scholarly journals An Intercomparison of GCM and RCM Dynamical Downscaling for Characterizing the Hydroclimatology of California and Nevada

2018 ◽  
Vol 19 (9) ◽  
pp. 1485-1506 ◽  
Author(s):  
Zexuan Xu ◽  
Alan M. Rhoades ◽  
Hans Johansen ◽  
Paul A. Ullrich ◽  
William D. Collins
Keyword(s):  
Surface Temperature ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Dynamical Downscaling ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Total Precipitation ◽  
Microphysics Scheme ◽  
Reanalysis Dataset ◽  
Simulated Surface

Abstract Dynamical downscaling is a widely used technique to properly capture regional surface heterogeneities that shape the local hydroclimatology. However, in the context of dynamical downscaling, the impacts on simulation fidelity have not been comprehensively evaluated across many user-specified factors, including the refinements of model horizontal resolution, large-scale forcing datasets, and dynamical cores. Two global-to-regional downscaling methods are used to assess these: specifically, the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research and Forecasting (WRF) Model with horizontal resolutions of 28, 14, and 7 km. The modeling strategies are assessed by comparing the VR-CESM and WRF simulations with consistent physical parameterizations and grid domains. Two groups of WRF Models are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM7 results (WRF_VRCESM) to evaluate the effects of large-scale forcing datasets. The simulated hydroclimatologies are compared with reference datasets for key properties including total precipitation, snow cover, snow water equivalent (SWE), and surface temperature. The large-scale forcing datasets are critical to the WRF simulations of total precipitation but not surface temperature, controlled by the wind field and atmospheric moisture transport at the ocean boundary. No significant benefit is found in the regional average simulated hydroclimatology by increasing horizontal resolution refinement from 28 to 7 km, probably due to the systematic biases from the diagnostic treatment of rainfall and snowfall in the microphysics scheme. The choice of dynamical core has little impact on total precipitation but significantly determines simulated surface temperature, which is affected by the snow-albedo feedback in winter and soil moisture estimations in summer.

scholarly journals Comparison of Analysis and Spectral Nudging Techniques for Dynamical Downscaling with the WRF Model over China

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Yuanyuan Ma ◽  
Yi Yang ◽  
Xiaoping Mai ◽  
Chongjian Qiu ◽  
Xiao Long ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Spectral Nudging ◽  
Environmental Prediction ◽  
Meteorological Elements

To overcome the problem that the horizontal resolution of global climate models may be too low to resolve features which are important at the regional or local scales, dynamical downscaling has been extensively used. However, dynamical downscaling results generally drift away from large-scale driving fields. The nudging technique can be used to balance the performance of dynamical downscaling at large and small scales, but the performances of the two nudging techniques (analysis nudging and spectral nudging) are debated. Moreover, dynamical downscaling is now performed at the convection-permitting scale to reduce the parameterization uncertainty and obtain the finer resolution. To compare the performances of the two nudging techniques in this study, three sensitivity experiments (with no nudging, analysis nudging, and spectral nudging) covering a period of two months with a grid spacing of 6 km over continental China are conducted to downscale the 1-degree National Centers for Environmental Prediction (NCEP) dataset with the Weather Research and Forecasting (WRF) model. Compared with observations, the results show that both of the nudging experiments decrease the bias of conventional meteorological elements near the surface and at different heights during the process of dynamical downscaling. However, spectral nudging outperforms analysis nudging for predicting precipitation, and analysis nudging outperforms spectral nudging for the simulation of air humidity and wind speed.

scholarly journals Simulation of Severe Thunderstorms in Conjugation of Westerly and Easterly on 31 March 2019 in Bangladesh

2022 ◽  
Vol 12 (3) ◽  
pp. 29-43
Author(s):  
Samarendra Karmakar ◽  
Mohan Kumar Das ◽  
Md Quamrul Hassam ◽  
Md Abdul Mannan
Keyword(s):  
South Asian ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Atmospheric Conditions ◽  
Microphysics Scheme ◽  
Severe Thunderstorms ◽  
Synoptic Conditions ◽  
Pbl Scheme ◽  
Single Moment

