met office science review meetings 2012 · • preliminary study consisting of ~12 start dates...

© Crown copyright Met Office

Modelling and prediction across timescales Tim Johns, Adam Scaife, Doug Smith, Malcolm Roberts MOSAC/SRG, 14-16 November 2012

Met Office Science Review Meetings 2012 MOSAC 17.10

SRG 9.10


Introduction

• Key messages:

– HadGEM3-based research applications

– N216L85 (60km) ORCA025L75 (25km) coupled model core configuration

• N320 (40km), N512 (25km), N768 (17km), and exploratory studies at N1024 (12km)

– INTEGRATE: coupled model development, process evaluation, assessment/release cycles

– Towards seamless coupled EPS in future

• Range of prediction timescales discussed:

– 1-5 day lead time (short range NWP/ocean forecasts)

– 1-15 day lead time (medium range NWP/ocean forecasts)

– Monthly-seasonal (seasonal ensemble prediction system – GloSea5)

– Interannual to decadal (decadal forecast system)

– Multi-decadal (climate sensitivity and climate predictions)


Modelling and prediction across timescales – Coupled NWP research Tim Johns, Ann Shelly, GCMP and SRCFD teams (Met Office) Acknowledgement: Nick Klingaman (University of Reading) MOSAC/SRG, 14-16 November 2012


Coupled NWP R&D in the Met Office

• Four working groups were set up ~2 years ago, to take forward Met Office specific actions in response to recommendations from an International Workshop on Upper Ocean-Atmosphere Interactions on Weather and Climate Timescales held at the Met Office in Dec 2009:

http://www.ncof.co.uk/Ocean-Atmosphere-Workshop-Dec-2009.html

• The coupled NWP initiative was taken forward over the past 2 years by a Working Group on Ocean-Atmosphere Coupling and Interactions on NWP timescales, which was set up to provide a focus for delivering initial phases of the underpinning R&D (but this WG is now disbanded)

• The work now continues under business-as-usual arrangements, resourced primarily by the Global Coupled Model Development and Processes team in Global Model Evaluation and Development (Foundation Science) in concert with Short-Range Coupled Forecast Development team in Ocean Forecasting R&D (Weather Science)

http://www.ncof.co.uk/Ocean-Atmosphere-Workshop-Dec-2009.html�


Motivation for coupled NWP R&D

1. To explore the role of air-sea coupling in potentially providing improved forecast skill (focusing on the 1-15 day timescale) – for both atmosphere and ocean/sea ice forecasting purposes

2. To probe systematic model errors and drifts that are robust across forecast timescales – to enhance understanding of errors and error-compensations with the aim of tackling process errors ‘at source’

3. To deliver an efficient platform for undertaking global coupled model evaluation and R&D feeding into future model releases and systems

→ Met Office future operational system drivers: • Coupled medium-range NWP system (MOGREPS/GloSea merger) • Coupled global short-range ocean forecasting system (MyOcean2) • High resolution global coupled ensemble NWP system (2020 vision)

→ Also aligns with the seamless prediction/model assessment agenda: more unified scientific formulation and experimental setups using global coupled models across timescales from days to decades (INTEGRATE project)


Recent progress

• FY2010-11 (Phase 1 study) • Preliminary study consisting of ~12 start dates using a previous

development version of HadGEM3-AO → Met Office PWS report 1

• FY2011-12 (Phase 2 study → focus for this talk) • Extensive set of case studies updated to HadGEM3-AO at

GlobalAtmos3 (GA3), with better ocean/ice/rivers initialisation, and start dates chosen for synergy with other projects → Met Office PWS report 2

PWS deliverable reports (available from the Met Office):

1. Shelly et al. 2011: “Preliminary case-study experiments with a global ocean-atmosphere coupled model configuration on 1-15 day timescale”

