Attribution of Biases of Interhemispheric Temperature Contrast in CMIP6 Models

One of the basic characteristics of Earth's modern climate is that the Northern Hemisphere(NH) is climatologically warmer than the Southern Hemisphere(SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average(0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from -0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the crossequatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents.Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.

Effects of clouds, sea surface temperature, and its diurnal variation on precipitation efficiency

The effects of clouds, sea surface temperature, and its diurnal variation on precipitation efficiency are investigated us ing grid-scale data from nine equilibrium sensitivity cloud-resolving model experiments driven without large-scale vertical velocity. The precipitation efficiencies are respectively defined in surface rainfall, cloud, and rain microphysical budgets. We mathematically and physically demonstrate the relationship between these precipitation efficiencies. The 2 ℃ increases in spatiotemporal invariant sea surface temperature （SST） from 27 ℃ to 29 ℃ and from 29 ℃ to 31 ℃, and the inclusion of diurnal SST difference 1 ℃ and the 1℃ increase in diurnal SST difference generate opposite changes in the precipitation efficiency by changing ice cloud-radiation interactions. The radiative and microphysical processes of ice clouds have opposite effects on the precipitation efficiency because of the rainfall increase associated with the reduction in the saturation mixing ratio caused by the exclusion of radiative effects and the decrease in rainfall related to the reduction in net condensation caused by the exclusion of deposition processes. The radiative effects of water clouds on the precipitation efficiency are statistically insensitive to the radiative effects of ice clouds.

Influence of Vapor Cloud Shape on Temperature Field of Unconfined Vapor Cloud Explosion

In order to analyze the influence of vapor cloud shape on temperature field effect of unconfined vapor cloud explosion(UVCE)and obtain creditable prediction method of explosion temperature effect,the transient temperature fields of cylindrical and hemispherical UVCEs with same methane concentration and mass were numerically studied by computational fluid dynamics(CFD)technology.According to numerical simulation results, the concepts of UVCE’s temperature-near-field and temperature-far-field were proposed,the corresponding ranges were given,and the temperature attenuation laws and differences in corresponding regions with different vapor cloud shapes were presented.Through comparing with Baker fireball model,the accuracy and visualizability in acquisition of entire temperature effect based on numerical simulation were further validated.The functional relations among maximum temperature,horizontal distance,initial temperature and vapor cloud mass in temperature-near-field and temperature-far-field were deduced by means of data fitting,respectively.These conclusions provided quantitative basis for forecast and protection of UVCE disaster.

MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS: METHODS AND IDEAL TESTS

Clouds have important effects on the infi＇ared radiances transmission in that the inclusion of cloud effects in data assimilation can not only improve the quality of the assimilated atmospheric parameters greatly, but also minimize the initial error of cloud parameters by adjusting part of the infrared radiances data. On the basis of the Grapes-3D-var （Global and Regional Assimilation and Prediction Enhanced System）, cloud liquid water, cloud ice water and cloud cover are added as the governing variables in the assimilation. Under the conditions of clear sky, partly cloudy cover and totally cloudy cover, the brightness temperature of 16 MODIS channels are assimilated respectively in ideal tests. Results show that when the simulated background brightness temperatures are lower than the observation, the analyzed field will increase the simulated brightness temperature by increasing its temperature and reducing its moisture, cloud liquid water, cloud ice water, and cloud cover. The simulated brightness temperature can be reduced if adjustment is made in the contrary direction. The adjustment of the temperature and specific humidity under the clear sky conditions conforms well to the design of MODIS channels, but it is weakened for levels under cloud layers. The ideal tests demonstrate that by simultaneously adding both cloud parameters and atmospheric parameters as governing variables during the assimilation of infrared radiances, both the cloud parameters and atmospheric parameters can be adjusted using the observed infrared radiances and conventional meteorological elements to make full use of the infrared observations.

STUDY ON THE RELATIONSHIP BETWEEN BRIGHTNESS TEMPERATURE FROM GMS-5 INFRARED CLOUD IMAGERY AND SURFACE RAIN RATES DURING THE RAINING SEASONS OF FUJIAN PROVINCE

The GMS-5 infrared cloud imagery for two yearly first raining seasons in 1998 and 1999 are used to study the relationship between brightness temperature and surface rain rates. The result shows that it is likely to have large probability of heavy precipitation with the decrease of brightness temperature and the gradual increase of rainfall intensity; for areas of low temperature, the brightness temperature is better determined for atmosphere above rain gauge stations with multiple points sampling than with single point one; for the yearly first raining season, the threshold brightness temperature is set at 4.6℃ for indication of heavy precipitation in the Fujian area.

