Implementation of a MEIoT Weather Station with Exogenous Disturbance Input.

Due to the emergence of the coronavirus disease (COVID 19), education systems in most countries have adapted and quickly changed their teaching strategy to online teaching. This paper presents the design and implementation of a novel Internet of Things (IoT) device, called MEIoT weather station, which incorporates an exogenous disturbance input, within the National Digital Observatory of Smart Environments (OBNiSE) architecture. The exogenous disturbance input involves a wind blower based on a DC brushless motor. It can be controlled, via Node-RED platform, manually through a sliding bar, or automatically via different predefined profile functions, modifying the wind speed and the wind vane sensor variables. An application to Engineering Education is presented with a case study that includes the instructional design for the least-squares regression topic for linear, quadratic, and cubic approximations within the Educational Mechatronics Conceptual Framework (EMCF) to show the relevance of this proposal. This work's main contribution to the state-of-the-art is to turn a weather monitoring system into a hybrid hands-on learning approach thanks to the integrated exogenous disturbance input.

Agricultural drought early warning from geostationary meteorological satellites: concept and demonstration over semi-arid tract in India.

Remote sensing data from Indian geostationary satellites (Kalapana-1, INSAT 3A) were used for the first time for early warning of agricultural drought and forewarning of crop vigour. An Early warning indicator (EWI) was developed from operational product of rainfall and reference evapotranspiration from observations of Kalpana-1 very high resolution radiometer (VHRR). The effectiveness of EWI was evaluated for the two drought years (2009 and 2012). The positive correlation (r = 0.66-0.68 for 2009 and r = 0.64-0.70 for 2012) between the EWI in the month of June-July and standardized precipitation index-1 (SPI-1) averaged over administrative unit (called district) indicates that EWI can be used successfully for drought early warning. Lag-response behaviour between EWI and crop vigour in terms of normalized difference vegetation index (NDVI) and LAI (leaf area index) over cropland was studied. Systematic patterns emerged for 30 days lag period between negative EWI and NDVI at both grid-scale (0.25°) and at district level. Linear relations were found between 10-day EWI and NDVI or LAI at 30 days lag during June-July period. Linear models were developed to forewarn crop vigour which was validated with realized NDVI from INSAT 3A charge-coupled device (CCD) observations within 95% accuracy. The EWI is recommended as potential indicator for early-season agricultural drought assessment and can be used for sub-district scale with finer scale rainfall and evaporation products from advanced next-generation geostationary meteorological satellites.

Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study.

BACKGROUND: Longitudinal and time series analyses are needed to characterize the associations between hydrometeorological parameters and health outcomes. Earth Observation (EO) climate data products derived from satellites and global model-based reanalysis have the potential to be used as surrogates in situations and locations where weather-station based observations are inadequate or incomplete. However, these products often lack direct evaluation at specific sites of epidemiological interest. METHODS: Standard evaluation metrics of correlation, agreement, bias and error were applied to a set of ten hydrometeorological variables extracted from two quasi-global, commonly used climate data products - the Global Land Data Assimilation System (GLDAS) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) - to evaluate their performance relative to weather-station derived estimates at the specific geographic locations of the eight sites in a multi-site cohort study. These metrics were calculated for both daily estimates and 7-day averages and for a rotavirus-peak-season subset. Then the variables from the two sources were each used as predictors in longitudinal regression models to test their association with rotavirus infection in the cohort after adjusting for covariates. RESULTS: The availability and completeness of station-based validation data varied depending on the variable and study site. The performance of the two gridded climate models varied considerably within the same location and for the same variable across locations, according to different evaluation criteria and for the peak-season compared to the full dataset in ways that showed no obvious pattern. They also differed in the statistical significance of their association with the rotavirus outcome. For some variables, the station-based records showed a strong association while the EO-derived estimates showed none, while for others, the opposite was true. CONCLUSION: Researchers wishing to utilize publicly available climate data - whether EO-derived or station based - are advised to recognize their specific limitations both in the analysis and the interpretation of the results. Epidemiologists engaged in prospective research into environmentally driven diseases should install their own weather monitoring stations at their study sites whenever possible, in order to circumvent the constraints of choosing between distant or incomplete station data or unverified EO estimates.

A mobile system for quantifying the spatial variability of the surface energy balance: design and application.

We present a mobile device for the quantification of the small-scale (a few square meters) spatial variability in the surface energy balance components and several auxiliary variables of short-statured (<1 m) canopies. The key element of the mobile device is a handheld four-component net radiometer for the quantification of net radiation, albedo and infrared surface temperature, which is complemented with measurements of air temperature, wind speed, soil temperature and soil water content. Data are acquired by a battery-powered data logger, which is mounted on a backpack together with the auxiliary sensors. The proposed device was developed to bridge between the spatial scales of satellite/airborne remote sensing and fixed, stationary tower-based measurements with an emphasis on micrometeorological, catchment hydrological and landscape-ecological research questions. The potential of the new device is demonstrated through four selected case studies, which cover the issues of net radiation heterogeneity within the footprint of eddy covariance flux measurements due to (1) land use and (2) slope and aspect of the underlying surface, (3) controls on landscape-scale variability in soil temperature and albedo and (4) the estimation of evapotranspiration based exclusively on measurements with the mobile device.

