Published papers

[1] Capability for short-range forecasting of the Kuroshio path variabilities south of Japan is studied by assimilating the absolute sea surface dynamic height data, which are derived from in situ hydrography and TOPEX/Poseidon (T/P) altimetry, into a high-resolution 1-1/2 layer primitive equation model every 15 days for 5 years from 1993 to 1997. The initialization scheme used is the variational method, which contains the nonlinear dynamics of the model as a weak constraint and is suitable for initialization in the western boundary current regions where initialization by simple optimal interpolation is inappropriate. The time series of the analysis field well represents the Kuroshio path variations during the study period. For example, the root-mean-square (RMS) differences from the observations falls within 0.3degrees for the location in latitude of the current axis off Enshu-nada and 11.4 cm for the sea level at Hachijo-jima Island while their observed RMS variabilities are 0.5degrees and 30.7 cm, respectively. By using the resulting fields as the initial conditions, 116 cases of 90-day forecast experiments for the Kuroshio path variations are then performed to assess the statistical properties of our assimilation system. Though significant bias is found in the forecast field southeast of Kyushu, the accuracy of our forecasted field south of Japan is much higher than that of persistence experiments, and the typical evolution of the Kuroshio into a large-amplitude path off Enshu-nada is successfully reproduced after the initialization. In particular, the eastward progression speed and the horizontal scale of the meander are quite similar to those observed. These results and the comparison with the RMS variability of the analysis field enable us to infer that roughly 60-day forecasts of the Kuroshio path variabilities south of Japan are possible. This indicates that our assimilation system is suitable for the operational short-range forecasting of the upper Kuroshio.

There are two problems with the shortwave penetration scheme used in Modular Ocean Model version 3 (MOM3): (i) the spatiotemporal variability of the thickness of the first layer resulting from the free surface is not considered, and (ii) shortwave irradiance penetrates the ocean bottom. Because both of these problems can cause artificial heat sources or sinks, their effects are evaluated in the present study using a MOM3-based ocean general circulation model. The first problem creates an artificial heat sink (source) in the regions of positive (negative) sea surface height (SSH) with a maximum amplitude greater than 10 W m-2 and decreases (increases) sea surface temperature (SST) by up to 0.3°C on the basis of annual mean. This change in SST leads to a reduction in global mean evaporation and, as a result, an increase in SSH, which enhances the artificial heat sink. After several years of integration, this positive feedback amplifies the effects of the first problem in cases of stand-alone ocean simulations forced by freshwater flux. The estimated artificial heat sink induced by the second problem reaches 50 W m-2, and the decrease in SST exceeds 1.0°C. However, the effects of this problem are restricted within shallow coastal areas and do not involve positive feedback.

The observation operators in the local ensemble transform Kalman filter (LETKF) were improved to enable use of observations in the vicinity of the poles in the data assimilation system composed of the atmospheric general circulation model for the Earth Simulator (AFES) and the LETKF. The improved observation operators allow to assimilate the observations located south (north) of southernmost (northernmost) Gaussian grid latitudes. An algorithm for searching the nearest observations from an analyzed grid for error covariance localization was also modified to efficiently assimilate observations near the poles. The new algorithms were incorporated into the LETKF, and the impacts of routine radiosonde observations at the South Pole during the periods of July 2012 and January 2013 were assessed. The radiosonde observations suppressed an artificial expansion of the analysis ensemble spread which occasionally caused numerical instability in the upper troposphere and the lower stratosphere over the Antarctic regions. The analysis was also improved in the Antarctic regions.

This chapter describes the updated version of Atmospheric General Circulation Model for the Earth Simulator (AFES 2). Modifications are intended (1) to increase the accuracy and efficiency of the Legendre transform at high resolutions and (2) to improve the physical performance. In particular, the Emanuel scheme replaces a simplified version of the Arakawa-Schubert scheme for the parametrization of cumulus convection. The Emanuel scheme parametrizes O(100m) drafts within subgrid-scale cumuli and does not have explicit dependency upon the grid size. Therefore the cloud model of the Emanuel scheme allows us to use it at high resolutions of O(10 km) where the validity of the ensemble cloud model of the Arakawa-Schubert scheme is questionable. Moreover, 10-year test runs indicate that the use of the Emanuel scheme improve the physical performance at a moderate resolution as well. Anomalies of the geopotential height and zonal winds in the middle to upper troposphere are reduced, although the improvements in terms of the distributions of precipitation and sea-level pressure are not significant. Improvements are attributable to a better vertical structure of temperature in the tropics due to more realistic estimation of mixing of the momentum, temperature, and moisture by the Emanuel scheme.

