scholarly journals The Boreal-Summer Intraseasonal Oscillations Simulated in a Hybrid Coupled Atmosphere–Ocean Model*

2004 ◽  
Vol 132 (11) ◽  
pp. 2628-2649 ◽  
Author(s):  
Xiouhua Fu ◽  
Bin Wang
Keyword(s):  
Three Dimensional ◽  
Intraseasonal Oscillation ◽  
Coupled Model ◽  
Coupled System ◽  
Ocean Model ◽  
Sea Surface ◽  
Boreal Summer ◽  
Surface Cooling ◽  
Internal Dynamics ◽  
Intraseasonal Oscillations

Abstract The boreal-summer intraseasonal oscillation (BSISO) simulated by an atmosphere–ocean coupled model is validated with the long-term observations [Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) rainfall, ECMWF analysis, and Reynolds' SST]. This validation focuses on the three-dimensional water vapor cycle associated with the BSISO and its interaction with underlying sea surface. The advantages of a coupled approach over stand-alone atmospheric approaches on the simulation of the BSISO are revealed through an intercomparison between a coupled run and two atmosphere-only runs. This coupled model produces a BSISO that mimics the one presented in the observations over the Asia– western Pacific region. The similarities with the observations include 1) the coherent spatiotemporal evolutions of rainfall, surface winds, and SST associated with the BSISO; 2) the intensity and period (or speed) of the northward-propagating BSISO; and 3) the tropospheric moistening (or drying) and overturning circulations of the BSISO. However, the simulated tropospheric moisture fluctuations in the extreme phases (both wet and dry) are larger than those in the ECMWF analysis. The simulated sea surface cooling during the wet phase is weaker than the observed cooling. Better representations of the interaction between convection and boundary layer in the GCM and including salinity effects in the ocean model are expected to further improve the simulation of the BSISO. The intercomparison between a coupled run and two atmospheric runs suggests that the air–sea coupled system is the ultimate tool needed to realistically simulate the BSISO. Though the major characteristics of the BSISO are very likely determined by the internal atmospheric dynamics, the correct interaction between the internal dynamics and underlying sea surface can only be sustained by a coupled system. The atmosphere-only approach, when forced with high-frequency (e.g., daily) SST, introduces an erroneous boundary interference on the internal dynamics associated with the BSISO. The implications for the predictability of the BSISO are discussed.

Limitation of One-Dimensional Ocean Models for Coupled Hurricane–Ocean Model Forecasts

2009 ◽  
Vol 137 (12) ◽  
pp. 4410-4419 ◽  
Author(s):  
Richard M. Yablonsky ◽  
Isaac Ginis
Keyword(s):  
North Atlantic Ocean ◽  
Three Dimensional ◽  
Ocean Model ◽  
Sea Surface ◽  
Upper Ocean ◽  
Surface Cooling ◽  
One Dimensional ◽  
Sea Surface Cooling ◽  
Ocean Models ◽  
The One

Abstract Wind stress imposed on the upper ocean by a hurricane can limit the hurricane’s intensity primarily through shear-induced mixing of the upper ocean and subsequent cooling of the sea surface. Since shear-induced mixing is a one-dimensional process, some recent studies suggest that coupling a one-dimensional ocean model to a hurricane model may be sufficient for capturing the storm-induced sea surface temperature cooling in the region providing heat energy to the hurricane. Using both a one-dimensional and a three-dimensional version of the same ocean model, it is shown here that the neglect of upwelling, which can only be captured by a three-dimensional ocean model, underestimates the storm-core sea surface cooling for hurricanes translating at <∼5 m s−1. For hurricanes translating at <2 m s−1, more than half of the storm-core sea surface cooling is neglected by the one-dimensional ocean model. Since the majority of hurricanes in the western tropical North Atlantic Ocean translate at <5 m s−1, the idealized experiments presented here suggest that one-dimensional ocean models may be inadequate for coupled hurricane–ocean model forecasting.

