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22 GHz和85 GHz的影响较为明显,对其它通道影响较小。对于小于85 GHz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85 GHz,相对湿度的影响最明显,其次是微波亮温,最后是地表温度。     

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。     

新型地基大气廓线微波探测仪及其参数反演

介绍的新型地基大气廓线微波探测仪样机,对进口并普遍使用的MP3000地基大气探测仪进行了结构创新,采用温度廓线测量的V波段（50~59 GHz）和湿度廓线测量的K波段（22~31 GHz）,每个频段采用7个通道。与MP3000不同,采用独立反射面,而非共享反射面的形式。接收机采用直接检波方式,而不采用超外差检波方式,避免了接收机下变频部分,结构上更简单,空间分辨率更高,维修更容易。这种新型设备具有体积小、质量轻、空间分辨率高和非线性误差低的特点。利用辐射传输方程和已知探空资料相关数据,计算各通道加权函数,计算各通道亮温,采用神经网络算法进行大气温度廓线的反演,结果证明,此样机在结构改进的基础上完全满足地基大气廓线仪结构简单,对时间分辨率和空间分辨率,温度廓线反演结果达到预期要求。     

多目标遗传算法反演对流层大气温湿廓线研究

针对地基微波辐射计反演对流层大气温湿廓线完全依赖于历史数据的问题,设计了一种新的反演算法和流程。在对历史探空数据的统计分析基础上,得到各层大气温湿参数经验范围。从经验库中随机构造一条大气温湿廓线作为初值,基于大气微波辐射传输模式MonoRTM模型,计算模拟亮温。比较计算值与实测亮温的接近程度,通过更新初值,不断迭代计算,逐步筛选出可行解,并通过设定大气温湿垂直递减率等约束条件,从可行解中约束出帕累托前沿。采用皮尔逊系数加权平均的方法,从帕累托前沿中得到全局满意解。研究结果表明,新建立的基于多目标遗传算法的不完全依赖于历史数据的对流层大气温湿廓线反演模型,有较好的自适应能力和鲁棒性,反演精度高。该模型可以满足微波辐射计在历史气象资料积累匮乏地区的使用需求。     

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。     

基于非表面参考技术的机载双频降水反演结果分析

双频降水测量雷达是我国计划发射的风云三号降水测量卫星上的主载荷。双频测量能够较好地估计粒子谱分布参数,提高降雨率定量反演的精度,对双频降水反演算法的研究是降水产品业务化的基础。首先介绍基于非SRT的双频降水反演算法的主要原理,随后采用模拟数据对反演算法的精度进行检验,并选取机载雷达外场校飞试验中的实测数据,分析了机载雷达降雨探测的合理性。结果表明:双频反演的DSD参数基本合理,能够准确地反映出层云降水中亮带的峰值信息,并且和在轨同步观测的星载降水测量雷达PR的探测结果相近。此外,还探讨了随机选取的机载反射率因子廓线的双频反演结果以及可能引起反演误差的原因,结果发现相态转换的高度以及水的体积比可能对4 km附近及其以上的区域有一定的影响,对4 km以下的部分则影响不大。同时温度对反演结果的影响主要集中在3.5 km附近,在其他高度层,温度的影响基本可以忽略。同时降雨率的精度还受到雷达系统误差的制约。总体而言,机载双频降水反演结果具有一定的精度,基本符合当时机载外场试验的实际天气状况,从而验证了机载雷达降雨探测的合理性。     

基于分组分裂窗算法的MTSAT-1R地表温度反演

以黑河流域上游和中游为研究区,针对MTSAT-1R卫星数据,运用MODTRAN 4.0及晴空状态下的TIGR大气廓线数据,发展了根据地表比辐射率、大气水汽含量、传感器观测角度分组模拟的分裂窗算法,进行地表温度反演。分析了传感器噪声、地表比辐射率和大气水汽含量3个参数对该算法的影响,并结合模拟数据、地面观测数据及MODIS地表温度产品,对反演结果进行分析评价。结果表明:当传感器垂直观测或大气水汽含量小于2.5g/cm2时,反演精度在1K以内;反演结果与地面观测数据对比差异较小,在阿柔站RMSE为3.7 K(日)/1.4 K(夜),在盈科站RMSE为2.4K(日)/2.0K(夜);与MODIS地表温度产品比较,空间分布呈现出一致性。总之,分组分裂窗算法能较好地用于MTSAT-1R卫星数据进行地表温度反演。     

