The Sydney Australia Wildfires of January 1994 - Meteorological Conditions and High Resolution Numerical Modeling Experiments

1996 ◽  
Vol 6 (3) ◽  
pp. 145 ◽  
Author(s):  
MS Speer ◽  
LM Leslie ◽  
JR Colquhoun ◽  
E Mitchell
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Weather Conditions ◽  
Detailed Examination ◽  
Meteorological Conditions ◽  
Limited Area ◽  
Research Activity ◽  
Southeastern Australia ◽  
South Wales ◽  
Resolution Model

Southeastern Australia is particularly vulnerable to wildfires during the spring and summer months, and the threat of devastation is present most years. In January 1994, the most populous city in Australia, Sydney, was ringed by wildfires, some of which penetrated well into suburban areas and there were many other serious fires in coastal areas of New South Wales (NSW). In recent years much research activity in Australia has focussed on the development of high resolution limited area models, for eventual operational prediction of meteorological conditions associated with high levels of wildfire risk. In this study, the period January 7-8, 1994 was chosen for detailed examination, as it was the most critical period during late December 1993/early January 1994 for the greater Sydney area. Routine forecast guidance from the Australian Bureau of Meteorology's operational numerical weather prediction (NWP) models was very useful in that both the medium and short range models predicted synoptic patterns suggesting extreme fire weather conditions up to several days in advance. However, vital information of a detailed nature was lacking. A new high resolution model was run at the operational resolution of 150 km and the much higher resolutions of 25 km and 5 km. The new model showed statistically significant greater skill in predicting details of wind, relative humidity and temperature patterns both near the surface and above the boundary layer. It also produced skilful predictions of the Forest Fire Danger Index.

scholarly journals Effectiveness of short term air quality emission controls: A high-resolution model study of Beijing during the APEC period

2019 ◽  
Author(s):  
Tabish Umar Ansari ◽  
Oliver Wild ◽  
Jie Li ◽  
Ting Yang ◽  
Weiqi Xu ◽  
...  
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Fine Particulate Matter ◽  
Meteorological Conditions ◽  
Atmospheric Pollutants ◽  
Small Contribution ◽  
Model Study ◽  
Emission Controls ◽  
Resolution Model ◽  
Current Emission

Abstract. We explore the impacts of emission controls on haze events in Beijing in October–November 2014 using high resolution WRF-Chem simulations. The model reproduces surface temperature and relative humidity profiles over the period well and captures the observed variations in key atmospheric pollutants. We highlight the sensitivity of simulated pollutant levels to meteorological variables and model resolution, and in particular to treatment of turbulent mixing in the planetary boundary layer. We note that simulating particle composition in the region remains a challenge, and we overpredict NH4 and NO3 at the expense of SO4. We find that the emission controls implemented for the APEC Summit period made a relatively small contribution to improved air quality (20–26 %), highlighting the important role played by favourable meteorological conditions over this period. We demonstrate that the same controls applied under less favourable meteorological conditions would have been insufficient to reduce pollutant levels to meet the required standards. Continued application of these controls over the 6-week period considered would only have reduced the number of haze days where daily-mean fine particulate matter exceeds 75 μg m−3 from 15 to 13 days. Our study highlights the limitations of current emission controls and the need for more stringent measures over a wider region during meteorologically stagnant weather.

scholarly journals Effects of Increasing Horizontal Resolution in a Convection-Permitting Model on Flood Forecasting: The 2011 Dramatic Events in Liguria, Italy

2015 ◽  
Vol 16 (4) ◽  
pp. 1843-1856 ◽  
Author(s):  
Silvio Davolio ◽  
Francesco Silvestro ◽  
Piero Malguzzi
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Flood Forecasting ◽  
Horizontal Resolution ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Flood Prediction ◽  
Meteorological Model ◽  
The Impact ◽  
Atmospheric Simulations

Abstract Coupling meteorological and hydrological models is a common and standard practice in the field of flood forecasting. In this study, a numerical weather prediction (NWP) chain based on the BOLogna Limited Area Model (BOLAM) and the MOdello LOCale in Hybrid coordinates (MOLOCH) was coupled with the operational hydrological forecasting chain of the Ligurian Hydro-Meteorological Functional Centre to simulate two major floods that occurred during autumn 2011 in northern Italy. Different atmospheric simulations were performed by varying the grid spacing (between 1.0 and 3.0 km) of the high-resolution meteorological model and the set of initial/boundary conditions driving the NWP chain. The aim was to investigate the impact of these parameters not only from a meteorological perspective, but also in terms of discharge predictions for the two flood events. The operational flood forecasting system was thus used as a tool to validate in a more pragmatic sense the quantitative precipitation forecast obtained from different configurations of the NWP system. The results showed an improvement in flood prediction when a high-resolution grid was employed for atmospheric simulations. In turn, a better description of the evolution of the precipitating convective systems was beneficial for the hydrological prediction. Although the simulations underestimated the severity of both floods, the higher-resolution model chain would have provided useful information to the decision-makers in charge of protecting citizens.