A variational data assimilation system is presented for the initialization of an ocean surface circulation forecast system. The authors' variational data assimilation system is designed to satisfy both statistical and dynamical constraints. As is usual, the statistical part of the assimilation scheme corresponds to the optimal interpolation scheme while the dynamical part works as a weak constraint for the model equations except for the time differential terms. Thus this variational data assimilation scheme can be regarded as an extended optimal interpolation capable of obtaining the analysis field that satisfies the model dynamics. Comparison with the results of assimilating altimetric data into a 1.5-layer primitive equation model by the classical optimal interpolation clearly shows the advantage of this assimilation method. For example, the analysis field is significantly improved, in particular, in the western boundary current regions and their extensions, where some assumptions inherent in the optimal interpolation, such as the Gaussian function for the error covariance matrix and the geostrophic balance for the error fields, break down because of the nonlinear nature of the currents. To show the effectiveness of this variational assimilation system for the initialization process, several numerical forecasting experiments are carried out using the analysis fields from the variational assimilation scheme and from the optimal interpolation as initial conditions. The case initialized by the optimal interpolation scheme exhibits inertia-gravity waves generated by the geostrophic initialization leading to contamination of the forecasting result. In contrast, the variational assimilation case can effectively reduce the generation of the gravity waves, thus providing the dynamically consistent analysis field. It is also shown that the accuracy of the short-range forecast with this variational data assimilation is sensitive to the initial guess of the gradient descent method. The computational cost of this assimilation system is lower than that using other sophisticated schemes such as the adjoint method and the Kalman filter, suggesting that this system is suitable for the operational forecasting of western boundary currents.

Using numerical simulations forced by a uniform realistic wind time series, the authors show that the presence of a mesoscale eddy field at midlatitudes accelerates the vertical propagation of the wind-forced near-inertial waves (NIW) and produces the emergence of a maximum of vertical velocity into the deep ocean (around 2500 m) characterized by a mean amplitude of 25 m day(-1), a dominant 2f frequency, and scales as small as O(30 km). These results differ from previous studies that reported a smaller depth and larger scales. The authors show that the larger depth observed in the present study (2500 m instead of 1700 m) is due to the wind forcing duration that allows the first five baroclinic modes to disperse and to impact the deep NIW maximum (instead of the first two modes as reported before). The smaller scales (30 km instead of 90 km) are explained by a resonance mechanism (described in previous studies) that affects the high NIW baroclinic modes, but only when small-scale relative vorticity structures (related to the mesoscale eddy field) have an amplitude that is large enough. These results, which point out the importance of the wind forcing duration and the resolution, indicate that the emergence of a deep NIW maximum with a 2f frequency reported before is a robust feature that is enhanced with more realistic conditions. Such 2f frequency in the deep interior raises the question of the mechanisms, still unresolved, that may ultimately transfer this superinertial energy into mixing at these depths.

Ensemble-based atmospheric data assimilation (DA) systems are sometimes afflicted with an underestimation of the ensemble spread near the surface caused by the use of identical boundary conditions for all ensemble members and the lack of atmosphere-ocean interaction. To overcome these problems, a new DA system has been developed by replacing an atmospheric GCM with a coupled atmosphere-ocean GCM, in which atmospheric observational data are assimilated every 6 h to update the atmospheric variables, whereas the oceanic variables are subject to no direct DA. Although SST suffers from the common biases among many coupled GCMs, two months of a retrospective analysis-forecast cycle reveals that the ensemble spreads of air temperature and specific humidity in the surface boundary layer are slightly increased and the forecast skill in the midtroposphere is rather improved by using the coupled DA system in comparison with the atmospheric DA system. In addition, surface atmospheric variables over the tropical Pacific have the basinwide horizontal correlation in ensemble space in the coupled DA system but not in the atmospheric DA system. This suggests the potential benefit of using a coupled GCM rather than an atmospheric GCM even for atmospheric reanalysis with an ensemble-based DA system.

Detailed mechanisms for frontogenesis/frontolysis of the Agulhas Return Current (ARC) Front, defined as the maximum of the meridional sea surface temperature (SST) gradient at each longitude within the ARC region (40A degrees-50A degrees E, 55A degrees-35A degrees S), are investigated using observational datasets. Due to larger (smaller) latent heat release to the atmosphere on the northern (southern) side of the front, the meridional gradient of surface net heat flux (NHF) is found throughout the year. In austral summer, surface warming is weaker (stronger) on the northern (southern) side, and thus the NHF tends to relax the SST front. The weaker (stronger) surface warming, at the same time, leads to the deeper (shallower) mixed layer on the northern (southern) side. This enhances the frontolysis, because deeper (shallower) mixed layer is less (more) sensitive to surface warming. In austral winter, stronger (weaker) surface cooling on the northern (southern) side contributes to the frontolysis. However, deeper (shallower) mixed layer is induced by stronger (weaker) surface cooling on the northern (southern) side and suppresses the frontolysis, because the deeper (shallower) mixed layer is less (more) sensitive to surface cooling. Therefore, the frontolysis by the NHF becomes stronger (weaker) through the mixed layer processes in austral summer (winter). The cause of the meridional gradient of mixed layer depth is estimated using diagnostic entrainment velocity and the Monin-Obukhov depth. Furthermore, the above mechanisms obtained from the observation are confirmed using outputs from a high-resolution coupled general circulation model. Causes of model biases are also discussed.

