Impact of FORMOSAT-3/COSMIC GPS radio occultation and dropwindsonde data on regional model predictions during the 2007 Mei-yu season

A study of the impact of FORMOSAT-3/COSMIC GPS radio occultation (RO) and dropwindsonde data on regional model simulations for a 11-day period during the 2007 Mei-yu season is presented. The Weather Research and Forecasting (WRF) model and its three-dimensional variation component, WRF-Var, are used for regional model predictions of heavy rainfall events in Taiwan. Without the use of GPS RO and dropwindsonde data, pressure and relative humidity are, in general, underestimated by the model; temperature predictions have a warm bias at the low level and a cold bias at the high level; and the east–west and north–south component winds have positive and negative biases, respectively. Incorporating GPS RO data tends to improve the prediction for longer integration. The assimilation of dropwindsonde data improves the forecast at the earlier time and at higher levels, and the improvement decreases over time. The reason the dropwindsonde data produce a positive impact earlier and the GPS RO data later is that there are few GPS RO observations in the fine domain. The large-scale simulation is first improved using the GPS RO observations, and the resulting changes can have a positive impact on the mesoscale at the later time. The dropwindsonde observations were taken inside the fine domain such that their impact can be detected early in the simulation. With both types of observation included, the prediction shows even greater improvement. At the earlier forecast time, there is nearly no impact from GPS and dropwindsonde data on rainfall forecasts. However, at the later integration time, the GPS data start to significantly improve the rainfall forecast. The dropwindsonde data also provide a positive impact on rainfall forecasts, but it is not as significant as that of the GPS data.     

GPS/INS navigation precision and its effect on airborne radio occultation retrieval accuracy

An airborne radio occultation (RO) system has been developed to retrieve atmospheric profiles of refractivity, moisture, and temperature. The long-term objective of such a system is deployment on commercial aircraft to increase the quantity of moisture observations in flight corridors in order to improve weather forecast accuracy. However, there are several factors important to operational feasibility that have an impact on the accuracy of the airborne RO results. We investigate the effects of different types of navigation system noise on the precision of the retrieved atmospheric profiles using recordings from the GNSS Instrument System for Multistatic and Occultation Sensing (GISMOS) test flights, which used an Applanix POS/AV 510 Global Positioning System (GPS)/Inertial Navigation System (INS). The data were processed using a carrier phase differential GPS technique, and then the GPS position and inertial measurement unit data were combined in a loosely coupled integrated inertial navigation solution. This study quantifies the velocity precision as a function of distance from GPS reference network sites, the velocity precision with or without an inertial measurement unit, the impact of the quality of the inertial measurement unit, and the compromise in precision resulting from the use of real-time autonomous GPS positioning. We find that using reference stations with baseline lengths of up to 760?km from the survey area has a negligible impact on the retrieved refractivity precision. We also find that only a small bias (less than 0.5% in refractivity) results from the use of an autonomous GPS solution rather than a post-processed differential solution when used in an integrated GPS/INS system. This greatly expands the potential range of an operational airborne radio occultation system, particularly over the oceans, where observations are sparse.     

单站地基GPS天顶延迟反演大气剖面研究

基于一定的大气折射率剖面模型和搜索方法,可以由GPS天顶延迟反演大气折射率剖面。利用上海气象站的探空数据和上海IGS站的GPS数据,对基于单站地基GPS天顶延迟的大气折射率剖面反演方法进行了验证。结果表明,根据目前处理得到的天顶延迟,反演剖面与实际剖面吻合较好。     