The diagnostic and prognostic studies of thunderstorms/squalls are very important to save live and loss of properties. The present study aims at diagnose the different tropospheric parameters, instability and synoptic conditions associated the severe thunderstorms with squalls, which occurred at different places in Bangladesh on 31 March 2019. For prognostic purposes, the severe thunderstorms occurred on 31 March 2019 have been numerically simulated. In this regard, the Weather Research and Forecasting (WRF) model is used to predict different atmospheric conditions associated with the severe storms. The study domain is selected for 9 km horizontal resolution, which almost covers the south Asian region. Numerical experiments have been conducted with the combination of WRF single-moment 6 class (WSM6) microphysics scheme with Yonsei University (YSU) PBL scheme in simulation of the squall events. Model simulated results are compared with the available observations. The observed values of CAPE at Kolkata both at 0000 and 1200 UTC were 2680.4 and 3039.9 J kg-1 respectively on 31 March 2019 and are found to be comparable with the simulated values. The area averaged actual rainfall for 24 hrs is found is 22.4 mm, which complies with the simulated rainfall of 20-25 mm for 24 hrs. Journal of Engineering Science 12(3), 2021, 29-43

The diurnal cycle can trigger convective self-aggregation 

2021 ◽  
Author(s):  
Gorm Gruner Jensen ◽  
Romain Fiévet ◽  
Jan O. Haerter
Keyword(s):  
Surface Temperature ◽  
Diurnal Cycle ◽  
Large Scale ◽  
Horizontal Resolution ◽  
Cold Pool ◽  
Atmospheric Sciences ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Spatio Temporal ◽  
Self Aggregation

<p>Convective self-aggregation (CSA) is an established modelling paradigm for large-scale thunderstorm clusters, as they form in mesoscale convective systems, the Madden-JulianOscillation or tropical cyclo-genesis [1]. The onset of CSA is characterized by the spontaneous formation of persistently dry patches with suppressed deep convective rainfall. Recently another type of spatio-temporal pattern formation was observed in simulations where the diurnal cycle was mimicked by a sinusoidally varying surface temperature [2]. This diurnal aggregation (DA) is characterized by clusters of intense rain that correlate negatively from one day to the next. </p><p>Here we demonstrate that the diurnal cycle can also act as a trigger of persistently dry patches resembling the early stages of CSA. When the surface temperature is held constant, CSA has been shown to occur within simulations of coarse horizontal model resolution, but not when the resolution was increased [3]. We show that, when a temporally periodic surface temperature forcing is imposed, persistently convection free patches occur even faster when the spatial resolution is increased. The failure to achieve CSA at high horizontal resolution has so far been attributed to the more pronounced cold pool effects at such resolution. In our simulations these cold pools in fact play a key role in promoting CSA. Our results have implications for the origin of persistent convective organization over continents and the sea — and point a path towards achieving such clustering under realistic conditions.</p><p><br>[1]  Christopher S Bretherton, Peter N Blossey, and Marat Khairoutdinov.  An energy-balance analysisof deep convective self-aggregation above uniform SST.Journal of the Atmospheric Sciences, 62(12):4273–4292, 2005.<br>[2]  J. O. Haerter, B. Meyer, and S. B. Nissen.  Diurnal self-aggregation.npj Climate and AtmosphericScience, 3:30, 2020.<br>[3]  Caroline  Muller  and  Sandrine  Bony.   What  favors  convective  aggregation  and  why?GeophysicalResearch Letters, 42(13):5626–5634, 2015.  doi:  https://doi.org/10.1002/2015GL064260.</p>

scholarly journals Simulation of Intensity, Track and Landfall of Tropical Cyclonic Storm Roanu over the Bay of Bengal Using WRF-ARW Model

2021 ◽  
Vol 10 (1) ◽  
pp. 33-45
Author(s):  
Ariful Alam ◽  
Shammy Ahmed ◽  
Sharmin Rahman ◽  
Umme Habiba ◽  
Muhammad Abul Kalam Mallik ◽  
...  
Keyword(s):  
Bay Of Bengal ◽  
Wrf Model ◽  
Short Wave ◽  
Horizontal Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Microphysics Scheme ◽  
Cyclonic Storm ◽  
Position Errors ◽  
Hourly Data

Almost every year, tropical cyclone forms over the Bay of Bengal in pre-monsoon and post-monsoon which strikes Bangladesh coast and the east coast of India. As the full thermodynamic features of a cyclone is not solved yet, an attempt has been made to simulate the track and landfall of cyclonic disturbances over the Bay of Bengal by using Weather Research and Forecasting (WRF) model. The WRF model (version 3.8) was run in a single domain of 20 km horizontal resolution. The model was run using WRF Single-Moment 3- class microphysics scheme, Kain- Fritsch (new Eta) cumulus physics scheme, Yonsei University planetary boundary layer scheme, revised MM5 surface layer physics scheme, Rapid Radiative Transfer Model (RRTM) for long-wave and Dudhia scheme for short-wave scheme. The model was run for 24-h, 48-h, 72-h and 96-h using the National Centre for Environmental Prediction (NCEP) high-resolution Global Final (FNL) Analysis 6-hourly data using initial and lateral boundary conditions. The model simulated landfall position errors are found 53 km, 129 km, 119km and 23 km and time errors are found 02 E, 06 D, 02 E and 00 for 96-h, 72-h, 48-h and 24-h model run respectively (E indicates Earlier and D indicates Delay). The minimum time and position error is found in 24-hrs simulation. The spatial distribution is captured by the model is almost appropriate but the computational station rainfall is found less than that of observed rainfall. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 10(1), 2021, P 33-45