2. Johns et al. 2012: “Report on extensive coupled ocean-atmosphere trials on NWP (1-15 day) timescales”


Phase 2 model & experiments

Coupled model

HadGEM3-AO N216L85 (GA3.0) + ORCA025L75 (NEMO3.2) + CICE (4.1) + OASIS coupler

Experiments

• ~130 coupled case studies to T+15 days, with 3-hourly coupling frequency

• Atmosphere-only and ocean-only control forecasts run for subsets of the coupled cases

• Selected start dates in the range June 2008 to November 2010

• Core set of 10 “winter” and 10 “summer” cases, plus MJO periods and other cases

Initialisation and boundary conditions • Coupled: free running (no flux adjustment/bias correction) starting from:

• Met Office operational NWP analysis at 12z (interpolated to N216L85) [Atmos/Land] • 12-hour ocean forecast, from analysed state at 0z to 12z, using the latest FOAM-NEMOVAR

model (ORCA025L75/NEMO3.2 + CICE) driven with operational NWP fluxes [Ocean/Ice] • Atmosphere-only controls: Persisted initial SST anomaly (wrt. GISST), sea ice fixed

• Ocean-only controls: Driven with 3-hourly mean fluxes output from atmos-only controls 2008 | 2009 | 2010


Ongoing work – FY2012-13 to FY2013-14

• Application of coupled NWP case studies to assessment of GA4 (done), and ENDGame (GA5) in coupled mode, alongside other tests

• Development of higher resolution coupled system (in progress) • Operational NWP and ocean forecast resolutions being used: N512 (c. 25km)

atmosphere and ORCA025 (c. 25km) ocean • Case studies and assessment to commence early next year • Initial case studies will use operational atmosphere and ocean initial states

• Delivery of global coupled forecasts to MyOcean 2 by April 2014 • Initially to use 0-5 day forecasts from new GloSea5 seasonal system • N216 (c. 60km) atmosphere coupled to ORCA025 (c. 25km) ocean • Initial assessment underway

• Improved infrastructure allowing coupled NWP case study techniques to be applied efficiently in model development/assessment cycles (INTEGRATE)

• Regional UKV coupled system (UKV 4km – 1.5km resolution atmosphere coupled to a 4km shelf seas) being developed - aiming for case studies in mid-2013

• Add wave coupling and coupled data assimilation for model initialization (global and regional coupled applications)


Ongoing collaborations

• Vertical Structure and Diabatic Processes of the MJO - MJO Task force – Nick Klingaman and Prince Xavier

• Evaluation of the Indian Monsoon – Ashis Mitra, NCMRWF

• Performance of the coupled model during DYNAMO field campaign in comparison with operational models – Chidong Zhang, U. of Miami

• Tropical Warm Pool Diurnal Variability Project (TWP+) - Use in-situ data from TWP+ and compare model results against satellite data to allow assessment of the diurnal cycle over a large area – Helen Beggs, BoM


Coupled NWP case study experiments – results Verification Seamless model assessment Phenomena


Tropics 500hPa Height DJF 925hPa T JJA

RMSE

BIAS

T+ 1 5 10 15 T+ 1 5 10 15

•Two examples of good coupled skill relative to atmosphere-only control forecasts •Tropics is the main area of atmospheric performance difference

•Performance mostly comparable in the extra-tropics


850hPa T JJA MSLP DJF Geopot. Height @ T+120 JJA

Comparison with operational global model in the Tropics

BIAS

RMSE

0.0

-0.3

-0.6

0.0

-0.3

-0.6

[hPa]

0

600

1000

T+ 1 2 3 4 5 T+ 1 2 3 4 5

0

600

1000


Ocean Verification (SST): Coupled versus ocean-only control forecasts

Coupled outperforms ocean-only control forecasts at all lead times

(for RMSE and bias, winter and summer)


JJA mean precipitation biases Day 11-15 - average over 10 cases

Improved precipitation over the Maritime continent with an interactive ocean

More vigorous local water cycle in the coupled model than atmosphere control


SST biases: Climate vs. Coupled NWP NH. Winter NH. Summer Climate:

