リケラボ論文検索は、全国の大学リポジトリにある学位論文・教授論文を一括検索できる論文検索サービスです。

リケラボ 全国の大学リポジトリにある学位論文・教授論文を一括検索するならリケラボ論文検索大学・研究所にある論文を検索できる

リケラボ 全国の大学リポジトリにある学位論文・教授論文を一括検索するならリケラボ論文検索大学・研究所にある論文を検索できる

大学・研究所にある論文を検索できる 「Statistical characteristics of Arctic forecast busts and their relationship to Arctic weather patterns in summer」の論文概要。リケラボ論文検索は、全国の大学リポジトリにある学位論文・教授論文を一括検索できる論文検索サービスです。

コピーが完了しました

URLをコピーしました

論文の公開元へ論文の公開元へ
書き出し

Statistical characteristics of Arctic forecast busts and their relationship to Arctic weather patterns in summer

Yamagami, Akio 松枝, 未遠 筑波大学

2022.02.08

概要

Recently, human activity in the Arctic region, such as trans-Arctic shipping, has increased due to the reduction in Arctic sea ice. Accurate weather forecasts will become increasingly important as the level of human activity in the Arctic continues to increase. Operational numerical weather predictions (NWPs) have been improved considerably over recent decades; however, they still occa- sionally generate large forecast errors referred to as “forecast busts.” This study investigates forecast busts over the Arctic between 2008 and 2019 using opera- tional forecasts from five leading NWP centers. Forecasts with an anomaly cor- relation coefficient below its climatological 10th percentile, and a root-mean- square error above its 90th percentile at a lead time of 144 hr, are regarded as “busts.” The occurrence frequency of forecast busts decreased from 2008 (13–7%) to 2012 and was between 2 and 6% for the period 2012–2019. Arctic fore- cast busts were most frequent in the May and July–September periods (~6 to 7%), but less frequent between December and March (~4%). The summertime forecast bust occurred more frequently when the initial pattern was the Green- land Blocking (GB) or Arctic Cyclone (AC) pattern rather than one of the other patterns. Some busts occurred without the weather pattern transition (~22 to 40%), but the others occurred with the pattern transition. These results help users to be careful when they use the forecasts initialized on GB and AC patterns.

この論文で使われている画像

参考文献

Bauer, P., Thorpe, A. and Brunet, G. (2015) The quiet revolution of numerical weather prediction. Nature, 525, 47–55. https://doi.org/10.1038/nature14956.

Bauer, P., Magnusson, L., Thépaut, J.N. and Hamill, T.M. (2016) Aspects of ECMWF model performance in polar areas. Quar- terly Journal of the Royal Meteorological Society, 142, 583–596. https://doi.org/10.1002/qj.2449.

Day, J.J., Sandu, I., Magnusson, L., Rodwell, M.J., Lawrence, H., Bormann, N. and Jung, T. (2019) Increased Arctic influence on the midlatitude flow during Scandinavian Blocking episodes. Quarterly Journal of the Royal Meteorological Society, 145, 3846– 3862. https://doi.org/10.1002/qj.3673.

Eguíluz, V.M., Fernández-Gracia, J., Irigoien, X. and Duarte, C.M. (2016) A quantitative assessment of Arctic shipping in 2010– 2014. Nature Scientific Reports, 6, 30682. https://doi.org/10. 1038/srep30682.

Grams, C.M., Magnusson, L. and Madonna, E. (2018) An atmo- spheric dynamics perspective on the amplification and propa- gation of forecast error in numerical weather prediction models: a case study. Quarterly Journal of the Royal Meteorologi- cal Society, 144, 2577–2591. https://doi.org/10.1002/qj.3353.

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S. and Thépaut, J. (2020) The ERA5 Global Reanalysis. Quarterly Jour- nal of the Royal Meteorological Society, 146, 1999–2049. https://doi.org/10.1002/qj.3803.

Jung, T. and Matsueda, M. (2016) Verification of global numerical weather forecasting systems in polar regions using TIGGE data. Quarterly Journal of the Royal Meteorological Society, 142, 574–582. https://doi.org/10.1002/qj.2437.

Jung, T., Kasper, M.A., Semmler, T. and Serrar, S. (2014) Arctic influ- ence on subseasonal midlatitude prediction. Geophysical Research Letters, 41, 3676–3680. https://doi.org/10.1002/2014GL059961.

Jung, T., Gordon, N.D., Bauer, P., Bromwich, D.H., Chevallier, M., Day, J.J., Dawson, J., Doblas-Reyes, F., Fairall, C., Goessling, H.F., Holland, M., Inoue, J., Iversen, T., Klebe, S., Lemke, P., Losch, M., Makshtas, A., Mills, B., Nurmi, P., Perovich, D., Reid, P., Renfrew, I.A., Smith, G., Svensson, G., Tolstykh, M. and Yang, Q. (2016) Advancing polar prediction capabilities on daily to seasonal time scales. Bulletin of the American Meteorological Society, 97, 1631–1647. https://doi.org/ 10.1175/BAMS-D-14-00246.1.

Lawrence, H., Bormann, N., Sandu, I., Day, J., Farnan, J. and Bauer, P. (2019) Use and impact of Arctic observations in the ECMWF Numerical Weather Prediction system. Quarterly Jour- nal of the Royal Meteorological Society, 145, 3432–3454. https://doi.org/10.1002/qj.3628.

