Atmospheric Temperature Measurements Research Articles

INNOVATIVE AIRSHIP DESIGN FOR REAL-TIME AIR QUALITY MONITORING USING IOT TECHNOLOGY

The effect of poor air quality on human health has been linked to both short-term and long-term exposure to air pollutants. One of the most important steps in reducing emissions is accurate identification of these pollutants. This can be achieved by using Internet of Things equipped remotely operated airships that can survey large areas and gather pollution data. The ability of an airship to function at low altitudes for extended periods is the main design requirement of airships. This study describes a methodology for conceptualizing and building a helium-filled blimp for remote measurement of atmospheric pollutants (Carbon monoxide, Carbon dioxide, and Sulphur dioxide), temperature, and pressure. An onboard telemetry system measures the data while the airship is in flight and transmits them in real time to a ground-based station. The experiment showed that remotely operated airships are capable of gathering air data and their quality, enabling environmental scientists and regulatory agencies to better understand the behaviour of air pollutants and take steps to mitigate them.

On the рossibility of multichannel optical backscattering sondes for joint balloon and lidar studies of the aerosol composition of the middle atmosphere

Aerosol backscattering sondes in the practice of aerological sounding, along with lidar observations, are used at night to study and monitor polar stratospheric clouds, tropospheric and stratospheric aerosol, cirrus clouds, pyroconvection, volcanic aerosol, as well as to verify remote methods and means of ground-based and satellite-based aerosol observations. For aerosol sondes, a simple two-wave measurement technique is used, which makes it possible to diagnose changes in aerosol composition by color index. The possibilities of the two-wave technique have limitations, which are discussed in this article. Aerological sounding combined with lidar observations expands the wavelength range for multi-wavelength studies, and direct measurements of atmospheric temperature increase the accuracy of aerosol sensing. The paper considers the application of 3 or more wavelenght techniques. Data from probe measurements using wavelengths of 470, 528, 850 and 940 nm and lidar sensing at wavelengths of 355 and 532 nm are presented.

Combined Lidar Signal Registration Technique for Atmospheric Temperature Measurements with the Primary Mirror of the Siberian Lidar Station

Combined Lidar Signal Registration Technique for Atmospheric Temperature Measurements with the Primary Mirror of the Siberian Lidar Station

Atmospheric Temperature Measurements Using Microwave Hyper-Spectrum from Geostationary Satellite: Band Design, Weighting Functions and Information Content

A passive microwave instrument will be carried by China’s geostationary microwave satellite. A microwave hyper-spectral band included by the instrument ranges from 52.6 to 57.3 GHz, and totally has 89 channels in this spectral domain. The design of the hyper-spectral band is described from the aspects of scientific objectives and specifications. The weighting functions for each channel are calculated utilizing radiative transfer simulations under clear sky conditions. Then, the information content as well as the degree of freedom for signal are computed and analyzed to characterize this hyper-spectral sounding for atmospheric temperature profiling. Both the vertical distribution of the weighting functions and the width of retrieval averaging kernels indicate that the hyper-spectral band can provide more denser sampling for atmospheric temperature. The information content for the hyper-spectral band is approximately 46% higher than that of the ATMS-type channel 3 to 15, indicating that hyper-spectral measurement can improve the accuracy of retrieval. The most informative channels mainly locate near 57 GHz, having good consistency with the existing channels. The height range where the retrieval using the hyper-spectral observations is sensitive to the true profile, begins from about 800 to 1 hPa. Some channels can be considered as alternatives to each other since they have very similar information content and weighting functions. These results are expected to provide a valuable reference for future applications of the microwave hyper-spectral measurements.

Correction method for temperature measurements inside clouds using rotational Raman lidar.

Rotational Raman lidar is an important technique for detecting atmospheric temperature. However, in cloud regions with strong elastic scattering conditions, elastic scattering crosstalk (ESC) is prevalent due to insufficient out-of-band suppression of the optical filter, resulting significant deviations in temperature retrieval. To address this challenge, a temperature correction technique for optically-thin clouds based on the backscatter ratio is proposed. Using the least-squares method, a temperature correction function is formulated based on the relationship between the ESC and backscatter ratio of clouds. Subsequently, the backscatter ratio is used to correct the rotational Raman ratio of clouds, thereby obtaining the vertical distribution of atmospheric temperature within the cloud layer. The feasibility of this method was assessed through numerical simulations and experimentally validated using a temperature and aerosol detection lidar at the Xi'an University of Technology (XUT). The results indicate that the difference between the retrieved temperature profile under high signal-to-noise ratio conditions and radiosonde data is less than 1.5 K. This correction technique enables atmospheric temperature measurements under elastic scattering conditions with a backscatter ratio less than 115, advancing research on atmospheric structure and cloud microphysics.

