Thermal IR Channels Research Articles

Joint 3D-Wind Retrievals with Stereoscopic Views from MODIS and GOES

Atmospheric motion vectors (AMVs), derived by tracking patterns, represent the winds in a layer characteristic of the pattern. AMV height (or pressure), important for applications in atmospheric research and operational meteorology, is usually assigned using observed IR brightness temperatures with a modeled atmosphere and can be inaccurate. Stereoscopic tracking provides a direct geometric height measurement of the pattern that an AMV represents. We extend our previous work with multi-angle imaging spectro–radiometer (MISR) and GOES to moderate resolution imaging spectroradiometer (MODIS) and the GOES-R series advanced baseline imager (ABI). MISR is a unique satellite instrument for stereoscopy with nine angular views along track, but its images have a narrow (380 km) swath and no thermal IR channels. MODIS provides a much wider (2330 km) swath and eight thermal IR channels that pair well with all but two ABI channels, offering a rich set of potential applications. Given the similarities between MODIS and VIIRS, our methods should also yield similar performance with VIIRS. Our methods, as enabled by advanced sensors like MODIS and ABI, require high-accuracy geographic registration in both systems but no synchronization of observations. AMVs are retrieved jointly with their heights from the disparities between triplets of ABI scenes and the paired MODIS granule. We validate our retrievals against MISR-GOES retrievals, operational GOES wind products, and by tracking clear-sky terrain. We demonstrate that the 3D-wind algorithm can produce high-quality AMV and height measurements for applications from the planetary boundary layer (PBL) to the upper troposphere, including cold-air outbreaks, wildfire smoke plumes, and hurricanes.

Identification of Weather Events from INSAT-3D RGB Scheme using RAPID Tool

Real-time analysis of products and information dissemination (RAPID), a web-based quick visualization and analysis tool for INSAT satellite data has been presented for identification of weather events. The combination of channels using red-green-blue (RGB) composites of INSAT-3D satellite and its physical significant value content is presented. The solar reflectance and brightness temperatures are the major components of this scheme. The shortwave thermal infrared (1.6 μm), visible (0.5 μm) and thermal IR channels (10.8 μm) representing cloud microstructure is known as Day Microphysics (DMP) and the brightness temperature (BT) differences between 10.8, 12.0 and 3.9 μm is referred to as Night Microphysics (NMP). The thresholds technique have been developed separately for both the RGB products of two years (2015-17 of December to February) of data for the identification of fog, snow and low clouds. The validation of these thresholds has been carried out against in situ visibility data from IMD observatories. The RGBs, i.e. DMP and NMP have a reasonable good agreement with ground-based observations and Moderate Resolution Imaging Spectroradiometer (MODIS) data. This threshold technique yields a very good probability of fog detection more than 94% and 85% with acceptable false alarm conditions less than 8% and 10% for DMP and NMP respectively. The technique has significantly minimized the misclassification between low clouds, snow, and fog and found useful for day-to-day weather forecast.

Cloud base height from sky imager and cloud speed sensor

Cloud base height (CBH) is a critical input to short-term solar forecasting algorithms, yet CBH measurements are difficult to obtain. Existing methods to detect CBH include radiosondes, ceilometers, and the stereographic method. However, these methods are deficient for intra-hour forecasting due to high costs or low temporal resolution. While satellite images could overcome these limitations, only the cloud top height can be determined from the thermal IR channel. We describe the integration of a cloud shadow speed sensor (CSS) with angular cloud speed from a sky imager to determine CBH. Furthermore, an improved methodology to determine cloud motion vectors from the CSS is presented, which offers lower noise and greater accuracy and stability than existing methods. Two months at the UC San Diego campus were used for validation against measurements from meteorological aerodrome reports (METAR) and an on-site ceilometer. Typical daily root mean square differences (RMSD) are 126m which corresponds to 16.9% of the observed CBH. Normalized RMSD remains below 30% for all days. The daily bias is usually less than 80m which suggests that the method is robust and that most of the RMSD is driven by short-term random fluctuations in CBH. Unlike sky image stereography the present method can be applied to measurements at a single site making it widely applicable.

