Dynamical downscaling simulation and future projection of precipitation over China

Bao, Jiawei; Feng, Jinming; Wang, Yongli

doi:10.1002/2015jd023275

Cited by 98 publications

(74 citation statements)

References 67 publications

(54 reference statements)

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“…Figure showed the spatial distribution of annual precipitation and the 5 year trends for the RF period from 1982 to 2001 by the observation, GFDL data sets, and the RCM run. RCM could capture the general pattern of annual precipitation with a transition from drought in northwestern China (an arid and semiarid region) to wet in southeastern China (a humid region), as shown in Figures a and c; while GFDL showed a maximum precipitation area in the Sichuan Basin [ Bao et al ., ] and a rain belt in the YZ river basin (Figure b) which were not found in the observation (seasonal precipitation has similar conclusions, which are not shown here). In addition, both GFDL and RCM could capture the positive 5 year trends of precipitation in southeastern China (Figures d–f).…”

Section: Resultsmentioning

confidence: 99%

“…Dynamic downscaling based on regional climate models (RCM) that have high resolution are often adopted to study local climate and extreme events forced by GCMs [ Bao et al ., ; Burger et al ., ; Gao et al ., ; Knutson et al ., ; Pielke and Wilby , ; Shi et al ., ; Singh et al ., ; Tang et al ., ; Zhai et al ., ; Zou and Zhou , ]. Wang et al .…”

Section: Introductionmentioning

confidence: 99%

“…In the present study, we focused on detecting changes in future precipitation extremes over eight river basins in China and their trends under midrange emissions scenarios (RCP4.5) from the experimental design of CMIP5 [ Taylor et al ., ]. The regional climate model RegCM version 4 (RegCM4) from the Abdus Salam International Center for Theoretical Physics (ICTP) was adopted for dynamic downscaling of GFDL‐ESM2M [ Dunne et al ., ], participated in the CMIP5 and showed moderate performance in simulating present climate extremes [ Bao et al ., ; Sillmann et al ., ]. First, we evaluated the performance of RegCM4 in simulating mean and extreme precipitation for the reference period (RF) from 1982 to 2001 over eight river basins in China compared with the precipitation extremes of the observation and GFDL (Figure ).…”

Section: Introductionmentioning

confidence: 99%

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Detecting changes in future precipitation extremes over eight river basins in China using RegCM4 downscaling

Qin

Xie

2016

JGR Atmospheres

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To detect the frequency and intensity of precipitation extremes in China for the middle 21st century, simulations were conducted with the regional climate model RegCM4 forced by the global climate model GFDL_ESM2M under the middle emission scenario (RCP4.5). Compared with observed precipitation extremes for the reference period from 1982 to 2001, RegCM4 generally performed better in most river basins of China relative to GFDL. In the future period 2032–2051, more wet extremes will occur relative to the present period in most study areas, especially in southeast China while significantly less dry extremes will occur in arid and semiarid areas in northwest China. In contrast, areas in northwest China showed an increase in the trend of dry extremes (CDD) and a decrease in the trend of wet extremes (R95p and Rx5day), which might result in more drought in the future. Finally, we discuss in detail the possible reason of these processes, such as zonal wind, vertical wind, and water vapor. In the Huaihe river basin (HU), reduced south winds in summer (June–August) and a decrease of the upward vertical p velocity cause less future precipitation and might lead to changes of extreme events. We also completed correlation analysis between the precipitation extreme indices and the climate factors and found that the precipitation extremes were more sensitive to the annual and seasonal mean precipitation, total water vapor, and upward vertical wind relative to the geopotential height and 2 m temperature over most river basins in China. Perhaps the changes of some wet extremes could be verified partly through changes of annual precipitation due to their high consistence.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Detecting changes in future precipitation extremes over eight river basins in China using RegCM4 downscaling

Qin

Xie

2016

JGR Atmospheres

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“…To further validate the applicability of these data in the TP, we selected continuous observed daily precipitation and temperature from 10 meteorological stations in the TP during 1981–2000 to compare with CMFD, and two meteorological variables from CMFD were generally consistent with observations. Although some mismatch still occurred around the edge of the simulated control domain between CMFD and RegCM4 results, RegCM4 generally displayed a reasonable and satisfactory performance in reproducing the patterns and magnitudes of mean precipitation and temperature in the TP due to its high resolution and the skill of the driving GCM (Bao, Feng, & Wang, ). Besides, the parameters we selected to adjust during calibration of the VIC model include the infiltration parameter (b_inf), the depth of the first and second soil layers (d1 and d2), and three baseflow parameters (Ds, Ws, and Dsmax; B. N. Nijssen et al, ; L. L. Zhang et al, ).…”

