Search

The Journal of the Meteorological Society of Japan (JMSJ) is a well-established journal in the field of meteorology and related sciences. The editorial board is committed to continuously improving the journal for authors, readers, and reviewers. In 2024, the JMSJ will publish its 102nd volume and will discontinue the note service for submissions. The journal has recently implemented minor reforms in the technical editing process. The JMSJ Award for 2023 was presented to authors who conducted novel research on important topics. The most accessed papers in 2023 included topics such as geostationary meteorological satellites and reanalysis data. The journal also organized three special editions on various topics. JMSJ authors are encouraged to use J- STAGE Data for archiving datasets related to their papers. The journal expresses gratitude to the meteorological research community for their support and looks forward to continued success in 2024. [Extracted from the article]

This review paper aims to provide readers with a broad range of meteorological backgrounds with basic information on marine low clouds and the concept of their parameterizations used in global climate models. The first part of the paper presents basic information on marine low clouds and their importance in climate simulations in a comprehensible way. It covers the global distribution and important physical processes related to the clouds, typical examples of observational and modeling studies of such clouds, and the considerable importance of changes in low clouds for climate simulations. In the latter half of the paper, the concept of cloud parameterizations that determine cloud fraction and cloud water content in global climate models, which is sometimes called cloud "macrophysics", is introduced. In the parameterizations, the key element is how to assume or determine the inhomogeneity of water vapor and cloud water content in model grid boxes whose size is several tens to several hundreds of kilometers. Challenges related to cloud representation in such models that must be tackled in the next couple of decades are discussed. [ABSTRACT FROM AUTHOR]

The regional data assimilation system at the Japan Meteorological Agency uses a variational data assimilation system based on the non-hydrostatic model ASUCA (named ASUCA-Var). This paper reviews the configurations and current status of ASUCA-Var. To consider the consistency of analysis and prognostic variables, the control variables of ASUCA-Var include soil variables and basic atmospheric variables. The background-errors based on the control variables are calculated every 3 h for land and sea grid points to better reflect the representative error covariance structure, considering daily variations and differences in structure on land and sea. Although the cost function is designed to be a perfect quadratic form, the basic field update method in the optimization process allows the nonlinearity of the observation operator and numerical weather prediction model to be incorporated into the solution of optimization problem in the incremental four-dimensional variational (4D-Var) method. The outer/inner models used in the incremental 4D-Var method are based on ASUCA, with suitable configurations according to each resolution and applied linearization. Observation operators are implemented for various kinds of observations used, with unified interfaces encapsulating external simulators. Variational quality control and variational bias correction are also introduced for advanced observation handling within the variational system. Parallelization is introduced to enhance computational efficiency, including adjoint calculations. To assess the impact of assimilated observations, degrees of freedom for signal are also available. Additionally, as a system for operational use, ASUCA-Var is designed for sustainable development. The meso-scale analysis and local analysis workflows are presented as operational implementations of ASUCA-Var. ASUCA-Var enhances forecasting in a wide range of validation indices. The major future improvements of ASUCA-Var include the introduction of the flow-dependent background-error and extension of the control variable to hydrometeors, which are expected to enhance the prediction accuracy of the operational regional model. [ABSTRACT FROM AUTHOR]

This paper focuses on the uncertainty of summer precipitation estimations produced by Global Satellite Mapping of Precipitation (GSMaP) over Mongolia, a region with complex terrain and sparse weather observation networks. We first compared the average summer precipitation over Mongolian territory as reported by several precipitation products. Although the interannual variability of the product was comparable, the amount of recorded precipitation differed among various products. The rain gauge-based analysis reported the lowest amount of precipitation, whereas the satellite-based GSMaP_MVK (Moving Vector algorithm with Kalman filter) reported the highest amount. Our results represent the first estimate of the characteristic differences among various precipitation-monitoring products, including Global Precipitation Measurement (GPM)-based products, as they relate to climatic and hydrometeorological assessments in Mongolia. We then performed a detailed comparison using a case study, in which a heavy rainfall event was captured by the GPM mission's core observatory near Ulaanbaatar in July 2016. In this case, gauged and ungauged GSMaP estimates of the precipitation over the mountain area significantly differed between algorithm versions 6 and 7. An intercomparison of atmospheric numerical modeling, the GPM core observatory, and rain gauge observation revealed that the rain gauge calibration of GSMaP effectively moderates the large error of the ungauged GSMaP data. The source of the significant ungauged GSMaP error is likely to be the rain rate estimates in algorithm version 7. However, the GSMaP gauge-calibrated estimates of the precipitation over mountainous areas may be affected by a potential underestimation of gauge analysis due to the missing localized precipitation occurring in the large gaps of the routine observation network. We expect that these findings will be helpful for developers aiming to further improve the GSMaP algorithm. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including atmospheric sciences, sea surface temperature and climate model simulations.

