euro-cordex-luc: a new initiative on coordinated regional ... · icrc cordex stockholm may 2016...

ICRC CORDEX Stockholm May 2016

EURO-CORDEX-LUC: A new initiative on coordinated regional

land use change experiments

Diana Rechid, Nathalie de Noblet-Ducoudré, Oliver Branch, Rita M Cardoso, Erika Coppola, Edouard Davin, Rowan Fealy, Borbála Gálos, Filippo Giorgi, Miguel Angel Gaertner,

Klaus Goergen, Andreas Haensler, Nils Hempelmann, Daniela Jacob, Eleni Katragkou, Klaus Keuler, Enrique Sánchez, Sebastian Knist, Juliane Otto, Andrew Pitman, Swantje Preuschmann,

Pedro MM Soares, Gustav Strandberg, Claas Teichmann, Robert Vautard

& Partners from the FPS LUCAS consortium:Marcus Breil, Calum Brown, Xuefeng Cui, Richard Fuchs, Irena Hajnsek, Tomas Halenka,

Jan Erik Haugen, Martin Herold, Andreas Huth, Hans-Jürgen Panitz, Kai Radtke, Gerd Schädler, Clemens Simmer, Merja Tölle

www.euro-cordex.net www.lucidproject.org.au www.cordex.org

© Climate Service Center Germany D. Rechid, EURO-CORDEX-LUC, ICRC CORDEX 2016

Structure

Part I: Land Use Change in the Regional Earth System Schematic overview Land use change and climate interactions in Europe: status of knowledge Some major challenges for modelling

Part II: LUCAS - Land Use & Climate Across Scales - a EURO-CORDEX & LUCID initiative LUCAS Framework: Integration of models and data across scales Towards Regional Climate System Models Science questions and coordinated experiments


Land use in Europe

Large fragmentation of land use and small-scale land use changes Direct physical impacts of land use change also depend on conditions in atmosphere and soil radiative effects: e.g. clouds evaporative effects: available energy and soil moisture strong variation during seasons and across Europe Source: Pixabay, CC0 Public Domain


Land use change in the Earth SystemA

tmos

pher

e Ve

geta

tion

Soi

l

Energy Water Momentum Substances

Climate System

Human SystemsLand Ecosystems

Land use change LUCAnthropogenic land cover change

Land managment change

Ecosystem Services

Emissions

Biochemicalimpacts

MitigationAdaptation

Land use policies

Global to localclimate change

Biophysicalimpacts

Change of land surface properties

Natural land cover change

Local to regionalclimate change

© D.Rechid, GERICS


Land use change in the Earth System: biophysical impactsA

tmos

pher

e Ve

geta

tion

Soi

l

Energy Water Momentum Substances

Climate System

Land Ecosystems

Land use change LUCe.g. Afforestation / Reforestation

Biophysicalimpacts

Change of land surface properties

© D.Rechid, GERICS

© Climate Service Center Germany 6 D. Rechid, Climate Change, 7 Nov 2014

Regional Climate System

Land Ecosystems

Land use change LUCe.g. Afforestation /Reforestation

Biophysicalimpacts

Change ofland surfaceproperties Albedo

T

Example: Simplified scheme of physical (first order) impacts on surface temperature T

Net surface shortwave radiation

© D.Rechid, GERICS



Land Ecosystems


Biophysicalimpacts


T


T


Vegetation coverRooting depth

Evapo-transpirationLatent heat fluxBowen ratio

© D.Rechid, GERICS



Land Ecosystems


Biophysicalimpacts


T


T T

Roughness




TurbulenceLatent heat fluxSensible heat flux

© D.Rechid, GERICS



Land Ecosystems


Biophysicalimpacts


T


T T

Roughness

Overall warming or cooling? depends on availability of energy and water




TurbulenceLatent heat fluxSensible heat flux

© D.Rechid, GERICS


Example study Land Mangement Change:Impact of cropland albedo management (by Davin et al., 2014)

Source: Davin, E. L., S. I. Seneviratne, P. Ciais, A. Olioso, and T. Wang (2014), Preferential cooling of hot extremes from cropland albedo management, Proc. Natl. Acad. Sci. U.S.A., doi:10.1073/pnas.1317323111.