陆地资源卫星数据地表温度反演

针对目前陆地资源卫星(Landsat-8)地表温度反演过程中,地表比辐射率估计和敏感度分析中存在的不足,对这两方面进行改进,提出了一种基于Landsat-8数据的地表温度反演算法。该文主要从劈窗算法的推导、参数的估计、敏感度分析等方面进行研究。对于大气透过率的计算,首先用与其有相邻过境时间的MODIS数据反演大气水汽含量,然后通过中分辨率的大气传输模型(Moderate Resolution Atmospheric Transmission,MODTRAN)模拟大气水汽含量与透过率的关系,最后得到大气透过率。对于发射率的计算,通过分类和ASTER提供的光谱库获得。将大气辐射传输方程模拟的地表温度与此劈窗算法反演的地表温度做比较,结果表明平均精度达到0.82K。最后研究了大气水汽含量对地表温度的影响。结果显示,当大气水汽含量误差为0.1g/cm2,其对温度反演精度的影响最大不超过0.3K;当大气水汽含量的反演误差较大的时候,其对温度反演精度的影响较大。     

MODIS数据地表温度反演劈窗算法比较

针对MODIS数据,分析比较了QIN和Wan-Dozier两种劈窗算法地表温度(LST)反演精度和误差分布。首先利用辐射传输模型MODTRAN4.0,结合TIGR大气廓线数据,评价两种算法绝对精度,然后基于误差传递理论分析评价二者的总精度,最后对两种算法的LST反演结果进行比较。研究表明针对所有廓线数据,两种算法绝对精度相差不大,但Wan-Dozier算法绝对精度受地表温度和水汽含量变化的影响程度要大于QIN算法;两种算法总精度相差不大,且主要误差源均为算法绝对精度和地表比辐射率精度,QIN算法反演结果对地表比辐射率的敏感性要略高于Wan-Dozier算法;两种算法得到研究区LST分布情况基本一致,均可表现空间LST分布差异,其中水体和裸土的LST反演结果差异较大,城镇和植被平均温度差异在0.5 K以内。     

AMSR-E亮温数据与MODIS陆表分类产品结合反演全球陆表温度

AMSR-E被动微波传感器获取的亮温数据与MODIS陆表分类产品(MOD12)相结合,将全球陆表分为16类,并假设每种类型的地表在各个被动微波通道具有较一致的发射率,在此基础上针对每种陆表类型分别建立了陆表温度反演算法。在算法的建立过程中,为了避免混合像元以及冻土、积雪发射率不确定性带来的影响,仅对单一地表类型占90%以上以及MODIS陆表温度产品高于273K的被动微波像元进行回归。同时,考虑到降雨对回归结果的影响,在数据选择中加入了降雨判识,在被动微波亮温数据中除去了降雨像元。利用上述算法,用2004年1～10月的全球部分地区AMSR-E数据在MODIS陆表分类产品的基础上对每种地表类型分别进行了陆表温度反演,并与MODIS陆表温度产品进行对比,结果显示相关性较好,均方根误差为2～4 K。     

人工神经网络反演算法反演北京地区湿度廓线

微波湿度计（MWHS）是风云三号卫星的主要有效载荷之一,其频率为150GHz（双极化）和183.3lGHz（三通道）,分别用于探测大气窗区和水汽廓线。采用垂直于飞行方向的交轨扫描方式,科学目标是探测大气湿度的垂直分布。本文简要介绍微波大气湿度探测的基本原理,阐述了湿度廓线反演的各种方法,着重运用人工神经网络算法,反演北京地区的大气湿度的垂直分布。结果表明,运用风云三号微波湿度计数据,大气湿度垂直分布反演值与已知的探空数据相比,虽有误差,但在可接受范围之内,反演结果可应用于气象,通信等领域,并具有重要应用价值。     

Satellite-derived low-level atmospheric water vapour content from synergy of AVHRR with HIRS

