In all dust uplift models, two categories of airborne particles are considered, a saltating population and a dust population [Shao, 2008]. Saltation particles have diameters ≳ 100 μ m and can be emitted by aerodynamic forces or impacts of other saltators with the surface [Kok et al., 2012]. Their motion after ejection is dominated by gravitational forces, and they are expected to exist only in a saltation layer extending a few centimeters from the surface. The dust population contains much smaller and less massive particles which are more dif ﬁ cult to lift via aerodynamic forces due to cohesion forces in the soil. These particles can be ejected by saltator surface impacts and can be lifted above the saltation layer to become suspended for long durations. Although wind tunnel experiments by Alfaro et al.  and the parameterization of Shao  indicated the presence of wind speed dependent disaggregation, Kok [2011b] found that ﬁ eld experiments [Gillette et al., 1972, 1974; Gillette, 1974; Sow et al., 2009] are not consistent with this ﬁ nding and suggested the wind speed dependence was an indication that steady state emission was not reached. Kok [2011a] provided scale invariant model of dust emission by brittle fragmentation of aggregates of dust particles in the soil which was found to be in excellent agreement with measured emitted particle size distributions. In this paper we present measurements of the size-resolved dust ﬂ uxes retrieved from aircraft measurements throughout the depth of the boundary layer in the heart of the Saharan Desert. These were made as part of the Fennec project. To our knowledge, these are the ﬁ rst measurements of size-resolved dust ﬂ uxes to be made from an aircraft. The Fennec project investigated the relationship between dynamics, dust, and radiation in the Earth ’ s deepest boundary layer under the unique conditions of the Saharan heat low [Cuesta et al., 2009] and included deployment of eight automatic weather stations
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In August 2009, we also carried out aircraft measurements over Moshiri and Taiki, Hokkaido. Both Moshiri and Taiki were observed on GOSAT’s path 5. Tokachi-Obihiro Air- port was used as a base camp for the Hokkaido measure- ments. The aircraft measurements were carried out on 26 Au- gust 2009 over the Moshiri observatory in the Geospace Re- search Center of the Solar-Terrestrial Environment Labora- tory of Nagoya University, which is located in northwest- ern Hokkaido. The Moshiri observatory, a GOSAT valida- tion observational site, operates a g-b FTS and meteorologi- cal instruments.
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The TORERO cruise track of the RV Ka’imimoana, and flight tracks of TORERO research flights RF12 and RF17 are shown in Fig. 1. The objective of RF12 was to measure BrO profiles in the upper tropical free troposphere (FT) un- der pristine conditions and over the maximum accessible al- titude range of the NSF/NCAR GV aircraft (0.1 to 14.5 km). RF17 was optimized to characterize the chemical and radi- ation state of the atmosphere above the ship. RF17 is used here to compare the data from in situ and remote sensing in- struments in the lower atmosphere (up to 2 km). The GV air- craft conducted a “flyby” near the ship and measured vertical profiles of BrO, IO and glyoxal mixing ratios up to 10.5 km. These vertical profiles complement the boundary layer ob- servations with information about atmospheric composition aloft. Results discussed in this study used the following in- struments, methods and models.
