scholarly journals Impact of improved near infrared water vapor line data on absorption of solar radiation in GCMs

2001 ◽  
Vol 28 (24) ◽  
pp. 4591-4594 ◽  
Author(s):  
Ralf Bennartz ◽  
Ulrike Lohmann
1998 ◽  
Vol 189 (2) ◽  
pp. 291-300 ◽  
Author(s):  
Oleg L. Polyansky ◽  
Nikolai F. Zobov ◽  
Serena Viti ◽  
Jonathan Tennyson
Keyword(s):  

1998 ◽  
Vol 11 (2) ◽  
pp. 1050-1053
Author(s):  
R.W. Carlson ◽  
K.H. Baines ◽  
T. Encrenaz ◽  
P. Drossart ◽  
M. Roos-Serote ◽  
...  

AbstractThe Galileo Near Infrared Mapping Spectrometer (NIMS) obtains spectral images in the wavelength range 0.7 to 5.2 μm with a spectral resolving power of approximately 200. This spectral range allows NIMS to sense cloud-reflected solar radiation, thermal emission produced in the deep atmosphere, and auroral emission from the thermosphere of Jupiter. Using 5 μm thermal emission spectroscopy, the amount of water vapor in the deep atmosphere, at approximately the (i to 8 bar level, is found to vary by a factor > 100. Deep atmosphere ammonia was also found to vary, with a spatial behavior different from that of water vapor. No evidence is found for a massive water cloud. Using reflected solar radiation in conjunction with thermal emission, two cloud layers are found, the upper at 0.5 bars and a lower one at 1-1.3 bars. The inferred absorption properties of these clouds are consistent with ammonia crystals (the upper cloud) and ammonium hydrosulfide particles (the lower cloud).


Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 505
Author(s):  
Gregoriy Kaplan ◽  
Offer Rozenstein

Satellite remote sensing is a useful tool for estimating crop variables, particularly Leaf Area Index (LAI), which plays a pivotal role in monitoring crop development. The goal of this study was to identify the optimal Sentinel-2 bands for LAI estimation and to derive Vegetation Indices (VI) that are well correlated with LAI. Linear regression models between time series of Sentinel-2 imagery and field-measured LAI showed that Sentinel-2 Band-8A—Narrow Near InfraRed (NIR) is more accurate for LAI estimation than the traditionally used Band-8 (NIR). Band-5 (Red edge-1) showed the lowest performance out of all red edge bands in tomato and cotton. A novel finding was that Band 9 (Water vapor) showed a very high correlation with LAI. Bands 1, 2, 3, 4, 5, 11, and 12 were saturated at LAI ≈ 3 in cotton and tomato. Bands 6, 7, 8, 8A, and 9 were not saturated at high LAI values in cotton and tomato. The tomato, cotton, and wheat LAI estimation performance of ReNDVI (R2 = 0.79, 0.98, 0.83, respectively) and two new VIs (WEVI (Water vapor red Edge Vegetation Index) (R2 = 0.81, 0.96, 0.71, respectively) and WNEVI (Water vapor narrow NIR red Edge Vegetation index) (R2 = 0.79, 0.98, 0.79, respectively)) were higher than the LAI estimation performance of the commonly used NDVI (R2 = 0.66, 0.83, 0.05, respectively) and other common VIs tested in this study. Consequently, reNDVI, WEVI, and WNEVI can facilitate more accurate agricultural monitoring than traditional VIs.


1938 ◽  
Vol 34 (2) ◽  
pp. 208-208
Author(s):  
N. I. Kalitin

Biomedgiz. Leningrad branch. 1937 208 pp. Pr. 6 rubles. 50 kopecks. The content of the book is much wider than what the reader has a right to expect, judging by its title. The book concerns not only the measurement of radiant energy and touches on not only issues of interest to doctors working in resorts. The properties of solar radiation under various conditions, the influence of water vapor, ozone, dustiness of the atmosphere, the value of scattered radiation reflected from the sky and clouds, which is usually not paid enough attention, all these and many other issues are covered in detail in the book of prof. N.I. Kalitina largely on the basis of her own long-term research.


Energies ◽  
2017 ◽  
Vol 11 (1) ◽  
pp. 37 ◽  
Author(s):  
Jose Rogada ◽  
Lourdes Barcia ◽  
Juan Martinez ◽  
Mario Menendez ◽  
Francisco de Cos Juez

Power plants producing energy through solar fields use a heat transfer fluid that lends itself to be influenced and changed by different variables. In solar power plants, a heat transfer fluid (HTF) is used to transfer the thermal energy of solar radiation through parabolic collectors to a water vapor Rankine cycle. In this way, a turbine is driven that produces electricity when coupled to an electric generator. These plants have a heat transfer system that converts the solar radiation into heat through a HTF, and transfers that thermal energy to the water vapor heat exchangers. The best possible performance in the Rankine cycle, and therefore in the thermal plant, is obtained when the HTF reaches its maximum temperature when leaving the solar field (SF). In addition, it is necessary that the HTF does not exceed its own maximum operating temperature, above which it degrades. The optimum temperature of the HTF is difficult to obtain, since the working conditions of the plant can change abruptly from moment to moment. Guaranteeing that this HTF operates at its optimal temperature to produce electricity through a Rankine cycle is a priority. The oil flowing through the solar field has the disadvantage of having a thermal limit. Therefore, this research focuses on trying to make sure that this fluid comes out of the solar field with the highest possible temperature. Modeling using data mining is revealed as an important tool for forecasting the performance of this kind of power plant. The purpose of this document is to provide a model that can be used to optimize the temperature control of the fluid without interfering with the normal operation of the plant. The results obtained with this model should be necessarily contrasted with those obtained in a real plant. Initially, we compare the PID (proportional–integral–derivative) models used in previous studies for the optimization of this type of plant with modeling using the multivariate adaptive regression splines (MARS) model.


2020 ◽  
Vol 220 ◽  
pp. 01019
Author(s):  
Elvira Fazalova ◽  
Konstantin Kochunov ◽  
Elena Bodyago ◽  
Georgii Konoplev ◽  
Nikolay Mukhin ◽  
...  

Optical and photoelectric properties of poly (ohydroxyamide) (PHA) sensitized with zinc phthalocyanines were investigated in the visible and near infrared spectral regions. The structures were deposited on glass substrates by centrifugation and subsequent drying of a PHA film without thermal annealing. Optical spectra revealed characteristic absorption peaks of phthalocyanine in the longer wavelength region at 620-640 nm and 680-700 nm; absorption of the PHA matrix monotonously increases to the shorter wavelengths starting from 700 nm. Measurements of the photocurrent under irradiation with a high-power LED at a wavelength 630 nm showed photoconductivity related to the organic dye; photoconductivity also was observed while irradiated at 540 nm, presumably due to the absorption of PHA matrix. For non-sensitized (dye-free) PHA films no detectable photocurrents were produced by 630 nm irradiation. It was shown that introducing of phthalocyanines significantly improves optical absorption and photoconductivity of PHA thin films at the wavelengths, where the maximum in the spectral distribution of solar radiation lies. It was concluded that phthalocyanine-sensitized PHA has the potential use as a photosensitive organic material for solar applications, for example in developing composite organicinorganic structures with ferroelectrics.


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