Abstract

The infrared sensor systems AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High resolution Infrared Radiation Sounder) on board the NOAA-7 satellite are studied theoretically by means of radiative transfer calculations to enable the development of new retrieval techniques for atmospheric water vapour profiles. Simulations of radiometer signals have been performed for a large set of atmospheres from the middle and tropical latitudes. Subsequent development of a physical-statistical retrieval method demonstrates the usefulness of a coupling of both radiometers for water vapour retrievals in a single HIRS field of view. Total column amounts as well as the amounts in thick layers (150-200 hPa (thick) in the lower troposphere can be derived with an accuracy of 5-15 per cent and 15-25 per cent respectively. The amounts in thinner layers (50hPa) can be estimated with accuracies between 20 and 30 per cent. The AVHRR split window channels are a powerful tool in the water vapour retrievals. The technique developed benefits from the simultaneous retrieval of temperature profiles and surface temperatures. Accounting for scan-angle dependencies explicitly leads to improved retrievals. The synergy of AVHRR with HIRS increases the number of retrievals in partially cloudy fields of view compared with HIRS retrievals alone. A case study demonstrates the capability of the method to resolve water vapour structures with a high spatial resolution and its value in areas where conventional measurements from radiosonde ascents are sparse.     

Simulation of atmospheric profile retrieval from hyperspectral infrared data under cloudy conditions

In this paper, simulated space-based high spectral resolution AIRS (Atmospheric Infrared Sounder) infrared radiances with different cloud top heights and effective cloud fractions are used to demonstrate measurement sensitivity and atmospheric profile retrieval performance. Simulated cloudy retrievals of atmospheric temperature and moisture derived from the statistical eigenvector regression algorithm are analysed with different effective cloud fractions and different cloud heights. The results show that knowledge of cloud height is critical to sounding retrieval performance and the root mean square error of retrieved temperature and the mixed ratio of water vapour below the cloud top increases with effective cloud fraction. When there is 50 hPa error in the cloud height the retrieval accuracy of temperature and humidity decrease, compared with when the cloud height is known perfectly; the temperature retrieval is more sensitive to cloud height error than humidity retrieval. Collocated cloudy AIRS and the associated clear MODIS (Moderate Resolution Imaging Spectroradiometer) infrared observations within the AIRS field of view (FOV) are also used to demonstrate profile retrieval improvement below the cloud layer. It is demonstrated that using collocated clear MODIS multispectral imager data along with AIRS high spectral resolution infrared radiances can greatly improve the single FOV cloudy retrieval even under opaque cloudy conditions.     

Validation of INSAT-3D temperature and moisture sounding retrievals using matched radiosonde measurements

An evaluation of temperature and moisture profiles retrieved from a geostationary Indian National Satellite (INSAT-3D) sounder, launched in 2013, is performed against collocated radiosonde (RAOB) observation measurements of more than 1 year. This evaluation is carried out in terms of bias and root mean square error (RMSE) in temperature and relative humidity. An error analysis is carried out for different surface types, different seasons and day/night cases. The key finding of this study is that INSAT-3D retrievals show good agreement with RAOB measurements with overall RMSE accuracies ~1–2 K and 10–20%, respectively, for temperature and relative humidity in the troposphere. However, the temperature and relative humidity retrievals over land or in dry atmosphere show degraded performance. This degradation might be related to uncertainty in surface emissivity over land and possibility of undetected cloud in dry atmospheric condition. In addition to it, a similar analysis is carried out to assess the relative performance of INSAT-3D-retrieved profiles, Atmospheric Infrared Sounder (AIRS) L2 Standard Physical Retrieval (AIRS-only) version 6 (AIRS2RET) profiles and European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim) reanalysis with respect to spatially and temporally collocated RAOBs. In this analysis, temperature and moisture profiles from RAOBs serve as reference measurements and all retrievals and ERA-interim are compared with RAOBs. AIRS and INSAT-3D temperature retrievals gave comparable accuracies in upper and lower troposphere where as the quality degrades in middle troposphere resulting in larger errors. This may be due to improper bias correction coefficients used for brightness temperature of clear sky pixels before physical retrievals. In case of relative humidity, INSAT-3D profiles have comparable accuracies as AIRS in troposphere.     

