Latitudinal and Scan-dependent Biases of Microwave Humidity Sounder Measurements and Their Dependences on Cloud Ice Water Path

The relationship between differences in microwave humidity sounder(MHS)–channel biases which represent measured brightness temperatures and model-simulated brightness temperatures, and cloud ice water path(IWP) as well as the influence of the cloud liquid water path(LWP) on the relationship is examined. Seven years(2011–17) of NOAA-18 MHS-derived measured brightness temperatures and IWP/LWP data generated by the NOAA Comprehensive Large Array-data Stewardship System Microwave Surface and Precipitation Products System are used. The Community Radiative Transfer Model, version2.2.4, is used to simulate model-simulated brightness temperatures using European Center for Medium-Range Weather Forecasts reanalysis data as background fields. Scan-angle deviations of the MHS window channel biases range from-1.7 K to1.0 K. The relationships between channels 2, 4, and 5 biases and scan angle are symmetrical about the nadir. The latitudedependent deviations of MHS window channel biases are positive and range from 0–7 K. For MHS non-window channels,the latitudinal deviations between measured brightness temperatures and model-simulated brightness temperatures are larger when the detection height is higher. No systematic warm or cold deviations are found in the global spatial distribution of difference between measured brightness temperatures and model-simulated brightness temperatures over oceans after removing scan-angle and latitudinal deviations. The corrected biases of five different MHS channels decrease differently with respect to the increase in IWP. This decrease is stronger when LWP values are higher.     

A solely radiance-based spectral angular distribution model and its application in deriving clear-sky spectral fluxes over tropical oceans

The radiation budget at the top of the atmosphere plays a critical role in climate research. Compared to the broadband flux, the spectrally resolved outgoing longwave radiation or flux(OLR), with rich atmospheric information in different bands,has obvious advantages in the evaluation of GCMs. Unlike methods that need auxiliary measurements and information, here we take atmospheric infrared sounder(AIRS) observations as an example to build a self-consistent algorithm by an angular distribution model(ADM), based solely on radiance observations, to estimate clear-sky spectrally resolved fluxes over tropical oceans. As the key step for such an ADM, scene type estimations are obtained from radiance and brightness temperature in selected AIRS channels. Then, broadband OLR as well as synthetic spectral fluxes are derived by the spectral ADM and validated using both synthetic spectra and CERES(Clouds and the Earth's Radiant Energy System) observations. In most situations, the mean OLR differences between the spectral ADM products and the CERES observations are within ±2 W m~(-2), which is less than 1% of the typical mean clear-sky OLR over tropical oceans. The whole algorithm described in this study can be easily extended to other similar hyperspectral radiance measurements.     

Distributions of Downwelling Radiance at 10 and 20 μm in the High Arctic

In the Arctic, most of the infrared (IR) energy emitted by the surface escapes to space in two atmospheric windows centred at 10 and 20?μm. As the Arctic warms and its water vapour burden increases, the 20?μm cooling-to-space window, in particular, is expected to become increasingly opaque (or “closed”), trapping more IR radiation, with implications for the Arctic’s radiative energy balance. Since 2006, the Canadian Network for the Detection of Atmospheric Change has measured downwelling IR radiation with Atmospheric Emitted Radiance Interferometers at the Polar Environment Atmospheric Research Laboratory at Eureka, Canada, providing measurements of the 10 and 20?μm windows in the High Arctic. In this work, measurements of the distribution of downwelling 10 and 20?µm brightness temperatures at Eureka are separated based on cloud cover, providing a comparison to an existing 10?µm climatology from the Southern Great Plains. The downwelling radiance at both 10 and 20?μm exhibits strong seasonal variability as a result of changes in cloud cover, temperature, and water vapour. Given the 20?µm window’s limited transparency, its ability to allow surface IR radiation to escape to space is found to be highly sensitive to changes in atmospheric water vapour and temperature. When separated by season, brightness temperatures in the 20?µm window are independent of cloud optical thickness in the summer, indicating that this window is opaque in the summer. This may have long-term consequences, particularly as warmer temperatures and increased water vapour “close” the 20?μm window for a prolonged period each year.     