Equilibrium climate sensitivity (ECS) is defined as the change in the global mean surface air temperature due to the doubling or quadrupling of CO2 in a climate model simulation. This metric is used to determine the uncertainty in future climate projections, and therefore, the impact of model changes on ECS is of large interest to the climate modeling community. In this paper, we propose a new graphical method, which is an extension of Gregory's linear regression method, to represent the impact of model changes on ECS, climate forcing, and climate feedbacks in a single diagram. Using this visualization method, one can (a) quantify whether the model or process change amplifies, reduces, or has no impact on global warming, (b) evaluate the percentage changes in ECS, climate forcing, and climate feedbacks, and (c) quantify the ranges of the uncertainties in the estimated changes. We demonstrate this method using an example of climate sensitivity simulations with and without interactive chemistry. This method can be useful for multimodel assessments where the response of multiple models for the same model experiment (e.g., usage of interactive chemistry compared with the prescribed chemistry as shown here) can be assessed simultaneously, which is otherwise difficult to compare and comprehend. We also demonstrate how this method can be used to examine the spread in ECS, climate forcing, and climate feedbacks with respect to the multimodel mean (or one benchmark model) for multimodel frameworks such as Coupled Model Intercomparison Project Phase 5 or for different ensemble members in a large ensemble of simulations conducted using a single model. [ABSTRACT FROM AUTHOR]

The performance of the Meteorological Research Institute-Atmospheric General Circulation model version 3.2 (MRI-AGCM3.2) in simulating precipitation is compared with that of global atmospheric models registered to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The Atmospheric Model Intercomparison Project (AMIP) experiments simulated by 36 Atmospheric General Circulation Model (AGCM)s and the High Resolution Model Intercomparison Project (HighResMIP) highresSST-present experiments simulated by 23 AGCMs were analyzed. Simulations by MRI-AGCM3.2S (20-km grid size) and MRI-AGCM3.2H (60-km grid size) are included as a part of the HighResMIP highresSST-present experiments. MRI-AGCM3.2S has the highest horizontal resolution of all 59 AGCMs. As for the global distribution of seasonal and annual average precipitation, monthly precipitation over East Asia, and the seasonal march of rainy zone over Japan, MRI-AGCM3.2 models perform better than or equal to CMIP6 AMIP AGCMs and HighResMIP AGCMs. HighResMIP AGCMs (average grid size 78 km) perform better than CMIP6 AMIP AGCMs (180 km) in simulating seasonal and annual precipitation over the globe, and summer (June to August) precipitation over East Asia. MRI-AGCM3.2 models perform better than or equal to CMIP6 AMIP AGCMs and HighResMIP AGCMs in simulating extreme precipitation events over the globe. Correlation analysis between grid size and model performance using all 59 models revealed that higher horizontal resolution models are better than lower resolution models in simulating the global distribution of seasonal and annual precipitation and the global distribution of intense precipitation, and the local distribution of summer precipitation over East Asia. [ABSTRACT FROM AUTHOR]

Rice is an important commodity in the Philippines. In the Cagayan Valley (CV), rice production provides employment to more than half of the region's population and any climate variability and change can cause negative impacts on crop production and people's livelihoods. This paper attempts to understand projected climate changes in seasonal rainfall and mean temperature (2011-2040) to inform climate change adaptation planning in CV. The climate change projections were provided to crop and water resource modeling, agricultural market modeling, food insecurity vulnerability analysis, community-based climate change adaptation planning, and policy simulation. The results are presented for the Provinces of Cagayan, Isabela, Nueva Vizcaya, and Quirino based on the statistical downscaling of three global climate models (BCM2, CNCM3, and MPEH5) and two emission scenarios (A1B and A2). A spatial interpolation technique was utilized in interpolating downscaled climate projections at weather stations to grids, and subsequently aggregated to administrative provinces. Results obtained in the downscaling showed anticipated significant climate changes from 2011 to 2040 in terms of rainfall and temperatures relative to 1971-2000. Consistent signals of climate change were found in many seasons and variables, whereas conflicting signs of changes were found in a few cases. A larger warming effect is projected for a daily minimum temperature than that for the maximum temperature, thus reducing diurnal temperature range. Precipitation is projected to increase in general in the Valley. Regarding seasonality, dry months (March-April-May) will continue to remain dry but during the rainy season, July and November are likely to become more notable wet months. There are also indications of an increasing frequency of heavy rainfall events, prolonged dry spell events and extreme daytime temperatures (especially in Aparri). [ABSTRACT FROM AUTHOR]

