Introduction to A Regional Coupled Forecasting System

2020 ◽  
Author(s):  
Mingkui Li ◽  
Shaoqing Zhang
Keyword(s):  
National Laboratory ◽  
Coupled Model ◽  
Ocean Model ◽  
Asia Pacific ◽  
Model Resolution ◽  
Coupled Models ◽  
Regional Ocean Model System ◽  
Extended Range ◽  
Coupled Data Assimilation ◽  
The Impact

<p>A regional coupled prediction system for the Asia-Pacific area (AP-RCP) has been established. The AP-RCP system consists of WRF-ROMS (Weather Research and Forecast and Regional Ocean Model System) coupled models combined with local observing information through dynamically downscaling coupled data assimilation. The system generates 18-day atmospheric and oceanic environment forecasts on a daily quasi-operational schedule at Qingdao Pilot National Laboratory for Marine Science and Technology (QNLM). The AP-RCP system mainly includes 2 different coupled model resolutions: 27km WRF coupled with 9km ROMS, and 9km WRF coupled with 3km ROMS. This study evaluates the impact of enhancing coupled model resolution on the extended-range forecasts, focusing on forecasts of typhoon onset, and improved precipitation and typhoon intensity forecasts. Results show that enhancing coupled model resolution is a necessary step to realize the extended-range predictability of the atmosphere and ocean environmental conditions that include a plenty of local details. The next challenges include improving the planetary boundary physics and the representation of air-sea and air-land interactions when the model can resolve the kilometer or sub-kilometer processes.</p>

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

2009 ◽  
Vol 22 (10) ◽  
pp. 2541-2556 ◽  
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.

scholarly journals The impact of resolving the Rossby radius at mid-latitudes in the ocean: results from a high-resolution version of the Met Office GC2 coupled model

2016 ◽  
Vol 9 (10) ◽  
pp. 3655-3670 ◽  
Author(s):  
Helene T. Hewitt ◽  
Malcolm J. Roberts ◽  
Pat Hyder ◽  
Tim Graham ◽  
Jamie Rae ◽  
...  
Keyword(s):  
High Resolution ◽  
Coupled Model ◽  
Ocean Model ◽  
The Body ◽  
Western Boundary ◽  
Coupled Models ◽  
Technical Developments ◽  
Enhanced Resolution ◽  
Circumpolar Current ◽  
The Impact

Abstract. There is mounting evidence that resolving mesoscale eddies and western boundary currents as well as topographically controlled flows can play an important role in air–sea interaction associated with vertical and lateral transports of heat and salt. Here we describe the development of the Met Office Global Coupled Model version 2 (GC2) with increased resolution relative to the standard model: the ocean resolution is increased from 1/4 to 1/12° (28 to 9 km at the Equator), the atmosphere resolution increased from 60 km (N216) to 25 km (N512) and the coupling period reduced from 3 hourly to hourly. The technical developments that were required to build a version of the model at higher resolution are described as well as results from a 20-year simulation. The results demonstrate the key role played by the enhanced resolution of the ocean model: reduced sea surface temperature (SST) biases, improved ocean heat transports, deeper and stronger overturning circulation and a stronger Antarctic Circumpolar Current. Our results suggest that the improvements seen here require high resolution in both atmosphere and ocean components as well as high-frequency coupling. These results add to the body of evidence suggesting that ocean resolution is an important consideration when developing coupled models for weather and climate applications.

scholarly journals The impact of resolving the Rossby radius at mid-latitudes in the ocean: results from a high-resolution version of the Met Office GC2 coupled model

2016 ◽  
Author(s):  
Helene T. Hewitt ◽  
Malcolm J. Roberts ◽  
Pat Hyder ◽  
Tim Graham ◽  
Jamie Rae ◽  
...  
Keyword(s):  
High Resolution ◽  
Coupled Model ◽  
Ocean Model ◽  
The Body ◽  
Coupled Models ◽  
Surface Ocean ◽  
Technical Developments ◽  
Enhanced Resolution ◽  
Circumpolar Current ◽  
The Impact

