scholarly journals The impact of resolution on meteorological, chemical and aerosol properties in regional simulations with WRF-Chem

2017 ◽  
Vol 17 (2) ◽  
pp. 1511-1528 ◽  
Author(s):  
Paola Crippa ◽  
Ryan C. Sullivan ◽  
Abhinav Thota ◽  
Sara C. Pryor
Keyword(s):  
Spatial Resolution ◽  
Model Performance ◽  
Specific Humidity ◽  
Spatiotemporal Variability ◽  
Limited Area ◽  
Monthly Precipitation ◽  
Regional Models ◽  
Skill Scores ◽  
The Impact ◽  
Aerosol Properties

Abstract. Limited area (regional) models applied at high resolution over specific regions of interest are generally expected to more accurately capture the spatiotemporal variability of key meteorological and climate parameters. However, improved performance is not inevitable, and there remains a need to optimize use of numerical resources and to quantify the impact on simulation fidelity that derives from increased resolution. The application of regional models for climate forcing assessment is currently limited by the lack of studies quantifying the sensitivity to horizontal spatial resolution and the physical–dynamical–chemical schemes driving the simulations. Here we investigate model skill in simulating meteorological, chemical and aerosol properties as a function of spatial resolution, by applying the Weather Research and Forecasting model with coupled Chemistry (WRF-Chem) over eastern North America at different resolutions. Using Brier skill scores and other statistical metrics it is shown that enhanced resolution (from 60 to 12 km) improves model performance for all of the meteorological parameters and gas-phase concentrations considered, in addition to both mean and extreme aerosol optical depth (AOD) in three wavelengths in the visible relative to satellite observations, principally via increase of potential skill. Some of the enhanced model performance for AOD appears to be attributable to improved simulation of meteorological conditions and the concentration of key aerosol precursor gases (e.g., SO2 and NH3). Among other reasons, a dry bias in the specific humidity in the boundary layer and a substantial underestimation of total monthly precipitation in the 60 km simulations are identified as causes for the better performance of WRF-Chem simulations at 12 km.

scholarly journals Value-added by high-resolution regional simulations of climate-relevant aerosol properties

2016 ◽  
Author(s):  
P. Crippa ◽  
R. C. Sullivan ◽  
A. Thota ◽  
S. C. Pryor
Keyword(s):  
Temporal Variability ◽  
Radiative Forcing ◽  
Model Performance ◽  
Value Added ◽  
Climate Forcing ◽  
Specific Humidity ◽  
Limited Area ◽  
Skill Scores ◽  
Spatio Temporal ◽  
The Impact

Abstract. Despite recent advances in global Earth System Models (ESMs), the current global mean aerosol direct and indirect radiative effects remain uncertain, as does their future role in climate forcing and regional manifestations. Reasons for this uncertainty include the high spatio-temporal variability of aerosol populations. Thus, limited area (regional) models applied at higher resolution over specific regions of interest are generally expected to "add value", i.e. improve the fidelity of the physical-dynamical-chemical processes that induce extreme events and dictate climate forcing, via more realistic representation of spatio-temporal variability. However, added value is not inevitable, and there remains a need to optimize use of numerical resources, and to quantify the impact on simulation fidelity that derives from increased resolution. Here we quantify the value added by enhanced spatial resolution in simulations of the drivers of aerosol direct radiative forcing by applying the Weather Research and Forecasting model with coupled Chemistry (WRF-Chem) over eastern North America at different resolutions. Using Brier Skill Scores and other statistical metrics it is shown that enhanced resolution (from 60 to 12 km) improves model performance for all of the meteorological parameters and gas phase concentrations considered, in addition to both mean and extreme Aerosol Optical Depth (AOD) in three wavelengths in the visible relative to satellite observations, principally via increase of potential skill. Some of the enhanced model performance for AOD appears to be attributable to improved simulation of specific humidity and the resulting impact on aerosol hygroscopic growth/hysteresis.

scholarly journals B-matrix estimation in the Copernicus European Regional Re-Analysis (CERRA)

