Aircraft Meteorological Data Relay Research Articles

An Analysis of the Spatial and Temporal Synergy between Profiles of Aircraft-Based Observations and Operational Radiosonde Reports over the United States

Abstract Aircraft-based observations (ABOs) are an important component of the global observation system. Observations of pressure, temperature and wind are obtained from thousands of routine commercial flights daily via the Aircraft Meteorological Data Relay (AMDAR) program, while a subset of approximately 145 aircraft globally (and 135 within the continental United States) also produce observations of water vapor from the Water Vapor Sensing System–II (WVSS–II). Aircraft equipped with WVSS–II provide the basic parameters as radiosonde observations throughout most of the troposphere, often at higher temporal and spatial frequency. Since these aircraft are operated according to the demands of passenger and cargo, the availability of aircraft profiles varies significantly in space and time, with more profiles during daytime and early evening than overnight, more profiles on weekdays than weekends, and more during the summer months. The number of available profiles was significantly impacted by reductions in travel during the Covid-19 pandemic but has recovered substantially. The potential for aircraft profiles to support the operational radiosonde network is explored, including the effect of various spatial and temporal matching criteria. Radiosonde launches at 0000 UTC that are well-aligned with aircraft profiles are found across the continental United States, but well-covered 1200 UTC launches are strongly biased to the east. ABO coverage of asynoptic launch times is also explored. The busiest sites usually have multiple compatible aircraft profiles at both synoptic and asynoptic times. This redundancy lends robustness to the observation network and enables forecasters to monitor atmospheric evolution more continuously throughout the day.

Comparing Quality Control Procedures Based on Minimum Covariance Determinant and One-Class Support Vector Machine Methods of Aircraft Meteorological Data Relay Data Assimilation in a Binary Typhoon Forecasting Case

This study investigates the impact of assimilating Aircraft Meteorological Data Relay (AMDAR) observations on the prediction of two typhoons, Nesat and Haitang (2017), using the Gridpoint Statistical Interpolation (GSI) assimilation system and the Weather Research and Forecasting (WRF) model. Two quality control (QC) methods, Minimum Covariance Determinant (MCD) and one-class Support Vector Machine (OCSVM), were employed to perform QC on the AMDAR observations before data assimilation. The QC results indicated that both methods significantly reduced kurtosis, skewness, and discrepancies between the AMDAR data and the reanalysis data. The data distribution after applying the MCD-QC method exhibited a closer resemblance to a Gaussian distribution. Four numerical experiments were conducted to assess the impact of different AMDAR data qualities on typhoon forecasting, including a control experiment without data assimilation (EXP-CNTL), assimilating all AMDAR observations (EXP-RAW), assimilating observations after applying MCD-QC (EXP-MCD), and assimilating observations after applying OCSVM-QC (EXP-SVM). The results demonstrated that using AMDAR data in assimilation improved the track and intensity prediction of the typhoons. Furthermore, utilizing QC before assimilation enhanced the performance of track forecasting prediction, with EXP-MCD showing the best performance. As for intensity prediction, the three assimilation experiments exhibited varying strengths and weaknesses at different times, with EXP-MCD showing smaller intensity forecast errors on average.

Estimates of the spatially complete, observational-data-driven planetary boundary layer height over the contiguous United States

