樋口 篤志

Third-generation geostationary meteorological satellites (GEOs), such as Himawari-8/9 Advanced Himawari Imager (AHI), Geostationary Operational Environmental Satellites (GOES)-R Series Advanced Baseline Imager (ABI), and Meteosat Third Generation (MTG) Flexible Combined Imager (FCI), provide advanced imagery and atmospheric measurements of the Earth’s weather, oceans, and terrestrial environments at high-frequency intervals. Third-generation GEOs also significantly improve capabilities by increasing the number of observation bands suitable for environmental change detection. This review focuses on the significantly enhanced contribution of third-generation GEOs for disaster monitoring and risk mitigation, focusing on atmospheric and terrestrial environment monitoring. In addition, to demonstrate the collaboration between GEOs and Low Earth orbit satellites (LEOs) as supporting information for fine-spatial-resolution observations required in the event of a disaster, the landfall of Typhoon No. 19 Hagibis in 2019, which caused tremendous damage to Japan, is used as a case study.

Assessing the seasonal patterns of the Amazon rainforests has been difficult because of the paucity of ground observations and persistent cloud cover over these forests obscuring optical remote sensing observations. Here, we use data from a new generation of geostationary satellites that carry the Advanced Baseline Imager (ABI) to study the Amazon canopy. ABI is similar to the widely used polar orbiting sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), but provides observations every 10–15 min. Our analysis of NDVI data collected over the Amazon during 2018–19 shows that ABI provides 21–35 times more cloud-free observations in a month than MODIS. The analyses show statistically significant changes in seasonality over 85% of Amazon forest pixels, an area about three times greater than previously reported using MODIS data. Though additional work is needed in converting the observed changes in seasonality into meaningful changes in canopy dynamics, our results highlight the potential of the new generation geostationary satellites to help us better understand tropical ecosystems, which has been a challenge with only polar orbiting satellites.

A tornado associated with category 5 Super Typhoon Hagibis occurred on October 12, 2019 in Ichihara City, Chiba Prefecture, Japan. An X-band phased array weather radar revealed the occurrence of the tornado at the south edge of its parent cloud, which had several characteristics of a classic supercell (mesocyclone, hook-shaped echo, bounded weak echo region, and vault shape). Phased array radar observation also revealed a three-dimensional multiscale structure of the tornado with a mesocyclone and misocyclone at different altitudes. The misocyclone, the vorticity of which intensified for several minutes under the mesocyclone, resulted in the formation of a tornado and debris ball. The echo top height of the debris ball abruptly increased at the time when the vorticity of the misocyclone maximized at low levels, suggesting a rapid evolution of tornadic vortex and the associated damage on the ground.

This study highlights the severity of the low snow water equivalent (SWE) and remarkably high temperatures in 2020 in Japan, where reductions in SWE have significant impacts on society due to its importance for water resources. A continuous 60-year land surface simulation forced by reanalysis data revealed that the low SWE in many river basins in the southern snowy region of mainland Japan are the most severe on record. The impact of the remarkably high temperatures in 2020 on the low SWE was investigated by considering the relationships among SWE, temperature, and precipitation. The main difference between the 2020 case and prior periods of low SWE is the record-breaking high temperatures. Despite the fact that SWE was the lowest in 2020, precipitation was much higher than that in 2019, which was one of the lowest SWE on record pre-2020. The results indicate the possibility that even more serious low-SWE periods will be caused if lower precipitation and higher temperatures occur simultaneously.

The third-generation meteorological satellites equipped with highly-improved imagers provide a huge amount of Earth observation data. Himawari-8 is the first unit of the Japan Meteorological Agency’s third generation of geostationary satellites. After its starting operation in 2015, there are several websites that provide remotely sensed images in real time. However, it is hard to develop a real-time and full-resolution website, due to the large amount of data to be handled. Himawari-8 real-time web is only one website that provides full-resolution remotely sensed images in real time. To reduce network traffic and increase the access speed of it from other countries out of Japan, mirror websites of each country are needed. In this paper, we propose a cost-effective mirroring system for the Himawari-8 real-time web. A mirroring model is introduced to avoid the problem of big data processing in the mirror websites. We adopt a file copy tool based on high-performance and flexible protocol (HpFP) to transfer meteorological satellite data from the Himawari-8 real-time web to the mirror websites. Our first target is Thailand, one of the most disaster-prone countries in South-East Asia. The mirror website is set up at an institution in Thailand connected via collaborative international networks, e.g., Japan Gigabit Network (JGN) and Asia Pacific Advanced Network (APAN). The results show that the proposed mirroring system is able to overcome the big data issue by reducing the central processing unit (CPU) usage in the mirror website and transferring remotely sensed image files at high speed over international networks even under packet loss conditions. This suggests that our mirroring system has a potential for deployment in other Asian and Oceanian countries.

