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Schär, Christoph, Oliver Fuhrer, Andrea Arteaga, et al. "Kilometer-Scale Climate Models: Prospects and Challenges." Bulletin of the American Meteorological Society 101, no. 5 (2020): E567—E587. http://dx.doi.org/10.1175/bams-d-18-0167.1.
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Abstract Currently major efforts are underway toward refining the horizontal resolution (or grid spacing) of climate models to about 1 km, using both global and regional climate models (GCMs and RCMs). Several groups have succeeded in conducting kilometer-scale multiweek GCM simulations and decadelong continental-scale RCM simulations. There is the well-founded hope that this increase in resolution represents a quantum jump in climate modeling, as it enables replacing the parameterization of moist convection by an explicit treatment. It is expected that this will improve the simulation of the water cycle and extreme events and reduce uncertainties in climate change projections. While kilometer-scale resolution is commonly employed in limited-area numerical weather prediction, enabling it on global scales for extended climate simulations requires a concerted effort. In this paper, we exploit an RCM that runs entirely on graphics processing units (GPUs) and show examples that highlight the prospects of this approach. A particular challenge addressed in this paper relates to the growth in output volumes. It is argued that the data avalanche of high-resolution simulations will make it impractical or impossible to store the data. Rather, repeating the simulation and conducting online analysis will become more efficient. A prototype of this methodology is presented. It makes use of a bit-reproducible model version that ensures reproducible simulations across hardware architectures, in conjunction with a data virtualization layer as a common interface for output analyses. An assessment of the potential of these novel approaches will be provided.
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Ban, Nikolina, Cécile Caillaud, Erika Coppola, et al. "The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation." Climate Dynamics 57, no. 1-2 (2021): 275–302. http://dx.doi.org/10.1007/s00382-021-05708-w.
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AbstractHere we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of $$\sim $$ ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution ($$\sim $$ ∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from $$\sim \,$$ ∼ −40% at 12 km to $$\sim \,$$ ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.
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Mittermaier, M. P., and G. Csima. "Ensemble versus Deterministic Performance at the Kilometer Scale." Weather and Forecasting 32, no. 5 (2017): 1697–709. http://dx.doi.org/10.1175/waf-d-16-0164.1.
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Abstract What is the benefit of a near-convection-resolving ensemble over a near-convection-resolving deterministic forecast? In this paper, a way in which ensemble and deterministic numerical weather prediction (NWP) systems can be compared is demonstrated using a probabilistic verification framework. Three years’ worth of raw forecasts from the Met Office Unified Model (UM) 12-member 2.2-km Met Office Global and Regional Ensemble Prediction System (MOGREPS-UK) ensemble and 1.5-km Met Office U.K. variable resolution (UKV) deterministic configuration were compared, utilizing a range of forecast neighborhood sizes centered on surface synoptic observing site locations. Six surface variables were evaluated: temperature, 10-m wind speed, visibility, cloud-base height, total cloud amount, and hourly precipitation. Deterministic forecasts benefit more from the application of neighborhoods, though ensemble forecast skill can also be improved. This confirms that while neighborhoods can enhance skill by sampling more of the forecast, a single deterministic model state in time cannot provide the variability, especially at the kilometer scale, where rapid error growth acts to limit local predictability. Ensembles are able to account for the uncertainty at larger, synoptic scales. The results also show that the rate of decrease in skill with lead time is greater for the deterministic UKV. MOGREPS-UK retains higher skill for longer. The concept of a skill differential is introduced to find the smallest neighborhood size at which the deterministic and ensemble scores are comparable. This was found to be 3 × 3 (6.6 km) for MOGREPS-UK and 11 × 11 (16.5 km) for UKV. Comparable scores are between 2% and 40% higher for MOGREPS-UK, depending on the variable. Naively, this would also suggest that an extra 10 km in spatial accuracy is gained by using a kilometer-scale ensemble.
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Zeman, Christian, Nils P. Wedi, Peter D. Dueben, Nikolina Ban, and Christoph Schär. "Model intercomparison of COSMO 5.0 and IFS 45r1 at kilometer-scale grid spacing." Geoscientific Model Development 14, no. 7 (2021): 4617–39. http://dx.doi.org/10.5194/gmd-14-4617-2021.
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Abstract. The increase in computing power and recent model developments allow for the use of global kilometer-scale weather and climate models for routine forecasts. At these scales, deep convective processes can be partially resolved explicitly by the model dynamics. Next to horizontal resolution, other aspects such as the applied numerical methods, the use of the hydrostatic approximation, and time step size are factors that might influence a model's ability to resolve deep convective processes. In order to improve our understanding of the role of these factors, a model intercomparison between the nonhydrostatic COSMO model and the hydrostatic Integrated Forecast System (IFS) from ECMWF has been conducted. Both models have been run with different spatial and temporal resolutions in order to simulate 2 summer days over Europe with strong convection. The results are analyzed with a focus on vertical wind speed and precipitation. Results show that even at around 3 km horizontal grid spacing the effect of the hydrostatic approximation seems to be negligible. However, time step proves to be an important factor for deep convective processes, with a reduced time step generally allowing for higher updraft velocities and thus more energy in vertical velocity spectra, in particular for shorter wavelengths. A shorter time step is also causing an earlier onset and peak of the diurnal cycle. Furthermore, the amount of horizontal diffusion plays a crucial role for deep convection with more diffusion generally leading to larger convective cells and higher precipitation intensities. The study also shows that for both models the parameterization of deep convection leads to lower updraft and precipitation intensities and biases in the diurnal cycle with a precipitation peak which is too early.
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Pay, M. T., F. Martínez, M. Guevara, and J. M. Baldasano. "Air quality forecasts at kilometer scale grid over Spanish complex terrains." Geoscientific Model Development Discussions 7, no. 2 (2014): 2293–334. http://dx.doi.org/10.5194/gmdd-7-2293-2014.
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Abstract. CALIOPE-AQFS represents the current state-of-the-art in air quality forecasting systems running at high resolution over high performance computing platforms. It provides 48 h forecast of main pollutants over Spain at 4 km horizontal resolution, and over the most populated areas with complex terrains in Spain (Barcelona, Madrid and Andalucia domains) at 1 km. Increased horizontal resolution from 4 km to 1 km over the aforementioned domains leads to finer texture and more realistic concentration maps, justified by the increase of NO2/O3 spatial correlation coefficients from 0.79/0.69 (4 km) to 0.81/0.73 (1 km). High resolution emissions using the bottom-up HERMESv2.0 model are essential to improve the model performance when increasing resolution at urban scale, but it is not sufficient. Decreasing grid spacing does not reveal the expected improvement on hourly statistics, decreasing NO2 bias only in ~ 2 μg m−3 and increasing O3 bias in ~ 1 μg m−3. The grid effect is less pronounced for PM10 because part of its mass consists of secondary aerosols which are less affected by a decreasing grid size in contrast to the locally emitted primary components. The resolution increase has the highest impact over Barcelona, where air flow is mainly controlled by mesoscale phenomena and a lower PBL. Despite the merits and potential uses of the 1 km simulation, the limitations of current model formulations do not allow confirming their expected superiority close to highly urbanized areas and large sources. Future work should combine high grid resolution with techniques that decrease subgrid variability and models that consider urban morphology and thermal parameters.
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Bauville, Arthur, and Stefan M. Schmalholz. "Thermo-mechanical model for the finite strain gradient in kilometer-scale shear zones." Geology 41, no. 5 (2013): 567–70. http://dx.doi.org/10.1130/g33953.1.
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Pay, M. T., F. Martínez, M. Guevara, and J. M. Baldasano. "Air quality forecasts on a kilometer-scale grid over complex Spanish terrains." Geoscientific Model Development 7, no. 5 (2014): 1979–99. http://dx.doi.org/10.5194/gmd-7-1979-2014.
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Abstract. The CALIOPE Air Quality Forecast System (CALIOPE-AQFS) represents the current state of the art in air quality forecasting systems of high-resolution running on high-performance computing platforms. It provides a 48 h forecast of NO2, O3, SO2, PM10, PM2.5, CO, and C6H6 at a 4 km horizontal resolution over all of Spain, and at a 1 km horizontal resolution over the most populated areas in Spain with complex terrains (the Barcelona (BCN), Madrid (MAD) and Andalusia (AND) domains). Increased horizontal resolution from 4 to 1 km over the aforementioned domains leads to finer textures and more realistic concentration maps, which is justified by the increase in NO2/O3 spatial correlation coefficients from 0.79/0.69 (4 km) to 0.81/0.73 (1 km). High-resolution emissions using the bottom-up HERMESv2.0 model are essential for improving model performance when increasing resolution on an urban scale, but it is still insufficient. Decreasing grid spacing does not reveal the expected improvement in hourly statistics, i.e., decreasing NO2 bias by only ~ 2 μg m−3 and increasing O3 bias by ~ 1 μg m−3. The grid effect is less pronounced for PM10, because part of its mass consists of secondary aerosols, which are less affected than the locally emitted primary components by a decreasing grid size. The resolution increase has the highest impact over Barcelona, where air flow is controlled mainly by mesoscale phenomena and a lower planetary boundary layer (PBL). Despite the merits and potential uses of the 1-km simulation, the limitations of current model formulations do not allow confirmation of their expected superiority close to highly urbanized areas and large emissions sources. Future work should combine high grid resolutions with techniques that decrease subgrid variability (e.g., stochastic field methods), and also include models that consider urban morphology and thermal parameters.
