Articles | Volume 11, issue 6
Geosci. Model Dev., 11, 2373–2392, 2018
https://doi.org/10.5194/gmd-11-2373-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 11, 2373–2392, 2018
https://doi.org/10.5194/gmd-11-2373-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper 19 Jun 2018
Model evaluation paper | 19 Jun 2018
The seasonal relationship between intraseasonal tropical variability and ENSO in CMIP5
Tatiana Matveeva et al.
Related authors
No articles found.
Marine Bretagnon, Aurélien Paulmier, Véronique Garçon, Boris Dewitte, Séréna Illig, Nathalie Leblond, Laurent Coppola, Fernando Campos, Federico Velazco, Christos Panagiotopoulos, Andreas Oschlies, J. Martin Hernandez-Ayon, Helmut Maske, Oscar Vergara, Ivonne Montes, Philippe Martinez, Edgardo Carrasco, Jacques Grelet, Olivier Desprez-De-Gesincourt, Christophe Maes, and Lionel Scouarnec
Biogeosciences, 15, 5093–5111, https://doi.org/10.5194/bg-15-5093-2018, https://doi.org/10.5194/bg-15-5093-2018, 2018
Short summary
Short summary
In oxygen minimum zone, the fate of the organic matter is a key question as the low oxygen condition would preserve the OM and thus enhance the biological carbon pump while the high microbial activity would foster the remineralisation and the greenhouse gases emission. To investigate this paradigm, sediment traps were deployed off Peru. We pointed out the influence of the oxygenation as well as the organic matter quantity and quality on the carbon transfer efficiency in the oxygen minimum zone.
Michelle I. Graco, Sara Purca, Boris Dewitte, Carmen G. Castro, Octavio Morón, Jesús Ledesma, Georgina Flores, and Dimitri Gutiérrez
Biogeosciences, 14, 4601–4617, https://doi.org/10.5194/bg-14-4601-2017, https://doi.org/10.5194/bg-14-4601-2017, 2017
Short summary
Short summary
The Peruvian coastal upwelling ecosystem is a natural laboratory to study climatic variability and climate change. We examined the variability in the OMZ in the last decades in connection with the equatorial Pacific strong 1997–1998 El Niño event and the influence of central Pacific El Niño events and enhanced equatorial Kelvin wave activity since 2000. The data reveal two contrasting regimes and a long-term trend corresponding to a deepening of the oxygen-deficient waters and warming.
Luis Bravo, Marcel Ramos, Orlando Astudillo, Boris Dewitte, and Katerina Goubanova
Ocean Sci., 12, 1049–1065, https://doi.org/10.5194/os-12-1049-2016, https://doi.org/10.5194/os-12-1049-2016, 2016
Short summary
Short summary
We evaluated the seasonal variability in Ekman transport, pumping and their relative contribution to total upwelling along the central-northern Chile region (~30ºS) from a high-resolution atmospheric model simulation. The results showed that the relative contribution of Ekman transport and pumping to the vertical transport along the coast, considering the estimated wind drop-off length, indicated meridional alternation between both mechanisms, modulated by orography and the intricate coastline.
Oscar Vergara, Boris Dewitte, Ivonne Montes, Veronique Garçon, Marcel Ramos, Aurélien Paulmier, and Oscar Pizarro
Biogeosciences, 13, 4389–4410, https://doi.org/10.5194/bg-13-4389-2016, https://doi.org/10.5194/bg-13-4389-2016, 2016
Short summary
Short summary
The Southeast Pacific hosts one of the most extensive oxygen minimum zone (OMZ), yet the dynamics behind it remain unveiled. We use a high-resolution coupled physical–biogeochemical model to document the seasonal cycle of dissolved oxygen within the OMZ in both the coastal zone and the offshore ocean. The OMZ seasonal variability is driven by the seasonal fluctuations of the dissolved oxygen eddy flux, with a peak in Austral winter (fall) at the northern (southern) boundary and near the coast.
A. Olchev, A. Ibrom, O. Panferov, D. Gushchina, H. Kreilein, V. Popov, P. Propastin, T. June, A. Rauf, G. Gravenhorst, and A. Knohl
Biogeosciences, 12, 6655–6667, https://doi.org/10.5194/bg-12-6655-2015, https://doi.org/10.5194/bg-12-6655-2015, 2015
Short summary
Short summary
The time series analysis of the main meteorological parameters and components of CO2 and H2O fluxes showed a high evapotranspiration (ET) and gross primary production (GPP) sensitivity of the tropical rainforest to meteorological variations caused by El Niño-Southern Oscillation (ENSO) events. Incoming solar radiation is the main governing factor that is responsible for ET and GPP variability. Changes in precipitation due to moderate ENSO events did not have any notable effect on ET and GPP.
I. Hernández-Carrasco, J. Sudre, V. Garçon, H. Yahia, C. Garbe, A. Paulmier, B. Dewitte, S. Illig, I. Dadou, M. González-Dávila, and J. M. Santana-Casiano
Biogeosciences, 12, 5229–5245, https://doi.org/10.5194/bg-12-5229-2015, https://doi.org/10.5194/bg-12-5229-2015, 2015
Short summary
Short summary
We have reconstructed maps of air-sea CO2 fluxes at high resolution (4 km) in the offshore Benguela region using sea surface temperature and ocean colour data and CarbonTracker CO2 fluxes data at low resolution (110 km).
The inferred representation of pCO2 improves the description provided by CarbonTracker, enhancing small-scale variability.
We find that the resolution, as well as the inferred pCO2 data itself, is closer to in situ measurements of pCO2.
