scholarly journals Boreal summer intraseasonal oscillation in a superparameterized general circulation model: effects of air–sea coupling and ocean mean state

2020 ◽  
Vol 13 (11) ◽  
pp. 5191-5209
Author(s):  
Yingxia Gao ◽  
Nicholas P. Klingaman ◽  
Charlotte A. DeMott ◽  
Pang-Chi Hsu

Abstract. The effect of air–sea coupling on simulated boreal summer intraseasonal oscillation (BSISO) is examined using atmosphere–ocean-mixed-layer coupled (SPCAM3-KPP, referred to as SPK throughout) and uncoupled configurations of the superparameterized (SP) Community Atmospheric Model, version 3 (SPCAM3, referred to as SPA throughout). The coupled configuration is constrained to either observed ocean mean state or the mean state from the SP coupled configuration with a dynamic ocean (SPCCSM3), to understand the effect of mean-state biases on the BSISO. All configurations overestimate summer mean subtropical rainfall and its intraseasonal variance. All configurations simulate realistic BSISO northward propagation over the Indian Ocean and western Pacific, in common with other SP configurations. Prescribing the 31 d smoothed sea surface temperature (SST) from the SPK simulation in SPA worsens the overestimated BSISO variance. In both coupled models, the phase relationship between intraseasonal rainfall and SST is well captured. This suggests that air–sea coupling improves the amplitude of simulated BSISO and contributes to the propagation of convection. Constraining SPK to the SPCCSM3 mean state also reduces the overestimated BSISO variability but weakens BSISO propagation. Using the SPCCSM3 mean state also introduces a 1-month delay to the BSISO seasonal cycle compared to SPK with the observed ocean mean state, which matches well with observation. Based on a Taylor diagram, both air–sea coupling and SPCCSM3 mean-state SST biases generally lead to higher simulated BSISO fidelity, largely due to their abilities to suppress the overestimated subtropical BSISO variance.

2020 ◽  
Author(s):  
Yingxia Gao ◽  
Nicholas P. Klingaman ◽  
Charlotte A. DeMott ◽  
Pang-Chi Hsu

Abstract. The effect of air-sea coupling on the simulated boreal summer intraseasonal oscillation (BSISO) is examined using atmosphere—ocean-mixed-layer coupled (SPCAM3-KPP) and uncoupled configurations of the Super-Parameterized (SP) Community Atmospheric Model, version 3 (SPCAM3). The coupled configuration is constrained to either the observed ocean mean state or the mean state from the SP coupled configuration with a dynamic ocean (SPCCSM3), to understand the effect of mean state biases on the BSISO in the latter. All configurations overestimate summer mean subtropical rainfall and its intraseasonal variance. All configurations simulate realistic BSISO northward propagation over the Indian Ocean and western Pacific, in common with other SP configurations. Constraining SPCAM3-KPP to the SPCCSM3 mean state reduces the overestimated BSISO variability, but also weakens BSISO propagation. Using the SPCCSM3 mean state also introduces a one-month delay to the BSISO seasonal cycle compared to SPCAM3-KPP with the observed ocean mean state, which matches well with the reanalysis. The phase relationship between intraseasonal rainfall and sea surface temperature (SST) is captured by all coupled models, but with a shorter delay between suppressed convection and warm SST relative to the reanalysis. Prescribing the 31-day smoothed SSTs from the SPCAM3-KPP simulations in SPCAM3 worsens the overestimated BSISO variance. This suggests that air-sea coupling improves the amplitude of the simulated BSISO. Based on a Taylor diagram, SPCCSM3 mean state SST biases and air-sea coupling both lead to higher simulated BSISO fidelity, largely due to their ability to suppress the overestimated subtropical BSISO variance.


