南海トラフ地震の地殻変動監視のためには、スロースリップイベントを客観的および即時に検知することが重要である。大きな地震が発生した場合には、一般にその周辺で余効変動が観測されるが、余効変動によりスロースリップイベントによる変動が隠されてしまう場合がある。本研究では1996年に発生した日向灘の地震に伴う余効変動を補正することにより、1998～2001年に発生した日向灘南部のスロースリップイベントを検出した。すべりの中心は宮崎・鹿児島県沖にあり、規模はMw 6.7相当であった。また、GNSS日値の処理の中で2011年東北地震以降に短期的なばらつきが大きくなった原因を特定・改善し、東海から豊後水道までだった長期的スロースリップの客観検知領域を日向灘に拡張した。
日本の南西部にある南海トラフ沿いでは、大規模な地震が繰り返し発生しており、近い将来次の地震が発生すると考えられている。これらの地震活動はフィリピン海プレートのユーラシアプレート下への沈み込みに関係しており、プレート境界の固着は大地震の源となり、その周辺に地殻変動をもたらす。したがって、この地域の地殻変動を理解することは、プレートの結合状態の変化を検出し、巨大地震を理解・監視するために重要である。ここでは、陸域観測技術衛星フェーズドアレイLバンドSARのデータを用いて、干渉SARの時系列解析を行った結果を紹介する。データは2007年から2010年までと2014年から2022年を収集し、アセンディング軌道とディセンディング軌道の両方について解析した。結果的に、プレート沈み込みに伴う広範な地殻変動は、前期の解析では見られず、後期の解析で見られるようになった。この理由は、衛星軌道の精度の違いによるものと考えられる。
When an earthquake occurs and a tsunami threatens, rapid issuance of the first tsunami warning is important for timely evacuation of coastal residents. For tsunami early warning, estimates of an earthquake's hypocenter and magnitude are usually used. In Japan, the Japan Meteorological Agency (JMA) magnitude MJ, which is based on the observed displacement amplitude, is used to estimate the first tsunami warning. Slow tsunami earthquakes, such as the 1896 Meiji Sanriku earthquake, generate high tsunami waves but relatively small seismic waves. Thus, the use of MJ can cause underestimation of the size of such earthquakes and, therefore, lead to underestimation of the tsunami wave height. Quantitative understanding of the underestimation of slow tsunami earthquake magnitudes is needed, but local seismic records of slow tsunami earthquakes are scarce. In this study, we conducted spectrum analyses of teleseismic waves and used previously reported moment rate functions to construct synthetic local seismic wave records for slow tsunami earthquakes. First, we used data of earthquakes that occurred off the Japanese coast to confirm the validity of this method of constructing synthetic records. Then, we assumed tsunami earthquakes occurring off Miyagi Prefecture or the Sanriku Coast of Japan with the same moment rate functions as five major historical slow tsunami earthquakes, and compared our estimated magnitudes for these assumed earthquakes with the moment magnitudes (MW) of the five slow tsunami earthquakes. We found that MJ underestimated the size of the assumed earthquakes by 1 or more magnitude units when compared with MW. We also evaluated M100, a scale introduced after the 2011 Tohoku earthquake to supplement MJ and avoid underestimation of magnitude 9 class earthquakes. We found that M100 underestimated magnitudes by 0.5 or more magnitude units. Additionally, we suggest that amplitude distributions obtained from long-period seismic monitors, which were introduced to prevent underestimation of the magnitude of huge earthquakes, may be effectively used to estimate magnitudes of slow tsunami earthquakes.
Long-term and short-term slow slip events (SSEs) have occurred repeatedly in the Nankai Trough subduction zone, Japan. The SSEs may incrementally stress the adjacent parts of the locked megathrust zone. When SSEs occur, it is important to determine whether they are similar to previous repeated events, in order to judge whether the probability of occurrence of a large Nankai Trough earthquake is relatively high. In this study, we objectively detected short-term SSEs in the Nankai Trough subduction zone by correlating the GNSS daily and 6-hour coordinates with a ramp function with a one-week slope, excluding common noise and long-term trends. The spatiotemporal distribution of short-term SSEs detected was in good agreement with the occurrence of deep low-frequency earthquakes. In addition, assuming slip on a rectangular fault on a plate boundary, we estimated the moment magnitude of long-term SSEs from displacement data for two years and obtained results that were close to those of previous studies.
