The Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE) cruise in the Gulf of Mexico (GOM) was conducted in May 2019 by NASA and the Bureau of Ocean Energy Management to determine the feasibility of using satellite data to measure air quality (AQ) in a region of concentrated oil and natural gas (ONG) operations. SCOAPE featured nitrogen dioxide (NO2) instrumentation (Pandora, Teledyne API analyzer) at Cocodrie, LA (29.26°, -90.66°), and on the Research Vessel Point Sur operating off the Louisiana coast with measurements of ozone, carbon monoxide (CO) and volatile organic compounds (VOC). The findings: (1) both satellite and Pandora NO2 observations revealed two AQ regimes over the GOM, the first influenced by tropical air in 10-14 May, the second influenced by flow from urban areas on 15-17 May; (2) Comparisons of OMI v4 and TROPOMI v1.3 TC (total column) NO2 data with all Pandora NO2 column observations on the Point Sur averaged 13% agreement with the largest difference during 15-17 May (~20%). At Cocodrie, LA, at the same time, the satellite-Pandora agreement was ~5%. (3) Three new-model Pandora instruments displayed a TC NO2 precision of 0.01 Dobson Units (~5%); (4) Regions of smaller and older operations displayed high methane (CH4) readings, presumably from leakage; VOC were also detected at high concentrations. Given an absence of regular AQ data in and near the GOM, SCOAPE data constitute a baseline against which future observations can be compared.

Speleothem oxygen isotope records (δ18O) of tropical South American rainfall in the late Quaternary show a zonal “South American Precipitation Dipole” (SAPD). The dipole is characterized by opposing east-west precipitation anomalies compared to the present—wetter in the east and drier in the west at the mid-Holocene (∼7 ka), and drier in the east and wetter in the west at the Last Glacial Maximum (LGM; ∼21 ka). However, the SAPD remains enigmatic because it is expressed differently in western versus eastern δ18O records and isotope-enabled climate model simulations usually misrepresent the magnitude and/or spatial pattern of δ18O change. Here, we address the SAPD enigma in two parts. First, we re-interpret the δ18O data to account for upwind rainout effects that are known to be pervasive in tropical South America, but are not always considered in Quaternary paleoclimate studies. Our revised interpretation reconciles the δ18O data with cave infiltration and other proxy records, and indicates that the centroid of tropical South American rainfall has migrated zonally over time. Second, using an energy balance model of tropical atmospheric circulation, we hypothesize that zonal migration of the precipitation centroid can be explained by regional energy budget shifts, such as changing Saharan albedo associated with the African Humid Period, that have not been modeled in previous SAPD studies. This hypothesis of a migrating precipitation centroid presents a new framework for interpreting δ18O records from tropical South America and may help explain the zonal rainfall anomalies that predate the late Quaternary.

Amongst various applications that experience a multi-directional particle source is the muon scattering tomography where a number of horizontal detectors of a limited angular acceptance conventionally track the cosmic-ray muons. In this study, we exhibit an elementary strategy that might be at disposal in diverse computational applications in the GEANT4 simulations with the purpose of hemispherical particle sources. To further detail, we initially generate random points on a spherical surface for a sphere of a practical radius by employing Gaussian distributions for the three components of the Cartesian coordinates, thereby obtaining a generating surface for the initial positions of the corresponding particles. Since we do not require the half bottom part of the produced spherical surface for our tomographic applications, we take the absolute value of the vertical component in the Cartesian coordinates by leading to a half-spherical shell, which is traditionally called a hemisphere. Last but not least, we direct the generated particles into the target material to be irradiated by favoring a selective momentum direction that is based on the vector construction between the random point on the hemispherical surface and the origin of the target material, hereby optimizing the particle loss through the source biasing. We also show a second scheme where the coordinate transformation is performed between the spherical coordinates and the Cartesian coordinates, and the above-mentioned procedure is applied to orient the generated muons towards the target material. In the end, a recipe hinged on the restrictive planes from our previous study is furthermore provided, and we incorporate our strategies by using G4ParticleGun in the GEANT4 code. While we plan to exert our strategy in the computational practices for muon scattering tomography, these source schemes might find its straightforward applications in different neighboring fields including but not limited to atmospheric sciences, space engineering, and astrophysics where a 3D particle source is a necessity for the modeling goals.

