward by 0.5 km or less, which is less than the resolution of the interpolated radar dataset. Fig A1b reveals RH profiles for rainy and dry periods using a threshold of 0.25 mm. Both profiles are shifted toward moister conditions than in Fig. 9, but the difference in RH between 850 hPa and 500 hPa remains about 10-15%. Additionally, the dry period RH profile maintains its shape and remains between the profiles for phases 8-3 and phases 4-7. The RH profiles below 800 hPa for dry periods and phases 4-7 remain nearly identical. Thus, we determine that our main conclusions are not unduly influenced by the choice of rainfall threshold given in separating times during an active LCE into rainy and dry periods. APPENDIX B Testing statistical significance for echo-top PDFs Statistical significance among differences in echo-top PDFs described in Sec. 5 and RH profiles shown in Section 6 is determined using a Mann-Whitney U-test with a 95% confidence level. For echo-top PDFs, each separate contiguous cloud echo observed by S-PolkaPolKa theoretically represents a separate degree of freedom (DOF). Determining the exact DOF would thus require a complicated radar echo tracking algorithm or determining spatial and temporal autocorrelation of radar data at each data point for three and a half months. Instead we make an unrealistically conservative assumption that very few individual echo objects exist. For a rainfall threshold of 0.1mm, the number of convective echoes detected during wet periods is greater than that observed during dry periods by a factor of about 12. Suppose we assume that only one new contiguous convective echo is observed each hour, and we assume that 12 times that amount is observed during wet conditions. The DOF for dry periods in Fig. 6c is equal to the number of hours classified as falling within a dry period, or 133; and the DOF for wet periods is 12*(number of hours classified as wet period), or 12*190 = 2280. Acknowledgments: The authors are grateful to all the engineers and scientists at NCAR who worked many hours to ensure that the S-PolKa system ran smoothly throughout DYNAMO as well as the DOE personnel responsible for launching soundings at Gan every three hours for several months. Hannah Barnes, Stacy Brodzik, Casey Burleyson, Kaustav Chakravarty, Deanna Hence, Zhujun Li, and Kristen Rasmussen maintained UW science operations at S-PolKa in the field with the authors. Beth Tully refined graphics and proofread the manuscript. Three anonymous reviewers provided excellent constructive comments to improve this manuscript. S. Powell was supported by DOE grants DE-SC0001164/ER-64572 and DE-SC0008452 and NSF grant AGS-1059611. 9. References Andersen, J. A., and Z. Kuang (2012), Moist static energy budget of MJO-like disturbance in the atmosphere of a zonally symmetric aquaplanet, J. Clim., 25, 2782-2804. Barnes, H. C., and R. A. Houze, Jr. (2013), The precipitating cloud population of the Madden-Julian Oscillation over the Indian and west Pacific oceans, J. Geophys. Res., in press. Benedict, J. J., and D. A. Randall (2007), Observed characteristics of the MJO relative to maximum rainfall, J. Atmos. Sci., 64, 2332-2354. Bladé, I., and D. L. Hartmann (1993): Tropical intraseasonal oscillations in a simple nonlinear model, J. Atmos. Sci., 50, 2922-2939. Chen, S. S., R. A. Houze, Jr., and B. E. Mapes (1996), Multiscale variability of deep convection in relation to large-scale circulation in TOGA COARE, J. Atmos. Sci., 53, 1380-1409. Chen, S. S., and R. A. Houze, Jr. (1997a), Diurnal variation and life cycle of deep convective systems over the tropical Pacific warm pool, Quart. J. Roy. Meteor. Soc., 123, 357-388. Chen, S. S., and R. A. Houze, Jr. (1997b), Interannual variability of deep convection over the tropical warm pool, J. Geophys. Res., 102, 25,783-25,795. Churchill, D. D., and R. A. Houze, Jr. (1984), Development and structure of winter monsoon cloud clusters on 10 December 1978, J. Atmos. Sci., 41, 933-960. Del Genio, A. D., Y. Chen, D. Kim, and M.-S. Yao (2012), The MJO transition from shallow to deep convection in Cloudsat/CALIPSO data and GISS GCM simulations, J. Clim., 25, 3755-3770. Didlake, A. C., Jr., and R. A. Houze, Jr. (2009), Convective-scale downdrafts in the principal rainband of Hurricane Katrina (2005), Mon. Weather Rev., 137, 3269-3293. Gill, A. E. (1980), Some simple solutions for heat-induced tropical circulation, Q. J. R. Meteorol. Soc., 106, 447-462. Godfrey, J. S., R. A. Houze, Jr., R. H. Johnson, R. Lukas, J.