scholarly journals Combinational Optimization of the WRF Physical Parameterization Schemes to Improve Numerical Sea Breeze Prediction Using Micro-Genetic Algorithm

2021 ◽  
Vol 11 (23) ◽  
pp. 11221
Author(s):  
Ji Won Yoon ◽  
Sujeong Lim ◽  
Seon Ki Park
Keyword(s):  
Genetic Algorithm ◽  
Wind Speed ◽  
Land Surface ◽  
Wrf Model ◽  
Longwave Radiation ◽  
Sea Breeze ◽  
Meteorological Variables ◽  
Parameterization Schemes ◽  
Micro Genetic Algorithm ◽  
Physical Parameterization

This study aims to improve the performance of the Weather Research and Forecasting (WRF) model in the sea breeze circulation using the micro-Genetic Algorithm (micro-GA). We found the optimal combination of four physical parameterization schemes related to the sea breeze system, including planetary boundary layer (PBL), land surface, shortwave radiation, and longwave radiation, in the WRF model coupled with the micro-GA (WRF-μGA system). The optimization was performed with respect to surface meteorological variables (2 m temperature, 2 m relative humidity, 10 m wind speed and direction) and a vertical wind profile (wind speed and direction), simultaneously for three sea breeze cases over the northeastern coast of South Korea. The optimized set of parameterization schemes out of the WRF-μGA system includes the Mellor–Yamada–Nakanishi–Niino level-2.5 (MYNN2) for PBL, the Noah land surface model with multiple parameterization options (Noah-MP) for land surface, and the Rapid Radiative Transfer Model for GCMs (RRTMG) for both shortwave and longwave radiation. The optimized set compared with the various other sets of parameterization schemes for the sea breeze circulations showed up to 29 % for the improvement ratio in terms of the normalized RMSE considering all meteorological variables.

Development of stochastically perturbed parameterization scheme for the Noah Land Surface Model with the optimized random forcing parameters using the micro-genetic algorithm

2021 ◽  
Author(s):  
Sujeong Lim ◽  
Claudio Cassardo ◽  
Seon Ki Park
Keyword(s):  
Genetic Algorithm ◽  
Land Surface ◽  
Weather Forecasting ◽  
Land Surface Model ◽  
Surface Model ◽  
Ensemble Spread ◽  
Near Surface ◽  
Random Forcing ◽  
Micro Genetic Algorithm ◽  
Stochastically Perturbed

<p>The ensemble data assimilation system is beneficial to represent the initial uncertainties and flow-dependent background error covariance (BEC). In particular, the inevitable model uncertainties can be expressed by ensemble spread, that is the standard deviation of ensemble BEC. However, the ensemble spread generally suffers from under-estimated problems. To alleviate this problem, recent studies employed stochastic perturbation schemes to increases the ensemble spreads by adding the random forcing in the model tendencies (i.e., physical or dynamical tendencies) or parameterization schemes (i.e., PBL, convective scheme, etc.). In this study, we focus on the near-surface uncertainties which are affected by the interactions between the land and atmosphere process. The land surface model (LSM) provides various fluxes as the lower boundary condition to the atmosphere, influencing the accuracy of hourly-to-seasonal scale weather forecasting, but the surface uncertainties were not much addressed yet. In this study, we developed the stochastically perturbed parameterization (SPP) scheme for the Noah LSM. The Weather Research and Forecasting (WRF) ensemble system is used for regional weather forecasting over East Asia, especially over the Korean Peninsula. As a testbed experiment with the newly-developed Noah LSM-SPP system, we first perturbed the soil temperature — a crucial variable for the near-surface forecasts by affecting sensible heat fluxes, land surface skin temperature and surface air temperature, and hence lower-tropospheric temperature. Here, the random forcing used in perturbation is made by the tuning parameters for amplitude, length scale, and time scales: they are commonly determined empirically by trial and error. In order to find optimal tuning parameter values, we applied a global optimization algorithm — the micro-genetic algorithm (micro-GA) — to achieve the smallest root-mean-squared errors. Our results indicate that optimization of the random forcing parameters contributes to an increase in the ensemble spread and a decrease in the ensemble mean errors in the near-surface and lower-troposphere uncertainties. Further experiments will be conducted by including soil moisture in the testbed.</p>

scholarly journals Optimization of Noah and Noah_MP WRF Land Surface Schemes in Snow-Melting Conditions over Complex Terrain