Coupled Sea Ice-Ocean Model of the Arctic Ocean

1998 ◽  
Vol 120 (2) ◽  
pp. 77-84 ◽  
Author(s):  
I. V. Polyakov ◽  
I. Yu. Kulakov ◽  
S. A. Kolesov ◽  
N. Eu. Dmitriev ◽  
R. S. Pritchard ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Three Dimensional ◽  
Coupled Model ◽  
Ocean Model ◽  
Distribution Functions ◽  
Constitutive Law ◽  
Prognostic Models ◽  
The Arctic ◽  
The Arctic Ocean ◽  
Ocean Layer

A fully prognostic coupled ice-ocean model is described. The ice model is based on the elastic-plastic constitutive law with ice mass and compactness described by distribution functions. The ice thermodynamics model is applied individually to each ice thickness category. Advection of the ice partial mass and concentrations is parameterized by a fourth-order algorithm that conserves monotonicity of the solution. The ocean is described as a three-dimensional time-dependent baroclinic model with free surface. The coupled model is applied to establish the Arctic Ocean seasonal climatology using fully prognostic models for ice and ocean. Results reflect the importance of the ice melting/freezing in the formation of the thermohaline structure of the upper ocean layer.

scholarly journals An Evaluation and Implementation of the Regional Coupled Ice-Ocean Model of the Baltic Sea

2017 ◽  
Author(s):  
Jaromir Jakacki ◽  
Sebastian Meler
Keyword(s):  
Baltic Sea ◽  
Three Dimensional ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Ocean Model ◽  
System Model ◽  
The Baltic Sea ◽  
Community Earth System Model ◽  
The Baltic ◽  
Ice Model

Abstract. A three dimensional, regional coupled ice-ocean model based on the open-source Community Earth System Model has been developed and implemented for the Baltic Sea. The model consists of 66 vertical levels and has a horizontal resolution of approx. 2.3 km. The paper focuses on sea ice component results but the main changes have been introduced in the ocean part of the coupled model. The hydrodynamic part, being one of the most important components, has been also presented and validated. The ice model results were validated against the radar and satellite data, and the method of validation based on probability was introduced. In the last two decades satellite and model results show an increase in the ice extent over the whole Baltic Sea, which is an evidence of a negative trend in air temperature in recent decades and increasing of winter discharge from the catchment area.

scholarly journals A Precipitation-Based Index for Tropical Intraseasonal Oscillations

2020 ◽  
Vol 33 (3) ◽  
pp. 805-823 ◽  
Author(s):  
Shuguang Wang
Keyword(s):  
Real Time ◽  
Decadal Variability ◽  
Intraseasonal Oscillation ◽  
Longwave Radiation ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Eof Analysis ◽  
Intraseasonal Oscillations ◽  
Precipitation Anomalies ◽  
Tropical Intraseasonal Oscillations

AbstractCharacteristic patterns of precipitation-associated tropical intraseasonal oscillations, including the Madden–Julian oscillation (MJO) and boreal summer intraseasonal oscillation (BSISO), are identified using local empirical orthogonal function (EOF) analysis of the Tropical Rainfall Measuring Mission (TRMM) precipitation data as a function of the day of the year. The explained variances of the EOF analysis show two peaks across the year: one in the middle of the boreal winter corresponding to the MJO and the other in the middle of summer corresponding to the BSISO. Comparing the fractional variance indicates that the BSISO is more coherent than the MJO during the TRMM period. Similar EOF analyses with the outgoing longwave radiation (OLR) confirm this result and indicate that the BSISO is less coherent before the TRMM era (1979–98). In contrast, the MJO exhibits much less decadal variability. A precipitation-based index for tropical intraseasonal oscillation (PII) is derived by projecting bandpass-filtered precipitation anomalies to the two leading EOFs as a function of day of the year. A real-time version that approximates the PII is further developed using precipitation anomalies without any bandpass filtering. It is further shown that this real-time PII index may be used to diagnose precipitation in the subseasonal forecasts.

Kernel Analog Forecasting of Tropical Intraseasonal Oscillations

2017 ◽  
Vol 74 (4) ◽  
pp. 1321-1342 ◽  
Author(s):  
Romeo Alexander ◽  
Zhizhen Zhao ◽  
Eniko Székely ◽  
Dimitrios Giannakis
Keyword(s):  
Intraseasonal Oscillation ◽  
Empirical Method ◽  
Temperature Data ◽  
Training Data ◽  
Weighted Averaging ◽  
Boreal Summer ◽  
Madden Julian Oscillation ◽  
Pattern Correlation ◽  
Intraseasonal Oscillations ◽  
Tropical Intraseasonal Oscillations

