Abstract

In the hybrid variational–ensemble data assimilation schemes preconditioned on the square root of background covariance , is a linear map from the model space to a higher-dimensional space. Because of the use of the nonsquare matrix , the transformed cost function still contains the inverse of . To avoid this inversion, all studies have used the diagonal quadratic form of the background term in practice without any justification. This study has shown that this practical cost function belongs to a class of cost functions that come into play whenever the minimization problem is transformed from the model space to a higher-dimension space. Each such cost function is associated with a vector in the kernel of (Ker ), leading to an infinite number of these cost functions in which the practical cost function corresponds to the zero vector. These cost functions are shown to be the natural extension of the transformed one from the orthogonal complement of Ker to the full control space.

In practice, these cost functions are reduced to a practical form where calculation does not require a predefined vector in Ker , and are as valid as the transformed one in the control space. That means the minimization process is not needed to be restricted to any subspace, which is contrary to the previous studies. This was demonstrated using a real observation data assimilation system. The theory justifies the use of the practical cost function and its variant in the hybrid variational–ensemble data assimilation method.

Abstract

A cloud-resolving nonhydrostatic four-dimensional variational data assimilation system (NHM-4DVAR) was modified to directly assimilate radar reflectivity and applied to a data assimilation experiment using actual observations of a heavy rainfall event. Modifications included development of an adjoint model of the warm rain process, extension of control variables, and development of an observation operator for radar reflectivity.

The responses of the modified NHM-4DVAR were confirmed by single-observation assimilation experiments for an isolated deep convection, using pseudo-observations of rainwater at the initial and end times of the data assimilation window. The results showed that the intensity of convection could be adjusted by assimilating appropriate observations of rainwater near the convection and that undesirable convection could be suppressed by assimilating small or no reflectivity.

An assimilation experiment using actual observations of a local heavy rainfall in the Tokyo, Japan, metropolitan area was conducted with a horizontal resolution of 2 km. Precipitable water vapor derived from global positioning system data was assimilated at 5-min intervals within 30-min assimilation windows, and surface and wind profiler data were assimilated at 10-min intervals. Doppler radial wind and radar-reflectivity data below the elevation angle of 5.4° were assimilated at 1-min intervals.

The 4DVAR assimilation reproduced a line-shaped rainband with a shape and intensity consistent with the observation. Assimilation of radar-reflectivity data intensified the rainband and suppressed false convection. The simulated rainband lasted for 1 h in the extended forecast and then gradually decayed. Sustaining the low-level convergence produced by northerly winds in the western part of the rainband was key to prolonging the predictability of the convective system.

Abstract

Numerical simulations of the diurnal evolution of tropical island convection observed during the Maritime Continent Thunderstorm Experiment (MCTEX) are performed using the Meteorological Research Institute nonhydrostatic model (MRI NHM). The MRI NHM is double-nested within a form of the Australian Bureau of Meteorology Research Centre’s Limited-Area Assimilation and Prediction System specially operated for the MCTEX period.

Excellent agreement is found between the simulation and observed evolution of the convective clouds over the Tiwi Islands on 27 November 1995. A transition from horizontal convection occurring during the morning to vertical convection in afternoon is evident.

In the morning, the sea breeze appears along the coastlines, with a clear contrast evident in structure between the windward and leeward sides. At the windward coast, the sea breeze intrudes inland more rapidly, where the larger surface heat flux modifies the lowest air mass and makes the sea breeze front (SBF) indistinct. On the other hand, at the leeward coast, the upward motion at the head of the SBF is larger and deeper. Shallow convective clouds therefore have a preference for alignment along the leeward SBF. Over the interior of the islands ahead of SBFs, shallow convective clouds corresponding to the Rayleigh–Benard convection occur at corners of open polygonal shaped cells and seem randomly distributed. Within the SBFs, organization of convection characteristic of horizontal convective rolls (HCRs) is evident. These HCRs are preferred at the windward coast and occur within cloud-free regions. Clouds associated with the SBFs appear to develop preferentially at the cross points of the SBFs and HCRs where the surface convergence is enhanced.

