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Measurements of downburst outflows using standard meteorological instruments (e.g., anemometers) are rare due to their transient and localized nature. However, video recordings of such events are becoming more frequent. This short communication (Technical Note) study presents a new approach to estimating the kinematics of a downburst event using video footage recordings of the event. The main geometric dimensions of the event, such as downdraft diameter, cloud base height, outflow depth, and the radius of the outflow at a given moment in time, are estimated by sizing them against reference structures of known dimensions that are present in the video footage. From this analysis, and knowing the frame rate of the video recording, one can estimate the characteristic velocities in the downburst event, such as the mean downdraft velocity and the mean velocity of the radial outflow propagation. The proposed method is tested on an August 2015 downburst event that hit Tucson, Arizona, United States. The diameter of the downburst outflow increased with the time from approximately 1.10 km to 3.35 km. This range of values indicates that the event was a microburst. The mean descending velocity of downburst downdraft was 8.9 m s−1 and the horizontal velocity of outflow propagation was 17.7 m s−1. The latter velocity is similar to the measured wind gust at the nearby weather station and Doppler radar. The outflow depth is estimated at 160 m, and the cloud base height was approximately 1.24 km. Estimating the kinematics of downbursts using video footage, while subject to certain limitations, does yield a useful estimation of the main downburst kinematics that contribute to a better quantification of these localized windstorms. [ABSTRACT FROM AUTHOR]

The rapid changes occurring in the polar regions require an improved understanding of the processes that are driving these changes. At the same time, increased human activities such as marine navigation, resource exploitation, aviation, commercial fishing, and tourism require reliable and relevant weather information. One of the primary goals of the World Meteorological Organization's Year of Polar Prediction (YOPP) project is to improve the accuracy of numerical weather prediction (NWP) at high latitudes. During YOPP, two Canadian "supersites" were commissioned and equipped with new ground-based instruments for enhanced meteorological and system process observations. Additional pre-existing supersites in Canada, the United States, Norway, Finland, and Russia also provided data from ongoing long-term observing programs. These supersites collected a wealth of observations that are well suited to address YOPP objectives. In order to increase data useability and station interoperability, novel Merged Observatory Data Files (MODFs) were created for the seven supersites over two Special Observing Periods (February to March 2018 and July to September 2018). All observations collected at the supersites were compiled into this standardized NetCDF MODF format, simplifying the process of conducting pan-Arctic NWP verification and process evaluation studies. This paper describes the seven Arctic YOPP supersites, their instrumentation, data collection and processing methods, the novel MODF format, and examples of the observations contained therein. MODFs comprise the observational contribution to the model intercomparison effort, termed YOPP site Model Intercomparison Project (YOPPsiteMIP). All YOPPsiteMIP MODFs are publicly accessible via the YOPP Data Portal (Whitehorse: 10.21343/a33e-j150, Huang et al., 2023a; Iqaluit: 10.21343/yrnf-ck57, Huang et al., 2023b; Sodankylä: 10.21343/m16p-pq17, O'Connor, 2023; Utqiaġvik: 10.21343/a2dx-nq55, Akish and Morris, 2023c; Tiksi: 10.21343/5bwn-w881, Akish and Morris, 2023b; Ny-Ålesund: 10.21343/y89m-6393, Holt, 2023; and Eureka: 10.21343/r85j-tc61, Akish and Morris, 2023a), which is hosted by MET Norway, with corresponding output from NWP models. [ABSTRACT FROM AUTHOR]

Cyclones tracking northward across the Bay of Bengal represent a significant threat to life and safety when they make landfall. Surface moorings of the Ocean Moored Network for the Northern Indian Ocean in the Bay of Bengal have been deployed to provide real-time observations in support of improved alerts and predictions of cyclones. Engineering goals are both to develop robust surface moorings that survive and to field meteorological and oceanographic instruments that reliably provide data in real time. While the mooring design and reliability were previously reported, the focus here is on the motivations for installing the instrumentation, and on experience gained during the passage of cyclone Amphan in May 2020, examining the sensor as well as mooring performance. The paper presents reasons for fielding the chosen sensors, merits, and shortcomings during the effort to observe Amphan, and recommendations for how to better address the challenges of providing real-time observations of cyclones in the Bay of Bengal. [ABSTRACT FROM AUTHOR]

The complex spatial and temporal structure of cumulus clouds complicates their representation in weather and climate models. Classic meteorological instrumentation struggles to fully capture these features. Networks of multiple high‐resolution hemispheric cameras are increasingly used to fill this data gap, and provide information on this missing multi‐dimensional spatial information. In this study, a path‐tracing algorithm is used to generate virtual camera images of resolved clouds in large‐eddy simulations (LES). These images are then used as a camera network simulator, allowing reconstructions of three‐dimensional cloud edges from the model output. Because the actual LES cloud field is fully known, the combined path‐tracing and reconstruction method can be statistically analyzed. The method is applied to LES realizations of summertime shallow cumulus at the Jülich Observatory for Cloud Evolution (JOYCE), Germany, which also routinely operates a camera network. We find that the path‐tracing method allows accurate reconstruction of up to 70% of the visible cloud edges. Additional sensitivity tests show that the method is robust for changes in its hyperparameters. The sensitivity to cloud optical thickness is also investigated, finding a cloud boundary placement error of approximately 182 m. This error can be considered typical for cloud boundary reconstruction using real stereo camera imagery. The results provide proof of principle for future use of the method for evaluating LES clouds against camera network imagery, and for further optimizing the configuration of such camera networks. Plain Language Summary: We propose an algorithm to make camera images from clouds as simulated on large and fast computers. The algorithm relies on so‐called path‐ or ray‐tracing techniques as often applied in modern gaming or computer‐generated imagery in movies. This method not only yields beautiful cloud visualizations, it also enables the emulation of scientific camera networks such as the one currently operational at the Jülich Observatory of Cloud Evolution (JOYCE) in west Germany. From the images, three‐dimensional structures of the simulated cloud fields can be reconstructed. This technique allows the scientific evaluation of the model clouds against images from real camera networks. This would mean a significant step forward from the use of common vertically pointing meteorological instruments such as lidar or radar. However, before such an effort is undertaken, the accuracy of the method still needs to be determined. For this purpose, the cloud edges, or outer hulls, are reconstructed for selected days in summer. These reconstructed edges are then compared to the original clouds in the simulation. We find that the method satisfactorily reproduces the high‐resolution geometry of clouds, providing proof of principle for this approach and opening a new way of comparing high‐resolution meteorological models with camera measurements. Key Points: Pairs of hemispheric ray‐tracing renderings of shallow cumulus fields in large‐eddy simulations are used to reconstruct cloud boundariesThe method robustly reproduces close to 70% of the visible cloud boundariesThe results provide proof of principle for its use as a stereo camera simulator for evaluating convective clouds in high‐resolution models [ABSTRACT FROM AUTHOR]

