Abstract

An ensemble Kalman filter (EnKF) that uses a regional mesoscale atmosphere–ocean coupled model was preliminarily examined to provide realistic sea surface temperature (SST) estimates and to represent the uncertainties of SST in ensemble data assimilation strategies. The system was evaluated through data assimilation cycle experiments over a one-month period from July to August 2014, during which time a tropical cyclone (TC) as well as severe rainfall events occurred. The results showed that the data assimilation cycle with the coupled model reproduced SST distributions realistically even without assimilating SST and sea surface salinity observations, and atmospheric variables provided to ocean models can, therefore, control oceanic variables physically to some extent. The forecast error covariance calculated in the EnKF with the coupled model showed dependency on oceanic vertical mixing for near-surface atmospheric variables due to the difference of variability between the atmosphere and the ocean as well as the influence of SST variations on the atmospheric boundary layer. The EnKF with the coupled model reproduced the intensity change of Typhoon Halong (2014) during the mature phase more realistically than with an uncoupled atmosphere model, although there remained a degradation of the SST estimate, particularly around the Kuroshio region. This suggests that an atmosphere–ocean coupled data assimilation system should be developed that is able to physically control both atmospheric and oceanic variables.

Abstract

A new sensitivity analysis method is proposed for the ensemble prediction system in which a tropical cyclone (TC) position is taken as a metric. Sensitivity is defined as a slope of linear regression (or its approximation) between state variable and a scalar representing the TC position based on ensemble simulation. The experiment results illustrate important regions for ensemble TC track forecast. The typhoon-position-oriented sensitivity analysis (TyPOS) is applied to Typhoon Shanshan (2006) for the verification time of up to 48 h. The sensitivity field of the TC central latitude with respect to the vorticity field obtained from large-scale random initial perturbation is characterized by a horizontally tilted pattern centered at the initial TC position. These sensitivity signals are generally maximized in the middle troposphere and are far more significant than those with respect to the divergence field. The results are consistent with the sensitivity signals obtained from existing methods. The verification experiments indicate that the signals from TyPOS quantitatively reflect an ensemble-mean position change as a response to the initial perturbation. Another experiment with Typhoon Dolphin (2008) demonstrates the long-term analysis of forecast sensitivity up to 96 h. Several additional tests have also been carried out to investigate the dependency among ensemble members, the impacts of using different horizontal grid spacing, and the effectiveness of ensemble-Kalman-filter-based perturbations.

ABSTRACT

This study statistically investigates the characteristics of tropical cyclones (TCs) undergoing rapid intensification (RI) in the western North Pacific in the 37 years from 1979 to 2015 and the relevant atmospheric and oceanic environments. Among 900 TCs, 201 TCs undergoing RI (RI-TCs) are detected by our definition as a wind speed increase of 30 kt (15.4 m s⁻¹) or more in a 24-h period. RI-TCs potentially occur throughout the year, with low variation in RI-TC occurrence rate among the seasons. Conversely, the annual occurrence of RI-TC varies widely. In El Niño years, TCs tend to undergo RI mainly as a result of average locations at the time of tropical storm formation (TSF) being farther east and south, whereas TCs experience RI less frequently in La Niña years. The occurrence rates of RI-TC increased from the 1990s to the late 2000s. The RI onset time is typically 0–66 h after the TSF and the duration that satisfies the criteria of RI is 1–2 days. RI frequently occurs over the zonally elongated area around the eastern Philippine Sea. The development stage and life-span are longer in RI-TCs than in TCs that do not undergo RI. RI-TCs are small at the time of TSF and tend to develop as intense TCs as a result of environmental conditions favorable for TC development, weak vertical wind shear, high convective available potential energy, and tropical cyclone heat potential. The occurrence rates of RI-TCs that make landfall in Japan and the Philippines are higher than in China and Vietnam.

Abstract

To clarify the effect of fluctuations in surface stress and heat fluxes on the intensity of a mature-state hurricane, a sensitivity analysis is performed by using a cloud-permitting nonhydrostatic axisymmetric adjoint model. The response function of our experiment is tangential velocity at the top of the boundary layer in the eyewall.