This study describes a high-speed correction method for geolocation information of geostationary satellite data for accurate physical analysis. Geostationary satellite observations with high temporal resolution provide instantaneous analysis and prompt reports. We have previously reported the quasi real-time analysis of solar radiation at the surface and top of the atmosphere using geostationary satellite data. Estimating atmospheric parameters and surface albedo requires accurate geolocation information to estimate the solar radiation accurately. The physical analysis algorithm for Earth observations is verified by the ground truth. In particular, downward solar radiation at the surface is validated by pyranometers installed at ground observation sites. The ground truth requires that the satellite observation data pixels be accurately linked to the location of the observation equipment on the ground. Thus, inaccurate geolocation information disrupts verification and causes complex problems. It is difficult to determine whether error in the validation of physical quantities arises from the estimation algorithm, satellite sensor calibration, or a geolocation problem. Geolocation error hinders the development of accurate analysis algorithms; therefore, accurate observational information with geolocation information based on latitude and longitude is crucial in atmosphere and land target analysis. This method provides the basic data underlying physical analysis, parallax correction, etc. Because the processing speed is important in geolocation correction, we used the phase-only correlation (POC) method, which is fast and maintains the accuracy of geolocation information in geostationary satellite observation data. Furthermore, two-dimensional fast Fourier transform allowed the accurate correction of multiple target points, which improved the overall accuracy. The reference dataset was created using NASA’s Shuttle Radar Topography Mission 1-s mesh data. We used HIMAWARI-8/Advanced HIMAWARI Imager data to demonstrate our method, with 22,709 target points for every 10-min observation and 5826 points for every 2.5 min observation. Despite the presence of disturbances, the POC method maintained its accuracy. Column offset and line offset statistics showed stability and characteristic error trends in the raw HIMAWARI standard data. Our method was sufficiently fast to apply to quasi real-time analysis of solar radiation every 10 and 2.5 min. Although HIMAWARI-8 is used as an example here, our method is applicable to all geostationary satellites. The corrected HIMAWARI 16 channel gridded dataset is available from the open database of the Center for Environmental Remote Sensing (CEReS), Chiba University, Japan. The total download count was 50,352,443 on 8 July 2020. Our method has already been applied to NASA GeoNEX geostationary satellite products.

We developed a simulation code named WT, which calculates tephra fallout from eruption plumes bent by wind. This proposed model assumes a series of radial particle sources arraying along the theoretically predicted trajectory of the plume center. To validate WT, we reconstructed the tephra dispersal during the 2011 sub-Plinian eruption of Shinmoedake in Japan. This eruption was ideal for the validation because it was observed through various approaches; however, high-resolution data of the fluctuating plume height made it difficult to determine a representative eruption time and plume height for running the simulations. Also, the amount of particle segregation along the plume could not be determined a priori. We thus implemented inversion calculations to study the optimum particle segregation pattern for possible ranges of time and the plume height, and the misfit between the observed and calculated mass loadings on the ground was evaluated. After this process and the following analysis, the optimum eruption time was determined for one of three major explosions (18:00 Japan Standard Time on 26 January). The optimum plume height was estimated to be 4 km above sea level, slightly lower than the estimation derived by the weather satellite (5 km). When wind shear exists, the WT model has a significant advantage in reconstructing tephra dispersal over the classical code named Tephra2, the prototype of WT. The WT inversion implies a simple segregation model from a well-mixed plume, and further studies on particle segregation patterns will help to improve the accuracy of forward WT simulations.

GeoNEX is a collaborative project led by scientists from NASA, NOAA, and many other institutes around the world to generate Earth monitoring products using data streams from the latest Geostationary (GEO) sensors including the GOES-16/17 Advanced Baseline Imager (ABI), the Himawari-8/9 Advanced Himawari Imager (AHI), and more. An accurate and consistent product of the Top-Of-Atmosphere (TOA) reflectance and brightness temperature is the starting point in the scientific processing pipeline and has significant influences on the downstream products. This paper describes the main steps and the algorithms in generating the GeoNEX TOA products, starting from the conversion of digital numbers to physical quantities with the latest radiometric calibration information. We implement algorithms to detect and remove residual georegistration uncertainties automatically in both GOES and Himawari L1bdata, adjust the data for topographic relief, estimate the pixelwise data-acquisition time, and accurately calculate the solar illumination angles for each pixel in the domain at every time step. Finally, we reproject the TOA products to a globally tiled common grid in geographic coordinates in order to facilitate intercomparisons and/or synergies between the GeoNEX products and existing Earth observation datasets from polar-orbiting satellites.