Combining the Perspective of Satellite- and Ground-Based Observations to Analyze Cloud Frontal Systems

AbstractA method is presented to analyze the cloud life cycle of frontal systems passing over European supersites. It combines information on the vertical profiles of cloud properties derived from ground-based observations with cloud products obtained from satellite-based observations, including their spatial variability. The Euler and Lagrange perspectives are adopted to consider the history of a cloud system that passes the supersites. The forward model known as RTTOV (Radiative Transfer for the Television and Infrared Observation Satellite Operational Vertical Sounder) and the ground-based “CloudNET” products are used to simulate synthetic satellite observations at the supersites, which are subsequently compared with the actual observations of the Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument. Different metrics are considered to quantify and interpret the consistency of the synthetic and the observed satellite data: brightness temperatures at the thermal IR channels, the split-window channels, and trispectral combinations, as well as the outgoing longwave radiation. In this way, the uncertainties of the individual datasets are investigated. This knowledge provides the motivation to combine the disjunct cloud products from satellite with those from ground instruments to characterize the development of the passing cloud frontal systems. In addition, back trajectories started at different stages of the cloud system were used to analyze its history prior to the supersite overpass. The trajectories are used to study, for example, the life time of the cloud frontal system, changes of the cloud phase, and the evolution of cloud physics such as optical thickness, effective particle size, and water path. As a test bed, a case study with a cold front passing Lindenberg, Germany, is presented.

Combined MW-IR Precipitation Evolving Technique (PET) of convective rain fields

Abstract. This paper describes a new multi-sensor approach for convective rain cell continuous monitoring based on rainfall derived from Passive Microwave (PM) remote sensing from the Low Earth Orbit (LEO) satellite coupled with Infrared (IR) remote sensing Brightness Temperature (TB) from the Geosynchronous (GEO) orbit satellite. The proposed technique, which we call Precipitation Evolving Technique (PET), propagates forward in time and space the last available rain-rate (RR) maps derived from Advanced Microwave Sounding Units (AMSU) and Microwave Humidity Sounder (MHS) observations by using IR TB maps of water vapor (6.2 μm) and thermal-IR (10.8 μm) channels from a Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer. PET is based on two different modules, the first for morphing and tracking rain cells and the second for dynamic calibration IR-RR. The Morphing module uses two consecutive IR data to identify the motion vector to be applied to the rain field so as to propagate it in time and space, whilst the Calibration module computes the dynamic relationship between IR and RR in order to take into account genesis, extinction or size variation of rain cells. Finally, a combination of the Morphing and Calibration output provides a rainfall map at IR space and time scale, and the whole procedure is reiterated by using the last RR map output until a new MW-based rainfall is available. The PET results have been analyzed with respect to two different PM-RR retrieval algorithms for seven case studies referring to different rainfall convective events. The qualitative, dichotomous and continuous assessments show an overall ability of this technique to propagate rain field at least for 2–3 h propagation time.

Landsat 7 ETM+ 영상에서 얻은 지표온도와 지형인자의 상관성 분석

인공위성영상은 적외선 채널을 이용하여 지표에서 복사되는 열을 감지할 수 있기 때문에 이를 이용하여 도심지역의 지표온도와 열섬현상과의 관계를 밝히기 위한 많은 노력이 있어왔다. 그러나 사면향과 경사와 같은 지형인자와 지표온도와의 관계성에 관한 연구는 그동안 다소 미흡하였다. 이에 본 연구에서는 사면향과 경사와 같은 지형인자의 변화에 따라 지표온도가 어떻게 변화하는지를 Landsat 7 ETM+을 사용하여 연구하였으며 지표에서 발생하는 인본열을 감지할 수 있는 가능성을 평가하였다. 지표의 사면향은 지표온도분포에 중요한 인자로 영향을 주지 않지만, 사면의 기울기는 태양의 고저에 의해 많은 영향을 받는 것으로 나타났다. 또한 위성영상은 지표면과 이루는 각으로 인해 영상에 정확한 지표온도를 기록할 수 없지만, 사면의 기울기 보정을 통해 보정한 결과 평균 지표온도분포 분석에서는 큰 영향을 미치지 않는 것으로 확인 되었다. 또한 위성영상을 통해 지표발산 인본열 추출의 가능성을 확인하였다. Because the satellite imagery can detect the radiative heat from the surface using the thermal IR (TIR) channel, there have been many efforts to verify the relationship between the land surface temperature (LST) and urban heat island. However, the relationship between geomorphological characteristics like surface aspects and LST is relatively less studied. Therefore, the geomorphological elements, for example, surface aspects and surface slopes, are considered to evaluate their effects on the change of the surface temperature distribution using the Landsat 7 ETM+ TIR channel and the possibility of the image to detect anthropogenic heat from the surface. We found that the surface aspect is ignorable but the surface slope with the sun elevation influences on the surface temperature distribution. Also, the radiative heat from the surface to the atmosphere could not be accurately recorded by the satellite image due to the surface slope but the slope correction process used in this study could correct the surface temperature under slope condition and the slope correction, in fact, was not influenced on the average temperature of the surface. The possibility of the anthropogenic heat detection from the surface from the satellite imagery was verified as well.