-L. Redelsperger, A. Sumi, and R. Weller (1998), COARE: An interim report, J. Geophys. Res., 103 (7), 14 395-14 450. Gottschalck, J., P. E. Roundy, C. J. Schreck III, A. Vintzileos, and C. Zhang (2013), Large-scale atmospheric and oceanic conditions during the 2011-2012 DYNAMO field campaign, Mon. Weather Rev., in press. Haertel, P. T., G. N. Kiladis, A. Denno, and T. M. Rickenbach (2008), Vertical-mode decompositions of 2-day waves and the Madden-Julian oscillation. J. Atmos. Sci., 65, 813-833. Hendon, H. H., and M. L. Salby (1994), The life cycle of the Madden-Julian oscillation, J. Atmos. Sci., 51, 2225-2237. Hohenegger, C., and B. Stevens (2013), Preconditioning deep convection with cumulus congestus, J. Atmos. Sci., 70, 448-464. Houze, R. A., Jr., S. S. Chen, D. E. Kingsmill, Y. Serra, and S. E. Yuter (2000), Convection over the Pacific warm pool in relation to the Kelvin-Rossby wave, J. Atmos. Sci., 57, 3058-3089. Houze, R. A., Jr. (2004), Mesoscale convective systems. Rev. Geophys., 42, RG4003, doi:10.1029/2004RG000150. Johnson, R. H., T. M. Rickenbach, S. A. Rutledge, P. E. Ciesielski, and W. H. Schubert (1999), Trimodal characteristics of tropical convection, J. Clim., 12, 2397-2418. Katsumata, M., R. H. Johnson, and P. E. Ciesielski (2009), Observed synoptic-scale variability during the developing phase of an ISO over the Indian Ocean during MISMO, J. Atmos. Sci., 66, 3434-3448. Kemball-Cook, S. R., and B. C. Weare (2001), The onset of convection in the Madden-Julian oscillation, J. Clim., 14, 780-793. Kiladis, G. N., K. H. Straub, P. T. Haertel (2005), Zonal and vertical structure of the Madden-Julian oscillation, J. Atmos. Sci., 62, 2790-2809. Knutson, R. R., and K. M. Weickmann (1987), 30-60 day atmospheric oscillations: Composite life cycles of convection and circulation anomalies, Mon. Weather Rev., 115, 1406-1436. Knutson, R. R., K. M. Weickmann, and J. E. Kutzbach (1986), Global-scale intraseasonal oscillations of outgoing longwave radiation and 250mb zonal wind during Northern Hemisphere summer, Mon. Weather Rev., 114, 605-623. Lau, K. M., and L. Peng (1987), Origin of low-frequency (intraseasonal) oscillations in the tropical atmosphere, Part I: Basic Theory. J. Atmos. Sci., 44, 950-972. Lin, X., and R. H. Johnson (1996), Heating, moistening, and rainfall over the western Pacific warm pool during TOGA COARE, J. Atmos. Sci., 53, 3367-3383. Long, C. N., and D. J. Holdridge (2012), Investigations of possible low-level temperature and moisture anomalies during the AMIE field campaign on Manus Island, ARM Technical Report, DOE/SC-ARM/TR-119. Available at http://www.arm.gov/. Madden, R. A., and P. R. Julian (1971), Detection of a 40-50-day oscillation in the zonal wind in the tropical Pacific, J. Atmos. Sci., 28, 702-708. Madden, R. A., and P. R. Julian (1972), Description of global-scale circulation cells in the tropics with a 40-50 day period, J. Atmos. Sci., 29, 1109-1123. Maloney, E. D. (2009), The moist static energy budget of a composite tropical intraseasonal oscillation in a climate model, J. Clim., 22, 711-729. Maloney, E. D., and D. L. Hartmann (1998), Frictional moisture convergence in a composite life cycle of the Madden-Julian oscillation, J. Clim., 11, 2387-2403. Masunaga, H. (2013), A satellite study of tropical moist convection and environmental variability: A moisture and thermal budget analysis, J. Atmos. Sci., in press. Masunaga, H., T. S. L'Ecuyer, and C. D. Kummerow (2006), The Madden-Julian oscillation recorded in early observations from the Tropical Rainfall Measuring Mission (TRMM), J. Atmos. Sci., 63, 2777-2794. Matthews, A. J. (2000), Propagation mechanisms for the Madden-Julian oscillation, Q. J. R. Meteorol. Soc., 126, 2637-2651. Matthews, A. J. (2008), Primary and successive events in the Madden-Julian oscillation, Q. J. R. Meteorol. Soc., 134, 439-453. Muller, C. J., L. E. Back, P. A. O’Gorman, and K. A. Emanuel (2009), A model for the relationship between tropical precipitation and column water vapor, Geophys. Res. Lett., 36, L16804, doi:10.1029/2009GL039667. Nogués-Paegle, J., B.