scholarly journals Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 205
Author(s):  
Laura Rontu ◽  
Emily Gleeson ◽  
Daniel Martin Perez ◽  
Kristian Pagh Nielsen ◽  
Velle Toll
Keyword(s):  
Optical Properties ◽  
Real Time ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Limited Area ◽  
Prediction System ◽  
Heating Rates ◽  
Radiative Fluxes ◽  
Numerical Weather ◽  
The Impact

The direct radiative effect of aerosols is taken into account in many limited-area numerical weather prediction models using wavelength-dependent aerosol optical depths of a range of aerosol species. We studied the impact of aerosol distribution and optical properties on radiative transfer, based on climatological and more realistic near real-time aerosol data. Sensitivity tests were carried out using the single-column version of the ALADIN-HIRLAM numerical weather prediction system, set up to use the HLRADIA simple broadband radiation scheme. The tests were restricted to clear-sky cases to avoid the complication of cloud–radiation–aerosol interactions. The largest differences in radiative fluxes and heating rates were found to be due to different aerosol loads. When the loads are large, the radiative fluxes and heating rates are sensitive to the aerosol inherent optical properties and the vertical distribution of the aerosol species. In such cases, regional weather models should use external real-time aerosol data for radiation parametrizations. Impacts of aerosols on shortwave radiation dominate longwave impacts. Sensitivity experiments indicated the important effects of highly absorbing black carbon aerosols and strongly scattering desert dust.

scholarly journals Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System

2020 ◽  
Author(s):  
Laura Rontu ◽  
Emily Gleeson ◽  
Daniel Martin Perez ◽  
Kristian Pagh Nielsen ◽  
Velle Toll
Keyword(s):  
Optical Properties ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Limited Area ◽  
Prediction System ◽  
Heating Rates ◽  
Radiative Fluxes ◽  
Numerical Weather ◽  
The Impact

The direct radiative effect of aerosols is taken into account in many limited area numerical weather prediction models using wavelength-dependent aerosol optical depths of a range of aerosol species. We study the impact of aerosol distribution and optical properties on radiative transfer, based on climatological and more realistic near real-time aerosol data. Sensitivity tests were carried out using the single column version of the ALADIN-HIRLAM numerical weather prediction system, set up to use the HLRADIA broadband radiation scheme. The tests were restricted to clear-sky cases to avoid the complication of cloud-radiation-aerosol interactions. The largest differences in radiative fluxes and heating rates were found to be due to different aerosol loads. When the loads are large, the radiative fluxes and heating rates are sensitive to the aerosol inherent optical properties and vertical distribution of the aerosol species. Impacts of aerosols on shortwave radiation dominate longwave impacts. Sensitivity experiments indicated the important effects of highly absorbing black carbon aerosols and strongly scattering desert dust.

scholarly journals SINGV – the Convective-Scale Numerical Weather Prediction System for Singapore

2019 ◽  
Vol 36 (3) ◽  
Author(s):  
Xiang-Yu Huang ◽  
Dale Barker ◽  
Stuart Webster ◽  
Anurag Dipankar ◽  
Adrian Lock ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Extreme Rainfall ◽  
Prediction System ◽  
Local Data ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
The United Kingdom ◽  
Convective Scale ◽  
The Impact

Extreme rainfall is one of the primary meteorological hazards in Singapore, as well as elsewhere in the deep tropics, and it can lead to significant local flooding. Since 2013, the Meteorological Service Singapore (MSS) and the United Kingdom Met Office (UKMO) have been collaborating to develop a convective-scale Numerical Weather Prediction (NWP) system, called SINGV. Its primary aim is to provide improved weather forecasts for Singapore and the surrounding region, with a focus on improved short-range prediction of localized heavy rainfall. This paper provides an overview of the SINGV development, the latest NWP capabilities at MSS and some key results of evaluation. The paper describes science advances relevant to the development of any km-scale NWP suitable for the deep tropics and provides some insights into the impact of local data assimilation and utility of ensemble predictions.

