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High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

TL;DR: The High-ResMIP (High-resolution Model Intercomparison Project) as mentioned in this paper is a multi-model approach to the systematic investigation of the impact of horizontal resolution on the simulated mean climate and its variability.
Abstract: . Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

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Geosci. Model Dev., 9, 4185–4208, 2016
www.geosci-model-dev.net/9/4185/2016/
doi:10.5194/gmd-9-4185-2016
© Author(s) 2016. CC Attribution 3.0 License.
High Resolution Model Intercomparison Project
(HighResMIP v1.0) for CMIP6
Reindert J. Haarsma
1
, Malcolm J. Roberts
2
, Pier Luigi Vidale
3
, Catherine A. Senior
2
, Alessio Bellucci
4
, Qing Bao
5
,
Ping Chang
6
, Susanna Corti
7
, Neven S. Fu
ˇ
ckar
8
, Virginie Guemas
8,23
, Jost von Hardenberg
7
, Wilco Hazeleger
1,9,10
,
Chihiro Kodama
11
, Torben Koenigk
12
, L. Ruby Leung
13
, Jian Lu
13
, Jing-Jia Luo
14
, Jiafu Mao
15
,
Matthew S. Mizielinski
2
, Ryo Mizuta
16
, Paulo Nobre
17
, Masaki Satoh
18
, Enrico Scoccimarro
4,22
, Tido Semmler
19
,
Justin Small
20
, and Jin-Song von Storch
21
1
Weather and Climate modeling, Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
2
Met Office Hadley Centre, Exeter, UK
3
NCAS-Climate, University of Reading, Reading, UK
4
Climate Simulation and Prediction Divsion, Centro Euro-Mediterraneo per i Cambiamenti Climatici, Bologna, Italy
5
Institute of Atmospheric Physics, Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid
Dynamics, Chinese Academy of Sciences, Beijing, China P. R.
6
Department of Oceanography, Texas A&M University, College Station, Texas, USA
7
Institute of Atmospheric Sciences and Climate, National Research Council, Bologna, Italy
8
Earth Sciences, Barcelona Supercomputing Center, Barcelona, Spain
9
Netherlands eScience Center, Amsterdam, the Netherlands
10
Meteorology and Air Quality, Wageningen University, Wageningen, the Netherlands
11
Atmospheric Science, Japan Agency for Marine-Earth Science and Technology, Tokyo, Japan
12
Climate Research, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
13
Earth System Analysis and Modeling, Pacific Northwest National Laboratory, Richland, USA
14
Climate Dynamics, Bureau of Meteorology, Melbourne, Australia
15
Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory,
Oak Ridge,Tennessee, USA
16
Climate Research Department, Meteorological Research Institute, Tsukuba, Japan
17
Climate Modeling, Instituto Nacional de Pesquisas Espaciais, São José dos Campos, Brazil
18
Atmosphere and Ocean Research Institute, The University of Tokyo, Tokyo, Japan
19
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
20
Climate and Global Dynamics Divsion, National Center for Atmospheric Research, Boulder, Colorado, USA
21
The Ocean in the Earth System, Max-Planck-Institute for Meteorology, Hamburg, Germany
22
Sezione di Bologna, Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy
23
Meteo-France, Centre National de Recherches Meteorologiques, Toulouse, France
Correspondence to: Reindert J. Haarsma (haarsma@knmi.nl)
Received: 30 March 2016 Published in Geosci. Model Dev. Discuss.: 12 April 2016
Revised: 5 July 2016 Accepted: 10 October 2016 Published: 22 November 2016
Published by Copernicus Publications on behalf of the European Geosciences Union.

