Aircraft Flight Tracks Research Articles

TrackMatcher – a tool for finding intercepts in tracks of geographical positions

Abstract. Working with measurement data in atmospheric science often necessitates the co-location of observations from instruments or platforms at different locations with different geographical and/or temporal data coverage. The varying complexity and abundance of the different data sets demand a consolidation of the observations. This paper presents a tool for (i) finding temporally and spatially resolved intersections between two- or three-dimensional geographical tracks (trajectories) and (ii) extracting observations and other derived parameters in the vicinity of intersections to achieve the optimal combination of various data sets and measurement techniques. The TrackMatcher tool has been designed specifically for matching height-resolved remote sensing observations along the ground track of a satellite with position data of aircraft (flight tracks) and clouds (cloud tracks) and is intended to be an extension for ships (ship tracks) and air parcels (forward and backward trajectories). The open-source algorithm is written in the Julia programming language. The core of the matching algorithm consist of interpolating tracks of different objects with a piecewise cubic Hermite interpolating polynomial with the subsequent identification of an intercept point by minimising the norm between the different track point coordinate pairs. The functionality wrapped around the two steps allows for the application of the TrackMatcher tool to a wide range of scenarios. Here, we present three examples of matching satellite tracks with the position of individual aircraft and clouds that demonstrate the usefulness of TrackMatcher for application in atmospheric science.

Satellite Observations of the Impact of Individual Aircraft on Ice Crystal Number in Thin Cirrus Clouds

AbstractContrails can persist in cloud‐free supersaturated air, increasing high‐cloud cover, and inside natural cirrus cloud, modifying the microphysical properties of them. The latter effect is almost unknown, partly because of the lack of height‐resolved measurements and the capability of measurements to penetrate inside the cloud. New retrievals of the ice crystal number concentration from combined satellite cloud radar and lidar measurements (CloudSat/CALIPSO; DARDAR‐Nice algorithm) now allow for satellite‐based assessment inside the clouds. We investigate this issue at intersections between the aircraft flight tracks and these retrieval profiles. Regions behind the aircraft inside the flight track were compared to the adjacent regions and to ahead of the aircraft, along the satellites' profiles, where DARDAR‐Nice identify geometrically thin cirrus clouds. This comparison revealed a statistically significant increase of 25% and 54% in the concentration of ice crystals with the minimum size of 5 μm around 300–540‐m beneath an aircraft's flight altitude.

The impact of weather patterns and related transport processes on aviation's contribution to ozone and methane concentrations from NO<sub><i>x</i></sub> emissions

Abstract. Aviation-attributed climate impact depends on a combination of composition changes in trace gases due to emissions of carbon dioxide (CO2) and non-CO2 species. Nitrogen oxides (NOx = NO + NO2) emissions induce an increase in ozone (O3) and a depletion of methane (CH4), leading to a climate warming and a cooling, respectively. In contrast to CO2, non-CO2 contributions to the atmospheric composition are short lived and are thus characterised by a high spatial and temporal variability. In this study, we investigate the influence of weather patterns and their related transport processes on composition changes caused by aviation-attributed NOx emissions. This is achieved by using the atmospheric chemistry model EMAC (ECHAM/MESSy). Representative weather situations were simulated in which unit NOx emissions are initialised in specific air parcels at typical flight altitudes over the North Atlantic flight sector. By explicitly calculating contributions to the O3 and CH4 concentrations induced by these emissions, interactions between trace gas composition changes and weather conditions along the trajectory of each air parcel are investigated. Previous studies showed a clear correlation between the prevailing weather situation at the time when the NOx emission occurs and the climate impact of the NOx emission. Here, we show that the aviation NOx contribution to ozone is characterised by the time and magnitude of its maximum and demonstrate that a high O3 maximum is only possible if the maximum occurs early after the emission. Early maxima occur only if the air parcel, in which the NOx emission occurred, is transported to lower altitudes, where the chemical activity is high. This downward transport is caused by subsidence in high-pressure systems. A high ozone magnitude only occurs if the air parcel is transported downward into a region in which the ozone production is efficient. This efficiency is limited by atmospheric NOx and HOx concentrations during summer and winter, respectively. We show that a large CH4 depletion is only possible if a strong formation of O3 occurs due to the NOx emission and if high atmospheric H2O concentrations are present along the air parcel's trajectory. Only air parcels, which are transported into tropical areas due to high-pressure systems, experience high concentrations of H2O and thus a large CH4 depletion. Avoiding climate-sensitive areas by rerouting aircraft flight tracks is currently computationally not feasible due to the long chemical simulations needed. The findings of this study form a basis of a better understanding of NOx climate-sensitive areas and through this will allow us to propose an alternative approach to estimate aviation's climate impact on a day-to-day basis, based on computationally cheaper meteorological simulations without computationally expensive chemistry. This comprises a step towards a climate impact assessment of individual flights, here with the contribution of aviation NOx emissions to climate change, ultimately enabling routings with a lower climate impact by avoiding climate-sensitive regions.

