74 research outputs found
Comparing the Performance of Two Road Weather Models in the Netherlands
High-quality road condition forecasts are a prerequisite for road authorities to ensure wintertime road safety. Harsh winter conditions can cause problems for traffic not only in countries where snowy winters are common but also in regions where the temperature drops below the freezing point occasionally. This study reports on the evaluation of the Royal Netherlands Meteorological Institute's (KNMI) new road weather forecasting model by comparing it with the Finnish Meteorological Institute's (FMI) road weather model, both run for 321 Dutch road weather stations, four times daily (0300, 0900, 1500, and 2100 UTC) during the test period, 15 January-28 February 2015. Road surface temperature forecasts by both models were evaluated against observations. The KNMI model produced slightly more accurate forecasts than the FMI model. The main reason for the difference is probably due to the optimization of the physical properties of the KNMI model for the Netherlands, whereas the FMI model is designed for quite different Finnish wintertime meteorological conditions. However, in general the road surface temperature forecasts were of quite comparable quality.Peer reviewe
Effect of a simulation-based workshop on multidisplinary teamwork of newborn emergencies : An intervention study Medical Education
Peer reviewe
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The WWRP Polar Prediction Project (PPP)
Mission statement: “Promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on time scales from hours to seasonal”. Increased economic, transportation and research activities in polar regions are leading to more demands for sustained and improved availability of predictive weather and climate information to support decision-making. However, partly as a result of a strong emphasis of previous international efforts on lower and middle latitudes, many gaps in weather, sub-seasonal and seasonal forecasting in polar regions hamper reliable decision making in the Arctic, Antarctic and possibly the middle latitudes as well.
In order to advance polar prediction capabilities, the WWRP Polar Prediction Project (PPP) has been established as one of three THORPEX (THe Observing System Research and Predictability EXperiment) legacy activities. The aim of PPP, a ten year endeavour (2013-2022), is to promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on hourly to seasonal time scales. In order to achieve its goals, PPP will enhance international and interdisciplinary collaboration through the development of strong linkages with related initiatives; strengthen linkages between academia, research institutions and operational forecasting centres; promote interactions and communication between research and stakeholders; and foster education and outreach.
Flagship research activities of PPP include sea ice prediction, polar-lower latitude linkages and the Year of Polar Prediction (YOPP) - an intensive observational, coupled modelling, service-oriented research and educational effort in the period mid-2017 to mid-2019
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Advancing polar prediction capabilities on daily to seasonal time scales
It is argued that existing polar prediction systems do not yet meet users’ needs; and possible ways forward in advancing prediction capacity in polar regions and beyond are outlined.
The polar regions have been attracting more and more attention in recent years, fuelled by the perceptible impacts of anthropogenic climate change. Polar climate change provides new opportunities, such as shorter shipping routes between Europe and East Asia, but also new risks such as the potential for industrial accidents or emergencies in ice-covered seas. Here, it is argued that environmental prediction systems for the polar regions are less developed than elsewhere. There are many reasons for this situation, including the polar regions being (historically) lower priority, with less in situ observations, and with numerous local physical processes that are less well-represented by models. By contrasting the relative importance of different physical processes in polar and lower latitudes, the need for a dedicated polar prediction effort is illustrated. Research priorities are identified that will help to advance environmental polar prediction capabilities. Examples include an improvement of the polar observing system; the use of coupled atmosphere-sea ice-ocean models, even for short-term prediction; and insight into polar-lower latitude linkages and their role for forecasting. Given the enormity of some of the challenges ahead, in a harsh and remote environment such as the polar regions, it is argued that rapid progress will only be possible with a coordinated international effort. More specifically, it is proposed to hold a Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 in which the international research and operational forecasting community will work together with stakeholders in a period of intensive observing, modelling, prediction, verification, user-engagement and educational activities
The Year of Polar Prediction
The Year of Polar Prediction (YOPP) has the mission to enable a significant improvement in environmental prediction capabilities for the polar regions and beyond, by coordinating a period of intensive observing, modelling, prediction, verification, user- engagement and education activities. The YOPP Core Phase will be from mid-2017 to mid-2019, flanked by a Preparation Phase and a Consolidation Phase. YOPP is a key component of the World Meteorological Organization – World Weather Research Programme (WMO-WWRP) Polar Prediction Project (PPP).
