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Jia Wang, L. A. Mysak, and R. G. Ingram

Abstract

Hibler's dynamic-thermodynamic sea ice model with viscous-plastic rheology is used to simulate the seasonal cycle of sea ice motion, thickness, compactness, and growth rate in Hudson Bay under monthly climatological atmospheric forcing and a prescribed ocean surface current field. The sea ice motion over most of the domain is driven mainly by the wind stress. Wintertime sea ice velocities are only of the order of 1–5 (× 10−4 m s−1) due to the nearly solid ice cover and the closed boundary constraint of Hudson Bay. However, the velocities rise to 0.10–0.20 m s−1 during the melting and freezing seasons when there is partial ice cover. The simulated thickness distribution in mid–April, the time of heaviest ice cover, ranges from 1.3 m in James Bay to 1.7 m in the northern part of Hudson Bay, which compares favorably with observations. The area-averaged growth rate, computed from the model is 1.5–0.5 cm day−1 from December to March, is negative in May (indicative of melting) and reaches its minimum value of −4.2 cm day−1 (maximum melting rate) in July. During autumn, the main freezing season, the growth rate ranges from 1 to 2 cm day−1. In the model, sea ice remains along the south shore of Hudson Bay in summer, as observed, even though the surface air temperatures are higher there than in central and northern Hudson Bay. A sensitivity experiment shows that this is mainly due to the pile-up of ice driven southward by the northwesterly winds. The simulated results for ice cover in other seasons also compare favorably with the observed climatology and with measurements from satellites. In particular, the model gives complete sea ice cover in winter and ice-free conditions in late summer. A series of sensitivity experiments in which the model parameters and external forcing are varied is also carried out.

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Jia Wang, Lawrence A. Mysak, and R. Grant Ingram

Abstract

The summer ocean circulation in Hudson Bay is studied numerically using the Blumberg-Mellor model with a 27.5 km × 27.5 km horizontal grid and a realistic bottom topography. In the control run 1) monthly climatological forcing fields of wind stress, oceanic inflow/outflow, and salt and heat fluxes are used. In addition, results are presented for a number ot sensitivity experiments: 2) no topography (otherwise conditions are identical to the control run), 3) no wind forcing, 4) no oceanic inflow/outflow, 5) no heat and salt fluxes, 6) no temperature and salinity variations, and 7) without the nonlinear terms.

While the overall simulated circulation in Hudson Bay is cyclonic, the strong steering of the flow by the bathymetry is particularly noticeable. Mesoscale topographic gyres are simulated, and the separation of the coastal current due to topographic bumps occurs in several locations. The simulated circulation also has well-developed vorticity features and narrow, density-driven coastal jets along the western, southern, and eastern shores of Hudson Bay, which enhance the wind-driven alongshore current. From various sensitivity experiments, it is estimated that the total transport of 0.55 Sv (Sv ≡ 106 m3 s−1) is made up of a 0.23 Sv wind-driven transport, a 0.12 Sv density-driven transport, and a 0.2 Sv inflow/outflow induced transport. It is also found that the wind-driven circulation in Hudson Bay shows a recirculation, whereas the density-driven and inflow/outflow induced transports do not.

A one-dimensional version of the model is also used to simulate the thermohaline vertical structure over a seasonal cycle. In particular, the observed deepening of the mixed layer in fall is reasonably well reproduced by the model.

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Qiongqiong Cai, Dmitry Beletsky, Jia Wang, and Ruibo Lei

Abstract

The interannual and decadal variability of summer Arctic sea ice is analyzed, using the longest reconstruction (1850-2017) of Arctic sea ice extent available, and its relationship with the dominant internal variabilities of the climate system is further investigated quantitatively. The leading empirical orthogonal function (EOF) mode of summer Arctic sea ice variability captures an in-phase fluctuation over the Arctic Basin. The second mode characterizes a sea ice dipolar pattern with out-of-phase variability between the Pacific Arctic and the Atlantic Arctic. Summer sea ice variability is impacted by the major internal climate patterns: the Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO) and Dipole Anomaly (DA), with descending order of importance based on the multiple regression analyses. The internal climate variability of the five teleconnection patterns accounts for up to 46% of the total variance in sea ice mode 1 (thermodynamical effect), and up to 30% of the total variance in mode 2 (dynamical effect). Furthermore, the variability of sea ice mode 1 decreased from 46% during 1953-2017 to 28% during 1979-2017, while the variability of mode 2 increased from 11% during 1953-2017 to 30% during 1979-2017. The increasingly greater reduction of Arctic summer sea ice during the recent four decades was enhanced with the positive ice/ocean albedo feedback loop being accelerated by the Arctic amplification, contributed in part by the atmospheric thermodynamical forcing from -AO, +NAO, +DA, +AMO, and –PDO and by the dynamical transpolar sea ice advection and outflow driven by +DA- and +AMO-derived strong anomalous meridional winds. Further analysis, using multiple large ensembles of climate simulations and single-forcing ensembles, indicates that the mode 1 of summer sea ice, dominated by the multidecadal oscillation, is partially a forced response to anthropogenic warming.