Energy-scaling of a diode-pumped Alexandrite laser and prototype development for a compact general-purpose Doppler lidar.

We present design and performance data of an energy-scaled diode-pumped Alexandrite laser in single longitudinal mode operation developed as a beam source in a mobile general-purpose Doppler lidar. A maximum pulse energy in Q-switched operation of 4.6mJ and a maximum average power of 2.7W were achieved for a repetition rate range from 500 to 750Hz with excellent beam quality of M 2=1.1. Two rugged and compact demonstrator lasers were built and integrated into mobile lidar systems, where a bandwidth of approximately 3MHz is measured. Measurements of atmospheric winds and temperatures were conducted during several field campaigns from summer 2022 to spring 2023.

Lateral scanning Raman scattering lidar for accurate measurement of atmospheric temperature and water vapor from ground to height of interest: publisher's note.

This publisher's note contains corrections to Opt. Lett.48, 2595 (2023).10.1364/OL.488924.

Lateral scanning Raman scattering lidar for accurate measurement of atmospheric temperature and water vapor from ground to height of interest.

A novel lateral scanning Raman scattering lidar (LSRSL) system is proposed, aiming to realize the accurate measurement of atmospheric temperature and water vapor from the ground to a height of interest and to overcome the effect of a geometrical overlap function of backward Raman scattering lidar. A configuration of the bistatic lidar is employed in the design of the LSRSL system, in which four horizontally aligned telescopes mounted on a steerable frame to construct the lateral receiving system are spatially separated to look at a vertical laser beam at a certain distance. Each telescope, combined with a narrowband interference filter, is utilized to detect the lateral scattering signals of the low- and high-quantum-number transitions of the pure rotational Raman scattering spectra and vibrational Raman scattering spectra of N2 and H2O. The profiling of lidar returns in the LSRSL system is performed by the elevation angle scanning of the lateral receiving system, in which the intensities of the lateral Raman scattering signals at each setting of elevation angles are sampled and analyzed. Preliminary experiments are carried out after the construction of a LSRSL system in Xi'an city, whose retrieval results and statistical error analyses present a good performance in the detection of atmospheric temperature and water vapor from the ground to a height of 1.11 km and show the feasibility for combination with backward Raman scattering lidar in atmospheric measurement.

Development of an atmosphere temperature measurement system based on computational fluid dynamics and neural network algorithms

To study the impact of atmospheric temperature on architectural design, energy-saving control systems, and smart home systems, the accuracy of atmospheric temperature measurement systems must be increased by 0.1 °C or higher. However, given that existing temperature measurement systems have difficulty eliminating radiation interference, they may have a radiation error of approximately 1 °C. Therefore, we designed a novel temperature measurement system comprising three sensor probes and a radiation shield. The thin film of the platinum resistance probe was fixed at the center of a spherical copper shell. These plates can prevent all types of radiation from reaching the probe surface. The lower plate could effectively guide the airflow to the sensor probes. The radiation error can be decreased by reducing the radiation interference and increasing the air velocity. The system radiation errors under different environmental conditions were quantified using a computational fluid dynamics (CFD) approach. A neural network algorithm was used to fit the CFD simulation data to form a radiation error correction method with high accuracy and universality. Experiments conducted under different environments revealed that the average radiation error of the system was +0.09 °C. The root mean square error and mean absolute error between the experimental radiation errors and the radiation errors provided by the correction method were +0.037 °C and +0.031 °C, respectively. The correlation coefficient between the temperature of the new system and the reference temperature was 0.999. Our findings suggest that this new system may potentially reduce the radiation error to within 0.1 °C.

