Динамический даунскейлинг высокого разрешения исторических и будущих климатических проекций в Центральной Азии

Эркин Исаев ^{a,d *}, Акихико Мурата ^b, Шин Фукуи ^b, Рой К. Сидл ^a,c

^a Институт Исследований Горных Сообществ, Университет Центральной Азии, ул. Токтогула, 138, Бишкек, 720001, Кыргызская Республика

^b Институт Метеорологических Исследований, Японское Метеорологическое Агентство, 1-1 Нагаминэ, Цукуба, Ибараки, 305-0052, Япония

^c Институт Глобальных Инновационных Исследований, Токийский Университет Сельского Хозяйства и Технологий, Фучу, 7293212, Япония

^d Продовольственная и Сельскохозяйственная Организация ООН, Региональное Отделение для Азии и Тихого Океана, Бангкок,10700, Таиланд

https://doi.org/10.29258/CAJWR/2024-R1.v10-1/91-114.eng

*E-mail: erkiwa@gmail.com

Акихико Мурата: amurata@mri-jma.go.jp; Шин Фукуи: sfukui@mri-jma.go.jp; Рой К. Сидл: roy.sidle@ucentralasia.org

5 марта, 2024

Аннотация

Изменение климата ставит различные проблемы перед сельским хозяйством и практикой управления водными ресурсами в Центральной Азии (ЦА). Центральное место среди этих проблем занимают динамика криосферы, хрупкие горные экосистемы и текущие стихийные бедствия, что подчеркивает необходимость надежных прогнозов изменения регионального климата. Впервые в Центральной Азии был проведен динамический даунскейлинг с пространственным разрешением 5 км. В результате был получен региональный набор данных, включающий периоды с 1980 по 2000 год и с 2076 по 2096 год. Результаты показывают, что динамический даунскейлинг значительно улучшает моделирование температуры и осадков в ЦА по сравнению с моделями общей циркуляции (МОЦ) и другими региональными климатическими моделями (РКМ) за счет лучшего представления топографии и связанных с ней метеорологических полей. Наш анализ показывает, что в Центральной Азии будет наблюдаться значительная тенденция потепления с прогнозируемым увеличением на 6°C по сценарию SSP5-8.5 в период с 2076 по 2096 год. Ярко выраженное потепление наблюдается в горных районах ЦА с осени до весны, что может быть объяснено обратной связью снег-альбедо. Прогнозируется увеличение количества осадков с зимы до весны и уменьшение с лета до осени.

Доступно на английском

Скачать статью (анг)

Для цитирования:

Isaev, E., Murata, A., Fukui, Sh.,Sidle, R. (2024). High-resolution dynamic downscaling of historical and future climate projections over Central Asia. Central Asian Journal of Water Research,  10(1), 91-114. https://doi.org/10.29258/CAJWR/2024-R1.v10-1/91-114.eng

Список литературы

Aitaliev, A., Sakyev, D., Nazarkulov, K., Amanova, M., Brejneva, V., Spektorenko, N., Aidaraliev, N., Sataev, S., Jumanazarov, A., & Ymanbekov, K. (2020). Atlas of natural and man-made hazards on the territory of the Kyrgyz Republic. Ministry Emergency Situations Ministry. Kyrgyz Republic. https://mchs.gov.kg/ru/atlas/

Alexander, L. V., Zhang, X., Peterson, T. C., Caesar, J., Gleason, B., Klein Tank, A. M. G., Haylock, M., Collins, D., Trewin, B., Rahimzadeh, F., Tagipour, A., Rupa Kumar, K., Revadekar, J., Griffiths, G., Vincent, L., Stephenson, D. B., Burn, J., Aguilar, E., Brunet, M., … Vazquez-Aguirre, J. L. (2006). Global observed changes in daily climate extremes of temperature and precipitation. Journal of Geophysical Research: Atmospheres, 111(D5), 5109. https://doi.org/10.1029/2005JD006290

Bernauer, T., & Siegfried, T. (2012). Climate change and international water conflict in Central Asia. Http://Dx.Doi.Org/10.1177/0022343311425843, 49(1), 227–239. https://doi.org/10.1177/0022343311425843

Bruyère, C. L., Done, J. M., Holland, G. J., & Fredrick, S. (2014). Bias corrections of global models for regional climate simulations of high-impact weather. Climate Dynamics, 43, 1847–1856. https://doi.org/10.1007/s00382-013-2011-6