The structural characterization of the sealed or shielded nuclear materials constitutes an indispensable aspect that necessitates a careful transportation, a limited interaction, and under certain circumstances an on-site investigation for the nuclear fields including but not limited to nuclear waste management, nuclear forensics, and nuclear proliferation. To attain this purpose, among the promising non-destructive/non-hazardous techniques that are performed for the interrogation of the nuclear materials is the muon tomography where the target materials are discriminated by the interplay between the atomic number, the material density, and the material thickness on the basis of the scattering angle and the absorption in the course of the muon propagation within the target volume. In this study, we employ the Monte Carlo simulations by using the GEANT4 code to demonstrate the capability of muon tomography based on the dual-parameter analysis in the examination of the nuclear waste barrels. Our current hodoscope setup consists of three top and three bottom plastic scintillators made of polyvinyl toluene with the thickness of 0.4 cm, and the composite target material is a cylindrical nuclear waste drum with the height of 96 cm and the radius of 29.6 cm where the outermost layer is stainless steel with the lateral thickness of 3.2 cm and the filling material is ordinary concrete that encapsulates the nuclear materials of dimensions 20×20×20 cm3. By simulating with a narrow planar muon beam of 1×1 cm 2 over the uniform energy interval between 0.1 and 8 GeV, we determine the variation of the average scattering angle together with the standard deviation by utilizing a 0.5-GeV bin length, the counts of the scattering angle by using a 1-mrad step, and the number of the absorption events for the five prevalent nuclear materials starting from cobalt and ending in plutonium. Via the duo-parametric analysis that is founded on the scattering angle as well as the absorption in the present study, we show that the presence of the nuclear materials in the waste barrels is numerically visible in comparison with the concrete-filled waste drum without any nuclear material, and the muon tomography is capable of distinguishing these nuclear materials by coupling the information about the scattering angle and the number of absorption in the cases where one of these two parameters yields strong similarity for certain nuclear materials.

Dust is a meteorological phenomenon that has a strong impact on the environment, air quality, and human health. In the USA one of the most widely used databases of information on dust events is the Storm Events Database (SED). This project aims to examine the reliability and usefulness of the SED as a source for documenting the climatology of dust storms (DS) across the USA. While SED provides information potentially useful for understanding the frequency, distribution, and importance of DS across the USA, our analysis of DS from 2000 to 2020 shows that many DS were missing while some recorded events of less severe blowing dust (BLDU) in the SED were incorrectly reported as DS. Although the dust records from SED have been widely utilized to study dust related physical and societal issues, the limitations found in this study need to be taken into consideration in future studies.

Electric field mills are used popularly for atmospheric electric field measurements. Atmospheric Electric Field variation is the primary signature for Lightning Early Warning systems. There is a characteristic change in the atmospheric electric field before lightning during a thundercloud formation. A voltage controlled variable capacitance is being proposed as a method for non-contacting measurement of electric fields. A varactor based mini electric field measurement system is developed, to detect any change in the atmospheric electric field and to issue lightning early warning system. Since this is a low-cost device, this can be used for developing countries which are facing adversities. A network of these devices can help in forming a spatial map of electric field variations over a region, and this can be used for more improved atmospheric electricity studies in developing countries.

In this work we extend previous studies by exploring the potential impact of spectroscopic knowledge along with atmospheric state knowledge on retrievals of carbon dioxide (XCO2) and methane (XCH4) column amounts from laser differential absorption spectrometer (LAS) measurements. This has been done for multiple CO2 absorption lines in the 1.57 and 2.05 μm regions, and for CH4 in the 1.65 μm region. One such potential source of error in performing XCO2 retrievals is modeled surface pressure. Since it has been proposed to derive surface pressure from LAS-based O2 measurements in lieu of modeled surface pressure for use in XCO2 retrievals as a means of error reduction, our past work has also attempted to characterize and quantify potential improvements in XCO2 retrieval error associated with O2-derived surface pressure for a set of CO2 and O2 absorption line combinations. All of our previous analyses have relied on a radiative-transfer-based simulation framework utilizing the Line-by-Line Radiative Transfer Model (LBLRTM), version 12.2 (release date November, 2012). LBLRTM has undergone several upgrades since version 12.2, to include updates to its line parameter database, updates to its continuum model, and bug fixes. Our current work revisits our prior assessments using the latest version of LBLRTM (version 12.8) and comparisons are provided and discussed.