Related subject area
Climate and Earth system modeling
Developing a common, flexible and efficient framework for weakly coupled ensemble data assimilation based on C-Coupler2.0
JULES-CN: a coupled terrestrial carbon–nitrogen scheme (JULES vn5.1)
Ensemble prediction using a new dataset of ECMWF initial states – OpenEnsemble 1.0
Global evaluation of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 (r5986)
Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1
A process-based evaluation of the Intermediate Complexity Atmospheric Research Model (ICAR) 1.0.1
Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model
Sensitivity of surface solar radiation to aerosol–radiation and aerosol–cloud interactions over Europe in WRFv3.6.1 climatic runs with fully interactive aerosols
Evaluation of regional climate models ALARO-0 and REMO2015 at 0.22° resolution over the CORDEX Central Asia domain
Using the anomaly forcing Community Land Model (CLM 4.5) for crop yield projections
PMIP4 experiments using MIROC-ES2L Earth system model
Simulating the mid-Holocene, last interglacial and mid-Pliocene climate with EC-Earth3-LR
Understanding the development of systematic errors in the Asian summer monsoon
ICON in Climate Limited-area Mode (ICON release version 2.6.1): a new regional climate model
Evaluation of polar stratospheric clouds in the global chemistry–climate model SOCOLv3.1 by comparison with CALIPSO spaceborne lidar measurements
Lossy compression of Earth system model data based on a hierarchical tensor with Adaptive-HGFDR (v1.0)
Methane chemistry in a nutshell – the new submodels CH4 (v1.0) and TRSYNC (v1.0) in MESSy (v2.54.0)
Coordinating an operational data distribution network for CMIP6 data
Implementation of sequential cropping into JULESvn5.2 land-surface model
Development of four-dimensional variational assimilation system based on the GRAPES–CUACE adjoint model (GRAPES–CUACE-4D-Var V1.0) and its application in emission inversion
HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses
CLIMADA v1.4.1: towards a globally consistent adaptation options appraisal tool
FORTE 2.0: a fast, parallel and flexible coupled climate model
Optimization of the sulfate aerosol hygroscopicity parameter in WRF-Chem
Updated European hydraulic pedotransfer functions with communicated uncertainties in the predicted variables (euptfv2)
Spin-up characteristics with three types of initial fields and the restart effects on forecast accuracy in the GRAPES global forecast system
GTS v1.0: a macrophysics scheme for climate models based on a probability density function
Calibration of temperature-dependent ocean microbial processes in the cGENIE.muffin (v0.9.13) Earth system model
Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations
Physically Regularized Machine Learning Emulators of Aerosol Activation
SimCloud version 1.0: a simple diagnostic cloud scheme for idealized climate models
DiRong1.0: a distributed implementation for improving routing network generation in model coupling
The GPU version of LICOM3 under HIP framework and its large-scale application
Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model using WAVEWATCHIII version 6.07
Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations
Geospatial input data for the PALM model system 6.0: model requirements, data sources and processing
An improved multivariable integrated evaluation method and NCL code for multimodel intercomparison (MVIETool version 1.0)
Exploring the parameter space of the COSMO-CLM v5.0 regional climate model for the Central Asia CORDEX domain
FaIRv2.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration
A Schwarz iterative method to evaluate ocean- atmosphere coupling schemes. Implementation and diagnostics in IPSL-CM6-SW-VLR
Reproducing complex simulations of economic impacts of climate change with lower-cost emulators
The benefits of increasing resolution in global and regional climate simulations for European climate extremes
Sensitivity of precipitation and temperature over Mount Kenya area to physics parameterization options in a high-resolution model simulation performed with WRFV3.8.1
European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)
Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6
A computationally efficient method for probabilistic local warming projections constrained by history matching and pattern scaling, demonstrated by WASP–LGRTC-1.0
R2D2 v2.0: accounting for temporal dependences in multivariate bias correction via analogue rank resampling
Extending the Modular Earth Submodel System (MESSy v2.54) model hierarchy: the ECHAM/MESSy IdeaLized (EMIL) model setup
Boreal summer intraseasonal oscillation in a superparameterized general circulation model: effects of air–sea coupling and ocean mean state
Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response
Chao Sun, Li Liu, Ruizhe Li, Xinzhu Yu, Hao Yu, Biao Zhao, Guansuo Wang, Juanjuan Liu, Fangli Qiao, and Bin Wang
Geosci. Model Dev., 14, 2635–2657, https://doi.org/10.5194/gmd-14-2635-2021, https://doi.org/10.5194/gmd-14-2635-2021, 2021
Short summary
Short summary
Data assimilation (DA) provides better initial states of model runs by combining observations and models. This work focuses on the technical challenges in developing a coupled ensemble-based DA system and proposes a new DA framework DAFCC1 based on C-Coupler2. DAFCC1 enables users to conveniently integrate a DA method into a model with automatic and efficient data exchanges. A sample DA system that combines GSI/EnKF and FIO-AOW demonstrates the effectiveness of DAFCC1.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen Sitch, and Sönke Zaehle
Geosci. Model Dev., 14, 2161–2186, https://doi.org/10.5194/gmd-14-2161-2021, https://doi.org/10.5194/gmd-14-2161-2021, 2021
Short summary
Short summary
Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
Pirkka Ollinaho, Glenn D. Carver, Simon T. K. Lang, Lauri Tuppi, Madeleine Ekblom, and Heikki Järvinen
Geosci. Model Dev., 14, 2143–2160, https://doi.org/10.5194/gmd-14-2143-2021, https://doi.org/10.5194/gmd-14-2143-2021, 2021
Short summary
Short summary
OpenEnsemble 1.0 is a novel dataset that aims to open ensemble or probabilistic weather forecasting research up to the academic community. The dataset contains atmospheric states that are required for running model forecasts of atmospheric evolution. Our capacity to observe the atmosphere is limited; thus, a single reconstruction of the atmospheric state contains some errors. Our dataset provides sets of 50 slightly different atmospheric states so that these errors can be taken into account.
Yan Sun, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang, Ronny Lauerwald, Fabienne Maignan, Victoria Naipal, Yilong Wang, Hui Yang, and Haicheng Zhang
Geosci. Model Dev., 14, 1987–2010, https://doi.org/10.5194/gmd-14-1987-2021, https://doi.org/10.5194/gmd-14-1987-2021, 2021
Short summary
Short summary
We evaluated the performance of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 against remote sensing, ground-based measurement networks and ecological databases. The simulated carbon, nitrogen and phosphorus fluxes among different spatial scales are generally in good agreement with data-driven estimates. However, the recent carbon sink in the Northern Hemisphere is substantially underestimated. Potential causes and model development priorities are discussed.
Hui Wan, Shixuan Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, and Huiping Yan
Geosci. Model Dev., 14, 1921–1948, https://doi.org/10.5194/gmd-14-1921-2021, https://doi.org/10.5194/gmd-14-1921-2021, 2021
Short summary
Short summary
Numerical models used in weather and climate research and prediction unavoidably contain numerical errors resulting from temporal discretization, and the impact of such errors can be substantial. Complex process interactions often make it difficult to pinpoint the exact sources of such errors. This study uses a series of sensitivity experiments to identify components in a global atmosphere model that are responsible for time step sensitivities in various cloud regimes.
Johannes Horak, Marlis Hofer, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Geosci. Model Dev., 14, 1657–1680, https://doi.org/10.5194/gmd-14-1657-2021, https://doi.org/10.5194/gmd-14-1657-2021, 2021
Short summary
Short summary
This process-based evaluation of the atmospheric model ICAR is conducted to derive recommendations to increase the likelihood of its results being correct for the right reasons. We conclude that a different diagnosis of the atmospheric background state is necessary, as well as a model top at an elevation of at least 10 km. Alternative boundary conditions at the top were not found to be effective in reducing this model top elevation. The results have wide implications for future ICAR studies.
Yong Wang, Guang J. Zhang, Shaocheng Xie, Wuyin Lin, George C. Craig, Qi Tang, and Hsi-Yen Ma
Geosci. Model Dev., 14, 1575–1593, https://doi.org/10.5194/gmd-14-1575-2021, https://doi.org/10.5194/gmd-14-1575-2021, 2021
Short summary
Short summary
A stochastic deep convection parameterization is implemented into the US Department of Energy Energy Exascale Earth System Model Atmosphere Model version 1 (EAMv1). Compared to the default model, the well-known problem of
too much light rain and too little heavy rainis largely alleviated over the tropics with the stochastic scheme. Results from this study provide important insights into the model performance of EAMv1 when stochasticity is included in the deep convective parameterization.
Sonia Jerez, Laura Palacios-Peña, Claudia Gutiérrez, Pedro Jiménez-Guerrero, Jose María López-Romero, Enrique Pravia-Sarabia, and Juan Pedro Montávez
Geosci. Model Dev., 14, 1533–1551, https://doi.org/10.5194/gmd-14-1533-2021, https://doi.org/10.5194/gmd-14-1533-2021, 2021
Short summary
Short summary
This research explores the role of aerosols when modeling surface solar radiation at regional scales (over Europe). A set of model experiments was performed with and without dynamical modeling of atmospheric aerosols and their direct and indirect effects on radiation. Results showed significant differences in the simulated solar radiation, mainly driven by the aerosol impact on cloudiness, which calls for caution when interpreting model experiments that do not include aerosols.
