Antarctic atmospheric boundary layer observations with the Small Unmanned Meteorological Observer (SUMO)

Between&nbsp;January&nbsp;2012 and June&nbsp;2017 a small unmanned aerial system (sUAS), known as the Small Unmanned Meteorological Observer (SUMO), was used to observe the state of the atmospheric boundary layer in the Antarctic. During six Antarctic field campaigns, 116 SUMO flights were completed. These flights took place during all seasons over both permanent ice and ice-free locations on the Antarctic continent and over sea ice in the western Ross Sea. Sampling was completed during spiral ascent and descent flight paths that observed the temperature, humidity, pressure and wind up to 1000&thinsp;m above ground level and sampled the entire depth of the atmospheric boundary layer, as well as portions of the free atmosphere above the boundary layer. A wide variety of boundary layer states were observed, including very shallow, strongly stable conditions during the Antarctic winter and deep, convective conditions over ice-free locations in the summer. The Antarctic atmospheric boundary layer data collected by the SUMO sUAS, described in this paper, can be retrieved from the United States Antarctic Program Data Center (https://www.usap-dc.org, last access: 8&nbsp;March&nbsp;2021). The data for all flights conducted on the continent are available at https://doi.org/10.15784/601054 (Cassano, 2017), and data from the Ross Sea flights are available at https://doi.org/10.15784/601191 (Cassano, 2019). </div

Observations of the atmosphere and surface state over Terra Nova Bay, Antarctica, using unmanned aerial systems

In September 2012 five Aerosonde unmanned aircraft were used to make measurements of the atmospheric state over the Terra Nova Bay polynya, Antarctica, to explore the details of air–sea ice–ocean coupling. A total of 14 flights were completed in September 2012. Ten of the flight missions consisted of two unmanned aerial systems (UAS) sampling the atmosphere over Terra Nova Bay on 5 different days, with one UAS focusing on the downwind evolution of the air mass and a second UAS flying transects roughly perpendicular to the low-level winds. The data from these coordinated UAS flights provide a comprehensive three-dimensional data set of the atmospheric state (air temperature, humidity, pressure, and wind) and surface skin temperature over Terra Nova Bay. The remaining UAS flights during the September 2012 field campaign included two local flights near McMurdo Station for flight testing, a single UAS flight to Terra Nova Bay, and a single UAS flight over the Ross Ice Shelf and Ross Sea polynya. A data set containing the atmospheric and surface data as well as operational aircraft data have been submitted to the United States Antarctic Program Data Coordination Center (USAP-DCC)

Remote and Autonomous Measurements of Precipitation for the Northwest Ross Ice Shelf, Antarctica

The Antarctic Precipitation System project deployed and maintained four sites across the northwestern Ross Ice Shelf in Antarctica from November&nbsp;2017 to November&nbsp;2019. The goals for the project included the collection of in situ observations of precipitation in Antarctica spanning a duration of 2&nbsp;years, an improvement in the understanding of precipitation events across the Ross Ice Shelf, and the ability to validate precipitation data from atmospheric numerical models. At each of the four sites the precipitation was measured with an OTT Pluvio2 precipitation gauge. Additionally, snow accumulation at the site was measured with a sonic ranging sensor and using GPS interferometric reflectivity. Supplemental observations of temperature, wind speed, particle count, particle size and speed, and images and video from a camera were collected to provide context to the precipitation measurements. The collected dataset represents some of the first year-round observations of precipitation in Antarctica at remote locations using an autonomous measurement system. The acquired observations have been quality-controlled and post-processed, and they are available for retrieval through the United States Antarctic Program Data Center (https://doi.org/10.15784/601441, Seefeldt, 2021). </div

Process-resolving Regional Arctic System Model for Advanced Modeling and Prediction of Arctic Climate System