Comparison of different techniques in atmospheric temperature-humidity sensing from space

Numerical closed-loop experiments on retrieving atmospheric temperature and humidity profiles by high-resolution measurements of the outgoing thermal infrared (IR) radiation using a Russian Fourier spectrometer (IRFS-2) were performed. Three techniques were used: multiple linear regression (MLR), the iterative physical-mathematical approach (IPMA), and artificial neural networks (ANNs). The MLR technique gives significant root mean square (RMS) errors in the retrieval of the temperature profile, especially in the troposphere region; these errors may be as great as 2–3 K. The ANN and IPMA techniques are considerably more accurate, giving approximately equal RMS errors of 1.0–1.5 K at altitudes of 2–30 km. For all interpretation techniques, a growth of errors of retrieval of temperature in the lower troposphere is observed and is especially substantial (up to 3 K for the near-surface temperature) in thermal sensing over land. The systematic errors of temperature retrieval for the ANN technique are practically zero, and for the other two techniques, they do not exceed 0.4 K. The differences in thermal sensing of the atmosphere over water and land manifest themselves in the appearance of an additional five determined coefficients of expansion of the spectral dependence of the IR emissivity of land in principal components. This leads to increased errors on thermal sensing in the lower troposphere, up to ~0.5 K for all interpretation techniques. The information content of the IRFS-2 device measurements with regard to the atmospheric humidity profile is relatively small because of the values of the errors of measurements of the outgoing radiation in the shortwave range, and in particular, in the water vapour absorption band 6.3 µm. The ANN technique makes it possible to determine relative humidity in the troposphere with RMS errors of 10–15%. In the case of observations over water, the mean errors of the ANN technique are practically equal to zero, and for the MLR and IPMA techniques, they are of an approximately equal order of magnitude, namely 2–4% of relative humidity. The IPMA and MLR techniques give RMS humidity errors of 15–20% and up to 40%, respectively.     

高光谱大气红外探测器通道选择方法及试验研究

考虑到高光谱大气红外探测器通道之间的相关性、变分同化的时效性等,需要进行通道选择。利用主成分-逐步回归法进行AIRS通道选择研究。由于短波CO2通道易受太阳光影响,分白天和夜晚进行。具体执行过程中,首先进行通道预处理,然后分别对温度和湿度雅可比矩阵进行主成分分析,并采用逐步回归法找出对前几个主成分影响较大的通道得到入选的通道子集。进而根据经验和实际观测资料,为了达到全局最优并兼顾局部,基于分区的思想,采用主成分-双区逐步回归法进行通道选择。结果表明:①利用AIRS进行反演时,合理选择通道是非常必要的;②主成分-双区逐步回归法得到的通道组合进行温度、湿度反演的误差整体比基于信息熵分步迭代小。〖JP〗     

Single frequency processing of atmospheric radio occultations

Tracking of the radio signals broadcast by the Global Positioning System (GPS) satellites as they are occulted from a GPS receiver by the Earth's atmosphere can provide high resolution vertical profiles of atmospheric refractivity, temperature and water vapour. Most implementations of this radio occultation technique use two GPS frequencies to correct for ionospheric effects. However, during most soundings, one of the frequencies is degraded by the introduction of the so-called Anti-Spoofing (AS) encryption mode. A retrieval method is discussed in this work for periods when only one of the two frequency signals has good quality. This method uses only the frequency with higher signal-to-noise ratio. We illustrate the quality of the atmospheric profiles obtained from such single frequency retrievals using GPS/MET data from the periods where the AS was turned off and the two frequencies were available. The results enable us to ensure the quality of a climate record of thousands of radio occultations collected by GPS/MET during the period with AS encryption, and the data processing of future missions with similar constraints, like IOX, can be performed.     

Derivation and Comparison of Water Vapor between Infrared Channels and Near Infrared Channels from FY\|3

Atmospheric water vapor content has important significance for radiometric correction of satellite image,understanding of atmospheric micro\|physical process,precipitation prediction and so on.We will retrievie atmospheric column water vapor based on Moderate Resolution Imaging Spectroradiometer (MERSI)near infrared channels and Visible and Infrared Radiometer (VIRR)thermal infrared channels datas of FY\|3A,respectively.Comparing the retrieval results of MERSI,VIRR and the observations of sounding ground stations respectively,we find :① the observed correlation between retrieval results of MERSI and observations is 0.763,while retrieval results of VIRR has poor correlations with observations,which is0.169.What’s more,The retrieval accuracy of MERSI (1.108 g/cm2)is higher than that of VIRR (1.894 g/cm2);②The average atmospheric column water vapor with three channels of MERSI has higher retrieval accuracy than channel 17th(1.133 g/cm2),18th(1.424 g/cm2),19th(1.827 g/cm2).The main reason is that three channels have different sensitivities of water vapor,and utilizing three channels to retrieve atmospheric column water vapor content can reach the effect of perfection.