scholarly journals Volcanic ash modeling with the online NMMB-MONARCH-ASH v1.0 model: model description, case simulation, and evaluation

2017 ◽  
Vol 17 (6) ◽  
pp. 4005-4030 ◽  
Author(s):  
Alejandro Marti ◽  
Arnau Folch ◽  
Oriol Jorba ◽  
Zavisa Janjic
Keyword(s):  
Volcanic Ash ◽  
Prediction Models ◽  
Transport Model ◽  
Weather Prediction ◽  
Mount Etna ◽  
Model Description ◽  
Tephra Dispersal ◽  
Coupling Strategy ◽  
Simulation And Evaluation ◽  
Ash Cloud

Abstract. Traditionally, tephra transport and dispersal models have evolved decoupled (offline) from numerical weather prediction models. There is a concern that inconsistencies and shortcomings associated with this coupling strategy might lead to errors in the ash cloud forecast. Despite this concern and the significant progress in improving the accuracy of tephra dispersal models in the aftermath of the 2010 Eyjafjallajökull and 2011 Cordón Caulle eruptions, to date, no operational online dispersal model is available to forecast volcanic ash. Here, we describe and evaluate NMMB-MONARCH-ASH, a new online multi-scale meteorological and transport model that attempts to pioneer the forecast of volcanic aerosols at operational level. The model forecasts volcanic ash cloud trajectories, concentration of ash at relevant flight levels, and the expected deposit thickness for both regional and global configurations. Its online coupling approach improves the current state-of-the-art tephra dispersal models, especially in situations where meteorological conditions are changing rapidly in time, two-way feedbacks are significant, or distal ash cloud dispersal simulations are required. This work presents the model application for the first phases of the 2011 Cordón Caulle and 2001 Mount Etna eruptions. The computational efficiency of NMMB-MONARCH-ASH and its application results compare favorably with other long-range tephra dispersal models, supporting its operational implementation.

scholarly journals Volcanic ash modeling with the on-line NMMB/BSC-ASHv1.0 model: model description, case simulation and evaluation

2016 ◽  
Author(s):  
Alejandro Marti ◽  
Arnau Folch ◽  
Oriol Jorba ◽  
Zavisa Janjic
Keyword(s):  
Volcanic Ash ◽  
Prediction Models ◽  
Transport Model ◽  
Weather Prediction ◽  
Model Description ◽  
Tephra Dispersal ◽  
Coupling Strategy ◽  
On Line ◽  
Simulation And Evaluation ◽  
Ash Cloud

Abstract. Traditionally, tephra transport and dispersal models have evolved decoupled (off-line) from numerical weather prediction models. There is a concern that inconsistencies and shortcomings associated to this coupling strategy might lead to errors in the ash cloud forecast. Despite this concern, and the significant progress to improve the accuracy of tephra dispersal models in the aftermath of the 2010 Eyjafjallajökull and 2011 Cordón Caulle eruptions, to date, no operational on-line dispersal model is available to forecast volcanic ash. Here, we describe and evaluate NMMB/BSC-ASH, a new on-line multiscale meteorological and transport model that attempts to pioneer the forecast of volcanic aerosols at operational level. The model predicts volcanic ash cloud trajectories, concentration of ash at relevant flight levels, and the expected deposit thickness for both regional and global configurations. Its on-line coupling approach improves the current state-of-the-art of tephra dispersal models, especially in situations where meteorological conditions are changing rapidly in time, two-way feedbacks are significant, or distal ash cloud dispersal simulations are required. This work presents the model application for the first phases of the 2011 Cordón Caulle and 2001 Mt. Etna eruptions. The computational efficiency of NMMB/BSC-ASH and its application results compare favorably with other long-range tephra dispersal models, supporting its operational implementation.

scholarly journals A global model study of ozone enhancement during the August 2003 heat wave in Europe

2007 ◽  
Vol 4 (5) ◽  
pp. 285 ◽  
Author(s):  
G. Guerova ◽  
N. Jones
Keyword(s):  
Heat Wave ◽  
Prediction Models ◽  
Extreme Event ◽  
Transport Model ◽  
Weather Prediction ◽  
Surface Ozone ◽  
Anthropogenic Emissions ◽  
Model Study ◽  
Reactive Pollutant ◽  
Surface O3