Very-long-period oscillations in the atmosphere (0–110 km) – Part 2: Latitude– longitude comparisons and trends

Abstract. Measurements of atmospheric temperatures show a variety of long-term oscillations. These can be simulated by computer models and exhibit multi-annual, decadal, and even centennial periods. They extend from the ground up to the lower thermosphere. Recent analyses have shown that they exist in the models even if the model boundaries are kept constant with respect to influences of the sun, ocean, and greenhouse gases. Therefore, these parameters appear not to be responsible for the excitation of these oscillations, i.e. the oscillations might be rather self-excited. However, influences of land surface and vegetation changes had not been entirely excluded. This is studied in the present analysis. It turns out that such influences might be active in the lowermost atmospheric levels. Long-term trends of atmospheric parameters such as the temperature are important for the understanding of the ongoing climate change. Their study is mostly based on data sets that are 1 to a few decades long. The trend values are generally small and so are the amplitudes of the long-period oscillations. It can therefore be difficult to disentangle these structures, especially if the interval of trend analysis is comparable to the period of the oscillations. If the oscillations are self-excited, there may be a non-anthropogenic contribution to the climate change which is difficult to determine. Long-term changes of the cold-point tropopause are analysed here as an example.

Brillouin shift and temperature measurement by spontaneous Rayleigh‐Brillouin scattering profiles using different models

AbstractSpontaneous Rayleigh‐Brillouin scattering spectra in nitrogen have been measured in the pressure range from 4 to 7 bar at a wide temperature from 291 to 399 K with a scattering angle of about 90°, and then fitted to different theoretical models (S6, V3, and G3). The result of the root‐mean‐square errors of fitting residuals shows that the V3 and G3 models have good fitting performance. However, compared to the predicted Brillouin shift, the maximum relative errors in deducing the Brillouin shift from fitted data are 0.6% for the S6, 3.3% for the V3 and 4.6% the G3 models. The S6 model is the most accurate model in retrieving temperature for the absolute error below 3.5 K while the absolute error is less than 25 K for the V3 model and 35 K for the G3 model. Although the V3 and G3 models may not be suitable for the atmospheric temperature measurement, they are more potential for the high‐temperature measurement of unknown environmental pressures.

An Investigation of the Fengyun-4A/B GIIRS Performance on Temperature and Humidity Retrievals

The Fengyun-4A/B (FY-4A/B) geostationary satellite carries the Geostationary Interferometric Infrared Sounder (GIIRS). The instrument parameters of the GIIRS on FY-4A and FY-4B are not exactly the same, which is crucial for the atmospheric temperature and humidity measurements. The objective of this paper is to discuss the influence of spectral range on the retrieval for the FY-4A/B GIIRS. Firstly, we performed channel selection to choose the appropriate channels for retrieval. Then, the multiple cycling utilization of the physical retrieval method is proposed and conducted for improving the accuracy, and the retrieval results of FY-4A/B GIIRS are compared. Finally, perturbation analysis is performed to discuss the sensitivity of the retrieval to temperature perturbations due to the difference in spectral range between the two GIIRS. The results show the retrieval method can realize the improvement of the average accuracy by more than 0.9 K for temperature and 3.0% for humidity. As the spectral range widens, the retrieval accuracy of FY-4B GIIRS is superior to that of FY-4A GIIRS from 130 hPa to 400 hPa. Furthermore, perturbation analysis also shows the extension of the spectral range is beneficial to the retrieval. This study could offer the usefulness of current GIIRS instruments with observed on-orbit bias, and a reference for the parameter design of the subsequent instruments.

The effect of low temperature on the explosion characteristics of a methane/air mixtures

Prevention and mitigation of unwanted explosions require knowledge of explosion characteristics. Available explosion data are not always adequate for use in a particular application. For example, predicting the behavior of gas explosions at a lower temperature should be based on the explosion data obtained at these temperatures and not atmospheric. Basic knowledge of the methane explosions at low temperatures is desirable for a thorough understanding of this gas that cannot be found in the literature. In the presented research, the methane/air deflagrations were studied in the millisecond time domain. The standard 20-L deflagration chamber was adopted to produce consistent and reproducible data for the comparison of atmospheric and low initial temperature measurements. Methane/air mixtures were studied experimentally for concentrations between 4.6 vol.% and 16.6 vol.% and two initial temperatures of 20 and −5 °C. More than three hundred and fifty pressure–time curves were recorded and analyzed. Twenty-five deflagration curves of the methane/air mixtures were studied in 20-L volume for the first time, including thirteen pressure–time curves at −5 °C. The effects of temperature on the maximum rate of pressure rise and deflagration index were investigated. The evaluated experiments’ results are the maximum pressure rise rate of 261 bar/s at −5 °C. This work allowed potential hazards involving the handling and storing of fuels. Many pieces of knowledge must be collected to advance the phenomenological understanding of low-temperature deflagrations to make realistic theoretical predictions and correlations.