Chang, S., Isaev, E., Chen, H., Wu, B., Meng, J., Yan, N., & Ma, Z. (2024). Exploring the Linkages between Different Types of Drought and Their Impacts on Crop Production in Kyrgyzstan. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/JSTARS.2024.3359429

CHIRPS: Rainfall Estimates from Rain Gauge and Satellite Observations | Climate Hazards Center – UC Santa Barbara. (2022). https://www.chc.ucsb.edu/data/chirps

CMIP5 Data Search | CMIP5 | ESGF-CoG. (2022). https://esgf-node.llnl.gov/search/cmip5/

cmip6 Data Search | cmip6 | ESGF-CoG. (2022). https://esgf-node.llnl.gov/search/cmip6/

CORDEX-DKRZ Data Search | CORDEX-DKRZ | ESGF-CoG. (2022). https://esgf-data.dkrz.de/search/cordex-dkrz/

Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific Data 2015 2:1, 2(1), 1–21. https://doi.org/10.1038/sdata.2015.66

Gulakhmadov, A., Chen, X., Gulahmadov, N., Liu, T., Anjum, M. N., & Rizwan, M. (2020). Simulation of the Potential Impacts of Projected Climate Change on Streamflow in the Vakhsh River Basin in Central Asia under CMIP5 RCP Scenarios. Water 2020, Vol. 12, Page 1426, 12(5), 1426. https://doi.org/10.3390/W12051426

Harris, I., Osborn, T. J., Jones, P., & Lister, D. (2020). Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific Data 2020 7:1, 7(1), 1–18. https://doi.org/10.1038/s41597-020-0453-3

Hirai, M., & Oh’izumi, M. (2004). Development of a new landsurface model for JMA-GSM. Development of a New Landsurface Model for JMA-GSM. Extended Abstract of 20th Conference on Weather Analysis and Forecasting/16th Conference on NWP. P2.22.

Huang, A., Zhou, Y., Zhang, Y., Huang, D., Zhao, Y., & Wu, H. (2014). Changes of the annual precipitation over central Asia in the twenty-first century projected by multimodels of CMIP5. Journal of Climate, 27(17), 6627–6646. https://doi.org/10.1175/JCLI-D-14-00070.1

Iles, C. E., Vautard, R., Strachan, J., Joussaume, S., Eggen, B. R., & Hewitt, C. D. (2020). The benefits of increasing resolution in global and regional climate simulations for European climate extremes. Geoscientific Model Development, 13(11), 5583–5607. https://doi.org/10.5194/GMD-13-5583-2020

Immerzeel, W. W., Van Beek, L. P. H., & Bierkens, M. F. P. (2010). Climate change will affect the asian water towers. Science, 328(5984), 1382–1385. https://doi.org/10.1126/SCIENCE.1183188/SUPPL_FILE/IMMERZEEL.SOM.PDF

Isaev, E., Ajikeev, B., Shamyrkanov, U., Kalnur, K., Maisalbek, K., & Sidle, R. C. (2022). Impact of Climate Change and Air Pollution Forecasting Using Machine Learning Techniques in Bishkek. Aerosol and Air Quality Research, 22(3), 210336. https://doi.org/10.4209/AAQR.210336

Isaev, E., Ermanova, M., Sidle, R. C., Zaginaev, V., Kulikov, M., & Chontoev, D. (2022). Reconstruction of Hydrometeorological Data Using Dendrochronology and Machine Learning Approaches to Bias-Correct Climate Models in Northern Tien Shan, Kyrgyzstan. Water, 14(15), 2297. https://doi.org/10.3390/W14152297

Isaev, E. K., Aniskina, O. G., & Mostamandi, S. V. (2017). Investigation of sensitivity of the hydrodynamic modeling in an area with difficult terrain to the parameters of the planetary boundary layer. Works of Voeikov Main Geophysical Observatory, 584, 123–142. https://www.researchgate.net/publication/339042796_Investigation_of_sensitivity_of_the_hydrodynamic_modeling_in_an_area_with_difficult_terrain_to_the_parameters_of_the_planetary_boundary_layer

Isaev, E., Kulikov, M., Shibkov, E., & Sidle, R. C. (2022). Bias correction of Sentinel-2 with unmanned aerial vehicle multispectral data for use in monitoring walnut fruit forest in western Tien Shan, Kyrgyzstan. Https://Doi.Org/10.1117/1.JRS.17.022204, 17(2), 022204. https://doi.org/10.1117/1.JRS.17.022204

Isaev, E., & Omurzakova, S. (2019). On the possibility of drought detection and modeling in Kyrgyzstan (in Russian). Bulletin of the Kyrgyz- Russian Slavic University, 11, 172–176.