We investigate the Asian Summer Monsoon (ASM) response to global dust emissions in the Coupled Model Intercomparison Project Phase 6 (CMIP6) models, which is the first CMIP to include an experiment with a doubling of global dust emissions relative to their preindustrial levels. Dust emissions cause a strong atmospheric heating over Asia that leads to a pronounced hemispheric energy imbalance. This results in a surface cooling over Asia, an enhanced Indian Sumer Monsoon, and a southward shift of the Western Pacific Intertropical Convergence Zone (ITCZ) that are consistent across models. However, the East Asian Summer Monsoon response shows large uncertainties across models, arising from the diversity in models’ simulated dust emissions, and in the dynamical response to these changes. Our results demonstrate the central role of dust absorption in influencing the ASM, and the importance of accurate dust simulations for constraining the ASM and the ITCZ in climate models.

We present a new statistical interpolation method to estimate fire perimeters from Active Fires detection data from satellite-based sensors, such as MODIS, VIIRS, and GOES-16. Active Fires data is available at varying temporal and spatial resolutions (375m and up several times a day, or 2km every 15 minutes), but pixels are often missing due to clouds or incomplete data. The question arises how to fill in the missing pixels, which is useful, e.g., to distinguish in an automated fashion between a single large fire visible as separate clusters of detection pixels because of cloud cover, and separate fires. We process the satellite data into information when was fire first detected at a location, and when was clear ground without fire detected at the location last. We are then looking for the most likely fire arrival time, which satisfies such constraints. Models at various levels of complexity are possible. Our base assumption in the absence of information to the contrary is that the fire keeps progressing without change, which is expressed as the assumption that the gradient of the fire arrival time is approximately constant. The method is then formulated as an optimization problem to minimize the total change in the gradient of the fire arrival time subject to the constraints given by the data. We consider probabilistic interpretations of the method as well as extensions, such as soft constraints to accommodate the uncertainty of the detection and the uncertainty where exactly the fire is within the pixel. This method is statistical in nature and it does not use fuel information or a fire propagation model. The results are demonstrated on satellite observations of large wildfires in the U.S. in summer 2018 and compared with ground and aerial data.

Ambient air quality (AQ) is an environmental and socio-economic issue increasingly decisive in the sustainable development of a territory. At low density territories of Continental Portugal, a good AQ can contribute to the development of various sectors of activity like health and wellness tourism and organic farming, affecting positively the socio-economic situation. The main goal of this study was to build information on ozone concentration in ambient air for the present and on a climate change scenario. The territory case study – the “cerne do Entre-Norte-e-Centro”–, consists of seven municipalities: Aguiar da Beira, Castro Daire, Moimenta da Beira, Sátão, Sernancelhe, Tarouca and Vila Nova de Paiva. Geographically it belongs to the North and Centre of Mainland Portugal (NUTS II) and the Douro and Dão-Lafões subregions (NUTS III). In this area (151.195 hectares) there is not any station of AQ monitoring. Data provided by the Portuguese Air Quality Network was analysed to determine the spatio-temporal evolution of different pollutants covered by actual Portuguese legislation, with special focus on ozone and nitrogen dioxide. This information was compared with the data provided by Copernicus Atmosphere Monitoring Service. It was build hazard and vulnerability charts as well as the chart of risk to the territory under study. This knowledge will improve the decision-making process in terms of public politics. In addition it contributes to an increased visibility and attractiveness of this area, as a tourism destination through environmental differentiation in this endogenous resource.

