scholarly journals RELATIONSHIP OF THE GREENLAND HALIBUT STOCKS IN THE OKHOTSK SEA WITH ENVIRONMENTAL FACTORS

2020 ◽  
Vol 200 ◽  
pp. 58-81
Author(s):  
V. V. Kulik ◽  
S. V. Prants ◽  
M. V. Budyansky ◽  
M. Yu. Uleysky ◽  
P. A. Fayman ◽  
...  
Keyword(s):  
Time Lag ◽  
Additive Model ◽  
Circulation Model ◽  
The Arctic ◽  
Okhotsk Sea ◽  
Greenland Halibut ◽  
Arctic Oscillation Index ◽  
Western Kamchatka ◽  
Arrival Times ◽  
The Arctic Oscillation

Dynamics of the greenland halibut biomass in the fishery districts of the Okhotsk Sea (or subzones) is considered. The biomass variation in the East-Sakhalin subzone has a significant (p < 0.05) negative correlation with the number of 3+ fish in other subzones, with the time lag of 3 years (r = –0.53) and 4 years (r = –0.49), that is interpreted as alternative distribution of the halibut recruitment from the common spawning area either to this district or other ones. From other hand, the recruits abundance in other districts is significantly and positively associated (r = 0.52, p < 0.05) with the index of zonal atmosphere transfer in January and with the index of meridional atmosphere transfer in March of the years of hatching. The recruitment dependence on the spawning stock could be explained by Beaverton-Holt equation with the residuals significantly and positively (r = 0.64, p = 0.03) related with the Arctic Oscillation index. Transport of the eggs, larvae and juveniles of greenland halibut from the spawning grounds at western Kamchatka to the western Okhotsk Sea is considered as the mechanism of its recruitment distribution between the districts in relation with atmospheric indices. The transport was simulated for 1993–2017 using the circulation model JCOPE2 as the movement of 250,000 artificial passive particles, imitating eggs and larvae, with water flows at the depth 40–50 m where their main aggregations are supposed. The particles were released in the area at western Kamchatka where the maximal concentration of spawning females occurred. Number of the particles reached the sections off eastern Sakhalin and their arrival times were computed, their pathways were tracked. The portion of particles released in December and reached northern Sakhalin within 150 days changed in significant positive correlation (r = 0.44, p < 0.05) with dynamics of the halibut stock in the East-Sakhalin subzone, with the time lag 6 years. Even closer correlation (r = 0.94, p < 0.05) could be found for the optimum income of the particles released in October or November in the general additive model of the stock. Using the model results for the recent years, the greenland halibut stock decreasing in the East-Sakhalin subzone is forecasted for the next 6 years.

scholarly journals The ground-based FTIR network's potential for investigating the atmospheric water cycle

2010 ◽  
Vol 10 (7) ◽  
pp. 3427-3442 ◽  
Author(s):  
M. Schneider ◽  
K. Yoshimura ◽  
F. Hase ◽  
T. Blumenstock
Keyword(s):  
General Circulation ◽  
Water Cycle ◽  
Circulation Model ◽  
Hadley Circulation ◽  
Reanalysis Data ◽  
The Arctic ◽  
Atmospheric Water ◽  
Arctic Oscillation Index ◽  
Northern Atlantic ◽  
The Arctic Oscillation

Abstract. We present tropospheric H216O and HD16O/H216O vapour profiles measured by ground-based FTIR (Fourier Transform Infrared) spectrometers between 1996 and 2008 at a northern hemispheric subarctic and subtropical site (Kiruna, Northern Sweden, 68° N and Izaña, Tenerife Island, 28° N, respectively). We compare these measurements to an isotope incorporated atmospheric general circulation model (AGCM). If the model is nudged towards meteorological fields of reanalysis data the agreement is very satisfactory on time scales ranging from daily to inter-annual. Taking the Izaña and Kiruna measurements as an example we document the FTIR network's unique potential for investigating the atmospheric water cycle. At the subarctic site we find strong correlations between the FTIR data, on the one hand, and the Arctic Oscillation index and the northern Atlantic sea surface temperature, on the other hand. The Izaña FTIR measurements reveal the importance of the Hadley circulation and the Northern Atlantic Oscillation index for the subtropical middle/upper tropospheric water balance. We document where the AGCM is able to capture these complexities of the water cycle and where it fails.

scholarly journals Seasonal Forecasting with a Simple General Circulation Model: Predictive Skill in the AO and PNA

2005 ◽  
Vol 18 (4) ◽  
pp. 597-609 ◽  
Author(s):  
Jacques Derome ◽  
Hai Lin ◽  
Gilbert Brunet
Keyword(s):  
General Circulation ◽  
Initial Conditions ◽  
Circulation Model ◽  
Atmospheric Model ◽  
The Arctic ◽  
Small Perturbations ◽  
Predictive Skill ◽  
The Pacific ◽  
The Arctic Oscillation ◽  
Environmental Prediction

