Cloud, radiation, and surface heat flux simulations using Polar WRF with 3DVAR

2020 ◽  
Author(s):  
dae hui Kim ◽  
Hyun Mee Kim ◽  
Jinkyu Hong
Keyword(s):  
Heat Flux ◽  
Forecast Error ◽  
Arctic Region ◽  
Cold Start ◽  
Cloud Microphysics ◽  
Surface Radiation ◽  
The Arctic ◽  
Warm Start ◽  
Korea Meteorological Administration ◽  
The Arctic Region

<p>In the Arctic region, cloud is an important factor affecting surface radiation and heat flux. Despite the development of cloud microphysics schemes in the Polar WRF, clouds in the Arctic region still have uncertainties. In this study, the possibility of improving cloud simulations by using data assimilation (DA) and its effects on the enhancement of the forecast accuracy for surface fluxes and meteorological variables are evaluated. The experimental period is from 1 to 19 September 2017.</p><p>Forecasts from both the cold start experiment without DA and the warm start experiment with DA underestimated summer arctic clouds. When satellite radiances (AMSU-A and MHS) were assimilated at the analysis time, the distribution and quantity of water vapor were simulated more realistically, which results in the improvement of cloud simulations at the forecast time. As a result, the 25–30 hour forecast error of the downward shortwave (longwave) radiation flux in the warm start experiment which assimilated both conventional observations and satellite radiance data was reduced by 8.1% (12.7%), compared to that in the cold start experiment. The 25–30 hour forecast error of the upward latent (sensible) heat flux in the warm start experiment was also reduced by 7.8% (3.3%), compared to that in the cold start experiment. For the 2 m temperature and 10 m wind, the forecast error with DA was less than that without DA at almost all observation stations. More detailed results will be presented in the conference.</p><p><strong>Acknowledgments</strong></p><p>This work was supported by the Korea Polar Research Institute (KOPRI, PN20081) and the Korea Meteorological Administration Research and Development Program under grant KMI2018-03712. The simulations are mostly carried out by utilising the supercomputer system supported by the National Center for Meteorological Supercomputer of Korea Meteorological Administration (KMA).</p>

Nuclear icebreaker fleet and power supply on the basis of floating power units

2018 ◽  
Vol 35 (4) ◽  
pp. 110-113
Author(s):  
V. A. Tupchienko ◽  
H. G. Imanova
Keyword(s):  
Foreign Policy ◽  
Power Supply ◽  
Nuclear Power ◽  
Arctic Region ◽  
Nuclear Industry ◽  
The Arctic ◽  
Far North ◽  
The Arctic Region

The article deals with the problem of the development of the domestic nuclear icebreaker fleet in the context of the implementation of nuclear logistics in the Arctic. The paper analyzes the key achievements of the Russian nuclear industry, highlights the key areas of development of the nuclear sector in the Far North, and identifies aspects of the development of mechanisms to ensure access to energy on the basis of floating nuclear power units. It is found that Russia is currently a leader in the implementation of the nuclear aspect of foreign policy and in providing energy to the Arctic region.

Chemical Composition of Atmospheric Aerosol in the Arctic Region and Adjoining Seas along the Routes of Marine Expeditions in 2018–2019

2020 ◽  
Vol 33 (5) ◽  
pp. 480-489
Author(s):  
L. P. Golobokova ◽  
T. V. Khodzher ◽  
O. N. Izosimova ◽  
P. N. Zenkova ◽  
A. O. Pochyufarov ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Atmospheric Aerosol ◽  
Arctic Region ◽  
The Arctic ◽  
The Arctic Region

Estimating Friction Reduction ForCasing Operations in High-Angle Wells in The Arctic Region - A Russia Case History

2011 ◽  
Author(s):  
Chimerebere Onyekwere Nkwocha ◽  
Evgeny Glebov ◽  
Alexey Zhludov ◽  
Sergey Galantsev ◽  
David Kay
Keyword(s):  
Case History ◽  
Arctic Region ◽  
Friction Reduction ◽  
The Arctic ◽  
High Angle ◽  
The Arctic Region

scholarly journals Temperature and Relative Humidity Profile Retrieval from Fengyun-3D/HIRAS in the Arctic Region

2021 ◽  
Vol 13 (10) ◽  
pp. 1884
Author(s):  
Jingjing Hu ◽  
Yansong Bao ◽  
Jian Liu ◽  
Hui Liu ◽  
George P. Petropoulos ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Real Time ◽  
Wide Spectrum ◽  
Warm Season ◽  
Arctic Region ◽  
Cold Season ◽  
The Arctic ◽  
Practical Applications ◽  
A New Technique ◽  
The Arctic Region