Environmental observations are crucial for understanding the state of the environment. However, current observation networks are limited in their spatial and temporal resolution due to high costs. For many applications, data acquisition with a higher resolution would be desirable. Recently, Internet of Things (IoT)-enabled low-cost sensor systems have offered a solution to this problem. While low-cost sensors may have lower quality than sensors in official measuring networks, they can still provide valuable data. This study describes the requirements for such a low-cost sensor system, presents two implementations, and evaluates the quality of the factory calibration for a widely used low-cost precipitation sensor. Here, 20 sensors have been tested for an 8-month period against three reference instruments at the meteorological site of the TU Dresden (Dresden University of Technology). Furthermore, the factory calibration of 66 rain gauges has been evaluated in the lab. Results show that the used sensor falls short for the desired out-of-the-box use case. Nevertheless, it could be shown that the accuracy could be improved by further calibration. [ABSTRACT FROM AUTHOR]

Between the years 1913 to 1914 the De Filippi Expedition, led by the Italian explorer and mountaineer Filippo De Filippi (1869–1938), traversed the Himalayan Range from Kashmir to Baltistan and Xinjiang. Exploring mostly unknown territories, traveling more than 2000 kilometers, and equipped with advanced instruments for geodetic and meteorological measurements, the expedition members surveyed, mapped and collected rocks and fossils including from the remote Aksai Chin region. After almost two years, the expedition returned to Italy, however, publication of the findings was delayed due to the outbreak of the First World War. The fossil material and syntheses of the geology and stratigraphy of the area represented unique documents on this sector of Western Tibet, with the Cretaceous Period being documented by the expedition for the first time in the whole Trans-Himalayan Range. The Aksai Chin region remains poorly explored even today, and the De Filippi collection which is housed in the Natural History Museum of the University of Florence now represents one of the few records available for reconstructing the stratigraphy of the area. It constitutes a valuable resource regarding the history of the scientific exploration and understanding of the geology and paleontology of the region, providing a unique window into a very remote and fascinating part of the world. [ABSTRACT FROM AUTHOR]

The amount and the phase of cold-season precipitation accumulating in the upper Saint John River (SJR) basin are critical factors in determining spring runoff, ice jams, and flooding. To study the impact of winter and spring storms on the snowpack in the upper SJR basin, the Saint John River Experiment on Cold Season Storms (SAJESS) was conducted during winter–spring 2020–2021. Here, we provide an overview of the SAJESS study area, field campaign, and data collected. The upper SJR basin represents 41 % of the entire SJR watershed and encompasses parts of the US state of Maine and the Canadian provinces of Quebec and New Brunswick. In early December 2020, meteorological instruments were co-located with an Environment and Climate Change Canada station near Edmundston, New Brunswick. This included a separate weather station for measuring standard meteorological variables, an optical disdrometer, and a micro rain radar. This instrumentation was augmented during an intensive observation period that also included upper-air soundings, surface weather observations, a multi-angle snowflake camera, and macrophotography of solid hydrometeors throughout March and April 2021. During the study, the region experienced a lower-than-average snowpack that peaked at ∼ 65 cm, with a total of 287 mm of precipitation (liquid-equivalent) falling between December 2020 and April 2021, a 21 % lower amount of precipitation than the climatological normal. Observers were present for 13 storms during which they conducted 183 h of precipitation observations and took more than 4000 images of hydrometeors. The inclusion of local volunteers and schools provided an additional 1700 measurements of precipitation amounts across the area. The resulting datasets are publicly available from the Federated Research Data Repository at 10.20383/103.0591 (Thompson et al., 2023). We also include a synopsis of the data management plan and a brief assessment of the rewards and challenges of conducting the field campaign and utilizing community volunteers for citizen science. [ABSTRACT FROM AUTHOR]

The first long-term rainfall monitoring experiment using the commercial microwave links (CMLs) network in East China is introduced. The network, located in Jiangyin, Jiangsu Province, consists of 49 links with frequencies ranging from 15 GHz to 26 GHz and lengths from 1.14 km to 4.78 km. An OTT PARSIVEL disdrometer is deployed to refine the local rain-induced attenuation relationship, and the CML observations are compared simultaneously with five rain gauges. The inversion parameters of the CML are optimized by minimizing the error of the accumulated rainfall of historical rainfall events. The inversion results show that the daily accumulated rainfall retrieved by the CMLs agrees well with the rain gauge measurements. As an opportunistic approach to monitor near-surface rainfall with high spatiotemporal representativeness and accuracy, the CML network can be used to monitor and forecast urban flood disasters, especially in regions where the widepread deployment of conventional meteorological instruments is impractical. [ABSTRACT FROM AUTHOR]

The quasi-biennial oscillation (QBO) of the stratospheric tropical winds influences the global circulation over a wide range of latitudes and altitudes. Although it has strong effects on surface weather and climate, climate models have great difficulties in simulating a realistic QBO, especially in the lower stratosphere. Therefore, global wind observations in the tropical upper troposphere and lower stratosphere (UTLS) are of particular interest for investigating the QBO and the tropical waves that contribute significantly to its driving. In our work, we focus on the years 2018–2022 and investigate the QBO and different tropical wave modes in the UTLS region using global wind observations made by the Aeolus satellite instrument and three meteorological reanalyses: the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-5), the Japanese 55-year Reanalysis (JRA-55) of the Japan Meteorological Agency (JMA), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Further, we compare these data with observations of selected radiosonde stations. By comparison with Aeolus observations, we find that, on zonal average, the QBO in the lower stratosphere is well represented in all three reanalyses, with ERA-5 performing best. Averaged over the years 2018–2022, agreement between Aeolus and the reanalyses is better than 1 to 2 m s -1 , with somewhat larger differences during some periods. Differently from zonal averages, radiosonde stations provide only local observations and are therefore biased by global-scale tropical waves, which limits their use as a QBO standard. While reanalyses perform well on zonal average, there can be considerable local biases between reanalyses and radiosondes. We also find that, in the tropical UTLS, zonal wind variances of stationary waves and the most prominent global-scale traveling equatorial wave modes, such as Kelvin waves, Rossby-gravity waves, and equatorial Rossby waves, are in good agreement between Aeolus and all three reanalyses (in most cases better than 20 % of the peak values in the UTLS). On zonal average, this supports the use of reanalyses as a reference for comparison with free-running climate models, while locally, certain biases exist, particularly in the QBO wind shear zones and around the 2019–2020 QBO disruption. [ABSTRACT FROM AUTHOR]