Numerical experiments with a parameterization of mires in the COSMO-D2 convection permitting limited-area numerical weather prediction framework

2020 ◽  
Author(s):  
Jürgen Helmert ◽  
Alla Yurova ◽  
Denis Blinov ◽  
Inna Rozinkina ◽  
Michael Baldauf ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Numerical Experiments ◽  
Meteorological Parameters ◽  
Weather Prediction ◽  
Heat Diffusion ◽  
Limited Area ◽  
Lower Boundary Condition ◽  
Numerical Weather ◽  
Screen Level ◽  
The Impact

<p>Europe - especially the northern and middle latitudes - is one of Earth’s mire-rich regions. Among the main distribution areas for mires in Central Europe the coastal region along the southeastern corner of the North Sea (Frisia) shows the highest density of mires. Despite of the important role of mires acting as a carbon sink and modifying the Bowen ratio with influence on screen level meteorological parameters their adequate representation in land-surface schemes used in numerical weather prediction and climate models is still insufficient.</p><p>With the recent version 5.06 the COSMO model (Baldauf et al., 2017) offers a parameterization of mires based on Yurova et al. (2014). In this approach the heat diffusion in the vertical domain of the soil multilayer model TERRA is considered with modified equations describing the thermal conductivity for peat with given water/ice contents. The mire hydrology is parameterized by the solution of the Richard's equation in the vertical domain extended by the formulation of a lower boundary condition as a climatological layer of permanent saturation used to simulate the water table position, in conjunction with a mire‐specific evapotranspiration and runoff parameterization.</p><p>The impact of the mire parameterization on screen level meteorological parameters and mesoscale processes was investigated in two numerical experiments with COSMO-D2 in a convection permitting limited-area numerical weather prediction (NWP) framework for summer 2018 and winter 2018/2019.</p><p>We will present results from the objective verification system and discuss the impact of geospatial physiographic data for an improved representation of mires in the NWP framework.</p>

Influence of Near Real-Time Green Vegetation Fraction Data on the Numerical Weather Prediction in WRF over North China

2020 ◽  
Author(s):  
Bing Lu ◽  
Ji-Qin Zhong ◽  
Wei Wang ◽  
Shi-Hao Tang ◽  
Zhao-Jun Zheng
Keyword(s):  
Real Time ◽  
Numerical Weather Prediction ◽  
North China ◽  
Weather Prediction ◽  
Specific Humidity ◽  
Numerical Weather ◽  
Vegetation Fraction ◽  
Green Vegetation ◽  
The Impact ◽  
Mean Square Errors

<p>Green vegetation fraction (GVF) has a prominent influence on the partitioning of surface sensible and latent heat fluxes in numerical weather prediction models. However, the multi-year monthly GVF climatology, which is the most commonly-used representation of vegetation states in models, has limited ability to capture the real-time vegetation status. In our study, a near real-time (NRT) GVF dataset generated from 8-day composite of the normalized difference vegetation index (NDVI) is compared with the 10-year averaged monthly GVF provided by the Weather Research and Forecasting (WRF) model. We examine the annual and inter-annual variability of the GVF over North China in details. Many differences of the GVF between the two datasets are found over the dryland cropland and grassland areas. Two experiments using different GVF datasets are performed to assess the impact of the GVF on the forecasts of screen-level temperature and humidity for one year. The results show that using the NRT GVF can lead to a widespread reduction of 2-m temperature in the order of 0.5 ℃, and an increase of 2-m humidity during the warm season. An evaluation against in-situ observations displays an overall positive impact on the near surface parameter forecasts. Over the dryland cropland and grassland areas, a quantitative validation shows that the root mean square errors of 24-h forecasts decline by 9%, 10% and 6% for 2-m temperature, 2-m specific humidity and 10-m wind speed, respectively, in May of 2012. Our study demonstrates that the NRT GVF can provide a more realistic representation of vegetation state which in turn helps to improve the short-range forecasts in the arid and semiarid regions of North China.</p>

scholarly journals The impact of periodization methods on the kinetic energy spectra for limited-area numerical weather prediction models

