One-Dimensional Variational Retrieval of Temperature and Humidity Profiles from the FY4A GIIRS

A physical retrieval approach based on the one-dimensional variational(1 D-Var) algorithm is applied in this paper to simultaneously retrieve atmospheric temperature and humidity profiles under both clear-sky and partly cloudy conditions from FY-4 A GIIRS(geostationary interferometric infrared sounder) observations. Radiosonde observations from upper-air stations in China and level-2 operational products from the Chinese National Satellite Meteorological Center(NSMC)during the periods from December 2019 to January 2020(winter) and from July 2020 to August 2020(summer) are used to validate the accuracies of the retrieved temperature and humidity profiles. Comparing the 1 D-Var-retrieved profiles to radiosonde data, the accuracy of the temperature retrievals at each vertical level of the troposphere is characterized by a root mean square error(RMSE) within 2 K, except for at the bottom level of the atmosphere under clear conditions. The RMSE increases slightly for the higher atmospheric layers, owing to the lack of temperature sounding channels there.Under partly cloudy conditions, the temperature at each vertical level can be obtained, while the level-2 operational products obtain values only at altitudes above the cloud top. In addition, the accuracy of the retrieved temperature profiles is greatly improved compared with the accuracies of the operational products. For the humidity retrievals, the mean RMSEs in the troposphere in winter and summer are both within 2 g kg^(–1). Moreover, the retrievals performed better compared with the ERA5 reanalysis data between 800 h Pa and 300 h Pa both in summer and winter in terms of RMSE.

A COMPARISON OF THE RETRIEVAL OF ATMOSPHERIC TEMPERATURE PROFILES USING OBSERVATIONS OF THE 60 GHZ AND 118.75 GHZ ABSORPTION LINES

The Microwave Temperature Sounder-Ⅱ(MWTS-Ⅱ) and Microwave Humidity and Temperature Sounder(MWHTS) onboard the Fengyun-3 C(FY-3 C) satellite can be used to detect atmospheric temperature profiles. The MWTS-II has 13 temperature sounding channels around the 60 GHz oxygen absorption band and the MWHTS has 8 temperature sounding channels around the 118.75 GHz oxygen absorption line. The data quality of the observed brightness temperatures can be evaluated using atmospheric temperature retrievals from the MWTS-Ⅱ and MWHTS observations. Here, the bias characteristics and corrections of the observed brightness temperatures are described. The information contents of observations are calculated, and the retrieved atmospheric temperature profiles are compared using a neural network(NN) retrieval algorithm and a one-dimensional variational inversion(1 D-var) retrieval algorithm. The retrieval results from the NN algorithm show that the accuracy of the MWTS-Ⅱ retrieval is higher than that of the MWHTS retrieval, which is consistent with the results of the radiometric information analysis. The retrieval results from the 1 D-var algorithm show that the accuracy of MWTS-Ⅱ retrieval is similar to that of the MWHTS retrieval at the levels from 850-1,000 h Pa, is lower than that of the MWHTS retrieval at the levels from 650-850 h Pa and 125-300 h Pa, and is higher than that of MWHTS at the other levels. A comparison of the retrieved atmospheric temperature using these satellite observations provides a reference value for assessing the accuracy of atmospheric temperature detection at the 60 GHz oxygen band and 118.75 GHz oxygen line. In addition, based on the comparison of the retrieval results, an optimized combination method is proposed using a branch and bound algorithm for the NN retrieval algorithm, which combines the observations from both the MWTS-Ⅱand MWHTS instruments to retrieve the atmospheric temperature profiles. The results show that the optimal combination can further improve the accuracy of MWTS-Ⅱ retrieval and enhance the detection accuracy of atmospheric temperatures near the surface.

Assessing the response of dryland barley yield to climate variability in semi-arid regions,Iran

