大气遥感辐射传输模式的一种有效的Jacobian算法

介绍并验证了一种快速、精确地计算Jacobian的解析方法(辐射传输方程的线性化,简称LR方法),将其结果与NAST-I真正的线性模式及数值方法(差分方法)的Jacobian值进行比较。结果表明,这种解析算法不仅快速、精确,而且独立于辐射传输方程,在有效Jacobian计算中只需要输入大气透过率,可适用于任何垂直探测器权重函数的计算。     

利用测温声雷达回波图估算大气扩散的一种参数化方法

本文提出了一种基于湍流扩散统计理论的利用声雷达回波图估算大气扩散参数的新方法。这种新方法,仅需要从声雷达回波图上读出边界层结构的信息并取得常规地面测风资料,即可利用参数化公式进行计算,不需进行Pasquill稳定度分类。 所应用的参数化公式用外场观测资料进行了检验,表明公式计算结果与观测值比较符合。这种方法计算得到的扩散参数也与P-G扩散曲线进行了比较。     

Value-added Impact of Geostationary Hyperspectral Infrared Sounders on Local Severe Storm Forecasts——via a Quick Regional OSSE

Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction(NWP) models to reliably predict high-impact weather events such as local severe storms(LSSs). High spectral resolution or hyperspectral infrared(HIR) sounders from geostationary orbit(GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields—an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE(Observing System Simulation Experiment)framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO(low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference(RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated, and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems(such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km.     

Quality Assessment and Forecast Sensitivity of Global Remote Sensing Observations

The satellite-derived wind from cloud and moisture features of geostationary satellites is an important data source for numerical weather prediction(NWP) models. These datasets and global positioning system radio occultation(GPSRO)satellite radiances are assimilated in the four-dimensional variational atmospheric data assimilation system of the UKMO Unified Model in India. This study focuses on the importance of these data in the NWP system and their impact on short-term24-h forecasts. The quality of the wind observations is compared to the short-range forecast from the model background. The observation increments(observation minus background) are computed as the satellite-derived wind minus the model forecast with a 6-h lead time. The results show the model background has a large easterly wind component compared to satellite observations. The importance of each observation in the analysis is studied using an adjoint-based forecast sensitivity to observation method. The results show that at least around 50% of all types of satellite observations are beneficial. In terms of individual contribution, METEOSAT-7 shows a higher percentage of impact(nearly 50%), as compared to GEOS, MTSAT-2and METEOSAT-10, all of which have a less than 25% impact. In addition, the impact of GPSRO, infrared atmospheric sounding interferometer(IASI) and atmospheric infrared sounder(AIRS) data is calculated. The GPSRO observations have beneficial impacts up to 50 km. Over the Southern Hemisphere, the high spectral radiances from IASI and AIRS show a greater impact than over the Northern Hemisphere. The results in this study can be used for further improvements in the use of new and existing satellite observations.     

Added-value of GEO-hyperspectral Infrared Radiances for LocalSevere Storm Forecasts Using the Hybrid OSSE Method

正021-0443-1.Article Highlights:·The added-value from a GEO-hyperspectral IR sounder is studied by using a hybrid OSSE method.·The hybrid OSSE system can be used to evaluate the simulated GEO CrIS-FSR data by verifying the simulated LEO CrIS-FSR compared to the real CrIS-FSR.·The assimilation of GEO-hyperspectral IR data improves atmospheric temperature, moisture, wind, and precipitation forecasts.·An overall 5%RMSE reduction was found from using a GEO hyperspectral IR sounder on the atmospheric variables.     

任意基线雷达反射率因子垂直剖面生成算法

该文提出了一种基于雷达体扫资料的任意基线雷达反射率因子垂直剖面的生成算法。在计算雷达反射率因子垂直剖面上的格点在雷达极坐标中的仰角、方位和斜距位置后, 采用径向、方位上的最近邻居和垂直方向的线性内插相结合的客观分析方法得到格点上的反射率因子分析值。在垂直线性内插时分别用dBZ值和Z值 (单位: mm6/m3) 进行插值。结果表明:用该方法得到的雷达反射率因子垂直剖面从回波强度和空间位置来看都是合理的; 当采用垂直线性内插时, 用dBZ值插值比用Z值插值得到的雷达反射率因子垂直剖面在空间分布上更连续, 反射率因子分析值总体上更接近观测值; 低仰角的插值效果比高仰角的好。     

