著者
OTSUKA Shigenori KOTSUKI Shunji OHHIGASHI Marimo MIYOSHI Takemasa
出版者
Meteorological Society of Japan
雑誌
気象集誌. 第2輯 (ISSN:00261165)
巻号頁・発行日
pp.2019-061, (Released:2019-09-03)
被引用文献数
1

Since January 2016, RIKEN has been running an extrapolation-based nowcasting system of global precipitation in real time. Although our previous paper reported its advantage of the use of data assimilation in a limited verification period, long-term stability of its forecast accuracy through different seasons has not been investigated. In addition, the algorithm was updated seven times between January 2016 and March 2018. Therefore, this paper aims to present how motion vectors can be derived more accurately, and how data assimilation can constrain an advection-diffusion model for extrapolation stably for the long-term operation. The Japan Aerospace Exploration Agency's Global Satellite Mapping of Precipitation (GSMaP) Near-Real-Time product is the only input to the nowcasting system. Motion vectors of precipitation areas are computed by a cross-correlation method, and the Local Ensemble Transform Kalman Filter generates a smooth, complete set of motion vectors. Precipitation areas are moved by the motion vectors up to 12 hours, and the product, called “GSMaP RIKEN Nowcast”, is disseminated on a webpage in real time. Most of the algorithmic updates were related to better estimating motion vectors, and the forecast accuracy was gradually and consistently improved by these updates. Particularly, the threat scores increased the most around 40°S and 40°N. A performance drop in the northern hemisphere winter was also reduced by reducing noise in advection. The time series of ensemble spread showed that an increase in the number of available motion vectors by a system update led to a decrease in the ensemble spread, and vice versa.
著者
Pavetti Infanzon Alicia Tanaka Kenji Kotsuki Shunji Tanaka Shigenobu
出版者
水文・水資源学会
巻号頁・発行日
pp.100006, 2014 (Released:2014-12-01)

Paraguay had dense forest cover until the 1970s but due to agricultural expansion, the country lost almost two thirds of its Atlantic forest (Huang et al., 2007). Such landscape transformation is believed to influence regional climate because it alters surface-atmosphere interactions . This research aims to reproduce past surface parameters for Paraguay and apply them to investigate the impacts of land use change in November rainfall. For this, the AVHRR NDVI data series (1981-2006) and SPOT Vegetation product (1999-current) were correlated to adjust the AVHRR product in order to reduce sampling errors. These surface parameters, along with vegetation scenarios for the 1990s and 2000s, were then used in meso-scale numerical weather prediction model (CReSiBUC) to perform two sets of simulations for November 2006 -2011 to assess the potential regional impacts of land cover change on precipitation during November and the mechanisms that may lead to variations in regional climate.