2021 ◽  
Author(s):  
Adam El-Said ◽  
Pierre Brousseau ◽  
Roger Randriamampianina ◽  
Martin Ridal
Keyword(s):  
Regime Change ◽  
Forecast Skill ◽  
Specific Humidity ◽  
Limited Area ◽  
Seasonal Component ◽  
Weather Regime ◽  
Skill Scores ◽  
The Impact ◽  
European Regional

<p>A new augmented Ensemble of Data Assimilations (EDA) technique, which estimates background error covariances (B-matrix), has been developed for the new Copernicus European Regional Re-Analysis (CERRA-EDA). CERRA-EDA has 10 members with two main pools of forecast differences: seasonal and daily. The seasonal component is pre-prepared (`offline') at reanalysis-resolution (5.5km). The new augmentation governs the time-dependent mixture of winter and summer differences of this seasonal component with respect to the time of year. The daily component is (`online') and averaged in moving succession over 2.5 days with subsequent B-matrix computation every 2 days. This daily component runs at 11km and the forecasts are interpolated to 5.5km prior to use. The seasonal-daily split is set to a fixed value of 80-20\% for CERRA production. The EDA is cycled 6-hourly while CERRA has a 3-hour analysis cycle. The B-matrix is modelled on a bi-Fourier limited area weather model, where dependence of vertical correlations on horizontal scale (non-separability), horizontal homogeneity and isotropy are assumed. The mass-wind and specific humidity fields are related via vorticity and geopotential and the relationships are estimated via multiple linear regressions enforcing simplified analogues of flow-dependence. </p><p>We demonstrate the potential of CERRA-EDA to estimate rapid changes in weather regime change over Europe by assessing B-matrix statistics and forecast skill scores in a case study. The case study assesses two like-periods bearing different weather regimes, Mar-03 (blocking regime) and Mar-18 (NAO- regime). The aptitude of the B-matrix to reflect weather regime change is shown to be mostly dependent on the observation network in a given year. We also illustrate the impact of: change in observation networks over time, and varying the seasonal-daily split. This is shown through analysing the spatio-temporal evolution of background standard deviations. Finally, analysis and forecast skill scores up to 24-hours are also shown to offer improvements worth considering.</p>

scholarly journals The Suitability of the Satellite Metrological Inputs Source on the Hydrological Model in a Small Urban Catchment

2016 ◽  
Author(s):  
Song Song ◽  
Youpeng Xu ◽  
Jiali Wang ◽  
Jinkang Du ◽  
Jianxin Zhang ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Potential Evapotranspiration ◽  
Model Performance ◽  
Yangtze River Delta ◽  
Precipitation Data ◽  
Model Quality ◽  
Small Catchment ◽  
Explanatory Variables ◽  
Distributed Models ◽  
The Impact

Distributed/semi-distributed models are considered to be sensitive to the spatial resolution of the data input. In this paper, we take a small catchment in high urbanized Yangtze River Delta, Qinhuai catchment as study area, to analyze the impact of spatial resolution of precipitation and the potential evapotranspiration (PET) on the long-term runoff and flood runoff process. The data source includes the TRMM precipitation data, FEWS download PET data, and the interpolated metrological station data. GIS/RS technique was used to collect and pre-process the geographical, precipitation and PET series, which were then served as the input of CREST (Coupled Routing and Excess Storage) model to simulate the runoff process. The results clearly showed that, the CREST model is applicable to the Qinhuai catchment; the spatial resolution of precipitation had strong influence on the modelled runoff results and the metrological precipitation data cannot be substituted by the TRMM data in small catchment; the CREST model was not sensitive to the spatial resolution of the PET data, while the estimation fourmula of the PET data was correlated with the model quality. This paper focused on the small urbanized catchment, suggesting the influential explanatory variables for the model performance, and providing reliable reference for the study in similar area.

scholarly journals The effects of spatial discretization on performances and parameters of urban hydrological model

2019 ◽  
Vol 80 (3) ◽  
pp. 517-528 ◽  
Author(s):  
Qing Chang ◽  
So Kazama ◽  
Yoshiya Touge ◽  
Shunsuke Aita
Keyword(s):  
Spatial Resolution ◽  
Scale Effects ◽  
Model Performance ◽  
Computation Time ◽  
Rainfall Runoff ◽  
Total Runoff ◽  
Sensing Technology ◽  
Impervious Area ◽  
Runoff Modeling ◽  
The Impact

