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Wave-optics uncertainty propagation and regression-based bias model in GNSS radio occultation bending angle retrievals

机译:GNSS无线电校正角检索GNSS无线电掩护中的波光学不确定性传播与基于回归的偏置模型

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A new reference occultation processing system (rOPS) will include a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval chain with integrated uncertainty propagation. In this paper, we focus on wave-optics bending angle (BA) retrieval in the lower troposphere and introduce (1)?an empirically estimated boundary layer bias (BLB) model then employed to reduce the systematic uncertainty of excess phases and bending angles in about the lowest 2?km of the troposphere and (2)?the estimation of (residual) systematic uncertainties and their propagation together with random uncertainties from excess phase to bending angle profiles. Our BLB model describes the estimated bias of the excess phase transferred from the estimated bias of the bending angle, for which the model is built, informed by analyzing refractivity fluctuation statistics shown to induce such biases. The model is derived from regression analysis using a large ensemble of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) RO observations and concurrent European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields. It is formulated in terms of predictors and adaptive functions (powers and cross products of predictors), where we use six main predictors derived from observations: impact altitude, latitude, bending angle and its standard deviation, canonical transform (CT) amplitude, and its fluctuation index. Based on an ensemble of test days, independent of the days of data used for the regression analysis to establish the BLB model, we find the model very effective for bias reduction and capable of reducing bending angle and corresponding refractivity biases by about a factor of 5. The estimated residual systematic uncertainty, after the BLB profile subtraction, is lower bounded by the uncertainty from the (indirect) use of ECMWF analysis fields but is significantly lower than the systematic uncertainty without BLB correction. The systematic and random uncertainties are propagated from excess phase to bending angle profiles, using a perturbation approach and the wave-optical method recently introduced by Gorbunov and Kirchengast?(2015), starting with estimated excess phase uncertainties. The results are encouraging and this uncertainty propagation approach combined with BLB correction enables a robust reduction and quantification of the uncertainties of excess phases and bending angles in the lower troposphere.
机译:新的参考常用处理系统(ROP)将包括具有集成不确定性传播的全球导航卫星系统(GNSS)无线电常见(RO)检索链。在本文中,我们专注于较低对流层中的波光光学弯曲角度(BA)检索,并引入(1)?然后使用经验估计的边界层偏置(BLB)模型,以减少多个阶段的系统不确定性和弯曲角度关于对流层的最低2千地,(2)?估计(残留)系统的不确定性以及它们的传播以及来自过量相对于弯曲角度谱的随机不确定性。我们的BLB模型描述了从弯曲角的估计偏置传递的过量相位的估计偏置,其通过分析所显示的折射率波动统计来了解模型,以诱导这种偏差。该模型使用用于气象,电离层和气候(宇宙)RO观察和中等天气预报(ECMWF)分析领域的大型星座观测系统的大型星座观察系统的回归分析。它在预测器和自适应功能(预测器的权力和交叉产品)方面配制,在那里我们使用六个主要预测因子来源于观察:冲击高度,纬度,弯曲角度及其标准偏差,规范变换(CT)幅度及其波动指数。基于测试日的集合,独立于用于回归分析的数据的日期建立BLB模型,我们发现模型对于偏差减小并且能够减少弯曲角度和相应的折射率偏差约为5倍。估计的残余系统不确定度在短螺纹轮廓减法之后,由ECMWF分析领域的(间接)使用的不确定性较低,但显着低于没有BLB校正的系统不确定性。系统和随机的不确定因素通过扰动方法和最近由Gorbunov和Kirchengast引入的波 - 光学方法来传播到弯曲角度分布?(2015),从估计过量的不确定性开始。结果是令人鼓舞的,这种不确定性传播方法与BLB校正结合使用,使得能够减小和定量较低对流层中的过量阶段的不确定性和弯曲角度。

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