Assessing Sensitivity of Observations in Source Term Estimation for Nuclear Accidents

2012 ◽  
Author(s):  
Yuanwei Ma ◽  
Dezhong Wang ◽  
Wenji Tan ◽  
Zhilong Ji ◽  
Kuo Zhang
Keyword(s):  
Data Assimilation ◽  
Source Term ◽  
Dynamic Models ◽  
Source Parameters ◽  
Nuclear Accident ◽  
Fukushima Nuclear Accident ◽  
Observation Data ◽  
Source Terms ◽  
Highly Nonlinear ◽  
Assimilation System

In the Fukushima nuclear accident, due to the lack of field observations and the complexity of source terms, researchers failed to estimate the source term accurately immediately. Data assimilation methods to estimate source terms have many good features: they works well with highly nonlinear dynamic models, no linearization in the evolution of error statistics, etc. This study built a data assimilation system using the ensemble Kalman Filter for real-time estimates of source parameters. The assimilation system uses a Gaussian puff model as the atmospheric dispersion model, assimilating forward with the observation data. Considering measurement error, numerical experiments were carried on to verify the stability and accuracy of the scheme. Then the sensitivity of observation configration is tested by the twin experiments. First, the single parameter release rate of the source term is estimated by different sensor grid configurations. In a sparse sensors grid, the error of estimation is about 10%, and in a 11*11 grid configuration, the error is less than 1%. Under the analysis of the Fukushima nuclear accident, ahead for the actual situation, four parameters are estimated at the same time, by 2*2 to 11*11 grid configurations. The studies showed that the radionuclides plume should cover as many sensors as possible, which will lead a to successful estimation.

scholarly journals Intraseasonal SST–precipitation relationship in a coupled reanalysis experiment using the MRI coupled atmosphere–ocean data assimilation system

2021 ◽  
Author(s):  
Chiaki Kobayashi ◽  
Yosuke Fujii ◽  
Ichiro Ishikawa
Keyword(s):  
Data Assimilation ◽  
Surface Temperature ◽  
Heat Propagation ◽  
Observation Data ◽  
Near Surface ◽  
Ocean Data Assimilation ◽  
Meteorological Research Institute ◽  
Atmospheric Observations ◽  
Data Assimilation System ◽  
Assimilation System

AbstractTo evaluate the atmosphere–ocean coupled data assimilation system developed at the Meteorological Research Institute, the lead-lag relation between the intraseasonal variations (with a time scale of 20–100 days) in precipitation and sea surface temperature (SST) is examined in the tropics. It is shown that the relationship over the tropical western Pacific in the coupled reanalysis experiment (CDA) follows the observed relationship more closely than that in the uncoupled reanalysis experiment (UCPL). However, the lead-lag correlations with the observed SST are almost identical between precipitations in CDA and UCPL, indicating that the atmospheric component is strongly constrained by atmospheric observations and hardly affected by the SSTs as boundary conditions. Better representation of the SST–precipitation relationship in CDA is, thus, mostly due to the SST variation modified by the model physics. Comparison with additional reanalysis experiments using coupled and uncoupled systems that assimilate only in-situ observations without satellite observations suggests that the coupled model's physics complements the relatively weak observation constraints and reduces the degradation of the SST–precipitation relationship. Additional analysis for CDA suggests that the warming-to-cooling (cooling-to-warming) transition of the surface net flux, which is in phase with precipitation, is delayed from the positive (negative) peak of SST due to downward heat propagation in the ocean. Comparison of the oceanic near-surface temperature field with observation data indicates that the downward propagation of heat signals is too fast in CDA, resulting in smaller lags of transitions of the net heat flux and precipitation behind SST peaks.

scholarly journals Forecasting Radiation Effects on Wildlife in Japan After the Fukushima Nuclear Accident, Based on Limited Information of Post-Accident Early Stage in 2011

2014 ◽  
Vol XL-2 ◽  
pp. 13-20 ◽  
Author(s):  
M. U. Saito ◽  
T. Doko ◽  
F. Koike
Keyword(s):  
Radiation Effects ◽  
Early Stage ◽  
Regional Distribution ◽  
Nuclear Accident ◽  
Radioactive Isotopes ◽  
Fukushima Nuclear Accident ◽  
Observation Data ◽  
Limited Information ◽  
Radioactive Materials ◽  
Chronic Radiation

