The Brazilian Earth System Model ocean–atmosphere (BESM-OA) version 2.5: evaluation  of  its CMIP5 historical simulation

Veiga, Sandro F.; Nobre, Paulo; Giarolla, Emanuel; Capistrano, Vinícius; Baptista, Manoel; Marquez, André Lanfer; Figueroa, Silvio Nilo; Bonatti, José Paulo; Kubota, Paulo Yoshio; Nobre, Carlos A.

doi:10.5194/gmd-12-1613-2019

Cited by 33 publications

(47 citation statements)

References 92 publications

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“…This study used two CMIP5 numerical experiments: (i) piControl: it runs for 700 years, forced by invariant preindustrial atmospheric CO 2 concentration level (280ppmv) and (ii) Abrupt 4xCO 2 : it runs for 460 years, comprising an 90 abrupt instantaneous quadrupling of atmospheric CO 2 level concentration from the piControl simulation. The design of both experiments follows the CMIP5 protocol (Taylor et al, 2012) and was described by Veiga et al, (2019).…”

Section: Numerical Designmentioning

confidence: 99%

“…Our goal is to 80 investigate the coupled processes underlying the polar warming by seasons. The paper was organized as follows: Section 2 provides a description of the climate models and experimental design[s] used in this work, focusing on the BESM-OA V2.5 model (Veiga et al, 2019;Giarolla et al, 2015;Nobre et al, 2013). In Section 3, the seasonality of the surface warming in high latitudes is examined of both northern and southern hemispheres and results from different models are compared.…”

Section: Introductionmentioning

confidence: 99%

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Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO<sub>2</sub> experiment

Casagrande¹,

Souza²,

Nobre³

et al. 2019

Preprint

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Abstract. The numerical climate simulation from Brazilian Earth System Model (BESM) are used here to investigate the response of Polar Regions to a forced increase of CO2 (Abrupt-4xCO2) and compared with Coupled Model Intercomparison Project 5 (CMIP5) simulations. Polar Regions are described as the most climatically sensitive areas of the globe, with an enhanced warming occurring during the cold seasons. The asymmetry between the two poles is related to the thermal inertia and the coupled ocean atmosphere processes involved. While in the northern high latitudes the amplified warming signal is associated to a positive snow and sea ice albedo feedback, for southern high latitudes the warming is related to a combination of ozone depletion and changes in the winds pattern. The numerical experiments conducted here demonstrated a very clear evidence of seasonality in the polar amplification response. In winter, for the northern high latitudes (southern high latitudes) the range of simulated polar warming varied from 15 K to 30 K (2.6 K to 10 K). In summer, for northern high latitudes (southern high latitudes) the simulated warming varies from 3 K to 15 K (3 K to 7 K). The vertical profiles of air temperature indicated stronger warming at surface, particularly for the Arctic region, suggesting that the albedo-sea ice feedback overlaps with the warming caused by meridional transport of heat in atmosphere. The latitude of the maximum warming was inversely correlated with changes in the sea ice within the model’s control run. Three climate models were identified as having high polar amplification for cold season in both poles: MIROC-ESM, BESM-OA V2.5 and GFDL-ESM2M. We suggest that the large BIAS found between models can be related to the differences in each model to represent the feedback process and also as a consequence of the distinct sea ice initial conditions of each model. The polar amplification phenomenon has been observed previously and is expected to become stronger in coming decades. The consequences for the atmospheric and ocean circulation are still subject to intense debate in the scientific community.

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Section: Numerical Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO<sub>2</sub> experiment

Casagrande¹,

Souza²,

Nobre³

et al. 2019

Preprint

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“…This inter-model dispersion arises principally from differences in how the climate models simulate climate feedback processes. Among them, cloud feedback constitutes the largest source of variation in the climate sensitivity estimates (Cess et al, 1989(Cess et al, , 1990; Dufresne and Bony, 2008;Vial et al, 2013;Caldwell et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Assessing the performance of climate change simulation results from BESM-OA2.5 compared with a CMIP5 model ensemble

et al. 2020

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Abstract. The main features of climate change patterns, as simulated by the coupled ocean–atmosphere version 2.5 of the Brazilian Earth System Model (BESM), are compared with those of 25 other CMIP5 models, focusing on temperature, precipitation, atmospheric circulation, and radiative feedbacks. The climate sensitivity to quadrupling the atmospheric CO2 concentration was investigated via two methods: linear regression (Gregory et al., 2004) and radiative kernels (Soden and Held, 2006; Soden et al., 2008). Radiative kernels from both the National Center for Atmospheric Research (NCAR) and the Geophysical Fluid Dynamics Laboratory (GFDL) were used to decompose the climate feedback responses of the CMIP5 models and BESM into different processes. By applying the linear regression method for equilibrium climate sensitivity (ECS) estimation, we obtained a BESM value close to the ensemble mean value. This study reveals that the BESM simulations yield zonally average feedbacks, as estimated from radiative kernels, that lie within the ensemble standard deviation. Exceptions were found in the high latitudes of the Northern Hemisphere and over the ocean near Antarctica, where BESM showed values for lapse rate, humidity feedback, and albedo that were marginally outside the standard deviation of the values from the CMIP5 multi-model ensemble. For those areas, BESM also featured a strong positive cloud feedback that appeared as an outlier compared with all analyzed models. However, BESM showed physically consistent changes in the temperature, precipitation, and atmospheric circulation patterns relative to the CMIP5 ensemble mean.

