RESUMEN
This paper introduces a technique to transform between geometric and barometric estimates of altitude and vice-versa. Leveraging forecast numerical weather models, the method is unbiased and has a vertical error with a standard deviation of around 30 m (100 ft), regardless of aircraft altitude, which makes it significantly more precise than established comparable conversion functions. This result may find application in various domains of civil aviation, including vertical RNP, systemized airspace, and automatic landing systems.
Asunto(s)
Aeronaves , Aviación , Altitud , Tiempo (Meteorología)RESUMEN
Oedaleus decorus asiaticus (Bey-Bienko) is a destructive pest in grasslands and adjacent farmland in northern China, Mongolia, and other countries in Asia. It has been supposed that this insect pest can migrate a long distance and then induce huge damages, however, the migration mechanism is still unrevealed. The current study uses insect light trap data from Yanqing (Beijing), together with regional meteorological data to determine how air flow contributes to the long-distance migration of O. decorus asiaticus. Our results indicate that sinking airflow is the main factor leading to the insects' forced landing, and the prevailing northwest wind was associated with O. decorus asiaticus taking off in the northwest and moving southward with the airflow from July to September. Meanwhile, the insects have a strong migratory ability, flying along the airflow for several nights. Thus, when the airflow from the northwest met the northward-moving warm current from the southwest, a large number of insects were dropped due to sinking airflow, resulting in a large outbreak. Our simulations suggest that the source of the grasshoppers involved in these outbreaks during early 2000s in northern China probably is in Mongolia, and all evidence indicates that there are two important immigrant routes for O. decorus asiaticus migration from Mongolia to Beijing. These findings improves our understanding of the factors guiding O. decorus asiaticus migration, providing valuable information to reduce outbreaks in China that have origins from outside the country.
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The correction of tropospheric influences via so-called path delays is critical for the analysis of observations from space geodetic techniques like the very long baseline interferometry (VLBI). In standard VLBI analysis, the a priori slant path delays are determined using the concept of zenith delays, mapping functions and gradients. The a priori use of ray-traced delays, i.e., tropospheric slant path delays determined with the technique of ray-tracing through the meteorological data of numerical weather models (NWM), serves as an alternative way of correcting the influences of the troposphere on the VLBI observations within the analysis. In the presented research, the application of ray-traced delays to the VLBI analysis of sessions in a time span of 16.5 years is investigated. Ray-traced delays have been determined with program RADIATE (see Hofmeister in Ph.D. thesis, Department of Geodesy and Geophysics, Faculty of Mathematics and Geoinformation, Technische Universität Wien. http://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-3444, 2016) utilizing meteorological data provided by NWM of the European Centre for Medium-Range Weather Forecasts (ECMWF). In comparison with a standard VLBI analysis, which includes the tropospheric gradient estimation, the application of the ray-traced delays to an analysis, which uses the same parameterization except for the a priori slant path delay handling and the used wet mapping factors for the zenith wet delay (ZWD) estimation, improves the baseline length repeatability (BLR) at 55.9% of the baselines at sub-mm level. If no tropospheric gradients are estimated within the compared analyses, 90.6% of all baselines benefit from the application of the ray-traced delays, which leads to an average improvement of the BLR of 1 mm. The effects of the ray-traced delays on the terrestrial reference frame are also investigated. A separate assessment of the RADIATE ray-traced delays is carried out by comparison to the ray-traced delays from the National Aeronautics and Space Administration Goddard Space Flight Center (NASA GSFC) (Eriksson and MacMillan in http://lacerta.gsfc.nasa.gov/tropodelays, 2016) with respect to the analysis performances in terms of BLR results. If tropospheric gradient estimation is included in the analysis, 51.3% of the baselines benefit from the RADIATE ray-traced delays at sub-mm difference level. If no tropospheric gradients are estimated within the analysis, the RADIATE ray-traced delays deliver a better BLR at 63% of the baselines compared to the NASA GSFC ray-traced delays.
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A method for predicting canopy wetness and humidity from remotely-acquired meteorological and radiation data is described. This method employs a surface energy balance model to scale from the above-canopy macroclimate to in-canopy microclimate conditions. Above-canopy temperature, vapor pressure, and wind speed inputs were obtained from objective analyses of hourly measurements from the synoptic weather network, while downwelling long- and shortwave radiation forcings were estimated from standard satellite observations. Precipitation (irrigation + rainfall) was the only input acquired in-field. Model predictions compared well with measurements of nighttime dew accumulation and relative humidity made in irrigated potato crops grown in central Wisconsin. Maximum dew amount measured in full canopies over four nights was reproduced to within 0.05 to 0.1 mm. The practical utility of this method to disease management was assessed by processing modeled and measured canopy microclimate data from two weather stations over three growing seasons through the BLITECAST disease forecasting system. Given the uncertainties inherent in the measurement of humidity, the model reasonably reproduced disease severity values generated from in-situ measurements in all but one case, where the canopy had suffered partial defoliation. Because the model simulates the microclimate within a healthy, uniform canopy, it may in many cases produce more reliable regional forecasts for plant disease than would a single set of in-situ measurements.