Abstract. This study aims to generate a spatially complete planetary boundary layer height (PBLH) product over the contiguous United States (CONUS). An eXtreme Gradient Boosting (XGB) regression model was developed using selected meteorological and geographical data fields as explanatory variables to fit the PBLH values derived from Aircraft Meteorological DAta Relay (AMDAR) reports hourly profiles at 13:00–14:00 LST (local solar time) during 2005–2019. A preprocessing step was implemented to exclude AMDAR data points that were unexplainable by the predictors, mostly under stable conditions. The PBLH prediction by this work as well as PBLHs from three reanalysis datasets (the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate – ERA5; the Modern-Era Retrospective analysis for Research and Applications, Version 2 – MERRA-2; and the North American Regional Reanalysis – NARR) were compared to reference PBLH observations from spaceborne lidar (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations, CALIPSO), airborne lidar (High Spectral Resolution Lidar, HSRL), and in situ research aircraft profiles from the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaigns. Compared with PBLHs from reanalysis products, the PBLH prediction from this work shows closer agreement with the reference observations, with the caveat that different PBLH products and estimates have different ways of identifying the PBLH; thus, their comparisons should be interpreted with caution. The reanalysis products show significant high biases in the western CONUS relative to the reference observations. One direct application of the dataset generated by this work is that it enables sampling of the PBLH at the sounding locations and times of sensors aboard satellites with an overpass time in the early afternoon, e.g., the Afternoon Train (A-train), the Suomi National Polar-orbiting Partnership (Suomi NPP), the Joint Polar Satellite System (JPSS), and the Sentinel-5 Precursor (Sentinel-5P) satellite sensors. As both AMDAR and ERA5 are continuous at hourly resolution, the observational-data-driven PBLHs may be extended to other daytime hours.

Morning Transition of the Boundary Layer over Dallas–Fort Worth

Abstract Temperature profiles of the lower atmosphere (<3 km) over complex urban areas are related to health risks, including heat stress and respiratory illness. This complexity leads to uncertainty in numerical simulations, and many studies call for more observations of the lower atmosphere over cities. Using 20 years of observations from the Aircraft Meteorological Data Relay (AMDAR) program over Dallas–Fort Worth, Texas, average profiles every 0.5 h are created from the 1.5 million individual soundings. Dallas–Fort Worth is ideal because it is a large urban area in the central Great Plains, has no major topographic or coastal influences, and has two major airports near the center of the urban heat island. With frequent and high-quality measurements over the city, we investigate the evolution of the lower atmosphere around sunrise to quantify the stability, boundary layer height, and duration of the morning transition when there are southerly winds, few clouds, and no precipitation so as to eliminate transient synoptic events. Characteristics of the lower atmosphere are separated by season and maximum wind speed because the the Great Plains low-level jet contributes to day-to-day variability. In all seasons, stronger wind over the city leads to a weaker nocturnal temperature inversion at sunrise and a shorter morning transition period, with the greatest difference during autumn and the smallest difference during summer. During summer, the boundary layer height at sunrise is higher on average, deepens the most as wind strengthens, and has the fewest days exhibiting a surface temperature inversion over the city. Significance Statement Cities impact health by creating an urban heat island caused by more heating at the surface, less evaporative cooling, and increased anthropogenic waste heat, and they can have high pollution. Cooling overnight stabilizes the lower atmosphere and traps pollutants near the surface until surface heating after sunrise mixes them away. Inadequate pollution observations make it difficult to study these issues. The greatest mixing occurs about 2 h after sunrise but can be modulated by wind speed. Observations from 1.5 million aircraft landing and taking off over Dallas–Fort Worth, Texas, reveal that strong low-level wind leads to morning transitions ending 0.84 h earlier on average than with light wind. Details from this vast dataset contribute to improved understanding of the lower atmosphere over cities and provide a baseline for simulations.

Characterizing and correcting the warm bias observed in Aircraft Meteorological Data Relay (AMDAR) temperature observations

Abstract. Some aircraft temperature observations, retrieved through the Aircraft Meteorological Data Relay (AMDAR), suffer from a significant warm bias when comparing observations with numerical weather prediction (NWP) models. In this paper we show that this warm bias of AMDAR temperature can be characterized and consequently reduced substantially. The characterization of this warm bias is based on the methodology of measuring temperature with a moving sensor and can be split into two separate processes. The first process depends on the flight phase of the aircraft and relates to difference of timing, as it appears that the times of measurement of altitude and temperature differ. When an aircraft is ascending or descending, this will result in a small bias in temperature due to the (on average) presence of an atmospheric temperature lapse rate. The second process is related to internal corrections applied to pressure altitude without feedback to temperature observation measurement. Based on NWP model temperature data, combined with additional information on Mach number and true airspeed, we were able to estimate corrections using data over an 18-month period from January 2017 to July 2018. Next, the corrections were applied to AMDAR observations over the period from September 2018 to mid-December 2019. Comparing these corrected temperatures with (independent) radiosonde temperature observations demonstrates a reduction of the temperature bias from 0.5 K to around zero and a reduction of standard deviation of almost 10 %.