Weather extremes have gained great attention to the general public and policy makers recently. Extratropical cyclones, frontal systems and atmospheric rivers are central components of weather over mid latitudes. These phenomena are associated with compound weather conditions, including dramatic changes in temperature, wind and extreme precipitation. In fact, wind extremes and heavy precipitation events occurring in the winter over land in the mid latitudes are mostly associated with extratropical cyclones. It is well known that the Iberian Peninsula, due to its location, is prone to the occurrence of these compound extreme events and associated hazards (Liberato et al., 2013; 2014). In this project our aim is to explore the usage of expert crowdsourcing for annotating weather systems associated to compound hydrometeorological extreme events over the Euro-Atlantic region, so automated methods and computational resources can be optimized in a future hybrid approach. This approach allows a sharing of lessons learned and a common design ground. Atmospheric phenomena annotation aims at bringing new dimensions to current big data problems in climate and atmospheric sciences. Today big data full potential in weather and climate science domain is still restricted by the poor semantic knowledge of data gathered and the inability to correlate data with other domains. Acknowledgements: This work is supported by the Portuguese Science and Technology Foundation (Fundação para a Ciência e Tecnologia – FCT), under the projects UID/GEO/50019/2013 – Instituto Dom Luiz and CMU/CS/0012/2017 – “eCSAAP - expert Crowdsourcing for Semantic Annotation of Atmospheric Phenomena”. Liberato et al. 2013 Nat. Hazards Earth Syst. Sci., 13:2239-2251 doi: 10.5194/nhess-13-2239-2013 Liberato 2014 Weather and Climate Extremes, 5-6: 16-28 doi: 10.1016/j.wace.2014.06.002

Ambient air quality is an increasingly prominent environmental factor within the sustainable development of an urban territory, due to a growing awareness on the harmful and transboundary nature of its effects. The main objective of this work was to build knowledge on the quality of ambient air and climate, in the metropolitan area of Brasília/DF, the capital of Brazil. The experimental procedure was designed so as to allow the response to this objective: a) appealed to the temporal series of pollutants measured in the existing regulatory network in this urban area, in the last 10 years; and the data from the National Institute of Meteorology – NIMET; b) correlated statistically all data analyzed. We found a poor spatial coverage of the network for monitoring of ambient air quality in urban area. The only pollutants measured continuously in Brasília/DF are respirable particles (PM10), which is manifestly insufficient, taking into account the different types of sources found. In this way, it is crucial to raise the level of knowledge about the quality of the resource “air” in this city to become more effective and efficient management. The information now obtained constitutes the basis for developing an urban strategy to increase the resilience of populations potentially affected by this problem, i.e., aims to guide the process of ambient air quality management of this Brazilian city to enable you to hold (when good) or, in other cases are initiated investigations/actions that improve.

The latest launched Sentinel satellite mission, the Sentinel-5 Precursor (Sentinel-5P) is one of the European Space Agency’s (ESA) new mission family – Sentinels. The sole payload on Sentinel-5P is the TROPspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (270 nm to 495 nm), near infrared (675 nm to 775 nm), and shortwave infrared (2305 nm - 2385 nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is providing measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of the 12 Distributed Active Archive Centers (DAACs) within NASA’s Earth Observing System Data and Information System (EOSDIS). The GES DISC archives and supports over a thousand data collections in the Focus Areas of Atmospheric Composition, Water & Energy Cycles, and Climate Variability. Under the End User License Agreement between NASA and ESA, GES DISC is curating TROPOMI Level-1B and Level-2 products and providing information services through enhanced tools and services that offer facile solutions for complex Earth science data and applications. This presentation will demonstrate up-to-date TROPOMI products including earthview radiance, solar irradiance, aerosol layer height, Carbon Monoxide, Nitrogen Dioxide, and cloud, as well as easy ways to access, visualize and subset TROPOMI data.

