Utilizing DYNAMO Observations to Improve the …xfu/NOAA_ESS_Proposal_2013.pdfBin Wang Brian Taylor Yaa-Yin Fong Chair, Department of Dean of SOEST Director of ORS Meteorology (808)

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RESEARCH PROPOSAL SUBMITTED TO NOAA EARTH SYSTEM SCIENCES (ESS), UNDERSTANDING AND IMPROVING PREDICTION OF TROPICAL CONVECTION (DYNAMO)

WITH FUNDING OPPORTUNITY NUMBER AS NOAA‐OAR‐CPO‐2013‐2003445

Utilizing DYNAMO Observations to Improve the Understanding of Madden Julian Oscillation and its Interactions with Tropical Cyclones

Principal Investigators: Joshua Xiouhua Fu (Lead) IPRC, University of Hawaii at Manoa 1680 East West Road, POST Bldg. 401, Honolulu, HI96822 Tel: 808‐956‐2629; Fax: 808‐956‐9425 E‐mail: [email protected]

Jae-Kyung E. Schemm Climate Prediction Center, NCEP/NWS/NOAA 5830 University Research Court, College Park, MD20740 Tel: 301‐683-3392, fax: 301‐683-1557 E‐mail:[email protected] Masaki Satoh Atmosphere and Ocean Research Institute University of Tokyo, 5-1-5 Kashiwanoha Kashiwa-shi, Chiba, 277-8568, Japan E‐mail:[email protected] Budget Period: August 01, 2013 – July 31, 2016 Budget: Year 1 Year 2 Year 3 Total UH $109,338 $114,209 $119,323 $342,870 CPC $47,000 $47,000 $49,000 $143,000 Total $156,338 $161,209 $168,323 $485,870 Endorsements ______________________ ___________________________ __________________________ Bin Wang Brian Taylor Yaa-Yin Fong Chair, Department of Dean of SOEST Director of ORS Meteorology (808) 956-7476 (808) 956-6182 (808) 956-7800 [email protected] [email protected] [email protected]

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Utilizing DYNAMO Observations to Improve the Understanding of Madden-Julian Oscillation and its Interactions with Tropical Cyclones Joshua Xiouhua Fu (Lead PI): IPRC, SOEST, University of Hawaii at Manoa J.-K. E. Schemm (PI): CPC, NCEP/NWS/NOAA; M. Satoh [PI]: AORI/University of Tokyo, Japan Budget Period: Aug. 01, 2013 –Jul. 31, 2016; Total Budget (UH & CPC): $485,870

ABSTRACT

The Madden‐Julian Oscillation (MJO) is the dominant mode of tropical convection variability on an intraseasonal time scale (30-60 days). It manifests as a couplet between a large-scale convective envelope and planetary-scale circulation. When the MJO propagates around the global tropics, the induced large-scale environmental changes strongly modulate tropical cyclone (TC) activity over all TC basins: the Indian Ocean and western Pacific; the Eastern North Pacific; the Gulf of Mexico; and the Atlantic Main Development Region (MDR). The arrival of the MJO active phase increases the probability of TC genesis and rapid intensification 3-4 times more than that during the suppressed phase. The strong modulation of the MJO on TC activity along with its 30-60-day recurrent period offers a golden opportunity for extended-range TC forecasting. Our understanding of the MJO-TC interactions, however, is very limited largely due to the scale separation between the MJO and TC as well as the lack of accurate data, which significantly impedes our progress on the modeling and predication of the MJO and plagues the extended-range TC forecasting with various uncertainties (e.g., false alarms, missing events, and ‘jumpy’ forecasts at different lead times (Fu 2012)). These issues will be addressed in this proposal in three parts. First, we will diagnose the MJO-TC interactions in the latest-generation high-resolution reanalysis (e. g., NCEP-CFSR, ERA-Interim) and state-of-the-art global models (e.g., NCEP GFS/CFSv2, UH, NICAM, and ECMWF models), which will reveal the weaknesses of these models. Second, the in-situ observations from the Dynamics of the Madden-Julian Oscillation (DYNAMO) field campaign will be used to further validate the representation of MJO-TC interactions and pinpoint the misrepresented physical processes in these models. Third, the pathways to improve model representation of MJO-TC interactions will be explored, for example, through numerical experiments, model improvement, and the development of multi-model ensemble. This proposal aims to improve our understanding of the MJO and its interactions with tropical

cyclones and to advance the extended-range TC forecasting capability in national models (NCEP

GFS/CFSv2) by utilizing the in-situ DYNAMO observations. Because the MJO and TC are two

dominant tropical convection systems on intraseasonal and synoptic timescales, respectively, this

study directly contributes to the priority 1 of the FY2013 ESS program “Understanding and

Improving Prediction of Tropical Convection using Results from the DYNAMO Field Campaign”.

The proposed study will address two societal challenges highlighted in NOAA Next Generation

Strategic Plan (NGSP) “Vulnerability of Coasts and their Resilience to Climate Impacts and

Changes in Extremes of Weather and Climate”. This project will help advance two core

capabilities of NOAA NGSP “Understanding and Modeling as well as Predictions and Projections”.

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TABLE OF CONTENTS

1. RESULTS FROM PREVIOUS RESEARCH 2. STATEMENT OF WORK 2.1. Scientific Background 2.2. Objectives and Approaches 2.3. Proposed Methodology 2.3.1. Models and Datasets 2.3.2. Research Tasks Task_1. Diagnosis of MJO-TC Interactions Task_2. Validation of MJO-TC Interactions with DYNAMO Observations Task_3. Pathways to Improve the Representation of MJO-TC Interactions 2.3.3. Work Plan 2.3.4. Personnel and Readiness 2.4. Relevance to the ESS Program and NOAA NGSP 2.5. Benefits to Scientific Community and General Public 2.6. References 3. BUDGET 4. BUDGET EXPLANATION 5. CURRICULUM VITAE 6. CURRENT AND PENDING SUPPORT

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1. RESULTS FROM PREVIOUS RESEARCH

The mechanisms and predictability of the MJO have been extensively investigated by the PI (Dr. Joshua Xiouhua Fu) at University of Hawaii (UH). Using a coupled model developed at UH (hereafter UH model), Fu et al. (2003) and Fu and Wang (2004) demonstrated that air‐sea coupling significantly increases the MJO intensity. Fu et al. (2007) further showed that air‐sea coupling is able to extend the MJO predictability by one week. Fu et al. (2008) used the UH model to carry out experimental MJO forecasts, which targeted a prominent MJO event observed during the TOGA COARE field campaign. They demonstrated that the boundary‐layer moistening by shallow convection detrainment speeds up the otherwise slow eastward propagation of the model MJO to match the observed MJO evolution beyond one month. Fu and Wang (2009) conducted a series of NWP‐type and AMIP‐type experiments to reveal the important role of stratiform rain (i.e., grid‐scale rain) in sustaining a robust MJO in the UH model. Fu and Hsu (2011) demonstrated that when MJO evolutions are well captured, the occurrence of a TC over the northern Indian Ocean can be realistically forecasted with a lead time of two weeks. With NOAA-funded support, we have: i) assessed the MJO prediction skills of NCEP GFS/CFSv2 and UH models during the Dynamics of the Madden-Julian Oscillation (DYNAMO) period; ii) revealed the strengths and weaknesses of these models in the representation of MJO initiation and propagation; and iii) evaluated NCEP reanalysis (i.e., CFSR) with DYNAMO observations. We have given five presentations in different national conferences and are preparing three manuscripts for the planned DYNAMO special issue. The PI (Dr. J.-K. Schemm) at the NCEP has extensive experience with intraseasonal and seasonal forecasts with both statistical and dynamical models. Dr. Schemm is a leading scientist on advancing national seasonal hurricane forecasts with high resolution NCEP CFS CGCM. Since 2009, she has been responsible for dynamic hurricane season prediction at NCEP/CPC utilizing the T382 CFS CGCM (Schemm and Long 2009) and has been providing the dynamic prediction input for the NOAA Hurricane Season Outlook. She has performed preliminary analyses of MJO and Atlantic hurricanes in the T382 CFS coupled model and found the high resolution CFS quite skillful in predicting both of these phenomena. In analyzing the northern hemisphere tropical storms in the T382 CFS, the detection and tracking criteria used in earlier studies (e.g. Camargo and Zebiak 2002) have been adopted to this higher resolution model. The favorable T382 CFS results include not only realistic reproduction of the interannual variability in hurricane activity as a result of ENSO fluctuations, but also of the shift to a more active hurricane era in the middle 1990s. The PI (Prof. M. Satoh) at the University of Tokyo has led the development of the first global cloud-system resolving model-NICAM (Satoh et al. 2008). A series of studies using the NICAM model was carried out by Prof. Satoh’s team to advance our understanding of monsoons, MJO, and tropical cyclones (e.g., Miura et al. 2007; Taniguchi et al. 2010; Satoh et al. 2012). 2. STATEMENT OF WORK 2.1. Scientific Background The Madden‐Julian Oscillation (MJO, Madden and Julian 1971; Wang 2005; Zhang2005) is the most prominent intraseasonal variability in the tropics. The canonical feature of the MJO has