Abstract. There is mounting evidence that resolving mesoscale eddies and boundary currents in the surface ocean field can play an important role in air-sea interaction associated with vertical and lateral transports of heat and salt. Here we describe the development of the Met Office Global Coupled Model version 2 (GC2) with increased resolution relative to the standard model: the ocean resolution is increased from 1/4° to 1/12° (28 km to 9 km at the Equator), the atmosphere resolution increased from 60 km (N216) to 25 km (N512) and the coupling frequency increased from 3-hourly to hourly. The technical developments that were required to build a version of the model at higher resolution are described as well as results from a 20 year simulation. The results demonstrate the key role played by the enhanced resolution of the ocean model: reduced Sea Surface Temperature biases, improved ocean heat transports, deeper and stronger overturning circulation and a stronger Antarctic Circumpolar Current. Our results suggest that the improvements seen here require high resolution in both atmosphere and ocean components as well as high frequency coupling. These results add to the body of evidence suggesting that ocean resolution is an important consideration when developing coupled models for weather and climate applications.

Impacts of ocean model resolution in S2S forecasts with the ECMWF coupled model

2020 ◽  
Author(s):  
Chris Roberts ◽  
Frederic Vitart ◽  
Magdalena Balmaseda ◽  
Franco Molteni
Keyword(s):  
North Atlantic ◽  
Storm Track ◽  
Coupled Model ◽  
Ocean Model ◽  
Surface Heating ◽  
Lead Times ◽  
Model Resolution ◽  
Seasonal Forecasts ◽  
The North ◽  
The Impact

<p>This study uses initialized forecasts to evaluate the wintertime North Atlantic response to an increase of ocean model resolution from ~100 km (LRO) to ~25 km (HRO) in the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS). Importantly, the simulated impacts are timescale-dependent such that impacts in subseasonal and seasonal forecasts cannot be extrapolated from multidecadal climate experiments. In general, mean biases are reduced in HRO relative to LRO configurations and the impact is increased at longer lead times. At subseasonal to seasonal lead times, surface heating anomalies over the Gulf Stream are associated with local increases to the poleward heat flux associated with transient atmospheric eddies. In contrast, surface heating anomalies in climate experiments are balanced by changes to the time-mean surface winds that resemble the steady response under linear dynamics. Some aspects of air-sea interaction exhibit a clear improvement with increased resolution at all lead times. However, it is difficult to identify the impact of increased ocean eddy activity in the variability of the overlying atmosphere. In particular, atmospheric blocking and the intensity of the storm track respond more strongly to mean biases and thus have a larger response at longer lead times. Finally, increased ocean resolution drives improvements to subseasonal predictability over Europe. This increase in skill seems to be a result of improvements to the Madden Julian Oscillation and its associated teleconnections rather than changes to air-sea interaction in the North Atlantic region.</p>

scholarly journals Error Covariance Estimation for Coupled Data Assimilation Using a Lorenz Atmosphere and a Simple Pycnocline Ocean Model

2013 ◽  
Vol 26 (24) ◽  
pp. 10218-10231 ◽  
Author(s):  
Guijun Han ◽  
Xinrong Wu ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Wei Li
Keyword(s):  
Data Assimilation ◽  
Time Scale ◽  
Coupled Model ◽  
Ocean Model ◽  
Multiple Time ◽  
Multiple Time Scale ◽  
Error Covariance ◽  
Coupled Data Assimilation ◽  
The Impact ◽  
Coupling Error

Abstract Coupled data assimilation uses a coupled model consisting of multiple time-scale media to extract information from observations that are available in one or more media. Because of the instantaneous exchanges of information among the coupled media, coupled data assimilation is expected to produce self-consistent and physically balanced coupled state estimates and optimal initialization for coupled model predictions. It is also expected that applying coupling error covariance between two media into observational adjustments in these media can provide direct observational impacts crossing the media and thereby improve the assimilation quality. However, because of the different time scales of variability in different media, accurately evaluating the error covariance between two variables residing in different media is usually very difficult. Using an ensemble filter together with a simple coupled model consisting of a Lorenz atmosphere and a pycnocline ocean model, which characterizes the interaction of multiple time-scale media in the climate system, the impact of the accuracy of coupling error covariance on the quality of coupled data assimilation is studied. Results show that it requires a large ensemble size to improve the assimilation quality by applying coupling error covariance in an ensemble coupled data assimilation system, and the poorly estimated coupling error covariance may otherwise degrade the assimilation quality. It is also found that a fast-varying medium has more difficulty being improved using observations in slow-varying media by applying coupling error covariance because the linear regression from the observational increment in slow-varying media has difficulty representing the high-frequency information of the fast-varying medium.

