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simulate MJO events [see reviews by Madden and Julian (1994) and Zhang (2005) ]. Building on previous observational, theoretical, and modeling work, the research described in this paper aims to assess the role of convective-scale wind-induced surface flux feedbacks in supporting convective clusters within the MJO and determine how important this feedback is for subsequent convective organization. Several hypotheses attempting to explain the observed physical characteristics of the MJO assert that
simulate MJO events [see reviews by Madden and Julian (1994) and Zhang (2005) ]. Building on previous observational, theoretical, and modeling work, the research described in this paper aims to assess the role of convective-scale wind-induced surface flux feedbacks in supporting convective clusters within the MJO and determine how important this feedback is for subsequent convective organization. Several hypotheses attempting to explain the observed physical characteristics of the MJO assert that
the central Indian Ocean during DYNAMO. In this paper we assess the response of surface fluxes and SST to intraseasonal convective anomalies, examining the evidence that intraseasonal interaction of the atmosphere with surface fluxes, or with the SST, is a significant contributor to the MJO. We use TOGA COARE and DYNAMO observations, and surface flux products based on global reanalyses. From these datasets we assess three hypothetical models of ocean–atmosphere interactions: Intraseasonal surface
the central Indian Ocean during DYNAMO. In this paper we assess the response of surface fluxes and SST to intraseasonal convective anomalies, examining the evidence that intraseasonal interaction of the atmosphere with surface fluxes, or with the SST, is a significant contributor to the MJO. We use TOGA COARE and DYNAMO observations, and surface flux products based on global reanalyses. From these datasets we assess three hypothetical models of ocean–atmosphere interactions: Intraseasonal surface
cycle analysis ( section 4 ) are defined. Section 5 provides a summary of the study’s findings along with a discussion of the resulting implications. 2. Data and methods The primary DYNAMO observations employed in this study—those from a sounding network, a cloud-sensitive radar, and an air–sea flux site—are available from http://data.eol.ucar.edu/master_list/?project=DYNAMO . a. Gridded sounding analysis The Indian Ocean sounding network was composed of six sites, making two quadrilaterals
cycle analysis ( section 4 ) are defined. Section 5 provides a summary of the study’s findings along with a discussion of the resulting implications. 2. Data and methods The primary DYNAMO observations employed in this study—those from a sounding network, a cloud-sensitive radar, and an air–sea flux site—are available from http://data.eol.ucar.edu/master_list/?project=DYNAMO . a. Gridded sounding analysis The Indian Ocean sounding network was composed of six sites, making two quadrilaterals
nominal location 0°, 80.5°E for (a) temperature, (b) specific humidity, and (c) wind speed. Other data sources used in this study include rainfall analyses available at 3 h and 0.25° horizontal resolution available from the 3B42v7 TRMM product ( Huffman et al. 2007 ). For computation of budget-derived rainfall as a residual from the moisture budget ( Yanai et al. 1973 ), surface latent heat fluxes were obtained from the TropFlux product (daily, 1° horizontal resolution) based on Praveen Kumar et al
nominal location 0°, 80.5°E for (a) temperature, (b) specific humidity, and (c) wind speed. Other data sources used in this study include rainfall analyses available at 3 h and 0.25° horizontal resolution available from the 3B42v7 TRMM product ( Huffman et al. 2007 ). For computation of budget-derived rainfall as a residual from the moisture budget ( Yanai et al. 1973 ), surface latent heat fluxes were obtained from the TropFlux product (daily, 1° horizontal resolution) based on Praveen Kumar et al
active phase develops, convective features increase in scale and organization, expanding from isolated cells to large clusters spanning hundreds of kilometers. Synoptic-scale moisture convergence is the dominant source of moisture during the active phase and explains a large fraction of the observed precipitation ( Lin and Johnson 1996 ; Johnson and Ciesielski 2013 ; de Szoeke et al. 2015 ). Convection and surface fluxes are also affected by convectively forced cold pools. Over the tropical ocean
active phase develops, convective features increase in scale and organization, expanding from isolated cells to large clusters spanning hundreds of kilometers. Synoptic-scale moisture convergence is the dominant source of moisture during the active phase and explains a large fraction of the observed precipitation ( Lin and Johnson 1996 ; Johnson and Ciesielski 2013 ; de Szoeke et al. 2015 ). Convection and surface fluxes are also affected by convectively forced cold pools. Over the tropical ocean
