scholarly journals Development of high-resolution future ocean regional projection datasets for coastal applications in Japan

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Shiro Nishikawa ◽  
Tsuyoshi Wakamatsu ◽  
Hiroshi Ishizaki ◽  
Kei Sakamoto ◽  
Yusuke Tanaka ◽  
...  
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
North Pacific Ocean ◽  
Coastal Region ◽  
Coupled Model ◽  
Projection Data ◽  
Regional Projection ◽  
The Kuroshio ◽  
Applications In Japan

AbstractIn this study, we developed two high-resolution future ocean regional projection datasets for coastal applications in Japan, in which we made use of dynamical downscaling via regional ocean models with atmospheric forcing from two climate models (i.e., MIROC5 and MRI-CGCM3) participating in Coupled Model Intercomparison Project Phase 5 (CMIP5) under historical, representative concentration pathway (RCP) 2.6, and RCP8.5 scenarios. The first dataset was an eddy-resolving 10-km resolution product covering the North Pacific Ocean area and ranging continuously from 1981 to 2100, in which the Kuroshio current and mesoscale structures were reasonably resolved. The second dataset was a 2-km resolution product covering the regional domain surrounding Japan and comprising 10–15-year time slices, in which the coastal geometry and current structure were resolved even more realistically. An important feature of these datasets was the availability of reference datasets based on atmospheric and oceanic reanalysis data for cross-validation during the historical run period. Using these reference datasets, biases of regional surface thermal properties and the Kuroshio states during the historical run period were evaluated, which constitute important information for users of the datasets. In these downscaled datasets, the future surface thermal responses were generally consistent with those of their original data. Utilizing the high-resolution property of the downscaled data, possible future impact analyses regarding coastal phenomena such as strait throughflows, coastal sea level variability, and the Kuroshio intrusion phenomenon into bays (“Kyucho” phenomenon) were demonstrated and the important role of the Kuroshio state representation was indicated, which had proved difficult to analyze using the low-resolution projection data. Given these properties, the present datasets would be useful in climate change adaptation studies regarding the Japanese coastal region.

scholarly journals Local Sea-Level Rise Caused by Climate Change in the Northwest Pacific Marginal Seas Using Dynamical Downscaling

2021 ◽  
Vol 8 ◽  
Author(s):  
Yong-Yub Kim ◽  
Bong-Gwan Kim ◽  
Kwang Young Jeong ◽  
Eunil Lee ◽  
Do-Seong Byun ◽  
...  
Keyword(s):  
High Resolution ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
The Yellow Sea ◽  
Northwest Pacific ◽  
Tidal Amplitude ◽  
Marginal Seas ◽  
Rcp 8.5

Global climate models (GCMs) have limited capacity in simulating spatially non-uniform sea-level rise owing to their coarse resolutions and absence of tides in the marginal seas. Here, regional ocean climate models (RCMs) that consider tides were used to address these limitations in the Northwest Pacific marginal seas through dynamical downscaling. Four GCMs that drive the RCMs were selected based on a performance evaluation along the RCM boundaries, and the latter were validated by comparing historical results with observations. High-resolution (1/20°) RCMs were used to project non-uniform changes in the sea-level under intermediate (RCP 4.5) and high-end emissions (RCP 8.5) scenarios from 2006 to 2100. The predicted local sea-level rise was higher in the East/Japan Sea (EJS), where the currents and eddy motions were active. The tidal amplitude changes in response to sea-level rise were significant in the shallow areas of the Yellow Sea (YS). Dynamically downscaled simulations enabled the determination of practical sea-level rise (PSLR), including changes in tidal amplitude and natural variability. Under RCP 8.5 scenario, the maximum PSLR was ∼85 cm in the YS and East China Sea (ECS), and ∼78 cm in the EJS. The contribution of natural sea-level variability changes in the EJS was greater than that in the YS and ECS, whereas changes in the tidal contribution were higher in the YS and ECS. Accordingly, high-resolution RCMs provided spatially different PSLR estimates, indicating the importance of improving model resolution for local sea-level projections in marginal seas.