FY-3C无线电掩星折射率廓线的反演及验证

2013年,中国发射了首颗进行全球导航卫星系统(global navigation satellite system,GNSS)无线电掩星观测的气象卫星FY-3C,其掩星数据产品已由国家卫星气象中心(national satellite meteorological center,NSMC)发布。基于FY-3C附加相位数据,通过几何光学反演和全谱反演相结合的方法自主反演获取大气折射率廓线,并利用NSMC提供的折射率产品和欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts, ECMWF)的气候再分析数据集(ECMWF reanalysis-interim,ERA-Interim)对反演结果进行验证。2017年全年FY-3C掩星折射率自主反演的成功率为82%,与NSMC 83.5%的反演成功率基本一致。以ERA-Interim再分析资料为参考,自主反演折射率相对偏差绝对值在25 km以下,小于1.5%,略优于NSMC产品,但偏差标准差比NSMC产品略大,达到了3.6%。自主反演和NSMC的折射率廓线在高纬地区的相对偏差...     

Analysis of atmospheric and ionospheric structures using the GPS/MET and CHAMP radio occultation database: a methodological review

Since 1995, the global positioning system (GPS) has been exploited by the means of the radio occultation (RO) method to obtain the vertical profiles of refractivity, temperature, pressure, and water vapor in the neutral atmosphere and electron density in the ionosphere. Applying the RO method to the study of the Earths atmosphere was demonstrated for the first time with the GPS/MET experiment. Since then, several satellites with GPS receivers, suitable for RO experiments, have been launched including Oersted, SUNSAT, CHAMP, SAC-C, and GRACE. Future RO investigations that are planned now include FORMOSAT3/COSMIC and Terra-SAR missions. New elements in the RO technology are required to meet the goals of improving the accuracy and broadening the potential of the RO method. In this paper, a methodological review of RO investigations is presented to emphasize new directions in applying the RO method: measuring the vertical gradients of the refractivity in the atmosphere and electron density in the lower ionosphere, determination of the temperature regime in the upper stratosphere, investigation of the internal wave activity in the atmosphere, and study of the ionospheric disturbances on a global scale. These new directions may be relevant for investigating the relationships between processes in the atmosphere and mesosphere, the study of thermal regimes in the intermediate heights of the upper stratosphere—lower mesosphere, and the analysis of the influence of the space weather phenomena on the lower ionosphere.     

Impact of the spatial resolution of climatic data and soil physical properties on regional corn yield predictions using the STICS crop model

The assimilation of Earth observation (EO) data into crop models has proven to be an efficient way to improve yield prediction at a regional scale by estimating key unknown crop management practices. However, the efficiency of prediction depends on the uncertainty associated with the data provided to crop models, particularly climatic data and soil physical properties. In this study, the performance of the STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard) crop model for predicting corn yield after assimilation of leaf area index derived from EO data was evaluated under different scenarios. The scenarios were designed to examine the impact of using fine-resolution soil physical properties, as well as the impact of using climatic data from either one or four weather stations across the region of interest. The results indicate that when only one weather station was used, the average annual yield by producer was predicted well (absolute error <5%), but the spatial variability lacked accuracy (root mean square error = 1.3 t ha⁻¹). The model root mean square error for yield prediction was highly correlated with the distance between the weather stations and the fields, for distances smaller than 10 km, and reached 0.5 t ha⁻¹ for a 5-km distance when fine-resolution soil properties were used. When four weather stations were used, no significant improvement in model performance was observed. This was because of a marginal decrease (30%) in the average distance between fields and weather stations (from 10 to 7 km). However, the yield predictions were improved by approximately 15% with fine-resolution soil properties regardless of the number of weather stations used. The impact of the uncertainty associated with the EO-derived soil textures and the impact of alterations in rainfall distribution were also evaluated. A variation of about 10% in any of the soil physical textures resulted in a change in dry yield of 0.4 t ha⁻¹. Changes in rainfall distribution between two abundant rainfalls during the growing season led to a significant change in yield (0.5 t ha⁻¹ on average). Our results highlight the importance of using fine-resolution gridded daily precipitation data to capture spatial variations of rainfall as well as using fine-resolution soil properties instead of coarse-resolution soil properties from the Canadian soil dataset, especially for regions with high pedodiversity.     