This paper clarifies that the skillful time-scale characteristic of a model is one of the key factors to reproduce the amount precipitation at a specific location with the model. A comparison with data from an operational weather station of the Japan Meteorological Agency in Tokyo (Ote-machi) revealed that a model needed That a model requires 5-km-grid resolution and below to represent the power spectrum of hourly precipitation. A model with a higher resolution is probably needed to simulate hourly precipitation in Tokyo during the summer monsoon season. [ABSTRACT FROM AUTHOR]

High-resolution atmosphere-ocean coupled models are the primary tool for subseasonal to seasonal-scale (S2S) prediction. However, seasonal-scale sea surface temperature (SST) drift is inevitable due to the imbalance between the model components, which may deteriorate the prediction skill. Here, we investigate the performance of a simple flux adjustment method specifically designed to suppress seasonal-scale SST drift through case studies. The Nonhydrostatic Icosahedral Atmospheric Model (NICAM)-Center for Climate System Research Ocean Component Model (COCO) coupled weather/climate model, referred to as NICOCO, was used for wintertime 40-day integrations with a horizontal resolution of 14 km for the atmosphere and 0.25° for the ocean components. The coupled model with no flux adjustment suffers SST drift of typically -1.5 - 2°C in 40 days over the tropical, subtropical, and Antarctic regions. Simple flux adjustment was found to sufficiently suppress the SST drift. Nevertheless, the lead-lag correlation analysis revealed that air-sea interactions are likely to be appropriately represented under flux adjustment. Thus, high-resolution coupled models with flux adjustment can significantly improve S2S prediction. [ABSTRACT FROM AUTHOR]

The maximum storm surges caused by Typhoon Jebi (2018) were examined using a storm surge model and using track ensemble simulations based on a meteorological model and a parametric tropical cyclone (TC) model. The storm surge at Osaka Port was estimated more accurately by the meteorological model than the parametric TC model. The differences between both models were due to a "wind setup effect", where the topography enhanced surface winds over Osaka Bay. The typhoon-track ensemble simulations demonstrated that the maximum storm surge was dependent on the perturbation of the track of Typhoon Jebi along the entire coast of the Japanese Islands, including the main island, Kyushu, and Shikoku. Open shallow bays had maximum storm surges exceeding 2.50 m. In coastal areas where larger maximum storm surges were estimated, the longitudinally perturbed "worst-case course" appeared 0.4 - 0.8° west or east of the "hit course", indicating that the wind setup effect was an important factor in the maximum storm surge. The distance of the worst-case course from the hit course was almost the same as the radius of the maximum wind of Typhoon Jebi. Although the models had similar worstcase courses for each coastal area, the meteorological model estimated a slightly higher simulated maximum storm surge than the parametric TC model. For the main island, Kyushu, and Shikoku, approximately 6 % of the maximum storm surges exceeded 2.00 m. Although these values may differ for other typhoons and sampling points, it is important to estimate the maximum storm surges and worst-case courses at all coastal areas, including regions where storm surges by typhoons are unknown yet they occurred, because this will provide important information enabling effective disaster prevention and risk management. [ABSTRACT FROM AUTHOR]

Typhoon Jongdari (2018) took an unusual track along the circumference of an upper-tropospheric cold low (UTCL) before making landfall in Japan on 29 July. To investigate the effects of atmosphere-ocean interactions and interactions between the UTCL and Jongdari on the storm's track, numerical simulations were conducted with a 3-km-mesh nonhydrostatic atmosphere model and an atmosphere-wave-ocean coupled model, using different initial conditions created by adopting different start times of numerical integration. The UTCL was characterized by high potential vorticity (PV), low pressure, and low relative humidity on the 355-K isotherm surface. While the UTCL moved southwestward north of Jongdari from 25 to 27 July, simulation results indicate that Jongdari traveled counterclockwise along the circumference of the UTCL. After Jongdari moved westward, the coupled model clearly simulated sea surface cooling along the track. Jongdari weakened after making landfall while the UTCL also weakened south of Japan. In particular, latent heat flux from the sea and the resulting humidification of the upper troposphere through the convection affected the UTCL. When Jongdari redeveloped over the ocean south of Kyushu, some simulations showed that Jongdari merged with the UTCL there as a result of high PV in Jongdari and relatively low upper-tropospheric PV near the UTCL. Ocean coupling helped sustain the uppertropospheric PV near the UTCL and weakened the column of elevated PV associated with Jongdari, which affected the location of the tropopause folding transformed from the UTCL by lowering the PV column of Jongdari and weakening the upper-tropospheric outflow from the center. Because the steering flow of Jongdari was affected by the geostrophic-balanced cyclonic circulation created by the UTCL, a larger difference of the atmospheric initial conditions between the initial times had a stronger influence on track and intensity simulations of both Jongdari and UTCL than ocean coupling. [ABSTRACT FROM AUTHOR]

