By setting the value of productive assets under different types of ownership of the means of production as the marginal criterion for measuring the relative position of each form of ownership, we estimate the scale of...By setting the value of productive assets under different types of ownership of the means of production as the marginal criterion for measuring the relative position of each form of ownership, we estimate the scale of public and non-public sector assets in primary industry in China and changes in their relative proportions. Further, on the basis of previous estimates, we provide an extended estimate of the scale of public and non-public sector assets in secondary and tertiary industry and changes in their relative proportions. We found that in 2012, total productive assets in primary, secondary and tertiary industry were 487.53 trillion RMB, of which the public sector accounted for 53 percent, or 258.39 trillion RMB. In secondary and tertiary industry, the non-public sector contributed 67.59 percent and 75.20 percent respectively in terms of value- added and employment. This indicates the vitality of China＇s basic socialist economic system, in which public sector assets retain a dominant position and the non-public sector makes the primary economic contribution, and thus provides a theoretical justification for ownership reform in the primary stage of socialism in China and the ＂two unswervinglies＂ policy.展开更多
As one of the longest strike-slip fault in Asia,the Altyn Tagh Fault（ATF）defines the northern boundary of the Tibetan Plateau and plays a significant role inaccommodating the deformation resulting from the IndiaAsia...As one of the longest strike-slip fault in Asia,the Altyn Tagh Fault（ATF）defines the northern boundary of the Tibetan Plateau and plays a significant role inaccommodating the deformation resulting from the IndiaAsia convergence.展开更多
In this paper,a quantitative precipitation estimation based on the hydrometeor classification(HCA-QPE)algorithm was proposed for the first operational S band dual-polarization radar upgraded from the CINRAD/SA radar o...In this paper,a quantitative precipitation estimation based on the hydrometeor classification(HCA-QPE)algorithm was proposed for the first operational S band dual-polarization radar upgraded from the CINRAD/SA radar of China.The HCA-QPE algorithm,localized Colorado State University-Hydrometeor Identification of Rainfall(CSUHIDRO)algorithm,the Joint Polarization Experiment(JPOLE)algorithm,and the dynamic Z-R relationships based on variational correction QPE(DRVC-QPE)algorithm were evaluated with the rainfall events from March 1 to October 30,2017 in Guangdong Province.The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction,its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5 mm h-1;and the stronger the rainfall intensity,the greater the QPE improvement.Besides,the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms.This study preliminarily evaluated the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.展开更多
This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates （SEs）, and numerical predictions at the global scale. The strategy is designed to remove syste...This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates （SEs）, and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions （MPs） over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation （OI）-based merging scheme （referred as the HL-OI scheme） is used to combine unbiased gahge observations, SEs, and MPs to reduce random error from each source and to produce a gauge--satellite-model merged daily precipitation analysis, called BMEP-d （Beijing Climate Center Merged Estimation of Precipitation with daily resolution）, with complete global coverage. The BMEP-d data from a four-year period （2011- 14） demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD （GPCP one-degree daily） show that the consistencies between B MEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.展开更多
The Gated Recurrent Unit(GRU) neural network has great potential in estimating and predicting a variable. In addition to radar reflectivity(Z), radar echo-top height(ET) is also a good indicator of rainfall rate(R). I...The Gated Recurrent Unit(GRU) neural network has great potential in estimating and predicting a variable. In addition to radar reflectivity(Z), radar echo-top height(ET) is also a good indicator of rainfall rate(R). In this study, we propose a new method, GRU_Z-ET, by introducing Z and ET as two independent variables into the GRU neural network to conduct the quantitative single-polarization radar precipitation estimation. The performance of GRU_Z-ET is compared with that of the other three methods in three heavy rainfall cases in China during 2018, namely, the traditional Z-R relationship(Z=300R1.4), the optimal Z-R relationship(Z=79R1.68) and the GRU neural network with only Z as the independent input variable(GRU_Z). The results indicate that the GRU_Z-ET performs the best, while the traditional Z-R relationship performs the worst. The performances of the rest two methods are similar.To further evaluate the performance of the GRU_Z-ET, 200 rainfall events with 21882 total samples during May–July of 2018 are used for statistical analysis. Results demonstrate that the spatial correlation coefficients, threat scores and probability of detection between the observed and estimated precipitation are the largest for the GRU_Z-ET and the smallest for the traditional Z-R relationship, and the root mean square error is just the opposite. In addition, these statistics of GRU_Z are similar to those of optimal Z-R relationship. Thus, it can be concluded that the performance of the GRU_ZET is the best in the four methods for the quantitative precipitation estimation.展开更多
The performance of different quantitative precipitation estimation(QPE) relationships is examined using the polarimetric variables from the X-band polarimetric phased-array radars in Guangzhou,China.Three QPE approach...The performance of different quantitative precipitation estimation(QPE) relationships is examined using the polarimetric variables from the X-band polarimetric phased-array radars in Guangzhou,China.Three QPE approaches,namely,R(ZH),R(ZH,ZDR) and R(KDP),are developed for horizontal reflectivity,differential reflectivity and specific phase shift rate,respectively.The estimation parameters are determined by fitting the relationships to the observed radar variables using the T-matrix method.The QPE relationships were examined using the data of four heavy precipitation events in southern China.The examination shows that the R(ZH) approach performs better for the precipitation rate less than 5 mm h-1, and R(KDP) is better for the rate higher than 5 mm h-1, while R(ZH,ZDR) has the worst performance.An adaptive approach is developed by taking the advantages of both R(ZH) and R(KDP) approaches to improve the QPE accuracy.展开更多
Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a mult...Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.展开更多
The removal of organic matter and iron oxides could increase and decrease soil CEC in tropical and subtropical regions, but the quantitative information is insufficient so far about the change of soil CEC, the influen...The removal of organic matter and iron oxides could increase and decrease soil CEC in tropical and subtropical regions, but the quantitative information is insufficient so far about the change of soil CEC, the influence factors and their contribution. In this study, the subhorizon soils of 24 soil series in the tropical and subtropical China were used, pH, particle size composition, organic matter, iron oxides of these samples were measured, and also CECs were measured and compared for the original soils and after the removal of organic matter and iron oxides. The results showed that, compared with CEC of the original soil, the eliminating organic matter increased soil CEC significantly by 2.28% - 56.50% with a mean of 24.02%, but the further obliterating iron oxides decreased soil CEC significantly by 0.75% - 20.30% with a mean of 7.73%. CEC after the removal of organic matter and iron oxides had positive correlation with iron oxides (p < 0.01) and negative correlation with sand content (p < 0.01 and p < 0.05). CEC after organic matter eliminated was mainly decided by iron oxides (51.68%), followed by silt content (22.19%);while CEC after iron oxides obliterated was mainly determined by iron oxides (50.55%). The increase of CEC after organic matter eliminated was co-affected by the contents of clays, slits, iron oxides and pH (22.00% - 27.34%), while the decrease of CEC after iron oxides obliterated further was dominated by the content of organic matter (66.92%). More other soil parameters should be considered for higher predicting accuracy in the regression model of soil CEC after the removal of organic matter and iron oxides, and the recommended optimal models obtained in this study were as follows: for soil CEC after organic matter eliminated, CEC = 1.665 <span style="white-space:nowrap;">−</span> 0.546pH <span style="white-space:nowrap;">−</span> 0.024OM + 0.053Fe<sub>x</sub>O<sub>y</sub> <span style="white-space:nowrap;">−</span> 0.001Silt + 0.007Clay + 0.972CEC<sub>original</sub> (R<sup>2</sup> was 0.923, RSME was 1.55 cmol(+)<span style="white-space:nowrap;"><span style="white-space:nowrap;">∙</span></span>kg<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>1</sup>, p < 0.01), while for soil CEC after iron oxides further obliterated, CEC = 1.665 <span style="white-space:nowrap;">−</span> 0.546pH <span style="white-space:nowrap;">−</span> 0.024OM + 0.053Fe<sub>x</sub>O<sub>y</sub> <span style="white-space:nowrap;">−</span> 0.001Silt + 0.007Clay + 0.972CEC<sub>original</sub> (R<sup>2</sup> was 0.923, RMSE was 1.55 cmol(+)<span style="white-space:nowrap;"><span style="white-space:nowrap;">∙</span></span>kg<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>1</sup>, p < 0.01). Further research is needed in the future as for exploring internal functional mechanism in view of soil electrochemistry and mineralogy.展开更多
For a better understanding of the air mass exchange processes between the surface and free atmos-phere in the Himalayas,a Himalayan exchange between the surface and troposphere 2007 (HEST2007) campaign was carried out...For a better understanding of the air mass exchange processes between the surface and free atmos-phere in the Himalayas,a Himalayan exchange between the surface and troposphere 2007 (HEST2007) campaign was carried out in the Rongbuk Valley,on the northern slope of Mt.Qomolangma,in June 2007.The wind,tem-perature and radiation conditions were measured during the campaign.Using these observation data,together with the National Centers for Environmental Prediction/the National Center for Atmospheric Research (NCEP/NCAR) reanalysis data,the air mass exchange between the inside of the valley and the outside of the valley is quantitatively estimated,based on a closed-valley method.The air mass is strongly injected into the Rongbuk Valley in the after-noon,which dominates the diurnal cycle,by a strong downward along-valley wind,with a maximum down-ward transfer rate of 9.4 cm s?1.The total air volume flux injected into the valley was 2.6×1011 m3 d?1 in 24 hours in June 2007,which is 15 times the total volume of the val-ley.The air mass transfer into the valley also exhibited a clear daily variation during the HEST2007 campaign,which can be affected by the synoptic situations through the adjustment of local radiation conditions.展开更多
Quantitative thickness estimation of thin-layer is a great challenge in seismic exploration, especially for thin-layer below tuning thickness. In this article, we analyzed the seismic response cha- racteristics of rhy...Quantitative thickness estimation of thin-layer is a great challenge in seismic exploration, especially for thin-layer below tuning thickness. In this article, we analyzed the seismic response cha- racteristics of rhythm and gradual type of thin-layer wedge models and presented a new method for thin-layer thickness estimation which uses relative peak frequency increment. This method can de- scribe the peak frequency to thickness relationship of rhythm and gradual thin-layers in unified equa- tion while the traditional methods using amplitude information cannot. What＇s more, it won＇t be in- fluenced by the absolute value of thin-layer reflection coefficient and peak frequency of wavelet. The unified equations were presented which can be used for rhythm and gradual thin-layer thickness cal- culation. Model tests showed that the method we introduced has a high precision and it doesn＇t need to determine the value of top or bottom reflection coefficient, so it has a more wide application in practice. The application of real data demonstrated that the relative peak frequency increment attribute can character the plane distribution feature and thickness characteristic of channel sand bodies very well.展开更多