Sara Top, Lola Kotova, Lesley De Cruz, Svetlana Aniskevich, Leonid Bobylev, Rozemien De Troch, Natalia Gnatiuk, Anne Gobin, Rafiq Hamdi, Arne Kriegsmann, Armelle Reca Remedio, Abdulla Sakalli, Hans Van De Vyver, Bert Van Schaeybroeck, Viesturs Zandersons, Philippe De Maeyer, Piet Termonia, and Steven Caluwaerts
Geosci. Model Dev., 14, 1267–1293, https://doi.org/10.5194/gmd-14-1267-2021, https://doi.org/10.5194/gmd-14-1267-2021, 2021
Short summary
Short summary
Detailed climate data are needed to assess the impact of climate change on human and natural systems. The performance of two high-resolution regional climate models, ALARO-0 and REMO2015, was investigated over central Asia, a vulnerable region where detailed climate information is scarce. In certain subregions the produced climate data are suitable for impact studies, but bias adjustment is required for subregions where significant biases have been identified.
Yaqiong Lu and Xianyu Yang
Geosci. Model Dev., 14, 1253–1265, https://doi.org/10.5194/gmd-14-1253-2021, https://doi.org/10.5194/gmd-14-1253-2021, 2021
Short summary
Short summary
Crop growth in land surface models normally requires high-temporal-resolution climate data, but such high-temporal-resolution climate data are not provided by many climate model simulations due to expensive storage, which limits modeling choices if there is an interest in a particular climate simulation that only saved monthly outputs. Our work provides an alternative way to use the monthly climate for crop yield projections. Such an approach could be easily adopted by other crop models.
Rumi Ohgaito, Akitomo Yamamoto, Tomohiro Hajima, Ryouta O'ishi, Manabu Abe, Hiroaki Tatebe, Ayako Abe-Ouchi, and Michio Kawamiya
Geosci. Model Dev., 14, 1195–1217, https://doi.org/10.5194/gmd-14-1195-2021, https://doi.org/10.5194/gmd-14-1195-2021, 2021
Short summary
Short summary
Using the MIROC-ES2L Earth system model, selected time periods of the past were simulated. The ability to simulate the past is also an evaluation of the performance of the model in projecting global warming. Simulations for 21 000, 6000, and 127 000 years ago, and a simulation for 1000 years starting in 850 CE were simulated. The results showed that the model can generally describe past climate change.
Qiong Zhang, Ellen Berntell, Josefine Axelsson, Jie Chen, Zixuan Han, Wesley de Nooijer, Zhengyao Lu, Qiang Li, Qiang Zhang, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 1147–1169, https://doi.org/10.5194/gmd-14-1147-2021, https://doi.org/10.5194/gmd-14-1147-2021, 2021
Short summary
Short summary
Paleoclimate modelling has long been regarded as a strong out-of-sample test bed of the climate models that are used for the projection of future climate changes. Here, we document the model experimental setups for the three past warm periods with EC-Earth3-LR and present the results on the large-scale features. The simulations demonstrate good performance of the model in capturing the climate response under different climate forcings.
Gill M. Martin, Richard C. Levine, José M. Rodriguez, and Michael Vellinga
Geosci. Model Dev., 14, 1007–1035, https://doi.org/10.5194/gmd-14-1007-2021, https://doi.org/10.5194/gmd-14-1007-2021, 2021
Short summary
Short summary
Our study highlights a number of different techniques that can be employed to investigate the sources of model error. We demonstrate how this methodology can be used to identify the regions and model components responsible for the development of long-standing errors in the Asian summer monsoon. Once these are known, further work can be done to explore the local processes contributing to this behaviour and their sensitivity to changes in physical parameterisations and/or model resolution.
Trang Van Pham, Christian Steger, Burkhardt Rockel, Klaus Keuler, Ingo Kirchner, Mariano Mertens, Daniel Rieger, Günther Zängl, and Barbara Früh
Geosci. Model Dev., 14, 985–1005, https://doi.org/10.5194/gmd-14-985-2021, https://doi.org/10.5194/gmd-14-985-2021, 2021
Short summary
Short summary
A new regional climate model was prepared based on a weather forecast model. Slow processes of the climate system such as ocean state development and greenhouse gas emissions were implemented. A model infrastructure and evaluation tools were also prepared to facilitate long-term simulations and model evalution. The first ICON-CLM results were close to observations and comparable to those from COSMO-CLM, the recommended model being used at the Deutscher Wetterdienst and CLM Community.
Michael Steiner, Beiping Luo, Thomas Peter, Michael C. Pitts, and Andrea Stenke
Geosci. Model Dev., 14, 935–959, https://doi.org/10.5194/gmd-14-935-2021, https://doi.org/10.5194/gmd-14-935-2021, 2021
Short summary
Short summary
We evaluate polar stratospheric clouds (PSCs) as simulated by the chemistry–climate model (CCM) SOCOLv3.1 in comparison with measurements by the CALIPSO satellite. A cold bias results in an overestimated PSC area and mountain-wave ice is underestimated, but we find overall good temporal and spatial agreement of PSC occurrence and composition. This work confirms previous studies indicating that simplified PSC schemes may also achieve good approximations of the fundamental properties of PSCs.
Zhaoyuan Yu, Dongshuang Li, Zhengfang Zhang, Wen Luo, Yuan Liu, Zengjie Wang, and Linwang Yuan
Geosci. Model Dev., 14, 875–887, https://doi.org/10.5194/gmd-14-875-2021, https://doi.org/10.5194/gmd-14-875-2021, 2021
Short summary
Short summary
Few lossy compression methods consider both the global and local multidimensional coupling correlations, which could lead to information loss in data compression. Here we develop an adaptive lossy compression method, Adaptive-HGFDR, to capture both the global and local variation of multidimensional coupling correlations and improve approximation accuracy. The method can achieve good compression performances for most flux variables with significant spatiotemporal heterogeneity.
Franziska Winterstein and Patrick Jöckel
Geosci. Model Dev., 14, 661–674, https://doi.org/10.5194/gmd-14-661-2021, https://doi.org/10.5194/gmd-14-661-2021, 2021
Short summary
Short summary
Atmospheric methane is currently a hot topic in climate research. This is partly due to its chemically active nature. We introduce a simplified approach to simulate methane in climate models to enable large sensitivity studies by reducing computational cost but including the crucial feedback of methane on stratospheric water vapour. We further provide options to simulate the isotopic content of methane and to generate output for an inverse optimization technique for emission estimation.
Ruth Petrie, Sébastien Denvil, Sasha Ames, Guillaume Levavasseur, Sandro Fiore, Chris Allen, Fabrizio Antonio, Katharina Berger, Pierre-Antoine Bretonnière, Luca Cinquini, Eli Dart, Prashanth Dwarakanath, Kelsey Druken, Ben Evans, Laurent Franchistéguy, Sébastien Gardoll, Eric Gerbier, Mark Greenslade, David Hassell, Alan Iwi, Martin Juckes, Stephan Kindermann, Lukasz Lacinski, Maria Mirto, Atef Ben Nasser, Paola Nassisi, Eric Nienhouse, Sergey Nikonov, Alessandra Nuzzo, Clare Richards, Syazwan Ridzwan, Michel Rixen, Kim Serradell, Kate Snow, Ag Stephens, Martina Stockhause, Hans Vahlenkamp, and Rick Wagner
Geosci. Model Dev., 14, 629–644, https://doi.org/10.5194/gmd-14-629-2021, https://doi.org/10.5194/gmd-14-629-2021, 2021
Short summary
Short summary
This paper describes the infrastructure that is used to distribute Coupled Model Intercomparison Project Phase 6 (CMIP6) data around the world for analysis by the climate research community. It is expected that there will be ~20 PB (petabytes) of data available for analysis. The operations team performed a series of preparation "data challenges" to ensure all components of the infrastructure were operational for when the data became available for timely data distribution and subsequent analysis.