The acquisition of real-time temperature and relative humidity (RH) profiles in the Arctic is of great significance for the study of the Arctic’s climate and Arctic scientific research. However, the operational algorithm of Fengyun-3D only takes into account areas within 60°N, the innovation of this work is that a new technique based on Neural Network (NN) algorithm was proposed, which can retrieve these parameters in real time from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS) observations in the Arctic region. Considering the difficulty of obtaining a large amount of actual observation (such as radiosonde) in the Arctic region, collocated ERA5 data from European Centre for Medium-Range Weather Forecasts (ECMWF) and HIRAS observations were used to train the neural networks (NNs). Brightness temperature and training targets were classified using two variables: season (warm season and cold season) and surface type (ocean and land). NNs-based retrievals were compared with ERA5 data and radiosonde observations (RAOBs) independent of the NN training sets. Results showed that (1) the NNs retrievals accuracy is generally higher on warm season and ocean; (2) the root-mean-square error (RMSE) of retrieved profiles is generally slightly higher in the RAOB comparisons than in the ERA5 comparisons, but the variation trend of errors with height is consistent; (3) the retrieved profiles by the NN method are closer to ERA5, comparing with the AIRS products. All the results demonstrated the potential value in time and space of NN algorithm in retrieving temperature and relative humidity profiles of the Arctic region from HIRAS observations under clear-sky conditions. As such, the proposed NN algorithm provides a valuable pathway for retrieving reliably temperature and RH profiles from HIRAS observations in the Arctic region, providing information of practical value in a wide spectrum of practical applications and research investigations alike.All in all, our work has important implications in broadening Fengyun-3D’s operational implementation range from within 60°N to the Arctic region.

scholarly journals Advancement into the Arctic Region for Bioactive Sponge Secondary Metabolites

Marine Drugs ◽  
2011 ◽  
Vol 9 (11) ◽  
pp. 2423-2437 ◽  
Author(s):  
Samuel Abbas ◽  
Michelle Kelly ◽  
John Bowling ◽  
James Sims ◽  
Amanda Waters ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Arctic Region ◽  
The Arctic ◽  
The Arctic Region

scholarly journals High-time resolved radon-progeny measurements in the Arctic region (Svalbard Islands, Norway): results and potentialities

2017 ◽  
Author(s):  
Roberto Salzano ◽  
Antonello Pasini ◽  
Antonietta Ianniello ◽  
Mauro Mazzola ◽  
Rita Traversi ◽  
...  
Keyword(s):  
Limit Of Detection ◽  
Atmospheric Stability ◽  
Arctic Region ◽  
Climatic Conditions ◽  
The Arctic ◽  
Radon Emanation ◽  
Radon Progeny ◽  
Time Resolved ◽  
Scientific Challenge ◽  
The Arctic Region

Abstract. The estimation of radon progeny in the Arctic region represents a scientific challenge due to the required low limit of detection in consideration of the limited radon emanation associated with permafrost dynamics. This preliminary study highlighted, for the first time, the possibility to monitor radon progeny in the Arctic region with a higher time resolution. The composition of the radon progeny offered the opportunity to identify air masses dominated by long-range transport, in presence or not of near-constant radon progeny instead of long and short lived progenies. Furthermore, the different ratio between radon and thoron progenies evidenced the contributions of local emissions and atmospheric stability. Two different emanation periods were defined in accordance to the permafrost dynamics at the ground and several accumulation windows were recognized coherently to the meteo-climatic conditions occurring at the study site.

Reliability Analysis of Offshore Production Facilities Under Arctic Conditions Using Reliability Data From Other Areas

2014 ◽  
Vol 136 (2) ◽  
Author(s):  
Abbas Barabadi
Keyword(s):  
Reliability Analysis ◽  
High Stress ◽  
Arctic Region ◽  
Accelerated Failure Time Model ◽  
The Arctic ◽  
Reliability Data ◽  
Essential Information ◽  
Offshore Production ◽  
The Arctic Region ◽  
Production Facilities

The development of offshore energy resources involves highly complex and extensive technological processes. Reliability evaluation of offshore production facilities provides essential information in the design and operation phase. Historical reliability data play an important role in reliability analysis, and as such data reflect the effect of influencing factors that production facilities have experienced during their life cycle. Due to there being less offshore activity in the Arctic region compared with other areas, there is a lack of data and little experience available regarding operational equipment. In contrast to the Arctic region, oil and gas companies have a lot of experience and information related to the design and operation of offshore production facilities in the other parts of the world. Using this type of data and information, collected from similar systems but under different operational conditions, in design processes for the Arctic region may lead to incorrect design. This may increase health, safety, and environmental (HSE) risk or operating and maintenance costs. This paper develops a methodology for the application of the accelerated failure time model (AFT) to predict the reliability of equipment to be used in the Arctic region based on the available data. In the methodology used here, the available data is assumed to reflect the behavior of the equipment under low stress conditions, and using the AFT models the reliability of equipment in the Arctic environment, which represents high stress, is predicted. An illustrative example is used to demonstrate how the methodology can be applied in a real case.

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