The objectives of YOPP are to:
1. Improve the existing polar observing system (better coverage, higher-quality
observations);
2. Gather additional observations through field programmes aimed at improving
understanding of key polar processes;
3. Develop improved representation of key polar processes in coupled (and
uncoupled) models used for prediction;
4. Develop improved (coupled) data assimilation systems accounting for challenges
in the polar regions such as sparseness of observational data;
5. Explore the predictability of the atmosphere-cryosphere-ocean system, with a
focus on sea ice, on time scales from days to seasons;
6. Improve understanding of linkages between polar regions and lower latitudes
and assess skill of models representing these linkages;
7. Improve verification of polar weather and environmental predictions to obtain
better quantitative knowledge on model performance, and on the skill, especially
for user-relevant parameters;
8. Demonstrate the benefits of using predictive information for a spectrum of user
types and services;
9. Provide training opportunities to generate a sound knowledge base (and its
transfer across generations) on polar prediction related issues.
The PPP Steering Group provides endorsement for projects that contribute to YOPP to enhance coordination, visibility, communication, and networking. This White Paper is based largely on the much more comprehensive YOPP Implementation Plan (WWRP/PPP No. 3 – 2014), but has an emphasis on Arctic observations
WWRP Polar Prediction Project Implementation Plan for the Year of Polar Prediction (YOPP)
The Year of Polar Prediction (YOPP) is planned for mid-2017 to mid-2019, centred on 2018. Its goal is to enable a significant improvement in environmental prediction capabilities for the polar regions and beyond, by coordinating a period of intensive observing, modelling, prediction, verification, user-engagement and education activities. With a focus on time scales from hours to a season, YOPP is a major initiative of the World Meteorological Organization’s World Weather Research Programme (WWRP) and a key component of the Polar Prediction Project (PPP). YOPP is being planned and coordinated by the PPP Steering Group together with representatives from partners and other initiatives, including the World Climate Research Programme’s Polar Climate Predictability Initiative (PCPI).
The objectives of YOPP are to:
1. Improve the existing polar observing system (enhanced coverage, higher-quality observations).
2. Gather additional observations through field programmes aimed at improving understanding of key polar processes.
3. Develop improved representation of key polar processes in (un)coupled models used for prediction.
4. Develop improved (coupled) data assimilation systems accounting for challenges in the polar regions such as sparseness of observational data.
5. Explore the predictability of the atmosphere-cryosphere-ocean system, with a focus on sea ice, on time scales from hours to a season.
6. Improve understanding of linkages between polar regions and lower latitudes, assess skill of models representing these linkages, and determine the impact of improved polar prediction on forecast skill in lower latitudes.
7. Improve verification of polar weather and environmental predictions to obtain better quantitative knowledge on model performance, and on the skill, especially for user- relevant parameters.
8. Identify various stakeholders and establish their decisionmaking needs with respect to weather, climate, ice, and related environmental services.
9. Assess the costs and benefits of using predictive information for a spectrum of users and services.
10. Provide training opportunities to generate a sound knowledge base (and its transfer across generations) on polar prediction related issues.
YOPP is implemented in three distinct phases. During the YOPP Preparation Phase (2013 through to mid-2017) this Implementation Plan was developed, which includes key outcomes of consultations with partners at the YOPP Summit in July 2015. Plans will be further developed and refined through focused international workshops. There will be engagement with stakeholders and arrangement of funding, coordination of observations and modelling activities, and preparatory research. During the YOPP Core Phase (mid-2017 to mid-2019), four elements will be staged: intensive observing periods for both hemispheres, a complementary intensive modelling and prediction period, a period of enhanced monitoring of forecast use in decisionmaking including verification, and a special educational effort. Finally, during the YOPP Consolidation Phase (mid-2019 to 2022) the legacy of data, science and publications will be organized.
The WWRP-PPP Steering Group provides endorsement throughout the YOPP phases for projects that contribute to YOPP. This process facilitates coordination and enhances visibility, communication, and networking
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