This dataset contains measurements from the Meteorological Measurement System (MMS) instrument from the four ATom campaigns. MMS is a state-of-the-art instrument for measuring accurate, high resolution in situ airborne state parameters (pressure, temperature, turbulence index, and the 3-dimensional wind vector). These key measurements enable our understanding of atmospheric dynamics, chemistry, and microphysical processes. The MMS is used to investigate atmospheric mesoscale (gravity and mountain lee waves) and microscale (turbulence) phenomena. An accurate characterization of the turbulence phenomenon is important for the understanding of dynamic processes in the atmosphere, such as the behavior of buoyant plumes within cirrus clouds, diffusions of chemical species within wake vortices generated by jet aircraft, and microphysical processes in breaking gravity waves. Accurate temperature and pressure data are needed to evaluate chemical reaction rates as well as to determine accurate mixing ratios. Accurate wind field data establish a detailed relationship with the various constituents and the measured wind also verifies numerical models used to evaluate air mass origin.

This dataset provides Modeling Data Stream (MDS) and Reactivity Data Stream (RDS) products for each of the four ATom campaigns conducted from 2016 to 2018. MDS files contain the atmospheric constituents needed to model the RDS of the air parcels along ATom flight paths. The MDS is a continuous data stream (every 10 seconds) of the atmospheric content of these key chemical species derived from the in-situ measurements collected along ATom flight paths (as reported in the comprehensive related dataset ATom: Merged Atmospheric Chemistry, Trace Gases, and Aerosols). Values for chemical species measured by multiple instruments were selected from the instrument with better coverage and/or greater precision. Missing values were filled using interpolation for short gaps. For long gaps owing to instrument failure, values were estimated using multiple linear regressions from comparable parallel flights from other ATom campaigns. All species were flagged for instrument source and values were flagged for gap-filling status. In combination, MDS and RDS provide, in essence, a photochemical climatology for each air parcel along ATom flight paths containing the reactive species that control the loss of methane and the production and loss of ozone.

This dataset provides results of selected in-situ measurements of airflow and aerosol particles collected during the following airborne campaigns: NASA Atmospheric Tomography (ATom), Saharan Aerosol Long-range Transport and Aerosol-Cloud-interaction Experiment (SALTRACE), and Absorbing aerosol layers in a changing climate: aging, lifetime and dynamics (A-LIFE). The airborne campaigns were conducted between 2013-06-10 and 2018-05-21. Depending upon the aircraft instrumentation per flight and campaign, the data include aircraft position, relative humidity, temperature, pressure, angle of attack (AOA), the probe location, true and probe air speeds, and aerosol particle diameters as extracted from Cloud Imaging Probe (CIP) images for the ATom and A-LIFE flights. Also provided are the results of combining the airborne data with numerical modeling to simulate particle sampling efficiency. Simulations investigated how airflow around wing-mounted instruments affected sampling efficiency and the induced errors for different realistic flight conditions.

The NAMMA DC-8 Meteorological Measurement System (MMS) dataset used the MMS, which consists of three major systems: an air-motion sensing system to measure air velocity with respect to the aircraft, an aircraft-motion sensing system to measure the aircraft velocity with respect to the Earth, and a data acquisition system to sample, process, and record the measured quantities. The air-motion system consists of two airflow-angle probes, three total temperature probes each with a different response time, a pitot-static pressure probe, and a dedicated static pressure system. All probes and sensors are judiciously located at specific positions of the fuselage. The aircraft-motion sensing system consists of an embedded GPS ring laser inertial navigation system, and a multiple-antenna GPS attitude reference system. Customized software was developed to control, sample, and process all sensors and hardware. These data files were generated during support of the NASA African Monsoon Multidisciplinary Analyses (NAMMA) campaign, a field research investigation sponsored by the Science Mission Directorate of the National Aeronautics and Space Administration (NASA). This mission was based in the Cape Verde Islands, 350 miles off the coast of Senegal in west Africa. Commencing in August 2006, NASA scientists employed surface observation networks and aircraft to characterize the evolution and structure of African Easterly Waves (AEWs) and Mesoscale Convective Systems over continental western Africa, and their associated impacts on regional water and energy budgets.

The NAMMA DC-8 Meteorological Measurement System (MMS) dataset used the MMS, which consists of three major systems: an air-motion sensing system to measure air velocity with respect to the aircraft, an aircraft-motion sensing system to measure the aircraft velocity with respect to the Earth, and a data acquisition system to sample, process, and record the measured quantities. The air-motion system consists of two airflow-angle probes, three total temperature probes each with a different response time, a pitot-static pressure probe, and a dedicated static pressure system. All probes and sensors are judiciously located at specific positions of the fuselage. The aircraft-motion sensing system consists of an embedded GPS ring laser inertial navigation system, and a multiple-antenna GPS attitude reference system. Customized software was developed to control, sample, and process all sensors and hardware. These data files were generated during support of the NASA African Monsoon Multidisciplinary Analyses (NAMMA) campaign, a field research investigation sponsored by the Science Mission Directorate of the National Aeronautics and Space Administration (NASA). This mission was based in the Cape Verde Islands, 350 miles off the coast of Senegal in west Africa. Commencing in August 2006, NASA scientists employed surface observation networks and aircraft to characterize the evolution and structure of African Easterly Waves (AEWs) and Mesoscale Convective Systems over continental western Africa, and their associated impacts on regional water and energy budgets.