Research on the Measurement Accuracy of Shipborne Rayleigh Scattering Lidar

This paper aims to study the measurement accuracy of Rayleigh scattering lidar (light detection and ranging) based on a ship platform and analyze the influence of the laser beam uncertainty on the temperature inversion results. Taking the ship platform roll data as a reference, the Rayleigh scattering lidar oscillating model is simplified to a sine function, and the inversion accuracy of atmospheric temperature is analyzed under different settled observation angles and different roll angles. When the settled observation angle is 0° and the roll angle amplitudes are 10°, 20°, and 30°, the maximum deviations of the temperature within the height range of 30–80 km are 3.47 K, 13.73 K, and 22.78 K, respectively, and the average deviations are 2.35 K, 9.09 K, and 12.95 K, respectively. When the observation angle is set to 30° and the roll angle amplitudes are 10°, 20°, and 30°, the maximum deviations of the temperature within the height range of 30–80 km are 11.75 K, 27.49 K, and 53.50 K, respectively, and the average deviations are 11.05 K, 13.88 K, and 16.12 K, respectively. The results of this paper show that ship platform rolling greatly influences the measurement of atmospheric temperature, which provides a certain data reference for the construction and use of Rayleigh scattering lidar in the ship platform.

CASPA-ADM: a mission concept for observing thermospheric mass density

Cold Atom technology has undergone rapid development in recent years and has been demonstrated in space in the form of cold atom scientific experiments and technology demonstrators, but has so far not been used as the fundamental sensor technology in a science mission. The European Space Agency therefore funded a 7-month project to define the CASPA-ADM mission concept, which serves to demonstrate cold-atom interferometer (CAI) accelerometer technology in space. To make the mission concept useful beyond the technology demonstration, it aims at providing observations of thermosphere mass density in the altitude region of 300–400 km, which is presently not well covered with observations by other missions. The goal for the accuracy of the thermosphere density observations is 1% of the signal, which will enable the study of gas–surface interactions as well as the observation of atmospheric waves. To reach this accuracy, the CAI accelerometer is complemented with a neutral mass spectrometer, ram wind sensor, and a star sensor. The neutral mass spectrometer data is considered valuable on its own since the last measurements of atmospheric composition and temperature in the targeted altitude range date back to 1980s. A multi-frequency GNSS receiver provides not only precise positions, but also thermosphere density observations with a lower resolution along the orbit, which can be used to validate the CAI accelerometer measurements. In this paper, we provide an overview of the mission concept and its objectives, the orbit selection, and derive first requirements for the scientific payload.

The Challenge of Surface Type Changes Over the Aral Sea for Satellite Remote Sensing of Precipitation

Frequent false signals of precipitation in satellite passive microwave retrievals over the Aral Sea have been identified as being caused by an outdated surface database. The database includes the surface type, elevation, and the percentage of the primary surface type in each grid. It was also found that the grid resolution of 1/6 degree (∼18 km at the equator) of the outdated surface data was too coarse to process Global Precipitation Measurement (GPM) Mission microwave (GMI) imager data, which have a field of view (FOV) resolution of 31.68 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> for channels at 89 GHz, 166.5 GHz and 183.31 GHz). In this study, we generated a new surface database at a resolution of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$0.05^\circ \times 0.05^\circ $</tex-math></inline-formula> (∼5.6 km at the equator). Using the new surface data, the false precipitation problem above is addressed. At the same time, the retrieval accuracy for other parameters such as total precipitable water over the Aral Sea is significantly improved as well. The resolution of the database is suitable for most microwave and infrared sounding measurements of atmospheric temperature and moisture profiles as well as precipitation. By comparing this new surface data against the outdated surface data, we also see the loss of permanent ice in Antarctica and a dramatic reduction of water surface over the Aral Sea. Using a 40-year record of remote sensing data, we can observe the steady decrease in size of the Aral Sea, as a result of regional water use policies and natural climate change.

Modeling cycles and interdependence in irregularly sampled geophysical time series

AbstractWe show how an autoregressive Gaussian process model incorporating a time scale coefficient can be used to represent irregularly sampled geophysical time series. Selection of this coefficient, together with the order of autoregression, provides flexibility of the model appropriate to the structure of the data. This leads to a valuable improvement in the identification of the periodicities within and dependence between such series, which arise frequently and are often acquired at some cost in time and effort. We carefully explain the modeling procedure and demonstrate its efficacy for identifying periodic behavior in the context of an application to dust flux measurements from lake sediments in a region of subtropical eastern Australia. The model is further applied to the measurements of atmospheric carbon dioxide concentrations and temperature obtained from Antarctic ice cores. The model identifies periods in the glacial‐interglacial cycles of these series that are associated with astronomical forcing, determines that they are causally related, and, by application to current measurements, confirms the prediction of climate warming.

