大气温湿廓线反演问题的研究

介绍了反演大气温湿廓线的主要传感器特性,阐述了ATOVS、MODIS和AIRS这3个卫星传感器的仪器特征及其相应的大气温湿廓线反演原理和方法,对其利弊进行初步分析,总结了大气温湿廓线反演问题的发展趋势.     

红外高光谱资料反演有云时大气温湿廓线的模拟研究

在模拟星载红外高光谱辐射观测值对云高和有效云量的敏感性基础上展开了有云时大气温湿廓线反演的模拟研究,用特征向量统计反演法反演大气温湿廓线时进行云顶高度分类在一定程度上可提高反演精度,但在云顶以下高度反演误差仍然较大.在AIRS像元中加入匹配的晴空MODIS红外观测值,可以提高云顶以下高度的反演精度,云顶所在高度越高大气参数反演精度提高越大,尤其足温度反演精度,有云时模拟的均方根误差在整层大气中几乎小于2K.     

FY-3C无线电掩星折射率廓线的反演及验证

2013年,中国发射了首颗进行全球导航卫星系统(global navigation satellite system,GNSS)无线电掩星观测的气象卫星FY-3C,其掩星数据产品已由国家卫星气象中心(national satellite meteorological center,NSMC)发布。基于FY-3C附加相位数据,通过几何光学反演和全谱反演相结合的方法自主反演获取大气折射率廓线,并利用NSMC提供的折射率产品和欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts, ECMWF)的气候再分析数据集(ECMWF reanalysis-interim,ERA-Interim)对反演结果进行验证。2017年全年FY-3C掩星折射率自主反演的成功率为82%,与NSMC 83.5%的反演成功率基本一致。以ERA-Interim再分析资料为参考,自主反演折射率相对偏差绝对值在25 km以下,小于1.5%,略优于NSMC产品,但偏差标准差比NSMC产品略大,达到了3.6%。自主反演和NSMC的折射率廓线在高纬地区的相对偏差...     

FY-3A星MWHS反演中纬度和热带大气水汽

风云三号A星(FY-3A)搭载的微波湿度(MWHS)计采用双边带接收机体制,选择主要受水汽影响的(183.31±1) GHz,(183.31±3) GHz,(183.31±7) GHz和窗区150 GHz作为通道频率。本文首先分析了观测亮温值与利用辐射传输方程仿真的亮温值之间的关系,二者相比具有较好的一致性。其次利用神经网络方法反演大气相对湿度,并与线性回归方法进行对比,本文选用的区域内,神经网络方法优于线性回归法。最后,利用本文创建的神经网络模型与正在业务使用的AMSU-B反演模型进行反演均方差和稳定度对比,结果表明,本文创建的神经网络模型在所选区域,大气相对湿度反演精度与AMSU-B神经网络模型相当(反演均方差为15%-25%);水汽密度反演均方差除地面未知因素影响外,与探空观测相比,整体均方差小于1 g/m³;不论在中纬度地区还是热带地区,都能较好地反演大气湿度的垂直分布廓线。同时,本文初次尝试在神经网络反演湿度廓线中引入墨西哥帽小波函数,结果表明,运用墨西哥帽小波函数在保证反演性能的同时,能有效减小迭代时间,避免陷入局部迭代。     