Recent advancements in new generation geostationary satellites have facilitated the application of their datasets to terrestrial monitoring. In this application, geolocation accuracy is an essential issue because land surfaces are generally heterogeneous. In the case of the Advanced Himawari Imager (AHI) onboard Himawari-8, geometric correction of the Himawari Standard Data provided by the Japan Meteorological Agency (JMA data) was conducted using thermal infrared band with 2 km spatial resolution. Based on JMA data, the Center for Environmental Remote Sensing (CEReS) at Chiba University applied a further geometric correction using a visible band with 500 m spatial resolution and released a dataset (CEReS data). JMA data target more general users mainly for meteorological observations, whereas CEReS data aim at terrestrial monitoring for more precise geolocation accuracy. The objectives of this study are to clarify the temporal and spatial variations of geolocation errors in these two datasets and assess their stability for unexpected large misalignment. In this study, the temporal tendencies of the relative geolocation difference between the two datasets were analyzed, and temporal fluctuations of band 3 reflectances of JMA data and CEReS data at certain fixed sites were investigated. A change in the geolocation trend and occasional shifts greater than 2 pixels were found in JMA data. With improved image navigation performance, the geolocation difference was decreased in CEReS data, suggesting the high temporal stability of CEReS data. Overall, JMA data showed an accuracy of less than 2 pixels with the spatial resolution of band 3. When large geolocation differences were observed, anomalies were also detected in the reflectance of JMA data. Nevertheless, CEReS data successfully corrected the anomalous errors and achieved higher geolocation accuracy in general. As CEReS data are processed during the daytime due to the availability of visible bands, we suggest the use of CEReS data for effective terrestrial monitoring during the daytime.

1972年のLandsat衛星打ち上げ以来，人類は宇宙からの目を手に入れた。NOAA AVHRRシリーズによる衛星観測は全球植生モニタリングを可能とした。ここでは水文科学，地球水循環研究において特筆すべき衛星，またはセンサについて俯瞰する。ここで紹介するのは，1）TerraおよびAqua衛星に搭載された光学センサMODIS，2）マイクロ波放射計であるAMSRシリーズ，3）TRMM PR, GPM DPRによる降水レーダ，4）重力観測ミッションGRACE，および5）ひまわり8号，GOES-Rシリーズに代表される第3世代静止気象衛星群である。

In urban areas around the world, air temperature increases due to global warming and urbanization are adversely affecting human health and living environments. We used a numerical weather forecasting model to quantitatively simulate the effectiveness of citizen-driven urban forestry, the voluntary activity of citizens to plant and maintain trees in their residential areas, as a method for reducing summer air temperatures in the Tokyo metropolitan area, the largest urban area in Japan. We calculated the daily maximum air temperature for 10 days in the summer of 2007, and simulated the effects of five different levels of increased urban forest area per capita according to population distribution using albedo, heat capacity, and evapotranspiration. Increasing the forest cover by 3.3 m2 per capita reduced the daily maximum air temperature by only 0.014 °C, although the effect increased linearly with higher forest cover per capita. If forest planting is increased to about 30 m2 per capita, the air temperature reduction in the center of Tokyo could reach 0.4 to 0.5 °C, comparable to the increase in urban air temperature over the past hundred years due to global warming. The results suggest that the collective actions of individual citizens to increase urban forest cover can produce a significant effect on the mitigation of high air temperatures due to the urban heat island effect and climate change.

We introduce a novel rainfall-estimating algorithm with a random-forest machine-learning method only from Infrared (IR) observations. As training data, we use nine-band brightness temperature (BT) observations, obtained from IR radiometers, on the third-generation geostationary meteorological satellite (GEO) Himawari-8 and precipitation radar observations from the Global Precipitation Measurement core observatory. The Himawari-8 Rainfall-estimating Algorithm (HRA) enables us to estimate the rain rate with high spatial and temporal resolution (i.e., 0.04° every 10 min), covering the entire Himawari-8 observation area (i.e., 85°E-155°W, 60°S-60°N) based solely on satellite observations. We conducted a case analysis of the Kanto–Tohoku heavy rainfall event to compare HRA rainfall estimates with the near-real-time version of the Global Satellite Mapping of Precipitation (GSMaP_NRT), which combines global rainfall estimation products with microwave and IR BT observations obtained from satellites. In this case, HRA could estimate heavy rainfall from warm-type precipitating clouds. The GSMaP_NRT could not estimate heavy rainfall when microwave satellites were unavailable. Further, a statistical analysis showed that the warm-type heavy rain seen in the Asian monsoon region occurred frequently when there were small BT differences between the 6.9-μm and 7.3-μm of water vapor (WV) bands (ΔT6.9-7.3). Himawari-8 is the first GEO to include the 6.9-μm band, which is sensitive to middle-to-upper tropospheric WV. An analysis of the WV multibands' weighting functions revealed that ΔT6.9-7.3 became small when the WV amount in the middle-to-upper troposphere was small and there were optically thick clouds with the cloud top near the middle troposphere. Statistical analyses during boreal summer (August and September 2015 and July 2016) and boreal winter (December 2015 and January and February 2016) indicate that HRA has higher estimation accuracy for heavy rain from warm-type precipitating clouds than a conventional rain estimation method based on only one IR band.