2005 ◽  
Vol 18 (18) ◽  
pp. 3777-3795 ◽  
Author(s):  
Xian-An Jiang ◽  
Tim Li

Abstract The characteristic features of the boreal summer intraseasonal oscillation (BSISO) during its reinitiation period are studied using NCEP–NCAR reanalysis. Based on these observations and with the aid of an anomalous atmospheric general circulation model (AGCM), a possible mechanism responsible for the BSISO reinitiation is elucidated. The western equatorial Indian Ocean along the eastern African coast tends to be a key region for the phase transition of the BSISO from an enhanced to suppressed convective phase, or vise versa. The major precursory feature associated with reinitiation of suppressed convection is found in the divergence and reduced specific humidity in the boundary layer. Numerical experiments indicate that the low-level divergence is caused by the cold horizontal temperature advection and associated adiabatic warming (descending motion) in situ. The summer mean state is found to be important for the cold horizontal temperature advection through the modulation of a Gill-type response to an intraseasonal oscillation (ISO) heating in the eastern equatorial Indian Ocean. The results in this study suggest a self-sustained paradigm in the Indian Ocean for the BSISO; that is, the BSISO could be a basinwide phenomenon instead of a global circumstance system as hypothesized for the boreal winter ISO (i.e., the Madden–Julian oscillation).


2015 ◽  
Vol 28 (3) ◽  
pp. 1057-1073 ◽  
Author(s):  
Wenting Hu ◽  
Anmin Duan ◽  
Guoxiong Wu

Abstract The off-equatorial boreal summer intraseasonal oscillation (ISO) is closely linked to the onset, active, and break phases of the tropical Asian monsoon, but the accurate simulation of the eastward-propagating low-frequency ISO by current models remains a challenge. In this study, an atmospheric general circulation model (AGCM)–ocean mixed layer coupled model with high (10 min) coupling frequency (DC_10m) shows improved skill in simulating the ISO signal in terms of period, intensity, and propagation direction, compared with the coupled runs with low (1 and 12 h) coupling frequency and a stand-alone AGCM driven by the daily sea surface temperature (SST) fields. In particular, only the DC_10m is able to recreate the observed lead–lag phase relationship between SST (SST tendency) and precipitation at intraseasonal time scales, indicating that the ISO signal is closely linked to the subdaily air–sea interaction. During the ISO life cycle, air–sea interaction reduces the SST underlying the convection via wind–evaporation and cloud–radiation feedbacks, as well as wind-induced oceanic mixing, which in turn restrains convection. However, to the east of the convection, the heat-induced atmospheric Gill-type response leads to downward motion and a reduced surface westerly background flow because of the easterly anomalies. The resultant decreased oceanic mixing, together with the increased shortwave flux, tends to warm the SST and subsequently trigger convection. Therefore, the eastward-propagating ISO may result from an asymmetric east–west change in SST induced mainly by multiscale air–sea interactions.


2015 ◽  
Vol 143 (3) ◽  
pp. 778-793 ◽  
Author(s):  
Andrea Alessandri ◽  
Andrea Borrelli ◽  
Annalisa Cherchi ◽  
Stefano Materia ◽  
Antonio Navarra ◽  
...  

Abstract Ensembles of retrospective 2-month dynamical forecasts initiated on 1 May are used to predict the onset of the Indian summer monsoon (ISM) for the period 1989–2005. The subseasonal predictions (SSPs) are based on a coupled general circulation model and recently they have been upgraded by the realistic initialization of the atmosphere with initial conditions taken from reanalysis. Two objective large-scale methods based on dynamical-circulation and hydrological indices are applied to detect the ISM onset. The SSPs show some skill in forecasting earlier-than-normal ISM onsets, while they have difficulty in predicting late onsets. It is shown that significant contribution to the skill in forecasting early ISM onsets comes from the newly developed initialization of the atmosphere from reanalysis. On one hand, atmospheric initialization produces a better representation of the atmospheric mean state in the initial conditions, leading to a systematically improved monsoon onset sequence. On the other hand, the initialization of the atmosphere allows some skill in forecasting the northward-propagating intraseasonal wind and precipitation anomalies over the tropical Indian Ocean. The northward-propagating intraseasonal modes trigger the monsoon in some early-onset years. The realistic phase initialization of these modes improves the forecasts of the associated earlier-than-normal monsoon onsets. The prediction of late onsets is not noticeably improved by the initialization of the atmosphere. It is suggested that late onsets of the monsoon are too far away from the start date of the forecasts to conserve enough memory of the intraseasonal oscillation (ISO) anomalies and of the improved representation of the mean state in the initial conditions.