2014 ◽  
Vol 7 (5) ◽  
pp. 6489-6518
Author(s):  
V. Blažica ◽  
N. Gustafsson ◽  
N. Žagar
Keyword(s):  
Kinetic Energy ◽  
Discrete Cosine Transform ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Limited Area ◽  
Cosine Transform ◽  
Numerical Weather ◽  
Extension Zone ◽  
The Impact

Abstract. The paper deals with the comparison of the most common periodization methods used to obtain spectral fields of limited-area models for numerical weather prediction. The focus is on the impact the methods have on the spectra of the fields, which are used for verification and tuning of the models. A simplified model is applied with random fields that obey a known kinetic energy spectrum. The periodization methods under consideration are detrending, the discrete cosine transform and the application of an extension zone. For extension zone, three versions are applied: the Boyd method, the ALADIN method and the HIRLAM method. The results show that detrending and the discrete cosine transform have little impact on the spectra, as does the Boyd method for extension zone. For the ALADIN and HIRLAM methods, the impact depends on the width of the extension zone – the wider the zone, the more artificial energy and the larger impact on the spectra. The width of the extension zone correlates to the modifications in the shape of the spectra as well as to the amplitudes of the additional energy in the spectra.

Assessment of the Impact of Observations on Analyses Derived from Observing System Experiments

2012 ◽  
Vol 140 (1) ◽  
pp. 245-257 ◽  
Author(s):  
Cristina Lupu ◽  
Pierre Gauthier ◽  
Stéphane Laroche
Keyword(s):  
North America ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Radiosonde Data ◽  
Prediction System ◽  
Numerical Weather ◽  
Amount Of Information ◽  
The North ◽  
The Impact ◽  
Assimilation System

Abstract Observing system experiments (OSEs) are commonly used to quantify the impact of different observation types on forecasts produced by a specific numerical weather prediction system. Recently, methods based on degree of freedom for signal (DFS) have been implemented to diagnose the impact of observations on the analyses. In this paper, the DFS is used as a diagnostic to estimate the amount of information brought by subsets of observations in the context of OSEs. This study is interested in the evaluation of the North American observing networks applied to OSEs performed at the Meteorological Service of Canada for the period of January and February 2007. The relative values of the main observing networks over North America derived from DFS calculations are compared with those from OSEs in which aircraft or radiosonde data have been removed. The results show that removing some observation types from the assimilation system influences the effective weight of the remaining assimilated observations, which may have an increased impact to compensate for the removal of other observations. The response of the remaining observations when a given set of observations is denied is illustrated comparing DFS calculations with the observations’ impact estimated from OSEs.

scholarly journals Impact of Doppler Radar Wind Observations on Australian High-Resolution Numerical Weather Prediction

2020 ◽  
Vol 35 (2) ◽  
pp. 309-324
Author(s):  
Susan Rennie ◽  
Lawrence Rikus ◽  
Nathan Eizenberg ◽  
Peter Steinle ◽  
Monika Krysta
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Limited Area ◽  
Observation Error ◽  
Numerical Weather ◽  
Skill Scores ◽  
The Impact

Abstract The impact of Doppler radar wind observations on forecasts from a developmental, high-resolution numerical weather prediction (NWP) system is assessed. The new 1.5-km limited-area model will be Australia’s first such operational NWP system to include data assimilation. During development, the assimilation of radar wind observations was trialed over a 2-month period to approve the initial inclusion of these observations. Three trials were run: the first with no radar data, the second with radial wind observations from precipitation echoes, and the third with radial winds from both precipitation and insect echoes. The forecasts were verified against surface observations from automatic weather stations, against rainfall accumulations using fractions skill scores, and against satellite cloud observations. These methods encompassed verification across a range of vertical levels. Additionally, a case study was examined more closely. Overall results showed little statistical difference in skill between the trials, and the net impact was neutral. While the new observations clearly affected the forecast, the objective and subjective analyses showed a neutral impact on the forecast overall. As a first step, this result is satisfactory for the operational implementation. In future, upgrades to the radar network will start to reduce the observation error, and further improvements to the data assimilation are planned, which may be expected to improve the impact.

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