We use the coincident optical and radio-frequency measurements taken by the FORTE satellite to shed light on common optical signatures recorded by NASA and NOAA lightning imagers during Cloud-to-Ground (CG) lightning. We build flash cluster data for FORTE using the same clustering techniques as GLM and document the optical / RF evolution of an oceanic hybrid -CG flash over its 656 ms duration. The flash began with strong VHF emission from a Narrow Bipolar Event (NBE) that initiated a period of normal bilevel intracloud (IC) activity in two vertical layers (8 km and 12 km) that lasted for 490 ms. VHF waveforms show step leader activity ahead of seawater attachment in the return stroke. All impulsive VHF sources after the stroke come from the lower (8 km layer) only. K-changes are noted following the return stroke, but no subsequent strokes are detected. The optical flash began 136 ms after the NBE RF pulse. 22 of the 30 optical groups were dim and occurred during the in-cloud phase of the flash. This activity included both isolated pulses and sustained periods of illumination over tens of milliseconds. Initial cloud pulses accounted for 23% of the total optical radiance from the flash. Illumination during the return stroke contributed a further 58% of the total radiance, and the K-changes and cloud pulses after the stroke supplied the remaining 19%. These results highlight the benefit of having RF alongside optical lightning measurements for clarifying signatures in the optical data and providing information on their physical origins.

Snow and ice melt processes are a key in Earth’s energy-balance and hydrological cycle. Their quantification facilitates predictions of meltwater runoff as well as distribution and availability of fresh water. They control the balance of the Earth’s ice sheets and are acutely sensitive to climate change. These processes decrease the surface reflectance with unique spectral patterns due to the accumulation of liquid water and light absorbing particles (LAP), that require imaging spectroscopy to map and measure. Here we present a new method to retrieve snow grain size, liquid water fraction, and LAP mass mixing ratio from airborne and spaceborne imaging spectroscopy acquisitions. This methodology is based on a simultaneous retrieval of atmospheric and surface parameters using optimal estimation (OE), a retrieval technique which leverages prior knowledge and measurement noise in an inversion that also produces uncertainty estimates. We exploit statistical relationships between surface reflectance spectra and snow and ice properties to estimate their most probable quantities given the reflectance. To test this new algorithm we conducted a sensitivity analysis based on simulated top-of-atmosphere radiance spectra using the upcoming EnMAP orbital imaging spectroscopy mission, demonstrating an accurate estimation performance of snow and ice surface properties. A validation experiment using in-situ measurements of glacier algae mass mixing ratio and surface reflectance from the Greenland Ice Sheet gave uncertainties of ±16.4 μg/g_ice and less than 3%, respectively. Finally, we evaluated the retrieval capacity for all snow and ice properties with an AVIRIS-NG acquisition from the Greenland Ice Sheet demonstrating this approach’s potential and suitability for upcoming orbital imaging spectroscopy missions.

Fundamental understanding of the climate responses to solar variability is obscured by the large and complex climate variability. This long-standing issue is addressed here by examining climate responses under an extreme solar minimum (ESM) scenario, obtained by making the sun void of all magnetic fields. It is used to drive a whole atmosphere climate model with coupled ocean. The simulations reveal robust responses in the coupled climate system, and elucidate similarities and differences of responses to bottom-up and top-down forcing. Planetary waves (PWs) play a key role in both regional climate and the mean circulation changes. Responses of the largest scale PW during NH and SH winters differ, leading to hemispheric differences in the interplay between dynamical and radiative processes. The analysis exposes remarkable general similarities between climate responses in ESM simulations and those under nominal solar minimum conditions, even though the latter may not appear to be statistically significant.

Collision between ions and neutral particles is an essential characteristic of Earth’s ionosphere. This ion-neutral collision is usually caused by the polarization of neutral particles. This collision can also be caused by charge exchange, if the particle pair is parental, such as atomic oxygen and its ion. The total collision frequency is not the sum of the polarization and charge-exchange components, but is essentially equal to the dominant component. The total is enhanced only around the classic transition temperature, which is near the ionospheric temperature range (typically 200-2000 K). However, the magnitude of this enhancement has differed among previous studies; the maximum enhancement has been reported as 41% and 11% without physical explanation. In the present study, the contribution of the polarization force to the charge-exchange collision is expressed as a simple curved particle trajectory effect. As a result, the maximum enhancement is found to be 22%. It is discussed that the enhancement has been neglected in classic models partly due to confusion with the glancing particle contribution, which adds 10.5% to the polarization component. The enhancement has been neglected presumably also because there has been no functional form to express it. Such an expression is derived in this study.

