IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v108y2021i1d10.1007_s11069-021-04711-y.html
   My bibliography  Save this article

Temperature trend analysis and extreme high temperature prediction based on weighted Markov Model in Lanzhou

Author

Listed:
  • Zhiqiang Pang

    (Lanzhou University of Finance and Economics)

  • Zhaoxu Wang

    (Lanzhou University of Finance and Economics
    Qinghai Normal University)

Abstract

In this study, temporal trend analysis was conducted on the annual and quarterly meteorological variables of Lanzhou from 1951 to 2016, and a weighted Markov model for extremely high temperature prediction was constructed. Several non-parametric methods were used to analyse the trend of meteorological variables. Considering that sequence autocorrelation may affect the accuracy of the trend test, we performed an autocorrelation test and carried out trend analysis for sequences with autocorrelation after removing correlation. The results show that the maximum temperature, minimum temperature and average temperature in Lanzhou all have a significant upward trend and show different performances in each season. In detail, the trend of maximum temperature in the summer is not significant, while the upward trend of minimum temperature in the winter is the most significant, which leads to more and more “warm winter” phenomenon. Finally, we construct a weighted Markov prediction model for extremely high temperature and obtain the conclusion that the prediction results by the model are consistent with the actual situation.

Suggested Citation

  • Zhiqiang Pang & Zhaoxu Wang, 2021. "Temperature trend analysis and extreme high temperature prediction based on weighted Markov Model in Lanzhou," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 891-906, August.
    • Handle: RePEc:spr:nathaz:v:108:y:2021:i:1:d:10.1007_s11069-021-04711-y
    DOI: 10.1007/s11069-021-04711-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-021-04711-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-021-04711-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. A. N. Pettitt, 1979. "A Non‐Parametric Approach to the Change‐Point Problem," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 28(2), pages 126-135, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stephen J. Déry & Marco A. Hernández-Henríquez & Tricia A. Stadnyk & Tara J. Troy, 2021. "Vanishing weekly hydropeaking cycles in American and Canadian rivers," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    2. Kazi Ali Tamaddun & Ajay Kalra & Sajjad Ahmad, 2019. "Spatiotemporal Variation in the Continental US Streamflow in Association with Large-Scale Climate Signals Across Multiple Spectral Bands," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(6), pages 1947-1968, April.
    3. Jie Yang & Yimin Wang & Jun Yao & Jianxia Chang & Guoxin Xu & Xin Wang & Hui Hu, 2020. "Coincidence probability analysis of hydrologic low-flow under the changing environment in the Wei River Basin," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(2), pages 1711-1726, September.
    4. Alina Bărbulescu & Cristian Ștefan Dumitriu, 2021. "On the Connection between the GEP Performances and the Time Series Properties," Mathematics, MDPI, vol. 9(16), pages 1-19, August.
    5. Alfredas Račkauskas & Martin Wendler, 2020. "Convergence of U-processes in Hölder spaces with application to robust detection of a changed segment," Statistical Papers, Springer, vol. 61(4), pages 1409-1435, August.
    6. Hsin-Yu Chen & Yu-Hsiang Hsu & Chia-Chi Huang & Hsin-Fu Yeh, 2023. "Baseflow Variation in Southern Taiwan Basin," Sustainability, MDPI, vol. 15(4), pages 1-23, February.
    7. Catherine Araujo Bonjean & Alioune N’diaye & Olivier Santoni, 2019. "Who benefits from the return of the rains? The case of the Ferlo breeders in Senegal [A qui profite le retour des pluies ? Le cas des éleveurs du Ferlo]," CERDI Working papers halshs-02419601, HAL.
    8. Roquia Salam & Abu Reza Md. Towfiqul Islam & Shakibul Islam, 2020. "Spatiotemporal distribution and prediction of groundwater level linked to ENSO teleconnection indices in the northwestern region of Bangladesh," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 4509-4535, June.
    9. Jing Xu & Ping Zhao & Johnny C. L. Chan & Mingyuan Shi & Chi Yang & Siyu Zhao & Ying Xu & Junming Chen & Ling Du & Jie Wu & Jiaxin Ye & Rui Xing & Huimei Wang & Lu Liu, 2024. "Increasing tropical cyclone intensity in the western North Pacific partly driven by warming Tibetan Plateau," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    10. Sanghyuk Yoo & Sangyong Jeon & Seunghwan Jeong & Heesoo Lee & Hosun Ryou & Taehyun Park & Yeonji Choi & Kyongjoo Oh, 2021. "Prediction of the Change Points in Stock Markets Using DAE-LSTM," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    11. Uilson Ricardo Venâncio Aires & Demetrius David Silva & Michel Castro Moreira & Carlos Antônio Alvares Soares Ribeiro & Celso Bandeira de Melo Ribeiro, 2020. "The Use of the Normalized Difference Vegetation Index to Analyze the Influence of Vegetation Cover Changes on the Streamflow in the Manhuaçu River Basin, Brazil," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 1933-1949, April.
    12. Joseph Ngatchou-Wandji & Echarif Elharfaoui & Michel Harel, 2022. "On change-points tests based on two-samples U-Statistics for weakly dependent observations," Statistical Papers, Springer, vol. 63(1), pages 287-316, February.
    13. Hsin-Yu Chen & Chia-Chi Huang & Hsin-Fu Yeh, 2021. "Quantifying the Relative Contribution of the Climate Change and Human Activity on Runoff in the Choshui River Alluvial Fan, Taiwan," Land, MDPI, vol. 10(8), pages 1-14, August.
    14. Xue Zhong & Xiaohui Jiang & Leilei Li & Jing Xu & Huanyu Xu, 2020. "The Impact of Socio-Economic Factors on Sediment Load: A Case Study of the Yanhe River Watershed," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
    15. Dario Camuffo & Antonio della Valle & Francesca Becherini & Valeria Zanini, 2020. "Three centuries of daily precipitation in Padua, Italy, 1713–2018: history, relocations, gaps, homogeneity and raw data," Climatic Change, Springer, vol. 162(2), pages 923-942, September.
    16. Ijaz Ahmad & Li Wang & Faisal Ali & Fan Zhang, 2022. "Spatiotemporal Patterns of Extreme Precipitation Events over Jhelum River Basin," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
    17. Yuke Zhou & Junfu Fan & Xiaoying Wang, 2020. "Assessment of varying changes of vegetation and the response to climatic factors using GIMMS NDVI3g on the Tibetan Plateau," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-25, June.
    18. Tweneboah Senzu, Emmanuel, 2020. "Modern currency exchange rate behaviour and proposed trend-like forecasting model," MPRA Paper 99933, University Library of Munich, Germany.
    19. Nathan C. Healey & Jennifer A. Rover, 2022. "Analyzing the Effects of Land Cover Change on the Water Balance for Case Study Watersheds in Different Forested Ecosystems in the USA," Land, MDPI, vol. 11(2), pages 1-43, February.
    20. Solomon Temidayo Owolabi & Johanes A. Belle & Sonwabo Mazinyo, 2022. "Quantifying Intra-Catchment Streamflow Processes and Response to Climate Change within a Climatic Transitional Zone: A Case Study of Buffalo Catchment, Eastern Cape, South Africa," Mathematics, MDPI, vol. 10(16), pages 1-20, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:108:y:2021:i:1:d:10.1007_s11069-021-04711-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.