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The authors improve the high-resolution Global Satellite Mapping of Precipitation (GSMaP) product for Typhoon Morakot (2009) over Taiwan by using an orographic/nonorographic rainfall classification scheme. For the estimation of the orographically forced upward motion used in the orographic/nonorographic rainfall classification scheme, the optimal horizontal length scale for averaging the elevation data is examined and found to be about 50 km. It is inferred that as the air ascends en masse on the horizontal scale, it becomes unstable and convection develops. The orographic/nonorographic rainfall classification scheme is extended to the GSMaP algorithm for all passive microwave radiometers in orbit, including not just microwave imagers but also microwave sounders. The retrieved rainfall rates, together with infrared images, are used for the high-resolution rainfall products, which leads to much better agreement with rain gauge observations., 資料番号: PA1410041000

[ABSTRACT]During massive Asian dust episode for 1-2 April 2007, mass concentration of suspended particulate matter (SPM) rapidly began to increase in the morning on 1 April from coastal side of the Japan Sea. For the daytime 1 April, while rapid SPM increase and extreme high concentrations observed in Hokuriku and Tohoku, SPM concentrations in Kanto remained low level and increased from late afternoon. Ground lidar observation and rawinsonde sounding in Hokuriku show that the top height of dust layer (~ 2 km) approximately correspond to the base of temperature inversion. In Kanto, SPM increase began from east coast and then it advanced westward after 15 LT with easterly wind. The CloudSat/CPR and CALIPSO/CALIOP observations show that clouds over mainland Japan and the Japan Sea was found in the upper-level (> 6 km). Continuous meteorological observations show that cloud condensation and rainfall was not observed over mountains for the daytime 1 April. These results suggest that the temporal delaying of SPM increase in Kanto was caused by an indirect dust transport.

[ABSTRACT]Global distributions of cloud largely effect earth radiation budgets. The heating / cooling effect differs depending on a type of cloud due to the differences of the characteristics of radiative process. Thus, it is important to understand cloud distributions classified into some cloud types. A cloud type classification method has been developed using multiple bands in visible and infrared using geostationary satellite. However, it was hard to classify the cloud types because of limit of information from optical thickness and cloud top height. In 2006, Cloudsat satellite carrying the Cloud Profiling Radar (CPR) was launched, and its observation enables us to find vertical distributions of cloud globally. This study tried to characterize cloud / precipitation characteristics and classify cloud types from vertical distributions of clouds observed by Cloudsat CPR. This study applied a base of vertical-method of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) 2A23 algorithm to the vertical distributions of reflectivity factor (Z) from CPR in order to detect the bright band height (BBH) and cloud types. The detected BBH exists under 250-500 m from freezing height derived from a re-analysis data. The cloud types were classified into convective with large Z, stratiform with BBH, and others. In this presentation, we will also report the characteristics of global cloud distributions with / without precipitation, with shallow or anvil, and so on.

[ABSTRACT]SW radiation budget is estimated using geostationary satellites (GMS-5, GOES-8, GOES-10, METOSAT-5, METEOSAT-7). Each satellite data are calibrated, and optics properties of the cloud are retrieved. An accurate calibrated data propose the better accuracy for analysis of cloud and radiation budget. In this study, cloud and SW radiation budget analysis are done by CAPCOM algorithm and EXAM SYSTEM. On the other hand, aerosol optical thickness is retrieved by L-REAP algorithm. We discuss the possibility of aerosol-cloud-radiation interaction in north Pacific ocean and north Atlantic ocean.

[ABSTRACT]The climatological features of the diurnal cycle of cloudiness were investigated over three convective centers of interest over South Asia: over the Himalayas; north India and the Bay of Bengal (BOB). Three hourly blackbody brightness temperature (TBB) data from the METEOSAT-5 and rainfall data (3B42) from the Tropical Rainfall Measuring Mission (TRMM) were utilized. Analysis was concentrated on pre-monsoon and the summer monsoon season. Two methods were used to detect cloudiness: one method counted cloud clusters (CC) and utilized cloud tracking technique to identify time clusters (TC); and the other method computed cloud cover frequency (CCF). CC was defined as a contiguous area of pixels with TBB lower than the threshold of 219 K. The CCF was derived using 235 K as the threshold. From the analysis, it was noted that there were many CC over north India in the pre-monsoon season especially during the late afternoon hours. But deep convective activity was weaker over the region during the summer monsoon season. Bimodal diurnal cycle in CC occurrence was noted over the Himalayas during the summer monsoon season. It was noted that the peak convective activity occurred at 6 LT for the Bay of Bengal during both the summer monsoon and the pre-monsoon season. The life cycle of cloud clusters during summer monsoon season was also investigated. The diurnal cycle varied with location. There appeared a gradual delay in the preferred time of initiation, attainment of maximum area and dissipation as one progresses northward from BOB region through north India to the Himalayas.

[ABSTRACT]In this study, we develop a vicarious calibration technique and estimation algorithm of radiation budget for the global analysis. The vicarious calibration technique using three components ( clear sky sea surface, clear sky land surface, uniform cloud top) is applied to the geostationary satellites. This vicarious calibration technique is based on radiative transfer calculations and it has each optical properties (aerosol, cloud, surface BRDF/albedo) in three compon_~ntsT. he quality of three geostationary satellites (GMS-5, GOES-10, GOES-8) visible channel fixed accurately for global analysis. An accurate calibrated data set propose the better accuracy for analysis of cloud and radiation budget. Thus, cloud and radiation budget analysis algorithm are applied to new calibrated data set for global analysis. This is first result of trial for global analysis.