Influence of Ocean and Atmosphere Components on Simulated Climate Sensitivities

2013 ◽  
Vol 26 (1) ◽  
pp. 231-245 ◽  
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.

scholarly journals Efficient ensemble data assimilation for coupled models with the Parallel Data Assimilation Framework: Example of AWI-CM

2019 ◽  
Author(s):  
Lars Nerger ◽  
Qi Tang ◽  
Longjiang Mu
Keyword(s):  
Data Assimilation ◽  
Numerical Models ◽  
Computing Time ◽  
Coupled Model ◽  
Ocean Model ◽  
Coupled Models ◽  
Parallel Data ◽  
Efficient Data ◽  
Abstract Data ◽  
Assimilation Process

Abstract. Data assimilation integrates information from observational measurements with numerical models. When used with coupled models of Earth system compartments, e.g. the atmosphere and the ocean, consistent joint states can be estimated. A common approach for data assimilation are ensemble-based methods which use an ensemble of state realizations to estimate the state and its uncertainty. These methods are far more costly to compute than a single coupled model because of the required integration of the ensemble. However, with uncoupled models, the methods also have been shown to exhibit a particularly good scaling behavior. This study discusses an approach to augment a coupled model with data assimilation functionality provided by the Parallel Data Assimilation Framework (PDAF). Using only minimal changes in the codes of the different compartment models, a particularly efficient data assimilation system is generated that utilizes parallelization and in-memory data transfers between the models and the data assimilation functions and hence avoids most of the filter reading and writing and also model restarts during the data assimilation process. The study explains the required modifications of the programs on the example of the coupled atmosphere-sea ice-ocean model AWI-CM. Using the case of the assimilation of oceanic observations shows that the data assimilation leads only small overheads in computing time of about 15 % compared to the model without data assimilation and a very good parallel scalability. The model-agnostic structure of the assimilation software ensures a separation of concerns in that the development of data assimilation methods and be separated from the model application.

scholarly journals Model resolution influence on simulated sea ice decline

2008 ◽  
Vol 2 (5) ◽  
pp. 759-776 ◽  
Author(s):  
J. O. Sewall
Keyword(s):  
Sea Ice ◽  
Heat Transport ◽  
Coupled Model ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
Model Resolution ◽  
Ocean Heat Transport ◽  
Sea Ice Decline ◽  
Arctic Sea ◽  
Model Predictions

Abstract. Satellite observations and model predictions of recent and future Arctic sea ice decline have raised concerns over the timing and potential impacts of a seasonally ice-free Arctic Ocean. Model predictions of seasonally ice-free Arctic conditions are, however, highly variable. Here I present results from fourteen climate system models from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset that indicate modeled Arctic sea ice sensitivity to increased atmospheric CO2 forcing is strongly correlated with ice/ocean model horizontal resolution. Based on coupled model analyses and ice only simulations with the Los Alamos National Lab sea ice model (CICE), the correlation between declining Arctic sea ice cover and ice/ocean model resolution appears to depend largely on ocean model resolution and its influence on ocean heat transport into the Arctic basin. The correlation between model resolution, northward ocean heat transport, and the degree of Arctic ice loss is independent of ice model physics and complexity. This not only illustrates one difficulty in using numerical models to accurately predict the timing and magnitude of Arctic sea ice decline under increasing atmospheric greenhouse gas forcing, but also highlights one area where improved simulation (of northward ocean heat transport) could greatly decrease the uncertainties associated with predictions of future Arctic sea ice cover.

scholarly journals Multiscale Applications of Two Online-Coupled Meteorology-Chemistry Models During Recent Field Campaigns in Australia, Part II: Comparison of WRF/Chem and WRF/Chem-ROMS and Impacts of Air-Sea Interactions and Boundary Conditions

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 210 ◽  
Author(s):  
Zhang ◽  
Wang ◽  
Jena ◽  
Paton-Walsh ◽  
Guérette ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Temporal Variations ◽  
Ocean Model ◽  
Heat Fluxes ◽  
Atmospheric Pollutants ◽  
Spatial Distributions ◽  
Surface Heat Fluxes ◽  
Regional Ocean Model System ◽  
Field Campaigns ◽  
The Impact

