Abstract

Previous observational analysis and modeling studies indicate that air–sea coupling plays an essential role in improving MJO simulations and extending MJO forecasting skills. However, whether the SST feedback plays an indispensable role for the existence of the MJO remains controversial, and the precise physical processes through which the SST feedback may lead to better MJO simulations and forecasts remain elusive.

The DYNAMO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY) field campaign recently completed over the Indian Ocean reveals a new perspective and provides better data to improve understanding of the MJO. It is found that among the five MJO events that occurred during the DYNAMO/CINDY field campaign, only two MJO events (the November and March ones) have robust SST anomalies associated with them. For the other three MJO events (the October, December, and January ones), no coherent SST anomalies are observed. This observational scenario suggests that the roles of air–sea coupling on the MJO vary greatly from event to event.

To elucidate the varying roles of air–sea coupling on different MJO events, a suite of hindcast experiments was conducted with a particular focus on the October and November MJO events. The numerical results confirm that the October MJO is largely controlled by atmospheric internal dynamics, while the November MJO is strongly coupled with underlying ocean. For the November MJO event, the positive SST anomalies significantly improve MJO forecasting by enhancing the response of a Kelvin–Rossby wave couplet, which prolongs the feedback between convection and large-scale circulations, and thus favors the development of stratiform rainfall, in turn, facilitating the production of eddy available potential energy and significantly amplifying the intensity of the model November MJO.

Abstract

This study examines the DigiCORA and Global Climate Observing System Reference Upper-Air Network (GRUAN) humidity corrections of Vaisala RS92 radiosondes at three sites over the tropical Indian Ocean and surrounding areas during the Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign in 2011. The proprietary DigiCORA correction algorithm is built into the ground station software provided by Vaisala, whereas the GRUAN correction is an open source algorithm. Included in the GRUAN data product are uncertainty estimates for their corrections. This information is used to examine the statistical consistency of the various corrections.

In general, the algorithms produce a positive relative humidity (RH) correction that increases with altitude related primarily to a solar radiation dry bias adjustment. For example, in daytime soundings the relative RH correction increases from a few percent for temperatures >0°C to 20%–40% between 100 and 200 hPa. Comparison of corrected RH vertical profiles show only small differences (on the order of a few percent or less at any given level) between the DigiCORA and GRUAN algorithms, such that these corrections are considered to be statistically consistent at most levels.

In evaluating corrected humidity data with independent estimates of total precipitable water (TPW), good agreement was found at all sites between corrected sounding and ground-based microwave radiometer (MWR) estimates of TPW with mean differences ≤0.9 mm (or <2%), which is well within the uncertainty of these measurements. Overall, the correction algorithms examined herein perform well over a wide range of tropical moisture conditions.

Abstract

During the Dynamics of Madden–Julian Oscillation (DYNAMO) Experiment in 2011, airborne expendable conductivity–temperature–depth (AXCTD) probes and airborne expendable bathythermographs (AXBTs) were deployed using NOAA’s WP-3D Orion aircraft over the southern tropical Indian Ocean. From initial analysis of the AXCTD data, about 95% of profiles exhibit double mixed layer structures. The presence of a mixed layer from some of these profiles were erroneous and were introduced because of the AXCTD processing software not being able to correctly identify the starting point of the probe descent. This work reveals the impact of these errors in data processing and presents an objective method to remove such erroneous data from the profiles using spectrograms from raw audio files. Reconstructed AXCTD/AXBT profiles are compared with collocated shipborne conductivity–temperature–depth (CTD) and expendable bathythermograph (XBT) profiles and are found to be in good agreement.

Abstract

Convective initiation processes in the Madden–Julian oscillation (MJO) events that occurred during the Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY2011)/Dynamics of the Madden–Julian Oscillation (DYNAMO) intensive observation period (IOP) were investigated. Two episodes that were initiated in mid-October (MJO1) and mid-November (MJO2) 2011 were analyzed using European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and satellite data. Moisture budgets in the equatorial Indian Ocean (IO) domain (10°S–10°N, 60°–90°E) were analyzed in detail by separating each variable into basic-state (>80 day), intraseasonal (20–80 day), and high-frequency (<20 day) variations. The quality of the ECMWF reanalysis was also evaluated against the sounding data collected during the field campaign.

In both MJO events, the increase in precipitable water started 8–9 days prior to the convective initiation. Moisture advection decomposition revealed that advection of basic moisture by intraseasonal easterly anomalies and of intraseasonal moisture anomalies by the basic zonal wind were pronounced in these two events. The nonlinear high-frequency terms in the meridional moisture advection were the same order of magnitude as the primary term in the middle troposphere, implying systematic upscale transport of moisture. As a possible mechanism of the acceleration of easterly anomalies, amplification of off-equatorial Rossby wave trains that intruded into the equatorial zone was detected during the preconditioning periods in both MJO events.