Surface‐absorbed and top‐of‐atmosphere radiation fluxes for the Mackenzie River basin from satellite observations and a regional climate model and an evaluation of the model

Abstract

Both the earth‐reflected shortwave and outgoing longwave radiation (OLR) fluxes at the top of the atmosphere (TOA) as well as surface‐absorbed solar fluxes from Canadian Regional Climate Model (CRCM) simulations of the Mackenzie River Basin for the period March 2000 to September 2003 are compared with the radiation fluxes deduced from satellite observations. The differences between the model and satellite solar fluxes at the TOA and at the surface, which are used in this paper to evaluate the CRCM performance, have opposite biases under clear skies and overcast conditions, suggesting that the surface albedo is underestimated while cloud albedo is overestimated. The slightly larger differences between the model and satellite fluxes at the surface compared to those at the TOA indicate the existence of a small positive atmospheric absorption bias in the model. The persistent overestimation of TOA reflected solar fluxes and underestimation of the surface‐absorbed solar fluxes by the CRCM under all sky conditions are consistent with the overestimation of cloud fraction by the CRCM. This results in a larger shortwave cloud radiative forcing (CRF) both at the TOA and at the surface in the CRCM simulation. The OLR from the CRCM agrees well with the satellite observations except for persistent negative biases during the winter months under all sky conditions. Under clear skies, the OLR is slightly underestimated by the CRCM during the winter months and overestimated in the other months. Under overcast conditions the OLR is underestimated by the CRCM, suggesting an underestimation of cloud‐top temperature by the CRCM. There is an improvement in differences between model and satellite fluxes compared to previously reported results largely because of changes to the treatment of the surface in the model.     

Global precipitation estimates from satellite: Using difference fields of outgoing long‐wave radiation

Abstract

Global precipitation estimates using satellite data are derived using difference fields of outgoing long‐wave radiation (OLR). The difference fields consist of clear OLR minus cloudy OLR, which is a measure of long‐wave cloud radiative forcing at the top of the earth‐atmosphere system; and clear daytime OLR minus clear night‐time OLR, which is a measure of the diurnal variation of surface heating. All geophysical parameters used to compute OLR are derived from an analysis of the HIRS2/MSU sounding data. The derived global precipitation estimates show good agreement with collocated raingauge data over land. The correlation coefficient between the precipitation estimates derived using difference fields of OLR and raingauge data over land is about 0.65 for the FGGEyear. The correlation coefficient between precipitation estimates derived using difference fields of OLR and the GOES Precipitation Index (GPI) fraction is about 0.914 from 30°S to 30°N for July 1983, and between the precipitation estimates derived using difference fields of OLR and the difference field of atmospheric reflectance is about 0.86.

Using one set of coefficients, global precipitation fields are derived for each 10‐day period and each month of the FGGE year (from December 1978 to November 1979). These fields contain rich information on seasonal variations.     

Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

This study explores the structures of the correlations between infrared(IR)brightness temperatures(BTs)from the three water vapor channels of the Advanced Baseline Imager(ABI)onboard the GOES-16 satellite and the atmospheric state.Ensemble-based data assimilation techniques such as the ensemble Kalman filter(EnKF)rely on correlations to propagate innovations of BTs to increments of model state variables.Because the three water vapor channels are sensitive to moisture in different layers of the troposphere,the heights of the strongest correlations between these channels and moisture in clear-sky regions are closely related to the peaks of their respective weighting functions.In cloudy regions,the strongest correlations appear at the cloud tops of deep clouds,and ice hydrometeors generally have stronger correlations with BT than liquid hydrometeors.The magnitudes of the correlations decrease from the peak value in a column with both vertical and horizontal distance.Just how the correlations decrease depend on both the cloud scenes and the cloud structures,as well as the model variables.Horizontal correlations between BTs and moisture,as well as hydrometeors,in fully cloudy regions decrease to almost 0 at about 30 km.The horizontal correlations with atmospheric state variables in clear-sky regions are broader,maintaining non-zero values out to~100 km.The results in this study provide information on the proper choice of cut-off radii in horizontal and vertical localization schemes for the assimilation of BTs.They also provide insights on the most efficient and effective use of the different water vapor channels.     