Addressing the sensitivity of forecast impact to flight path design for targeted observations of extratropical winter storms: A demonstration in an OSSE framework

AbstractFew studies have examined the forecast uncertainties brought about from varying aircraft flight track patterns in targeted observations for extratropical winter storms. To examine the degree of uncertainty in downstream forecasts caused by different aircraft flight patterns, a series of observing system simulation experiments (OSSEs) are performed and demonstrated for two extratropical winter storms identified in the European Centre for Medium‐Range Weather Forecasts (ECMWF) T511 Nature Run using the National Centers for Environmental Prediction Global Data Assimilation System and Global Forecast System (Q1FY15). Winter storms were chosen to support operational Pacific Ocean targeting strategies using unmanned aircraft. For these two storms, objective and composite flight tracks are generated as they could occur in an operational field mission to sample sensitive areas and meteorologically important regions, and then the changes in downstream forecasts across the various flight tracks are evaluated. The forecast impact downstream is sensitive to flight track orientation and shows case‐dependent results, with some flight patterns leading to significant improvements, while others result in neutral to degraded forecasts. The degree of downstream uncertainty in the verification region can vary up to 8% from the different flight paths, depending on the metric used and the atmospheric variables analysed. Although the study is a demonstration of the technique and is limited to only two case studies, it suggests that uncertainty in flight path design should not be neglected in future field missions. Some guidance for mitigating this uncertainty is also discussed.

Aircraft Noise and Land Use Zoning Compatibility around the Juan Santamaría Airport, Costa Rica

The purpose of this study is to evaluate the noise generated by aeronautical operations around Juan Santamaría Airport and its compatibility with the land use and the proposed zoning around the airport. Aircraft noise can produce discomfort, interference with daily activities, and excessive vibrations; hence, land use planning around airports is of importance.
 Maps were prepared through computational models representing the noise levels generated by the operations of the airport. The operations were analyzed by aircraft type, schedules, and flight tracks, for 2013 and projections for: 2016, 2026, and 2036. Noise level data were collected with a sound level meter at 28 points surrounding the airport.
 Comparing the annual maps of 2013 and 2036 it was determined that 41,24 % of the analyzed area will present clearly perceivable increases (5 dB(A) to 10 dB(A)), and 1,36 % of the area will have double loudness increases (10 dB(A) to 14 dB(A)).
 The 2016 maps show locations where it is recommended to incorporate solutions in the construction regulation that reduce between 25 dB and 30 dB in the residential and scholar areas located within 65 dB(A) and 70 dB(A), such as Coco, Rincón Monge, Rincón Herrera, and Bajo Sorda. This finding is supported by field measurements.
 The proposed zoning was contrasted against the yearly day-night average sound level of 2036. The biggest issue of excessive aircraft noise is located near the west runway where a range above the 75 dB(A) is expected. Any edification of permanent residence must be banned in here.

Aircraft noise level calculation during take-off

A mathematical model with 4 degree of freedom created in Matlab for aircraft departure trajectory is described in this article. As a reference aircraft a midsize commercial passenger aircraft similar to an Airbus A320 has been chosen. The aircraft is represented by the rigid body and the parameters of model are collected from Airbus and the simulated departure trajectory at the Munich airport is based on a Standard Instrumental Departure. A semi-empirical model of Stone for predicting the jet noise has been used. The proposed model is validated against 10 real flights obtained from aircraft noise and flight track monitoring system at Munich airport. The computed error between the real data and modelling is reported on. Obtained results are presented numerical and graphically. The observed effects of flight operational parameters affecting the aircraft noise emission level during take-off represent subjects of discussions in the paper.