Air-sea interactions play an important role in atmospheric circulation and boundary layer conditions through changing convection processes and surface heat fluxes, particularly in coastal areas. These changes can affect the concentrations, distributions, and lifetimes of atmospheric pollutants. In this Part II paper, the performance of the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are intercompared for their applications over quadruple-nested domains in Australia during the three following field campaigns: The Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2) and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). The results are used to evaluate the impact of air-sea interaction representation in WRF/Chem-ROMS on model predictions. At 3, 9, and 27 km resolutions, compared to WRF/Chem, the explicit air-sea interactions in WRF/Chem-ROMS lead to substantial improvements in simulated sea-surface temperature (SST), latent heat fluxes (LHF), and sensible heat fluxes (SHF) over the ocean, in terms of statistics and spatial distributions, during all three field campaigns. The use of finer grid resolutions (3 or 9 km) effectively reduces the biases in these variables during SPS1 and SPS2 by WRF/Chem-ROMS, whereas it further increases these biases for WRF/Chem during all field campaigns. The large differences in SST, LHF, and SHF between the two models lead to different radiative, cloud, meteorological, and chemical predictions. WRF/Chem-ROMS generally performs better in terms of statistics and temporal variations for temperature and relative humidity at 2 m, wind speed and direction at 10 m, and precipitation. The percentage differences in simulated surface concentrations between the two models are mostly in the range of ±10% for CO, OH, and O3, ±25% for HCHO, ±30% for NO2, ±35% for H2O2, ±50% for SO2, ±60% for isoprene and terpenes, ±15% for PM2.5, and ±12% for PM10. WRF/Chem-ROMS at 3 km resolution slightly improves the statistical performance of many surface and column concentrations. WRF/Chem simulations with satellite-constrained boundary conditions (BCONs) improve the spatial distributions and magnitudes of column CO for all field campaigns and slightly improve those of the column NO2 for SPS1 and SPS2, column HCHO for SPS1 and MUMBA, and column O3 for SPS2 at 3 km over the Greater Sydney area. The satellite-constrained chemical BCONs reduce the model biases of surface CO, NO, and O3 predictions at 3 km for all field campaigns, surface PM2.5 predictions at 3 km for SPS1 and MUMBA, and surface PM10 predictions at all grid resolutions for all field campaigns. A more important role of chemical BCONs in the Southern Hemisphere, compared to that in the Northern Hemisphere reported in this work, indicates a crucial need in developing more realistic chemical BCONs for O3 in the relatively clean SH.

scholarly journals Wave–current interactions in a wind-jet region

Ocean Science ◽  
2019 ◽  
Vol 15 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Laura Ràfols ◽  
Manel Grifoll ◽  
Manuel Espino
Keyword(s):  
Numerical Models ◽  
Mixed Layer Depth ◽  
Coupled System ◽  
Ocean Model ◽  
Water Current ◽  
Northern Margin ◽  
Water Column Stratification ◽  
Regional Ocean Model System ◽  
Current Flows ◽  
The Impact

Abstract. Wave–current interactions (WCIs) are investigated. The study area is located at the northern margin of the Ebro shelf (northwestern Mediterranean Sea), where episodes of strong cross-shelf wind (wind jets) occur. The aim of this study is to validate the implemented coupled system and investigate the impact of WCIs on the hydrodynamics of a wind-jet region. The Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system, which uses the Regional Ocean Model System (ROMS) and Simulating WAves Nearshore (SWAN) models, is used in a high-resolution domain (350 m). Results from uncoupled numerical models are compared with a two-way coupling simulation. The results do not show substantial differences in the water current field between the coupled and the uncoupled runs. The main effect observed when the models are coupled is in the water column stratification, due to the turbulent kinetic energy injection and the enhanced surface stress, leading to a larger mixed-layer depth. Regarding the effects on the wave fields, the comparison between the coupled and the uncoupled runs shows that, when the models are coupled, the agreement of the modeled wave period significantly improves and the wave energy (and thus the significant wave height) decreases when the current flows in the same direction as the waves propagate.

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