Simultaneous Rain Research Articles

A learning‐based approach to regression analysis for climate data–A case of Northeast China

AbstractGlobal climate change is an important issue that all of humanity needs to address together. Precipitation is an important climatic feature for agricultural development and food security, and the study of precipitation and its associated climatic factors is important for the analysis of global change. As an important part of China's food production, Northeast China has a temperate monsoon climate with simultaneous rain and heat, which is favorable for crop growth. In this paper, a scientific workflow for climate data analysis with a learning‐based method is designed. Using climate data from typical models in CMIP6, a machine learning‐based approach is used to establish regression relationships between precipitation and climate variables such as temperature, humidity and wind speed in Northeast China, which is validated through a time series approach. We design a weight‐based model ensemble method and a learning‐based bias correction method, so that the ensemble model can achieve better performance. We also analyze the precipitation trends in Northeast China under the three Shared Socio‐economic Pathways (SSPs). This will help researchers to analyze the long‐term evolution and factors of climate.

Support vector machine tropical wind speed retrieval in the presence of rain for Ku-band wind scatterometry

Abstract. Wind retrieval parameters, i.e. quality indicators and the two-dimensional variational ambiguity removal (2DVAR) analysis speeds, are explored with the aim to improve wind speed retrieval during rain for tropical regions. We apply the well-researched support vector machine (SVM) method in machine learning (ML) to solve this complex problem in a data-oriented regression. To guarantee the effectiveness of SVM, the inputs are extensively analysed to evaluate their appropriateness for this problem, before the results are produced. The comparisons between distributions and differences between data of rain-contaminated winds, corrected winds and good quality C-band winds illustrate that the rain-distorted wind distributions become more nominal with SVM, hence much reducing the rain-induced biases and error variance. Further confirmation is obtained from a case with synchronous Himawari-8 observation indicating rain (clouds) in the scene. Furthermore, the estimation of simultaneous rain rate is attempted with some success to retrieve both wind and rain. Although additional observations or higher resolution may be required to better assess the accuracy of the wind and rain retrievals, the ML results demonstrate benefits of such methodology in geophysical retrieval and nowcasting applications.

Physical Retrieval of Rain Rate from Ground-Based Microwave Radiometry

Because of its clear physical meaning, physical methods are more often used for space-borne microwave radiometers to retrieve the rain rate, but they are rarely used for ground-based microwave radiometers that are very sensitive to rainfall. In this article, an opacity physical retrieval method is implemented to retrieve the rain rate (denoted as Opa-RR) using ground-based microwave radiometer data (21.4 and 31.5 GHz) of the tropospheric water radiometer (TROWARA) at Bern, Switzerland from 2005 to 2019. The Opa-RR firstly establishes a direct connection between the rain rate and the enhanced atmospheric opacity during rain, then iteratively adjusts the rain effective temperature to determine the rain opacity, based on the radiative transfer equation, and finally estimates the rain rate. These estimations are compared with the available simultaneous rain rate derived from rain gauge data and reanalysis data (ERA5). The results and the intercomparison demonstrate that during moderate rains and at the 31 GHz channel, the Opa-RR method was close to the actual situation and capable of the rain rate estimation. In addition, the Opa-RR method can well derive the changes in cumulative rain over time (day, month, and year), and the monthly rain rate estimation is superior, with the rain gauge validated R2 and the root-mean-square error value of 0.77 and 22.46 mm/month, respectively. Compared with ERA5, Opa-RR at 31GHz achieves a competitive performance.

