Oceanic transport of subpolar climate signals to mid-depth subtropical waters

Nature ◽  
10.1038/35356 ◽  
1998 ◽  
Vol 391 (6667) ◽  
pp. 575-577 ◽  
Author(s):  
Ruth G. Curry ◽  
Michael S. McCartney ◽  
Terrence M. Joyce
Keyword(s):  
Climate Signals ◽  
Oceanic Transport

The potential of oceanic transport and onshore leaching of additive-derived lead by marine macro-plastic debris

2016 ◽  
Vol 107 (1) ◽  
pp. 333-339 ◽  
Author(s):  
Etsuko Nakashima ◽  
Atsuhiko Isobe ◽  
Shin'ichiro Kako ◽  
Takaaki Itai ◽  
Shin Takahashi ◽  
...  
Keyword(s):  
Plastic Debris ◽  
Oceanic Transport

scholarly journals Impact of an observational time window on coupled data assimilation: simulation with a simple climate model

2017 ◽  
Vol 24 (4) ◽  
pp. 681-694 ◽  
Author(s):  
Yuxin Zhao ◽  
Xiong Deng ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Chang Liu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Climate Model ◽  
Time Window ◽  
Coupled Model ◽  
Circulation Model ◽  
Scale Interactions ◽  
Climate Signals ◽  
Coupled Data Assimilation ◽  
Climate Analysis

Abstract. Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.

scholarly journals Annually resolved climate signals in high-alpine ice cores

2014 ◽  
Vol 22 (1) ◽  
pp. 28-29 ◽  
Author(s):  
Margit Schwikowski ◽  
A Eichler ◽  
TM Jenk ◽  
I Mariani
Keyword(s):  
Ice Cores ◽  
Climate Signals
Sign in / Sign up

Export Citation Format

Share Document