Impact of Gulfstream-IV Dropsondes on Tropical Cyclone Prediction in a Regional OSSE System

Abstract Aircraft reconnaissance missions remain the primary means of collecting direct measurements of marine atmospheric conditions affecting tropical cyclone formation and evolution. The National Hurricane Center tasks the NOAA G-IV aircraft to sample environmental conditions that may impact the development of a tropical cyclone threatening to make landfall in the United States or its territories. These aircraft data are assimilated into deterministic models and used to produce real-time analyses and forecasts for a given tropical cyclone. Existing targeting techniques aim to optimize the use of reconnaissance observations and partially rely on regions of highest uncertainty in the Global Ensemble Forecast System. Evaluating the potential impact of various trade-offs in the targeting process is valuable for determining the ideal aircraft flight track for a prospective mission. AOML’s Hurricane Research Division has developed a system for performing regional observing system simulation experiments (OSSEs) to assess the potential impact of proposed observing systems on hurricane track and intensity forecasting. This study focuses on improving existing targeting methods by investigating the impact of proposed aircraft observing system designs through various sensitivity studies. G-IV dropsonde retrievals were simulated from a regional nature run, covering the life cycle of a rapidly intensifying Atlantic hurricane. Results from sensitivity studies provide insight into improvements for real-time operational synoptic surveillance targeting for hurricanes and tropical storms, where dropsondes released closer to the vortex–environment interface provide the largest impact on the track forecast. All dropsonde configurations provide a positive 2-day impact on intensity forecasts by improving the environmental conditions known to impact tropical cyclone intensity.

Algorithms for aircraft track optimization in flexible routing

The authors consider the problem of optimization of aircraft flight tracks in air traffic management (ATM) on basis of flexible routing technologies which involve the use of satellite navigation systems (SNS). It is shown that in optimizing a trajectory it is necessary to take into account the accuracy of track holding in flight which depends on accuracy of the navigation system and external flight path disturbances, e.g. wind. For solving the problem of optimization the authors propose to use the theory of graphs. The technique of constructing a dynamic SNS accuracy field and representing it as a graph was developed. It is proposed that the SNS field could be characterized by geometric dilution of precision changing both in space and in time. Based on the theory of graphs (A-star algorithm) the technique of constructing a trajectory of optimal length under conditions of SNS accuracy variations and external flight path disturbances is proposed. The criterion of optimization based on minimizing the true track is offered. The cost function taking into account the track holding accuracy in navigating by SNS and effects of external flight disturbances is justified. The article represents the results of A-star algorithm application for optimal flight track construction under conditions of SNS accuracy field variation and presence of prohibited zones in the provide zone of airspace

Aircraft Type Recognition Based on Target Track

The target recognition plays an important role in air traffic management, and the research on automatic aircraft recognition is still in the exploratory stage. Since aircrafts move at high speeds in complex background, it is still a challenging task to quickly extract valid features from small amounts of data for aircraft type recognition. The machine learning is capable of capturing discriminating information and can well identify potential patterns from the dataset. Thus, we employ a novel classification model based on machine learning with the use of some effective motion features extracted from aircraft flight track information as the input of the model such as maximum speed, cruise speed, maximum acceleration, maximum climb rate. We performed experiments on datasets collected by multiple sensors and the results demonstrated the effectiveness of proposed model in significantly improving the aircraft type recognition accuracy, especially for military aircrafts. Besides, the model avoids the inherent deficiencies of graphics and image processing, and can well meet the needs of the air traffic management.

The NASA Carbon Airborne Flux Experiment (CARAFE): instrumentation and methodology

Abstract. The exchange of trace gases between the Earth's surface and atmosphere strongly influences atmospheric composition. Airborne eddy covariance can quantify surface fluxes at local to regional scales (1–1000 km), potentially helping to bridge gaps between top-down and bottom-up flux estimates and offering novel insights into biophysical and biogeochemical processes. The NASA Carbon Airborne Flux Experiment (CARAFE) utilizes the NASA C-23 Sherpa aircraft with a suite of commercial and custom instrumentation to acquire fluxes of carbon dioxide, methane, sensible heat, and latent heat at high spatial resolution. Key components of the CARAFE payload are described, including the meteorological, greenhouse gas, water vapor, and surface imaging systems. Continuous wavelet transforms deliver spatially resolved fluxes along aircraft flight tracks. Flux analysis methodology is discussed in depth, with special emphasis on quantification of uncertainties. Typical uncertainties in derived surface fluxes are 40–90 % for a nominal resolution of 2 km or 16–35 % when averaged over a full leg (typically 30–40 km). CARAFE has successfully flown two missions in the eastern US in 2016 and 2017, quantifying fluxes over forest, cropland, wetlands, and water. Preliminary results from these campaigns are presented to highlight the performance of this system.