Precipitation and temperature are the most abiotic factors that greatly impact the yield of crop,particularly in dryland.Barley,as the main cereal is predominantly cultivated in dryland and the livelihood of smallholders depends on the production of this crop,particularly in arid and semi-arid regions.This study aimed to investigate the response of the grain yield of dryland barley to temperature and precipitation variations at annual,seasonal and monthly scales in seven counties of East and West Azerbaijan provinces in northwestern Iran during 1991-2010.Humidity index(HI)was calculated and its relationship with dryland barley yield was evaluated at annual and monthly scales.The results showed that the minimum,maximum and mean temperatures increased by 0.19℃/a,0.11℃/a and 0.10℃/a,respectively,while annual precipitation decreased by 0.80 mm/a during 1991-2010.Climate in study area has become drier by 0.22/a in annual HI during the study period.Negative effects of increasing temperature on the grain yield of dryland barley were more severe than the positive effects of increasing precipitation.Besides,weather variations in April and May were related more to the grain yield of dryland barley than those in other months.The grain yield of dryland barley was more drastically affected by the variation of annual minimum temperature comparing with other weather variables.Furthermore,our findings illustrated that the grain yield of dryland barley increased by 0.01 t/hm^(2) for each unit increase in annual HI during 1991-2010.Finally,any increase in the monthly HI led to crop yield improvement in the study area,particularly in the drier counties,i.e.,Myaneh,Tabriz and Khoy in Iran.

Research on the Application of the Radiative Transfer Model Based on Deep Neural Network in One-dimensional Variational Algorithm

As a typical physical retrieval algorithm for retrieving atmospheric parameters,one-dimensional variational(1 DVAR)algorithm is widely used in various climate and meteorological communities and enjoys an important position in the field of microwave remote sensing.Among algorithm parameters affecting the performance of the 1 DVAR algorithm,the accuracy of the microwave radiative transfer model for calculating the simulated brightness temperature is the fundamental constraint on the retrieval accuracies of the 1 DVAR algorithm for retrieving atmospheric parameters.In this study,a deep neural network(DNN)is used to describe the nonlinear relationship between atmospheric parameters and satellite-based microwave radiometer observations,and a DNN-based radiative transfer model is developed and applied to the 1 DVAR algorithm to carry out retrieval experiments of the atmospheric temperature and humidity profiles.The retrieval results of the temperature and humidity profiles from the Microwave Humidity and Temperature Sounder(MWHTS)onboard the Feng-Yun-3(FY-3)satellite show that the DNN-based radiative transfer model can obtain higher accuracy for simulating MWHTS observations than that of the operational radiative transfer model RTTOV,and also enables the 1 DVAR algorithm to obtain higher retrieval accuracies of the temperature and humidity profiles.In this study,the DNN-based radiative transfer model applied to the 1 DVAR algorithm can fundamentally improve the retrieval accuracies of atmospheric parameters,which may provide important reference for various applied studies in atmospheric sciences.

青藏高原冬季平均温度、湿度气候特征的REOF分析

通过对青藏高原 1 2 3个测站 ,1 961～ 1 998年冬季 ( 1 2月至翌年 2月 )平均温度、相对湿度资料做气候特征分析 ,得到 32°～ 33°N附近地区可能是高原南北温湿变化的分水岭 ,以北主要受干冷空气影响 ,以南主要受暖湿空气影响。用方差极大正交旋转EOF(即REOF)方法对以上资料进行分析 ,可以将青藏高原温度、相对湿度进行分型、分区 ,并对各区的温度、相对湿度特征进行分析。结果表明 ,近 40年来 ,各区的温度总趋势是在波动中逐步升高的。增温时段主要出现在 1 978～ 1 981年及 1 983年至今。 1 983年开始的增温 ,是近 40年来最强的一次 ,增温幅度大且持续时间长 ,但从 90年代开始增温幅度及范围出现波动。从温度线性倾向来看 ,东部高原增温幅度从南到北存在“大—小—大”的现象。高原大部分地区湿度变化总趋势是在波动中逐步增湿的 ,但高原北界以变干为主。从 80年代后期至今高原进入显著增湿阶段 ,但从 90年代中后期开始增湿幅度及范围出现波动。从湿度线性倾向来看东部高原增湿幅度从南到北存在逐步减小现象 ,甚至祁连山地区出现变干现象。

Theoretical analyses and numerical experiments of variational assimilation for one-dimensional ocean temperature model with techniques in inverse problems

In the present work, the data assimilation problem in meteorology and physical oceanography is re-examined using the variational optimal control approaches in combination with regularization techniques in inverse problem. Here the estimations of the initial condition, boundary condition and model parameters are performed simultaneously in the framework of variational data assimilation. To overcome the difficulty of ill-posedness, especially for the model parameters distributed in space and time, an additional term is added into the cost functional as a stabilized functional. Numerical experiments show that even with noisy observations the initial conditions and model parameters are recovered to an acceptable degree of accuracy.