A new method in making judgment matrix is proposed based on a basic value of “importance” and a relative measure level of “importance”. Factors affecting petroleum exploration are analyzed and Experts’ judgment m...A new method in making judgment matrix is proposed based on a basic value of “importance” and a relative measure level of “importance”. Factors affecting petroleum exploration are analyzed and Experts’ judgment matrix on a geologic formation is given. Expected value of each factor is computed and the volume of recoverable oil is estimated.展开更多
Objective This study focused on the Namco, the largest lake on the Tibet plateau as well as the highest large lake in the world. A large imbalance between water input and output of this lake has attracted great atten...Objective This study focused on the Namco, the largest lake on the Tibet plateau as well as the highest large lake in the world. A large imbalance between water input and output of this lake has attracted great attention in the field of hydrogeology during recent years. As there is no surface outflow from Namco, the large water imbalance can only be explained by water seepage. Synthetic aperture radar （SAR） image data were used for the first time in combination with hydrological data actually measured in the field and meteorological station data, to quantitatively acquire the information of surface fluctuation, water storage variation, and to estimate groundwater leakage from Namco Lake. The results provide theoretical support and data for further understanding the processes and extent of water resource response to global climate change, and also provide a scientific basis for rational development and utilization of water resource in the Tibetan Plateau.展开更多
With the pros and cons of the traditional optimization and probability pairing methods thoroughly considered, an improved optimal pairing window probability technique is developed using a dynamic relationship between ...With the pros and cons of the traditional optimization and probability pairing methods thoroughly considered, an improved optimal pairing window probability technique is developed using a dynamic relationship between the base reflectivity Z observed by radar and real time precipitation I by rain gauge. Then, the Doppler radar observations of base reflectivity for typhoons Haitang and Matsa in Wenzhou are employed to establish various Z-I relationships, which are subsequently used to estimate hourly precipitation of the two typhoons. Such estimations are calibrated by variational techniques. The results show that there exist significant differences in the Z-I relationships for the typhoons, leading to different typhoon precipitation efficiencies. The typhoon precipitation estimated by applying radar base reflectivity is capable of exhibiting clearly the spiral rain belts and mesoscale cells, and well matches the observed rainfall. Error statistical analyses indicate that the estimated typhoon precipitation is better with variational calibration than the one without. The variational calibration technique is able to maintain the characteristics of the distribution of radar-estimated typhoon precipitation, and to significantly reduce the error of the estimated precipitation in comparison with the observed rainfall.展开更多
Glacier-lake outburst debris flow(GLODF),unique in high altitude mountains where modern glacier is active,is significantly large in its scale of time and space,and strong in power of destroy.Following the world's ...Glacier-lake outburst debris flow(GLODF),unique in high altitude mountains where modern glacier is active,is significantly large in its scale of time and space,and strong in power of destroy.Following the world's becoming warmer,GLODF frequency gradually rises.In late years,quantitative estimation methodologies has been put into use of mass GLODF estimations.To improve former methodologies,this article suggests that the glacier(or the massif)on the trailing edge and the moraine dam are the two major systems providing independent glacier lake outburst possibilities.Bucket Effect exists in GLODF issues.Therefore focusing on the relatively unstable one of the above two provides better accuracy in estimation on GLODF possibility.Thus,this article summarizes method of presort through specific GLODF evaluation.展开更多
This study utilized data from an X-band phased array weather radar and ground-based rain gauge observations to conduct a quantitative precipitation estimation(QPE)analysis of a heavy rainfall event in Xiong an New Are...This study utilized data from an X-band phased array weather radar and ground-based rain gauge observations to conduct a quantitative precipitation estimation(QPE)analysis of a heavy rainfall event in Xiong an New Area from 20:00 on August 21 to 07:00 on August 22,2022.The analysis applied the Z-R relationship method for radar-based precipitation estimation and evaluated the QPE algorithm s performance using scatter density plots and binary classification scores.The results indicated that the QPE algorithm accurately estimates light to moderate rainfall but significantly underestimates heavy rainfall.The study identified disparities in the predictive accuracy of the QPE algorithm across various precipitation intensity ranges,offering essential insights for the further refinement of QPE techniques.展开更多
In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal s...In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal scales for better monitoring and prediction of these phenomena,as could be provided by weather radars.Based on an extensive archive of data from the X-band polarimetric radar and rain gauges observations gathered during the intensive AMMA campaigns in 2006–2007 and the Megha-Tropiques satellite measurement validation programme in 2010 in West Africa,we(i)simulated jointly realistic data for polarimetric radar variables and rain intensity using copula,and(ii)assessed rain rate estimation methods based on neural network(NN)inversion techniques and non-linearly calibrated parametric algorithms.The assessment of rainfall rate retrieval by these estimators is carried out using the part of the observations database not employed for calibration steps.The multiparametric algorithms R(ZH,K_(DP))and R(Z_(DR),K_(DP))perform better than R(ZH,Z_(DR))and R(ZH,Z_(DR),K_(DP)),especially since they are calibrated using copulas with upper tail dependencies,with KGE ranging in 0.68–0.75 and 0.79–0.82,respectively versus ranges of 0.40–0.64 and 0.20–0.51,for the two latter estimators.The neural network-based estimators RNN(Z_(DR),K_(DP))and RNN(ZH,K_(DP)),show KGE score characteristics comparable to those obtained from the best parametric relations,specifically optimized for the synthetic copula-based dataset.However,the neural network-based estimators were shown to be more robust when applied to a specific rainfall event.More specifically,neural network-based estimators trained on synthetic data are sensitive to the copulas’ability to capture the dependence between the variables of interest over the entire distribution of joint values.This leads to a near-cancellation of sensitivity to variability in the raindrop size distribution,as shown the coefficients of correlation near 1,especially for RNN(Z_(DR),K_(DP)),and for less extent RNN(Z_(H),K_(DP)).展开更多