It is desirable that a surface layer scheme in an atmospheric numerical model is consistent with an atmospheric boundary layer scheme incorporated in the same model. In this study, stability functions based on Monin-Obukhov similarity theory for momentum and heat, f m and f h, in the stable surface layer are derived from the Mellor-Yamada-Nakanishi-Niino (MYNN) scheme. The resulting stability functions are approximated by f m = 1 + 4.8z/L and f h = 0.74 + 6.0z/L, which can be analytically integrated with respect to height z to obtain momentum and heat fluxes, where L is the Obukhov length. The fluxes thus, obtained are compared with those acquired from stability functions in four previous studies: they are nearly the same as those from two of them, and show better agreement with observational data of the Surface Heat Budget of the Arctic Ocean experiment (SHEBA) over sea ice than those from the other two studies. Detailed comparisons of the results of the MYNN scheme with the SHEBA data suggest that significant variations of the fluxes observed during "winter" when the ice was covered with dry snow may have been caused by those of the surface roughness around the observational site. The stability functions obtained from the MYNN scheme predict that the bulk and flux Richardson numbers approach critical values of 0.26 and 0.21, respectively, in the limit of z/L ¥. These critical values result from the Kolmogorov hypothesis applied to the turbulent dissipation in the MYNN scheme and are considered to correspond to a transition from Kolmogorov to non-Kolmogorov turbulence. [ABSTRACT FROM AUTHOR]

In 2018, Typhoon Trami made landfall in Japan and maintained its intensity for a few days, then rapidly weakened after its recurvature. Subsequently, Typhoon Kong-Rey passed through the waters cooled by Trami while rapidly weakening. The region where both typhoons rapidly weakened is a region rich in oceanic mesoscale eddies overlying the Subtropical Countercurrent. To understand the role of a cold-core eddy, in the intensity change of these two typhoons, we examined the similarity and differences between the two typhoons, utilizing numerical simulations with a 2-km-mesh nonhydrostatic atmosphere model and an atmospheric-wave-ocean coupled model. Sensitivity experiments were performed by assuming a significant magnitude on the weakening of Trami during the mature phase; for example, we embedded an artificial cold-core eddy with a magnitude not based on in situ observations to gauge initial oceanic conditions. In contrast for Kong-Rey, nine ensemble simulations for initial atmospheric conditions were conducted instead of different-day initial oceanic conditions. The simulated rapid weakening of two typhoons was related to the low upper-ocean heat content caused by typhoon-induced sea surface cooling (SSC). Most simulations for Trami and Kong-Rey show a tendency of overdevelopment during the mature or weakening phase; the overdevelopment of Trami is caused by insufficiently simulated SSC and the embedded artificial cold eddy, which promoted the SSC; whereas, the overdevelopment of Kong-Rey is related to the failure of track simulation. A reasonable simulated track of Kong-Rey required greater time traveling over the Trami-induced SSC area to enhance weakening by reduction in inner-core moisture transport toward the center near the surface and in the inflow boundary layer on the upshear side. The reductions in downward motion in the center and the associated adiabatic heating were closely related to weakening in both typhoons. [ABSTRACT FROM AUTHOR]

The dual peak semidiurnal variation in surface rainfall rate over the tropics, simulated using a 3.5-km-mesh Nonhydrostatic Icosahedral Atmospheric Model (NICAM) for 26 - 31 December 2006, is analyzed and compared with data from the 17 year winter precipitation climatology of Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Precipitation Radar (PR), and the same 6 day data of Global Satellite Mapping of Precipitation, as well as infrared data from geostationary satellites. We focus on land areas including southern Africa and the Amazon. Over these land areas, the NICAM simulation captures the primary peak in the afternoon and the secondary peak in the early morning, at similar times to those captured using TRMM data. In the PR observation, the primary peak of rainfall is mainly due to convective rain, whereas the secondary peak is due to stratiform rain. In the NICAM simulation, if a simple method is used for the classification of convective/stratiform rain, convective rain is dominant all day long, and the rainfall rate is generally higher than in the PR observation. Nevertheless, an analysis of deep convection (DC) areas indicates consistency between the observation and NICAM; the primary peak of rainfall rate occurs at the mature stage of the number of DC areas, whereas the secondary peak occurs when the mean size of DC areas is almost at its highest point. However, in the NICAM simulation, the relative magnitudes of the two peaks are not represented well, and the contribution of the stratiform rain is underestimated. The present study indicates that a high-resolution global nonhydrostatic model like NICAM has the potential to overcome the limitations of coarse-resolution general circulation models by reproducing the semidiurnal variation of DC, although there is room for improvement. [ABSTRACT FROM AUTHOR]