This study examined a midlatitude low pressure system that deepened to 974 hPa over the Sea of Japan on 31 August 2016 using the Japanese 55-year reanalysis (JRA-55) dataset. The low appears to have developed by absorbing Typhoon Lionrock (2016). This unusual development of the low occurred in a relatively weak baroclinic environment in association with high potential vorticity air that moved southeastward and downward along a slantwise isentropic surface in the upper troposphere. Middle and lower tropospheric warming also contributed to the deepening of the surface low. In the last stage of its development, the upper-tropospheric trough became coupled with Typhoon Lionrock. Lionrock also contributed to the deepening of the low at an earlier stage by inducing moist air to flow in the lower troposphere between Lionrock and a high pressure system located to its north. The consequent latent heat release over the Sea of Japan led to intensification of the upper-tropospheric ridge and increased vorticity advection. These are also considered to have contributed to the deepening of the low.
This work quantified the skills of high-resolution regional nonhydrostatic models in forecasting tropical cyclones (TCs) in the Western North Pacific. The selected cases were almost all TCs during 2012–2014 with an initial time of 1200 UTC. The Japan Meteorological Agency (JMA)-nonhydrostatic model with a horizontal grid spacing of 5 km (NHM5km_atm) and its atmosphere-ocean coupled version (NHM5km_cpl) were used to conduct three-day forecasts. The JMA-global spectral model (GSM) outputs interpolated to a horizontal grid spacing of 0.5 degree were used for initial and lateral boundary conditions of the NHM5km_atm and NHM5km_cpl. The skills and GSM forecast skill were validated with respect to the Regional Specialized Meteorological Center Tokyo best track dataset. Results showed that use of the NHM5km_atm and NHM5km_cpl generally improved track forecasts at forecast times of 24–60 h. Track forecasts improved by as much as 20% for TCs with strong vertical shears of horizontal winds. However, a two-tailed test for the mean value revealed that the improvements were not statistically significant above the 90% confidence level. Use of the NHM5km_atm and NHM5km_cpl significantly improved TC intensity forecasts of 2–3 days by more than 20% with respect to the GSM, but strong TC intensities were not well predicted by short-term forecasts because of initialization deficiencies. Although the NHM5km_cpl tended to seriously underestimate TC intensities, it tended to produce the greatest increase in the correlation coefficient between observed and predicted intensity changes. This study also showed that the method used to determine the TC center position affects the track forecast error by up to a few percent and that the maximum wind speed forecast error depends on the best track dataset selected as a reference.
The continuous measurement of tropospheric ozone was made at the summit of Mt. Fuji (3776 m a.s.l.) for 6 years (1992-1998). The observations suggest some characteristic features of ozone in the middle troposphere over Japan. The annual variation at the summit of Mt. Fuji shows a bimodal seasonal trend; May and October maxima and August and December minima. The summer minimum, which causes the bimodal seasonal trend, is resulted from the domination of the ozone-depleted maritime air at the summit. In June, however, the enhanced ozone (>60 ppbv) is occasionally observed at the summit in the air with low water-vapor mixing ratio and high potential vorticity (PV), suggesting that it has origins in the stratosphere or the upper troposphere. The small variance of ozone during the winter is suggested by the winter photochemistry on ozone and strong zonal winds. The infrequent ozone intrusions from the stratosphere are also thought to contribute to the small variance of ozone during the winter. The synchronization of the annual course of daily-mean ozone with the clear-sky solar radiation at the summit from late autumn to early spring and the coincident of the both minima in late December suggest that the solar radiation controls ozone observed at the summit during this period of time. In the spring, the daily-mean ozone simultaneously increases with the daily solar radiation besides the ozone concentrations do not correlate with PV, suggesting that the spring ozone maximum at the summit of Mt. Fuji is mainly resulted from photochemical ozone production. However, the possibility of partial contribution of indirect stratospheric ozone intrusions or aged stratospheric ozone to the spring ozone maximum cannot be ruled out. The 6-year observation of ozone at the summit shows the increase trend of 0.49 ppbv year-1, but it is not significant at 95% significance level. 4.088
A new calibration system of methane (CH4) standard gases by using a wavelength-scanned cavity ring-down spectroscopy (WS-CRDS) analyzer was developed at the Japan Meteorological Agency (JMA) in collaboration with the Meteorological Research Institute. We used two sets of CH4 primary standard gases with mole fractions assigned based on the World Meteorological Organization (WMO) CH4 mole fraction scale maintained by the National Oceanic and Atmospheric Administration to test the performance of the new WS-CRDS calibration system. Our results showed high repeatability (0.06 nmol mol−1) and reproducibility (0.07 nmol mol−1) of measurements and good linearity against the WMO CH4 mole fraction scale. The CH4 calibration results for the new system agree well with those of the previous JMA calibration system, which employed a gas chromatograph with a flame ionization detector (GC/FID). These tests indicate that the new WS-CRDS CH4 calibration system at JMA will provide results that are consistent with those of the previous GC/FID system but with precision that is one order of magnitude higher. We also evaluated the stability and consistency of the JMA calibrations over the past 10 years by examining data from the World Calibration Centre (WCC) Round Robin comparison experiments in Asia and the regions in the southwest Pacific. The results of our study clearly demonstrate that the new calibration system will provide more precise CH4 measurements and improved traceability to the WMO scale of atmospheric CH4 measurements for the JMA/WCC comparisons.