超光谱热红外数据通道选择方法在O3和CH4廓线反演中的应用

与高光谱热红外数据相比,超光谱热红外数据中包含了臭氧(O₃)和甲烷(CH₄)在大气垂直剖面上更多的状态信息,为提升O₃和CH₄廓线的反演精度提供了可能。然而,超光谱热红外数据通道之间的间隔较窄,这在给数据引入一些特有可反演信息的同时还引入了大量的相似信息,这些特征均无法被现有的基于高光谱热红外数据的通道选择方法识别。为了保证超光谱热红外数据反演O₃和CH₄廓线的效率和精度,我们提出了一种基于大气灵敏度和雅可比剖面的通道优选方法(OWSP法)。该方法首先通过分析通道对不同气体的灵敏度情况,优选出受其他气体干扰较小的通道为初选通道;其次,深度分析通道雅可比特征后提出了优化雅可比矩阵的策略,具体为将通道雅可比量化为表征通道信息容量的因素,并采用迭代的方法获取最终的通道选择结果。本文将OWSP方法应用在阿拉善、北京—天津、长江三角洲和珠江三角洲4个典型地区的冬夏季大气条件下,与常用的最佳灵敏度法(OSP法)相比,OWSP方法所选的通道集合中冗余信息少,同时也可以识...     

利用走航式数据对南大洋大气CO2廓线遥感反演

利用中国第24次南极考察期间获取的南大洋上空走航式大气CO₂数据和大气红外探测器(AIRS)探测的辐射率, 进行基于纬度分类下的统计回归, 其结果作为物理反演的初始猜测场。通过逐线积分辐射传输模式, 利用AMSU大气温度廓线和AIRS中13个通道的辐射测值反演南大洋上空的大气CO₂浓度廓线, 与WDCGG提供的固定站点下的大气CO₂浓度进行比较, 反演精度随纬度的变化而变化, 从低纬到高纬相对误差分别为0.31%、1.17%、2.63%。与同期国外卫星产品CO₂/AIRS比较, 相对误差为1.11%、1.07%。     

风云三号 MWTS/MWHS 大气温度与水汽廓线反演 ——2008 年凤凰台风个例试验

本文结合中国国家标准大气(GB l920-80)与1976 年美国标准大气, 利用MPM (Millimeter Propagation Model, 毫米波传播模型)、ROS(Rosenkranz)模型和本文提出的改进混合模型(MIX, Mixed)计算大气吸收系数。采用 西北太平洋地区中国与日本16 个无线电高空探测仪836 组大气实测数据(海拔高度、气压、大气温度和湿度), 通 过大气辐射传输模型, 按MWTS/MWHS 的工作参数(中心频率、带宽和波段数目), 模拟大气辐射亮度温度, 用以验 证F     

利用走航式数据对南大洋大气CO2廓线遥感反演

利用中国第24次南极考察期间获取的南大洋上空走航式大气CO2数据和大气红外探测器(AIRS)探测的辐射率,进行基于纬度分类下的统计回归,其结果作为物理反演的初始猜测场。通过逐线积分辐射传输模式,利用AMSU大气温度廓线和AIRS中13个通道的辐射测值反演南大洋上空的大气CO2浓度廓线,与WDCGG提供的固定站点下的大气CO2浓度进行比较,反演精度随纬度的变化而变化,从低纬到高纬相对误差分别为0.31%、1.17%、2.63%。与同期国外卫星产品CO2/AIRS比较,相对误差为1.11%、1.07%。     

近地表大气逆温条件下的地表温度遥感反演与验证

为了减少近地表大气逆温对地表温度遥感反演精度的影响,提出在晴空的地表温度"通用劈窗算法"模型中增加一个温度改正项来实现。在建立该误差改正项时,利用正常条件下的通用劈窗算法系数和具有不同逆温强度的逆温廓线,并结合大气辐射传输模型MODTRAN计算,得到近地表大气逆温条件下的地表温度反演误差,并在分析了该误差值与相应的逆温强度的关系后,发现该温度改正项可以表示为近地表大气逆温强度的二次项函数。为了进一步提高地表温度的反演精度,将地表温度和大气水汽含量进行分组,分别针对每个分组来确定温度改正项方程的系数。模拟结果表明,在逆温强度为1.7 K/100m时,该温度改正项可以使地表温度的反演精度提高0.44 K。利用内蒙古海拉尔试验站的实测数据对地表温度反演结果进行了验证,在近地表大气存在逆温的条件下,该方法能提高地表温度的遥感反演精度0.47K。但是,由于本文提出的方法需要已知大气温度廓线来计算大气逆温强度,因此在实际应用中该方法受到了一定的限制。     