Simulation of wind damages associated with the PRIMAVERA European windstorm event set

2021 ◽  
Author(s):  
Tristan Perotin
Keyword(s):  
Climate Models ◽  
Dynamical Downscaling ◽  
Insurance Industry ◽  
Coupled Model ◽  
Correction Method ◽  
Weather Data ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Insurance Sector ◽  
Intercomparison Project

<p>Winter windstorms are one of the major natural hazards affecting Europe, potentially causing large damages. The study of windstorm risks is therefore particularly important for the insurance industry. Physical natural catastrophe models for the insurance industry appeared in the 1980s and enable a fine analysis of the risk by taking into account all of its components (hazard, vulnerability and exposure). One main aspect of this catastrophe modeling is the production and validation of extreme hazard scenarios. As observational weather data is very sparse before the 1980s, estimates of extreme windstorm risks are usually based on climate models, despite the limited resolution of these models. Even though this limitation can be partially corrected by statistical or dynamical downscaling and calibration techniques, new generations of climate models can bring new understanding of windstorm risks.</p><p>In that context, PRIMAVERA, a European Union Horizon2020 project, made available a windstorm event set based on 21 tier 1 (1950-2014) highresSST-present simulations of the High Resolution Model Intercomparison Project (HighResMIP) component of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The events were identified with a storm tracking algorithm, footprints were defined for each event as maximum gusts over a 72 hour period, and the footprints were re-gridded to the ERA5 grid and calibrated with a quantile mapping correction method. The native resolution of these simulations ranges from 150km (typical resolution of the CMIP5 models) to 25km.</p><p>We have studied the applicability of the PRIMAVERA European windstorm event set for the modeling of European windstorm risks for the insurance sector. Preliminary results show that losses simulated from the event set appear to be consistent with historical data for all of the included simulations. The event set enables a better representation of attritional events and storm clustering than other existing event sets. An alternative calibration technique for extreme gusts and potential future developments of the event set will be proposed.</p>

Frontal Scale Air–Sea Interaction in High-Resolution Coupled Climate Models

2010 ◽  
Vol 23 (23) ◽  
pp. 6277-6291 ◽  
Author(s):  
Frank O. Bryan ◽  
Robert Tomas ◽  
John M. Dennis ◽  
Dudley B. Chelton ◽  
Norman G. Loeb ◽  
...  
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Climate Models ◽  
Prediction Models ◽  
Weather Prediction ◽  
Surface Wind ◽  
Coupled Model ◽  
Climate System Model ◽  
Surface Wind Stress ◽  
Coupled Climate Models

Abstract The emerging picture of frontal scale air–sea interaction derived from high-resolution satellite observations of surface winds and sea surface temperature (SST) provides a unique opportunity to test the fidelity of high-resolution coupled climate simulations. Initial analysis of the output of a suite of Community Climate System Model (CCSM) experiments indicates that characteristics of frontal scale ocean–atmosphere interaction, such as the positive correlation between SST and surface wind stress, are realistically captured only when the ocean component is eddy resolving. The strength of the coupling between SST and surface stress is weaker than observed, however, as has been found previously for numerical weather prediction models and other coupled climate models. The results are similar when the atmospheric component model grid resolution is doubled from 0.5° to 0.25°, an indication that shortcomings in the representation of subgrid scale atmospheric planetary boundary layer processes, rather than resolved scale processes, are responsible for the weakness of the coupling. In the coupled model solutions the response to mesoscale SST features is strongest in the atmospheric boundary layer, but there is a deeper reaching response of the atmospheric circulation apparent in free tropospheric clouds. This simulated response is shown to be consistent with satellite estimates of the relationship between mesoscale SST and all-sky albedo.

scholarly journals Added value of high-resolution climate projections over South Korea on the scaling of precipitation with temperature

2021 ◽  
Author(s):  
Liying Qiu ◽  
Eun-Soon Im
Keyword(s):  
Global Warming ◽  
High Resolution ◽  
South Korea ◽  
Spatial Pattern ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Models ◽  
Added Value ◽  
Climate Projections