Camilla Mathison, Andrew J. Challinor, Chetan Deva, Pete Falloon, Sébastien Garrigues, Sophie Moulin, Karina Williams, and Andy Wiltshire
Geosci. Model Dev., 14, 437–471, https://doi.org/10.5194/gmd-14-437-2021, https://doi.org/10.5194/gmd-14-437-2021, 2021
Short summary
Short summary
Sequential cropping (also known as multiple or double cropping) is a common cropping system, particularly in tropical regions. Typically, land surface models only simulate a single crop per year. To understand how sequential crops influence surface fluxes, we implement sequential cropping in JULES to simulate all the crops grown within a year at a given location in a seamless way. We demonstrate the method using a site in Avignon, four locations in India and a regional run for two Indian states.
Chao Wang, Xingqin An, Qing Hou, Zhaobin Sun, Yanjun Li, and Jiangtao Li
Geosci. Model Dev., 14, 337–350, https://doi.org/10.5194/gmd-14-337-2021, https://doi.org/10.5194/gmd-14-337-2021, 2021
Kalyn Dorheim, Steven J. Smith, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 365–375, https://doi.org/10.5194/gmd-14-365-2021, https://doi.org/10.5194/gmd-14-365-2021, 2021
Short summary
Short summary
Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. Simple climate models are diverse, including highly idealized and process-based models. Here we present a hybrid approach that combines the strength of two types of simple climate models in a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainties.
David N. Bresch and Gabriela Aznar-Siguan
Geosci. Model Dev., 14, 351–363, https://doi.org/10.5194/gmd-14-351-2021, https://doi.org/10.5194/gmd-14-351-2021, 2021
Short summary
Short summary
Climate change is a fact and adaptation a necessity. The Economics of Climate Adaptation methodology provides a framework to integrate risk and reward perspectives of different stakeholders, underpinned by the CLIMADA impact modelling platform. This extended version of CLIMADA enables risk assessment and options appraisal in a modular form and occasionally bespoke fashion yet with high reusability of functionalities to foster usage in interdisciplinary studies and international collaboration.
Adam T. Blaker, Manoj Joshi, Bablu Sinha, David P. Stevens, Robin S. Smith, and Joël J.-M. Hirschi
Geosci. Model Dev., 14, 275–293, https://doi.org/10.5194/gmd-14-275-2021, https://doi.org/10.5194/gmd-14-275-2021, 2021
Short summary
Short summary
FORTE 2.0 is a flexible coupled atmosphere–ocean general circulation model that can be run on modest hardware. We present two 2000-year simulations which show that FORTE 2.0 is capable of producing a stable climate. Earlier versions of FORTE were used for a wide range of studies, ranging from aquaplanet configurations to investigating the cold European winters of 2009–2010. This paper introduces the updated model for which the code and configuration are now publicly available.
Ah-Hyun Kim, Seong Soo Yum, Dong Yeong Chang, and Minsu Park
Geosci. Model Dev., 14, 259–273, https://doi.org/10.5194/gmd-14-259-2021, https://doi.org/10.5194/gmd-14-259-2021, 2021
Short summary
Short summary
A new method to estimate the sulfate aerosol hygroscopicity parameter (κSO4) is suggested that can consider κSO4 for two different sulfate species instead of prescribing a single κSO4 value, as in most previous studies. The new method simulates more realistic cloud droplet concentrations and, thus, a more realistic cloud albedo effect than the original method. The new method is simple and readily applicable to modeling studies investigating sulfate aerosols’ effect in aerosol–cloud interactions.
Brigitta Szabó, Melanie Weynants, and Tobias K. D. Weber
Geosci. Model Dev., 14, 151–175, https://doi.org/10.5194/gmd-14-151-2021, https://doi.org/10.5194/gmd-14-151-2021, 2021
Short summary
Short summary
This paper presents updated European prediction algorithms (euptf2) to compute soil hydraulic parameters from easily available soil properties. The new algorithms lead to significantly better predictions and provide a built-in prediction uncertainty computation. The influence of predictor variables on predicted soil hydraulic properties is explored and practical guidance on how to use the derived PTFs is provided. A website and an R package facilitate easy application of the updated predictions.
Zhanshan Ma, Chuanfeng Zhao, Jiandong Gong, Jin Zhang, Zhe Li, Jian Sun, Yongzhu Liu, Jiong Chen, and Qingu Jiang
Geosci. Model Dev., 14, 205–221, https://doi.org/10.5194/gmd-14-205-2021, https://doi.org/10.5194/gmd-14-205-2021, 2021
Short summary
Short summary
The spin-up in GRAPES_GFS, under different initial fields, goes through a dramatic adjustment in the first half-hour of integration and slow dynamic and thermal adjustments afterwards. It lasts for at least 6 h, with model adjustment gradually completed from lower to upper layers in the model. Thus, the forecast results, at least in the first 6 h, should be avoided when used. In addition, the spin-up process should repeat when the model simulation is interrupted.
Chein-Jung Shiu, Yi-Chi Wang, Huang-Hsiung Hsu, Wei-Ting Chen, Hua-Lu Pan, Ruiyu Sun, Yi-Hsuan Chen, and Cheng-An Chen
Geosci. Model Dev., 14, 177–204, https://doi.org/10.5194/gmd-14-177-2021, https://doi.org/10.5194/gmd-14-177-2021, 2021
Short summary
Short summary
A cloud macrophysics scheme utilizing grid-mean hydrometeor information is developed and evaluated for climate models. The GFS–TaiESM–Sundqvist (GTS) scheme can simulate variations of cloud fraction associated with relative humidity (RH) in a more consistent way than the default scheme of CAM5.3. Through better cloud–RH distributions, the GTS scheme helps to better represent cloud fraction, cloud radiative forcing, and thermodynamic-related climatic fields in climate simulations.
Katherine A. Crichton, Jamie D. Wilson, Andy Ridgwell, and Paul N. Pearson
Geosci. Model Dev., 14, 125–149, https://doi.org/10.5194/gmd-14-125-2021, https://doi.org/10.5194/gmd-14-125-2021, 2021
Short summary
Short summary
Temperature is a controller of metabolic processes and therefore also a controller of the ocean's biological carbon pump (BCP). We calibrate a temperature-dependent version of the BCP in the cGENIE Earth system model. Since the pre-industrial period, warming has intensified near-surface nutrient recycling, supporting production and largely offsetting stratification-induced surface nutrient limitation. But at the same time less carbon that sinks out of the surface then reaches the deep ocean.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
Short summary
Short summary
Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Sam J. Silva, Po-Lun Ma, Joseph C. Hardin, and Daniel Rothenberg
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-393, https://doi.org/10.5194/gmd-2020-393, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth System Models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling representation of the more detailed physics and chemistry at reduced computational cost while still retaining physical information.
Qun Liu, Matthew Collins, Penelope Maher, Stephen I. Thomson, and Geoffrey K. Vallis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-402, https://doi.org/10.5194/gmd-2020-402, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Clouds play an vital role in Earth's energy budget and even a small change in cloud fields can have a large impact on climate system. They also bring lots of uncertainties to climate models. Here we implement a simple diagnostic cloud scheme in order to reproduce the general radiative properties of clouds. The scheme can capture some key features of the cloud fraction and cloud radiative properties, thus providing a useful tool to explore the unsolved problems about clouds.
Hao Yu, Li Liu, Chao Sun, Ruizhe Li, Xinzhu Yu, Cheng Zhang, Zhiyuan Zhang, and Bin Wang
Geosci. Model Dev., 13, 6253–6263, https://doi.org/10.5194/gmd-13-6253-2020, https://doi.org/10.5194/gmd-13-6253-2020, 2020
Short summary
Short summary
Routing network generation is a major step for initializing the data transfer functionality for model coupling. The distributed implementation for routing network generation (DiRong1.0) proposed in this paper can significantly improve the global implementation of routing network generation used in some existing coupling software, because it does not introduce any gather–broadcast communications and achieves much lower complexity in terms of time, memory, and communication.