this mixing is unknown. Model cumulus parameterizations initialize buoyant updrafts with air properties from the BL (e.g., Arakawa and Schubert 1974 ; Betts 1976 ; Zhang and MacFarlane 1995 ; Mapes 2000 ; Fletcher and Bretherton 2010 ). Recent cloud-permitting models simulated an entrainment sink of BL MSE that slightly exceeded that due to downdrafts ( Thayer-Calder and Randall 2015 ). Turbulent flux from the ocean surface, mostly evaporation, supplies the BL with MSE. The BL transports MSE
this mixing is unknown. Model cumulus parameterizations initialize buoyant updrafts with air properties from the BL (e.g., Arakawa and Schubert 1974 ; Betts 1976 ; Zhang and MacFarlane 1995 ; Mapes 2000 ; Fletcher and Bretherton 2010 ). Recent cloud-permitting models simulated an entrainment sink of BL MSE that slightly exceeded that due to downdrafts ( Thayer-Calder and Randall 2015 ). Turbulent flux from the ocean surface, mostly evaporation, supplies the BL with MSE. The BL transports MSE
1. Introduction Ocean–atmosphere interaction is a key process in tropical weather and climate. The moisture flux from the ocean to atmosphere increases approximately exponentially with sea surface temperature (SST) through the Clausius–Clapeyron and bulk flux relationships ( Fairall et al. 1996b ). These processes are core to the evolution of El Niño–Southern Oscillation (ENSO; Neelin et al. 1998 ) on interannual time scales. On shorter, intraseasonal time scales, ocean–atmosphere interaction
1. Introduction Ocean–atmosphere interaction is a key process in tropical weather and climate. The moisture flux from the ocean to atmosphere increases approximately exponentially with sea surface temperature (SST) through the Clausius–Clapeyron and bulk flux relationships ( Fairall et al. 1996b ). These processes are core to the evolution of El Niño–Southern Oscillation (ENSO; Neelin et al. 1998 ) on interannual time scales. On shorter, intraseasonal time scales, ocean–atmosphere interaction
-Calder and Randall 2015 ). Surface sensible and evaporative latent heat fluxes (80%–90% is latent heat) are the source of the BL moist static energy. Turbulent entrainment and cumulus updrafts and downdrafts are its sinks. Marine cold pools were observed at the surface from the Research Vessel (R/V) Roger Revelle stationed in the central Indian Ocean (0°, 80°E) for most of two research cruise legs during the DYNAMO field campaign. The DYNAMO experiment ( Yoneyama et al. 2013 ; Johnson and Ciesielski
-Calder and Randall 2015 ). Surface sensible and evaporative latent heat fluxes (80%–90% is latent heat) are the source of the BL moist static energy. Turbulent entrainment and cumulus updrafts and downdrafts are its sinks. Marine cold pools were observed at the surface from the Research Vessel (R/V) Roger Revelle stationed in the central Indian Ocean (0°, 80°E) for most of two research cruise legs during the DYNAMO field campaign. The DYNAMO experiment ( Yoneyama et al. 2013 ; Johnson and Ciesielski
). Differences among the models are not easily attributed to individual processes. It is likely that the MJO owes its existence to a mixed summation of weakly unstable modes. In moisture mode theories, small positive feedbacks to the column moist static energy (MSE) budget induced by the responses of radiation ( Johnson et al. 2015 ; Del Genio and Chen 2015 ) and surface fluxes to convection may be all that is needed to overcome weak atmospheric gross moist stability ( Raymond and Fuchs 2009 ) and grow
). Differences among the models are not easily attributed to individual processes. It is likely that the MJO owes its existence to a mixed summation of weakly unstable modes. In moisture mode theories, small positive feedbacks to the column moist static energy (MSE) budget induced by the responses of radiation ( Johnson et al. 2015 ; Del Genio and Chen 2015 ) and surface fluxes to convection may be all that is needed to overcome weak atmospheric gross moist stability ( Raymond and Fuchs 2009 ) and grow
-level outflow. The latent heat release associated with the convection (the secondary circulation) fuels an increase in vertical mass flux, which entrains midlevel air and further intensifies the vortex. Thus, thermodynamical processes in the secondary circulation are important for maintaining the primary circulation that drives the secondary circulation. According to Ooyama (1982) , this mechanism is valid when the horizontal scale of the disturbance exceeds the Rossby radius of deformation. In principle
-level outflow. The latent heat release associated with the convection (the secondary circulation) fuels an increase in vertical mass flux, which entrains midlevel air and further intensifies the vortex. Thus, thermodynamical processes in the secondary circulation are important for maintaining the primary circulation that drives the secondary circulation. According to Ooyama (1982) , this mechanism is valid when the horizontal scale of the disturbance exceeds the Rossby radius of deformation. In principle