It has been almost four decades since the first launch of geostationary meteorological satellite by Japan Meteorological Agency (JMA). The specifications of the geostationary meteorological satellites have shown tremendous progresses along with the generations, which are now entering their third generation. The third-generation geostationary meteorological satellites not only yield basic data for weather monitoring, but also globally observe the Earth’s environment. The development of multi-band imagers with improved spatial resolution onboard the third-generation geostationary meteorological satellites brings us meteorological data in larger size than those of the second-generation ones. Thus, new techniques for domestic and world-wide dissemination of the observational big data are needed. In this paper, we develop a web-based data visualization for Himawari-8 satellite sensed images in real time and with full resolution. This data visualization is supported by the ecosystems, which uses a tiled pyramid representation and parallel processing technique for terrain on an academic cloud system. We evaluate the performance of our techniques for domestic and international users on laboratory experiments. The results show that our data visualization is suitable for practical use on a temporal preview of observation image data for the domestic users.

Summer high temperatures affecting urban areas pose a significant problem to human health. The Japanese megacity, Tokyo Metropolitan Area (TMA) in Kanto region, where significant urban shrinkage is expected to occur in the coming decades, is also vulnerable to such temperature issues. We investigated the impacts arising from changes in land use on future maximum surface air temperature (T-smax) at the regional scale in Kanto region. For our numerical experiments, we introduced surface parameters (i.e., albedo, evapotranspiration coefficient, and heat capacity) into the Japan Meteorological Agency Non-Hydrostatic Model (JMANHM), used for operational weather forecasts in Japan. The impacts were estimated regarding several urban planning scenarios, in which the micro scale afforestation in TMA was considered, i.e., compact-city, dispersed-city, and active afforestation. The obtained results indicated that the afforestation might decrease T-smax, and active afforestation within a compact-city scenario was the most effective for reducing l's, in Kanto region. Our findings also revealed a relatively smaller afforestation impact on T-smax, values in the coastal areas (e.g., Kanagawa) than those affecting inland regions (e.g., Saitama and Tokyo). In coastal areas located upwind of Kanto region, only local afforestation affected T-smax. On the other hand, in inland zones, located on the downwind side of Kanto region, afforestation in both local and upwind areas contributed to a decrease in T-smax. Consequently, the impacts of afforestation were larger in inland areas. (C) 2016 The Authors. Published by Elsevier GmbH.

<p>In this study, we introduce a rain potential map (RPM) that globally estimates rain probabilities every hour. More specifically, we created an RPM by associating the brightness temperature (Tb) of the infrared and water vapor channels observed by five geostationary meteorological satellites (GEO) with rain probabilities observed via rain radar of the Tropical Rainfall Measuring Mission (TRMM). By using our RPM, we improved the accuracy of the Global Satellite Mapping of Precipitation (GSMaP) product, which produces global precipitation data by integrating passive microwave and infrared radiometer data. More specifically, we removed GSMaP rain areas over the ocean in which all microwave sensors were unavailable and rain probabilities according to our RPM were below 14%, which improved the "threat score" of detection in GSMaP from 0.37 to 0.41 over the ocean. Conversely, we added rain areas over land in which all microwave sensors were unavailable and rain probabilities according to our RPM were greater than 37%, which improved the "threat score" of detection from 0.27 to 0.35 over land. Given that a GSMaP "threat score" with microwave observations is approximately 0.44, our improvements here are significant.</p>

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.

Recent advances in remote-sensing technology have enabled estimation of surface solar radiation, which is an important input for land surface models (LSMs). This study investigates the impacts of satellite-derived solar radiation on an LSM by performing sensitivity experiments with and without a satellite-derived solar radiation product known as “EXAM”. Using the LSM “SiBUC-SIMRIW”, land surface analyses over Japan at a 1-km resolution were performed, comparable to observations from flux towers. We demonstrate that using the EXAM solar radiation improves not only the net solar radiation analyses, but also the analyses of net long-wave radiation, sensible heat flux, and latent heat flux at four ground observation sites. This suggests that using the satellite-derived EXAM solar radiation improves the three main budgets, i.e., radiation, heat and water budgets, of the land surface simulation. The findings demonstrate consistent improvements, therefore, SiBUC-SIMRIW-based land surface analyses can be expected to be improved using EXAM. The sensitivity experiments over Japan demonstrate that the change in solar radiation inputs largely affects the simulated sensible and latent heat fluxes. A relatively large change in surface runoff is evident in heavy snowfall regions in winter, which could be caused by a change in the snow melting period.

スリランカにおけるパン蒸発量の長期変動とその要因を考察するため，パン蒸発量と関係する複数の気象要素についてトレンド解析を行った．その結果，1951-1973 年，1974-1993 年の両期間で気候帯によらずパン蒸発量が減少したことが分かった．さらに，（1）スリランカ周辺域のOLR減少，（2）湿潤条件下でのパン蒸発量減少，（3）日照時間の減少，（4）高温下ではPenman式の放射項の寄与が大きいこと，の4点から，少なくとも1974-1993年においては，雲量の増加に伴う日射量の減少がパン蒸発量減少の主因であると結論づけた.