Effects of sea surface temperature,cloud radiative and microphysical processes,and diurnal variations on rainfall in equilibrium cloud-resolving model simulations

The effects of sea surface temperature（SST）,cloud radiative and microphysical processes,and diurnal variations on rainfall statistics are documented with grid data from the two-dimensional equilibrium cloud-resolving model simulations.For a rain rate of higher than 3 mm.h 1,water vapor convergence prevails.The rainfall amount decreases with the decrease of SST from 29℃ to 27℃,the inclusion of diurnal variation of SST,or the exclusion of microphysical effects of ice clouds and radiative effects of water clouds,which are primarily associated with the decreases in water vapor convergence.However,the amount of rainfall increases with the increase of SST from 29℃ to 31℃,the exclusion of diurnal variation of solar zenith angle,and the exclusion of the radiative effects of ice clouds,which are primarily related to increases in water vapor convergence.For a rain rate of less than 3 mm.h 1,water vapor divergence prevails.Unlike rainfall statistics for rain rates of higher than 3 mm.h 1,the decrease of SST from 29℃ to 27℃ and the exclusion of radiative effects of water clouds in the presence of radiative effects of ice clouds increase the rainfall amount,which corresponds to the suppression in water vapor divergence.The exclusion of microphysical effects of ice clouds decreases the amount of rainfall,which corresponds to the enhancement in water vapor divergence.The amount of rainfall is less sensitive to the increase of SST from 29℃ to 31℃ and to the radiative effects of water clouds in the absence of the radiative effects of ice clouds.

基于机器学习方法的三维气流组织温度场重构

从局部离散流场数据点重构全局流场信息对数据中心机房的节能节碳具备重要的研究意义。基于局部散点对数据中心进行气流组织温度场快速重构,可有效降低数据中心总能耗。主要通过发展一种基于多特征输入的三维U形神经网络架构(U-net),利用布设在数据中心机房的温度传感器数据值进行气流组织温度场重构。并研究了在不同学习率与数据集大小的设置下,该机器学习模型的训练预测能力。对比结果表明:不同学习率对于模型训练的结果有较大影响,应通过预实验选取最佳学习率。在同等条件下,应优先选取较大的数据集进行训练,便于提取高维物理特征。

三亚市秋季一次大暴雨过程的对流云特征分析

利用自动气象观测站降水数据、ERA5再分析数据和葵花8号卫星数据,对2020年10月18日三亚市出现的大暴雨过程的对流云物理特征进行了分析。结果发现,强烈的南海辐合带和南下的大陆高压相互作用,及低空偏东风急流相伴,为此次大暴雨的发生提供了有利的动力和水汽条件,海上中尺度对流云团在偏东气流引导下移入三亚市,造成三亚市陆续出现强降水。对流云团的红外窗区通道和水汽通道亮温差能较好地反映雨强的大小,降水强度超过20.0 mm·h^(-1)时,出现亮温差小于0℃的亮温逆转现象。云顶高度、云光学厚度与雨强的相关性优于云顶温度的,而云粒子有效半径与雨强的相关性较差。20.0 mm·h^(-1)以上的短时强降水对应的云顶温度为-67.9℃、云顶高度为15.1 km、云光学厚度为114。在有利的大尺度环流背景下,对中尺度对流云团亮温、云特征参数进行深入分析得到的重要特征可为强对流天气的短时临近预报预警业务提供参考依据。

基于L波段探空观测的FY-4A云顶温度产品评估及其在冬季降水相态判识中的应用

利用2019—2021年冬季上海宝山站L波段探空资料对FY-4A云顶温度(CTT)产品进行评估,分析发现,FY-4A的云顶温度产品能够较好地反映单层云的云顶温度,对双层云或多层云的云顶温度则普遍高估(平均高估幅度超过14℃);当探空观测到的云顶高度不超过6 km或云顶温度不低于-20℃时,FY-4A云顶温度产品误差较小,平均偏差约为3℃。根据2021—2022年冬季长三角地区地面站观测的降水现象统计云顶温度与降水相态的关系,并对典型个例进行分析,结果表明,云顶温度低是出现降雪的必要条件之一,绝大部分降雪出现在云顶温度低于-12℃的情况下。FY-4A的云顶温度产品时空分辨率高、精度尚可,可以辅助预报员判识雨雪落区,在雨雪转换过程的预报服务中有较大的应用潜力。