[ABSTRACT]Horizontal distributions of explosively developing extratropical cyclone formed and developed in Northwestern Pacific Ocean in precipitation, water vapor, cloud liquid water, and surface wind fields are analyzed using the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) on Aqua Satellite dataset in recent 7 winter seasons. Cyclone center-relative compositing mean fields are constructed for four life stages: 1) developing, 2) maximum deepening, 3) minimum center sea level pressure (SLP), and 4) decaying. These stages are distinguished by a value and a kind of differentiation in center SLP using a database of cyclone tracking derived from a reanalysis dataset. The developing processes of the composited cyclone are documented. In developing stage, the・ water vapor pass (WVP) has south-north (high-low) contrast corresponding to the temperature distribution. Corresponding to the cold-dry air mass advections, WVP concentration starts from western part of the cyclone center in the maximum deepening stage. The concentration is distinct along the cold front in the minimum SLP stage. The horizontal distributions at the maximum deepening stage agree with the previous study using global objectively analyzed dataset (GANAL). As the deepening rate is larger, the value and concentration is higher and stronger. Precipitation appears around_ the root of front corresponding to large cloud liquid water, while there is no precipitation near the cyclone center in minimum center SLP and decaying stages regardless of the strength.

[ABSTRACT]The characteristics of backscattering coefficients ( cr0 ) observed by the Tropical Rainfall Measuring Mission (TRMM) / Precipitation Radar (PR) were investigated,for different vegetation covers; evergreen broadleaf forests ( ebf), woody savannas, savannas, open shrublands, and grasslands in Africa. For ebf, cr0 decreases rapidly from nadir to 3 °, then the rest of the angles are constant. On the other hand, cr0 gradually decreases from nadir to 17° for savannas, open shrublands, and grasslands. For woody savannas, cr0 value for each angle bin in the dry season is similar to that for savannas, but the characteristics of cr0 in the rainy season is similar to that for ebf. The maximum monthly mean precipitation corresponds to that of cr0 at nadir and 17° for grasslands and savannas. For grasslands, cr0 at 3 ° does not increase that is likely to be saturated from the dry season to the rainy season when Leaf Are Index (LAI) is more than 0.5. Seasonal variations of cr0 do not clearly correspond to that of precipitation for ebf where LAI is more than 3. It implies that cr0 at 3° is susceptible to vegetation canopy. It suggests that the combination of 3 ° and 17° of cr0 enable to classify vegetation land covers.

[ABSTRACT]Primary function of Center for Environmental Remote Sensing (CEReS) is to provide satellite dataset such as GMS, MTSAT-IR, and NOAA/AVHRR for research community. We started data archive system (DAS) re-construction since 2005. New DAS based on PC servers and RAID storages with Free Operi Source Software (FOSS). Such configuration changes allow us to easy-expansion of DAS and random data access via 1intemet, thus downloaded files by users have been increased since 2005. In addition, activities of Virtual Laboratory (VL) for diagnosing the climate system accelerate the volume of archived satellite data since 2007. Our primary task in VL is collection and utilizations of geostationary meteorological satellites, thus we re-process raw full-disk data into grided format (after geometric correction) and open through the internet. Such data processing is not only contributed to VL also related communities. We will play an important role as one of data active archive center (DAAC) in Asia for satellite and related dataset.

[ABSTRACT] A long-term accumulated observation data is expected to diagnose the climate study statistically. Although rain gauge data has been mainly utilized for rainfall climatology, satellite rainfall products combining data obtained by microwave radiometers (MWRs) in low Earth orbit and by infrared radiometers (IRs) such as the Global Precipitation Climatology Project (GPCP) are available since late 1970s. However, spatiotemporal resolution is rough (2.5 ° in latitude-longitude grid and 1 monthly) and the quality is not fully enough. Owing to sparse satellite MWR observations, rainfall is mainly estimated from IR. The great success of the Tropical Rainfall Measuring Mission (TRMM) accelerated development of the rain retrieval algorithm for MWR. High spatiotemporal resolution satellite rainfall products (0.1 °-0.25 ° in latitude-longitude grid and 0.5-3 hourly) have been available after the Tropical Rainfall Measuring Mission (TRMM) launch since 1998. The development of the rain retrieval algorithm combined MWRs and IR is enabling us to provide rainfall climatology using satellite rainfall data before the TRMM launch (-1998, pre-TRMM era). In this study, a prototype of GSMaP rainfall data in pre-TRMM era is constructed. Surface rainfall in 1987-1999 is estimated by the latest version of GSMaP MWR algorithms using the Special Sensor Microwave Imager (SSM/I) onboard Defencse Meteorological Satellite Program (DMSP) satellites F8, F10, F11, F12, F13, and F15. The Japanese-55-year Reanalysis data is used for atmospheric variables instead of the Global Analysis (GANAL). The 27 years of prototype GSMaP data may stand up to rainfall climate study. In this presentation, a time series and horizontal distributions of monthly-accumulated GSMaP rainfall will be compared with other satellite rainfall products. In pre-TRMM era, the geostationary meteorological satellite data is more important to estimate rainfall precisely because the MWRs observation is scarse.

7, KJ00007495720, P, 論文, Article