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An inexpensive, lightweight fiber optic micro-sensor that is suitable for applications which may require remote temperature sensing. The disclosed temperature sensor includes a phosphor material that, after receiving incident light stimulation, is adapted to emit phosphorescent radiation output signals, the amplitude decay rate and wavelength of which are functions of the sensed temperature.
The application of Raman scattering to remote sensing of subsurface water temperature and salinity is considered, and both theoretical and experimental aspects of the technique are discussed. Recent experimental field measurements obtained in coastal waters and on a trans-Atlantic/Mediterranean research cruise are correlated with theoretical expectations. It is concluded that the Raman technique for remote sensing of subsurface water temperature has been brought from theoretical and laboratory stages to the point where practical utilization can now be developed.
This paper describes experimental remote sensing of subsurface water temperature using the Raman spectroscopic technique. By the use of a pulsed laser and range gating detection techniques, Raman scattering is analyzed as a function of depth in a radar-like echo mode, and thus subsurface profiles of temperature and transmission are obtained. Experiments are described in which Raman data using polarization spectroscopy has been obtained from a ship as a function of depth in ocean water near Grand Bahama Island. A spectral temperature accuracy of + or - 1 C has been obtained from this data in the first two optical attenuation lengths. Raman data obtained from ocean water using the NASA airborne oceanographic lidar is also presented.
The paper describes a parameterization procedure for determining the actual surface temperature from the effective brightness temperature measured radiometrically in the 11-micron window region. The algorithm permits computation of the atmospheric correction without performing detailed radiative transfer calculations, and corrections for atmospheric water vapor and for variations of surface emittance are explained. The parameterization is based on model calculations performed with a line-by-line radiative transfer program, and the sensitivity of the retrieved surface temperature to uncertainties concerning the water vapor and the surface emittance is examined.
Surface temperatures and reflectances of an upper elevation Sierran mixed conifer forest were monitored using the Thematic Mapper Simulator sensor during the summer of 1985 in order to explore the possibility of using remote sensing to determine the distribution of solar energy on forested watersheds. The results show that the method is capable of quantifying the relative energy allocation relationships between the two cover types defined in the study. It is noted that the method also has the potential to map forest latent heat flux densities.
Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from MODIS over the dry and semiarid regions of northern China. Studies were conducted for both MODIS-Terra and MODIS-Aqua by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and MODIS land surface temperature, surface maximum and minimum air temperatures are estimated from 1km MODIS land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).
The main sources of error in remote sensing of sea surface temperature are discussed. The interfering effects of reflected solar radiation, reflected thermal flux, clouds and haze and atmospheric attenuation are examined. The components of measured sea surface radiances, such as clear column radiance, surface emission, atmospheric emission, reflected thermal downward flux, and reflection of solar flux, are analytically presented. The use of the 3.7 micron region window to obtain the radiance to four percent accuracy is discussed. The advantages to be obtained by the use of narrow bandpass channels are assessed.
Lake Chad, located in the middle of the African Sahel belt, underwent dramatic decreases in the 1970s and 1980s leaving less than ten percent of its 1960s surface water extent as open water. In this paper, we present an extended record (dry seasons 1988-2016) of the total surface water area of the lake (including both open water and flooded vegetation) derived using Land Surface Temperature (LST) data (dry seasons 2000-2016) from the NASA Terra MODIS sensor and EUMETSAT Meteosat-based LST measurements (dry seasons 1988-2001) from an earlier study. We also examine the total surface water area for Lake Chad using radar data (dry seasons 2015-2016) from the ESA Sentinel-1a mission. For the limited number of radar data sets available to us (18 data sets), we find on average a close match between the estimates from these data and the corresponding estimates from LST, though we find spatial differences in the estimates using the two types of data. We use these spatial differences to adjust the record (dry seasons 2000-2016) from MODIS LST. Then we use the adjusted record to remove the bias of the existing LST record (dry seasons 1988-2001) derived from Meteosat measurements and combine the two records. From this composite, extended record, we plot the total surface water area of the lake for the dry seasons of 1988-1989 through 2016-2017. We find for the dry seasons of 1988-1989 to 2016-2017 that the maximum total surface water area of the lake was approximately 16,800 sq. km (February and May, 2000), the minimum total surface water area of the lake was approximately 6400 sq. km (November, 1990), and the average was approximately 12,700 sq. km. Further, we find the total surface water area of the lake to be highly variable during this period, with an average rate of increase of approximately 143 sq. km per year.
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Global stratospheric infrared radiation patterns measured by Nimbus 2 satellite
The paper discusses the accuracy of atmospheric vertical temperature profile measurements performed by the Nimbus 5 microwave spectrometer and compares results obtained during the first 6 months of its operation with independent ground-truth measurements (coincident radiosonde measurements). The microwave spectrometer can measure temperature profiles averaged over the instrument weighting function (about 10 km) layers with a root-mean-square accuracy of a few tenths of a degree K for measurement integration times of 16 s. Lower tropospheric temperature data from the spectrometer measurements is used in the numerical weather prediction model of the National Meteorological Center.
Clear-column temperature profiles with a vertical resolution of 2 km in the troposphere and an accuracy of 1.5 K are obtained in the presence of multiple layers of broken clouds using narrow band-pass measurements carefully selected in the 4.18 and 15 micron regions of the CO2 bands.
A dual-frequency system is used to demonstrate the measurement of atmospheric temperature, through laser energy absorption monitoring at the center of an O2 resonant absorption line near 770 nm. It is shown that the average temperature of a 1 km path can be determined within 1.0 C, with a noise level of 0.3 C. An iterative algebraic expression for this method was developed, and is shown to be applicable in the troposphere; the effects of pressure and humidity on temperature determination were made clear by the algorithm and found to be small near the earth's surface.
Multichannel atmospheric correction equations for the NOAA 6 proposed by Bernstein (1982) and by McClain (1981) are evaluated by using satellite and in situ data collected over and in the Southern California Bight. The temporal and spatial variation of sea surface temperature over small scales is estimated from the data, and the effect of this variation in matching satellite and in situ data sets is discussed. Changes in the temperature fields between images are examined for diurnal variation and for surface advection of horizontal temperature gradients.
Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. The SiFSAP algorithm performs one retrieval for each FOV using an all-sky optimal estimation approach. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.
The remote determination of surface temperature and surface spectral emittance by use of airborne or satellite-borne thermal infrared instruments is not straightforward. The radiance measured is a function of surface temperature, the unknown surface spectral emittance, and absorption and emission in the intervening atmosphere. With a single measurement, the solution for temperature and spectral emittance is undedetermined. This article reviews two of the early approximate methods which have been fairly widely used to approach this problem.
A method is described for determining the water vapor content to within + or - 0.4 g/sq cm from remotely sensed radiances in three infrared channels, 11, 13, 18 microns. Using this method, it is possible to significantly improve the accuracy of sea surface temperature (SST) over what is obtainable with the two channel technique. A radiative computational scheme for the radiative transfer equation is used to study the manner in which the equivalent radiative temperature of the atmosphere changes as a function of wave number for different atmospheric conditions. Average climatological conditions are used to simulate the radiative response of the atmosphere. This radiative transfer simulation is used to compute brightness temperatures for radiosonde profiles obtained from oceanographic ships, which temperatures are in turn used to estimate the SST. Nimbus 4 IRIS spectral measurements corresponding to the profiles were used in the same way for purposes of comparison.