体積ひずみ計のような地殻変動データは、降水の影響を受けることがある。降水の影響を受ける地殻変動 データに対して降水補正は有効であり、降水補正にとって唯一の入力値である降水量データの品質は重要で ある。しかし、降水の影響を受けるものの雨量計が併設されていない地殻変動観測点も非常に多い。そのよう な観測点に雨量計が併設されていない地殻変動データの降水補正に用いる降水量データについて、どのよう な降水量データを利用するか検討する必要がある。 気象庁が設置した体積ひずみ計では、全ての観測点に雨量計を併設している。また、気象庁ではアメダスの 雨量計を平均約17km間隔で設置している。さらに、雨量計の観測とレーダーの観測を組み合わせた解析雨量 も作成している。本稿では、これら3つの降水量データによる体積ひずみ計の降水補正の効果を比較した。その 結果、体積ひずみ計に雨量計を併設することの重要性や、解析雨量の有効性が確認された。この結果は、雨 量計が併設されていない地殻変動データの降水補正にとって重要である。
地上気象観測所の周辺の観測環境が地上気温等の観測結果に及ぼす影響を評価することは重要である。特に、大気や雲からの大気放射（下向き長波長放射）が地表面温度等に影響を与えることにより、気温の観測結果を左右することが知られている。しかしながら、大気放射を観測する地点の数は限られている。このため、気温や水蒸気圧等の地上気象観測データから晴天時の大気放射量（下向き長波長放射照度）を推定する様々な計算式が提案され、陸面モデル等における1時間平均程度の大気境界層の熱エネルギー収支の簡易推定などに利用されている。ところが、これらの式は、特定の地域や過去の限られた期間における観測データに基づいて作成されていたことから、近年の日本付近の気象条件への適用の可能性については、改めて検証する必要があると思われた。
Because atmospheric turbulence sometimes causes serious problems for aircraft operations, so it is necessary to detect and bypass turbulence. However, turbulence is difficult to detect by the in situ radiosonde observations or by a wind profiler radar (WPR) network such as WINDAS of Japan Meteorological Agency because of the temporal resolution and available altitude data are inadequate. Therefore, information from the Pilot Weather Report (PIREP) has been almost the only usable turbulence data. To develop the next generation WPR and a better method to detect turbulence, Research Institute for Sustainable Humanosphere (RISH) of Kyoto University, National Institute of Information and Communications Technology (NICT), and Meteorological Research Institute carried out collaborative research from 2011 to 2015. As a part of this research project, experimental observations to compare the prototype of the next generation 1.3GHz WPR (LQ-13) and radiosondes (Vaisala RS92-SGP) were conducted during December, 2012 at NICT (Koganei City, Tokyo). In this study, we compared the turbulent eddy dissipation rates (EDRs) determined with WPR from the Doppler spectrum width data with those determined with radiosondes by using the Thorpe analysis method. The results showed that EDRs determined by both methods were almost consistent. Qualitatively, the EDR increases as the PIREP turbulent intensity increases, but quantitative conclusions could not be reached because there were not enough number of data for moderate or stronger turbulence cases. Because the retrieved EDRs were smaller than International Civil Aviation Organization (ICAO) Annex3 criteria, it will be necessary to assess the EDR criteria for turbulence intensity categories.