The author’s combined numerical model consisting of a third generation shallow water wave model and a 3 D tide surge model with wave dependent surface wind stress were used to study the influence of waves on tide sur...The author’s combined numerical model consisting of a third generation shallow water wave model and a 3 D tide surge model with wave dependent surface wind stress were used to study the influence of waves on tide surge motion. For the typical weather case, in this study, the magnitude and mechanism of the influence of waves on tide surges in the Bohai Sea were revealed for the first time. The results showed that although consideration of the wave dependent surface wind stresses raise slightly the traditional surface wind stress, due to the accumulated effects, the computed results are improved on the whole. Storm level maximum modulation can reach 0.4 m. The results computed by the combined model agreed well with the measured data.展开更多
The municipal solid waste (msw) is a source of landfill gas (msw)—with methane gas content. Preoccupations for landfill gas (msw) management date back since 1976 when, at a landfill (msw) in California (USA), it turn...The municipal solid waste (msw) is a source of landfill gas (msw)—with methane gas content. Preoccupations for landfill gas (msw) management date back since 1976 when, at a landfill (msw) in California (USA), it turned out practically that the landfill gas (msw) with methane gas content contains a gas with high caloric value that can be collected and used for economic purposes. The landfill gas (msw) contains methane gas (30% - 60% volume), carbon dioxide (45% - 50% volume), hydrogen sulfide and other gases. Methane gas, carbon dioxide, nitrous oxide and other gases are listed in Kyoto Protocol as high greenhouse gases. Their ecological-rational management is both a national and global preoccupation. In terms of greenhouse gases, especially methane gas, the landfill (msw) is held responsible for 3.5% - 5% of the total global greenhouse gases. Practically, the quantitative estimation of the methane gas in a municipal solid waste landfill can be done by measuring the landfill gas (msw) flow in an extraction-collection well. In Romania, a quantitative estimation relationship of methane gas from deposits (msw) was made, approaching the problem in a different way. This paper presents the calculation formula, the working algorithm, the municipal waste landfill equation and the NOMOGRAMA of a municipal solid waste landfill (msw). The NOMOGRAMA allows us to define the values for parameter -m- (number of months needed for an amount of municipal solid waste (msw) to degrade, starting with the year from which the landfill gas (msw) emission with methane gas content is calculated). Taking into account the environmental conditions for each location of municipal solid waste landfill, the calculation uses various indexes and approximations, while the fundamental parameter remains -m- defined by the NOMOGRAMA of the municipal solid waste landfill (msw). A municipal solid waste landfill (msw) is a conglomerate of waste with various biodegradation periods between 2 - 3 years and 5 - 10 - 30 years. Degradation of waste (msw) in to dissolved organic carbon will take place in a number of months defined -m- starting with the year from which the methane gas emission with the NOMOGRAMA of the municipal solid waste landfill (msw) is calculated. The -m- values for the year of the quantitative emission of methane gas can be also done analytically, which requires good experience in the ecologic-rational management of the municipal solid waste (msw).展开更多
Taking the land resources of 17 cities in Shandong Province as the basic data, the article studied on the economical supporting capacity of land resources in terms of the effect of land on economy. The author classifi...Taking the land resources of 17 cities in Shandong Province as the basic data, the article studied on the economical supporting capacity of land resources in terms of the effect of land on economy. The author classified 17 cities of Shandong Province into four types according to the economical supporting capacity of land resources by quantitatively estimating the evaluation indices of the total amount of land resources, the potential of urban and other nonagricultural land, and the integrated economical sup- porting capacity of land resources, etc. The author proposes the questions requiring further study at the end of this article.展开更多
基金the project"Research on the Basic Economic System in the Primary Stage of Socialism"(Grant No.11@ZH006)commissioned by the National Social Sciences Fund for 2011
文摘By setting the value of productive assets under different types of ownership of the means of production as the marginal criterion for measuring the relative position of each form of ownership, we estimate the scale of public and non-public sector assets in primary industry in China and changes in their relative proportions. Further, on the basis of previous estimates, we provide an extended estimate of the scale of public and non-public sector assets in secondary and tertiary industry and changes in their relative proportions. We found that in 2012, total productive assets in primary, secondary and tertiary industry were 487.53 trillion RMB, of which the public sector accounted for 53 percent, or 258.39 trillion RMB. In secondary and tertiary industry, the non-public sector contributed 67.59 percent and 75.20 percent respectively in terms of value- added and employment. This indicates the vitality of China＇s basic socialist economic system, in which public sector assets retain a dominant position and the non-public sector makes the primary economic contribution, and thus provides a theoretical justification for ownership reform in the primary stage of socialism in China and the ＂two unswervinglies＂ policy.
