The impact of orbital forcing on the climate of an intermediate-complexity coupled model

AbstractIn this work we use a regional atmosphere–ocean coupled model (RAOCM) and its stand-alone atmospheric component to gain insight into the impact of atmosphere–ocean coupling on the climate change signal over the Iberian Peninsula (IP). The IP climate is influenced by both the Atlantic Ocean and the Mediterranean sea. Complex interactions with the orography take place there and high-resolution models are required to realistically reproduce its current and future climate. We find that under the RCP8.5 scenario, the generalized 2-m air temperature (T2M) increase by the end of the twenty-first century (2070–2099) in the atmospheric-only simulation is tempered by the coupling. The impact of coupling is specially seen in summer, when the warming is stronger. Precipitation shows regionally-dependent changes in winter, whilst a drier climate is found in summer. The coupling generally reduces the magnitude of the changes. Differences in T2M and precipitation between the coupled and uncoupled simulations are caused by changes in the Atlantic large-scale circulation and in the Mediterranean Sea. Additionally, the differences in projected changes of T2M and precipitation with the RAOCM under the RCP8.5 and RCP4.5 scenarios are tackled. Results show that in winter and summer T2M increases less and precipitation changes are of a smaller magnitude with the RCP4.5. Whilst in summer changes present a similar regional distribution in both runs, in winter there are some differences in the NW of the IP due to differences in the North Atlantic circulation. The differences in the climate change signal from the RAOCM and the driving Global Coupled Model show that regionalization has an effect in terms of higher resolution over the land and ocean.

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Evaluation of a Coupled Model to Predict the Impact of Adaptive Behaviour in the Thermal Sensation of Occupants of Naturally Ventilated Buildings in Warm-Humid Regions

Sustainability ◽

10.3390/su13010255 ◽

2020 ◽

Vol 13 (1) ◽

pp. 255

Author(s):

Luciano C. de Faria ◽

Marcelo A. Romero ◽

Lúcia F. S. Pirró

Keyword(s):

Computational Models ◽

Thermal Sensation ◽

Coupled Model ◽

Adaptive Behaviour ◽

Humid Climate ◽

Clothing Insulation ◽

Tropical Regions ◽

Naturally Ventilated Buildings ◽

Adaptive Behaviours ◽

The Impact

Improving indoor environment quality and making urban centres in tropical regions more sustainable has become a challenge for which computational models for the prediction of thermal sensation for naturally ventilated buildings (NVBs) have major role to play. This work performed analysis on thermal sensation for non-residential NVBs located in Brazilian tropical warm-humid climate and tested the effectiveness of suggested adaptive behaviours to mitigate warm thermal sensation. The research method utilized transient computational fluid dynamics models coupled with a dynamic model for human thermophysiology to predict thermal sensation. The calculated results were validated with comparison with benchmark values from questionnaires and from field measurements. The calculated results for dynamic thermal sensation (DTS) seven-point scale showed higher agreement with the thermal sensation vote than with the predicted mean vote. The test for the suggested adaptive behaviours considered reducing clothing insulation values from 0.18 to 0.32 clo (reducing DTS from 0.1 to 0.9), increasing the air speed in 0.9 m/s (reducing DTS from 0.1 to 0.9), and applying both suggestions together (reducing DTS from 0.1 to 1.3) for five scenarios with operative temperatures spanning 34.5–24.0 °C. Results quantified the tested adaptive behaviours’ efficiency showing applicability to improve thermal sensation from slightly-warm to neutral.

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Impact of Resolution on the Tropical Pacific Circulation in a Matrix of Coupled Models

Journal of Climate ◽

10.1175/2008jcli2537.1 ◽

2009 ◽

Vol 22 (10) ◽

pp. 2541-2556 ◽

Cited By ~ 69

Author(s):

Malcolm J. Roberts ◽

A. Clayton ◽

M.-E. Demory ◽

J. Donners ◽

P. L. Vidale ◽

...