Improvement of Working Conditions and Opinions of Mine Workers When Battery Electric Vehicles (BEVs) Are Used Instead of Diesel Machines \u2014 Results of Field Trial at the Kittil\xe4 Mine, Finland

A major part of the European Union’s (EU) project Sustainable Intelligent Mining System (SIMS) is investigating the development of diesel-free/carbon–neutral underground mines in order to ensure sustainable underground mining in the future. Replacing diesel machines with electric vehicles in underground hard rock mines has been widely acknowledged by the mining industry worldwide as a critical step to improve working conditions by reducing diesel exhaust–related contaminants, to reduce mine ventilation electrical power cost by reducing mine airflow quantity, and to reduce mine greenhouse gas emissions. All of these are major requirements to achieve sustainable future underground mining practices. A field trial of Epiroc’s 2nd generation of Battery Electric Vehicles (BEVs) at Agnico Eagle Finland’s Kittilä mine was conducted during 2019–2020. Vehicles tested were MT42 mine truck, ST14 Load-Haul-Dump (LHD), and Boomer E2 jumbo drill rig. This paper outlines the improvement of the working conditions observed in the field trial, and the opinions of the mine personnel at Kittilä mine on using BEVs instead of diesel machines. Measurements of atmospheric contaminants and air temperatures taken during the field trial clearly demonstrated a significant improvement of working conditions when BEVs were operating as opposed to diesel machines. This field observation was supported by the opinion of the majority of the Kittilä mine workers. However, some remaining concerns must be addressed before BEVs can replace diesel machines.

An application of artificial intelligence for investigating the effect of COVID-19 lockdown on three-dimensional temperature variation in equatorial Africa

We present interesting application of artificial intelligence for investigating effect of the COVID-19 lockdown on 3-dimensional temperature variation across Nigeria (2°–15° E, 4°–14° N), in equatorial Africa. Artificial neural networks were trained to learn time-series temperature variation patterns using radio occultation measurements of atmospheric temperature from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC). Data used for training, validation and testing of the neural networks covered period prior to the lockdown. There was also an investigation into the viability of solar activity indicator (represented by the sunspot number) as an input for the process. The results indicated that including the sunspot number as an input for the training did not improve the network prediction accuracy. The trained network was then used to predict values for the lockdown period. Since the network was trained using pre-lockdown dataset, predictions from the network are regarded as expected temperatures, should there have been no lockdown. By comparing with the actual COSMIC measurements during the lockdown period, effects of the lockdown on atmospheric temperatures were deduced. In overall, the mean altitudinal temperatures rose by about 1.1 °C above expected values during the lockdown. An altitudinal breakdown, at 1 km resolution, reveals that the values were typically below 0.5 °C at most of the altitudes, but exceeded 1 °C at 28 and 29 km altitudes. The temperatures were also observed to drop below expected values at altitudes of 0–2 km, and 17–20 km.

Absolute detection of atmospheric temperature by using a scanning Fabry-Pérot interferometer in high spectral resolution lidar

In order to achieve a high signal-to-noise ratio by using small laser energy and telescope aperture, we present a detection method based on Rayleigh-Brillouin scattering (RBS) for the measurement of atmospheric temperature without response functions and calibration procedures by using high spectral resolution lidar (HSRL). Different from the traditional HSRL, a Fabry-Pérot interferometer (FPI) with a continuous tunable cavity and polarization optical scheme are employed in a high spectral resolution filter. In order to continuously change the resonant frequency of the FPI, an electro-optical crystal of potassium dideuterium phosphate (DKDP) with two ring electrodes is used as a continuous tunable cavity in the FPI. At each scanned frequency point corresponded with the resonant frequency of the FPI, the received signals of four discrete points on RBS are obtained. Atmospheric temperature is inverted by using a RBS model. The polarization optical scheme is used to suppress the solar background light, and improve the utilization of return signals. In detection experiment of atmospheric temperature, the detection height is 2 km at night and 1.5 km during the day by using a pulsed energy of 30 mJ and telescope diameter of 250 mm. The results are in good agreement with the data detected by radiosonde.