Observation of snowfall with a low-power FM-CW K-band radar (Micro Rain Radar)

Quantifying snowfall intensity especially under arctic conditions is a challenge because wind and snow drift deteriorate estimates obtained from both ground-based gauges and disdrometers. Ground-based remote sensing with active instruments might be a solution because they can measure well above drifting snow and do not suffer from flow distortions by the instrument. Clear disadvantages are, however, the dependency of e.g. radar returns on snow habit which might lead to similar large uncertainties. Moreover, high sensitivity radars are still far too costly to operate in a network and under harsh conditions. In this paper we compare returns from a low-cost, low-power vertically pointing FM-CW radar (Micro Rain Radar, MRR) operating at 24.1?GHz with returns from a 35.5?GHz cloud radar (MIRA36) for dry snowfall during a 6-month observation period at an Alpine station (Environmental Research Station Schneefernerhaus, UFS) at 2,650?m height above sea level. The goal was to quantify the potential and limitations of the MRR in relation to what is achievable by a cloud radar. The operational MRR procedures to derive standard radar variables like effective reflectivity factor (Z _e) or the mean Doppler velocity (W) had to be modified for snowfall since the MRR was originally designed for rain observations. Since the radar returns from snowfall are weaker than from comparable rainfall, the behavior of the MRR close to its detection threshold has been analyzed and a method is proposed to quantify the noise level of the MRR based on clear sky observations. By converting the resulting MRR-Z _e into 35.5?GHz equivalent Z _e values, a remaining difference below 1?dBz with slightly higher values close to the noise threshold could be obtained. Due to the much higher sensitivity of MIRA36, the transition of the MRR from the true signal to noise can be observed, which agrees well with the independent clear sky noise estimate. The mean Doppler velocity differences between both radars are below 0.3?ms^?1. The distribution of Z _e values from MIRA36 are finally used to estimate the uncertainty of retrieved snowfall and snow accumulation with the MRR. At UFS low snowfall rates missed by the MRR are negligible when comparing snow accumulation, which were mainly caused by intensities between 0.1 and 0.8 mm?h^?1. The MRR overestimates the total snow accumulation by about 7%. This error is much smaller than the error caused by uncertain Z _e?Csnowfall rate relations, which would affect the MIRA36 estimated to a similar degree.     

A Note on the FM-CW radar as a remote probe of the pacific trade-wind inversion

A vertically pointed FM-CW radar was used to monitor the Pacific Trade-Wind Inversion in the Hawaiian Islands during the summer of 1971. An instrumented aircraft was used forin situ measurements of radio refractivity and temperature. The correspondence between the position of the radar returns and the aircraft data was excellent. The strong returns seen by the radar were due chiefly to the strong lapse of humidity across the inversion.The radar indicated that over the island of Lanai the trade-wind inversion was highly variable both in position and intensity. At times the layer would move from above 2 km to less than 1 km in the space of five minutes associated with strong mechanical turbulence. Its thickness would change rapidly from tens of meters to hundreds of meters. Wave-like structure induced by the mountains on the east side were observed by the radar.Our analysis indicates that interpretation ofin situ aircraft measurements may be greatly aided by using the FM-CW radar as a guide.     

Principal study of the FM radar for improving the accuracy in quantitative rainfall rate measurement

The equations for estimating the rain echo power when FM-pulsed radar or FM-CW radar is used are derived. The results show that, with adequate frequency range selected, rain echo power may have a well-linear correlation with the rainfall rate, irrespective of the pattern of drop-size spectrum. Thus, it provides good remote sensing data for rainfall rate measurement.     