Crop fraction Change in 99th percentile of Tmax

  Direct biophysical effects of "no tillage" vs "tillage" increases surface albedo of croplands in summer: the resulting cooling effect is amplified during hot extremes


LUCID Land-Use and Climate, IDentification of robust impacts: First coordinated LUC experiments with an ensemble of seven global models

  Statistically significant changes of near surface temperature in regions with land cover changes

  In most temperate regions with similar magnitude as changes due to increased GHG/SST, generally of opposite sign

Source: de Noblet-Ducoudré, N., et al. (2012) : Determining robust impacts of land-use induced land-cover changes on surface climate over North America and Eurasia; Results from the first set of LUCID experiments. Journal of Climate, 25 : 3261-3281, DOI: 10.1175/JCLI-D-11-00338.1.

Change in 2m-temperature due to historical land cover change / due to GHG increasepresent day vs pre-industrial LCC

LUC- 2mT

SST/GHG+ 2mT


LUCID: land use implementation in GCM-LSMs

de Noblet-Ducoudré et al. (2012) Boisier et al. (2012)

-1,82 -1,62 -1,26 -1,13 -0,99 -0,61 -0,56

3,36 3,04 2,53 2,26 1,93 1,74 1,65

Changes in forest extent in North America (bars in %, numbers in 106 km2)

Important discrepancy

between models

Initial forest extent (in 1870) in North America (106 km2)

But different implementation

strategies

Same change in crop area provided to all models


LUCID: some lessons learned

de Noblet-Ducoudré et al. (2012) Boisier et al. (2012)

Different implementation strategies:explains ~1/3rd of

differences between climatic responses at the

continental scale


Summary: some challengesWhat is the magnitude of direct biophysical impacts of land use changes on climate at regional to local scales in Europe?

•  consistent LUC implementation in the models is important  base land use distribution in the RCMs on a common reference and impose

consistent LUC




consistent LUC

•  large spatial fragmentation of land use in Europe and LUC impacts are dominant on local to regional scale

  need for very high resolution modelling and observations




consistent LUC



•  In contrast to GHG forcing: LUC radiative forcing can also be negative, and spread in GCM response to LUC forcing is larger - so far only single RCM LUC studies

  Fill the scientific gap of missing robust information on biophysical feedbacks of LUC on regional climate


  Consider land use changes in coordinated regional multi-model simulations from continental to local scale



consistent LUC



•  In contrast to GHG forcing: LUC radiative forcing can also be negative, and spread in GCM response to LUC forcing is larger - so far only single RCM LUC studies



Part II

LUCAS - Land Use & Climate Across Scales - a EURO-CORDEX & LUCID initiativeproposed as Flagship Pilot Study to WCRP CORDEX


LUCAS Framework

© D.Rechid, GERICS


Q1

Q2

Q3

Q4

Q5

LUCAS: Science questions

How large is the contribution of LUC to detected past climate trends and changes in variability in Europe?

How strongly can local LUC attenuate negative impacts of climate change, e.g. increased amplitude of extreme events in Europe?

What is the relative contribution of selected LUC to regional climate changes in Europe under two different level of global warming?

What is the effect of spatial resolution on the magnitude and robustness of LUC-induced climate changes?

How sensitive are the regional climate models to LUC and how is this interrelated to the land-atmosphere coupling in different regions among the suite of models?


LUCAS: RCMs - towards Regional Climate System Models


Global climate models / Earth system models

RCMs

Biosphere

Atmosphere

Hydrosphere

Pedosphere

Regional Earth SystemAtmosphericvariables

two-waycoupling boundary conditions

© D.Rechid, GERICS





RCMs

Biosphere

Atmosphere

Hydrosphere

Pedosphere



Feedbacks© D.Rechid, GERICS





RCMs

Biosphere

Atmosphere

Hydrosphere

Pedosphere



Feedbacks

COSMO-CLM 5.0

COSMO-CLM 5.0 / VEG3D

COSMO-CLM / CLM

RCA4 / HARMONIE-CLIM

RegCM4 / CLM4.5

REMO / LUCHS

REMO / iMOVE

PROMES / ORCHIDEE

WRF / ORCHIDEE

WRF3.6

WRF3.7

COSMO-CLM / CLM / ParFlow (TerrSysMP)