基于一维变分法的微波辐射计反演边界层温湿廓线

地基微波辐射计能够克服星载遥感对低层大气不敏感的缺点,在边界层大气探测方面更具优势.一维变分反演算法考虑了辐射传输过程等物理机制,在应用于微波辐射计的反演时具有很高的可信度.针对微波辐射计信息含量较低以及一维变分算法收敛率不高等问题,提出利用地面气象要素改进算法在近地面层的反演精度和引入正则化算子提升算法的收敛特性.利用探空数据对上述改进方法的提升效果进行验证,结果表明:地面气象要素的引入使得反演算法在地表温湿度的均方根误差分别降低了78.2%和55.5%,对于上层大气温湿廓线也有小幅提升;正则化算子对算法的反演时间和反演精度影响很小,但是可以显著地减少未收敛样本个数和提升反演廓线的质量.

日光温室作物冠层夏季光照强度与空气温湿度时空变化规律研究

针对温室内不同时间、位置的环境参数存在变异性,且随天气与季节变化,日光温室冠层光照强度、空气温度和空气相对湿度的分布差异性问题,构建了基于无线传感器网络的环境监测系统。环境感知节点部署在作物冠层位置,集成了光照强度、空气温湿度等传感器。首先,基于实时采集的温室环境数据,采用反距离加权算法进行插值分析,得到环境参数的离散曲面;其次,通过基于质心坐标的K-means聚类算法,得到了温室内连通及非连通区域的代表性特征点;最后,采用半变异函数与变异系数方法对温室环境的空间变异性与时间变异性进行分析。实验结果表明,夏季日光温室在下午表现为高温与高光照,08:00、16:00的光照强度分别为12:00的24.2%、72.9%,08:00的空气温度(27.7℃)较12:00、16:00低约6.0℃,对应的空气湿度(90%)高约30%。晴天最大光照强度分别为阴天、雨天的1.4倍和4.6倍,晴天、阴天最高空气温度高于雨天(29.5℃)约6℃,最小空气相对湿度远低于雨天(84%)。夏季日光温室晴天与阴天表现为高温和低湿,雨天表现为高湿和低光照。各环境参数中,光照强度的空间变异性最强,变程为10.34 m。空气温湿度的空间变异性较弱,整体分布均匀。光照强度、空气温度和空气相对湿度的时间变异性均为中等变异程度。环境参数的特征点及时空变化规律有助于日光温室传感器的高效部署,为揭示作物与环境的交互作用提供了基础。

变温斜率与散射功率补偿的分布式光纤测温传感系统

针对分布式光纤拉曼测温传感系统中存在的空间分辨率与传感距离相互制约的问题以及在单模光纤上应用信噪比低的问题,提出一种加大探测脉冲宽度、提高信噪比而保持空间分辨率不变的方法,同时实现长距离传感。通过分析脉冲光在光纤中的传输过程以及光纤变温段的温度变化规律,利用温度变化曲线斜率与后向散射光功率建立温度补偿方案。实验证明,使用脉宽为50 ns的脉冲光与10 ns脉冲光相比,信噪比由33.38 dB提升到39.58 dB,10 km光纤末端测温最大稳态误差由±2.0℃减小到±1.0℃,20 km光纤末端测温最大稳态误差由±4.0℃减小到±2.0℃,同时空间分辨率保持1 m不变。

节能日光温室中番茄灰霉病发生规律的研究

通过 3年对节能日光温室环境温湿度监测、病菌孢子捕捉和番茄灰霉病发生规律研究明确 ,一般年份 ,灰霉病在番茄叶片上表现为明显的始发期、盛发期和末发期等 3个阶段 ;果实发病后 ,即进入盛发期。温室中病菌的发生与病害呈正相关 ,病菌的高峰期较病害的高峰期提前 10～ 15d。持续的低温、高湿、苗期带病等是引起番茄灰霉病发生的重要因子。提出要从优化设施环境等方面来控制番茄灰霉病的危害。