Abstract A primitive equation dry atmospheric model is used to perform ensemble seasonal predictions. The predictions are done for 51 winter seasons [December–January–February (DJF)] from 1948 to 1998. Ensembles of 24 forecasts are produced, with initial conditions of 1 December plus small perturbations. The model uses a forcing field that is calculated empirically from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses. The forcing used to forecast a given winter is the sum of its winter climatological forcing plus an anomaly. The anomalous forcing is obtained as that of the month prior to the start of the forecast (November), which is also calculated from NCEP data. The predictions are thus made without using any information about the season to be predicted. The ensemble-mean predictions for the 51 winters are verified against the NCEP–NCAR reanalyses. Comparisons are made with the results obtained with a full GCM. It is found that the skill of the simple GCM is comparable in many ways to that of the full GCM. The skill in predicting the amplitude of the main patterns of Northern Hemisphere mean-seasonal variability, the Arctic Oscillation (AO) and the Pacific–North American (PNA) pattern is also discussed. The simple GCM has skill not only in predicting the PNA pattern during winters with strong ENSO forcing, but it also has skill in predicting the AO in winters without appreciable ENSO forcing.

scholarly journals Where can the Arctic oscillation be reconstructed? Towards a reconstruction of climate modes based on stable teleconnections

2005 ◽  
Vol 1 (1) ◽  
pp. 17-56 ◽  
Author(s):  
G. Lohmann ◽  
N. Rimbu ◽  
M. Dima
Keyword(s):  
Arctic Oscillation ◽  
Ice Core ◽  
The Arctic ◽  
Boreal Winter ◽  
Arctic Oscillation Index ◽  
Climate Modes ◽  
Teleconnection Patterns ◽  
Temperature And Precipitation ◽  
The Arctic Oscillation ◽  
Coral Tree

Abstract. Proxy data can bring observed climate variability of the last 100 years into a long-term context. We identify regions of the Northern Hemisphere where the teleconnection patterns of the Arctic Oscillation are stationary. Our method provides a systematic way to examine optimal sites for the reconstruction of climate modes based on paleoclimatic archives that sensitively record temperature and precipitation variations. We identify the regions for boreal winter and spring that can be used to reconstruct the Arctic Oscillation index in the pre-instrumental period. Finally, this technique is applied to high resolution coral, tree ring, ice core and mollusk shell data to understand proxy-climate teleconnections and their use for climate reconstructions.

scholarly journals Chaotic Properties of the Arctic Oscillation Index

SOLA ◽  
2011 ◽  
Vol 7 ◽  
pp. 33-36 ◽  
Author(s):  
Yoshito Hirata ◽  
Yuko Shimo ◽  
Hiroshi L. Tanaka ◽  
Kazuyuki Aihara
Keyword(s):  
Arctic Oscillation ◽  
The Arctic ◽  
Arctic Oscillation Index ◽  
The Arctic Oscillation

scholarly journals A Numerical Sensitivity Study of the Influence of Siberian Snow on the Northern Annular Mode

2012 ◽  
Vol 25 (2) ◽  
pp. 592-607 ◽  
Author(s):  
Y. Peings ◽  
D. Saint-Martin ◽  
H. Douville
Keyword(s):  
General Circulation ◽  
Arctic Oscillation ◽  
Polar Vortex ◽  
Circulation Model ◽  
Sensitivity Study ◽  
The Arctic ◽  
Annular Mode ◽  
Northern Annular Mode ◽  
Model Free ◽  
The Arctic Oscillation

Abstract The climate version of the general circulation model Action de Recherche Petite Echelle Grande Echelle (ARPEGE-Climat) is used to explore the relationship between the autumn Siberian snow and the subsequent winter northern annular mode by imposing snow anomalies over Siberia. As the model presents some biases in the representation of the polar vortex, a nudging methodology is used to obtain a more realistic but still interactive extratropical stratosphere in the model. Free and nudged sensitivity experiments are compared to discuss the dependence of the results on the northern stratosphere climatology. For each experiment, a positive snow mass anomaly imposed from October to March over Siberia leads to significant impacts on the winter atmospheric circulation in the extratropics. In line with previous studies, the model response resembles the negative phase of the Arctic Oscillation. The well-documented stratospheric pathway between snow and the Arctic Oscillation operates in the nudged experiment, while a more zonal propagation of the signal is found in the free experiment. Thus, the study provides two main findings: it supports the influence of Siberian snow on the winter extratropical circulation and highlights the importance of the northern stratosphere representation in the models to capture this teleconnection. These findings could have important implications for seasonal forecasting, as most of the operational models present biases similar to those of the ARPEGE-Climat model.