基于多源遥感数据与模型对比的冬小麦土壤含水量区域监测研究

实时、精准的土壤水分含量监测是农业用水管理的基础,探究冬小麦土壤水分反演的最优模型对于提高农业用水效率和可持续发展均具有重要的意义。本研究以河南省鹤壁市浚县冬小麦种植区域的土壤水分含量为研究对象,采用无人机遥感数据、卫星遥感数据、田间采样数据,分别运用温度植被干旱指数模型、水云模型和改进的水云模型3种方法,进行土壤含水量反演对比分析与最优模型选择。结果表明,3种方法中10 cm深度的反演精度均高于20 cm,且R^(2)均大于0.4。其中采用改进的水云模型方法在10 cm深度的R^(2)为0.7055、RMSE为0.0209,20 cm深度的R^(2)为0.5069、RMSE为0.0271,优于水云模型和温度植被干旱指数的反演效果。因此,改进的水云模型是一种适合用于麦田土壤水分反演的方法,它能够提供较高的反演精度。

FY-4B与FY-4A云顶性质产品精度的一致性评估

风云四号(FY4)气象卫星是我国第二代静止气象卫星,FY4B云顶温度、云顶高度和云顶压强的反演算法与FY4A相同,为了方便用户更好地应用FY4B云顶产品,本文利用美国EOS/MODIS极轨气象卫星和日本第二代静止气象卫星Himawari-8云产品检验FY4A和FY4B反演的云顶产品精度的一致性,结果表明,FY4B云顶产品与FY4A具有很好的一致性,其中B星多层云的较大误差主要是由于云分类将卷云错判成了多层云所致。从全样本的检验结果可以看出FY4B云顶参数产品的精度与FY4A精度大体相当,两者的差异主要来自于通道光谱特征的改变、定标精度及所用的辐射传输模式的不同。

低温来流对深水水库过饱和总溶解气体输移的影响

梯级深水水库产生的水温分层现象可降低下游水库来流水温,导致泄洪水体总溶解气体(TDG)的过饱和程度随库区密度分层流的输移过程产生变化。以溪洛渡—向家坝区间为研究区域,基于原位观测和数值模拟相结合的研究手段,研究低温来流对深水水库过饱和TDG纵向和垂向输移过程的影响规律。研究表明:①来流水温降低2℃,TDG云团潜入位置提前36.4 km,峰值垂向位置下移55 m、垂向影响范围减少23%;②来流水温降低2℃,TDG饱和度110%以上云团输移至向家坝坝前阶段和后续阶段,包络面积衰减速率降幅分别为16%和44%;③从射流区到交换区过饱和TDG平均纵向迁移速度显著降低,降幅达92%;④来流水温降低2℃,向家坝表孔出流TDG饱和度峰值和均值的降低程度分别为机组出流的3.2倍和4倍;⑤水温降低对鱼类安全水深阈值的补偿效应可量化为0.20 m/℃。研究成果可为梯级深水水库汛期生态调度提供科学支撑。

一种冷链温湿度监测系统的设计与实现

针对我国冷链温湿度监测过程中存在的自动化程度低、实时性差等问题,设计了一种基于物联网与云平台的实时冷链温湿度监测系统。选用PT1000和AM2120传感器作为系统的信息采集部分,LPC824M芯片进行数据处理,配合无线通信模块BC28芯片和阿里云平台实现检测系统与上位机的高速通信。实验结果表明该系统具有低功耗、使用寿命长、运行稳定等特点,可实现对冷链系统中温湿度等数据的实时监测。系统安装方便,成本低廉,能够实时、准确地监测冷链系统环境温湿度变化状态,避免冷链系统因温湿度剧烈变化带来的损失。

