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Turbulence is what we want to avoid the most during flight. Numerical weather prediction (NWP) model–based methods for diagnosing turbulence have offered valuable guidance for pilots. NWP-based turbulence diagnostics show high accuracy in detecting turbulence in general. However, there is still room for improvements such as capturing convectively induced turbulence. In such cases, observation data can be beneficial to correctly locate convective regions and help provide corresponding turbulence information. Geostationary satellite data are commonly used for upper-level turbulence detection by utilizing its water vapor band information. The Geostationary Operational Environmental Satellite (GOES)-16 carries the Advanced Baseline Imager (ABI), which enables us to observe further down into the atmosphere with improved spatial, temporal, and spectral resolutions. Its three water vapor bands allow us to observe different vertical parts of the atmosphere, and from its infrared window bands, convective activity can be inferred. Such multispectral information from ABI can be helpful in inferring turbulence intensity at different vertical levels. This study develops U-Net based machine learning models that take ABI imagery as inputs to estimate turbulence intensity at three vertical levels: 10–18, 18–24, and above 24 kft (1 kft ≈ 300 m). Among six different U-Net-based models, U-Net3+ model with a filter size of three showed the best performance against the pilot report (PIREP). Two case studies are presented to show the strengths and weaknesses of the U-Net3+ model. The results tend to be overestimated above 24 kft, but estimates of 10–18 and 18–24 kft agree well with the PIREP, especially near convective regions. Significance Statement: Turbulence is directly related to aviation safety as well as cost-effective aircraft operation. To avoid turbulence, turbulence diagnostics are calculated from numerical weather prediction (NWP) model outputs and are provided to pilots. The goal of this study is to develop a satellite data–driven machine learning model that estimates turbulence intensity in three different vertical layers to provide additional information along with the NWP-based turbulence diagnostics. Validation results against pilot reports show that the machine learning model performs comparable to NWP-based turbulence diagnostics. Furthermore, results with different channel selections reveal that using multiple water vapor channels can help extract additional information for estimating turbulence intensity at lower levels. [ABSTRACT FROM AUTHOR]

Atmospheric turbulence at commercial aircraft cruising altitudes is a main threat to aviation safety worldwide. As the air transport industry expands and is continuously growing, investigating global response of aviation turbulence under climate change scenarios is required for preparing optimal and safe flying plans for the future. This study examines future frequencies of moderate-or-greater-intensity turbulence generated from various sources, viz., clear-air turbulence and mountain-wave turbulence that are concentrated in midlatitudes, and near-cloud turbulence that is concentrated in tropics and subtropics, using long-term climate model data of high-emissions scenario and historical condition. Here, we show that turbulence generated from all three sources is intensified with higher occurrences globally in changed climate compared to the historical period. Although previous studies have reported intensification of clear-air turbulence in changing climate, implying bumpier flights in the future, we show that intensification of mountain-wave turbulence and near-cloud turbulence can also be expected with changing climate. [ABSTRACT FROM AUTHOR]

