Application of Machine-Learning-Based Objective Correction Method in the Intelligent Grid Maximum and Minimum Temperature Predictions

Post-processing correction is an effective way to improve the model forecasting result. Especially, the machine learning methods have played increasingly important roles in recent years. Taking the meteorological observational data in a period of two years as the reference, the maximum and minimum temperature predictions of Shenyang station from the European Center for Medium-Range Weather Forecasts (ECMWF) and national intelligent grid forecasts are objectively corrected by using wavelet analysis, sliding training and other technologies. The evaluation results show that the sliding training time window of the maximum temperature is smaller than that of the minimum temperature, and their difference is the largest in August, with a difference of 2.6 days. The objective correction product of maximum temperature shows a good performance in spring, while that of minimum temperature performs well throughout the whole year, with an accuracy improvement of 97% to 186%. The correction effect in the central plains is better than in the regions with complex terrain. As for the national intelligent grid forecasts, the objective correction products have shown positive skills in predicting the maximum temperatures in spring (the skill-score reaches 0.59) and in predicting the minimum temperature at most times of the year (the skill-score reaches 0.68).

Design of weak current measurement system and research on temperature impact

A dedicated weak current measurement system was designed to measure the weak currents generated by the neutron ionization chamber.This system incorporates a second-order low-pass filter circuit and the Kalman filtering algorithm to effectively filter out noise and minimize interference in the measurement results.Testing conducted under normal temperature conditions has demonstrated the system's high precision performance.However,it was observed that temperature variations can affect the measurement performance.Data were collected across temperatures ranging from -20 to 70℃,and a temperature correction model was established through linear regression fitting to address this issue.The feasibility of the temperature correction model was confirmed at temperatures of -5 and 40℃,where relative errors remained below 0.1% after applying the temperature correction.The research indicates that the designed measurement system exhibits excellent temperature adaptability and high precision,making it particularly suitable for measuring weak currents.

Corrections of shipboard GPS radiosonde soundings and applications on historical records in the eastern tropical Indian Ocean and South China Sea

Shipboard radiosonde soundings are important for detecting and quantifying the multiscale variability of atmosphere-ocean interactions associated with mass exchanges.This study evaluated the accuracies of shipboard Global Positioning System(GPS)soundings in the eastern tropical Indian Ocean and South China Sea through a simultaneous balloon-borne inter-comparison of different radiosonde types.Our results indicate that the temperature and relative humidity(RH)measurements of GPS-TanKong(GPS-TK)radiosonde(used at most stations before 2012)have larger biases than those of ChangFeng-06-A(CF-06-A)radiosonde(widely used in current observation)when compared to reference data from Vaisala RS92-SGP radiosonde,with a warm bias of 5℃and dry bias of 10%during daytimes,and a cooling bias of-0.8℃and a moist bias of 6%during nighttime.These systematic biases are primarily attributed to the radiation effects and altitude deviation.An empirical correction algorithm was developed to retrieve the atmospheric temperature and RH profiles.The corrected profiles agree well with that of RS92-SGP,except for uncertainties of CF-06-A in the stratosphere.These correction algorithms were applied to the GPS-TK historical sounding records,reducing biases in the corrected temperature and RH profiles when compared to radio occultation data.The correction of GPS-TK historical records illustrated an improvement in capturing the marine atmospheric structure,with more accurate atmospheric boundary layer height,convective available potential energy,and convective inhibition in the tropical ocean.This study contributes significantly to improving the quality of GPS radiosonde soundings and promotes the sharing of observation in the eastern tropical Indian Ocean and South China Sea.

