环境一号卫星热红外数据监测核电站温排水分布——以大亚湾为例

选择2009年的2景环境一号卫星热红外数据,利用单通道算法计算了大亚湾海水表面温度,分析该算法反演的海温空间分布特征,得到如下结论:大亚湾和岭澳核电站排水的出口温度,比周围水温高3℃～5℃,呈现明显的扩散状。然后,综合直方图和选取的5个样本点,将本文反演结果和当天的MODIS海水表面温度产品进行比较,结果表明:二者的海温分布特征基本一致。本文证实了环境一号卫星热红外遥感数据监测温排水的可行性。     

基于PMDB数据集的海表温度反演误差统计分析

红外辐射计在测量海表温度时,大气水汽含量是影响遥感反演精度的主要因素之一。利用1988年1月~2009年11月60°N~60°S的SST和水汽月平均资料及AVHRR准同步实测数据集PMDB,分析了海表温度及其卫星反演误差和海面水汽含量的相关关系。结果表明：海表温度和水汽含量的纬度带月均值具有明显的季节变化特征。纬度越高,遥感SST偏离实测SST越小;在中低纬海域,PFSST算法通常低估了海表温度,而高纬度海域则高估了海表温度;SST误差的气候态月均值在中高纬海域具有较好的季节分布特征,与水汽、SST的季节变化相关性较高。     

GF-5卫星模拟单通道SST反演

针对国内外热红外数据空间分辨率低、反演温度精度低的问题,提出了基于高分辨率GF-5卫星热红外通道修订的单通道海表温度(sea surface temperature,SST)反演算法。以大气传输模型软件(moderate resolution atmospheric transmittance and radiance code4.0,MODTRAN 4.0)与全球大气廓线数据(thermodynamic initial guess retrieval,TIGR)为基础,采用Jiménez-MuozSobrino's单通道算法和QIN单通道算法对GF-5卫星热红外数据进行SST的模拟反演研究。通过对比不同条件下的反演误差,结果表明,B11通道的反演精度高、效果最好,B12、B10通道次之,B09通道反演精度最低;传感器垂直向下观测即观测天顶角为0°时的SST反演精度最高。由于单通道算法反演误差较大,因此进行了二次修订,修订后效果有明显改善,误差在1K以内。     

基于MODIS的海表面温度反演系统设计与实现

海表面温度(SST)是重要的海洋物理参数,对海洋研究具有重要意义.通过遥感数据反演是目前获取SST数据的主要方法之一.遥感反演数据具有反映大区域尺度的海温连续分布状况,且数据获取及时稳定等特点.本文基于IDL构建了面向EOS/MODIS数据的SST反演系统,讨论了系统的功能和结构,给出了具体的数据反演处理流程,对系统中采用的SST反演算法和云检测方法进行了详细说明.最后以我国东海海域为例,将反演结果与多年观测资料对比,表明系统反演得到的SST分布规律与多年观测资料一致,同时还利用同步观测的浮标数据和NASA MODIS SST产品对反演结果进行验证,结果显示系统反演的SST平均误差为1℃.数据精度满足海洋预报和其他科学研究的需要.     

风云三号传感器红外通道海表比辐射率模拟

海表比辐射率（SSE）是从卫星被动遥感数据反演海表温度（SST）的关键参数之一,本文讲述了利用Wu andSmith（1997）发展的SSE模型,对搭载在风云三号（FY-3A）上的红外大气探空仪（IRAS）第8（12.47μm）、9（11.11μm）、19（3.98μm）和20（3.76μm）波段,中分辨率光谱成像仪（MERSI）第5波段（11.54μm）,可见光红外扫描辐射计（VIRR）第3（3.65μm）、4（11.00μm）和5（12.13μm）波段的SSE进行模拟计算。模拟结果表明,SSE是观测角度、波长和海表粗糙度（海面风速）的函数。模拟值与IRAS、MERSI和VIRR红外通道波谱响应函数进行卷积计算得到波段SSE。在观测角度小于60°时,波段SSE对海面风速不敏感,使用风速为8m/s的SSE替代其他风速条件下的SSE所引起的误差小于0.5%。另外,使用波段SSE计算卫星观测值所导致的误差不超过0.05K,可以忽略不计。波段SSE随观测角度变化的规律可以用高斯函数进行描述,拟合误差小于0.02%,相关系数为1.000。本文的模拟结果可以用于SST的精确反演。     