Iturbide, M., Bedia, J., Herrera, S., Baño-Medina, J., Fernández, J., Frías, M. D., Manzanas, R., San-Martín, D., Cimadevilla, E., Cofiño, A. S., & Gutiérrez, J. M. (2019). The R-based climate4R open framework for reproducible climate data access and post-processing. Environmental Modelling & Software, 111, 2–54. https://doi.org/https://doi.org/10.1016/j.envsoft.2018.09.009

Jiang, J., Zhou, T., Chen, X., & Zhang, L. (2020). Future changes in precipitation over Central Asia based on CMIP6 projections. Environmental Research Letters, 15(5). https://doi.org/10.1088/1748-9326/AB7D03

Kain, J., & Fritsch, M. (1990). A One-Dimensional Entraining/Detraining Plume Model and Its Application in Convective Parameterization . Journal of the Atmospheric Sciences, 47(23), 2784–2802. https://journals.ametsoc.org/view/journals/atsc/47/23/1520-0469_1990_047_2784_aodepm_2_0_co_2.xml

Kaplina, A., Olofinskaya, N., Kozomara, M., & Mills Janine, Twymanand Selenge, S. (2018). Climate Change adaptation in Europe and Central asia: Adapting to a changing climate for resilient development. https://www.adaptation-undp.org/sites/default/files/resources/climate_change_adaptation_in_europe_and_central_asia.pdf

Kastridis, A., Stathis, D., Sapountzis, M., & Theodosiou, G. (2022). Insect Outbreak and Long-Term Post-Fire Effects on Soil Erosion in Mediterranean Suburban Forest. Land 2022, Vol. 11, Page 911, 11(6), 911. https://doi.org/10.3390/LAND11060911

Kida, H., Koide, T., Sasaki, H., & Chiba, M. (1991). A new approach to coupling a limited area model with a GCM for regional climate simulations. J. Meteor. Soc. Japan, 69, 723–728.

Kitagawa, H. (2000). Radiation processes. Separate Volume of Annual Report of NPD, 46, 16-31 (in Japanese).

Li, J., Yu, R., Yuan, W., Chen, H., Sun, W., & Zhang, Y. (2015). Precipitation over East Asia simulated by NCAR CAM5 at different horizontal resolutions. J. Adv. Model. Earth Syst., 7, 774–790. https://doi.org/10.1002/2014MS000414

Li, L.-L., Li, J., & Yu, R. (2022). Evaluation of CMIP6 HighResMIP models in simulating precipitation over Central Asia. Advances in Climate Change Research, 13(1), 1–13. https://doi.org/https://doi.org/10.1016/j.accre.2021.09.009

Lin, Y. H., & Farley, R. D. (1983). Bulk parameterization of the snow field in a cloud model. J.Clim. Appl. Meteor., 22, 1065–1092.

Luo, Y., Wang, X., Piao, S., Sun, L., Ciais, P., Zhang, Y., Ma, C., Gan, R., & He, C. (2018). Contrasting streamflow regimes induced by melting glaciers across the Tien Shan – Pamir – North Karakoram. Scientific Reports 2018 8:1, 8(1), 1–9. https://doi.org/10.1038/s41598-018-34829-2

Manandhar, S., Xenarios, S., Schmidt-Vogt, D., Hergarten, C., & Foggin, M. (2018). Climate Vulnerability & Adaptive Capacity of Mountain Societies in Central Asia. https://ucentralasia.org/media/wygpwq22/web-no3-msri-research-paper.pdf

Mizuta, R., Yoshimura, H., Murakami, H., Matsueda, M., Endo, H., Ose, T., Kamiguchi, K., Hosaka, M., Sugi, M., Yukimoto, S., Kusunoki, S., & Kitoh, A. (2012). Climate Simulations Using MRI-AGCM3.2 with 20-km Grid. Journal of the Meteorological Society of Japan. Ser. II, 90A(A), 233–258. https://doi.org/10.2151/JMSJ.2012-A12

Murata, A., Sasaki, H., Kawase, H., & Nosaka, M. (2016). Evaluation of precipitation over an oceanic region of Japan in convection-permitting regional climate model simulations. Climate Dynamics 2016 48:5, 48(5), 1779–1792. https://doi.org/10.1007/S00382-016-3172-X