Abstract

This study uses Dynamics of the Madden–Julian Oscillation (DYNAMO) shipborne [Research Vessel (R/V) Roger Revelle] radar and Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) datasets to investigate MJO-associated convective systems in specific organizational modes [mesoscale convective system (MCS) versus sub-MCS and linear versus nonlinear]. The Revelle radar sampled many “climatological” aspects of MJO convection as indicated by comparison with the long-term TRMM PR statistics, including areal-mean rainfall (6–7 mm day⁻¹), convective intensity, rainfall contributions from different morphologies, and their variations with MJO phase. Nonlinear sub-MCSs were present 70% of the time but contributed just around 20% of the total rainfall. In contrast, linear and nonlinear MCSs were present 10% of the time but contributed 20% and 50%, respectively. These distributions vary with MJO phase, with the largest sub-MCS rainfall fraction in suppressed phases (phases 5–7) and maximum MCS precipitation in active phases (phases 2 and 3). Similarly, convective–stratiform rainfall fractions also varied significantly with MJO phase, with the highest convective fractions (70%–80%) in suppressed phases and the largest stratiform fraction (40%–50%) in active phases. However, there are also discrepancies between the Revelle radar and TRMM PR. Revelle radar data indicated a mean convective rain fraction of 70% compared to 55% for TRMM PR. This difference is mainly due to the reduced resolution of the TRMM PR compared to the ship radar. There are also notable differences in the rainfall contributions as a function of convective intensity between the Revelle radar and TRMM PR. In addition, TRMM PR composites indicate linear MCS rainfall increases after MJO onset and produce similar rainfall contributions to nonlinear MCSs; however, the Revelle radar statistics show the clear dominance of nonlinear MCS rainfall.

Abstract

Tropospheric moisture is a key factor controlling the global climate and its variability. For instance, moistening of the lower troposphere is necessary to trigger the convective phase of a Madden–Julian oscillation (MJO). However, the relative importance of the processes controlling this moistening has yet to be quantified. Among these processes, the importance of the moistening by shallow convection is still debated. The authors use high-frequency observations of humidity and convection from the Research Vessel (R/V) Mirai that was located in the Indian Ocean ITCZ during the Cooperative Indian Ocean Experiment on Intraseasonal Variability/Dynamics of the MJO (CINDY/DYNAMO) campaign. This study is an initial attempt to directly link shallow convection to moisture variations within the lowest 4 km of the atmosphere from the convective scale to the mesoscale. Within a few tens of minutes and near shallow convection occurrences, moisture anomalies of 0.25–0.5 g kg⁻¹ that correspond to tendencies on the order of 10–20 g kg⁻¹ day⁻¹ between 1 and 4 km are observed and are attributed to shallow convective clouds. On the scale of a few hours, shallow convection is associated with anomalies of 0.5–1 g kg⁻¹ that correspond to tendencies on the order of 1–4 g kg⁻¹ day⁻¹ according to two independent datasets: lidar and soundings. This can be interpreted as the resultant mesoscale effect of the population of shallow convective clouds. Large-scale advective tendencies can be stronger than the moistening by shallow convection; however, the latter is a steady moisture supply whose importance can increase with the time scale. This evaluation of the moistening tendency related to shallow convection is ultimately important to develop and constrain numerical models.

Abstract

The Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign, conducted over the Indian Ocean from October 2011 to March 2012, was designed to study the initiation of the Madden–Julian oscillation (MJO). Two prominent MJOs occurred in the experimental domain during the special observing period in October and November. Data from a northern and a southern sounding array (NSA and SSA, respectively) have been used to investigate the apparent heat sources and sinks (Q ₁ and Q ₂) and radiative heating rates Q _R throughout the life cycles of the two MJO events. The MJO signal was far stronger in the NSA than the SSA. Time series of Q ₁, Q ₂, and the vertical eddy flux of moist static energy reveal an evolution of cloud systems for both MJOs consistent with prior studies: shallow, nonprecipitating cumulus during the suppressed phase, followed by cumulus congestus, then deep convection during the active phase, and finally stratiform precipitation. However, the duration of these phases was shorter for the November MJO than for the October event. The profiles of Q ₁ and Q ₂ for the two arrays indicate a greater stratiform rain fraction for the NSA than the SSA—a finding supported by TRMM measurements. Surface rainfall rates and net tropospheric Q _R determined as residuals from the budgets show good agreement with satellite-based estimates. The cloud radiative forcing was approximately 20% of the column-integrated convective heating and of the same amplitude as the normalized gross moist stability, leaving open the possibility of radiative–convective instability for the two MJOs.