Abstract This study evaluates the resolution dependency of scaling precipitation with temperature from the perspective of the added value of high-resolution (5-km) dynamical downscaling using various kinds of long-term climate change projections over South Korea. Three CMIP5 Global Climate Models (GCMs) with different climate sensitivities, and one pseudo global warming (PGW) experiment, are downscaled by Weather Research and Forecasting (WRF) one-way double nested modeling system with convective parameterization for the reference (1976-2005) and future (2071-2100) periods under RCP8.5 scenario. A detailed comparison of the driving GCM/PGW, 20-km mother simulation, and 5-km nested simulation demonstrates improved representation of precipitation with increasing resolution not only in the spatial pattern and magnitude for both the mean and the extremes, but also in a more realistic representation of extreme precipitation’s sensitivities to temperature. According to the projected precipitation changes downscaled from both GCM ensemble and PGW, there will be intensified precipitation, particularly for the extremes, over South Korea under the warming, which is primarily contributed by CP increase that shows higher temperature sensitivity. This study also compares the extreme precipitation-temperature scaling relations within-epoch (apparent scaling) and between-epoch (climate scaling). It confirms that the magnitude and spatial pattern of the two scaling rates can be quite different, and the precipitation change over Korea under global warming is mainly controlled by thermodynamic factors.

scholarly journals A Quantitative Method to Evaluate Tropical Cyclone Tracks in Climate Models

2018 ◽  
Vol 35 (9) ◽  
pp. 1807-1818 ◽  
Author(s):  
Yixuan Shen ◽  
Yuan Sun ◽  
Suzana J. Camargo ◽  
Zhong Zhong
Keyword(s):  
Climate Models ◽  
North Pacific Ocean ◽  
Model Performance ◽  
Coupled Model ◽  
Evaluation Methods ◽  
Track Density ◽  
Direct Model ◽  
Indirect Evaluation ◽  
Intercomparison Project ◽  
Track Simulation

AbstractThe ability to simulate tropical cyclones (TCs) realistically is an important factor in the performance evaluation of climate models. In previous studies, indirect evaluation methods have been proposed that are based on the comparison of TC-related background circulation between model results and observations. Direct model evaluation methods, in most cases, are limited to the model skill in simulating the TC frequency, intensity, and track density. Here we propose a new method to quantitatively and directly evaluate the ability of climate models in simulating TC tracks. The method consists of two indicators that account for the model performance in simulating TC track density and the geographic properties of TC tracks, respectively. This method is applied to evaluate the skill of climate models in simulating TC tracks over the western North Pacific Ocean. The explicit models include seven from phase 5 of the Coupled Model Intercomparison Project and eight from the U.S. CLIVAR Hurricane Working Group (HWG), as well as four downscaled HWG models. Our results indicate the order of these 15 explicit models according to their ability to simulate TC tracks. In addition, we show that, for one of the models, the TC track simulation is greatly improved by using downscaling.

scholarly journals High resolution climate change projections for the Pyrenees region

2020 ◽  
Vol 17 ◽  
pp. 191-208
Author(s):  
María P. Amblar-Francés ◽  
Petra Ramos-Calzado ◽  
Jorge Sanchis-Lladó ◽  
Alfonso Hernanz-Lázaro ◽  
María C. Peral-García ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
21St Century ◽  
Statistical Downscaling ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Climate Projections ◽  
Climate Change Projections ◽  
Climate Conditions ◽  
The Impact