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Idier, Déborah, Albert Falqués, Jérémy Rohmer, and Jaime Arriaga. "Self-organized kilometer-scale shoreline sand wave generation: Sensitivity to model and physical parameters." Journal of Geophysical Research: Earth Surface 122, no. 9 (2017): 1678–97. http://dx.doi.org/10.1002/2017jf004197.
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Xia, Ming. "An upscale theory of thermal-mechanical coupling particle simulation for non-isothermal problems in two-dimensional quasi-static system." Engineering Computations 32, no. 7 (2015): 2136–65. http://dx.doi.org/10.1108/ec-04-2014-0076.
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Purpose – The purpose of this paper is to present an upscale theory of the thermal-mechanical coupling particle simulation for non-isothermal problems in two-dimensional quasi-static system, under which a small length-scale particle model can exactly reproduce the same mechanical and thermal results with that of a large length-scale one. Design/methodology/approach – The objective is achieved by extending the upscale theory of particle simulation for two-dimensional quasi-static problems from an isothermal system to a non-isothermal one. Findings – Five similarity criteria, namely geometric, material (mechanical and thermal) properties, gravity acceleration, (mechanical and thermal) time steps, thermal initial and boundary conditions (Dirichlet/Neumann boundary conditions), under which a small-length-scale particle model can exactly reproduce both the mechanical and thermal behavior with that of a large length-scale model for non-isothermal problems in a two-dimensional quasi-static system are proposed. Furthermore, to test the proposed upscale theory, two typical examples subjected to different thermal boundary conditions are simulated using two particle models of different length scale. Originality/value – The paper provides some important theoretical guidances to modeling thermal-mechanical coupled problems at both the engineering length scale (i.e. the meter scale) and the geological length scale (i.e. the kilometer scale) using the particle simulation method directly. The related simulation results from two typical examples of significantly different length scales (i.e. a meter scale and a kilometer scale) have demonstrated the usefulness and correctness of the proposed upscale theory for simulating non-isothermal problems in two-dimensional quasi-static system.
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Muñoz-Esparza, Domingo, Robert D. Sharman, and Stanley B. Trier. "On the Consequences of PBL Scheme Diffusion on UTLS Wave and Turbulence Representation in High-Resolution NWP Models." Monthly Weather Review 148, no. 10 (2020): 4247–65. http://dx.doi.org/10.1175/mwr-d-20-0102.1.
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AbstractMesoscale numerical weather prediction (NWP) models are routinely exercised at kilometer-scale horizontal grid spacings (Δx). Such fine grids will usually allow at least partial resolution of small-scale gravity waves and turbulence in the upper troposphere and lower stratosphere (UTLS). However, planetary boundary layer (PBL) parameterization schemes used with these NWP model simulations typically apply explicit subgrid-scale vertical diffusion throughout the entire vertical extent of the domain, an effect that cannot be ignored. By way of an example case of observed widespread turbulence over the U.S. Great Plains, we demonstrate that the PBL scheme’s mixing in NWP model simulations of Δx = 1 km can have significant effects on the onset and characteristics of the modeled UTLS gravity waves. Qualitatively, PBL scheme diffusion is found to affect not only background conditions responsible for UTLS wave activity, but also to control the local vertical mixing that triggers or hinders the onset and propagation of these waves. Comparisons are made to a reference large-eddy simulation with Δx = 250 m to statistically quantify these effects. A significant and systematic overestimation of resolved vertical velocities, wave-scale fluxes, and kinetic energy is uncovered in the 1-km simulations, both in clear-air and in-cloud conditions. These findings are especially relevant for upper-level gravity wave and turbulence simulations using high-resolution kilometer-scale NWP models.
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Langhans, Wolfgang, Juerg Schmidli, and Christoph Schär. "Bulk Convergence of Cloud-Resolving Simulations of Moist Convection over Complex Terrain." Journal of the Atmospheric Sciences 69, no. 7 (2012): 2207–28. http://dx.doi.org/10.1175/jas-d-11-0252.1.
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Abstract The explicit treatment of moist convection in cloud-resolving models with kilometer-scale horizontal resolution is increasingly used for atmospheric research and numerical weather prediction purposes. However, several previous studies have implicitly questioned the physical validity of this approach, as the accurate representation of the structure and evolution of moist convective phenomena requires considerably higher resolution. Unlike these studies, which focused on single convective systems, here the convergence of bulk properties of an ensemble of moist convective cells in kilometer-scale simulations is considered. To address the convergence, the authors focus on the bulk net heating and moistening in a large control volume, the associated vertical fluxes, and the diurnal evolution of regionally averaged precipitation. Besides numerical convergence, “physical” convergence (Reynolds number increases with resolution) is addressed for two conceptually different subgrid-mixing approaches (1D mesoscale and 3D LES). Simulations are conducted for a 9-day period of diurnal summer convection over the Alps, using a large computational domain with grid spacings of 4.4, 2.2, 1.1, and 0.55 km and grid-independent topography. Results show that for the model and episode considered, the simulated bulk properties and vertical fluxes converge numerically toward the 0.55-km solution. In terms of bulk effects, differences between the simulations are surprisingly small, even within the physical convergence framework that exhibits a sensitivity of the small-scale dynamics and ensuing convective structures to the horizontal resolution. Despite some sensitivities related to the applied turbulence closure, the results support the feasibility of kilometer-scale models to appropriately represent the bulk feedbacks between moist convection and the larger-scale flow.
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Segall, Paul, and Kyle Anderson. "Repeating caldera collapse events constrain fault friction at the kilometer scale." Proceedings of the National Academy of Sciences 118, no. 30 (2021): e2101469118. http://dx.doi.org/10.1073/pnas.2101469118.
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Fault friction is central to understanding earthquakes, yet laboratory rock mechanics experiments are restricted to, at most, meter scale. Questions thus remain as to the applicability of measured frictional properties to faulting in situ. In particular, the slip-weakening distance dc strongly influences precursory slip during earthquake nucleation, but scales with fault roughness and is challenging to extrapolate to nature. The 2018 eruption of Kīlauea volcano, Hawaii, caused 62 repeatable collapse events in which the summit caldera dropped several meters, accompanied by MW 4.7 to 5.4 very long period (VLP) earthquakes. Collapses were exceptionally well recorded by global positioning system (GPS) and tilt instruments and represent unique natural kilometer-scale friction experiments. We model a piston collapsing into a magma reservoir. Pressure at the piston base and shear stress on its margin, governed by rate and state friction, balance its weight. Downward motion of the piston compresses the underlying magma, driving flow to the eruption. Monte Carlo estimation of unknowns validates laboratory friction parameters at the kilometer scale, including the magnitude of steady-state velocity weakening. The absence of accelerating precollapse deformation constrains dc to be ≤10 mm, potentially much less. These results support the use of laboratory friction laws and parameters for modeling earthquakes. We identify initial conditions and material and magma-system parameters that lead to episodic caldera collapse, revealing that small differences in eruptive vent elevation can lead to major differences in eruption volume and duration. Most historical basaltic caldera collapses were, at least partly, episodic, implying that the conditions for stick–slip derived here are commonly met in nature.
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Barszcz, Agnieszka, Jason A. Milbrandt, and Julie M. Thériault. "Improving the Explicit Prediction of Freezing Rain in a Kilometer-Scale Numerical Weather Prediction Model." Weather and Forecasting 33, no. 3 (2018): 767–82. http://dx.doi.org/10.1175/waf-d-17-0136.1.
