The impact of SST on the weather forecast quality in the Bulgarian Antarctic Base area on Livingstone Island

2020 ◽  
Author(s):  
Boriana Chtirkova ◽  
Elisaveta Peneva
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Wrf Model ◽  
Weather Forecast ◽  
Horizontal Resolution ◽  
Initial Time ◽  
Test Cases ◽  
Validation Data ◽  
The Impact ◽  
Forecast Quality

<p>The weather forecast of good quality is essential for the humans living and operating in the Bulgarian Antarctic Base. The numerical weather prediction models in southern high latitude regions still need improvement as the user community is limited, little test cases are documented and validation data are scarce. Not lastly, the challenge of distributing the output results under poor internet conditions has to be addressed.</p><p>The Bulgarian Antarctic Base (BAB) is located on the Livingstone Island coast at 62⁰S and 60⁰W. The influence of the Southern ocean is significant, thus important to be correctly taken into account in the numerical forecast. The modeling system is based on the WRF model, configured in three nested domains down to 1 km horizontal resolution, centered in BAB. The main objective of the study is to quantify the Sea Surface Temperature (SST) impact and to recommend the frequency and way to perform measurements of the SST near the base. The focus is on prediction of right initial time and period of “bad” weather events like storms, frontal zones, and severe winds. Several test cases are considered with available measurements of temperature, pressure and wind speed in BAB during the summer season in 2017. The numerical 3 days forecast is performed and the model skill to capture the basic meteorological events in this period is discussed. Sensitivity experiments to SST values in the nearby marine area are concluded and the SST influence on the model forecast quality is analyzed.</p>

scholarly journals Progress towards an improved parameterisation of small-scale orographic impacts on the atmospheric boundary layer

2021 ◽  
Author(s):  
Julian Quimbayo-Duarte ◽  
Juerg Schmidli
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Vertical Flux ◽  
Initial Time ◽  
Small Scale ◽  
Mean Flow ◽  
Horizontal Momentum ◽  
The Impact

<p>An accurate representation of the momentum budget in numerical models is essential in the quest for reliable weather forecasting, from large scales (climate models) to small scales (numerical weather prediction models, NWP). It is well known that orographic waves play an important role in large-scale circulation. The vertical propagation of such waves is associated with a vertical flux of horizontal momentum, which may be transferred to the mean flow by wave-mean flow interaction and wave-breaking (Sandu et al., 2019). The orography scales inducing such phenomena are often smaller than the model resolution, even for NWP models, leading to the need for parameterisation schemes for orographic drag. Yet, such parameterization in current models is fairly limited (Vosper et al., 2020). The present work aims to contribute to an improved understanding and parameterization of the impact of small-scale orography on the lower atmosphere with a focus on the stable atmospheric boundary layer.</p><p>As a first step, an idealized set of experiments has been designed to explore the capabilities of the Icosahedral Nonhydrostatic model in its large eddy simulation mode (ICON-LES, Dipankar et al., 2015) to represent turbulence processes in the stably-stratified atmosphere. Initial experiments testing the model performance over flat terrain (GABLS experiment, Beare et al., 2006), orographic wave generation (shallow bell-shaped topography, Xue et al., 2000) and moderate complex terrain (U-shaped valley, Burns and Chemel 2014) have been conducted. The results demonstrate that ICON-LES adequately represents the boundary layer processes for the investigated cases in comparison to the literature.</p><p>In a second step, an idealized set of experiments of atmospheric flow over idealized sinusoidal and multiscale terrain has been designed to study the impact of the orographically-induced gravity waves on the total surface drag and the vertical flux of horizontal momentum. The influence of different atmospheric conditions is assessed by varying the background wind speed and the temperature stratification at the initial time.</p>

The impact of vertical resolution on tropical cyclone simulation

2020 ◽  
Author(s):  
Wei Huang ◽  
Mengjuan Liu ◽  
Xu Zhang ◽  
Jian-wen Bao
Keyword(s):  
Tropical Cyclone ◽  
Prediction Models ◽  
Weather Prediction ◽  
Vertical Mixing ◽  
Forecast Model ◽  
Horizontal Resolution ◽  
Model Solution ◽  
Vertical Resolution ◽  
Solution Convergence ◽  
The Impact

