Turbulent parameters in the middle atmosphere: Theoretical estimates deduced from a gravity-wave resolving general circulation model

We present a scaling analysis for the stratified turbulent and small-scale turbulent regimes of atmospheric flow with emphasis on the mesosphere. We distinguish rotating-stratified macroturbulence turbulence (SMT), stratified turbulence (ST), and small-scale isotropic Kolmogorov turbulence (KT), and we specify the length and time scales and the characteristic velocities for these regimes. It is shown that the buoyancy scale (Lb) and the Ozmidov scale (Lo) are the main parameters that describe the transition from SMT to KT. We employ the buoyancy Reynolds number and horizontal Froude number to characterize ST and KT in the mesosphere. This theory is applied to simulation results from a high-resolution general circulation model with a Smagorinsky-type turbulent diffusion scheme for the sub-grid scale parameterization. The model allows us to derive the turbulent root-mean-square (RMS) velocity in the KT regime. It is found that the turbulent RMS velocity has a single maximum in summer and a double maximum in winter months. The secondary maximum in the winter MLT we associate with a secondary gravity wave breaking phenomenon. The turbulent RMS velocity results from the model agree well with Full Correlation Analyses based on MF-radar measurements. A new scaling for the mesoscale horizontal velocity based on the idea of direct energy cascade in masoscales is proposed. The latter findings for mesoscale and small-scale characteristic velocities supports the idea proposed in this research that mesoscale and small-scale dynamics in the mesosphere are governed by SMT, ST, and KT in the statistical average.

Inversion method for measuring multi-hole probe surface pressure distribution of supersonic compressible atmospheric flow field

The conventional method of measuring a multi-hole probe is based on Bernoulli’s equation and suffers from certain model errors. A computational fluid dynamics (CFD)-based method was used in this study to reduce the theoretical error and establish a parametric model of the surface pressure of a spherical multi-hole pressure probe for measuring compressible flow fields at supersonic velocities. A flow field inversion method based on the parametric model is proposed herein. Numerical simulations were conducted to validate the proposed method. The experiment results show that in the compressible atmospheric flow field within Mach 1.2–1.7, the measurement errors of the inversion method were 1.3% and 2.35% for velocity and angle, respectively, thus verifying the feasibility of the method. Thus, a new method of measuring multi-hole pressure probe atmospheric flow fields was demonstrated.

The Search for Atmospheric Laminar Channels: Experimental Results and Method Dissemination

In this paper, a practical application of theoretical developments found in our previous works is explored in relation to atmospheric lidar data. Multifractal structures, previously named “laminar channels”, have been identified in atmospheric profiles—these exhibit cellular and self-structuring properties, and are spatially ordered across the atmospheric profile. Furthermore, these structures have been connected to the spontaneous emergence of turbulent behavior in the calm atmospheric flow. Calculating the location and occurrence of these channels can help identify features of atmospheric evolution, such as the development of the planetary boundary layer (PBL). Employing this theoretical background to atmospheric lidar data, attempts are made to confirm this suggestion and extract information about atmospheric structure and evolution by analyzing turbulent vortex scale dynamics and scale-corresponding Lyapunov exponents that form the basis of identifying the laminar channels in atmospheric lidar profiles. A parameter named “scale laminarity index” is then introduced, which quantifies the relation between vortex scale and chaoticity throughout the profile. Finally, the algorithmic methods employed in this study are described and distributed for future use.

Multi-day hail clusters and isolated hail days in Switzerland – large-scale flow conditions and precursors