4186 R. J. Haarsma et al.: High Resolution Model Intercomparison Project for CMIP6
Abstract. Robust projections and predictions of climate vari-
ability and change, particularly at regional scales, rely on the
driving processes being represented with fidelity in model
simulations. The role of enhanced horizontal resolution in
improved process representation in all components of the cli-
mate system is of growing interest, particularly as some re-
cent simulations suggest both the possibility of significant
changes in large-scale aspects of circulation as well as im-
provements in small-scale processes and extremes.
However, such high-resolution global simulations at cli-
mate timescales, with resolutions of at least 50 km in the at-
mosphere and 0.25
in the ocean, have been performed at
relatively few research centres and generally without overall
coordination, primarily due to their computational cost. As-
sessing the robustness of the response of simulated climate
to model resolution requires a large multi-model ensemble
using a coordinated set of experiments. The Coupled Model
Intercomparison Project 6 (CMIP6) is the ideal framework
within which to conduct such a study, due to the strong link
to models being developed for the CMIP DECK experiments
and other model intercomparison projects (MIPs).
Increases in high-performance computing (HPC) re-
sources, as well as the revised experimental design for
CMIP6, now enable a detailed investigation of the impact
of increased resolution up to synoptic weather scales on the
simulated mean climate and its variability.
The High Resolution Model Intercomparison Project
(HighResMIP) presented in this paper applies, for the first
time, a multi-model approach to the systematic investigation
of the impact of horizontal resolution. A coordinated set of
experiments has been designed to assess both a standard and
an enhanced horizontal-resolution simulation in the atmo-
sphere and ocean. The set of HighResMIP experiments is di-
vided into three tiers consisting of atmosphere-only and cou-
pled runs and spanning the period 1950–2050, with the pos-
sibility of extending to 2100, together with some additional
targeted experiments. This paper describes the experimental
set-up of HighResMIP, the analysis plan, the connection with
the other CMIP6 endorsed MIPs, as well as the DECK and
CMIP6 historical simulations. HighResMIP thereby focuses
on one of the CMIP6 broad questions, “what are the origins
and consequences of systematic model biases?”, but we also
discuss how it addresses the World Climate Research Pro-
gram (WCRP) grand challenges.
1 Introduction
Recent studies with global high-resolution climate models
have demonstrated the added value of enhanced horizontal
atmospheric resolution compared to the output from models
in the CMIP3 and CMIP5 archive. They showed significant
improvement in the simulation of aspects of the large-scale
circulation such as El Niño–Southern Oscillation (ENSO)
(Shaffrey et al., 2009; Masson et al., 2012), tropical insta-
bility waves (Roberts et al., 2009), the Gulf Stream (Kirt-
man et al., 2012), and Kuroshio (Ma et al., 2016), and their
influence on the atmosphere (Minobe et al., 2008; Chas-
signet and Marshall, 2008; Kuwano-Yoshida et al., 2010;
Small et al., 2014b; Ma et al., 2015), the global water cycle
(Demory et al., 2014), snow cover (Kapnick and Delworth,
2013), the Atlantic inter-tropical convergence zone (ITCZ)
(Doi et al., 2012), the jet stream (Lu et al., 2015; Sakaguchi
et al., 2015), storm tracks (Hodges et al., 2011), and Euro–
Atlantic blocking (Jung et al., 2012). High horizontal reso-
lution in the atmosphere has a positive impact in represent-
ing the non-Gaussian probability distribution associated with
the climatology of quasi-persistent low-frequency variabil-
ity weather regimes (Dawson et al., 2012). In addition, the
increased resolution enables a more realistic simulation of
small-scale phenomena with potentially severe impacts such
as tropical cyclones (Shaevitz et al., 2015; Zhao et al., 2009;
Bengtsson et al., 2007; Murakami et al., 2015; Walsh et al.,
2012; Ohfuchi et al., 2004; Bell et al., 2013; Strachan et al.,
2013; Walsh et al., 2015), tropical–extratropical interactions
(Baatsen et al., 2015; Haarsma et al., 2013), and polar lows
(Zappa et al., 2014). Other phenomena that are sensitive to
increasing resolution are ocean mixing, sea-ice dynamics,
the diurnal precipitation cycle (Sato et al., 2009; Birch et
al., 2014; Vellinga et al., 2016), quasi biennial oscillation
(QBO) (Hertwig et al., 2015), the Madden–Julian oscillation
(MJO) representation (Peatman et al., 2015), atmospheric
low-level coastal jets and their impact on sea surface temper-
ature (SST) bias along eastern boundary upwelling regions
(Patricola and Chang, 2016; Zuidema et al., 2016), and mon-
soons (Sperber et al., 1994; Lal et al., 1997; Martin, 1999).
The improved simulation of climate also results in better rep-
resentation of extreme events such as heat waves, droughts
(Van Haren et al., 2015), and floods. Enhanced horizontal
resolution in ocean models can also have beneficial impacts
on the simulations. Such impacts include improved simula-
tion of boundary currents, Indonesian throughflow, and wa-
ter exchange through narrow straits, coastal currents such as
the Kuroshio, Leeuwin Current, and Eastern Australian Cur-
rent, upwelling, oceanic eddies, SST fronts (Sakamoto et al.,
2012; Delworth et al., 2012; Small et al., 2015), ENSO (Ma-
sumoto et al., 2004; Smith et al., 2000; Rackow et al., 2016),
and sea-ice drift and deformation (Zhang et al., 1999; Gent
et al., 2010). Although enhanced resolution in atmosphere
and ocean models had a beneficial impact on a wide range
of modes of internal variability, the relatively short high-
resolution simulations make it difficult to sort that out in de-
tail due to large decadal fluctuations in interannual variability
in for instance ENSO (Sterl et al., 2007).
The requirement for a multitude of multi-centennial sim-
ulations, due to the slow adjustment times in the Earth sys-
tem, and the inclusion of Earth system processes and feed-
backs, such as those that involve biogeochemistry, have
meant that model resolution within CMIP has progressed rel-
Geosci. Model Dev., 9, 4185–4208, 2016 www.geosci-model-dev.net/9/4185/2016/