The F2-layer propagation factor M(3000)F2 is important to ionospheric studies owning to its use in HF radio communication/ionospheric modelling. This study focused on reducing the shortcomings in the use of M(3000)F2 IRI-model for obtaining hmF2, especially in the African equatorial region, by obtaining an empirical ‘constructed model’ (M(3000)F2CM ) using the Korhogo (geomag. lat. 1.26°S, long. 67.38°E, dip.-0.670S) data (M(3000)F2KOR). The data spans 8 years (1993-2000) under magnetically quiet conditions (Ap< 20nT). The Regression method technique was used in obtaining the M(3000)F2CM. The M(3000)F2KOR results revealed that low solar activity (LSA) years have predominantly higher magnitudes than high solar activities (HSA) for all seasons, revealing solar activity dependence. The regression coefficient (R2) for the M(3000)F2KOR versus F10.7 relationship was stronger during the solstices. The associated diurnal equations obtained for all seasons from the regression plot of the M(3000)F2KOR-F10.7 relationship were used to obtained the constructed model equation given by , which allows the prediction of diurnal, seasonal and solar cycle variation of the M(3000)F2 parameter. M(3000)F2CM predicted well when tested at different solar activities. Generally, M(3000)F2CM performed reasonably well in comparison with the IRI model (M(3000)F2IRI) when validated with Ouagadougou (lat. 0.59°S, long. 71.46°E) observed data - M(3000)F2OUA. The %deviation of M(3000)F2CM versus M(3000)F2OUA during HSA and LSA ranges from -10.8- 5.3/-7.6 - 15.8 for solstices/equinoxes; whereas %deviation of M(3000)F2IRI versus M(3000)F2OUA spans -15.5 - 9.2 and -9.7 - 17.7 in similar order of seasons. These results suggest that the new model has a measure of potential for its use in the equatorial region.

Molecular oxygen collides with its first positive ion in the earth’s ionosphere. The collision frequency of this particle pair is used to calculate the electric conductivity. However, for this parental pair there are two collision types, resonant and nonresonant, and the selection of the collision type has been different among previous studies in calculation of conductivity. In the present study we clarify that the nonresonant collision is essential for this pair because relevant temperatures are low. That is, the peak of the ionospheric conductivity is located at altitudes between 100 and 130 km, where the temperatures of ions and neutral particles are usually lower than 600 K, for which nonresonant collision is dominant. The collision frequency would be underestimated by 30% if the resonant collision was assumed at 110-km altitude (where the temperature is 240 K). The impact of this difference on the conductivity is estimated to be small (3%), primarily because molecular nitrogen is much more abundant than molecular oxygen. Although we have confirmed that the nonresonant collision is essential, we also include the resonant type, primarily in case of possible elevated temperature events. A set of ion–neutral collision frequency coefficients for calculating the conductivity is summarized, including other particle pairs, in the Appendices. Small corrections to the classical coefficients are made.

Twilight Photometer observations were carried out at low latitude station Kolhapur (16039’42.2” N, 74014’20.8” E) India, during the period 1 January 2009 to 31 December 2011 to yield a reasonable qualitative picture of the day-to-day variability of the vertical distribution of the atmospheric aerosols from about 6 km to a maximum of 350 km. In this study an attempt was made to observe twilight airglow red lines using the vertical profiles of aerosols. The rate of change of red light due to the twilight airglow shows narrow peaks with ~ 600-1000% rise in intensity than due to aerosol twilight glow. The principal aspiration of this study is to highlight the conspicuous capability of Semiautomatic twilight photometer to study the twilight airglow emission lines. Twilight Photometer, although currently seldom used, is still a very effective and the most appropriate ground based passive remote sensing tool for long-term monitoring of different atmospheric components in a wide range of altitude for day-to-day basis. It is an efficient system having a simple and inexpensive underlying principle of operations, yet exhibits extremely accurate and precise usage and can be operated by even a person of average skill. However, it can be seen that the resultant data was consistent with nearest peer technologies, such as LIDARs, Balloon-Borne instruments, rocket measurements, satellite observations etc. It is the first attempt in India to obtain the twilight airglow data using Twilight photometer.