A generative adversarial network-based unified model integrating bias correction and downscaling for global SST

本文提出了一种基于生成对抗网络的全球海表面温度(sea surface temperature,SST)偏差订正及降尺度整合模型.该模型的生成器使用偏差订正模块将数值模式预测结果进行校正,再用可复用的共享降尺度模块将订正后的数据分辨率逐次提高.该模型的判别器可鉴别偏差订正及降尺度结果的质量,以此为标准进行对抗训练。同时,在对抗损失函数中含有物理引导的动力学惩罚项以提高模型的性能.本研究基于分辨率为1°的GFDL SPEAR模式的SST预测结果,选择遥感系统(Remote Sensing System)的观测资料作为真值,面向月尺度ENSO与IOD事件以及天尺度海洋热浪事件开展了验证试验:模型在将分辨率提高到0.0625°×0.0625°的同时将预测误差减少约90.3%,突破了观测数据分辨率的限制,且与观测结果的结构相似性高达96.46%.

Accurate quantitative CF-LIBS analysis of both major and minor elements in alloys via iterative correction of plasma temperature and spectral intensity

The chemical composition of alloys directly determines their mechanical behaviors and application fields.Accurate and rapid analysis of both major and minor elements in alloys plays a key role in metallurgy quality control and material classification processes.A quantitative calibration-free laser-induced breakdown spectroscopy(CF-LIBS)analysis method,which carries out combined correction of plasma temperature and spectral intensity by using a secondorder iterative algorithm and two boundary standard samples,is proposed to realize accurate composition measurements.Experimental results show that,compared to conventional CF-LIBS analysis,the relative errors for major elements Cu and Zn and minor element Pb in the copperlead alloys has been reduced from 12%,26%and 32%to 1.8%,2.7%and 13.4%,respectively.The measurement accuracy for all elements has been improved substantially.

Bias correction of sea surface temperature retrospective forecasts in the South China Sea

Offline bias correction of numerical marine forecast products is an effective post-processing means to improve forecast accuracy. Two offline bias correction methods for sea surface temperature(SST) forecasts have been developed in this study: a backpropagation neural network(BPNN) algorithm, and a hybrid algorithm of empirical orthogonal function(EOF) analysis and BPNN(named EOF-BPNN). The performances of these two methods are validated using bias correction experiments implemented in the South China Sea(SCS), in which the target dataset is a six-year(2003–2008) daily mean time series of SST retrospective forecasts for one-day in advance, obtained from a regional ocean forecast and analysis system called the China Ocean Reanalysis(CORA),and the reference time series is the gridded satellite-based SST. The bias-correction results show that the two methods have similar good skills;however, the EOF-BPNN method is more than five times faster than the BPNN method. Before applying the bias correction, the basin-wide climatological error of the daily mean CORA SST retrospective forecasts in the SCS is up to-3°C;now, it is minimized substantially, falling within the error range(±0.5°C) of the satellite SST data.

Bias Correction and Ensemble Projections of Temperature Changes over Ten Subregions in CORDEX East Asia

Regional climate models(RCMs)participating in the Coordinated Regional Downscaling Experiment(CORDEX)have been widely used for providing detailed climate change information for specific regions under different emissions scenarios.This study assesses the effects of three common bias correction methods and two multi-model averaging methods in calibrating historical(1980−2005)temperature simulations over East Asia.Future(2006−49)temperature trends under the Representative Concentration Pathway(RCP)4.5 and 8.5 scenarios are projected based on the optimal bias correction and ensemble averaging method.Results show the following:(1)The driving global climate model and RCMs can capture the spatial pattern of annual average temperature but with cold biases over most regions,especially in the Tibetan Plateau region.(2)All bias correction methods can significantly reduce the simulation biases.The quantile mapping method outperforms other bias correction methods in all RCMs,with a maximum relative decrease in root-mean-square error for five RCMs reaching 59.8%(HadGEM3-RA),63.2%(MM5),51.3%(RegCM),80.7%(YSU-RCM)and 62.0%(WRF).(3)The Bayesian model averaging(BMA)method outperforms the simple multi-model averaging(SMA)method in narrowing the uncertainty of bias-corrected results.For the spatial correlation coefficient,the improvement rate of the BMA method ranges from 2%to 31%over the 10 subregions,when compared with individual RCMs.(4)For temperature projections,the warming is significant,ranging from 1.2°C to 3.5°C across the whole domain under the RCP8.5 scenario.(5)The quantile mapping method reduces the uncertainty over all subregions by between 66%and 94%.