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Abstract A freezing rain event, in which the Meteorological Centre of Canada’s 2.5-km numerical weather prediction system significantly underpredicted the quantity of freezing rain, is examined. The prediction system models precipitation types explicitly, directly from the Milbrandt–Yau microphysics scheme. It was determined that the freezing rain underprediction for this case was due primarily to excessive refreezing of rain, originating from melting snow and graupel, in and under the temperature inversion of the advancing warm front ultimately depleting the supply of rain reaching the surface. The refreezing was caused from excessive collisional freezing between rain and graupel. Sensitivity experiments were conducted to examine the effects of a temperature threshold for collisional freezing and on varying the values of the collection efficiencies between rain and ice-phase hydrometeors. It was shown that by reducing the rain–graupel collection efficiency and by imposing a temperature threshold of −5°C, above which collisional freezing is not permitted, excessive rain–graupel collection and graupel formation can be controlled in the microphysics scheme, leading to an improved simulation of freezing rain at the surface.
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Adhikari, Surendra, Erik R. Ivins, and Eric Larour. "ISSM-SESAW v1.0: mesh-based computation of gravitationally consistent sea-level and geodetic signatures caused by cryosphere and climate driven mass change." Geoscientific Model Development 9, no. 3 (2016): 1087–109. http://dx.doi.org/10.5194/gmd-9-1087-2016.
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Abstract. A classical Green's function approach for computing gravitationally consistent sea-level variations associated with mass redistribution on the earth's surface employed in contemporary sea-level models naturally suits the spectral methods for numerical evaluation. The capability of these methods to resolve high wave number features such as small glaciers is limited by the need for large numbers of pixels and high-degree (associated Legendre) series truncation. Incorporating a spectral model into (components of) earth system models that generally operate on a mesh system also requires repetitive forward and inverse transforms. In order to overcome these limitations, we present a method that functions efficiently on an unstructured mesh, thus capturing the physics operating at kilometer scale yet capable of simulating geophysical observables that are inherently of global scale with minimal computational cost. The goal of the current version of this model is to provide high-resolution solid-earth, gravitational, sea-level and rotational responses for earth system models operating in the domain of the earth's outer fluid envelope on timescales less than about 1 century when viscous effects can largely be ignored over most of the globe. The model has numerous important geophysical applications. For example, we compute time-varying computations of global geodetic and sea-level signatures associated with recent ice-sheet changes that are derived from space gravimetry observations. We also demonstrate the capability of our model to simultaneously resolve kilometer-scale sources of the earth's time-varying surface mass transport, derived from high-resolution modeling of polar ice sheets, and predict the corresponding local and global geodetic signatures.
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Li, Hongqi, Yanran Li, Qiuhong Zhao, Yue Lu, and Qiang Song. "The Tractor and Semitrailer Routing Considering Carbon Dioxide Emissions." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/509160.
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The incorporation of the minimization of carbon dioxide (CO2) emissions in the VRP is important to logistics companies. The paper deals with the tractor and semitrailer routing problem with full truckload between any two depots of the network; an integer programming model with the objective of minimizing CO2emissions per ton-kilometer is proposed. A two-stage approach with the same core steps of the simulated annealing (SA) in both stages is designed. The number of tractors is provided in the first stage and the CO2emissions per ton-kilometer are then optimized in the second stage. Computational experiments on small-scale randomly generated instances supported the feasibility and validity of the heuristic algorithm. To a practical-scale problem, the SA algorithm can provide advice on the number of tractors, the routes, and the location of the central depot to realize CO2emissions decrease.
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Poujol, Basile, Andreas F. Prein, and Andrew J. Newman. "Kilometer-scale modeling projects a tripling of Alaskan convective storms in future climate." Climate Dynamics 55, no. 11-12 (2020): 3543–64. http://dx.doi.org/10.1007/s00382-020-05466-1.
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Abstract Convective storms produce heavier downpours and become more intense with climate change. Such changes could be even amplified in high-latitudes since the Arctic is warming faster than any other region in the world and subsequently moistening. However, little attention has been paid to the impact of global warming on intense thunderstorms in high latitude continental regions, where they can produce flash flooding or ignite wildfires. We use a model with kilometer-scale grid spacing to simulate Alaska’s climate under present and end of the century high emission scenario conditions. The current climate simulation is able to capture the frequency and intensity of hourly precipitation compared to rain gauge data. We apply a precipitation tracking algorithm to identify intense, organized convective systems, which are projected to triple in frequency and extend to the northernmost regions of Alaska under future climate conditions. Peak rainfall rates in the core of the storms will intensify by 37% in line with atmospheric moisture increases. These results could have severe impacts on Alaska’s economy and ecology since floods are already the costliest natural disaster in central Alaska and an increasing number of thunderstorms could result in more wildfires ignitions.
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Ito, Junshi, Syugo Hayashi, Akihiro Hashimoto, et al. "Stalled Improvement in a Numerical Weather Prediction Model as Horizontal Resolution Increases to the Sub-Kilometer Scale." SOLA 13 (2017): 151–56. http://dx.doi.org/10.2151/sola.2017-028.
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Luo, Yali, Steven K. Krueger, and Kuan-Man Xu. "Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-Phase Microphysics Using a Cloud-Resolving Model." Journal of the Atmospheric Sciences 63, no. 11 (2006): 2831–47. http://dx.doi.org/10.1175/jas3785.1.
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Abstract This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement Program and output from the University of California, Los Angeles/Colorado State University cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties analyzed by applying the SCM’s assumptions about cloud vertical overlap and horizontal homogeneity to its profiles of cloud water/ice mixing ratio, cloud fraction, and snow flux differed from the cloud radar observations while the CRM simulation reproduced most of the observed cirrus properties. The present study evaluates, through a comparison with the CRM, the SCM’s representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. This study finds that, although the SCM’s detrainment rate profile averaged over the entire simulation period is comparable to the CRM’s, detrainment in the SCM is comparatively sporadic and vertically localized. Too much detrained ice is sublimated when first detrained. Snow formed from detrained cloud ice falls through too deep of a layer. These aspects of the SCM’s parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM), and suggest several possible improvements for the SCM: 1) allowing multiple coexisting cumulus cloud types as in the original Arakawa–Schubert scheme, 2) prognostically determining the stratiform cloud fraction, and 3) explicitly predicting the snow mixing ratio. These would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow flux.
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Luo, Yali, Steven K. Krueger, and Shrinivas Moorthi. "Cloud Properties Simulated by a Single-Column Model. Part I: Comparison to Cloud Radar Observations of Cirrus Clouds." Journal of the Atmospheric Sciences 62, no. 5 (2005): 1428–45. http://dx.doi.org/10.1175/jas3425.1.
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Abstract This study describes and demonstrates a new method for identifying deficiencies in how cloud processes are represented in large-scale models. Kilometer-scale-resolving cloud radar observations and cloud-resolving model (CRM) simulations were used to evaluate the representation of cirrus clouds in the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model for a 29-day period during June and July 1997 at the Atmospheric Radiation Measurement Program site in Oklahoma. To produce kilometer-scale cirrus statistics from the SCM results, synthetic subgrid-scale (SGS) cloud fields were generated using the SCM’s cloud fraction and hydrometeor content profiles, and the SCM’s cloud overlap and horizontal inhomogeneity assumptions. Three sets of SCM synthetic SGS cloud fields were analyzed. Two NOSNOW sets were produced in which clouds did not include snow; one set used random overlap, the other, maximum/random. In the SNOW set, clouds included snow and random overlap was used. The three sets were sampled in the same way as the cloud-radar-detected cloud fields and the CRM-simulated cloud fields. The mean cirrus cloud occurrence frequency for the SCM NOSNOW cloud fields agrees with the observed value as well as the CRM’s does, while that for SCM SNOW cloud fields is only half that observed. In most aspects, the SCM’s cirrus properties differ significantly from the cloud radar’s and the CRM’s, which generally agree. In comparison, there are too many physically thin SCM NOSNOW cirrus layers (most occupy only a single model layer) and too many physically thick SCM SNOW cirrus layers (most are thicker than 4 km). For the optically thin subset of cirrus layers, 1) the mean, mode, and median ice water path, and layer-mean ice water content (IWC) values for the SCM are significantly larger than the observed and CRM values; 2) the SCM layer-mean IWCs decrease with cloud physical thickness, opposite to the observations and CRM results; and 3) the range of layer-mean effective radii in the SCM thin cirrus is too narrow.
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Lambert, Marc-André, Erik H. Saenger, Beatriz Quintal, and Stefan M. Schmalholz. "Numerical simulation of ambient seismic wavefield modification caused by pore-fluid effects in an oil reservoir." GEOPHYSICS 78, no. 1 (2013): T41—T52. http://dx.doi.org/10.1190/geo2011-0513.1.