This study aims at improving understanding of the environments supporting summer MCS initiation in the U.S. Great Plains. A self-organizing map analysis is conducted to identify four types of summer MCS initiation environments during 2004-2017: Type-1 and Type-2 feature favorable large-scale environments, Type-3 has favorable lower-level and surface conditions but unfavorable upper-level circulation, while Type-4 features the most unfavorable large-scale environments. Despite the unfavorable large-scale environment, convection-centered composites reveal the presence of favorable sub-synoptic scale environments for MCS initiation in Type-3 and Type-4. All four types of MCS initiation environments delineate a clear eastward propagating feature in many meteorological fields, such as potential vorticity, surface pressure and equivalent potential temperature, upstream up to 25 west of and ~36 hours before MCS initiation. While the propagating environments and local, non-propagating low-level moisture are important to MCS initiation at the foothill of the Rocky Mountains, MCS initiation in the Great Plains is supported by the coupled dynamical and moisture anomalies, both associated with eastward propagating waves. Hence, the MCSs initiated at the plains can produce more rainfall than those initiated at the foothill due to more abundant moisture supply. By tracking MCSs and mid-tropospheric perturbations (MPs), a unique type of sub-synoptic disturbances with Rocky Mountains origin, it is shown that ~30% of MPs is associated with MCS initiation, mostly in Type-4. Although MPs are related to a small fraction of MCS initiation, MCSs that are associated with MPs tend to produce more rainfall in a larger area with a stronger convective intensity.

We report observations of a magnetosheath jet followed by a period of decelerated background plasma. During this period, THEMIS-A magnetometer showed abrupt disturbances which, in the wavelet spectrum, appeared as prominent and irregular pulsations in two frequency bands (7.6–9.2 and 12–17 mHz) within the Pi2 range. The observations suggest–for the first time to our knowledge–that these pulsations were locally generated by the abrupt magnetic field changes driven by the jet’s interaction with the ambient magnetosheath plasma. Furthermore, similar pulsations, detected by THEMIS-D inside the magnetosphere with a 140 seconds time-lag (which corresponds to the propagation time of a disturbance travelling with Alfvenic speed), are shown to be directly associated with the ones in the magnetosheath, which raises the question of how exactly these pulsations are propagated through the magnetopause.

Surface pressure measurements on Mars have revealed a wide variety of atmospheric phenomena. The Mars Science Laboratory Rover Environmental Monitoring Station pressure sensor dataset is now the longest duration record of surface pressure on Mars. We use the first 2580 martian sols of measurements to identify atmospheric pressure waves with periods of tens of minutes to hours using wavelet analysis on residual pressure after the tidal harmonics are removed. We find these waves have a clear diurnal cycle with strongest activity in the early morning and late evening and a seasonal cycle with the strongest waves in the second half of the martian year (Ls = 180-360°). The strongest such waves of the entire mission occurred during the Mars Year 34 global dust storm. Comparable atmospheric waves are identified using atmospheric modeling with the MarsWRF general circulation model in a “nested” high spatial resolution mode. With the support of the modeling, we find these waves best fit the expected properties of inertia-gravity waves with horizontal wavelengths of O(100s) of km.

We report the first observation of the largest Martian lee wave and its atmospheric characteristics over Arsia Mons Elongated Cloud (AMEC). We analyze the wavelength, the cloud’s height, and wind speed from the lee wave structure. The estimated wind speed is 86±4.9 m/s, with a wavelength of 60± 0.3 km at the height of 55±7 km. This is the largest lee wave structure that appears during dust storm season (Ls=230 to Ls=300) and strongly contributes to the planet’s Aerosol Optical Depth (AOD) level. Estimated AOD varies from 1.7 (Red channel) to 2.5 (Blue channel), and indicates the maximum contribution from the water ice crystal. The estimated angstrom exponent (α) value signifies coarse mode particle presence in the cloud with an effective radius of 3.2μm. The presence of water ice crystal contributes to the albedo level’s increment to 0.8 and signifies the formation temperature for AMEC to be around 190 K.