基于雷达—雨量计降水融合方法提高极端降水监测能力

高时空分辨率、高精度的降水产品对于极端降水的监测以及防灾减灾具有重要意义。地面雨量计提供点尺度降水精确观测,但无法精细化捕捉对流性强降水的空间分布。雷达观测可以精细地刻画降水的空间分布特征,但雷达定量估计降水（QPE,quantitative precipitation estimation）产品估测精度易受雷达观测偏差和Z–R（雷达反射率—降水率）关系等因素影响。因此,本文开展高时空分辨率的雷达—雨量计降水融合算法研究,集成雨量计观测和雷达定量估计降水产品各自的优点。该算法主要步骤包括:雨量站观测数据格点化、局地雨量计订正雷达QPE和雷达—雨量计降水融合三个部分。首先利用克里金插值方法,对雨量站观测的降水进行插值,得到格点降水信息;再通过局地雨量计订正方法系统性地订正雷达QPE产品,以提高雷达QPE产品精度;最后,结合降水类型,通过雷达—雨量计降水融合算法,产生高时空分辨率、高精度的雷达—雨量计降水融合产品。通过郑州“21·7”暴雨、台风“烟花”和2021年8月随州暴雨三个典型的极端降水个例,对雷达—雨量计降水融合算法产生的雷达—雨量计降水融合产品进行了系统地评估和分析。结果表明,在不同的极端降水个例和不同的降水时段,雷达—雨量计降水融合产品精度上优于雷达QPE产品,且在降水的空间分布上较雨量站观测格点插值产品更能精细地刻画降水的结构特征。表明算法得到的雷达—雨量计降水融合产品的准确性较高,对极端降水有较好地捕捉和监测能力。     

EFFECTS OF A CLOUD FILTERING METHOD FOR FENGYUN-3C MICROWAVE HUMIDITY AND TEMPERATURE SOUNDER MEASUREMENTS OVER OCEAN ON RETRIEVALS OF TEMPERATURE AND HUMIDITY

For Microwave Humidity and Temperature sounder (MWHTS) measurements over the ocean, a cloud filtering method is presented to filter out cloud- and precipitation-affected observations by analyzing the sensitivity of the simulated brightness temperatures of MWHTS to cloud liquid water, and using the root mean square error (RMSE) between observation and simulation in clear sky as a reference standard. The atmospheric temperature and humidity profiles are retrieved using MWHTS measurements with and without filtering by multiple linear regression (MLR), artificial neural networks (ANN) and one- dimensional variational (1DVAR) retrieval methods, respectively, and the effects of the filtering method on the retrieval accuracies are analyzed. The numerical results show that the filtering method can improve the retrieval accuracies of the MLR and the 1DVAR retrieval methods, but have little influence on that of the ANN. In addition, the dependencies of the retrieval methods upon the testing samples of brightness temperature are studied, and the results show that the 1DVAR retrieval method has great stability due to that the testing samples have great impact on the retrieval accuracies of the MLR and the ANN, but have little impact on that of the 1DVAR.     

Characteristics of the winter boundary layer over the African Plateau: 26 ° S

Characteristics of the winter boundary layer over the (elevation 1600 m) in the vicinity of Johannesburg, 26 ° S, 29 ° E, are described in relation to air pollution potential by means of doppler sounder observations and background climatological data. Regional mean winds for the 800 h Pa level show that the winter boundary layer is dominated by a cell of high pressure over the Limpopo River Valley to the northeast of Johannesburg. To the south of Johannesburg, westerly circumpolar flow is prevalent and encroaches onto the plateau during the passage of frontal perturbations. Doppler sounder wind and turbulence profiles, averaged for the months of August 1984 and June 1985, are presented to establish a boundary-layer climatology. Diurnally averaged doppler sounder profiles for both months revealed a very consistent convective/day — stable/night cycle in the very dry winter conditions. A sharp radiation inversion formed just after sunset up to the 150–200 m level and grew in depth to reach 300 m on average near sunrise. The inversion caused a reduction in frictional drag and the formation of nocturnal low level jet during westerly encroachment. A case study is evaluated to determine the detailed structure of the low level jet near Johannesburg. The thermal wind plays a role in the nocturnal acceleration; mechanisms for its development and maintenance are explored. Additional work is presented on the synoptic cycle and its influence on air pollution dispersion over the African Plateau.     

Experimental calibration of a cost-effective X-band weather radar for climate ecological studies in southern Ecuador

In this paper setup, operational problems and a straightforward calibration approach for a cost-effective X-Band radar are presented. The LAWR (Local Area Weather Radar) system is based on conventional ship radar technology which is adapted to register rainfall within a range of about 60 km with a spatial resolution of 500 m per pixel. The instrument offers neither Doppler processing nor vertical scan capabilities but uses 20° wide (vertical) beam. The calibration suffers from an unfavorably distributed and very sparse rain gauge network, heavy clutter contamination of the signal and obstructions by surrounding terrain. A specific scaling approach is developed, that includes satellite data on cloud frequency and distribution, to overcome these limitations. Observed clutter is removed and missing values are replaced by bilinear interpolation of the undisturbed signals. A temporal and spatial bias of the radar signal is corrected using an omni-directional spatial distribution hypothesis. This is possible because of the location of the radar site in the transition zone between high rainfall on the eastern Andean slopes and low rainfall on the leeward side. A further limitation of the system is that the LAWR does not provide information on the measured reflectivity Z but dimensionless counts (8 bit resolution). Calibration is performed assuming a linear relation between radar output and rainfall as recommended by the systems manufacturer. The intercomparison of rain gauge and scatterometer data with calibrated radar rainfall reveals a good performance of the developed calibration approach.     

