High-Resolution COSMO-CLM Modeling and an Assessment of Mesoscale Features Caused by Coastal Parameters at Near-Shore Arctic Zones (Kara Sea)

Coastal Arctic regions are characterized by severe mesoscale weather events that include extreme wind speeds, and the rugged shore conditions, islands, and mountain ranges contribute to mesoscale event formation. High-resolution atmospheric modeling is a suitable tool to reproduce and estimate some of these events, and so the regional non-hydrostatic climate atmospheric model COSMO-CLM (Consortium for Small-scale Modeling developed within the framework of the international science group CLM-Community) was used to reproduce mesoscale circulation in the Arctic coast zone under various surface conditions. Mid-term experiments were run over the Arctic domain, especially over the Kara Sea region, using the downscaling approach, with ≈12 km and ≈3 km horizontal grid sizes. The best model configuration was determined using standard verification methods; however, the model run verification process raised questions over its quality and aptness based on the high level of small-scale coastline diversity and associated relief properties. Modeling case studies for high wind speeds were used to study hydrodynamic mesoscale circulation reproduction, and we found that although the model could not describe the associated wind dynamic features at all scales using ≈3 km resolution, it could simulate different scales of island wind shadow effects, tip jets, downslope winds, vortex chains, and so on, quite realistically. This initial success indicated that further research could reveal more about the detailed properties of mesoscale circulations and extreme winds by applying finer resolution modeling.

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High-resolution refinement of a storm loss model and estimation of return periods of loss-intensive storms over Germany

Natural Hazards and Earth System Science ◽

10.5194/nhess-11-2821-2011 ◽

2011 ◽

Vol 11 (10) ◽

pp. 2821-2833 ◽

Cited By ~ 33

Author(s):

M. G. Donat ◽

T. Pardowitz ◽

G. C. Leckebusch ◽

U. Ulbrich ◽

O. Burghoff

Keyword(s):

High Resolution ◽

Statistical Characteristics ◽

Extreme Value Analysis ◽

Small Scale ◽

Storm Event ◽

Return Periods ◽

Storm Events ◽

Value Analysis ◽

Loss Model ◽

Wind Speeds

Abstract. A refined model for the calculation of storm losses is presented, making use of high-resolution insurance loss records for Germany and allowing loss estimates on a spatial level of administrative districts and for single storm events. Storm losses are calculated on the basis of wind speeds from both ERA-Interim and NCEP reanalyses. The loss model reproduces the spatial distribution of observed losses well by taking specific regional loss characteristics into account. This also permits high-accuracy estimates of total cumulated losses, though slightly underestimating the country-wide loss sums for storm "Kyrill", the most severe event in the insurance loss records from 1997 to 2007. A larger deviation, which is assigned to the relatively coarse resolution of the NCEP reanalysis, is only found for one specific rather small-scale event, not adequately captured by this dataset. The loss model is subsequently applied to the complete reanalysis period to extend the storm event catalogue to cover years when no systematic insurance records are available. This allows the consideration of loss-intensive storm events back to 1948, enlarging the event catalogue to cover the recent 60+ years, and to investigate the statistical characteristics of severe storm loss events in Germany based on a larger sample than provided by the insurance records only. Extreme value analysis is applied to the loss data to estimate the return periods of loss-intensive storms, yielding a return period for storm "Kyrill", for example, of approximately 15 to 21 years.

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Comparison of sea ice kinematics at different resolutions modeled with a grid hierarchy in the Community Earth System Model (version 1.2.1)

Geoscientific Model Development ◽

10.5194/gmd-14-603-2021 ◽

2021 ◽

Vol 14 (1) ◽

pp. 603-628

Author(s):

Shiming Xu ◽

Jialiang Ma ◽

Lu Zhou ◽

Yan Zhang ◽

Jiping Liu ◽

...