基于Apache Spark的MODIS海表温度反演方法

为应对海量遥感影像快速计算的需求,通过对影像获取、算法和计算过程优化和改进,提出了一种基于Apache Spark并行计算框架的MODIS海表温度反演方法,实现了海量MODIS遥感影像的海表温度快速反演.应用四轮网络查询请求获取特定的时空范围影像数据,提高影像获取阶段的效率;应用简化算法参数、拟合过程变量改进海表温度劈窗算法,使之适合快速并行计算;应用弹性分布式数据集（RDD）窄依赖关系的优点,避免并行计算中的数据交换延迟.通过单机模式与集群模式对比实验,发现集成了并行计算框架的集群模式影像处理效率约为单机模式的10倍.研究结果表明了融合集群计算技术的海表温度反演过程有效提高了传统单机应用程序的处理效率.     

卫星遥感反演土壤有机质研究进展

土壤有机质是评价土壤质量的关键指标,了解土壤有机质含量及其空间分布,对实现土壤养分精准管理、促进农业可持续发展具有重要意义。近年来,遥感技术的迅猛发展为土壤属性定量化研究提供了丰富的数据源,卫星遥感反演土壤有机质逐渐吸引了更多的关注。文章针对土壤有机质反演的相关研究,阐述了土壤遥感及传感器发展历程、土壤有机质遥感反演机理;系统归纳了直接法、间接法以及实测高光谱与卫星遥感相结合3种反演方法的发展现状;将不同研究方法的优势及不足进行对比,并详细分析制约土壤有机质反演精度的关键因素,最后对卫星遥感反演土壤有机质的发展趋势进行展望。     

基于随机森林和遥感的台风降水云光谱与降水关系研究

台风降水云系的云顶光谱-微物理信息与降水强度的变化密切相关,是卫星遥感定量反演降水的重要参数。以2001—2012年西北太平洋的7个典型超强台风和5个非超级台风为研究对象,基于热带测雨卫星搭载的测雨雷达与可见光红外扫描仪的融合资料,建立了降水云顶光谱-微物理参数反演台风降水的随机森林（RF）模型。结果表明：随机森林模型的交叉验证显示,反演的降水强度与观测的降水强度的相关系数为0.773,均方根误差为0.299 mm/h,表明该模型具有较高的降水反演精度。在随机森林构建过程输入的所有云顶光谱—微物理参数中,3.7 μm云顶亮温对模型的方差贡献最大,重要性最高;而由于台风中心云系整体均发展旺盛且云顶较高,10.8 μm云顶红外通道亮温以及云光学厚度、云水含量对模型的方差贡献较小,重要性低。     

中国江淮、黄淮地区陆面微波比辐射率的变化特征

陆面微波比辐射率较高且易变,造成陆面上反演降水以及其它大气参数较为困难。对于地表特征复杂的中国,陆面微波比辐射率的研究还很有限。通过利用Tropical Rainfall Measuring Mission（TRMM）卫星上同步扫描的VIRS（红外和可见光）与TMI（微波）资料以及微波辐射传输模式反演了中国江淮、黄淮地区陆面微波比辐射率。然后,结合MODIS提供的地表类型数据,分析了江淮、黄淮地区不同地表微波比辐射率的时空变化特征。 结果表明该地区的农作物地表比辐射率最小,垂直与水平比辐射率极化差最大;而森林地表比辐射率最大,极化差最小。此外,不同地表的微波比辐射率昼夜变化明显,季节变化不明显。比辐射率估算误差中,地表温度、微波亮温和大气相对湿度3因子的准确计算对22GHz和85GHz的影响较为明显,对其它通道影响较小。对于小于85GHZ的通道,比辐射率估算精度受微波亮温的影响最为明显,地表温度其次,相对湿度最小;对于高频85OHz,相对湿度的影响最明显,其次是微波亮温,最后是地表温度。     

基于高空间分辨率的热污染遥感监测研究进展

综述了卫星遥感热红外海表温度反演原理,并对海表温度中的“皮温”和“体温”进行了界定;着重总结了热红外遥感海表温度反演的主要方法-单通道法、分裂窗法、多角度法等;详细介绍了具有较高热红外通道空间分辨率卫星传感器Landsat TM/ETM+、CBERS-02 IRMSS、ASTER、HJ-1B IRS的海表温度反演算法,并对各卫星热红外通道特点进行了对比;最后,对影响热红外温度反演精度的因素进行了简要分析,指出了目前研究存在的问题并对未来的研究方向进行了展望。     