鼎湖山不同演替阶段森林土壤水分时空变异研究

PDF HTML阅读 XML下载 导出引用 引用提醒 鼎湖山不同演替阶段森林土壤水分时空变异研究 DOI: 10.5846/stxb201912022603 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（31600353，41430529）；广东省自然科学基金项目（2016A030310450）；广东省林业科技创新平台项目（2020-KYXM-09） Temporal and spatial variability of soil moisture in a forest succession series in Dinghushan Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:土壤水分作为森林生态系统水分蓄库的主体，森林土壤水分储量及其时空动态与变异对揭示区域植被恢复与气候变化背景下的森林生态系统水文过程响应与服务功能变化机制具有重要意义。本研究以南亚热带地区典型森林植被演替序列马尾松人工林（Pinus massoniana coniferous forest，PF）-马尾松针阔叶混交林（mixed Pinus massoniana/broad-leaved forest，MF）-季风常绿阔叶林（monsoon evergreen broad-leaved forest，MEBF）为研究对象，依托中国生态系统研究网络森林样地建设与监测统一规范对鼎湖山森林生态系统定位站站区内分布的上述森林类型土壤水分的长期定位观测（2005-2015年），通过分析各演替阶段森林土壤不同土层（0-15、15-30、30-45、45-60、60-75和75-90 cm）土壤体积含水量观测数据，探究该区域森林植被恢复过程中的土壤水分变化及其时空变异。结果表明：在雨热同期且干湿季明显的南亚热带地区，鼎湖山森林土壤储水量及其时间动态受降雨量的影响显著，森林土壤层对降雨具有强烈的调蓄和稳定作用，伴随PF→MF→MEBF自然演替进程，调蓄水分能力逐步增强。林型间，由初期阶段PF到顶级群落MEBF，森林土壤水分储量逐渐提高，且演替后期林型相对于早期林型，土壤储水量均呈现为较小的年际与年内变幅。干、湿季而言，干季时林型间的土壤储水量差异大于湿季，干季时MEBF和MF土壤含水量分别是PF的1.33倍和1.11倍。从土壤含水量的干、湿季期间变异来看，不同林型各土层土壤含水量的变异系数大小均表现为干季大于湿季；垂直剖面方向上，突出表现为无论干湿季MEBF各层土壤含水量变异均比其他两种林型较为缓和，充分体现了MEBF优越的土壤水分时空调配能力。整体上，伴随PF→MF→MEBF自然演替进程，土壤水分储量及其稳定性逐步提升。 Abstract:Soil moisture is the main component of water storage in forest ecosystems. The soil water reserve of forests and its spatiotemporal dynamics and variations are of great significance for revealing the response of hydrological processes and the change mechanism of service functions in forest ecosystems under the background of regional vegetation restoration and climate change. In this study, we focused on the typical forests in lower subtropical China: a Pinus massoniana forest (PF), mixed Pinus massoniana/broad-leaved forest (MF), and monsoon evergreen broad-leaved forest (MEBF), which formed a natural successional sequence in this region. Based on the unified standards for the construction and monitoring of forest plots by the Chinese Ecosystem Research Network, long-term positioning observation of soil moisture in the above forest types of the Dinghushan Forest Ecosystem Research Station was conducted during the 2005-2015 period. Through analysis of the measured soil volumetric water content in different soil layers (0-15, 15-30, 30-45, 45-60, 60-75 and 75-90 cm) of the above mentioned forests at each stage of succession, the change in soil water storage and its spatiotemporal variation in the process of forest vegetation restoration in this region were explored. The data showed that in the southern subtropical regions with simultaneous rain and heat and distinct dry and wet seasons, soil water storage and its seasonal dynamics in Dinghushan were significantly affected by rainfall, and the soil layer had a strong regulatory and stabilizing effect on rainfall. With natural succession from the planted (PF) to the climax (MEBF) stage, the ability to regulate and store water gradually increased. Among forest types, from the initial stage (PF) to the top community (MEBF), the soil water storage of the forest ecosystem gradually increased, and compared with the early forest types, the soil water storage of late succession forest types showed small interannual and intra-annual variation. At a seasonal scale, the difference in soil water storage between forest types in the dry season was greater than that in the wet season. The soil water content of MEBF and MF in the dry season was 1.33 times and 1.11 times that of PF, respectively. According to the variation in the soil water content in dry and wet seasons, the coefficient of variation of the soil water content in each soil layer of the different forest types was greater in the dry season than in the wet season. In the vertical direction, this coefficient of variation highlighted that the variation in the soil water content in each layer of MEBF was more moderate than that in the other two forest types in both the dry and wet seasons, which reflected the superior water regulation ability of MEBF. On the whole, with natural succession from the planted (PF) to the climax (MEBF) forest, the soil water storage and its stability improved. 参考文献 相似文献 引证文献