Pengfei Wang, Jinrong Jiang, Pengfei Lin, Mengrong Ding, Junlin Wei, Feng Zhang, Lian Zhao, Yiwen Li, Zipeng Yu, Weipeng Zheng, Yongqiang Yu, Xuebin Chi, and Hailong Liu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-323, https://doi.org/10.5194/gmd-2020-323, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
The global ocean general circulation models are a fundamental tool for oceanography research, ocean forecast, and climate change research. The increasing resolution will greatly improve the simulation of the model, but it also demands much more computing resources. In this study, we have ported an ocean general circulation model to a heterogeneous computing system and have developed a 3–5 km model version. A 14-year integration has been conducted and the preliminary results have been evaluated.
Steven R. Brus, Phillip J. Wolfram, Luke P. Van Roekel, and Jessica D. Meixner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-351, https://doi.org/10.5194/gmd-2020-351, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Wind generated waves are an important process in the global climate system. They mediate many interactions between the ocean, atmosphere, and sea ice. Models which describe these waves are computationally expensive and have often been excluded from coupled Earth system models. To address this, we have developed a capability for the WAVEWATCHIII model which allows model resolution to be varied globally across the coastal the open ocean. This allows for improved accuracy at reduced computing time.
Øyvind Seland, Mats Bentsen, Dirk Olivié, Thomas Toniazzo, Ada Gjermundsen, Lise Seland Graff, Jens Boldingh Debernard, Alok Kumar Gupta, Yan-Chun He, Alf Kirkevåg, Jörg Schwinger, Jerry Tjiputra, Kjetil Schanke Aas, Ingo Bethke, Yuanchao Fan, Jan Griesfeller, Alf Grini, Chuncheng Guo, Mehmet Ilicak, Inger Helene Hafsahl Karset, Oskar Landgren, Johan Liakka, Kine Onsum Moseid, Aleksi Nummelin, Clemens Spensberger, Hui Tang, Zhongshi Zhang, Christoph Heinze, Trond Iversen, and Michael Schulz
Geosci. Model Dev., 13, 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020, https://doi.org/10.5194/gmd-13-6165-2020, 2020
Short summary
Short summary
The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. The temperature and precipitation patterns has improved compared to NorESM1. The model reaches present-day warming levels to within 0.2 °C of observed temperature but with a delayed warming during the late 20th century. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period of 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.1, and 3.9 K.
Wieke Heldens, Cornelia Burmeister, Farah Kanani-Sühring, Björn Maronga, Dirk Pavlik, Matthias Sühring, Julian Zeidler, and Thomas Esch
Geosci. Model Dev., 13, 5833–5873, https://doi.org/10.5194/gmd-13-5833-2020, https://doi.org/10.5194/gmd-13-5833-2020, 2020
Short summary
Short summary
For realistic microclimate simulations in urban areas with PALM 6.0, detailed description of surface types, buildings and vegetation is required. This paper shows how such input data sets can be derived with the example of three German cities. Various data sources are used, including remote sensing, municipal data collections and open data such as OpenStreetMap. The collection and preparation of input data sets is tedious. Future research aims therefore at semi-automated tools to support users.
Meng-Zhuo Zhang, Zhongfeng Xu, Ying Han, and Weidong Guo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-310, https://doi.org/10.5194/gmd-2020-310, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Overall model performance evaluation in simulating multiple fields is crucial for geoscientific model development, inter-comparison, and application with increasing models available recently. We make key improvements for the Multivariable Integrated Evaluation (MVIE) method and develop a simple-to-use and straightforward tool, Multivariable Integrated Evaluation Tool (MVIETool) based on the improved MVIE, which will assist researchers to efficiently evaluate multivariable model performance.
Emmanuele Russo, Silje Lund Sørland, Ingo Kirchner, Martijn Schaap, Christoph C. Raible, and Ulrich Cubasch
Geosci. Model Dev., 13, 5779–5797, https://doi.org/10.5194/gmd-13-5779-2020, https://doi.org/10.5194/gmd-13-5779-2020, 2020
Short summary
Short summary
The parameter space of the COSMO-CLM RCM is investigated for the Central Asia CORDEX domain using a perturbed physics ensemble (PPE) with different parameter values. Results show that only a subset of model parameters presents relevant changes in model performance and these changes depend on the considered region and variable: objective calibration methods are highly necessary in this case. Additionally, the results suggest the need for calibrating an RCM when targeting different domains.
Nicholas J. Leach, Stuart Jenkins, Zebedee Nicholls, Christopher J. Smith, John Lynch, Michelle Cain, Tristram Walsh, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-390, https://doi.org/10.5194/gmd-2020-390, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
This paper presents an update of the FaIR simple climate model, used for estimating the impact of anthropogenic greenhouse gas and aerosol emissions on the global climate. This update aims to significantly increase the structural simplicity of the model, making it more understandable and transparent. This simplicity allows it to be implemented in a wide range of environments, including Excel. We suggest that it could be used not only in academic or corporate research, but also in education.
Olivier Marti, Sébastien Nguyen, Pascale Braconnot, Sophie Valcke, Florian Lemarié, and Eric Blayo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-307, https://doi.org/10.5194/gmd-2020-307, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
State-of-the-art Earth System models, like the ones used in the CMIP6 intercomparison project, suffer from temporal inconsistencies at the ocean-atmosphere interface. In this study, a mathematically consistent iterative Schwarz method is used as a reference. It's tremendous computational cost make it unusable for production runs. But it allow us to evaluate the error made when using legacy coupling schemes. The impact on the climate at longer time scale, from days to decades, is not evaluated.
Jun'ya Takakura, Shinichiro Fujimori, Kiyoshi Takahashi, Naota Hanasaki, Tomoko Hasegawa, Yukiko Hirabayashi, Yasushi Honda, Toshichika Iizumi, Chan Park, Makoto Tamura, and Yasuaki Hijioka
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-349, https://doi.org/10.5194/gmd-2020-349, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
To simplify calculating economic impacts of climate change, Statistical methods called emulators are developed and evaluated. There are trade-offs between model complexity and emulation performance. Aggregated economic impacts can be approximated by relatively simple emulators, but complex emulators are necessary to accommodate finer-scale economic impacts.
Carley E. Iles, Robert Vautard, Jane Strachan, Sylvie Joussaume, Bernd R. Eggen, and Chris D. Hewitt
Geosci. Model Dev., 13, 5583–5607, https://doi.org/10.5194/gmd-13-5583-2020, https://doi.org/10.5194/gmd-13-5583-2020, 2020
Short summary
Short summary
We investigate how increased resolution affects the simulation of European climate extremes for global and regional climate models to inform modelling strategies. Precipitation extremes become heavier with higher resolution, especially over mountains, wind extremes become somewhat stronger, and for temperature extremes warm biases are reduced over mountains. Differences with resolution for the global model appear to come from downscaling effects rather than improved large-scale circulation.
Martina Messmer, Santos J. González-Rojí, Christoph C. Raible, and Thomas F. Stocker
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-347, https://doi.org/10.5194/gmd-2020-347, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Sensitivity experiments with the WRF model are run to find an optimal parameterization setup for precipitation around Mount Kenya at a scale that resolves convection (1 km). Precipitation is compared against many weather stations and gridded observational data sets. Both the temporal correlation of monthly precipitation sums and pattern correlations show that fewer nests lead to a more constrained simulation with higher correlation. The Grell-Freitas cumulus scheme obtains most accurate results.
