Cloud top height retrieval using polarizing remote sensing data of POLDER

A retrieval method of cloud top heights using polarizing remote sensing is proposed in this paper. Using the vector radiative transfer model in a coupled atmosphere-ocean system, the factors influencing the upwelling linear polarizing radiance at top-of-atmosphere are analyzed, which show that the upwelling linear polarizing radiance varies remarkably with the cloud top height, but has negligible sensitivity with cloud albedo and aerosol scattering above the cloud layer. Based on this property, a cloud top height retrieval algorithm using polarizing remote sensing was developed. The algorithm has been applied to the polarizing remote sensing data of Polarization and Directionality of the Earth＇s Reflectances-2 （POLDER-2）. The retrieved cloud top height from POLDER-2 compares well with the Moderate Resolution Imaging Spectroradiometer （MODIS） operational product with a bias of-0.83 km and standard deviation of 1.56 km.     

Evaluating evapotranspiration using data mining instead of physical-based model in remote sensing

Theoretical and Applied Climatology - Precise calculations for determining the water requirements of plants and the extent of evapotranspiration are crucial in determining the volume of water...     

Modelling the ground heat flux of an urban area using remote sensing data

Summary During the Basel Urban Boundary Layer Experiment (BUBBLE) conducted in 2002, micrometeorological in-situ data were collected for different sites using a variety of instruments. This provides a unique data set for urban climate studies. Nevertheless, the spatial distribution of energy and heat fluxes can only be taken into account with remote sensing methods or numerical models. Therefore, multiple satellite images from different platforms (NOAA-AVHRR, MODIS and LANDSAT ETM+) were acquired, processed and analysed. In addition, a high resolution digital elevation model (DEM) and a 1 m resolution digital surface model (DSM) of a large part of the city of Basel was utilized. This paper focuses on the calculation and modelling of the ground (or storage) heat flux density using remotely sensed data combined with in-situ measurements using three different approaches. First, an empirical regression function was generated to estimate the storage heat flux from NDVI values second approach used the Objective Hysteresis Model (OHM) which is often used for in-situ measurements. The last method used information of the geometric parameters of urban street canyons, computed from the high resolution digital urban surface model. Modelled and measured data are found to be in agreement within ±30 Wm⁻² and result in a coefficient of determination (R²) of 0.95.     

Aerosol remote sensing over land: A comparison of satellite retrievals using different algorithms and instruments

An inter-comparison study of the aerosol optical thickness (AOT) at 0.55 μm retrieved using different satellite instruments and algorithms based on the analysis of backscattered solar light is presented for a single scene over central Europe on October 13th, 2005. For the first time comparisons have been performed for as many as six instruments on multiple satellite platforms. Ten different algorithms are briefly discussed and inter-compared. It was found that on the scale of a single pixel there can be large differences in AOT retrieved over land using different retrieval techniques and instruments. However, these differences are not as pronounced for the average AOT over land. For instance, the average AOT at 0.55 μm for the area 7–12E, 49–53N was equal to 0.14 for MISR, NASA MODIS and POLDER algorithms. It is smaller by 0.01 for the ESA MERIS aerosol product and larger by 0.04 for the MERIS BAER algorithm. AOT as derived using AATSR gives on average larger values as compared to all other instruments, while SCIAMACHY retrievals underestimate the aerosol loading. These discrepancies are explained by uncertainties in a priori assumptions used in the different algorithms and differences in the sensor characteristics. Validation against AERONET shows that MERIS provides the most accurate AOT retrievals for this scene.     

Forecasting mesoscale convective systems in the Urals using the WRF model and remote sensing data

The results are presented ofmodeling the formation and evolution ofmesoscale convective systems (MCS) accompanied by severe weather events over the territory of the Western Urals by the WRF-ARW numerical model of the atmosphere. Twenty-three cases of mesoscale convective complexes and mesoscale squall lines are considered for 2002-2015. The Terra/Aqua MODIS data, the data of weather radars installed in Perm and Izhevsk, and the data from the Roshydromet observation network were used to verify the model forecasts. It is demonstrated that the parameters of MCS intensity are simulated by the model with high reliability; however, the quality of the forecast of the spatial position of MCS is unsatisfactory in most cases. It is revealed that the model grid spacing strongly affects the forecast skill scores. In some cases the model successfully simulates the formation and evolution of MCS accompanied by severe weather events and can be used for their short-range forecast with the time accuracy of ±(1-2) hours.     

Examination of the quality of GOSAT/CAI cloud flag data over Beijing using ground-based cloud data

It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.     

