An indigenous state-of-the-art High Wind Speed Recording (HWSR) system for coastal meteorological observatories

The continuous and accurate monitoring of wind speed and direction is of utmost importance to weatherman, particularly during the cyclonic storms. Wind monitoring also helps the meteorologists in tracking the cyclone accurately and estimating their devastating potential. One major disadvantage of all the existing wind monitoring and storing systems is their huge consumption of power, and hence are not suitable during cyclonic storms due to mains power supply failure. So an attempt has been made by the authors to design and develop a low cost, low power, more accurate and maintenance free High Wind Speed Recording (HWSR) System for the coastal meteorological observatories along the East and West Coasts of India. One such system after successful field trials have been installed at Meteorological Office, Puri in the Orissa coast, and 19 more stations are proposed along East and West Coasts of India. The system meets the operational accuracy requirements and vector averaging of wind data as recommended by the World Meteorological Organisation (WMO, 1992). The system design aspects and scope for expansion have been presented in this paper.

Recovery processes in a large offshore wind farm

Wind turbines in a wind farm extract energy from the atmospheric flow and convert it into electricity, resulting in a localized momentum deficit in the wake that reduces energy availability for downwind turbines. Atmospheric momentum convergence from above, below, and the sides into the wakes replenishes the lost momentum, at least partially, so that turbines deep inside a wind farm can continue to function. In this study, we explore recovery processes in a hypothetical offshore wind farm with particular emphasis on comparing the spatial patterns and magnitudes of horizontal- and vertical-recovery processes and understanding the role of mesoscale processes in momentum recovery in wind farms. For this purpose, we use the Weather Research and Forecasting (WRF) model, a state-of-the-art mesoscale model equipped with a wind turbine parameterization, to simulate a hypothetical large offshore wind farm with different wind turbine spacings under realistic initial and boundary conditions. Different inter-turbine spacings range from a densely packed wind farm (case I: low inter-turbine distance of 0.5 km ∼ 5 rotor diameter) to a sparsely packed wind farm (case III: high inter-turbine distance of 2 km ∼ 20 rotor diameter). In this study, apart from the inter-turbine spacings, we also explored the role of different ranges of background wind speeds over which the wind turbines operate, ranging from a low wind speed range of 3–11.75 m s−1 (case A) to a high wind speed range of 11–18 m s−1 (case C). Results show that vertical turbulent transport of momentum from aloft is the main contributor to recovery in wind farms except in cases with high-wind-speed range and sparsely packed wind farms, where horizontal advective momentum transport can also contribute equally. Vertical recovery shows a systematic dependence on wind speed and wind farm density that is quantified using low-order empirical equations. Wind farms significantly alter the mesoscale flow patterns, especially for densely packed wind farms under high-wind-speed conditions. In these cases, the mesoscale circulations created by the wind farms can transport high-momentum air from aloft into the atmospheric boundary layer (ABL) and thus aid in recovery in wind farms. To the best of our knowledge, this is one of the first studies to look at wind farm replenishment processes under realistic meteorological conditions including the role of mesoscale processes. Overall, this study advances our understanding of recovery processes in wind farms and wind farm–ABL interactions.

High Wind Speed Inversion Model of CYGNSS Sea Surface Data Based on Machine Learning

In response to the deficiency of the detection capability of traditional remote sensing means (scatterometer, microwave radiometer, etc.) for high wind speed above 25 m/s, this paper proposes a GNSS-R technique combined with a machine learning method to invert high wind speed at sea surface. The L1-level satellite-based data from the Cyclone Global Navigation Satellite System (CYGNSS), together with the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) data, constitute the original sample set, which is processed and trained with Support Vector Regression (SVR), the combination of Principal Component Analysis (PCA) and SVR (PCA-SVR), and Convolutional Neural Network (CNN) methods, respectively, to finally construct a sea surface high wind speed inversion model. The three models for high wind speed inversion are certified by the test data collected during Typhoon Bavi in 2020. The results show that all three machine learning models can be used for high wind speed inversion on sea surface, among which the CNN method has the highest inversion accuracy with a mean absolute error of 2.71 m/s and a root mean square error of 3.80 m/s. The experimental results largely meet the operational requirements for high wind speed inversion accuracy.

