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Future Extreme Climate Prediction in Western Jilin Province Based on Statistical DownScaling Model: International Geoscience and Remote Sensing Symposium (IGARSS)

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Future Extreme Climate Prediction in Western Jilin Province Based on Statistical DownScaling Model: International Geoscience and Remote Sensing Symposium (IGARSS). / Zhang, P.; Yin, D.; Atkinson, P.M.
2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings. IEEE, 2019. p. 9886-9889.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Zhang, P, Yin, D & Atkinson, PM 2019, Future Extreme Climate Prediction in Western Jilin Province Based on Statistical DownScaling Model: International Geoscience and Remote Sensing Symposium (IGARSS). in 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings. IEEE, pp. 9886-9889. https://doi.org/10.1109/IGARSS.2019.8898108

APA

Zhang, P., Yin, D., & Atkinson, P. M. (2019). Future Extreme Climate Prediction in Western Jilin Province Based on Statistical DownScaling Model: International Geoscience and Remote Sensing Symposium (IGARSS). In 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings (pp. 9886-9889). IEEE. https://doi.org/10.1109/IGARSS.2019.8898108

Vancouver

Zhang P, Yin D, Atkinson PM. Future Extreme Climate Prediction in Western Jilin Province Based on Statistical DownScaling Model: International Geoscience and Remote Sensing Symposium (IGARSS). In 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings. IEEE. 2019. p. 9886-9889 Epub 2019 Jul 28. doi: 10.1109/IGARSS.2019.8898108

Author

Zhang, P. ; Yin, D. ; Atkinson, P.M. / Future Extreme Climate Prediction in Western Jilin Province Based on Statistical DownScaling Model : International Geoscience and Remote Sensing Symposium (IGARSS). 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings. IEEE, 2019. pp. 9886-9889

Bibtex

@inproceedings{fe55dd0eed8a4acbbdb5b72f1126fcad,
title = "Future Extreme Climate Prediction in Western Jilin Province Based on Statistical DownScaling Model: International Geoscience and Remote Sensing Symposium (IGARSS)",
abstract = "Based on the measured data of 12 meteorological stations in western Jilin province from 1961 to 2017, the prediction factors of NCEP reanalysis data were selected through correlation analysis. Combined with the global climate model HadCM3 data in the two scenarios of A2 and B2, the Statistical DownScaling Model (SDSM) for western Jilin province was established. By means of SDSM, this study simulated the changes of temperature, precipitation and eight climate extreme indices (SU25, FD0, CDD, CWD, TXn, TNn, TXx and TNx in western Jilin province in the four periods (2030s, 2050s, 2070s and 2090s). In the two scenarios of A2 and B2, the interannual temperature increases in western Jilin province would be 1-5 °C and 1.5-4 °C respectively. In the A2 scenario, SU25 would increase by 3-9 days and FD0 would decrease by 10-18 days. In the B2 scenario, SU25 would increase by 3-7 days and FD0 would decrease by 9-14 days. Under the both A2 and B2 scenarios, six indices (SU25, CWD, TNn, TXn, TNx and TXx) would increase obviously, while the other two indices (CDD and FD0) would decrease. Under the scenario B2, the increase of eight climate extreme indices in western Jilin province would be less than those under the scenario A2.",
author = "P. Zhang and D. Yin and P.M. Atkinson",
year = "2019",
month = nov,
day = "14",
doi = "10.1109/IGARSS.2019.8898108",
language = "English",
isbn = "9781538691557",
pages = "9886--9889",
booktitle = "2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Future Extreme Climate Prediction in Western Jilin Province Based on Statistical DownScaling Model

T2 - International Geoscience and Remote Sensing Symposium (IGARSS)

AU - Zhang, P.

AU - Yin, D.

AU - Atkinson, P.M.

PY - 2019/11/14

Y1 - 2019/11/14

N2 - Based on the measured data of 12 meteorological stations in western Jilin province from 1961 to 2017, the prediction factors of NCEP reanalysis data were selected through correlation analysis. Combined with the global climate model HadCM3 data in the two scenarios of A2 and B2, the Statistical DownScaling Model (SDSM) for western Jilin province was established. By means of SDSM, this study simulated the changes of temperature, precipitation and eight climate extreme indices (SU25, FD0, CDD, CWD, TXn, TNn, TXx and TNx in western Jilin province in the four periods (2030s, 2050s, 2070s and 2090s). In the two scenarios of A2 and B2, the interannual temperature increases in western Jilin province would be 1-5 °C and 1.5-4 °C respectively. In the A2 scenario, SU25 would increase by 3-9 days and FD0 would decrease by 10-18 days. In the B2 scenario, SU25 would increase by 3-7 days and FD0 would decrease by 9-14 days. Under the both A2 and B2 scenarios, six indices (SU25, CWD, TNn, TXn, TNx and TXx) would increase obviously, while the other two indices (CDD and FD0) would decrease. Under the scenario B2, the increase of eight climate extreme indices in western Jilin province would be less than those under the scenario A2.

AB - Based on the measured data of 12 meteorological stations in western Jilin province from 1961 to 2017, the prediction factors of NCEP reanalysis data were selected through correlation analysis. Combined with the global climate model HadCM3 data in the two scenarios of A2 and B2, the Statistical DownScaling Model (SDSM) for western Jilin province was established. By means of SDSM, this study simulated the changes of temperature, precipitation and eight climate extreme indices (SU25, FD0, CDD, CWD, TXn, TNn, TXx and TNx in western Jilin province in the four periods (2030s, 2050s, 2070s and 2090s). In the two scenarios of A2 and B2, the interannual temperature increases in western Jilin province would be 1-5 °C and 1.5-4 °C respectively. In the A2 scenario, SU25 would increase by 3-9 days and FD0 would decrease by 10-18 days. In the B2 scenario, SU25 would increase by 3-7 days and FD0 would decrease by 9-14 days. Under the both A2 and B2 scenarios, six indices (SU25, CWD, TNn, TXn, TNx and TXx) would increase obviously, while the other two indices (CDD and FD0) would decrease. Under the scenario B2, the increase of eight climate extreme indices in western Jilin province would be less than those under the scenario A2.

U2 - 10.1109/IGARSS.2019.8898108

DO - 10.1109/IGARSS.2019.8898108

M3 - Conference contribution/Paper

SN - 9781538691557

SP - 9886

EP - 9889

BT - 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings

PB - IEEE

ER -