50-yr mean

Coupled NWP: 10 cases Day 7 Day 1 Day 14


Diurnal Cycle of SST

Atlantic Buoy 3: 11.5N 38W -Buoy -Day1 fcst -Day5 fcst -Day10 fcst -Day15 fcst

At this location: •Model shows similar variability to buoy data •Bias varies with forecast lead time •Larger events captured by model

José Rodríguez

July 2008

304 K

303 K

302 K

301 K

300 K

Generally: •Model tends to overestimate maxima •Minima exhibit lower bias


Diurnal range of SST (K) Coupled Model

(Note that the HadGEM3 colour scale covers twice the range of HadDTR)

HadDTR (Kennedy et al. 2007)


Oct 20

Oct 21

Oct 22

Oct 23

....……

……….

………

Jan 15

Jan 16

Day 1 Day 2 … Day 15 Fcst Fcst Fcst

YOTC MJO-E and MJO-F Investigating the phase relationship between Convection and SST

2 strong MJO events between Oct 2009 to Jan 2010, in YOTC period

Coupled case studies for each start date: Oct 20th 2009 to Jan 16th 2010

OLR as proxy for convection

OLR/SST anomalies calculated for each date (wrt. climatologies from NOAA OLR/OSTIA reanalyses)

5 day running mean applied to each forecast to smooth high frequency variability

Lead-lag correlation analysis between SST and OLR for consecutive day 1, day 2 … forecasts (for observed state, coupled model and atmos control)


OLR/SST phase relationship : Indian Ocean Coupled model Atmosphere control Observed state

Warm SST’s lead enhanced convection by ~5-10days

MJO related fluxes have no influence on SST so convection adjusts to a location where SST is favourable Results in an in-phase relationship Coupled model maintains phase lagged relationship

Day 1 Day 2 Day 4 Day 5


MJO performance – correlation analysis

Bi-variate correlation for

forecast and YOTC analysis:

20091015 - 20091205

(a) OLR

(a) U850

Coupled

model

Atm. control

Atm. Control: YOTC initialisation

•Coupled model demonstrates most skilful OLR performance but is less skilful for winds.

•Need to determine impact of using different ‘truth’ on correlation scores Nick Klingaman, U. Reading

Persistence


Central pressure (<990hPa) captured by day 3 in coupled model forecast

but atmosphere control has shallower depression.

Additional skill comes from interactive ocean – see cooling in BoB in

evolution of the SST (day 3-day 1: colour shading)

Analysis

Coupled Model

Atmos Control

Synoptic Case Study: Bay Of Bengal Tropical Monsoon depression August 2008 – Day 3 Forecasts

992 990

990


FOAM analysis

Day 3 minus day 1 sub surface temperature at 88E

Coupled model

Day 3 minus day 1 sub-surface temperature at 88E

Shows skill in capturing mixed layer temperature evolution out to day 3.

N S

50m

150m

250m

50m

150m

250m

Synoptic Case Study: Bay Of Bengal Tropical Monsoon depression Ocean Temperature section along 88E


Summary

Air-sea-ice coupling shows promise for improving short to medium range forecasting skill, even without SST bias correction

Coupled NWP case study hindcasts are competitive with atmosphere-only control forecasts in mean bias and RMSE skill in the extra-tropics, and show improvements in skill in the tropics in both the atmosphere and ocean components

Such case studies are a useful tool in seamless model assessment – in part because they are computationally fast to run (each HadGEM3-AO case study runs in ~2 hrs on IBM P7 on 9 nodes)

Plan further analysis of coupled NWP cases study results, and development of diagnostics/metrics to assess model performance and investigate robust signals of coupled model systematic errors that emerge on short timescales (→ papers)

Modelling and prediction across timescales – Monthly to Seasonal development Adam Scaife, Alberto Arribas MOSAC/SRG, 14-16 November 2012 © Crown copyright Met Office

Why monthly to seasonal prediction?

