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Use of moisture sensitive satellite radiances in the Canadian Meteorological Centre Unified 3D-var system

机译:在加拿大气象中心统一3D-VAR系统中使用水分敏感卫星辐射

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The Canadian Meteorological Centre's (CMC) three Dimensional Variational (3D-var) is an incremental analysis system that is currently used by both our global and regional models with very little modifications. During the last few years, it has undergone a series of upgrades from isobaric to a terrain-following coordinate, and most importantly the direct assimilation of satellite radiances. The quality control (QC) of observations was also upgraded to a variational quality control whereby the data rejection/acceptance decisions are taken consistently during the minimization problem. In terms of radiance data, the system currently uses so-called raw level-1b AMSU-A that are QC, and bias controlled by the data user and not the producer. The QC and thinning algorithms of the radiance data are more complex and system dependent, but their impact on analyses and forecasts are very large and now comparable to the radiosonde data in the SH. The resolution of NWP forecast/analysis systems is forever increasing and so is the volume of data from various instruments. The volume of satellite data has become quite a challenge even at the level of ingest and QC. one aspect of NWP systems which definitely can benefit from this additional data is the moisture analysis. In that context we have started to experiment with the ingest of water sensitive radiances from the HIRS and AMSU-B instruments onboard NOAA-15 and NOAA-16. As will be shown, the quality of both the temperature and moisture analyses are significantly improved when using these additional satellite data. Preliminary evaluations from 10-day forecasts indicate marked improvements in Quantitative Precipitation Forecast (QPF).
机译:加拿大气象中心的(CMC)三维变分(3D-VAR)是一种增量分析系统,目前由我们的全球和区域模型进行了很少的修改。在过去的几年中,它经历了一系列从异屋到地形坐标的一系列升级,最重要的是卫星广域的直接同化。观察的质量控制(QC)也升级到变分质量控制,从而在最小化问题期间始终如一地持续数据抑制/接受决策。在辐射数据方面,系统目前使用所谓的原始Level-1B AMSU-A,它是QC的,并且由数据用户而不是生产者控制的偏差。辐射数据的QC和变薄算法更复杂,系统依赖性,但它们对分析和预测的影响非常大,现在与SH中的无线电探测数据相媲美。 NWP预测/分析系统的分辨率是永恒的,各种仪器的数据量也是如此。即使在摄取和QC水平,卫星数据的体积也变得非常挑战。 NWP系统的一个方面肯定可以从这种附加数据中受益的是水分分析。在这方面,我们已经开始尝试从HIR和AMSU-B仪器的摄取水敏感的辐射,滚动NOAA-15和NOAA-16。如将显示,当使用这些额外的卫星数据时,温度和水分分析的质量显着提高。 10天预测的初步评估表明定量降水预测(QPF)的显着改善。

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