Keyword(s):

High Resolution ◽

Sea Ice ◽

Earth System Model ◽

System Model ◽

The Arctic ◽

Small Scale ◽

Earth System ◽

Atmospheric Circulation Patterns ◽

Community Earth System Model ◽

Climate Studies

Abstract. High-resolution sea ice modeling is becoming widely available for both operational forecasts and climate studies. In traditional Eulerian grid-based models, small-scale sea ice kinematics represent the most prominent feature of high-resolution simulations, and with rheology models such as viscous–plastic (VP) and Maxwell elasto-brittle (MEB), sea ice models are able to reproduce multi-fractal sea ice deformation and linear kinematic features that are seen in high-resolution observational datasets. In this study, we carry out modeling of sea ice with multiple grid resolutions by using the Community Earth System Model (CESM) and a grid hierarchy (22, 7.3, and 2.4 km grid stepping in the Arctic). By using atmospherically forced experiments, we simulate consistent sea ice climatology across the three resolutions. Furthermore, the model reproduces reasonable sea ice kinematics, including multi-fractal spatial scaling of sea ice deformation that partially depends on atmospheric circulation patterns and forcings. By using high-resolution runs as references, we evaluate the model's effective resolution with respect to the statistics of sea ice kinematics. Specifically, we find the spatial scale at which the probability density function (PDF) of the scaled sea ice deformation rate of low-resolution runs matches that of high-resolution runs. This critical scale is treated as the effective resolution of the coarse-resolution grid, which is estimated to be about 6 to 7 times the grid's native resolution. We show that in our model, the convergence of the elastic–viscous–plastic (EVP) rheology scheme plays an important role in reproducing reasonable kinematics statistics and, more strikingly, simulates systematically thinner sea ice than the standard, non-convergent experiments in landfast ice regions of the Canadian Arctic Archipelago. Given the wide adoption of EVP and subcycling settings in current models, it highlights the importance of EVP convergence, especially for climate studies and projections. The new grids and the model integration in CESM are openly provided for public use.

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Combined wind measurements by two different lidar instruments in the Arctic middle atmosphere

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-5-4123-2012 ◽

2012 ◽

Vol 5 (3) ◽

pp. 4123-4156 ◽

Cited By ~ 3

Author(s):

J. Hildebrand ◽

G. Baumgarten ◽

J. Fiedler ◽

U.-P. Hoppe ◽

B. Kaifler ◽

...

Keyword(s):

Middle Atmosphere ◽

The Arctic ◽

Horizontal Wind ◽

Small Scale ◽

Wind Component ◽

Lower Altitude ◽

Wind Speeds ◽

Lidar Measurements ◽

Wind Measurements ◽

Good Agreement

Abstract. During a joint campaign in January 2009 the Rayleigh/Mie/Raman (RMR) lidar and the sodium lidar at the ALOMAR Observatory (69° N, 16° E) in Northern Norway were operated simultaneously for more than 40 h, collecting data for wind measurements in the middle atmosphere from 30 up to 110 km altitude. At the upper (lower) altitude range where the RMR (sodium) lidar can operate, both lidars probe the same sounding volume, allowing to compare the derived wind speeds. We present the first simultaneous common volume wind measurements in the middle atmosphere using two different lidar instruments. The comparison of winds derived by RMR and sodium lidar is excellent for long integration times of 10 h as well as shorter ones of 1 h. Combination of data from both lidars allows identifying wavy structures between 30 and 110 km altitude, whose amplitudes increase with height. We have also performed lidar measurements of the same wind component using two independent branches of the RMR lidar and found a good agreement of the results but also identified inhomogeneities in the horizontal wind at about 55 km altitude of up to 20 ms−1. Such small scale inhomogeneities in the horizontal wind field are an essential challenge when comparing data from different instruments.

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An Evaluation of QPF from the WRF, NAM, and GFS Models Using Multiple Verification Methods over a Small Domain

Weather and Forecasting ◽

10.1175/waf-d-16-0020.1 ◽

2016 ◽

Vol 31 (4) ◽

pp. 1363-1379 ◽

Cited By ~ 13

Author(s):

Haifan Yan ◽

William A. Gallus

Keyword(s):

High Resolution ◽

Wrf Model ◽

Radar Data ◽

Early Morning ◽

Small Scale ◽

Time Interval ◽

Verification Methods ◽

Small Domain ◽

Arw Model ◽

Neighborhood Scale

Abstract The ARW model was run over a small domain centered on Iowa for 9 months with 4-km grid spacing to better understand the limits of predictability of short-term (12 h) quantitative precipitation forecasts (QPFs) that might be used in hydrology models. Radar data assimilation was performed to reduce spinup problems. Three grid-to-grid verification methods, as well as two spatial techniques, neighborhood and object based, were used to compare the QPFs from the high-resolution runs with coarser operational GFS and NAM QPFs to verify QPFs for various precipitation accumulation intervals and on two grid configurations with different resolutions. In general, NAM had the worst performance not only for model skill but also for spatial feature attributes as a result of the existence of large dry bias and location errors. The finer resolution of NAM did not offer any advantage in predicting small-scale storms compared to the coarser GFS. WRF had a large advantage for high precipitation thresholds. A greater improvement in skill was noted when the accumulation time interval was increased, compared to an increase in the spatial neighborhood size. At the same neighborhood scale, the high-resolution WRF Model was less influenced by the grid on which the verification was done than the other two models. All models had the highest skill from midnight to early morning, because the least wet bias, location, and coverage errors were present then. The lowest skill was shown from late morning through afternoon. The main cause of poor skill during this period was large displacement errors.