Observational and model studies suggest that the stratosphere exerts a significant influence on the tropical troposphere. The corresponding influence, through dynamical coupling, of the stratosphere on the extratropical troposphere has over the last 15 - 20 years been intensively investigated, with consequent improvement in scientific understanding which is already being exploited by weather forecasting and climate prediction centres. The coupling requires both communication of dynamical effects from stratosphere to troposphere and feedbacks within the troposphere which enhance the tropospheric response. Scientific understanding of the influence of the stratosphere on the tropical troposphere is far less developed. This review summarises the current observational and modelling evidence for that influence, on timescales ranging from diurnal to centennial. The current understanding of potentially relevant mechanisms for communication and for feedbacks within the tropical troposphere and the possible implications of the coupling for weather and climate prediction are discussed. These include opportunities for model validation and for improved subseasonal and seasonal forecasting and the effects, for example, of changes in stratospheric ozone and of potential geoengineering approaches. Outstanding scientific questions are identified and future needs for observational and modelling work to resolve these questions are suggested. [ABSTRACT FROM AUTHOR]

In this study, we assess the prediction skill of the Boreal Summer Intra-Seasonal Oscillation (BSISO) mode of one-month simulations using a global Non-hydrostatic Icosahedral Atmospheric Model (NICAM) with explicit cloud microphysics and a grid spacing of 14 km. The simulations were run as a series of hindcast experiments every day of August from 2000 to 2014. A total of 465 simulations were run with a 13950-day integration. Using forecast skill scores for statistical measurements, it was found that the model showed an overall BSISO prediction skill of approximately 24 days. The prediction skill tended to be slightly higher (~ 2 days) when BSISO events began in the initial phases 7 to 1, which corresponded to the re-initiation phase of the BSISO, during which a major convective center over the Philippine Sea decayed and a new convective envelope began aggregating over the western Indian Ocean. The phase speed and the evolution of the amplitude of the BSISO were well simulated by the model with a clear northwest-southeastward tilted outgoing longwave radiation (OLR) structure over the Maritime Continent and the western Pacific. However, the propagation speed was slower during phases 6 and 7, and the amplitude of the BSISO largely decayed during phases 8 - 1, which is likely to have been associated with the stagnant behavior of the convective cells over the Philippines sea. Based on a regression coefficient analysis using the moist static energy, the stagnation of the propagation over the Philippines was found to be largely attributable to the small southerly background bias in the model over the Philippines. The bias in the large-scale circulation was likely to have been associated with the bias in the moisture field and the background monsoonal circulation. We concluded that the model physics controlling the background fields are important factors in improving BSISO prediction skill. [ABSTRACT FROM AUTHOR]

In this study, we examine the resolution dependence of the convective spectrum in Community Atmospheric Model version 5 (CAM5) simulations, focusing on the transition from shallow to deep convection and the associated cloud-radiative effect (CRE) change. We first apply the bin method (percentile binning) on precipitation intensity to obtain the convective spectrum in the tropics. The same approach is also used in the column-integrated moist static energy (MSE) budget analysis. The binning results show that over the light-rain regime, the convective structure is dominated by shallow convection, functioning to destabilize the atmosphere by importing columnintegrated MSE. The heavy-rain regime shows the coexistence of deep and shallow convection, which inclines to stabilize the atmosphere by exporting the column-integrated MSE. Moreover, we also note that the longwave (LW) component of CRE (LWCRE) is more sensitive to the change of model spatial resolution than the shortwave (SW) component of CRE (SWCRE), characterized by a stronger response in the coarser resolution run over the heavy-rain regime. The resolution dependence of convective spectrum and CRE changes presented in this study highlights the importance of scale-aware cumulus parameterization design in climate models, which is not yet implemented in CAM5. [ABSTRACT FROM AUTHOR]

The transport and removal processes of aerosol particles, as well as their potential impacts on clouds and climate, are strongly dependent on the particle sizes. Recent advances in computational capabilities enable us to develop sectional aerosol schemes for general circulation models and chemical transport models. The sectional aerosol modeling framework provides a capacity to explicitly simulate the variations in size distributions due to microphysical processes such as nucleation and coagulation, based on the mechanisms suggested from laboratory studies and field observations. Here, we develop a two-moment sectional aerosol scheme for Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS-bin) for use in Nonhydrostatic ICosahedral Atmospheric Model (NICAM) as an alternative to the original mass-based (single-moment) SPRINTARS-orig aerosol module. NICAM-SPRINTARS is a seamless multiscale model that has been used for regional-to-global simulations of different resolutions based on the same model framework. In this study, we performed global simulations with NICAM-SPRINTARS-bin at typical climate model resolution (Δx ~ 230 km) with nudging to a meteorological re-analysis. We compared our results with equivalent simulations for the original model (NICAM-SPRINTARS-orig) and observations including 500nm aerosol optical depth and 440-870nm Angstrom Exponent in AErosol RObotic NETwork (AERONET) measurements, particle number concentrations measured at Global Atmospheric Watch (GAW) sites and size-resolved number concentrations measured at European Supersites for Atmospheric Aerosol Research (EUSAAR) and German Ultrafine Aerosol Network (GUAN) sites. We found that compared to NICAM-SPRINTARS-orig, NICAM-SPRINTARS-bin demonstrates the long-range transport of ultra-fine particles to high latitudes and predicts higher Angstrom Exponent and total number concentrations that better agrees with observations. The latter underscores the importance of resolving the microphysical processes that determine concentrations of ultra-fine aerosol particles and explicitly represent size-dependent deposition in predicting these properties. However, number concentrations of coarse particles are still underestimated by both the original mass-based and the new microphysical schemes. Further efforts are needed to understand the reasons for the differences with the observed size distributions, including testing different emission and secondary organic aerosol production schemes, incorporating inter-species coagulation and black carbon aging, as well as performing simulations with higher spatial resolutions. [ABSTRACT FROM AUTHOR]