<p>It is well known that horizontal resolution has a great deal of impact on tropical cyclone simulations using numerical weather prediction models.  It is relatively less discussed in the literature how vertical resolution affects the solution convergence of tropical cyclone simulations.  In this study, the resolved kinetic energy spectrum, the Richardson number probability density function and resolved flow features are used as metrics to examine the behavior of solution convergence in tropical cyclone simulations using the Weather and Forecast Model (WRF).  It is found that for convective-scale simulations of a real tropical cyclone case with 3-km horizontal resolution, the model solution does not converge until a vertically stretched vertical resolution approaches 200 layers or more.  The results from this study confirm the results from a few previous studies that the subgrid turbulent mixing, particularly, the vertical mixing, plays a significant role in the behavior of model solution convergence with respect to vertical resolution.  They also provide a basis for the vertical grid configuration selection for the operational tropical cyclone model of Shanghai Meteorological Service.</p>

scholarly journals Experiments of Hurricane Initialization with Airborne Doppler Radar Data for the Advanced Research Hurricane WRF (AHW) Model

2009 ◽  
Vol 137 (9) ◽  
pp. 2758-2777 ◽  
Author(s):  
Qingnong Xiao ◽  
Xiaoyan Zhang ◽  
Christopher Davis ◽  
John Tuttle ◽  
Greg Holland ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Prediction Models ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Initial Time ◽  
Forecast Errors ◽  
Hurricane Wrf ◽  
The Impact ◽  
Airborne Doppler Radar

Abstract Initialization of the hurricane vortex in weather prediction models is vital to intensity forecasts out to at least 48 h. Airborne Doppler radar (ADR) data have sufficiently high horizontal and vertical resolution to resolve the hurricane vortex and its imbedded structures but have not been extensively used in hurricane initialization. Using the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation (3DVAR) system, the ADR data are assimilated to recover the hurricane vortex dynamic and thermodynamic structures at the WRF model initial time. The impact of the ADR data on three hurricanes, Jeanne (2004), Katrina (2005) and Rita (2005), are examined during their rapid intensification and subsequent weakening periods before landfall. With the ADR wind data assimilated, the three-dimensional winds in the hurricane vortex become stronger and the maximum 10-m winds agree better with independent estimates from best-track data than without ADR data assimilation. Through the multivariate incremental structure in WRF 3DVAR analysis, the central sea level pressures (CSLPs) for the three hurricanes are lower in response to the stronger vortex at initialization. The size and inner-core structure of each vortex are adjusted closer to observations of these attributes. Addition of reflectivity data in assimilation produces cloud water and rainwater analyses in the initial vortex. The temperature and moisture are also better represented in the hurricane initialization. Forty-eight-hour forecasts are conducted to evaluate the impact of ADR data using the Advanced Research Hurricane WRF (AHW), a derivative of the Advanced Research WRF (ARW) model. Assimilation of ADR data improves the hurricane-intensity forecasts. Vortex asymmetries, size, and rainbands are also simulated better. Hurricane initialization with ADR data is quite promising toward reducing intensity forecast errors at modest computational expense.

scholarly journals Met Office Unified Model Tropical Cyclone Performance Following Major Changes to the Initialization Scheme and a Model Upgrade

2016 ◽  
Vol 31 (5) ◽  
pp. 1433-1449 ◽  
Author(s):  
Julian T. Heming
Keyword(s):  
Prediction Models ◽  
Positive Impact ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Unified Model ◽  
Track Forecast ◽  
Forecast Errors ◽  
Forecast Bias ◽  
Initialization Scheme ◽  
The Impact

Abstract The Met Office has used various schemes to initialize tropical cyclones (TCs) in its numerical weather prediction models since the 1980s. The scheme introduced in 1994 was particularly successful in reducing track forecast errors in the model. Following modifications in 2007 the scheme was still beneficial, although to a lesser degree than before. In 2012 a new trial was conducted that showed that the scheme now had a detrimental impact on TC track forecasts. As a consequence of this, the scheme was switched off. The Met Office Unified Model (MetUM) underwent a major upgrade in 2014 including a new dynamical core, changes to the model physics, an increase in horizontal resolution, and changes to satellite data usage. An evaluation of the impact of this change on TC forecasts found a positive impact both on track and particularly intensity forecasts. Following implementation of the new model formulation in 2014, a new scheme for initialization of TCs in the MetUM was developed that involved the assimilation of central pressure estimates from TC warning centers. A trial showed that this had a positive impact on both track and intensity predictions from the model. Operational results from the MetUM in 2014 and 2015 showed that the combined impact of the model upgrade and new TC initialization scheme was a dramatic cut in both TC track forecast errors and intensity forecast bias.