A comparison of satellite-retrieved and simulated cloud coverage in the Baltic Sea area as part of the BALTIMOS project

A cloud-detection algorithm for METEOSAT first generation data has been developed. The algorithm utilizes solely infrared data from the METEOSAT thermal infrared window channel at around 11.5 μm. The developed algorithm estimates an assumed clear-sky brightness temperature from time series analysis on pixel bases. Land-/sea-depending dynamic thresholds are then utilized discriminating the infrared images in cloudy, undecided, and cloud free pixels. The cloud-detection algorithm has been validated against synoptic observations. The developed cloud-detection scheme has been applied to 10 years (1992–2001) of METEOSAT data, extracting cloud coverage statistics for the Baltic Sea catchment area. These have been compared to corresponding cloud coverage statistics derived from the BALTIMOS coupled model system. Building overall averaged values of the cloud coverage in the period from 1999 to 2001 gives results with very good agreement between simulation and observation: the total METEOSAT-derived cloud coverage amounts to 0.65 compared to 0.63 for BALTIMOS. In contrast, large discrepancies in the phase of the diurnal cycle of cloud coverage have been observed. A significant trend in total cloud amount was observed neither from the model nor from the satellite.     

An evaluation of the surface radiation budget over North America for a suite of regional climate models against surface station observations

Components of the surface radiation budget (SRB) [incoming shortwave radiation (ISR) and downwelling longwave radiation (DLR)] and cloud cover are assessed for three regional climate models (RCM) forced by analysed boundary conditions, over North America. We present a comparison of the mean seasonal and diurnal cycles of surface radiation between the three RCMs, and surface observations. This aids in identifying in what type of sky situation simulated surface radiation budget errors arise. We present results for total-sky conditions as well as overcast and clear-sky conditions separately. Through the analysis of normalised frequency distributions we show the impact of varying cloud cover on the simulated and observed surface radiation budget, from which we derive observed and model estimates of surface cloud radiative forcing. Surface observations are from the NOAA SURFRAD network. For all models DLR all-sky biases are significantly influenced by cloud-free radiation, cloud emissivity and cloud cover errors. Simulated cloud-free DLR exhibits a systematic negative bias during cold, dry conditions, probably due to a combination of omission of trace gas contributions to the DLR and a poor treatment of the water vapor continuum at low water vapor concentrations. Overall, models overestimate ISR all-sky in summer, which is primarily linked to an underestimate of cloud cover. Cloud-free ISR is relatively well simulated by all RCMs. We show that cloud cover and cloud-free ISR biases can often compensate to result in an accurate total-sky ISR, emphasizing the need to evaluate the individual components making up the total simulated SRB.     

Climatology of cloud and radiation fields in a numerical weather prediction model

Summary Satellite-derived datasets are used to verify the cloud cover and radiation field generated by a T62 (horizontal resolution) version of the operational global model at the National Meteorological Centre (NMC). An ensemble of five day forecasts for July 1985 is used, as well as 30 day climatological forecasts for July 1985, October 1985, January 1986, and April 1986.Monthly averages of radiation fields are compared with Earth Radiation Budget Experiment (ERBE) data. For the four months examined, clear-sky outgoing longwave radiation (clear-sky OLR) and absorbed shortwave radiation (clear-sky SW) tend to agree roughly with ERBE. Model global mean OLR, however, exceeds that of ERBE by 10 W m^–2.Comparison of effective cloud cover to corresponding fields cataloged by the International Satellite Cloud Climatology Project (ISCCP C1) reveals deficiencies in the amount of supersaturation cloudiness and the vertical distribution of convective clouds. Large inaccuracies in model radiation fields are closely related to deficiencies in the cloud parameterization. An inventory of model cloudiness, in comparison to satellite data, is conducted.With 18 Figures     

AN ERROR ANALYSIS ON THE SIMULATED DATA OF TOVS HIRS BY RTTOV5 MODEL*

The sounding data of meteorological satellites provide not only the real time weather information about the distribution of both cloud and rainfall,but also some others about the movement and state of atmosphere.They are important variables and parameters for NWP model used to simulate and predict atmospheric state.In order to introduce remote sensing information from satellites into NWP model,there is an efficient way of establishing an RT model by use of the atmosphere radiation sounding data of meteorological satellites to get the variables and parameters valuable to NWP model.In this paper,we set up profiles of air temperature and water vapor from the surface to upper (0.1 hPa) using the radiosounding data and the surface data from May to August 1998 atmosphere East Asia.A TOVS RT model (RTTOV5) is provided to compute the value of radiation value of HIRS channels in NOAA14.Then the radiation values of 19 HIRS channels are gotten.After matching these data computed by the RT model and the corresponding values coming from satellite sounding in time,the statistic distribution of bias between tile model output and the satellite sounding at each sounding channel can be gotten.At the same time.the distribution of RMS to every TOVS HIRS channel,the standard biases to different scanning angle to each channel are also obtained.     

