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Home » Use of the Ocean-Land-Atmosphere Model (OLAM) with Cloud System-Resolving Refined Local Mesh to Study MJO Initiation.
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Use of the Ocean-Land-Atmosphere Model (OLAM) with Cloud System-Resolving Refined Local Mesh to Study MJO Initiation.

Abstract Lack of understanding of MJO initiation, as well as the inability of most global models to adequately simulate the MJO and its initiation, limits our subseasonal to interannual prediction capability, including forecasts of extreme events such as Atlantic hurricanes, West Coast flooding, and ENSO. The model used here, the Ocean-Land-Atmosphere Model (OLAM), has a grid topology that enables local mesh refinement to any degree without the need for special grid nesting algorithms. Hence, although it is a global model, OLAM allows local mesh refinements in the DYNAMO observing area that enables explicit simulation of cloud systems. This allows both the global context of the MJO as well as local processes on the cloud system scale to be handled seamlessly in one model. We will use OLAM hindcasts of the three MJO events during October-December 2011 to examine the importance of environmental moisture, shear, and the evolution of cloud populations to MJO initiation. We address the following:

• How well does OLAM represent the evolution of atmospheric variables compared to DYNAMO observations? The quadrilateral DYNAMO array provided vertical humidity, wind, and temperature soundings as well as advective tendencies that will be compared to OLAM fields during the three initiation events to determine model fidelity. The ability of OLAM to represent both the MJO and convectively coupled equatorial waves (CCEWs) will be assessed. Further, statistics from the suite of centimeter and millimeter DYNAMO radars, as well as surface flux and wind datasets from ships, buoys, and aircraft, will be used to validate OLAM.

• What Processes Contribute to Tropospheric Moistening in Advance of MJO Initiation in OLAM? A comprehensive analysis of OLAM tropospheric humidity evolution as it relates to MJO initiation and CCEWs will be conducted. The column-integrated moisture budget will be used to assess the importance of vertical and horizontal advection, condensational drying, and surface evaporation to the moistening process in advance of MJO initiation. The role of gustiness due to sub-gridscale motions in affecting surface flux will be assessed. Follow-up mechanism denial experiments (e.g. not allowing surface flux feedbacks) or sensitivity experiments will be conducted to determine MJO initiation sensitivity to various moistening processes.

• How Do Cloud Populations Vary in Advance of MJO Initiation, and How Do These Variations Interact with the Large-Scale Environment and CCEWs to Enable MJO Initiation? How cloud populations evolve in advance of the MJO initiation will be examined with OLAM. We will assess how important shallow convection is for moistening the free troposphere in advance of MJO deep convective initiation, and how changing convective organization due to CCEWs and MCSs affect the moisture tendency due to clouds. We will also examine the hypothesis that both a deep moist layer and substantial lower tropospheric shear are necessary to produce long-lived MCSs that mark the genesis of MJO events. We will document how the gross moist stability of the modeled atmosphere varies with cloud regime. OLAM hindcasts will be compared to hindcast experiments with a conventional parameterized model, to suggest where parameterization improvements might improve simulations of MJO initiation.

This proposal directly addresses the CPO DYNAMO competition by using OLAM to analyze the initiation of the MJO during the DYNAMO time period, specifically by validating OLAM using field campaign data. We are particularly interested in determining the processes that most strongly regulate the moisture budget in advance of MJO initiation, as well as the unique contributions of different cloud regimes to the moistening process. This proposal supports NOAA’s NGSP by helping to improve parameterizations that will allow more accurate predictions of future climate, allowing society to better anticipate and respond to the challenges of climate change. This proposal entails research that advances the nation’s core capabilities in understanding and modeling the climate system, a primary goal of the CPO.

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