Impact of two-way coupling and sea-surface temperature on precipitation forecasts in regional atmosphere and ocean models

2019 ◽  
Vol 145 (718) ◽  
pp. 228-242 ◽  
Author(s):  
Benedikt Strajnar ◽  
Jure Cedilnik ◽  
Anja Fettich ◽  
Matjaž Ličer ◽  
Neva Pristov ◽  
...  
2006 ◽  
Vol 19 (23) ◽  
pp. 6069-6088 ◽  
Author(s):  
T. N. Krishnamurti ◽  
Arindam Chakraborty ◽  
Ruby Krishnamurti ◽  
William K. Dewar ◽  
Carol Anne Clayson

Abstract Improved seasonal prediction of sea surface temperature (SST) anomalies over the global oceans is the theme of this paper. Using 13 state-of-the-art coupled global atmosphere–ocean models and 13 yr of seasonal forecasts, the performance of individual models, the ensemble mean, the bias-removed ensemble mean, and the Florida State University (FSU) superensemble are compared. A total of 23 400 seasonal forecasts based on 1-month lead times were available for this study. Evaluation metrics include both deterministic and probabilistic skill measures, such as verification of anomalies based on model and observed climatology, time series of specific climate indices, standard deterministic ensemble mean scores including anomaly correlations, root-mean-square (RMS) errors, and probabilistic skill measures such as equitable threat scores for seasonal SST forecasts. This study also illustrates the Niño-3.4 SST forecast skill for the equatorial Pacific Ocean and for the dipole index for the Indian Ocean. The relative skills of total SST fields and of the SST anomalies from the 13 coupled atmosphere–ocean models are presented. Comparisons of superensemble-based seasonal forecasts with recent studies on SST anomaly forecasts are also shown. Overall it is found that the multimodel superensemble forecasts are characterized by considerable RMS error reductions and increased accuracy in the spatial distribution of SST. Superensemble SST skill also persists for El Niño and La Niña forecasts since the large comparative skill of the superensemble is retained across such years. Real-time forecasts of seasonal sea surface temperature anomalies appear to be possible.


2017 ◽  
Vol 51 (4) ◽  
pp. e9-e14 ◽  
Author(s):  
Hiroto Kajita ◽  
Atsuko Yamazaki ◽  
Takaaki Watanabe ◽  
Chung-Che Wu ◽  
Chuan-Chou Shen ◽  
...  

2019 ◽  
Vol 3 ◽  
pp. 929
Author(s):  
Marianus Filipe Logo ◽  
N M. R. R. Cahya Perbani ◽  
Bayu Priyono

Provinsi Nusa Tenggara Timur (NTT) merupakan penghasil rumput laut kappaphycus alvarezii kedua terbesar di Indonesia berdasarkan data Badan Pusat Statistik (2016). Oleh karena itu diperlukan zonasi daerah potensial budidaya rumput laut kappaphycus alvarezii untuk pengembangan lebih lanjut. Penelitian ini bertujuan untuk menentukan daerah yang potensial untuk budidaya rumput laut kappaphycus alvarezii di Provinsi NTT berdasarkan parameter sea surface temperature (SST), salinitas, kedalaman, arus, dissolved oxygen (DO), nitrat, fosfat, klorofil-a, dan muara sungai. Penentuan kesesuaian lokasi budidaya dilakukan dengan memberikan bobot dan skor bagi setiap parameter untuk budidaya rumput laut kappaphycus alvarezii menggunakan sistem informasi geografis melalui overlay peta tematik setiap parameter. Dari penelitian ini diperoleh bahwa kadar nitrat, arus, kedalaman, dan lokasi muara sungai menjadi parameter penentu utama. Jarak maksimum dari bibir pantai adalah sekitar 10 km. Potensial budidaya rumput laut kappaphycus alvarezii ditemukan di Pulau Flores bagian barat, kepulauan di Kabupaten Flores Timur dan Alor, selatan Pulau Sumba, Pulau Rote, dan Teluk Kupang.


Author(s):  
Diaz Juan Navia ◽  
Diaz Juan Navia ◽  
Bolaños Nancy Villegas ◽  
Bolaños Nancy Villegas ◽  
Igor Malikov ◽  
...  

Sea Surface Temperature Anomalies (SSTA), in four coastal hydrographic stations of Colombian Pacific Ocean, were analyzed. The selected hydrographic stations were: Tumaco (1°48'N-78°45'W), Gorgona island (2°58'N-78°11'W), Solano Bay (6°13'N-77°24'W) and Malpelo island (4°0'N-81°36'W). SSTA time series for 1960-2015 were calculated from monthly Sea Surface Temperature obtained from International Comprehensive Ocean Atmosphere Data Set (ICOADS). SSTA time series, Oceanic Nino Index (ONI), Pacific Decadal Oscillation index (PDO), Arctic Oscillation index (AO) and sunspots number (associated to solar activity), were compared. It was found that the SSTA absolute minimum has occurred in Tumaco (-3.93°C) in March 2009, in Gorgona (-3.71°C) in October 2007, in Solano Bay (-4.23°C) in April 2014 and Malpelo (-4.21°C) in December 2005. The SSTA absolute maximum was observed in Tumaco (3.45°C) in January 2002, in Gorgona (5.01°C) in July 1978, in Solano Bay (5.27°C) in March 1998 and Malpelo (3.64°C) in July 2015. A high correlation between SST and ONI in large part of study period, followed by a good correlation with PDO, was identified. The AO and SSTA have showed an inverse relationship in some periods. Solar Cycle has showed to be a modulator of behavior of SSTA in the selected stations. It was determined that extreme values of SST are related to the analyzed large scale oscillations.


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