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Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation

Atmosphere ◽

10.3390/atmos12030350 ◽

2021 ◽

Vol 12 (3) ◽

pp. 350

Author(s):

Vladimir Platonov ◽

Mikhail Varentsov

Keyword(s):

Arctic Region ◽

Weather Conditions ◽

Atmospheric Model ◽

Reanalysis Data ◽

Environmental Data ◽

Added Value ◽

The Arctic ◽

Russian Arctic ◽

Wind Speeds

Diverse and severe weather conditions and rapid climate change rates in the Arctic emphasize the need for high-resolution climatic and environmental data that cannot be obtained from the scarce observational networks. This study presents a new detailed hydrometeorological dataset for the Russian Arctic region, obtained as a long-term hindcast with the nonhydrostatic atmospheric model COSMO-CLM for the 1980–2016 period. The modeling workflow, evaluation techniques, and preliminary analysis of the obtained dataset are discussed. The model domain included the Barents, Kara, and Laptev Seas with ≈12-km grid spacing. The optimal model setup was chosen based on preliminary simulations for several summer and winter periods with varied options, and included the usage of ERA-Interim reanalysis data as forcing data, the new model version 5.05 with so-called ICON-based physics, and a spectral nudging technique. The wind speed and temperature climatology in the new COSMO-CLM dataset closely agreed with the ERA-Interim reanalysis, but with detailed spatial patterns. The added value of the higher-resolution COSMO-CLM data with respect to the ERA-Interim was most pronounced for higher wind speeds during downslope windstorms with the influence of mountain ranges on the temperature patterns, including surface temperature inversions. The potential applications and plans of further product development are also discussed.

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Image Collection Simulation Using High-Resolution Atmospheric Modeling

Remote Sensing ◽

10.3390/rs12193214 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3214

Author(s):

Andrew Kalukin ◽

Satoshi Endo ◽

Russell Crook ◽

Manoj Mahajan ◽

Robert Fennimore ◽

...

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Atmospheric Model ◽

Remote Sensing Image ◽

Atmospheric Modeling ◽

Atmospheric Effects ◽

Multispectral Imagery ◽

Modeling Framework ◽

Voxel Grid ◽

Image Collection

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.

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Numerical Modeling of Meteotsunami–Tide Interaction in the Eastern Yellow Sea

Atmosphere ◽

10.3390/atmos10070369 ◽

2019 ◽

Vol 10 (7) ◽

pp. 369 ◽

Cited By ~ 1

Author(s):

Ki-Young Heo ◽

Jae-Seon Yoon ◽

Jae-Seok Bae ◽

Taemin Ha

Keyword(s):

High Resolution ◽

Yellow Sea ◽

Atmospheric Pressure ◽

High Tide ◽

Atmospheric Modeling ◽

Tidal Currents ◽

Coastal Communities ◽

The Yellow Sea ◽

Small Scale ◽

Western Coast

Meteotsunamis originating from atmospheric pressure disturbances have frequently occurred in oceans worldwide and their destructive long waves have recently threatened local coastal communities. In particular, meteotsunamis occurring in the Yellow Sea caused unexpected casualties and property damage to local communities on the western coast of the Korean Peninsula in 2007 and 2008. These events attracted the attention of many engineers and scientists because abrupt extreme waves have struck several coasts and ports even under fine weather conditions. Furthermore, the Yellow Sea has the highest tide and most powerful tidal currents in the world, and consequently, meteotsunami events there could be more destructive and harmful to local coastal communities when such events occur during high tide or a critical phase with strong tidal currents. In this study, numerical experiments were conducted to identify the qualitative effect of the interaction between a meteotsunami and the tide on the generation and amplification mechanisms of meteotsunamis occurring in the Yellow Sea. In general, small-scale meteotsunamis, such as those that occur in the Yellow Sea, should be analyzed using a high-resolution modeling system because water motions can be affected by local terrain. To achieve this objective, high-resolution atmospheric modeling was conducted to reproduce the atmospheric pressure disturbances observed in the Yellow Sea; then, the generation and propagation of the meteotsunami over real topographies was simulated using a phase-resolving wave model. Both an atmospheric model (Weather Research and Forecasting Model (WRF)) and a shallow water equation model (COrnell Multigrid COupled Tsunami Model (COMCOT)) were employed to simulate the generation and transformation of the meteotsunami.