2017 ◽  
Vol 145 (12) ◽  
pp. 4727-4745 ◽  
Author(s):  
Elena Tomasi ◽  
Lorenzo Giovannini ◽  
Dino Zardi ◽  
Massimiliano de Franceschi
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Winter Season ◽  
Wrf Model ◽  
Longwave Radiation ◽  
Shortwave Radiation ◽  
Land Use Classification ◽  
Near Surface ◽  
Thermal Inversion ◽  
Alpine Valley

The paper presents the results of high-resolution simulations performed with the WRF Model, coupled with two different land surface schemes, Noah and Noah_MP, with the aim of accurately reproducing winter season meteorological conditions in a typical Alpine valley. Accordingly, model results are compared against data collected during an intensive field campaign performed in the Adige Valley, in the eastern Italian Alps. In particular, the ability of the model in reproducing the time evolution of 2-m temperature and of incoming and outgoing shortwave and longwave radiation is examined. The validation of model results highlights that, in this context, WRF reproduces rather poorly near-surface temperature over snow-covered terrain, with an evident underestimation, during both daytime and nighttime. Furthermore it fails to capture specific atmospheric processes, such as the temporal evolution of the ground-based thermal inversion. The main cause of these errors lies in the miscalculation of the mean gridcell albedo, resulting in an inaccurate estimate of the reflected solar radiation calculated by both Noah and Noah_MP. Therefore, modifications to the initialization, to the land-use classification, and to both land surface models are performed to improve model results, by intervening in the calculation of the albedo, of the snow cover, and of the surface temperature. Qualitative and quantitative analyses show that, after these changes, a significant improvement in the comparability between model results and observations is achieved. In particular, outgoing shortwave radiation is lowered, 2-m temperature maxima increased accordingly, and ground-based thermal inversions are better captured.

scholarly journals Evaluation of the Simulation of Typhoon Lekima (2019) Based on Different Physical Parameterization Schemes and FY-3D Satellite’s MWHS-2 Data Assimilation

2021 ◽  
Vol 13 (22) ◽  
pp. 4556
Author(s):  
Dongmei Xu ◽  
Xuewei Zhang ◽  
Hong Li ◽  
Haiying Wu ◽  
Feifei Shen ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Wrf Model ◽  
Background Field ◽  
Weather Research And Forecasting ◽  
Initial Field ◽  
Parameterization Schemes ◽  
Microwave Humidity Sounder ◽  
Radiance Data ◽  
Physical Parameterization

In this study, the case of super typhoon Lekima, which landed in Jiangsu and Zhejiang Province on 4 August 2019, is numerically simulated. Based on the Weather Research and Forecasting (WRF) model, the sensitivity experiments are carried out with different combinations of physical parameterization schemes. The results show that microphysical schemes have obvious impacts on the simulation of the typhoon’s track, while the intensity of the simulated typhoon is more sensitive to surface physical schemes. Based on the results of the typhoon’s track and intensity simulation, one parameterization scheme was further selected to provide the background field for the following data assimilation experiments. Using the three-dimensional variational (3DVar) data assimilation method, the Microwave Humidity Sounder-2 (MWHS-2) radiance data onboard the Fengyun-3D satellite (FY-3D) were assimilated for this case. It was found that the assimilation of the FY-3D MWHS-2 radiance data was able to optimize the initial field of the numerical model in terms of the model variables, especially for the humidity. Finally, by the inspection of the typhoon’s track and intensity forecast, it was found that the assimilation of FY-3D MWHS-2 radiance data improved the skill of the prediction for both the typhoon’s track and intensity.

scholarly journals Idealized WRF model sensitivity simulations of sea breeze types and their effects on offshore windfields