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been depicted as an eastward-propagating couplet between a convective envelope and first-baroclinic large-scale circulation along the equator (Madden and Julian 1972). The convective envelope is composed of multi-scale cloud systems (Nakazawa 1988). As the season evolves, the action centers of the MJO-related convective envelope and circulation migrate north and south. During boreal winter, the MJO action centers shift to the Southern Hemisphere and manifest as a dominant eastward-propagating circum-global mode. On its way eastward, the convective phase of the MJO spawns frequent occurrences of tropical cyclones (TC) over the tropical Indian Ocean (Bessafi and Wheeler 2006; Ho et al. 2006), Australian region, and the South Pacific Convergence Zone (Hall et al. 2001; Chand and Walsh 2010), occasionally over the South China Sea (SCS), and Western North Pacific (WNP). During boreal summer, the MJO action centers shift to the Northern Hemisphere and have a dominant northward-propagating component, particularly over the Indo-western Pacific sector, along with an eastward circum-global component. On its passage, the MJO modulates tropical cyclone activity over the Indian Ocean (Kikuchi et al. 2009), the

SCS/WNP (Liebmann et al. 1994; Nakazawa 2006), the Eastern North Pacific (ENP), the Gulf of Mexico, and the Atlantic MDR (Molinari et al. 1997; Maloney and Hartmann 2000; Mo 2000; Higgins and Shi 2001; Klotzbach 2010). The recurrent nature of the MJO with a period of 30-60-days and its strong modulation of tropical cyclones offer an opportunity for extended-range TC forecasting. Gray (1979) first noticed that the occurrences of tropical cyclones tend to cluster in time and space with 2-3 weeks active period separated by 2-3 weeks quiescent period. Using the global outgoing long-wave radiation (OLR) dataset available for the First GARP Global Experiment (FGGE) year, Nakazawa (1986) discovered that almost all TC geneses and intensifications in this year occurred in the convective phase of the MJO. The composite study of Liebmann et al. (1994) showed that the convective phase of the MJO favors TC occurrences through enhancing large-scale low-level vorticity and convergence as well as generating more eddy disturbances (as potential TC seedlings). With increased observational and reanalysis datasets, subsequent research has revealed the specific features of tropical cyclones that are strongly modulated by the MJO, such as the timing and location of TC genesis, rapid intensification, and trajectory. Aiyyer and Molinari (2008) documented a TC clustering event that occurred over the ENP and the Gulf of Mexico during August-September 1998. They found that the westerly wind bursts associated with the arrival of the MJO increases the vertical shear of the near-equatorial ITCZ over the ENP, shifting TC occurrences to the northern edge of the ITCZ. The MJO-related westerly winds further extend into the Gulf of Mexico and meet with easterly trades. The resultant shear flows produce a large-scale cyclonic vorticity environment and favor the clustering of TCs (Maloney and Hartmann 2000; Kossin et al. 2010). The composite study of Wang and Zhou (2008) found that those TCs moving through the convective phase of the MJO are about three times more likely to experience rapid intensification than those that do not. A recent study by Klotzbach (2012) found that over Atlantic basin the probability of TC rapid intensification is ten times’ greater when the MJO acts to reduce the vertical shear than when the MJO enhances the vertical shear. There are also studies documenting that the trajectories of TCs are significantly modulated by the MJO over the WNP (Chen et al. 2009; Wu et al. 2011) and Atlantic sector (Kossin et al. 2010). Among the studies addressing the modulation of the MJO on TC activity, most of them have a focus on TC genesis; only a few, if any, are on TC rapid intensification and trajectory. The importance of large-scale environment on TC genesis has long been recognized (Gary 1968, 1998). The six most important large-scale environmental variables are: high sea surface

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temperature; large low-level vorticity; high tropospheric humidity; small vertical shear; and distance from the equator. The active and suppressed phases of the MJO significantly modify the large-scale environment and embedded high-frequency disturbances (including equatorial waves). Both the modified environment and high-frequency disturbances act to modulate TC activity. A Genesis Potential Index (GPI), which is defined as a quantity to measure the environmental favorability of TC genesis (Emanuel and Nolan 2004), has been used to assess the impact of the MJO. Using NCEP-NCAR and ERA-40 reanalyses, Camargo et al. (2009) found that the mid-tropospheric humidity and lower-level tropospheric vorticity are the two most important factors through which the MJO modulates the tropical cyclones. Using ERA-Interim reanalysis and long-term simulations from the GFDL HIRAM (Zhao et al. 2009), Jiang et al. (2012) found that low-level cyclonic vorticity, enhanced mid-level relative humidity, and reduced vertical wind shear all contribute to the modulation of TC genesis. The finding of Camargo et al. (2009) is from a global perspective, while the result of Jiang et al. (2012) is limited to the ENP. Some specific processes through which the MJO modulates TC activity over individual basins are discussed here. The Indian Ocean has been viewed as an initiation place for the MJO, largely due to the canonical schematics depicted in Madden and Julian (1972) although recently, some controversial arguments have been made (Matthews 2008; Straub 2012). During boreal winter, the mean ITCZ is close to the equator. When the MJO develops over the Indian Ocean, the large-scale tropospheric humidity is significantly enhanced within the convective envelope. The near-equatorial westerly wind bursts are also enhanced and two cyclonic vorticity strips are formed on both sides of the equator, which evolves into a pair of Rossby-wave-like disturbances (Ferreira et al. 1996). Fueled by the humid environment provided by the MJO, some of these paired cyclonic disturbances eventually develop into twin tropical cyclones (Shen et al. 2012). Similar modulating processes also occur in western Pacific, particularly during El Nino years (Keen 1982; Lander 1990; Schreck and Molinari 2009). During boreal summer the monsoon trough is established at the far north of the equator. The modulation involves the northward-propagating monsoon intraseasonal oscillation (Kikuchi et al. 2009; Kikuchi and Wang 2010; Taniguchi et al. 2010; Fu and Hsu 2011). Over the WNP, once the monsoon trough is established, the shear flows and confluent zone between the monsoon westerly and easterly trades are favorable spots for TC genesis through wave accumulation (Chang and Webster 1990; Holland 1995; Ritchie and Holland 1999; Li et al. 2003; Yoshida and Ishikawa 2012). The arrival of the MJO convective phase will further enhance the monsoon trough and local eddy activity (Maloney and Hartmann 2001a) as well as amplify and contract various incoming equatorial waves (e. g., Mixed-Rossby-Gravity (MRG) waves, Rossby waves, and easterly waves], favoring the formation of tropical cyclones (Aiyyer and Molinari 2003; Frank and Roundy 2006; Schreck et al. 2011; Schreck et al. 2012). The Kelvin waves within the MJO convective envelope also increase the probability of TC genesis in the WNP (Schreck and Molinari 2011). The MJO weakens dramatically once it reaches the central Pacific and quickly moves to the ENP due to the presence of cold tongue in the central and southeast Pacific (Madden and Julian 1972). The MJO convection and circulation re-intensify once upon reaching the ENP and the Gulf of Mexico (Maloney and Esbensen, 2003). The modulation of the MJO on TC in this sector is largely through the interactions with the ITCZ and easterly waves. The westerly wind bursts associated with the MJO enhance the cyclonic vorticity strips in the northern edge of the ITCZ (Aiyyer and