Murata, A., Sasaki, H., Kawase, H., Nosaka, M., Aoyagi, T., Oh’izumi, M., Seino, N., Shido, F., Hibino, K., Ishihara, K., Murai, H., Yasui, S., Wakamatsu, S., & Takayabu, I. (2017). Projection of Future Climate Change over Japan in Ensemble Simulations Using a Convection-Permitting Regional Climate Model with Urban Canopy. SOLA, 13, 219–223. https://doi.org/10.2151/SOLA.2017-040

Muratalieva, N. (2022). Climate change in CA. CABAR.Asia. https://cabar.asia/ru/izmenenie-klimata-v-tsentralnoj-azii-tochka-nevozvrata-projdena

Nakanishi, M., & Niino, H. (2004). An improved Mellor–Yamada level-3 model with condensation physics: Its design and verification. Bound. Layer Meteor., 112, 1–31.

Nakano, M., Kato, T., Hayashi, S., Kanada, S., Yamada, Y., & Kurihara, K. (2012). Development of a 5-km-Mesh Cloud-System-Resolving Regional Climate Model at the Meteorological Research Institute. Journal of the Meteorological Society of Japan. Ser. II, 90A(A), 339–350. https://doi.org/10.2151/JMSJ.2012-A19

Nowak, A., Nowak, S., Nobis, M., & Nobis, A. (2016). Vegetation of screes of the montane and colline zones in the Pamir-Alai Mts in Tajikistan (Middle Asia). Tuexenia, 36, 223–248. https://doi.org/10.14471/2016.36.001

Oh’izumi, M. (2014). Introduction of PBL schemes to iSiB submodel in NHRCM. Proc. of the Fall Conference of Meteor. Soc. of Japan (in Japanese), 172.

Ozturk, T., Turp, M. T., Türkeş, M., & Kurnaz, M. L. (2017). Projected changes in temperature and precipitation climatology of Central Asia CORDEX Region 8 by using RegCM4.3.5. Atmospheric Research, 183, 296–307. https://doi.org/10.1016/J.ATMOSRES.2016.09.008

Pachauri, R.K., Meyer, L. A. (2014). IPCC. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II, and III to the Fifth Assessment Report of the In-tergovernmental Panel on Climate Change;

Park, S., Lim, C. H., Kim, S. J., Isaev, E., Choi, S. E., Lee, S. D., & Lee, W. K. (2021). Assessing climate change impact on cropland suitability in kyrgyzstan: Where are potential high-quality cropland and the way to the future. Agronomy, 11(8). https://doi.org/10.3390/AGRONOMY11081490

Qiu, Y., Feng, J., Yan, Z., Wang, J., & Li, Z. (2021). High-resolution dynamical downscaling for regional climate projection in Central Asia based on bias-corrected multiple GCMs. Climate Dynamics 2021 58:3, 58(3), 777–791. https://doi.org/10.1007/S00382-021-05934-2

Qiu, Y., Hu, Q., & Zhang, C. (2017). WRF simulation and downscaling of local climate in Central Asia. International Journal of Climatology, 37, 513–528. https://doi.org/10.1002/JOC.5018

Rasmussen, R., Liu, C., Ikeda, K., Gochis, D., Yates, D., Chen, F., Tewari, M., Barlage, M., Dudhia, J., Yu, W., Miller, K., Arsenault, K., Grubišić, V., Thompson, G., & Gutmann, E. (2011). High-Resolution Coupled Climate Runoff Simulations of Seasonal Snowfall over Colorado: A Process Study of Current and Warmer Climate. Journal of Climate, 24(12), 3015–3048. https://doi.org/10.1175/2010JCLI3985.1

Russo, E., Kirchner, I., Pfahl, S., Schaap, M., & Cubasch, U. (2019). Sensitivity studies with the regional climate model COSMO-CLM 5.0 over the CORDEX Central Asia Domain. Geoscientific Model Development, 12(12), 5229–5249. https://doi.org/10.5194/GMD-12-5229-2019

Russo, E., Lund Sørland, S., Kirchner, I., Schaap, M., Raible, C. C., & Cubasch, U. (2020). Exploring the parameter space of the COSMO-CLM v5.0 regional climate model for the Central Asia CORDEX domain. Geoscientific Model Development, 13(11), 5779–5797. https://doi.org/10.5194/GMD-13-5779-2020