Sentinel-3 SLSTR active fire detection and FRP product: Pre-launch algorithm development and performance evaluation using MODIS and ASTER datasets

The Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) is a dual-view Earth observing instrument that builds on the heritage of the Along Track Scanning Radiometer (ATSR) series. SLSTR is planned for launch in 2013 on Sentinel-3, with two concurrently operating satellites planned for daily global coverage. Here we review the aspects of the SLSTR instrument design specifically targeted at biomass burning events, including operation of the SWIR channels at night and the inclusion of low-gain middle infrared and thermal IR channels that will minimise saturation over even high intensity fires. We detail the active fire detection and fire radiative power dataset to be provided from these SLSTR observations, which will be part of the SLSTR land product suite aimed at supporting both Global Monitoring for Environment and Security (GMES) operational services and scientific applications. We describe in detail the pre-launch active fire product algorithm, which uses data from the SLSTR near-nadir scan. The algorithm detects pixels containing actively burning fires, and uses the MIR radiance method to estimate their fire radiative power (FRP). We test the algorithm using a series of EOS MODIS scenes covering a range of fire-affected forest and savannah environments, comparing performance to that of the existing MODIS MOD14 ‘Fire and Thermal Anomaly’ products. Across 385 scenes covering Africa, South America and Australia, we find that the SLSTR algorithm applied to MODIS data detects in total 20% more fire pixels than does the MOD14 algorithm applied to the same data. Some scenes show very large differences, while others showed no differences, and some of the extra detections made by SLSTR maybe false alarms. For a better evaluation, we use the simultaneous high spatial resolution active fire detections made from ASTER to provide an independent accuracy assessment. Across 45 separate geographical regions covered simultaneously by ASTER and MODIS, we find that the SLSTR algorithm in fact detects 13% more correctly identified clusters of active fire pixels than the MOD14 algorithm, and that these contain 36% more active fire pixels. In particular, the SLSTR algorithm shows increased detection probabilities at small/low FRP fires, mainly due to the more liberal characteristics of its potential fire pixel detection stage. This performance enhancement comes, however, at the expense of a small (<2%) increase in commission error (i.e. false alarm rate) when compared to MOD14. The SLSTR algorithms ability to better detect low FRP fires maybe important, since these are usually the most common component of a region's fire regime.

PM-GCD – a combined IR–MW satellite technique for frequent retrieval of heavy precipitation

Abstract. Precipitation retrievals based on measurements from microwave (MW) radiometers onboard low-Earth-orbit (LEO) satellites can reach high level of accuracy – especially regarding convective precipitation. At the present stage though, these observations cannot provide satisfactory coverage of the evolution of intense and rapid precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications – especially in supporting authorities for flood alerts and weather warnings. To tackle this problem, over the past two decades several techniques have been developed combining accurate MW estimates with frequent infrared (IR) observations from geosynchronous (GEO) satellites, such as the European Meteosat Second Generation (MSG). In this framework, we have developed a new fast and simple precipitation retrieval technique which we call Passive Microwave – Global Convective Diagnostic, (PM-GCD). This method uses MW retrievals in conjunction with the Global Convective Diagnostic (GCD) technique which discriminates deep convective clouds based on the difference between the MSG water vapor (6.2 μm) and thermal-IR (10.8 μm) channels. Specifically, MSG observations and the GCD technique are used to identify deep convective areas. These areas are then calibrated using MW precipitation estimates based on observations from the Advanced Microwave Sounding Unit (AMSU) radiometers onboard operational NOAA and Eumetsat satellites, and then finally propagated in time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique, analyzing its results for a case study that refers to a flood event that struck the island of Sicily in southern Italy on 1–2 October 2009.

