INTRODUCTION TO OCEANOGRAPHY A. Suryachandra Rao Indian Institute of Tropical Meteorology.
HPC for better understanding of the tropical meteorology
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Transcript of HPC for better understanding of the tropical meteorology
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HPC for better understanding of the tropical meteorology
Y. Kajikawa and H. TomitaOct 11th, 2013, @GMCL, PNU
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Necessity of …
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History of climate modeling (1)
Richardson’s Dream (1910s-1920s)
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History of climate modeling (2)ENIAC (Electronic Numerical Integrator And Computer) was
the first electronic general-purpose computer.
http://en.wikipedia.org/wiki/ENIAC
1947-1955@Maryland
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[Q] Why does the climate model require the HPC?
http://www.nies.go.jp/kanko/kankyogi/19/04-09.html
1. Increase of resolutionTo know more detail structure!
e.g. horizontal Resolution in usual climate model :100km ( 2000 ) / 20km (2005 )3.5km on K-computer
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2. Increase of processesTo know more complex interactions.
Atm. Ocn. Lnd. modelsCarbon cycle, aerosol, chemistry, dynamic
vegetation processExternal forcing
Variability of solar constantCO2 emission scenario by IPCC run
-> Earth System model
[Q] Why does the climate model require the HPC?
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[Q] Why does the climate model require the HPC?
http://www.jma.go.jp/jma/kishou/know/kisetsu_riyou/glossary/ensenble.html
3. Increase of ensemblesTo make our results more reliable.Statistical knowledge is necessary.
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Importance of the cloud process (1)
1. Engine for general circulation :– Cumulus has an important role
for atmospheric heat transfer over the globe. (latitudinal direction).
2. Hierarchical structure generates many phenomena.» Cloud cluster , super cloud
cluster, tropical cyclone, MJO, … 7
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• Large impact on the energy balance in climate: • Parasol effect :
reduce the incoming solar incidence.• Green house effect :
cloud emits infrared radiation into the surface and space.– Difficulty :
the interaction with aerosol and chemistry through radiation process• Indirect effect of aerosol : optical
thickness of cloud and cloud life time.• Direct effect of aerosol is also important.
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Importance of the cloud process (2)
Parasol effect Reflection of solar incident
Greenhouse effect Emission of infrared
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99…Very difficult to model the cloud!
cumulus
Shallow cloud
cirrus
Various cloud types exist in our earth!
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10Earth diameter :12740km10km
10km
Cloud cluster ~ 100km
1 km
Super cloud cluster ~ 1000km MJOCloud element: cumulus
Hierarchical structure of clouds
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Example of cloud origination meso-scale cloud
Cloud drop aggregation
Fall as precipitation
Cooling by evaporation
Cold poolGeneration of
new clouds
Generation of new clouds
understanding of cloud dynamics
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Cloud has many features and large impact on the climate through the
complicated processes.
What should we start to study the cloud
processes by modeling
in the age of HPC ?
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Cumulus: Each of cumuli cannot be expressed directly due to
too coarse grid The effect of cumulus is taken a count as parameterization
Grid intervals: 100 km
Each of clouds < 10 km
Uncertainty : many methods generate many results!
Expression of the clouds 10 years ago
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Cumulus (cloud-system ) can be resolved! To avoid the parameterizationHigh reliability / expression of cloud dynamics (w/ cold
pool)
New Approach from 2004
Grid intervals: a few km
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Numerical techniques in the new approach
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• Global cloud-system resolving model– Icosahedral grid
• To get a quasi-homogeneous grid– nonhydrostatic DC
• To resolve cloud scale– explicit cloud expression:
• To avoid the ambiguity of cumulus parameterization.
NICAM ( Tomita & Satoh 2004, Satoh et al. 2008 )
• NICAM project : ~2000 – The first target machine :
Earth Simulator– Now, porting to K computer system Prof. Satoh (AORI, Tokyo univ.) Dr. Tomita (RIKEN AICS)
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Icosahedral grid system?
Regular Icosahedron = Polyhedron with 20 triangular faces.
By dividing each triangles in to 4 small triangle, we can obtain one-higher resolution.
e.g. a -> b -> c-> d …
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DynamicsGoverning equations Fully compressible non-hydrostatic system Spatial discretizationHorizontal grid configuration
Vertical grid configurationTopography
Finite Volume Method
Icosahedral grid with spring dynamics smoothing (Tomita et al. 2001/2002)Lorenz gridTerrain-following coordinate
Conservation Total mass, total energy (Satoh 2002, 2003)Temporal scheme Slow mode - explicit scheme ( RK2, RK3 )
Fast mode - Horizontal Explicit Vertical Implicit scheme Physics Turbulence/shallow clouds MYNN 2.0,2.5(Nakanishi and Niino 2004) modified by Noda(2009)Surface flux Louis (1979), Uno et al. (1995)Radiation MSTRNX (Sekiguchi and Nakajima, 2005)Cloud microphysics NSW6 (Tomita 2008) --- 6 caegories of water ( 1moment-bulk)Cloud parameterization NONESurface process MATSIRO(Takata et al.)
Ref. Satoh et al. 2008 J. Comput. Phys. / Tomita & Satoh 2004 Fluid Dyn. Res.
Recent DC description paper : Tomita et al. 2011, ECMWF workshop proceeding
NICAM current implementation
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• NICAM high resolution run:– 14km, 7km, 3.5km, – 1.8km, 800m, 400m
• Many terms :– Cloud permitting?– Cloud resolving?– Cloud system-resolving? (GCRM)– Meso-scale resolving?
• In the terms of methodology,– To avoid the ambiguity of cumulus parameterizationMethodological cloud-system resolving!
Objection : Cloud resolving model? (Grey zone problem)
The examination of impact
without Cumulus Parameterization is the most important!
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What can the GCRM perform?Explicit expression of cloud clusters from the basic dynamical
mechanism ( Cold pool dynamics )Explicit expression of lifecycle of typhoon (onset &development)
e.g .NICAM 7-km simulation
筑波大・田中博教授 (2010, vol.29-1, NAGARE)
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20NICAM 7km-mesh, one-month simulation: initial = 15 Dec. 2006
23 Dec. 2006
報道発表資料 図2
31 Dec. 2006 8 Jan. 2007
Miura et al. 2007 Science
We can capture MJO realistically by GCRM
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We are now in the K-computer, 10 Peta-FLOPS, era !!
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Earth Simulator Now, we can run such simulations of several decades with “K”, and make a
breakthrough from the case study
Case study(Miura et al 2007)
Several weeks and monthAthena Project: (Sato et al 2012)
Athena Cray XT-4
From the demonstration to scientific knowledge
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10000km 1000km 100km 10km 1km 100m 10m
cumulusBlocking
Low-pressure Cloud cluster stratus
Tropical cyclone
Grand Challenge project:
GL13 (800m)
GL12 (1.7km)
GL11 (3.5km)
GL10 (7km)
GL09 (14km)
GL08 (30km)
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Successfully conducted the GL13(870m) simulation
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Essential change of convection statistics
The convection structure, number of convective cells, and distance to the nearest convective cell dramatically changed around 2.0km
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Future direction of climate modelingIncreases of resolution, model component, ensemble
A key factor to sophisticate the atmospheric modelCloud modelingA new method is to express explicitly each of clouds
A main topics of climate research using K computerCumulus, cloud organization, tropical cyclone, MJOHigh resolution ( less than 2.0km grid spacing) can resolve
convection core using multiple grid.
Summary
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감사합니다
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