Variational data assimilation for deriving global climate analyses from GNSS radio occultation data

A comprehensive global navigation satellite system (GNSS) based radio occultation (RO) data set is available for meteorology and climate applications since the start of GNSS RO measurements aboard the CHAllenging Mini-satellite Payload (CHAMP) satellite in February 2001. Global coverage, all-weather capability, long-term stability and accuracy not only makes this innovative use of GNSS signals a valuable supplement to the data set assimilated into numerical weather prediction (NWP) systems but also an excellent candidate for global climate monitoring. We present a 3D variational data assimilation (3D-Var) scheme developed to derive consistent global analysis fields of temperature, specific humidity, and surface pressure from GNSS RO data. The system is based on the assimilation of RO data within 6 h time windows into European Centre for Medium-Range Weather Forecasts (ECMWF) short-term (24 h, 30 h) forecasts, to derive climatologic monthly mean fields. July 2003 was used as a test-bed for assessing the system’s performance. The results show good agreement with climatologies derived from RO data only and recent NWP impact studies. These findings are encouraging for future developments to apply the approach for longer term climatologic analyses, validation of other data sets, and atmospheric variability studies.     

GPS radio holography as a tool for remote sensing of the atmosphere, mesosphere, and terrestrial surface from space

GPS radio occultation (RO) signals are highly coherent and precise, and thus sufficient for holographic investigation of the atmosphere, ionosphere, and the Earth's surface from space. In principle, three-dimensional radio-holographic remote sensing is possible by using new radio holographic equations to retrieve the radio field within the atmosphere from a radio field known at some interface outside the atmosphere. A simplified two-dimensional form of the radio-holographic equations which are developed under an assumption of local spherical symmetry can be used to obtain two-dimensional radio images of the atmosphere and terrestrial surface. To achieve this, radio holograms recorded by a GPS receiver onboard a low earth orbit (LEO) satellite at two GPS frequencies can be used and focused synthetic aperture principle applied. Analysis of GPS/MET RO data is presented to show the effectiveness of a radio-holographic approach. It is shown that the amplitude of GPS radio signals (in addition to phase data) can be used to obtain detailed altitude profiles of the vertical gradient of refractivity in the atmosphere and electron density in the mesosphere. The results demonstrate the applicability of GPS radio holography for a detailed global study of the natural processes in the atmosphere and mesosphere. Electronic Publication     

Tropospheric refractivity and zenith path delays from least-squares collocation of meteorological and GNSS data

Precise positioning requires an accurate a priori troposphere model to enhance the solution quality. Several empirical models are available, but they may not properly characterize the state of troposphere, especially in severe weather conditions. Another possible solution is to use regional troposphere models based on real-time or near-real time measurements. In this study, we present the total refractivity and zenith total delay (ZTD) models based on a numerical weather prediction (NWP) model, Global Navigation Satellite System (GNSS) data and ground-based meteorological observations. We reconstruct the total refractivity profiles over the western part of Switzerland and the total refractivity profiles as well as ZTDs over Poland using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays) developed at ETH Zürich. In these two case studies, profiles of the total refractivity and ZTDs are calculated from different data sets. For Switzerland, the data set with the best agreement with the reference radiosonde (RS) measurements is the combination of ground-based meteorological observations and GNSS ZTDs. Introducing the horizontal gradients does not improve the vertical interpolation, and results in slightly larger biases and standard deviations. For Poland, the data set based on meteorological parameters from the NWP Weather Research and Forecasting (WRF) model and from a combination of the NWP model and GNSS ZTDs shows the best agreement with the reference RS data. In terms of ZTD, the combined NWP-GNSS observations and GNSS-only data set exhibit the best accuracy with an average bias (from all stations) of 3.7 mm and average standard deviations of 17.0 mm w.r.t. the reference GNSS stations.     