R. J. Haarsma et al.: High Resolution Model Intercomparison Project for CMIP6 4187
atively slowly. In CMIP3, the horizontal typical resolution
was 250 km in the atmosphere and 1.5
in the ocean, while
more than 7 years later in CMIP5 this had only increased to
150 km and 1
respectively. Higher-resolution simulations,
with resolutions of at least 50 km in the atmosphere and 0.25
in the ocean, have only been performed at relatively few re-
search centres until now, and generally these have been indi-
vidual “simulation campaigns” rather than large multi-model
comparisons (e.g. Shaffrey et al., 2009; Navarra et al., 2010;
Delworth et al., 2012; Kinter et al., 2013; Mizielinski et al.,
2014; Davini et al., 2016). Due to the large computer re-
sources needed for these simulations, synergy will be gained
if they are carried out in a coordinated way, enabling the
construction of a multi-model ensemble (since the ensemble
size for each model will be limited) with common integra-
tion periods, forcing, and boundary conditions. The CMIP3
and CMIP5 databases provide outstanding examples of the
success of this approach. The multi-model mean has often
proven to be superior to individual models in seasonal (Hage-
dorn et al., 2005) and decadal forecasting (Bellucci et al.,
2015) as well as in climate projections (Tebaldi and Knutti,
2007) in response to radiative forcing. Moreover, significant
scientific understanding has been gained from analysing the
inter-model spread and attempting to attribute this spread to
model formulation (Sanderson et al., 2015).
The primary goal of HighResMIP is to determine the ro-
bust benefits of increased horizontal model resolution based
on multi-model ensemble simulations to make this practi-
cal, vertical resolution will not be considered. The argument
for this is that the scaling between horizontal and vertical
resolution must obey N/f , where N is the Brunt–Väisälä
frequency and f the Coriolis parameter. This implies a fac-
tor of 100, between horizontal and vertical resolution, which
is well satisfied by the model configurations in the High-
ResMIP group. In addition, components such as aerosols will
be simplified to improve comparability between models. The
top priority CMIP6 broad question for HighResMIP is “what
are the origins and consequences of systematic model bi-
ases?”, which will focus on understanding model error (ap-
plied to mean state and variability), via process-level assess-
ment, rather than on climate sensitivity. This has motivated
our choices in terms of proposed simulations, which empha-
size sampling the recent past and the next few decades where
internal climate variability is a more important factor than
climate sensitivity to changes in greenhouses gases (Hawkins
and Sutton, 2011), at least at regional scales.
The use of process-based assessment is crucial to High-
ResMIP, since we aim to better understand the dynamical
and physical reasons for differences in model results induced
by resolution change, in order to increase our trust in the
fidelity of models. Such process understanding will either
contribute to bolstering our confidence in results from lower-
resolution (but with greater complexity) CMIP simulations
or to enabling a better understanding of the limitations of
such models. There are an increasing number of studies sug-
gesting that, in individual models, important processes are
better represented at higher resolution, indicating ways to po-
tentially increase our confidence in climate projections (e.g.
Vellinga et al., 2016). A wide variety of processes will be as-
sessed, from global and regional drivers of climate variabil-
ity, down to mesoscale eddies in atmosphere and ocean in
the atmosphere these include tropical cyclones (Zhao et al.,
2009; Bell et al., 2013; Rathmann et al., 2014; Roberts et al.,
2015; Walsh et al., 2015) and eddy–mean flow interactions
(Novak et al., 2015; Schiemann et al., 2016), while for the
ocean they are an important mechanism for mesoscale air–
sea interactions (Chelton and Xie, 2010; Bryan et al., 2010;
Frenger et al., 2013; Ma et al., 2015, 2016), trans-basin heat
transport (e.g. Agulhas leakage) (Sein et al., 2016), convec-
tion, and oceanic fronts.
HighResMIP will coordinate the efforts in the high-
resolution modelling community. Joint analysis, based on
process-based assessment and seeking to attribute model per-
formance to emerging physical climate processes (without
the complications of (bio)geochemical Earth system feed-
backs) and sensitivity of model physics to model resolution,
will further highlight the impact of enhanced horizontal reso-
lution on the simulated climate. As the widespread impact of
horizontal resolution, in the range of a few hundred to about
10 km, on climate simulation has been demonstrated in the
past, it is expected that HighResMIP will contribute to many
of the grand challenges of the WCRP, and hence such analy-
sis may begin to reveal at what resolution in this range par-
ticular processes can be robustly represented.
The remainder of this paper is structured as follows. Sec-
tion 2 gives an overview of the simulations, while Sect. 3
describes the tiers of simulation in detail. Section 4 makes
links between these and the CMIP6 DECK and other CMIP6
MIPs, Sect. 5 describes the data storage and sharing plans,
and Sects. 6 and 7 describe the analysis and potential ap-
plication plans. Conclusions and discussion are contained in
Sect. 8. Several appendices contain more detail of the exper-
imental design and forcing.
2 Outline of HighResMIP simulations
The main experiments will be divided into Tiers 1, 2, and
3. They are illustrated in Fig. 1. We provide an outline of
these different tiers, with more detail in Sect. 3. Each set of
simulations comprises model resolutions at both a standard
and a high resolution, where the standard-resolution model
is expected to be used in a set of CMIP6 DECK simulations
and is considered the entry card for HighResMIP.
The Tier 1 experiments will be historical forced atmo-
sphere (ForcedAtmos) runs for the period 1950–2014. A
number of centres have already performed similar high-
resolution simulations and published their results (CAM5
Bacmeister et al., 2014; HadGEM3 Mizielinski et al., 2014;
NICAM Satoh et al., 2014; EC-Earth Haarsma et al., 2013);
www.geosci-model-dev.net/9/4185/2016/ Geosci. Model Dev., 9, 4185–4208, 2016