Evaluation and Mitigation of Rain Effect on Wave Direction and Period Estimation From X-Band Marine Radar Images

In this article, the accuracy of wave direction and period estimation from <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">X</i> -band marine radar images under different rain rates is analyzed, and a simple subimage selection scheme is proposed to mitigate the rain effect. First, each radar image is divided into multiple subimages, and the subimages with relatively clear wave signatures are identified based on the random-forest-based classification model. Then, wave direction is estimated by performing the Radon transform on each valid subimage. As for wave period estimation, a new method is proposed. Texture features are first extracted from each pixel of the selected subimage using the gray-level co-occurrence matrix and combined as a feature vector. Those feature vectors extracted from both rain-free and rain-contaminated training samples are then used to train a random-forest-based wave period regression model. The shore-based <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">X</i> -band marine radar images, simultaneous rain rate data, as well as buoy-measured wave data collected on the West Coast of the United States are used to analyze the rain effect on wave parameter estimation accuracy and validate the proposed method. Experimental results show that the proposed subimage selection scheme improves the estimation accuracy of both wave direction and wave period under different rain rates, with reductions of root-mean-square errors (RMSEs) by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{6.9}^\circ$</tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{6.0}^\circ$</tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{4.9}^\circ$</tex-math></inline-formula> , and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{1.0}^\circ$</tex-math></inline-formula> for wave direction under rainless, light rain, moderate rain, and heavy rain conditions, respectively. As for wave period estimation, the RMSEs decrease by 0.13, 0.20, 0.30, and 0.20 s under those four rainfall intensity levels, respectively.

Rain Detection From X-Band Marine Radar Images: A Support Vector Machine-Based Approach

Since rain alters the histogram pattern of radar images, rain-contaminated radar data can be identified. In this article, a support vector machine (SVM)-based method for rain detection using X-band marine radar images is presented. First, the normalized histogram bin values for each image are extracted and combined into feature vector. Then, SVMs are employed to classify between rain-free and rain-contaminated images. Radar images and simultaneous rain rate data collected from a sea trial in North Atlantic Ocean are utilized for model training and testing. Comparison with the zero pixel percentage (ZPP) threshold method shows that the SVM-based method obtains higher detection accuracy, with 98.4% for the Decca radar data and 99.7% for the Furuno radar. It is also found that as the total number of bins does not significantly affect detection accuracy, the proposed method can be applied to different radar systems directly with a suitable number of bins. In addition, compared to the ZPP threshold method, the SVM-based method proves to be more robust even with limited training samples.

Validation of the Hurricane Imaging Radiometer Forward Radiative Transfer Model for a Convective Rain Event

The airborne Hurricane Imaging Radiometer (HIRAD) was developed to remotely sense hurricane surface wind speed (WS) and rain rate (RR) from a high-altitude aircraft. The approach was to obtain simultaneous brightness temperature measurements over a wide frequency range to independently retrieve the WS and RR. In the absence of rain, the WS retrieval has been robust; however, for moderate to high rain rates, the joint WS/RR retrieval has not been successful. The objective of this paper was to resolve this issue by developing an improved forward radiative transfer model (RTM) for the HIRAD cross-track viewing geometry, with separated upwelling and specularly reflected downwelling atmospheric paths. Furthermore, this paper presents empirical results from an unplanned opportunity that occurred when HIRAD measured brightness temperatures over an intense tropical squall line, which was simultaneously observed by a ground based NEXRAD (Next Generation Weather Radar) radar. The independently derived NEXRAD RR created the simultaneous 3D rain field “surface truth”, which was used as an input to the RTM to generate HIRAD modeled brightness temperatures. This paper presents favorable results of comparisons of theoretical and the simultaneous, collocated HIRAD brightness temperature measurements that validate the accuracy of this new HIRAD RTM.