Abstract This paper presents the results of forecasting the Madden–Julian oscillation (MJO) and boreal summer intraseasonal oscillation (BSISO) through the use of satellite-obtained global brightness temperature data with a recently developed nonparametric empirical method. This new method, referred to as kernel analog forecasting, adopts specific indices extracted using the technique of nonlinear Laplacian spectral analysis as baseline definitions of the intraseasonal oscillations of interest, which are then extended into forecasts through an iterated weighted averaging scheme that exploits the predictability inherent to those indices. The pattern correlation of the forecasts produced in this manner remains above 0.6 for 50 days for both the MJO and BSISO when 23 yr of training data are used and 37 days for the MJO when 9 yr of data are used.

scholarly journals Relative Roles of Background Moisture and Vertical Shear in Regulating Interannual Variability of Boreal Summer Intraseasonal Oscillations

2016 ◽  
Vol 29 (19) ◽  
pp. 7009-7025 ◽  
Author(s):  
Li Deng ◽  
Tim Li
Keyword(s):  
Interannual Variability ◽  
Intraseasonal Oscillation ◽  
Longwave Radiation ◽  
Tropical Indian Ocean ◽  
Atmospheric Model ◽  
Vertical Shear ◽  
Boreal Summer ◽  
Moisture Condition ◽  
Intensity Index ◽  
Intraseasonal Oscillations

Abstract The interannual variability of the boreal summer intraseasonal oscillation (BSISO) is investigated using observed outgoing longwave radiation (OLR) and ERA-Interim data for the period of 1980–2012. It is found that the interannual variability of BSISO intensity is much stronger in the tropical western Pacific (TWP) than the tropical Indian Ocean (TIO). A BSISO intensity index is defined based on a multivariate EOF analysis in TWP. It is found that strong BSISO years are associated with El Niño–like sea surface temperature anomalies in the tropical Pacific, anomalous easterly shear, and enhanced background moisture condition in the region. Using a 2.5-layer atmospheric model with a specified idealized background mean state, the authors further examine the relative roles of background moisture and vertical shear fields in modulating the BSISO intensity. Sensitivity numerical experiments indicate that the background moisture change is most important in regulating the BSISO intensity, whereas the background vertical shear change also plays a role.

scholarly journals Subseasonal Forecasting with an Icosahedral, Vertically Quasi-Lagrangian Coupled Model. Part I: Model Overview and Evaluation of Systematic Errors

2018 ◽  
Vol 146 (5) ◽  
pp. 1601-1617 ◽  
Author(s):  
Shan Sun ◽  
Rainer Bleck ◽  
Stanley G. Benjamin ◽  
Benjamin W. Green ◽  
Georg A. Grell
Keyword(s):  
Time Scales ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Coupled Model ◽  
Systematic Errors ◽  
Ocean Model ◽  
Grid Structure ◽  
Ensemble Forecasts ◽  
Vertical Coordinate ◽  
Hybrid Coordinate Ocean Model

Abstract The atmospheric hydrostatic Flow-Following Icosahedral Model (FIM), developed for medium-range weather prediction, provides a unique three-dimensional grid structure—a quasi-uniform icosahedral horizontal grid and an adaptive quasi-Lagrangian vertical coordinate. To extend the FIM framework to subseasonal time scales, an icosahedral-grid rendition of the Hybrid Coordinate Ocean Model (iHYCOM) was developed and coupled to FIM. By sharing a common horizontal mesh, air–sea fluxes between the two models are conserved locally and globally. Both models use similar adaptive hybrid vertical coordinates. Another unique aspect of the coupled model (referred to as FIM–iHYCOM) is the use of the Grell–Freitas scale-aware convective scheme in the atmosphere. A multiyear retrospective study is necessary to demonstrate the potential usefulness and allow for immediate bias correction of a subseasonal prediction model. In these two articles, results are shown based on a 16-yr period of hindcasts from FIM–iHYCOM, which has been providing real-time forecasts out to a lead time of 4 weeks for NOAA’s Subseasonal Experiment (SubX) starting July 2017. Part I provides an overview of FIM–iHYCOM and compares its systematic errors at subseasonal time scales to those of NOAA’s operational Climate Forecast System version 2 (CFSv2). Part II uses bias-corrected hindcasts to assess both deterministic and probabilistic subseasonal skill of FIM–iHYCOM. FIM–iHYCOM has smaller biases than CFSv2 for some fields (including precipitation) and comparable biases for other fields (including sea surface temperature). FIM–iHYCOM also has less drift in bias between weeks 1 and 4 than CFSv2. The unique grid structure and physics suite of FIM–iHYCOM is expected to add diversity to multimodel ensemble forecasts at subseasonal time scales in SubX.