A Physical Method for the Calibration of the AVHRR/3 Thermal IR Channels. Part II: An In-Orbit Comparison of the AVHRR Longwave Thermal IR Channels on board MetOp-A with IASI

Abstract Obtaining stable and accurate satellite radiances for climate change research requires extremely high standards for satellite calibration. Many satellite sensors do not currently meet the accuracy criteria, especially heritage sensors such as the Advanced Very High Resolution Radiometer (AVHRR), which shows scene temperature–dependent trends and biases of up to 0.5 K. Recently, however, a detailed study of the AVHRR/3 prelaunch data showed significant problems with both the calibration algorithm and the prelaunch data and indicated that the inherent accuracy of the AVHRR may actually be quite high. A new approach has been suggested that fixed many of the issues with the current (operational) calibration, but has not yet been applied to the in-orbit case. In this paper the behavior of the AVHRR in orbit is examined and compared to the operational AVHRR radiances from the Meteorological Operation (MetOp)-A with those based on the new calibration to radiances derived from the Infrared Atmosphere Sounding Instrument (IASI). It is shown that the current AVHRR calibration does indeed introduce large (0.5 K) biases, but these biases are remarkably stable. It is further shown that, with some modification related to differences between the prelaunch test environment and the in-orbit environment, a physically based AVHRR calibration can match IASI to better than ~0.05 K, which is an order of magnitude better than what is currently available. Finally, it is shown that, while the new calibration is capable of providing accurate and stable radiances for the nadir view, off-nadir biases of up to 1.5 K still exist at the largest zenith angles and at the coldest scene temperatures (~210 K). For surface temperature determination, however, the scan angle bias is very small (&amp;lt;0.02 K), implying that the new AVHRR calibration will provide a significant improvement to, for example, sea surface temperature measurements, one of the Global Climate Observing System (GCOS)-designated essential climate variables.

An analysis of drought events for central plains of Iran through an employment of NOAA-AVHRR data

Drought is a major problematic phenomenon for the mostly semi-arid country of Iran. The north centralregions of Iran (north of Esfahan and Ghom province) have suffered from severe droughts several times duringthe last three decades. The frequent occurrence of drought in these regions is due to low and inconsistentprecipitation, abnormally high temperatures, increases in surface albedo and evapotranspiration; especiallyduring spring. The surface characteristics of Kashan and Ghom regions consist of salty flats and sandy hillscovered by sparse vegetation. The average elevation of the area is 1987 mASL. In the present work, NOAAAVHRRdata have been employed to assess vegetation indices and environmental conditions in the study regionfor the years 1998 – 2004; which are then compared to actual ground data such as rainfall, temperature andrelative humidity for a detailed drought analysis. Spatial and temporal variations of meteorological droughts inKashan have been analyzed using Standardized Precipitation Index (SPI) at annual and seasonal scales, and havebeen generated through GIS based interpolation. Vegetative and thermal drought indices have been calculatedusing NDVI, VCI, and TCI values derived from NOAA-AVHRR data. Results from applying remotely senseddata show that this area is generally of low vegetation index values. The artificial forests and farmlands at thefoothills of the mountains northwest of Kashan region showed relatively high vegetation index values. TCI andVCI generally show a good relationship with meteorological observations. According to the output of utilizationNDVI and VCI, 2000 and 2001 years were characteristic of drought conditions, while 2002 and 2004 did nonrepresent drought years. Since TCI index is completely dependent on surface temperature, the combined analysisof the May and April results were influenced by the low land surface temperatures experienced in April, andtherefore it was very different from the other indices i.e. NDVI and VCI. Therefore thermal IR channels can beemployed used to monitor drought conditions in the semi-arid and arid regions of Iran to assess these regions,environmental conditions.

Case study of Mesoscale Convective Systems over Hungary on 29 June 2006 with satellite, radar and lightning data