雾灵山山基掩星观测反演误差分析

运用山基GPS掩星探测技术对2005年8月河北雾灵山山基GPS掩星观测试验数据进行了处理,获得了接收机高度以下的大气折射率廓线;分析了掩星反演结果的内部符合情况,并利用同时进行的联合探空观测数据,将探空结果与掩星反演结果进行了比对分析.分析结果表明,山基GPS掩星反演大气折射率的内部符合精度优于1%,与常规探空结果的平均偏差为5.9%.反演结果偏小,标准偏差为5.6%.     

The Role of Ground-Based GPS Meteorological Observations in Numerical Weather Prediction

For lack of sufficient observations, the definition of atmospheric moisture fields (including water vapor and clouds) remains a difficult problem whose solution is essential for improved weather forecasts. Moisture fields are under-observed in time and space, primarily because the distribution of water in the atmosphere is highly variable. Because water is important in weather and climate processes, a significant effort has been expended to develop new or improved remote sensing systems to mitigate this problem. One such system uses ground-based Global Positoning System (GPS) receivers to make accurate all-weather estimates of atmospheric refractivity at very low cost. This largely unanticipated application of GPS had led to a new and potentially significant upper-air observing system for meteorological agencies and researchers around the world (Wolfe & Gutman, 2000). The first and most mature use of GPS for this purpose is in the estimation of integrated (total column) precipitable water vapor above a fixed site (Duan et al., 1996, with improvements by Niell, 1996, and Fang et al., 1998). The techniques currently used by the National Oceanic and Atmospheric Administration's Forecast Systems Laboratory (NOAA/FSL) to collect, process, and distribute GPS water vapor observations are mature and almost ready for transition to operational use. NOAA/FSL has shown that GPS integrated water vapor data can be used effectively in objective (i. e., numerical weather prediction) and subjective weather forecasting. To understand the strengths and limitations of GPS for weather forecasting, it is essential to understant what types of information are currently available to forecasters and modelers, and how models use the data to describe the current and probable future state of the atmosphere. It is also important to understand the current trends in modern weather prediction to ensure that GPS observing system play a significant role in the future. ? 2001 John Wiley & Sons, Inc.     

基于IGS超级跟踪站的近实时GPS气象研究及应用

目前国内许多城市开始将CORS综合应用网服务于气象部门,为给地基GPS气象研究人员提供一个真实的研究环境,本文基于IGS超级跟踪站网络搭建了一个近实时GPS气象系统,并结合实测数据验证了该系统的有效性。基于该平台可以系统地研究GPS遥感水汽、层析水汽三维分布、数值天气预报同化GPS水汽以及利用电离层分布进行空间天气预报等理论。     

利用GPS/MET与CHAMP掩星资料反演地球中性大气参数的比较

采用Abel积分反演算法 ,在干大气模式下 ,分别针对GPS/MET与CHAMP特定掩星事件的Level2数据进行处理 ,得到了相应的折射指数与大气参数廓线。分别将反演结果与UCAR和GFZ公布的结果进行比较 ,证明了反演算法的正确性与通用性。分析了两个温度反演结果都存在系统误差和CHAMP温度反演结果误差较大的原因 ,并提出了改进建议     