Commercial microwave links instead of rain gauges: fiction or reality?

Commercial microwave links (MWLs) were suggested about a decade ago as a new source for quantitative precipitation estimates (QPEs). Meanwhile, the theory is well understood and rainfall monitoring with MWLs is on its way to being a mature technology, with several well-documented case studies, which investigate QPEs from multiple MWLs on the mesoscale. However, the potential of MWLs to observe microscale rainfall variability, which is important for urban hydrology, has not been investigated yet. In this paper, we assess the potential of MWLs to capture the spatio-temporal rainfall dynamics over small catchments of a few square kilometres. Specifically, we investigate the influence of different MWL topologies on areal rainfall estimation, which is important for experimental design or to a priori check the feasibility of using MWLs. In a dedicated case study in Prague, Czech Republic, we collected a unique dataset of 14 MWL signals with a temporal resolution of a few seconds and compared the QPEs from the MWLs to reference rainfall from multiple rain gauges. Our results show that, although QPEs from most MWLs are probably positively biased, they capture spatio-temporal rainfall variability on the microscale very well. Thus, they have great potential to improve runoff predictions. This is especially beneficial for heavy rainfall, which is usually decisive for urban drainage design.

A space weather forecasting system with multiple satellites based on a self-recognizing network.

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

Aerodynamic analysis of cup anemometers performance: the stationary harmonic response.

The effect of cup anemometer shape parameters, such as the cups' shape, their size, and their center rotation radius, was experimentally analyzed. This analysis was based on both the calibration constants of the transfer function and the most important harmonic term of the rotor's movement, which due to the cup anemometer design is the third one. This harmonic analysis represents a new approach to study cup anemometer performances. The results clearly showed a good correlation between the average rotational speed of the anemometer's rotor and the mentioned third harmonic term of its movement.

Error in the sampling area of an optical disdrometer: consequences in computing rain variables.

The aim of this study is to improve the estimation of the characteristic uncertainties of optic disdrometers in an attempt to calculate the efficient sampling area according to the size of the drop and to study how this influences the computation of other parameters, taking into account that the real sampling area is always smaller than the nominal area. For large raindrops (a little over 6 mm), the effective sampling area may be half the area indicated by the manufacturer. The error committed in the sampling area is propagated to all the variables depending on this surface, such as the rain intensity and the reflectivity factor. Both variables tend to underestimate the real value if the sampling area is not corrected. For example, the rainfall intensity errors may be up to 50% for large drops, those slightly larger than 6 mm. The same occurs with reflectivity values, which may be up to twice the reflectivity calculated using the uncorrected constant sampling area. The Z-R relationships appear to have little dependence on the sampling area, because both variables depend on it the same way. These results were obtained by studying one particular rain event that occurred on April 16, 2006.

A radiosonde using a humidity sensor array with a platinum resistance heater and multi-sensor data fusion.

This paper describes the design and implementation of a radiosonde which can measure the meteorological temperature, humidity, pressure, and other atmospheric data. The system is composed of a CPU, microwave module, temperature sensor, pressure sensor and humidity sensor array. In order to effectively solve the humidity sensor condensation problem due to the low temperatures in the high altitude environment, a capacitive humidity sensor including four humidity sensors to collect meteorological humidity and a platinum resistance heater was developed using micro-electro-mechanical-system (MEMS) technology. A platinum resistance wire with 99.999% purity and 0.023 mm in diameter was used to obtain the meteorological temperature. A multi-sensor data fusion technique was applied to process the atmospheric data. Static and dynamic experimental results show that the designed humidity sensor with platinum resistance heater can effectively tackle the sensor condensation problem, shorten response times and enhance sensitivity. The humidity sensor array can improve measurement accuracy and obtain a reliable initial meteorological humidity data, while the multi-sensor data fusion technique eliminates the uncertainty in the measurement. The radiosonde can accurately reflect the meteorological changes.

System analysis of a tilted field-widened Michelson interferometer for high spectral resolution lidar.

High spectral resolution lidars (HSRLs) have shown great value in aircraft aerosol remote sensing application and are planned for future satellite missions. A compact, robust, quasi-monolithic tilted field-widened Michelson interferometer is being developed as the spectral discrimination filter for an second-generation HSRL(HSRL-2) at NASA Langley Research Center. The Michelson interferometer consists of a cubic beam splitter, a solid arm and an air arm. Piezo stacks connect the air arm mirror to the body of the interferometer and can tune the interferometer within a small range. The whole interferometer is tilted so that the standard Michelson output and the reflected complementary output can both be obtained. In this paper, the transmission ratio is proposed to evaluate the performance of the spectral filter for HSRL. The transmission ratios over different types of system imperfections, such as cumulative wavefront error, locking error, reflectance of the beam splitter and anti-reflection coatings, system tilt, and depolarization angle are analyzed. The requirements of each imperfection for good interferometer performance are obtained.