In Switzerland, hail regularly occurs in multi-day hail clusters. The atmospheric conditions prior to and during multi-day hail clusters are described and contrasted to the conditions prior to and during isolated hail days. The analysis focuses on hail days that occurred between April and September 2002–2019 within 140 km of the Swiss radar network. Hail days north and south of the Alps are defined using a minimum area threshold of a radar-based hail product. Multi-day clusters are defined as 5 d windows containing 4 or 5 hail days and isolated hail days as 5 d windows containing a single hail day. The reanalysis ERA-5 is used to study the large-scale flow in combination with objectively identified cold fronts, atmospheric blocking events, and a weather type classification. Both north and south of the Alps, isolated hail days have frequency maxima in May and August–September, whereas clustered hail days occur mostly in July and August. Composites of atmospheric variables indicate a more stationary and meridionally amplified atmospheric flow both north and south of the Alps during multi-day hail clusters. On clustered hail days north of the Alps, blocks are more frequent over the North Sea, and surface fronts are located farther from Switzerland than on isolated hail days. Clustered hail days north of the Alps are also characterized by significantly higher most unstable convective available potential energy (MUCAPE) values, warmer daily maximum surface temperatures, and higher atmospheric moisture content than isolated hail days. Hence, both stationary flow conditions and anomalous amounts of moisture are necessary for multi-day hail clusters on the north side. In contrast, differences in MUCAPE on the south side between clustered hail days and isolated hail days are small. The mean sea level pressure south of the Alps is significantly deeper, the maximum temperature is colder, and local moisture is significantly lower on isolated hail days. Both north and south of the Alps, the upper-level atmospheric flow over the eastern Atlantic is meridionally more amplified 3 d prior to clustered hail days than prior to isolated days. Moreover, blocking occurs prior to more than 10 % of clustered hail days over Scandinavia, but no blocks occur prior to isolated hail days. Half of the clustered hail days south of the Alps are also clustered north of the Alps. On hail days clustering only south of the Alps, fronts are more frequently located on the Alpine ridge, and local low-level winds are stronger. The temporal clustering of hail days is coupled to specific synoptic- and local-scale flow conditions; this information may be exploited for short- to medium-range forecasts of hail in Switzerland.

The default methods in the 2019 Refinement drastically reduce estimates of global carbon sinks of harvested wood products

Background The stock dynamics of harvested wood products (HWPs) are a relevant component of anthropogenic carbon cycles. Generally, HWP stock increases are treated as carbon removals from the atmosphere, while stock decreases are considered emissions. Among the different approaches suggested by the Intergovernmental Panel on Climate Change (IPCC) for accounting HWPs in national greenhouse gas inventories, the production approach has been established as the common approach under the Kyoto Protocol and Paris Agreement. However, the 24th session of the Conference of the Parties to the United Nations Framework Convention on Climate Change decided that alternative approaches can also be used. The IPCC has published guidelines for estimating HWP carbon stocks and default parameters for the various approaches in the 2006 Guidelines, 2013 Guidance, and 2019 Refinement. Although there are significant differences among the default methods in the three IPCC guidelines, no studies have systematically quantified or compared the results from the different guidelines on a global scale. This study quantifies the HWP stock dynamics and corresponding carbon removals/emissions under each approach based on the default methods presented in each guideline for 235 individual countries/regions. Results We identified relatively good consistency in carbon stocks/removals between the stock-change and the atmospheric flow approaches at a global level. Under both approaches, the methodological and parameter updates in the 2019 Refinement (e.g., considered HWPs, starting year for carbon stocks, and conversion factors) resulted in one-third reduction in carbon removals compared to the 2006 Guidelines. The production approach leads to a systematic underestimation of global carbon stocks and removals because it confines accounting to products derived from domestic harvests and uses the share of domestic feedstock for accounting. The 2013 Guidance and the 2019 Refinement reduce the estimated global carbon removals under the production approach by 15% and 45% (2018), respectively, compared to the 2006 Guidelines. Conclusions Gradual refinements in the IPCC default methods have a considerably higher impact on global estimates of HWP carbon stocks and removals than the differences in accounting approaches. The methodological improvements in the 2019 Refinement halve the global HWP carbon removals estimated in the former version, the 2006 Guidelines.

Design, Construction and Evaluation of an Oscillating Vane Gust Generator for Atmospheric Flow Simulation

The study of unsteady aerodynamic phenomena in wind tunnels is supported by gust-generating devices capable of generating adjustable magnitude and periodicity velocity fluctuations in a flowfield. Gusts are typically generated actively by introducing moving vanes to direct the flow, or passively by tailoring the boundary layer growth and shape in the tunnel. The flow facility used here is a student-built closed-return low-speed wind tunnel, with a test section size of 750 mm × 750 mm and a maximum speed of 25 m/s. A two-vane gust generator utilizing NACA0018 airfoil sections of 150 mm chord length was designed and installed upstream of the test section. The flowfield was mapped with the installed vanes with and without gust actuation, utilizing a hot wire system. The tunnel with gust vanes exhibits a spatially uniform baseline turbulence intensity of 5%, with a steady state velocity deficit of 1 m/s in the vane–wake region. Upon introducing the gusting conditions at vane deflection angles of up to ±45°, velocity differences of up to 4 m/s were attained at 18 m/s freestream velocity at oscillation frequencies ranging between 1 Hz and 2 Hz.

