© crown copyright met office hadgem3 monsoon simulation sensitivities using idealised experiments...

© Crown copyright Met Office

HadGEM3 monsoon simulation sensitivities using idealised experiments

June 2013SAPRISE workshop, Exeter University

Richard Levine, Wilfran Moufouma-Okia, Gill Martin, Andrew Turner, Stephanie Bush


Introduction

Focus of systematic error work is on regional convection characteristics over area covering equatorial Indian Ocean and India

Start from scratch, where are main problem areas and how do they interact, what about effect of remote biases?

Approach: idealised experiments forcing different regions with realistic conditions using regional nudging techniques and regional model simulations

1. Atmosphere-only simulations with prescribed SST systematic monsoon bias seen in all configurations, need ocean coupling for correct representation of processes, however, coupling results in SST biases with additional detrimental impacts on monsoon

2. Coupled simulations what forces main SST biases


Atmosphere-only runs with prescribed SST


Methodology

Control: • GA3.0 / GA2.0• N96 (~135km) and N216 resolution (~60km) • NWP 5-day forecast for 2010 at N512 resolution (~25km)

Nudging experiments:• Nudging of theta (indirectly affecting moisture) and U,V from model level 4 upwards to ERA interim re-analysis (includes interannual variability)• Applied both globally and regionally in separate experiments

Regional climate runs:• CORDEX WASIA domain• ~50Km resolution• 6-hourly forcing at boundaries from ERA interim re-analysis


HadGEM3 JJA precipitation and 850hPa wind biases

systematic climate errors:

• little sensitivity to resolution up to N216 (60km) (enhanced India rainfall in recent (GA5.0) N512 (25km), coincides with substantially enhanced monsoon depression activity)

• error pattern same in RCM, magnitude reduced: partly locally forced

• climate time-scale error pattern develops within few days in global NWP


GA5.0 Monsoon depressions: N512 vs N96total rainfall in years with depressions

trajectories and rainfall contribution

total minus depressionrainfall

~10x more strong systems

fully formed cyclonic systems

N512

N96

~3x more weak systems

includes weaker cyclonicdisturbances

N512

N96


Seasonal cycle of main precipitation biases

• Excessive WEIO and Himalayan rainfall biases largest during spring and summer

Coincides with timing of monsoon development and lack of C India rainfall

• Lack development ofWEIO rainfall in RCMcoincides with enhanceddevelopment of C India rainfall (as also seenwith many physics changes)


Nudging experimentsglobal nudging: reference for best obtainable simulation using regional nudging techniques

Global nudging reduces biases:

almost eliminates WEIO bias, rainfall moves north from equator,monsoon flow (as expected) near perfect,

however Indian dry bias partly remains withpreferential rainfall over Himalayas andsurrounding ocean

Fundamental land / orographic precipitation problem which is insensitive to large-scale circulation


EIO nudgingsuppresseslocal wet biasand feedbackson Indian dry biasand N India flowbias

SASIA nudgingmaximum impact on Indian rainfall, weaker feedback on WEIO rainfall and convergence

Nudging experiments: regional


TROP PAC nudging: smaller impact on mean-state, improves large-scale monsoon IAV

strengthens NW Pacific sub-tropical high, weakens monsoon outflow, enhances convergence over BoB / SCS

these changes also seen with other experiments improving Indian rainfall, Indian error develops first,Pacific errors not yet seen in NWP 5-day forecast, so feedback India W Pacific feedback probably strongest

Nudging experiments: regional


Sensitivity to boundary locations in RCMSmall further improvement by removing effect of WEIO bias (already small in RCM, due to boundary constraints on EIO convergence)

Large improvement by removing effect of Himalayas bias Indian bias sensitive to orographic bias


No Tibetan Plateau:“minor” weakening of Himalayan rainfall and flow into N India,only small impact on ΔTT(red vs black lines)

No Tibetan Plateau and Himalayas: almost completely removes monsoon from Indian subcontinent, major impact on ΔTT (green)

Foiling over Himalayas: substantially weakensHimalayan rainfall and associated flow, enhancesC/N India rainfall and monsoon trough flow, large impact on ΔTT (blue)

Sensitivity to orography in GCM

Monsoon sensitivity in HadGEM3 mainly from steep Himalayan orography, not TP [cf. Boos and Kuang 2010]

Barrier effect and elevated heating over Himalayas both important [foiling experiment perhaps could extend further eastwards over rainfall max]


Sensitivity to steepness of Himalayas

original orography

• smoothing slopesshifts rainfall southwards similar to RCM experiment with change to northern boundary

• sensitivity bothto mean and sub-gridorography

may be issue withdynamics / convection (and coupling) nearsteep orography, emphasized bystrong monsoon feedbacks


Coupled runs


HadGEM3 N Indian Ocean cold SST bias (Levine and Turner 2012, Clim Dyn)


rainfall (colours) and vertically integrated moisture flux (vector) anomalies

~30% reduction in summer monsoon rainfall in coupled model compared to equivalent AMIP run

effect of cold Arabian Sea SST bias on local evaporation and moisture fluxes during summer

coupled model SST bias


Development of SST biasbias develops in winter, sustained into (early) monsoon season

initialised coupled simulations show bias does not develop with spring-time or later initialisation


N Arabian Sea SST bias common in CMIP3/CMIP5 (Marathayil et al 2013 ERL, Levine et al 2013 Clim Dyn)

In CMIP3/CMIP5 SST bias develops in winter due to excessively strong winter monsoon, related to wide-spread continental cold surface temperature biasand equatorial wet bias


Methodology

Controls: • Gregorian (nudging) / 360-day (1.5xENT) version of HadGEM3-AO GA4.0, but with GA3.0 entrainment/detrainment rates (increases sensitivity of equatorial convection to 1.5xENT in AMIP tests)

Nudging experiments:• nudging theta (indirectly affecting moisture) over subarea for model levels 2-20 (approximately up to ~3000m) to ERA interim re-analysis (includes IAV.. )• 27 year simulations

try and reduce cold continental temperature bias 1.5xENT experiments: regionally applied 1.5x convective entrainment over WEIO 30 year simulations

try and weaken WEIO convection


HadGEM3 coupled experiments with regional nudging reducing widespread continental cold surface bias weakens meridional winter monsoon circulation and reduces SST cold bias

surface temperature anomalies (colours), 10m wind anomalies (vectors)precipitation anomalies (negative: red contours, positive: blue contours)

caveat:orography mismatch with nudging?


Enhanced equatorial entrainment experimentAimed at weakening equatorial convection


1.5x entrainmentweakens WEIO convection,though still large bias remaining, no effect on meridional surface winds

BOX 1

BOX 2


1.5x entrainmentdominant changes to large-scale circulation are zonal iso meridional

caveat:max. weakening of WEIO convection is 25%


Conclusions

• In AMIP simulations: Indian monsoon systematic error is mainly locally forced in area covering India, N and equatorial Indian Ocean Results suggest Indian land rainfall, WEIO rainfall, and Himalayan rainfall biases would exist on their own, but also feedback on each other

Latest configuration shows progressive sensitivity to resolution (N96–N216–N512), with potential role for monsoon depressions

• Additional dry bias in coupled simulations forced by SST bias, which originally develops due to strong winter monsoon simulations in progress suggest that this is mainly (caveat) due to continental cold surface temperature bias (Arabian peninsula, Iranian plateau, N India, Tibetan plateau)

continental T bias develops rapidly in NWP simulations, widespread valley cooling problem?


The end

© crown copyright met office hadgem3 monsoon simulation sensitivities using idealised experiments...

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nudging of theta