Saito, K., Fujita, T., Yamada, Y., Ishida, J. I., Kumagai, Y., Aranami, K., Ohmori, S., Nagasawa, R., Kumagai, S., Muroi, C., Kato, T., Eito, H., & Yamazaki, Y. (2006). The Operational JMA Nonhydrostatic Mesoscale Model. Monthly Weather Review, 134(4), 1266–1298. https://doi.org/10.1175/MWR3120.1

Saito, K., Ishida, J. I., Aranami, K., Hara, T., Segawa, T., Narita, M., & Honda, Y. (2007). Nonhydrostatic Atmospheric Models and Operational Development at JMA. Journal of the Meteorological Society of Japan. Ser. II, 85B, 271–304. https://doi.org/10.2151/JMSJ.85B.271

Sasaki, H., Kurihara, K., Takayabu, I., & Uchiyama, T. (2008). Preliminary Experiments of Reproducing the Present Climate Using the Non-hydrostatic Regional Climate Model. SOLA, 4, 25–28. https://doi.org/10.2151/SOLA.2008-007

Sasaki, H., Sato, Y., Adachi, K., & Kida, H. (2000). Performance and evaluation of the MRI regional climate model with the spectral boundary coupling method. J. Meteor. Soc. Japan, 78, 477–489.

Sillmann, J., Kharin, V. V., Zwiers, F. W., Zhang, X., & Bronaugh, D. (2013). Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. Journal of Geophysical Research: Atmospheres, 118(6), 2473–2493. https://doi.org/10.1002/JGRD.50188

Ta, Z., Yu, Y., Sun, L., Chen, X., Mu, G., & Yu, R. (2018). Assessment of precipitation simulations in Central Asia by CMIP5 climate models. Water (Switzerland), 10(11). https://doi.org/10.3390/W10111516

Vakulchuk, R., Daloz, A. S., Overland, I., Sagbakken, H. F., & Standal, K. (2022). A void in Central Asia research: climate change. Https://Doi.Org/10.1080/02634937.2022.2059447, 1–20. https://doi.org/10.1080/02634937.2022.2059447

Wang, Q., Yi, S., & Sun, W. (2017). Precipitation-driven glacier changes in the Pamir and Hindu Kush mountains. Geophysical Research Letters, 44(6), 2817–2824. https://doi.org/10.1002/2017GL072646

Wang, X., Chen, Y., Li, Z., Fang, G., Wang, F., & Hao, H. (2021). Water resources management and dynamic changes in water politics in the transboundary river basins of Central Asia. Hydrol. Earth Syst. Sci., 25, 3281–3299. https://doi.org/https://doi.org/10.5194/hess-25-3281-2021

Wang, Y., Feng, J., Luo, M., Wang, J., & Qiu, Y. (2020). Uncertainties in simulating central Asia: Sensitivity to physical parameterizations using Weather Research and Forecasting model. International Journal of Climatology, 40(14), 5813–5828. https://doi.org/10.1002/JOC.6567

Wehner, M. (2013). Methods of projecting future changes in extremes. Water Sci. Technol. Libr., 65, 223–237.

Yabu, S., Murai, S., & Kitagawa, H. (2005). Clear sky radiation scheme. Separate Volume of Annual Report of NPD, 51, 53-64 (in Japanese).

Yonehara, H., Tokuhiro, T., Nagasawa, R., Ujiie, M., Shimokobe, A., Nakagawa, M., Sekiguchi, R., Kanehama, T., Sato, H., & Saito, K. (2017). Upgrade of parameterization schemes in JMA’s operational global NWP model. In WGNE Research Activities in Atmospheric and Oceanic Modelling (pp. 17–18). CAS/JSC Working Group on Numerical Experimentation.

Zeng, X. M., Wang, M., Zhang, Y., Wang, Y., & Zheng, Y. (2016). Assessing the Effects of Spatial Resolution on Regional Climate Model Simulated Summer Temperature and Precipitation in China: A Case Study. Advances in Meteorology, 2016. https://doi.org/10.1155/2016/7639567

Zhu, X., Wei, Z., Dong, W., Ji, Z., Wen, X., Zheng, Z., Yan, D., & Chen, D. (2020). Dynamical downscaling simulation and projection for mean and extreme temperature and precipitation over central Asia. Climate Dynamics, 54(7–8), 3279–3306. https://doi.org/10.1007/S00382-020-05170-0