Evaluating a satellite-based sea surface temperature by shipboard survey in the Northwest Indian Ocean

A summer-time shipboard meteorological survey is described in the Northwest Indian Ocean. Shipboard observations are used to evaluate a satellite-based sea surface temperature（SST）, and then find the main factors that are highly correlated with errors. Two satellite data, the first is remote sensing product of a microwave, which is a Tropical Rainfall Measuring Mission Microwave Imager（TMI）, and the second is merged data from the microwave and infrared satellite as well as drifter observations, which is Operational Sea Surface Temperature and Sea Ice Analysis（OSTIA）. The results reveal that the daily mean SST of merged data has much lower bias and root mean square error as compared with that from microwave products. Therefore the results support the necessary of the merging infrared and drifter SST with a microwave satellite for improving the quality of the SST. Furthermore, the correlation coefficient between an SST error and meteorological parameters, which include a wind speed, an air temperature, a relative humidity, an air pressure, and a visibility. The results show that the wind speed has the largest correlation coefficient with the TMI SST error. However, the air temperature is the most important factor to the OSTIA SST error. Meanwhile,the relative humidity shows the high correlation with the SST error for the OSTIA product.

Monitoring of steam chamber in steam-assisted gravity drainage based on the temperature sensitivity of oil sand

Thermosensitivity experiments and simulation calculations were conducted on typical oil sand core samples from Kinosis,Canada to predict the steam chamber development with time-lapse seismic data during the steam-assisted gravity drain-age(SAGD).Using an ultrasonic base made of polyether ether ketone resin instead of titanium alloy can improve the signal en-ergy and signal-to-noise ratio and get clear first arrival;with the rise of temperature,heavy oil changes from glass state(at-34.4℃),to quasi-solid state,and to liquid state(at 49.0℃)gradually;the quasi-solid heavy oil has significant frequency dis-persion.For the sand sample with high oil saturation,its elastic property depends mainly on the nature of the heavy oil,while for the sand sample with low oil saturation,the elastic property depends on the stiffness of the rock matrix.The elastic property of the oil sand is sensitive to temperature noticeably,when the temperature increases from 10℃ to 175℃,the oil sand samples decrease in compressional and shear wave velocities significantly.Based on the experimental data,the quantita-tive relationship between the compressional wave impedance of the oil sand and temperature was worked out,and the tem-perature variation of the steam chamber in the study area was predicted by time-lapse seismic inversion.

Automated estimation of stellar fundamental parameters from low resolution spectra: the PLS method

PLS （Partial Least Squares regression） is introduced into an automatic estimation of fundamental stellar spectral parameters. It extracts the most correlative spectral component to the parameters （Teff, log g and [Fe/H]）, and sets up a linear regression function from spectra to the corresponding parameters. Considering the properties of stellar spectra and the PLS algorithm, we present a piecewise PLS regression method for estimation of stellar parameters, which is composed of one PLS model for Teff, and seven PLS models for log g and [Fe/H] estimation. Its performance is investigated by large experiments on flux calibrated spectra and continuum normalized spectra at different signal-to-noise ratios （SNRs） and resolutions. The results show that the piecewise PLS method is robust for spectra at the medium resolution of 0.23 nm. For low resolution 0.5 nm and 1 nm spectra, it achieves competitive results at higher SNR. Experiments using ELODIE spectra of 0.23 nm resolution illustrate that our piecewise PLS models trained with MILES spectra are efficient for O ～ G stars： for flux calibrated spectra, the systematic offsets are 3.8%, 0.14 dex, and -0.09 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.44 dex and 0.38 dex, respectively; for continuum normalized spectra, the systematic offsets are 3.8%, 0.12dex, and -0.13 dex for Teff, log g and [Fe/H], with error scatters of 5.2%, 0.49 dex and 0.41 dex, respectively. The PLS method is rapid, easy to use and does not rely as strongly on the tightness of a parameter grid of templates to reach high precision as Artificial Neural Networks or minimum distance methods do.

非接触光电测温技术在高炉上的探索及应用

文章介绍了光电测温仪在测量高温时的原理与优势,并根据现场状况进行了改造,使其适应恶劣的环境。