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We have modeled numerically the seismic response of a poroelastic inclusion with properties applicable to an oil reservoir that interacts with an ambient wavefield. The model includes wave-induced fluid flow caused by pressure differences between mesoscopic-scale (i.e., in the order of centimeters to meters) heterogeneities. We used a viscoelastic approximation on the macroscopic scale to implement the attenuation and dispersion resulting from this mesoscopic-scale theory in numerical simulations of wave propagation on the kilometer scale. This upscaling method includes finite-element modeling of wave-induced fluid flow to determine effective seismic properties of the poroelastic media, such as attenuation of P- and S-waves. The fitted, equivalent, viscoelastic behavior is implemented in finite-difference wave propagation simulations. With this two-stage process, we model numerically the quasi-poroelastic wave-propagation on the kilometer scale and study the impact of fluid properties and fluid saturation on the modeled seismic amplitudes. In particular, we addressed the question of whether poroelastic effects within an oil reservoir may be a plausible explanation for low-frequency ambient wavefield modifications observed at oil fields in recent years. Our results indicate that ambient wavefield modification is expected to occur for oil reservoirs exhibiting high attenuation. Whether or not such modifications can be detected in surface recordings, however, will depend on acquisition design and noise mitigation processing as well as site-specific conditions, such as the geologic complexity of the subsurface, the nature of the ambient wavefield, and the amount of surface noise.
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Schiavone, James A., Kun Gao, David A. Robinson, Peter J. Johnsen, and Mathieu R. Gerbush. "Large Roll Vortices Exhibited by Post-Tropical Cyclone Sandy during Landfall." Atmosphere 12, no. 2 (2021): 259. http://dx.doi.org/10.3390/atmos12020259.
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Roll vortices are frequent features of a hurricane’s boundary layer, with kilometer or sub-kilometer horizontal scale. In this study, we found that large roll vortices with O (10 km) horizontal wavelength occurred over land in Post-Tropical Cyclone Sandy (2012) during landfall on New Jersey. Various characteristics of roll vortices were corroborated by analyses of Doppler radar observations, a 500 m resolution Weather Research and Forecasting (WRF) simulation, and an idealized roll vortex model. The roll vortices were always linear-shaped, and their wavelengths of 5–14 km were generally larger than any previously published for a tropical cyclone over land. Based on surface wind observations and simulated WRF surface wind fields, we found that roll vortices significantly increased the probability of hazardous winds and likely caused the observed patchiness of treefall during Sandy’s landfall.
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Huang, Huaguo. "Accelerated RAPID Model Using Heterogeneous Porous Objects." Remote Sensing 10, no. 8 (2018): 1264. http://dx.doi.org/10.3390/rs10081264.
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To enhance the capability of three-dimensional (3D) radiative transfer models at the kilometer scale (km-scale), the radiosity applicable to porous individual objects (RAPID) model has been upgraded to RAPID3. The major innovation is that the homogeneous porous object concept (HOMOBJ) used for a tree crown scale is extended to a heterogeneous porous object (HETOBJ) for a forest plot scale. Correspondingly, the radiosity-graphics-combined method has been extended from HOMOBJ to HETOBJ, including the random dynamic projection algorithm, the updated modules of view factors, the single scattering estimation, the multiple scattering solutions, and the bidirectional reflectance factor (BRF) calculations. Five cases of the third radiation transfer model intercomparison (RAMI-3) have been used to verify RAPID3 by the RAMI-3 online checker. Seven scenes with different degrees of topography (valleys and hills) at 500 m size have also been simulated. Using a personal computer (CPU 2.5 GHz, memory 4 GB), the computation time of BRF at 500 m is only approximately 13 min per scene. The mean root mean square error is 0.015. RAPID3 simulated the enhanced contrast of BRF between backward and forward directions due to topography. RAPID3 has been integrated into the free RAPID platform, which should be very useful for the remote sensing community. In addition, the HETOBJ concept may also be useful for the speedup of ray tracing models.
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Rosolem, R., T. Hoar, A. Arellano, et al. "Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale." Hydrology and Earth System Sciences 18, no. 11 (2014): 4363–79. http://dx.doi.org/10.5194/hess-18-4363-2014.
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Abstract. Above-ground cosmic-ray neutron measurements provide an opportunity to infer soil moisture at the sub-kilometer scale. Initial efforts to assimilate those measurements have shown promise. This study expands such analysis by investigating (1) how the information from aboveground cosmic-ray neutrons can constrain the soil moisture at distinct depths simulated by a land surface model, and (2) how changes in data availability (in terms of retrieval frequency) impact the dynamics of simulated soil moisture profiles. We employ ensemble data assimilation techniques in a "nearly-identical twin" experiment applied at semi-arid shrubland, rainfed agricultural field, and mixed forest biomes in the USA. The performance of the Noah land surface model is compared with and without assimilation of observations at hourly intervals, as well as every 2 days. Synthetic observations of aboveground cosmic-ray neutrons better constrain the soil moisture simulated by Noah in root-zone soil layers (0–100cm), despite the limited measurement depth of the sensor (estimated to be 12–20cm). The ability of Noah to reproduce a "true" soil moisture profile is remarkably good, regardless of the frequency of observations at the semi-arid site. However, soil moisture profiles are better constrained when assimilating synthetic cosmic-ray neutron observations hourly rather than every 2 days at the cropland and mixed forest sites. This indicates potential benefits for hydrometeorological modeling when soil moisture measurements are available at a relatively high frequency. Moreover, differences in summertime meteorological forcing between the semi-arid site and the other two sites may indicate a possible controlling factor to soil moisture dynamics in addition to differences in soil and vegetation properties.
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Tonttila, J., E. J. O'Connor, S. Niemelä, P. Räisänen, and H. Järvinen. "Cloud-base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations." Atmospheric Chemistry and Physics Discussions 11, no. 3 (2011): 9607–33. http://dx.doi.org/10.5194/acpd-11-9607-2011.
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Abstract. The statistics of cloud-base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in Central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that, as expected, AROME significantly underestimates the variability of vertical velocity at cloud-base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4–6 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70–80% of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 4 times the physically-defined grid spacing. The results illustrate the need for special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.
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Kretzschmar, Jan, Johannes Stapf, Daniel Klocke, Manfred Wendisch, and Johannes Quaas. "Employing airborne radiation and cloud microphysics observations to improve cloud representation in ICON at kilometer-scale resolution in the Arctic." Atmospheric Chemistry and Physics 20, no. 21 (2020): 13145–65. http://dx.doi.org/10.5194/acp-20-13145-2020.
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Abstract. Clouds play a potentially important role in Arctic climate change but are poorly represented in current atmospheric models across scales. To improve the representation of Arctic clouds in models, it is necessary to compare models to observations to consequently reduce this uncertainty. This study compares aircraft observations from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign around Svalbard, Norway, in May–June 2017 and simulations using the ICON (ICOsahedral Non-hydrostatic) model in its numerical weather prediction (NWP) setup at 1.2 km horizontal resolution. By comparing measurements of solar and terrestrial irradiances during ACLOUD flights to the respective properties in ICON, we showed that the model systematically overestimates the transmissivity of the mostly liquid clouds during the campaign. This model bias is traced back to the way cloud condensation nuclei (CCN) get activated into cloud droplets in the two-moment bulk microphysical scheme used in this study. This process is parameterized as a function of grid-scale vertical velocity in the microphysical scheme used, but in-cloud turbulence cannot be sufficiently resolved at 1.2 km horizontal resolution in Arctic clouds. By parameterizing subgrid-scale vertical motion as a function of turbulent kinetic energy, we are able to achieve a more realistic CCN activation into cloud droplets. Additionally, we showed that by scaling the presently used CCN activation profile, the hydrometeor number concentration could be modified to be in better agreement with ACLOUD observations in our revised CCN activation parameterization. This consequently results in an improved representation of cloud optical properties in our ICON simulations.
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Naumann, Ann Kristin, and Christoph Kiemle. "The vertical structure and spatial variability of lower-tropospheric water vapor and clouds in the trades." Atmospheric Chemistry and Physics 20, no. 10 (2020): 6129–45. http://dx.doi.org/10.5194/acp-20-6129-2020.
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Abstract. Horizontal and vertical variability of water vapor is omnipresent in the tropics, but its interaction with cloudiness poses challenges for weather and climate models. In this study we compare airborne lidar measurements from a summer and a winter field campaign in the tropical Atlantic with high-resolution simulations to analyze the water vapor distributions in the trade wind regime, its covariation with cloudiness, and their representation in simulations. Across model grid spacing from 300 m to 2.5 km, the simulations show good skill in reproducing the water vapor distribution in the trades as measured by the lidar. An exception to this is a pronounced moist model bias at the top of the shallow cumulus layer in the dry winter season which is accompanied by a humidity gradient that is too weak at the inversion near the cloud top. The model's underestimation of water vapor variability in the cloud and subcloud layer occurs in both seasons but is less pronounced than the moist model bias at the inversion. Despite the model's insensitivity to resolution from hecto- to kilometer scale for the distribution of water vapor, cloud fraction decreases strongly with increasing model resolution and is not converged at hectometer grid spacing. The observed cloud deepening with increasing water vapor path is captured well across model resolution, but the concurrent transition from cloud-free to low cloud fraction is better represented at hectometer resolution. In particular, in the wet summer season the simulations with kilometer-scale resolution overestimate the observed cloud fraction near the inversion but lack condensate near the observed cloud base. This illustrates how a model's ability to properly capture the water vapor distribution does not necessarily translate into an adequate representation of shallow cumulus clouds that live at the tail of the water vapor distribution.