Keyword(s):

Coupled Model ◽

Walker Circulation ◽

Ocean Model ◽

Tropical Pacific ◽

Coupled Models ◽

Model Stability ◽

The Mean ◽

The Impact ◽

Mean State ◽

The Tropical Pacific

Abstract Results are presented from a matrix of coupled model integrations, using atmosphere resolutions of 135 and 90 km, and ocean resolutions of 1° and 1/3°, to study the impact of resolution on simulated climate. The mean state of the tropical Pacific is found to be improved in the models with a higher ocean resolution. Such an improved mean state arises from the development of tropical instability waves, which are poorly resolved at low resolution; these waves reduce the equatorial cold tongue bias. The improved ocean state also allows for a better simulation of the atmospheric Walker circulation. Several sensitivity studies have been performed to further understand the processes involved in the different component models. Significantly decreasing the horizontal momentum dissipation in the coupled model with the lower-resolution ocean has benefits for the mean tropical Pacific climate, but decreases model stability. Increasing the momentum dissipation in the coupled model with the higher-resolution ocean degrades the simulation toward that of the lower-resolution ocean. These results suggest that enhanced ocean model resolution can have important benefits for the climatology of both the atmosphere and ocean components of the coupled model, and that some of these benefits may be achievable at lower ocean resolution, if the model formulation allows.

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Coupling a land-surface model with a crop growth model to improve ET flux estimations in the Upper Ganges basin, India

Hydrology and Earth System Sciences ◽

10.5194/hess-18-4223-2014 ◽

2014 ◽

Vol 18 (10) ◽

pp. 4223-4238 ◽

Cited By ~ 12

Author(s):

G. M. Tsarouchi ◽

W. Buytaert ◽

A. Mijic

Keyword(s):

Growth Model ◽

Land Surface ◽

Coupled Model ◽

Crop Growth ◽

Original Model ◽

Surface Model ◽

Strong Impact ◽

Crop Growth Model ◽

Mean Error ◽

The Impact

Abstract. Land-Surface Models (LSMs) are tools that represent energy and water flux exchanges between land and the atmosphere. Although much progress has been made in adding detailed physical processes into these models, there is much room left for improved estimates of evapotranspiration fluxes, by including a more reasonable and accurate representation of crop dynamics. Recent studies suggest a strong land-surface–atmosphere coupling over India and since this is one of the most intensively cultivated areas in the world, the strong impact of crops on the evaporative flux cannot be neglected. In this study we dynamically couple the LSM JULES with the crop growth model InfoCrop. JULES in its current version (v3.4) does not simulate crop growth. Instead, it treats crops as natural grass, while using prescribed vegetation parameters. Such simplification might lead to modelling errors. Therefore we developed a coupled modelling scheme that simulates dynamically crop development and parametrized it for the two main crops of the study area, wheat and rice. This setup is used to examine the impact of inter-seasonal land cover changes in evapotranspiration fluxes of the Upper Ganges River basin (India). The sensitivity of JULES with regard to the dynamics of the vegetation cover is evaluated. Our results show that the model is sensitive to the changes introduced after coupling it with the crop model. Evapotranspiration fluxes, which are significantly different between the original and the coupled model, are giving an approximation of the magnitude of error to be expected in LSMs that do not include dynamic crop growth. For the wet season, in the original model, the monthly Mean Error ranges from 7.5 to 24.4 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 5.4–11.6 mm month−1. For the dry season, in the original model, the monthly Mean Error ranges from 10 to 17 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 2.2–3.4 mm month−1. The new modelling scheme, by offering increased accuracy of evapotranspiration estimations, is an important step towards a better understanding of the two-way crops–atmosphere interactions.

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Assessment of Extreme Storm Surges over the Changjiang River Estuary from a Wave–Current Coupled Model

Journal of Marine Science and Engineering ◽

10.3390/jmse9111222 ◽

2021 ◽

Vol 9 (11) ◽

pp. 1222

Author(s):

Yutao Chi ◽

Zengrui Rong

Keyword(s):

Return Period ◽

River Estuary ◽

Coupled Model ◽

Storm Surges ◽

Distribution Model ◽

Changjiang River ◽

Changjiang River Estuary ◽

The Changjiang River ◽

The Changjiang River Estuary ◽

The Impact

Disastrous storm surges and waves caused by typhoons are major marine dynamic disasters affecting the east China coast and the Changjiang River Estuary, especially when they occur coincidentally. In this study, a high-resolution wave–current coupled model consisting of ADCIRC (Advanced Circulation) and SWAN (Simulating Waves Nearshore) was established and validated. The model shows reasonable skills in reproducing the surge levels and waves. The storm surges and associated waves are then simulated for 98 typhoons affecting the Changjiang River Estuary over the past 32 years (1987–2018). Two different wind fields, the ERA reanalysis and the ERA-based synthetic wind with a theoretical typhoon model, were adopted to discern the potential uncertainties associated with winds. Model results forced by the ERA reanalysis show comparative skills with the synthetic winds, but differences may be relatively large in specific stations. The extreme surge levels with a 50-year return period are then presented based on the coupled model results and the Gumbel distribution model. Higher risk is presented in Hangzhou Bay and the nearshore region along the coast of Zhejiang. Comparative runs with and without wave effects were conducted to discern the impact of waves on the extreme surge levels. The wave setup contributes to 2–12.5% of the 50-year extreme surge level. Furthermore, the joint exceedance probabilities of high surge levels and high wave height were evaluated with the Gumbel–logistic statistic model. Given the same joint return period, the nearshore region along the coast of Zhejiang is more vulnerable with high surges and large waves than the Changjiang River Estuary with large waves and moderate surges.