Abstract. The Pyrenees, located in the transition zone of Atlantic and Mediterranean climates, constitute a paradigmatic example of mountains undergoing rapid changes in environmental conditions, with potential impact on the availability of water resources, mainly for downstream populations. High-resolution probabilistic climate change projections for precipitation and temperature are a crucial element for stakeholders to make well-informed decisions on adaptation to new climate conditions. In this line, we have generated high–resolution climate projections for 21st century by applying two statistical downscaling methods (regression for max and min temperatures, and analogue for precipitation) over the Pyrenees region in the frame of the CLIMPY project over a new high-resolution (5 km × 5 km) observational grid using 24 climate models from CMIP5. The application of statistical downscaling to such a high resolution observational grid instead of station data partially circumvent the problems associated to the non-uniform distribution of observational in situ data. This new high resolution projections database based on statistical algorithms complements the widely used EUROCORDEX data based on dynamical downscaling and allows to identify features that are dependent on the particular downscaling method. In our analysis, we not only focus on maximum and minimum temperatures and precipitation changes but also on changes in some relevant extreme indexes, being 1986–2005 the reference period. Although climate models predict a general increase in temperature extremes for the end of the 21st century, the exact spatial distribution of changes in temperature and much more in precipitation remains uncertain as they are strongly model dependent. Besides, for precipitation, the uncertainty associated to models can mask – depending on the zones- the signal of change. However, the large number of downscaled models and the high resolution of the used grid allow us to provide differential information at least at massif level. The impact of the RCP becomes significant for the second half of the 21st century, with changes – differentiated by massifs – of extreme temperatures and analysed associated extreme indexes for RCP8.5 at the end of the century.

scholarly journals Assessing Past Climate Biases and the Added Value of CORDEX-CORE Precipitation Simulations over Africa

2021 ◽  
Vol 13 (11) ◽  
pp. 2058
Author(s):  
Gnim Tchalim Gnitou ◽  
Guirong Tan ◽  
Ruoyun Niu ◽  
Isaac Kwesi Nooni
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Spatial Coverage ◽  
Wide Range

The present study investigates the skills of CORDEX-CORE precipitation outputs in simulating Africa’s key seasonal climate features, emphasizing the added value (AV) of the dynamical downscaling approach from which they were derived. The results indicate the models’ good skills in capturing African rainfall patterns and dynamics at satellite-based observation resolutions, with up to 65.17% significant positive AV spatial coverage for the CCLM5 model and up to 55.47% significant positive AV spatial coverage for the REMO model. Unavoidable biases are however present in rainfall-abundant areas and are reflected in the AV results, but vary based on the season, the sub-area, and the Global Climate Model–Regional Climate Models (GCM-RCM) combination considered. The RCMs’ ensemble mean generally performs better than individual GCM–RCM simulations. A further analysis of the GCM–RCM model chain indicates a strong influence of the dynamical downscaling approach on the driving GCMs. However, exceptions are found in some seasons for specific RCMs’ outputs, where GCMs are influential. The findings also revealed that observational uncertainties can influence AV and contribute to a 6 to 34% difference in significant positive AV spatial coverage results. An analysis of these results suggests that the AV by CORDEX-CORE simulations over Africa depend on how well the GCM physics are integrated to those of the RCMs and how these features are accommodated in the high-resolution setting of the downscaling experiments. The deficiencies of the CORDEX-CORE simulations could be related to how well key processes are represented within the RCM models. For Africa, these results show that CORDEX-CORE products could be adequate for a wide range of high-resolution precipitation data applications.

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

scholarly journals Parameter Optimization for Real-World ENSO Forecast in an Intermediate Coupled Model

2019 ◽  
Vol 147 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
Yuchu Zhao ◽  
Zhengyu Liu ◽  
Fei Zheng ◽  
Yishuai Jin
Keyword(s):  
Data Assimilation ◽  
Parameter Optimization ◽  
Real World ◽  
Climate Models ◽  
Coupled Model ◽  
Prediction Skill ◽  
Model Parameters ◽  
Real World Data ◽  
The Real ◽  
Advection Term

Abstract We performed parameter estimation in the Zebiak–Cane model for the real-world scenario using the approach of ensemble Kalman filter (EnKF) data assimilation and the observational data of sea surface temperature and wind stress analyses. With real-world data assimilation in the coupled model, our study shows that model parameters converge toward stable values. Furthermore, the new parameters improve the real-world ENSO prediction skill, with the skill improved most by the parameter of the highest climate sensitivity (gam2), which controls the strength of anomalous upwelling advection term in the SST equation. The improved prediction skill is found to be contributed mainly by the improvement in the model dynamics, and second by the improvement in the initial field. Finally, geographic-dependent parameter optimization further improves the prediction skill across all the regions. Our study suggests that parameter optimization using ensemble data assimilation may provide an effective strategy to improve climate models and their real-world climate predictions in the future.

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