Following further inland propagation of SBFs, weak precipitation starts and the Rayleigh–Benard convection is disturbed by resulting outflows. At the merging stage, the clouds organize at the leeward central part of the islands in the form of an east–west line. In this convergence zone between the two SBFs, explosive growth of convection occurs and cloud top reaches the tropopause. In the case simulated here, the associated downdrafts are not strong compared with the upward motion due to a lack of the midlevel dry air necessary to enhance evaporative cooling.

The inclusion of ice phase physics in the simulation produces little qualitative difference in storm development and the associated surface rainfall distribution, but yields stronger updrafts and higher cloud-top heights. The vertical profile of the apparent heat source (Q ₁) in the ice phase experiment shows double peaks corresponding to the condensation and freezing levels.

Sensitivity experiments show that the orographic undulations as well as the horizontal scale of the island are important factors determining the timing of cloud merger and convective intensity. Without hills, the transition to the explosive growth in the merger stage is delayed. This results in weaker rainfall, even if the hills are relatively flat. A smaller island produced weaker convection, which means that the total rain produced by each island is not proportional to island area. These results suggest that the intensity of tropical island convection is determined not only by the convective stability of the environmental atmosphere but is influenced significantly by the island-scale circulations, that is, horizontal convection in the morning that ultimately forces the deep convection during the afternoon.

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

The authors evaluated the effects of assimilating three-dimensional Doppler wind lidar (DWL) data on the forecast of the heavy rainfall event of 5 July 2010 in Japan, produced by an isolated mesoscale convective system (MCS) at a meso-gamma scale in a system consisting of only warm rain clouds. Several impact experiments using the nonhydrostatic four-dimensional variational data assimilation system (NHM-4DVAR) and the Japan Meteorological Agency nonhydrostatic model with a 2-km horizontal grid spacing were conducted in which 1) no observations were assimilated (NODA), 2) radar reflectivity and radial velocity determined by Doppler radar and precipitable water vapor determined by GPS satellite observations were assimilated (CTL), and 3) radial velocity determined by DWL were added to the CTL experiment (LDR) and five data denial and two observational error sensitivity experiments. Although both NODA and CTL simulated an MCS, only LDR captured the intensity, location, and horizontal scale of the observed MCS. Assimilating DWL data improved the wind direction and speed of low-level airflows, thus improving the accuracy of the simulated water vapor flux. The examination of the impacts of specific assimilations and assigned observation errors showed that assimilation of all data types is important for forecasting intense MCSs. The investigation of the MCS structure showed that large amounts of water vapor were supplied to the rainfall event by southerly flow. A midlevel inversion layer led to the production of exclusively liquid water particles in the MCS, and in combination with the humid airflow into the MCS, this inversion layer may be another important factor in its development.

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

Horizontal convective rolls (HCRs) that develop in sea breezes greatly influence local weather in coastal areas. In this study, the authors present a realistic simulation of sea-breeze HCRs over an urban-scale area at a resolution of a few meters. An advanced Down-Scaling Simulation System (DS³) is built to derive the analyzed data using a nonhydrostatic model and data assimilation scheme that drive a building-resolving computational fluid dynamics (CFD) model. The mesoscale-analyzed data well capture the inland penetration of the sea breeze in northeastern Japan. The CFD model reproduces the HCRs over Sendai Airport in terms of their coastal initiation, inland growth, streamwise orientation, specific locations, roll wavelength, secondary flows, and regional differences due to complex surfaces. The simulated HCRs agree fairly well with those observed by dual-Doppler lidar and heliborne sensors. Both the simulation and observation analyses suggest that roll updrafts typically originate in the narrow bands of low-speed streaks and warm air near the ground. The HCRs are primarily driven and sustained by a combination of wind shear and buoyancy forces within the slightly unstable sea-breeze layer. In contrast, the experiment without data assimilation exhibits a higher deficiency in the reproduction of roll characteristics. The findings highlight that CFD modeling, given reliable mesoscale weather and surface conditions, aids in high-precision forecasting of HCRs at unprecedented high resolutions, which may help determine the roll structure, dynamics, and impacts on local weather.