Spatial and temporal distributions of Clear‐Air Turbulence (CAT) in the Northern Hemisphere were investigated using 41 years (1979–2019) of the European Centre for Medium‐range Weather Forecast Reanalysis version 5 (ERA5) data. We used two groups of CAT diagnostics to determine occurrence frequencies: (a) commonly used empirical turbulence indices (TI1, TI2, and TI3) and their components [vertical wind shear (VWS), deformation, ‐divergence, and divergence tendency], and (b) theoretical instability indicators [Richardson number (Ri), potential vorticity (PV), and Brunt‐Vӓisӓlӓ frequency]. The empirical indices showed high frequencies of moderate‐or‐greater (MOG)‐level CAT potential over the East Asian, Eastern Pacific, and Northwestern Atlantic regions in winter. Over East Asia, the entrance region of strong upper‐level jets showed the highest frequencies in TI1, TI2, and TI3 due mainly to strong VWS. The Eastern Pacific and Northwestern Atlantic areas near the exit region of jets had relatively high frequencies of these indices and also Ri. PV frequency was high on the southern side of jet primarily due to negative relative vorticity. Long‐term increasing trends of MOG‐level CAT potential also appeared in those three regions mainly due to warming in lower latitudes. The most significant increasing trend was found over East Asia, due to the strengthening of the East Asian jet and increased VWS due to the strong meridional temperature gradients in the mid‐troposphere induced by warming in the tropics and cooling in eastern Eurasia. These trends over East Asia, if continued, are expected to be of importance to efficient aviation operations across the northwestern Pacific Ocean. Plain Language Summary: Strong bumpiness of cruising aircraft can lead to physical injuries for crews and passengers, which is mostly occurred due to atmospheric turbulence by enhanced wind shear near upper‐level jet stream. Spatial characteristics of turbulence and their long‐term trends at cruising altitude in Northern Hemisphere were examined using the up‐to‐date global reanalysis data. The result showed that East Asia, Eastern Pacific, and Northwestern Atlantic regions have a higher frequency of turbulence than other areas. In particular, East Asia was found to be the highest frequency and the largest increasing trend of strong turbulence, which is collocated with a heavy air‐traffic region between East Asia and North America across the North Pacific Ocean. This implies that the potential of encountering turbulence over East Asia could be increased further, if the jet stream will be strengthened continually due to climate change in this region. Key Points: Spatial and temporal distributions of Clear‐Air Turbulence (CAT) indices for 41 years in the Northern Hemisphere are derived using the highest resolution of reanalysis dataThe CAT potentials are high in three regions: the East Asian, Eastern Pacific, and Northwestern Atlantic regions due to upper‐level jetsIncreasing trend of CAT potentials is the largest in East Asia due to warming in tropics and cooling over the Eurasian continent, which have a high impact on transpacific flights [ABSTRACT FROM AUTHOR]

A global Korean deterministic aviation turbulence guidance (G-KTG) system and a global Korean probabilistic turbulence forecast (G-KPT) system are developed using outputs from the operational Global Data Assimilation and Prediction System of the Korea Meteorological Administration, and the performance skill of the systems are evaluated against in situ flight eddy dissipation rates (EDRs) recorded for one year (September 2018–August 2019). G-KTG and G-KPT consider clear-air turbulence (CAT) and mountain wave turbulence diagnostics, while G-KTG additionally considers near-cloud turbulence (NCT) diagnostics. In the G-KTG system, the various combinations of deterministic EDR forecasts are tested by different ensemble means of individual turbulence diagnostics. In the G-KPT system, the probabilistic forecast is established by counting the number of diagnostics that exceed a certain threshold for strong intensity turbulence on the given model grid. The evaluation results of the G-KTG system based on the area under the relative operating characteristic curve (AUC) reveal that G-KTG, which consists of CAT and NCT diagnostics, shows the highest AUC value among the various G-KTG combinations; in addition, the summertime performance is significantly improved when NCT diagnostics are included. In the evaluation results of the G-KTG system over the globe, U.S., and East Asia regions, the recent graphical turbulence guidance system–based G-KTG shows better performance than the regional KTG–based G-KTG for all three regions. For all altitude bands, the G-KPTs with 40% probability as the minimal threshold for alerting forecasters of strong turbulence show higher values of true skill statistic than the G-KTGs. [ABSTRACT FROM AUTHOR]