High-resolution model Verification Evaluation (HiVE). Part 1: Using neighbourhood techniques for the assessment of ocean model forecast skill

2020 ◽  
Author(s):  
Jan Maksymczuk ◽  
Ric Crocker ◽  
Marion Mittermaier ◽  
Christine Pequignet
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Ocean Model ◽  
Forecast Skill ◽  
Model Verification ◽  
Model Forecast ◽  
Verification Methods ◽  
Resolution Model ◽  
The Right ◽  
Spatial Verification

<div> <p>HiVE is a CMEMS funded collaboration between the atmospheric Numerical Weather Prediction (NWP) verification and the ocean community within the Met Office, aimed at demonstrating the use of spatial verification methods originally developed for the evaluation of high-resolution NWP forecasts, with CMEMS ocean model forecast products. Spatial verification methods provide more scale appropriate ways to better assess forecast characteristics and accuracy of km-scale forecasts, where the detail looks realistic but may not be in the right place at the right time. As a result, it can be the case that coarser resolution forecasts verify better (e.g. lower root-mean-square-error) than the higher resolution forecast. In this instance the smoothness of the coarser resolution forecast is rewarded, though the higher-resolution forecast may be better. The project utilised open source code library known as Model Evaluation Toolkit (MET) developed at the US National Center for Atmospheric Research. </p> </div><div> <p> </p> </div><div> <p>This project saw, for the first time, the application of spatial verification methods to sub-10 km resolution ocean model forecasts. The project consisted of two parts. Part 1 describes an assessment of the forecast skill for SST of CMEMS model configurations at observing locations using an approach called HiRA (High Resolution Assessment). Part 2 is described in the companion poster to this one.  </p> </div><div> <p> </p> </div><div> <p>HiRA is a single-observation-forecast-neighbourhood-type method which makes use of commonly used ensemble verification metrics such as the Brier Score (BS) and the Continuous Ranked Probability Score (CRPS). In this instance all model grid points within a predefined neighbourhood of the observing location are considered equi-probable outcomes (or pseudo-ensemble members) at the observing location. The technique allows for an inter-comparison of models with different grid resolutions as well as between deterministic and probabilistic forecasts in an equitable and consistent way. In this work it has been applied to the CMEMS products delivered from the AMM7 (~7km) and AMM15 (~1.5km) model configurations for the European North West Shelf that are provided by the Met Office. </p> </div><div> <p> </p> </div><div> <p>It has been found that when neighbourhoods of equivalent extent are compared for both configurations it is possible to show improved forecast skill for SST for the higher resolution AMM15 both on- and off-shelf, which has been difficult to demonstrate previously using traditional metrics. Forecast skill generally degrades with increasing lead time for both configurations, with the off-shelf results for the higher resolution model showing increasing benefits over the coarser configuration. </p> </div>

scholarly journals An online trajectory module (version 1.0) for the non-hydrostatic numerical weather prediction model COSMO

2013 ◽  
Vol 6 (1) ◽  
pp. 1223-1257
Author(s):  
A. K. Miltenberger ◽  
S. Pfahl ◽  
H. Wernli
Keyword(s):  
High Resolution ◽  
Wind Field ◽  
Model Simulation ◽  
Weather Prediction ◽  
Limited Area ◽  
Model Output ◽  
Wind Fields ◽  
Time Step ◽  
Flow Distortion ◽  
Cosmo Model

Abstract. A module to calculate online trajectories has been implemented into the non-hydrostatic limited-area weather prediction and climate model COSMO. Whereas offline trajectories are calculated with wind fields from model output, which is typically available every one to six hours, online trajectories use the simulated wind field at every model time step (typically less than a minute) to solve the trajectory equation. As a consequence, online trajectories much better capture the short-term temporal fluctuations of the wind field, which is particularly important for mesoscale flows near topography and convective clouds, and they do not suffer from temporal interpolation errors between model output times. The numerical implementation of online trajectories in the COSMO model is based upon an established offline trajectory tool and takes full account of the horizontal domain decomposition that is used for parallelization of the COSMO model. Although a perfect workload balance cannot be achieved for the trajectory module (due to the fact that trajectory positions are not necessarily equally distributed over the model domain), the additional computational costs are fairly small for high-resolution simulations. Various options have been implemented to initialize online trajectories at different locations and times during the model simulation. As a first application of the new COSMO module an Alpine North Föhn event in summer 1987 has been simulated with horizontal resolutions of 2.2 km, 7 km, and 14 km. It is shown that low-tropospheric trajectories calculated offline with one- to six-hourly wind fields can significantly deviate from trajectories calculated online. Deviations increase with decreasing model grid spacing and are particularly large in regions of deep convection and strong orographic flow distortion. On average, for this particular case study, horizontal and vertical positions between online and offline trajectories differed by 50–190 km and 150–750 m, respectively, after 24 h. This first application illustrates the potential for Lagrangian studies of mesoscale flows in high-resolution convection-resolving simulations using online trajectories.

