An automated procedure for forecasting mid- and upper-level turbulence that affects aircraft is described. This procedure, termed the Graphical Turbulence Guidance system, uses output from numerical weather prediction model forecasts to derive many turbulence diagnostics that are combined as a weighted sum with the relative weights computed to give best agreement with the most recent available turbulence observations (i.e., pilot reports of turbulence or PIREPs). This procedure minimizes forecast errors due to uncertainties in individual turbulence diagnostics and their thresholds. Thorough statistical verification studies have been performed that focused on the probabilities of correct detections of yes and no PIREPs by the forecast algorithm. Using these statistics as a guide, the authors have been able to intercompare individual diagnostic performance, and test various diagnostic threshold and weighting strategies. The overall performance of the turbulence forecast and the effect of these strategies on performance are described.

The statistical properties of turbulence at upper levels in the atmosphere [upper troposphere and lower stratosphere (UTLS)] are still not well known, partly because of the lack of adequate routine observations. This is despite the obvious benefit that such observations would have for alerting aircraft of potentially hazardous conditions, either in real time or for route planning. To address this deficiency, a research project sponsored by the Federal Aviation Administration has developed a software package that automatically estimates and reports atmospheric turbulence intensity levels (as EDR ≡ ε1/3, where ε is the energy or eddy dissipation rate). The package has been tested and evaluated on commercial aircraft. The amount of turbulence data gathered from these in situ reports is unprecedented. As of January 2014, there are ~200 aircraft outfitted with this system, contributing to over 137 million archived records of EDR values through 2013, most of which were taken at cruise levels of commercial aircraft, that is, in the UTLS. In this paper, techniques used for estimating EDR are outlined and comparisons with pilot reports from the same or nearby aircraft are presented. These reports allow calibration of EDR in terms of traditionally reported intensity categories (“light,” “moderate,” or “severe”). The results of some statistical analyses of EDR values are also presented. These analyses are restricted to the United States for now, but, as this program is expanded to international carriers, such data will begin to become available over other areas of the globe.

This review paper summarizes current knowledge available for aviation operations related to meteorology and provides suggestions for necessary improvements in the measurement and prediction of weather-related parameters, new physical methods for numerical weather predictions (NWP), and next-generation integrated systems. Severe weather can disrupt aviation operations on the ground or in-flight. The most important parameters related to aviation meteorology are wind and turbulence, fog visibility (Vis) and ceiling, rain and snow amount and rates, icing, ice microphysical parameters, convection and precipitation intensity, microbursts, hail, and lightning. Measurements of these parameters are also functions of sensor response times and measurement thresholds in extreme weather conditions. In addition to these, airport environments can play an important role leading to intensification of extreme weather conditions or high impact weather events, e.g., anthropogenic ice fog. To observe meteorological parameters, new remote sensing platforms, namely wind LIDAR, sodars, radars, and geostationary satellites, and in-situ observations at the surface and in the cloud, as well as aircraft and Unmanned Aerial Vehicles (UAV) mounted sensors, are becoming more common. Because of prediction issues at smaller time and space scales (e.g., <1 km), meteorological forecasts from NWP models need to be continuously improved. Aviation weather forecasts also need to be developed to provide information that represents both deterministic and statistical approaches. In this review, we present available resources and issues for aviation meteorology and evaluate them for required improvements related to measurements, nowcasting, forecasting, and climate change, and emphasize future challenges.