Marie-Estelle Demory, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Erasmo Buonomo, Ole B. Christensen, James M. Ciarlo ̀, Rowan Fealy, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Retish Senan, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, https://doi.org/10.5194/gmd-13-5485-2020, 2020
Short summary
Short summary
Now that global climate models (GCMs) can run at similar resolutions to regional climate models (RCMs), one may wonder whether GCMs and RCMs provide similar regional climate information. We perform an evaluation for daily precipitation distribution in PRIMAVERA GCMs (25–50 km resolution) and CORDEX RCMs (12–50 km resolution) over Europe. We show that PRIMAVERA and CORDEX simulate similar distributions. Considering both datasets at such a resolution results in large benefits for impact studies.
George C. Hurtt, Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, Jonathan C. Doelman, Justin Fisk, Shinichiro Fujimori, Kees Klein Goldewijk, Tomoko Hasegawa, Peter Havlik, Andreas Heinimann, Florian Humpenöder, Johan Jungclaus, Jed O. Kaplan, Jennifer Kennedy, Tamás Krisztin, David Lawrence, Peter Lawrence, Lei Ma, Ole Mertz, Julia Pongratz, Alexander Popp, Benjamin Poulter, Keywan Riahi, Elena Shevliakova, Elke Stehfest, Peter Thornton, Francesco N. Tubiello, Detlef P. van Vuuren, and Xin Zhang
Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020, https://doi.org/10.5194/gmd-13-5425-2020, 2020
Short summary
Short summary
To estimate the effects of human land use activities on the carbon–climate system, a new set of global gridded land use forcing datasets was developed to link historical land use data to eight future scenarios in a standard format required by climate models. This new generation of land use harmonization (LUH2) includes updated inputs, higher spatial resolution, more detailed land use transitions, and the addition of important agricultural management layers; it will be used for CMIP6 simulations.
Philip Goodwin, Martin Leduc, Antti-Ilari Partanen, H. Damon Matthews, and Alex Rogers
Geosci. Model Dev., 13, 5389–5399, https://doi.org/10.5194/gmd-13-5389-2020, https://doi.org/10.5194/gmd-13-5389-2020, 2020
Short summary
Short summary
Numerical climate models are used to make projections of future surface warming for different pathways of future greenhouse gas emissions, where future surface warming will vary from place to place. However, it is so expensive to run complex models using supercomputers that future projections can only be produced for a small number of possible future emissions pathways. This study presents an efficient climate model to make projections of local surface warming using a desktop computer.
Mathieu Vrac and Soulivanh Thao
Geosci. Model Dev., 13, 5367–5387, https://doi.org/10.5194/gmd-13-5367-2020, https://doi.org/10.5194/gmd-13-5367-2020, 2020
Short summary
Short summary
We propose a multivariate bias correction (MBC) method to adjust the spatial and/or inter-variable properties of climate simulations, while also accounting for their temporal dependences (e.g., autocorrelations).
It consists on a method reordering the ranks of the time series according to their multivariate distance to a reference time series.
Results show that temporal correlations are improved while spatial and inter-variable correlations are still satisfactorily corrected.
Hella Garny, Roland Walz, Matthias Nützel, and Thomas Birner
Geosci. Model Dev., 13, 5229–5257, https://doi.org/10.5194/gmd-13-5229-2020, https://doi.org/10.5194/gmd-13-5229-2020, 2020
Short summary
Short summary
Numerical models of Earth's climate system have been gaining more and more complexity over the last decades. Therefore, it is important to establish simplified models to improve process understanding. In our study, we present and document the development of a new simplified model setup within the framework of a complex climate model system that uses the same routines to calculate atmospheric dynamics as the complex model but is simplified in the representation of clouds and radiation.
Yingxia Gao, Nicholas P. Klingaman, Charlotte A. DeMott, and Pang-Chi Hsu
Geosci. Model Dev., 13, 5191–5209, https://doi.org/10.5194/gmd-13-5191-2020, https://doi.org/10.5194/gmd-13-5191-2020, 2020
Short summary
Short summary
Both the air–sea coupling and ocean mean state affect the fidelity of simulated boreal summer intraseasonal oscillation (BSISO). To elucidate their relative effects on the simulated BSISO, a set of experiments was conducted using a superparameterized AGCM and its coupled version. Both air–sea coupling and cold ocean mean state improve the BSISO amplitude due to the suppression of the overestimated variance, while the former (latter) could further upgrade (degrade) the BSISO propagation.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
Short summary
Short summary
Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Cited articles
An, S.-I. and Jin, F.-F.: Collective role of zonal advective and thermocline
feedbacks in ENSO mode, J. Climate, 14, 3421–3432,
https://doi.org/10.1175/1520-0442(2001)014<3421:CROTAZ>2.0.CO;2, 2001.
Barnston, A., Tippett, M. K., L'Heureux, M. L., Li, S., and DeWitt, D. G.:
Skill of real-time seasonal ENSO model predictions during 2002–2011: is our
capability increasing?, B. Am. Meteorol. Soc., 93, 631–651,
https://doi.org/10.1175/BAMS-D-11-00111.1, 2012.
Bjerknes, J.: A possible response of the atmospheric Hadley circulation to
equatorial anomalies of Ocean temperature, Tellus, 18, 820–829, 1966.
Boulanger, J.-P., Menkes, C., and Lengaigne, M.: Role of high- and
low-frequency winds and wave reflection in the onset, growth and termination
of the 1997/1998 El Niño, Clim. Dynam., 22, 267–280,
https://doi.org/10.1007/s00382-003-0383-8, 2004.
Cai, W., Santoso, A., Wang, G., Yeh, S.-W., An, S.-Il, Cobb, K. M., Collins,
M., Guilyardi, E., Jin, F.-F., Kug, J.-S., Lengaigne, M., McPhaden, M. J.,
Takahashi, K., Timmermann, A., Vecchi, G., Watanabe, M., and Wu, L.: ENSO and
greenhouse warming, Nat. Clim. Change, 5, 849–859,
https://doi.org/10.1038/nclimate2743, 2015.
Capotondi, A., Ham, Y. G., Wittenberg, A. T., and Kug, J.-S.: Climate model
biases and El Niño Southern Oscillation (ENSO) simulation, US CLIVAR
Variations, 13, 21–25, 2015.
Chiang, J. C. H. and Vimont, D. J.: Analogous Pacific and Atlantic meridional
modes of tropical atmosphere–ocean variability, J. Climate, 17, 4143–4158,
2004.
Choi, J., An, S. I., and Yeh, S. W.: Decadal amplitude modulation of two
types of ENSO and its relationship with the mean state, Clim. Dynam., 38,
2631–2644, https://doi.org/10.1007/s00382-011-1186-y, 2012.
Diaz, H. F., Hoerling, M. P., and Eischeid, J. K.: ENSO variability,
teleconnections and climate change, Int. J. Climatol., 21, 1845–1862,
https://doi.org/10.1002/joc.631, 2001.
Dommenget, D. and Yu, Y.: The effects of remote SST forcings on ENSO
dynamics, variability and diversity, Clim. Dynam., 49, 2605–2624,
https://doi.org/10.1007/s00382-016-3472-1, 2018.
Fedorov, A.: The response of the coupled tropical ocean–atmosphere to
westerly wind bursts, Q. J. Roy. Meteor. Soc., 128, 1–23,
https://doi.org/10.1002/qj.200212857901, 2002.
Guo, Y., Duane, E., Waliser, and Xianan, J.: A systematic relationship
between the representations of convectively coupled equatorial wave activity
and the Madden–Julian oscillation in climate model simulations, J. Climate,
28, 1881–1904, https://doi.org/10.1175/JCLI-D-14-00485.1, 2015.
Gushchina, D. and Dewitte, B.: The relationship between intraseasonal
tropical variability and ENSO and its modulation at seasonal to decadal
timescales, Cent. Eur. J. Geosci., 1, 175–196,
https://doi.org/10.2478/s13533-011-0017-3, 2011.