Using Commercial Aircraft Meteorological Data to Assess the Heat Budget of the Convective Boundary Layer Over the Santiago Valley in Central Chile

The World Meteorological Organization Aircraft Meteorological Data Relay (AMDAR) programme refers to meteorological data gathered by commercial aircraft and made available to weather services. It has become a major source of upper-air observations whose assimilation into global models has greatly improved their performance. Near busy airports, AMDAR data generate semi-continuous vertical profiles of temperature and winds, which have been utilized to produce climatologies of atmospheric-boundary-layer (ABL) heights and general characterizations of specific cases. We analyze 2017–2019 AMDAR data for Santiago airport, located in the centre of a 40times 100 km^2 subtropical semi-arid valley in central Chile, at the foothills of the Andes. Profiles derived from AMDAR data are characterized and validated against occasional radiosondes launched in the valley and compared with routine operational radiosondes and with reanalysis data. The cold-season climatology of AMDAR temperatures reveals a deep nocturnal inversion reaching up to 700 m above ground level (a.g.l.) and daytime warming extending up to 1000 m a.g.l. Convective-boundary-layer (CBL) heights are estimated based on AMDAR profiles and the daytime heat budget of the CBL is assessed. The CBL warming variability is well explained by the surface sensible heat flux estimated with sonic anemometer measurements at one site, provided advection of the cool coastal ABL existing to the west is included. However, the CBL warming accounts for just half of the mean daytime warming of the lower troposphere, suggesting that rather intense climatological diurnal subsidence affects the dynamics of the daytime valley ABL. Possible sources of this subsidence are discussed.

Examining the Compatibility of Aircraft Moisture Observations and Operational Radiosondes

AbstractThe addition of moisture observations via the Water Vapor Sensing System (WVSS) from about 150 aircraft available operationally through the World Meteorological Organization (WMO) Aircraft Meteorological Data Relay (AMDAR) program now provides highly reliable thermodynamic profiles of the troposphere. The nearly 900 profiles available daily provide greater temporal and spatial density than the operational radiosonde network over many parts of the United States. Previous studies comparing WVSS reports with specially collocated radiosondes have documented the quality and consistency of the WVSS observations. These studies, however, have been limited for short periods at a single location. This study expands on the earlier evaluations by using operational U.S. radiosondes from 2015 in a variety of locations, seasons, and climates. Comparison profiles at radiosonde sites were calculated in pressure layers and then interpolated to terrain-following sigma coordinates to account for the differences in elevations of comparison sites and provide a better means of integrating the higher vertical resolution of AMDAR observations taken in the boundary layer. Overall, systematic differences between the WVSS and radiosondes are smallest just above the surface, with the WVSS observations being slightly moister than the radiosondes aloft, with WVSS reports being moister during ascent than descent—possibly the result of small hysteresis effects. Standard deviations averaged 1.3 g kg−1 near the surface over the yearlong period. Differences varied by season and region. Overall, the results indicate that WVSS observations are compatible with radiosonde reports and can be used with high confidence to fill temporal and spatial data gaps.

Comparing diagnosed observation uncertainties with independent estimates: A case study using aircraft‐based observations and a convection‐permitting data assimilation system

AbstractAircraft can report in situ observations of the ambient temperature by using aircraft meteorological data relay (AMDAR) or these can be derived using mode‐select enhanced tracking data (Mode‐S EHS). These observations may be assimilated into numerical weather prediction models to improve the initial conditions for forecasts. The assimilation process weights the observation according to the expected uncertainty in its measurement and representation. The goal of this paper is to compare observation uncertainties diagnosed from data assimilation statistics with independent estimates. To quantify these independent estimates, we use metrological comparisons, made with in‐situ research‐grade instruments, as well as previous studies using collocation methods between aircraft (mostly AMDAR reports) and other observing systems such as radiosondes. In this study we diagnose a new estimate of the vertical structure of the uncertainty variances using observation‐minus‐background and observation‐minus‐analysis statistics from a Met Office limited area three‐dimensional variational data assimilation system (3 km horizontal grid‐length, 3‐hourly cycle). This approach for uncertainty estimation is simple to compute but has several limitations. Nevertheless, the resulting diagnosed variances have a vertical structure that is like that provided by the independent estimates of uncertainty. This provides confidence in the uncertainty estimation method, and in the diagnosed uncertainty estimates themselves. In the future our methodology, along with other results, could provide ways to estimate the uncertainty for the assimilation of aircraft‐based temperature observations.