15th Conference on Polar Meteorology and OceanographyThe Regional Arctic System Model (RASM) is a fully coupled limited-domain ice-ocean-atmosphere-land hydrology model. Its domain is pan-Arctic, with the atmosphere and land components configured on a 50-km or 25-km grid. The ocean and sea ice components are configured on rotated sphere meshes with four configuration options: 1/12o (~9.3km) or 1/48o (~2.4km) in the horizontal space and with 45 or 60 vertical layers. As a regional climate model, RASM requires boundary conditions along its lateral boundaries and in the upper atmosphere, which are derived either from global atmospheric reanalyses for simulations of the past to present or from Earth System models (ESMs) for climate projections. In the former case, this allow comparison of RASM results with observations in place and time, which is a unique capability not available in global ESMs. RASM has been developed and used to investigate critical processes controlling the evolution of the Arctic climate system under a diminishing sea ice cover. Several examples of key physical processes and coupling between different model components will be presented, that improve the representation of the past and present Arctic climate system. The impact of such processes and feedbacks will be discussed with regard to improving model physics and reducing biases in the representation of its initial state for prediction of Arctic climate at time scales from synoptic to intra-annual

High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections

The article of record as published may be found at https://agu.confex.com/agu/osm20/meetingapp.cgi/Paper/641925Ocean Sciences Meeting 2020The Arctic is one of the most challenging regions to model climate change due to its complexity, including the cryosphere, small scale processes and feedbacks controlling its amplified response to global climate change. The combination of these factors defines the need for high spatial and temporal model resolution, which is commonly not practical for most state-of-the-art global Earth system models (ESMs), including those participating in the Coupled Model Intercomparison Project Phase 6. We offer an alternative approach to improve model physics and reduce uncertainties in modeling Arctic climate using a high resolution regional climate system model for dynamical downscaling of output from ESMs. The Regional Arctic System Model (RASM) has been developed to better understand the past and present operation of the Arctic climate system and to predict its change at time scales up to decades. RASM is a coupled model, consisting of the atmosphere, ocean, sea ice, land hydrology and river routing scheme components. Its domain is pan-Arctic, with 50-km or 25-km grids for the atmosphere and land components. The ocean and sea ice components are configured at ~9.3-km or ~2.4-km grids horizontally and with 45 or 60 vertical layers. For hindcast simulations, RASM derives boundary conditions from global atmospheric reanalyses, allowing comparison with observations in place and time, which is a unique capability not available with ESMs. We will discuss improvements to RASM model physics offered by high resolution and in generation of internally consistent realistic initial conditions for Arctic climate prediction. We will also discuss the need for fine-tuning of scale aware parameterizations of sub-grid physical processes in varying model configurations. Finally, selected results will be presented to demonstrate gains of dynamical downscaling in comparison with observations and with the global reanalysis and predictions

Cryo-annealing of Photoreduced CdS Quantum Dot–Nitrogenase MoFe Protein Complexes Reveals the Kinetic Stability of the E₄(2N2H) Intermediate

A critical step in the mechanism of N2 reduction to 2NH3 catalyzed by the enzyme nitrogenase is the reaction of the four-electron/four-proton reduced intermediate state of the active-site FeMo-cofactor (E4(4H)). This state is a junction in the catalytic mechanism, either relaxing by the reaction of a metal bound Fe-hydride with a proton forming H2 or going forward with N2 binding coupled to the reductive elimination (re) of two Fe-hydrides as H2 to form the E4(2N2H) state. E4(2N2H) can relax to E4(4H) by the oxidative addition (oa) of H2 and release of N2 or can be further reduced in a series of catalytic steps to release 2NH3. If the H2 re/oa mechanism is correct, it requires that oa of H2 be associative with E4(2N2H). In this report, we have taken advantage of CdS quantum dots in complex with MoFe protein to achieve photodriven electron delivery in the frozen state, with cryo-annealing in the dark, to reveal details of the E-state species and to test the stability of E4(2N2H). Illumination of frozen CdS:MoFe protein complexes led to formation of a population of reduced intermediates. Electron paramagnetic resonance spectroscopy identified E-state signals including E2 and E4(2N2H), as well as signals suggesting the formation of E6 or E8. It is shown that in the frozen state when pN2 is much greater than pH2, the E4(2N2H) state is kinetically stable, with very limited forward or reverse reaction rates. These results establish that the oa of H2 to the E4(2N2H) state follows an associative reaction mechanism