Relationship between Climatic Variables and Reproduction Number (R0) of Confirmed COVID-19 Cases

Most transmittable diseases appear in a specific season and the effect of climate on COVID-19 is of special interest. This study aimed to investigate the relationship between climatic variables and R0 of COVID-19 cases in one hundred areas around the world. The daily confirmed cases COVID-19 and climatic data of each area per day from January 2020 to March 2021 are utilized in the study. The GWR and MLR methods were used to identify the relationship between R0 of COVID-19 cases and climatic variables. The MLR results showed a significant (p-value < 0.05) weak inverse relationship between R0 of COVID-19 cases and wind speed, but a positive significant (p-value < 0.01) relationship with precipitation. It implies that lower COVID-19 cases were recorded with high wind speed and low precipitations. Based on GWR, R0 of COVID-19 infection against principal climatic variables has found statistically significant using Monte Carlo p-value test and the effect of climatic variables on COVID-19 infection appears to vary geographically. However, besides climatic variables, many socio-economic factors could influence the virus transmission and will be considered in future studies.

A Review of Parameterizations for Enthalpy and Momentum Fluxes from Sea Spray in Tropical Cyclones

The intensity of tropical cyclones is sensitive to the air-sea fluxes of enthalpy and momentum. Sea spray plays a critical role in mediating enthalpy and momentum fluxes over the ocean’s surface at high wind speeds, and parameterizing the influence of sea spray is a crucial component of any air-sea interaction scheme used for the high wind regime where sea spray is ubiquitous. Many studies have proposed parameterizations of air-sea flux that incorporate the microphysics of sea spray evaporation and the mechanics of sea spray stress. Unfortunately, there is not yet a consensus on which parameterization best represents air-sea exchange in tropical cyclones, and the different proposed parameterizations can yield substantially different tropical cyclone intensities. This paper seeks to review the developments in parameterizations of the sea spray-mediated enthalpy and momentum fluxes for the high wind speed regime and to synthesize key findings that are common across many investigations.

Development of a Laser Gas Analyzer for Fast CO2 and H2O Flux Measurements Utilizing Derivative Absorption Spectroscopy at a 100 Hz Data Rate

We report the development of a laser gas analyzer that measures gas concentrations at a data rate of 100 Hz. This fast data rate helps eddy covariance calculations for gas fluxes in turbulent high wind speed environments. The laser gas analyzer is based on derivative laser absorption spectroscopy and set for measurements of water vapor (H2O, at wavelength ~1392 nm) and carbon dioxide (CO2, at ~2004 nm). This instrument, in combination with an ultrasonic anemometer, has been tested experimentally in both marine and terrestrial environments. First, we compared the accuracy of results between the laser gas analyzer and a high-quality commercial instrument with a max data rate of 20 Hz. We then analyzed and compared the correlation of H2O flux results at data rates of 100 Hz and 20 Hz in both high and low wind speeds to verify the contribution of high frequency components. The measurement results show that the contribution of 100 Hz data rate to flux calculations is about 11% compared to that measured with 20 Hz data rate, in an environment with wind speed of ~10 m/s. Therefore, it shows that the laser gas analyzer with high detection frequency is more suitable for measurements in high wind speed environments.

COSMO-CLM Russian Arctic hindcast 1980 – 2016: experimental design and first evaluation results

&lt;p&gt;Detailed long-term hydrometeorological dataset for Russian Arctic seas was created using hydrodynamic modelling via regional nonhydrostatic atmospheric model COSMO-CLM for 1980 &amp;#8211; 2016 period with ~12 km grid. Many test experiments with different model options for summertime and wintertime periods were evaluated to determine the best model configuration. Verification has showed that optimal model setup included usage of ERA-Interim reanalysis as forcing data, new model version 5.05 with a so-called ICON-based physics and spectral nudging technique. Final long-term experiments were simulated on the MSU Supercomputer Complex &amp;#8220;Lomonosov-2&amp;#8221; become more than 120 Tb data volume excluding many side files.&lt;/p&gt;&lt;p&gt;Primary evaluation of obtained dataset was done for surface wind and temperature variables. There are some mesoscale details in wind sped climatology reproduced by COSMO-CLM dataset including the Svalbard, Severnaya Zemlya islands, and the western coast of the Novaya Zemlya island. At the same time, high wind speed frequencies based on COSMO-CLM data increased compared to ERA-Interim, especially over Barents Sea, Arctic islands (Novaya Zemlya) and some seacoasts and mainland areas. Regional details are manifested in wind speed increase and marked well for large lakes and orography (Taymyr and Kola peninsulas, Eastern Siberia highlands).&lt;/p&gt;&lt;p&gt;Comparison of two periods (1980 &amp;#173;&amp;#173;&amp;#8211; 1990 and 2010 &amp;#8211; 2016) has shown that spatial distributions of high wind speed frequencies are very similar, but there are some detailed differences. Wind speed frequencies above 20.8 m/s has been decreased in the last decade over the Novaya Zemlya, southwest from Svalbard, middle Siberia inlands; however, it has been increased over Franz Josef Land and Severnaya Zemlya.&lt;/p&gt;&lt;p&gt;Large-scale temperature climatology patterns have shown a good accordance between ERA-Interim and COSMO-CLM datasets. Significant temperature patterns are detailed relief and lakes manifestations, e.g., over Scandinavian mountains, Eastern Siberian and Taymyr highlands, Novaya Zemlya ranges. The added value in the 1% temperature percentile patterns is more pronounced, especially in the mountainous Eastern Siberia. Regional features are prominent over Onega and Ladoga lakes, and western Kara Sea. There is a remarkable warming over islands and Eastern Siberia valleys, and more clear temperature differentiation between ridges and valleys.&lt;/p&gt;&lt;p&gt;The nearest prospect of the COSMO-CLM Russian Arctic dataset application is its comparison with other appropriate datasets including reanalyses, satellite data, observations, etc. This will provide important and useful information about opportunities and restrictions of this dataset regarding different variables and specific regions, outline the limits of its applicability and get framework of possible tasks. The other important task is to share this dataset with scientific community.&lt;/p&gt;