Climate varies a lot and this can greatly amplify or oppose any trend: Tropical Floods during 2010/11 Russian heatwave 2010 Recent Cold European and US winters

Temperature

Time (years)

Climate Change

Climate Change + Variability

Barcelona, Spain, March 2010 Dry Water Pan, Kenya, 2011

How can we make progress?

Initial

Conditions

Forecast

System

Boundary

Conditions

Model

Ensembles

Obs Analysis

GHGs Aerosol

Hcast Solar

Model 1

Model 2

Model 3

One approach is model perturbations but we need model improvements: long timescale modes & processes, teleconnections and response to external forcing

ENSO predictions from UKMO, ECMWF & MeteoFr

Global Seasonal Forecast System 4

GloSea4 Range: 7months Model: HadGEM3

Resolution: N96L85O(1) Initialisation: daily, NWP state + ocean analysis Method: Full field + hindcast bias correction

Ensembles: SKEB2 stoch. physics, lagged initialisation Forecasts: Seasonal 2 day-1, 42 members updated weekly

Monthly 2 day-1, 28 members updated daily Reference: Arribas et al., 2011

Seasonal Hindcasts: different strategies around the world

Hindcast length

Frequency of system upgrades

Centre's priorities

JMA ~ 30 yr

NCEP ~ 40 yr 8 yr Link to re-analysis

ECWMF ~ 25 yr 5 yr Med-range

UK Met Office * 14 yr 1 yr Link to model development

* Arribas et al., Mon. Wea. Rev., 2011

Recent Upgrades

Summer 2009: GloSea4 becomes operational

Nov 2010

• Vertical high-res (L85 strat. / L75 ocean) • Sea-ice assimilation (concentrations) • Updated hcst (1996-2009)

May 2011

• Monthly system operational

Dec 2012 • Horizontal high-res (N216 atm. / 0.25 ocean) • NEMOVAR

JJA

DJF

Forecast Observed

GloSea4 ENSO Teleconnections El Niño – La Niña

Skill for Arctic Sea-ice area

Observations Hindcast/Forecast

Real time forecasts contributed to ARCUS multi model project

MJO prediction skill

Improved System 5

GloSea5 Range: 7months

Model: HadGEM3H Resolution: N216L85O(0.25)

Initialisation: daily, NWP state + NEMOVAR 0.25deg Method: Full field + hindcast bias correction

Ensembles: SKEB2 stoch. physics, lagged initialisation Forecasts: Seasonal 2 day-1: 42 members updated weekly

Monthly 2 day-1: 28 members updated daily Reference: MacLachlan et al., 2013, in prep.

Benefits of higher spatial resolution

Obs The westward extension of Niño is a common error

in many climate models. It affects remote regions.

High-res model has

better ENSO pattern and

teleconnections

Low resolution

High resolution

El Niño Southern Oscillation Skill (Nino 3.4 SST: ACC / RMSE & Spread)

ACC

May JJA Nov DJF

GloSea5 (red)

GloSea4 (blue)

RMSE

Improved Teleconnection Pattern

OBS

GloSea5

GloSea4

R=0.64

R=0.56

Scaife et al., GRL, 2011

Realistic Blocking Frequency

Benefits of higher ocean resolution: Improved Bias, Atlantic Blocking and Prediction Skill

Gulf Stream Bias

Wly wind bias

=> Blocking Deficit

Low Res 1o

No Gulf Stream Bias

No Wly wind bias

=> Good Blocking

High Res 0.25o

Improved Seasonal Forecast Skill

GloSea5

Hindcast Atlantic pressure

Significant NAO skill! r~0.5

Future: An international system KMA (Rep. of Korea)

• Joint seasonal forecast system • Shared workload and to extend hindcast

NCMRWF (India) • Implementing GloSea for research

Seamless with Med-range (2013): Research project to merge MOGREPS-15 and GloSea5 for med-range in 2013

Seamless with Decadal (~2014): GloSea5 will be extended – in research mode - to decadal timescales in 2013

