scholarly journals The Impact of Spatial Resolution, Land Use, and Spinup Time on Resolving Spatial Precipitation Patterns in the Himalayas

2018 ◽  
Vol 19 (10) ◽  
pp. 1565-1581 ◽  
Author(s):  
P. N. J. Bonekamp ◽  
E. Collier ◽  
W. W. Immerzeel
Keyword(s):  
High Resolution ◽  
Observational Data ◽  
Spatial Resolution ◽  
Dynamical Downscaling ◽  
Wrf Model ◽  
Temperature Fields ◽  
High Mountain ◽  
Surface Boundary ◽  
The Impact

Abstract Frequently used gridded meteorological datasets poorly represent precipitation in the Himalayas because of their relatively low spatial resolution and the associated representation of the complex topography. Dynamical downscaling using high-resolution atmospheric models may improve the accuracy and quality of the precipitation fields. However, most physical parameterization schemes are designed for a spatial resolution coarser than 1 km. In this study the Weather Research and Forecasting (WRF) Model is used to determine which resolution is required to most accurately simulate monsoon and winter precipitation, 2-m temperature, and wind fields in the Nepalese Himalayas. Four model nests are set up with spatial resolutions of 25, 5, 1, and 0.5 km, respectively, and a typical 10-day period in summer and winter in 2014 are simulated. The model output is compared with observational data obtained from automatic weather stations, pluviometers, and tipping buckets in the Langtang catchment. Results show that, despite issues with the quality of the observational data due to undercatch of snowfall, the highest resolution of 500 m does provide the best match with the observations and gives the most plausible spatial distribution of precipitation. The quality of the wind and temperature fields is also improved, whereby the cold temperature bias is decreased. Our results further elucidate the performance of WRF at high resolution and demonstrate the importance of accurate surface boundary conditions and spinup time for simulating precipitation. Furthermore, they suggest that future modeling studies of High Mountain Asia should consider a subkilometer grid for accurately estimating local meteorological variability.

scholarly journals Impact of Dynamically Downscaling Two CMIP5 Models on the Historical and Future Changes in Winter Extratropical Cyclones along the East Coast of North America

2018 ◽  
Vol 31 (20) ◽  
pp. 8499-8525 ◽  
Author(s):  
Zhenhai Zhang ◽  
Brian A. Colle
Keyword(s):  
High Resolution ◽  
North America ◽  
East Coast ◽  
Dynamical Downscaling ◽  
Wrf Model ◽  
Cmip5 Models ◽  
Extratropical Cyclones ◽  
Western Atlantic ◽  
Global Circulation Models ◽  
The Impact

This study investigates the impact of dynamical downscaling on historical and future projections of winter extratropical cyclones over eastern North America and the western Atlantic Ocean. Six-hourly output from two global circulation models (GCMs), CCSM4 and GFDL-ESM2M, from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used to create the initial and boundary conditions for 20 historical (1986–2005) and 20 future (2080–99) winter simulations using the Weather Research and Forecasting (WRF) Model. Two sets of WRF grid spacing (1.0° and 0.2°) are examined to determine the impact of model resolution. Although the cyclone frequency in the WRF runs is largely determined by the GCM predictions, the higher-resolution WRF reduces the underprediction in cyclone intensity. There is an increase in late-twenty-first-century cyclone activity over the east coast of North America in CCSM4 and its WRF, whereas there is little change in GFDL-ESM2M and WRF given that there is a larger decrease in the temperature gradient in this region. There is a future increase in relatively deep cyclones over the East Coast in the high-resolution WRF forced by CCSM4. These storms are weaker than the historical cases early in their life cycle, but then because of latent heating they rapidly develop and become stronger than the historical events. This increase does not occur in the low-resolution WRF or the high-resolution WRF forced by GFDL since the latent heat increase is relatively small. This implies that the diabatic processes during cyclogenesis may become more important in a warmer climate, and these processes may be too weak in existing coarse-resolution GCMs.