Retrieval of land surface temperature from the Kalpana-1 VHRR data using a single-channel algorithm and its validation over western India

Indian geostationary satellite Kalpana-1 (K1) offers a potential to capture the diurnal cycle of land surface temperature (LST) through thermal infrared channel (10.5–12.5 μm) observations of the Very High Resolution Radiometer (VHRR) sensor. A study was carried out to retrieve LST by adapting a generalized single-channel (SC) algorithm (Jiménez-Muñoz and Sobrino, 2003) for the VHRR sensor over India. The basis of SC algorithm depends on the concept of Atmospheric Functions (AFs) that are dependent on transmissivity, upwelling and downwelling radiances of the atmosphere. In the present study AFs were computed for the VHRR sensor through the MODTRAN simulations based upon varying atmospheric and surface inputs. The AFs were fitted with the atmospheric columnar water vapour content and a set of coefficients was derived for LST retrieval. The K1-LST derived with the SC algorithm was validated with (a) in situ measurements at two sites located in western parts of India and (b) the MODIS LST products. Comparison of K1-LST with the in situ measurements demonstrated that SC algorithm was successful in capturing the prominent diurnal variations of 283–332 K in the LST at desert and agriculture experimental sites with a rmse of 1.6 K and 2.7 K, respectively. Inter comparison of K1-LST and MODIS LST showed a reasonable agreement between these two retrievals up to LST of 300 K, however a cold bias up to 7.9 K was observed in MODIS LST for higher LST values (310–330 K) over the hot desert region.     

FY-3C/VIRR中红外图像太阳光污染订正

风云三号C星(FY-3C)上搭载的可见光红外扫描辐射计VIRR (Visible and Infra-Red Radiometer)是继承风云一号卫星光学成像仪器,它在高纬度昼夜交替区域附近由于地平线附近太阳光照射,导致仪器扫描镜和其他部件产生杂散光,导致对地观测图像被污染,尤其VIRR中红外第3通道(3.7 μm)图...     

Retrieval of land surface temperature (LST) from landsat TM6 and TIRS data by single channel radiative transfer algorithm using satellite and ground-based inputs

The present study proposes land surface temperature (LST) retrieval from satellite-based thermal IR data by single channel radiative transfer algorithm using atmospheric correction parameters derived from satellite-based and in-situ data and land surface emissivity (LSE) derived by a hybrid LSE model. For example, atmospheric transmittance (τ) was derived from Terra MODIS spectral radiance in atmospheric window and absorption bands, whereas the atmospheric path radiance and sky radiance were estimated using satellite- and ground-based in-situ solar radiation, geographic location and observation conditions. The hybrid LSE model which is coupled with ground-based emissivity measurements is more versatile than the previous LSE models and yields improved emissivity values by knowledge-based approach. It uses NDVI-based and NDVI Threshold method (NDVI^THM) based algorithms and field-measured emissivity values. The model is applicable for dense vegetation cover, mixed vegetation cover, bare earth including coal mining related land surface classes. The study was conducted in a coalfield of India badly affected by coal fire for decades. In a coal fire affected coalfield, LST would provide precise temperature difference between thermally anomalous coal fire pixels and background pixels to facilitate coal fire detection and monitoring. The derived LST products of the present study were compared with radiant temperature images across some of the prominent coal fire locations in the study area by graphical means and by some standard mathematical dispersion coefficients such as coefficient of variation, coefficient of quartile deviation, coefficient of quartile deviation for 3rd quartile vs. maximum temperature, coefficient of mean deviation (about median) indicating significant increase in the temperature difference among the pixels. The average temperature slope between adjacent pixels, which increases the potential of coal fire pixel detection from background pixels, is significantly larger in the derived LST products than the corresponding radiant temperature images.