2010 ◽  
Vol 23 (10) ◽  
pp. 2801-2816 ◽  
Author(s):  
Suhee Park ◽  
Song-You Hong ◽  
Young-Hwa Byun

Abstract In this paper, the intraseasonal oscillation (ISO) and its possible link to dynamical seasonal predictability within a general circulation model framework is investigated. Two experiments with different convection scheme algorithms, namely, the simplified Arakawa–Schubert (SAS) and the relaxed Arakawa–Schubert (RAS) convection algorithms, were designed to compare seasonal simulations from 1979 to 2002 on a seasonal model intercomparison project (SMIP)-type simulation test bed. Furthermore, the wave characteristics (wave intensity, period, and propagation) of the simulated ISO signal provided by the model with two different convection schemes for extended boreal summers from 1997 to 2004 were compared to the observational ISO signal. Precipitation in the boreal summer was fairly well simulated by the model irrespective of the convection scheme used, but the RAS run outperformed the SAS run with respect to tabulated skill scores. Decomposition of the interannual variability of boreal summer precipitation based on observations and model results demonstrates that the seasonal predictability of precipitation is dominated by the intraseasonal component over the warm pool area and the SST-forced signal over the equatorial Pacific Ocean, implying that the seasonal mean anomalies are more predictable under active ISO conditions as well as strong ENSO conditions. Comparison of the ISO simulations with the observations revealed that the main features, such as the intensity of precipitation variance in the intraseasonal time scale and the evolution of propagating ISOs, were reproduced fairly well by the model; however, the wave characteristics associated with the ISO signals were better captured by the experiment with the RAS scheme than the SAS scheme. This study further suggests that accurate simulation of the ISO can improve the seasonal predictability of dynamical seasonal prediction systems.


2004 ◽  
Vol 17 (21) ◽  
pp. 4109-4134 ◽  
Author(s):  
Y. Zheng ◽  
D. E. Waliser ◽  
W. F. Stern ◽  
C. Jones

Abstract This study compares the tropical intraseasonal oscillation (TISO) variability in the Geophysical Fluid Dynamics Laboratory (GFDL) coupled general circulation model (CGCM) and the stand-alone atmospheric general circulation model (AGCM). For the AGCM simulation, the sea surface temperatures (SSTs) were specified using those from the CGCM simulation. This was done so that any differences in the TISO that emerged from the two simulations could be attributed to the coupling process and not to a difference in the mean background state. The comparison focused on analysis of the rainfall, 200-mb velocity potential, and 850-mb zonal wind data from the two simulations, for both summer and winter periods, and included comparisons to analogous diagnostics using NCEP–NCAR reanalysis and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) rainfall data. The results of the analysis showed three principal differences in the TISO variability between the coupled and uncoupled simulations. The first was that the CGCM showed an improvement in the spatial variability associated with the TISO mode, particularly for boreal summer. Specifically, the AGCM exhibited almost no TISO variability in the Indian Ocean during boreal summer—a common shortcoming among AGCMs. The CGCM, on the other hand, did show a considerable enhancement in TISO variability in this region for this season. The second was that the wavenumber–frequency spectra of the AGCM exhibited an unrealistic peak in variability at low wavenumbers (1–3, depending on the variable) and about 3 cycles yr−1 (cpy). This unrealistic peak of variability was absent in the CGCM, which otherwise tended to show good agreement with the observations. The third difference was that the AGCM showed a less realistic phase lag between the TISO-related convection and SST anomalies. In particular, the CGCM exhibited a near-quadrature relation between precipitation and SST anomalies, which is consistent with observations, while the phase lag was reduced in the AGCM by about 1.5 pentads (∼1 week). The implications of the above results, including those for the notions of “perfect SST” and “two tier” experiments, are discussed, as are the caveats associated with the study's modeling framework and analysis.