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Molinari 2008) and strengthen the meridional potential vorticity gradient in this region. The baroclinic-barotropic instability is favored in this region due to the enhanced northward decrease of potential vorticity, which forces the ITCZ breakdown and vortex roll-up, thus leading to TC genesis (Molinari et al. 1997; Ferreira and Schubert 1997; Wang and Magnusdottir 2005). The instability and confluent flows between the westerly wind bursts and easterly trades over the ENP and the Gulf of Mexico provide a favorable environment for the amplification of incoming easterly waves and lead to TC genesis (Molinari and Vollaro 2000; Aiyyer and Molinari 2008). Over the Atlantic MDR, significant modulation of the MJO on TC activity is also documented (Mo 2000; Higgins and Shi 2001; Klotzbach 2010) although little, if any, MJO-related convection is observed in this sector. Unlike other basins, the modulation in the Atlantic MDR is largely realized through the remote impact of the MJO (Klotzback 2010; Schreck et al. 2012). It is well recognized that African easterly waves (Thorncroft and Hodges, 2001) are the primary TC precursors in this region (Landsea 1993; Schreck et al. 2012). Dunkerton et al. (2008) suggested that the critical layer of an easterly wave is a sweet spot for TC genesis due to the containment of deep moist convection and cyclonic vorticity aggregation within the critical layer (Montgomery et al., 2006, 2010). The modulation of the MJO on TC activity is primarily through enhanced tropospheric humidity as MJO transitions into fast-moving Kelvin waves (Sobel and Kim 2012; Ventrice et al. 2012), enhanced activity of African easterly waves (Ventrice et al. 2011), and reduced vertical wind shear over the Atlantic MDR when MJO-related convection resides over the African and Indian Ocean sector (Klotzbach 2010). A review of previous studies clearly underlines the need to realistically represent the structure, intensity, and propagation of the MJO in order to capture its modulation of TC activity. With improved representation of the MJO in some state-of-the-art global models (Miura et al. 2007; Bechtold et al. 2008; Fu et al. 2008; Weaver et al. 2011), increasingly successful case studies have shown that as MJO evolutions are well reproduced, useful forecasting skill of TC occurrences can reach beyond one week (Fudeyasu et al. 2008; Vitart 2009; Taniguchi et al. 2010; Fu and Hsu 2011; Satoh et al. 2012; Shen et al. 2012). However, current extended-range TC forecasting still has a variety of uncertainties such as false alarms, missing events, and “jumpy” forecasts at different lead times (Elsberry et al. 2009; Vitart et al. 2010; Belanger et al. 2012). During the DYNAMO field campaign, five MJO events along with about 30 TCs occurred in the tropical Indian Ocean and South Pacific Convergence Zone. In this proposal, we plan to take advantage of the DYNAMO observations to improve the understanding of the MJO and its interactions with tropical cyclones. The expected outcomes of this project are: i) to advance the understanding of MJO-TC interactions; ii) to reveal the possible causes of the uncertainties of extended-range TC forecasting; and iii) to explore the ways to improve extended-range TC forecasting skill. The findings from the proposed study are expected to provide a useful guide to reduce forecasting uncertainties, thereby making extended-range TC forecasting more appropriate for operational applications.

2.2. Objectives and Approaches

Through the collective efforts of the weather and climate communities, significant progress has been

made in recent years on the understanding, modeling and prediction of the MJO (i.e., Lau and Waliser

2011; Wang and Liu 2011; Sobel and Maloney 2012; Benedict et al. 2012). This is a big step forward

on the way to address the grand challenge of seamless prediction, particularly to bridge the gap

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between weather forecast and climate prediction (Brunet et al. 2010; Waliser et al. 2012). The

successful launch of the DYNAMO field campaign collected a lot of precious in-situ data from a

variety of observational platforms. This dataset is ready to be utilized to further advance our

understanding of the MJO and its interactions with tropical cyclones.

In this proposal, we will: i) document the representation of MJO-TC interactions in several state-of-the-art global models; ii) identify the key processes misrepresented on MJO-TC interactions and possible consequences on extended-range TC forecasting; and iii) explore the pathways to improve the representation of MJO-TC interactions and advance extended-range TC forecasting.

The above objectives will be achieved through following steps: 1) Examine the fidelity of MJO-TC interactions in the NCEP GFS/CFSv2, UH, ECMWF, and NICAM global models. 2) Conduct further in-depth diagnosis with several selected MJO-TC interaction cases during DYNAMO period and validations of global and regional models with DYNAMO observations. 3) Carry out numerical experiments to examine the modulating processes of the MJO on TC activity over individual TC basins. 4) Explore the possible avenues to improve the representation of MJO-TC interactions and to advance the capability of extended-range TC forecasting. 2.3. Proposed Methodology 2.3.1. Models and Datasets NCEP GFS/CFSv2: The coupled atmosphere‐ocean model used in the NCEP Climate Forecast

System version 2 is similar to that used for the CFSR (Saha et al. 2010) with a resolution of

T126 for the atmospheric component, which is the 2009 version of the NCEP Global Forecast System

(GFS). The oceanic component is the GFDL Modular Ocean Model version 4 (MOM4), which

includes a built‐in interactive sea ice component. The CFSv2 reforecasts were initialized from the

CFSR. Real‐time outputs from the GFS/CFSv2 have been used for the NOAA weekly/seasonal global

hazards (including TC) and climate outlooks.

UH: The University of Hawaii Coupled Model combines the ECHAM4 AGCM and UH

intermediate ocean model (Fu et al. 2003). The ECHAM4 AGCM was developed at

Max‐Planck‐Institute for Meteorology of Germany and documented in detail by Roeckner et al.

(1996). The UH intermediate ocean model (Wang et al. 1995) is a tropical upper ocean model with

intermediate complexity that has comprehensive mixed‐layer physics and upper ocean dynamics. This

coupled model simulates the MJO in both boreal winter (Fu and Wang 2004) and boreal summer well

(Fu et al. 2003). The potential predictability of the MJO in the UH model is beyond one month (Fu et

al. 2007). The UH model has shown useful MJO prediction skill beyond two weeks (Fu et al. 2008,

2009, 2011).

NICAM/ECMWF: The NICAM is the first global cloud-system resolving model without using cumulus parameterization, which was developed at the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and the University of Tokyo (Satoh et al. 2008). Its horizontal grid interval is approximately 7 km. There are 40 vertical levels from the surface up to 38 km and the vertical interval increases from 160 m to 2.9 km with height. The NICAM has shown very

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impressive capability in reproducing the MJO and tropical cyclones (Satoh et al. 2012). The ECMWF is a coupled system (Vitart et al. 2008) with the ECMWF Integrated Forecast System (IFS) known as cycle 36r2 (operational in 2011) as its atmospheric component, which has a horizontal resolution of T639 (about 30 km); its ocean component is a general circulation model called the Hamburg Ocean Primitive Equation (HOPE; Wolff et al. 1997). The ECMWF is one of the best operational systems for the forecasting of the MJO and tropical cyclones (Vitart 2009; Vitart et al. 2010).

HWRF: The Hurricane WRF is NCEP operational hurricane forecast model (Gopalakrishnan et al. 2011). The HWRF is a non-hydrostatic regional model with movable two-way nested vortex capability. It is also coupled to Princeton Ocean Model (POM). Model physics are adopted from the advanced physics packages of NCEP GFS and GFDL models. The HWRF will be used in this proposal to conduct the case study for downscaling MJO-TC interactions.