Background error covariance with balance constraints for aerosol species and applications in variational data assimilation

Abstract. Balance constraints are important for background error covariance (BEC) in data assimilation to spread information between different variables and produce balance analysis fields. Using statistical regression, we develop a balance constraint for the BEC of aerosol variables and apply it to a three-dimensional variational data assimilation system in the WRF/Chem model; 1-month forecasts from the WRF/Chem model are employed for BEC statistics. The cross-correlations between the different species are generally high. The largest correlation occurs between elemental carbon and organic carbon with as large as 0.9. After using the balance constraints, the correlations between the unbalanced variables reduce to less than 0.2. A set of data assimilation and forecasting experiments is performed. In these experiments, surface PM2.5 concentrations and speciated concentrations along aircraft flight tracks are assimilated. The analysis increments with the balance constraints show spatial distributions more complex than those without the balance constraints, which is a consequence of the spreading of observation information across variables due to the balance constraints. The forecast skills with the balance constraints show substantial and durable improvements from the 2nd hour to the 16th hour compared with the forecast skills without the balance constraints. The results suggest that the developed balance constraints are important for the aerosol assimilation and forecasting.

Aviation effects on already-existing cirrus clouds.

Determining the effects of the formation of contrails within natural cirrus clouds has proven to be challenging. Quantifying any such effects is necessary if we are to properly account for the influence of aviation on climate. Here we quantify the effect of aircraft on the optical thickness of already-existing cirrus clouds by matching actual aircraft flight tracks to satellite lidar measurements. We show that there is a systematic, statistically significant increase in normalized cirrus cloud optical thickness inside mid-latitude flight tracks compared with adjacent areas immediately outside the tracks.

Tracking elevated pollution layers with a newly developed hyperspectral Sun/Sky spectrometer (4STAR): Results from the TCAP 2012 and 2013 campaigns

AbstractTotal columnar water vapor (CWV), nitrogen dioxide (NO2), and ozone (O3) are derived from a newly developed, hyperspectral airborne Sun‐sky spectrometer (4STAR) for the first time during the two intensive phases of the Two‐Column Aerosol Project (TCAP) in summer 2012 and winter 2013 aboard the DOE G‐1 aircraft. We compare results with coincident measurements. We find 0.045 g/cm2 (4.2%) negative bias and 0.28 g/cm2 (26.3%) root‐mean‐square difference (RMSD) in water vapor layer comparison with an in situ hygrometer and an overall RMSD of 1.28 g/m3 (38%) water vapor amount in profile by profile comparisons, with differences distributed evenly around zero. RMSD for O3 columns average to 3%, with a 1% negative bias for 4STAR compared with the Ozone Measuring Instrument along aircraft flight tracks for 14 flights during both TCAP phases. Ground‐based comparisons with Pandora spectrometers at the Goddard Space Flight Center, Greenbelt, Maryland, showed excellent agreement between the instruments for both O3 (1% RMSD and 0.1% bias) and NO2 (17.5% RMSD and −8% bias). We apply clustering analysis of the retrieved products as a case study during the TCAP summer campaign to identify variations in atmospheric composition of elevated pollution layers and demonstrate that combined total column measurements of trace gas and aerosols can be used to define different pollution layer sources, by comparing our results with trajectory analysis and in situ airborne miniSPLAT (single‐particle mass spectrometer) measurements. Our analysis represents a first step in linking sparse but intense in situ measurements from suborbital campaigns with total column observations from space.

Measuring the levels of noise at the İstanbul Atatürk Airport and comparisons with model simulations

Airport noise and its impact on the surrounding areas are major issues in the aviation industry. The İstanbul Atatürk Airport is a major global airport with passenger numbers increasing rapidly per annum. The noise levels for day, evening and night times were modeled around the İstanbul Atatürk Airport according to the European Noise Directive using the actual data records for the year 2011. The “ECAC Doc. 29-Interim” method was used for the computation of the aircraft traffic noise. In the setting the noise model for the local airport topography was taken into consideration together with the noise source data, the airport loadings, features of aircraft and actual air traffic data. Model results were compared with long-term noise measurement values for calibration. According to calibration results, classifications of the aircraft type and flight tracks were revised. For noise model validation, the daily noise measurements at four additional locations were used during the verification period. The input data was re-edited only for these periods and the model was validated. A successful model performance was obtained in several zones around the airport. The validated noise model of the İstanbul Atatürk Airport can be now utilized both for determining the noise levels in the future and for producing new strategies which are about the land use planning, operational considerations for the air traffic management and the noise abatement procedures.