Based on a convective gravity wave drag parameterization scheme in a numerical weather prediction (NWP) model, previously proposed near-cloud turbulence (NCT) diagnostics for better detecting turbulence near convection are tested and evaluated by using global in situ flight data and outputs from the operational global NWP model of the Korea Meteorological Administration for one year (from December 2016 to November 2017). For comparison, 11 widely used clear air turbulence (CAT) diagnostics currently used in operational NWP-based aviation turbulence forecasting systems are separately computed. For selected cases, NCT diagnostics predict more accurately localized turbulence events over convective regions with better intensity, which is clearly distinguished from the turbulence areas diagnosed by conventional CAT diagnostics that they mostly failed to forecast with broad areas and low magnitudes. Although overall performance of NCT diagnostics for one whole year is lower than conventional CAT diagnostics due to the fact that NCT diagnostics exclusively focus on the isolated NCT events, adding the NCT diagnostics to CAT diagnostics improves the performance of aviation turbulence forecasting. Especially in the summertime, performance in terms of an area under the curve (AUC) based on probability of detection statistics is the best (AUC = 0.837 with a 4% increase, compared to conventional CAT forecasts) when the mean of all CAT and NCT diagnostics is used, while performance in terms of root-mean-square error is the best when the maximum among combined CAT and single NCT diagnostic is used. This implies that including NCT diagnostics to currently used NWP-based aviation turbulence forecasting systems should be beneficial for safety of air travel. [ABSTRACT FROM AUTHOR]

To test more consistent and reliable upper-level turbulence forecasts, seven global numerical weather prediction (NWP) model outputs are used to construct the multimodel-based ensemble forecasts for clear-air turbulence (CAT). We used the updated version of the well-known Ellrod index, the Ellrod–Knox index (EKI), which is currently an operational CAT diagnostic for the significant weather chart at one of the World Area Forecast Centers. In this study, we tested two types of ensemble forecasts. First is an ensemble mean of all EKI forecasts from the NWP models. Second is a probabilistic forecast that is computed by counting how many individual EKI values from the seven NWP models exceed a certain EKI threshold at each grid point. Here, to calibrate the best EKI thresholds for the moderate-or-greater CAT intensity, the individual EKI thresholds, which vary depending on the resolutions and configurations of the NWP models, are selected using the 95th, 98th, and 98th percentiles of the probability density functions for the EKIs derived from the seven NWP models for a 6-month period. Finally, performance skills of both the ensemble mean and probabilistic forecasts are evaluated against the observations of in situ aircraft eddy dissipation rate and pilot reports. As a result, the ensemble mean forecast shows a better performance skill than the individual EKI forecasts. The reliability diagram for the probabilistic forecast gives a better reliability when using high-percentile EKI values as the threshold although it still suffers overestimation of CAT events likely due to the lack of observation and ensemble spreads. [ABSTRACT FROM AUTHOR]

Some of the Aircraft Meteorological Data Relay (AMDAR) data include a turbulence metric of the derived equivalent vertical gust (DEVG), in addition to wind and temperature. As the cube root of the eddy dissipation rate (EDR) is the International Civil Aviation Organization standard turbulence reporting metric, we attempt to retrieve the EDR from the DEVG for more reliable and consistent observations of aviation turbulence globally. Using the DEVG in the AMDAR data archived from October 2015 to September 2018 covering a large portion of the Southern Hemisphere and North Pacific and North Atlantic oceans, we convert the DEVG to the EDR using two methods, after conducting quality control procedures to remove suspicious turbulence reports in the DEVG. The first method remaps the DEVG to the EDR using a lognormal mapping scheme, while the second one uses the best-fit curve between the EDR and DEVG developed in a previous study. The DEVG-derived EDRs obtained from the two methods are evaluated against in situ EDR data reported by US-operated carriers. For two specified regions of the Pacific Ocean and Europe, where both the DEVG-derived EDRs and in situ EDRs were available, the DEVG-derived EDRs obtained by the two methods were generally consistent with in situ EDRs, with slightly better statistics obtained by the first method than the second one. This result is encouraging for extending the aviation turbulence data globally with the single preferred EDR metric, which will contribute to the improvement of global aviation turbulence forecasting as well as to the construction of the climatology of upper-level turbulence. [ABSTRACT FROM AUTHOR]