基金supported by the National Natural Sciences Foundation of China(Grants No.41202156 and 41330211)China Geological Survey(Grants No.12120115026901 and 12120115027001)the Institute of Geology,CAGS(Grant No.J1520)
文摘As one of the longest strike-slip fault in Asia,the Altyn Tagh Fault（ATF）defines the northern boundary of the Tibetan Plateau and plays a significant role inaccommodating the deformation resulting from the IndiaAsia convergence.
基金National Key Research and Development Program of China(2017YFC1404700,2018YFC1506905)Open Research Program of the State Key Laboratory of Severe Weather(2018LASW-B09,2018LASW-B08)+7 种基金Science and Technology Planning Project of Guangdong Province,China(2019B020208016,2018B020207012,2017B020244002)National Natural Science Foundation of China(41375038)Special Scientific Research Fund of Meteorological Public Welfare Profession of China(GHY201506006)2017-2019Meteorological Forecasting Key Technology Development Special Grant(YBGJXM(2017)02-05)Guangdong Science&Technology Plan Project(2015A020217008)Zhejiang Province Major Science and Technology Special Project(2017C03035)Scientific and Technological Research Projects of Guangdong Meteorological Service(GRMC2018M10)Natural Science Foundation of Guangdong Province(2018A030313218)
文摘In this paper,a quantitative precipitation estimation based on the hydrometeor classification(HCA-QPE)algorithm was proposed for the first operational S band dual-polarization radar upgraded from the CINRAD/SA radar of China.The HCA-QPE algorithm,localized Colorado State University-Hydrometeor Identification of Rainfall(CSUHIDRO)algorithm,the Joint Polarization Experiment(JPOLE)algorithm,and the dynamic Z-R relationships based on variational correction QPE(DRVC-QPE)algorithm were evaluated with the rainfall events from March 1 to October 30,2017 in Guangdong Province.The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction,its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5 mm h-1;and the stronger the rainfall intensity,the greater the QPE improvement.Besides,the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms.This study preliminarily evaluated the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41275076, 41305057, 41175066, 41175086, and 40905046)the Beijing Natural Science Foundation (Grant No. 8144046)+1 种基金the National High Technology Research and Development Program of China (Grant Nos. 2009AA122005 and 2009BAC51B03)the National Basic Research Program of China (Grant No. 2010CB 951902)
文摘This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates （SEs）, and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions （MPs） over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation （OI）-based merging scheme （referred as the HL-OI scheme） is used to combine unbiased gahge observations, SEs, and MPs to reduce random error from each source and to produce a gauge--satellite-model merged daily precipitation analysis, called BMEP-d （Beijing Climate Center Merged Estimation of Precipitation with daily resolution）, with complete global coverage. The BMEP-d data from a four-year period （2011- 14） demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD （GPCP one-degree daily） show that the consistencies between B MEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.
基金jointly supported by the National Science Foundation of China (Grant Nos. 42275007 and 41865003)Jiangxi Provincial Department of science and technology project (Grant No. 20171BBG70004)。
文摘The Gated Recurrent Unit(GRU) neural network has great potential in estimating and predicting a variable. In addition to radar reflectivity(Z), radar echo-top height(ET) is also a good indicator of rainfall rate(R). In this study, we propose a new method, GRU_Z-ET, by introducing Z and ET as two independent variables into the GRU neural network to conduct the quantitative single-polarization radar precipitation estimation. The performance of GRU_Z-ET is compared with that of the other three methods in three heavy rainfall cases in China during 2018, namely, the traditional Z-R relationship(Z=300R1.4), the optimal Z-R relationship(Z=79R1.68) and the GRU neural network with only Z as the independent input variable(GRU_Z). The results indicate that the GRU_Z-ET performs the best, while the traditional Z-R relationship performs the worst. The performances of the rest two methods are similar.To further evaluate the performance of the GRU_Z-ET, 200 rainfall events with 21882 total samples during May–July of 2018 are used for statistical analysis. Results demonstrate that the spatial correlation coefficients, threat scores and probability of detection between the observed and estimated precipitation are the largest for the GRU_Z-ET and the smallest for the traditional Z-R relationship, and the root mean square error is just the opposite. In addition, these statistics of GRU_Z are similar to those of optimal Z-R relationship. Thus, it can be concluded that the performance of the GRU_ZET is the best in the four methods for the quantitative precipitation estimation.
