Aerodynamic design, analysis, and validation techniques for the Tianwen-1 entry module

The clear differences between the atmosphere of Mars and the Earth coupled with the lack of a domestic research basis were significant challenges for the aerodynamic prediction and verification of Tianwen-1. In addition, the Mars entry, descent, and landing (EDL) mission led to specific requirements for the accuracy of the aerodynamic deceleration performance, stability, aerothermal heating, and various complex aerodynamic coupling problems of the entry module. This study analyzes the key and difficult aerodynamic and aerothermodynamic problems related to the Mars EDL process. Then, the study process and results of the design and optimization of the entry module configuration are presented along with the calculations and experiments used to obtain the aerodynamic and aerothermodynamic characteristics in the Martian atmosphere. In addition, the simulation and verification of the low-frequency free oscillation characteristics under a large separation flow are described, and some special aerodynamic coupling problems such as the aeroelastic buffeting response of the trim tab are discussed. Finally, the atmospheric parameters and aerodynamic characteristics obtained from the flight data of the Tianwen-1 entry module are compared with the design data. The data obtained from the aerodynamic design, analysis, and verification of the Tianwen-1 entry module all meet the engineering requirements. In particular, the flight data results for the atmospheric parameters, trim angles of attack, and trim axial forces are within the envelopes of the prediction deviation zones.

Monitoring and Predictive Estimations of Atmospheric Parameters in the Catchment Area of Lake Baikal

The paper is concerned with a methodological approach to monitoring the state of atmospheric parameters in the catchment area of Lake Baikal, including real-time analysis of actual distributed data with the determination of analog years according to the preset proximity of comparative indicators and the most probable long-term predictive distributions of surface temperatures, precipitation, pressure, and geopotential with a lead time of up to 9–12 months. We have developed the information-analytical system GeoGIPSAR to conduct the real-time analysis of spatial and point data by various processing methods and obtain long-term prognostic estimates of water inflow into the lake.

Traceable total ozone column retrievals from direct solar spectral irradiance measurements in the ultraviolet

Total column ozone (TCO) is commonly measured by Brewer and Dobson spectroradiometers. Both types of instruments are using four wavelengths in the ultraviolet radiation range to derive TCO. For the calibration and quality assurance of the measured TCO both instrument types require periodic field comparisons with a reference instrument. This study presents traceable TCO retrievals from direct solar spectral irradiance measurements with the portable UV reference instrument QASUME. TCO is retrieved by a spectral fitting technique derived by a minimal least square fit algorithm using spectral measurements in the wavelength range between 305 nm and 345 nm. The retrieval is based on an atmospheric model accounting for different atmospheric parameters such as effective ozone temperature, aerosol optical depth, Rayleigh scattering, SO2, ground air pressure, ozone absorption cross sections and top-of-atmosphere solar spectrum. Traceability means, that the QASUME instrument is fully characterized and calibrated in the laboratory to SI standards (International System of Units). The TCO retrieval method from this instrument is independent from any reference instrument and does not require periodic in situ field calibration. The results show that TCO from QASUME can be retrieved with a relative standard uncertainty of less than 0.8 %, when accounting for all possible uncertainties from the measurements and the retrieval model, such as different cross sections, different reference solar spectra, uncertainties from effective ozone temperature or other atmospheric parameters. The long-term comparison of QASUME TCO with a Brewer and a Dobson in Davos, Switzerland, reveals, that all three instruments are consistent within 1 % when using the ozone absorption cross section from the University of Bremen. From the results and method presented here, other absolute SI calibrated cost effective solar spectroradiometers, such as array spectroradiometers, may be applied for traceable TCO monitoring.

Non-uniformity of the long-term trends in some tropospheic Stratospheric and mesospheric parameters

During the last 3 decades. the concentrations of greenhouse gases have increased monotonically. These are expected to produce warming in the troposphere and cooling at higher altitudes. Expetimental observations of various atmospheric parameters were examined. It was noted that not all parameters showed monotonic trends. In some cases, the trends before and after about 1970-75 were opposite or, the trends developed only after 1970-75. The reason for this transition needs to be explored. A possible cause could be a more rapid increase of CFC concentration in recent years. Also, effect of meteorological fators speciailly sea-surface temperature changes before and after 1975. could be a possible cause though this in turn may be relaled to increasing levels of greenhouse gases.

The Early-type Stars from the LAMOST Survey: Atmospheric Parameters

Massive stars play key roles in many astrophysical processes. Deriving the atmospheric parameters of massive stars is important to understanding their physical properties, and thus the atmospheric parameters are key inputs to trace the evolution of massive stars. Here we report our work on adopting the data-driven technique called stellar label machine (SLAM) with the nonlocal thermal equilibrium TLUSTY synthetic spectra as the training data set to estimate the stellar parameters of Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) optical spectra for early-type stars. We apply two consistency tests to verify this machine-learning method and compare stellar labels given by SLAM with the labels in the literature for several objects having high-resolution spectra. We provide the stellar labels of effective temperature (T eff), surface gravity ( log g ), metallicity ([M/H]), and projected rotational velocity ( v sin i ) for 3931 and 578 early-type stars from the LAMOST low-resolution survey (LRS) and medium-resolution survey (MRS), respectively. To estimate the average statistical uncertainties of our results, we calculated the standard deviation between the predicted stellar label and the prelabeled published values from the high-resolution spectra. The uncertainties of the four parameters are σ(T eff) = 2185 K, σ ( log g ) = 0.29 dex, and σ ( v sin i ) = 11 km s − 1 for MRS, and σ(T eff) = 1642 K, σ ( log g ) = 0.25 dex, and σ ( v sin i ) = 42 km s − 1 for LRS spectra, respectively. We note that the parameters of T eff, log g , and [M/H] can be better constrained using LRS spectra than using MRS spectra, most likely due to their broad wavelength coverage, while v sin i is constrained better by MRS spectra than by LRS spectra, probably due to the relatively accurate line profiles of MRS spectra.

Retrieving exoplanet atmospheric parameters using random forest regression

Understanding of exoplanet atmospheres can be extracted from the transmission spectra using an important tool based on a retrieval technique. However, the traditional retrieval method (e.g. MCMC and nested sampling) consumes a lot of computational time. Therefore, this work aims to apply the random forest regression, one of the supervised machine learning technique, to retrieve exoplanet atmospheric parameters from the transmission spectra observed in the optical wavelength. We discovered that the random forest regressor had the best accuracy in predicting planetary radius ( R F i t 2 = 0.999) as well as acceptable accuracy in predicting planetary mass, temperature, and metallicity of planetary atmosphere. Our results suggested that the random forest regression consumes significantly less computing time while gives the predicted results equivalent to those of the nested sampling PLATON retrieval.

Spectral Characteristics of Solar Radiation in Timisoara, Romania

This study deals with the spectral distribution of solar radiation in Timisoara, Romania. Solar spectrum at the ground level was estimated based on Leckner’s spectral solar irradiance model and measured atmospheric parameters over the years 2019-2020. The average photon energy index (APE) was used to capture the characteristic signature of the solar radiation spectrum. The results emphasize considerable differences between the solar radiation spectrum in Timisoara and the standard AM1.5G spectrum. During 2019-2020, APE has taken values between 1.841 eV and 1.929 eV, indicating both red- and blue-shift from the standard AM1.5G spectrum. To our best knowledge this is the first study which discusses the signature of solar radiation spectrum in terms of APE for a location in Romania.