Modelling and prediction across timescales – Decadal prediction Doug Smith, Nick Dunstone, Rosie Eade, Leon Hermanson, Adam Scaife MOSAC/SRG, 14-16 November 2012 © Crown copyright Met Office

Decadal Prediction System

DePreSys Range: 10 years Model: HadCM3

Resolution: N48L19O(1.25) Initialisation: Relaxation to atmos + ocean analysis

Method: Anomaly initialization Ensembles: 10 members, random perturbations

Hindcasts: 1st November 1960 to 2009 Forecasts: Updated annually (1st Sep)

Reference: Smith et al., 2007

© Crown copyright Met Office (Eade et al. in press)

Skill of temperature extremes

• Significant skill, especially for multi-year periods, but lower than mean

• Arises from climate change signal • Hindcasts start Nov 1st each year 1960 to 2005, with 9 ensemble members

• Assess extremes using daily data, Moderate extremes (10th percentile)

• 4 definitions (e.g. cold days, cold nights, warm days, warm nights)

© Crown copyright Met Office (Eade et al. in press)

Skill of wet extremes

• Some skill, but much lower than for temperature

• Can be higher than the mean – larger trends in extremes

• Initialization improvements up to two years • Assessed from daily data

• Wet: precipitation rate greater than 90th percentile (of rainy days)


Tropical storm predictions beyond the seasonal range

(Smith et al. 2010)

Initialised Uninitialised Persistence

Skill of Atlantic tropical storms from both external forcing and initialisation

Initialised - Uninitialised Skill of initialised predictions

5-ye

ar s

urfa

ce

tem

pera

ture


External forcing of tropical storms

Dunstone et al., submitted

Booth et al., 2012

Nor

th A

tlant

ic S

ST

Observations Model


Impact of aerosols on near future (2010 to 2040)

Dunstone et al., submitted

Surf

ace

te

mpe

ratu

re

Circ

ulat

ion

• Aggressive aerosol mitigation in RCP2.6 ⇒ reduced cooling (more warming) in N. Atlantic ⇒ stronger anomalous Hadley circulation ⇒ ITCZ shifts north ⇒ more storms

Stor

ms

2010 2050 2100

Also noted by Villarini and Vecchi 2012

© Crown copyright Met Office (Smith et al. submitted)

Anomaly vs Full Field Initialization DJF precipitation (months 2-4)

Observations

El Niño – La Niña rainfall composites

Hindcast skill • Skill in areas related to El Niño

• Stronger teleconnections in full field ⇒ higher skill

• Teleconnections depend on underlying state

• Highlights need for improved models


Exchange of decadal predictions

(Smith et al. submitted)

Multi-model forecast of 2011

• Many groups have now developed decadal prediction systems for CMIP5

• What about the coming decade?

• Met Office coordinate an informal exchange of near real-time predictions

• 9 dynamical + 3 empirical

• High skill for first annual mean

• Initialized are cooler than uninitialized projections (except N. Atl and N. Pac)

Impact of initialization on 2012-16

Upgraded Decadal Predictions

DePreSys2 Range: 10 years Model: HadGEM3

Resolution: N96L85O(1) Initialisation: Relaxation to atmos + ocean analysis

Method: Anomaly initialization Ensembles: 10 members, random perturbations

Hindcasts: 1st November 1960 to 2009 Forecasts: Updated annually (1st Nov)

Reference: Knight et al., 2013 (in prep)


HadGEM3 initialization tests Temperature years 2 - 5


HadGEM3 vs HadCM3 Temperature years 2 - 5

Modelling and prediction across timescales – High-resolution climate modelling Malcolm Roberts, et al MOSAC/SRG, 14-16 November 2012 © Crown copyright Met Office

A partnership in weather and climate research

Joint Weather and Climate Research Programme

High resolution climate

modelling research

Malcolm Roberts, Matthew Mizielinski,

Lizzie Kendon, Stuart Webster + Met Office (with thanks to the many MO groups

involved in model development etc)