Due to the 11 March 2011 Tohoku earthquake, massive radioactive materials were released from the Fukushima Daiichi Nuclear Power Plant (Fukushima NPP). It is crucial to predict the regional distribution and magnitude of the effects on wildlife by radioactive materials. However, during the post-accident early stage in 2011, limited information on large-scale pollution and prediction maps was open to public. Hence, this paper aimed to provide (1) the pollution map covering areas within 300 km from the Fukushima NPP where the radiation intensity exceeded 0.5 μSv/h, (2) pollution maps which predicted air dose for the next 30 years after the accident, and (3) maps of areas where wildlife might be affected by radioactive isotopes by the Fukushima nuclear accident. First, the relative contributions of <sup>131</sup>I, <sup>134</sup>Cs, and <sup>137</sup>Cs were estimated from time series observation data. Second, a 30-year prediction of the pollution was calculated based on the isotope half-lives. Third, the chronic radiation effects on vertebrates were estimated using the threshold dose rate proposed by Sazykina et al. (2009). We examined the chronic radiation effects on morbidity, reproduction, and longevity. The results indicated that radioactive materials could have affected vertebrate morbidity within a 350 km<sup>2</sup> area in early April 2011; the threshold level was the median result of Sazykina et al. (2009) with bootstrapping. Based on the prediction, a 15.5 km<sup>2</sup> region will remain affected after 30 years. These areas should be monitored to confirm the effects of radioactivity on wildlife.

scholarly journals JRAero: the Japanese Reanalysis for Aerosol v1.0

2017 ◽  
Vol 10 (9) ◽  
pp. 3225-3253 ◽  
Author(s):  
Keiya Yumimoto ◽  
Taichu Y. Tanaka ◽  
Naga Oshima ◽  
Takashi Maki
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Horizontal Resolution ◽  
Japan Meteorological Agency ◽  
Observation Data ◽  
Aerosol Transport ◽  
Aerosol Model ◽  
Meteorological Research Institute ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. A global aerosol reanalysis product named the Japanese Reanalysis for Aerosol (JRAero) was constructed by the Meteorological Research Institute (MRI) of the Japan Meteorological Agency. The reanalysis employs a global aerosol transport model developed by MRI and a two-dimensional variational data assimilation method. It assimilates maps of aerosol optical depth (AOD) from MODIS onboard the Terra and Aqua satellites every 6 h and has a TL159 horizontal resolution (approximately 1.1°  ×  1.1°). This paper describes the aerosol transport model, the data assimilation system, the observation data, and the setup of the reanalysis and examines its quality with AOD observations. Comparisons with MODIS AODs that were used for the assimilation showed that the reanalysis showed much better agreement than the free run (without assimilation) of the aerosol model and improved under- and overestimation in the free run, thus confirming the accuracy of the data assimilation system. The reanalysis had a root mean square error (RMSE) of 0.05, a correlation coefficient (R) of 0.96, a mean fractional error (MFE) of 23.7 %, a mean fractional bias (MFB) of 2.8 %, and an index of agreement (IOA) of 0.98. The better agreement of the first guess, compared to the free run, indicates that aerosol fields obtained by the reanalysis can improve short-term forecasts. AOD fields from the reanalysis also agreed well with monthly averaged global AODs obtained by the Aerosol Robotic Network (AERONET) (RMSE  =  0.08, R = 0. 90, MFE  =  28.1 %, MFB  =  0.6 %, and IOA  =  0.93). Site-by-site comparison showed that the reanalysis was considerably better than the free run; RMSE was less than 0.10 at 86.4 % of the 181 AERONET sites, R was greater than 0.90 at 40.7 % of the sites, and IOA was greater than 0.90 at 43.4 % of the sites. However, the reanalysis tended to have a negative bias at urban sites (in particular, megacities in industrializing countries) and a positive bias at mountain sites, possibly because of insufficient anthropogenic emissions data, the coarse model resolution, and the difference in representativeness between satellite and ground-based observations.

scholarly journals JRAero: the Japanese Reanalysis for Aerosol v1.0

2017 ◽  
Author(s):  
Keiya Yumimoto ◽  
Taichu Y. Tanaka ◽  
Naga Oshima ◽  
Takashi Maki
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Horizontal Resolution ◽  
Japan Meteorological Agency ◽  
Observation Data ◽  
Aerosol Transport ◽  
Aerosol Model ◽  
Meteorological Research Institute ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. A global aerosol reanalysis product named the Japanese Reanalysis for Aerosol (JRAero) was constructed by the Meteorological Research Institute (MRI) of the Japan Meteorological Agency. The reanalysis employs a global aerosol transport model developed by MRI and a 2-dimensional variational data assimilation method. It assimilates maps of aerosol optical depth (AOD) from MODIS onboard Terra and Aqua satellites every 6 hours and has a TL159 horizontal resolution (approximately 1.1° × 1.1°). This paper describes the aerosol transport model, the data assimilation system, the observation data, and the set-up of the reanalysis and examines its quality. Comparisons with MODIS AODs showed that the reanalysis showed much better agreement than the free run (without assimilation) of the aerosol model and improved under- and overestimation in the free run, thus confirming the accuracy of the data assimilation system. The reanalysis had a root mean square error (RMSE) = 0.05, a correlation coefficient (R) = 0.96, a mean fractional error (MFE) = 23.7 %, a mean fractional bias (MFB) = 2.8 %, and an index of agreement (IOA) = 0.98. The better agreement of the first guess, compared with the free run, indicates that aerosol fields obtained by the reanalysis can improve short-term forecasts. AOD fields from the reanalysis also agreed well with monthly averaged global AODs obtained by the Aerosol Robotic Network (AERONET) (RMSE = 0.08, R = 0.90, MFE = 28.1 %, MFB = 0.6 %, and IOA = 0.93). Site-by-site comparison showed that the reanalysis was considerably better than the free run; RMSE was  0.90 at 40.7 % of the sites, and IOA was > 0.90 at 43.4 % of the sites. However, the reanalysis tended to have a negative bias at urban sites (in particular, megacities in industrializing countries) and a positive bias at mountain sites, possibly because of insufficient anthropogenic emissions data, the coarse model resolution, and the difference in representativeness between satellite and ground-based observations.