In this study, future changes in the rainy season in East Asia are projected based on massive ensemble simulations of about 100 members with a 60-km mesh global atmospheric model (the 60-km model hereinafter) called the "Database for Policy Decision-Making for Future Climate Change (d4PDF)". For the present-climate, historical observed sea surface temperatures (SSTs) are prescribed to the 60-km model. In the future, 4°C warmer climate relative to the preindustrial climate, six different SST distributions projected by Atmosphere-Ocean General Circulation Models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are given to the 60-km model. In the future, summer precipitation will generally increase in most regions of East Asia, but will decrease over western Japan. Precipitation decreases in June around 30 - 35°N over China, Korea and Japan. The Probability Density Function directly was derived from the massive ensemble simulations at each grid point in June and revealed that the most intense precipitation increase will occur in some regions where moderate precipitation decreases will take place in terms of the simple ensemble average. In western Japan, the onset of rainy season will delay and the retreat will occur earlier, resulting in a shorter rainy season. The decrease of precipitation in June over western Japan may be attributed to the counter-effect of the convergence of moisture to the south of Japan, originating in the southward shift of the western North Pacific subtropical high. The projected decrease in June precipitation over western Japan is confirmed to be robust, regardless of model differences in horizontal resolution, convection schemes, and with/without air-sea interactions. [ABSTRACT FROM AUTHOR]

Ozone loss pathways and their rates in the ozone quasi-biennial oscillation (QBO), which is simulated by a chemistry-climate model developed by the Meteorological Research Institute of Japan, are evaluated using an objective pathway analysis program (PAP). The analyzed chemical system contains catalytic cycles caused by NOx, HOx, ClOx, Ox, and BrOx. PAP quantified the rates of all significant catalytic ozone loss cycles, and evaluated the partitioning among these cycles. The QBO amplitude of the sum of all cycles amounts to about 4 and 14% of the annual mean of the total ozone loss rate at 10 and 20 hPa, respectively. The contribution of catalytic cycles to the QBO of the ozone loss rate is found to be as follows: NOx cycles contribute the largest fraction (50 - 85%) of the QBO amplitude of the total ozone loss rate; HOx cycles are the second-largest (20 - 30%) below 30 hPa and the third-largest (about 10%) above 20 hPa; Ox cycles rank third (5 - 20%) below 30 hPa and second (about 20%) above 20 hPa; ClOx cycles rank fourth (5 - 10%); and BrOx cycles are almost negligible. The relative contribution of the NOx and Ox cycles to the QBO amplitude of ozone loss differs by up to 10% and 20%, respectively, from their contribution to the annual mean ozone loss rate. The ozone QBO at 20 hPa is mainly driven by ozone transport, which then alters the ozone loss rate. In contrast, the ozone QBO at 10 hPa is driven chemically by NOx and the temperature dependence of [O]/[O3], which results from the temperature dependence of the reaction O + O2 + M O 3 + M. In addition, the ozone QBO at 10 hPa is influenced by the overhead ozone column, which affects [O]/[O3] (through ozone photolysis) and the ozone production rate (through oxygen photolysis). [ABSTRACT FROM AUTHOR]

This study evaluates possible changes in tropical cyclone (TC) precipitation over Japan under a future warmer climate using an ensemble projection generated by a non-hydrostatic regional climate model with a resolution of 5 km (NHRCM05) under the RCP8.5 scenario. NHRCM05 reproduces TC precipitation and TC intensity more accurately than does a general circulation model with a resolution of 20 km. The number of TCs approaching Japan is projected to decrease under the future climate, while the TC precipitation rate increases. As these two effects cancel each other out, total TC precipitation, and the frequency of the moderate TC precipitation that is usual under the present climate, shows no significant change. On the other hand, the frequency of extreme TC precipitation increases significantly because the intensification of the TC precipitation rate outweighs the reduction in TC frequency. The increase in the TC precipitation rate is caused primarily by the increase in water vapor around the TCs, which in turn results from the increase in environmental water vapor. The intensification and structural changes to TCs also contribute to the enhanced TC precipitation. [ABSTRACT FROM AUTHOR]