Derivation of lake mixing and stratification indices from high-resolution lake buoy data

Lake Analyzer is a numerical code coupled with supporting visualization tools for determining indices of mixing and stratification that are critical to the biogeochemical cycles of lakes and reservoirs. Stability indices, including Lake Number, Wedderburn Number, Schmidt Stability, and thermocline depth are calculated according to established literature definitions and returned to the user in a time series format. The program was created for the analysis of high-frequency data collected from instrumented lake buoys, in support of the emerging field of aquatic sensor network science. Available outputs for the Lake Analyzer program are: water temperature (error-checked and/or down-sampled), wind speed (error-checked and/or down-sampled), metalimnion extent (top and bottom), thermocline depth, friction velocity, Lake Number, Wedderburn Number, Schmidt Stability, mode-1 vertical seiche period, and Brunt-Väisälä buoyancy frequency. Secondary outputs for several of these indices delineate the parent thermocline depth (seasonal thermocline) from the shallower secondary or diurnal thermocline. Lake Analyzer provides a program suite and best practices for the comparison of mixing and stratification indices in lakes across gradients of climate, hydro-physiography, and time, and enables a more detailed understanding of the resulting biogeochemical transformations at different spatial and temporal scales.     

Environmental effects on yellowfin tuna catch by the Taiwan longline fishery in the Arabian Sea

In this study, we collected environmental variables to investigate their effects on the catch per unit effort (CPUE) of yellowfin tuna in the Arabian Sea during the period 1980–2005. We used an advanced time series analysis, including a state-space approach to remove seasonality, and wavelet analysis to investigate transient relationships. For large-scale environmental effects, we used the dipole mode index (DMI) to represent the Indian Ocean dipole; for local environmental factors, we investigated sea surface temperature (SST), thermocline depth and chlorophyll-a (chl-a) concentration. The main factors causing interannual variations in the CPUE might change with time. CPUE showed positive correlations with SST and DMI from the beginning of the 1980s to the middle of the 1990s. It also showed a significant coherence with chl-a, especially a long-term positive correlation for the regular longline fishery in 1998–2005 with a periodicity of 2 years. Both regular and deep longline CPUEs were found to have significant coherence with thermocline depth having a periodicity of 3 years. The relations were of opposite signs such that the shallow thermocline depth produced a high CPUE for the regular longline fishery and deep thermocline depth caused a high CPUE for the deep longline fishery.     

Bottom influence on the reflectance of the sea

Abstract

Solar irradiance reflectance spectra of seawater with a variable content of particulate and dissolved materials as well as a variable bottom depth and composition were calculated. A two-flow radiative transfer model was employed, where the spectral signatures, characteristic for diverse seawater and bottom types, were introduced as input parameters. Optical signals in the spectral bands of LANDSAT MSS and TM, SPOT HRV and TIROS-N AVHRR scanners were computed in order to establish algorithms for remote determination of the bottom depth and composition. Several algorithms were proposed and their applicability discussed. The algorithms appear to be applicable down to depths of 3-20 m, depending on the water column and bottom composition.     

Detection of Rossby waves in multi-parameters in multi-mission satellite observations and HYCOM simulations in the Indian Ocean

Rossby waves are difficult to detect with in situ methods. However, as we show in this paper, they can be clearly identified in multi-parameters in multi-mission satellite observations of sea surface height (SSH), sea surface temperature (SST) and ocean color observations of chlorophyll-a (chl-a), as well as 1/12° global HYbrid Coordinate Ocean Model (HYCOM) simulations of SSH, SST and sea surface salinity (SSS) in the Indian Ocean. While the surface structure of Rossby waves can be elucidated from comparisons of the signal in different sea surface parameters, models are needed to gain direct information about how these waves affect the ocean at depth. The first three baroclinic modes of the Rossby waves are inferred from the Fast Fourier Transform (FFT), and two-dimensional Radon Transform (2D RT). At many latitudes the first and second baroclinic mode Rossby wave phase speeds from satellite observations and model parameters are identified. Wavelet transforms of these multi-parameters from satellite observations and model simulations help to discriminate between the annual and semi-annual signal of these Rossby waves. This comprehensive study reveals that the surface signature of Rossby waves in SSS anomalies is likely to be between 0.05 and 0.3 psu in the South Indian Ocean.     