2012 ◽  
Vol 12 (6) ◽  
pp. 15837-15881 ◽  
Author(s):  
C. J. Steele ◽  
S. R. Dorling ◽  
R. von Glasow ◽  
J. Bacon
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Wrf Model ◽  
Sea Breeze ◽  
Offshore Wind ◽  
Eastern Coast ◽  
State University ◽  
Sea Breezes ◽  
Gradient Wind

Abstract. The behaviour and characteristics of the marine component of sea breeze cells have received little attention relative to their onshore counterparts. Yet there is a growing interest and dependence on the offshore wind climate from, for example, a wind energy perspective. Using idealized model experiments, we investigate the sea breeze circulation at scales which approximate to those of the Southern North Sea, a region of major ongoing offshore wind farm development. We also contrast the scales and characteristics of the pure and the little known corkscrew and backdoor sea breeze types, where the type is pre-defined by the orientation of the synoptic scale flow relative to the shoreline. We find, crucially, that pure sea breezes, in contrast to corkscrew and backdoor types, can lead to substantial wind speed reductions offshore and that the addition of a second eastern coastline emphasises this effect through generation of offshore "calm zones". The offshore extent of all sea breeze types is found to be sensitive to both the influence of Coriolis acceleration and to the boundary layer scheme selected. These extents range, for example for a pure sea breeze produced in a 2 m s−1 offshore gradient wind, from 10 km to 40 km between the Mellor-Yamada-Nakanishi-Niino and the Yonsei State University schemes, respectively. The corkscrew type restricts the development of a backdoor sea breeze on the eastern coast and is also capable of traversing a 100 km offshore domain even under high gradient wind speed (>15 m s−1) conditions. Realistic variations in sea surface skin temperature during the sea breeze season do not significantly affect the circulation, suggesting that a thermal contrast is only needed as a precondition to the development of the sea breeze. We highlight how sea breeze impacts on circulation need to be considered in order to improve the accuracy of assessments of the offshore wind energy climate.

scholarly journals Sensitivity of Indian summer monsoon simulation to physical parameterization schemes in the WRF model

2017 ◽  
Vol 74 (1) ◽  
pp. 43-66 ◽  
Author(s):  
JV Ratnam ◽  
SK Behera ◽  
R Krishnan ◽  
T Doi ◽  
SB Ratna
Keyword(s):  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Wrf Model ◽  
Parameterization Schemes ◽  
Physical Parameterization

How are the coastal breezes affected by changes in the land surface? Analysis from a case study using WRF

2021 ◽  
Author(s):  
Roberto Mulero-Martinez ◽  
Carlos Román-Cascón ◽  
Marie Lothon ◽  
Fabienne Lohou ◽  
Carlos Yagüe ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface ◽  
Wrf Model ◽  
Sea Breeze ◽  
Sea Breezes ◽  
Temperature Changes ◽  
Precipitation Regimes ◽  
Thermally Driven

<p>Sea breezes are common and recurrent thermally-driven wind circulations formed in coastal areas under conditions of weak synoptic forcing. The different heat capacity between the land and the sea causes the thermal contrast needed for their formation. Therefore, the temperature changes at the surface of both the sea and the land influence the breezes characteristics. In this work, we investigate how sensitive are the sea breezes to changes in land cover and soil moisture, which may have a direct impact on the surface temperature inland. This is done through the design of different sensitivity experiments performed with the Weather Research and Forecasting (WRF) model, where we tested the effect of the land use and soil moisture modification. This was done through the simulation of a typical sea-breeze case study in the coastal area of the southwest of the Iberian Peninsula (Gulf of Cádiz). The differences among the experiments are compared spatially and confronted with observations from different meteorological towers at the coast and inland. A special emphasis is made on the changes observed in the area of the National Park of Doñana. This area is characterised by large shallow marshes with varying seasonal status and extensive rice crops. Thus, contrasting conditions of the surface are typically observed, which also depend on the previous hydrological conditions. Preliminary results highlight the importance of the correct representation of the surface inland to obtain a proper simulation of the sea-breeze system. Besides, new lines of research emerge to analyse the impacts caused by other potential modifications in the surface conditions of the land and the ocean (e.g., global change, urbanization, crop modification, changes in precipitation regimes or sea surface temperature, etc).</p>