Load-Measuring Pot Bearing with Built-In Load Cell —Part II: Fatigue Performance and Experimental Temperature Correction

This paper presents the results of fatigue performance tests performed up to 10 million cycles on a load-measuring pot bearing with built-in load cell to verify its field applicability and proposes an empirical temperature correction formula. In Part I of this work, various measurement performances of the load-measuring pot bearing were evaluated through static and dynamic loading tests. Bridge bearings are subjected to the effect of fatigue caused by the repeated application of moving loads and exposed to harsh site conditions including cold and hot weathers differently to laboratory conditions. Accordingly, the durability of the load-measuring pot bearing with built-in load cell shall be secured and the environmental effects like temperature shall be minimized for its application on field. This study conducted fatigue tests up to 10 million cycles on a load-measuring pot bearing with the capacity of 1000 kN to examine eventual degradation of the measurement accuracy with respect to the number of fatigue loading cycles. In addition, the experimental temperature correction procedure is proposed to obtain the temperature correction formula enabling to correct the effect of temperature on the load measurement.

Influence of Temperature on the Inter-pressure of Soil Water Tension with Correcting Method

When the electronic temperature sensor was incorporated into a system of soil water tension and the insidetube temperature was monitored in real time, it is concluded that the inside temperature increased by 26.9 ℃ and the inside pressure changed about 14.6 Kpa, when the pottery soil was replaced by the sealing plug. When the soil water was relatively stable in the experimental salvers, the in-side pressure stil varied regularly with the temperature. When the inside temperature increased by 22.2 ℃, the inside pressure varied about 7.4 Kpa. Through com-pensation calculation of the inside tension, the temperature in the warming and cooling periods was compensated, which was useful to correct the tension measurement errors induced from the changing temperature. When the measuring interval was 4 hours and the temperature difference was 18.1 ℃, the tension difference of both points was only 0.278 Kpa, compared to the difference up to 6.5 Kpa before compensation.

Land Surface Temperature Change in Hangzhou Urban Area in Recent 20 Years Based on Landsat Image

Since the reform and opening-up in 1978, the urbanization level of our country has been continuously improved and the urban development has made great progress. However, with the rapid expansion of urban construction land, the population density and building density have been greatly increased, resulting in the urban heat island effect, which has negative impact on the urban thermal environment and restricts the high-quality development of urbanization. This paper focuses on how the urban surface thermal environment of Hangzhou changes in 20 years. In this paper, the characteristics of land surface temperature (LST) in Hangzhou urban area from 2000 to 2020 were studied by using Landsat images. The radiative transfer equation method is used to retrieve the land surface temperature, and the retrieval results are analyzed. The results show that: 1) the land surface temperature in Hangzhou city area has a slight upward trend in the past 20 years;2) the area of high temperature area is expanding;3) the land surface temperature in the city center area has decreased significantly in the past 20 years, while the ground temperature in other areas around the city center has increased significantly.

Temperature dependence of CsI:Tl coupled to a PIN photodiode and a silicon photomultiplier

With the aim of simulating the harsh temperature condition of space, a thallium-activated cesium iodide crystal(CsI:Tl) detector readout with a PIN photodiode(CsI:Tl(PD)) and with a silicon photomultiplier(CsI:Tl(SiPM)) is investigated over a temperature range from-40 to 40 ℃. With the increase in temperature, the output signal increases by ～ 24% with CsI:Tl(PD) and decreases by ～69% with CsI:Tl(SiPM). To reduce the effect of temperature in outer space, a method of bias voltage compensation is adopted for CsI:Tl(SiPM). Our study demonstrates that after correcting the temperature the variation in the analog-to-digital converter's amplitude is< 3%.

Effects of Temperature on the Dynamic Properties of Asphalt Mixtures

By using the falling weight deflectometer（FWD）,the dynamic loading tests on different thickness of asphalt mixture pavement in different temperature were performed.The experimental results show that the effects of temperature on dynamic properties of asphalt mixture are significant,and the thickness of asphalt mixture is also another important influence factor.The comparisons indicate that effect of temperature on the behaviors of dynamic loading properties and static loading properties of asphalt mixture were quite different.