Integration, Quality Assurance, and Usage of Global Aircraft Observations in CRA

This paper presents a detailed description of integration, quality assurance procedure, and usage of global aircraft observations for China’s first generation global atmospheric reanalysis (CRA) product (1979–2018). An integration method named “classified integration” is developed. Aircraft observations from nine different sources are integrated into the Integrated Global Meteorological Observation Archive from Aircraft (IGMOAA), a new dataset from the National Meteorological Information Center (NMIC) of the China Meteorological Administration (CMA). IGMOAA consists of global aircraft temperature, wind, and humidity data from the surface to 100 hPa, extending from 1973 to the present. Compared with observations assimilated in the Climate Forecast System Reanalysis (CFSR) of NCEP, the observation number of IGMOAA increased by 12.9% between 2010 and 2014, mainly as a result of adding more Chinese Aircraft Meteorological Data Relay (AMDAR) data. Complex quality control procedures for aircraft observations of NCEP are applied to detect data errors. Observations are compared with ERA-Interim reanalysis from 1979 to 2018 to investigate data quality of different types and aircraft, and subsequently to develop the blacklists for CRA. IGMOAA data have been assimilated in CRA in 2018 and are real-time updated at the CMA Data-as-a-Service (CMADaaS) platform. For CRA, the fits to observations improve over time. From 1994 to 2018, root-mean-square error (RMSE) of observations relative to CRA background decreases from 1.8 to 1.0°C for temperature above 300 hPa, and from 4.5 to 3 m s−1 for zonal wind. The RMSE for humidity appears to exhibit an apparent seasonal variation with larger errors in summer and smaller ones in winter.

Fast dual‐doppler LiDAR retrieval of boundary layer wind profiles

Operational doppler LiDARs (light detection and ranging) are often heavily engaged in specialised phenomenon detection, as well as dedicated surveillance scans, leaving little room for further additions to the tightly packed scanning strategy. This paper presents a fast method for retrieval of the urban boundary layer wind profile using existing scan data from two long-range doppler LiDARs at the Hong Kong International Airport (HKIA). Leveraging occasional range height indicator scans originally designed to aid the monitoring of terrain-induced wind disturbances, vertical profiles of the horizontal winds between 150 and 750m above ground level are estimated near the intersection point. The LiDAR-derived wind profiles are validated against measurements from a nearby wind profiler, as well as Aircraft Meteorological Data Relay (AMDAR) flight observations, for a 1-year period, 2019. Results indicated close agreement in terms of wind speed and direction between the LiDAR-derived profiles and wind profiler measurements, particularly above 300m. A slant angle correction factor is found to effectively alleviate the underestimation of the horizontal wind components at higher beam angles while also improving the consistency of the retrieved wind speed profile across different altitudes. For the AMDAR comparison, large discrepancies in wind speed and direction might be attributed to the natural variability of glide path winds well-known to HKIA. This study demonstrates the potential of extracting additional boundary layer wind information from ‘part-time’ scans of operational doppler LiDARs.

Retrieval of eddy dissipation rate from derived equivalent vertical gust included in Aircraft Meteorological Data Relay (AMDAR)

Abstract. 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.

