Paper Published in Atmospheric Research

Title: Spatiotemporal patterns of future temperature and precipitation over China projected by PRECIS under RCPs

Journal: Atmospheric Research

DOI: https://doi.org/10.1016/j.atmosres.2020.105303

Abstract: In this study, the spatiotemporal patterns of future temperature and precipitation changes over China are explored with the regional climate model PRECIS at two horizontal resolutions (25 km and 50 km). The gauge-based temperature (CN05.1) and precipitation data (APHRODITE) are used to validate the performance of PRECIS. The results show that PRECIS has better performance in reproducing the present climatology in spatial distribution and annual cycle than its driving GCM, particularly in some cold months and the high latitude regions, though the simulation is worse in precipitation over the high-cold Tibet Plateau of China. Compared to the observation, the difference between the simulations at 50 km (R50) and 25 km (R25) resolutions is very small. Projected annual temperature and precipitation will increase gradually with the time over most regions of China, especially in the late of this century. The results from R25 show the mean temperature over China will increase by ~1.3(1.5) °C in the early century, 2.7(3.5) °C in the middle century, and 3.5(5.9) °C in the late century under RCP4.5(8.5), which are all smaller than the values from its driving GCM. Most models project that the temperature will have more increases in cold months (i.e., January to March) while the southeastern region will show smaller changes relative to other sub-regions. Additionally, China will receive more precipitation from the overall trend, but the increased amplitude among different concentration scenarios and models are different obviously. The projections from R25 show more precipitation than the R50 and their driving GCM. For instance, the annual mean precipitation will increase by ~15(22) % for GCM, ~20(33) % for R50 and ~ 22(37) % for R25 in the late of this century over the entire China under RCP4.5(8.5). The annual cycles of precipitation at sub-regions also show a distinct variation. The changes are smaller in October or November than other months for the southeastern and central regions, while the percentage change is larger in the northwest, which will alleviate the pressure of water shortage in this arid region of China.

Paper Accepted by Atmospheric Research

The following paper about the spatiotemporal patterns of future temperature and precipitation over China has recently been accepted for publication by Atmospheric Research.

Wu, Y., J. Guo, H. Lin, J. Bai, and X. Wang. Spatiotemporal patterns of future temperature and precipitation over China projected by PRECIS under RCPs. Atmospheric Research, accepted on October 6, 2020.

More details will come soon once the paper is published.

Paper Published in Journal of Geophysical Research: Atmospheres

Title: Factorial Sensitivity Analysis of Physical Schemes and Their Interactions in RegCM

Journal: Journal of Geophysical Research: Atmospheres

DOI: https://doi.org/10.1029/2020JD032501

Abstract: It is well known that the choices of physical schemes in Regional Climate Models (RCMs) can cause considerable uncertainties in future climate projections. In this study, a factorial sensitivity analysis method has been proposed to screen out statistically significant schemes and interactions, which assists in selecting the optimized physical scheme combination from a long‐term perspective with affordable computational costs. The Regional Climate Model (RegCM) is used as an example to illustrate how the approach works. In detail, all schemes are fully tested through 120 experimental runs based on a factorial design; the contributions and statistical significance (P value) of individual schemes and their interactions to temperature, precipitation, wind speed, and wind direction are then quantified. The performance of the proposed approach is then demonstrated through a case study of Canada. The results indicate that there exist considerable spatial and temporal simulated variations associated with different scheme combinations. It is also suggested that individual physical schemes have dominant influences on simulated variations, but some effects explained by their interactions are statistically significant and thus cannot be neglected. In particular, the planetary boundary layer (PBL) scheme, moisture scheme, and land surface model are found to be the dominant factors affecting the uncertainties of temperature, precipitation, and wind speed in future climate projections over Canada, respectively. Furthermore, the potential relationships between the vegetation cover conditions and the sensitivity of physical schemes are explored. The proposed approach is an attempt to analyze the sensitivity influenced by not only individual physical schemes and also their multilevel interactions.

Paper Published in Theoretical and Applied Climatology

Title: Projections of daily mean surface temperature over the Beijing-Tianjin-Hebei region through a stepwise cluster downscaling method

Journal: Theoretical and Applied Climatology

DOI: https://doi.org/10.1007/s00704-020-03172-w

Abstract: A stepwise cluster analysis (SCA) method is developed to downscale the daily mean surface temperature of 23 meteorological stations over the Beijing-Tianjin-Hebei (BTH) region in North China. Through comparisons of three evaluation indicators, including correction coefficients (CORRs), root mean square errors (RMSEs), and mean relative errors (MREs), between model simulations and observations, the SCA is proven to be capable of simulating the daily mean temperature in the baseline period (1961–2005). The projections of mean surface temperature under RCP4.5 and RCP8.5 scenarios are then developed using the SCA model. The results show that the mean surface temperature at most stations would keep increasing in future throughout the twenty-first century. The largest magnitude and rate of temperature increase are reported in the northwest mountains of the BTH region (especially obvious in winter), suggesting that the response to climate change in highland regions is more sensitive than that in low elevations. It is also reported that the projected changes in mean surface temperature in coastal regions are smaller than those in plain areas. This could be due to ocean’s moderating influence in the HadGEM2-ES. In terms of seasonal changes in surface temperature, the smallest magnitude of warming is expected in summer while the highest is likely to occur in winter, especially under RCP8.5 emission scenarios. Furthermore, the annual cycle analysis for temperature changes suggests that the highest amplitude of warming is expected in cold months (i.e., February or December) while the smallest is likely to occur in warm months (i.e., July or August).

Paper Published in Science of The Total Environment

Title: Evaluating the added values of regional climate modeling over China at different resolutions

Journal: Science of The Total Environment

DOI: https://doi.org/10.1016/j.scitotenv.2020.137350

Abstract: Previous studies have suggested that dynamical downscaling to global climate models can produce improved climate simulations at regional and local scales. However, the expensive computational requirements of dynamical downscaling inevitably add a limit to the spatial resolution of the resulting regional climate simulations. In order to find a balance between computational requirements and simulation improvements, it is extremely important to investigate how the spatial resolution of regional climate simulation affects the added values of dynamical downscaling; yet, it is still not well understood. Therefore, in this study, we conduct long-term climate simulations for the entire country of China with the PRECIS regional climate model at two different spatial resolutions (i.e., 25 and 50 km). The purpose is to evaluate whether a fine-resolution model simulation, given its considerable requirements for computational resources, would add more valuable information for understanding regional climatology than a coarse-resolution model simulation. Our results show that the PRECIS can reasonably reproduce the spatial distribution of seasonal and monthly mean temperature and precipitation over the most of regions in China. However, in the process of downscaling, RCM with higher resolution cannot always produce more accurate output. In regard to precipitation simulations, compared with the host GCM, it is difficult to determine exactly a homogeneous improvement of performance in downscaling, both in terms of spatial patterns as well as magnitude of errors. For interannual variability, variations in temperature are closer to observation than precipitation and the high-resolution R25 has better skills over the northwest than R50. Moreover, except for the west, it is shown that PRECIS is able to better reproduce the probability distribution function of precipitation and some impact-relevant indices such as the number of consecutive wet days and simple precipitation intensity index in spatial distribution.