Abstract

Dynamics of the Madden–Julian Oscillation (DYNAMO) and Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) observations and reanalysis-based surface flux products are used to test theories of atmosphere–ocean interaction that explain the Madden–Julian oscillation (MJO). Negative intraseasonal outgoing longwave radiation, indicating deep convective clouds, is in phase with increased surface wind stress, decreased solar heating, and increased surface turbulent heat flux—mostly evaporation—from the ocean to the atmosphere. Net heat flux cools the upper ocean in the convective phase. Sea surface temperature (SST) warms during the suppressed phase, reaching a maximum before the onset of MJO convection. The timing of convection, surface flux, and SST is consistent from the central Indian Ocean (70°E) to the western Pacific Ocean (160°E).

Mean surface evaporation observed in TOGA COARE and DYNAMO (110 W m⁻²) accounts for about half of the moisture supply for the mean precipitation (210 W m⁻² for DYNAMO). Precipitation maxima are an order of magnitude larger than evaporation anomalies, requiring moisture convergence in the mean, and on intraseasonal and daily time scales. Column-integrated moisture increases 2 cm before the convectively active phase over the Research Vessel (R/V) Roger Revelle in DYNAMO, in accordance with MJO moisture recharge theory. Local surface evaporation does not significantly recharge the column water budget before convection. As suggested in moisture mode theories, evaporation increases the moist static energy of the column during convection. Rather than simply discharging moisture from the column, the strongest daily precipitation anomalies in the convectively active phase accompany the increasing column moisture.

Abstract

A surface diurnal warm layer is diagnosed from Seaglider observations and develops on half of the days in the Cooperative Indian Ocean Experiment on Intraseasonal Variability/Dynamics of the Madden–Julian Oscillation (CINDY/DYNAMO) Indian Ocean experiment. The diurnal warm layer occurs on days of high solar radiation flux (>80 W m⁻²) and low wind speed (<6 m s⁻¹) and preferentially in the inactive stage of the Madden–Julian oscillation. Its diurnal harmonic has an exponential vertical structure with a depth scale of 4–5 m (dependent on chlorophyll concentration), consistent with forcing by absorption of solar radiation. The effective sea surface temperature (SST) anomaly due to the diurnal warm layer often reaches 0.8°C in the afternoon, with a daily mean of 0.2°C, rectifying the diurnal cycle onto longer time scales. This SST anomaly drives an anomalous flux of 4 W m⁻² that cools the ocean. Alternatively, in a climate model where this process is unresolved, this represents an erroneous flux that warms the ocean. A simple model predicts a diurnal warm layer to occur on 30%–50% of days across the tropical warm pool. On the remaining days, with low solar radiation and high wind speeds, a residual diurnal cycle is observed by the Seaglider, with a diurnal harmonic of temperature that decreases linearly with depth. As wind speed increases, this already weak temperature gradient decreases further, tending toward isothermal conditions.

Abstract

This study quantifies, from a systematic set of regional ocean–atmosphere coupled model simulations employing various coupling intervals, the effect of subdaily sea surface temperature (SST) variability on the onset and intensity of Madden–Julian oscillation (MJO) convection in the Indian Ocean. The primary effect of diurnal SST variation (dSST) is to raise time-mean SST and latent heat flux (LH) prior to deep convection. Diurnal SST variation also strengthens the diurnal moistening of the troposphere by collocating the diurnal peak in LH with those of SST. Both effects enhance the convection such that the total precipitation amount scales quasi-linearly with preconvection dSST and time-mean SST. A column-integrated moist static energy (MSE) budget analysis confirms the critical role of diurnal SST variability in the buildup of column MSE and the strength of MJO convection via stronger time-mean LH and diurnal moistening. Two complementary atmosphere-only simulations further elucidate the role of SST conditions in the predictive skill of MJO. The atmospheric model forced with the persistent initial SST, lacking enhanced preconvection warming and moistening, produces a weaker and delayed convection than the diurnally coupled run. The atmospheric model with prescribed daily-mean SST from the coupled run, while eliminating the delayed peak, continues to exhibit weaker convection due to the lack of strong moistening on a diurnal basis. The fact that time-evolving SST with a diurnal cycle strongly influences the onset and intensity of MJO convection is consistent with previous studies that identified an improved representation of diurnal SST as a potential source of MJO predictability.