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Paoli, R., O. Thouron, J. Escobar, J. Picot, and D. Cariolle. "High-resolution large-eddy simulations of sub-kilometer-scale turbulence in the upper troposphere lower stratosphere." Atmospheric Chemistry and Physics Discussions 13, no. 12 (2013): 31891–932. http://dx.doi.org/10.5194/acpd-13-31891-2013.
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Abstract. Large-eddy simulations of sub-kilometer-scale turbulence in the upper troposphere lower stratosphere (UTLS) are carried out and analyzed using the mesoscale atmospheric model Méso-NH. Different levels of turbulence are generated using a large-scale stochastic forcing technique that was especially devised to treat atmospheric stratified flows. The study focuses on the analysis of turbulence statistics, including mean quantities and energy spectra, as well as on a detailed description of flow topology. The impact of resolution is also discussed by decreasing the grid spacing to 2 m and increasing the number of grid points to 8×109. Because of atmospheric stratification, turbulence is substantially anisotropic, and large elongated structures form in the horizontal directions, in accordance with theoretical analysis and spectral direct numerical simulations of stably stratified flows. It is also found that the inertial range of horizontal kinetic energy spectrum, generally observed at scales larger than a few kilometers, is prolonged into the sub-kilometric range, down to the Ozmidov scales that obey isotropic Kolmorogov turbulence. The results are in line with observational analysis based on in situ measurements from existing campaigns.
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Biondi, Franco. "Dendroclimatic Reconstruction at Kilometer-Scale Grid Points: A Case Study from the Great Basin of North America." Journal of Hydrometeorology 15, no. 2 (2014): 891–906. http://dx.doi.org/10.1175/jhm-d-13-0151.1.
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AbstractPreparing for future hydroclimatic variability greatly benefits from long (i.e., multicentury) records at seasonal to annual time steps that have been gridded at kilometer-scale spatial intervals over a geographic region. Kriging is commonly used for optimal interpolation of environmental data, and space–time geostatistical models can improve kriging estimates when long temporal sequences of observations exist at relatively few points on the landscape. A network of 22 tree-ring chronologies from single-leaf pinyon (Pinus monophylla) in the central Great Basin of North America was used to extend hydroclimatic records both temporally and spatially. First, the line of organic correlation (LOC) method was used to reconstruct October–May total precipitation anomalies at each tree-ring site, as these ecotonal environments at the lower forest border are typically moisture-limited areas. Individual site reconstructions were then combined using a hierarchical model of spatiotemporal kriging that produced annual anomaly maps on a 12 km × 12 km grid during the period in common among all chronologies (1650–1976). Hydroclimatic episodes were numerically identified using their duration, magnitude, and peak. Precipitation anomalies were spatially more variable during wet years than during dry years, and the evolution of drought episodes over space and time could be visualized and quantified. The most remarkable episode in the entire reconstruction was the early 1900s pluvial, followed by the late 1800s drought. The 1930s Dust Bowl drought was among the top 10 hydroclimatic episodes in the past few centuries. These results directly address the needs of water and natural resource managers with respect to planning for worst-case scenarios of drought duration and magnitude at the watershed level.
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Jacob, Marek, Pavlos Kollias, Felix Ament, Vera Schemann, and Susanne Crewell. "Multilayer cloud conditions in trade wind shallow cumulus – confronting two ICON model derivatives with airborne observations." Geoscientific Model Development 13, no. 11 (2020): 5757–77. http://dx.doi.org/10.5194/gmd-13-5757-2020.
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Abstract. Airborne remote sensing observations over the tropical Atlantic Ocean upstream of Barbados are used to characterize trade wind shallow cumulus clouds and to benchmark two cloud-resolving ICON (ICOsahedral Nonhydrostatic) model simulations at kilometer and hectometer scales. The clouds were observed by an airborne nadir-pointing backscatter lidar, a cloud radar, and a microwave radiometer in the tropical dry winter season during daytime. For the model benchmark, forward operators convert the model output into the observational space for considering instrument-specific cloud detection thresholds. The forward simulations reveal the different detection limits of the lidar and radar observations, i.e., most clouds with cloud liquid water content greater than 10−7 kg kg−1 are detectable by the lidar, whereas the radar is primarily sensitive to the “rain” category hydrometeors in the models and can detect even low amounts of rain. The observations reveal two prominent modes of cumulus cloud top heights separating the clouds into two layers. The lower mode relates to boundary layer convection with tops closely above the lifting condensation level, which is at about 700 m above sea level. The upper mode is driven by shallow moist convection, also contains shallow stratiform outflow anvils, and is closely related to the trade inversion at about 2.3 km above sea level. The two cumulus modes are sensed differently by the lidar and the radar observations and under different liquid water path (LWP) conditions. The storm-resolving model (SRM) at a kilometer scale barely reproduces the cloud modes and shows most cloud tops being slightly above the observed lower mode. The large-eddy model (LEM) at hectometer scale reproduces better the observed cloudiness distribution with a clear bimodal separation. We hypothesize that slight differences in the autoconversion parameterizations could have caused the different cloud development in the models. Neither model seems to account for in-cloud drizzle particles that do not precipitate down to the surface but generate a stronger radar signal even in scenes with low LWP. Our findings suggest that even if the SRM is a step forward for better cloud representation in climate research, the LEM can better reproduce the observed shallow cumulus convection and should therefore in principle better represent cloud radiative effects and water cycle.
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Zheng, Kaiwen, and Maxim Nikurashin. "Downstream Propagation and Remote Dissipation of Internal Waves in the Southern Ocean." Journal of Physical Oceanography 49, no. 7 (2019): 1873–87. http://dx.doi.org/10.1175/jpo-d-18-0134.1.
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AbstractRecent microstructure observations in the Southern Ocean report enhanced internal gravity waves and turbulence in the frontal regions of the Antarctic Circumpolar Current extending a kilometer above rough bottom topography. Idealized numerical simulations and linear theory show that geostrophic flows impinging on rough small-scale topography are very effective generators of internal waves and estimate vigorous wave radiation, breaking, and turbulence within a kilometer above bottom. However, both idealized simulations and linear theory assume periodic and spatially uniform topography and tend to overestimate the observed levels of turbulent energy dissipation locally at the generation sites. In this study, we explore the downstream evolution and remote dissipation of internal waves generated by geostrophic flows using a series of numerical, realistic topography simulations and parameters typical of Drake Passage. The results show that significant levels of internal wave kinetic energy and energy dissipation are present downstream of the rough topography, internal wave generation site. About 30%–40% of the energy dissipation occurs locally over the rough topography region, where internal waves are generated. The rest of the energy dissipation takes place remotely and decays downstream of the generation site with an e-folding length scale of up to 20–30 km. The model we use is two-dimensional with enhanced viscosity coefficients, and hence it can result in the underestimation of the remote wave dissipation and its decay length scale. The implications of our results for turbulent energy dissipation observations and mixing parameterizations are discussed.
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Vionnet, Vincent, Ingrid Dombrowski-Etchevers, Matthieu Lafaysse, Louis Quéno, Yann Seity, and Eric Bazile. "Numerical Weather Forecasts at Kilometer Scale in the French Alps: Evaluation and Application for Snowpack Modeling." Journal of Hydrometeorology 17, no. 10 (2016): 2591–614. http://dx.doi.org/10.1175/jhm-d-15-0241.1.