Further validation of a new methodology for surface moisture and vegetation optical depth retrieval

A series of validation studies for a recently developed soil moisture and optical depth retrieval algorithm is presented. The approach is largely theoretical, and uses a non-linear iterative optimization procedure to solve a simple radiative transfer equation for the two parameters from dual polarization satellite microwave brightness temperatures. The satellite retrievals were derived from night-time 6.6?GHz Nimbus Scanning Multichannel Microwave Radiometer (SMMR) observations, and were compared to soil moisture data sets from the USA, Mongolia, Turkmenistan and Russia. The surface temperature, which is also an unknown parameter in the model, is derived off-line from 37?GHz vertical polarized brightness temperatures. The new theoretical approach is independent of field observations of soil moisture or canopy biophysical measurements and can be used at any wavelength in the microwave region. The soil moisture retrievals compared well with the surface moisture observations from the various locations. The vegetation optical depth also compared well to time series of Normalized Difference Vegetation Index (NDVI) and showed similar seasonal patterns. From a global perspective, the satellite-derived surface soil moisture was consistent with expected spatial patterns, identifying both known dry areas such as deserts and semi-arid areas and moist agricultural areas very well. Spatial patterns of vegetation optical depth were found to be in agreement with NDVI. The methodology described in this study should be directly transferable to the Advanced Microwave Scanning Radiometer (AMSR) on the recently launched AQUA satellite.     

How consistent is the satellite derived SST–LHF relationship in comparison with observed values?

Time series data for sea surface temperature (moored buoy), wind speed, air temperature, sea level pressure, relative humidity, short wave radiation and rainfall were collected close to the Lakshadweep islands for five months from July 2000 to cover two seasons, namely summer monsoon and autumn. Day and night passes of TMI data for the same period were analysed to compare with the observed values. Daily mean values were then generated from both satellite‐derived as well as observed parameters and daily latent heat flux (LHF) values computed using the advanced COARE‐3.0 version of the model. In concurrence with earlier studies, the observed LHF–SST relationship was inverse as the SST during this season seldom fell below 27°C. On the contrary, the satellite derived LHF–SST relationship exhibited a direct correlation. It is also observed that the satellite underestimation of SST increases linearly on either side of a threshold value of 28.5°C. Although the SST over the eastern Arabian Sea was generally above 27°C, the satellite underestimation often produced SSTs less than 27°C, thereby supporting a linear relationship with LHF, as suggested by Zhang and McPhaden. Similarly for SSTs higher than 28°C, the satellite underestimation prevented a further decrease of LHF (to sustain the linear relationship) by virtue of the inverse relationship for SSTs higher than 28°C. The overestimation of SST and wind speed in the satellite scenario generates a virtual enhancement of LHF values without cooling the sea surface. The linear relationship between SST and LHF is thus nothing but a virtual display of the observed inverse SST–LHF relationship.     

Remote observation of the sea surface and atmosphere The oceanic skin effect

Abstract

A comparison is made between the measurements of sea surface temperature (SST), obtained using an infrared radiometer mounted on a vessel of the British Antarctic Survey, and from a conventional Meteorological Office rubber bucket with mercury thermometer. These measurements are used to investigate the size and variability of the oceanic skin effect from the tropical Atlantic to the waters of Antarctica. The implication of the skin effect on the validation of satellite-borne infrared sensors of the sea surface temperature is also investigated. In terms of the overall average for the complete Atlantic Ocean data set, the skin of the sea is about 0-30 deg K cooler than the bulk at about 10cm below the surface. There are only a few cases of the skin being warmer than the bulk temperature, on the other hand there are some occasions when the skin can be of the order of 1 -0 deg K cooler than the bulk. There is a suggestion that the skin effect at night-time is smaller than it is during the day-time, and a possible explanation of this is given in terms of the complication of the diurnal thermocline. The skin effect can be an important source of error in the validation of space-borne sensors of SST, particularly with the requirement for high accuracy of SST measurement for climate studies. In terms of the retrieval of SST from satellite infrared sensors the skin effect is only one of several physical effects that create uncertainty in the value of SST.     