High spectral resolution infrared sounders are an integral component of the global observing system and are used in a broad range of applications. This is enabled by their high accuracies which are ensured by rigorous calibration/validation activities. One of these activities is the post‐launch intercomparison with other high spectral resolution infrared sounders using simultaneous nadir overpasses (SNOs). This paper introduces a novel application of the previously developed SNO methodology by including time difference histogram symmetrization and a spatial sampling uncertainty. Where possible, radiometric measurement uncertainties are included and propagated through the statistics. Comparisons of Atmospheric Infrared Sounder (AIRS), METOP‐A/B/C Infrared Atmospheric Sounding Interferometer (IASI), and Cross‐track Infrared Sounder (CrIS) from 1 October 2019, to 1 October 2020, are analyzed. Results show AIRS and IASI differences as well as CrIS and AIRS differences are generally less than 0.4 K across the spectrum, and CrIS and IASI differences are generally less than 0.25 K. Comparison of the Suomi National Polar‐Orbiting Partnership and NOAA‐20 CrIS instruments via IASI and AIRS shows differences are generally less than 0.1 K across all bands and that the two CrIS instruments statistically agree within their radiometric uncertainties except for the narrow 2,370 cm−1 region where artifacts due to brightness temperature conversion are prone to occur. Plain Language Summary: One of the primary sources of information used to monitor Earth's weather patterns are satellite based meteorological instruments that measure radiation in the infrared region with high spectral resolution. Agencies worldwide use data from these types of instruments to provide input into weather prediction models. The long term data sets are also very valuable for multi‐decadal climate studies. To ensure the value of these data, the instruments need to be properly calibrated using external references. This paper details and expands upon the previously established methodology of one commonly used calibration technique—called SNOs. This method compares nadir‐viewing data from different instruments measuring radiation coming from the same mass of atmosphere in time and space. Introduced in this paper are two additions to the methodology: (a) a symmetrization of the time differences between when the instruments measure the specific air mass, and (b) an uncertainty estimate on the comparison based on the spatial coincidence of the measurements. Results from this methodology demonstration show how well the current suite of satellite‐based instrumentation measuring infrared radiation at high spectral resolution agree with each other. Key Points: Simultaneous nadir overpass comparisons include time difference symmetrization, spatial sampling uncertainty, and Cross‐track Infrared Sounder (CrIS) radiometric uncertaintyDifferences between Suomi National Polar‐Orbiting Partnership (SNPP) CrIS and NOAA‐20 CrIS are generally less than 0.1 K and within combined radiometric measurement uncertaintiesDifferences between Atmospheric Infrared Sounder (AIRS) and CrIS or AIRS and Infrared Atmospheric Sounding Interferometer (IASI) generally less than 0.4 K, differences between CrIS and IASI generally less than 0.25 K [ABSTRACT FROM AUTHOR]

Environmental observations are crucial for understanding the state of the environment. However, current observation networks are limited in spatial and temporal resolution due to high costs. For many applications, data acquisition with a higher resolution would be desirable. Recently, Internet of Things (IoT) -enabled low-cost sensor systems offer a solution to this problem. While low-cost sensors may have lower quality than sensors in official measuring networks, they can still provide valuable data. This study describes the requirements for such a low-cost sensor system, presents two implementations, and evaluates the quality of the factory calibration for a widely used low-cost precipitation sensor. Here, twenty sensors have been tested for an 8-month period against three reference instruments at the meteorological site of the TU Dresden. Further, the factory calibration of 66 rain gauges has been evaluated in the lab. Results show that the used sensor falls short for the desired out-of-the-box use case. Nevertheless, it could be shown that the accuracy could be improved by further calibration. [ABSTRACT FROM AUTHOR]

A tunable diode laser absorption spectroscopy (TDLAS) device has been developed to study long-path atmospheric transmission near diode pumped alkali laser (DPAL) emission wavelengths. By employing a single aperture and retro reflector in a mono-static configuration, the noise associated with atmospheric and platform jitter were reduced by a factor of ∼30 and the open-air path length was extended to 4.4 km and over a very broad spectral range, up to 120 cm−1. Water vapor absorption lines near the rubidium (Rb) and cesium (Cs) variants of the DPAL near 795 and 894 nm, oxygen lines near the potassium (K) DPAL near 770 nm, and water vapor absorption in the vicinity of the neodymium-doped yttrium aluminum garnet (Nd:YAG) laser 1.064 μm and chemical oxygen iodine laser (COIL) 1.3 μm lines were studied. The detection limit for path absorbance increases from ΔA = 0.0017 at 100 m path length to 0.085 for the 4.4 km path. Comparison with meteorological instruments for maritime and desert environments yields agreement for the 2.032 km path to within 1.5% for temperature, 4.5% for pressure, and 5.1% for concentration, while agreements for the 4.4 km path are within 1.4% for temperature, 7.7% for pressure, and 23.5% for concentration. An intra cavity output spectroscopy (ICOS) device was also used as a spectral reference to verify location of atmospheric lines. Implications of TDLAS collection system design on signal-to-noise (S/N) are discussed as well as the effect of path turbulence on baseline noise and inform the selection of the DPAL variant least affected by molecular absorption. Graphical Abstract This is a visual representation of the abstract. [ABSTRACT FROM AUTHOR]

A case study of a special event of low‐level windshear and turbulence at the Hong Kong International Airport is performed. The mountainous Lantau Island to the south of the Airport may lead to terrain‐disrupted airflow disturbances in the Airport area in certain wind directions, resulting in low‐level windshear and turbulence to the aircraft. There are a number of novel features in the flow field in the airport region. First, over the seas to the west of the airport, there is sharp convergence between northerly flow and southerly flow within a short distance. Second, in the temperature measurements over this region, there are sharp increases and decreases in temperature. The performance of a high‐resolution numerical weather prediction model in predicting these features is studied. It is shown that, though the model is quite successful in reproducing some features, it may not be able to capture some novel features, such as a sharp rise of temperature and sharp convergence of the airflow. The case study may be a useful reference for aviation weather forecasters and mountain meteorologists. [ABSTRACT FROM AUTHOR]

Abstract A case study of a special event of low‐level windshear and turbulence at the Hong Kong International Airport is performed. The mountainous Lantau Island to the south of the Airport may lead to terrain‐disrupted airflow disturbances in the Airport area in certain wind directions, resulting in low‐level windshear and turbulence to the aircraft. There are a number of novel features in the flow field in the airport region. First, over the seas to the west of the airport, there is sharp convergence between northerly flow and southerly flow within a short distance. Second, in the temperature measurements over this region, there are sharp increases and decreases in temperature. The performance of a high‐resolution numerical weather prediction model in predicting these features is studied. It is shown that, though the model is quite successful in reproducing some features, it may not be able to capture some novel features, such as a sharp rise of temperature and sharp convergence of the airflow. The case study may be a useful reference for aviation weather forecasters and mountain meteorologists.