Measuring crop residue cover using remote sensing techniques

Summary Crop residues are managed under conservation tillage programs to leave as much as possible on the surface for minimization soil erosion and for improving water quality. Because current methods for measuring crop residue cover are tediuous and somewhat subjective, there is a need for new methods to measure residue cover that are rapid, accurate, and objective. We discuss the potential for discriminating crop residues from soils using reflectance and fluorescence techniques and examine experimentally the changes in wheat residue fluorescence during weathering. The fluorescence of crop residue was a board band phenomenon with emissions extending from 420 to 600 nm for excitation of 350–420 nm. Soils had low intensity broad band emissions over the 400–690 nm region for excitations of 300–600 nm. We found that the fluorescence intensities for the crop residues were much greater than the fluorescence of the soils, but as the crop residues decompose, their blue-green fluorescence intensities approach the fluorescence of the soils. We conclude that fluorescence techniques are less ambiguous and better suited for discriminating crop residues from soils than the reflectance methods. However, the potential problems, that must be addressed to implement the fluorescence technique, are (i) adequate excitation energy must be supplied to induce fluorescence and (ii) the fluorescence signal is small relative to normal, ambient sunlight. Nevertheless, if properly implemented, we believe that the fluorescence techniques can be used to quantify crop residue cover in the field.With 7 Figures     

中国区域多种微波遥感土壤湿度产品质量评估

以自动土壤水分观测站土壤湿度作为验证数据, 对2012年中国区域ASCAT、WINDSAT、FY3B、SMOS 4种微波遥感土壤湿度产品按省份进行了评估研究。结果表明:ASCAT质量最优, 在中国大多数地区与观测数据的相关系数较高, 归一化标准偏差较小。WINDSAT其次, 质量优于FY3B, 而SMOS在中国大部分地区质量差, 受无线电频率干扰严重。4种产品在中国西北地区表现均略好, 如山西、陕西、宁夏等省区。研究还发现, 同一卫星土壤湿度产品在同一季节, 不同地区评估质量不同, 这可能与不同地区的地表植被覆盖类型有关。     

Air temperature retrieval from remote sensing data based on thermodynamics

Summary A new approach to retrieving air temperature from land surface temperature is presented. The new method is based on thermodynamics. Two important parameters, namely crop water stress index and aerodynamic resistance, were used to build a quantitative relationship between the land surface temperature and the ambient air temperature. The method was applied using MODIS satellite data for a location situated in the North China Plain. Comparing the measurement values at meteorological stations with air temperature, derived by the method for certain pixels, indicates that derived values can be obtained within an accuracy of 3°C for more than 80% of data processed. Sensitivity studies also suggest that inaccuracies associated with measurement error in the model variables are also within the 3°C range.     

基于地基微波辐射计遥感的天津大气水汽和液态水特征

利用2013年3月至2017年2月天津西青地基35通道微波辐射计观测资料,分析天津地区大气水汽和液态水特征。结果表明：天津地区各季节积分水汽和积分液态水的日变化趋势基本一致,均呈单峰型日变化特征,其中夏季最大,秋季次之,冬季最小。各季节积分水汽最大值出现在23：00时（北京时,下同）的概率均明显大于其他时次,夏季和冬季的积分液态水的最大值出现在14时的概率最大,春季和秋季分别出现在10时和13时的概率最大。天津地区水汽密度由地面至3.5 km处逐渐减小,递减梯度由夏季、秋季、春季和冬季的顺序依次增大,各季节从1.5 km往上日变化均不明显。1 km以下,春季、夏季和秋季平均水汽密度的日变化曲线呈双峰型,主峰值分别出现在08时、11时和12时左右。冬季呈单峰型变化,峰值区出现在12-16时。液态水密度随高度分层变化,夏季的液态水密度大值区（0.08-0.14 g·m^-3）为5-6 km,在18-20时出现最大值。秋季、春季和冬季液态水密度的大值区出现的高度为1.5-3.5 km,但数值依次减小,春季和冬季的最大值出现在05时前后,秋季则出现在02时左右。另外天津地区水汽、液态水与温度和降水量的变化趋势基本一致,除夏季06-18时及冬季部分时次外,水汽与温度呈正相关。液态水与温度相关性较差,但与降水量呈正相关,全年液态水与降水量夜间的相关性大于白天。     

长三角地区城市用地扩展及城乡热环境的特征分析

利用1993年和2004年长三角地区的卫星遥感资料,分析了该地区的3个主要区域南京、上海、苏锡常及其周边的土地利用类型变化,定量地评价城市用地扩展程度.结合2004年地表温度(LST)卫星资料,揭示了城乡LST空间分布特征及其差异.结果表明:上海、苏锡常和南京11a期间城市建设用地动态度K分别为204.0%、354.3%和99.2%,苏锡常城市扩展程度最快;不同土地覆盖类型的LST不同,城市用地LST最高,其次作物地,林地最低;城乡之间平均地表温差具有季节变化,冬季最大,而秋季最小.     