A Predictability Measure Applied to Seasonal Predictions of the Arctic Oscillation

2007 ◽  
Vol 20 (18) ◽  
pp. 4733-4750 ◽  
Author(s):  
Youmin Tang ◽  
Hai Lin ◽  
Jacques Derome ◽  
Michael K. Tippett
Keyword(s):  
Confidence Level ◽  
General Circulation ◽  
Arctic Oscillation ◽  
A Priori ◽  
Circulation Model ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Central Pacific ◽  
The Arctic Oscillation ◽  
Sst Anomalies

Abstract In this study, ensemble seasonal predictions of the Arctic Oscillation (AO) were conducted for 51 winters (1948–98) using a simple global atmospheric general circulation model. A means of estimating a priori the predictive skill of the AO ensemble predictions was developed based on the relative entropy (R) of information theory, which is a measure of the difference between the forecast and climatology probability density functions (PDFs). Several important issues related to the AO predictability, such as the dominant precursors of forecast skill and the degree of confidence that can be placed in an individual forecast, were addressed. It was found that R is a useful measure of the confidence that can be placed on dynamical predictions of the AO. When R is large, the prediction is likely to have a high confidence level whereas when R is small, the prediction skill is more variable. A small R is often accompanied by a relatively weak AO index. The value of R is dominated by the predicted ensemble mean. The relationship identified here, between model skills and the R of an ensemble prediction, offers a practical means of estimating the confidence level of a seasonal forecast of the AO using the dynamical model. Through an analysis of the global sea surface temperature (SST) forcing, it was found that the winter AO-related R is correlated significantly with the amplitude of the SST anomalies over the tropical central Pacific and the North Pacific during the previous October. A large value of R is usually associated with strong SST anomalies in the two regions, whereas a poor prediction with a small R indicates that SST anomalies are likely weak in these two regions and the observed AO anomaly in the specific winter is likely caused by atmospheric internal dynamics.

scholarly journals Classification of Polar-Night Jet Oscillations and Their Relationship to Fast and Slow Variations in a Global Mechanistic Circulation Model of the Stratosphere and Troposphere

2010 ◽  
Vol 23 (23) ◽  
pp. 6438-6444 ◽  
Author(s):  
Masashi Kohma ◽  
Seiya Nishizawa ◽  
Shigeo Yoden
Keyword(s):  
Low Frequency ◽  
Polar Vortex ◽  
Circulation Model ◽  
Negative Temperature ◽  
The Arctic ◽  
Eof Analysis ◽  
Polar Night ◽  
Low Pass ◽  
Cold Events ◽  
The Arctic Oscillation

Abstract Polar-night jet oscillation (PJO), which is a low-frequency intraseasonal oscillatory variation in the winter stratosphere, is analyzed statistically with a 14 000-yr-long dataset obtained with an idealized global mechanistic circulation model of the stratosphere and troposphere. After performing an empirical orthogonal function (EOF) analysis on the low-pass-filtered time series of the northern polar temperature, 10 647 PJO events are identified and classified into four groups. About 80% of them are two groups of warm events while the rest are two groups of cold events, which are newly identified variations with opposite sign from the warm events by the same EOF analysis. All of them show slow downward propagations of a positive or negative temperature anomaly, with a relatively short or long lifetime. Composite analysis with such a large number of samples shows that each group has its own typical relationship to unfiltered relatively fast variations in the polar stratosphere known as stratospheric sudden warming and polar vortex intensification and to the slow variation in the troposphere known as the Arctic Oscillation. Statistically significant evidence of the downward dynamical influence of PJO on the surface is obtained for a group of warm events with a longer lifetime.

scholarly journals Influence of the Madden–Julian Oscillation on the Arctic Oscillation Prediction in S2S Operational Models

2021 ◽  
Vol 9 ◽  
Author(s):  
Yang Zhou ◽  
Yang Wang
Keyword(s):  
Arctic Oscillation ◽  
Time Lag ◽  
Prediction Skill ◽  
The Arctic ◽  
Negative Phase ◽  
Initial Time ◽  
Madden Julian Oscillation ◽  
Global Circulation Models ◽  
The Arctic Oscillation ◽  
The Relationship

The connections between the Madden–Julian Oscillation (MJO) and the Arctic Oscillation (AO) are examined in both observations and model forecasts. In the observations, the time-lag composites are carried out for AO indices and anomalies of 1,000-hPa geopotential height after an active or inactive initial MJO. The results show that when the AO is in its positive (negative) phase at the initial time, the AO activity is generally enhanced (weakened) after an active MJO. Reforecast data of the 11 operational global circulation models from the Sub-seasonal to Seasonal (S2S) Prediction Project are further used to examine the relationship between MJO activity and AO prediction. When the AO is in its positive phase on the initial day of the S2S prediction, an initial active MJO can generally improve the AO prediction skill in most of the models. This is consistent with results found in the observations that a leading MJO can enhance the AO activity. However, when the AO is in its negative phase, the relationship between the MJO and AO prediction is not consistent among the 11 models. Only a few S2S models provide results that agree with the observations. Furthermore, the S2S prediction skill of the AO is examined in different MJO phases. There is a significantly positive relationship between the MJO-related AO activity and the AO prediction skill. When the AO activity is strong (weak) in an MJO phase, including the inactive MJO, the models tend to have a high (low) AO prediction skill. For example, no matter what phase the initial AO is in, the AO prediction skill is generally high in MJO phase 7, in which the AO activity is generally strong. Thus, the MJO is an important predictability source for the AO forecast in the S2S models.

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