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Abstract Numerical weather prediction (NWP) systems operating at kilometer scale in mountainous terrain offer appealing prospects for forecasting the state of snowpack in support of avalanche hazard warning, water resources assessment, and flood forecasting. In this study, daily forecasts of the NWP system Applications of Research to Operations at Mesoscale (AROME) at 2.5-km grid spacing over the French Alps were considered for four consecutive winters (from 2010/11 to 2013/14). AROME forecasts were first evaluated against ground-based measurements of air temperature, humidity, wind speed, incoming radiation, and precipitation. This evaluation shows a cold bias at high altitude partially related to an underestimation of cloud cover influencing incoming radiative fluxes. AROME seasonal snowfall was also compared against output from the Système d’Analyse Fournissant des Renseignements Atmosphériques à la Neige (SAFRAN) specially developed for alpine terrain. This comparison reveals that there are regions of significant difference between the two, especially at high elevation, and possible causes for these differences are discussed. Finally, AROME forecasts and SAFRAN reanalysis have been used to drive the snowpack model Surface Externalisée (SURFEX)/Crocus (SC) and to simulate the snowpack evolution over a 2.5-km grid covering the French Alps during four winters. When evaluated at the experimental site of Col de Porte, both simulations show good agreement with measurements of snow depth and snow water equivalent. At the scale of the French Alps, AROME-SC exhibits an overall positive bias, with the largest positive bias found in the northern and central French Alps. This study constitutes the first step toward the development of a distributed snowpack forecasting system using AROME.
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Rüdisühli, Stefan, Michael Sprenger, David Leutwyler, Christoph Schär, and Heini Wernli. "Attribution of precipitation to cyclones and fronts over Europe in a kilometer-scale regional climate simulation." Weather and Climate Dynamics 1, no. 2 (2020): 675–99. http://dx.doi.org/10.5194/wcd-1-675-2020.
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Abstract. This study presents a detailed analysis of the climatological distribution of precipitation in relation to cyclones and fronts over Europe for the 9-year period 2000–2008. The analysis uses hourly output of a COSMO (Consortium for Small-scale Modeling) model simulation with 2.2 km grid spacing and resolved deep convection. Cyclones and fronts are identified as two-dimensional features in 850 hPa geopotential, equivalent potential temperature, and wind fields and subsequently tracked over time based on feature overlap and size. Thermal heat lows and local thermal fronts are removed based on track properties. This dataset then serves to define seven mutually exclusive precipitation components: cyclonic (near cyclone center), cold-frontal, warm-frontal, collocated (e.g., occlusion area), far-frontal, high-pressure (e.g., summer convection), and residual. The approach is illustrated with two case studies with contrasting precipitation characteristics. The climatological analysis for the 9-year period shows that frontal precipitation peaks in winter and fall over the eastern North Atlantic and the Alps (> 70 % in winter), where cold frontal precipitation is also crucial year-round; cyclonic precipitation is largest over the North Atlantic (especially in summer with > 40 %) and in the northern Mediterranean (widespread > 40 %); high-pressure precipitation occurs almost exclusively over land and primarily in summer (widespread 30 %–60 %, locally >80 %); and the residual contributions uniformly amount to about 20 % in all seasons. Considering heavy precipitation events (defined based on the local 99.9th all-hour percentile) reveals that high-pressure precipitation dominates in summer over the continent (50 %–70 %, locally >80 %); cold fronts produce much more heavy precipitation than warm fronts; and cyclones contribute substantially (50 %–70 %), especially in the Mediterranean in fall through spring and in northern Europe in summer.
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Fuhrer, Oliver, Tarun Chadha, Torsten Hoefler, et al. "Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0." Geoscientific Model Development 11, no. 4 (2018): 1665–81. http://dx.doi.org/10.5194/gmd-11-1665-2018.
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Abstract. The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non-hydrostatic climate model for a near-global setup running on the full Piz Daint supercomputer on 4888 GPUs (graphics processing units). The dynamical core of the model has been completely rewritten using a domain-specific language (DSL) for performance portability across different hardware architectures. Physical parameterizations and diagnostics have been ported using compiler directives. To our knowledge this represents the first complete atmospheric model being run entirely on accelerators on this scale. At a grid spacing of 930 m (1.9 km), we achieve a simulation throughput of 0.043 (0.23) simulated years per day and an energy consumption of 596 MWh per simulated year. Furthermore, we propose a new memory usage efficiency (MUE) metric that considers how efficiently the memory bandwidth – the dominant bottleneck of climate codes – is being used.
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RAZZAQUE, SOEBUR, PETER MÉSZÁROS, and ELI WAXMAN. "HIGH ENERGY NEUTRINOS FROM A SLOW JET MODEL OF CORE COLLAPSE SUPERNOVAE." Modern Physics Letters A 20, no. 31 (2005): 2351–67. http://dx.doi.org/10.1142/s0217732305018414.
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It has been hypothesized recently that core collapse supernovae are triggered by mildly relativistic jets following observations of radio properties of these explosions. Association of a jet, similar to a gamma-ray burst jet but only slower, allows shock acceleration of particles to high energy and non-thermal neutrino emission from a supernova. Detection of these high energy neutrinos in upcoming kilometer scale Cherenkov detectors may be the only direct way to probe inside these astrophysical phenomena as electromagnetic radiation is thermal and contains little information. Calculation of high energy neutrino signal from a simple and slow jet model buried inside the pre-supernova star is reviewed here. The detection prospect of these neutrinos in water or ice detector is also discussed in this brief review. Jetted core collapse supernovae in nearby galaxies may provide the strongest high energy neutrino signal from point sources.
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Adhikari, S., E. R. Ivins, and E. Larour. "ISSM-SESAW v1.0: mesh-based computation of gravitationally consistent sea level and geodetic signatures caused by cryosphere and climate driven mass change." Geoscientific Model Development Discussions 8, no. 11 (2015): 9769–816. http://dx.doi.org/10.5194/gmdd-8-9769-2015.
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Abstract. A classical Green's function approach to computing gravitationally consistent sea level variations, following mass redistribution on the earth surface, employed in contemporary state-of-the-art sea-level models naturally suits the spectral methods for numerical evaluation. The capability of these methods to resolve high wave number features such as small glaciers is limited by the need for large numbers of pixels and high-degree (associated Legendre) series truncation. Incorporating a spectral model into (components of) earth system models that generally operate on an unstructured mesh system also requires cumbersome and repetitive forward and inverse transform of solutions. In order to overcome these limitations of contemporary models, we present a novel computational method that functions efficiently on a flexible mesh system, thus capturing the physics operating at kilometer-scale yet capable of simulating geophysical observables that are inherently of global scale with minimal computational cost. The model has numerous important geophysical applications. Coupling to a local mesh of 3-D ice-sheet model, for example, allows for a refined and realistic simulation of fast-flowing outlet glaciers, while simultaneously retaining its global predictive capability. As an example model application, we provide time-varying computations of global geodetic and sea level signatures associated with recent ice sheet changes that are derived from space gravimetry observations.
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Tonttila, J., E. J. O'Connor, S. Niemelä, P. Räisänen, and H. Järvinen. "Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations." Atmospheric Chemistry and Physics 11, no. 17 (2011): 9207–18. http://dx.doi.org/10.5194/acp-11-9207-2011.
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Abstract. The statistics of cloud base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that AROME significantly underestimates the variability of vertical velocity at cloud base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4–8 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70–80 % of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 10 km in the presented case. Adding a TKE-term on the resolved grid-point vertical velocity can compensate for the underestimation, but only for altitudes below approximately the boundary layer top height. The results illustrate the need for a careful consideration of the scales the model is able to accurately resolve, as well as for a special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.
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Aguilar, L., and M. L. L. Wijerathne. "On a Mass Evacuation Simulator with Complex Autonomous Agents and Applications." Journal of Earthquake and Tsunami 10, no. 05 (2016): 1640021. http://dx.doi.org/10.1142/s1793431116400212.
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This paper presents the details of a mass evacuation simulator with complex autonomous agents on a high resolution model of environment along with demonstrative applications that highlight its usefulness, need and uniqueness. Most of existing mass evacuation simulators are based on simplified models, and the use of complex models is limited to small scale simulations. This simulator makes use of high performance computing to introduce a complex agent system to simulate evacuations in hundreds of square kilometer size domains. The framework of the developed multi-agent system and some of the agents’ constituent functions for interacting with high resolution grid are briefly explained. Interactions are validated using field observations. Two sets of applications are presented to demonstrate the systems use for simulating mixed mode evacuation and evacuation in dynamically changing environment.
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Sauvage, César, Cindy Lebeaupin Brossier, and Marie-Noëlle Bouin. "Towards kilometer-scale ocean–atmosphere–wave coupled forecast: a case study on a Mediterranean heavy precipitation event." Atmospheric Chemistry and Physics 21, no. 15 (2021): 11857–87. http://dx.doi.org/10.5194/acp-21-11857-2021.
