Projected changes in temperature and precipitation climatology of Central Asia CORDEX Region 8 by using RegCM4.3.5

Öztürk, Tuğba; Turp, M. Tufan; Türkeş, Murat; Kurnaz, M. Levent

doi:10.1016/j.atmosres.2016.09.008

Cited by 88 publications

(73 citation statements)

References 51 publications

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“…The findings proved by this study are quite similar with our study. Based on the Regional Climate Model RegCM4.3.5, Ozturk et al (2017) investigated the projected future changes in precipitation and temperature in Central Asia. For the future changes in precipitation, a decreasing trend is expected in most of the region of the period 2071-2100 relative to the reference period 1971-2000.…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal characteristics of future changes in precipitation and temperature in Central Asia

Luo

Meng

Duan

et al. 2018

Intl Journal of Climatology

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The arid and semi‐arid areas in Central Asia have scarce water resources and fragile ecosystems that are especially sensitive and vulnerable to climate change. Reliable information regarding future projections of change in climate is crucial for long‐term planning of water resources management and structural adjustment of agriculture in this region. However, the low‐density meteorological observation network brings great challenges for investigating the effects of climate variations. In this study, variations of precipitation and temperature in Central Asia were examined by a combination of gridded climate dataset of the Climate Research Unit and the latest general circulation models (GCMs) under a representative concentration pathway 4.5. Three downscaling methods, Delta, Advanced Delta, and Bayesian model averaging (BMA) methods, translate the coarse GCMs to local climatic variations for the period 2021–2060 relative to 1965–2004. Major results suggested that the Advanced Delta and BMA methods outperformed the Delta method in precipitation downscaling. Projected precipitation exhibited a general increasing trend at a rate of 4.63 mm/decade for entire Central Asia with strong spatiotemporal heterogeneity. While a declining trend was observed in the southwestern and central parts of Central Asia in summer. The projected temperature was revealed an obvious ascending at 0.37°C/decade, while the warming rate accelerated in higher latitude and mountainous areas. [Correction added on 03 December 2018, after first online publication: The preceding statement has been corrected in this version.] The surface land coverage had significant effects on the variations of precipitation and temperature, respectively. The driven factors of local climate were suggested by analysing the relationships between climate variations and large‐scale atmospheric circulation fields anomalies. The findings of this study aims to provide useful information to improve our understanding for future climate change and benefit local decision makers.

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Section: Discussionmentioning

confidence: 99%

Spatiotemporal characteristics of future changes in precipitation and temperature in Central Asia

Luo

Meng

Duan

et al. 2018

Intl Journal of Climatology

View full text Add to dashboard Cite

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“…While the predicted spatial patterns in their study were similar than presented here, our results suggest that the increase of precipitation at high elevations would be most pronounced during summer season ( Figure S5). In a recent study by Ozturk et al (2017) two GCMs (MPI-ESM-MR and HadGEM2-ES) were dynamically downscaled to Central Asian region using regional climate model (RegCM4.3.5). Their study demonstrated that even in case of two different climate models, the predicted rise of temperature can differ by several degrees when climate conditions are being estimated at the end of this century.…”

