The key question is how (and if) the assimilation of atmospheric chemical observa- tions improves the capability of regional models in reproducing the distribution of tropospheric pollutants. The study is carried out using the BOLCHEM (BOLam + CHEMistry) which is based on the meteorological hydrostatic mesoscale model BO- LAM (Bologna Limited Area Model) and two photochemical mechanisms: SAPRC90 and CB-IV. The meteorology is coupled online-one way with the chemistry. A sequential Optimal Interpolation routine is implemented in this model for gaseous pollutants data assimilation such as ozone, nitrogen dioxide, carbon monoxide to es- timate the correlation between the temporal-spatial resolution of observations and its impact on air-quality forecast through sensitivity tests. We test and evaluate the performance of this simplified assimilation scheme using different approaches: (1) assimilation of ground-based and satellite measurements of O3 and NO2 , and (2) Observing System Simulation Experiment (OSSE) of simulated satellite observations. The first approach aims at estimating the benefit gained from the use of existing observations, while the second one at evaluating the
Impact of ground and satellite measurements on a regional meteorological-chemical model
D'Isidoro M;Fierli F;Maurizi A;
2008
Abstract
The key question is how (and if) the assimilation of atmospheric chemical observa- tions improves the capability of regional models in reproducing the distribution of tropospheric pollutants. The study is carried out using the BOLCHEM (BOLam + CHEMistry) which is based on the meteorological hydrostatic mesoscale model BO- LAM (Bologna Limited Area Model) and two photochemical mechanisms: SAPRC90 and CB-IV. The meteorology is coupled online-one way with the chemistry. A sequential Optimal Interpolation routine is implemented in this model for gaseous pollutants data assimilation such as ozone, nitrogen dioxide, carbon monoxide to es- timate the correlation between the temporal-spatial resolution of observations and its impact on air-quality forecast through sensitivity tests. We test and evaluate the performance of this simplified assimilation scheme using different approaches: (1) assimilation of ground-based and satellite measurements of O3 and NO2 , and (2) Observing System Simulation Experiment (OSSE) of simulated satellite observations. The first approach aims at estimating the benefit gained from the use of existing observations, while the second one at evaluating theI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