Wind Speed and Altitude Dependent AMDAR Observational Error and Its Impacts on Data Assimilation and Forecasting

Aircraft Meteorological Data Relay (AMDAR) observations have been widely used in numerical weather prediction (NWP) because of its high spatiotemporal resolution. The observational error of AMDAR is influenced by aircraft flight altitude and atmospheric condition. In this study, the wind speed and altitude dependent observational error of AMDAR is estimated. The statistical results show that the temperature and the observational error in wind speeds slightly decrease as altitude increases, and the observational error in wind speed increases as wind speed increases. Pseudo single AMDAR observation assimilation tests demonstrate that the wind speed and altitude dependent observational error can provide more reasonable analysis increment. Furthermore, to assess the performance of wind speed and altitude dependent observational error on data assimilation and forecasting, two-month 3-hourly cycling data assimilation and forecast experiments based on the Weather Research and Forecasting Model (WRF) and its Data Assimilation system (WRFDA) are performed for the period during 1 September-31 October, 2017. The results of the two-month 3-hourly cycling experiments indicate that new observational error improves analysis and forecast of wind field and geo-potential height, and has slight improvements on temperature. The Fractions Skill Score (FSS) of the 6-h accumulated precipitation shows that new wind speed and altitude dependent observational error leads to better precipitation forecast skill than the default observational error in the WRFDA does.

Mixing layer height estimated from AMDAR and its relationship with PMs and meteorological parameters in two cities in North China during 2014–2017

The mixing layer height (MLH) plays an important role in atmospheric pollution by influencing the vertical diffusion of pollutants. The Aircraft Meteorological Data Relay (AMDAR) from the airports in Beijing (BJ) and Shijiazhuang (SJZ) during 2014–2017 was used to investigate temporal characteristics of the daily maximum MLH (MLHmax) and their relationships with surface meteorological parameters and particulate matters (PM1, PM2.5, and PM10).The seasonal mean of MLHmax in BJ was higher than that of SJZ, and shows the seasonal variation trend of summer> spring >autumn > winter in both cities. The MLHmax was found to have a positive correlation with daily average wind speed at 2 m (WS) in all seasons except summer and a significant negative correlation with daily average relative humidity at 2 m (RH) in four seasons. These implied a high risk of air pollution during low-MLHmax period. Subsequently, a higher negative relationship between MLHmax and PMs was obtained in both cities in autumn and winter based on the polynomial regression method, with a coefficient of determination (R2) of 0.37–0.71 in autumn and 0.52–0.88 in winter. In BJ, the sequence of R2 was PM1 >PM2.5 >PM10, yet a total opposite trend was observed in SJZ. It illustrated that the greatest contribution to local emissions in BJ and SJZ is PM1 and PM10 respectively, which means that the impact of MLHmax to local emissions and the secondary formed pollutants is stronger than that of long range transport. The ammoniate (NH4+), nitrate (NO3−) and sulfate (SO42−) also performed a better correlation with MLHmax than elemental carbon (EC) and organic carbon (OC) in BJ; while in SJZ, a better correlation between MLHmax and EC is easy to be found, while NO3− and SO42− performed a worse correlation with it. Therefore, PM pollution was characterized by secondary formation in BJ but by primary emissions in SJZ.

Improved estimation of air pollutant emissions from landing and takeoff cycles of civil aircraft in China

Civil aircraft emissions during landing and takeoff (LTO) are important air pollutant sources, but have been given insufficient attention in China. Accurate estimation of these emissions is limited by a lack of important parameters, such as detailed flight information and the dynamic time in climb and approach modes during LTO that are dependent on mixing layer height (MLH). We developed a flight-time/flight-height relationship using real-time height information in Aircraft Meteorological Data Relay data, and then calculated the actual time for each flight in those two modes based on the actual MLH from meteorological observation. Hourly emissions of civil aircraft were then estimated based on the database of each flight. Total emissions of NOx, CO, SO2, HC and PM from LTO cycles of domestic flights in China during 2015 were 37.78 Gg, 30.25 Gg, 12.00 Gg, 2.38 Gg and 0.75 Gg, respectively. Substantial monthly, daily and hourly variations of emissions due to the flight schedule as well as MLH were calculated. Large differences were found between the new estimation and emissions calculated based on traditional method. Compared with the emissions estimated based on default parameter obtained from International Civil Aviation Organization, the average difference of annual emission among airports with new estimation for various pollutants was approximately 30.3% in climb mode and 81.4% in approach mode; compared with the emissions estimated based on the method proposed by China National Guide, the average difference of annual emission among airports were 37.4% (NOx), 8.4% (CO), 73.1% (HC) and 58.1% (PM) during LTO process. The monthly airport-specific emissions per LTO were also proposed. These can provide necessary and meaningful support for the revision of the values in National Guide.

