| 1. |
- Cohen, Judah, et al.
(författare)
-
ARCTIC CHANGE AND POSSIBLE INFLUENCE ON MID-LATITUDE CLIMATE AND WEATHER - A US CLIVAR White Paper
- 2018
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The Arctic has warmed more than twice as fast as the global average since the mid 20th century, a phenomenon known as Arctic amplification (AA). These profound changes to the Arctic system have coincided with a period of ostensibly more frequent events of extreme weather across the Northern Hemisphere (NH) mid-latitudes, including extreme heat and rainfall events and recent severe winters. Though winter temperatures have generally warmed since 1960 over mid-to-high latitudes, the acceleration in the rate of warming at high-latitudes, relative to the rest of the NH, started approximately in 1990. Trends since 1990 show cooling over the NH continents, especially in Northern Eurasia. The possible link between Arctic change and mid-latitude climate and weather has spurred a rush of new observational and modeling studies. A number of workshops held during 2013-2014 have helped frame the problem and have called for continuing and enhancing efforts for improving our understanding of Arctic-mid-latitude linkages and its attribution to the occurrence of extreme climate and weather events. Although these workshops have outlined some of the major challenges and provided broad recommendations, further efforts are needed to synthesize the diversified research results to identify where community consensus and gaps exist. Building upon findings and recommendations of the previous workshops, the US CLIVAR Working Group on Arctic Change and Possible Influence on Mid-latitude Climate and Weather convened an international workshop at Georgetown University in Washington, DC, on February 1-3, 2017. Experts in the fields of atmosphere, ocean, and cryosphere sciences assembled to assess the rapidly evolving state of understanding, identify consensus on knowledge and gaps in research, and develop specific actions to accelerate progress within the research community. With more than 100 participants, the workshop was the largest and most comprehensive gathering of climate scientists to address the topic to date. In this white paper, we synthesize and discuss outcomes from this workshop and activities involving many of the working group members.
|
|
| 2. |
- Notz, Dirk, et al.
(författare)
-
Arctic Sea Ice in CMIP6
- 2020
-
Ingår i: Geophysical Research Letters. - 0094-8276 .- 1944-8007. ; 47:10
-
Tidskriftsartikel (refereegranskat)abstract
- We examine CMIP6 simulations of Arctic sea‐ice area and volume. We find that CMIP6 models produce a wide spread of mean Arctic sea‐ice area, capturing the observational estimate within the multimodel ensemble spread. The CMIP6 multimodel ensemble mean provides a more realistic estimate of the sensitivity of September Arctic sea‐ice area to a given amount of anthropogenic CO2 emissions and to a given amount of global warming, compared with earlier CMIP experiments. Still, most CMIP6 models fail to simulate at the same time a plausible evolution of sea‐ice area and of global mean surface temperature. In the vast majority of the available CMIP6 simulations, the Arctic Ocean becomes practically sea‐ice free (sea‐ice area <1 × 106 km2) in September for the first time before the Year 2050 in each of the four emission scenarios SSP1‐1.9, SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5 examined here.
|
|
| 3. |
- Ortega, Pablo, et al.
(författare)
-
Improving Arctic Weather and Seasonal Climate Prediction : Recommendations for Future Forecast Systems Evolution from the European Project APPLICATE
- 2022
-
Ingår i: Bulletin of The American Meteorological Society - (BAMS). - 0003-0007 .- 1520-0477. ; 103:10, s. E2203-E2213
-
Tidskriftsartikel (refereegranskat)abstract
- The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development.
|
|
| 4. |
|
|
| 5. |
- Sterl, Andreas, et al.
(författare)
-
A look at the ocean in the EC-Earth climate model
- 2012
-
Ingår i: Climate Dynamics. - : Springer Science and Business Media LLC. - 0930-7575 .- 1432-0894. ; 39:11, s. 2631-2657
-
Tidskriftsartikel (refereegranskat)abstract
- EC-Earth is a newly developed global climate system model. Its core components are the Integrated Forecast System (IFS) of the European Centre for Medium Range Weather Forecasts (ECMWF) as the atmosphere component and the Nucleus for European Modelling of the Ocean (NEMO) developed by Institute Pierre Simon Laplace (IPSL) as the ocean component. Both components are used with a horizontal resolution of roughly one degree. In this paper we describe the performance of NEMO in the coupled system by comparing model output with ocean observations. We concentrate on the surface ocean and mass transports. It appears that in general the model has a cold and fresh bias, but a much too warm Southern Ocean. While sea ice concentration and extent have realistic values, the ice tends to be too thick along the Siberian coast. Transports through important straits have realistic values, but generally are at the lower end of the range of observational estimates. Exceptions are very narrow straits (Gibraltar, Bering) which are too wide due to the limited resolution. Consequently the modelled transports through them are too high. The strength of the Atlantic meridional overturning circulation is also at the lower end of observational estimates. The interannual variability of key variables and correlations between them are realistic in size and pattern. This is especially true for the variability of surface temperature in the tropical Pacific (El Nio). Overall the ocean component of EC-Earth performs well and helps making EC-Earth a reliable climate model.
|
|
| 6. |
|
|
