Data Assimilation and Model Simulations in the California Current

1999 ◽  
Author(s):  
Robert L. Haney
Keyword(s):  
Data Assimilation ◽  
California Current ◽  
Model Simulations

scholarly journals Development of an OMI AI data assimilation scheme for aerosol modeling over bright surfaces – a step toward direct radiance assimilation in the UV spectrum

2020 ◽  
Author(s):  
Jianglong Zhang ◽  
Robert J. D. Spurr ◽  
Jeffrey S. Reid ◽  
Peng Xian ◽  
Peter R. Colarco ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Data Assimilation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Uv Spectrum ◽  
Model Simulations ◽  
Monitoring Instrument ◽  
Radiance Assimilation ◽  
Data Assimilation Scheme ◽  
Assimilation Scheme

Abstract. Using the Vector LInearized Discrete Ordinate Radiative Transfer (VLIDORT) code as the main driver for forward model simulations, a first-of-its-kind data assimilation scheme has been developed for assimilating Ozone Monitoring Instrument (OMI) aerosol index (AI) measurements into the Naval Aerosol Analysis and Predictive System (NAAPS). This study suggests both RMSE and absolute errors can be significantly reduced in NAAPS analyses with the use of OMI AI data assimilation, when compared to values from NAAPS natural runs. Improvements in model simulations demonstrate the utility of OMI AI data assimilation for improving the accuracy of aerosol model analysis over cloudy regions and bright surfaces. However, the OMI AI data assimilation alone does not out-perform aerosol data assimilation that uses passive-based aerosol optical depth (AOD) products over cloud free skies and dark surfaces. Further, as AI assimilation requires the deployment of a fully-multiple-scatter-aware radiative transfer model in the forward simulations, computational burden is an issue. Nevertheless, the newly-developed modeling system contains the necessary ingredients for assimilation of radiances in the ultra-violet (UV) spectrum, and our study shows the potential of direct radiance assimilation at both UV and visible spectrums, possibly coupled with AOD assimilation, for aerosol applications in the future. Additional data streams can be added, including data from TROPOspheric Monitoring Instrument (TROPOMI), Ozone Mapping and Profiler Suite (OMPS) and eventually with the Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) mission.

scholarly journals A study on the aerosol optical properties over East Asia using a combination of CMAQ-simulated aerosol optical properties and remote-sensing data via a data assimilation technique

2011 ◽  
Vol 11 (23) ◽  
pp. 12275-12296 ◽  
Author(s):  
R. S. Park ◽  
C. H. Song ◽  
K. M. Han ◽  
M. E. Park ◽  
S.-S. Lee ◽  
...  
Keyword(s):  
Optical Properties ◽  
Data Assimilation ◽  
East Asia ◽  
Single Scattering ◽  
Single Scattering Albedo ◽  
Dust Particles ◽  
Aerosol Optical Properties ◽  
Fine Grid ◽  
Model Simulations ◽  
Particulate Pollution

Abstract. To more accurately estimate direct radiative forcing (DRF) by aerosols, and better investigate particulate pollution over East Asia, precise calculations of the optical properties of aerosols, such as aerosol optical depth (AOD), single scattering albedo (SSA) and aerosol extinction coefficient (σext), are of primary importance. The aerosol optical properties over East Asia were investigated in this study, based on US EPA Models-3/CMAQ v4.5.1 model simulations. The CMAQ model simulations in this study were improved in several ways compared to those in a previous study (Song et al., 2008). Although the details of the improvements were described in the manuscript, the following points should be emphasized: (1) two data assimilation techniques were employed for producing more accurate AOD products and meteorological fields over East Asia; (2) updated/upgraded emission inventories were used in the CMAQ model simulations with a fine grid resolution of 30 × 30 km2; and (3) the 4-D particulate composition calculated from the CMAQ model simulations was converted into 3-D or 4-D aerosol optical products, using the Malm and Hand (2007) algorithm with significant further modifications. The results from the CMAQ model simulations (without assimilation) showed great improvements compared to those from a previous study. For example, in terms of the regression coefficients (R), R values were increased from 0.48–0.68 (previous study) to 0.62–0.79 (this study). The monthly-averaged CMAQ-simulated single scattering albedo (SSA) also agreed well with the AERONET SSA, with the exceptions of the Hong Kong and Taipei sites, where the air qualities were strongly influenced by active biomass burning events from January to April. There were also excellent matches between the vertical profiles of the CMAQ-simulated σext and LIDAR-retrieved σext. It was also found that the contributions of (NH4)2SO4 during summer, NH4NO3 during winter, sea-salt particles during winter and dust particles during spring to the total AOD were large over East Asia. In particular, the largest contribution of NH4NO3 to the total AOD was found over East Asia during winter. Therefore, it was suggested that this contribution of NH4NO3 should not be neglected. In order to produce more accurate AOD products, the CMAQ-simulated AODs were further assimilated with the MODIS-retrieved AODs. Both of the assimilated and AERONET AODs were better correlated with each other than the CMAQ-simulated and AERONET AODs. The obvious benefits from this study would be that with these improved aerosol optical properties, the particulate pollution (e.g. AOD can be served as a proxy to PM2.5 or PM10) and DRF by aerosols over East Asia can be more satisfactorily investigated in future.

scholarly journals Model-Reduced Variational Data Assimilation

2006 ◽  
Vol 134 (10) ◽  
pp. 2888-2899 ◽  
Author(s):  
P. T. M. Vermeulen ◽  
A. W. Heemink
Keyword(s):  
Diffusion Coefficient ◽  
Data Assimilation ◽  
Original Model ◽  
Variational Data Assimilation ◽  
Reduced Model ◽  
New Approach ◽  
Model Simulations ◽  
Computational Costs ◽  
Recent Estimate ◽  
Reduced Space

Abstract This paper describes a new approach to variational data assimilation that with a comparable computational efficiency does not require implementation of the adjoint of the tangent linear approximation of the original model. In classical variational data assimilation, the adjoint implementation is used to efficiently compute the gradient of the criterion to be minimized. Our approach is based on model reduction. Using an ensemble of forward model simulations, the leading EOFs are determined to define a subspace. The reduced model is created by projecting the original model onto this subspace. Once this reduced model is available, its adjoint can be implemented very easily and can be used to approximate the gradient of the criterion. The minimization process can now be solved completely in reduced space with negligible computational costs. If necessary, the procedure can be repeated a few times by generating new ensembles closer to the most recent estimate of the parameters. The reduced-model-based method has been tested on several nonlinear synthetic cases for which a diffusion coefficient was estimated.

Data assimilation of physical and chlorophyll a observations in the California Current System using two biogeochemical models

2017 ◽  
Vol 109 ◽  
pp. 55-71 ◽  
Author(s):  
Jann Paul Mattern ◽  
Hajoon Song ◽  
Christopher A. Edwards ◽  
Andrew M. Moore ◽  
Jerome Fiechter
Keyword(s):  
Data Assimilation ◽  
Chlorophyll A ◽  
Current System ◽  
California Current ◽  
California Current System ◽  
Biogeochemical Models
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