Section: Discussionmentioning

confidence: 99%

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Lü

Wang

Shao

et al. 2018

Hydrological Processes

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Understanding climate change impacts on hydrological regime and assessing future water supplies are essential to effective water resources management and planning, which is particularly true for the Tibetan Plateau (TP), one of the most vulnerable areas to climate change. In this study, future climate change in the TP was projected for 2041–2060 by a high‐resolution regional climate model, RegCM4, under 3 representative concentration pathways (RCPs): 2.6, 4.5, and 8.5. Response of all key hydrological elements, that is, evapotranspiration, surface run‐off, baseflow, and snowmelt, to future climate in 2 typical catchments, the source regions of Yellow and Yangtze rivers, was further investigated by the variable infiltration capacity microscale hydrological model incorporated with a 2‐layer energy balance snow model and a frozen soil/permafrost algorithm at a 0.25°×0.25° spatial scale. The results reveal that (a) spatial patterns of precipitation and temperature from RegCM4 agree fairly well with the data from China Meteorological Forcing Dataset, indicating that RegCM4 well reproduces historical climatic information and thus is reliable to support future projection; (b) precipitation increase by 0–70% and temperature rise by 1–4 °C would occur in the TP under 3 RCPs. A clear south‐eastern–north‐western spatial increasing gradient in precipitation would be seen. Besides, under RCP8.5, the peak increase in temperature would approach to 4 °C in spring and autumn in the east of the TP; (c) evapotranspiration would increase by 10–60% in 2 source regions due to the temperature rise, surface run‐off and baseflow in higher elevation region would experience larger increase dominantly due to the precipitation increase, and streamflow would display general increases by more than 3% and 5% in the source regions of Yellow and Yangtze rivers, respectively; (d) snowmelt contributes 11.1% and 16.2% to total run‐off in the source regions of Yellow and Yangtze rivers, respectively, during the baseline period. In the source region of Yangtze River, snowmelt run‐off would become more important with increase of 17.5% and 18.3%, respectively, under RCP2.6 and RCP4.5 but decrease of 15.0% under RCP8.5.

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“…The anomaly approach first calculates a gridded climatology, then the final data-set is obtained by adding a gridded daily anomaly to the climatology. These data have been shown to be reliable and widely used in the evaluation of model performance over China (Yu et al, 2011;Bao et al, 2015;Yu et al, 2015;Yang et al, 2016). The CN05.1 data-set is interpolated to the WRF grids using the objective analysis interpolation (Barnes, 1964).…”

Section: Experiments Design and Observationmentioning

confidence: 99%

Impact of different cumulus convective parameterization schemes on the simulation of precipitation over China

Huang

Gao

2017

Tellus A: Dynamic Meteorology and Oceanography

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The impact of two cumulus convective schemes on the simulation of the precipitation over China is investigated using the Weather Research and Forecasting (WRF) model. Simulations for the period of 1982-2004 are performed at a horizontal resolution of 30 km and forced by NCEP Reanalysis II data. Results show precipitation simulated with the WRF model is quite sensitive to the choice of Kain-Fritsch and Grell cumulus schemes. Both the schemes have distinct skills in predicting the seasonal mean pattern, annual cycle and interannual variation in precipitation. The results show that the Kain-Fritsch scheme tends to overestimate the magnitude of the summer and annual mean precipitation over the main rain-belts, while the Grell scheme tends to underestimate these effects, particularly the simulation of the summer extreme precipitation. However, the Kain-Fritsch scheme is more skilful in capturing the seasonal mean pattern and annual cycle with higher spatial correlations in the main rain-belts. The Grell scheme shows some advantages for northern China and the Tibetan Plateau, especially in representing the interannual variation. The optimal ensemble approach is used to determine the best combination of the two schemes, with the results giving a better overall performance than the individual schemes alone in predicting summer precipitation. The temporal correlation coefficient of precipitation for the ensemble is significantly higher, while the root mean square error of extreme precipitation is reduced compared with the Kain-Fritsch and Grell results. This shows that the ensemble approach based on the optimal ensemble weight combines the advantages of the two cumulus schemes efficiently.

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Dynamical downscaling simulation and future projection of precipitation over China

Cited by 98 publications

References 67 publications

Detecting changes in future precipitation extremes over eight river basins in China using RegCM4 downscaling

Detecting changes in future precipitation extremes over eight river basins in China using RegCM4 downscaling

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Impact of different cumulus convective parameterization schemes on the simulation of precipitation over China

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