Gushchina, D. and Dewitte, B.: Intraseasonal tropical atmospheric variability
associated with the two flavors of El Niño, Mon. Weather Rev., 140,
3669–3681, https://doi.org/10.1175/MWR-D-11-00267.1, 2012.
Gushchina, D. and Dewitte, B.: Decadal modulation of the ITV ∕ ENSO
relationship and the two types of El Niño, Clim. Dynam.,
https://doi.org/10.1007/s00382-018-4235-y, online first, 2018.
Ham, Y.-G. and Kug, J.-S.: How well do current climate models simulate two
types of El Niño?, Clim Dynam., 39, 383–398,
https://doi.org/10.1007/s00382-011-1157-3, 2012.
Hayashi, Y.: A generalized method for resolving transient disturbances into
standing and travelling waves by space–time spectral analysis, J. Atmos.
Sci., 36, 1017–1029, https://doi.org/10.1175/1520-0469(1979)036<1017:AGMORT>2.0.CO;2,
1979.
Hendon, H. H., Wheeler, M. C., and Zhang, C.: Seasonal dependence of the
MJO–ENSO relationship, J. Climate, 20, 531–543, https://doi.org/10.1175/JCLI4003.1,
2007.
Horel, J. D. and Wallace, J. M.: Planetary-Scale Atmospheric Phenomena
Associated with the Southern Oscillation, Mon. Weather Rev., 109, 813–829,
https://doi.org/10.1175/1520-0493(1981)109<0813:PSAPAW>2.0.CO;2, 1981.
Hu, S. and Fedorov, A. V.: An exceptional easterly wind burst stalling El
Niño of 2014, P. Natl. Acad. Sci. USA, 113, 2005–2010,
https://doi.org/10.1073/pnas.1514182113, 2016.
Jiang, X., Waliser, D. E., Xavier, P. K., Petch, J., Klingaman, N. P.,
Woolnough, S. J., Guan, B., Bellon, G., Crueger, T., DeMott, C., Hannay, C.,
Lin, H., Hu, W., Kim, D., Lappen, C. L., Lu, M. M., Ma, H. Y., Miyakawa, T.,
Ridout, J. A., Schubert, S. D., Scinocca, J., Seo, K. H., Shindo, E., Song,
X., Stan, C., Tseng, W. L., Wang, W., Wu, T., Wu, X., Wyser, K., Zhang, G.
J., ans Zhu, H.: Vertical structure and physical processes of the
Madden-Julian oscillation: Exploring key model physics in climate
simulations, J. Geophys. Res.-Atmos, 120, 4718–4748,
https://doi.org/10.1002/2014JD022375, 2015.
Jin, F.-F.: An equatorial ocean recharge paradigm for ENSO, Part I:
Conceptual model, J. Atmos. Sci., 54, 811–829,
https://doi.org/10.1175/1520-0469(1997)054<0811:AEORPF>2.0.CO;2, 1997.
Jin, F.-F., Lin. L., Timmermann, A., and Zhao, J.: Ensemble-mean dynamics of
the ENSO recharge oscillator under state-dependent stochastic forcing,
Geophys. Res. Lett., 34, L03807, https://doi.org/10.1029/2006GL027372, 2007.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M.,
Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang,
J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437–471,
https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Karamperidou, C., Jin, F. F., and Conroy, J. L.: The importance of ENSO
nonlinearities in tropical pacific response to external forcing, Clim.
Dynam., 49, 2695–2704, https://doi.org/10.1007/s00382-016-3475-y, 2017.
Keen, R. A.: The role of cross-equatorial tropical cyclone pairs in the
Southern Oscillation, Mon. Weather Rev., 110, 1405–1416,
https://doi.org/10.1175/1520-0493(1982)110<1405:TROCET>2.0.CO;2, 1982.
Keshavamurti, R. N.: Response of the atmosphere to sea surface temperature
anomalies over the equatorial Pacific and the teleconnections of the Southern
Oscillation, J. Atmos. Sci., 39, 1241–1259,
https://doi.org/10.1175/1520-0469(1982)039<1241:ROTATS>2.0.CO;2, 1982.
Kessler, W. S., McPhaden, M. J., and Weickmann, K. M.: Forcing of
intraseasonal Kelvin waves in the equatorial Pacific, J. Geophys. Res., 100,
10613–10631, https://doi.org/10.1029/95JC00382, 1995.
Kim, S. T. and J.-Y. Yu: The two types of ENSO in CMIP5 models, Geophys. Res.
Lett, 39, L11704, https://doi.org/10.1029/2012GL052006, 2012.
Klingaman, N. P., Jiang, X., Xavier, P. K., Petch, J., Waliser, D., and
Woolnough, S. J.: Vertical structure and physical processes of the
Madden-Julian oscillation: Linking hindcast fidelity to simulated diabatic
heating and moistening, J. Geophys. Res.-Atmos, 120, 4690–4717,
https://doi.org/10.1002/2014JD022374, 2015.
Kug, J.-S., Jin, F.-F., Sooraj, K. P., and Kang, I.-S.: State-dependent
atmospheric noise associated with ENSO, Geophys. Res. Lett., 35, L05701,
https://doi.org/10.1029/2007GL032017, 2008.
Larson, S. and Kirtman, B.: The Pacific meridional mode as a trigger for ENSO
in a high-resolution coupled model, Geophys. Res. Lett., 40, 3189–3194,
2013.
Lengaigne, M., Boulanger, J. P., Menkes, C., Madec, G., Delecluse, P.,
Guilyardi, E., and Slingo, J.: The March 1997 Westerly Wind Event and the
Onset of the 1997/98 El Niño: Understanding the Role of the Atmospheric
Response, J. Climate, 16, 3330–3343,
https://doi.org/10.1175/1520-0442(2003)016<3330:TMWWEA>2.0.CO;2, 2003.
Levine, A. F. Z. and Jin, F.-F.: A simple approach to quantifying the noise
ENSO interaction, Part I: Deducing the state dependency of the windstress
forcing using monthly mean data, Clim. Dynam., 48, 1–18,
https://doi.org/10.1007/s00382-015-2748-1, 2015.
Levine, A. F. Z. and McPhaden, M. J.: How the July 2014 easterly wind burst
gave the 2015–2016 El Niño a head start, Geophys. Res. Lett., 43,
6503–6510, https://doi.org/10.1002/2016GL069204, 2016.
Levine, A., Jin, F. F., and McPhaden, M. J.: Extreme Noise–Extreme El
Niño: How State-Dependent Noise Forcing Creates El Niño–La Niña
Asymmetry, J. Climate, 29, 5483–5499, https://doi.org/10.1175/JCLI-D-16-0091.1, 2016.
Lin, J.-L., Kiladis, G. N., Mapes, B. E., Weickmann, K. M., Sperber, K. R.,
Lin, W., Wheeler, M. C., Schubert, S. D., Genio, A. D., Donner, L.G., Emori,
S., Gueremy, J.-F., Hourdin, F., Rasch, P. J., Roeckner, E., and Scinocca, J.
F.: Tropical intraseasonal variability in 14 IPCC AR4 climate models, Part I:
convective signals, J. Climate, 19, 2665–2690, https://doi.org/10.1175/JCLI3735.1,
2006.
Luther, D. S., Harrison, D. E., and Knox, R. A.: Zonal winds in the central
equatorial Pacific and El Niño, Science, 222, 327–330,
https://doi.org/10.1126/science.222.4621.327, 1983.
McPhaden, M. J.: A 21st century shift in the relationship between ENSO SST
and warm water volume anomalies, Geophys. Res. Lett., 39, L09706,
https://doi.org/10.1029/2012GL051826, 2012.