Restoring Natural River Flows, Through Optimal Ground WaterRecharge and Improved Drainage Prevention of Pollution in Rivers

Prevention of pollution in rivers and water bodies involves proper treatment of the sewage, drainage and other liquid effluents joining the river streams,as well as maintaining the natural river flows which have been diminishing due to the excessive drawl of river stream waters for the purpose of drinking water schemes, irrigation and some industrial uses, where ground water could be used, if available. Sub-soil ground water levels have also been going down on account of the excessive population growth in the last six decades, resulting into more and more dependence on river waters. This situation needs to be changed by enhancing the rain water harvesting and ground water recharge volumes with innovative and special measures so as to return to minimum drawl of river waters for drinking and other uses. The proposed measures could be summarized as follows. (i) Restoring Natural River Flows would involve (a) Reducing the surface water Drawl to a minimum. (b) Optimal Utilization of Ground Water for Drinking Water Supply, Irrigation and other uses. (c) Enhancing River Flows through improved surface drainage. (ii) Synchronized Water Supply and Precipitation Storage-cum- Recharge Systems in Water Scarcity areas. (a) Water Supply Schemes equipped with simultaneous rain water harvesting structures. (iii) Optimal Ground Water Recharge and Improved Drainage by innovative and special methods such as (a) Optimal Ground Water Recharge through Village Ponds, equipped with precipitation overflow diversion and recharge system. (b) Waste Water Drainage Treatment at discharge points before outfall into rivers.

Hybrid nanogenerator and enhancement of water–solid contact electrification using triboelectric charge supplier

Artificially embedded surface charges can dramatically improve the output energy of water–solid contact electrification devices, but the embedded charges easily escape or are cancelled out by adsorption of opponent ions in ambient conditions. Here, we demonstrate a hybrid energy harvesting nanogenerator by combing water–solid and solid–solid contact electrification schemes. It consists of a water–solid contact electrification device and wind-fluttering ribbons that regularly supplies triboelectric surface charges on the solid surface and hence, the high density of surface charges can remain on the surface. This scheme can enhance the harvesting energy by up to a factor of 30 during rain. Moreover, the fluttering ribbons independently collect electric energy from mild winds without rain. This scheme provides a facile, cost-effective, and robust approach to enhance the energy-harvesting efficiency of a water–solid contact electrification device and to combine the energy harvesting from simultaneous rain and wind.

Potential Use of BEST® Sediment Trap in Splash - Saltation Transport Process by Simultaneous Wind and Rain Tests.

The research on wind-driven rain (WDR) transport process of the splash-saltation has increased over the last twenty years as wind tunnel experimental studies provide new insights into the mechanisms of simultaneous wind and rain (WDR) transport. The present study was conducted to investigate the efficiency of the BEST® sediment traps in catching the sand particles transported through the splash-saltation process under WDR conditions. Experiments were conducted in a wind tunnel rainfall simulator facility with water sprayed through sprinkler nozzles and free-flowing wind at different velocities to simulate the WDR conditions. Not only for vertical sediment distribution, but a series of experimental tests for horizontal distribution of sediments was also performed using BEST® collectors to obtain the actual total sediment mass flow by the splash-saltation in the center of the wind tunnel test section. Total mass transport (kg m-2) were estimated by analytically integrating the exponential functional relationship using the measured sediment amounts at the set trap heights for every run. Results revealed the integrated efficiency of the BEST® traps at 6, 9, 12 and 15 m s-1 wind velocities under 55.8, 50.5, 55.0 and 50.5 mm h-1 rain intensities were, respectively, 83, 106, 105, and 102%. Results as well showed that the efficiencies of BEST® did not change much as compared with those under rainless wind condition.