Statistical Modeling with a Hidden Markov Tree and High-resolution Interpolation for Spaceborne Radar Reflectivity in the Wavelet Domain

With the increasing availability of precipitation radar data from space, enhancement of the resolution of spaceborne precipitation observations is important, particularly for hazard prediction and climate modeling at local scales relevant to extreme precipitation intensities and gradients. In this paper, the statistical characteristics of radar precipitation reflectivity data are studied and modeled using a hidden Markov tree (HMT) in the wavelet domain. Then, a high-resolution interpolation algorithm is proposed for spaceborne radar reflectivity using the HMT model as prior information. Owing to the small and transient storm elements embedded in the larger and slowly varying elements, the radar precipitation data exhibit distinct multiscale statistical properties, including a non-Gaussian structure and scale-to-scale dependency. An HMT model can capture well the statistical properties of radar precipitation, where the wavelet coefficients in each sub-band are characterized as a Gaussian mixture model (GMM), and the wavelet coefficients from the coarse scale to fine scale are described using a multiscale Markov process. The state probabilities of the GMM are determined using the expectation maximization method, and other parameters, for instance, the variance decay parameters in the HMT model are learned and estimated from high-resolution ground radar reflectivity images. Using the prior model, the wavelet coefficients at finer scales are estimated using local Wiener filtering. The interpolation algorithm is validated using data from the precipitation radar onboard the Tropical Rainfall Measurement Mission satellite, and the reconstructed results are found to be able to enhance the spatial resolution while optimally reproducing the local extremes and gradients.     

基于注意力反向投影网络的天气雷达回波超分辨率重建算法

高分辨率的天气雷达数据能揭示探测天气目标的精细结构,对灾害性天气分析和预报预警至关重要。提高天气雷达反射率数据分辨率可以提升现有业务天气雷达对中小尺度强对流灾害性天气的监测和预警能力。本文在不改变雷达硬件的情况下,提出了基于注意力反向投影网络(Attention Back-Projection Network,ABPN)的天气雷达回波超分辨率重建算法用于提高雷达反射率数据分辨率。ABPN通过在深度反向投影网络(Deep Back-Projection Network,DBPN)中加入长短跳跃连接和通道注意力机制,对关键区域精细化重建结构特征。通过对实际天气过程超分辨率重建测试,结果表明,ABPN算法在雷达回波重建质量和主观视觉评估上有明显的优势,特别是在回波细节和天气雷达的边缘结构特征方面。     

多普勒天气雷达识别和预警下击暴流

发生在机场周围的下击暴流,对飞机起降安全构成重大威胁。多普勒天气雷达以其高时空分辨率成为监测和预警下击暴流的有力工具。对国内外利用多普勒天气雷达研究下击暴流的现状进行了综述,包括下击暴流的基本概念、回波特征以及目前国内外主要算法:基于切变段法、图像处理法和线性判别分析法。最后对多普勒天气雷达识别和预警下击暴流的研究现状进行了总结,为国内开展这方面研究提供参考和借鉴。     

Three-dimensional Fusion of Spaceborne and Ground Radar Reflectivity Data Using a Neural Network–Based Approach

The spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission satellite(TRMM PR) can provide good measurement of the vertical structure of reflectivity, while ground radar(GR) has a relatively high horizontal resolution and greater sensitivity. Fusion of TRMM PR and GR reflectivity data may maximize the advantages from both instruments.In this paper, TRMM PR and GR reflectivity data are fused using a neural network(NN)–based approach. The main steps included are: quality control of TRMM PR and GR reflectivity data; spatiotemporal matchup; GR calibration bias correction;conversion of TRMM PR data from Ku to S band; fusion of TRMM PR and GR reflectivity data with an NN method;interpolation of reflectivity data that are below PR's sensitivity; blind areas compensation with a distance weighting–based merging approach; combination of three types of data: data with the NN method, data below PR's sensitivity and data within compensated blind areas. During the NN fusion step, the TRMM PR data are taken as targets of the training NNs, and gridded GR data after horizontal downsampling at different heights are used as the input. The trained NNs are then used to obtain 3D high-resolution reflectivity from the original GR gridded data. After 3 D fusion of the TRMM PR and GR reflectivity data, a more complete and finer-scale 3D radar reflectivity dataset incorporating characteristics from both the TRMM PR and GR observations can be obtained. The fused reflectivity data are evaluated based on a convective precipitation event through comparison with the high resolution TRMM PR and GR data with an interpolation algorithm.     

The water phase of precipitation—a comparison between observed, estimated and predicted values

The results from two projects aimed at improving precipitation products for the Norwegian Road Authorities are presented and compared in this paper: A precipitation forecast with water phase type (rain, sleet, snow) from the HIRLAM weather prediction model, and a precipitation type estimate based on synoptic observations and weather radar data. Operational forecasts of water phase type from HIRLAM are biased towards predicting too many cases with snow. This is caused by the mainly positive difference between model terrain and real topography. It is shown that additional calculations of snow melting based on temperature and humidity in the lowest model level reduce this error. The second product presented here is a precipitation type estimate based on synoptic observations and weather radar data. Synoptic observations of 2 m-temperature and dew point temperature at 3 h temporal resolution are used to estimate the water phase of precipitation at ground level. The dew point temperature is converted to relative humidity. Temperature and relative humidity are interpolated in space using a digital elevation model after deriving local vertical gradients of the two variables. The water phase is estimated and merged with the actual radar precipitation estimate every 15 min. The result is a high resolution image showing the intensity and the water phase of precipitation. A comparison to observed water phase types at the synoptic stations for the winter season 2002/2003 shows that the percentage correct is 86%. The Probability of Detection is 0.84 for rain and 0.97 for snow. For January 2002, the observed, estimated, and forecasted water phase types are compared at an independent set of precipitation stations in Southern Norway. The results confirm the good quality of the precipitation type estimate and show that the adjustment of HIRLAM water phase type to real topography improves the forecast in cases with observed rain.     

FY-3A微波资料偏差订正及台风路径预报应用

我国极轨气象卫星FY-3A大大增强了对地球系统的综合探测能力,而偏差订正对卫星资料的应用非常必要。试验中FY-3A卫星微波资料的偏差订正方案是在Harris等的TOVS辐射资料偏差订正经验方法的基础上结合WRF-3DVAR系统发展的,偏差订正后微波资料各通道拟合结果基本位于主对角线上,大多数卫星观测数据与观测算子利用背景场计算的亮温值分布趋于合理,偏差得到很大程度的降低。偏差订正后,利用数值模式直接同化FY-3A气象卫星微波资料,通过对2008年和2009年的4个台风进行预报评估表明:同化FY-3A气象卫星资料后路径预报能力提高明显,尤其是36 h后路径预报结果;同化FY-3A气象卫星微波资料后台风预报路径误差平均降低20%,而只同化常规资料路径误差仅仅降低了4%。     

Atmospheric profile retrieval with AIRS data and validation at the ARM CART site

The physical retrieval algorithm of atmospheric temperature and moisture distribution from the Atmospheric InfraRed Sounder （AIRS） radiances is presented. The retrieval algorithm is applied to AIRS clear-sky radiance measurements. The algorithm employs a statistical retrieval followed by a subsequent nonlinear physical retrieval. The regression coefficients for the statistical retrieval are derived from a dataset of global radiosonde observations （RAOBs） comprising atmospheric temperature, moisture, and ozone profiles. Evaluation of the retrieved profiles is performed by a comparison with RAOBs from the Atmospheric Radiation Measurement （ARM） Program Cloud And Radiation Testbed （CART） in Oklahoma, U. S. A.. Comparisons show that the physically-based AIRS retrievals agree with the RAOBs from the ARM CART site with a Root Mean Square Error （RMSE） of 1K on average for temperature profiles above 850 hPa, and approximately 10% on average for relative humidity profiles. With its improved spectral resolution, AIRS depicts more detailed structure than the current Geostationary Operational Environmental Satellite （GOES） sounder when comparing AIRS sounding retrievals with the operational GOES sounding products.