DATASETS: The datasets that will be used in this study include: 1) observations collected during DYNAMO field campaigns from October 2011 to March 2012; 2) latest-generation NOAA/NCEP reanalysis (the CFSR) for past 29 years (1982‐2010) and its real‐time extension starting from 2011; 3) Global Tropical Cyclone best track data (Knapp et al. 2010); and 4) other observations including precipitation from CMORPH, SST from TMI, and OLR from NOAA NESDIS; 5) the hindcasts of NCEP GFS/CFSv2, UH, and ECMWF (15/45‐day integrations every day (or week) during 2008‐2012) and real‐time forecasts; and 6) the NICAM hindcasts during CINDY/DYNAMO period and 8-year (2001-2002, 2004-2009) simulations from the Athena project. 2.3.2. Research Tasks The overarching goal of this project is to improve the understanding of MJO-TC interactions and to advance extended-range TC forecasting. In order to achieve this goal, we will first document MJO-TC interactions in the CFSR, GFS/CFSv2, UH, NICAM and ECMWF models. A detailed case study focusing on MJO-TC interactions during DYNAMO period will follow. The feasibility of regional model (i.e., HWRF) downscaling to improve the representation of MJO-TC interactions will be examined. The validation from global and regional models with DYNAMO observations is expected to expose specific model weaknesses. Further numerical experiments will be performed to examine the modulating processes of the MJO on TC activity over individual TC basins such as the Indian Ocean, WNP, ENP, Gulf of Mexico, and Atlantic MDR. The aforementioned diagnostics and modeling efforts will pave the way for the improved representation of MJO-TC interactions in these models, eventually leading to advanced extended-range TC forecasting. Task_1. Diagnosis of MJO-TC Interactions In the seminal paper of Madden and Julian (1972), the MJO has been depicted as an equatorial eastward-propagating couplet between a large-scale deep convection and first-baroclinic planetary-scale circulation. Largely motivated by this classical picture, a simple MJO index is developed by Wheeler and Hendon (2004) with the first two EOF modes of 15oS-15oN averaged OLR and 850-hPa/200-hPa zonal winds. This so-called Wheeler-Hendon Real-time Multivariate MJO (RMM) index has been recommended by the WCRP/WWRP MJO Task Force as a standard measure of MJO forecasting skill (Lin et al. 2008; Gottschalck et al. 2010). Although this index

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explains only about 50% of the total variance of tropical intraseasonal variability and does not necessarily capture all important processes through which the MJO modulates TC activity, we plan to use this simple index as a first step to examine MJO-TC interactions in the CFSR and in the aforementioned models, to make our results comparable with previous studies (Camargo et al. 2009; Vitart 2009; Satoh et al. 2012). For this project, we will focus on the period from 2008 to 2012. The first three years overlap with the Year of Tropical Convection (Waliser et al. 2012) and Asian Monsoon Years (Wang et al. 2008). Both international programs aimed to improve the understanding and prediction of intraseasonal variability and tropical cyclones. The last two years cover the DYNAMO field campaign period (Zhang 2012, DYNAMO summary). The composite MJO-TC relationships for the observations and the models during these five years will be developed. The composite strategy will be the same as that used in Vitart (2009) and Satoh et al. (2012). First, the observed OLR and 850-hPa/200-hPa zonal winds from the CFSR will be used to construct the observed RMM index. Based on the RMM index, the circum-global MJO events can be divided into eight phases. Composite, then, will be carried out to document the tropical cyclone activity at each MJO phase for individual TC basins. This effort will establish a statistical, yet observationally-based, MJO-TC relationship for each TC basin. A similar procedure will be used to establish the MJO-TC relationships in the models. The hindcasts from 1998 to 2012 generated with these models will be used to achieve this goal. Inter-comparisons among model results and the observations will reveal the strengths and weaknesses of individual models over given TC basins. The above composite approach offers a useful statistical measure of the models’ gross representation of MJO-TC interactions, but won’t reveal to what degree the modulating processes have been realistically represented in the models. Further analyses have been proposed to address this issue. Previous studies have indicated that the large-scale variables that comprise the GPI are the major environmental parameters through which the MJO modulates TC activity, not necessarily the three variables used to define Wheeler-Hendon index. In this section, we will directly assess the intraseasonal forecasting skills of the GPI and its component variables (e.g., mid-tropospheric humidity and lower-level vorticity) in the models. To effectively extract intraseasonal variability from the hindcasts, long-term observations will be added before the hindcasts and zeroes will be padded after the hindcasts. Then, band-pass filtering will be applied to the extended time series. The effectiveness of this approach in extracting intraseasonal variability has been demonstrated by Wheeler and Weickmann (2001) and Fu et al. (2011). The spatial pattern correlations between the observed anomaly and forecasted anomaly will be assessed to measure the skills of the GPI and its components. Inter-comparisons of the MJO skills measured with the RMM index and that with the GPI and its components will reveal in what degree the simple RMM index captures the MJO modulating processes on TC activity. Another important question regarding MJO-TC interactions is, will improved MJO forecasting lead to advanced extended-range TC forecasting? In order to answer this question, intraseasonal TC forecasting skill will be assessed with the method used in Vitart et al. (2010). The relationships between the MJO skills measured with different metrics and TC skills will be examined. This assessment will be conducted for the global tropics and individual TC basins. We will further explore to what degree the model flaws in representing the MJO can be connected to extended-range TC forecasting problems: such as false alarms, missing events, and “jumpy” forecasts.

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Task_2. Validation of MJO-TC Interactions with DYNAMO Observations

The DYNAMO field campaign (details about this program can be found at http://www.eol. ucar.edu/projects/dynamo) has deployed cloud and precipitation radars, air‐sea flux and aircraft instruments and also launched soundings at the DYNAMO southern and northern arrays near Gan island (0.7oS, 73.2oE) and surrounding areas (Zhang 2012, DYNAMO summary). The entire six‐month field campaign is divided into three periods: i) Special Observing Period (SOP) from 1 October 2011 to 9 November 2011; ii) Intensive Observing Period (IOP) from 10 November 2011 to 15 January 2012; and iii) Extended Observing Period (EOP) from 16 January 2012 to 31 March 2012. In the SOP, all aforementioned instruments operated with soundings launched every three hours. In the IOP, the same observations were carried out except with reduced soundings every six hours. In the EOP, only cloud and precipitation radars and a sounding every 6 hours were available at Gan Island. Some preliminary analyses of in-situ observations can be found online (e.g.: LASP DYNAMO Meeting, http://www.eol.ucar.edu/ projects/dynamo/meetings/2012/jul/index.html and DYNAMO/AMIE Radar Workshop, http:// www.eol.ucar.edu/projects/dynamo/meetings/2012/aug/).

During the entire six-month DYNAMO field campaign, five MJO events developed over the Indian Ocean (Figure 1) and about 30 tropical cyclones formed in Indo-Southern Pacific sector. Each MJO event has its own uniqueness. Their forecasting skills along with associated extended-range TC forecasting skills will be examined in detail. During the IOP of the DYNAMO field campaign, one very interesting MJO-TC interaction case is observed: the near-equatorial tropical cyclogenesis (named as “TC05A” by JTWC) around November 26 associated with the November MJO. Because this event was well observed by in-situ instruments of the DYNAMO array, several observational studies have been focused on this event (e.g., the presentation of Jim Moum at: http://www.eol.ucar.edu/projects/dynamo/meetings/2012/jul/index.html). We propose to carry out a detailed modeling study of this event and validate models with the DYNAMO observations. This effort will advance our understanding of MJO-TC interactions and has the potential to improve extended-range TC forecasting. Figure 2 shows the satellite image and low-level winds on November 23, 2011, which is about three days before the genesis of TC05A. The active convection of the November MJO develops in the tropical Indian Ocean along with enhanced tropospheric humidity. The MJO-associated westerly wind bursts directly blow over the DYNAMO array and three cyclonic Rossby-wave-like vortices are generated near the equator. The paired vortices west of the array mimic the classical picture of pre-staging twin tropical cyclones (Ferreira et al. 1996; Shen et al. 2012). The vortex just east of the array is likely caused by the shear flows between the near-equatorial westerly and strong easterly around 10oN. To what degree these flows are part of the MJO will be addressed in our research. After three days, the paired vortices west of the array weaken significantly and eventually decay, while the one east of the array intensifies into the tropical cyclone-TC05A near the southern tip of the Indian peninsula and move northwest into the Arabian Sea.

Two-stage validations are planned for this specific event. First-stage validation will focus on the global

models’ capability to reproduce the large-scale environmental evolutions of the November MJO.