Examining Terrain Effects on an Upstate New York Tornado Event Utilizing a High-Resolution Model Simulation

2021 ◽  
Author(s):  
Luke J. LeBel ◽  
Brian H. Tang ◽  
Ross A. Lazear
Keyword(s):  
New York ◽  
High Resolution ◽  
Wind Shear ◽  
Model Simulation ◽  
Wrf Model ◽  
Severe Weather ◽  
Streamwise Vorticity ◽  
Low Level ◽  
Severe Convection ◽  
The Impact

AbstractThe complex terrain at the intersection of the Mohawk and Hudson valleys of New York has an impact on the development and evolution of severe convection in the region. Specifically, previous research has concluded that terrain-channeled flow in the Mohawk and Hudson valleys likely contributes to increased low-level wind shear and instability in the valleys during severe weather events such as the historic 31 May 1998 event that produced a strong (F3) tornado in Mechanicville, New York.The goal of this study is to further examine the impact of terrain channeling on severe convection by analyzing a high-resolution WRF model simulation of the 31 May 1998 event. Results from the simulation suggest that terrain-channeled flow resulted in the localized formation of an enhanced low-level moisture gradient, resembling a dryline, at the intersection of the Mohawk and Hudson valleys. East of this boundary, the environment was characterized by stronger low-level wind shear and greater low-level moisture and instability, increasing tornadogenesis potential. A simulated supercell intensified after crossing the boundary, as the larger instability and streamwise vorticity of the low-level inflow was ingested into the supercell updraft. These results suggest that terrain can have a key role in producing mesoscale inhomogeneities that impact the evolution of severe convection. Recognition of these terrain-induced boundaries may help in anticipating where the risk of severe weather may be locally enhanced.

Thermo-Solutal Convection of a Nanofluid Utilizing Fourier’s-Type Compass Conditions

2020 ◽  
Vol 9 (4) ◽  
pp. 362-374
Author(s):  
J. C. Umavathi ◽  
Ali J. Chamkha
Keyword(s):  
Brownian Motion ◽  
Prandtl Number ◽  
Boundary Conditions ◽  
Volume Fraction ◽  
Temperature Fields ◽  
Physical Parameters ◽  
Surface Boundary ◽  
Perturbation Scheme ◽  
Runge Kutta ◽  
The Impact

Nanotechnology has infiltrated into duct design in parallel with many other fields of mechanical, medical and energy engineering. Motivated by the excellent potential of nanofluids, a subset of materials engineered at the nanoscale, in the present work, a new mathematical model is developed for natural convection in a vertical duct containing nanofluid. Numerical scrutiny for the double-diffusive free and forced convection within a duct encumbered with nanofluid is performed. Buongiorno’s model is deployed to define the nanofluid. Robin boundary conditions are used to define the surface boundary conditions. Thermal and concentration equations envisage the viscous, Brownian motion, thermosphores of the nanofluid, Soret and Dufour effects. Using the Boussi-nesq approximation the solutal buoyancy effect as a result of gradients in concentration are incorporated. The conservation equations which are nonlinear are numerically estimated using fourth order Runge-Kutta methodology and analytically ratifying regular perturbation scheme. The mass, heat, nanoparticle concentration and species concentration fields on eight dimensionless physical parameters such as thermal and mass Grashof numbers, Brownian motion parameter, thermal parameter, Prandtl number, Eckert number, Schmidt parameter, and Soret parameter are calculated. The impact of these parameters are outlined pictorially. The velocity and temperature fields are boosted with the thermal Grashof number. The Soret and the Schemidt parameters reduces the nanoparticle volume fraction but it heightens the momentum, temperature and concentration. At the cold wall thermal and concentration Grashof numbers reduces the Nusselt values but they increase the Nusselt values at the hot wall. The reversal consequence was attained at the hot plate. The perturbation and Runge-Kutta solutions are equal in the nonappearance of Prandtl number. The (E. Zanchini, Int. J. Heat Mass Transfer 41, 3949 (1998)). results are restored for the regular fluid. The heat transfer rate is high for nanofluid when matched with regular fluid.