It is important to grasp ground motion distributions right after a major earthquake. Ground motion is very sensitive to subsurface structure, but because seismic stations are sparsely distributed, it is necessary to estimate ground motion distributions at sites with no stations from subsurface structure data at those sites and ground motions data recorded only at surrounding stations. In this study, we investigated relationship between ground motion and subsurface structure to estimate ground motion distribution applying corrections according to the subsurface structure differences. Maximum velocity responses with a period of 3 s or longer were correlated with the first natural period of the deep subsurface structure, but maximum velocity responses with a shorter period correlated more strongly with the average S-wave velocity in the upper 30 m (AVS30) than with the first natural period. However, the ratios of maximum velocity responses at one station to those at a nearby station often differed for different earthquakes, indicating that there is limitation in estimating the ratios of maximum velocity responses only from the subsurface structures. Moreover, we did not detect any notable correlations between the subsurface structures and the durations of the velocity responses. Although these results were obtained by using relative velocity responses, similar results were obtained when pseudo-velocity responses were used.
Electrical charges related to cloud-to-ground (CG) lightning discharge were investigated using ground electric fields measured around the Shonai area in the Tohoku district, Japan. First, the requirement for preciseness for least-squares fitting of the electric fields derived theoretically assuming a point electrical charge to the measured electric fields is discussed. The horizontal resolution needed to obtain appropriate solutions is proposed using a set of theoretical electric fields made by electrical charges at heights with intervals of 0.1 km. A numerical fitting with the proposed spatial resolution was applied to the measured ground electric fields, and the locations and amounts of charges were estimated for 19 negative CG lightning discharges that occurred around Shonai during the warm and cold seasons in 2012. The estimated locations of the charges were compared to the atmospheric temperature, Doppler radar measurements, and the distribution of very-high-frequency (VHF) radiation sources detected by a VHF-based lightning detection system for two events. In one of the analyzed events, the estimated electrical charge revealed the characteristics of a negative charge that could have caused the discharge. In the other event, the charge was estimated to have been located at low altitude, and the event could not be interpreted by the usual negative CG lightning discharge model. The discussion concerning the numerical fitting presented in this study may be useful for future investigations of the electrical charge related to lightning discharges based on a small number of ground electric field measurements.
We examined the standard gas scales and the stability of methane (CH4) standard gases that have been used for atmospheric measurements at the Japan Meteorological Agency (JMA) since 2000. Calibration of the JMA standards at the National Oceanic and Atmospheric Administration (NOAA) using the NOAA04 gravimetric scale, which is the accepted World Meteorological Organization (WMO) CH4 mole fraction scale, showed that CH4 mole fractions in the NOAA04 scale differ by +1.3 to −4.5 nmol mol−1 from those in the gravimetric scale in use at JMA. We established a linear relationship between the differences, which can be used for conversion between the two scales. Stability tests showed significant drift of −1 nmol mol−1 yr−1 for the mole fractions of two of the standard gases tested; all other standards were shown to be stable. Experiments comparing the results obtained for standards used at JMA and the Meteorological Research Institute (MRI) between 2000 and 2014 verified the conversion to the WMO scale and the drift correction used. The Inter-Comparison Experiments for Greenhouse Gases Observation (iceGGO) program in Japan can provide a useful means of validating the MRI/JMA CH4 scale and comparing it with other gravimetric scales used in Japan.
Estimation of tropical cyclone (TC) intensity by using satellite observations is essential for operational TC warnings in the western North Pacific basin where reconnaissance aircraft observations are not conducted. The Japan Meteorological Agency (JMA) typically uses a method of estimating the maximum wind speed of a TC based on the brightness temperature at the 10, 19, 21, 37, and 85-GHz channels of the TRMM Microwave Imager (TMI). In the original method, parameters for concentric circles and annular regions within 2° latitude from the TC center were calculated to represent the TC structure. To improve the estimation, parameters for the four quadrants on the forward, backward, left, and right sides of the TC center relative to the TC motion were added to represent asymmetric components of the TC structure. These parameters were calculated for TC cases from 1998 through 2008 in the western North Pacific basin, and k-means clustering was applied to the parameters to classify the TC cases into 10 clusters. Then a regression equation for the estimation of the TC intensity was computed for each cluster. Several selected parameters and the maximum wind speed in the best track data of the JMA were set for the explanatory variables and the explained variable, respectively, for each regression equation. The improved estimation method, based on the TC cases from 1998 through 2008, was applied to TCs from 2009 through 2012 to validate the estimation of maximum wind speed. The root mean square error derived from all validated cases was 6.26 m s-1. The estimates in the clusters for TCs that had relatively asymmetric structures were mostly improved in comparison with those based on the original estimation method. However, in several clusters for TCs that had relatively symmetric structure, the estimation errors were larger than those of the original method. This suggests that the improvement of the estimation method in the present study is limited because of several factors, including the fact that the TC maximum wind speed in the best track data is mainly based on the Dvorak analysis and thus has a certain amount of error, as well as the uncertainty of the TC position determined by using interpolation of the 6-hourly best track data.