(Near-)real-time orbit determination for GNSS radio occultation processing

The processing of GPS radio occultation measurements for use in numerical weather predictions requires a precise orbit determination (POD) of the host satellite in near-real-time. Making use of data from the GRAS instrument on Metop-A, the performance of different GPS ephemeris products and processing concepts for near-real-time and real-time POD is compared. While previous analyses have focused on the achievable along-track velocity accuracy, this study contributes a systematic comparison of the resulting estimated bending angles. This enables a more rigorous trade-off of different orbit determination methodologies in relation to the end-user needs for atmospheric science products. It is demonstrated that near-real-time GPS orbit and clock products have reached a sufficient quality to determine the Metop-A along-track velocity with an accuracy of better than 0.05 mm/s that was formerly only accessible in post-processing. The resulting bending angles are shown to exhibit standard deviation and bias differences of less than 0.3 % compared with post-processed products up to altitudes of at least 40 km, which is notably better than 1 % accuracy typically assumed for numerical weather predictions in this height regime. Complementary to the analysis of ground-based processing schemes, the potential of autonomous on-board orbit determination is investigated for the first time. Using actual GRAS flight data, it is shown that a 0.5 m 3D rms position accuracy and a 0.2 mm/s along-track velocity accuracy can in fact be obtained in real-time with the currently available GPS broadcast ephemeris quality. Bending angles derived from the simulated real-time processing exhibit a minor performance degradation above tangent point heights of 40 km but negligible differences with respect to ground-based products below this altitude. Onboard orbit determination and, if desired, bending angle computation, can thus enable a further simplification of the ground segment in future radio occultation missions and contribute to reduced product latencies for radio occultation data assimilation in numerical weather predictions.     

Single frequency processing of Ørsted GPS radio occultation measurements

The Global Positioning System (GPS) radio occultation measurements obtained using the TurboRogue GPS receiver on the Danish satellite Ørsted have been processed using the single frequency method. Atmospheric profiles of refractivity and temperature are derived and validated against numerical weather prediction data from the European Centre for Medium-Range Weather Forecast (ECMWF). Results from the Ørsted GPS measurement campaign in February 2000 indicate that the single frequency method can provide retrievals with accuracy comparable to that of using two frequencies. From comparisons between measured dry temperature profiles and corresponding dry temperature profiles derived from ECMWF analysis fields, we find a mean difference of less than 0.5 K and a standard deviation of 2–4 K between 500 and 30 hPa in height. Above 30 hPa the impact of the ionosphere becomes more dominant and more difficult to eliminate using the single frequency method, and the results show degraded accuracy when compared to previous analysis results of occultation data from other missions using the dual frequency method. At latitudes less than 40° (denoted low latitudes), the standard deviation is generally smaller than at latitudes higher than 40° (denoted high latitudes). A small temperature bias is observed centered at 200 hPa for low latitudes and at 300 hPa for high latitudes. This indicates that the ECMWF analyses do not adequately resolve the tropopause temperature minimum. In the lowest part of the troposphere an observed warm bias is thought to be due to erroneous tracking of the GPS signal in cases of atmospheric multipath propagation.     

Quality assessment of COSMIC/FORMOSAT-3 GPS radio occultation data derived from single- and double-difference atmospheric excess phase processing

This study evaluates the quality of GPS radio occultation (RO) atmospheric excess phase data derived with single- and double-difference processing algorithms. A spectral analysis of 1 s GPS clock estimates indicates that a sampling interval of 1 s is necessary to adequately remove the GPS clock error with single-difference processing. One week (May 2–8, 2009) of COSMIC/FORMOSAT-3 data are analyzed in a post-processed mode with four different processing strategies: (1) double-differencing with 1 s GPS ground data, (2) single-differencing with 30 s GPS clock estimates (standard COSMIC Data Analysis and Archival Center product), (3) single-differencing with 5 s GPS clocks, and (4) single-differencing with 1 s GPS clocks. Analyses of a common set of 5,596 RO profiles show that the neutral atmospheric bending angles and refractivities derived from single-difference processing with 1 s GPS clocks are the highest quality. The random noise of neutral atmospheric bending angles between 60 and 80 km heights is about 1.50e−6 rad for the single-difference cases and 1.74e−6 rad for double-differencing. An analysis of pairs of collocated soundings also shows that bending angles derived from single-differencing with 1 s GPS clocks are more consistent than with the other processing strategies. Additionally, the standard deviation of the differences between RO and high-resolution European Center for Medium range Weather Forecasting (ECMWF) refractivity profiles at 30 km height is 0.60% for single-differencing with 1 and 5 s GPS clocks, 0.68% for single-differencing with 30 s clocks, and 0.66% for double-differencing. A GPS clock-sampling interval of 1 s or less is required for single- and zero-difference processing to achieve the highest quality excess atmospheric phase data for RO applications.     