In August 2016, a monsoon gyre persisted over the western North Pacific and was associated with the genesis of multiple devastating tropical cyclones (TCs). A series of hindcast simulations were performed using the nonhydrostatic icosahedral atmospheric model (NICAM) to reproduce the temporal evolution of this monsoon gyre. The simulations that were initiated at dates during the mature stage of the monsoon gyre successfully reproduced its termination and the subsequent intensification of the Bonin high, whereas the simulations initiated before the formation and during the developing stage of the gyre failed to reproduce subsequent gyre evolution even at a short lead time. These experiments further suggest a possibility that the development of the Bonin high is related to the termination of the monsoon gyre. The high predictability of the termination is likely due to the predictable midlatitudinal signals that intensify the Bonin high. [ABSTRACT FROM AUTHOR]

Geographical distributions of heavy snowfall, especially in the Pacific Ocean side of Japan, have not been previously elucidated due to low occurrence frequency of heavy snowfall and limited number of snow observation points. This study investigates the characteristics of synoptic conditions for heavy daily snowfall from western to northeastern Japan in the present climate, analyzing high-resolution regional climate ensemble experiments with 5-km grid spacing. The Japanese 55-year Reanalysis (JRA-55) and the 10-ensemble members of the database for Policy Decision making for Future climate change (d4PDF) historical experiments are applied to the lateral boundary conditions of the regional climate model. Dynamical downscaling using d4PDF (d4PDF-DS) enabled us to evaluate much heavier snowfall events than those simulated by dynamical downscaling using JRA-55 (JRA55-DS). Over the Sea of Japan side, heavy snowfall occurs due to cold air outbreaks, while over the Pacific Ocean side, heavy snowfall is brought about by extratropical cyclones passing along the Pacific Ocean coast. A comparison between JRA55-DS and d4PDF-DS indicated that heavier snowfall can occur due to more developed extratropical cyclones and enhanced cold air damming in the Tokyo metropolitan area. The geographical distributions of extremely heavy snowfall are different between two typical synoptic conditions, i.e., cold air outbreaks and extratropical cyclones. The difference is much clearer in the extremely heavy snowfall events than in all snowfall events. Heavy daily snowfall occurs in January and February on the Pacific Ocean side, in December and January on the Sea of Japan side, and in November and March in high mountainous areas. Saturated water vapor pressure is largest around 0°C under the snowing conditions. Synoptic conditions from late fall to winter are closely related to preferable conditions for heavy snowfall over the mountainous areas where the surface air temperature is much less than 0°C in the heavy snowfall events. [ABSTRACT FROM AUTHOR]

The cloud variability and regime transition from stratocumulus to cumulus across the sea surface temperature front in the Kuroshio region over the East China Sea are important regional climate features and may affect the Earth's energy balance. However, because of large uncertainties among available cloud products, it is unclear which cloud datasets are more reliable for use in studying the regional cloud features and in validating cloud simulations in the region by climate models. In this study, the monthly low cloud amount (LCA) and total cloud amount (TCA) datasets in the region from Cloud--Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), Moderate-resolution Imaging Spectroradiometer (MODIS), and International Comprehensive Ocean-- Atmosphere Data Set (ICOADS) are validated against the combined product of CloudSat + CALIPSO (CC) in terms of consistency and discrepancy in the climatologically mean, seasonal cycle, and interannual variation. The results show that LCA and TCA derived from MODIS and CALIPSO present relatively high consistency with CC data in the climatological annual mean and show similar behaviors in seasonal cycle. The consistency in LCA between the three datasets and the CC is generally good in cold seasons (winter, spring, and fall) but poor in summer. MODIS shows the best agreement with CC in fall, with a correlation coefficient of 0.77 at a confidence level over 99 %. CALIPSO and MODIS can provide a competitive description of TCA in all seasons, and ICOADS is good in terms of the climatological seasonal mean of TCA in winter only. Moreover, the interannual complivariation of LCA and TCA from all datasets is highly correlated with that from CC in both winter and spring with the Matching Score ranging between 2/3 and 1. Further analysis with long-term data suggests that both LCA and TCA from ICOADS and MODIS can be good references for studies of cloud interannual variability in the region. [ABSTRACT FROM AUTHOR]