Large‐scale correlation of rainfall rate based on data from Spanish sites

SUMMARYModern and future satellite systems working in the Ka and Q/V bands often require the application of site diversity to mitigate the degradations caused by rain. Satellite systems operating in these bands may make use of multi‐beam techniques to provide high‐capacity services. To achieve an efficient performance in both techniques, precise information is necessary on the occurrence of simultaneous rain fades in various links under a given satellite coverage. This is attained through the knowledge of the spatial characteristics of rainfall rate over the area of interest.The availability of a large database of rain gauge data from about 50 sites in Spain has allowed the undertaking of a study on the large‐scale spatial distribution of rainfall rate. Joint distributions and correlation parameters have been investigated for pairs of sites, and experimental results have been compared with predictions based on the ITU‐R site diversity model, obtaining the best results when stratiform rainfall is dominant in both sites. Some statistical dependence has been found even for distances above 700 km. The values obtained from the statistical analysis have been represented taking a given site as reference in maps of contour lines using standard mapping procedures. Correlation parameters are expected to decrease with distance; however, the contour maps reveal a significant influence of climatic and geographic factors such as weather fronts, orography or the proximity to the sea. The statistics and maps obtained are useful to optimise both power sharing in multi‐beam satellite systems and the application of site diversity. Copyright © 2014 John Wiley &amp; Sons, Ltd.

Short-Term Rain Attenuation Frequency Scaling for Satellite Up-Link Power Control Applications

In this paper, a novel stochastic dynamic model for the short-term frequency scaling of rain attenuation is presented. The model captures the dynamic characteristics of the instantaneous frequency scaling factor and provides the means to incorporate them in simultaneous rain attenuation time series generation, as well as in analytical calculations. Moreover, an analytical framework is proposed for rain attenuation prediction at a given frequency based on the rain attenuation measured at another frequency. The proposed model can be used for the timely activation of an open-loop up-link power control scheme in broadband satellite communication networks operating at frequencies above 10 GHz. It is applied to simulated rain attenuation data that have been obtained using the Synthetic Storm Technique on rain rate experimental data. Finally, it is shown how the new model improves the performance of an up-link power control scheme in terms of system availability.

Yearly variability of rain attenuation over a communication link at 13 GHz during monsoon months over Indian eastern region

In this paper, results on yearly variability of measured attenuation at 13 GHz under rainy conditions over a microwave communication link path situated between Sarojini College and Airport of Dum Dum area in Kolkata have been presented. The link belongs to an user agency and suffers a large attenuation due to heavy rain. The variation microwave amplitude was monitored and rain rate measurements were made on regular basis simultaneously by a fast response rain gauge in the monsoon months during 2007 and 2008. The observed microwave radio signal was characterized with a steady signal level ~−42 to −43 dBm with fade depth ~1 to 2 dB under clear sky situation. The results on attenuation have been studied in relation to simultaneous rain rate measurements. Yearly variability of rain attenuation has also been highlighted. These results are also useful for designing and installation of future microwave communication links both for terrestrial and satellite paths in this part of India, where rain characteristics are similar to Indian eastern coastal station. The probability distribution of attenuation and rain rates has been deduced from measured observations.

18.7 GHz tropospheric scintillation and simultaneous rain attenuation measured at Spino d'Adda and Darmstadt with Italsat

We present experimental results on the relationship between rain attenuation and simultaneous scintillation, obtained with measurements of attenuation time series at 18.7 GHz, collected in two slant paths to Italsat (13.2° E): at Spino d'Adda (Italy, a 37.7° slant path, times series of 50 samples/s and 1 sample/s) and Darmstadt (Germany, a 32.7° slant path, 1 sample/s). We have found that the average rain attenuation A (dB) and the average standard deviation σm (dB) in 1‐min intervals (calculated from the 1 sample/s time series), of the scintillation standard deviation σ (dB), are linked by a power law σm = C3aA, or by the more refined model σm = C3bA, that can be due to an effective thin layer of turbulence aloft. The constants C3a,3b can be estimated by applying the ITU−R formula for scintillation predictions. For conservative design, a best fit model of the conditional standard deviation of σ is also provided, as a function of A, as σs = CsAd (dB), where Cs and d are constants.

