Multiyear climate prediction with initialization based on 4D-Var data assimilation

2016 ◽  
Vol 43 (8) ◽  
pp. 3903-3910 ◽  
Author(s):  
Takashi Mochizuki ◽  
Shuhei Masuda ◽  
Yoichi Ishikawa ◽  
Toshiyuki Awaji
Keyword(s):  
Data Assimilation ◽  
Climate Prediction

Application of Data Assimilation to Ocean and Climate Prediction

2016 ◽  
pp. 3-10
Author(s):  
Michael J. Bell ◽  
Matthew J. Martin ◽  
Nancy K. Nichols
Keyword(s):  
Data Assimilation ◽  
Climate Prediction

scholarly journals Pengaruh Central Pacific dan eastern Pacific El Nino terhadap variabilitas curah hujan di Sulawesi

2018 ◽  
Vol 15 (2) ◽  
pp. 73
Author(s):  
Budi Prasetyo ◽  
Nikita Pusparini
Keyword(s):  
Data Assimilation ◽  
El Niño ◽  
El Nino ◽  
Climate Prediction ◽  
Eastern Pacific ◽  
Central Pacific ◽  
Eastern Pacific El Niño ◽  
Ocean Data Assimilation ◽  
Ep El Niño ◽  
Climate Prediction Center

Pulau Sulawesi dipengaruhi oleh fenomena Central Pacific (CP) dan Eastern Pacific (EP) El Niño. Curah hujan Sulawesi mencakup ketiga pola hujan yang ada di Indonesia yaitu Monsunal, equatorial, dan lokal. Variabilitas ketiga pola curah hujan tersebut akan memberikan respon yang berbeda terhadap pengaruh dari kedua tipe El Niño tersebut. Maka, Kajian ini akan membahas pengaruh dari kedua tipe El Niño  terhadap curah hujan Sulawesi. Penelitian ini Menggunakan data curah hujan bulanan berasal dari Climate Prediction Center (CPC) National Oceanic and Atmospheric Administration (NOAA), Suhu Permukaan Laut (SPL) bulanan dari System Ocean Data Assimilation (SODA) versi 2.2.4 dan oceanic Niño Indeks (ONI) dengan periode  Januari 1950 hingga Desember 2010 (60 tahun). Perhitungan statistik sederhana berupa perata-rataan, korelasi, dan analisa komposit digunakan dalam kajian ini. Penentuan tipe El Niño menggunakan tiga buah indeks yang berbeda. Hasilnya diperoleh bahwa Curah hujan Sulawesi berkurang saat kedua tipe El Niño. Penurunan curah hujan akibat EP El Niño berkisar antara 5 – 20 mm sedangkan akibat CP El Niño berkisar antara 2-12 mm. Wilayah Sulawesi dengan pola curah hujan monsunal merupakan wilayah yang mengalami penurunan curah hujan terbesar akibat kedua tipe El Niño tersebut, kemudian diikuti dengan pola curah hujan equatorial dan terakhir Lokal.

Model-consistent ocean data assimilation for seasonal to decadal climate prediction

2020 ◽  
Author(s):  
Sebastian Brune ◽  
Holger Pohlmann ◽  
Kristina Fröhlich ◽  
Johanna Baehr
Keyword(s):  
Data Assimilation ◽  
Large Scale ◽  
Climate Model ◽  
Climate Prediction ◽  
Meridional Overturning Circulation ◽  
Atmospheric Variability ◽  
Decadal Time Scale ◽  
Sense Data ◽  
Ocean Data Assimilation ◽  
Assimilation Scheme

<p>In Earth's climate system, the slowly varying ocean represents an important source of memory for predictions on the seasonal to decadal time scale. The ocean picks up atmospheric variability on a broad range of scales and feeds back on the large-scale atmospheric circulation. While today’s comprehensive Earth system models (ESMs) used in climate prediction are able to simulate this atmosphere-ocean feedback in a broad sense, data assimilation - which brings the climate model close to the observed state – allows the use of ESMs for climate predictions. We propose that the quality of climate predictions can be improved by initializing the ESMs using a model-consistent assimilation of observations resulting in (1) an initialization of the ESM with a model state close to the observed one, while (2) minimizing a potential initialization shock resulting from a mismatch between the simulated climate state and observations.<br />Here we demonstrate our approach towards a model-consistent assimilation of two ESMs used in climate prediction at Universität Hamburg and Deutscher Wetterdienst: MPI-ESM and ICON-ESM. Central to our approach is a weakly coupled assimilation setup, consisting of an Ensemble Kalman filter assimilation scheme in the ocean component (MPI-ESM, ICON-ESM) and a nudging assimilation scheme in the atmospheric component (MPI-ESM). We show that our approach facilitates a large part of atmosphere-ocean interaction already within the assimilation, allowing for a quick adaption of the assimilation in case of unrealistic behaviour of key processes. For two key large-scale oceanic processes, Atlantic meridional overturning circulation and oceanic Rossby waves, we analyze how sensitive they are to the degree of atmosphere-ocean interaction allowed for during assimilation and what this implies for the respective climate predictions. </p>

Integral Control Data Assimilation in Wave Predictions

1997 ◽  
Author(s):  
L.H. Holthuijsen ◽  
N. Booij ◽  
M. van Endt ◽  
S. Caires ◽  
C. Guedes Soares
Keyword(s):  
Data Assimilation ◽  
Control Data ◽  
Integral Control
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