Since 1987, more than 13 200 rockfalls have been inventoried by the ministère des Transports du Québec (MTQ) as having impacted the national road Route 132 in northern Gaspésie. This natural hazard represents a nearly permanent danger for road users. Traditional mitigation measures can be ineffective on poorly consolidated, deformed and highly fractured rockwalls such as those found in northern Gaspésie. To address this issue, implementing preventive risk management based on the factors that trigger rock instabilities could be the most effective method. Earthquake, rainfall and freeze–thaw cycles are commonly considered to be the main rockfall-triggering factors. This study aims to better understand the climatic conditions conducive to rockfalls in northern Gaspésie in order to provide knowledge to implement an appropriate risk management strategy. Three rockwalls were scanned with terrestrial laser scanning (TLS) instruments during specific pre-targeted weather conditions. Over a period of 18 months, 17 surveys have allowed us to identify 1287 rockfalls with a magnitude above 0.005 m 3 on a scanned surface of 12 056 m 2. In addition, meteorological instruments and a 550 cm thermistor string have been installed directly on a vertical rockwall. It appears that some weather conditions influence the occurrence, frequency and magnitude of rockfalls. In winter, rockfall frequency is 12 times higher during a superficial thaw than during a cold period in which temperature remains below 0 ∘ C. In summer, rockfall frequency is 22 times higher during a heavy rainfall event than during a mainly dry period. Superficial freeze–thaw cycles (< 50 cm) cause mostly a high frequency of small-magnitude events, while deeper spring thaw (> 100 cm) results in a high frequency of large-magnitude events. The influence of weather conditions on rockfall frequency and magnitude is crucial in order to improve risk management, since large-magnitude events represent higher potential hazards. This study provides a classification of weather conditions based on their ability to trigger rockfalls of different magnitudes. This knowledge could be used to implement a risk management strategy. [ABSTRACT FROM AUTHOR]

The determination of Precipitable Water Vapor (PWV) using GNSS data with Precise Point Processing (PPP) is a useful alternative for precisely estimating atmospheric water vapor. The use of GNSS data allows for all-weather PWV tracking 24 h a day, 7 days a week. The weighted mean temperature (Tm) is an important variable in deriving GNSS-PWV values with high accuracy, especially in tropical zones. Unfortunately, the usual method of obtaining Tm is through expensive meteorological instruments such as radiosondes which are not available in every region of Thailand. This current research derives empirical models of Tm based on two data sets: one provided by the Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua platform, and one provided in the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA5 Reanalysis. GNSS-PWV was calculated for 76 GNSS CORS around Thailand using Tm values calculated by the developed models in conjunction with GipsyX software. Results were validated against AIRS-PWV values, and compared against other existing Tm models. Results based on the developed AIRS-Tm and ERA5-Tm models, as well as the existing Suwantong, Bevis, Mendes, Schueler, and GPT3 models, showed mean biases in PWV difference against AIRS-PWV values of 0.3, 0.2, − 0.3, 1.0, 0.8, 1.8, and 1.1 mm, respectively. These results conclude that the mean bias of GPS-PWV estimations can be reduced when a more localized countrywide Tm model is used versus a global model. [ABSTRACT FROM AUTHOR]

An assessment has been made of the correctness of using DS1922L-F5 automatic thermographs and DS1923-F5 thermohygrographs in monitoring air temperature and relative humidity in mountain–depression landscapes by comparing data obtained with loggers and standard psychrometric thermometers installed at the Tunka weather station (Republic of Buryatia). A comparative analysis is carried out using standard statistical methods. It is found that the differences in the readings of the instruments do not exceed the instrumental error of temperature measurement (0.1°C) in 75% of cases and the error in relative humidity measurements (5%) in 98% of cases. In analyzing the daily average values, these ranges increase to 80 and 100%, respectively. The correlation coefficients between data obtained by standard meteorological instruments and compact automatic loggers are higher than 95% both for temperature and for humidity. Based on the results of the study, the conclusion is drawn regarding the correctness of the use of these instruments in microclimate monitoring. Since 2007, air temperature and humidity measurements have been made at 56 model sites synchronously with observations at Roshydromet weather stations. The peculiarities of the temperature regime and the regime of relative humidity of the mountain–depression landscapes of southwestern Cisbaikalia (Tunka and Mondy depressions) are described. Statistically significant differences in air temperatures on the slopes and at the bottom of each of the depressions in individual months and over a year, as well as the differences in the temperature regime between the depressions due to the structure, area, relative height, and depressions coefficient, are shown. In average annual values, the temperature difference between similar landforms in two depressions is about 2°C. The same order of magnitude is shown by the microclimatic differences between the slopes in each of the depressions. [ABSTRACT FROM AUTHOR]

Glacier mass balance is typically estimated using a range of in-situ measurements, remote sensing measurements, and physical and temperature index modelling techniques. With improved data collection and access to large datasets, data-driven techniques have recently gained prominence in modelling natural processes. The most common data-driven techniques used today are linear regression models and, to some extent, non-linear machine learning models such as artificial neural networks. However, the entire host of capabilities of machine learning modelling has not been applied to glacier mass balance modelling. This study used monthly meteorological data from ERA5-Land to drive four machine learning models: random forest (ensemble tree type), gradient-boosted regressor (ensemble tree type), support vector machine (kernel type) and artificial neural networks (neural type). We also use ordinary least squares linear regression as a baseline model against which to compare the performance of the machine learning models. Further, we assess the requirement of data for each of the models and the requirement for hyperparameter tuning. Finally, the importance of each meteorological variable in the mass balance estimation for each of the models is estimated using permutation importance. All machine learning models outperform the linear regression model. The neural network model depicted a low bias, suggesting the possibility of enhanced results in the event of biased input data. However, the ensemble tree-based models, random forest and gradient-boosted regressor outperformed all other models in terms of the evaluation metrics and interpretability of the meteorological variables. The gradient-boosted regression model depicted the best coefficient of determination value of 0.713. The feature importance values associated with all machine learning models suggested high importance to meteorological variables associated with ablation. This is in line with predominantly negative mass balance observations. We conclude that machine learning techniques are promising in estimating glacier mass balance and can incorporate information from more significant meteorological variables as opposed to a simplified set of variables used in temperature index models. [ABSTRACT FROM AUTHOR]

Since the evaporation duct height (EDH) only covers the antenna height of most shipborne microwave radars, mastering the EDH in advance has great significance in achieving long-range target detection. In this paper, a set of hydrological and meteorological sensors based on the gradient meteorological instrument (GMI) were built to monitor the evaporation duct of the South China Sea (SCS). However, the monitoring needed to be interrupted during the battery replacement of the sensor, which could result in the loss of some important data collection. On the basis of the inductively coupled power transfer (ICPT) technology, the resonance principle was used to compensate the inductive reactance on the closed steel ring (CSR), and the energy stored in the super capacitor was introduced for data collection and return. A novel measuring system for the detection of an evaporation duct was proposed. To avoid iterative calculation by setting the initial value of the current evaporation duct models in large-scale and multi time evaporation duct prediction and diagnosis, on the basis of the non-iterative air–sea flux (NAF) model, the EDH was obtained by introducing the K theoretical flux observation method into the atmospheric refractive index equation. Finally, preliminary experimental results are presented for the detection of evaporation duct to demonstrate the feasibility and effectiveness of the proposed system. The communication accuracy rate of the proposed system was 99.7%. The system transmission power reached 22.8 W. The research results of the NAF model adaptability showed that the mean value of the EDH was 8.7 m, which was lower than the mean EDH of the SCS. The EDH calculated by the NAF model in the unstable air–sea stratification state was slightly lower than that calculated by the NPS model. The diagnosis of the EDH by the NAF model was similar to that of the NPS model, but the calculation stability of the NAF model was better. [ABSTRACT FROM AUTHOR]