Atmospheric boundary‐layer characteristics from ceilometer measurements. Part 1: A new method to track mixed layer height and classify clouds

The use of Automatic Lidars and Ceilometers (ALC) is increasingly extended beyond monitoring cloud base height to the study of atmospheric boundary layer (ABL) dynamics. Therefore, long‐term sensor network observations require robust algorithms to automatically detect the mixed layer height (ZML). Here, a novel automatic algorithm CABAM (Characterising the Atmospheric Boundary layer based on ALC Measurements) is presented. CABAM is the first non‐proprietary mixed layer height algorithm specifically designed for the commonly deployed Vaisala CL31 ceilometer. The method tracks ZML, takes into account precipitation, classifies the ABL based on cloud cover and cloud type, and determines the relation between ZML and cloud base height. CABAM relies solely on ALC measurements. Results perform well against independent reference (AMDAR: Aircraft Meteorological Data Relay) measurements and supervised ZML detection. AMDAR‐derived temperature inversion heights allow ZML evaluation throughout the day. Very good agreement is found in the afternoon when the mixed layer height extends over the full ABL. However, during night or the morning transition the temperature inversion is more likely associated with the top of the residual layer. From comparison with SYNOP reports, the ABL classification scheme generally correctly distinguishes between convective and stratiform boundary‐layer clouds, with slightly better performance during daytime. Applied to 6 years of ALC observations in central London, Kotthaus and Grimmond (), a companion paper, demonstrate CABAM results are valuable to characterise the urban boundary layer over London, United Kingdom, where clouds of various types are frequent.

Evaluation of Accuracy of Chinese AMDAR Data for 2015

AbstractTwo comparative studies have been performed to evaluate the accuracy of Chinese Aircraft Meteorological Data Relay (AMDAR) weather reports. The comparison between AMDAR reports and radiosonde observations shows that the root-mean-square differences (RMSDs) in temperature, wind speed, and wind direction are 1.06°C, 1.95 m s−1, and 22°, respectively, within a spatial range of ≤20 km and a temporal window of ≤15 min. The comparison between AMDAR reports collected by different aircraft reveals that observation uncertainties in temperature, wind speed, and wind direction are 0.59°C, 0.90 m s−1, and 12°, respectively. The spatial and temporal representativeness as well as the environmental factors that may affect the evaluation results are also discussed in detail in the two comparative studies. The results of the present study provide valuable information on and high confidence in the application of Chinese AMDAR in numerical weather prediction models.

Characterization of aircraft emissions and air quality impacts of an international airport

Beijing Capital International Airport (ZBAA) is the world's second busiest airport. In this study, the emissions of air pollutants from aircraft and other sources at ZBAA in 2015 were estimated using an improved method, which considered the mixing layer height calculated based on aircraft meteorological data relay (AMDAR), instead of using the height (915m) recommended by ICAO. The yearly emissions of NOx, CO, VOCs, SO2, and PM2.5 at the airport were 8.76×103, 4.43×103, 5.43×102, 4.80×102, and 1.49×102ton/year, respectively. The spatial–temporal distribution of aircraft emissions was systematically analyzed to understand the emission characteristics of aircraft. The results indicated that NOx was mainly emitted during the take-off and climb phases, accounting for 20.5% and 55.5% of the total emissions. CO and HC were mainly emitted during the taxi phase, accounting for 91.6% and 92.2% of the total emissions. Because the mixing layer height was high in summer, the emissions of aircraft were at the highest level throughout the year. Based on the detailed emissions inventory, four seasons simulation using WRF-CMAQ model was performed over the domain surrounding the airport. The results indicated that the contribution to PM2.5 was relatively high in winter; the average impact was about 1.15μg/m3 within a radius of 1km around the airport. Meanwhile, the near surroundings and southwest areas of the airport are the most sensitive to PM2.5.