scholarly journals Continuous high-resolution midlatitude-belt simulations for July–August 2013 with WRF

2017 ◽  
Vol 10 (5) ◽  
pp. 2031-2055 ◽  
Author(s):  
Thomas Schwitalla ◽  
Hans-Stefan Bauer ◽  
Volker Wulfmeyer ◽  
Kirsten Warrach-Sagi
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Temperature Fields ◽  
Surface Model ◽  
Limited Area ◽  
Data Set ◽  
Latitude Belt ◽  
Simulated Precipitation ◽  
The Impact

Abstract. Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

scholarly journals Large-scale atmospheric forcing and topographic modification of precipitation rates over High Asia – a neural-network-based approach

2015 ◽  
Vol 6 (1) ◽  
pp. 61-81 ◽  
Author(s):  
L. Gerlitz ◽  
O. Conrad ◽  
J. Böhner
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
Large Scale ◽  
Local Scale ◽  
Predictor Variables ◽  
High Mountain ◽  
Target Area ◽  
Monthly Precipitation ◽  
Highly Nonlinear

Abstract. The heterogeneity of precipitation rates in high-mountain regions is not sufficiently captured by state-of-the-art climate reanalysis products due to their limited spatial resolution. Thus there exists a large gap between the available data sets and the demands of climate impact studies. The presented approach aims to generate spatially high resolution precipitation fields for a target area in central Asia, covering the Tibetan Plateau and the adjacent mountain ranges and lowlands. Based on the assumption that observed local-scale precipitation amounts are triggered by varying large-scale atmospheric situations and modified by local-scale topographic characteristics, the statistical downscaling approach estimates local-scale precipitation rates as a function of large-scale atmospheric conditions, derived from the ERA-Interim reanalysis and high-resolution terrain parameters. Since the relationships of the predictor variables with local-scale observations are rather unknown and highly nonlinear, an artificial neural network (ANN) was utilized for the development of adequate transfer functions. Different ANN architectures were evaluated with regard to their predictive performance. The final downscaling model was used for the cellwise estimation of monthly precipitation sums, the number of rainy days and the maximum daily precipitation amount with a spatial resolution of 1 km2. The model was found to sufficiently capture the temporal and spatial variations in precipitation rates in the highly structured target area and allows for a detailed analysis of the precipitation distribution. A concluding sensitivity analysis of the ANN model reveals the effect of the atmospheric and topographic predictor variables on the precipitation estimations in the climatically diverse subregions.

Fog forecasting for Schiphol airport at sub-kilometre scale.  

2021 ◽  
Author(s):  
Gert-Jan Steeneveld ◽  
Roosmarijn Knol
Keyword(s):  
Spatial Resolution ◽  
Numerical Models ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Physical Processes ◽  
Radiation Fog ◽  
Fog Forecasting ◽  
Elevation Data ◽  
The Individual ◽  
The Impact

<p>Fog is a critical weather phenomenon for safety and operations in aviation. Unfortunately, the forecasting of radiation fog remains challenging due to the numerous physical processes that play a role and their complex interactions, in addition to the vertical and horizontal resolution of the numerical models. In this study we evaluate the performance of the Weather Research and Forecasting (WRF) model for a radiation fog event at Schiphol Amsterdam Airport (The Netherlands) and further develop the model towards a 100 m grid spacing. Hence we introduce high resolution land use and land elevation data. In addition we study the role of gravitational droplet settling, advection of TKE, top-down diffusion caused by strong radiative cooling at the fog top. Finally the impact of heat released by the terminal areas on the fog formation is studied. The model outcomes are evaluated against 1-min weather observations near multiple runways at the airport.</p><p>Overall we find the WRF model shows an reasonable timing of the fog onset and is well able to reproduce the visibility and meteorological conditions as observed during the case study. The model appears to be relatively insensitive to the activation of the individual physical processes. An increased spatial resolution to 100 m generally results in a better timing of the fog onset differences up to three hours, though not for all runways. The effect of the refined landuse dominates over the effect of refined elevation data. The modelled fog dissipation systematically occurs 3-4 h hours too early, regardless of physical processes or spatial resolution. Finally, the introduction of heat from terminal buildings delays the fog onset with a maximum of two hours, an overestimated visibility of 100-200 m and a decrease of the LWC with 0.10-0.15 g/kg compared to the reference.</p>

scholarly journals Evaluating the impact of spatial resolution on tropospheric NO<sub>2</sub> column comparisons within urban areas using high-resolution airborne data