Spurious mountain-wave features have been reported as false alarms of light-or-stronger numerical weather prediction (NWP)-based cruise level turbulence forecasts especially over the western mountainous region of North America. To reduce this problem, a hybrid sigma–pressure vertical coordinate system was implemented in NOAA's operational Rapid Refresh model, version 4 (RAPv4), which has been running in parallel with the conventional terrain-following coordinate system of RAP version 3 (RAPv3). Direct comparison of vertical velocity |w| fields from the RAPv4 and RAPv3 models shows that the new RAPv4 model significantly reduces small-scale spurious vertical velocities induced by the conventional terrain-following coordinate system in the RAPv3. For aircraft-scale turbulence forecasts, |w| and |w|/Richardson number (|w|/Ri) derived from both the RAPv4 and RAPv3 models are converted into energy dissipation rate (EDR) estimates. Then, those EDR-scaled indices are evaluated using more than 1.2 million in situ EDR turbulence reports from commercial aircraft for 4 months (September–December 2017). Scores of the area under receiver operating characteristic curves for the |w|- and |w|/Ri-based EDR forecasts from the RAPv4 are 0.69 and 0.83, which is statistically significantly improved over the RAPv3 of 0.63 and 0.77, respectively. The new RAPv4 became operational on 12 July 2018 and provides better guidance for operational turbulence forecasting over North America. [ABSTRACT FROM AUTHOR]

Although a terrain-following vertical coordinate is well suited for the application of surface boundary conditions, it is well known that the influences of the terrain on the coordinate surfaces can contribute to increase numerical errors, particularly over steep topography. To reduce these errors, a hybrid sigma–pressure coordinate is formulated in the Weather Research and Forecasting (WRF) Model, and its effects are illustrated for both an idealized test case and a real-data forecast for upper-level turbulence. The idealized test case confirms that with the basic sigma coordinate, significant upper-level disturbances can be produced due to numerical errors that arise as the advection of strong horizontal flow is computed along coordinate surfaces that are perturbed by smaller-scale terrain influences. With the hybrid coordinate, this artificial noise is largely eliminated as the mid- and upper-level coordinate surfaces correspond much more closely to constant pressure surfaces. In real-data simulations for upper-level turbulence forecasting, the WRF Model using the basic sigma coordinate tends to overpredict the strength of upper-air turbulence over mountainous regions because of numerical errors arising as a strong upper-level jet is advected along irregular coordinate surfaces. With the hybrid coordinate, these errors are reduced, resulting in an improved forecast of upper-level turbulence. Analysis of kinetic energy spectra for these simulations confirms that artificial amplitudes in the smaller scales at upper levels that arise with the basic sigma coordinate are effectively removed when the hybrid coordinate is used. [ABSTRACT FROM AUTHOR]

The variation of wind-optimal transatlantic flight routes and their turbulence potential is investigated to understand how upper-level winds and large-scale flow patterns can affect the efficiency and safety of long-haul flights. In this study, the wind-optimal routes (WORs) that minimize the total flight time by considering wind variations are modeled for flights between John F. Kennedy International Airport (JFK) in New York, New York, and Heathrow Airport (LHR) in London, United Kingdom, during two distinct winter periods of abnormally high and low phases of North Atlantic Oscillation (NAO) teleconnection patterns. Eastbound WORs approximate the JFK-LHR great circle (GC) route following northerly shifted jets in the +NAO period. Those WORs deviate southward following southerly shifted jets during the −NAO period, because eastbound WORs fly closely to the prevailing westerly jets to maximize tailwinds. Westbound WORs, however, spread meridionally to avoid the jets near the GC in the +NAO period to minimize headwinds. In the −NAO period, westbound WORs are north of the GC because of the southerly shifted jets. Consequently, eastbound WORs are faster but have higher probabilities of encountering clear-air turbulence than westbound ones, because eastbound WORs are close to the jet streams, especially near the cyclonic shear side of the jets in the northern (southern) part of the GC in the +NAO (−NAO) period. This study suggests how predicted teleconnection weather patterns can be used for long-haul strategic flight planning, ultimately contributing to minimizing aviation's impact on the environment. [ABSTRACT FROM AUTHOR]