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Abstract. The western Mediterranean Sea area is frequently affected in autumn by heavy precipitation events (HPEs). These severe meteorological episodes, characterized by strong offshore low-level winds and heavy rain in a short period of time, can lead to severe flooding and wave-submersion events. This study aims to progress towards an integrated short-range forecast system via coupled modeling for a better representation of the processes at the air–sea interface. In order to identify and quantify the coupling impacts, coupled ocean–atmosphere–wave simulations were performed for a HPE that occurred between 12 and 14 October 2016 in the south of France. The experiment using the coupled AROME-NEMO-WaveWatchIII system was notably compared to atmosphere-only, coupled atmosphere–wave and ocean–atmosphere simulations. The results showed that the HPE fine-scale forecast is sensitive to both couplings: the interactive coupling with the ocean leads to significant changes in the heat and moisture supply of the HPE that intensify the convective systems, while coupling with a wave model mainly leads to changes in the low-level dynamics, affecting the location of the convergence that triggers convection over the sea. Result analysis of this first case study with the AROME-NEMO-WaveWatchIII system does not clearly show major changes in the forecasts with coupling and highlights some attention points to follow (ocean initialization notably). Nonetheless, it illustrates the higher realism and potential benefits of kilometer-scale coupled numerical weather prediction systems, in particular in the case of severe weather events over the sea and/or in coastal areas, and shows their affordability to confidently progress towards operational coupled forecasts.
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Chappelow, J. E. "On the depths and shapes of the freshest kilometer-scale simple craters on the lunar maria: A new crater shape model." Meteoritics & Planetary Science 53, no. 4 (2017): 813–25. http://dx.doi.org/10.1111/maps.12853.
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Pichelli, Emanuela, Erika Coppola, Stefan Sobolowski, et al. "The first multi-model ensemble of regional climate simulations at kilometer-scale resolution part 2: historical and future simulations of precipitation." Climate Dynamics 56, no. 11-12 (2021): 3581–602. http://dx.doi.org/10.1007/s00382-021-05657-4.
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Kirmse, Andrew, and Jonathan de Ferranti. "Calculating the prominence and isolation of every mountain in the world." Progress in Physical Geography: Earth and Environment 41, no. 6 (2017): 788–802. http://dx.doi.org/10.1177/0309133317738163.
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A global-scale calculation identifies peaks in a digital elevation model (DEM) and computes their isolation and topographic prominence. A new DEM is presented that covers the entire globe at 90 meter resolution with no substantial voids or artifacts. All peaks with at least 1 kilometer of isolation are found, and the closest higher ground is identified. For prominence, all peaks with at least ∼30 meters are found, and the key saddle is identified. The prominence algorithm uses results from Morse–Smale topology to run in parallel on standard, freely available elevation data. Thirteen previously unknown “ultra-prominent” mountains with at least 1500 meters of prominence are listed.
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Kober, Kirstin, and George C. Craig. "Physically Based Stochastic Perturbations (PSP) in the Boundary Layer to Represent Uncertainty in Convective Initiation." Journal of the Atmospheric Sciences 73, no. 7 (2016): 2893–911. http://dx.doi.org/10.1175/jas-d-15-0144.1.
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Abstract Stochastic perturbations allow for the representation of small-scale variability due to unresolved physical processes. However, the properties of this variability depend on model resolution and weather regime. A physically based method is presented for introducing stochastic perturbations into kilometer-scale atmospheric models that explicitly account for these dependencies. The amplitude of the perturbations is based on information obtained from the model’s subgrid turbulence parameterization, while the spatial and temporal correlations are based on physical length and time scales of the turbulent motions. The stochastic perturbations lead to triggering of additional convective cells and improved precipitation amounts in simulations of two days with weak synoptic forcing of convection but different amounts of precipitation. The perturbations had little impact in a third case study, where precipitation was mainly associated with a cold front. In contrast, an unphysical version of the scheme with constant perturbation amplitude performed poorly since there was no perturbation amplitude that would give improved amounts of precipitation during the day without generating spurious convection at other times.
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Xia, Ming. "Thermo-mechanical coupling particle simulation of three-dimensional large-scale non-isothermal problems." Engineering Computations 34, no. 5 (2017): 1551–71. http://dx.doi.org/10.1108/ec-04-2016-0135.
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Purpose The main purpose of this paper is to present a comprehensive upscale theory of the thermo-mechanical coupling particle simulation for three-dimensional (3D) large-scale non-isothermal problems, so that a small 3D length-scale particle model can exactly reproduce the same mechanical and thermal results with that of a large 3D length-scale one. Design/methodology/approach The objective is achieved by following the scaling methodology proposed by Feng and Owen (2014). Findings After four basic physical quantities and their similarity-ratios are chosen, the derived quantities and its similarity-ratios can be derived from its dimensions. As the proposed comprehensive 3D upscale theory contains five similarity criteria, it reveals the intrinsic relationship between the particle-simulation solution obtained from a small 3D length-scale (e.g. a laboratory length-scale) model and that obtained from a large 3D length-scale (e.g. a geological length-scale) one. The scale invariance of the 3D interaction law in the thermo-mechanical coupled particle model is examined. The proposed 3D upscale theory is tested through two typical examples. Finally, a practical application example of 3D transient heat flow in a solid with constant heat flux is given to illustrate the performance of the proposed 3D upscale theory in the thermo-mechanical coupling particle simulation of 3D large-scale non-isothermal problems. Both the benchmark tests and application example are provided to demonstrate the correctness and usefulness of the proposed 3D upscale theory for simulating 3D non-isothermal problems using the particle simulation method. Originality/value The paper provides some important theoretical guidance to modeling 3D large-scale non-isothermal problems at both the engineering length-scale (i.e. the meter-scale) and the geological length-scale (i.e. the kilometer-scale) using the particle simulation method directly.
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Leroyer, Sylvie, Stéphane Bélair, Syed Z. Husain, and Jocelyn Mailhot. "Subkilometer Numerical Weather Prediction in an Urban Coastal Area: A Case Study over the Vancouver Metropolitan Area." Journal of Applied Meteorology and Climatology 53, no. 6 (2014): 1433–53. http://dx.doi.org/10.1175/jamc-d-13-0202.1.
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AbstractNumerical weather prediction is moving toward the representation of finescale processes such as the interactions between the sea-breeze flow and urban processes. This study investigates the ability and necessity of using kilometer- to subkilometer-scale numerical simulations with the Canadian urban modeling system over the complex urban coastal area of Vancouver, British Columbia, Canada, during a sea-breeze event. Observations over the densely urbanized areas, collected from the Environmental Prediction in Canadian Cities (EPiCC) network and from satellite imagery, are used to evaluate several aspects of the urban boundary layer features simulated in three model configurations with different grid spacings (2.5 km, 1 km, and 250 m). In agreement with the observations, results from the numerical experiments with 1-km and 250-m grid spacings suggest that two sea-breeze flows converge over the residential areas of Vancouver. The resulting convergence line oscillates around the hill ridge, depending on thermal contrast and flow strength. This propagation mode impacts the growing urban boundary layer, with the presence of subsidence and entrainment events. Urban-induced circulation is superimposed with the sea-breeze circulation and realistically slows down the propagation of the sea-breeze front to the south. A clear improvement is obtained for numerical experiments with 1-km instead of 2.5-km grid spacing. The use of subkilometer grid spacing provides a more detailed representation of the surface thermal forcing and of local circulations, with results more sensitive to the airflow variability and, thus, to the location of measurement sites. Joint analyses of kilometer- and subkilometer-scale numerical experiments are thus recommended for different environmental applications.
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Paoli, R., O. Thouron, J. Escobar, J. Picot, and D. Cariolle. "High-resolution large-eddy simulations of stably stratified flows: application to subkilometer-scale turbulence in the upper troposphere–lower stratosphere." Atmospheric Chemistry and Physics 14, no. 10 (2014): 5037–55. http://dx.doi.org/10.5194/acp-14-5037-2014.
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Abstract. Large-eddy simulations of stably stratified flows are carried out and analyzed using the mesoscale atmospheric model Méso-NH for applications to kilometer- and subkilometer-scale turbulence in the in the upper troposphere–lower stratosphere. Different levels of turbulence are generated using a large-scale stochastic forcing technique that was especially devised to treat atmospheric stratified flows. The study focuses on the analysis of turbulence statistics, including mean quantities and energy spectra, as well as on a detailed description of flow topology. The impact of resolution is also discussed by decreasing the grid spacing to 2 m and increasing the number of grid points to 8 × 109. Because of atmospheric stratification, turbulence is substantially anisotropic, and large elongated structures form in the horizontal directions, in accordance with theoretical analysis and spectral, direct numerical simulations of stably stratified flows. It is also found that the inertial range of horizontal kinetic energy spectrum, generally observed at scales larger than a few kilometers, is prolonged into the subkilometric range, down to the Ozmidov scales that obey isotropic Kolmogorov turbulence. This study shows the capability of atmospheric models like Méso-NH to represent the turbulence at subkilometer scales.