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Glyoxal is the simplest alpha-dicarbonyl and is one of the most prevalent dicarbonyls in the ambient atmosphere. Global models indicate that its major source is oxidation of biogenic compounds, led by isoprene (47 %) with smaller contributions from monoterpenes (4 %) and methylbutenol (0.8 %) (Fu et al., 2008). Other important glyoxal sources in- clude the oxidation of anthropogenic species, such as ethyne and aromatics (30 %), and direct production from biomass burning (18 %) (Fu et al., 2008). However, these global es- timates are uncertain, in part because of the limited num- ber of ambient measurements of glyoxal. For example, en- hanced glyoxal concentrations over the equatorial ocean have recently been reported from satellite and ship-based instru- ments, indicating a source of CHOCHO from the oxidation of marine emissions (Sinreich et al., 2010; Mahajan et al., 2014). The major loss processes for glyoxal include photol- ysis, reaction with OH and NO 3 , and deposition to aerosol
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Air is drawn through a 6.3 mm inner-diameter PFA tube that extends 28 cm below the WB-57F skin and is housed in an airfoil structure. The inlet opening is oriented perpen- dicular to the direction of airflow around the aircraft, elimi- nating super-micron particles from the sample flow at WB- 57F flight speeds. A PFA tee in the sample line, located 5 cm from the inlet tip, is used to add zero and/or calibration gases to the inlet. Tubing and fittings housed inside the airfoil are temperature-controlled to 45 ◦ C. Inside the heated main in- strument enclosure, the sample passes through a custom but- terfly valve similar to that described by Gao et al. (1999) con- structed of PEEK material with a PFA vane before entering the LIF cell. The majority of the sample flow ( ∼ 1500 sccm) exits through the primary cell exhaust (see Fig. 4) opposite the inlet, and about 250 sccm are drawn through each of the LIF cell arms to eliminate dead volume in the analysis region. The cell exhaust passes through a second butterfly valve and then to a 160 L min −1 scroll pump.
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in situ aircraft measurements). Overall, the correlation be- tween the IASI retrievals and the aircraft measurements is very good (0.80–0.89), but IASI retrievals have a low bias between − 0.69 and − 1.74 % as compared to the in situ air- craft measurements (convolved), and the residual standard deviations are between 1.07 and 1.25 %. From Fig. 8 we can- not see significant differences of the errors among different campaigns of HIPPO, which were taken in different seasons. However, on average the bias from HIPPO-1 in January 2009 is the largest, particularly in the high Northern Hemisphere. We found this large bias is associated with the small DOF during the cold winter in the Arctic region.
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Due to its rather long atmospheric residence time GEM will reach the stratosphere. The information on the behaviour of mercury in the upper troposphere and lower stratosphere (UT–LS) is tenuous because of lack of measurements due to instrumental limitations. Only recently has the progress in measurement techniques enabled extensive but short-term aircraft measurements of mercury distribution in the tropo- sphere and lower stratosphere (Ebinghaus and Slemr, 2000; Friedli et al., 2003a, b, 2004; Banic et al., 2003; Ebinghaus et al., 2007; Radke et al., 2007; Talbot et al., 2007, 2008; Swartzendruber et al., 2008, 2009a; Slemr et al., 2009, 2014; Lyman and Jaffe, 2012; Brooks et al., 2014; Ambrose et al., 2015; Shah et al., 2016; Weigelt et al., 2016). All observa- tions have so far shown a pronounced decrease of gaseous mercury (GEM + GOM) concentrations in the lower strato- sphere (Ebinghaus et al., 2007; Radke et al., 2007; Talbot et al., 2007; Slemr et al., 2009; Lyman and Jaffe, 2012), which implies a conversion to PM. This implication is supported by observations of high PM concentrations in the lower strato- sphere but not in the upper troposphere (Murphy et al., 1998, 2006). However, the mechanism of this conversion and its importance for the atmospheric mercury cycle is not known. Since May 2005 mercury has been measured during monthly CARIBIC (Civil Aircraft for the Regular Investiga- tion of the Atmosphere Based on an Instrumented Container; Brenninkmeijer et al., 2007) flights. The objective of these measurements is to gain information on the worldwide dis- tribution of mercury in the UT–LS (Slemr et al., 2009) and on mercury emissions from biomass burning and other sources (Ebinghaus et al., 2007; Slemr et al., 2014). Here we describe the mercury instrumentation, present a method for post-flight data processing, and discuss the results of several fractiona- tion experiments.
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agreement with more recent measurements (e.g. Dufour et al., 2005 and Laube et al., 2008). CFC-113 is not one of our target trace gases (retrieved quantities), but we find that this adjustment improves the agreement between simulated and measured radiance values in the spectral regions where CFC- 113 emits. The PAN a priori value is set to zero in our re- trieval approach, but an a priori standard deviation estimated from Glatthor et al. (2007) is used. Annual mean HCFC-22 values from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS; see e.g. Bernath et al., 2005) are used. CFC-11 and CFC-12 profiles are combined from measurements of the High Altitude Gas Analyser (HA- GAR) instrument (see e.g. Werner et al., 2009 and Homan et al., 2010) on-board the M55-Geophysica and values from Remedios et al. (2007b) for the upper altitudes.
