| 1. Identity statement | ||||
| Reference Type | Conference Abstract (Conference Proceedings) | |||
| Site | mtc-m16d.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP7W/3D9SGSP | |||
| Repository | sid.inpe.br/mtc-m19/2012/12.28.12.17 | |||
| Last Update | 2015:03.18.18.52.02 (UTC) administrator | |||
| Metadata Repository | sid.inpe.br/mtc-m19/2012/12.28.12.17.02 | |||
| Metadata Last Update | 2018:06.05.04.13.34 (UTC) administrator | |||
| Secondary Key | INPE--PRE/ | |||
| Citation Key | CintraCamp:2012:SaOb | |||
| Title | Global Temperature Assimilation using Artificial Neural Networks in SPEEDY Model: Satellite Observation  | |||
| Year | 2012 | |||
| Access Date | 2024, July 27 | |||
| Secondary Type | PRE CI | |||
| Number of Files | 1 | |||
| Size | 38 KiB | |||
| 2. Context | ||||
| Author | 1 Cintra, Rosangela Saher Correa 2 Campos Velho, H. F. | |||
| Resume Identifier | 1 8JMKD3MGP5W/3C9JJ75 | |||
| Group | 1 LAC-CTE-INPE-MCTI-GOV-BR 2 LAC-CTE-INPE-MCTI-GOV-BR | |||
| Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| Author e-Mail Address | 1 rosangela.cintra@lac.inpe.br 2 haroldo@lac.inpe.br | |||
| e-Mail Address | marcelo.pazos@inpe.br | |||
| Conference Name | European Geosciences Union (EGU) General Assembly. | |||
| Conference Location | Viena | |||
| Date | 22 a 27 de abril de 2012 | |||
| Book Title | Abstracts | |||
| History (UTC) | 2012-12-28 12:18:01 :: marcelo.pazos@sid.inpe.br -> administrator :: 2012 2018-06-05 04:13:34 :: administrator -> marcelo.pazos@inpe.br :: 2012 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Content Type | External Contribution | |||
| Version Type | publisher | |||
| Abstract | An Artificial Neural Network (ANN) is designed to investigate a application for data assimilation. This procedure provides an appropriated initial condition to the atmosphere to numerical weather prediction (NWP). The NWP incorporates the equations of atmospheric dynamics with physical process and it can predict the future state of the atmosphere. Data assimilation procedure combines information from observations and from a prior short-term forecast producing an current state estimate. Operational satellite data are taken and processed in real-time and distributed around the world. The use of observations from the earth-orbiting satellites in operational NWP provides large data volumes and increases the computational effort. The goal here is to simulate the process for assimilating temperature data computed from satellite radiances and introduce new technique in analysis to Weather Forecasting and climate. This performance can be faster than conventional schemes for data assimilation. The numerical experiment is carried out with global model: the Simplified Parameterizations, primitivE-Equation DYnamics (SPEEDY) and the synthetic observations of temperatures from model plus a random noise. For the data assimilation technique was applied a Multilayer Perceptron (MLP-NN) with supervised training, which observation, local point observation and the Local Ensemble Transform Kalman Filter (LETKF) analysis are used as input vector. The global analysis is done in the activation MLP-NN with only, synthetic observation and its local point. In this experiment, the MLP-ANN was trained with the first six months considering the years 1982, 1983, and 1984 data. A hindcasting experiment for data assimilation performed a cycle for January of 1985 with MLP-NN and SPEEDY model. LETKF was performed at the same cycle. The results for MLP-NN analysis are very close with the results obtained from LETKF. The simulations show that the major advantage of using ANN is the better computational performance, with similar quality of analysis. The CPU-time assimilation with MLP-NN is 80% less than LETKF with the same observations. | |||
| Area | COMP | |||
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Global Temperature Assimilation... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
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| 4. Conditions of access and use | ||||
| data URL | http://urlib.net/ibi/8JMKD3MGP7W/3D9SGSP | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGP7W/3D9SGSP | |||
| Language | en | |||
| Target File | cintra_global.pdf | |||
| User Group | marcelo.pazos@inpe.br | |||
| Reader Group | administrator marcelo.pazos@inpe.br | |||
| Visibility | shown | |||
| Read Permission | allow from all | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Mirror Repository | sid.inpe.br/mtc-m19@80/2009/08.21.17.02.53 | |||
| Next Higher Units | 8JMKD3MGPCW/3ESGTTP | |||
| Citing Item List | sid.inpe.br/bibdigital/2013/09.22.23.14 3 sid.inpe.br/mtc-m21/2012/07.13.14.59.36 2 | |||
| Host Collection | sid.inpe.br/mtc-m19@80/2009/08.21.17.02 | |||
| 6. Notes | ||||
| Empty Fields | archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi edition editor format isbn issn keywords label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url volume | |||
| 7. Description control | ||||
| e-Mail (login) | marcelo.pazos@inpe.br | |||
| update | ||||