As a result of an integration backward to 4 min prior to the specified time, a dipole pattern appears in the sensitivity fields with respect to the vertical velocity, the potential temperature, and the mixing ratio of water vapor. A positive (negative) sensitivity is found in the hurricane interior (exterior) relative to the verification region. It exhibits an increase of tangential velocity 4 min after the introduction of positive (negative) perturbations in potential temperature or in the mixing ratio of water vapor in the interior (exterior). These sensitivities are not related to the changes in the central pressure field. With further backward integration, the sensitivity signals reach down to the surface and are located in the exterior region of the hurricane. While the sensitivity with respect to surface friction (heat flux) is strongly negative (positive) within a certain radius, the sensitivity can be positive (negative) beyond that radius. This means that both stronger friction and a reduction in moist air supply in the exterior region of the hurricane can serve to strengthen the maximum tangential velocity. To the authors’ knowledge, this effect has not been explained in previous studies.

Abstract

This work quantifies the benefits of using a high-resolution atmosphere–ocean coupled model in tropical cyclone (TC) intensity forecasts in the vicinity of Japan. To do so, a large number of high-resolution calculations were performed by running the Japan Meteorological Agency (JMA) nonhydrostatic atmospheric mesoscale model (AMSM) and atmosphere–ocean coupled mesoscale model (CMSM). A total of 281 3-day forecasts were compiled for 34 TCs from April 2009 to September 2012 for each model. The performance of these models is compared with the JMA global atmospheric spectral model (GSM) that is used for the operational TC intensity guidance. The TC intensities are better predicted by CMSM than the other models. The improvement rates in CMSM relative to GSM and AMSM generally increase with increasing forecast time (FT). CMSM is better than GSM and AMSM by 27.4% and 21.3% at FT = 48 h in terms of minimum sea level pressure, respectively. Regarding the maximum wind speed, CMSM is better than GSM and AMSM by 12.8% and 19.5% at FT = 48 h, respectively. This is due to smaller initial intensity errors and sea surface cooling consistent with in situ observations that suppress erroneous TC intensification. Thus, a high-resolution coupled model is promising for TC intensity prediction in the area surrounding Japan, where most of the TCs are in a decay stage. In contrast, coupling to the upper-ocean model yields only a negligible difference in the TC track forecast skill on average.

Abstract

This study examines the diurnal variation of the convective area and eye size of 30 rapidly intensifying tropical cyclones (RI TCs) that occurred in the western North Pacific from 2015 to 2017 utilizing Himawari-8 satellite imagery. The convective area can be divided into the active convective area (ACA), mixed phase, and inactive convective area (IACA) based on specific thresholds of brightness temperature. In general, ACA tends to develop vigorously from late afternoon to early the next morning, while mixed phase and IACA develop during the day. This diurnal pattern indicates the potential for ACA to evolve into mixed phase or IACA over time. From the 30 samples, RI TCs tend to have at least a single-completed diurnal signal of ACA inside the radius of maximum wind (RMW) during the rapidly intensifying period. In the same period, the RMW also contracts significantly. Meanwhile, more intense storms such as those of category 4 or 5 hurricane intensity are apt to have continuous ACA inside the RMW and maintain eyewall convective clouds. These diurnal patterns of the ACA could vary depending on the impact of large-scale environments such as vertical wind shear, ocean heat content, environmental mesoscale convection, and terrain. The linear regression analysis shows that from the tropical storm stage, RI commences after a slow intensification period, which enhances both the primary circulation and eyewall convective cloud. Finally, after the eye structure appears in satellite imagery, its size changes inversely to the diurnal variation of the convective activity (e.g., the eye size becomes larger during the daytime).

Abstract

In ensemble-based assimilation schemes for cloud-resolving models (CRMs), the precipitation-related variables have serious sampling errors. The purpose of the present study is to examine the sampling error properties and the forecast error characteristics of the operational CRM of the Japan Meteorological Agency (JMANHM) and to develop a sampling error damping method based on the CRM forecast error characteristics.

The CRM forecast error was analyzed for meteorological disturbance cases using 100-member ensemble forecasts of the JMANHM. The ensemble forecast perturbation correlation had a significant noise associated with the precipitation-related variables, because of sampling errors. The precipitation-related variables were likely to suffer this sampling error in most precipitating areas. An examination of the forecast error characteristics revealed that the CRM forecast error satisfied the assumption of the spectral localization, while the spatial localization with constant scales, or variable localization, were not applicable to the CRM.