scholarly journals MATISSE: an ArcGIS tool for monitoring and nowcasting meteorological hazards

2015 ◽  
Vol 12 (1) ◽  
pp. 163-169 ◽  
Author(s):  
V. Rillo ◽  
A. L. Zollo ◽  
P. Mercogliano
Keyword(s):  
Prediction Models ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Weather Conditions ◽  
Meteorological Conditions ◽  
Economic Losses ◽  
Statistical Characterization ◽  
Adverse Weather ◽  
Aviation Hazards ◽  
Meteorological Hazards

Abstract. Adverse meteorological conditions are one of the major causes of accidents in aviation, resulting in substantial human and economic losses. For this reason it is crucial to monitor and early forecast high impact weather events. In this context, CIRA (Italian Aerospace Research Center) has implemented MATISSE (Meteorological AviaTIon Supporting SystEm), an ArcGIS Desktop Plug-in able to detect and forecast meteorological aviation hazards over European airports, using different sources of meteorological data (synoptic information, satellite data, numerical weather prediction models data). MATISSE presents a graphical interface allowing the user to select and visualize such meteorological conditions over an area or an airport of interest. The system also implements different tools for nowcasting of meteorological hazards and for the statistical characterization of typical adverse weather conditions for the airport selected.

scholarly journals Comparison between Geostatistical Interpolation and Numerical Weather Model Predictions for Meteorological Conditions Mapping

2020 ◽  
Vol 5 (2) ◽  
pp. 15 ◽  
Author(s):  
Javier López Gómez ◽  
Francisco Troncoso Pastoriza ◽  
Enrique Granada Álvarez ◽  
Pablo Eguía Oller
Keyword(s):  
Local Level ◽  
Weather Prediction ◽  
Ground Truth ◽  
Weather Conditions ◽  
Meteorological Conditions ◽  
Accurate Information ◽  
Numerical Weather ◽  
Weather Model ◽  
Geostatistical Interpolation ◽  
Solid Foundation

Mapping of meteorological conditions surrounding road infrastructures is a critical tool to identify high-risk spots related to harsh weather. However, local or regional data are not always available, and researchers and authorities must rely on coarser observations or predictions. Thus, choosing a suitable method for downscaling global data to local levels becomes essential to obtain accurate information. This work presents a deep analysis of the performance of two of these methods, commonly used in meteorology science: Universal Kriging geostatistical interpolation and Weather Research and Forecasting numerical weather prediction outputs. Estimations from both techniques are compared on 11 locations in central continental Portugal during January 2019, using measured data from a weather station network as the ground truth. Results show the different performance characteristics of both algorithms based on the nature of the specific variable interpolated, highlighting potential correlations to obtain the most accurate data for each case. Hence, this work provides a solid foundation for the selection of the most appropriate tool for mapping of weather conditions at the local level over linear transport infrastructures.

scholarly journals The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1

2018 ◽  
Vol 11 (1) ◽  
pp. 257-281 ◽  
Author(s):  
Piet Termonia ◽  
Claude Fischer ◽  
Eric Bazile ◽  
François Bouyssel ◽  
Radmila Brožková ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Weather Forecasting ◽  
Weather Prediction ◽  
Forecast Model ◽  
Canonical Model ◽  
Limited Area ◽  
Climate Simulations ◽  
Process Studies

Abstract. The ALADIN System is a numerical weather prediction (NWP) system developed by the international ALADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Météo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 partner institutes of this consortium. These configurations are called the ALADIN canonical model configurations (CMCs). There are currently three CMCs: the ALADIN baseline CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations. The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs, (iii) to document their most recent versions, and (iv) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the partner institutes of the ALADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here.

scholarly journals An online trajectory module (version 1.0) for the nonhydrostatic numerical weather prediction model COSMO

2013 ◽  
Vol 6 (6) ◽  
pp. 1989-2004 ◽  
Author(s):  
A. K. Miltenberger ◽  
S. Pfahl ◽  
H. Wernli
Keyword(s):  
High Resolution ◽  
Wind Field ◽  
Weather Prediction ◽  
Limited Area ◽  
Model Output ◽  
Wind Fields ◽  
Time Step ◽  
Flow Distortion ◽  
Computational Costs ◽  
Cosmo Model