Comparison of wind-induced air pressure fluctuations at sites with different land use

&lt;p&gt;Previous studies showed at a forest site, that small air pressure fluctuations that are generated during periods of high wind speed significantly enhance topsoil gas transport, which is called pressure-pumping. The strength of these air pressure fluctuations can be described by the pressure pumping coefficient (&lt;em&gt;PPC&lt;/em&gt;) which is defined as the mean absolute slope between two measurements (0.5&amp;#160;s) per 30 min interval. It was shown that at this site a quadratic relationship exists between the &lt;em&gt;PPC &lt;/em&gt;and above canopy wind speed.&lt;/p&gt;&lt;p&gt;To investigate the variability of small air pressure fluctuations, high-frequency airflow and air pressure measurements were carried out at ten European and American sites with different land use (grassland, crop, forest, urban). The air pressure fluctuations were generally measured above the soil surface and airflow above the site-specific canopy (above trees in forests, on the top of a high building in the city). The measurements took place between 2016 and 2020 and commonly lasted at least one month per site.&lt;/p&gt;&lt;p&gt;Results show that the site-specific &lt;em&gt;PPC &lt;/em&gt;increases in a quadratic relationship with above-canopy wind speed at all sites. The data was very close to a quadratic relationship at sites with rather uniform forests and level topography (R&amp;#178; &gt; 0.92), while more complex sites revealed a larger scattering of this correlation (R&amp;#178; &gt; 0.65).&lt;/p&gt;&lt;p&gt;At some sites, the &lt;em&gt;PPC &lt;/em&gt;is also highly dependent on the prevailing wind direction. It is shown that the local surface roughness of the plant canopy can be excluded as a main driver of the PPC. Moreover, analysis of surface roughness parameters suggests that the topographic exposure around the measurement sites is responsible for the variability in the &lt;em&gt;PPC&lt;/em&gt;.&lt;/p&gt;&lt;p&gt;However, due to the limited data availability and the complexity of the sites (topography, canopy, buildings), it cannot yet be ruled out that other effects have an influence on the &lt;em&gt;PPC&lt;/em&gt;. In any case, from the results it can be inferred that wind-induced air pressure fluctuations responsible for pressure-pumping are detectable over a variety of natural and artificial surfaces. It must, therefore, be assumed that they have the potential to increase the diffusion-limited transport rate of trace gases in the soil as well as the soil-atmosphere exchange of trace gases over a large number of surfaces during periods of high wind speed.&lt;/p&gt;

A Novel Sea Surface Roughness Parameterization Based on Wave State and Sea Foam

A wave state related sea surface roughness parameterization scheme that takes into account the impact of sea foam is proposed in this study. Using eight observational datasets, the performances of two most widely used wave state related parameterizations are examined under various wave conditions. Based on the different performances of two wave state related parameterizations under different wave state, and by introducing the effect of sea foam, a new sea surface roughness parameterization suitable for low to extreme wind conditions is proposed. The behaviors of drag coefficient predicted by the proposed parameterization match the field and laboratory measurements well. It is shown that the drag coefficient increases with the increasing wind speed under low and moderate wind speed conditions, and then decreases with increasing wind speed, due to the effect of sea foam under high wind speed conditions. The maximum values of the drag coefficient are reached when the 10 m wind speeds are in the range of 30–35 m/s.