Evaluation of Low-Level Winds from WRF Model that Driven by Different Background Field Data with Applications to Wind Energy Forecasting

2012 ◽  
Vol 608-609 ◽  
pp. 692-697 ◽  
Author(s):  
Xiao Lin Liu ◽  
Zhao Ming Yang ◽  
Shuang Long Jing ◽  
Zhi Qiang Wang ◽  
Shi Gong Wang
Keyword(s):  
Wind Power ◽  
Large Scale ◽  
Prediction Models ◽  
Rapid Development ◽  
Weather Prediction ◽  
Wrf Model ◽  
Northwest China ◽  
Low Level ◽  
Background Data ◽  
The Impact

With the large-scale and rapid development of wind power in China, the accuracy of wind power prediction is asked for higher. So how to improve the accuracy of numerical weather prediction models which forecast wind has become an important and critical issue. That the accuracy of numerical prediction models as well as the bias of background data is main cause why generate simulated error. This paper attempted to employ the advanced WRF model to simulate the low-level wind in arid region of northwest China, and then evaluated the impact size that using FNL and GFS background data. The results show that using FNL and GFS data simulated wind is very close. It is found that simulation results driven by the FNL assimilated data are worse sometimes. Consequently, we can conclude that FNL assimilated data as well as GFS forecast data are close and the assimilation of FNL data is still need to improvement in northwest China.

Variational Assimilation of Cloud Liquid/Ice Water Path and Its Impact on NWP

2015 ◽  
Vol 54 (8) ◽  
pp. 1809-1825 ◽  
Author(s):  
Yaodeng Chen ◽  
Hongli Wang ◽  
Jinzhong Min ◽  
Xiang-Yu Huang ◽  
Patrick Minnis ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Liquid Water ◽  
Weather Prediction ◽  
Wrf Model ◽  
Liquid Water Path ◽  
Cloud Liquid Water ◽  
Water Path ◽  
Ice Water Path ◽  
Ice Water ◽  
The Impact

AbstractAnalysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this research, the variational data assimilation (DA) system for the Weather Research and Forecasting (WRF) Model (WRFDA) is further developed to assimilate satellite cloud products that will produce the cloud liquid water and ice water analysis. Observation operators for the cloud liquid water path and cloud ice water path are developed and incorporated into the WRFDA system. The updated system is tested by assimilating cloud liquid water path and cloud ice water path observations from Global Geostationary Gridded Cloud Products at NASA. To assess the impact of cloud liquid/ice water path data assimilation on short-term regional numerical weather prediction (NWP), 3-hourly cycling data assimilation and forecast experiments with and without the use of the cloud liquid/ice water paths are conducted. It is shown that assimilating cloud liquid/ice water paths increases the accuracy of temperature, humidity, and wind analyses at model levels between 300 and 150 hPa after 5 cycles (15 h). It is also shown that assimilating cloud liquid/ice water paths significantly reduces forecast errors in temperature and wind at model levels between 300 and 150 hPa. The precipitation forecast skills are improved as well. One reason that leads to the improved analysis and forecast is that the 3-hourly rapid update cycle carries over the impact of cloud information from the previous cycles spun up by the WRF Model.

scholarly journals Toward a Weather-Based Forecasting System for Fire Blight and Downy Mildew

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 484 ◽  
Author(s):  
Ana Firanj Sremac ◽  
Branislava Lalić ◽  
Milena Marčić ◽  
Ljiljana Dekić
Keyword(s):  
Downy Mildew ◽  
Fire Blight ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Atmospheric Model ◽  
Plasmopara Viticola ◽  
Forecasting System ◽  
Nwp Model ◽  
The Impact

The aim of this research is to present a weather-based forecasting system for apple fire blight (Erwinia amylovora) and downy mildew of grapevine (Plasmopara viticola) under Serbian agroecological conditions and test its efficacy. The weather-based forecasting system contains Numerical Weather Prediction (NWP) model outputs and a disease occurrence model. The weather forecast used is a product of the high-resolution forecast (HRES) atmospheric model by the European Centre for Medium-Range Weather Forecasts (ECMWF). For disease modelling, we selected a biometeorological system for messages on the occurrence of diseases in fruits and vines (BAHUS) because it contains both diseases with well-known and tested algorithms. Several comparisons were made: (1) forecasted variables for the fifth day are compared against measurements from the agrometeorological network at seven locations for three months (March, April, and May) in the period 2012–2018 to determine forecast efficacy; (2) BAHUS runs driven with observed and forecast meteorology were compared to test the impact of forecasted meteorological data; and (3) BAHUS runs were compared with field disease observations to estimate system efficacy in plant disease forecasts. The BAHUS runs with forecasted and observed meteorology were in good agreement. The results obtained encourage further development, with the goal of fully utilizing this weather-based forecasting system.

scholarly journals A Case Study of Observed and Modeled Barrier Flow in the Denmark Strait in May 2015

2017 ◽  
Vol 145 (6) ◽  
pp. 2385-2404 ◽  
Author(s):  
Alice K. DuVivier ◽  
John J. Cassano ◽  
Steven Greco ◽  
G. David Emmitt
Keyword(s):  
Wrf Model ◽  
Horizontal Resolution ◽  
Surface Energy Budget ◽  
Vertical Resolution ◽  
Structure Comparison ◽  
Denmark Strait ◽  
Pbl Scheme ◽  
Barrier Jets ◽  
The Impact ◽  
Jet Structure