Impacts of snow accumulation on air temperature measured by automatic weather stations on the Antarctic ice sheet

The heights of automatic weather station （AWS） sensors over the Antarctic ice sheet are nominal and change with snow accumulation or ablation. Therefore, the measured data may not be used directly. In this study, we analyzed the impact of snow accumulation on AWS observations using continuous measurements from three AWS that were deployed on the traverse route from the Zhongshan Station to Dome A over East Antarctica. We then corrected the measured air temperature to account for changes in the sensor height relative to the snow surface to improve the authenticity and representativeness of the observation data from the AWS. The results show that （i） the annual mean snow accumulations at Dome A, Eagle and LGB69 were approximately O. 11 m, 0.30 m and 0.49 m, respectively, and the corresponding annual mean air temperature differences between the corrected and measured values at 1 m in height were 0.34℃, 0.29℃ and 0.35℃ （ii） the impact on air temperature from accumulation decreases with height from the surface; （iii） the air temperature difference between the corrected and measured values was not directly proportional to the snow accumulation but was related to the seasonal air temperature variations and the intensity of the local surface inversion; and （iv） the averaged corrected air temperature was higher than the measured values except during the summer when there were days without temperature inversion. The magnitude of the temperature difference between the corrected and measured was mainly determined by snow accumulation and the intensity of the local surface inversion.

Projection of temperature change and extreme temperature events in the Lancang–Mekong River basin

The Lancang–Mekong River basin(LMRB) is under increasing threat from global warming. In this paper, the projection of future climate in the LMRB is explored by focusing on the temperature change and extreme temperature events. First, the authors evaluate the bias of temperature simulated by the Weather Research and Forecasting model. Then, correction is made for the simulation by comparing with observation based on the non-parametric quantile mapping using robust empirical quantiles(RQUANT) method. Furthermore, using the corrected model results, the future climate projections of temperature and extreme temperature events in this basin during 2016–35, 2046–65, and 2080–99 are analyzed. The study shows that RQUANT can effectively reduce the bias of simulation results. After correction, the simulation can capture the spatial features and trends of mean temperature over the LMRB, as well as the extreme temperature events. Besides, it can reproduce the spatial and temporal distributions of the major modes. In the future, the temperature will keep increasing, and the warming in the southern basin will be more intense in the wet season than the dry season. The number of extreme high-temperature days exhibits an increasing trend, while the number of extreme low-temperature days shows a decreasing trend. Based on empirical orthogonal function analysis, the dominant feature of temperature over this basin shows a consistent change. The second mode shows a seesaw pattern.

EVALUATION OF CORRECTIONS ON TURBULENT FLUXES OBTAINED BY EDDY COVARIANCE METHOD IN HIGH WINDS

This paper investigates processing of fast-response data and corrections of turbulent fluxes obtained by using eddy covariance method based on data collected at an offshore observation tower during three Cold-intrusion(CI)events in the South China Sea in 2010. This study presents the data processing procedure in detail and compares frictional velocities(u*), sensible heat fluxes(H) and latent heat fluxes(LE) yielded by using different averaging periods and different coordinate rotation methods; evaluates the sonic temperature correction for sensible heat flux and the Webb correction for latent heat flux as a function of 10 m wind speed(u10) during the CIs. The results show(1) that the different averaging periods of 30 min and 10 min cause biases of u*(H, LE) within 5%(15%, 62%). The values of u*(H,LE) averaged from 30 mins are mostly larger than those averaged from 10 mins. We suggest that the averaging period of 10 min is not sufficiently long to capture all scale eddies and recommend 30 min averaging period in calculating turbulent fluxes using eddy covariance method during CIs;(2) that the values of u*(H, LE) obtained from double rotation(DR2) and those obtained from planar fit rotation(PF) have good agreements and correlation coefficients between them are larger than 0.99. Because PF method requires unchanged environment and it is easier to apply DR2 method, we suggest DR2 coordinate rotation method in processing fast-response data; and(3) that the median values of frictional velocity(sensible heat flux and latent heat flux) binned according to 2 m s^(-1) intervals of u_(10) increase(decrease,increase) by less than 9%(4%, 10%) by Coriolis corrections(sonic temperature corrections, Webb corrections), which decreases(decreases, increases) with increasing u10 when u10 are 5-17 m s^(-1).

