Spatial-temporal fractions verification for high-resolution ensemble forecasts

Experiments with two ensemble systems of the resolutions of 10 km (MF10km) and 2 km (MF2km) were designed to examine the value of cloud-resolving ensemble forecast in predicting small spatiotemporal-scale precipitation. Since the verification was performed on short-term precipitation at high resolution, uncertainties from small-scale processes caused the traditional verification methods inconsistent with the subjective evaluation. An extended verification method based on the Fractions Skill Score (FSS) was introduced to account for these uncertainties. The main idea is to extend the concept of spatial neighborhood in FSS to the time and ensemble dimension. The extension was carried out by recognizing that even if ensemble forecast is used, small-scale variability still exists in forecasts and influences verification results. In addition to FSS, the neighborhood concept was also incorporated into reliability diagrams and relative operating characteristics to verify the reliability and resolution of two systems. The extension of FSS in time dimension demonstrates the important role of temporal scales in short-term precipitation verification at small spatial scales. The extension of FSS in ensemble space is called ensemble FSS, which is a good representative of FSS in ensemble forecast in comparison with FSS of ensemble mean. The verification results show that MF2km outperforms MF10km in heavy rain forecasts. In contrast, MF10km was slightly better than MF2km in predicting light rain, suggesting that the horizontal resolution of 2 km is not necessarily enough to completely resolve convective cells

Geostationary satellite data assimilation in mesoscale forecast systems : A review

This article reviews the current status and ongoing developments in assimilating so-called next generation geostationary satellite data into mesoscale numerical weather forecast systems. While increased quality and quantity of data have brought unprecedented opportunities for data assimilation (DA) to improve initial conditions of mesoscale forecasts, taking full advantage of these high-resolution data, including cloud and precipitation affected weather observations is a challenge for current DA systems. We overview some key issues in the development of the effective utilization of geostationary satellite data in mesoscale forecasts

Extension of the SAL method for verification of high resolution ensemble forecasts

近年の観測データを用いた研究から、風成海洋循環の変動に伴う黒潮続流域での海洋前線の南北シフトが、 海洋から大気への熱的な強制の変動を通じて、海盆ス ケールの大気循環変動に影響を与る可能性が示唆され ている (Frankignoul et al. 2011, Taguchi et al. 2012)。 しかし既往研究で採用された診断的な解析手法では、 海洋前線変動の大気への影響の因果関係を直接的に明 らかに出来ないため、大気大循環モデルに海洋前線ス ケールの海面水温 (SST) 偏差を与える感度実験が、国 内外で精力的に実施されている (例えば Okajima et al. 2014)。本研究では、このような海洋前線変動に対する 大気応答実験を大気海洋結合モデルを用いて行うこと により、より現実的な条件の下での海洋前線変動に対 する大気応答を調べ、究極的には、そのような大気応 答の海洋への再影響を評価することを目的とする。P3a3 Meteorological Society of Japan (日本気象学会) Autumn meeting 2012 (3-5 October 2012, Hokkaido University

Numerical Simulation on Retrieval of Meso-γ; Scale Precipitable Water Vapor Distribution with the Quasi-Zenith Satellite System (QZSS)

A simulation study was conducted to investigate the retrieval of meso-γ scale precipitable water vapor (PWV) distribution with the Quasi-Zenith Satellite System (QZSS) using output from a non-hydrostatic model (JMA NHM). The evaluation was performed on PWV values obtained by simulating three different methods: using all GPS satellites above an elevation angle higher than 10° (PWVG) (conventional Global Navigation Satellite System (GNSS) meteorology method), using only the QZSS satellite at the highest elevation (PWVQ), and using only the GPS satellite at the highest elevation (PWVHG).  The three methods were compared by assuming the vertically integrated water vapor amounts of the model as true PWV. As a result, the root mean square errors of PWVG, PWVQ, and PWVHG were 2.78, 0.13, and 0.59 mm, respectively, 5 min before the rainfall. The time series of PWVHG had a large discontinuity (˜ 2 mm) when the GPS satellite with the highest elevation changed, while that of PWVQ was small because the elevation at which the highest QZSS satellites change was much higher. The standard deviation of PWVQ was smaller than those of PWVG and PWVHG, which vary significantly depending on GPS satellite geometry.  When the spatial distributions of PWVG and PWVQ were compared to the meso-γ scale distribution of the reference PWV, PWVG smoothed out the PWV fluctuations, whereas PWVQ captured them well, due to the higher spatial resolution achievable using only high-elevation slant paths. These results suggest that meso-γ scale water vapor fluctuations associated with a thunderstorm can be retrieved using a dense GNSS receiver network and analyzing PWV from a single high-elevation GNSS satellite. In this study, we focus on QZSS, since this constellation would be especially promising in this context, and it would provide nearly continuous PWV observations as its highest satellite changes, contrary to using the highest satellites from multiple GNSS constellations