The Japan Meteorological Agency Regional Atmospheric Transport Model (JMA-RATM, previously called the Mesoscale Tracer Transport Model) that is used operationally for the Volcanic Ash Fall Forecast has been revised. Major improvements of the JMA-RATM are as follows: (i) For the initial condition of the eruption column model, the time-series variation of eruption cloud echo height data observed by weather radars is used instead of visual camera observation. (ii) For the input meteorological field, the grid point values of the Local Forecast Model (LFM, 2 km grid spacing and 60 vertical layers) are available instead of the Mesoscale Model (MSM, 5 km spacing and 50 layers); both models originate from the JMA Nonhydrostatic Model (JMA-NHM). (iii) In the atmospheric transport model calculations, Suzuki's resistance law is extended with the Cunningham slip correction, and rainout (in-cloud scavenging) and washout (below-cloud scavenging) processes by snow and graupel are incorporated in addition to rain. The target of the model predictions is tephra fall, which includes both ash fall quantity and lapilli fall area. Comparative calculations with the JMA-RATM were conducted for the lapilli fall event during the eruptions of Shinmoe-dake volcano on 26-27 January, 14 February, 13 March and 18 April 2011. The use of the time-series data of eruption cloud echoes and the LFM grid point values was effective for predictions of both ash fall quantity and lapilli fall area. The Cunningham slip correction had a marginal effect on the ash fall prediction. In-cloud and below-cloud scavenging processes had a large influence on the ash fall prediction; therefore, the scavenging rate will need to be calibrated against ash fall observation data in rain or snow. The values for the density and form of tephra, based on observation data, also had a large impact on the lapilli fall prediction; however, the occurrence of undetected error requires future research on the effect of wind in the eruption column model.
Future hydroclimate projections for Central America and the Caribbean were investigated with quantified uncertainties using 20-km and 60-km mesh global atmospheric general circulation models. In these regions, only a few future climate projections with high horizontal resolutions are available, although Central America and the Caribbean are characterized by spatial and temporal complexities in climate. Horizontal resolutions of 20 km and 60 km are comparable to those of regional climate models for a large region. Both the 20-km and 60-km mesh models reproduced reasonably well the observed seasonal precipitation patterns. Precipitation was projected to decrease in most of this region in all seasons by the end of this century. Evaporation from the ocean was projected to increase throughout the year, except in the Intertropical Convergence Zone, whereas evaporation from land areas was generally projected to decrease in the dry season and to increase in the rainy season. Surface soil moisture and total runoff in most land areas were therefore projected to decrease in both models in all seasons. Annual mean streamflow in the future climate was projected to decrease in most of Central America and the Caribbean as a result of decreased precipitation and increased evaporation. The values of hydroclimate variables over four land-only domains in the future climate changed significantly on a monthly basis within each season. In contrast, changes in the annual means of hydroclimate variables for individual countries were highly uncertain. Corresponding address: T. Nakaegawa, Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan. E-mail: tnakaega@mri-jma.go.jp © 2014 by the Japan Meteorological Agency / Meteorological Research Institute Nakaegawa, T. et al. Vol. 65 16 tropical region that is projected to be most responsive to global change, primarily in terms of decreased precipitation and increased precipitation variability (Giorgi, 2006; Tebaldi et al., 2006). For example, a drying trend in the summer in this region is projected in MME studies (Neelin et al., 2006; Rauscher et al., 2008; Campbell et al., 2011). Associated with the drying trend, annual mean streamflow in the Rio Lempa, in Central America, is projected to decrease (Maurer et al., 2009). Many studies have been