基于水汽密度比例因子的三维水汽层析算法

针对传统水汽密度层析方法的缺点,设计并实现了一种基于水汽密度比例因子的三维水汽层析算法,提高了观测数据的利用率。利用香港CORS网的实测GPS和气象数据,并结合研究区域内45004探空站的探空数据,验证了该算法用于实测数据的可行性及精度,并分析了不同天气对层析新算法的影响。试验结果表明:该算法在观测数据的利用率上远大于传统层析方法,以探空数据为参考基准,RMS、水汽廓线相关系数和误差分布均优于传统方法。此外,降水天气对层析结果影响要比无降水天气的影响大。     

Different mechanisms of the ionospheric influence on GPS occultation signals

A local mechanism for strong ionospheric effects on radio occultation (RO) global positioning satellite system (GPS) signals is described. Peculiar zones centered at the critical points (the tangent points) in the ionosphere, where the gradient of the electron density is perpendicular to the RO ray trajectory, strongly influence the amplitude and phase of RO signals. It follows from the analytical model of local ionospheric effects that the positions of the critical points depend on the RO geometry and the structure of the ionospheric disturbances. Centers of strong ionospheric influence on RO signals can exist, for example, in the sporadic E-layers, which are inclined by 3–6° relative to the local horizontal direction. Also, intense F2 layer irregularities can contribute to the RO signal variations. A classification of the ionospheric influence on the GPS RO signals is introduced using the amplitude data, which indicates different mechanisms (local, diffraction, etc.) for radio waves propagation. The existence of regular mechanisms (e.g., local mechanism) indicates a potential for separating the regular and random parts in the ionospheric influence on the RO signals.     

高斯函数在香港地区对流层层析实验中的应用

将GPS信号的斜路径湿延迟当作层析的观测量能够有效获取对流层的三维水汽场。由于射线分布的不均匀和观测网地形的扁平,观测方程是不适定的,因此需要添加一些约束条件来确定唯一解。由于水汽在垂直方向变化很快,合理的垂直约束在获取准确的水汽场上起着重要作用。研究了香港地区湿折射率的垂直分布特征,发现高斯函数能很好地表达湿折射率与高度的关系,利用高斯函数建立约束方程获得的层析解能很好地与探空数据和欧洲中尺度天气预报中心（ECMWF）数据吻合。相对于指数约束所得结果,层析湿折射率的标准差在整个对流层减小了3.8 mm/km,在低对流层减小了4.7 mm/km。实验也表明,利用其他气象数据,如无线电探空数据,作为湿折射率的先验信息,也可以得到较好的层析解。     

4D GPS water vapor tomography: new parameterized approaches

Water vapor is a key variable in numerical weather prediction, as it plays an important role in atmospheric processes. Nonetheless, the distribution of water vapor in the atmosphere is observed with a coarse resolution in time and space compared to the resolution of numerical weather models. GPS water vapor tomography is one of the promising methods to improve the resolution of water vapor measurements. This paper presents new parameterized approaches for the determination of water vapor distribution in the troposphere by GPS. We present the methods and give first results validating the approaches. The parameterization of voxels (volumetric pixels) by trilinear and spline functions in ellipsoidal coordinates are introduced in this study. The evolution in time of the refractivity field is modeled by a Kalman filter with a temporal resolution of 30 s, which corresponds to the available GPS-data rate. The algorithms are tested with simulated and with real data from more than 40 permanent GPS receiver stations in Switzerland and adjoining regions covering alpine areas. The investigations show the potential of the new parameterized approaches to yield superior results compared to the non parametric classical one. The accuracy of the tomographic result is quantified by the inter-quartile range (IQR), which is decreased by 10–20% with the new approaches. Further, parameterized voxel solutions have a substantially smaller maximal error than the non parameterized ones. Simulations show a limited ability to resolve vertical structures above the top station of the network with GPS tomography.