Improved Micro Rain Radar snow measurements using Doppler spectra post-processing

The Micro Rain Radar 2 (MRR) is a compact Frequency Modulated Continuous Wave (FMCW) system that operates at 24 GHz. The MRR is a low-cost, portable radar system that requires minimum supervision in the field. As such, the MRR is a frequently used radar system for conducting precipitation research. Current MRR drawbacks are the lack of a sophisticated post-processing algorithm to improve its sensitivity (currently at +3 dBz), spurious artefacts concerning radar receiver noise and the lack of high quality Doppler radar moments. Here we propose an improved processing method which is especially suited for snow observations and provides reliable values of effective reflectivity, Doppler velocity and spectral width. The proposed method is freely available on the web and features a noise removal based on recognition of the most significant peak. A dynamic dealiasing routine allows observations even if the Nyquist velocity range is exceeded. Collocated observations over 115 days of a MRR and a pulsed 35.2 GHz MIRA35 cloud radar show a very high agreement for the proposed method for snow, if reflectivities are larger than −5 dBz. The overall sensitivity is increased to −14 and −8 dBz, depending on range. The proposed method exploits the full potential of MRR's hardware and substantially enhances the use of Micro Rain Radar for studies of solid precipitation

Marine and terrestrial influences on ice nucleating particles during continuous springtime measurements in an Arctic oilfield location

Aerosols that serve as ice nucleating particles (INPs) have the potential to modulate cloud microphysical properties and can therefore impact cloud radiative forcing (CRF) and precipitation formation processes. In remote regions such as the Arctic, aerosol–cloud interactions are severely understudied yet may have significant implications for the surface energy budget and its impact on sea ice and snow surfaces. Further, uncertainties in model representations of heterogeneous ice nucleation are a significant hindrance to simulating Arctic mixed-phase cloud processes. We present results from a campaign called INPOP (Ice Nucleating Particles at Oliktok Point), which took place at a US Department of Energy Atmospheric Radiation Measurement (DOE ARM) facility in the northern Alaskan Arctic. Three time- and size-resolved aerosol impactors were deployed from 1 March to 31 May 2017 for offline ice nucleation and chemical analyses and were co-located with routine measurements of aerosol number and size. The largest particles (i.e., ≥&thinsp;3&thinsp;µm or “coarse mode”) were the most efficient INPs by inducing freezing at the warmest temperatures. During periods with snow- and ice-covered surfaces, coarse mode INP concentrations were very low (maximum of 6&thinsp;×&thinsp;10−4&thinsp;L−1 at −15&thinsp;∘C), but higher concentrations of warm-temperature INPs were observed during late May (maximum of 2&thinsp;×&thinsp;10−2&thinsp;L−1 at −15&thinsp;∘C). These higher concentrations were attributed to air masses originating from over open Arctic Ocean water and tundra surfaces. To our knowledge, these results represent the first INP characterization measurements in an Arctic oilfield location and demonstrate strong influences from mineral and marine sources despite the relatively high springtime pollution levels. Ultimately, these results can be used to evaluate the anthropogenic and natural influences on aerosol composition and Arctic cloud properties.</p

JOYCE: Jülich Observatory for cloud evolution

The Jülich Observatory for Cloud Evolution (JOYCE), located at Forschungszentrum Jülich in the most western part of Germany, is a recently established platform for cloud research. The main objective of JOYCE is to provide observations, which improve our understanding of the cloudy boundary layer in a midlatitude environment. Continuous and temporally highly resolved measurements that are specifically suited to characterize the diurnal cycle of water vapor, stability, and turbulence in the lower troposphere are performed with a special focus on atmosphere–surface interaction. In addition, instruments are set up to measure the micro- and macrophysical properties of clouds in detail and how they interact with different boundary layer processes and the large-scale synoptic situation. For this, JOYCE is equipped with an array of state-of-the-art active and passive remote sensing and in situ instruments, which are briefly described in this scientific overview. As an example, a 24-h time series of the evolution of a typical cumulus cloud-topped boundary layer is analyzed with respect to stability, turbulence, and cloud properties. Additionally, we present longer-term statistics, which can be used to elucidate the diurnal cycle of water vapor, drizzle formation through autoconversion, and warm versus cold rain precipitation formation. Both case studies and long-term observations are important for improving the representation of clouds in climate and numerical weather prediction models

The Second ARM Training and Science Application Event : Training the Next Generation of Atmospheric Scientists

Non peer reviewe

The relative impact of cloud condensation nuclei and ice nucleating particle concentrations on phase partitioning in Arctic mixed-phase stratocumulus clouds