Seismic stations are increasingly used to monitor river activity and to quantify sediment transport during flood events. In tropical regions, cyclone‐induced floods are often associated with heavy rain and strong wind episodes, generating complex seismic records involving the simultaneous signature of water, sediment, rainfall and wind. Hence, seismic characterization of rain and wind is then required to better decipher each process and improve our understanding of the river seismic signature. In this study, we investigate experimentally the seismic response of rain and wind using data recorded by geophones deployed in various soil types and at different burial depth (BD), co‐located with various meteorological instruments. Our results show that the power spectral density (PSD) of the seismic noise intensifies at a frequency between 60 and 500 Hz for rain and 5 and 500 Hz for wind, in the presence of rain precipitation as low as 0.025 mm/min and/or wind speed ≥3 m/s. PSD analysis indicates that the seismic signal associated with rain decreases with the BD with a value of ∼2–5 dB in a depth difference of 10 cm. We also observe that each soil type has its own seismic signature. The 4‐min root mean square correlation between the seismic signal amplitude and the rain precipitation suggests that they best correlate with Pearson coefficient >0.90 at BD of 30 cm. The transfer function between the precipitation rate (or kinetic energy) and the seismic signal amplitude shows that the signal recorded by the geophone can be used as a robust proxy for these parameters. Plain Language Summary: In addition to recording deep Earth activity such as earthquakes or volcanic eruptions, seismic sensors can measure numbers of naturally‐induced ground vibrations such as those generated by rivers activities. In tropical areas during cyclonic events, heavy rain (and strong wind) leads to the presence of severe flooding, during which several activities in and on the river (e.g., sediment transport, wind, water, and rain) generate ground vibration, making the overall signals recorded by seismic sensors complex to interpret. To better decipher the river seismic signature, investigating the wind and rain signatures are then essential. In this study, we investigate experimentally the seismic response of rain and wind from data recorded by geophones and complemented by different meteorological sensors. The obtained results show that (a) the strength of the seismic noise intensifies with frequency for rain and wind; (b) the seismic signal associated with rain decreases with the burying depth of the sensor; (c) the amplitude of the seismic signal correlates with rain precipitation when the sensor is well buried and (d) the signal recorded by the geophone can be used as a robust proxy for rain precipitation. Key Points: At frequencies >1 Hz different seismic responses overlap in frequency range and the observed spectra represent their cumulative effectsThe rain precipitation and wind intensity are strongly correlated with the seismic noise at frequencies >80 HzDifferent seismic responses are observed according to the soil types the instrument is emplaced in [ABSTRACT FROM AUTHOR]

Wind profiling radars are very useful instruments in meteorological forecasting for evaluating the three dimensional wind velocities. The challenging part of this job is to identify the true Doppler peaks of atmospheric origin from a noisy Doppler profile. This paper presents a novel algorithm for the Doppler peak estimation in windprofilers. The normalized Doppler spectrum of each range bin is divided into multiple clusters and low signal to noise ratio (SNR) clusters are discarded. Then, clusters having no continuity along height axis are filtered out and finally the remaining clusters are interpolated to get the wind profile. The algorithm performs very well even when the signal SNR is consistently below −3 dB over successive range bins. The proposed algorithm is found to have improved performance compared to existing algorithms with a reduced computational time. [ABSTRACT FROM AUTHOR]

• In general aviation, the proportion of fatal go-around accidents has increased. • The timing of the go-around decision in various circumstances needs more training. • Recent training updates have not resulted in better go-around accident statistics. Introduction: Changes in General Aviation (GA) accident rates, specifically in the go-around phase, are examined by comparing the number of accidents, the proportion of fatal accidents, and the proportion of certain causes of accidents over time. Methods: Two sets of accidents from 2000 to 2004 and from 2013 to 2017 were extracted from the National Transportation Safety Board (NTSB) online database. Results: Although the total number of GA accidents per landing significantly decreased over time, the proportion of fatal accidents in the go-around phase increased. Fatalities most often occurred in instrument meteorological conditions. Conclusion: Advances in technology and training show improvements in GA accident rates, but not for accidents in the go-around phase. Practical Applications: Scenario-based learning is recommended to include specific instruction concerning the timing of go-around procedures in unstable flights. [ABSTRACT FROM AUTHOR]

On 15 March 2021, the strongest sandstorm of the last 10 years occurred in China. The MODIS, MPL lidar, EDM 180, ADI 2080 and Meteorological observation instruments were used to observe the dust in Jinan, China, while the HYSPLIT model was also employed to find the source. It was found that the dust originated from Mongolia and the Gobi desert and was transported to Jinan at night on 14th March, lasting until the 18th. Multi-layer dust was observed, of which the dust below the height of 1 km was strongest with the VDR about 0.2 and the maximum extinction coefficient up to 3 km−1. The values of AOD and AE were greater than 2 and less than 0.25, respectively. The mass concentrations of PM10 and PM2.5 increased rapidly, and were up to 573 µg/m3 and 3406 µg/m3, respectively. Additionally, the mass concentration ratio decreased rapidly, with a minimum of 17%. The particle size of the dust was mainly distributed between 0.58–6.50 micros due to larger particles increasing dramatically; simultaneously, both the proportion and the value for calcium ions in PM2.5 went up. The dust had an obvious impact on the vertical structure of the air temperature, resulting in occurrence of a strong inversion layer. [ABSTRACT FROM AUTHOR]