4188 R. J. Haarsma et al.: High Resolution Model Intercomparison Project for CMIP6
0
50
150
100
1950
2000
2050
2100
2015
Tier 1
Tier 2
Tier 3
Model run time [yr]
Forcing and B.C. time [yr]
CMIP6 HighResMIP
Figure 1. Schematic outline of Tiers 1, 2, and 3. Tier 1 is a 64-year
AMIP simulation from 1950 to 2014 with historical forcings. The
first part of Tier 2 (coupled ocean–atmosphere simulations) consists
of a 50-year integration starting from the 1950 initial state under
1950s conditions. Thereafter this simulation will be continued by
two branches of 100 years: one continuing with the 1950s forcing
(control run) and the other using until 2014 historical forcings and
for 2015–2050 SSPx (scenario run). Tier 3 is the extension of Tier 1
from 2014 to 2050 (obliged, solid line) and 2051–2100 (optional,
dashed line) for SSPx.
hence, these runs should not present prohibitively large
technical difficulties. Restricting the ForcedAtmos runs to
the historical period also makes it possible for numerical
weather prediction (NWP) centres to contribute to the multi-
model ensemble. Nineteen international groups have ex-
pressed interest in completing these simulations as shown
in Appendix A. All centres participating in HighResMIP are
obliged to participate at least in Tier 1.
The coupled experiments in Tier 2 are more challenging,
but provide an opportunity to understand the role of natu-
ral variability, due to the centennial scale, and to investigate
the impact of high resolution on future climate. Although
a few centres have previously carried out high-resolution
coupled simulations such as SINTEX-F2, GFDL, Hadley,
MIROC, and CESM (Masson et al., 2012; Delworth et al.,
2012; Mecking et al., 2016; Sakamoto et al., 2012; Small
et al., 2014a), considerable issues including mean-state bi-
ases, climate drift, and ocean spin-up remain. Due to these
issues and the large amount of computer resources needed to
complete both a reference and a transient simulation, fewer
centres (currently six) are confirmed participants for these
experiments. The period of the coupled simulations is 1950–
2050.
Future atmosphere-only simulations for the period 2015–
2100 will be carried out in Tier 3. Although the future pe-
riod covers the entire present century, the simulations can
for computational reasons be restricted to the mid-century
(2050).
For a clean evaluation of the impact of horizontal resolu-
tion, additional tuning of the high-resolution version of the
model should be avoided. The experimental set-up and de-
sign of the standard resolution experiments will be exactly
the same as for the high-resolution runs. This enables the use
of HighResMIP simulations for sensitivity studies investigat-
ing the impact of resolution. If unacceptably large physical
biases emerge in the high-resolution simulations, all neces-
sary alterations should be thoroughly documented. The re-
quirement of no additional tuning is more relevant for the
coupled runs because atmosphere-only models are strongly
constrained by the prescribed SSTs.
2.1 Common forcing fields
To focus on the impact of resolution on the design of the
HighResMIP, simulations should minimize the difference in
forcings and model set-up that would hamper the interpreta-
tion of the results.
Most of the forcing fields are the same as those used in the
CMIP6 Historical Simulation that are described separately
in this Special Issue (Eyring et al., 2016) and are provided
via the CMIP6 data portal. For the future time period, GHG
and aerosol concentrations from a high-end emission sce-
nario of the Shared Socioeconomic Pathways (SSPs) will be
prescribed, which in the following will be denoted by SSPx.
A summary of the differences in forcing between the CMIP6
AMIPII protocol and the Tier 1 and 2 simulations is given in
Table 1.
2.1.1 Aerosol
A potential large source of uncertainty is the aerosol forc-
ing for the same aerosol emissions, different models can
simulate very different aerosol concentrations, hence produc-
ing different radiative forcing. In HighResMIP, each model
will use its own aerosol concentration background climatol-
ogy. To this will be added an anthropogenic time-varying,
albeit uniform, forcing provided via the MACv2-SP method
by Stevens et al. (2016). These will be computed using a new
approach to prescribe aerosols in terms of optical proper-
ties and fractional change in cloud droplet effective radius
to provide a more consistent representation of aerosol forc-
ing. This will provide an aerosol forcing field that minimizes
the differences between models as well as reduces the need
for model tuning. This method is also the standard method in
CMIP6 DECK for models without interactive aerosols.
2.1.2 Land surface
The land surface properties will also be different from the
CMIP6 AMIPII protocol. Given the requirement to make
model forcing as simple as possible to aid comparability,
the land surface properties will be climatological seasonally
varying conditions of leaf area index (LAI), with no dynamic
vegetation and a constant land use/land cover consistent with
Geosci. Model Dev., 9, 4185–4208, 2016 www.geosci-model-dev.net/9/4185/2016/