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Strongly Coupled Assimilation of a Hypothetical Ocean Current Observing Network within a Regional Ocean-Atmosphere Coupled Model: An OSSE Case Study of Typhoon Hato

Monthly Weather Review ◽

10.1175/mwr-d-20-0108.1 ◽

2021 ◽

Author(s):

Luke Phillipson ◽

Yi Li ◽

Ralf Toumi

Keyword(s):

Coupled Model ◽

Ocean Currents ◽

Hf Radar ◽

Ocean Current ◽

Coastal Current ◽

Strongly Coupled ◽

Ocean Atmosphere ◽

Atmospheric Observations ◽

Surface Drifters ◽

The Impact

AbstractThe forecast of tropical cyclone (TC) intensity is a significant challenge. In this study, we showcase the impact of strongly coupled data assimilation with hypothetical ocean currents on analyses and forecasts of Typhoon Hato (2017). Several observation simulation system experiments were undertaken with a regional coupled ocean-atmosphere model. We assimilated combinations of (or individually) a hypothetical coastal current HF radar network, a dense array of drifter floats and minimum sea-level pressure. During the assimilation, instant updates of many important atmospheric variables (winds and pressure) are achieved from the assimilation of ocean current observations using the cross-domain error covariance, significantly improving the track and intensity analysis of Typhoon Hato. As compared to a control experiment (with no assimilation), the error of minimum pressure decreased by up to 13 hPa (4 hPa / 57 % on average). The maximum wind speed error decreased by up to 18 knots (5 knots / 41 % on average). By contrast, weakly coupled implementations cannot match these reductions (10% on average). Although traditional atmospheric observations were not assimilated, such improvements indicate there is considerable potential in assimilating ocean currents from coastal HF radar, and surface drifters within a strongly coupled framework for intense landfalling TCs.

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Application and Comparison of Uncertainty Quantification Methods for Railway Vehicle Dynamics with Random Mechanical Parameters

Mechanika ◽

10.5755/j01.mech.25.6.23278 ◽

2019 ◽

Vol 25 (6) ◽

pp. 455-462

Author(s):

Dawei Zhang ◽

Peijuan Xu ◽

Daniele Bigoni

Keyword(s):

Uncertainty Quantification ◽

Vehicle Dynamics ◽

Deterministic Model ◽

Coupled Model ◽

Latin Hypercube Sampling ◽

Collocation Methods ◽

Impact Behavior ◽

Railway Vehicle ◽

Parametric Uncertainties ◽

The Impact

This paper aims to investigate uncertainties in railway vehicle suspension components and the implement of uncertainty quantification methods in railway vehicle dynamics. The sampling-based method represented by Latin Hypercube Sampling (LHS) and generalized polynomial chaos approaches including the stochastic Galerkin and Collocation methods (SGM and SCM) are employed to analyze the propagation of uncertainties from the parameters input in a vehicle-track mathematical model to the results of running dynamics. In order to illustrate the performance qualities of SGM, SCM and LHS, a stochastic wheel model with uncertainties of the stiffness and damping is firstly formulated to study the vertical displacement of wheel. Numerical results show that SCM, which can be easily implemented by means of the existing deterministic model, has explicit advantages over SGM and LHS in terms of the efficiency and accuracy. Furthermore, a simplified stochastic bogie model with three random suspension parameters is also established by means of SCM and LHS to analyze the critical speed, which is affected obviously by the parametric uncertainties. Finally, a stochastic vertical vehicle-track coupled model with parametric uncertainties is built comprehensively on the basis of SCM, by which the impact behavior of wheel-rail interaction under a rail defect is investigated and the dynamic response of vehicles under the track irregularity is explored in terms of the Sperling index. It concludes that the uncertainties of parameters have a significant influence on P2 force and Sperling index from the view of the running quality.