Second-stage validation will focus on the regional model’s capability to capture the genesis, intensity

changes, and trajectory of TC05A. Both CFSR and DYNAMO observations will be used in these validations. For global models, the sequences of tropospheric moistening, development of westerly wind bursts, generation of three vortices, and formation of TC05A will be examined with

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daily hindcasts at different lead times. In-situ DYNAMO observations will be used to validate the air-sea coupling processes and vertical structures of the modeled November MJO. Preliminary analysis of the UH hindcasts (Fu et al. 2012; https://ams.confex.com/ams/30Hurricane/ webprogram/Paper205971. html) indicated that the genesis of TC05A can be forecasted with some confidence for a lead time of at least one week. At the same time, the southern vortex also tends to grow into a tropical cyclone in the model. The proposed validation is expected to reveal the misrepresented processes that lead to this false alarm. Regional model downscaling will be further carried out to examine the impact of large-scale circulation on this false alarm. The arrival of so-called “MJO front” on November 24, 2011 over the array (Jim Moun 2012, Overview of Revelle Observations) and the formation of TC05A along with its northward movement have been well captured by DYNAMO northern array, NOAA aircraft P3 instruments/dropsondes and French Falcon aircraft (Zhang 2012, DYNAMO summary). These DYNAMO observations will be used to validate the ultra-high-resolution (~1km) regional model downscaling with the HWRF. The CFSR will be used as lateral-boundary constraints for the regional model. The proposed validation will focus on the evolutions of the MJO front, the initiation of seedling vortex of TC05A, the air-sea fluxes, the intensification of the vortex and its movement. This regional model downscaling and validation exercise will definitely deepen our understanding of the MJO-TC interactions and provide insights to improve its representation in both global and regional models. This effort will also lead to the development of a global-regional nested system that is not only able to provide extended-range TC occurrence probability forecasting (experimental result is available at: http://iprc.soest.hawaii.edu/users/xfu /TC_fcst/TC.html), but also has the potential to offer early warning information on TC intensity and tracks. Task_3. Pathways to Improve the Representation of MJO-TC Interactions In order to improve the representation of MJO-TC interactions and to advance the extended-range TC forecasting capability, three avenues will be explored in this section: i) well-designed numerical experiments will be carried out to test the MJO modulating processes on TC activity over individual TC basins; ii) attempts will be made to improve the representation of MJO-TC interactions in NCEP GFS/CFSV2 and UH models; iii) the impact of the multi-model ensemble on extended-range TC forecasting will be explored. In addition to the case of TC05A, which was observed during the DYNAMO IOP, more TC cases will be selected to test the models’ representation of the MJO modulating processes over individual TC basins. The case selections will consider typical MJO modulating scenarios in different regions: twin tropical cyclones over the Indian Ocean; TC genesis from an enhanced monsoon trough by the MJO over the WNP; TC clustering over the ENP and Gulf of Mexico associated with the arrival of westerly wind bursts of the MJO; TC genesis over the Atlantic MDR associated with the reduced vertical shear and enhanced easterly wave activity by the MJO. Hurricane ‘Sandy’ (Oct 22-29, 2012 over Atlantic basin) will be selected as a special case due to the drastic damage caused by its landfall and interactions with a mid-latitude cyclone over the northeast coast. For each selected case, a hierarchy of evaluations of model performances will be conducted: from the large-scale environmental changes of the MJO (such as the tropospheric humidity, westerly wind bursts, and vertical shear et al.) to the regional/local changes of cyclonic vorticity strips in the Indian Ocean, incoming equatorial waves in the WNP, meridional potential

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vorticity gradient in the ENP and Gulf of Mexico, and easterly waves in the Atlantic MDR. Then, reforecasts will be carried out with modified initial conditions that filter out the environmental modulations of the MJO. The filtering procedure will follow that used by Wheeler and Kiladis (1999), Roundy and Frank (2004), and Frank and Roundy (2006). The resultant impact on TC forecasting after excluding MJO signals in the initial conditions will directly measure the modulating effect of the MJO. The hierarchy evaluations along with the subsequent numerical experiments directly assess the role of the MJO on modulating TC activity and the models’ capability in representing these modulating processes. With decades of adventures in MJO modeling, it is found that a better MJO simulation can be achieved in several ways: by making the occurrence of deep convection harder in the model through imposing a stringent trigger; making the entrainment rate more sensitive to environmental humidity or the rain re-evaporation rate larger (Tokioka et al. 1988; Wang and Schlesinger 1999; Maloney and Hartmann 2001b; Kim et al. 2012), or by explicitly representing organized Meso-scale Convective Systems (MCS) (e.g., Randall et al. 2003; Miura et al. 2007) or mimicking the role of the MCS by better partitioning of stratiform/convective rainfall (Tompkins and Jung 2003; Fu and Wang 2009; Seo and Wang 2011). However, our understanding of the numerical processes that govern TC occurrence in global general circulation models is very poor due to limited research. Currently, there are two studies that touch upon this topic. Zhao et al. (2012) found that the global number of TCs in the GFDL HIRAM is very sensitive to the entrainment rate and horizontal mixing. Stronger horizontal mixing systematically leads to more TCs in the model. Increasing entrainment rate results in an initial shape increase of TCs and then a decrease. On the other hand, Kim et al. (2012) found that in NASA GISS model increasing entrainment rate intensifies the model MJO but reduces global TC number; increasing the rain re-evaporation rate enhances the MJO and also increases TC number in the model. The sensitivity of TC activity to cumulus parameters has never been documented for NCEP GFS/CFSv2 and UH models. We propose to carry out a series of sensitive experiments with these models to improve our understanding of the impact of important model parameters (e.g., entrainment/detrainment rate, rain re-evaporation rate, and horizontal mixing) on the MJO-TC interactions in the models. The findings from these sensitivity experiments will provide insights and clues to further improve the misrepresented physical processes identified from the above diagnostics and modeling studies. It is also well known that improving dynamical models takes very long cycles and needs community-wide collective efforts (Jakob, 2010). The process-oriented studies with DYNAMO observations (such as those presented in LASP DYNAMO Meeting and DYNAMO/AMIE Radar Workshop) are expected to improve our understanding of the MJO and TC or tropical convection on the process level, eventually leading to more physically-based parameterizations of cumulus convection, clouds, and air-sea fluxes. Combining the lessons learned from our proposed diagnosis and modeling studies with the new developments from the process-oriented studies, improved representation of MJO-TC interactions in the aforementioned models can be achieved. At the same time, we propose to take advantage of the available hindcasts from the aforementioned models (e.g., NCEP GFS/CFSv2, UH, NICAM, and ECMWF) and explore the possibility of improving extended-range TC forecasting with the development of multi-model ensemble (Krishnamurti et al. 1999). 2.3.3. Work Plan

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Year one (01 August 2013 – 31 July 2014): (1) document MJO modulation of tropical cyclones with Wheeler-Hendon index in the CFSR and hindcasts from the GFS/CFSv2, UH, NICAM, ECMWF (CPC/UH/UT); (2) test the sensitivity of MJO-TC interactions to cumulus parameters in UH, GFS/CFSv2 models (UH/CPC); (3) conduct inter‐model comparisons with results from the CFSR, CFSv2, UH, NICAM, and ECMWF (UH/CPC); (4) write and submit manuscripts to peer‐reviewed journals (UH/CPC/UT). Year two (01 August 2014 – 31 July 2015): (1) document the skill relationships between MJO prediction and extended-range TC forecasting for the models (UH/CPC/UT); (2) validate global models’ representation of MJO-TC interactions with the CFSR and DYNAMO/CINDY observations with a focus on the November MJO and TC05A (UH/CPC/UT); (3) conduct regional-model downscaling for the genesis, intensity change, and track of TC05A and the false alarm case of the southern vortex (UH); and (4) write and submit manuscripts to peer‐reviewed journals (UH/CPC/UT). Year three (01 August 2015 – 31 July 2016): (1) carry out more detailed analyses on the relationships between the flaws of model MJO and uncertainties in extended-range TC forecasting (UH/CPC/UT); (2) conduct detailed evaluations of selected MJO-TC interaction cases for individual TC basins (CPC/UH/UT); (3) conduct numerical experiments with MJO signals excluded from initial conditions (UH/UT/CPC); (4) test the impact of a multi-model ensemble on extended-range TC forecasting (UH/CPC); and (5) write and submit manuscripts to peer‐reviewed journals (CPC/UT/UH). 2.3.4. Personnel and Readiness All three PIs of this proposal have comprehensive knowledge and demonstrated expertise in carrying out diagnostic, modeling, and prediction studies of the MJO and tropical cyclones. Dr. Jae-Kyung E. Schemm carried out seasonal TC forecasting with NCEP coupled models (CFSv1/CFSV2) for years and will be able to conduct the proposed numerical experiments. Dr. Masaki Satoh led the development of the first global cloud-system resolving model, NICAM, and conducted numerous studies to improve the understanding of the MJO and TC using NICAM. Dr. Joshua Xiouhua Fu developed the UH model (ECHAM4 plus UH intermediate ocean coupled model) and used this model to conduct modeling and prediction studies of the MJO and TC. 2.4. Relevance to the ESS Program and NOAA NGSP This project directly responds to the priority 1 of FY2013 ESS program “Understanding and