AN ERROR ANALYSIS ON THE SIMULATED DATA OF TOVS HIRS BY RTTOV5 MODEL

The sounding data of meteorological satellites provide not only the real time weatherinformation about the distribution of both cloud and rainfall,but also some others about themovement and state of atmosphere.They are important variables and parameters for NWP modelused to simulate and predict atmospheric state.In order to introduce remote sensing informationfrom satellites into NWP model,there is an efficient way of establishing an RT model by use of theatmosphere radiation sounding data of meteorological satellites to get the variables and parametersvaluable to NWP model.In this paper,we set up profiles of air temperature and water vapor fromthe surface to upper (0.1 hPa) using the radiosounding data and the surface data from May toAugust 1998 atmosphere East Asia.A TOVS RT model (RTTOV5) is provided to compute thevalue of radiation value of HIRS channels in NOAA14.Then the radiation values of 19 HIRSchannels are gotten.After matching these data computed by the RT model and the correspondingvalues coming from satellite sounding in time,the statistic distribution of bias between tile modeloutput and the satellite sounding at each sounding channel can be gotten.At the same time.thedistribution of RMS to every TOVS HIRS channel,the standard biases to different scanning angleto each channel are also obtained.     

云参数对RTTOV5模式模拟误差的影响分析

该文根据1998年8月的业务TOVS反演的温度、水汽垂直廓线资料以及其它资料, 利用RTTOV5模式模拟NOAA14极轨气象卫星上相应红外探测 (HIRS) 通道的辐射亮温值, 将模拟值对比实测TOVS探测资料, 结果表明, 晴空模式模拟亮温与实测值的误差小于部分有云时的误差, 模拟误差受云的影响呈反相变化, 对水汽敏感的中低层探测通道在晴空时的误差小于部分有云情况; 通过对比白天和夜间短波窗区探测通道模拟误差, 分析了其受地面反射太阳光辐射的影响的大小及其原因所在; 并利用RTTOV5的伴随模式和Jacobine模式分析了模式模拟误差对初始场云参数的敏感性。该研究为TOVS/ATOVS探测资料在3DR或4DR变分同化中的直接应用奠定了基础。     

基于卫星亮温资料同化对2009年热带风暴“浪卡”的数值研究

本文利用三维变分同化系统（WRFDA）,设计了4个同化试验方案,将ATOVS卫星亮温资料直接同化到中尺度数值模式（WRF）中,研究同化ATOVS不同卫星亮温资料对2009年04号热带风暴“浪卡”数值模拟的影响。结果表明,直接同化卫星亮温资料能够改善初始场结构（大气流场、温度场）,尤其是对西太平洋反气旋系统,进而提高对热带气旋路径的模拟精度。同化不同类型的ATOVS卫星亮温资料对于热带气旋的移动路径有着不同程度的改善,其中以HIRS3和HIRS4资料同化对热带气旋移动路径改善效果最好。     

An Assessment of MJO and Tropical Waves Simulated by Different Versions of the GAMIL Model

Simulated outgoing longwave radiation (OLR) outputs by two versions of the grid-point atmospheric general circulation model (GAMIL) were analyzed to assess the influences of improvements in cloud microphysics and convective parameterization schemes on the simulation of the Madden-Julian oscillation (MJO) and other tropical waves. The wavenumber-frequency spectral analysis was applied to isolate dominant modes of convectively coupled equatorial waves, including the MJO, Kelvin, equatorial Rossby (ER), mixed Rossby-gravity (MRG), and inertio-gravity (IG) waves. The performances of different versions of the GAMIL model (version 1.0 (GAMIL1.0) and version 2.0 (GAMIL2.0)) were evaluated by comparing the power spectrum distributions of these waves among GAMIL1.0, GAMIL2.0, and observational data. GAMIL1.0 shows a weak MJO signal, with the maximum variability occurring separately at wavenumbers 1 and 4 rather than being concentrated on wavenumbers 1–3, suggesting that GAMIL1.0 could not effectively capture the intraseasonal variability. However, GAMIL2.0 is able to effectively reproduce both the symmetric and anti-symmetric waves, and the significant spectra of the MJO, Kelvin, and MRG waves are in agreement with observational data, indicating that the ability of GAMIL2.0 to simulate the MJO and other tropical waves is enhanced by improving the cloud microphysics and convective parameterization schemes and implying that such improvements are crucial to further improving this model’s performance.     