We have been developing a global, high-resolution, coupled atmosphere-ocean general circulation model, named CFES, which was designed to achieve efficient computational performance on the Earth Simulator. A brief description of CFES and some preliminary results obtained from 66-month integration are presented. Although some deficiencies are apparent in the results, realistically simulaled small-scale structures such as extratropical cyclones and sea surface temperature fronts in the mid-latitudes, and seasonal variation of tropical sea surface temperature and polar sea-ice extent encourage us to study mechanism and predictability of high-impact phenomena and their relation to the global-scale circulations using CFES.

[1] A 4-dimensional variational data assimilation system has been used to better define the mean seasonal state of the North Pacific. The synthesis of available observational records and a sophisticated general circulation model produces a dynamically consistent time-varying dataset which exhibits realistic features of the global ocean circulation and requires no artificial sources or sinks for the temperature and salinity fields. The dataset enables us to clarify the water mass formation and movement processes. A sensitivity experiment using our system reveals that the origin of the North Pacific Intermediate Water can be traced back to the Okhotsk and Bering Seas in the subarctic region and to the subtropical Kuroshio region further south, consistent with recent observational findings. This result illustrates that the ocean state derived from our data assimilation has greater information and forecast potential than that obtained from earlier methods.

Local air-sea interactions over the high sea surface temperature (SST) band along the Hawaiian Lee Countercurrent (HLCC) are examined with a focus on dynamical feedback of SST-induced wind stress to the ocean using the atmosphere-ocean coupled general circulation model (CGCM). A pair of ensemble CGCM simulations are compared to extract the air-sea interactions associated with HLCC: the control simulations and other simulations, the latter purposely eliminating influences of the high SST band on the sea surface flux computations in the CGCM. The comparison reveals that oceanic response to surface wind convergence and positive wind stress curl induced by the high SST band increases (decreases) the HLCC speed in the southern (northern) flank of the HLCC. The HLCC speed changes are driven by the Ekman suction associated with positive wind stress curl over the warm HLCC via the thermal wind balance. The HLCC speed increase is more significant than its decrease. This dynamical feedback is likely to be important to sustain the extension of the HLCC far to the west. The heat budget analysis confirms that advection of warm water from the west associated with this significant current speed increase plays a role in the southward shift of theHLCCaxis. The dynamical feedback with the HLCC speed increase can potentially amplify the seasonal and interannual variations of HLCC. © 2013 American Meteorological Society.

The Gulf Stream transports large amounts of heat from the tropics to middle and high latitudes, and thereby affects weather phenomena such as cyclogenesis(1,2) and low cloud formation(3). But its climatic influence, on monthly and longer timescales, remains poorly understood. In particular, it is unclear how the warm current affects the free atmosphere above the marine atmospheric boundary layer. Here we consider the Gulf Stream's influence on the troposphere, using a combination of operational weather analyses, satellite observations and an atmospheric general circulation model(4). Our results reveal that the Gulf Stream affects the entire troposphere. In the marine boundary layer, atmospheric pressure adjustments to sharp sea surface temperature gradients lead to surface wind convergence, which anchors a narrow band of precipitation along the Gulf Stream. In this rain band, upward motion and cloud formation extend into the upper troposphere, as corroborated by the frequent occurrence of very low cloud- top temperatures. These mechanisms provide a pathway by which the Gulf Stream can affect the atmosphere locally, and possibly also in remote regions by forcing planetary waves(5,6). The identification of this pathway may have implications for our understanding of the processes involved in climate change, because the Gulf Stream is the upper limb of the Atlantic meridional overturning circulation, which has varied in strength in the past(7) and is predicted to weaken in response to human- induced global warming in the future(8).

Recent activities on ensemble data assimilation and its application to observing-system research at the Japan Agency for Marine-Earth Science and Technology are reviewed. A revised version of an ensemble-based data assimilation system for global atmospheric data has been developed on the second-generation Earth Simulator. This system assimilates conventional atmospheric observations and satellite-based wind data into an atmospheric general circulation model using the local ensemble transform Kalman filter (LETKF), a deterministic ensemble Kalman filter algorithm that is extremely efficient with parallel computer architecture. The updated system incorporates improvements to the previous system in the forecast model, data assimilation algorithm and input data. Using the LETKF system, observations taken during field campaigns are evaluated by data assimilation experiments involving adding or removing observations. The results of these observing-system experiments successfully demonstrate the value of the observations and are highly useful for exploring the predictability of atmospheric disturbances.