Improving Prediction of Tropical Convection”. The proposed study will: i) utilize

DYNAMO/CINDY observations and the CFSR to advance the understanding of the MJO-TC

interactions (the MJO and TC are two dominant tropical convection variabilities on intraseasonal

and synoptic timescales, respectively); ii) identify the key processes misrepresented in the NCEP

GFS/CFSv2 models that account for the uncertainties in extended-range TC forecasting; iii)

explore the pathways to improve the representation of MJO-TC interactions and advance the

extended-range TC forecasting. The proposed study will address two societal challenges

highlighted in NOAA Next Generation Strategic Plan (NGSP) “Vulnerability of Coasts and their

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Resilience to Climate Impacts and Changes in Extremes of Weather and Climate”. The successful

completion of this project will help advance two core capabilities of NOAA NGSP “Understanding

and Modeling as well as Predictions and Projections” and contribute to the economic and societal

well‐being of the Nation.

2.5. Benefits to Scientific Community and General Public This research will help enhance our understanding of the MJO-TC interactions and identify causes of the errors in the representation of the MJO-TC interactions in state-of-the-art global climate models. Our results will provide an assessment of the capability of the NCEP operational weather/climate forecast models and possible ways to improve them for better operational intraseasonal MJO and extended-range TC forecasts for the public. 2.6. References

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Achuthavarier, D., Manganello, J., Cash, B., Jung, T., Palmer, T., and Wedi, N., 2012: The

Intra-Seasonal Oscillation and its control of tropical cyclones simulated by high-resolution

global atmospheric models. Clim. Dyn., in press.

19

Schemm, J. and L. Long, 2009: Dynamic Hurricane Season Prediction Experiment with the NCEP CFS. Workshop on High Resolution Climate Modeling, Trieste, ICTP, Italy.

Schreck, C. J. and J. Molinari, 2009: A case study of an outbreak of twin tropical cyclones. Mon. Wea.

Rev., 137, 863-875.

Schreck, C. J., and Molinari, 2011: Tropical cyclogenesis associated with Kelvin waves and the

Madden-Julian oscillation. Mon. Wea. Rev., 139, 2723-2734.

Schreck, C. J., J. Molinari, and K. I. Mohr, 2011: Attributing tropical cyclogenesis to equatorial waves

in the western North Pacific. J. Atmos. Sci., 68, 195-209.

Schreck, C. J., J. Molinari, and A. Aiyyer, 2012: A global view of equatorial waves and tropical

cyclogenesis. Mon. Wea. Rev., 140, 774-788.

Seo, K.-H., and W. Wang, 2011: The Madden-Julian Oscillation simulated in the NCEP climate

forecast system model: The importance of stratiform heating. J. Climate, in press

Shen, B.-W., W.-K. Tao, Y.-L. Lin, and A. Laing, 2012: Genesis of twin tropical cyclones as revealed

by a global mesoscale model: The role of mixed-Rossby gravity waves. J. Geophys. Res., 117,

D13114, doi:10.1029/2012JD017450.

Sobel, A. H., and D. Kim, 2012: The MJO-Kelvin wave transition. Geophys. Res. Lett., in press.

Sobel, A. H., and E. D. Maloney, 2012: Moisture modes and the eastward propagation of the MJO. J.

Atmos. Sci., in press.

Straub, K. H., 2012: MJO initiation in the realtime multivariate MJO index. J. Climate, in press.

Taniguchi, H., W. Yanase, and M. Satoh, 2010: Ensemble simulation of cyclone Nargis by a Global

Cloud-system-resolving model: modulation of cyclogenesis by the Madden-Julian Oscillation.

J. Meteor. Soc. Japan, 88, 571-591.

Tokioka, T., K. Yamazaki, A. Kitoh, and T. Ose, 1988: The equatorial 30‐60‐day oscillation and the

Arakawa‐Schubert penetrative cumulus parameterization. J. Meteor. Soc. Japan, 66,

883‐901.

Tompkins, A., and T. Jung, 2003: Influence of process interactions on MJO-like convective structures

in the IFS model. The ECMWF/CLIVAR Workshop on “Simulation and Prediction of Intra-

Seasonal Variability with emphasis on the MJO”, Nov. 3-6, 2003.

Thorncroft, C., and K. Hodges, 2001: African easterly wave variability and its relationship to Atlantic

tropical cyclone activity. J. Climate, 14, 1166-1179.

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2722.

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environmental conditions for Atlantic tropical cyclogenesis. Mon. Wea. Rev., 140, 2198-2214.

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F. Molteni, and T. N. Palmer, 2008: The new VarEPS-monthly forecasting system: A first step

towards seamless prediction. Quart. J. Roy. Meteor. Soc., 134, 1789-1799.

Vitart, F., 2009: Impact of the Madden-Julian Oscillation on tropical storms and risk of landfall in the

ECMWF forecast system. Geophys. Res. Lett., 36, L15802, doi:10.1029/2009GL039089.

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weekly tropical cyclone activity in the Southern Hemisphere. Mon. Wea. Rev., 138, 3671-3682.

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Highlights. Bull. Am. Met. Soc., 93, DOI:10.1175/2011BAMS3095.1.

20

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006-0238-z.

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NCEP Climate Forecast System. J. Climate, 24, 4676-4694.

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and temperature in the wavenumber-frequency domain. J. Atmos. Sci., 56, 374-399.

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coherent synoptic to intraseasonal tropical variability. Mon. Wea. Rev., 129, 2677-2694.

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frequency on parameters in a GCM. J. Atmos. Sci., 69, 2272-2283.

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Figure 1. Hovemoller diagram of observed OLR anomalies averaged between 10oS and 10oN (Shading, unit: W m-2) along with MJO, Kelvin and Rossby waves (Contours, only -10 and 10 W m-2 lines are drawn).

Figure 2. (upper panel) Infrared satellite image, and (lower panel) analyzed low-level wind vectors and relative humidity (RH) on November 23, 2011. The box in the lower panel represents the DYNAMO array (Courtesy of MJO-Conversation).

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3. BUDGET

UH Portion:

Year 1 01 August 2013 – 31 July 2014 Year 2 01 August 2014 – 31 July 2015

Year 3 01 August 2015 – 31 July 2016

A. Salaries and Wages

1. Senior Personnel

Year 1 Year 2 Year 3 Total

X. Fu (3 mon/yr) 24,300 25,515 26,791 76,606

2. Post‐doc (12 mon/yr) 52,000 54,600 57,330 163,930

B. Fringe Benefits (36.68% for XF) 8,913 9,359 9,827 28,099 C. Travel 4,000 4,000 4,000 12,000 D. Publication 4,000 4,000 4,000 12,000 E. Computer Service 1,000 1,000 1,000 3,000 Total Direct Costs 94,213 98,474 102,948 295,635

Indirect Costs (36.7 %) 15,125 15,735 16,375 47,235

Total Costs 109,338 114,209 119,323 342,870

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CPC Portion: (For purposes of this budget the years are August through July of the following year.)