Diurnal Climatology of the Boundary Layer in Southern California Using AMDAR Temperature and Wind Profiles

AbstractObservations from commercial aircraft [e.g., the Aircraft Meteorological Data Relay (AMDAR) automated weather reports] have been increasing dramatically. Two main applications of the aircraft data are use in short-term forecasts and assimilation into numerical weather prediction models. Now that more than 10 years of measurements exist, using this dataset to construct a description of the long-term climatological behavior (a “climatology”) of the lower atmosphere is explored with two main objectives. The first objective is to examine strengths and weaknesses of using the dataset to construct a climatology of the lower atmosphere. Unlike the traditional twice-daily radiosonde launches, the high frequency of observations at major airports allows for an unprecedented set of diurnal information at many locations globally. The second objective is to obtain a climatology of the lower atmosphere of Southern California, specifically at Los Angeles, San Diego, and Ontario, during the spring and summer when the boundary layer is well defined and easily detected. The June 2001–14 climatology reveals that the deepening of the boundary layer overnight is consistent with a cloud-topped boundary layer. Whereas the average boundary layer height decreases right after sunrise at San Diego, at Los Angeles the deeper boundary layer persists about 4 h after sunrise and then decreases rapidly over 2 h as the onshore sea breeze strengthens. Morning intrusions of the marine air inland are easily detected at Ontario in some months but are practically nonexistent during July and August.

On the Impact and Benefits of AMDAR Observations in Operational Forecasting—Part I: A Review of the Impact of Automated Aircraft Wind and Temperature Reports

Abstract This paper reviews the impact of World Meteorological Organization (WMO) Aircraft Meteorological Data Relay (AMDAR) observations on operational numerical weather prediction (NWP) forecasts at both regional and global scales that support national and local weather forecast offices across the globe. Over the past three decades, data collected from commercial aircraft have helped reduce flight-level wind and temperature forecast errors by nearly 50%. Improvements are largest in 3–48-h forecasts and in regions where the automated reports 1) are most numerous, 2) cover a broad area, and 3) are available at multiple levels (e.g., made during aircraft ascent and descent). Improvements in weather forecasts due to these data have already had major impacts on a variety of aspects of airline operations, ranging from fuel savings from improved wind and temperature forecasts used in flight planning to passenger comfort and safety due to better awareness of en route and near-terminal weather hazards. Aircraft wind and temperature observations now constitute the third most important dataset for global NWP and, in areas of ample reports, have become the single most important dataset for use in shorter-term, regional NWP applications. Automated aircraft reports provide the most cost-effective data source for improving NWP, being more than 5 times more cost effective than any other major-impact observing system. They also present an economical alternative for obtaining tropospheric profiles both in areas of diminishing conventional observation and as a supplement to existing datasets, both in time and space. An evaluation of moisture observations becoming available from an increasing number of AMDAR-equipped aircraft will be presented in Part II of this paper, including examples of the use of the full array of AMDAR observations in a variety of forecasting situations.

Variational Correction of Aircraft Temperature Bias in the NCEP’s GSI Analysis System

Abstract Various studies have noted that aircraft temperature data have a generally warm bias relative to radiosonde data around 200 hPa. In this study, variational aircraft temperature bias correction is incorporated in the Gridpoint Statistical Interpolation analysis system at the National Centers for Environmental Prediction. Several bias models, some of which include information about aircraft ascent/descent rate, are investigated. The results show that the aircraft temperature bias correction cools down the atmosphere analysis around 200 hPa, and improves the analysis and forecast fits to the radiosonde data. Overall, the quadratic aircraft ascent/descent rate bias model performs better than other bias models tested here, followed closely by the aircraft ascent/descent rate bias model. Two other issues, undocumented in previous studies, are also discussed in this paper. One is the bias correction of aircraft report (AIREP) data. Unlike Aircraft Meteorological Data Relay (AMDAR) data, where unique corrections are applied for each aircraft, bias correction is applied indiscriminately (without regard to tail numbers) to all AIREP data. The second issue is the problem of too many aircraft not reporting time in seconds, or too infrequently, to be able to determine accurate vertical displacement rates. In addition to the finite-difference method employed to estimate aircraft ascent/descent rate, a tensioned-splines method is tested to obtain more continuously smooth aircraft ascent/descent rates and mitigate the missing time information.