Abstract Selecting a proper spatial resolution for urban rainfall runoff modeling was not a trivial issue because it could affect the model outputs. Recently, the development of remote sensing technology and increasingly available data source had enabled rainfall runoff process to be modeled at detailed and microscales. However, the models with less complexity might have equally good performance with less model establishment and computation time. This study attempted to explore the impact of model spatial resolution on model performance and parameters. Models with different discretization degree were built up on the basis of actual drainage networks, urban parcels and specific land use. The results showed that there was very little difference in the total runoff volumes while peak flows showed obvious scale effects which could be up to 30%. Generally, model calibration could compensate the scale effect. The calibrated models with different resolution showed similar performances. The consideration of effective impervious area (EIA) as a calibration parameter marginally increased performance of the calibration period but also slightly decreased performance in the validation period which indicated the importance of detailed EIA identification.

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.

scholarly journals A Numerical Sensitivity Analysis of Soil Moisture Feedback on Convective Precipitation

2019 ◽  
Vol 20 (1) ◽  
pp. 23-44 ◽  
Author(s):  
Marika Koukoula ◽  
Efthymios I. Nikolopoulos ◽  
Jonilda Kushta ◽  
Nikolaos S. Bartsotas ◽  
George Kallos ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Spatial Resolution ◽  
Land Surface ◽  
Atmospheric Model ◽  
Atmospheric Modeling ◽  
Heat Fluxes ◽  
Convective Precipitation ◽  
Limited Area ◽  
The Impact

Abstract Of the boundary conditions that affect the simulation of convective precipitation, soil moisture is one of the most important. In this study, we explore the impact of the soil moisture on convective precipitation, and factors affecting it, through an extensive numerical experiment based on four convective precipitation events that caused moderate to severe flooding in the Gard region of southern France. High-spatial-resolution (1 km) weather simulations were performed using the integrated atmospheric model Regional Atmospheric Modeling System/Integrated Community Limited Area Modeling System (RAMS/ICLAMS). The experimental framework included comparative analysis of five simulation scenarios for each event, in which we varied the magnitude and spatial distribution of the initial volumetric water content using realistic soil moisture fields with different spatial resolution. We used precipitation and surface soil moisture from radar and satellite sensors as references for the comparison of the sensitivity tests. Our results elucidate the complexity of the relationship between soil moisture and convective precipitation, showing that the control of soil water content on partitioning land surface heat fluxes has significant impacts on convective precipitation. Additionally, it is shown how different soil moisture conditions affect the modeled microphysical structure of the clouds, which translates into further changes in the magnitude and distribution of precipitation.

scholarly journals The Impact of Spatial Variation of Westerlies On Comprehensive And Extreme Precipitation Over Iran

2021 ◽  
Author(s):  
Nabi Mirzaei ◽  
Bohloul Alijani ◽  
Zahra Hejazizadeh ◽  
Mohammad Darand ◽  
Mohammad Hossein Naserzadeh
Keyword(s):  
Spatial Variation ◽  
Extreme Precipitation ◽  
Heavy Precipitation ◽  
Specific Humidity ◽  
The Arctic ◽  
Monthly Precipitation ◽  
Teleconnection Patterns ◽  
The Arctic Oscillation ◽  
The Impact ◽  
The Relationship

Abstract This study analyzed the impact of spatial variation in westerlies on widespread and heavy precipitation over Iran using the sinuosity index. Four groups of datasets were used for the period from 1979 to 2020, containing the gridded geopotential height, specific humidity, precipitation data, and the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) teleconnection patterns. The results demonstrate that the trend in sinuosity variation has been decreased during the 1979-1999 sub period but increased from 2000 to 2020. The analysis of the trend in cumulative sinuosity for the above two sub periods indicates that sinuosity rate has been greater in the latter than in the former all over the year except in October. The overall trend in sinuosity variation exhibits an increase by 0.0018, significantly. Maximum sinuosity can be observed in January, March, and December, and minimum sinuosity is seen in October. The relationship between heavy precipitation and sinuosity suggests that daily precipitation has increased by 3 mm with a rise of 0.2 in the value of sinuosity, monthly precipitation by 10 mm, and the annual value by 38 mm. Thus, the rate of correlation between sinuosity and precipitation over Iran equals to 0.74. Sinuosity increase in the 0-70° E range indicates an increase in wave depth and the occurrence of a cut off low. The most important factor in the persistence of widespread extreme precipitation has been the formation of these lows in the 20-40°E and 20-35°N ranges.