Wireless remote weather monitoring system based on MEMS technologies.

This study proposes a wireless remote weather monitoring system based on Micro-Electro-Mechanical Systems (MEMS) and wireless sensor network (WSN) technologies comprising sensors for the measurement of temperature, humidity, pressure, wind speed and direction, integrated on a single chip. The sensing signals are transmitted between the Octopus II-A sensor nodes using WSN technology, following amplification and analog/digital conversion (ADC). Experimental results show that the resistance of the micro temperature sensor increases linearly with input temperature, with an average TCR (temperature coefficient of resistance) value of 8.2 × 10(-4) (°C(-1)). The resistance of the pressure sensor also increases linearly with air pressure, with an average sensitivity value of 3.5 × 10(-2) (Ω/kPa). The sensitivity to humidity increases with ambient temperature due to the effect of temperature on the dielectric constant, which was determined to be 16.9, 21.4, 27.0, and 38.2 (pF/%RH) at 27 °C, 30 °C, 40 °C, and 50 °C, respectively. The velocity of airflow is obtained by summing the variations in resistor response as airflow passed over the sensors providing sensitivity of 4.2 × 10(-2), 9.2 × 10(-2), 9.7 × 10(-2) (Ω/ms(-1)) with power consumption by the heating resistor of 0.2, 0.3, and 0.5 W, respectively. The passage of air across the surface of the flow sensors prompts variations in temperature among each of the sensing resistors. Evaluating these variations in resistance caused by the temperature change enables the measurement of wind direction.

Initial ground-based thermospheric wind measurements using Doppler asymmetric spatial heterodyne spectroscopy (DASH).

We present the first thermospheric wind measurements using a Doppler Asymmetric Spatial Heterodyne (DASH) spectrometer and the oxygen red-line nightglow emission. The ground-based observations were made from Washington, DC and include simultaneous calibration measurements to track and correct instrument drifts. Even though the measurements were made under challenging thermal and light pollution conditions, they are of good quality with photon statistics uncertainties between about three and twenty-nine meters per second, depending on the nightglow intensity. The wind data are commensurate with a representative set of Millstone Hill Fabry-Perot wind measurements selected for similar geomagnetic and solar cycle conditions.

Shade material evaluation using a cattle response model and meteorological instrumentation.

Shade structures are often considered as one method of reducing stress in feedlot cattle. Selection of a suitable shade material can be difficult without data that quantify material effectiveness for stress reduction. A summer study was conducted during 2007 using instrumented shade structures in conjunction with meteorological measurements to estimate relative effectiveness of various shade materials. Shade structures were 3.6 m x 6.0 m x 3.0 m high at the peak and 2.0 m high at the sides. Polyethylene shade cloth was used in three of the comparisons and consisted of effective coverings of 100%, 60% with a silver reflective coating, and 60% black material with no reflective coating. Additionally, one of the structures was fitted with a poly snow fence with an effective shade of about 30%. Each shade structure contained a solar radiation meter and a black globe thermometer to measure radiant energy received under the shade material. Additionally, meteorological data were collected as a non-shaded treatment and included temperature, humidity, wind speed, and solar radiation. Data analyses was conducted using a physiological model based on temperature, humidity, solar radiation and wind speed; a second model using black globe temperatures, relative humidity, and wind speed was used as well. Analyses of the data revealed that time spent in the highest stress category was reduced by all shade materials. Moreover, significant differences (P < 0.05) existed between all shade materials (compared to no-shade) for hourly summaries during peak daylight hours and for 'full sun' days.

Using automated point dendrometers to analyze tropical treeline stem growth at Nevado de Colima, Mexico.

The relationship between wood growth and environmental variability at the tropical treeline of North America was investigated using automated, solar-powered sensors (a meteorological station and two dendrometer clusters) installed on Nevado de Colima, Mexico (19° 35' N, 103° 37' W, 3,760 m a.s.l.). Pure stands of Pinus hartwegii Lindl. (Mexican mountain pine) were targeted because of their suitability for tree-ring analysis in low-latitude, high-elevation, North American Monsoon environments. Stem size and hydroclimatic variables recorded at half-hour intervals were summarized on a daily timescale. Power outages, insect outbreaks, and sensor failures limited the analysis to non-consecutive months during 2001-2003 at one dendrometer site, and during 2002-2005 at the other. Combined data from the two sites showed that maximum radial growth rates occur in late spring (May), as soil temperature increases, and incoming short-wave radiation reaches its highest values. Early season (April-May) radial increment correlated directly with temperature, especially of the soil, and with solar radiation. Stem expansion at the start of the summer monsoon (June-July) was mostly influenced by moisture, and revealed a drought signal, while late season relationships were more varied.