Section: Discussionmentioning

confidence: 99%

Features of Tajikistan's past and future climate

Aalto

Kämäräinen

Shodmonov³

et al. 2017

Intl Journal of Climatology

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Tajikistan is an exceptionally vulnerable Central Asian country in the face of climate change due to its' high exposure and sensitivity to climate change combined with poor adaptation capacity. Therefore, comprehensive climate data are needed for efficient planning of mitigation and adaptation. Here, the key spatio-temporal features of Tajikistan's climate were analysed based on historical data from 52 stations with the longest time-series covering nearly 80 years. In addition, bias-corrected CMIP5 climate models were used to simulate future temperature and precipitation conditions across a range of time periods and greenhouse gas emission scenarios. The results show that the mean annual temperatures have risen in Tajikistan since the 1930s, average rate of change being approximately 0.1 ∘ C decade −1 . For precipitation, only a weak signal of change could be detected. The high-resolution (30 arc seconds) spatial analyses reveal the strong control of topography on Tajikistan's climate with such coupling leading mean annual air temperatures to vary from −13.7 ∘ C (eastern mountain regions) to 17.3 ∘ C (low-altitude plains). Similarly, the mean annual precipitation vary from less than 50 mm to over 1000 mm, spring being the wettest of the seasons. The future climate simulations suggest drastic increase in air temperatures; at the end of this century the temperature multi-model mean can be approximately 2 ∘ C (Representative Concentration Pathways, RCP2.6) to 7 ∘ C (RCP8.5) higher compared to . Precipitation scenarios indicate increase in the eastern part of the country and decrease in the west. Finally, the applied spatial uncertainty analyses stress the need for the future development of the climate station network especially in high-elevation areas associated with complex topography. These results show the pronounced climatic variation in Tajikistan and the expected near-and long-term changes in air temperature and precipitation conditions, thus forming a sound basis for future planning of national mitigation and adaptation activities.

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“…It includes, almost entirely, two of the most important and populous countries: China and Russia. The region, despite being mainly characterized by arid and semi-arid climatic conditions, presents a wide variety of climatic zones, from the desert zones of the Gobi and the Arabian Peninsula, to the cold and dry areas of Siberia and the wet Northern Indian Monsoon region (Ozturk et al, 2017). Therefore, it offers the unique opportunity to test the model sensitivity to different climatic conditions at once.…”

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confidence: 99%

Sensitivity studies with the regional climate model COSMO-CLM 5.0 over the CORDEX Central Asia Domain

et al. 2019

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Due to its extension, geography and the presence of several underdeveloped or developing economies, the Central Asia domain of the Coordinated Regional Climate Downscaling Experiment (CORDEX) is one of the most vulnerable regions on Earth to the effects of climate changes. Reliable information on potential future changes with high spatial resolution acquire significant importance for the development of effective adaptation and mitigation strategies for the region. In this context, regional climate models (RCMs) play a fundamental role.In this paper, the results of a set of sensitivity experiments with the regional climate model COSMO-CLM version 5.0, for the Central Asia CORDEX domain, are presented. Starting from a reference model setup, general model performance is evaluated for the present day, testing the effects of singular changes in the model physical configuration and their mutual interaction with the simulation of monthly and seasonal values of three variables that are important for impact studies: near-surface temperature, precipitation and diurnal temperature range. The final goal of this study is twofold: having a general overview of model performance and its uncertainties for the considered region and determining at the same time an optimal model configuration.Results show that the model presents remarkable deficiencies over different areas of the domain. The combined change of the albedo, taking into consideration the ratio of forest fractions, and the soil conductivity, taking into account the ratio of liquid water and ice in the soil, allows one to achieve the best improvements in model performance in terms of cli-matological means. Importantly, the model seems to be particularly sensitive to those parameterizations that deal with soil and surface features, and that could positively affect the repartition of incoming radiation. The analyses also show that improvements in model performance are not achievable for all domain subregions and variables, and they are the result of a compensation effect in the different cases. The proposed better performing configuration in terms of mean climate leads to similar positive improvements when considering different observational data sets and boundary data employed to force the simulations. On the other hand, due to the large uncertainties in the variability estimates from observations, the use of different boundaries and the model internal variability, it has not been possible to rank the different simulations according to their representation of the monthly variability.This work is the first ever sensitivity study of an RCM for the CORDEX Central Asia domain and its results are of fundamental importance for further model development and for future climate projections over the area.

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Projected changes in temperature and precipitation climatology of Central Asia CORDEX Region 8 by using RegCM4.3.5

Cited by 88 publications

References 51 publications

Spatiotemporal characteristics of future changes in precipitation and temperature in Central Asia

Spatiotemporal characteristics of future changes in precipitation and temperature in Central Asia

Features of Tajikistan's past and future climate

Sensitivity studies with the regional climate model COSMO-CLM 5.0 over the CORDEX Central Asia Domain

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