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Influence of Ocean and Atmosphere Components on Simulated Climate Sensitivities

Journal of Climate ◽

10.1175/jcli-d-12-00121.1 ◽

2013 ◽

Vol 26 (1) ◽

pp. 231-245 ◽

Cited By ~ 27

Author(s):

Michael Winton ◽

Alistair Adcroft ◽

Stephen M. Griffies ◽

Robert W. Hallberg ◽

Larry W. Horowitz ◽

...

Keyword(s):

Sea Ice ◽

Climate Models ◽

Climate Model ◽

Model Simulation ◽

Coupled Model ◽

Ocean Model ◽

Historical Simulation ◽

Model Version ◽

Salinity Response ◽

The Impact

Abstract The influence of alternative ocean and atmosphere subcomponents on climate model simulation of transient sensitivities is examined by comparing three GFDL climate models used for phase 5 of the Coupled Model Intercomparison Project (CMIP5). The base model ESM2M is closely related to GFDL’s CMIP3 climate model version 2.1 (CM2.1), and makes use of a depth coordinate ocean component. The second model, ESM2G, is identical to ESM2M but makes use of an isopycnal coordinate ocean model. The authors compare the impact of this “ocean swap” with an “atmosphere swap” that produces the GFDL Climate Model version 3 (CM3) by replacing the AM2 atmospheric component with AM3 while retaining a depth coordinate ocean model. The atmosphere swap is found to have much larger influence on sensitivities of global surface temperature and Northern Hemisphere sea ice cover. The atmosphere swap also introduces a multidecadal response time scale through its indirect influence on heat uptake. Despite significant differences in their interior ocean mean states, the ESM2M and ESM2G simulations of these metrics of climate change are very similar, except for an enhanced high-latitude salinity response accompanied by temporarily advancing sea ice in ESM2G. In the ESM2G historical simulation this behavior results in the establishment of a strong halocline in the subpolar North Atlantic during the early twentieth century and an associated cooling, which are counter to observations in that region. The Atlantic meridional overturning declines comparably in all three models.

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Stability and Variability of the Thermohaline Circulation in the Past and Future: a Study with a Coupled Model of Intermediate Complexity

Geophysical Monograph Series - The Oceans and Rapid Climate Change ◽

10.1029/gm126p0261 ◽

2013 ◽

pp. 261-275 ◽

Cited By ~ 5

Author(s):

Audrey Ganopolski ◽

Stefan Rahmstorf

Keyword(s):

Thermohaline Circulation ◽

Coupled Model ◽

The Past ◽

Intermediate Complexity

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The role of air-sea coupling on the simulation of intraseasonal rainfall variability over the South Pacific in ECHAM5-SIT

10.5194/egusphere-egu21-12770 ◽

2021 ◽

Author(s):

Sunil Kumar Pariyar ◽

Noel Keenlyside ◽

Wan-Ling Tseng

Keyword(s):

General Circulation ◽

Rainfall Variability ◽

Intraseasonal Variability ◽

Phase Relationship ◽

Coupled Model ◽

South Pacific ◽

South Pacific Convergence Zone ◽

The South ◽

The Impact

We investigate the impact of air-sea coupling on the simulation of the intraseasonal variability of rainfall over the South Pacific using the ECHAM5 atmospheric general circulation model coupled with Snow-Ice-Thermocline (SIT) ocean model. We compare the fully coupled simulation with two uncoupled simulations forced with sea surface temperature (SST) climatology and daily SST from the coupled model. The intraseasonal rainfall variability over the South Pacific Convergence Zone (SPCZ) is reduced by 17% in the uncoupled model forced with SST climatology and increased by 8% in the uncoupled simulation forced with daily SST. The coupled model best simulates the key characteristics of the two intraseasonal rainfall modes of variability in the South Pacific, as identified by an Empirical Orthogonal Function (EOF) analysis. The spatial structure of the two EOF modes in all three simulations is very similar, suggesting these modes are independent of air-sea coupling and primarily generated by the dynamics of the atmosphere. The southeastward propagation of rainfall anomalies associated with two leading rainfall modes in the South Pacific depends upon the eastward propagating Madden-Julian Oscillation (MJO) signals over the Indian Ocean and western Pacific. Air-sea interaction seems crucial for such propagation as both eastward and southeastward propagations substantially reduced in the uncoupled model forced with SST climatology. Prescribing daily SST from the coupled model improves the simulation of both eastward and southeastward propagations in the uncoupled model forced with daily SST, showing the role of SST variability on the propagation of the intraseasonal variability, but the periodicity differs from the coupled model. The change in the periodicity is attributed to a weaker SST-rainfall relationship that shifts from SST leading rainfall to a nearly in-phase relationship in the uncoupled model forced with daily SST.

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