S2S meeting, February 14, 2014 NOAA Center for weather and climate prediction S2S contribution with a global non-hydrostatic model Quick review of research and proposal Kazuyoshi Oouchi (JAMSTEC) Thanks to: NICAM Univ of Tokyo and AICS/RIKEN

case study ensemble of case study in multi-months time frame “climate” research/projection Research characterization in the past 10 years GOAL: to increase understanding and reliability of projection of global cloud/convection K-computer(2012-) Earth Simulator(2002~) upgrade of supercomputer S2S focus Sub-seasonal Variability ・ TC, MJO, ・ monsoon-related phenomena

Short History & model characteristics (1/2) Key feature of GCRM : resolve clouds, let them self-develop in the model resolve what type of clouds/convection ? - element of hierarchy – cumulus convection, mesoscale convection, cloud cluster - multi-scale interaction => How they are essential to “S2S predictability” supercomputers resources determine reliability ! (ensemble number, resolution, integration period …) available: Earth Simulator2,3 & K-computer

Typical horizontal resolutions : 14, 7, 3.5 km, … 870m (Miyamoto et al.2013 GRL) Integration periods : 1, 3, 5 months x [a few years] naturally focused on sub-seasonal time range Milestone sub-seasonal experiments - boreal winter experiments (2006 MJO) - boreal summer experiments (2004 MJO) - AMIP run (1979-, 30years) Short History & model characteristics (2/2)

28km 14km 7km3.5km 1.7km 870m by Y. Miyamoto, H. Tomita (AICS,RIKEN) 6UTC, 25 Aug Impacts ot resolusion 7km 28km 14km 3.5km 1.7km 870m

14km 7km 3.5km 1.7km 870m by Y. Miyamoto (AICS,RIKEN) Impacts of resolution (Tropical Cyclone Bolaven) The eye is clearer at the resolutions higher than 7-km  “structure” and accurate intensity discussion

MJO cloud clusters observed from satellite and reproduced by NICAM previously demonstrated its potential to produce “good looking” MJOs Miura et al. (2007,Science) Plan views of CMT displayed relative to center of MJO Miyakawa et al. (2012.JAS) ES-era: MJO case studies

First-ever subkilometer global simulation: dx=870m (Miyamoto et al GRL) Multi-ensembles: MJO case sweep ensemble Multi year experiments: 30 years AMIP-like experiment cf. 8 summers: Athena project (Kinter et al.,2012,BAMS) K-era : further increasing the resolution …

RMM diagram of CINDY/DYNAMO MJO cases. (NOAA-OLR + NCEP reanalysis) Initial dates used for simulations are marked by orange circles (10, 15, 20 Oct and 13, 17, 21 Nov). Assigning initial dates Criteria: ・ , Winter cases (October – March) ・ Average amplitude of phases 2 – 5 ≧ 1 in RMM diagram (Wheeler and Hendon 2004) ⇒ 19 cases Initial dates: ・ The first day the MJO enters Phase 2 ・ The first day the MJO enters phases 1 and 8, if traceable. ⇒ 54 initial dates a MJO sweep experiment (by Tomiki Miyakawa)

Model Configuration No observation after initial date is given to the model: “forecast” mode simulation

11 CINDY/DYNAMO MJO cases RMM diagrams for two MJO cases of CINDY/DYNAMO. Black: NOAA-OLR + ERA-interim, (case1: 50 days, case 2 : 48 days) Red: NICAM (40 days), initialized at Phase 8 Blue: NICAM (40 days), initialized at Phase 1 Purple: NICAM (40 days), initialized at Phase 2 Longitude-time sections (Hovmellor diagrams) of the two MJO cases. Colors are daily OLR averaged between 5S – 5N. Resolutions of NICAM data are lowered to equal NOAA-OLR data. Runs initialized at Phase 1 are shown. CINDY/DYNAMO MJO cases NICAM NOAA Case 1 Case 2

(W/m 2 ) NOAA NICAM 20 Nov 30 Nov 10 Dec CINDY/DYNAMO case 2 10S – 10N, 40E – 20W TRMMNICAM 20 Nov 30 Nov 10 Dec Precip OLR “Maritime Continent Prediction Barrier” problem (Vitart et al. 2007, Weaver et al. 2011, Fu et al. 2011) is not seen

COR > 0.6 for 26 – 28 days Bivariate correlation with regards of lead time (Lin et al. 2008, Gottschalck et al. 2010) phase 8 start phase 2 start all (54 cases) phase 1 start COR days

Case sweep ensemble simulation of winter MJOs through 2003 – 2012 is performed. CINDY/DYNAMO case 2 is included, which showed coherent eastward propagating convective envelope. MJO forecast skill measured by bivariate correlation ⇒ about 27 days. Mean rainfall anomaly patterns that accompany MJOs appear to be well produced. Summary of MJO research

Proposal for contribution (1/2) 1 scale interaction related to cloud organization => gray zone problem - what processes are parameterizable or not - any insights from GCRM (non-hydrostatic) model ? 2 sub-seasonal typical extreme event - how the GCRM has strength in expressing sub-seasonal phenomena (MJO, ISV, tropical cyclone …) 3 atmosphere-ocean coupling ( will start within a few years ) - how much coupling is essential to sub-seasonal phenomena in terms of energetics, structure and predictabilities - with the GCRM framework ? Make the most of the GCRM benefits … Process study for understanding predictability

Proposal for contribution (2/2) 1Specific case study of sub-seasonal phenomena 2Sensitivity study for understanding predictability (e.g., physical schemes) 3Coordinated experiment (upon requests) 4Data sharing for inter-comparison ▶ hindcast - AMIP run ( ) at 14-km ▶ forecast – experimental forecast run will start within the next five years for uncoupled mode, and for coupled mode afterwards (unit, 1-6 months) [for] process study & inter-comparison [not for] routine predictability simulations (trade-off between ensemble size and resolution) Data sharing with existing data & coordinated experiments what type of GCRM experiment & data would be beneficial for S2S participating groups and community ?

Thank you !

Supplementary slides

Development since 2000 Tomita and Satoh (2005, Fluid Dyn. Res.) Satoh et al. (2008, J. Comp. Phys.) First global dx=3.5km run in 2004 using the Earth Simulator (JAMSTEC) Tomita et al.(2005, Geophys. Res. Lett.) Miura et al.(2007, Science) International collaborations Athena project ( ): COLA, NICS, ECMWF, JAMSTEC, Univ. of Tokyo G8-call ICOMEX (2011-): Germany, UK, France, US, Japan K-computer studies (10PF; Kobe,Riken, since 2012) NICAM: Nonhydrostatic Icosahedral Atmospheric Model

GPCP - 1dd NICAM MJO phase composited rainfall anomaly

Tuning NSW6 An unrealistic feature with NSW6 A larger amount of cloud ice remaining in the upper troposphere. A higher stability in the upper troposphere. This possibly prohibited smaller-scale sporadic convection and enhanced stronger organized system localized near forcing. Tuning for MJO speed & organization TC initiation Energy balance (OLR) More than 150 runs until now.

Settings very close to those of Miura et al. (2007) and Miura et al. (2009). The Earth Simulator Initial: October 16, 2011 Duration: 40 days Initial data: interpolated from NCEP ds083.2 Microphysics: Grabowski (1998) OLR: NICAM (14-km mesh)OLR: NOAA a CINDY MJO – pilot run (by Hiroaki Miura)