This study developed an algorithm for estimating solar radiation from space using a neural network (NN) with an improved learning algorithm to approximate radiative transfer code. The NN solver for the solar radiation budget is based on radiative transfer calculations. All data sets for testing and training the NN were generated from radiative transfer code. Thus the NN traces the radiative transfer calculation that is approximated by a learning algorithm. To demonstrate the effectiveness of the NN approach for high-speed estimation and multiparameter problems, the NN was applied to data from a geostationary satellite and a Sun-synchronous subrecurrent orbit satellite. The developed algorithm was applied to data from the Multi-functional Transport Satellite-1 Replacement (MTSAT-1R) geostationary satellite, and estimations were validated against in situ observations for March 2006 at four SKYNET sites. Byproducts of the algorithm include UVA, UVB, and photosynthetically active radiation (PAR) fluxes as well as direct and diffuse components. The NN approach enables semi-real-time analysis of these products by high-speed calculation. In addition, the NN allows for consideration of detailed particle optical parameters in the solar radiation budget without the need for a massive database. The method was also applied to observations from the Advanced Earth Observing Satellite-II/Global Imager (ADEOS-II/GLI) for May 2003. The results showed trends in the direct and diffuse components of downward solar radiation over the North Pacific Ocean. This report outlines the construction of the NN for radiation budget estimation and demonstrates the effectiveness of the NN approach.

During the Typical Asian Dust episode from the end of March-early April 2007 (TAD-2007), the mass concentration of suspended particulate matter (SPM) began to increase rapidly on the morning of 1 April in Hokuriku and Tohoku but remained low in Kanto. Ground-level lidar and rawinsonde sounding in Hokuriku observed a dust layer at similar to 2 km corresponding to the base of the temperature inversion. In Kanto, which is leeward of Japan's central mountain ranges, SPM increase began from the east coast and then advanced westward after 18 JST with easterly winds. Merged CloudSat and CALIPSO datasets indicated that clouds over mainland Japan and the Sea of Japan were located in the upper-level atmosphere (&gt; 6 km). Continuous meteorological observations showed that cloud condensation and rainfall were not observed over the mountains during the daytime of 1 April. These results suggest that the delay in the SPM increase in Kanto was caused by dust being indirectly transported to that region by flowing around the central mountains.

To confirm the structure of convective circulation in the atmospheric boundary layer (ABL) over the northwestern Pacific Ocean around the Southwest Islands of Japan under a subtropical high, we perform intensive observations using radiosonde and Aerosonde in August 2002 and high-resolution three-dimensional numerical simulations. A well-mixed subcloud layer exists below 0.7 km during the observation period. The absolute values of the correlation coefficient between anomalies in potential temperature and mixing ratio of water vapor are mainly small (less than 0.3) in the lower subcloud layer. The frequency of a positive correlation coefficient at a height of 0.1 km is only 46%. This suggests that fewer warm moist thermals exist in the lower subcloud layer. The simulation results using 100-m horizontal grid resolution show a moist air mass in updraft regions. These thermals are driven by positive buoyant flux, and this positive buoyancy is contributed by moisture, i.e., density anomalies in water vapor and dry air, instead of heat. This should be attributed to the supply of small sensible and abundant latent heat fluxes from the sea surface under the small air-sea temperature difference.

人間社会の活動に特化した空間として発展した都市は無秩序な拡大をしてきたために様々な問題を生み出しており，その問題の一つとして都市部ではヒートアイランド現象（Urban Heat Island Phenomenon）が深刻化している。このヒートアイランド現象は真夏日・熱帯夜の日数を増加させるだけではなく，集中豪雨の日数増加に間接的な影響を与えることも示唆されている。 そこで，本研究では東京都および埼玉県南部の計51市区町村を研究対象地域とし，レーダー・アメダス解析雨量を用いることにより都市の熱環境と都市構造が近年増加傾向にある都市の対流性降雨に与える影響の評価を行った。ここで，使用した都市構造パラメータは熱的特性値，人工排熱，緑被率，海からの平均距離，平均標高，建物構造パラメータ，水域面積の割合である。 結果，昼間において30mm/h以上の降雨回数と各都市構造パラメータとの間には熱的特性値，建物高度，粗度，人工排熱，緑被率，海からの平均距離において相関関係が見られた。また，夜間においては降雨回数と各都市構造パラメータの明確な関係を確認することは出来なかったが，レーダー・アメダス（30mm/h以上の降雨回数）の空間分布により，西方の降雨回数が東に移動し研究対象地域に降雨をもたらしている様子が見て取れた。