Abstract

Horizontal convective rolls form in coastal areas around Sendai Airport during sea-breeze events. Using a building-resolving computational fluid dynamics model nested in an advanced forecast system with a data assimilation scheme, the authors perform a series of sensitivity experiments to investigate the impacts of land use and buildings on these rolls. The results show that the roll positions, intensities, and structures are significantly affected by variations in land use and the presence of buildings. Land-use heterogeneity is responsible for generating rolls with evident regional features. Major rolls tend to develop downwind of warm surfaces, and they dominate over neighboring rolls; thus, a heterogeneity-scale mode is imposed on the inherent roll wavelength. The roll’s rapid growth is attributable to warm surfaces that initiate a strong coupling among turbulent thermals, convective updrafts, pressure perturbations, and secondary flows in sea breezes. The heterogeneity-induced features differ considerably from the nearly homogeneous features that form over uniform surfaces. Additionally, the wake flow behind buildings helps organize near-surface warm air into streamwise bands that drive streaky ejections. The building-induced turbulence acts to modify secondary flows and displace roll updrafts toward building wakes. Such effects are most effective over villages with scattered houses that are aligned with the ambient wind. Building signatures are elongated in downwind open areas due to sustained secondary circulations. An analysis of turbulent kinetic energy shows that both land use and buildings regulate energy generation and transport, resulting in a clear response in roll growth. Thus, including complex surfaces in forecast models helps determine detailed characteristics and structures of roll convection over coastal regions.

Abstract

Recently, a humidity estimation technique was developed by using the turbulence echo characteristics detected with a wind-profiling radar. This study is concerned with improvement of the retrieval algorithm for delineating a humidity profile from the refractive index gradient (M) inferred from the echo power. To achieve a more precise estimate of humidity, a one-dimensional variational method is adopted. Because the radar data provide only the absolute value of M, its sign must be determined in the retrieval. A statistical probability for the sign of M [Pr(z)] is introduced to the cost function of the variational method to determine the optimum result with reduced calculation cost. GPS-derived integrated water vapor (IWV) was assimilated together with the radar-derived |M| for constraining the signs of |M| to agree with the radar-derived IWV and the GPS-derived IWV. Humidity profiles were retrieved from the Middle and Upper Atmosphere (MU) radar–Radio Acoustic Sounding System (RASS) data for July–August 1999 using the first guess calculated from the time interpolation of radiosonde results. The |M| profiles from the MU radar–RASS were assimilated at 21 height layers between 1.5 and 7.5 km. A genetic algorithm is employed to find the global optimum. The humidity profiles are retrieved with the same vertical resolution as that of the observation values. The precision of the retrieval result using the new method is superior to that of the conventional method. The difference between the analysis and simultaneous radiosonde results was related to a large error in the first guess. The sensitivity of the analysis result to the shape of the Pr(z) profile was investigated, and the result appears to be insensitive to the profile of Pr(z). The improvement over the conventional method is especially evident for the case of a large error in the first guess.

Abstract

Over the past 100 years, the collaborative effort of the international science community, including government weather services and the media, along with the associated proliferation of environmental observations, improved scientific understanding, and growth of technology, has radically transformed weather forecasting into an effective global and regional environmental prediction capability. This chapter traces the evolution of forecasting, starting in 1919 [when the American Meteorological Society (AMS) was founded], over four eras separated by breakpoints at 1939, 1956, and 1985. The current state of forecasting could not have been achieved without essential collaboration within and among countries in pursuing the common weather and Earth-system prediction challenge. AMS itself has had a strong role in enabling this international collaboration.