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XiaoJing Jia, Hai Lin, June-Yi Lee, and Bin Wang

Abstract

Multimodel ensemble (MME) seasonal forecasts are analyzed to evaluate numerical model performance in predicting the leading forced atmospheric circulation pattern over the extratropical Northern Hemisphere (NH). Results show that the time evolution of the leading tropical Pacific sea surface temperature (SST)-coupled atmospheric pattern (MCA1), which is obtained by applying a maximum covariance analysis (MCA) between 500-hPa geopotential height (Z 500) in the extratropical NH and SST in the tropical Pacific Ocean, can be predicted with a significant skill in March–May (MAM), June–August (JJA), and December–February (DJF) one month ahead. However, most models perform poorly in capturing the time variation of MCA1 in September–November (SON) with 1 August initial condition. Two possible reasons for the models’ low skill in SON are identified. First, the models have the most pronounced errors in the mean state of SST and precipitation along the central equatorial Pacific. Because of the link between the divergent circulation forced by tropical heating and the midlatitude atmospheric circulation, errors in the mean state of tropical SST and precipitation may lead to a degradation of midlatitude forecast skill. Second, examination of the potential predictability of the atmosphere, estimated by the ratio of the total variance to the variance of the model forecasts due to internal dynamics, shows that the atmospheric potential predictability over the North Pacific–North American (NPNA) region is the lowest in SON compared to the other three seasons. The low ratio in SON is due to a low variance associated with external forcing and a high variance related to atmospheric internal processes over this area.

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Lie-Yauw Oey, Jia Wang, and M.-A. Lee

Abstract

In eastern boundary upwelling ecosystems, substantial variance of biological productivity (~50%) can often be related to physical forcing such as winds and ocean temperatures. Robust biophysical connections are less clear-cut in western boundary currents. Here the authors show that interannual variation of fish catch along the western boundary current of the North Pacific, the Kuroshio, significantly correlates (r = 0.67; p < 0.001) with the current’s off-slope (more fish) and on-slope (less fish) sideways shifts in the southern East China Sea. Remotely, transport fluctuations and fish catch are related to the oscillation of a wind stress-curl dipole in the tropical–subtropical gyre of the western North Pacific. Locally, the current’s sideways fluctuations are driven by transport fluctuations through a feedback process between along-isobath pressure gradients and vertical motions: upwelling (downwelling) during the off-slope (on slope) shift, which in turn significantly enhances (depresses) the chlorophyll-a (Chl-a) concentration in winter and early spring. The authors hypothesize that changes in the phytoplankton biomass as indicated by the Chl-a lead to changes in copepodites, the main food source of the fish larvae, and hence also to the observed variation in fish catch.

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Mengmeng Lu, Song Yang, Junbin Wang, Yuting Wu, and Xiaolong Jia

Abstract

The thermal effect of the entire Tibetan Plateau (TP) tends to strengthen the South Asian summer monsoon (SASM); however, how does this monsoon component respond to the thermal conditions of different TP domains? How do the thermal conditions of the entire TP influence other monsoons, including the East Asian summer monsoon (EASM) and the Southeast Asian summer monsoon (SEASM)? These questions are addressed by conducting an experiment with the CESM, which is forced by reducing the surface albedo over the plateau by half, from a TP-averaged 0.20 to 0.10, from May to September, and similar experiments for different TP domains. Both observational and model results show that the entire TP heating intensifies the large-scale Asian monsoon, the SASM, and the EASM but surprisingly weakens the SEASM. It is also surprising that the TP heating exerts a stronger effect on the EASM than on the SASM. The southern TP (south of 35°N) does not show the strongest impact on the SASM in comparison with other TP domains, and it exerts the weakest impact on the EASM, which is most strongly influenced by the thermal effect of the eastern (east of 90°E) and northern TP. The western TP weakens the SEASM (as do the other domains), and it strengthens other monsoon components. The thermal conditions of the southern and eastern TP are accompanied by signals of tropical atmospheric response at relatively broader spatial scales, whereas those of the northern TP more apparently lead to a significant wave train extending eastward from the TP to western Eurasia over the higher latitudes.