Understanding the Surface Temperature Cold Bias in CMIP5 AGCMs over the Tibetan Plateau

The temperature biases of 28 CMIP5 AGCMs are evaluated over the Tibetan Plateau(TP) for the period 1979–2005. The results demonstrate that the majority of CMIP5 models underestimate annual and seasonal mean surface 2-m air temperatures(T_(as)) over the TP. In addition, the ensemble of the 28 AGCMs and half of the individual models underestimate annual mean skin temperatures(T_s) over the TP. The cold biases are larger in T_(as) than in T_s, and are larger over the western TP. By decomposing the T_s bias using the surface energy budget equation, we investigate the contributions to the cold surface temperature bias on the TP from various factors, including the surface albedo-induced bias, surface cloud radiative forcing, clear-sky shortwave radiation, clear-sky downward longwave radiation, surface sensible heat flux, latent heat flux,and heat storage. The results show a suite of physically interlinked processes contributing to the cold surface temperature bias.Strong negative surface albedo-induced bias associated with excessive snow cover and the surface heat fluxes are highly anticorrelated, and the cancelling out of these two terms leads to a relatively weak contribution to the cold bias. Smaller surface turbulent fluxes lead to colder lower-tropospheric temperature and lower water vapor content, which in turn cause negative clear-sky downward longwave radiation and cold bias. The results suggest that improvements in the parameterization of the area of snow cover, as well as the boundary layer, and hence surface turbulent fluxes, may help to reduce the cold bias over the TP in the models.     

基于FY-3/IRAS利用非线性模式反演OLR

FY-3系列卫星星载IRAS仪器设有26个通道,其中20个通道用于探测地球大气在红外波段的热辐射,通道辐射率代表了地球大气系统在大气顶的向外辐射光谱信息,与总波段的射出长波辐射（OLR）通量相关性高。该文基于逐线辐射传输模式计算软件LBLRTM对全球2521条大气廓线的大气顶射出辐射率模拟数据,计算了每条廓线的OLR和FY-3B/IRAS,FY-3C/IRAS通道辐射率,用统计回归方法建立了利用IRAS的多通道辐射率计算OLR的非线性理论回归模式;应用模式和FY-3B/IRAS,FY-3C/IRAS的L1级数据,处理得到2016年4月1-30日的全球日平均、月平均OLR格点产品。与Aqua/CERES,Terra/CERES仪器宽波段观测OLR产品对比表明:对于水平分辨率为1°×1°的全球月平均OLR格点产品,均方根误差为2.22 W·m-2,相关系数为0.9982 W·m-2,平均偏差为-0.2 W·m-2,表明FY-3/IRAS仪器定标及反演模式均达到较高水平。文中还回顾了历史上不同气象卫星的多种OLR反演算法模式,并对不同模式精度进行了比较。     

RegCM4对中国东部区域气候模拟的辐射收支分析

利用卫星和再分析数据,评估了区域气候模式Reg CM4对中国东部地区辐射收支的基本模拟能力,重点关注地表净短波(SNS)、地表净长波(SNL)、大气顶净短波(TNS)、大气顶净长波(TNL)4个辐射分量。结果表明:1)短波辐射的误差值在夏季较大,而长波辐射的误差值在冬季较大。但各辐射分量模拟误差的空间分布在冬、夏季都有较好的一致性。2)对于地表辐射通量,SNS表现为正偏差(向下净短波偏多),在各分量中误差最大,区域平均误差值近50 W/m2;SNL表现为负偏差(向上净长波偏多);对于大气顶辐射通量,TNS和TNL分别表现为"北负南正"的误差分布和整体正偏差。3)利用空间相关和散点线性回归方法对4个辐射分量的模拟误差进行归因分析,发现在云量、地表反照率、地表温度三个直接影响因子中,云量模拟误差的贡献最大,中国东部地区云量模拟显著偏少。     