On 29 June 2006 two Mesoscale Convective Systems (MCS) crossed Hungary causing severe weather, heavy precipitation, hail and strong wind. The first MCS transformed to a Mesoscale Convective Vortex (MCV) in its dissipating phase. The case was analyzed using different remote sensing devices: satellites, radars and a lightning detection system. Visible images from the METEOSAT-8 satellite were used to discriminate thin and thick parts of the anvil and to identify the overshooting tops. Structures like cold rings and cold-U/V shapes detected from infrared imagery indicate possible penetration of the storm top into the tropopause or lower stratosphere. The near and medium infrared solar channels (and some thermal IR channel differences) provide information on cloud top microphysics. The spatial distribution of the cloud top ice crystal size was investigated with the use of the so called “convective storms” composite imagery obtained from brightness temperature and reflectivity differences of water vapor, infrared and short-wave channels. The MODIS band 1 (0.645 µm) image of the TERRA satellite shows gravity wave generation at the top of the thunderstorm cloud, which could be connected to the strength and pulsations of the updraft. Satellite images were overlaid with radar reflectivities, which are characterized by an asymmetric bow echo. It is concluded that composites of satellite, radar and lightning data help to assess relative locations of main up- and downdrafts and important features of the severe storm.

A Night-Rain Delineation Algorithm for Infrared Satellite Data Based on Microphysical Considerations

Information about the microstructure and precipitation potential of cloud revealed by the brightness temperature difference between a thermal IR channel (11 mm) and a mid-IR channel (3.7 mm) at nighttime is implemented into a precipitation delineation algorithm. The algorithm is simple to implement and uses data available from almost all of the operational and research satellites. The delineation algorithm performs well also in cases of warm clouds over land for which passive microwave algorithms fail.

Satellite-Based Insights into Precipitation Formation Processes in Continental and Maritime Convective Clouds at Nighttime

Abstract Nighttime microphysical retrievals can be obtained to a much lesser accuracy than those of the daytime, because of lack of the solar radiation. However, a proper treatment of the brightness temperature difference (BTD) between a thermal IR channel (11 μm) and a mid-IR channel (3.7 μm) reveals information about the microstructure and precipitation potential of clouds at nighttime. The two factors that contribute to large BTD are the particle size at cloud top and the optical depth of the cloud layer. These two factors have contradictory effects on precipitation. The respective contributions were simulated and compared with observations of the Tropical Rainfall Measuring Mission. Based on that, a method was developed to use the distribution of BTD with cloud-top temperature for retrieving cloud microstructure and precipitation properties.

An algorithm to overlay continental boundaries and latitude-longitude grids over INSAT-VHRR images

The VHRR imagers aboard geostationary satellites have been the major source of quasi-continuous meteorological weather monitoring over tropical and subtropical latitudes. Accurate geolocation of pixels with respect to continental boundaries in digital VHRR images, irrespective of problems of cloud cover obscuration, is an essential prerequisite for proper utilization of VHRR data for any meteorological and oceanographic applications. In this paper, we present a user-friendly algorithm to overlay continental boundaries and geographical coordinate grids on VHRR images from geostationary satellites such as INSAT. The geometric scheme adopted for generating the required information is free from limitations of cloud cover or lack of contrast in visible or thermal IR channel images. The algorithm produces satisfactory geolocation accuracies for most meteorological and oceanographic applications. The algorithm is general and could be used for VHRR images from other geostationary satellites (METEOSAT, GMS, and GOES) by incorporating the necessary information about their VHRR scan characteristics.

Global land monitoring using AVHRR time series

Global Vegetation Index (GVI) time series of multispectral AVHRR weekly composite data with a 0.15° resolution have been collected from NOAA-9 and -11 since 1985. A prototype global land monitoring system was developed based on monthly maps of standardized anomalies of satellite derived Normalized Difference Vegetation Index, NDVI, and Channel 4 brightness temperature, T 4. Processing included post-launch updated calibration and cloud screening, filling in the cloud induced gaps by monthly averaging and interpolation, and suppressing residual noise by smoothing. Monthly maps were used to derive climatology, in terms of multiannual means and variability, and monthly standardized anomalies, which allow monitoring such extreme natural events as droughts and floods. However, some discontinuity and residual trends, which can still be traced in time series, preclude accurate detection of moderate ecosystem changes. Discontinuity results from the switch from NOAA-9 to NOAA-11 in 1988, and Mt.Pinatubo eruption in 1991. Residual trends can be attributed to a combined effect of satellite orbit drift and possible persistent error in calibration of solar channels. The satellite drift affects the solar and thermal IR channels through systematic variation of illumination geometry and diurnal heating/cooling of the surface and atmosphere, respectively. Examples are given to illustrate the magnitude of these effects.