Environmental context. During the 2003 European summer, record high temperatures were measured and some regions experienced 14 consecutive days with maximum temperatures above 35°C, thus triggering a heat wave. The prolonged heat and strong insolation facilitated the build up of exceptionally long-lasting and spatially extensive episodes of high ozone concentrations close to the surface. Ozone is a very reactive pollutant with known effects on both human and vegetation health. It is important to build robust models that can predict its concentration in a similar manner to which weather prediction models operate. Abstract. The European summer of 2003 was characterised by intense heat, prolonged isolation and suppressed ventilation of the boundary layer which, combined with large anthropogenic emissions and strong fires, resulted in a build up of an unprecedentedly high and long-lasting photochemical smog over large parts of the continent. In this work, a global chemistry and transport model GEOS-Chem is compared with surface O3 concentrations observed in 2003 in order to examine the extent to which the model is capable of reproducing such an extreme event. The GEOS-Chem reproduces the temporal variation of O3 at the Jungfraujoch mountain site, Switzerland, including the enhanced concentrations associated with the August 2003 heat wave (r = 0.84). The spatial distribution of the enhanced surface O3 over Spain, France, Germany and Italy is also captured to some extent (r = 0.63), although the largest concentrations appear to be located over the Italian Peninsula in the model rather than over Central Europe as suggested by the surface O3 observations. In general, the observed differences between the European averaged O3 concentrations in the summer of 2003 to those in 2004 are larger in the observations than in the model, as the model reproduces relatively well the enhanced levels in 2003 but overestimates those observed in 2004. Preliminary contributions of various sources to the O3 surface concentrations over Europe during the heat wave indicate that anthropogenic emissions from Europe contribute the most to the O3 build up near the surface (40 to 50%, i.e. 30 ppb). The contribution from anthropogenic emissions from the other major source regions of the northern hemisphere, in particular North America, tends to be smaller than those of other years. The model indicates that the large fires that occurred in that year contributed up to 5% (3 ppb) to surface O3 in close proximity to the fire regions and less elsewhere in Europe. Biogenic volatile organic compounds (VOCs) emitted by grass and forest areas contributed up to 10% (5–6 ppb) of surface O3 over France, Germany and northern Italy, which represents a contribution that is twice as large than that found in 2004. These results in terms of contributions from various sources, particularly biogenic emissions, should be seen as preliminary, as the response of vegetation to such extreme events may not be well represented in the model.

Dispersion Modelling at the London VAAC 10 Years after the Eyjafjallajökull Ash Cloud

2020 ◽  
Author(s):  
Frances Beckett ◽  
Claire Witham ◽  
Susan Leadbetter ◽  
Ric Crocker ◽  
Helen Webster ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Source Parameters ◽  
Atmospheric Dispersion ◽  
Lessons Learned ◽  
Volcanic Ash Cloud ◽  
Atmospheric Dispersion Models ◽  
Ash Cloud

<p>It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull caused chaos to air traffic across Europe. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. Here we present the development of the NAME atmospheric dispersion model and modifications to its application in the London VAAC forecasting system since 2010, based on the lessons learned.</p><p>Our ability to represent both the vertical and horizontal transport of ash in the atmosphere and its removal have been improved through the introduction of new schemes to represent the sedimentation and wet deposition of volcanic ash, and updated schemes to represent deep atmospheric convection and parameterizations for plume spread due to unresolved mesoscale motions. A good simulation of the transport and dispersion of a volcanic ash cloud requires an accurate representation of the source and we have introduced more sophisticated approaches to representing the eruption source parameters, and their uncertainties, used to initialize NAME. Further, atmospheric dispersion models are driven by 3-dimensional meteorological data from Numerical Weather Prediction (NWP) models and the Met Office’s upper air wind field data is now more accurate than it was in 2010. These developments have resulted in a more robust modelling system at the London VAAC, ready to provide forecasts and guidance during the next volcanic ash event affecting their region.</p>

Forecasting of Tornadoes and Downbursts

2020 ◽  
Author(s):  
Djordje Romanic
Keyword(s):  
Chaos Theory ◽  
Prediction Models ◽  
Weather Prediction ◽  
Small Scale ◽  
Weather Forecasts ◽  
Wind Speeds ◽  
The Past ◽  
Extreme Wind ◽  
Extreme Wind Speeds ◽  
Numerical Weather Prediction Models