devoted to impact assessments, adaptation plans, and mitigation measures on the basis of these future climate projections (e.g., IPCC, 2007b, 2012; Bueno et al., 2008; Smith et al., 2011). These studies require modeling at small scales (local, regional, or national), because actual impacts due to climate changes are highly specific to localities, and adaptation plans and mitigation measures also depend on locality. Weather extremes have distinct effects on human activities such as agricultural production, water use, and transportation, and weather changes in future climates will likewise affect these activities (IPCC, 2012). As a prerequisite for reliable future climate projections, climate models need to simulate small-scale atmospheric phenomena such as weather extremes and storm patterns in present-day climates. Climate scientists have therefore been asked to model projected future climate changes at horizontal scales of tens of kilometers or even finer. Because computational demands limit the resolution of atmosphere-ocean GCMs (AOGCMs), fine-scale studies commonly use dynamical regional climate downscaling techniques to obtain high-resolution information on future climate changes. Regional climate models (RCMs) are typically used to downscale large-scale phenomena for smaller target regions with high-resolution grids (e.g., Christensen and Christensen, 2007; Kanada et al., 2010). Problems can arise in this type of downscaling from the lateral boundary conditions, because no interaction is modeled between the target domain and the whole globe, and large-scale systematic errors can result (e.g., Kanamaru and Kanamitsu, 2007). A high-resolution atmospheric GCM (AGCM) using a grid of approximately 20 km has recently been used to downscale large-scale phenomena (Mizuta et al., 2006; Kitoh et al., 2009) and is expected to overcome these limitations. The 20-km mesh model simulation, however, is computationally demanding and can use only a single dataset of projected sea surface temperature (SST) as a lower boundary condition. This constraint hinders uncertainty evaluations that incorporate multiple lower boundary conditions. To address this issue, additional experiments with low-resolution versions of the same model (60-km and 180-km mesh) are a plausible way to quantify uncertainties in the conditions and in resolution dependency (Kitoh et al., 2009). Single-model approaches have been used to attempt to project future climates in Central America and the Caribbean with a GCM (e.g., Angeles et al., 2007) and an RCM (e.g., Campbell et al., 2011; Taylor et al., 2012; Diro et al., 2012), but statistical tests to quantify uncertainties could not be applied in those projections because of limited computer resources. The MME approach with a high horizontal resolution has not yet been used to project future climate in this region, although attempts with GCMs have been made using coarse horizontal resolutions (Giorgi, 2006; Neelin et al., 2006; Rauscher et al., 2008, 2011). In this study, we performed 25-year time-slice experiments using both 20-km and 60-km mesh models and analyzed future hydroclimate changes for Central America and the Caribbean with quantified uncertainty. 2. Model, experiment, and experimental conditions 2.1 Model We developed a global hydrostatic AGCM at the Meteorological Research Institute (MRI) and Japan Meteorological Agency (JMA) based on the JMA short-term, numerical, weather-prediction model (60-km mesh) used operationally in the early 2000s (Mizuta et al., 2006). We modified the operational model for long-term climate simulations at MRI by incorporating a semi-Lagrangian scheme and tuning some of the physical parameterizations. The AGCM has a horizontal grid size of about 20 km, which is implemented with the spectral transform method by using a triangular truncation at wave number 959 with a linear Gaussian grid (TL959); the model has 60 layers in the vertical, with the model top at 0.1 hPa (MRI-AGCM3.1S). The AGCM includes many subgrid-scale parameterizations, the Arakawa-Schubert scheme with prognostic closure for the cumulus parameterization, and the latest JMA-Simple biosphere model for the land biosphere-hydrosphere parameterization. For streamflow, we used the digital river routing network dataset Total River Integrated Pathway (TRIP; Oki and Sud, 1998) as a boundary condition along with the Global River flow model (Nohara et al., 2006; Nakaegawa and Hosaka, 2008). The model is described in detail by Mizuta et al. (2006). 