This study investigates the interactions between cloud dynamics and aerosols in idealized large-eddy simulations (LES) of Arctic mixed-phase stratocumulus clouds (AMPS) observed at Oliktok Point, Alaska, in April 2015. This case was chosen because it allows the cloud to form in response to radiative cooling starting from a cloud-free state, rather than requiring the cloud ice and liquid to adjust to an initial cloudy state. Sensitivity studies are used to identify whether there are buffering feedbacks that limit the impact of aerosol perturbations. The results of this study indicate that perturbations in ice nucleating particles (INPs) dominate over cloud condensation nuclei (CCN) perturbations; i.e., an equivalent fractional decrease in CCN and INPs results in an increase in the cloud-top longwave cooling rate, even though the droplet effective radius increases and the cloud emissivity decreases. The dominant effect of ice in the simulated mixed-phase cloud is a thinning rather than a glaciation, causing the mixed-phase clouds to radiate as a grey body and the radiative properties of the cloud to be more sensitive to aerosol perturbations. It is demonstrated that allowing prognostic CCN and INPs causes a layering of the aerosols, with increased concentrations of CCN above cloud top and increased concentrations of INPs at the base of the cloud-driven mixed layer. This layering contributes to the maintenance of the cloud liquid, which drives the dynamics of the cloud system.</p

Airborne observations of Arctic air mass transformations during the HALO-(AC)3 campaign

The HALO-(AC)3 campaign was conducted in March and April 2022 to investigate warm air intrusions into the Arctic and marine cold air outbreaks. In coordinated flights over the Arctic, the High Altitude and Long Range Research Aircraft (HALO), equipped with a remote sensing payload and dropsondes, investigated these air mass transformations together with the research aircraft Polar 5 and Polar 6. In this report, we give an overview about the research flights and preliminary results from projects, which are carried out by employees of the Leipzig Institute for Meteorology (LIM).Die HALO-(AC)3 Kampagne wurde im März und April 2022 durchgeführt, umWarmlufteinbrüche in die Arktis und marine Kaltluftausbrüche zu untersuchen. Das 'High Altitude and Long Range Research Aircraft' (HALO), ausgestattet mit Instrumenten zur Fernerkundung und Standardmeteorologiesonden, untersuchte zusammen mit den Forschungsflugzeugen Polar 5 und Polar 6, in koordinierten Flügen über der Arktis, diese Veränderungen der Luftmassen. In diesem Bericht wird eine Übersicht über die durchgeführten Forschungsflüge gegeben und Forschungsprojekte werden vorgestellt, welche von Mitarbeitern des Leipziger Instituts für Meteorologie (LIM) durchgeführt werden

Internet of Things for Environmental Sustainability and Climate Change

Our world is vulnerable to climate change risks such as glacier retreat, rising temperatures, more variable and intense weather events (e.g., floods, droughts, and frosts), deteriorating mountain ecosystems, soil degradation, and increasing water scarcity. However, there are big gaps in our understanding of changes in regional climate and how these changes will impact human and natural systems, making it difficult to anticipate, plan, and adapt to the coming changes. The IoT paradigm in this area can enhance our understanding of regional climate by using technology solutions, while providing the dynamic climate elements based on integrated environmental sensing and communications that is necessary to support climate change impacts assessments in each of the related areas (e.g., environmental quality and monitoring, sustainable energy, agricultural systems, cultural preservation, and sustainable mining). In the IoT in Environmental Sustainability and Climate Change chapter, a framework for informed creation, interpretation and use of climate change projections and for continued innovations in climate and environmental science driven by key societal and economic stakeholders is presented. In addition, the IoT cyberinfrastructure to support the development of continued innovations in climate and environmental science is discussed

A Bird’s Eye View: Development of an Operational ARM Unmanned Aerial Systems Capability for Atmospheric Research in Arctic Alaska

Unmanned aerial capabilities offer exciting new perspectives on the Arctic atmosphere and the US Department of Energy is working with partners to offer such perspectives to the research community. Thorough understanding of aerosols, clouds, boundary layer structure and radiation is required to improve representation of the Arctic atmosphere in weather forecasting and climate models. To develop such understanding, new perspectives are needed to provide details on the vertical structure and spatial variability of key atmospheric properties, along with information over difficult-to-reach surfaces such as newly-forming sea ice. Over the last three years, the US Department of Energy (DOE) has supported various flight campaigns using unmanned aircraft systems (UAS, also known as UAVs and drones) and tethered balloon systems (TBS) at Oliktok Point, Alaska. These activities have featured in-situ measurements of thermodynamic state, turbulence, radiation, aerosol properties, cloud microphysics and turbulent fluxes to provide a detailed characterization of the lower atmosphere. Alongside a suite of active and passive ground-based sensors and radiosondes deployed by the DOE Atmospheric Radiation Measurement (ARM) program through the third ARM Mobile Facility (AMF-3), these flight activities demonstrate the ability of such platforms to provide critically-needed information. In addition to providing new and unique datasets, lessons learned during initial campaigns have assisted toward the development of an exciting new community resource

Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project

Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project has been established in 2016. It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, ship-borne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data