This study provides an overview of the Asian monsoon and its change as simulated by atmosphere-ocean coupled general circulation models and high-resolution atmospheric general circulation models, focusing on the seasonal mean circulation and precipitation climatology. After reviewing the drivers of and the elements that affect the monsoon, the ability of those climate models to reproduce the Asian monsoon is assessed. The Asian monsoon is better reproduced in the Coupled Modeling Intercomparison Project phase 5 (CMIP5) models than in the CMIP3 models, although biases remain. Projected future changes in the Asian monsoon at the end of the 21st century are then reviewed. Overall projections are similar for both CMIP3 and CMIP5 models with increases in precipitation, albeit with weakened circulation in the South Asian summer, enhanced circulation and increased precipitation in the East Asian summer, and latitude-dependent changes in the winter monsoon circulation in East Asia. However, differences exist in the projected local changes, leading to uncertainty in projections. [ABSTRACT FROM AUTHOR]

Regional climate models have been useful in climate studies and in downscaling climate projections from global climate models, especially for areas characterized by complex topography and coastline features, such as the Philippines. However, several factors may affect model skill, such as uncertainties related to the boundary conditions and model configuration. This study evaluates the performance of the non-hydrostatic regional climate model (NHRCM) over the Philippines. Present-day climate simulations at 50 km resolution are conducted using two sets of boundary conditions (ECMWF ERA-Interim and the NCEP/NCAR Reanalysis Project NNRP1), as well as two convective parameterization schemes in the model (Grell and Kain-Fritsch). Results show that the seasonal changes in the spatial distribution of temperature, rainfall, and winds over the Philippines are simulated reasonably well. NHRCM has an overall cold and dry bias over land, the degree of which depends on the boundary condition and the convective scheme used. After adjusting the simulated temperature because of the difference in topography, the temperature differs from that observed by -0.90°C to -0.42°C on average. The rainfall bias in NHRCM ranges from -62.13 % to -25.20 %. Regardless of the boundary condition, the Grell scheme results in the lowest temperature bias with high skill scores, while the Kain-Fritsch scheme gives the lowest rainfall bias with high correlation and skill scores. The boundary conditions also influence model skill, such that the model bias is lower for temperature when ERA-Interim is used, but lower for rainfall with NNRP1. NHRCM represents the seasonal cycles of temperature and rainfall for all regions, but tends to generate more occurrences of cold and dry months. Improvements in the model are still possible, but these results indicate the potential of the model to be used for providing essential information for describing historical and future changes in the Philippine climate. [ABSTRACT FROM AUTHOR]

The characteristics of diurnal precipitation variability are evaluated over the tropical Maritime Continent (MC) from both satellite observations and high-resolution simulations performed using the Weather Research and Forecasting (WRF) model. Simulations using the Kain-Fritsch convective scheme showed a slight improvement in representing the precipitation diurnal cycle compared with those using the other two schemes examined here. The influence of boundary forcing was compared between the National Center for Environmental Prediction-Final Analysis (NCEP-FNL) and the Norwegian Earth System Model (NorESM). In these experiments, simulations with NCEP-FNL data as lateral boundary conditions outperformed those with NorESM boundary conditions. All WRF simulations exaggerated the amplitude of diurnal precipitation over the land. However, the WRF captured the principal shape of the observed diurnal cycle well. An empirical orthogonal function (EOF) analysis was applied and the first two modes from satellite data explained up to about 80 % of the total diurnal variance. The results confirm that the land-sea breeze circulation plays a significant role in the diurnal cycle of precipitation. The radiatively induced land-sea breeze circulation and its timing were well reproduced in the WRF simulations. These results suggest that higher resolution simulations that reproduce heterogeneous local-scale processes are likely necessary in order to resolve diurnal variability of precipitation and its future changes over the MC. [ABSTRACT FROM AUTHOR]

Dynamical downscaling (DDS) is performed using regional climate models (RCMs) with global atmospheric states as the input, but there is no consensus among researchers on how to define and estimate the resolvable scale of the various climatic variables obtained by DDS. Sources of RCM uncertainties, including both internal model and intermodel variability, have been assessed by performing ensemble simulations and model intercomparisons, sometimes under the controversial assumption that model bias is independent of the climatic state. Compared with low-resolution global climate simulations, DDS can add value in several ways. For example, because they consider high-resolution topographic data, RCMs can often capture mesoscale phenomena and can better represent climate dynamics. Another downscaling method, empirical statistical downscaling (ESD), is complementary to DDS because it is based on a different philosophy (i.e., sources of information) and on a mostly different set of assumptions. More collaboration and communication should be encouraged among those who develop models, those who use models and perform downscaling, those who use downscaling data, and those who make decisions based on the scientific results provided by models. In addition, ensemble experiments should be devised that can more effectively benefit impact studies. Using DDS and ESD, separately or in combination, users can maximize the utility of local climate information. [ABSTRACT FROM AUTHOR]