scholarly journals Impact of Large-Scale Afforestation on Surface Temperature: A Case Study in the Kubuqi Desert, Inner Mongolia Based on the WRF Model

Forests ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 368
Author(s):  
Liming Wang ◽  
Xuhui Lee ◽  
Duole Feng ◽  
Congsheng Fu ◽  
Zhongwang Wei ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Inner Mongolia ◽  
Large Scale ◽  
Wrf Model ◽  
Bowen Ratio ◽  
Bare Soil ◽  
Surface Temperature Change ◽  
Mean Values ◽  
Temperature Changes ◽  
Atmospheric Feedback

Afforestation activities in the Kubuqi Desert, Inner Mongolia, China, have substantially increased tree and shrub coverage in this region. In this study, the response of the surface temperature to afforestation is simulated with the Weather Research and Forecasting model. The surface temperature changes are decomposed into contributions from the intrinsic surface biophysical effect and atmospheric feedback, using the theory of intrinsic biophysical mechanism. The effect of afforestation on the surface temperature is 1.34 K, −0.48 K, 2.09 K and 0.22 K for the summer daytime, the summer nighttime, the winter daytime and the winter nighttime, respectively, for the grid cells that have experienced conversion from bare soil to shrub. The corresponding domain mean values are 0.15 K, −0.2 K, 0.67 K, and 0.06 K. The seasonal variation of surface temperature change is mainly caused by changes in roughness and Bowen ratio. In the daytime, the surface temperature changes are dominated by the biophysical effect, with albedo change being the main biophysical factor. In the nighttime, the biophysical effect (mainly associated with roughness change) and the atmospheric feedback (mainly associated with change in the background air temperature) contribute similar amounts to the surface temperature changes. We conclude that the atmospheric feedback can amplify the influence of the surface biophysical effect, especially in the nighttime.

The different mechanisms of extreme snowfall in the eastern and southern Tibetan Plateau.

2021 ◽  
Author(s):  
Nan Yao ◽  
Lian Liu ◽  
Yaoming Ma
Keyword(s):  
Water Vapor ◽  
Tibetan Plateau ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Wrf Model ◽  
Eastern Region ◽  
The Tibetan Plateau ◽  
Local Circulation ◽  
China Meteorological Administration ◽  
Dynamic Conditions

<p>Snowfall is a key component of the hydrological system of the Tibetan Plateau (TP), and it is also a very sensitive factor to climate change. To understand the mechanism of extreme snowfall in different regions of the TP, we used the 50-year snow depth data from the China Meteorological Administration (CMA) ground observations and the ERA5 reanalysis datasets of European Centre for Medium-Range Weather Forecasts (ECMWF). Results show the threshold of extreme snow in the southern TP is four times greater than that in the eastern region. Sixteen numerical experiments using the weather research and forecasting (WRF) model were conducted to quantify the contribution of water vapor and dynamic conditions to snowfall events. Here are the preliminary results: (1) For the snowfall event caused by local circulation in the eastern TP, the contribution of dynamic conditions is greater than that of moisture conditions. An increase of 10% in the wind field (water vapor) will enhance the snow water equivalent (SWE) by more than 25% (10%). (2) For large-scale circulation, q has a greater effect. But the overall increase in snowfall is smaller than the local circulation. (3) The severe snowfall frequently takes place in the southern TP, where water vapor channel and topographic uplift are significant factors to snowfall. we think the southern simulation will produce interesting results. Our results will provide scientific reference in improving the snowstorm forecasting and disaster prevention and mitigation.</p>

Secondary Ice Production in Antarctic Clouds: a process neglected in large-scale models

2020 ◽  
Author(s):  
Georgia Sotiropoulou ◽  
Etienne Vignon ◽  
Gillian Young ◽  
Thomas Lachlan-Cope ◽  
Alexis Berne ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Weather Prediction ◽  
Wrf Model ◽  
Weddell Sea ◽  
Microphysics Scheme ◽  
Ice Multiplication ◽  
Ice Production ◽  
Low Sensitivity ◽  
The Impact