Year 2013 2014 2015 Total

Salaries and Overhead

Schemm (1 mo/yr) N/C N/C N/C

Contract Support Scientist (4 mo/yr) $38.0K $40.0K $42.0K $120.0K

Equipment

Workstation $0.0K $0.0K $0.0K

Peripherals $2.0K $0.0K $0.0K $2.0K

Supplies and

Data Costs $1.0K $1.0K $1.0K $3.0K

Travel $4.0K $4.0K $4.0K $12.0K

Publications $2.0K $2.0K $2.0K $6.0K

TOTALS $47.0K $47.0K $49.0K $143.0K

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4. BUDGET EXPLANATION

UH Portion:

Personnel: 3‐month/yr salary is requested for the PI. A 5% inflation rate is assumed. Computation of fringe benefit is based on 36.68% for the PI.

Travel: The budget is based on an estimate of one domestic trip per year for the PI ($2000) and the post‐doc ($2000) to attend scientific meetings relevant to this research project. Other direct costs: The post‐doctoral researcher will receive training on this project for three years. The post‐doc’s stipends are projected to increase 5% per year. The post‐doc will be trained in diagnosis and numerical modeling. The publication cost is based on estimation of about 35 pages published in refereed journals at a page charge of $120, plus a few color figures. Computer services include the charges for accessing SOEST Research Computing Facility and IPRC supercomputers and printers. Indirect costs: The University of Hawaii charges indirect costs at a rate of 36.7% of the total modified direct costs6 .

CPC Portion:

Personnel: Dr. J. Schemm is a federal employee and is supported by the CPC base. She will make an in-kind contribution of 1 month per year on the project. She will oversee the NCEP CFS/GFS forecast analysis and data transfer, and will be available for overall research activity consultation. Travel: The budget is based on an estimate of one domestic trip per year ( $ 2 0 0 0 ) for the PI and support staff to attend scientific meetings relevant to this research project. Other direct costs: 4 m o n t h s a l a r y o f a s u p p o r t s t a f f i s r e q u e s t e d f o r e a c h y e a r . Salaries include an overhead and benefits factor of 1.8 for contractor support. The stipends are projected to increase 5% per year. Support is also being sought for disk space for data storage, page costs for 1 publication/year.

6 The modified direct costs do not include post‐doc stipends and computer service charges

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5. CURRICULUM VITAE

5.1. PI: Dr. Joshua Xiouhua Fu, Associate Researcher IPRC, SOEST, University of Hawaii 1680 East West Road, POST Bldg. 401, Honolulu, Hawaii96822 Tel: 808‐956‐2629; Fax: 808‐956‐9425 E‐mail: [email protected] Education: Ph. D., Meteorology, Department of Meteorology, University of Hawaii, 1998 M. S., Atmospheric Physics, Chinese Academy Sciences, 1988 B. S., Meteorology, Chengdu Meteorological College, 1985

Employment (1999­present): Associate Researcher, IPRC, University of Hawaii, Jan. 2006‐present Assistant Researcher, IPRC, University of Hawaii, Jul. 2002‐Dec. 2005 Research Associate, IPRC, University of Hawaii, Oct.1999‐Jun. 2002 Postdoctoral Fellow, Wyrtki Center, University of Hawaii, Jan.1999‐Oct.1999 Research interests: Intraseasonal‐to‐Interannual Climate Variability Climate Modeling and Prediction Ocean‐Atmosphere Interaction Development and Improvement of Climate Model Synergistic activity: Referee for more than 14 national and international journals; proposal reviewer for

NSF, NOAA, and NASA.

Member of YOTC MJO Task Force: WCRP­CLIVAR/WWRP­THORPEX Year of Tropical Convection (YOTC) 2009­ Member of US CLIVAR PPAI Panel: US CLIVAR Predictability, Prediction, and Application Interface (PPAI) 2010­ Member of USCLIVAR Extreme Working Group, 2012­ Selected publications: Fu, X., and P. Hsu, 2011: Extended‐range ensemble forecasting of tropical cyclogenesis in

the northern Indian Ocean: Modulation of Madden-Julian Oscillation. Geophys. Res. Lett., 38, L15803, doi:10.1029/2011GL048249.

Fu X., B. Wang, J‐Y Lee, W. Wang, and L. Gao, 2010: Se n si t i v i t y o f dyn a mi ca l i n t ra se a so n a l pre di ct i on ski l l s t o d i f f e re n t initial conditions. Mon. Wea. Rev., 139, 2572-2592.

Tao, L., X. Fu, and B. Wang, 2009: The moisture structure of ISO in western North Pacific revealed by AIRS. Acta Meteorologica Sinica, 23, 191‐205.

Fu, X., and B. Wang, 2009: Critical role of stratiform rainfall in sustaining the Madden‐Julian Oscillation: GCM experiments. J. Climate, 22, 3939‐3959.

26

Tao, L., X. Fu, and W. S. Lu, 2009: Moisture structure of quasi‐biweekly mode revealed by AIRS in western Pacific. Adv. Atmos. Sci., 26, 513‐522.

Yang, B., X. Fu, and B. Wang, 2009: Atmosphere‐ocean conditions jointly guide convection of the boreal‐summer intraseasonal oscillation: Satellite observations. J. Geophys. Res.­Atmos., 113, D11105.

Fu, X., B. Wang, Q. Bao, P. Liu, and B. Yang, 2008: Experimental dynamical forecast of an MJO event observed during TOGA‐COARE period. AOSL, 1, 24‐28.

Fu, X., B. Yang, Q. Bao, and B. Wang, 2008: Sea surface temperature feedback extends the predictability of tropical intraseasonal oscillation. Mon. Wea. Rev., 136, 577‐597.

Fu, X., B. Wang, D. E. Waliser, and L. Tao, 2007: Impact of atmosphere‐ocean coupling on the predictability of monsoon intraseasonal oscillations. J. Atmos. Sci., 64, 157‐174.

Fu, X., B. Wang, and L. Tao, 2006: Satellite data reveal the 3‐D moisture structure of tropical intraseasonal oscillation and its coupling with underlying ocean. Geophys. Res. Lett., 33, L03705, doi:10.1029/2005GL025074.

Fu, X., and B. Wang, 2004: The boreal‐summer intraseasonal oscillations simulated in a hybrid coupled atmosphere‐ocean model. Mon. Wea. Rev., 132, 2628‐2649.

Fu, X. and B. Wang, 2004: Differences of boreal‐summer intraseasonal oscillations simulated in an atmosphere‐ocean coupled model and an atmosphere‐only model. J. Climate, 17, 1263‐1271

Fu, X., B. Wang, T. Li, and J. McCreary, 2003: Coupling between northward propagating intraseasonal oscillation and sea surface temperature in the Indian Ocean. J. Atmos. Sci., 60, 1733‐1753

Fu, X. and B. Wang, 2003: Influences of continental monsoons and air‐sea coupling on the climate of the equatorial Pacific. J. Climate, 16, 3132‐3152

27

5.2. PI: Dr. Jae-Kyung E. Schemm, Research Meteorologist Current Position: Research Meteorologist, Development Branch, CPC/NCEP/NWS/NOAA

EDUCATION: B.S. Meteorology, 1969 Seoul National University, Seoul, Korea M.S. Meteorology, 1972 University of Wisconsin, Madison, Wisconsin Ph.D. Meteorology, 1981 University of Maryland, College Park, Maryland

Employment: 1993 to present: Research Meteorologist, Development Branch, Climate Prediction Center, NCEP/NWS/NOAA 1991 to 1993: Senior Scientific Analyst, General Science Corporation. Data Assimilation Office, GLA/GSFC/NASA 1986 to 1993: Scientific Analyst, Centel Federal Services Corporation Global Modeling and Simulation Branch, GLA/GSFC/NASA 1985 to 1986: Research Associate, Department of Meteorology, University of Maryland, College Park, MD 1981 to 1984: Research Associate, Institute for Physical Sciences and Technology, University of Maryland, College Park, MD

Recent Awards: US Dept. of Commerce Bronze Medal, 2000 US Dept. of Commerce Gold Medal, 2005

Community Services: APEC Climate Center NWS Focal Point and Working Group Member, 2001 – present NAME Project of WCRP-CLIVAR/VAMOS and GEWEX, Member of Science Working Group, 2001 - 2008 US CLIVAR, Member of Science Working Group on Extremes, 2010 – present

Recent Publications:

Schemm, J., L. Long, 2009: Dynamic hurricane season prediction experiment with the NCEP CFS. Workshop on High Resolution Climate Modeling, Trieste, ICTP, Italy.