R. J. Haarsma et al.: High Resolution Model Intercomparison Project for CMIP6 4189
Table 1. Forcings and initialization for the Historic simulations (pre-2015).
Input CMIP6 AMIPII HighResMIP Tier 1
highresSST-present
Tier 2 coupled
hist-1950, control-1950
Period 1979–2014 1950–2014 1950–2014
SST, sea-ice forcing Monthly 1
PCMDI dataset
(merge of HadISST2 and
NOAA OI-v2)
Daily
1
4
HadISST2-based
dataset (Rayner et al., 2016)
N/A
Anthropogenic aerosol
forcing
Concentrations or emissions,
as used in Historic CMIP6
simulations (Eyring et al.,
2016)
Recommended: specified
aerosol optical depth and
effective radius deltas from
the MACv2.0-SP model
(Stevens et al., 2016)
Same as Tier 1
Volcanic As used in Historic As used in Historic Same as Tier 1
Natural aerosol forcing
dust, DMS
As used in Historic Same Same
GHG concentrations As used in Historic Same Same
Ozone forcing CMIP6 monthly concentra-
tions, 3-D field, or zonal mean,
as in Historic
Same Same
Solar variability As in Historic Same Same
Imposed boundary
conditions land sea mask,
orography, land surface
types, soil properties, leaf
area index/canopy height,
river paths
Based on observations,
documented. LAI to evolve
consistently with land use
change.
Land use fixed in time, LAI
repeat (monthly or otherwise)
cycle representative of the
present-day period around
2000
Same as Tier 1
Initial atmosphere state Unspecified from prior model
simulation, or observations, or
other reasonable ways.
ERA-20C reanalysis
recommended (ideally same
at high and standard resolu-
tion)
From spin-up of coupled
model in Sect. 3.2.1
Initial land surface state Unspecified as above. May
require several years of spin-up,
cycling 1979 or starting in early
1970s
ERA-20C reanalysis
recommended, spun up in
some way
From spin-up
Ensemble number Typically 3 1 1
Initial ocean/sea-ice state N/A N/A From coupled spin-up
the present-day period, centered around 2000. Consideration
was given to attempting to further constrain land surface
properties to be more similar between groups, but this was
rejected given the complex and different ways in which re-
motely sensed values are mapped to model land surface prop-
erties. However, an additional targeted experiment has been
included to further investigate the sensitivity to land surface
representation. This is outlined in Appendix C.
2.1.3 Initialization and spin-up of the atmosphere–land
system
As discussed in Eyring et al. (2016), the initialization of land
surface and atmosphere requires several years of spin-up to
reach quasi-equilibrium before the simulation proper can be-
gin. We recommend this is done using the first few years
of the forcing datasets before restarting in 1950. We further
recommend that the initial condition for the atmosphere and
land for 1950 (for the highresSST-present and the highres-
1950 experiment) come from the ERA-20C reanalysis from
www.geosci-model-dev.net/9/4185/2016/ Geosci. Model Dev., 9, 4185–4208, 2016