半透明云风矢量高度算法中云下背景辐射的估计

半透明云风矢量高度指定是卫星风矢量算法的重要部分,需要来自半透明云体的辐射和云下背景辐射两个变量。云下背景辐射发生在云层下面,未被卫星直接观测到,为了在半透明云风矢量高度指定算法中更精确地获得云下背景辐射,使用风矢量附近无云区的红外/水汽散点图,估计云下背景辐射。分析表明:在追踪区域里存在无云区的情况下,追踪区的最高红外亮温可代表红外通道的背景辐射;而水汽通道的背景辐射,却在红外亮温高值区段内水汽亮温相对较低区段。追踪区内找不到无云区时应扩大搜索范围,找到无云区后可估计云下背景辐射。在半透明云风矢量高度指定算法中使用云下背景辐射估计的改进算法前后,计算FY-2气象卫星进行风矢量,并将结果与欧洲中期天气预报中心（ECMWF）分析场进行对比表明,在半透明风矢量高度指定算法中使用云下背景辐射估计,FY-2气象卫星风矢量误差明显降低。     

基于亮温通道变率的FY-3C微波湿度计陆地云检测新方法

云检测是卫星资料同化的重要前处理步骤,无论是晴空资料同化还是有云资料同化,都需要准确地区分有云和晴空资料。由于陆地地表发射率的多变性和微波能穿透部分云类的特点,微波湿度计资料在陆地上空的云检测研究一直是难点。利用快速辐射传输模式（CRTM）分析了不同云类条件下FY-3C微波湿度计（MWHS-Ⅱ）各通道亮温的通道间变率特征,根据MWHS-Ⅱ亮温通道间变率随云高以及云中液态水含量的增大而减小的特点,提出了一个基于亮温通道变率的MWHS-Ⅱ陆地资料云检测方法。与已有的云产品比较结果表明:新的云检测算法能有效地剔除大部分受云影响的资料,剔除后的晴空资料观测和模拟偏差更好地符合高斯分布。新方法对过冷水云、冰云、重叠云的检测能力较强,正确检测率可以达到80%,对卷云以及高度较低的水云的检测能力相对较弱。新方法能有效利用MWHS-Ⅱ观测资料自身完成云检测,在MWHS-Ⅱ资料同化中有很好的应用前景。      

The impact of geophysical parameters on longwave radiation budget at the top and base of the atmosphere

Summary The effect of clouds on longwave radiation budget at the top and base of the atmosphere is studied by using the HIRS2/MSU-retrieved temperature and humidity fields, and cloud fields and the International Satellite Cloud Climatology Project-produced fields. Detailed studies are carried out at four selected sites: one at Equatorial Eastern Pacific (ITCZ) area, one at Libyan Desert (Libya), one at Ottawa, Montreal (Ottawa), and one at central Europe (Europe). The monthly mean differences in outgoing longwave radiation (OLR) (the ISCCP-based OLR minus the HIRS2-based OLR), ranging from –2.8 Wm^–2 at ITCZ to –15.4 Wm^–2 at Ottawa, are less than the monthly mean differences in surface downward flux, ranging from –2.7 Wm^–2 at Libya to 40.6 Wm^–2 at the ITCZ. The large differences in surface downward flux are mainly due to large differences in cloud amount and moisture in the low levels of the atmosphere.Monthly mean OLR and surface downward flux can be derived either (1) from instantaneous temperature, humidity, and cloud fields over a month period or (2) from monthly mean temperature, humidity, and cloud fields. The monthly mean OLR and surface downward flux derived from the first approach is compared with the second. The differences in OLR are small, ranging from –0.05 Wm^–2 to 6.2 Wm^–2, and the differences in surface downward flux is also small, ranging from 0.4 Wm^–2 to 6.4 Wm^–2.List of Acronyms AVHRR Advanced Very High Resolution radiometer - ERB Earth Radiation Budget - ERBE Earth Radiation Budget Experiment - FGGE First Global GARP Experiment - GARP Global Atmospheric Research Program - GCM General Circulation Model - GISS Goddard Institute for Space Studies - GLA Goddard Laboratory for Atmospheres - GMS Geostationary Meteorological Satellite - GOES Geostationary Operational Environmental Satellite - HIRS2 High Resolution Infrared Radiation Sounder/2 - ISCCP International Satellite Cloud Climatology Project - IR Infrared - MSU Microwave Sounding Unit - NFOV Narrow Field of View - NOAA National Oceanic and Atmospheric Administration - NESDIS National Environmental Satellite Data Information Service - TOVS TIROS Operational Vertical Sounder With 4 Figures