旅游环境舒适度评价及其时空分异——以杭州西湖为例

旅游环境舒适度是影响旅游者出行决策和消费行为的重要因素,进一步影响到目的地适游期长短和旅游设施利用率。影响旅游舒适度的因素主要包括气候与环境两方面。以杭州西湖景区为研究对象,尝试将影响舒适度的空气质量、噪音等环境因素与气候因素共同纳入评价体系,选取温度、相对湿度、二氧化碳、一氧化碳、噪音5项指标和6个代表性检测点,进行为期1a定时定点检测,在排除二氧化碳与一氧化碳影响的基础上,构建了旅游环境舒适度评价模型,研究景区尺度存在的旅游环境舒适度时空分异特征。研究发现:不舒适时段主要集中在1月上旬到2月下旬,舒适和较舒适时段主要集中于2月下旬到7月中旬、8月下旬到11月下旬;山区与湖区各项环境指标要优于近城区、游客集聚区及交通繁忙区,平均舒适度山区(1.30)>湖心区(1.66)>城区(1.82)>近城区(2.02)>游人集聚区(2.47)>交通繁忙区(2.48)。6个观测点在不同时段表现的舒适度差异也不同,差异最大的时段出现在4月中旬到5月中旬,差异最小时段出现在1月上旬到2月下旬。温湿度与噪音存在反向协同作用,引起环境舒适度变化。温湿度舒适时段往往旅游活动频繁,导致噪音升高降低了旅游环境舒适度。温湿度不舒适期旅游活动减少使得声环境相对舒适。

敦煌莫高窟第108窟西壁岩体内温湿度变化规律研究

敦煌莫高窟保存有大量精美的壁画,随着时间的推移,一些洞窟的壁画产生了酥碱、起甲、空鼓等病害。大量研究表明,盐分运移和富集是导致壁画产生病害的主要因素,而岩体内水汽梯度和温度梯度的存在则为盐分的运移提供了先决条件。为寻找出温度和相对湿度在岩体内部的变化规律以及它们之间的相互影响与制约关系,我们在第108窟西壁壁画脱落处钻孔安装了温湿度监测设备,开展洞窟岩体内温湿度的长期监测。本文以莫高窟第108窟西壁岩体内最近3年的温湿度实测数据为依据,通过对温湿度数据采用横向、纵向对比,得出如下结论:岩体内浅部区域,在温度增高的方向上,水汽呈减少的趋势。在垂直和水平方向上,温度变化呈周期性,相对湿度则由表向里逐渐升高,且在一定深度内达到稳定。本次研究探索了洞窟岩体内温度对相对湿度的影响以及温湿度的变化规律,为进一步分析壁画病害机制和采取防范措施提供了科学依据。

西南喀斯特地区几种主要土地覆被下土壤CO_2-C通量研究

中国西南喀斯特地区土壤营养元素流失形势严峻,揭示不同土地覆被下土壤CO2-C的释放规律,是认识喀斯特这一特殊环境诸多营养元素循环问题的一个重要途径。采用静态箱-气相色谱法对贵州喀斯特地区4种不同土地覆被下的土壤CO2-C释放通量进行观测研究。结果表明,(1)不同的土地覆被下土壤CO2-C释放通量有显著的差别,其释放顺序为:森林((134.1±78.8)mg/(m2·h))>次生林((70.8±122.3)mg/(m2·h))>玉米地((55.5±78.0)mg/(m2·h))>烧荒地((35.5±91.4)mg/(m2·h))。各样点季节变化都比较明显,夏季平均排放量最高,冬季最低。(2)凋落物对森林土壤CO2-C释放的影响较大,有凋落物覆盖的土壤CO2-C释放量((134.1±78.8)mg/(m2·h))高于无凋落物覆盖的林地土壤((111.2±80.3)mg/(m2·h)),凋落物分解对森林土壤CO2-C释放总量的贡献约占17%。基于地面气温,计算得出森林和森林(无凋落物)的Q10分别为1.92、2.10。(3)除次生林和烧荒地外,其余各样地CO2-C释放通量均与土壤各层温度呈显著正相关关系,但绝大多数样地与土壤湿度(WFPS)之间相关性不显著。

塑料三连栋温室的温、湿度变化规律初探及相应调控措施

通过使用多点式温、湿度记录仪 ,结合温室设备的不同处理方式 ,对塑料三连栋温室温、湿度进行全年连续记录 ,初步摸索出塑料三连栋温室温、湿度的变化规律 ,并初步提出了温、湿度的调控措施。