Bell, G., E. Blake, S. Goldenberg, T. Kimberlain, C. Landsea, R. Pasch and J. Schemm 2009: Tropical cyclones: Atlantic basin [in state of climate in 2008]. Bull. of Amer. Met. Soc., 90, S79-83.

Wang, H., J. Schemm, A. Kumar, W. Wang, L. Long, M. Chelliah, G. Bell and P. Peng, 2009 : A statistical forecast model for Atlantic hurricane activity based on the NCEP dynamical seasonal forecast. J. Climate, 22, 4481-4500.

Gochis, D., J. Schemm, W. Shi, L. Long, W. Higgins and A. Douglas, 2009: “A community forum for the evaluation and use of seasonal forecasts of the North American Monsoon: The NAME forecast forum.” EOS, Vol. 90, No. 29, 249-250.

Seo, K., W. Wang, J. Gottschalk, Q. Zhang, J. Schemm, W. Higgins and A. Kumar, 2009 : Evaluation of MJO forecast skill from several statisitcal and dynamical forecast models. J. Climate, 22, 2372-2388.

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Schubert, S. and US CLIVAR Drought Working Group Participants, 2009: “A U.S. CLIVAR project to assess and compare the responses of global climate models to drought-related SST forcing patterns: overview and results.” J. Climate, 22, 5251-5272. Mo, K., J. Schemm and S. Yoo, 2009: “Influence of ENSO and the Atlantic multi-decadal oscillation on drought over the United States.” J. Climate, 22, 5962-5982 Gutzler, D. and NAMAP2 Participants, 2009: “Simulations of the 2004 North American

Monsoon: NAMAP2.” J. Climate, 22, 6716-6740. Mo, K., L. Long, Y. Xia, S.-K. Yang, J. Schemm and M. Ek, 2011: “Drought indices based on the Climate Forecast System Reanalysis and ensemble NLDAS .” J. Hydromet., 12, 181-205.

Lee, S., J. Lee, K. Ha, B. Wang and J. Schemm, 2011: “Deficiencies and possibilities for long-lead coupled climate prediction of the Western North Pacific–East Asian monsoon. ” Clim. Dyn., 36, 1173-1199

Bell, G. D., E. Blake, T. Kimberlain, C. Landsea, J. Schemm, R. Pasch and S. Goldenberg, 2011: Tropical cyclones: Atlantic Basin [in State of the Climate in 2010]. Bull. of Amer. Met. Soc., 92(6), S115-121.

29

5.3. PI: Prof. Masaki Satoh, Professor Atmosphere and Ocean Research Institute University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8568, Japan [email protected]

Selected Publications

Yoshizaki, M., K. Yasunaga, S. Iga, M. Satoh, T. Nasuno, A. T. Noda, H. Tomita and M. Fujita, 2012: Why do super clusters and Madden Julian Oscillation coexist over the equatorial region? SOLA, 8, 33-36. doi:10.2151/sola.2012-009.

Yamada, Y., K., Oouchi, M. Satoh, A. T. Noda, and H. Tomita, 2011: Sensitivity of tropical cyclones to large- scale environment in a global non-hydrostatic model with explicit cloud microphysics. In Cyclones: Formation, Triggers and Control, K. Oouchi and H. Fudeyasu (eds.), Nova Science Publishers, Inc., Chapter 7, 145-159.

Satoh, M., K. Oouchi, T. Nasuno, H. Taniguchi, Y. Yamada, H. Tomita, C. Kodama, J. Kinter, D. Achuthavarier, J. Manganello, B. Cash, T. Jung, T. Palmer, and N. Wedi, 2011: The intra-seasonal oscillation and its control of tropical cyclones simulated by high-resolution global atmospheric models. Clim. Dyn., DOI 10.1007.

Kinter III, J. L., B. Cash, D. Achuthavarier, J. Adams, E. Altshuler, P. Dirmeyer, B. Doty, B. Huang, L. Marx, J. Manganello, C. Stan, T. Wakefield, E. Jin, T. Palmer, M. Hamrud, T. Jung, M. Miller, P. Towers, N. Wedi, M. Satoh, H. Tomita, C. Kodama, T. Nasuno, K. Oouchi, Y. Yamada, H. Taniguchi, P. Andrews, T. Baer, M. Ezell, C. Halloy, D. John, B. Loftis, R. Mohr, and K. Wong, 2012: Revolutionizing climate modeling - Project Athena: A multi-institutional, international collaboration. Bull. Am. Meteorol. Soc., in press.

Matsuno, T., M. Satoh, H. Tomita, T. Nasuno, S. Iga, H. Miura, A. T. Noda, K. Oouchi, T. Sato, H. Fudeyasu, W. Yanase, 2011: Cloud-cluster-resolving global atmosphere modeling - A challenge for the new age of tropical meteorology. In The Global Monsoon System, Research and Forecast, 2nd Edition, Chih-Pei Chang, Yihui Ding, Ngar-Cheung Lau, Richard H Johnson, Bin Wang, and Tetsuzo Yasunari (eds.), World Scientific Pub Co Inc, pp. 608.

Taniguchi, H., W. Yanase, and M. Satoh, 2010: Ensemble simulation of cyclone Nargis by a global cloud-system-resolving model-modulation of cyclogenesis by the Madden-Julian Oscillation. J. Meteor. Soc. Japan, 88, 571-591.

Satoh, M., T. Nasuno, H. Miura, H. Tomita, S. Iga, Y. Takayabu, 2008: Precipitation statistics comparison between global cloud resolving simulation with NICAM and TRMM PR data. In High Resolution Numerical Modelling of the Atmosphere and Ocean, Wataru Ohfuchi and Kevin Hamilton (eds.), 99-112, ISBN-13: 978-0387366715, 293pp.

Satoh, M., T. Matsuno, H. Tomita, H. Miura, T. Nasuno, and S. Iga, 2008: Nonhydrostatic Icosahedral Atmospheric Model (NICAM) for global cloud resolving simulations. J. Comput. Physics, special issue on Predicting Weather, Climate and Extreme events, 227, 3486-3514, doi:10.1016/j.jcp.2007.02.006.

30

6. CURRENT AND PENDING SUPPORT 6.1. PI: Joshua Xiouhua Fu Current support

NSF: Title: Dynamics of the boreal summer intraseasonal oscillation: Mult-scale interaction, 08/15/2010‐07/31/2013, 2‐mon, $597,427. (PI: Bin Wang, Co-PI: Joshua Xiouhua Fu, Kazu Kikuchi)

NOAA: Title: Application of DYNAMO/AMIE observations to validate and improve the representation of MJO initiation and propagation in the NCEP CFSv2, 09/01/2011‐ 08/31/2014, 1‐mon, $232,942. (PI: Joshua Xiouhua Fu) APCC: Title: Development of APCC seamless prediction system, 08/01/2012‐ 05/31/2013, 4‐mon, $260,870. (PI: Bin Wang, Co-PI: June-Yi Lee, Joshua Xiouhua Fu) Pending support

This proposal

6.2. PI: Dr. Jae-Kyung E. Schemm Current support Agency: NOAA CPO/CTB Status: Current Title: Multi-model ensemble forecasts of MJO Amount: $170K/year Period: July, 2010 – June 2013 PI: B. Wang Co-PI: D. Waliser Co-Is: S. Schubert, B. Kirtman, H. Hendon, I. Kang, J. Lee, X. Fu, P. Liu, J.

Gottschalck, A. Kunar, J. Schemm, S. Lord and A. Vintzileos Agency: NOAA CPO/MAPP Status: Current Title: Predictability of Atlantic Hurricane Activity by the NMME Coupled Models Amount: $135K/year Period: August, 2012 – September, 2015 PI: A. Barnston Co-PI: M. Tippet and J. Schemm

Pending support

This proposal