© D.Rechid, GERICS


LUCAS: Evaluation concept

© D.Rechid, GERICS


Example: TERENO Terrestrial Environmental Observatory

Source: Simmer, C. et al. (2015), Monitoring and Modeling the Terrestrial System from Pores to Catchments: The Transregional Collaborative Research Center on Patterns in the Soil–Vegetation–Atmosphere System, Bull. Am. Meteorol. Soc., 96(10), 1765–1787, doi:10.1175/BAMS-D-13-00134.1.

Eifel/Lower Rhine Valley ObservatoryRur catchment site Distinct land use gradientCatchment-based measurements that include: •  flux towers •  gauging stations •  weather stations •  meteorological X- and C-band radars •  cosmic ray soil moisture probes

  multi-compartment & multi-scale

see also: http://teodoor.icg.kfa-juelich.de/overview/observatories/ELRV_Observatory

MONITORING OF THE RUR CATCHMENT. The development of techniques to map and under-stand patterns, and to use this to model and predict

the terrestrial system, requires a real counterpart for analysis and testing. TR32 identified the Rur catch-ment (Fig. 1) as its central observation site because

FIG. 1A. Map depicts the Rur catchment including the position of monitoring devices like weather, river gauging, EC, and cosmic-ray stations, as well as a polarimetric weather radar coverage inset for TR32 [X-band radar BoXPol at Meteorological Institute of the University of Bonn (MIUB)]; TERENO [X-band radar JuXPol at Forschungszentrum Jülich GmbH (FZJ)]; and the surrounding C-band radars of DWD, including the nonpolarimetric Rainscanner at Wüstebach and other instrumentation. Active and remnants of open-pit mines are delineated by dashed red lines. The wind rose inset at the top is based on hourly observations of DWD at the weather station Aachen (about 200 m MSL) at the western edge of the catchment for the years 2008–13. The mean wind speed is printed at the end of the eight directional lines. Each circle represents the percentage of time the wind comes from that direction, while the colors indicate the respective discretization into wind speed intervals.

1770 OCTOBER 2015|


Model experiments

LUCAS Phase I : Idealised experiments on continental scale for past and future


LUCAS: Experiments for the past - ERA-Interim

© D.Rechid, GERICS


LUCAS: Experiments for the future - GCM /SSPs*RCPs

© D.Rechid, GERICS


  global grid 0.25 x 0.25 degree spatial resolution

  850-2100 annual land-use states, transitions, and new: agriculture management layers

  12 possible land-use classes, > 100 possible transitions per grid cell per year, including crop rotations

  Agriculture management layers including irrigation, fertilizer, and biofuel management

New generation “Land Use Harmonization” LUH2in preparation to CMIP6 by LUMIP (by Hurrt et al.)

LUH2 v1.0h release (April 29, 2016): historical land-use forcing dataset 850 - 2015http://luh.umd.edu/data.shtml


Provision of Land Use Forcing for CMIP6 from LUMIPLand units in each grid cell

http://luh.umd.edu/data.shtml

Forested Primary Land Non forested Primary land

Secondary land forested

Non forested Secondary

land

Managed Pasture land

C4 Annual

crop

C3 Annual Crop Urban

land

Rangeland

C3 Perennial

Crop

C4 Perennial

crop

C3 Nitrogen

fixing crop

© de Noblet-Ducoudré [pers. communication]


  EURO-CORDEX-LUC workshop on Thursday, 5 to 7 pm, U28

Next steps

Consistent integration of land use change into the RCMs:

•  learn from LUMIP protocol (global Land Use Model Intercomparison Project) •  use a common reference vegetation distribution in the regional models •  consistent translation of land use forcing: clear allocation methods of new land use

on existing land use types   clear land use implementation protocol

Detailed definition of idealised experiments on continental scale (phase I)   concrete simulation protocol