基金Guangzhou Science and Technology Plan Project(202103000030)Guangdong Meteorological Bureau Science and Technology Project(GRMC2020Z08)a project co-funded by the Development Team of Radar Application and Severe Convection Early Warning Technology(GRMCTD202002)。
文摘The performance of different quantitative precipitation estimation(QPE) relationships is examined using the polarimetric variables from the X-band polarimetric phased-array radars in Guangzhou,China.Three QPE approaches,namely,R(ZH),R(ZH,ZDR) and R(KDP),are developed for horizontal reflectivity,differential reflectivity and specific phase shift rate,respectively.The estimation parameters are determined by fitting the relationships to the observed radar variables using the T-matrix method.The QPE relationships were examined using the data of four heavy precipitation events in southern China.The examination shows that the R(ZH) approach performs better for the precipitation rate less than 5 mm h-1, and R(KDP) is better for the rate higher than 5 mm h-1, while R(ZH,ZDR) has the worst performance.An adaptive approach is developed by taking the advantages of both R(ZH) and R(KDP) approaches to improve the QPE accuracy.
基金supported by National Key R&D Program of China(Grant No.2022YFC3003903)the S&T Program of Hebei(Grant No.19275408D),the Key-Area Research and Development Program of Guangdong Province(Grant No.2020B1111200001)+1 种基金the Key Project of Monitoring,Early Warning and Prevention of Major Natural Disasters of China(Grant No.2019YFC1510304)the Joint Fund of Key Laboratory of Atmosphere Sounding,CMA,and the Research Centre on Meteorological Observation Engineering Technology,CMA(Grant No.U2021Z05).
文摘Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.
文摘The removal of organic matter and iron oxides could increase and decrease soil CEC in tropical and subtropical regions, but the quantitative information is insufficient so far about the change of soil CEC, the influence factors and their contribution. In this study, the subhorizon soils of 24 soil series in the tropical and subtropical China were used, pH, particle size composition, organic matter, iron oxides of these samples were measured, and also CECs were measured and compared for the original soils and after the removal of organic matter and iron oxides. The results showed that, compared with CEC of the original soil, the eliminating organic matter increased soil CEC significantly by 2.28% - 56.50% with a mean of 24.02%, but the further obliterating iron oxides decreased soil CEC significantly by 0.75% - 20.30% with a mean of 7.73%. CEC after the removal of organic matter and iron oxides had positive correlation with iron oxides (p < 0.01) and negative correlation with sand content (p < 0.01 and p < 0.05). CEC after organic matter eliminated was mainly decided by iron oxides (51.68%), followed by silt content (22.19%);while CEC after iron oxides obliterated was mainly determined by iron oxides (50.55%). The increase of CEC after organic matter eliminated was co-affected by the contents of clays, slits, iron oxides and pH (22.00% - 27.34%), while the decrease of CEC after iron oxides obliterated further was dominated by the content of organic matter (66.92%). More other soil parameters should be considered for higher predicting accuracy in the regression model of soil CEC after the removal of organic matter and iron oxides, and the recommended optimal models obtained in this study were as follows: for soil CEC after organic matter eliminated, CEC = 1.665 <span style="white-space:nowrap;">−</span> 0.546pH <span style="white-space:nowrap;">−</span> 0.024OM + 0.053Fe<sub>x</sub>O<sub>y</sub> <span style="white-space:nowrap;">−</span> 0.001Silt + 0.007Clay + 0.972CEC<sub>original</sub> (R<sup>2</sup> was 0.923, RSME was 1.55 cmol(+)<span style="white-space:nowrap;"><span style="white-space:nowrap;">∙</span></span>kg<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>1</sup>, p < 0.01), while for soil CEC after iron oxides further obliterated, CEC = 1.665 <span style="white-space:nowrap;">−</span> 0.546pH <span style="white-space:nowrap;">−</span> 0.024OM + 0.053Fe<sub>x</sub>O<sub>y</sub> <span style="white-space:nowrap;">−</span> 0.001Silt + 0.007Clay + 0.972CEC<sub>original</sub> (R<sup>2</sup> was 0.923, RMSE was 1.55 cmol(+)<span style="white-space:nowrap;"><span style="white-space:nowrap;">∙</span></span>kg<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>1</sup>, p < 0.01). Further research is needed in the future as for exploring internal functional mechanism in view of soil electrochemistry and mineralogy.