Tornadoes and downbursts cause extreme wind speeds that often present a threat to human safety, structures, and the environment. While the accuracy of weather forecasts has increased manifold over the past several decades, the current numerical weather prediction models are still not capable of explicitly resolving tornadoes and small-scale downbursts in their operational applications. This chapter describes some of the physical (e.g., tornadogenesis and downburst formation), mathematical (e.g., chaos theory), and computational (e.g., grid resolution) challenges that meteorologists currently face in tornado and downburst forecasting.

scholarly journals HGPT2: An ERA5-Based Global Model to Estimate Relative Humidity

2021 ◽  
Vol 13 (11) ◽  
pp. 2179
Author(s):  
Pedro Mateus ◽  
Virgílio B. Mendes ◽  
Sandra M. Plecha
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Real Time ◽  
Prediction Models ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Global Navigation Satellite Systems ◽  
International Gnss Service ◽  
Weighted Mean Temperature

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.

scholarly journals Fengyun Meteorological Satellite Products for Earth System Science Applications

2021 ◽  
Author(s):  
Di Xian ◽  
Peng Zhang ◽  
Ling Gao ◽  
Ruijing Sun ◽  
Haizhen Zhang ◽  
...  
Keyword(s):  
Data Sharing ◽  
Satellite Data ◽  
Prediction Models ◽  
Weather Forecasting ◽  
Numerical Models ◽  
Weather Prediction ◽  
Vegetation Indices ◽  
Open Data ◽  
Earth System ◽  
Inversion Algorithm

AbstractFollowing the progress of satellite data assimilation in the 1990s, the combination of meteorological satellites and numerical models has changed the way scientists understand the earth. With the evolution of numerical weather prediction models and earth system models, meteorological satellites will play a more important role in earth sciences in the future. As part of the space-based infrastructure, the Fengyun (FY) meteorological satellites have contributed to earth science sustainability studies through an open data policy and stable data quality since the first launch of the FY-1A satellite in 1988. The capability of earth system monitoring was greatly enhanced after the second-generation polar orbiting FY-3 satellites and geostationary orbiting FY-4 satellites were developed. Meanwhile, the quality of the products generated from the FY-3 and FY-4 satellites is comparable to the well-known MODIS products. FY satellite data has been utilized broadly in weather forecasting, climate and climate change investigations, environmental disaster monitoring, etc. This article reviews the instruments mounted on the FY satellites. Sensor-dependent level 1 products (radiance data) and inversion algorithm-dependent level 2 products (geophysical parameters) are introduced. As an example, some typical geophysical parameters, such as wildfires, lightning, vegetation indices, aerosol products, soil moisture, and precipitation estimation have been demonstrated and validated by in-situ observations and other well-known satellite products. To help users access the FY products, a set of data sharing systems has been developed and operated. The newly developed data sharing system based on cloud technology has been illustrated to improve the efficiency of data delivery.

scholarly journals Parametrizations of Liquid and Ice Clouds’ Optical Properties in Operational Numerical Weather Prediction Models

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 89
Author(s):  
Harel. B. Muskatel ◽  
Ulrich Blahak ◽  
Pavel Khain ◽  
Yoav Levi ◽  
Qiang Fu
Keyword(s):  
Optical Properties ◽  
Numerical Weather Prediction ◽  
Radiation Transfer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Effective Size ◽  
Asymmetry Factor ◽  
Numerical Weather ◽  
Numerical Weather Prediction Models ◽  
Spectral Averaging

Parametrization of radiation transfer through clouds is an important factor in the ability of Numerical Weather Prediction models to correctly describe the weather evolution. Here we present a practical parameterization of both liquid droplets and ice optical properties in the longwave and shortwave radiation. An advanced spectral averaging method is used to calculate the extinction coefficient, single scattering albedo, forward scattered fraction and asymmetry factor (bext, v, f, g), taking into account the nonlinear effects of light attenuation in the spectral averaging. An ensemble of particle size distributions was used for the ice optical properties calculations, which enables the effective size range to be extended up to 570 μm and thus be applicable for larger hydrometeor categories such as snow, graupel, and rain. The new parameterization was applied both in the COSMO limited-area model and in ICON global model and was evaluated by using the COSMO model to simulate stratiform ice and water clouds. Numerical weather prediction models usually determine the asymmetry factor as a function of effective size. For the first time in an operational numerical weather prediction (NWP) model, the asymmetry factor is parametrized as a function of aspect ratio. The method is generalized and is available on-line to be readily applied to any optical properties dataset and spectral intervals of a wide range of radiation transfer models and applications.

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