Tropical Rainfall Measuring Mission (TRMM) data during June-August 1998-2003 are used to investigate diurnal variations of rain and cloud systems over the tropics and midlatitudes. The peak time of the coldest minimum brightness temperature derived from the Visible and Infrared Scanner (VIRS) and the maximum rain rate derived from the Precipitation Radar (PR) and the TRMM Microwave Imager (TMI) are compared. Time distributions are generally consistent with previous studies. However, it is found that systematic shifts in peak time relative to each sensor appeared over land, notably over western North America, the Tibetan Plateau, and oceanic regions such as the Gulf of Mexico. The peak time shift among PR, TMI, and VIRS is a few hours. The relationships among the amplitude of diurnal variation, convective frequency, storm height, and rain amount are further investigated and compared to the systematic peak time shifts. The regions where the systematic shift appears correspond to large amplitude of diurnal variation, high convective frequency, and high storm height. Over land and over ocean near the coast, the relationships are rather clear, but not over open ocean. The sensors likely detect different stages in the evolution of convective precipitation, which would explain the time shift. The PR directly detects near-surface rain. The TMI observes deep convection and solid hydrometeors, sensing heavy rain during the mature stage. VIRS detects deep convective clouds in mature and decaying stages. The shift in peak time particularly between PR (TMI) and VIRS varies by region.

We investigated the diurnal variation of water vapor mixing between the atmospheric boundary layer (ABL) and the free atmosphere over the Loess Plateau in China. Water vapor and wind velocity in the troposphere were observed using a ground-based microwave radiometer and a wind profiler radar in 2005 and 2006. On sunny days in early summer, a strong vertical wind was generated in the afternoon followed by ABL development. Strong convection was enhanced when active cumulus convection developed in the afternoon. In such cases, water vapor decreased in the lower atmosphere from the early morning until late afternoon, while water vapor increased in the upper atmosphere. This finding suggests that water vapor was exchanged diurnally between the ABL and the free atmosphere. The strong convection in the ABL, which was developed by sensible heat from the land surface, played critical roles with link to cumulus convection in such vertical mixing of water vapor. Influences of other processes such as a local circulation and advection of cloud systems were also discussed.

Observations of the surface layer and the atmospheric boundary layer (ABL) were collected as part of the Lower Atmosphere and Precipitation Study (LAPS), which investigated the relationship between the surface conditions and the ABL processes. The LAPS was part of the Core Research for Evolutional Science and Technology (CREST) program, under the auspices of the Japan Science and Technology Agency (JST). Observations began in August 2003 over a flat surface region in mid-latitude China at 32·55°N, 116·78°E. Observations before, during, and after the Meiyu season in China provided data for surface conditions varying from relatively dry to moist. Preliminary analysis of the surface and the ABL observations shows relationships between the surface fluxes and the ABL structure. ABL depth was enhanced by sensible heat flux. Fluctuations in the ABL depth corresponded to plume-like wind structures within the ABL. Day-to-day variability in ABL depth was controlled mainly by buoyancy flux over the surface during dry periods. It was also affected by vertical motion at the top of the ABL, especially during wet periods.

Satellite remote sensing of surface-related variables is essential for understanding regional or global land-surface processes. This study focuses on a Temperature/Vegetation Index (TVX) matrix that combines surface temperature (Ts) and a normalized difference vegetation index (NDVI). The results of our study show the behaviour of the TVX matrix on continental scales. The study domain includes eastern Eurasia and monsoon Asia-regions with great variability in land-surface conditions. The data used included a 10-day composite Advanced Very High Resolution Radiometer (AVHRR) dataset compiled by the US Geological Survey (USGS). The relaxation in the determination algorithm for TVX slope (an upper envelope line in a TVX matrix box) was conducted to obtain both the negative and positive slope. The TVX slope can be derived from previous studies as the monsoon advanced and retreated over the tropics. However, over the Tibetan Plateau, a time series of the TVX slope showed an opposite sign compared to those in previous studies (represented by a positive TVX slope). Scatter plotting of the TVX matrix pixel sets was conducted for the evaluation of a variety of TVX matrix pixels. The TVX slope error sometimes occurred over arid regions because of a few green pixels corresponding to oases or irrigated areas. On the Tibetan Plateau, ‘two’ TVX slopes, both negative and positive, were found in the scatterplot. The reason for the two TVX slopes is the energy consumption in the soil, particularly, the phase change from frozen to liquid water. However, further study will be required to understand the mechanisms on the Plateau.