基金financed by the National Natural Science Foundation of China (Grant No.40533018)the Ministry of Science and Technology of the People’s Republic of China (Grant No.2009CB421403)the Chinese Academy of Sciences (Grant Nos.KZCX3-SW-231 and 8-070203)
文摘For a better understanding of the air mass exchange processes between the surface and free atmos-phere in the Himalayas,a Himalayan exchange between the surface and troposphere 2007 (HEST2007) campaign was carried out in the Rongbuk Valley,on the northern slope of Mt.Qomolangma,in June 2007.The wind,tem-perature and radiation conditions were measured during the campaign.Using these observation data,together with the National Centers for Environmental Prediction/the National Center for Atmospheric Research (NCEP/NCAR) reanalysis data,the air mass exchange between the inside of the valley and the outside of the valley is quantitatively estimated,based on a closed-valley method.The air mass is strongly injected into the Rongbuk Valley in the after-noon,which dominates the diurnal cycle,by a strong downward along-valley wind,with a maximum down-ward transfer rate of 9.4 cm s?1.The total air volume flux injected into the valley was 2.6×1011 m3 d?1 in 24 hours in June 2007,which is 15 times the total volume of the val-ley.The air mass transfer into the valley also exhibited a clear daily variation during the HEST2007 campaign,which can be affected by the synoptic situations through the adjustment of local radiation conditions.
基金supported by the Fundamental Research Funds for the Central Universities,Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20110022120004)China National Key S&T Project on Marine Carbonate Reservoir Characterization(No.2011ZX05004003)
文摘Quantitative thickness estimation of thin-layer is a great challenge in seismic exploration, especially for thin-layer below tuning thickness. In this article, we analyzed the seismic response cha- racteristics of rhythm and gradual type of thin-layer wedge models and presented a new method for thin-layer thickness estimation which uses relative peak frequency increment. This method can de- scribe the peak frequency to thickness relationship of rhythm and gradual thin-layers in unified equa- tion while the traditional methods using amplitude information cannot. What＇s more, it won＇t be in- fluenced by the absolute value of thin-layer reflection coefficient and peak frequency of wavelet. The unified equations were presented which can be used for rhythm and gradual thin-layer thickness cal- culation. Model tests showed that the method we introduced has a high precision and it doesn＇t need to determine the value of top or bottom reflection coefficient, so it has a more wide application in practice. The application of real data demonstrated that the relative peak frequency increment attribute can character the plane distribution feature and thickness characteristic of channel sand bodies very well.
文摘A new method in making judgment matrix is proposed based on a basic value of “importance” and a relative measure level of “importance”. Factors affecting petroleum exploration are analyzed and Experts’ judgment matrix on a geologic formation is given. Expected value of each factor is computed and the volume of recoverable oil is estimated.
基金financially supported by the National Natural Science Foundation of China(grant No.61301025)the Jiangsu Provincial Natural Science Foundation of China(grant No.BK20130853)the Fundamental Research Funds for the Central Universities(grant No.2016B07114)
文摘Objective This study focused on the Namco, the largest lake on the Tibet plateau as well as the highest large lake in the world. A large imbalance between water input and output of this lake has attracted great attention in the field of hydrogeology during recent years. As there is no surface outflow from Namco, the large water imbalance can only be explained by water seepage. Synthetic aperture radar （SAR） image data were used for the first time in combination with hydrological data actually measured in the field and meteorological station data, to quantitatively acquire the information of surface fluctuation, water storage variation, and to estimate groundwater leakage from Namco Lake. The results provide theoretical support and data for further understanding the processes and extent of water resource response to global climate change, and also provide a scientific basis for rational development and utilization of water resource in the Tibetan Plateau.
基金Key Project of Social Development in Zhejiang Province (2006C13025, 2007C13G1610002)
文摘With the pros and cons of the traditional optimization and probability pairing methods thoroughly considered, an improved optimal pairing window probability technique is developed using a dynamic relationship between the base reflectivity Z observed by radar and real time precipitation I by rain gauge. Then, the Doppler radar observations of base reflectivity for typhoons Haitang and Matsa in Wenzhou are employed to establish various Z-I relationships, which are subsequently used to estimate hourly precipitation of the two typhoons. Such estimations are calibrated by variational techniques. The results show that there exist significant differences in the Z-I relationships for the typhoons, leading to different typhoon precipitation efficiencies. The typhoon precipitation estimated by applying radar base reflectivity is capable of exhibiting clearly the spiral rain belts and mesoscale cells, and well matches the observed rainfall. Error statistical analyses indicate that the estimated typhoon precipitation is better with variational calibration than the one without. The variational calibration technique is able to maintain the characteristics of the distribution of radar-estimated typhoon precipitation, and to significantly reduce the error of the estimated precipitation in comparison with the observed rainfall.
文摘Glacier-lake outburst debris flow(GLODF),unique in high altitude mountains where modern glacier is active,is significantly large in its scale of time and space,and strong in power of destroy.Following the world's becoming warmer,GLODF frequency gradually rises.In late years,quantitative estimation methodologies has been put into use of mass GLODF estimations.To improve former methodologies,this article suggests that the glacier(or the massif)on the trailing edge and the moraine dam are the two major systems providing independent glacier lake outburst possibilities.Bucket Effect exists in GLODF issues.Therefore focusing on the relatively unstable one of the above two provides better accuracy in estimation on GLODF possibility.Thus,this article summarizes method of presort through specific GLODF evaluation.