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Finally, it has to be pointed out that by us- ing this computer program the accuracy of the calcu- lation has been significantly improved, including also better stability and aircraft safety during flight. The duration necessary for completing the Load and Trim Sheet has been shortened from the ten minutes on average required to do this manually, to one to two minutes, thus leaving time for complete and precise control of staff working on unloading / loading of baggage and cargo, and total aircraft handling.
B¨ogel and Baumann (1991) describe a method of analysis of R858 measurements during pilot-induced maneuvers to esti- mate static pressure errors. Crawford and Dobosy (1992) de- scribe the Best Aircraft Turbulence (BAT) differential pres- sure flow-angle probe which addresses the static pressure problem by averaging pressure on several ports. Here, we develop a method to predict the static pressure error directly by using pressure measurements from the R858 air veloc- ity probe which, on the UWKA, is mounted at the tip of a boom, as shown in Fig. 1. The probe is a hemisphere- cylinder configuration in which a hemispherical surface is at the end of a 2.5 cm diameter, 12.5 cm long cylindrical section. Pressure measurements on ports in a hemispheri- cal surface are used for airspeed and flow angle determina- tion (Brown et al., 1983). There are 5 ports: one central port which approximates total pressure, two ports separated by
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The CARIBIC container housing altogether 15 instruments is flown aboard one of Lufthansa’s Airbus 340–600. This aircraft was mechanically and electrically modified and equipped with a permanent air inlet system in November 2004 (Brenninkmeijer et al., 2007). The CARIBIC mea- surement container is deployed monthly on four consecutive long-range flights, such as Frankfurt – Caracas – Frankfurt – Osaka – Frankfurt, totaling about 40 flight hours. Each in- strument in the container is equipped with its own computer that controls the measurement process and collects data. The instruments communicate via an Ethernet bus system with a master computer for control purposes. The master com- puter collects via the ARINC-429 bus system aircraft data on position, temperature, pressure, wind and some other pa- rameters and records internal status data on temperatures at different places in the container and pressures at different points within the air sampling and distribution system. The communication between the master computer and the instru- ments is recorded and used for post-flight synchronization of the measurements. To avoid contamination of the instruments by strongly polluted air near airports, pumping systems are
As a first step toward characterizing the error budget of TES δ D retrievals, we examine the scan-by-scan variability within single TES transect special observations over the Alaskan interior boreal forest. To optimize for clear-sky and warm conditions, only measurements from July and August (2011– 2013) are considered here. This corresponds to 27 Alaskan interior transects, and a total of 253 TES scans with DOFS greater than 1.1. Figure 2 shows the mean δD and standard deviation of δD for each transect (thin gray line), and the overall average (thick black line). At the near-surface pres- sure level, the TES retrieval is somewhat influenced by the prior. This is also true at altitudes above 10 000 m. The stan- dard deviation of δD has one peak at approximately 2000 m altitude (826 hPa pressure level) and another broad peak at 5000 to 7000 m altitude (511 to 422 hPa pressure levels) be- cause the peak variability also corresponds to the levels with peak TES sensitivity to HDO / H 2 O. The overall mean δD
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The M 2 AV has a wingspan of 2 m and a maximum take-off weight of approximately 6 kg including 1.5 kg meteorologi- cal equipment. The cruising speed of about 22 m s −1 and the power supply for about 50 to 60 min of flight allow flight distances of up to 70 km. The M 2 AV is automatically oper- ated by an electronic autopilot (see below). This allows for measurement flights in the lower ABL over larger distances outside the range of sight and in remote areas. Thereby, the M 2 AV follows the flight pattern which was sent to the aircraft before take-off (van den Kroonenberg et al., 2008). Within the telemetry range of 5 km the ground staff is able to fol- low and monitor the position, attitude and speed of the air- craft. Changes of the waypoints and altitudes are possible within that range. Figure 1 shows the M 2 AV flying near the Meteorological Observatory Lindenberg – Richard-Aßmann- Observatory (MOL-RAO) during the LITFASS-2009 cam- paign.