A neighboring ensemble (NE) method was developed, which was based on the spectral localization that estimated the forecast error correlation at the target grid point, using ensemble members for neighboring grid points. To introduce this method into an ensemble-based variational assimilation scheme, the present study horizontally divided the NE forecast error into large-scale portions and deviations. As single observation assimilation experiments showed, this “dual-scale NE” method was more successful in damping the sampling error and generating plausible, deep vertical profile of precipitation analysis increments, compared to a simple spatial localization method or a variable localization method.

Abstract

This work investigates the rapid weakening (RW) processes of Typhoon Trami (2018) by examining sea surface temperature (SST) cooling based on air–sea coupled simulations during typhoon passage. The cold wake and Trami’s RW occurred as the storm was moving at a very slow translation speed. A marked structural change of Trami is found in a three-dimensional ocean-coupled model experiment during the RW stage, in which the convective clouds and convective bursts in the inner core of the simulated TC dramatically decrease, resulting in the loss of diabatic heating and leading to weakening of the TC. In the simulation, the enthalpy flux dramatically decreases in the inner core because of the SST cooling during the RW period, while a stable boundary layer (SBL) is formed in the TC’s inner-core region. The expanding SBL coverage stabilizes the atmosphere and suppresses convection in the inner core, leading to weakening of the storm. A more stable atmosphere in the cold wake is also identified by the inner-core dropsonde data from the field program of Tropical Cyclones-Pacific Asian Research Campaign for Improvement of Intensity Estimations/Forecasts. The strong SST cooling also changes the evolution of Trami’s eyewall replacement cycle (ERC) and limits the eyewall contraction after the ERC.

Abstract

This paper discusses the benefits of using a hybrid ensemble Kalman filter and four-dimensional variational (4D-Var) data assimilation (DA) system rather than a 4D-Var system employing the National Meteorological Center (NMC, now known as NCEP) method (4D-Var-Bnmc) to predict severe weather events. An adjoint-based 4D-Var system was employed with a background error covariance matrix constructed from the NMC method and perturbations in a local ensemble transform Kalman filter system. The DA systems are based on the Japan Meteorological Agency’s nonhydrostatic model. To reduce the sampling noise, three types of implementation (the spatial localization, spectral localization, and neighboring ensemble approaches) were tested. The assimilation of a pseudosingle observation of sea level pressure located at a tropical cyclone (TC) center yielded analysis increments physically consistent with what is expected of a mature TC in the hybrid systems at the beginning of the assimilation window, whereas analogous experiments performed using the 4D-Var-Bnmc system did not. At the end, the structures of the 4D-Var-based increments became similar to one another, while the analysis increment by the 4D-Var-Bnmc system was broad in the horizontal direction. Realistic DA experiments showed that all of the hybrid systems provided initial conditions that yielded more accurate TC track and intensity forecasts than those achievable by the 4D-Var-Bnmc system. The hybrid systems also yielded some statistically significant improvements in forecasting local heavy rainfall events in terms of fraction skill scores when a 160 km × 160 km window size was used. The overall skills of the hybrid systems were relatively independent of the choice of implementation.

Abstract

The sporadic formation of short-lived convective clouds in the eye of Tropical Cyclone (TC) Trami (2018) is investigated using dropsonde data and simulation results from a coupled atmosphere–ocean model. According to the satellite data, top height of the convective clouds exceeds 9 km above mean sea level, considerably taller than that of typical hub clouds (2–3 km). These clouds are located 10–30 km away from the TC center. Hence, these convective clouds are called deep eye clouds (DECs) in this study. The dropsonde data reveal an increase in relative humidity in the eye region during the formation of DECs. Short-lived convective clouds are simulated up to the middle troposphere in the eye region in the coupled model. Investigation of thermodynamic conditions shows a weakened low-level warm core and associated favorable conditions for convection in the eye region during the formation of DECs. DECs are formed after the weakening and outward displacement of convective heating within the eyewall. To elucidate the influence of the changes in convective heating within the eyewall on the formation of DECs, we calculate secondary circulation and associated adiabatic warming induced by convective heating within the eyewall using the Sawyer–Eliassen equation. In the eye region, weakening of subsidence and associated vertical potential temperature advection is observed as DECs are formed. This suggests that the weakening and outward displacement of convective heating within the eyewall create favorable conditions for the sporadic formation of DECs.