Intelligent identification of oceanic eddies in remote sensing data via Dual-Pyramid UNet

Oceanic eddies are an omnipresent phenomenon of seawater flow and critical in transporting oceanic energy and material. Consequently, mastering and comprehending the characteristics of ocean eddies through detecting and recognizing eddies contributes to the understanding of oceanography. In traditional oceanography, a series of methods to identify eddies with physical or geometric characteristics have been developed. Deep learning frameworks have recently been applied in the eddy detection field. In this paper, a Dual-Pyramid UNet architecture that combines a pyramid split attention (PSA) module and atrous spatial pyramid pooling (ASPP) is proposed to identify oceanic eddies from remote sensing data. The encoder and decoder parts can effectively integrate low-level and high-level features, thus ensuring that feature information is not lost in large quantities after the nonlinear connection mode. In addition, the PSA and ASPP modules are introduced into the encoding, decoding, and skip connections to enhance feature extraction. Experiments were implemented in two typical study areas—the North Atlantic and South Atlantic. The recognition results demonstrate that Dual-Pyramid UNet can outperform four other competitive AI-based methods, especially for eddy edges and small-scale eddies.摘要海洋涡旋是大洋中重要的组成部分, 对海洋能量和物质的输送至关重要. 海洋涡旋的检测和表征无论是对于海洋气象学, 海洋声学还是海洋生物学等领域都具有重要的研究价值. 本文基于UNet架构, 并结合金字塔分割注意力(PSA)模块和空洞空间卷积池化金字塔(ASPP)构造了Dual-Pyramid UNet模型, 以平面异常和海表面温度数据中进行海洋涡旋的识别. 实验在北大西洋和南大西洋两个涡旋活跃区域进行并选用多个评价指标对识别结果进行评价以证明模型的优异性能.     

丘陵区土壤热通量遥感估算模型适应性分析

利用具有丘陵区典型特征的四川省乐至县气象站的土壤热通量和净辐射观测数据,分析了二者的变化特征,并验证了土壤热通量遥感估算模型的适用性。分析结果表明：晴空土壤热通量G与净辐射Rn存在明显日变化,最大值出现13时左右;其比值G／Rn受土壤湿润程度和地表覆盖的影响,地表湿润、覆盖率高,比值小。在干旱时,瞬时比值可高达0．7,而湿润情况,可低至0．05。对目前广泛使用的G／Rn卫星遥感模型估算结果与实测值的对比分析表明,不同的G／Rn卫星遥感估算模型估算结果存在明显的差异,仅依靠植被指数的模型不适合南方丘陵区。本研究认为Bastiaanssen等的模型较适合丘陵区的土壤热通量遥感估算模型。     

Modeling water and heat balance components for the river basin using remote sensing data on underlying surface characteristics

The method of the AVHRR-3 (NOAA) radiometer measurement data subject processing is produced for the retrieval of underlying surface temperature and several vegetation characteristics under cloud-free conditions. A technology for deriving the values of these parameters from the MODIS (EOS/Terra and Aqua) radiometer data is developed. The estimation of the temperature and vegetation characteristics is carried out for the Seim River basin (Kursk region) with the catchment area of 7460 km² for 2003–2005 vegetation seasons. Practical coincidence of estimations of AVHRR- and MODIS-derived temperatures, as well as the coincidence with ground observation results, is revealed. Statistics of these estimation errors is analyzed. Satellite-derived estimations of land surface temperature (LST) and vegetation characteristics are used for the calibration and verification of the developed model of the vertical heat and water transfer in the soil-vegetation-atmosphere system (SVAT). The model is intended for calculations of evapotranspiration, soil water and heat content, latent and sensible heat fluxes, and other water and heat balance components. The abilities to compute these parameters using the satellite estimations of the leaf area index and projective vegetation cover fraction as the model parameters and LST satellite estimations as the model input variable are investigated.     

Sub-seasonal interannual variability associated with the excess and deficit Indian winter monsoon over the Western Himalayas

During the winter season (Dec., Jan., and Feb.; DJF) the western Himalaya (WH) receives one-third of its annual precipitation due to Indian winter monsoon (IWM). The IWM is characterized by eastward-moving synoptic weather systems called western disturbances. Seasonal interannual precipitation variability is positively correlated with monthly interannual variabilities. However, it was found that the monthly interannual variabilities differ. The interannual variability for Jan. is negatively correlated with that for Dec. and Feb. Because the entire seasonal interannual variability is in phase with the El Niño Southern Oscillation, it is interesting to investigate such contrasting behavior. Composite analysis based on extreme wet and dry seasons indicates that Dec. and Feb. precipitation variabilities have a high positive (low negative) correlation with eastern (western) equatorial Pacific warming (cooling), whereas Jan. precipitation variability exhibits negligible correlations. Seasonal mid/upper tropospheric cooling over the Himalayas enhances anomalous cyclonic circulation, which along with suppressed convection over the western equatorial Pacific, shifts the 200-hPa subtropical westerly jet southward over the Himalayas. Due to the upper tropospheric anomalous cyclonic circulation, mass transfer favors anticyclone formation at the mid/lower troposphere, which is enhanced in Jan. due to a warmer mid troposphere and hence decreases precipitation compared with Dec. and Feb. Additionally, a weakening of meridional moisture flux transport from the equatorial Indian Ocean to WH is observed in Jan. Further analysis reveals that mid-tropospheric and surface temperatures over WH also play dominant roles, acting as local forcing where the preceding month’s surface temperature controls the succeeding month’s precipitation.