McPhaden, M. J., Zhang, X., Hendon, H. H., and Wheeler, M. C.: Large scale
dynamics and MJO forcing of ENSO variability, Geophys. Res. Lett., 33,
L16702, https://doi.org/10.1029/2006GL026786, 2006.
Menkes, C. E., Lengaigne, M., Vialard, J., Puy, M., Marchesiello, P.,
Cravatte, S., and Cambon, G.: About the role of Westerly Wind Events in the
possible development of an El Niño in 2014, Geophys. Res. Lett., 41,
6476–6483, 2014.
Neelin, J. D., Battisti, D. S., Hirst, A. C., Jin, F. F., Wakata, Y.,
Yamagata, T., and Zebiak, S. E.: ENSO theory, J. Geophys. Res.-Oceans, 103,
14261–14290, https://doi.org/10.1029/97JC03424, 1998.
Puy, M., Vialard, J., Lengaigne, M., and Guilyardi, E.: Modulation of
equatorial Pacific westerly/easterly wind events by the Madden–Julian
oscillation and convectively-coupled Rossby waves, Clim. Dynam., 46,
2155–2178, https://doi.org/10.1007/s00382-015-2695-x, 2016.
Rasmusson, E. M. and Carpenter, T. H.: Variations in Tropical Sea-Surface
Temperture and Surface Wind Fields associated with the Southern Oscillation
El Niño, Mon. Weather Rev., 110, 354–384,
https://doi.org/10.1175/1520-0493(1982)110<0354:VITSST>2.0.CO;2, 1982.
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L.
V., Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea
surface temperature, sea ice, and night marine air temperature since the late
nineteenth century, J. Geophys. Res.-Atmos., 108, 4407,
https://doi.org/10.1029/2002JD002670, 2003.
Takahashi, K., Montecinos, A., Goubanova, K., and Dewitte, B.: ENSO regimes:
Reinterpreting the canonical and Modoki El Niño, Geophys. Res. Lett., 38,
L10704, https://doi.org/10.1029/2011GL047364, 2011.
Takahashi, K., Karamperidou, C., and Dewitte, B.: A simple theoretical model
of strong and moderate El Niño regimes, Clim. Dynam.,
https://doi.org/10.1007/s00382-018-4100-z, online first, 2018.
Taschetto, A. S., Gupta, A. S., Jourdain, N. C., Santoso, A., Ummenhofer, C.
C., and England, M. H.: Cold tongue and warm pool ENSO events in CMIP5: mean
state and future projections, J. Climate, 27, 2861–2885,
https://doi.org/10.1175/JCLI-D-13-00437.1, 2014.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and
the experiment design, B. Am. Meteorol. Soc., 93, 485–498,
https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Thual, S., Majda, A. J., and Stechmann, S. N.: A stochastic skeleton model
for the MJO, J. Atmos. Sci., 71, 697–715, https://doi.org/10.1175/JAS-D-13-0186.1, 2014.
Trenberth, K. E., Branstator, G. W., Karoly, D., Kumar, A., Lau, N. C., and
Ropelewski, C.: Progress during TOGA in understanding and modeling global
teleconnections associated with tropical sea surface temperatures, J.
Geophys. Res.-Oceans, 103, 14291–14324, https://doi.org/10.1029/97JC01444, 1998.
Vimont, D. J., Battisti, D. S., and Hirst A. C.: Footprinting: a seasonal
connection between the tropics and mid-latitudes, Geophys. Res. Lett., 28,
3923–3926, 2001.
Wang, C. and Picaut, J.: Understanding ENSO physics – A review, Earth's
Climate, Geophysical Monograph Series 147, 21–48, https://doi.org/10.1029/147GM02,
2004.
Wheeler, M. C. and Kiladis, G. N.: Convectively coupled equatorial waves:
Analysis of clouds and temperature in the wavenumber–frequency domain, J.
Atmos. Sci., 56, 374–399,
https://doi.org/10.1175/1520-0469(1999)056<0374:CCEWAO>2.0.CO;2, 1999.
Xavier, P. K., Petch, J. C., Klingaman, N. P., Woolnough, S. J., Jiang, X.,
Waliser, D. E., Caian, M., Cole, J., Hagos, S. M., Hannay, C., Kim, D.,
Miyakawa, T., Pritchard, M. S., Roehrig, R., Shindo, E., Vitart, F., and
Wang, H.: Vertical structure and physical processes of the Madden-Julian
Oscillation: Biases and uncertainties at short range, J. Geophys. Res.-Atmos,
120, 4749–4763, https://doi.org/10.1002/2014JD022718, 2015.
Xiang, B., Wang, B., and Li, T.: A new paradigm for the predominance of
standing Central Pacific Warming after the late 1990s, Clim. Dynam., 41,
327–340, https://doi.org/10.1007/s00382-012-1427-8, 2013.
Xu, K., Tam, C. Y., Zhu, C., Liu, B., and Wang, W.: CMIP5 Projections of Two
Types of El Niño and Their Related Tropical Precipitation in the
Twenty-First Century, J. Climate, 30, 849–864,
https://doi.org/10.1175/JCLI-D-16-0413.1, 2017.
Yeh, S. W., Kug, J. S., Dewitte, B., Kwon, M. H., Kirtman, B. P., and Jin, F.
F.: El Niño in a changing climate, Nature, 461, 511–514,
https://doi.org/10.1038/nature08316, 2009.
You, Y. and Furtado, J. C.: The role of South Pacific atmospheric variability
in the development of different types of ENSO, Geophys. Res. Lett., 1–9,
https://doi.org/10.1002/2017GL073475, 2017.
Yu, J.-Y. and Kim, S. T.: Identification of Central-Pacific and
Eastern-Pacific types of ENSO in CMIP3 models, Geophys. Res. Lett., 37,
L15705, https://doi.org/10.1029/2010GL044082, 2010.
Yu, J.-Y. and Kim, S. T.: Relationships between extratropical sea level
pressure variations and the Central Pacific and Eastern Pacific types of
ENSO, J. Climate, 24, 708–720, 2011.
Zhang, C. and Dong, M.: Seasonality in the Madden–Julian oscillation, J.
Climate, 17, 3169–3180,
https://doi.org/10.1175/1520-0442(2004)017<3169:SITMO>2.0.CO;2, 2004.
Zhang, C. and Gottschalck, J.: SST anomalies of ENSO and the Madden–Julian
oscillation in the equatorial Pacific, J. Climate, 15, 2429–2445,
https://doi.org/10.1175/1520-0442(2002)015<2429:SAOEAT>2.0.CO;2, 2002.
Zhang, T. and Sun, D.-Z.: ENSO asymmetry in CMIP5 models, J. Climate, 27,
4070–4093, https://doi.org/10.1175/JCLI-D-13-00454.1, 2014.
Zhang, H. H., Clement, A., and Di Nezio, P.: The South Pacific meridional
mode: a mechanism for ENSO-like variability, J. Climate, 27, 769–783, 2014.
Zhao, M., Hendon, H. H., Alves, O., and Wang, G.: Weakened Eastern Pacific El
Niño Predictability in the Early 21st Century, J. Climate, 29,
6805–6822, https://doi.org/10.1175/JCLI-D-15-0876.1, 2016.
Short summary
Predicting El Niño both in current condition and for the next century is a key societal need. Intraseasonal atmosphere variability (ITV) plays an important role in triggering of El Niño; the El Niño/ITV relationship may change in future climate. The purpose of this study is to select the models that are most skilful in simulation of the ITV/El Niño relationship and thus promising for investigation of the El Niño mechanism under global climate change. Five models of CMIP5 project were selected.
Predicting El Niño both in current condition and for the next century is a key societal need....
