11 research outputs found

    THE YEAR OF POLAR PREDICTION (YOPP): CHALLENGES AND OPPORTUNITIES IN ICE-OCEAN FORECASTING

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    In response to a growing interest in the Arctic in recent years, the number of real-time short-medium range sea ice prediction systems has been increasing, and now includes several systems covering the full Arctic Ocean, for example: the Arctic Cap Nowcast/Forecast System (ACNFS; Posey et al., 2010), Towards an Operational Prediction system for the North Atlantic European coastal Zones (TOPAZ; Bertino and Lisæter, 2008), and the Canadian Centre for Marine and Environmental Prediction’s Global Ice Ocean Prediction System (GIOPS; Smith et al., 2015) and Regional Ice Prediction System (RIPS; Lemieux et al., 2015; Buehner et al., 2013). In addition, numerous ice-ocean hindcasts1 and reanalyses have been made and intercompared through the Arctic Ocean Model Intercomparison Project (AOMIP; Johnson et al., 2007) and the CLIVAR Global Synthesis and Observations Panel (GSOP) Ocean Reanalysis Intercomparison Project (ORA-IP; Balmaseda et al., 2015). Despite this significant effort, it is difficult to ascertain the true skill of these prediction systems and their primary sources of error, as reliable observations are limited and verification techniques tend to vary from one group to another. As a result, the potential benefits of sea ice prediction for various user groups (e.g. national ice services, marine transportation and resource exploitation, coupling with numerical weather prediction) have been hindered by uncertainty regarding the skillfulness of predictions and how best to use them. An intercomparison of sea ice fields from existing systems by the GODAE Oceanview Intercomparison and Validation Task Team (www.godae.org) has been initiated, although a larger coordinated international effort is needed. The upcoming Year of Polar Prediction (YOPP) aims to address these challenges in the context of a broader initiative toward improved polar environmental predictions for both hemispheres

    Radiative forcing of the direct aerosol effect from AeroCom Phase II simulations

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    We report on the AeroCom Phase II direct aerosol effect (DAE) experiment where 16 detailed global aerosol models have been used to simulate the changes in the aerosol distribution over the industrial era. All 16 models have estimated the radiative forcing (RF) of the anthropogenic DAE, and have taken into account anthropogenic sulphate, black carbon (BC) and organic aerosols (OA) from fossil fuel, biofuel, and biomass burning emissions. In addition several models have simulated the DAE of anthropogenic nitrate and anthropogenic influenced secondary organic aerosols (SOA). The model simulated all-sky RF of the DAE from total anthropogenic aerosols has a range from −0.58 to −0.02Wm−2, with a mean of −0.27Wm−2 for the 16 models. Several models did not include nitrate or SOA and modifying the estimate by accounting for this with information from the other AeroCom models reduces the range and slightly strengthens the mean. Modifying the model estimates for missing aerosol components and for the time period 1750 to 2010 results in a mean RF for the DAE of −0.35Wm−2. Compared to AeroCom Phase I (Schulz et al., 2006) we find very similar spreads in both total DAE and aerosol component RF. However, the RF of the total DAE is stronger negative and RF from BC from fossil fuel and biofuel emissions are stronger positive in the present study than in the previous AeroCom study.We find a tendency for models having a strong (positive) BC RF to also have strong (negative) sulphate or OA RF. This relationship leads to smaller uncertainty in the total RF of the DAE compared to the RF of the sum of the individual aerosol components. The spread in results for the individual aerosol components is substantial, and can be divided into diversities in burden, mass extinction coefficient (MEC), and normalized RF with respect to AOD. We find that these three factors give similar contributions to the spread in results

    Interactions between the atmosphere, cryosphere, and ecosystems at northern high latitudes

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    Abstract The Nordic Centre of Excellence CRAICC (Cryosphere–Atmosphere Interactions in a Changing Arctic Climate), funded by NordForsk in the years 2011–2016, is the largest joint Nordic research and innovation initiative to date, aiming to strengthen research and innovation regarding climate change issues in the Nordic region. CRAICC gathered more than 100 scientists from all Nordic countries in a virtual centre with the objectives of identifying and quantifying the major processes controlling Arctic warming and related feedback mechanisms, outlining strategies to mitigate Arctic warming, and developing Nordic Earth system modelling with a focus on short-lived climate forcers (SLCFs), including natural and anthropogenic aerosols. The outcome of CRAICC is reflected in more than 150 peer-reviewed scientific publications, most of which are in the CRAICC special issue of the journal Atmospheric Chemistry and Physics. This paper presents an overview of the main scientific topics investigated in the centre and provides the reader with a state-of-the-art comprehensive summary of what has been achieved in CRAICC with links to the particular publications for further detail. Faced with a vast amount of scientific discovery, we do not claim to completely summarize the results from CRAICC within this paper, but rather concentrate here on the main results which are related to feedback loops in climate change–cryosphere interactions that affect Arctic amplification
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