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426 citations

Journal ArticleDOI
TL;DR: In this paper, the main advancements of the Beijing Climate Center (BCC) climate system model from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to phase 6 (CMP6) are presented, in terms of physical parameterizations and model performance.
Abstract: . The main advancements of the Beijing Climate Center (BCC) climate system model from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to phase 6 (CMIP6) are presented, in terms of physical parameterizations and model performance. BCC-CSM1.1 and BCC-CSM1.1m are the two models involved in CMIP5, whereas BCC-CSM2-MR, BCC-CSM2-HR, and BCC-ESM1.0 are the three models configured for CMIP6. Historical simulations from 1851 to 2014 from BCC-CSM2-MR (CMIP6) and from 1851 to 2005 from BCC-CSM1.1m (CMIP5) are used for models assessment. The evaluation matrices include the following: (a) the energy budget at top-of-atmosphere; (b) surface air temperature, precipitation, and atmospheric circulation for the global and East Asia regions; (c) the sea surface temperature (SST) in the tropical Pacific; (d) sea-ice extent and thickness and Atlantic Meridional Overturning Circulation (AMOC); and (e) climate variations at different timescales, such as the global warming trend in the 20th century, the stratospheric quasi-biennial oscillation (QBO), the Madden–Julian Oscillation (MJO), and the diurnal cycle of precipitation. Compared with BCC-CSM1.1m, BCC-CSM2-MR shows significant improvements in many aspects including the tropospheric air temperature and circulation at global and regional scales in East Asia and climate variability at different timescales, such as the QBO, the MJO, the diurnal cycle of precipitation, interannual variations of SST in the equatorial Pacific, and the long-term trend of surface air temperature.