Case Study of the Rain Attenuation at Ka Band

This paper presents one year rain rate intensity and rain attenuation at Universiti Sains Malaysia (USM). Communication systems operating at frequencies above 10 GHz in equatorial climates are subjected to many fade occurrences due to heavy rain. Measurement of rain attenuation at Ku-band will be used to estimate the rain attenuation at Ka-band. The Ramachandran and Kumar model was used to calculate rain attenuation at Ka-band. Rain rate analysis using 1-minute data measurement at USM shows that the rain rate exceeded 110 mm/h for 0.01% of a year (R 0.01). Simultaneous rain attenuation (A 0.01) at Ku-band was at 18 dB and by using the predicted model, the rain attenuation at Ka-band was found to be 30 dB at 0.01% of time rain attenuation exceeded.

Fog collection in the western Mediterranean basin (Valencia region, Spain)

Four different mountainous locations were selected in the Valencia region, East coast of the Iberian Peninsula, for fog water collection studies. Data for 2004 were obtained by means of an instrument ensemble consisting essentially of a passive cylindrical fog water collector, a raingauge, a wind direction and velocity sensor and a temperature and humidity probe. An approximate data reduction technique was also found for this specific ensemble to eliminate the simultaneous rain water component from the fog water measurements. Main results indicate that fog water collection holds significant potential in this region, and especially for southern locations. Annual rates of fog water yield can be as high as 7.0 l/m 2/day in the southern locations, in contrast to 2.0 l/m 2/day collected at one site in a northern location. The highest summer fog water yield was 4.6 l/m 2/day, a relatively large value. Except for the summer period, fog episodes delivering sizeable water volumes are inherently coupled to rainfall. Hourly frequencies of fog collection were also examined to show a distinct daily cycle in summer, denoting orographic fog formation during this period. Lastly, winds were analysed to resolve the most suitable directions for fog collector alignment.

Monitoring of rainfall by ground-based passive microwave systems: models, measurements and applications

Abstract. A large set of ground-based multi-frequency microwave radiometric simulations and measurements during different precipitation regimes are analysed. Simulations are performed for a set of frequencies from 22 to 60 GHz, representing the channels currently available on an operational ground-based radiometric system. Results are illustrated in terms of comparisons between measurements and model data in order to show that the observed radiometric signatures can be attributed to rainfall scattering and absorption. An inversion algorithm has been developed, basing on the simulated data, to retrieve rain rate from passive radiometric observations. As a validation of the approach, we have analyzed radiometric measurements during rain events occurred in Boulder, Colorado, and at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains (SGP) site in Lamont, Oklahoma, USA, comparing rain rate estimates with available simultaneous rain gauge data.

Modeling and measurement of rainfall by ground-based multispectral microwave radiometry

The potential of ground-based multispectral microwave radiometers in retrieving rainfall parameters is investigated by coupling physically oriented models and retrieval methods with a large set of experimental data. Measured data come from rain events that occurred in the USA at Boulder, Colorado, and at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains (SGP) site in Lamont, OK. Rain cloud models are specified to characterize both nonraining clouds, stratiform and convective rainfall. Brightness temperature numerical simulations are performed for a set of frequencies from 20 to 60 GHz at zenith angle, representing the channels currently deployed on a commercially available ground-based radiometric system. Results are illustrated in terms of comparisons between measurements and model data in order to show that the observed radiometric signatures can be attributed to rainfall scattering and absorption. A new statistical inversion algorithm, trained by synthetic data and based on principal component analysis is also developed to classify the meteorological background, to identify the rain regime, and to retrieve rain rate from passive radiometric observations. Rain rate estimate comparisons with simultaneous rain gauge data and rain effect mitigation methods are also discussed.

Correction to "Separation of Simultaneous Rain and Ice Depolarization"

Correction to "Separation of Simultaneous Rain and Ice Depolarization"

Separation of Simultaneous Rain and Ice Depolarization

In the case of depolarization due to rain or to ice crystals, the differential attenuation, the differential phase shift, and the canting angle of the depolarizing medium can all be calculated independently from dual polarized measurement results. However, this is not possible when rain and ice are causing depolarization at the same time. This paper presents a calculation method which makes it possible to derive during simultaneous rain and ice depolarization some of the characterising parameters of each part separately. The method makes use of an a priori known relation between the differential attenuation and the differential phase shift of rain and of ice. The calculation method is tested on measured depolarization events, and yields good results.