文摘This study utilized data from an X-band phased array weather radar and ground-based rain gauge observations to conduct a quantitative precipitation estimation(QPE)analysis of a heavy rainfall event in Xiong an New Area from 20:00 on August 21 to 07:00 on August 22,2022.The analysis applied the Z-R relationship method for radar-based precipitation estimation and evaluated the QPE algorithm s performance using scatter density plots and binary classification scores.The results indicated that the QPE algorithm accurately estimates light to moderate rainfall but significantly underestimates heavy rainfall.The study identified disparities in the predictive accuracy of the QPE algorithm across various precipitation intensity ranges,offering essential insights for the further refinement of QPE techniques.
文摘In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal scales for better monitoring and prediction of these phenomena,as could be provided by weather radars.Based on an extensive archive of data from the X-band polarimetric radar and rain gauges observations gathered during the intensive AMMA campaigns in 2006–2007 and the Megha-Tropiques satellite measurement validation programme in 2010 in West Africa,we(i)simulated jointly realistic data for polarimetric radar variables and rain intensity using copula,and(ii)assessed rain rate estimation methods based on neural network(NN)inversion techniques and non-linearly calibrated parametric algorithms.The assessment of rainfall rate retrieval by these estimators is carried out using the part of the observations database not employed for calibration steps.The multiparametric algorithms R(ZH,K_(DP))and R(Z_(DR),K_(DP))perform better than R(ZH,Z_(DR))and R(ZH,Z_(DR),K_(DP)),especially since they are calibrated using copulas with upper tail dependencies,with KGE ranging in 0.68–0.75 and 0.79–0.82,respectively versus ranges of 0.40–0.64 and 0.20–0.51,for the two latter estimators.The neural network-based estimators RNN(Z_(DR),K_(DP))and RNN(ZH,K_(DP)),show KGE score characteristics comparable to those obtained from the best parametric relations,specifically optimized for the synthetic copula-based dataset.However,the neural network-based estimators were shown to be more robust when applied to a specific rainfall event.More specifically,neural network-based estimators trained on synthetic data are sensitive to the copulas’ability to capture the dependence between the variables of interest over the entire distribution of joint values.This leads to a near-cancellation of sensitivity to variability in the raindrop size distribution,as shown the coefficients of correlation near 1,especially for RNN(Z_(DR),K_(DP)),and for less extent RNN(Z_(H),K_(DP)).
文摘The author’s combined numerical model consisting of a third generation shallow water wave model and a 3 D tide surge model with wave dependent surface wind stress were used to study the influence of waves on tide surge motion. For the typical weather case, in this study, the magnitude and mechanism of the influence of waves on tide surges in the Bohai Sea were revealed for the first time. The results showed that although consideration of the wave dependent surface wind stresses raise slightly the traditional surface wind stress, due to the accumulated effects, the computed results are improved on the whole. Storm level maximum modulation can reach 0.4 m. The results computed by the combined model agreed well with the measured data.
文摘The municipal solid waste (msw) is a source of landfill gas (msw)—with methane gas content. Preoccupations for landfill gas (msw) management date back since 1976 when, at a landfill (msw) in California (USA), it turned out practically that the landfill gas (msw) with methane gas content contains a gas with high caloric value that can be collected and used for economic purposes. The landfill gas (msw) contains methane gas (30% - 60% volume), carbon dioxide (45% - 50% volume), hydrogen sulfide and other gases. Methane gas, carbon dioxide, nitrous oxide and other gases are listed in Kyoto Protocol as high greenhouse gases. Their ecological-rational management is both a national and global preoccupation. In terms of greenhouse gases, especially methane gas, the landfill (msw) is held responsible for 3.5% - 5% of the total global greenhouse gases. Practically, the quantitative estimation of the methane gas in a municipal solid waste landfill can be done by measuring the landfill gas (msw) flow in an extraction-collection well. In Romania, a quantitative estimation relationship of methane gas from deposits (msw) was made, approaching the problem in a different way. This paper presents the calculation formula, the working algorithm, the municipal waste landfill equation and the NOMOGRAMA of a municipal solid waste landfill (msw). The NOMOGRAMA allows us to define the values for parameter -m- (number of months needed for an amount of municipal solid waste (msw) to degrade, starting with the year from which the landfill gas (msw) emission with methane gas content is calculated). Taking into account the environmental conditions for each location of municipal solid waste landfill, the calculation uses various indexes and approximations, while the fundamental parameter remains -m- defined by the NOMOGRAMA of the municipal solid waste landfill (msw). A municipal solid waste landfill (msw) is a conglomerate of waste with various biodegradation periods between 2 - 3 years and 5 - 10 - 30 years. Degradation of waste (msw) in to dissolved organic carbon will take place in a number of months defined -m- starting with the year from which the methane gas emission with the NOMOGRAMA of the municipal solid waste landfill (msw) is calculated. The -m- values for the year of the quantitative emission of methane gas can be also done analytically, which requires good experience in the ecologic-rational management of the municipal solid waste (msw).
文摘Taking the land resources of 17 cities in Shandong Province as the basic data, the article studied on the economical supporting capacity of land resources in terms of the effect of land on economy. The author classified 17 cities of Shandong Province into four types according to the economical supporting capacity of land resources by quantitatively estimating the evaluation indices of the total amount of land resources, the potential of urban and other nonagricultural land, and the integrated economical sup- porting capacity of land resources, etc. The author proposes the questions requiring further study at the end of this article.