424 citations

Journal ArticleDOI
TL;DR: The authors discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting.
Abstract: Earth system models are complex and represent a large number of processes, resulting in a persistent spread across climate projections for a given future scenario. Owing to different model performances against observations and the lack of independence among models, there is now evidence that giving equal weight to each available model projection is suboptimal. This Perspective discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting. These approaches are needed to distil the most credible information on regional climate changes, impacts, and risks for stakeholders and policy-makers.

397 citations

References
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Journal ArticleDOI
TL;DR: The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance the authors' knowledge of climate variability and climate change.
Abstract: The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades...

12,384 citations

Journal ArticleDOI
TL;DR: A weekly 1° spatial resolution optimum interpolation (OI) sea surface temperature (SST) analysis has been produced at the National Oceanic and Atmospheric Administration (NOAA) using both in situ and satellite data from November 1981 to the present as mentioned in this paper.
Abstract: A weekly 1° spatial resolution optimum interpolation (OI) sea surface temperature (SST) analysis has been produced at the National Oceanic and Atmospheric Administration (NOAA) using both in situ and satellite data from November 1981 to the present. The weekly product has been available since 1993 and is widely used for weather and climate monitoring and forecasting. Errors in the satellite bias correction and the sea ice to SST conversion algorithm are discussed, and then an improved version of the OI analysis is developed. The changes result in a modest reduction in the satellite bias that leaves small global residual biases of roughly −0.03°C. The major improvement in the analysis occurs at high latitudes due to the new sea ice algorithm where local differences between the old and new analysis can exceed 1°C. Comparisons with other SST products are needed to determine the consistency of the OI. These comparisons show that the differences among products occur on large time- and space scales wit...

4,346 citations


"High Resolution Model Intercomparis..." refers background in this paper

  • ...Since the high-resolution simulations will approach 25 km, this means there is a requirement for a daily, 14 ◦ dataset for a period longer than satellite-based datasets (such as Reynolds et al., 2002) are able to provide....

    [...]

Journal ArticleDOI
TL;DR: In this article, the authors present the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21-CMIP6-Endorsed MIPs.
Abstract: . By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.

4,192 citations

Journal ArticleDOI
TL;DR: In this article, a new high-resolution regional climate change ensemble has been established for Europe within the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) initiative.
Abstract: A new high-resolution regional climate change ensemble has been established for Europe within the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) initiative. The first set of simulations with a horizontal resolution of 12.5 km was completed for the new emission scenarios RCP4.5 and RCP8.5 with more simulations expected to follow. The aim of this paper is to present this data set to the different communities active in regional climate modelling, impact assessment and adaptation. The EURO-CORDEX ensemble results have been compared to the SRES A1B simulation results achieved within the ENSEMBLES project. The large-scale patterns of changes in mean temperature and precipitation are similar in all three scenarios, but they differ in regional details, which can partly be related to the higher resolution in EURO-CORDEX. The results strengthen those obtained in ENSEMBLES, but need further investigations. The analysis of impact indices shows that for RCP8.5, there is a substantially larger change projected for temperature-based indices than for RCP4.5. The difference is less pronounced for precipitation-based indices. Two effects of the increased resolution can be regarded as an added value of regional climate simulations. Regional climate model simulations provide higher daily precipitation intensities, which are completely missing in the global climate model simulations, and they provide a significantly different climate change of daily precipitation intensities resulting in a smoother shift from weak to moderate and high intensities.

1,627 citations

Journal ArticleDOI
TL;DR: The motivation for using multi-model ensembles, the methodologies published so far and their results for regional temperature projections are outlined, and the challenges in interpreting multi- model results are discussed.
Abstract: Recent coordinated efforts, in which numerous climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Thos...

1,582 citations


"High Resolution Model Intercomparis..." refers background in this paper

  • ..., 2015) as well as in climate projections (Tebaldi and Knutti, 2007) in response to radiative forcing....

    [...]

  • ...The multi-model mean has often proven to be superior to individual models in seasonal (Hagedorn et al., 2005) and decadal forecasting (Bellucci et al., 2015) as well as in climate projections (Tebaldi and Knutti, 2007) in response to radiative forcing....

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