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Harnisch, Florian, and Christian Keil. "Initial Conditions for Convective-Scale Ensemble Forecasting Provided by Ensemble Data Assimilation." Monthly Weather Review 143, no. 5 (2015): 1583–600. http://dx.doi.org/10.1175/mwr-d-14-00209.1.
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Abstract A kilometer-scale ensemble data assimilation system (KENDA) based on a local ensemble transform Kalman filter (LETKF) has been developed for the Consortium for Small-Scale Modeling (COSMO) limited-area model. The data assimilation system provides an analysis ensemble that can be used to initialize ensemble forecasts at a horizontal grid resolution of 2.8 km. Convective-scale ensemble forecasts over Germany using ensemble initial conditions derived by the KENDA system are evaluated and compared to operational forecasts with downscaled initial conditions for a short summer period during June 2012. The choice of the inflation method applied in the LETKF significantly affects the ensemble analysis and forecast. Using a multiplicative background covariance inflation does not produce enough spread in the analysis ensemble leading to a degradation of the ensemble forecasts. Inflating the analysis ensemble instead by either multiplicative analysis covariance inflation or relaxation inflation methods enhances the analysis spread and is able to provide initial conditions that produce more consistent ensemble forecasts. The forecast quality for short forecast lead times up to 3 h is improved, and 21-h forecasts also benefit from the increased spread. Doubling the ensemble size has not only a clear positive impact on the analysis but also on the short-term ensemble forecasts, while a simple representation of model error perturbing parameters of the model physics has only a small impact. Precipitation and surface wind speed ensemble forecasts using the high-resolution KENDA-derived initial conditions are competitive compared to the operationally used downscaled initial conditions.
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Müller, Malte, Yurii Batrak, Jørn Kristiansen, Morten A. Ø. Køltzow, Gunnar Noer, and Anton Korosov. "Characteristics of a Convective-Scale Weather Forecasting System for the European Arctic." Monthly Weather Review 145, no. 12 (2017): 4771–87. http://dx.doi.org/10.1175/mwr-d-17-0194.1.
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In this study a 1-yr dataset of a convective-scale atmospheric prediction system of the European Arctic (AROME-Arctic) is compared with the ECMWF’s medium-range forecasting, ensemble forecasting, and reanalysis systems, by using surface and radiosonde observations of wind and temperature. The focus is on the characteristics of the model systems in the very short-term forecast range (6–15 h), but without a specific focus on lead-time dependencies. In general, AROME-Arctic adds value to the representation of the surface characteristics. The atmospheric boundary layer thickness, during stable conditions, is overestimated in the global models, presumably because of a too diffusive turbulence scheme. Instead, AROME-Arctic shows a realistic mean thickness compared to the radiosonde observations. All models behave similarly for the upper-air verification and surprisingly, as well, in forecasting the location of a polar low in the short-range forecasts. However, when comparing with the largest wind speeds from ocean surface winds and at coastal synoptic weather stations during landfall of a polar low, AROME-Arctic shows the most realistic values. In addition to the model intercomparison, the limitation of the representation of sea ice and ocean surface characteristics on kilometer scales are discussed in detail. This major challenge is illustrated by showing the rapid drift and development of sea ice leads during a cold-air outbreak. As well, the available sea surface temperature products and a high-resolution ocean model result are compared qualitatively. New developments of satellite products, ocean–sea ice prediction models, or parameterizations, tailored toward high-resolution atmospheric Arctic prediction, are necessary to overcome this limitation.
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Shin, Hyeyum Hailey, and Jimy Dudhia. "Evaluation of PBL Parameterizations in WRF at Subkilometer Grid Spacings: Turbulence Statistics in the Dry Convective Boundary Layer." Monthly Weather Review 144, no. 3 (2016): 1161–77. http://dx.doi.org/10.1175/mwr-d-15-0208.1.
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Abstract Planetary boundary layer (PBL) parameterizations in mesoscale models have been developed for horizontal resolutions that cannot resolve any turbulence in the PBL, and evaluation of these parameterizations has been focused on profiles of mean and parameterized flux. Meanwhile, the recent increase in computing power has been allowing numerical weather prediction (NWP) at horizontal grid spacings finer than 1 km, at which kilometer-scale large eddies in the convective PBL are partly resolvable. This study evaluates the performance of convective PBL parameterizations in the Weather Research and Forecasting (WRF) Model at subkilometer grid spacings. The evaluation focuses on resolved turbulence statistics, considering expectations for improvement in the resolved fields by using the fine meshes. The parameterizations include four nonlocal schemes—Yonsei University (YSU), asymmetric convective model 2 (ACM2), eddy diffusivity mass flux (EDMF), and total energy mass flux (TEMF)—and one local scheme, the Mellor–Yamada–Nakanishi–Niino (MYNN) level-2.5 model. Key findings are as follows: 1) None of the PBL schemes is scale-aware. Instead, each has its own best performing resolution in parameterizing subgrid-scale (SGS) vertical transport and resolving eddies, and the resolution appears to be different between heat and momentum. 2) All the selected schemes reproduce total vertical heat transport well, as resolved transport compensates differences of the parameterized SGS transport from the reference SGS transport. This interaction between the resolved and SGS parts is not found in momentum. 3) Those schemes that more accurately reproduce one feature (e.g., thermodynamic transport, momentum transport, energy spectrum, or probability density function of resolved vertical velocity) do not necessarily perform well for other aspects.
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Kendon, Elizabeth J., Nikolina Ban, Nigel M. Roberts, et al. "Do Convection-Permitting Regional Climate Models Improve Projections of Future Precipitation Change?" Bulletin of the American Meteorological Society 98, no. 1 (2017): 79–93. http://dx.doi.org/10.1175/bams-d-15-0004.1.
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Abstract Regional climate projections are used in a wide range of impact studies, from assessing future flood risk to climate change impacts on food and energy production. These model projections are typically at 12–50-km resolution, providing valuable regional detail but with inherent limitations, in part because of the need to parameterize convection. The first climate change experiments at convection-permitting resolution (kilometer-scale grid spacing) are now available for the United Kingdom; the Alps; Germany; Sydney, Australia; and the western United States. These models give a more realistic representation of convection and are better able to simulate hourly precipitation characteristics that are poorly represented in coarser-resolution climate models. Here we examine these new experiments to determine whether future midlatitude precipitation projections are robust from coarse to higher resolutions, with implications also for the tropics. We find that the explicit representation of the convective storms themselves, only possible in convection-permitting models, is necessary for capturing changes in the intensity and duration of summertime rain on daily and shorter time scales. Other aspects of rainfall change, including changes in seasonal mean precipitation and event occurrence, appear robust across resolutions, and therefore coarse-resolution regional climate models are likely to provide reliable future projections, provided that large-scale changes from the global climate model are reliable. The improved representation of convective storms also has implications for projections of wind, hail, fog, and lightning. We identify a number of impact areas, especially flooding, but also transport and wind energy, for which very high-resolution models may be needed for reliable future assessments.
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Vionnet, Vincent, Stéphane Bélair, Claude Girard, and André Plante. "Wintertime Subkilometer Numerical Forecasts of Near-Surface Variables in the Canadian Rocky Mountains." Monthly Weather Review 143, no. 2 (2015): 666–86. http://dx.doi.org/10.1175/mwr-d-14-00128.1.
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Abstract Numerical weather prediction (NWP) systems operational at many national centers are nowadays used at the kilometer scale. The next generation of NWP models will provide forecasts at the subkilometer scale. Large impacts are expected in mountainous terrain characterized by highly variable orography. This study investigates the ability of the Canadian NWP system to provide an accurate forecast of near-surface variables at the subkilometer scale in the Canadian Rocky Mountains in wintertime when the region is fully covered by snow. Observations collected at valley and high-altitude stations are used to evaluate forecast accuracy at three different grid spacing (2.5, 1, and 0.25 km) over a period of 15 days. Decreasing grid spacing was found to improve temperature forecasts at high-altitude stations because of better orography representation. In contrast, no improvement is obtained at valley stations due to an inability of the model to fully capture at all resolutions the intensity of valley cold pools forming during nighttime. Errors in relative humidity reveal that the model tends to overestimate relative humidity at all resolutions, without improvement with decreasing grid spacing. Wind speed forecasts show large improvements with decreasing grid spacing for high-altitude stations exposed to or sheltered from wind. However, no systematic improvement with decreasing grid spacing is found for all stations, which is similar to previous studies. In addition, the model’s sensitivity at subkilometer grid spacing is investigated by evaluating the effects of (i) accounting for additional drag generated by subgrid orographic features, (ii) considering slope angle and aspect on surface radiation, and (iii) using high-resolution initialization for the surface fields.