© Crown copyright Met Office M. J. Best, J. Santanello, A. Boone, M.Ek and other panel members...

© Crown copyright Met Office

M. J. Best, J. Santanello, A. Boone, M.Ek and other panel members

GEWEX Global Land Atmosphere System Study (GLASS)WGNE annual meeting

March 2014


The aim of GLASS is to promote community activities that improve:

1. our best estimates and the model representation of state variables

1. our understanding of land/atmosphere feedbacks

1. our understanding of the role of land surface in predictability.

Global Land Atmosphere System Study (GLASS)


Cross-Cutting projects/actions:GLACE2 – Links to S2S (land sfc adding to predictability)LUCID2 – Links to iLeaps ALMIP2 – Links to GHP DICE – Links to GASSPLUMBER – Links to GHP

Launching in next 12 months:GSWP3 – Links to carbon community (iLEAPS)PILDAS – Links to WGNE

Being plannedLoCo SGP testbed...GABLS4-DICE-over-ICE? (joint GASS-GLASS)

GLASS Project Updates :


• Provide a comprehensive set of land surface states for the period including entire 20th century and recent years (~1901 – recent) that can serve as a long-term land surface reanalysis suite.

• Include carbon models, to explore/attribute a possible carbon-related effect or changes in Hydro-Energy-Eco functioning.

• Explore uncertainties of input datasets and their propagation through different schemes (LSMs) and super-ensembles (multi-input and multi- model, 1979 - present).

• Uncertainty in future land surface states (multi-GCMs and scenarios, 2000 - 2100)

• Build a robust evaluation framework through component-wise verification (e.g. routing scheme for a validation of discharge (flux); GRACE for a validation of terrestrial water storage variation (storage))

• Includes engagement of the carbon community and inclusion of a suite of LSMs in varying hydrological and carbon treatments.

Follow up to GSWP2 (1986-1995) : NEW aspects :


GSWP-3:Long term retrospective Exp


Enable better communication among developers of land data assimilation systems (LDAS)

Develop and test a framework for LDAS comparison and evaluation Compare land assimilation methods (EnKF, EKF...). Conduct sensitivity studies of assimialtion input parameters (such as model and observation errors). Provide guidance and priorities for future land assimilation research and applications

Ultimately, produce enhanced global datasets of land surface fields

Project for the Intercomparison of Land Data Assimilation Systems (PILDAS):

Objectives


PILDAS : setup


The development of a beta version of the Protocol for theAnalysis of Land Surface Models (PALS, http://pals.unsw.edu. au) is underway.

• PALS is a web application for evaluating land surfacemodels and the observed data sets used to test them (e.g.FLUXNET, GHP).

• The PALS website is designed to analyze in a standardway uploaded single site model simulations with FLUXNETand other observations.

• A related activity is that of a joint GHP-GLASS project todemonstrate benchmarking approaches using PALS, andestablishing empirical benchmarks in PALS from which toevaluate a suite of models.

PALS-current & perspectives


PLUMBER sites

E E

E

D

B

B

DGM GGC

WS

P

E – Evergreen NeedleleafB – Evergreen BroadleafD – Deciduous Broadleaf

W – Woody SavannaS – SavannaP – Permanent Wetlands

W

EE BD

M – Mixed ForestG - GrasslandC – Cropland


Rankings relative to benchmarks

Mean Bias Error MBE

Normalised Mean Error NME

Standard Deviation sd

Correlation coefficient r


Range of Sites for Radiation

Hyytiala Mopane


Range of Sites for Precipitation

Kruger Palang


GLACE-CMIP5

Aims:

Investigate effects of changes in soil moisture content and soil moisture-climate coupling for future climate projections

• Impacts on regional climate (temperature extremes, precipitation)

• Shifts in hot spots of soil moisture-atmosphere coupling

• Impacts on global carbon cycle

• Interactions with land use changes

16


Experimental set-up

Soil moisture (point in Central Europe)

GLACE-CMIP5 investigates the impact of decadal changes in soil moisture on climate