Radioactive source terms for the Fukushima nuclear accident

2015 ◽  
Vol 59 (1) ◽  
pp. 214-222 ◽  
Author(s):  
WuHui Lin ◽  
LiQi Chen ◽  
Wen Yu ◽  
Hao Ma ◽  
Zhi Zeng ◽  
...  
Keyword(s):  
Radioactive Source ◽  
Nuclear Accident ◽  
Fukushima Nuclear Accident ◽  
Source Terms

Data assimilation system for estimating methane flows using satellite data

2020 ◽  
Author(s):  
Marina Platonova
Keyword(s):  
Data Assimilation ◽  
Satellite Data ◽  
Numerical Experiments ◽  
Transport Model ◽  
Time Interval ◽  
Observation Data ◽  
Three Dimensional Model ◽  
Passive Impurity ◽  
Data Assimilation System ◽  
Assimilation System

&lt;p&gt;This work is devoted to the urgent task of assessing regional flows of greenhouse gases from the Earth's surface according to satellite observations. The article presents the practical and theoretical results of the first year of study in the PhD program, later they will be included in the final dissertation. Flows will be estimated based on the observational data assimilation system for a three-dimensional model of diffusive transport of gas components in the atmosphere (MOZART-4). Model for Ozone and Associated Chemical Indicators, Version 4 (MOZART-4) is an autonomous global model for the transport of chemicals in the atmosphere.&lt;/p&gt;&lt;p&gt;The development of a modern system for the assimilation of real satellite data for assessing greenhouse gas sources is currently a very important theoretical and practical area in science. The ensemble approach is relevant and has great potential for using both stochastic and variational methods. In the process of implementation, this is an order of magnitude simpler, since there are no cumbersome matrix calculations using the model.&lt;/p&gt;&lt;p&gt;To solve the problem of estimating methane flows, the parameter estimation problem was solved: an algorithm for data assimilation was developed; the Kalman filter with the transformation of the local ensemble was used as the basis for it. Using an example of a model problem, an algorithm for estimating the concentration of a passive impurity and a parameter is developed. The case was also considered when only one parameter can be estimated in the assimilation system. In this case it is considered that at the forecasting stage the parameter does not change, and the calculations in accordance with the transport model are included in the operator H, for example, as in Feng (2009,2017). H is the observation operator; transfers predicted values to observation points (and observed variables). For example, for satellite methane data, H includes:&lt;/p&gt;&lt;ol&gt;&lt;li&gt;a) interpolation to the observation point;&lt;/li&gt; &lt;li&gt;b) vertical averaging (using the middle core);&lt;/li&gt; &lt;li&gt;c) if the observation data is obtained from a large time interval, then the operator H also includes a forecast for the model in time.&lt;/li&gt; &lt;/ol&gt;&lt;p&gt;Numerical experiments were carried out with model and real data. Using numerical experiments with the model, it was shown that a large problem (global) can be solved sequentially by subregion, independently in each subregion, which allowed the use of MPI and OpenMP.&lt;/p&gt;

Data Assimilation for Fukushima Nuclear Accident Assessments

2017 ◽  
Author(s):  
Mei Xu ◽  
Biao Yuan ◽  
Liangyu Wang ◽  
Lijun Zhang
Keyword(s):  
Data Assimilation ◽  
Dose Rate ◽  
Radiation Field ◽  
Nuclear Power ◽  
Nuclear Accident ◽  
Radioactive Material ◽  
Fukushima Nuclear Accident ◽  
The Real ◽  
Kalman Filter Algorithm ◽  
Good Agreement

In order to investigate the feasibility of data assimilation in a real nuclear accident environment, measurements of Fukushima nuclear accident were considered. The data assimilation system was constructed by using the Lagrangian puff model as the radioactive material diffusion model, and 86 group real dose rate data from the accident as the observations, and the Ensemble Kalman Filter algorithm as the assimilation algorithm. The experimental results show that the assimilated nuclear accident radiation field is in good agreement with the actual measurements, the land contaminated areas are concentrated in the northwest of the nuclear power plant. With the increase of the real measurements, the error of the radiation field decreases with time. Compared with the results with no assimilation, the uncertainty of assimilated dose rate was reduced more than 80%. Through the data assimilation, the whole error of the radiation field is about 30%. The utilization of the real measurements can reduce the uncertainty of the model prediction.

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