scholarly journals Ice Algae Model Intercomparison Project phase 2 (IAMIP2)

2020 ◽  
Author(s):  
Hakase Hayashida ◽  
Meibing Jin ◽  
Nadja S. Steiner ◽  
Neil C. Swart ◽  
Eiji Watanabe ◽  
...  
Keyword(s):  
Sea Ice ◽  
Initial Conditions ◽  
Three Dimensional ◽  
Coupled Model ◽  
Marine Ecosystems ◽  
Ocean Model ◽  
Ice Algae ◽  
Phase 2 ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. Ice algae play a fundamental role in shaping polar marine ecosystems and biogeochemistry. This role can be investigated by field observations, however the influence of ice algae at the regional and global scales remains unclear due to limited spatial and temporal coverage of observations, and because ice algae are typically not included in current Earth System Models. To address this knowledge gap, we introduce a new model intercomparison project (MIP), referred to here as the Ice Algae Model Intercomparison Project phase 2 (IAMIP2). IAMIP2 is built upon the experience from its previous phase, and expands its scope to global coverage (both Arctic and Antarctic) and centennial timescales (spanning the mid-twentieth century to the end of the twenty-first century). Participating models are three-dimensional regional and global coupled sea ice–ocean models that incorporate sea-ice ecosystem components. These models are driven by the same initial conditions and atmospheric forcing datasets by incorporating and expanding the protocols of the Ocean Model Intercomparison Project, an endorsed MIP of the Coupled Model Intercomparison Project phase 6 (CMIP6). Doing so provides more robust estimates of model bias and uncertainty, and consequently advances the science of polar marine ecosystems and biogeochemistry. A diagnostic protocol is designed to enhance the reusability of the model data products of IAMIP2. Lastly, the limitations and strengths of IAMIP2 are discussed in the context of prospective research outcomes.

Weakened impact of the Atlantic Niño on the future Guinean coast rainfall

2021 ◽  
Author(s):  
Koffi Worou ◽  
Hugues Goosse ◽  
Thierry Fichefet
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Rainfall Variability ◽  
Coupled Model ◽  
Sea Surface ◽  
Boreal Summer ◽  
Tropical Atlantic ◽  
Equatorial Atlantic ◽  
Sea Level Pressure ◽  
Guinean Coast

<p>Much of the rainfall variability in the Guinean coast area during the boreal summer is driven by the sea surface temperature (SST) variations in the eastern equatorial Atlantic, amplified by land-atmosphere interactions. This oceanic region corresponds to the center of action of the Atlantic Equatorial mode, also termed Atlantic Niño (ATL3), which is the leading SST mode of variability in the tropical Atlantic basin. In years of positive ATL3, above normal SST conditions in the ATL3 area weaken the sea level pressure gradient between the West African lands and the ocean, which in turn reduces the monsoon flow penetration into Sahel. Subsequently, the rainfall increases over the Guinean coast area. According to observations and climate models, the relation between the Atlantic Niño and the rainfall in coastal Guinea is stationary over the 20<sup>th</sup> century. While this relation remains unchanged over the 21<sup>st</sup> century in climate model projections, the strength of the teleconnection is reduced in a warmer climate. The weakened ATL3 effect on the rainfall over the tropical Atlantic (in years of positive ATL3) has been attributed to the stabilization of the atmosphere column above the tropical Atlantic. Analysis of historical and high anthropogenic emission scenario (the Shared Socioeconomic Pathways 5-8.5) simulations from 31 models participating in the sixth phase of the Coupled Model Intercomparison Project suggests an additional role of the Bjerkness feedback. A weakened SST amplitude related to ATL3 positive phases reduces the anomalous westerlies, which in turn increases the upwelling cooling effect on the sea surface. Both the Guinean coast region and the equatorial Atlantic experiment the projected rainfall reduction associated with ATL3, with a higher confidence over the ocean than over the coastal lands.</p>

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