The Alpha Jet Atmospheric eXperiment (AJAX) is a partnership between NASA's Ames Research Center and H211, L.L.C., facilitating routine in-situ measurements over California, Nevada, and the coastal Pacific in support of satellite validation. The standard payload complement includes rigorously-calibrated ozone (O3), formaldehyde (HCHO), carbon dioxide (CO2), and methane (CH4) mixing ratios, as well as meteorological data including 3-D winds. Multiple vertical profiles (to ~8.5 km) can be accomplished in each 2-hr flight. The AJAX project has been collecting trace gas data on a regular basis in all seasons for over a decade, helping to assess satellite sensors' health and calibration over significant portions of their lifetimes, and complementing surface and tower-based observations collected elsewhere in the region.AJAX supports NASA's Orbiting Carbon Observatory (OCO-2/3) and Japan's Greenhouse Gases Observing Satellite (GOSAT) and GOSAT-2, and collaborates with many other research organizations (e.g. California Air Resources Board (CARB), NOAA, United States Forest Service (USFS), Environmental Protection Agency (EPA)). AJAX celebrated its 200th science flight in 2016, and previous studies have investigated topics as varied as stratospheric-to-tropospheric transport, forest fire plumes, atmospheric river events, long-range transport of pollution from Asia to the western US, urban outflow, and emissions from gas leaks, oil fields, and dairies.

This dataset contains cloud type and coarse aerosol contents measured by the University of Vienna's second-generation Cloud Aerosol and Precipitation Spectrometer (CAPS) instrument mounted to the NASA DC-8 aircraft during the four ATom campaigns that occurred from 2016 to 2018. CAPS measures particle size distributions in a size range between nominally 0.5 micrometers and 960 micrometers. The sizes range between approximately 0.5 and 50 micrometers is covered by the optical particle counter component of CAPS-the Cloud and Aerosol Spectrometer with Depolarization Detection (CAS-DPOL). The sizes range from 15 to 930 micrometers is measured with the optical array probe called Cloud imaging Probe (CIP). Cloud types are determined using an algorithm developed to detect and classify clouds using measurements of CAPS. Relative humidity and temperature are considered by the algorithm. The cloud indicator provides a classification on a 1 Hz basis and separates data in cloud-free, aerosol-cloud transition regime (ACTR), liquid clouds, clouds in the mixed-phase temperature regime (MPTR), and cirrus clouds. The coarse aerosol product provides cloud and aerosol particle number concentrations at standard pressure (1013.25 hPa) and standard temperature (273.15 K) in selected size ranges. Particle sizes refer to ammonium sulfate optical equivalent diameter (m=1.52 + 0.0i).

This dataset contains single-particle aerosol composition as measured by the Particle Analysis by Laser Mass Spectrometry (PALMS) instrument during the four ATom campaigns from 2016-2018. Single aerosol particles are classified into several particle types, including: mixed sulfate/organic nitrate, biomass burning, elemental carbon, mineral/metallic, meteoric material, alkali salt, sea salt, heavy oil combustion, and others. Particle types are reported as raw number fractions and as absolute mass concentrations. PALMS measures aerosol composition for particles from diameter ~100 to 5000 nm, with most of the particle data in the size range ~150 to 3000 nm. Also included are absolute aerosol concentrations measured by a modified Laser Aerosol Spectrometer (LAS). Integrated number, surface area, and volume concentrations from LAS are reported over multiple size ranges.

This dataset provides results of selected in-situ measurements of airflow and aerosol particles collected during the following airborne campaigns: NASA Atmospheric Tomography (ATom), Saharan Aerosol Long-range Transport and Aerosol-Cloud-interaction Experiment (SALTRACE), and Absorbing aerosol layers in a changing climate: aging, lifetime and dynamics (A-LIFE). The airborne campaigns were conducted between 2013-06-10 and 2018-05-21. Depending upon the aircraft instrumentation per flight and campaign, the data include aircraft position, relative humidity, temperature, pressure, angle of attack (AOA), the probe location, true and probe air speeds, and aerosol particle diameters as extracted from Cloud Imaging Probe (CIP) images for the ATom and A-LIFE flights. Also provided are the results of combining the airborne data with numerical modeling to simulate particle sampling efficiency. Simulations investigated how airflow around wing-mounted instruments affected sampling efficiency and the induced errors for different realistic flight conditions.

This dataset contains cloud type and coarse aerosol contents measured by the University of Vienna's second-generation Cloud Aerosol and Precipitation Spectrometer (CAPS) instrument mounted to the NASA DC-8 aircraft during the four ATom campaigns that occurred from 2016 to 2018. CAPS measures particle size distributions in a size range between nominally 0.5 micrometers and 960 micrometers. The sizes range between approximately 0.5 and 50 micrometers is covered by the optical particle counter component of CAPS-the Cloud and Aerosol Spectrometer with Depolarization Detection (CAS-DPOL). The sizes range from 15 to 930 micrometers is measured with the optical array probe called Cloud imaging Probe (CIP). Cloud types are determined using an algorithm developed to detect and classify clouds using measurements of CAPS. Relative humidity and temperature are considered by the algorithm. The cloud indicator provides a classification on a 1 Hz basis and separates data in cloud-free, aerosol-cloud transition regime (ACTR), liquid clouds, clouds in the mixed-phase temperature regime (MPTR), and cirrus clouds. The coarse aerosol product provides cloud and aerosol particle number concentrations at standard pressure (1013.25 hPa) and standard temperature (273.15 K) in selected size ranges. Particle sizes refer to ammonium sulfate optical equivalent diameter (m=1.52 + 0.0i).