Power Factor Correction Rectifier with a Variable Frequency Voltage Source in Vehicular Application

This paper presents a PFCVF (Power Factor Correction) rectifier that uses a variable frequency source for alternators for electric and hybrid vehicles application. In such application, the frequency of the signal in the alternator changes according to the vehicle speed, more over the loading effect on the alternator introduces harmonic currents and increases the alternator apparent power requirements. To overcome these problems and aiming more stability and better design of the alternator, a new third harmonic injection technique is proposed. This technique allows to preserve a good THD (Total Harmonic Distortion) of the input source at any frequency and to decrease losses in semiconductors switches, thereby allowing more stability and reducing the apparent power requirements. A comparative study between the standard and the new technique is made and highlights the effectiveness of the new design. A detailed analysis of the proposed topology is presented and simulations as well as experimental results are shown.

Soft-Sensing Method of Water Temperature Measurement for Controlled Cooling System

Aiming at the water temperature measuring problem for controlled cooling system of rolling plant,a new water temperature measuring method based on soft-sensing method with a water temperature model of on-line self correction parameter was built.A water temperature compensation factor model was also built to improve coiling temperature control precision.It was proved that the model meets production requirements.The soft-sensing technique has extensive applications in the field of metal forming.

IMPACT OF SUMMER WARMING ON DYNAMICS-STATISTICS-COMBINED METHOD TO PREDICT THE SUMMER TEMPERATURE IN CHINA

Based on NCEP/NCAR daily reanalysis data, climate trend rate and other methods are used to quantitatively analyze the change trend of China's summer observed temperature in 1983—2012. Moreover, a dynamics-statistics-combined seasonal forecast method with optimal multi-factor portfolio is applied to analyze the impact of this trend on summer temperature forecast. The results show that: in the three decades, the summer temperature shows a clear upward trend under the condition of global warming, especially over South China, East China, Northeast China and Xinjiang Region, and the trend rate of national average summer temperature was 0.27℃ per decade. However, it is found that the current business model forecast(Coupled Global Climate Model) of National Climate Centre is unable to forecast summer warming trends in China, so that the post-processing forecast effect of dynamics-statistics-combined method is relatively poor. In this study, observed temperatures are processed first by removing linear fitting trend, and then adding it after forecast to offset the deficiency of model forecast indirectly. After test, ACC average value in the latest decade was 0.44 through dynamics-statistics-combined independent sample return forecast. The temporal correlation(TCC) between forecast and observed temperature was significantly improved compared with direct forecast results in most regions, and effectively improved the skill of the dynamics-statistics-combined forecast method in seasonal temperature forecast.

Analysis of Altimeter Wet Troposphere Range Correction

Wet path delay caused by tropospheric water vapor must be considered before altimeter data are used in oceanic application. This paper analyzed several methods of atmosphere water range correction (AWRC) using Seasat, Geosat, TOPEX and ERS-1 data, especially the calculated delay path using brightness temperature of TMR on TOPEX and EMR on ERS-1; and discussed some other problems of AWRC.

Improved Non-uniformity Correction Method for Uncooled Microbolometer

The uncooled microbolometer has a severe temperature requirement for non-uniformity correction. An improved two-point non-uniformity correction method is proposed, which can operate in wider uniform substrate temperatures. This method can control the bias voltage of MOS transistors by memory and DAC to meet two restrictions about responsivity and offset before traditional two-point calibration is implemented. The simulation results seem that this non-uniformity correction can work at uniform substrate temperature with fluctuant range of 4K.