Pier Luigi Vidale, Marie-Estelle Demory,

Reinhard Schiemann, Jane Strachan

+ NCAS-Climate

MOSAC/SRG Nov 2012

Joint Weather and Climate Research Programme A partnership in climate research

N96

130km

N144

90km

N216

60km

N320

40km N512

25km N768

17km N1024

12km

ORCA1

1°

ORCA025

0.25°

ORCA12

0.08°

MetUM global atmosphere/coupled model climate configurations in use

Ocean/sea-ice

Atmosphere/land

Essentially the same physics/dynamics parameters used throughout model hierarchy

Explicit convection

GloSea5

Planned

UPSCALE

Project to assess impact of global explicit convection

Texas UK-ESM1?


Progress + plans (NCAS-Climate + Met Office projects)

• UJCC-HiGEM projects (2004-8) – Coupled 90km atm – 1/3° ocean; 60km atmosphere-only

• HadGEM3/CAPTIVATE/INTEGRATE/HRCM projects – Develop higher resolution HadGEM3-AO model

• UPSCALE (2011-12) lead by Prof Vidale – 5 member ensemble of 25km atmosphere-only (present day + future

timeslice) – 144M Cray core hours from PrACE (European supercomputing)

• To look at variability and extremes (e.g. 2003 European heat wave, recent cold winters, blocking)

• predictability of tropical cyclone numbers • Explicit convection (2012-)

– 12km global model with explicit convection (no parameterisation) • Diurnal cycle, MJO and global impact (motivated by CASCADE)

• Planned

– Texas/JPL/JWCRP – coupled 25km atmos-ocean + convection-permitting over US domain

– Coupled explicit convection/eddy-resolving


Resolution is not all about small-

scale detail

• Large-scale errors common to all resolutions can lead to important differences elsewhere – Little change in radiation, big changes in global water cycle – There are indications of convergence at resolutions of order 40-

60km

• Blocking generally thought to be large-scale – Convection-permitting model can represent drought duration

much more realistically

• Resolving basic large-scale features – For example ocean boundary currents

Energy budget in HadGEM-family AGCMs

Adapted from Trenberth et al., 2009, 2011

Fluxes: W/m2

Energy balance at TOA and surface Globally too much surface SW radiation compared to observations and reanalyses Excess in latent heat and precipitation consistent with excess in OLR

Demory et al, in prep

Over land

Robustness of results member ensembles HadGAM1 & HadGEM3-A: 2 different models with different water budgets Same tendency with resolution: convergence around N216-N320

High local recycling Low transport

Resolution Lower local recycling Higher transport



Atlantic basin interannual variability

OSTIA-forced climate

integrations

Correlations : with HURDAT

N96 0.63 N216 0.69 N512 0.72

UPSCALE project (PrACE), P.L. Vidale


Tropical cyclone track density (transits per month)


1.5km UK climate model

• First time convection-permitting model run for extended period over UK

• Spans southern UK

• Variable resolution rim

• Driven by 12km European RCM, forced by ERA-interim or N216-HadGEM3

• Convection scheme is ‘off’

• 50 sec time step Kendon et al, 2012


Peak intensity 20

10

5

2

1

0.5

0.2

0.1

20

10

5

2

1

0.5

0.2

0.1

Radar 12km-radar

1.5km-12km 1.5km-radar 1 6 12 18 24 36 72 hr 1 6 12 18 24 36 72 hr

1 6 12 18 24 36 72 hr 1 6 12 18 24 36 72 hr

0.001 0.005 0.02 0.1 -0.02 -0.005 0 0.005 0.02

Joint probability distribution of rain spell duration versus peak amount. [Rain > 0.1mm/h]

Spell duration versus peak intensity


Nested Indian monsoon simulations

• EMBRACE project

• Using Stuart Webster’s nesting suite to look at Indian monsoon

• very powerful and cheap way to examine resolution, parameter changes on particular processes