2011 ◽  
Vol 139 (1) ◽  
pp. 79-95 ◽  
Author(s):  
Marcus Thatcher ◽  
John L. McGregor

Abstract In this paper the authors dynamically downscale daily-averaged general circulation model (GCM) datasets over Australia using the Conformal Cubic Atmospheric Model (CCAM). The technique can take advantage of the wider range of Coupled Model Intercomparison Project phase 3 (CMIP3) daily-averaged GCM datasets than is available using 3-hourly datasets. The daily-averaged host GCM atmospheric data are fitted to a time interpolation formula and then differentiated in time to produce a first-order estimate of the atmosphere at 0000 UTC on each simulation day. The processed GCM data are forced into CCAM using a scale-selective filter with an 18° radius. Since this procedure is unable to account for the diurnal cycle, the forcing data are only applied to winds and air temperatures once per day between 800 and 100 hPa. Lateral boundary conditions are not required since CCAM employs a variable-resolution global grid. The technique is evaluated by downscaling daily-averaged 2.5° NCEP reanalyses over Australia at 60-km resolution from 1971 to 2000 and comparing the results to downscaling the 6-hourly reanalyses and to simulating with sea surface temperature (SST)-only forcing. The results show that the daily-averaged downscaling technique can simulate average seasonal maximum and minimum screen temperatures and rainfall similar to those obtained downscaling 6-hourly reanalyses. Some implications for regional climate projections are considered by downscaling four daily-averaged GCM datasets from the twentieth-century climate in coupled models (20C3M) experiment over Australia.


2007 ◽  
Vol 20 (2) ◽  
pp. 255-278 ◽  
Author(s):  
Andrea Alessandri ◽  
Silvio Gualdi ◽  
Jan Polcher ◽  
Antonio Navarra

Abstract A land surface model (LSM) has been included in the ECMWF Hamburg version 4 (ECHAM4) atmospheric general circulation model (AGCM). The LSM is an early version of the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and it replaces the simple land surface scheme previously included in ECHAM4. The purpose of this paper is to document how a more exhaustive consideration of the land surface–vegetation processes affects the simulated boreal summer surface climate. To investigate the impacts on the simulated climate, different sets of Atmospheric Model Intercomparison Project (AMIP)-type simulations have been performed with ECHAM4 alone and with the AGCM coupled with ORCHIDEE. Furthermore, to assess the effects of the increase in horizontal resolution the coupling of ECHAM4 with the LSM has been implemented at different horizontal resolutions. The analysis reveals that the LSM has large effects on the simulated boreal summer surface climate of the atmospheric model. Considerable impacts are found in the surface energy balance due to changes in the surface latent heat fluxes over tropical and midlatitude areas covered with vegetation. Rainfall and atmospheric circulation are substantially affected by these changes. In particular, increased precipitation is found over evergreen and summergreen vegetated areas. Because of the socioeconomical relevance, particular attention has been devoted to the Indian summer monsoon (ISM) region. The results of this study indicate that precipitation over the Indian subcontinent is better simulated with the coupled ECHAM4–ORCHIDEE model compared to the atmospheric model alone.


2011 ◽  
Vol 24 (21) ◽  
pp. 5506-5520 ◽  
Author(s):  
Daehyun Kim ◽  
Adam H. Sobel ◽  
Eric D. Maloney ◽  
Dargan M. W. Frierson ◽  
In-Sik Kang

Abstract Systematic relationships between aspects of intraseasonal variability (ISV) and mean state bias are shown in a number of atmospheric general circulation model (AGCM) simulations. When AGCMs are categorized as either strong ISV or weak ISV models, it is shown that seasonal mean precipitation patterns are similar among models in the same group but are significantly different from those of the other group. Strong ISV models simulate excessive rainfall over the South Asian summer monsoon and the northwestern Pacific monsoon regions during boreal summer. Larger ISV amplitude also corresponds closely to a larger ratio of eastward-to-westward-propagating variance, but no model matches the observations in both quantities simultaneously; a realistic eastward-to-westward ratio is simulated only when variance exceeds that observed. Three sets of paired simulations, in which only one parameter in the convection scheme is changed to enhance the moisture sensitivity of convection, are used to explore the common differences between the two groups in greater detail. In strong ISV models, the mean and the standard deviation of surface latent heat flux is greater, convective rain fraction is smaller, and tropical tropospheric temperatures are lower compared to weak ISV models. The instantaneous joint relationships between daily gridpoint relative humidity and precipitation differ in some respects when strong and weak ISV models are compared, but these differences are not systematic enough to explain the differences in ISV amplitude. Conversely, there are systematic differences in the frequency with which specific values of humidity and precipitation occur. In strong ISV models, columns with a higher saturation fraction and rain rate occur more frequently and make a greater contribution to total precipitation.


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