(Focus on climate-change projections ≠ GLACE-1 and GLACE-2: Focus on sub-seasonal and seasonal forecasting)

17


• Design: ETH Zurich (Sonia Seneviratne), KNMI (Bart van den Hurk)• Analysis: ETH Zurich (Sonia Seneviratne, Micah Wilhelm, Tanja

Stanelle)• MPI-ESM: Stefan Hagemann, Victor Brovkin, Martin Claussen• CESM: Dave Lawrence, Matthew Higgins• EC-Earth: Arndt Meier, Ben Smith, Markku Rummukainen,

Bart van den Hurk• GFDL: Alexis Berg, Sergey Malyshev, Kirsten Findell • IPSL: Frederique Cheruy, Agnès Ducharne, Joséfine Ghattas,

Jean-Louis Dufresne• Additional interested participants: Paul Dirmeyer, Pierre

Friedlingstein, Randy Koster, Julia Pongratz

18S.I. Seneviratne, ETH Zurich / GLACE-CMIP5

Participating groups


~18-25% of climate change signal in Mediterranean region due to soil moisture-temperature feedbacks


Temperature impacts


Effects on precipitation are also found, especially in JJA & NHNoisier than for temperature (see DJF)Overall: drier future soils lead to reduced precipitationIn absolute terms [mm/d]: larger for precipitation extremes than mean precipitation


Precipitation impacts


GLACE “Hotspot” Regions

Koster et al., 2004. Science, 305, 1138-1140


Outline of DICE(DIurnal Cycle Experiment)

• These stages test:

LSM and SCM stand-alone performance against observations (stage 1)

What is the impact of coupling? (stage 2)

How sensitive are different LSM and SCM to variations in forcing? (stage 3)

3a

3b


Re-visiting GABLS-2

• CASES-99 campaign

• Leon, near Witchita, Kansas. 37o N, -96o E

• Relatively flat

• Prairie grassland

• 1900 UTC 23 Oct 1999 – 1900 UTC 26 Oct 1999

• Clear skies

No cloud

No precip

• Different nocturnal BL stability:

i. Intermittant

ii. Turbulent

iii. RadiativeCourtesy of Joan Cuxart


ModelsModel Contact

scientistInstitute Stages

submittedLevels Sensitivity

testsArome Eric Bazille Meteo France All 60/70 resolution

Arpege Eric Bazille Meteo France All 60/70 resolution

ECEARTH Reinder Ronda Wageningen SCM only 91 LAI

GDPS3.0 Ayrton Zadra CMC All 79

GFDL Sergey Malyshev Princeton All 24

GISS_E2 Ann Fridlind, Andy Ackerman

GISS All 40

IFS/HTESSEL Irina Sandu, Gianpaolo Balsamo

ECMWF All 137 LAI

MESO_NH Maria Jimenez UIB All 85 Bare soil

UM/JULES Adrian Lock, Martin Best

Met Office All 70 Vegetation

WRF-NOAH Weiguo Wang NUIST All 60 Lots!

WRF Wayne Angevine NOAA ? 119 PBL scheme

CAM5, CLM4 David Lawrence NCAR 1a, 1b ?

PBCM Pierre Gentine Columbia Not yet


Stage 1aSurface fluxes from 55m-forced LSM

Not all LSM provided u*

Coloured by LSM

H

LE

U*


Stage 1bNear surface evolution

20m 55m

θ

q

θ

q

RH RH


• More spread between models in stage 2

• Interesting lack of spread within (some) models

Stage 1 vs 2Bulk PBL sensitivity

Stage 1b Stage 2

θ

q

θ

q


Stage 3a: U* from SCMs’ atmospheric forcing

Coloured by SCM forcing


Stage 3b Daytime PBL sensitivity for 25th Octθ q

hPBL

© Crown copyright Met Office M. J. Best, J. Santanello, A. Boone, M.Ek and other panel members...

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Transcript of © Crown copyright Met Office M. J. Best, J. Santanello, A. Boone, M.Ek and other panel members...