Great advances in meteorological science were made in the late eighteenth century. In particular, meteorological instruments were carried on ships and the first systematic meteorological readings over the oceans were made. One of these collections of instrumental meteorological readings was carried out by the Malaspina expedition (1789-94), organized by the Spanish Crown to study its vast possessions around the world. We have recovered meteorological variables such as air temperature (maximum and minimum), atmospheric pressure (maximum and minimum), wind (intensity and direction), and appearance (state of the sky) from the documentation generated by the explorers during the journey. In total, nearly 13,000 instrumental data have been digitized and rescued from this maritime expedition. The comparison of daily temperature and pressure observations with reanalysis and weather stations data shows a good overall agreement. Moreover, apparent discrepancies during several anchored periods have allowed for testing the consistency and quality of these early instrumental marine weather readings. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) is one of the most important parameters to calculate the crop water demand. The key physical quantity of the water cycle can also pose a great challenge to the water balance for the decision-making on the agricultural water use plan at present. The ET0 in the facilities can be generally estimated by the improved empirical formula with high accuracy. But, much more meteorological parameters are required during estimation. It is prohibitively expensive for the experimental cost of ET0 estimation using measurement instruments for the meteorological parameters in the shading facilities. Alternatively, machine learning can be expected to easily obtain the meteorological parameters outside the facilities. However, only a few studies were focused on the estimation of ET0 in this case. In this study, an efficient and accurate estimation of the ET0 was proposed to clarify the relationship between the meteorological parameters inside and outside of Panax notoginseng shading facility. A Sobol sensitivity analysis was implemented to determine the effective meteorological parameters outside the facility as the model input. A Penman-Monteith model was used to calculate the standard values. Three ET0 estimation models (BO-SVR, BO-RF, and BO-ELM) were established, where the Bayesian Optimization (BO) was used to optimize the parameters in the Support Vector Regression (SVR), Random Forest (RF), and Extreme Learning Machine (ELM). The results showed that there was a strong correlation between six meteorological parameters inside and outside the shading facility, among which the average temperature, the maximum temperature, the minimum temperature, and average relative humidity were significantly correlated, and the coefficient of determination (R2) values were 0.914, 0.721, 0.925 and 0.923, respectively. The radiation term was close to 0 in the shading facility. The ET0 was approximately equal to the aerodynamic term, where the R2, the Root-Mean-Square Error (RMSE), and the Mean Absolute Error (MAE) were 0.999, 0.008 mm/d, and 0.006 mm/d, respectively. There was a strong correlation between the aerodynamic terms inside and outside the shading facility, where the R2, RMSE, and MAE were 0.856, 0.097 mm/d, and 0.073 mm/d, respectively. Therefore, it was feasible to estimate the ET0 in the shading facility of Panax notoginseng using the meteorological factors outside the facility. In Sobol sensitivity analysis, the ET0 in the shading facility was highly sensitive to the average relative humidity, average wind speed, maximum temperature, and average temperature, with the first-order sensitivity coefficients of 0.450, 0.304, 0.064, and 0.026, respectively. There was a small influence of the minimum temperature and sunshine duration on the ET0, where the first-order sensitivity coefficients were less than 0.01. Therefore, an optimal combination of four meteorological parameters was constructed for the improved model. The overall performance of the BO-ELM model in the test accuracy was better than those of the BO-SVR and BO-RF models. The highest accuracy was achieved for the BO-ELM model using the optimal combination of average relative humidity, average wind speed, the maximum temperature, and average temperature, particularly with the R2, RMSE, and MAE of 0.928, 0.069 mm/d, and 0.046 mm/d, respectively. The BO-ELM model was also well adapted to estimate the ET0 in the facility with a small number of meteorological parameters (average relative humidity, and average wind speed), with the R2, RMSE, and MAE of 0.910, 0.078 mm/d, and 0.057 mm/d, respectively. The computational cost of each estimation model was calculated from the parameter tuning time and modeling time of the model. Overall, the BO-SVR and BO-ELM models presented relatively short running time of 0.97 and 2.22 s, respectively. By contrast, the longest running time of 27.46 s was obtained in the BO-RF model. Therefore, the BO-ELM model can be expected to serve as the ET0 estimation in the shading facility in the absence of some meteorological parameters, fully considering the calculation accuracy and cost of the simulation. The findings can also provide an effective way for the estimation of ET0 in the shading facilities. [ABSTRACT FROM AUTHOR]

BACKGROUND: Sightseeing operations are characterized by the presence of passengers as well as favorable light and weather conditions. They include both fixed-wing aircraft and helicopters, an aspect that allows for a comparison of these two types of aircraft in similar operations. METHODS: A total of 95 accident reports from 2008 until 2018 were extracted from the NTSB online database, with each mentioning commercial sightseeing as their operation. RESULTS: O ut of a total of 95 accidents, 16 were fatal with a total of 58 people suffering fatal injuries. On average 3.625 people died in each fatal accident. There were significantly more accidents in Alaska and Hawaii than expected. There were significantly more accidents caused by the maintenance crew in helicopters than in airplanes, but significantly more pilot-related accidents in fixed-wing aircraft compared to helicopters. Despite favorable light and weather conditions, 37 accidents reported the environment as a contributing factor to the accident. CONCLUSION: Sightseeing accidents show a pronounced difference between helicopters and airplane accidents that point to different approaches when improving safety in either category. Although night and instrument meteorological conditions are largely absent in the dataset, wind conditions and unsuitable terrain are frequently mentioned. The experience of the pilots and the specific geography of the sightseeing area are likely to affect operational safety the most. The specific dangers of unsuitable terrain affect both helicopters and fixed-wing operations and may be assuaged by specific training or briefings. [ABSTRACT FROM AUTHOR]

Since 1987, more than 13,200 rockfalls have been inventoried by the Québec Ministry of Transport (MTQ) as having impacted the National Road 132 in northern Gaspésie. This natural hazard represents a nearly permanent danger for users. Traditional mitigation measures can be ineffective on poorly consolidated, deformed and highly fractured rockwall such as those found in northern Gaspésie. To address this issue, implementing a preventive risk management based on the factors that trigger rock instabilities could be the most effective method. Earthquake, rainfall and freeze-thaw cycles are commonly considered to be the main rockfall triggering factors. This study aims to better understand the climatic conditions conducive to rockfalls in northern Gaspésie in order to provide knowledge to implement an appropriate risk management strategy. Three rockwalls were scanned with a terrestrial laser scanner (TLS) during specific pre-targeted weather conditions. Over a period of 18 months, 17 surveys have allowed to identify 1287 rockfalls with a magnitude above 0.005 m2 on a scanned surface of 12 056 m². In addition, meteorological instruments and a 550 cm thermistor string have been installed directly on a vertical rockwall. It appears that some weather conditions influence occurrence, frequency, and magnitude of rockfalls. In winter, rockfall frequency is 12 times higher during a superficial thaw than during a cold period in which temperature remains below 0°C. In summer, rockfall frequency is 22 times higher during a heavy rainfall event than during a period mainly dry. Superficial freeze-thaw cycle (< 50 cm) causes mostly a high frequency of small magnitude events while deeper spring thaw (> 100 cm) results in a high frequency of large magnitude events. Influence of weather conditions on rockfall frequency and magnitude is crucial in order to improve risk management since large magnitude events represent higher potential hazards. This study provides a classification of weather conditions based on their ability to trigger rockfalls of different magnitudes. This knowledge could be used to implement a risk management strategy. [ABSTRACT FROM AUTHOR]

The research presents the inter-comparison of atmospheric variables measured by 9 automatic weather stations. This set of data was compared with the measurements of other weather stations in order to standardize the values that must be adjusted when taken to different areas. The data of a set of a total of 9 GMX500, which measures conventional meteorological variables, and 10 WS100 sensors, which measures precipitation parameters. The automatic stations were set up at the Huancayo Observatory (Geophysical Institute of Peru) for a period of 5 months. The data set of GMX500 were evaluated comparing with the average of the 9 sensors and the WS100 was compared with an optical disdrometer Parsivel 2 . The temperature, pressure, relative humidity, wind speed, rainfall rate, and drop size distribution were evaluated. A pair of GMX500 sensors presented high data dispersion; it was found found that the errors came from a bad configuration; once this problem was solved, good agreement was archived, with low RMSE and high correlation. It was found that the WS100 sensors overestimate the precipitation with a percentage bias close to 100% and the differences increase with the greater intensity of rain. The drop size distribution retrieved by WS100 have unrealistic behavior with higher concentrations in diameters of 1 mm and 5 mm, in addition to a flattened curve. [ABSTRACT FROM AUTHOR]

