scholarly journals Simulation of Surface Ozone Pollution in the Central Gulf Coast Region Using WRF/Chem Model: Sensitivity to PBL and Land Surface Physics

2010 ◽  
Vol 2010 ◽  
pp. 1-24 ◽  
Author(s):  
Anjaneyulu Yerramilli ◽  
Venkata Srinivas Challa ◽  
Venkata Bhaskar Rao Dodla ◽  
Hari Prasad Dasari ◽  
John H. Young ◽  
...  

The fully coupled WRF/Chem (Weather Research and Forecasting/Chemistry) model is used to simulate air quality in the Mississippi Gulf coastal region at a high resolution (4 km) for a moderately severe summer ozone episode between 18 CST 7 and 18 CST 10 June 2006. The model sensitivity is studied for meteorological and gaseous criteria pollutants (O3, NO2) using three Planetary Boundary Layer (PBL) and four land surface model (LSM) schemes and comparison of model results with monitoring station observations. Results indicated that a few combinations of PBL and LSMs could reasonably produce realistic meteorological fields and that the combination of Yonsei University (YSU) PBL and NOAH LSM provides best predictions for winds, temperature, humidity and mixed layer depth in the study region for the period of study. The diurnal range in ozone concentration is better estimated by the YSU PBL in association with either 5-layer or NOAH land surface model. The model seems to underestimate the ozone concentrations in the study domain because of underestimation of temperatures and overestimation of winds. The underestimation of NO2by model suggests the necessity of examining the emission data in respect of its accurate representation at model resolution. Quantitative analysis for most monitoring stations indicates that the combination of YSU PBL with NOAH LSM provides the best results for various chemical species with minimum BIAS, RMSE, and high correlation values.

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2738
Author(s):  
Andrea Reimuth ◽  
Veronika Locherer ◽  
Martin Danner ◽  
Wolfram Mauser

The strong expansion of residential rooftop photovoltaic (PV) and battery storage systems of recent years is expected to rise further. However, it is not yet clear to which degree buildings will be equipped with decentral energy producers. This study seeks to quantify the effects of different PV and battery installation rates on the residential residual loads and grid balancing flows. A land surface model with an integrated residential energy component is applied, which maintains spatial peculiarities and allows a building-specific set-up of PV systems, batteries, and consumption loads. The study area covers 3163 residential buildings located in a municipality in the south of Germany. The obtained results show minor impacts on the residual loads for a PV installation rate of less than 10%. PV installation rates of one third of all residential buildings of the study region lead to the highest spatial balancing via the grid. The rise in self-consumption when utilizing batteries leads to declined grid balancing between the buildings. For high PV installation rates, regional balancing diminishes, whereas energy excesses rise to 60%. They can be decreased up to 10% by the utilization of battery systems. Therefore, we recommend subsidy programs adjusted to the respective PV installation rates.


2020 ◽  
pp. 052
Author(s):  
Jean-Christophe Calvet ◽  
Jean-Louis Champeaux

Cet article présente les différentes étapes des développements réalisés au CNRM des années 1990 à nos jours pour spatialiser à diverses échelles les simulations du modèle Isba des surfaces terrestres. Une attention particulière est portée sur l'intégration, dans le modèle, de données satellitaires permettant de caractériser la végétation. Deux façons complémentaires d'introduire de l'information géographique dans Isba sont présentées : cartographie de paramètres statiques et intégration au fil de l'eau dans le modèle de variables observables depuis l'espace. This paper presents successive steps in developments made at CNRM from the 1990s to the present-day in order to spatialize the simulations of the Isba land surface model at various scales. The focus is on the integration in the model of satellite data informative about vegetation. Two complementary ways to integrate geographic information in Isba are presented: mapping of static model parameters and sequential assimilation of variables observable from space.


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