Optimization of snow density parameter of Noah Land Surface Model using micro-genetic algorithm for estimating snow depth

2021 ◽  
Author(s):  
Ebony Lee ◽  
Seon Ki Park
Keyword(s):  
Genetic Algorithm ◽  
Land Surface ◽  
Snow Depth ◽  
Fitness Function ◽  
Land Surface Model ◽  
Surface Model ◽  
Density Parameter ◽  
Snow Density ◽  
Noah Land Surface Model ◽  
Micro Genetic Algorithm

<p>The Noah Land Surface Model (Noah LSM) estimates snow depth using snow water equivalent and snow density. The snow density is determined by snow compaction, snowmelt water storing, and density of fresh snowfall. The Noah LSM usually underestimates snow depth compared to the ground observations in Korea, which occurs from the beginning of snowfall. We performed an optimal estimation of parameters related to the density of fresh snowfall, using micro-genetic algorithm (μ-GA) that uses the evolution process concept through natural selection and mutation mechanism. Ground observations from 36 sites of the Korea Meteorological Administration, for the recent 10 years (May 2009 – April 2019), are used for offline forcing of the Noah LSM and evaluating the fitness function in μ-GA. Optimized parameters reduced the density of fresh snowfall, and improved the simulated snow depth. The root-mean-square error of snow depth decreased from 8.1 cm to 7.1 cm.</p>

scholarly journals Influence of a Hailstreak on Boundary Layer Evolution

2005 ◽  
Vol 133 (4) ◽  
pp. 942-960 ◽  
Author(s):  
Zewdu T. Segele ◽  
David J. Stensrud ◽  
Ian C. Ratcliffe ◽  
Geoffrey M. Henebry
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
South Dakota ◽  
Land Surface ◽  
Surface Wind ◽  
Sea Breeze ◽  
Surface Wind Speed ◽  
Vegetation Coverage ◽  
Wind Speeds ◽  
Severe Thunderstorms

Severe thunderstorms developed on 20 June 1997 and produced heavy precipitation, damaging winds, and large hail over two swaths in southeastern South Dakota. Calculations of fractional vegetation coverage (scaled from 0 to 1) based upon composite satellite data indicate that, within the hailstreak region, vegetation coverage decreased from 0.50 to near 0.25 owing to the damaging effects of hail on the growing vegetation. The northern edge of the larger hailstreak was located a few kilometers south of Chamberlain, South Dakota, a National Weather Service surface observation site. Hourly observations from Chamberlain and several nearby surface sites in South Dakota are averaged over 7 days both before and after this hail event. These observations illustrate that the late-afternoon (nighttime) temperatures are 2°C higher (2°C lower) near the hailstreak after the event than before the event. Similarly, daily average dewpoint temperatures after the event are 2.6°C lower near the hailstreak. These changes are consistent with the influences of a recently devegetated zone on changes to the surface energy budget. To explore how these hailstreaks further affected the evolution of the planetary boundary layer in this region, two model simulations are performed using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5). In the control run, climatology is used for the land surface characteristics, and hence the simulation is independent of the hailstreaks. In the hailstreak simulation (HSS), the fractional vegetation coverage and soil moisture in the hailstreak regions are modified to reflect the likely conditions within the hailstreaks. Two different days are simulated: one with low surface wind speeds and one with stronger surface wind speeds. For the low surface wind speed case, the HSS simulation produces a sea-breeze-like circulation in the boundary layer by midmorning. For the stronger surface wind speed case, this sea-breeze-like circulation does not develop in the HSS, but the simulated low-level temperatures are modified over a larger area. These results suggest that to capture and reasonably simulate the evolution of boundary layer structures, there is a need for routine daily updates of land surface information. Hailstreaks also are important to consider in the future as the focus for observational studies on nonclassical mesoscale circulations.

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