• Can also be used to look at tropical cyclones, e.g. Hurricane Katrina

• swebster_EMBRACE_1page.ppt


Future plans • Analysis and understanding

– Work with cloud (and cloud-system) resolving models to understand/improve parameterisations

– Coupling to eddy+boundary current resolving ocean model – Understanding where models converge, e.g. based on emerging processes – Scale interactions:

• Clouds and climate • TCs and their contributions to global energy+water cycles • Planetary waves, blocking, feedbacks with land surface anomalies (heatwaves, droughts)

• Applications to study of climate change

– Model suitable for decadal scenario integrations – N512 future timeslice (2100) runs to look at changes in variability, e.g.

tropical cyclones – SUKV runs forced by global 60km model (present day + future) to look

at possible future changes in extreme precipitation

• Future projects – Collaboration with UTexas@Austin & JPL – 12km global integrations with explicit convection – Coupling to the ORCA12 eddy-resolving ocean – Welsh Extreme Weather Initiative using SUKV model


Local time of peak precipitation (diurnal cycle) – Mar-Apr 2008

N1024 (12km) with (top) and without

(middle) convective

parameterisation, with TRMM

observations (bottom)

Diurnal cycle with and without parameterised convection over the Maritime Continent

mosac_movie_jun_aug.avi


Questions


Extra slides

How resolution affects the hydrological cycle: a study with an atmospheric GCM

Adapted from Trenberth et al., 2007, 2011

Storage: 103km3, Fluxes: 103km3/year For water vapour transport from ocean to land: (i) atmospheric moisture convergence (ii) E - P from the ocean (iii) P - E from the land

Biases in climate models: too intense water cycle (P and E too high): common in IPCC models Water budget well balanced in climate models: not always the case in reanalyses: MERRA: (E-P)ocean = -1 Moisture transport (ocean to land or land to ocean) way too low at N48 resolution

These 3 numbers should be equal



Prolonged drought in SUKV model


Precipitation in JJA 2005 from range of global climate model resolutions (135km 12km) and observations


Proposed collaboration with Texas/JPL

• Submission of NSF-XCEDE proposal • Study water cycle globally and over US

– Global coupled 25km model – Regional models at convection-permitting scales (4km and

1.5km)


High resolution regional experiments

For UK/Europe:

• ERA-interim driven (1989-2008) 12km and 1.5km experiments (complete)

• N216-HadGEM3 driven – 8 experiments (ongoing):

For US:

• N512-HadGEM3 driven 4km and 1.5km experiments spanning continental US (planned JPL/UTexas collaboration)

12km

1.5km

Control (1996-2010)

Future (15y, ~2100) Prescribed aerosol

Aerosol modelling

Resolution : Eddy KE DJF

Paul Earnshaw, Sean Milton, David Walters

•5 Day Forecasts - 10 DJF Case Studies

• Initialised from N320 analyses

•Resolutions spanning N48 (250km) to N768 (17km)

•GA3.0 Physics & L70


Questions?

Summary: “Modelling and prediction across time scales”

• Baseline global coupled configuration: N216L85 atmosphere, ORCA0.25L75 ocean.

• Built, assessed and evaluated across time scales in INTEGRATE

• Supported by a developing research effort in coupled NWP, including assessment of links to errors in climate simulations

• Implementation in a new monthly to seasonal prediction system (GloSea5)

• Project in progress to create a merged medium-range to seasonal coupled EPS.

• Interannual to decadal system has moved to HadGEM3 (N96/ORCA1.0), with plans to explore benefits of N216/ORCA0.25.

• Benefits of higher global atmospheric resolution (N320/N512/N768/N1024) also under investigation through collaborative projects

• Research in high resolution modelling and ensemble design looking at multidecadal climate projection issues, as well as shorter time scales.

© Crown copyright Met Offices

met office science review meetings 2012 · • preliminary study consisting of ~12 start dates...

Documents