2.2 Experiments We performed time-slice, 25-year simulations for the present-day climate (1979−2003) and the future climate (2075−2099), as indicated in Table 1. For the present-day climate simulations, we used three horizontal resolutions: the original TL959 version (20 km), TL319, and TL95. The latter two correspond to grid sizes of 60 km (MRI-AGCM3.1H) and 180 km (MRI-AGCM3.1L), respectively. As lower boundary conditions for the present-day climate simulations, we used observed monthly SST and sea-ice concentration data (HadISST; Rayner et al., 2003). For the future climate, we made a single, 25-year, timeslice simulation for 2075−2099 by using the 20-km mesh model and assuming SRES scenario A1B. We used as lower boundary conditions the SST data obtained from observed SSTs and the projected SST from the CMIP3 MME dataset. Future hydroclimate changes over Central America and the Caribbean 2014 17 The lower boundary SST dataset comprised three components (Mizuta et al., 2008): the future change in the MME mean SST projected from a multi-model dataset, the trend in the MME mean SST, and the detrended observed SST for the period 1979−2003. The MME consisted of 18 CMIP3 GCMs, which are listed in Table 1 of Mizuta et al. (2008). Future changes in the MME mean SST were determined from the difference between the present-day and future climate simulations under SRES scenario A1B. Those future climate simulations show an El Niño–like pattern of mean changes in SST in the tropical Pacific (IPCC, 2007a). The resulting SST dataset, constructed for future climate simulation, has a higher mean and a clearly increasing trend in SST, but also includes time series of variabilities, including El Niño and La Niña events and the Tropical Atlantic SST dipole. Because El Niño–Southern Oscillation (ENSO) projections are not in agreement among the CMIP3 models in the Fourth Assessment Report (IPCC, 2007a), the use of observed variabilities may be the best possible choice. We obtained the lower boundary sea-ice concentration data in a similar fashion. The climatological global annual mean SST in the future climate increases by 2.16°C. Schematics of the process by which we developed these lower boundary conditions are given by Mizuta et al. (2008) and Kitoh et al. (2009, 2011). We used initial conditions obtained from previous 20-km mesh simulations (Mizuta et al., 2006) for both the present-day and future climate simulations. Spin-up time was 14 months for each simulation. Uncertainty is inherent in current climate change projections. In addition, the pattern of SST increase in the tropics and subtropics influences the regional response of the future climate (Xie et al., 2010; Clement et al., 2010), and the local spatial pattern of SST changes influences the precipitation decreases in Central America and the Caribbean (Rauscher et al., 2011). To quantify the uncertainty in climate change projections, we performed ensemble simulations with the 60-km mesh model. The model ensemble was composed of simulations with four different SST datasets: the MME mean SST and sea-ice concentrations used in the 20-km me
気象研究所が参画する研究プロジェクト「気候変動に伴う極端気象に強い都市創り」（Tokyo Metropolitan Area Convection Study for Extreme Weather Resilient Cities，TOMACS）では，2011年と2012年の夏季を中心に，首都圏における積乱雲の発達環境等を調べる目的でつくばにおいてゾンデ観測を実施した．この観測への利用を図るため，高層気象台で開発された気象観測用ゾンデの飛翔予測プログラム（Aerological Observation Simulation, AOS）について，落下予測精度の検証を行った．館野における2004年から2010年までの夏季（6月～9月）を対象期間とし、9時の高層気象観測のうち落下位置情報が取得されていた728事例について，AOSによる予測落下位置を観測された落下位置と比較したところ，予測と観測の位置ずれは平均としては偏りが小さく，距離誤差の平均は約16kmだった．観測された落下位置の75％は，70％予測楕円内に収まっていた．また、90％近い事例では，落下観測位置が90％予測楕円内にあり、落下範囲の予測はしきい値90％で概ね観測と整合していたといえる．いっぽう，99％予測楕円の中に含まれていた観測落下位置は全体の96％で，予測よりも低い割合にとどまった．70％予測楕円内に落下していた事例が70％以上あったことには，AOSで水平風速の予報誤差を表現するために設定されていた風速のばらつきよりも，計算に用いた数値予報モデルの水平風予報誤差が小さかったことが関係していた．また，観測時に降水のあった事例ではAOSの予測誤差が大きい傾向が見られた． 2011年と2012年の集中観測期間（Intensive Observation Period, IOP）を中心とするゾンデ観測に，AOSプログラムを適用した．この観測では，200g気球を用いて到達高度を現業観測より低い22 km程度とし，下部成層圏での東風の影響を受けにくくすることで，ゾンデ落下域が海上になりやすい設定とした．観測で得られたデータに基づき，AOSにおいて200 g気球使用時に用いる上昇速度・到達高度・降下速度のパラメータの見直しを行なった．その結果，落下予測精度が向上することを確認した．