Lillo, S.P. and Parsons, D.B. (2017) Investigating the dynamics of error growth in ECMWF medium-range forecast busts. Quar- terly Journal of the Royal Meteorological Society, 143, 1211–1226. https://doi.org/10.1002/qj.2938.

Magnusson, L. (2017) Diagnostic methods for understanding the origin of forecast errors. Quarterly Journal of the Royal Meteoro-logical Society, 143, 2129–2142. https://doi.org/10.1002/qj.3072.

Matsueda, M. and Kyouda, M. (2016) Wintertime East Asian flow patterns and their predictability on medium-range timescales. SOLA, 12, 121–126. https://doi.org/10.2151/sola.2016-027.

Matsueda, M. and Palmer, T.N. (2018) Estimates of flow-dependent predictability of wintertime Euro-Atlantic weather regimes in medium-range forecasts. Quarterly Journal of the Royal Meteoro- logical Society, 144, 1012–1027. https://doi.org/10.1002/qj.3265.

Matsueda, M. and Tanaka, H.L. (2008) Can MCGE outperform the ECMWF ensemble? SOLA, 4, 77–80. https://doi.org/10.2151/sola.2008-020.

Melia, N., Haines, K. and Hawkins, E. (2016) Sea ice decline and 21st century trans-Arctic shipping routes. Geophysical Research Letters, 43, 9720–9728. https://doi.org/10.1002/2016GL069315.

Nakanowatari, T., Inoue, J., Sato, K., Bertino, L., Xie, J., Matsueda, M., Yamagami, A., Sugimura, T., Yabuki, H. and Otsuka, N. (2018) Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea based on the TOPAZ4 ice-ocean data assimilation system. Cryosphere, 12, 2005–2020. https://doi.org/10.5194/tc-12-2005-2018.

Parsons, D.B., Lillo, S.P., Rattray, C.P., Bechtold, P., Rodwell, M.J. and Bruce, C.M. (2019) The role of continental mesoscale convective systems in forecast busts within global weather prediction sys- tems. Atmosphere, 10, 1–32. https://doi.org/10.3390/atmos10110681.

Rodwell, M.J., Magnusson, L., Bauer, P., Bechtold, P., Bonavita, M., Cardinali, C., Diamantakis, M., Earnshaw, P., Garcia- Mendez, A., Isaksen, L., Källén, E., Klocke, D., Lopez, P., McNally, T., Persson, A., Prates, F. and Wedi, N. (2013) Charac- teristics of occasional poor medium-range weather forecasts for Europe. Bulletin of the American Meteorological Society, 94, 1393–1405. https://doi.org/10.1175/BAMS-D-12-00099.1.

Sato, K., Inoue, J., Yamazaki, A., Kim, J.H., Makshtas, A., Kustov, V., Maturilli, M. and Dethloff, K. (2018) Impact on pre- dictability of tropical and mid-latitude cyclones by extra Arctic observations. Scientific Reports, 8, 12104. https://doi.org/10. 1038/s41598-018-30594-4

Simmonds, I. and Rudeva, I. (2012) The great Arctic cyclone of August 2012. Geophysical Research Letters, 39, L23709. https://doi.org/10.1029/2012GL054259.

Swinbank, R., Kyouda, M., Buchanan, P., Froude, L., Hamill, T.M., Hewson, T.D., Keller, J.H., Matsueda, M., Methven, J., Pappenberger, F., Scheuerer, M., Titley, H.A., Wilson, L. and Yamaguchi, M. (2016) The TIGGE project and its achieve- ments. Bulletin of the American Meteorological Society, 97, 49–67. https://doi.org/10.1175/BAMS-D-13-00191.1.

Wilks, D.S. (2019) Statistical Methods in the Atmospheric Sciences, 4th edition. Oxford: Elsevier Academic Press.

Yamagami, A., Matsueda, M. and Tanaka, H.L. (2017) Extreme Arc- tic cyclone in August 2016. Atmospheric Science Letters, 18, 307–314. https://doi.org/10.1002/asl.757.

Yamagami, A., Matsueda, M. and Tanaka, H.L. (2018a) Predictabil- ity of the 2012 great Arctic cyclone on medium-range time- scales. Polar Science, 15, 13–23. https://doi.org/10.1016/j.polar.2018.01.002.

Yamagami, A., Matsueda, M. and Tanaka, H.L. (2018b) Medium- range forecast skill for extraordinary Arctic cyclones in summer of 2008–2016. Geophysical Research Letters, 45, 4429–4437. https://doi.org/10.1029/2018GL077278.

Yamagami, A., Matsueda, M. and Tanaka, H.L. (2019) Skill of medium-range reforecast for summertime extraordinary Arctic cyclones in 1986–2016. Polar Science, 20, 107–116. https://doi. org/10.1016/j.polar.2019.02.003.

Yamazaki, A., Inoue, J., Dethloff, K., Maturilli, M. and König- Langlo, G. (2015) Impact of radiosonde observations on fore- casting summertime Arctic cyclone formation. Journal of Geo- physical Research: Atmospheres, 120, 3249–3273. https://doi.org/10.1002/2014JD022925.

参考文献をもっと見る

全国の大学の
卒論・修論・学位論文

一発検索!

この論文の関連論文を見る