2019 ◽  
Vol 12 (11) ◽  
pp. 6091-6111 ◽  
Author(s):  
Laura M. Judd ◽  
Jassim A. Al-Saadi ◽  
Scott J. Janz ◽  
Matthew G. Kowalewski ◽  
R. Bradley Pierce ◽  
...  
Keyword(s):  
High Resolution ◽  
Los Angeles ◽  
Spatial Heterogeneity ◽  
Spatial Resolution ◽  
Urban Areas ◽  
High Temporal Resolution ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
The Impact

Abstract. NASA deployed the GeoTASO airborne UV–visible spectrometer in May–June 2017 to produce high-resolution (approximately 250 m×250 m) gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2=0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward-viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO (Tropospheric Emissions: Monitoring Pollution), TROPOMI (TROPOspheric Monitoring Instrument), and OMI (Ozone Monitoring Instrument), the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale =0.88; TROPOMI scale =0.77; OMI scale =0.57). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×1015 molecules cm−2. Two publicly available OMI tropospheric NO2 retrievals are found to be biased low with respect to these Pandora observations. However, the agreement improves when higher-resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 standard product slope =0.18 and Berkeley High Resolution product slope =0.30). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high-spatial-resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high-temporal-resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results.

scholarly journals Introductory Talk

1988 ◽  
Vol 132 ◽  
pp. xxxiii-xxxiii
Author(s):  
G. Cayrel de Strobel
Keyword(s):  
High Resolution ◽  
The Sun ◽  
In The Beginning ◽  
The Impact

The idea to organize a Conference on high S/N spectroscopy came to me several years ago, in the beginning of the eighties, when the first tracings of Reticon spectra of 8 and 9 magnitude stars were published. I suddendly realized that the quality of those spectra was comparable to those we find in the at lasses of the Sun, Procyon, Arcturus and of a very few other very bright stars. I thought at that epoch, probably at the top of Mauna Kea, that when high-resolution spectroscopists will have collected enough high S/N results, then, time would be ripe to discuss the impact of these results on our Knowledge of Stellar Physics.

A review of selected parameterization schemes of WRF model over Poland area in short-term weather forecast

2020 ◽  
Author(s):  
Sebastian Kendzierski
Keyword(s):  
Spatial Resolution ◽  
Dynamical Downscaling ◽  
Wrf Model ◽  
Grid Cell ◽  
High Sensitivity ◽  
Weather Forecast ◽  
Absolute Error ◽  
Initial Time ◽  
Physical Parameters ◽  
Model Configuration

&lt;p&gt;The aim of the work is to present simulation results of Weather Research and Forecasting (WRF) Model for high-resolution dynamical downscaling done over selected part of Poland. The research carried out a few unique simulations for selected days of the year 2019. For each model run different configuration of physical parameters (parametrization of boundary layer) were used. Additionally, two model runs were tested using the same configuration for physical parameterizations, but with two different spatial resolution. Additionally the sensitivity of the model in terms of spatial resolution was analyzed. Model was configured using two nested domains with 9 km and 3 km grid cell resolutions. All WRF simulations was simulated using GFS gribs with its initial time of 00 UTC. The results were compared with meteorological observations from meteorological stations. Results show high sensitivity of the obtained dynamical downscaling geophysical fields to the selected model configuration. High verifiability of air temperature forecasts was obtained using YSU and MYNN3 BL schemes. Mean Absolute Error (MAE) for temperature prediction has lower values in the summer season. Studies show the most optimal model configuration for BL for Poland area.&lt;/p&gt;

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