本学会の研究グループ「水文過程のための最新リモートセンシング技術とその応用に関する研究」の活動について報告する。

The characteristics of winter precipitation systems over the northwestern Pacific are analyzed using data from multiple sensors on board the Tropical Rainfall Measuring Mission (TRMM) satellite. Using the Precipitation Radar (PR) and the Visible Infrared Scanner (VIRS), vertical and horizontal distribution of precipitation is investigated and compared with microwave signatures measured by the TRMM Microwave Imager (TMI). Winter precipitation patterns are classified into four types by the cloud and pressure pattern and the region: the extratropical cyclone and front pattern (CF) and the cold outbreak pattern (CO) over the Sea of Japan (CO-J), over the Yellow Sea (CO-Y), and over the Pacific Ocean (CO-P). For CO the height of precipitation is centered around 2 km and shallow, isolated, and weak (∼20 dBZ) precipitation dominates. Cloud top height reaches about 4 km. Compared with CO-Y and CO-J, CO-P tends to develop larger systems and to have melting layers near the surface. For CF the height of precipitation is concentrated around 3 km and precipitation is relatively broad with a large variation of intensity. These characteristics explain the differences between the retrieved rain rate by PR and TMI. TMI frequently misses precipitation for CO because the systems are usually shallow but less frequently misses weak precipitation than PR for CF because of emission from 85 GHz channel. When both PR and TMI detect rain, the PR rain rate is larger than TMI for CO and smaller than TMI for weak precipitation for CF. From the microwave signature for each pattern it was suggested that the size of precipitation system is one of the possible cause of the differences of rain estimation and detection.

Cloud systems over the Maritime Continent and the tropical western Pacific defined by the Geostationary Meteorological Satellite (GMS) were tracked, and their evolution was compared with cloud parameters [e.g., minimum blackbody brightness temperature (TBB), cloud area size, TBB gradient at cloud edges]. In addition, cloud systems observed by the Tropical Rainfall Measuring Mission (TRMM) were examined, and the relationship with precipitation was investigated. Analysis areas were divided into four regions: open ocean, coastal sea, coasts, and land. Cloud systems that did not split from or merge with other systems (28% of a total of 290 717 cloud systems) showed common features on cloud parameters in spite of different lifetimes or their locations. While the minimum TBB appeared in the beginning of their lifetimes, the cloud area was still expanding. At the time of first detection, the TBB gradient at the edge of the cloud system was the maximum and decreased with time. The rain rate was maximized when the TBB was at a minimum or earlier. For example, a system with the lifetime of 5 h over the ocean has a minimum TBB 2 h after the occurrence, a maximum area at 3 h, a maximum TBB gradient at 1 h, and a maximum rain rate at 1 h. Vertical development was significant in coasts, while remarkable horizontal expansion appeared over land. In particular, precipitation ice and storm height profiles showed differences among regions.

熱帯降雨観測衛星 (Tropoical Rainfall Measuring Mission：TRMM) に搭載されている降水レーダー (Precipitation Radar：PR) は，現在ある全球降水量マップ (例えば，Global Precipitation Climatology Project (GPCP)等) に比べ，水平分解能が細かいため流域単位での詳細な降水量分布の把握が可能である．本研究では分水嶺付近の降水量分布の特性に関して，東南アジア領域を流れるイラワジ川流域，メコン川流域に着目し，4年季節平均を施したTRMM-PR データを使い解析を行った. その結果以下のことが明らかになった．1)．下層風と地形の交わり方が降水量に与える影響を調べた結果，下層風が地形と直交する場合に降水量が最も多かった．また平均降水頻度，降水量，降水強度は，すべてのType で標高依存性を示した．2)．標高・降水量の横断図解析から，降水量は地形の隆起が起こるより風上側から増加し，分水嶺の風上側で最大降水量を示す．山岳地域では， 降水量のピークは谷地形の位置と良い一致を示した．3)．風上側と風下側の降水量の差を規格化した指数，IPDD (Index of Precipitation Distribution over the Divide) と分水嶺の標高との関係が得られたが，同時に季節性，地域性も認められた．しかし， この結果から，バリア効果のように降水量分布の特徴を分ける分水嶺の標高の閾値があると言える．4)．本研究では，解析対象領域全体の分水嶺効果を表す一般的な関係を提示することはできなかった．しかし，本研究で算出されたIPDD は，水平分解能が粗い全球降水量マップから流域内降水量を推定する際応用可能な指標となり得ると思われる.

The eddy covariance and energy balance method was employed to determine evapotranspiration (LE) over a wet temperate C3–C4 co-existing grassland in Japan. After sensible heat flux (H) was estimated via the eddy covariance technique, LE was calculated as the residual of the energy budget with calibration against the direct measurements of LE by a lysimeter. Daily mean LE varied from 0·8 to 10·5 MJ d−1, with a peak at 16·5 MJ d−1 in late July to early August. Day-to-day and seasonal variability in LE was affected appreciably by net radiation (Rn), atmospheric vapour pressure deficit (VPD), canopy surface conductance (gc) and leaf area index (LAI). Before the canopy closure, LE responded to LAI in a linear manner. However, LE decreased with increasing LAI later in summer. Daytime variation in the decoupling coefficient (Ω) demonstrates that the canopy decoupled from the atmosphere in the morning and LE was primarily driven by the available energy, while in the afternoon the canopy partially coupled to the atmosphere so that LE was sensitive to VPD and gc. Throughout the whole measurement period, Ω was generally larger than 0·5, suggesting that the available energy contributes more to LE than VPD.