Study of upper ocean parameters during passage of tropical cyclones over Indian seas

The primary energy supply for tropical cyclones is the upward latent heat fluxes that are directly related to Sea Surface Temperatures (SST). The strong winds induce a negative SST anomaly in the tropical cyclone wake. This is usually referred to as the ‘cold wake’. Many studies have suggested that the cold wake results in a significant reduction of upward latent heat fluxes that supply energy to the tropical cyclone, and hence provides a negative feedback on its intensity. The cold-wake feedback on the intensity of tropical cyclones is a strong motivation to understand the oceanic response to tropical cyclones. A recent study of re-examining the mechanisms controlling the cold wake has shown the importance of vertical Ekman pumping. Under the core of tropical cyclones (typically over a disk of 100 km radius), vertical pumping is responsible for a cooling of the entire water column, while surface heat fluxes and vertical mixing both contribute to the surface cooling during the cyclone passage. Farther away from the cyclone core, vertical mixing generally overwhelms the effect of vertical pumping, and also the effect of heat fluxes in the case of strong tropical cyclones. The study examines the Ekman pumping during the passage of few cyclonic storms in the Arabian Sea (AS) and Bay of Bengal (BOB) during last decade using different datasets such as Satellite (QuikScat) and reanalysis (ERA-Interim) data and calls up the value for satellite deliverables. Surface currents and subsurface temperature structure is examined further and for different Ekman pumping velocity (EPV), variable subsurface response is illustrated. The changes in ocean surface temperature, sea level and heat content obtained from the remote sensing data products, in the wake of cyclone are also reported and thus the usefulness of satellite products to study the coupled tropical system is demonstrated.     

卫星微波遥感受水成物影响及其敏感度分析研究

对卫星微波遥感水成物辐射效应的理解在云参数反演以及数值预报中使用受云和降水影响卫星资料等诸多应用中都是十分重要的。使用快速辐射传输模式CRTM,通过中尺度数值模式WRF预报输出的水成物信息,分析了云水、雨水、冰、雪和霰5类水成物对卫星微波遥感的影响及水成物辐射效应给卫星微波观测计算带来的误差特征,设计敏感性试验研究了卫星微波遥感对水成物含量、有效粒子半径和垂直分布层次的敏感度。结果表明:卫星微波遥感在多个探测频率上受水成物的影响较大,云水和雨水的影响主要以增温为主,雨水的影响幅度要大于云水,在影响最大的AMSUA 2通道,云水和雨水的增温分别可达到8 K和17 K左右。冰、雪和霰散射效应对卫星微波遥感的影响则主要以降温为主;相比之下,霰的影响量级最大,雪次之,两种水成物对微波遥感影响最大的通道为AMUSB的2通道,可达到-18 K和-9 K左右,冰的作用微乎其微。卫星微波遥感探测通道对水成物含量的敏感与受水成物辐射效应影响对应一致。卫星微波遥感不受云水和冰水粒子有效半径变化的影响,对雨、雪和霰大降水粒子的有效粒子半径较为敏感。同时,敏感性和影响程度随探测频率的不同呈现出影响的复杂性。此外,卫星微波探测对水成物垂直分布层次的敏感性表现为对水成物敏感探测通道的变化,其中AMSUB 3~5通道对高层水物质,包括冰、雪和霰垂直廓线的变化最为敏感。     

Relationship between SST gradients and upwelling off Peru and Chile: model/satellite data analysis

The upwelling system off Peru/Chile is characterized by significant mesoscale to submesoscale surface variability that results from the instability of the coastal currents (due to the strong vertical and horizontal shears) and to the marked density cross-shore gradients (associated with the mean upwelling). Here we investigate to what extent upwelling intensity can be inferred from sea surface temperature (SST) derived from remote sensing. As a first step in validation, a comparison between SST observations is performed, which indicates that the 1 km gridded multi-scale ultra-high-resolution (MUR) SST data set is defining a zone of maximum SST gradients closer to shore than the low-resolution National Centers for Environmental Information 0.25° resolution data set. Two model versions, at nominal resolutions of 2 km and 4 km, of the Massachusetts Institute of Technology general circulation model are analysed. A high-resolution version at 2 km is examined for the period 13 September 2011–23 January 2013, while a 4 km version is examined for 6 March 2011–22 April 2013. MUR shows maxima SST gradients in the range of 0.03 ± 0.02 K km^?1 while the model showed higher gradients around 0.05 ± 0.02 K km^?1. Based on coherence spectra, the relationship between upwelling rate (as inferred from the vertical velocity) and SST gradient is documented in the model from intraseasonal to annual timescales. It suggests that changes in SST gradient magnitudes are related to changes in the intensity of coastal upwelling off Peru and Chile. Such a relationship between SST gradients and vertical velocity would allow for the use of satellite-derived SSTs to monitor the intensity of coastal upwelling from the intraseasonal to annual timescales.