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The NCAR/NSF High-performance Instrumented Airborne Platform for Environmental Research (HIAPER), is a mod- ified Gulfstream V (GV) jet which hosted the Stratosphere- Troposphere Analyses of Regional Transport 2008 (START- 08) campaign (Pan et al., 2010) and the preliminary HIA- PER Pole-to-Pole Observations (pre-HIPPO) campaign dur- ing 2008. The two campaigns shared flight time and instru- mentation and made observations across North America, in- cluding a vertical profile above the Park Falls site in May, 2008. The HIAPER Pole-to-Pole Observations (HIPPO-1) campaign (Wofsy et al., 2010) covered a cross-section of the globe that spanned the Arctic to the Antarctic (Fig. 1) with profiles over Lamont and Lauder in January, 2009. The START-08/pre-HIPPO and HIPPO-1 missions used similar in situ instrumentation (Table 2). The water profiles are from the available H 2 O measurements on board the aircraft (e.g.,
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Programmable Flask Packages (PFPs) are used to col- lect discrete air samples on the C-130 flights. These air- sampling devices are used routinely on aircraft as part of the NOAA/ESRL Global Monitoring Division’s Car- bon Cycle and Greenhouse Gases network (Sweeney et al., 2013, and http://www.esrl.noaa.gov/gmd/ccgg/aircraft/ index.html). The PFP is composed of twelve 0.7 L borosili- cate glass flasks with glass valves sealed with Teflon O-rings at each end, a stainless steel manifold, and a data logging and control system. The 7.5 cm diameter cylindrical flasks are stacked in two rows of six. The flexible manifold con- nects all of the flasks in parallel on the inlet side of the flasks. The data logger records actual sample flush volumes and fill pressures during sampling, along with system sta- tus, GPS position, ambient (outside the aircraft) temperature, and relative humidity. One or two PFPs are sampled on each flight (12 or 24 flasks). A rack-mounted Programmable Com- pressor Package (PCP) that contains two air pumps (KNF- Neuberger MPU1906-N828-9.06 and PU1721-N811-3.05) with aluminum heads and Viton diaphragms plumbed in se- ries is used to flush and pressurize the flasks.
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For the tile that covers part of western Europe most of the spurious data are removed by the slope test; a majority of data removed by this test is because of missing SRTM DEM values over the sea. The elevation test, area under the first Gaussian test and neighbour test each remove ap- proximately 3 % of the data. For tropical forests the largest amount of data, about 35 %, is removed by the area under the first Gaussian test. About 10 % is removed by the differ- ence in elevation test, amplitude test and the neighbours test. The elevation test is principally intended to eliminate cloud contaminated data. When more aircraft LiDAR data become available for these regions it may be justified to relax the 8 m uncertainty range over dense forests to acknowledge the greater uncertainty in the SRTM and GLAS elevation data. The large effect of the area under the first Gaussian test may indicate problems with the ground return of the waveform for dense vegetation canopies. Therefore, in Sect. 4.2 it is inves- tigated how much the canopy height changes in response to changing the thresholds for the filters.
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Yet despite recommendations to do so (Mattson, Crider & Whittington, 1999; Mattson, Petrin & Young, 2001; Reithmaier, 2001; Munro, Kanki & Jordan, 2008; Ford, 2011) there has been little interest in extending CRM to incorporate maintenance personnel who, by the very nature of their job, are required to interact with flight crew on a daily basis. This may be due to the fact that, unlike those high-profile accidents where a breakdown in communication between pilots and cabin crew or pilots and air traffic controllers has been cited as contributing significantly to the outcome, there have been no such equivalent accidents due to poor communication between pilots and aircraft maintenance engineers. That is not to say, however, that communication deficiencies have not contributed in some form to at least one accident. A lack of teamwork and ineffective communication between a maintenance engineer and the flight crew has been highlighted by Latorella and Prabhu (2000) in the loss of a Nationair DC-8 in 1991. Although this is only one such example, it is important to acknowledge that the absence of accidents is not necessarily indicative of a healthy state of affairs (Reason, 1990; 1997). Heinrich’s (1931) ‘iceberg’ model (Figure 1.1) is one such expression of this in the safety literature despite a certain amount of criticism regarding the validity of the actual ratios 6 .