-C. Lee, and V. E. Kousky (1989), Observed modal characteristics of the intraseasonal oscillation, J. Clim., 2, 496-507. Ray, P., and T. Li (2013), Relative roles of circumnavigating waves and extratropics on the MJO and its relationship with the mean state, J. Atmos. Sci., 70, 876-893. Riley, E. M., B. E. Mapes, and S. N. Tulich (2011), Clouds associated with the Madden-Julian oscillation: A new perspective from Cloudsat, J. Atmos. Sci., 68, 3032-3051. Rui, H., and B. Wang (1990), Development characteristics and dynamic structure of tropical intraseasonal convection anomalies, J. Atmos. Sci., 47, 357-379. Salby, M. L., R. R. Garcia, and H. H. Hendon (1994), Planetary-Scale Circulations in the Presence of Climatological and Wave-Induced Heating, J. Atmos. Sci., 51, 2344-2367. Seo, K-H., and K-Y. Kim (2003), Propagation and initiation mechanisms of the Madden-Julian oscillation, J. Geophys. Res., 108(D13), 4384, doi:10.1029/2002JD002876,2003. Steiner, M., R. A. Houze, Jr., and S. E. Yuter (1995), Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data, J. Appl. Meteorol., 34, 1978-2007. Takayabu, Y. N. (1994), Large-scale cloud disturbances associated with equatorial waves. Part II: Westward-propagating inertio-gravity waves, J. Meteorol. Soc. Jpn., 72, 451-465. Virts, K. S., and J. M. Wallace (2010), Annual, Interannual, and Intraseasonal Variability of Tropical Tropopause Transition Layer Cirrus, J. Atmos. Sci., 67, 3113-3129. Vivekanandan, J., D. S. Zrni , S. M. Ellis, R. Oye, A. V. Ryzhkov, and J. Straka (1999), Cloud microphysics retrieval using S-band dual-polarization radar measurements, Bull. Am. Meteorol. Soc., 80, 381-388. Wang, B., and H. Rui (1990), Dynamics of the coupled moist Kelvin-Rossby wave on an equatorial beta-plane, J. Atmos. Sci., 47, 397-413. Wang, S., and A. H. Sobel (2012), Impact of imposed drying on deep convection in a cloud-resolving model, J. Geophys. Res., 117, D02112, doi:10.1029/2011JD016847. Wheeler, M. C., and H. H. Hendon (2004), An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction, Mon. Weather Rev., 132, 1917-1932. Wu, X., and L. Deng (2013), Comparison of moist static energy and budget between the GCM-simulated Madden-Julian Oscillation and observations over the Indian Ocean and western Pacific, J. Clim., 26, 4981-4993. Yamada, H., K. Yoneyama, M. Katsumata, and R. Shirooka (2010), Observations of a super cloud cluster accompanied by synoptic-scale eastward-propagating precipitating systems over the Indian Ocean, J. Atmos. Sci., 67, 1456-1473. Yanai, M., B. Chen, and W.-W. Tung (2000), The Madden-Julian oscillation observed during the TOGA COARE IOP: Global view, J. Atmos. Sci., 57, 2374-2396. Yasunaga, K., K. Yoneyama, Q. Moteki, M. Fujita, Y. N. Takayabu, J. Suzuki, T. Ushiyama, and B. E. Mapes (2010), Characteristics of 3-4- and 6-8-day period disturbances observed over the tropical Indian Ocean, Mon. Weather Rev., 138, 4158-4174. Yoneyama, K., et al. (2008), MISMO field experiment in the equatorial Indian Ocean, Bull. Am. Meteorol. Soc., 89, 1889-1903. Yoneyama, K., C. Zhang, and C. N. Long (2013), Tracking pulses of the Madden-Julian Oscillation. Bull. Am. Meteorol. Soc., in press. Yuter, S. E., and R. A. Houze, Jr. (1997), Measurements of raindrop size distributions over the Pacific warm pool and implications for Z-R relations, J. Appl. Meteorol., 36, 847-867. Zhang, C. (2005), Madden-Julian oscillation, Rev. Geophys., 43, RG2003, doi:10.1029/2004RG000158. Zuluaga, M. D., and R. A. Houze, Jr (2013), Evolution of the population of precipitating convective systems over the equatorial Indian Ocean in active phases of the Madden-Julian oscillation, J. Atmos. Sci., 70, 2713-2725. in press. Zhang, C. (2005), Madden-Julian oscillation, Rev. Geophys., 43, RG2003, doi:10.1029/2004RG000158. Table 1: Dates of occurrence of each WH MJO phase during DYNAMO-AMIE.
Table 2: Maximum lag correlation coefficients and the lag (in days) at which they occur (in parentheses) for filtered specific humidity anomaly time series at 850 hPa, 700 hPa, 500 hPa, and 300 hPa, as well as for the filtered time series of stratiform and convective areal coverage. Positive lags indicate that the quantity listed in that column occurs first. Because of the small sample size, none of the correlations are statistically significant.
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