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Trace gas transport in the 1999/2000 Arctic winter: comparison of nudged GCM runs with observations

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-3-2465-2003 ◽

2003 ◽

Vol 3 (3) ◽

pp. 2465-2497

Author(s):

M. K. van Aalst ◽

M. M. P. van den Broek ◽

A. Bregman ◽

C. Brühl ◽

B. Steil ◽

...

Keyword(s):

General Circulation ◽

Circulation Model ◽

Atmospheric Model ◽

Transport Processes ◽

The Arctic ◽

Trace Gas ◽

Small Scale ◽

Satellite Measurements ◽

Balloon Measurements ◽

Middle Stratosphere

Abstract. We have compared satellite and balloon observations of methane (CH4) and hydrogen fluoride (HF) during the Arctic winter 1999/2000 with results from the MA-ECHAM4 middle atmospheric general circulation model (GCM). For this purpose, the meteorology in the model was nudged towards ECMWF analyses. This nudging technique is shown to work well for this middle atmospheric model, and offers good opportunities for the simulation of realistic chemistry and transport processes. The current study focuses on transport of HF and CH4, initialized with satellite measurements from the HALOE instrument aboard the UARS satellite. We have compared the model results with HALOE data and balloon measurements throughout the winter, and analyzed the uncertainties associated with tracer initialization, boundary conditions and the passive tracer assumption. This comparison shows that the model represents the Arctic vortex well, including relatively small-scale features. However, while profiles outside the vortex match well, the model underestimates HF and overestimates CH4 concentrations inside the vortex, particularly in the middle stratosphere. This problem is also evident in a comparison of vortex descent rates based upon vortex average tracer profiles from MA-ECHAM4, and various observations, respectively. This could be due to an underestimate of diabatic subsidence in the model, or due to too much mixing between vortex and non-vortex air.

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An NWP Model Intercomparison of Surface Weather Parameters in the European Arctic during the Year of Polar Prediction Special Observing Period Northern Hemisphere 1

Weather and Forecasting ◽

10.1175/waf-d-19-0003.1 ◽

2019 ◽

Vol 34 (4) ◽

pp. 959-983 ◽

Cited By ~ 8

Author(s):

Morten Køltzow ◽

Barbara Casati ◽

Eric Bazile ◽

Thomas Haiden ◽

Teresa Valkonen

Keyword(s):

High Resolution ◽

Wind Speed ◽

The Arctic ◽

Small Scale ◽

Limited Area ◽

Model Intercomparison ◽

Near Surface ◽

Surface Weather ◽

High Resolution Models ◽

The Impact

AbstractIncreased human activity in the Arctic calls for accurate and reliable weather predictions. This study presents an intercomparison of operational and/or high-resolution models in an attempt to establish a baseline for present-day Arctic short-range forecast capabilities for near-surface weather (pressure, wind speed, temperature, precipitation, and total cloud cover) during winter. One global model [the high-resolution version of the ECMWF Integrated Forecasting System (IFS-HRES)], and three high-resolution, limited-area models [Applications of Research to Operations at Mesoscale (AROME)-Arctic, Canadian Arctic Prediction System (CAPS), and AROME with Météo-France setup (MF-AROME)] are evaluated. As part of the model intercomparison, several aspects of the impact of observation errors and representativeness on the verification are discussed. The results show how the forecasts differ in their spatial details and how forecast accuracy varies with region, parameter, lead time, weather, and forecast system, and they confirm many findings from mid- or lower latitudes. While some weaknesses are unique or more pronounced in some of the systems, several common model deficiencies are found, such as forecasting temperature during cloud-free, calm weather; a cold bias in windy conditions; the distinction between freezing and melting conditions; underestimation of solid precipitation; less skillful wind speed forecasts over land than over ocean; and difficulties with small-scale spatial variability. The added value of high-resolution limited area models is most pronounced for wind speed and temperature in regions with complex terrain and coastlines. However, forecast errors grow faster in the high-resolution models. This study also shows that observation errors and representativeness can account for a substantial part of the difference between forecast and observations in standard verification.

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