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“…Due to the insufficient current CPTEC supercomputing capacity for research and environmental prediction, there is a computational limitation to use BAM with sophisticated parameterization for highresolution global NWP (≈10 km) as well as for seasonal and decadal climate prediction. The simplified and fast physical parameterizations, which is called here as simplified version of BAM (BAM-v0), is the current atmospheric component of the CPTEC couple oceanatmosphere model-the Brazilian Earth System Model-Ocean-Atmosphere (BESM-OA), which is used for seasonal climate prediction and long integrations (Capistrano et al, 2018;Veiga et al, 2019). Details of BAM-v0 are explained later.…”

Section: Introductionmentioning

confidence: 99%

“…It is interesting that although this coupled model used a simplified physical parameterization in the atmospheric component, the model was able to reproduce the most important large-scale variabilities over the Atlantic, such as: the North Atlantic Oscillation, the Atlantic Meridional Mode and the Atlantic Meridional Overturning Circulation (AMOC) (Veiga et al 2019). This coupled model was also used for climate change studies (e.g., Capistrano et al, 2018). Nevertheless, the atmospheric climate variability, associated with largescale anomalies and teleconnections performance with prescribed SST analysis of the BAM-v0, has not yet been documented in any of the above-mentioned studies.…”

Section: Introductionmentioning

confidence: 99%

Climate variability over South America‐regional and large scale features simulated by the Brazilian Atmospheric Model (BAM‐v0)

Cavalcanti

Silveira

Figueroa

et al. 2019

Intl Journal of Climatology

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The reliability of climate prediction by a global model is directly related to the ability to simulate the observed climate variability and the main teleconnection patterns. Precipitation anomalies in certain regions are strongly affected by these features, and it is important to know if models are able to reproduce such patterns and influences. The main objective of this article is to analyse some global features of the Brazilian Atmospheric Model with simplified physics (BAM‐v0), and to discuss several aspects of climate variability over South America. Especially, the ability of the model in simulating the main teleconnection patterns that affect South America and the precipitation variability in several regions of Brazil associated with the Pacific and Atlantic Sea Surface Temperature. The model is the atmospheric component of the Brazilian Earth System Model‐Ocean–Atmosphere (BESM), which can be used to long integrations due to the simplified physics, considering computer limitations. Climate variability is investigated through analyses of variance and correlations, and teleconnections such as Southern Annular Mode (SAM) and Pacific South American (PSA) are obtained from EOF analyses. El Niño Southern Oscillation (ENSO) features are analysed through the Southern Oscillation Index and precipitation anomalies. BAM‐v0, even at coarse resolution, represents many climate variability features. It captures the influences of tropical Pacific and Atlantic Oceans on Northeast Brazil precipitation and reproduces the influences of ENSO over South America. SAM and PSA teleconnections are well simulated. Observed features of the South America Monsoon System are captured by the model, although the intensities of precipitation variability need to be improved. There are some deficiencies related to global budget, precipitation variance in some regions of the globe and precipitation anomalies in certain regions of South America. Identification of model deficiencies and variability analyses are important to model development and contribute to climate prediction improvements.

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The Brazilian Earth System Model ocean–atmosphere (BESM-OA) version 2.5: evaluation of its CMIP5 historical simulation

Cited by 33 publications

References 92 publications

Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO<sub>2</sub> experiment

Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO<sub>2</sub> experiment

Assessing the performance of climate change simulation results from BESM-OA2.5 compared with a CMIP5 model ensemble

Climate variability over South America‐regional and large scale features simulated by the Brazilian Atmospheric Model (BAM‐v0)

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The Brazilian Earth System Model ocean–atmosphere (BESM-OA) version 2.5: evaluation of its CMIP5 historical simulation

Cited by 33 publications

References 92 publications

Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO&lt;sub&gt;2&lt;/sub&gt; experiment

Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO&lt;sub&gt;2&lt;/sub&gt; experiment

Assessing the performance of climate change simulation results from BESM-OA2.5 compared with a CMIP5 model ensemble

Climate variability over South America‐regional and large scale features simulated by the Brazilian Atmospheric Model (BAM‐v0)

Contact Info

Product

Resources

About

Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO<sub>2</sub> experiment

Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO<sub>2</sub> experiment