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Accurate information regarding the maintenance status of an aircraft is essential for safe and efficient airline operations, yet there is evidence to suggest that pilots and line maintenance engineers do not always communicate effectively with each other. To date the majority of this evidence has been anecdotal, and formal studies have focused primarily on the shortcomings of the aircraft logbook as a communication medium. Despite the notion that poor communication between these two groups can potentially have undesirable consequences, there has been little discussion about how this might manifest within an airline environment. The studies undertaken for this research examined three distinct aspects of the pilot-maintenance interface: 1) the intergroup relationship between airline pilots and line maintenance engineers, 2) operational radio communications between airline pilots and line maintenance engineers, and 3) the effects of deficient pilot-maintenance communication on aircraft operations and flight safety. Thematically analysed discourse from a series of focus groups held at a large New Zealand airline, found that communication difficulties are primarily the result of an interrelating set of organisational, physical and psychosocial barriers, all of which influence the nature of the intergroup relationship between pilots and line maintenance engineers. The use of Interaction Process Analysis (IPA) to examine radio calls between pilots and maintenance personnel identified that while the two groups share similar communication patterns and styles, indications of these barriers were present within their communication exchanges. The effects of deficient communication were then examined using data from the United States Aviation Safety Reporting System (ASRS). Using Correspondence Analysis (CA) to map associations between deficient pilot-maintenance communication and adverse outcomes, evidence was found that poor communication can be associated with both schedule disruptions and potential safety ramifications.
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Each of the satellite instruments makes both daytime and nighttime measurements. For a given region, these measurements are separated by about 12 hours. The frequency of coverage for a given region is daily for IASI, and every other day for AIRS. However, local cloudiness and other weather conditions may prevent measurements on any particular day. Because the flux of infrared radiation from the Earth is higher during the daytime than at night, the daytime measurements generally have a lower uncertainty than the nighttime measurements. The ground- based continuous monitor used in the North Carolina case study (Chapter 3), shows a consistent diurnal pattern, with the NH 3 concentration peaking between 10 a.m. and 3 p.m. local standard
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different locations and seasons within the upper tropo- sphere, the tropical tropopause layer (TTL), and stratosphere. In the present context the most important were measure- ments performed within the TTL (for the definition of TTL, see Fueglistaler et al., 2009) over the Pacific from where most of the stratospheric air is predicted to originate (e.g., Fueglistaler et al., 2009; Aschmann et al., 2009; Hossaini et al., 2012b; Ashfold et al., 2012; WMO, 2014; Orbe et al., 2015). These include the measurements (a) by Schauffler et al. (1993, 1998, 1999), who found [VSLS] = 1.3 ppt (con- tribution 3) at the tropical tropopause over the central Pacific (Hawaii) in 1996, (b) by Laube et al. (2008) and Brinckmann et al. (2012), with [VSLS] = 2.25 ± 0.24 ppt (range 1.4– 4.6 ppt) and [VSLS] = 1.35 ppt (range 0.7–3.4 ppt) found within the TTL over northeastern Brazil in June 2005 and June 2008, respectively, and (c) most recently by Navarro et al. (2015), who found [VSLS] = 2.96 ± 0.42 and 3.27 ± 0.49 ppt at 17 km over the tropical eastern and west- ern Pacific in 2013 and 2014, respectively. Information on contribution 3 was further corroborated by measurements performed in the upper tropical troposphere by Sala et al. (2014), who found [VSLS] = 3.72 ± 0.60 ppt in the upper tropical troposphere over Borneo in fall 2011, and by Wisher et al. (2014), who inferred [VSLS] = 3.4 ± 1.5 ppt for the CARIBIC (Civil Aircraft for the Regular Investigation for the Atmosphere Based on an Instrument Container) flights from Germany to Venezuela and Colombia during 2009– 2011, Germany to South Africa during 2010 and 2011, and Germany to Thailand and Kuala Lumpur, Malaysia, during 2012 and 2013.
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