<p>In-situ measurements of Antarctic clouds frequently show that ice crystal number concentrations  are much higher than the available ice-nucleating particles, suggesting that Secondary Ice Production (SIP) may be active. Here we investigate the impact of two SIP mechanisms, Hallett-Mossop (H-M)and collisional break-up (BR), on a case from the Microphysics of Antarctic Clouds (MAC) campaign in Weddell Sea using the Weather and Research Forecasting (WRF) model. H-M is already included in the default version of the Morrison microphysics scheme in WRF; for BR we implement different parameterizations and compare their performance. H-M alone is not effective enough to reproduce the observed concentrations. In contrast, BR can result in realistic ice multiplication, independently of whether H-M is active or not. In particular, the Phillips parameterization results in very good agreement with observations, but its performance depends on the prescribed rimed fraction of the colliding ice particles. Finally, our results show low sensitivity to primary ice nucleation, as long as there are enough primary ice crystals to initiate ice-ice collisions. Our findings suggest that BR is a potentially important SIP mechanism in the pristine Antarctic atmosphere that is currently not represented in weather-prediction and climate models.</p>

Analyzing the atmospheric scales involved in sea-breeze formation and frontal characteristics

2020 ◽  
Author(s):  
Jon Ander Arrillaga ◽  
Pedro Jiménez ◽  
Jordi Vilà-Guerau de Arellano ◽  
Maria Antonia Jiménez ◽  
Carlos Román-Cascón ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Large Scale ◽  
Surface Wind ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Sea Breeze ◽  
Stable Stratification ◽  
Horizontal Resolution ◽  
Sea Temperature ◽  
The Moment

<p>We investigate sea-breeze (SB) frontal passages troughout a 10-year period. Spanning the whole period, numerical simulations from the Weather Research and Forecasting (WRF) model are compared with a comprehensive observational database from the Cabauw Experimental Site (Ruisdael Project). On the one hand, a fine horizontal resolution of 2 km is employed in the numerical simulations, and the observational vertical levels within the first 200 m above the surface are replicated. On the other hand, an algorithm based on objective and strict filters is applied to both observations and simulations to select the SB events. This methodology allows to investigate the atmospheric scales influencing the SB formation and their interaction with local turbulence in a robust and objective way.</p><p>By carrying out a filter-by-filter comparison, we find that the simulated large-scale conditions show a good rate of coincidence with the observations (69%). Small biases in the large scale wind direction, however, induce important deviations in the surface-wind evolution. Regarding the mesoscale forcings, the land-sea temperature gradient is overestimated in average up to 4 K, producing stronger SB fronts in WRF. The analysis of the SB frontal characteristics and impacts is carried out by classifying the events into three boundary-layer regimes (convective, transition and stable) based on the value of the sensible-heat flux at the moment of the SB onset. The stronger SB in the model leads to enhanced turbulence particularly in the convective and transition regimes: the friction velocity, for instance, is overstated by around 50% at the SB onset. In addition, the arrival of the SB front enhances the stable stratification and gives rise to faster afternoon and evening transitions compared with situations solely driven by local atmospheric turbulence.</p><p>The obtained results can be considered a benchmark of the aspects to be improved in order to produce finer SB forecasts and more adequate representations of the associated physical processes, particularly during the afternoon and evening transition of the ABL.</p>

scholarly journals Differences between downscaling with spectral and grid nudging using WRF

2012 ◽  
Vol 12 (8) ◽  
pp. 3601-3610 ◽  
Author(s):  
P. Liu ◽  
A. P. Tsimpidi ◽  
Y. Hu ◽  
B. Stone ◽  
A. G. Russell ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Regional Climate ◽  
Wrf Model ◽  
Global Climate Models ◽  
Small Scale ◽  
Data Set ◽  
Spectral Nudging

Abstract. Dynamical downscaling has been extensively used to study regional climate forced by large-scale global climate models. During the downscaling process, however, the simulation of regional climate models (RCMs) tends to drift away from the driving fields. Developing a solution that addresses this issue, by retaining the large scale features (from the large-scale fields) and the small-scale features (from the RCMs) has led to the development of "nudging" techniques. Here, we examine the performance of two nudging techniques, grid and spectral nudging, in the downscaling of NCEP/NCAR data with the Weather Research and Forecasting (WRF) Model. The simulations are compared against the results with North America Regional Reanalysis (NARR) data set at different scales of interest using the concept of similarity. We show that with the appropriate choice of wave numbers, spectral nudging outperforms grid nudging in the capacity of balancing the performance of simulation at the large and small scales.

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