Detection and Analysis of Water Vapor Transport by Airborne Lidars

Water vapor, a minor constituent of the earth's atmosphere, plays a major role in the radiation budget and the water cycle with important implications for weather and climate. Due to the heterogeneous distribution of its sources, evaporation, and sinks, condensation and precipitation, and due to the complexity of atmospheric motion and mixing, its distribution in the atmosphere is highly variable. Despite the high relevance of this trace gas, its variability challenges accurate measurements of its concentration. Advanced airborne lidar instruments aid to better observe water vapor and its transport in the atmosphere, in view of an improved understanding of atmospheric processes that are key to weather and climate research. The combination of a water vapor differential absorption lidar and a heterodyne detection Doppler wind lidar on an aircraft is new and allows to measure vertical profiles of the latent heat flux in a convective boundary layer and to portray the small- to large-scale humidity transport and variability along the aircraft flight track with high accuracy and spatial resolution.

Inverse carbon dioxide flux estimates for the Netherlands

CO2 fluxes for the Netherlands and surroundings are estimated for the year 2008, from concentration measurements at four towers, using an inverse model. The results are compared to direct CO2flux measurements by aircraft, for 6 flight tracks over the Netherlands, flown multiple times in each season. We applied the Regional Atmospheric Mesoscale Modeling system (RAMS) coupled to a simple carbon flux scheme (including fossil fuel), which was run at 10 km resolution, and inverted with an Ensemble Kalman Filter. The domain had 6 eco‐regions, and inversions were performed for the four seasons separately. Inversion methods with pixel‐dependent and ‐independent parameters for each eco‐region were compared. The two inversion methods, in general, yield comparable flux averages for each eco‐region and season, whereas the difference from the prior flux may be large. Posterior fluxes co‐sampled along the aircraft flight tracks are usually much closer to the observations than the priors, with a comparable performance for both inversion methods, and with best performance for summer and autumn. The inversions showed more negative CO2 fluxes than the priors, though the latter are obtained from a biosphere model optimized using the Fluxnet database, containing observations from more than 200 locations worldwide. The two different crop ecotypes showed very different CO2uptakes, which was unknown from the priors. The annual‐average uptake is practically zero for the grassland class and for one of the cropland classes, whereas the other cropland class had a large net uptake, possibly because of the abundance of maize there.

Aerial Observation of Aerosols Transported from East Asia — Chemical Composition of Aerosols and Layered Structure of an Air Mass over the East China Sea

Aerial observation was conducted during spring (March-April) 2008 over the East China Sea to analyze the transport of atmospheric pollutants from East Asia and the transformation processes during transport. Concentrations of sulfur dioxide (SO2), ozone (O3), total reactive nitrogen (NOy), carbon monoxide (CO), and black carbon (BC) were measured on board the aircraft, and chemical analyses of aerosols were performed subsequently by high-volume filter sampling of aerosols and ion chromatography and inductively coupled plasma-mass spectroscopy (ICP-MS) analyses. The distributions of gases and aerosols clearly suggested a layered structure to the air mass, in good agreement with predictions of the CFORS (Chemical weather FORecast System) model. The non-sea-salt (nss)-(sulfate (SO4 2- ))/((SO2) + nss(SO4 2- )) ratio value, which increased from north to south along the aircraft flight track, indicated oxidation of SO2 to form sulfuric acid during transport. In addition, pronounced chlorine loss suggested that substantial production of acidic substances occurred in the air mass as it moved away from China. The negative correlation between the Cl - /Na + ratio and the nss-sulfate concentration suggested that the reaction of sulfuric acid with sea salt was the main cause of the strong chlorine loss. On 28 March a very clear layered structure of the air mass was observed that could be clearly explained by the CFORS computer simulation model. Therefore, here the observation results obtained on 28 March 2008 are reported.

Retrieval of aerosol optical depth in vicinity of broken clouds from reflectance ratios: case study

