Multi-Model Projections of Climate Change in Different RCP Scenarios in an Arid Inland Region, Northwest China

Abstract

Based on three IPCC (Intergovernmental Panel on Climate Change) Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5), observed meteorological data, ERA-40 reanalysis data, and five preferred GCM (general circulation model) outputs selected from 23 GCMs of CMIP5 (Phase 5 of the Coupled Model Intercomparison Project), climate change scenarios including daily precipitation, maximum air temperature, and minimum air temperature from 2021 to 2050 in the Heihe River basin, which is the second largest inland river basin in Northwest China, were generated by constructing a statistical downscaling model (SDSM). Results showed that the SDSM had a good prediction capacity for the air temperature in the Heihe River basin. During the calibration and validation periods from 1961 to 1990 and from 1991 to 2000, respectively, the coefficient of determination (R2) and the Nash–Sutcliffe efficiency coefficient (NSE) were both larger than 0.9, while the root mean square error (RMSE) was within 20%. However, the SDSM showed a relative lower simulation efficiency for precipitation, with R2 and NSE values of most meteorological stations reaching 0.5, except for stations located in the downstream desert areas. Compared with the baseline period (1976–2005), changes in the annual mean precipitation simulated by different GCMs during 2021–2050 showed great difference in the three RCP scenarios, fluctuating from −10 to +10%, which became much more significant at seasonal and monthly time scales, except for the consistent decreasing trend in summer and increasing trend in spring. However, the maximum and minimum air temperature exhibited a similar increasing tendency during 2021–2050 in all RCP scenarios, with a higher increase in maximum air temperature, which increased as the CO2 concentration of the RCP scenarios increased. The results could provide scientific reference for sustainable agricultural production and water resources management in arid inland areas subject to climate change.

A controlled field experiment to investigate the deterioration of earthen heritage by wind and rain

“…However, in north west China the magnitude and frequency of wind and rain events have varied over decadal to centurial timescales [41][42][43]. Under future climate projections, wind speeds and annual rainfall are predicted to increase in northwest China [44][45][46][47], suggesting that rates of deterioration at sites such as Suoyang are likely also to increase. Figure 6 conceptually shows the current frequency and magnitude of clean wind, sediment laden wind and driving rain events at Suoyang but could also be modified to be applied to other earthen heritage sites in semi-arid areas.…”

Water Productivity Evaluation under Multi-GCM Projections of Climate Change in Oases of the Heihe River Basin, Northwest China

“…at stabilization after 2100 and the rising radiative forcing pathway leading to 8.5 W/m 2 (around 1370 ppm CO 2 eq) by 2100 [41]. Detailed information of the 23 GCMs referred to Wang et al [14].…”

“…However, these previous studies have neglected the performance assessment on GCM selection in terms of specific study areas, which could cause great uncertainties in the regional impact evaluation of climate change [12,13]. To solve this problem, Wang et al [14] firstly evaluated the 23 GCMs’ performances in the HRB, and then constructed the SDSM to provide the variation ranges of different climate variables simulated by multi-GCM under multiple scenarios, providing a reference for comparison between different GCMs and the concurrent issues related to downscaling. Climate change scenarios generated by Wang et al [14] were used in this study.…”

“…To solve this problem, Wang et al [14] firstly evaluated the 23 GCMs’ performances in the HRB, and then constructed the SDSM to provide the variation ranges of different climate variables simulated by multi-GCM under multiple scenarios, providing a reference for comparison between different GCMs and the concurrent issues related to downscaling. Climate change scenarios generated by Wang et al [14] were used in this study.…”

Spatially Explicit Modeling of Coupled Water and Carbon Processes Using a Distributed Ecohydrological Model in the Upper Heihe Watershed, China

“…Influenced by the westerly belt circulation and the cold continental polar air mass, the Upper Heihe watershed has an arid to semiarid climate with scarce and concentrated precipitation [21,22]. The water shortage and complex topography are major reasons for sparse vegetation coverage, and hence a more fragile ecological environment [23]. Hitherto, the estimations of ET and GPP in the Upper Heihe watershed were isolated.…”