基于一维变分算法的红外高光谱(IASI)卫星遥感大气温湿廓线研究

大气温湿度廓线是大气重要参数,在数值天气预报及天气预警中具有重要的应用价值。为获得高精度的大气温度与水汽混合比廓线数据,研究了基于Metop-A/IASI红外高光谱资料的大气温度与水汽混合比廓线变分反演方法。利用IASI高光谱传感器温度和水汽探测通道资料,结合CRTM模式和WRF模式预报技术,使用一维变分方法,研究了卫星资料质量控制、背景误差协方差本地化、观测误差协方差计算等方法,构建了大气温度及水汽混合比廓线变分反演系统,并在北京、青岛、沈阳3个地区开展了反演试验。以探空为标准的反演结果对比显示,使用WRF模式预报值作为背景场,温度的平均误差绝对值小于0.6K,均方根误差为0.89K;水汽混合比的平均误差绝对值小于0.021g/kg,均方根误差为0.02g/kg。试验结果表明:基于一维变分方法,可以利用Metop-A/IASI红外高光谱资料进行大气温度与水汽混合比廓线高精度探测。

高温季节不同防虫网覆盖方式下的设施环境温湿度变化规律

本试验通过使用智能型温湿度记录仪，以露地为对照，对夏季高温季节3种防虫网覆盖方式下（大棚覆盖、小拱棚覆盖、苗床覆盖）的空气温湿度以及土壤或基质温度进行连续记录，初步摸索出3种防虫网覆盖方式下温湿度的变化规律。结果表明，高温晴天、阴雨天以及雨天后晴天的白天，不同处理纱网内的空气温度都低于露地；14：00时，3种天气情况下的空气湿度都高于露地，而土温都低于露地。大棚纱网及苗床纱网由于通风条件好，在晴好天气空气温度比小棚纱网低2℃左右。苗床纱网基质温度整个高温生长季节较其它3种栽培方式的土壤温度低2-3℃，可有效的防止烂菜，全封闭的生长和管理模式也起到很好的防虫效果，因此苗床纱网基质栽培可以作为夏季高温季节较好的叶菜类栽培方式。

开放洞穴环境变化特征及其影响因素——以桂林凉风洞为例

通过对桂林凉风洞洞穴内、外温湿度、 p CO 2进行连续高频监测,发现洞穴温度受大气度温影响呈现出季节性变化规律。由于受到洞穴结构的阻隔作用影响,洞穴由外向里的温度变化幅度逐渐变小,并且响应的时间存在季节性差异。监测数据表明:洞穴内部温度的季节性变化幅度明显低于洞外气温变化幅度。比较洞内、外温度的时间序列发现,在季节尺度上洞穴温度升温阶段滞后时间长(与外部通风的气温流动交换慢),降温阶段滞后时间短(与外部通风的气温流动交换快,呈现突变特征),这可能与不同季节洞穴内部结构的“缓冲作用”的强弱变化有关。该洞穴空气中 p CO 2存在明显的夏季高、冬季低的季节性变化特征。并且外界大气环境季节性变化和洞穴上覆动植物的季节性活动,使得洞穴 p CO 2主控因素也存在季节性差异。

玉渊潭不同功能区春季负离子浓度变化研究

文章重点讨论了北京市玉渊潭公园春季负离子等级、负离子浓度的日变化以及温度、湿度对负离子变化的影响。在测定过程中,将玉渊潭公园分为乐园区、滨水区、铺路区、绿化区,使用DLY-3G型大气离子测量仪分别对每个区的负离子浓度进行测量,并采取单级系数和安培空气质量评价系数对负离子浓度等级进行评价。结果表明,玉渊潭公园乐园区、滨水区、铺路区及绿化区负离子释放量由少到多,4个功能区负离子等级分别为允许范围、一般清洁、一般清洁、中度清洁;乐园区、滨水区、铺路区及绿化区负离子在不同时刻呈现出不同的浓度值,且日变化都呈"双峰"型;对负离子浓度随温度、湿度变化的相关性进行分析,得出玉渊潭公园负离子浓度变化与温度成正相关关系、与湿度成负相关关系。综上所述,玉渊潭公园是一个休闲娱乐的好去处。

U形毛细管席冷却顶板换热性能数值模拟与分析

通过建立毛细管席的三维流-固耦合换热模型,应用CFD软件进行数值计算,分析各因素对供冷能力的影响和毛细管内水温变化规律,为毛细管席产品优化和设计参数的确定提供参考。

冷藏车开门时车内温湿度变化实验研究

配送过程中冷藏车开门时的热质交换会引起车内空气温湿度的剧烈变化,这使得食品的品质难以得到保证。针对目前冷藏车开门卸货时存在的一些问题,进行了对比实验,对不同条件下的车内温度、相对湿度变化进行了分析,得出在开门时长一定的情况下车厢内外空气温差是影响车内温升的主要因素,采用PVC门帘可以有效地抑制车内温度升高,一定程度上保证食品安全。