scholarly journals Impact of additional AMDAR data in the AROME-France model during May 2017

2019 ◽  
Vol 16 ◽  
pp. 215-222
Author(s):  
Alexis Doerenbecher ◽  
Jean-François Mahfouf
Keyword(s):  
Additional Data ◽  
Forecast Skill ◽  
Experimental Methodology ◽  
Scale Model ◽  
Limited Area ◽  
Telecommunication System ◽  
Skill Scores ◽  
Global Telecommunication System ◽  
The Impact ◽  
Aircraft Data

Abstract. From 1 May 2017 until 15 June 2017, the E-AMDAR operational service from EUMETNET disseminated more commercial aircraft data than usual on the Global Telecommunication System (GTS). Météo-France specifically requested the implementation of such a trial. It lead to an increase in the number of aircraft data over France, especially vertical profiles (ascents and descents). Though Météo-France routinely buys additional data with respect to the basic E-AMDAR service, this trial aimed at assessing the potential of French airlines to produce further data in collaboration with E-AMDAR and yield an observation network as dense as possible. This was the opportunity to check the impact of these additional data on forecast skill scores of the limited area and convective scale model AROME-France. A data denial experiment (OSE) was carried out on May 2017, by removing E-AMDAR profiles (about 14 % of data) to mimic the routine observing system. The reference was the operational AROME-France 3D-Var that assimilated all extra data in real-time. However, no dedicated flag allowed to distinguish supplementary data from routine ones. Therefore, a necessary step of the experimental methodology was to identify which data profile could be considered as supplementary. The examination of forecast skill scores from the denial experiment showed that the impact of the removal of the additional observations is rather small and mixed, depending upon the parameter of interest, the atmospheric level, and the forecast range. The case studies done did not exhibit any particular additional skill for the suite with augmented observations. The experimental set-up is described and the results are discussed on the basis of forecast scores, including precipitation scores. Finally, a number of recommendations are given for a more optimal assimilation of AMDAR data in the AROME-France model.

scholarly journals Evaluating Forecast Impact of Assimilating Microwave Humidity Sounder (MHS) Radiances with a Regional Ensemble Kalman Filter Data Assimilation System

2015 ◽  
Vol 30 (4) ◽  
pp. 964-983 ◽  
Author(s):  
Kathryn M. Newman ◽  
Craig S. Schwartz ◽  
Zhiquan Liu ◽  
Hui Shao ◽  
Xiang-Yu Huang
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Specific Humidity ◽  
Lead Times ◽  
Limited Area ◽  
Microwave Humidity Sounder ◽  
The Impact ◽  
Data Assimilation System ◽  
Assimilation System

Abstract This study examines the impact of assimilating Microwave Humidity Sounder (MHS) radiances in a limited-area ensemble Kalman filter (EnKF) data assimilation system. Two experiments spanning 11 August–13 September 2008 were run over a domain featuring the Atlantic basin using a 6-h full cycling analysis and forecast system. Deterministic 72-h forecasts were initialized at 0000 and 1200 UTC for a comparison of forecast impact. The two experiments were configured identically with the exception of the inclusion of the MHS radiances (AMHS) in the second to isolate the impacts of the MHS radiance data. The results were verified against several sources, and statistical significance tests indicate the most notable differences are in the midlevel moisture fields. Both configurations were characterized by high moisture biases when compared to the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim, also known as ERA-I) specific humidity fields, as well as precipitable water vapor from an observationally based product. However, the AMHS experiment has midlevel moisture fields closer to the ERA-I and observation datasets. When reducing the verification domain to focus on the subtropical and easterly wave regions of the North Atlantic Ocean, larger improvements in midlevel moisture at nearly all lead times is seen in the AMHS simulation. Finally, when considering tropical cyclone forecasts, the AMHS configuration shows improvement in intensity forecasts at several lead times as well as improvements at early to intermediate lead times for minimum sea level pressure forecasts.

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