At 0300 UTC 9 September 2010, commercial aircraft traveling between Tokyo and Hawaii encountered regions of moderate and severe intensity turbulence at about 12-km elevation in or just above banded structures in the cirrus anvil associated with an oceanic cyclone located off the east coast of Japan. The generation mechanisms of the cirrus bands and turbulence are investigated using the Advanced Research Weather Research and Forecasting Model with five nested domains having a finest horizontal grid spacing of 370 m. The simulation reproduces the satellite-observed patterns of cloud brightness, including the bands, and suggests that synoptic-scale vertical shear within the anvil cloud layer and radiative effects, including longwave cooling at cloud top and warming at cloud base, act together to produce banded structures within the southern edge of the cirrus cloud shield. The character of the bands within the nearly neutral or convectively unstable layer of the cirrus shield is similar to boundary layer rolls in that the vertical wind shear vectors are nearly parallel to the cirrus bands. The strong vertical shear aligned with the banded convection leads to flow deformations and mixing near the cloud top, resulting in localized moderate and severe turbulence. The estimated maximum value of the cube root of eddy dissipation rate within the bands is ~0.7 m2/3 s−1, consistent with severe turbulence levels experienced by large aircraft. [ABSTRACT FROM AUTHOR]

An observed sea fog event over the Eastern Yellow Sea on 15–16 April 2012 was reproduced in the Weather Research and Forecasting (WRF) simulation with high-resolution to investigate the roles of physical processes and synoptic-scale flows on advection fog with phase transition. First, it was verified by a satellite-based fog detection algorithm and in situ observation data. In the simulation, longwave (infrared) radiative cooling (LRC) with a downward turbulent sensible heat flux (SHF), due to the turbulence after sunset, triggered cloud formation over the surface when warm-moist air advection occurred. At night, warm air advection with continuous cooling due to longwave radiation and SHF near the surface modulated the change of the SHF from downward to upward, resulting in a drastic increase in the turbulent latent heat flux (LHF) that provided sufficient moisture at the lower atmosphere (self-moistening). This condition represents a transition from cold-sea fog to warm-sea fog. Enhanced turbulent mixing driven by a buoyancy force increased the depth of the sea fog and the marine atmospheric boundary layer (MABL) height, even at nighttime. In addition, cold air advection with a prevailing northerly wind at the top of the MABL led to a drastic increase in turbulent mixing and the MABL height and rapid growth of the height of sea fog. After sunrise, shortwave radiative warming in the fog layers offsetting the LRC near the surface weakened thermal instability, which contributed to the reduction in the MABL height, even during the daytime. In addition, dry advection of the northerly wind induced dissipation of the fog via evaporation. An additional sensitivity test of sea surface salinity showed weaker and shallower sea fog than the control due to the decrease in both the LHF and local self-moistening. Detailed findings from the simulated fog event can help to provide better guidance for fog detection using remote sensing. [ABSTRACT FROM AUTHOR]

A commercial aircraft, departing from Seoul to Jeju Island in South Korea, encountered a convectively induced turbulence (CIT) at about z = 2.2 km near Seoul on 28 October 2018. At this time, the observed radar reflectivity showed that the convective band with cloud tops of z = 6–7 km passed the CIT region with high values of spectral width (SW; larger than 4 m s–1). Using the 1 Hz wind data recorded by the aircraft, we estimated an objective intensity of the CIT as a cube root of eddy dissipation rate (EDR) based on the inertial range technique, which was about 0.33–0.37 m2/3 s−1. Radar-based EDR was also derived by lognormal mapping technique (LMT), showing that the EDR was about 0.3–0.35 m2/3 s−1 near the CIT location, which is consistent with in situ EDR. In addition, a feasibility of the CIT forecast was tested using the weather and research forecast (WRF) model with a 3 km horizontal grid spacing. The model accurately reproduced the convective band passing the CIT event with an hour delay, which allows the use of two methods to calculate EDR: The first is using both the sub-grid and resolved turbulent kinetic energy to infer the EDR; the second is using the LMT for converting absolute vertical velocity (and its combination with the Richardson number) to EDR-scale. As a result, we found that the model-based EDRs were about 0.3–0.4 m2/3 s−1 near the CIT event, which is consistent with the estimated EDRs from both aircraft and radar observations. [ABSTRACT FROM AUTHOR]