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Zhaoyun Chen, Yuwu Jiang, Jia Wang, and Wenping Gong

Abstract

Satellite images show that the Pearl River plume is entrained into the upwelling front in the northeastern South China Sea. To understand the processes and extend to other coastal zones, an idealized numerical model is used to investigate the upwelling dynamics in response to the arrival of the river plume. Upon forcing by an upwelling-favorable wind, the model reproduces the upwelling frontal jet with a stratified water column, which takes the river plume far away from the mouth of the estuary. The river plume introduces additional upwelling and downwelling at its inshore and offshore sides (defined as plume-related secondary upwelling circulation), respectively. For the initially unstratified water column, the plume-related secondary upwelling circulation is stronger and extends to deeper water than for the stratified condition. The surface boundary layer thins and the offshore current intensifies in the river plume. The variations in wind-driven current over the deep-water shelf in different stratified conditions are modulated by the vertical profiles of the eddy viscosity, which are shown by a one-dimensional numerical model. Offshore transport is reinforced when the head of the river plume arrives. Thereafter, it is changed by the cross-shore baroclinic geostrophic component of velocity, due to alongshore density variation by the river plume. The horizontal gradient of stress on the two sides of the river plume is responsible for the plume-related secondary upwelling circulation owing to different stress decay scales inside and outside the river plume.

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Jia Sun, Hailun He, Xiaomin Hu, Dingqi Wang, Cen Gao, and Jinbao Song

Abstract

We used a mesoscale atmospheric model to simulate Typhoon Hagupit (2008) in the South China Sea (SCS). First, we chose optimized parameterization schemes based on a series of sensitivity tests. The results suggested that a combination of the Kain–Fritsch cumulus scheme and the Goddard microphysics scheme was the best choice for reproducing both the track and intensity of Typhoon Hagupit. Next, the simulated rainfall was compared with microwave remote sensing products. This comparison validated the model results for both the magnitude of rainfall and the location of heavy rain relative to the typhoon’s center. Furthermore, the potential vorticity and vertical wind speed displayed the asymmetric horizontal and tilted vertical structures of Typhoon Hagupit. Finally, we compared the simulation of air–sea turbulent fluxes with estimations from an in situ buoy. The time series of momentum fluxes were roughly consistent, while the model still overestimated heat fluxes, especially right before the typhoon’s arrival at the buoy.

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Joshua-Xiouhua Fu, Wanqiu Wang, Yuejian Zhu, Hong-Li Ren, Xiaolong Jia, and Toshiaki Shinoda

Abstract

Six sets of hindcasts conducted with the NCEP GFS have been used to study the SST-feedback processes and assess the relative contributions of atmospheric internal dynamics and SST feedback on the October and November MJO events observed during the DYNAMO IOP (Oct- and Nov-MJO). The hindcasts are carried out with three variants of the Arakawa–Shubert cumulus scheme under TMI and climatological SST conditions. The positive intraseasonal SST anomaly along with its convergent Laplacian produces systematic surface disturbances, which include enhanced surface convergence, evaporation, and equivalent potential temperature no matter which cumulus scheme is used. Whether these surface disturbances can grow into a robust response of MJO convection depends on the characteristics of the cumulus schemes used. If the cumulus scheme is able to amplify the SST-initiated surface disturbances through a strong upward–downward feedback, the model is able to produce a robust MJO convection response to the underlying SST anomaly; otherwise, the model will not produce any significant SST feedback. A new method has been developed to quantify the “potential” and “practical” contributions of the atmospheric internal dynamics and SST feedback on the MJOs. The present results suggest that, potentially, the SST feedback could have larger contributions than the atmospheric internal dynamics. Practically, the contributions to the Oct- and Nov-MJO events are, respectively, dominated by atmospheric internal dynamics and SST feedback. Averaged over the entire period, the contributions from the atmospheric internal dynamics and SST feedback are about half and half.

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Meng-Pai Hung, Jia-Lin Lin, Wanqiu Wang, Daehyun Kim, Toshiaki Shinoda, and Scott J. Weaver

Abstract

This study evaluates the simulation of the Madden–Julian oscillation (MJO) and convectively coupled equatorial waves (CCEWs) in 20 models from the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and compares the results with the simulation of CMIP phase 3 (CMIP3) models in the IPCC Fourth Assessment Report (AR4). The results show that the CMIP5 models exhibit an overall improvement over the CMIP3 models in the simulation of tropical intraseasonal variability, especially the MJO and several CCEWs. The CMIP5 models generally produce larger total intraseasonal (2–128 day) variance of precipitation than the CMIP3 models, as well as larger variances of Kelvin, equatorial Rossby (ER), and eastward inertio-gravity (EIG) waves. Nearly all models have signals of the CCEWs, with Kelvin and mixed Rossby–gravity (MRG) and EIG waves being especially prominent. The phase speeds, as scaled to equivalent depths, are close to the observed value in 10 of the 20 models, suggesting that these models produce sufficient reduction in their effective static stability by diabatic heating. The CMIP5 models generally produce larger MJO variance than the CMIP3 models, as well as a more realistic ratio between the variance of the eastward MJO and that of its westward counterpart. About one-third of the CMIP5 models generate the spectral peak of MJO precipitation between 30 and 70 days; however, the model MJO period tends to be longer than observations as part of an overreddened spectrum, which in turn is associated with too strong persistence of equatorial precipitation. Only one of the 20 models is able to simulate a realistic eastward propagation of the MJO.

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