基于云平台的环境监测系统设计与实现

在科技不断进步和现代工业化的推动下,温湿度环境监测技术的应用范围正在不断扩大,然而,由于一些情况下现场操作的不便利和不安全性,远程获取数据有些困难,因此,设计一种基于云平台环境监测系统具有非常重要的现实意义。本文以ESP8266为核心控制器,通过DHT11温湿度传感器采集数据,并通过OLED显示屏显示,使用Arduino软件进行编程调试,通过在阿里云平台上搭建可视化环境实现温湿度的可视化功能,最终通过手机云智能App和网页Web端显示环境温湿度,从而达到实时监测环境温湿度的效果。

基于云服务器的大空间高温设备远程校准系统设计

针对高温设备内的有效加热区温度校准问题,使用热电偶和标准表对其均匀性进行多点测量,并根据空间大小自由布置测温点。标准器温度采集选用六位半高精度数字表,将温度数据传输至工控触摸屏前端观测,然后将现场数据传输至云服务器进行后续处理。同时,采用云服务器或手机终端进行远程操控,克服高温环境对人体的危害,且数据结果通过云端自动进行,极大地提高了校准效率。

储能用磷酸铁锂电池充电方法评估

为研究不同充电方式对储能用磷酸铁锂电池性能的影响,针对电池充电方法提出一种基于正态云聚类的综合评估模型。首先建立电化学-副反应析锂-热耦合模型,计算低温或不均温环境下电池充电方法各评价指标值;然后依据不同指标对电池性能的影响,通过组合赋权法确定权重,并利用正态灰色云聚类模型在处理模糊性复杂问题方面的优势划分评估等级。最后通过正态灰云评估策略得到6种不同充电模式的灰色聚类系数扇形图,其中不析锂的多阶段恒流充电方式的聚类系数c^(k=4)的相对权重为0,c^(k=1)与c^(k=2)的相对权重之和为0.877,该充电模式相比其他模式来说可以最大程度保证储能电池低温下长期稳定运行。相较于现有的锂电池充电方法评估体系,所用的锂离子电池充电评估方法考虑了电池低温、不均温、大倍率下的析锂等因素,为进一步研究储能用锂离子电池优化充电策略提供有效支撑。

花卉储运环境监测系统设计与实现

以STM32L4系列芯片作为主芯片,设计花卉储运环境监测系统,该系统能实时监测环境温湿度,并通过Wi-Fi将监测数据上传至阿里云平台。实验结果表明,该系统能够实现温湿度数据的实时、远程采集,可通过阿里云平台对数据进行管理,并可通过移动端APP进行数据查询,可为花卉储运环境监测提供技术支持。

追踪强对流云团演变探讨郑州7.20暴雨产生原因

2021年7月20日,河南省在异常偏北的西太平洋副热带高压、发展加强的台风“烟花”以及西南季风的共同影响下产生了暴雨,造成了严重的生命财产损失,其中郑州市受灾最为严重。基于Himawari-8卫星云顶亮温数据,利用迭代对流云团追踪算法,对此次暴雨过程的强对流云团进行识别与追踪,探究暴雨发生的原因。结果表明,造成此次暴雨过程的强对流云团于7月20日10∶10在河南省北部生成,受太行山和嵩山的阻挡以及台风西侧东南水汽持续输送在移动过程中不断发展加强,生命周期长达9.3 h。郑州暴雨开始于对流云团最强盛时刻,而暴雨维持期间,强对流云团面积逐渐减小、云顶亮温持续升高,不稳定能量的释放和降水的拖曳作用促进了云团的减弱,云团迅速消亡,降水停止。上述研究表明在水汽持续输送和地形阻挡影响下,强对流云团发展加强和长时间盘踞是造成郑州特大暴雨的直接原因。

2021年4月崇仁一次暴雨过程分析

基于2021-04-24-2021-04-25崇仁一次暴雨过程,利用常规气象资料、地面观测数据、FY-2G云顶亮温数据及NCEP 1°×1°再分析数据,结合物理量的诊断技术,对此次暴雨的环流形势、水汽条件、动力条件、热力条件及中尺度系统进行了深入的探究。研究表明:两槽一脊大尺度环流的存在大大促进了暴雨的形成;西南急流的形成使得大量水汽持续向暴雨地带传递;大气强烈的不稳定性及垂直上升运动为暴雨过程提供了热力条件和动力条件。研究结果为短时临近天气的预报预警工作提供参考。