滋賀県北部の水田地帯で，面的に観測点を配置した乱流観測を含む集中観測が2002年11月に行われた．この観測は，16点の乱流観測・ゾンデ・2点のソーダ・4台のシンティロメータ・航空機からの熱画像計測からなる大規模かつ集中的なものである．ここではその概要を述べる．

計測機種の違いによる乱流フラックスの誤差を評価するため，植生活動が活発で潜熱輸送量が大きい2001年5月14日～6月1日に筑波大学陸域環境研究センター(TERC)の観測圃場(草地)において乱流計測機の相互比較観測を行った．まず，赤外線カメラによって測定された地表面温度分布を測定し，加えてfootprint解析を行い，3m離れた2点の超音波風速温度計による顕熱フラックスとそれらのfootprintの地表面温度との対応関係を風向別に調べた．その結果，第1近似として両者の有意な相関は見られなかったので，風上地表面が一様である前提で乱流変動量の標準偏差と共分散(フラックス)を用いて比較を行った. 超音波風速温度計(DA-600, GILL-R3, ATI-SATI)に関しては全ての計測機間で出力特性が良く一致した．一方，水蒸気/CO2変動計については，特にLI-7500やOP2のデータが安定しており，湿度温度計などに対して平均値同士の簡便な再校正を施せば誤差を減らすことができた．計測機の違いによるフラックスの過小評価は見られなかったが，ダイナミックキャリブレーションを行う上で，校正を行う帯域において相関係数が低い場合，フラックスの過小評価を招く可能性が高いことが示唆された.

For the first time in India, an L-band (1357.5 MHz) lower atmospheric wind profiler (LAWP) has been installed and successfully operated at Gadanki, India, since September 1997. The first results of the accuracy can be given on the basis of about 24-day intercomparisons between LAWP and mesosphere-stratosphere-troposphere radar data. The root-mean-square differences (RMS deviation) have been found to range between 1.18 m/s and 1.6 m/s for the wind speed. The two wind profilers compliment each other quite well, considering both the availability and the reliability of the wind measurements. Statistics of the data availability can be shown based on 775 days of data in low mode and about 532 days of data in high mode. The 80% availability of the LAWP was determined with 3.6-km wind measurements in low mode and 5-km wind measurements in high mode. LAWP observations show well-marked planetary boundary layer diurnal variation on clear sunny days. We found that with a few exceptions the drier period has a higher boundary layer compared with the wet period, indicating that in the wet season, most of the net solar radiation evaporated moisture rather than heating the surface and therefore contributed little to buoyant forcing. We classified precipitating clouds into three types: convective, transition, and stratiform. Diurnal and seasonal variation of the occurrence of precipitating cloud systems shows that the precipitation primarily occurs in the afternoon and the convective and transition clouds are most frequent in the summer monsoon, while the occurrence of stratiform clouds is predominant in the winter monsoon.

タイを対象として雨季と乾季の季節変化に対する地表面湿潤度とフェノロジーの時間的応答を調べた.使用するデータとして,USGSからGlobal Land 1-km AVHRR Data Setを,NCDCから気象ステーションのデータを得た.広域のフェノロジーの情報はNOAA/AVHRRデータから算出したNDVIから得た.またVI-Ts法を用いて地表面湿潤度の季節変化を得た.そして,降水量,地表面湿潤度,そしてNDVIの時系列との間で比較を行なった.その結果,乾季から雨季へ移る期間において,十分な降雨が認められた日(124±21DOY),地表面が十分に湿潤になる時期(123±53DOY),更に植物の成長や活性が高まる時期の時間差が認められた.地表面が十分に湿る日に関しては土地被覆の違いによる時間差は認められなかったが,植物の成長や活性が高まる日に関しては森林(153±43DOY)と農地(170±46DOY)の間に時間差が得られた.一方,NDVIの変化からみて雨季から乾季へ移り変わる時期は,農地と森林の変化に差が見られた.農地では乾季に入ってすぐに変化が見られる一方,森林ではしばらくして生じる地上面湿潤度の低下につれてNDVIの変化が生じることがわかった.

For the purpose of estimating land surface fluxes over a large area, use of remote sensing techniques is and will be essential. Particularly, “in situ” collection of ground truth data has been a very important task for the development of satellite oriented “algorithms”. In this study, we observed “a patch scale” visible and near infrared spectral reflectance, which is obtainable from satellites, and land surface fluxes during and post-growing season at grassland and paddy field: Seasonal trends at grassland and at paddy field were quite different, because of the differences in water as well as growing environment. A good direct correlation was found between vegetation index (NDVI) and surface resistance during the growing season at grassland. A similar result was confirmed between NDVI and surface resistance at paddy field.