Abstract. A recently developed reflectance ratio (RR) method for the retrieval of aerosol optical depth (AOD) is evaluated using extensive airborne and ground-based data sets collected during the Cloud and Land Surface Interaction Campaign (CLASIC) and the Cumulus Humilis Aerosol Processing Study (CHAPS), which took place in June 2007 over the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site. A detailed case study is performed for a field of single-layer shallow cumuli observed on 12 June 2007. The RR method is applied to retrieve the spectral values of AOD from the reflectance ratios measured by the MODIS Airborne Simulator (MAS) for two pairs of wavelengths (660 and 470 nm, 870 and 470 nm) collected at a spatial resolution of 0.05 km. The retrieval is compared with an independent AOD estimate from three ground-based Multi-filter Rotating Shadowband Radiometers (MFRSRs). The interpolation algorithm that is used to project MFRSR point measurements onto the aircraft flight tracks is tested using AOD derived from NASA Langley High Spectral Resolution Lidar (HSRL). The RR AOD estimates are in a good agreement (within 5%) with the MFRSR-derived AOD values for the 660-nm wavelength. The AODs obtained from MAS reflectance ratios overestimate those derived from MFRSR measurements by 15–30% for the 470-nm wavelength and underestimate the 870-nm AOD by the same amount.

Climatology of Velocity and Temperature Turbulence Statistics Determined from Rawinsonde and ACARS/AMDAR Data

Abstract The climatology of the spatial structure functions of velocity and temperature for various altitudes (pressure levels) and latitude bands is constructed from the global rawinsonde network and from Aircraft Communications, Addressing, and Reporting System/Aircraft Meteorological Data Relay (ACARS/AMDAR) data for the tropics and Northern Hemisphere. The ACARS/AMDAR data provide very dense coverage of winds and temperature over common commercial aircraft flight tracks and allow computation of structure functions to scales approaching 1 km, while the inclusion of rawinsonde data provides information on larger scales approaching 10 000 km. When taken together these data extend coverage of the spatial statistics of the atmosphere from previous studies to include larger geographic regions, lower altitudes, and a wider range of spatial scales. Simple empirical fits are used to approximate the structure function behavior as a function of altitude and latitude in the Northern Hemisphere. Results produced for spatial scales less than ∼2000 km are consistent with previous studies using other data sources. Estimates of the vertical and global horizontal structure of turbulence in terms of eddy dissipation rate ε and thermal structure constant CT2 are derived from the structure function levels at the smaller scales.

Diagnosis of processes controlling water vapour in the tropical tropopause layer by a Lagrangian cirrus model

Abstract. We have developed a Lagrangian air-parcel cirrus model (LACM), to diagnose the processes controlling water in the tropical tropopause layer (TTL). LACM applies parameterised microphysics to air parcel trajectories. The parameterisation includes the homogeneous freezing of aerosol droplets, the growth/sublimation of ice particles, and sedimentation of ice particles, so capturing the main dehydration mechanism for air in the TTL. Rehydration is also considered by resetting the water vapour mixing ratio in an air parcel to the value at the point in the 4-D analysis/forecast data used to generate the trajectories, but only when certain conditions, indicative of convection, are satisfied. The conditions act to restrict rehydration of the Lagrangian air parcels to regions where convective transport of water vapour from below is significant, at least to the extent that the analysis/forecast captures this process. The inclusion of hydration and dehydration mechanisms in LACM results in total water fields near tropical convection that have more of the "stripy" character of satellite observations of high cloud, than do either the ECMWF analysis or trajectories without microphysics. The mixing ratios of total water in the TTL, measured by a high-altitude aircraft over Brazil (during the TROCCINOX campaign), have been reconstructed by LACM using trajectories generated from ECMWF analysis. Two other Lagrangian reconstructions are also tested: linear interpolation of ECMWF analysed specific humidity onto the aircraft flight track, and instantaneous dehydration to the saturation vapour pressure over ice along trajectories. The reconstructed total water mixing ratios along aircraft flight tracks are compared with observations from the FISH total water hygrometer. Process-oriented analysis shows that modelled cirrus cloud events are responsible for dehydrating the air parcels coming from lower levels, resulting in total water mixing ratios as low as 2 μmol/mol. Without adding water back to some of the trajectories, the LACM and instantaneous-dehydration reconstructions have a dry bias. The interpolated-ECMWF reconstruction does not suffer this dry bias, because convection in the ECMWF model moistens air parcels dramatically, by pumping moist air upwards. This indicates that the ECMWF model captures the gross features of the rehydration of air in the TTL by convection. Overall, the ECMWF models captures well the exponential decrease in total water mixing ratio with height above 250 hPa, so that all the reconstruction techniques capture more than 75% of the standard deviation in the measured total water mixing ratios over the depth of the TTL. By picking up the main contributing processes to dehydration and rehydration in the TTL, LACM reconstructs total water mixing ratios at the top of the TTL, close to the cold point, that are always in substantially better agreement with observations than instantaneous-dehydration reconstructions, and better than the ECMWF analysis for regions of high relative humidity and cloud.