Weather observing stations are subject to changes in instrumentation, location and surrounding environment over time. Parallel observations between old and new conditions are therefore vital to ensure that a reliable dataset can be built and used for long‐term climate analysis. Here, we examine the world's longest known sets of parallel temperature observations: daily data for Adelaide, South Australia, recorded using two different thermometer screens for 60 years from 1887 to 1947. These data are globally significant for their length and completeness, but the daily observations in the Glaisher stand have only recently been digitized for analysis. We find maximum temperatures recorded in the Glaisher stand are warmer than the Stevenson screen observations, with the difference increasing with absolute temperature, while minimum temperatures recorded in the Glaisher stand are consistently slightly cooler. These differences are similar to those identified using monthly means, as well as other studies of shorter datasets. However, the daily resolution enabled us to identify periods of inconsistent relationships due to changes in observations times (particularly from 1938 onwards), and quantify the differences during extreme events. In particular, percentile analysis revealed that the differences for extremely high temperatures are only slightly greater than the average difference during the warmer months. The data provide an opportunity to attempt the development of 160‐year continuous daily temperature record for one of the oldest colonial cities in the Southern Hemisphere. As expected, we find temperatures in recent decades to be the highest since 1859, although the Glaisher stand maximum temperature data in the 1860s are notably warm, likely due to dry conditions and persistent inhomogeneities. While the relationships we have identified cannot be applied to other 19th century Glaisher stand observations without careful metadata examination, they provide a possible tool for analysis and re‐examination of historical mid‐latitude temperature observations elsewhere around the world. [ABSTRACT FROM AUTHOR]

The closer mast has anemometers at 2m, 5m and 10m above ground and a 10m wind vane, while the further mast has eight anemometers at heights from 0.56m to 6.4m above ground level. One anemometer pulse corresponds to about 0.1m, so the anomalously high gusts of >30ms SP -1 sp (over 20ms SP -1 sp above background wind speed) could result from an entirely plausible incremental pulse rate approaching 200Hz. This extreme gust was apparently confirmed by a similar gust recorded by another anemometer at 2m above ground (Figure 2). This is because, first, the 2m, 5m and 10m anemometers are on a separate and taller mast than the others: the reduced vertical protrusion of the shorter mast results in less electric field enhancement and consequent reduced chance of corona current in the anemometers it carries. [Extracted from the article]

There is considerable import in creating more complete, better understood holdings of early meteorological data. Such data permit an improved understanding of climate variability and long-term changes. Early records are particularly incomplete in the tropics, with implications for estimates of global and regional temperature. There is also a relatively low level of scientific understanding of how these early measurements were made and, as a result, of their homogeneity and comparability to more modern techniques and measurements. Herein we describe and analyse a newly rescued set of long-term, up to six-way parallel measurements undertaken over 1884–1903 in Mauritius, an island situated in the southern Indian Ocean. Data include (i) measurements from a well-ventilated room, (ii) a shaded thermograph, (iii) instruments housed in a manner broadly equivalent to a modern Stevenson screen, (iv) a set of measurements by a hygrometer mounted in a Stevenson screen, and for a much shorter period (v) two additional Stevenson screen configurations. All measurements were undertaken within an ∼ 80 m radius of each other. To our knowledge this is the first such multidecadal multi-instrument assessment of meteorological instrument transition impacts ever undertaken, providing potentially unique insights. The intercomparison also considers the impact of different ways of deriving daily and monthly averages. The long-term comparison is sufficient to robustly characterize systematic offsets between all the instruments and seasonally varying impacts. Differences between all techniques range from tenths of a degree Celsius to more than 1 ∘ C and are considerably larger for maximum and minimum temperatures than for means or averages. Systematic differences of several tenths of a degree Celsius also exist for the different ways of deriving average and mean temperatures. All differences, except two average temperature series pairs, are significant at the 0.01 level using a paired t test. Given that all thermometers were regularly calibrated against a primary Kew standard thermometer maintained by the observatory, this analysis highlights significant impacts of instrument exposure, housing, siting, and measurement practices in early meteorological records. These results reaffirm the importance of thoroughly assessing the homogeneity of early meteorological records. [ABSTRACT FROM AUTHOR]

Natural seeder‐feeder processes play an essential role in the formation and enhancement of precipitation. However, the cloud‐seeding process from mixed‐phase clouds is still not well understood due to the lack of sufficient observations. Natural seeder‐feeder processes from mixed‐phase clouds (seeder clouds) to lower‐lying liquid clouds (feeder clouds) were observed on 19 occasions using ground‐based polarization lidar and radiosonde measurements from June 2018 to June 2020 at a mid‐latitude plain observatory in Wuhan (30.5°N, 114.4°E), China. Ice crystals originating from seeder clouds fell into feeder clouds located 0.2–2.2 km below. During the sedimentation between seeder and feeder clouds, ice crystals partly underwent sublimation when passing through the in‐between dry air layers. The feeder clouds inhibited those ice crystals from complete sublimation and grew them larger by riming or vapor deposition from a favorable liquid water supply. Subsequently, ice crystals were observed afresh falling from feeder clouds, forming ice virgae descending toward the surface. Owing to cloud seeding, feeder clouds with cloud‐top temperatures (CTTs) as warm as −0.2°C to −14.5°C could produce ice virgae, although these CTTs are generally considered somewhat insufficient to initiate primary ice nucleation. The observed optically thin feeder clouds prolonged the survival time/distance of falling ice crystals, indicating that denser feeder clouds may induce enhanced precipitation. Key Points: Natural seeder‐feeder processes from mixed‐phase clouds to lower‐lying liquid clouds were observed at a mid‐latitude plain site in WuhanFeeder clouds inhibited ice crystals from complete sublimation and grew them larger by supplying favorable liquid waterOwing to cloud seeding, feeder clouds with top temperatures as warm as −0.2 to −14.5°C produced ice virgae [ABSTRACT FROM AUTHOR]

Recent interest in quantifying trace gas emissions from point sources, such as measuring methane (CH4) emissions from oil and gas wells, has resulted in several methods being used to estimate emissions from sources with emission rates below 200g CH4 hour-1. The choice of measurement approach depends on how close observers can get to the source, the instruments available and the meteorological/micrometeorological conditions. As such, static chambers, dynamic chambers, HiFlow measurements, Gaussian plume modelling and backward Lagrangian stochastic (bLs) models have all been used, but there is no clear understanding of the accuracy or precision of each method. To address this, we copy the experimental design for each of the measurement methods to make single field measurements of a known source, to simulate single measurement field protocol, and then make repeat measurements to generate an understanding of the accuracy and precision of each method. Here, for comparison, we present estimates for the percentage difference between the measured emission and the known emission, A, and the average percentage difference for three repeat measurements, Ar , for emissions of 200 g CH4 h-1. Our results show that, even though the dynamic chamber repeatedly underestimates the emission, it is the most accurate for a single measurement and the accuracy improves with subsequent measurements (A = -11 %, Ar = -10 %). The single HiFlow emission estimate was also an underestimate, however, poor instrument precision resulted in reduced accuracy of emission estimate to becomes less accurate after repeat measurements (A = -16 %, Ar = -18 %). Of the far field methods, the bLs method underestimated emissions both for single and repeat measurements (A = -11 %, Ar = -7 %) while the GP method significantly overestimated the emissions (A = 33 %, Ar = 29 %) despite using the same meteorological and concentration data as input. Additionally, our results show that the accuracy and precision of the emission estimate increases as the flow rate of the source is increased for all methods. To our knowledge this is the first time that methods for measuring CH4 emissions from point sources less than 200 g CH4 h-1 have been quantitively assessed against a known reference source and each other. [ABSTRACT FROM AUTHOR]