New Perspectives on Ensemble Sensitivity Analysis with Applications to a Climatology of Severe Convection

Ensemble sensitivity analysis (ESA) is a statistical technique applied within an ensemble to reveal the atmospheric flow features that relate to a chosen aspect of the flow. Given its ease of use (it is simply a linear regression between a chosen function of the forecast variables and the entire atmospheric state earlier or simultaneously in time), ensemble sensitivity has been the focus of several studies over roughly the last ten years. Such studies have primarily tried to understand the relevant dynamics and/or key precursors of high-impact weather events. Other applications of ESA have been more operationally oriented, including observation targeting within data assimilation systems and real-time adjustment techniques that attempt to utilize both sensitivity information and observations to improve forecasts.While ESA has gained popularity, its fundamental properties remain a substantially underutilized basis for realizing the technique’s full scientific potential. For example, the relationship between ensemble sensitivity and the pure dynamics of the system can teach us how to appropriately apply various sensitivity-based applications, and combining sensitivity with other ensemble properties such as spread can distinguish between a fluid dynamics problem and a predictability one. This work aims to present new perspectives on ensemble sensitivity, and clarify its fundamentals, with the hopes of making it a more accessible, attractive, and useful tool in the atmospheric sciences. These new perspectives are applied in part to a short climatology of severe convection forecasts to demonstrate the unique knowledge that can gained through broadened use of ESA.

Evidence of preferential sweeping during snow settling in atmospheric turbulence

We present a field study of snow settling dynamics based on simultaneous measurements of the atmospheric flow field and snow particle trajectories. Specifically, a super-large-scale particle image velocimetry (SLPIV) system using natural snow particles as tracers is deployed to quantify the velocity field and identify vortex structures in a 22 m $\times$ 39 m field of view centred 18 m above the ground. Simultaneously, we track individual snow particles in a 3 m $\times$ 5 m sample area within the SLPIV using particle tracking velocimetry. The results reveal the direct linkage among vortex structures in atmospheric turbulence, the spatial distribution of snow particle concentration and their settling dynamics. In particular, with snow turbulence interaction at near-critical Stokes number, the settling velocity enhancement of snow particles is multifold, and larger than what has been observed in previous field studies. Super-large-scale particle image velocimetry measurements show a higher concentration of snow particles preferentially located on the downward side of the vortices identified in the atmospheric flow field. Particle tracking velocimetry, performed on high resolution images around the reconstructed vortices, confirms the latter trend and provides statistical evidence of the acceleration of snow particles, as they move toward the downward side of vortices. Overall, the simultaneous multi-scale particle imaging presented here enables us to directly quantify the salient features of preferential sweeping, supporting it as an underlying mechanism of snow settling enhancement in the atmospheric surface layer.

Introducing CRYOWRF v1.0: Multiscale atmospheric flow simulations with advanced snow cover modelling

Accurately simulating snow-cover dynamics and the snow-atmosphere coupling is of major importance for topics as wide-ranging as water resources, natural hazards and climate change impacts with consequences for sea-level rise. We present a new modelling framework for atmospheric flow simulations for cryospheric regions called CRYOWRF. CRYOWRF couples the state-of-the-art and widely used atmospheric model WRF, with the detailed snow-cover model SNOWPACK. CRYOWRF makes it feasible to simulate dynamics of a large number of snow layers governed by grain-scale prognostic variables with online coupling to the atmosphere for multiscale simulations from the synoptic to the turbulent scales. Additionally, a new blowing snow scheme is introduced in CRYOWRF and is discussed in detail. CRYOWRF's technical design goals and model capabilities are described and performance costs are shown to compare favourably with existing land surface schemes. Three case studies showcasing envisaged use-cases for CRYOWRF for polar ice sheets and alpine snowpacks are provided to equip potential users with templates for their research. Finally, the future road-map for CRYOWRF's development and usage is discussed.