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SMOS brightness temperature forward modelling and long term monitoring at ECMWF

机译:SMOS亮度温度前进建模和ECMWF的长期监测

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This paper presents the forward modelling aspects of the SMOS (Soil Moisture and Ocean Salinity) activities at ECMWF (European Centre for Medium-Range Weather Forecasts). Several parameterizations of the Community Microwave Emission Modelling Platform (CMEM) are used to simulate L-band Brightness Temperatures (TBs) and compared to the SMOS TBs for 2010-2011. We show that simulated TBs are primarily sensitive, by order of importance, to the soil roughness model, the vegetation opacity and the soil dielectric model. In particular, best CMEM results are obtained with the simple Wigneron soil roughness model and the Wigneron model for the vegetation opacity. For the soil dielectric model, performances of the Wang and Schmugge and the Mironov models are shown to be similar and better than the Dobson model. The Wang and Schmugge model is then used in the next steps of this paper combined with the Wigneron roughness and vegetation models. The paper describes a multi-angular multi-polarised bias correction method based on a linear resealing (mean and variance) computed at the monthly scale using SMOS observations and ECMWF-CMEM re-analysed TBs for a four year period (2010-2013). Results show that for 2010-2013 the seasonal multi-angular multi-polarisation bias correction approach reduces global RMSE to 7.91 K, compared to 16.7 K before bias correction, whereas the mean absolute bias is reduced to 1.39 K, compared to 11.04 K before bias correction. The consistency between the seasonality of simulated and the observed TBs is also improved by using a monthly bias correction, leading to correlation values improvement to 0.62 after bias correction compared to 0.56 before. The 2010-2013 bias correction applied to the 2014-2016 period at 40 degrees incidence reduces the global RMSE from 15.56 K to 8.19 K, and the mean absolute bias from 10.16 K to 2.51 K, with no impact on the correlation values that remain at 0.61 in both cases. Long term monitoring of SMOS TB is presented covering a 7-year period (2010-2016) at both polarisations, at 40 incidence angle. Results show that the consistency between SMOS and ECMWF reanalysis based TBs progressively improved between 2010 and 2016, pointing out improvements of level 1 SMOS TB products quality through the SMOS lifetime.
机译:本文介绍了ECMWF的SMOS(土壤水分和海洋盐水)活动的前进建模方面(欧洲的中距离天气预报中心)。社区微波发射建模平台(CMEM)的几个参数化用于模拟L波段亮度温度(TBS),并与2010-2011的SMOS TBS相比。我们表明,模拟的TBS主要通过重要性顺序敏感到土壤粗糙度模型,植被不透明度和土介质模型。特别是,用简单的Wigneron土壤粗糙度模型和用于植被不透明的Wigneron模型获得最佳CMEM结果。对于土壤介电模型,王和施密望的性能和Mironov模型被认为是类似的,而不是多宇模型。然后将王和施密望模型用于本文的下一步,结合Wigneron粗糙度和植被模型。本文描述了一种基于使用SMOS观测和ECMWF-CMEM在每月规模计算的线性重新预测(均值和方差)的多角度多极化偏置校正方法,并使用SMOS观察和ECMWF-CMEM重新分析了TBS四年(2010-2013)。结果表明,对于2010 - 2013,季节性多角度多极化偏压校正方法将全局RMSE减少到7.91克,而偏置校正前的16.7 k,而平均绝对偏置减少到1.39 k,相比偏差前11.04 k更正。通过使用每月偏压校正,模拟和观察到的TBS的季节性之间的一致性也得到了改善,导致在偏压校正和之前的0.56比较后的相关值改善0.62。 2010-2013偏置校正适用于2014-2016的校正,40度发病率将全球RMSE降低到15.56 k至8.19 k,并且平均绝对偏置从10.16 k到2.51 k,没有影响仍然存在的相关值两种情况下0.61。 SMOS结核病的长期​​监测介绍了在两个偏热下的7年期(2010-2016),在40个偏振中。结果表明,2010年和2016年间,SMOS和ECMWF重新分析的TBS之间的一致性逐步改善,通过SMOS终身指出了1级SMOS TB产品质量的改进。

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