The states of coupling between clouds and surface or boundary layer have been investigated much more extensively for marine stratocumulus clouds than for continental low clouds, partly due to more complex thermodynamic structures over land. A manifestation is a lack of robust remote sensing methods to identify coupled and decoupled clouds over land. Following the idea for determining cloud coupling over the ocean, we have generalized the concept of coupling and decoupling to low clouds over land, based on potential temperature profiles. Furthermore, by using ample measurements from lidar and a suite of surface meteorological instruments at the U.S. Department of Energy's Atmospheric Radiation Measurement Program's Southern Great Plains site from 1998 to 2019, we have developed a method to simultaneously retrieve the planetary boundary layer (PBL) height (PBLH) and coupled states under cloudy conditions during the daytime. The new lidar-based method relies on the PBLH, the lifted condensation level, and the cloud base to diagnose the cloud coupling. The coupled states derived from this method are highly consistent with those derived from radiosondes. Retrieving the PBLH under cloudy conditions, which has been a persistent problem in lidar remote sensing, is resolved in this study. Our method can lead to high-quality retrievals of the PBLH under cloudy conditions and the determination of cloud coupling states. With the new method, we find that coupled clouds are sensitive to changes in the PBL with a strong diurnal cycle, whereas decoupled clouds and the PBL are weakly related. Since coupled and decoupled clouds have distinct features, our new method offers an advanced tool to separately investigate them in climate systems. [ABSTRACT FROM AUTHOR]

The article presents the basic concepts of wind and its characteristics. The methods and the main technical tools for the measurement of wind parameters, including sea conditions were described. Conclusions are drawn on new and promising sensors for use in marine environments.

Introduction. The article reviews the history of the origin and development of meteorological observations in the East of Russia and some Eastern countries of Eurasia. Goals. The paper seeks not just to describe the sequence of events from the history of the development of meteorology as a science in the East, but rather to find patterns that lead to the chain of research on the nature of the region, identify the main stages or periods thereof, consider and clarify the development of meteorology in the East of Russia and Eastern Eurasia. Materials. The work employs a set of complementary research methods, such as theoretical analysis of geographical and historical literature on the problem under consideration; provides insights into archival materials and published sources; conducts comparative analysis of events from the history of the origin and development of meteorological science on the Eastern borders of our country. Conclusions. The study of archival materials and published sources made it possible to determine trends in the development of meteorological research in the region. The article primarily focuses on the influence of the Beijing Magnetic Meteorological and Main Physical Observatories on the emergence and development of the meteorological network of the East.

The paper considers the transition algorithm from incoherent models to partially coherent ones by the example of the problem of synthesizing a two‐dimensional partially coherent model of a distributed radar object by its five‐point and nine‐point incoherent models. The transition algorithm includes the analytical expressions which allow determining powers and correlation functions of emitting signals for both types of models. The result is confirmed by numerical modeling. The comparison of the precision reflection altimeter formation and correlation function of angular glint provided by equivalent incoherent and partially coherent models is carried out. Key Points: Matrix simulatorAngle noisePartially coherent model [ABSTRACT FROM AUTHOR]

INTRODUCTION: Accidents with aircraft standing are more likely with helicopters than fixed-wing aircraft due to the common presence of off-airport landings and the possibility of the rotor system to strike objects in its immediate surroundings. METHODS: A total of 115 accidents involving helicopters characterized as "standing" as a broad phase of flight were selected from the NTSB online database for the period 1998 until 2018. RESULTS: Accidents reporting fatal (8.7%) or serious injuries (7.8%) were significantly less likely to occur when the aircraft was substantially damaged (84.3%) or destroyed (5.2%). The majority of the cases occurred after off-airport landings (57.4%), which were reported significantly more often in Alaska (N= 15). A main rotor strike with an individual was at the basis of each of the 10 fatal accidents in the dataset and in 8 of these cases the cause of the accident was attributed to the victim. None of the accidents occurred in instrument meteorological conditions, but, in particular, high winds and gusts proved a main cause of accident (18.3%). CONCLUSION: Pilot, passengers, and crew endangered themselves when they were outside the aircraft while the rotors were still turning. Helicopter operating manuals should highlight the limitations and dangers for wind and wind gusts not only during takeoff and flight, but specifically when standing. [ABSTRACT FROM AUTHOR]

The National Remote Sensing Centre (NRSC) has established its ground station named Antarctica Ground Station for Earth Observation Satellites (AGEOS) at Bharati station located at Larsemann hills area of Antarctica for the tracking and data acquisition from polar orbiting satellites. A communication link through a geostationary satellite in C-band is being used for transferring data to the mainland. There is a need to enhance the data rate in the near future considering the huge volume of data being acquired at AGEOS. A satellite link operating at Ka-band is proposed for accommodating the bandwidth requirements. It is necessary to estimate the worst case atmospheric attenuation at Ka-band over Larsemann hills area for calculating the link margins required. The India Meteorological Department (IMD) has setup a wide range of meteorological instruments at Bharati station and the local data collected for the years 2020, 2021 and 2022 are used in this study. The link is assumed to operate at a frequency of 20 GHz with linear polarization. An exceedance probability of 0.1% is used to arrive at the annual statistics of the attenuation. Recommendations by the International Telecommunication Union (ITU) are followed and the estimation is carried out using MATLAB. An estimated total atmospheric attenuation of 2.28 dB is obtained. The results are used further for carrying out link budgeting for a Ka-band satellite communication link between Bharati station and India. [ABSTRACT FROM AUTHOR]

Abstract Aircraft can report in situ observations of the ambient temperature by using aircraft meteorological data relay (AMDAR) or these can be derived using mode‐select enhanced tracking data (Mode‐S EHS). These observations may be assimilated into numerical weather prediction models to improve the initial conditions for forecasts. The assimilation process weights the observation according to the expected uncertainty in its measurement and representation. The goal of this paper is to compare observation uncertainties diagnosed from data assimilation statistics with independent estimates. To quantify these independent estimates, we use metrological comparisons, made with in‐situ research‐grade instruments, as well as previous studies using collocation methods between aircraft (mostly AMDAR reports) and other observing systems such as radiosondes. In this study we diagnose a new estimate of the vertical structure of the uncertainty variances using observation‐minus‐background and observation‐minus‐analysis statistics from a Met Office limited area three‐dimensional variational data assimilation system (3 km horizontal grid‐length, 3‐hourly cycle). This approach for uncertainty estimation is simple to compute but has several limitations. Nevertheless, the resulting diagnosed variances have a vertical structure that is like that provided by the independent estimates of uncertainty. This provides confidence in the uncertainty estimation method, and in the diagnosed uncertainty estimates themselves. In the future our methodology, along with other results, could provide ways to estimate the uncertainty for the assimilation of aircraft‐based temperature observations.