Outlook

LUCAS Phase II : High resolution experiments in pilot regions for past and future


Pilot regions and nests for high resolution modelling

Criteria for Pilot Regions:

Distinct pattern of land-atmosphere coupling strength (e.g. Knist et al., in preparation)

Regions with major rapid historic land use transitions (e.g. Munteanu et al., 2014)

Availability of high-quality observational data (e.g. Szilágyi & Kovács, 2010; Zacharias et al., 2011; Simmer et al., 2015)

x

EURO-CORDEX orography

TERENO Terrestrial Environmental Observatory: Eifel/Lower Rhine Valley Observatory

[m]

xExample Pilot regions / Pilot region nests(not fixed so far)

© GERICS


LUCAS Phase II : High resolution experiments


Global Re-analyses Data

Human Systems

Ecosystems

Regional Earth System

EmissionsLand use change

Natural land coverdynamics

GHG & aerosol emissions / concentrations

Atmosphericvariables

Anthropogenic land cover / change & land managment

Observations& ModelsPast re-constructions

Models & ScenariosFuture projections

ERA-Interim

at 1 km:HILDA(Fuchs et al. 2013)

RCMs 25 km

RCMs 10 km

RCMs 3 km

Pilot regions

Pilot region nest

Continental scale

© D.Rechid, GERICS


Thank you for your attention!

Do you have questions, comments, suggestions? Would you like to contribute?

Please contact: [email protected]

Source: Pixabay, CC0 Public Domain


I 1

I 2

I 3

I 4

Expected impacts


  Identify potential biases that arise from missing land use dynamics in regional climate change projections and help improve the simulated impacts

  Support decisions on land management by revealing the potential of LUC to attenuate negative impacts of global warming

  Better constrain further strategic development of coupled land-atmosphere and regional earth system models


High-resolution reconstructions of historic land use for Europe between 1900-2010

Source: Fuchs R., M. Herold, P.H. Verburg, J.G.P.W. Clevers (2013): A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe, Biogeosciences, 10(3), 1543–1559, doi:10.5194/bg-10-1543-2013

HILDA: HIstoric Land Dynamics Assessment

EU27 + Switzerland 1 km resolution(1950-2010 15,46 % of land area affected by land use changes)

  Areas of major urbanisation and afforestation/reforestation for 1950-2010


Example study Land Cover Change:Potential re-/afforestation in Europe (by Galos et al. 2012, 2013)

Simulation domain with the present forest cover in the regional model

Horizontal resolution: 0.22°

Increase of forest cover with potential afforestation compared to present forested area


Example study Land Cover Change:Potential re-/afforestation in Europe (by Galos et al. 2012, 2013)

Surface temperature change JJA

driven by GHG concentration change2071-2090 vs. 1961-1990

driven by re-/afforestation2071-2090

Precipitation change JJA


Forests Croplands

Natural Grasslands

Grass

Crops Crops

Crops

Grass

Grass Forests

Initial state: 50% grass, 50% forests

Final imposed state: 50% crops

implemented

Forests

Forests

Different LUC Implementation Strategies:Where do/did croplands/pastures come from?

© de Noblet-Ducoudré


Agent-based land use modellingExplore the development of European land system under different climatic and socio-economic scenarios (e.g. SSP-RCP combinations), defining:

•  Climate impacts (land productivity)•  Societal demand levels for range of ecosystem goods

and services•  Institutional & political interventions•  Adaptation options and individual/social behaviour

Model based on decision-making of individual land managers and institutional actors; includes economic and non-economic factors & cross-sectoral competition

Starting from 2010 baseline land cover, simulate changes in:•  Broad land use categories based on production type

and intensity– tailored to requirements of climate models

•  Ecosystem service supply•  Institutional/political strategies

CRAFTY – EU Competition for Resources between Agent Functional TYpes (here: baseline simulation of some broad land use categories) Outputs available at flexible spatial and temporal scales; default annual, 1km2

Calum Brown; University of Edinburgh, personal communication

© C. Brown, University of Edinburgh

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