Abstract Mesoscale barrier jets in the Denmark Strait are common in winter months and have the capability to influence open ocean convection. This paper presents the first detailed observational study of a summertime (21 May 2015) barrier wind event in the Denmark Strait using dropsondes and observations from an airborne Doppler wind lidar (DWL). The DWL profiles agree well with dropsonde observations and show a vertically narrow (~250–400 m) barrier jet of 23–28 m s−1 near the Greenland coast that broadens (~300–1000 m) and strengthens farther off coast. In addition, otherwise identical regional high-resolution Weather Research and Forecasting (WRF) Model simulations of the event are analyzed at four horizontal grid spacings (5, 10, 25, and 50 km), two vertical resolutions (40 and 60 levels), and two planetary boundary layer (PBL) parameterizations [Mellor–Yamada–Nakanishi–Niino, version 2.5 (MYNN2.5) and University of Washington (UW)] to determine what model configurations best simulate the observed jet structure. Comparison of the WRF simulations with wind observations from satellites, dropsondes, and the airborne DWL scans indicate that the combination of both high horizontal resolution (5 km) and vertical resolution (60 levels) best captures observed barrier jet structure and speeds as well as the observed cloud field, including some convective clouds. Both WRF PBL schemes produced reasonable barrier jets with the UW scheme slightly outperforming the MYNN2.5 scheme. However, further investigation at high horizontal and vertical resolution is needed to determine the impact of the WRF PBL scheme on surface energy budget terms, particularly in the high-latitude maritime environment around Greenland.

scholarly journals Verification of Forecast Weather Surface Variables over Vietnam Using the National Numerical Weather Prediction System

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Tien Du Duc ◽  
Lars Robert Hole ◽  
Duc Tran Anh ◽  
Cuong Hoang Duc ◽  
Thuy Nguyen Ba
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Model Performance ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Prediction System ◽  
Regional Models ◽  
Global Spectral Model ◽  
Numerical Weather ◽  
The Us

The national numerical weather prediction system of Vietnam is presented and evaluated. The system is based on three main models, namely, the Japanese Global Spectral Model, the US Global Forecast System, and the US Weather Research and Forecasting (WRF) model. The global forecast products have been received at 0.25- and 0.5-degree horizontal resolution, respectively, and the WRF model has been run locally with 16 km horizontal resolution at the National Center for Hydro-Meteorological Forecasting using lateral conditions from GSM and GFS. The model performance is evaluated by comparing model output against observations of precipitation, wind speed, and temperature at 168 weather stations, with daily data from 2010 to 2014. In general, the global models provide more accurate forecasts than the regional models, probably due to the low horizontal resolution in the regional model. Also, the model performance is poorer for stations with altitudes greater than 500 meters above sea level (masl). For tropical cyclone performance validations, the maximum wind surface forecast from global and regional models is also verified against the best track of Joint Typhoon Warning Center. Finally, the model forecast skill during a recent extreme rain event in northeast Vietnam is evaluated.

scholarly journals QuikSCAT Impacts on Coastal Forecasts and Warnings: Operational Utility of Satellite Ocean Surface Vector Wind Data

2008 ◽  
Vol 23 (5) ◽  
pp. 878-890 ◽  
Author(s):  
Ralph F. Milliff ◽  
Peter A. Stamus
Keyword(s):  
Survey Design ◽  
Weather Prediction ◽  
Winter Season ◽  
Late Summer ◽  
Weather Forecast ◽  
Ocean Surface ◽  
Site Visit ◽  
Island States ◽  
The Impact ◽  
Vector Wind

Abstract This study reports on the operational utility of ocean surface vector wind (SVW) data from Quick Scatterometer (QuikSCAT) observations in the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) Weather Forecast Offices (WFOs) covering the coastal United States, including island states and territories. Thirty-three U.S. coastal WFOs were surveyed, and 16 WFO site visits were conducted, from late summer 2005 to the 2005/06 winter season, in order to quantify the impact of QuikSCAT SVW data on forecasts and warnings, with a particular focus on operations affecting marine users. Details of the survey design and site visit strategies are described. Survey results are quantified and site visit impressions are discussed. Key findings include (i) QuikSCAT data supplement primary datasets and numerical weather prediction fields, in the manual production of local public (weather) and marine forecasts and warnings; (ii) operational utility of satellite SVW data would be enhanced by SVW retrievals of finer temporal resolution, closer to the coasts; and (iii) rain flags in the SVW data have little impact on utility for WFO operations.

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