Abstract. A module to calculate online trajectories has been implemented into the nonhydrostatic limited-area weather prediction and climate model COSMO. Whereas offline trajectories are calculated with wind fields from model output, which is typically available every one to six hours, online trajectories use the simulated resolved wind field at every model time step (typically less than a minute) to solve the trajectory equation. As a consequence, online trajectories much better capture the short-term temporal fluctuations of the wind field, which is particularly important for mesoscale flows near topography and convective clouds, and they do not suffer from temporal interpolation errors between model output times. The numerical implementation of online trajectories in the COSMO-model is based upon an established offline trajectory tool and takes full account of the horizontal domain decomposition that is used for parallelization of the COSMO-model. Although a perfect workload balance cannot be achieved for the trajectory module (due to the fact that trajectory positions are not necessarily equally distributed over the model domain), the additional computational costs are found to be fairly small for the high-resolution simulations described in this paper. The computational costs may, however, vary strongly depending on the number of trajectories and trace variables. Various options have been implemented to initialize online trajectories at different locations and times during the model simulation. As a first application of the new COSMO-model module, an Alpine north foehn event in summer 1987 has been simulated with horizontal resolutions of 2.2, 7 and 14 km. It is shown that low-tropospheric trajectories calculated offline with one- to six-hourly wind fields can significantly deviate from trajectories calculated online. Deviations increase with decreasing model grid spacing and are particularly large in regions of deep convection and strong orographic flow distortion. On average, for this particular case study, horizontal and vertical positions between online and offline trajectories differed by 50–190 km and 150–750 m, respectively, after 24 h. This first application illustrates the potential for Lagrangian studies of mesoscale flows in high-resolution convection-resolving simulations using online trajectories.

scholarly journals Screen-level non-GTS data assimilation in a limited-area mesoscale model

2010 ◽  
Vol 10 (6) ◽  
pp. 1129-1149 ◽  
Author(s):  
M. Milelli ◽  
M. Turco ◽  
E. Oberto
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Data Assimilation ◽  
Planetary Boundary Layer ◽  
Prediction Models ◽  
Mesoscale Model ◽  
Positive Impact ◽  
Weather Prediction ◽  
Limited Area ◽  
Very High

Abstract. The forecast in areas of very complex topography, as for instance the Alpine region, is still a challenge even for the new generation of numerical weather prediction models which aim at reaching the km-scale. The problem is enhanced by a general lack of standard observations, which is even more evident over the southern side of the Alps. For this reason, it would be useful to increase the performance of the mathematical models by locally assimilating non-conventional data. Since in ARPA Piemonte there is the availability of a great number of non-GTS stations, it has been decided to assimilate the 2 m temperature, coming from this dataset, in the very-high resolution version of the COSMO model, which has a horizontal resolution of about 3 km, more similar to the average resolution of the thermometers. Four different weather situations have been considered, ranging from spring to winter, from cloudy to clear sky. The aim of the work is to investigate the effects of the assimilation of non-GTS data in order to create an operational very high-resolution analysis, but also to test the option of running in the future a very short-range forecast starting from these analyses (RUC or Rapid Update Cycle). The results, in terms of Root Mean Square Error, Mean Error and diurnal cycle of some surface variables such as 2 m temperature, 2 m relative humidity and 10 m wind intensity show a positive impact during the assimilation cycle which tends to dissipate a few hours after the end of it. Moreover, the 2 m temperature assimilation has a slightly positive or neutral impact on the vertical profiles of temperature, eventhough some calibration is needed for the precipitation field which is too much perturbed during the assimilation cycle, while it is unaffected in the forecast period. So the stability of the planetary boundary layer, on the one hand, has not been particularly improved by the new-data assimilation, but, on the other hand, it has not been destroyed. It has to be pointed out that a correct description of the planetary boundary layer, even only the lowest part of it, could be helpful to the forecasters and, in general, to the users, in order to deal with meteorological hazards such as snow (in particular snow/rain limit definition), or fog (description of temperature inversions).

scholarly journals The ALADIN System and its Canonical Model Configurations AROME CY41T1 and ALARO CY40T1

2017 ◽  
Author(s):  
Piet Termonia ◽  
Claude Fischer ◽  
Eric Bazile ◽  
François Bouyssel ◽  
Radmila Brožková ◽  
...  
Keyword(s):  
High Resolution ◽  
Numerical Weather Prediction ◽  
Weather Forecasting ◽  
Weather Prediction ◽  
Forecast Model ◽  
Canonical Model ◽  
Limited Area ◽  
Prediction System ◽  
Climate Simulations ◽  
Process Studies

Abstract. The ALADIN System is a numerical weather prediction system (NWP) developed by the international ALADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Météo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 Partner Institutes of this consortium. These configurations are called the ALADIN Canonical Model Configurations (CMCs). There are currently three CMCs: the ALADIN baseline-CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations. The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs and to document their most recent versions, and (iii) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the Partner Institutes of the ALADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here.

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