Wet tropospheric range corrections for radar altimeter over Indian Ocean

Abstract A relation between wet tropospheric range correction and precipitable water has been proposed for correcting satellite-borne radar altimeter data over the Indian Ocean region for south-west monsoon months (May-July). The proposed regional relation, which used data from May-July 1979, gave an rms error of 1·53 mm as compared to rms error of 4·54mm for Liu and Mock's relation using global data. The precipitable water values ranged from 30 mm to 75 mm with larger concentration of data points between 40 to 65 mm. The wet tropospheric range correction could be useful for analysing ERS-1 radar altimeter data over Indian oceans whose dual angle split thermal IR channels and/or microwave channels could be used for estimating total precipitable water with an accuracy of 2 to 4 mm. We have also investigated the variability of equivalent temperature with precipitable water and air temperature and found that they are not strongly correlated with each other.

Anatomy of 1986 Augustine volcano eruptions as recorded by multispectral image processing of digital AVHRR weather satellite data

Eighteen digital AVHRR (advanced very high resolution radiometer) data sets from NOAA-6 and NOAA-9 polar-orbiting satellites recorded between 27 March and 7 April 1986 depict the eruptive activity of Augustine volcano, located 280 km SW of Anchorage, Alaska. The synoptic view (resolution of either 1.1 or 4.4 km), frequent coverage (often twice a day), and multispectral coverage (five bands: 0.58–0.68; 0.72–1.1; 3.55–3.93; 10.5–11.3; and 11.5–12.5 μm) makes the AVHRR broadly applicable to analyzing explosive eruption clouds. The small scale of the Augustine activity (column heights of 2–13 km and eruption rates of 2x106–8x107 metric tonnes/day) facilitated intensive multispectral study because the plumes generally covered areas within the 550x550 km area of one easily manipulated image field. Hourly ground weather data and twice-daily radiosonde measurements from stations surrounding the volcano plus numerous volcanological observations were made throughout the eruption, providing important ground truth with which to calibrate the satellite data. The total erupted volume is estimated to be at least 0.102 km3. The pattern of changing eruption rates determined by satellite observations generally correlate with more detailed estimates of explosion magnitudes. Multispectral processing techniques were used to distinguish eruption clouds from meteorological clouds. Variable weather during the Augustine eruption offered an opportunity to test various trial algorithms. A ratio between thermal IR channels four and five, served to delineate the ashbearing eruption plumes from ordinary clouds. Future work is needed to determine whether the successful multispectral discrimination is caused by wavelength-dependent variable emission of silicate ash or reflects a spectral role of sulfuric acid aerosol in the plume.

Comparison of the Information Content of Data from the LANDSAT-4 Thematic Mapper And the Multispectral Scanner

Simultaneous data acquisition by the Landsat-4 Thematic Mapper (TM) and the Multispectral Scanner (MSS) permits the comparison of the two types of image data with respect to engineering performance and data applications. In this paper the "information" contained in data from the visible and near-IR channels is evaluated for five agricultural scenes, leading to the conclusion that the TM provides a significant advance in information gathering capability as expressed in terms of bits per pixel or bits per unit area. The six reflective channels of the TM acquire 18 bits of information per pixel out of a possible 6 × (8 bits) = 48 bits, while the four MSS channels acquire 10 bits of information per pixel out of a possible 4 × (7 bits) = 28 bits. Thus the TM and MSS are equally efficient in gathering information (18/48 = 10/28), contrary to the expected tendency toward lower efficiency as spatial resolution is improved and spectral channels are added to an observing system. The result is attributed to: 1) Superior selection of spectral channels in the TM; 2) Higher precision of the TM data, i.e., lower system noise, and 3) the advantage of higher spatial resolution, even in agricultural areas where fields are larger than the MSS pixel size. Because the MSS lacks a thermal IR channel, the 10-12-micrometer data of the TM at 120-m resolution are analyzed theoretically using an energy balance approach.

Calibration of a satellite infrared radiometer

The calibration procedure is described for a two-channel imaging radiometer on board the Heat Capacity Mapping Mission, a single sensor satellite in a near polar orbit. The Heat Capacity Mapping Radiometer measures radiation temperature and reflectivity with an instantaneous FOV of 600 m and a noise equivalent temperature of 0.4 K at 280 K in the thermal IR channel. Unexplained changes in the system during satellite launch were treated through comparison with surface/atmosphere data to force agreement. This necessitated an offset from the prelaunch calibration by 5.5 K. Later comparisons showed no difference. Possible explanations are described.