On the sensitivity of seasonal and diurnal precipitation to cumulus parameterization over CORDEX-EA-II

Niu, Xiaorui; Tang, Jianping; Wang, Shuyu; Fu, Congbin; Chen, Deliang

doi:10.1007/s00382-019-05010-w

Cited by 22 publications

(17 citation statements)

References 78 publications

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“…1). The configurations of these simulations are summarized in Table 1, and a detailed description of the model setup can be found in Niu et al (2020).…”

Section: Model and Sensitivity Experimentsmentioning

confidence: 99%

The performance of CORDEX-EA-II simulations in simulating seasonal temperature and elevation-dependent warming over the Tibetan Plateau

et al. 2021

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To explore the driving mechanisms of elevation-dependent warming (EDW) over the Tibetan Plateau (TP), the output from a suite of numerical experiments with different cumulus parameterization schemes (CPs) under the Coordinated Regional Climate Downscaling Experiments-East Asia (CORDEX-EA-II) project is examined. Results show that all experiments can broadly capture the observed temperature distributions over the TP with consistent cold biases, and the spread in temperature simulations commonly increases with elevation with the maximum located around 4000–5000 m. Such disagreements among the temperature simulations could to a large extent be explained by their spreads in the surface albedo feedback (SAF). All the experiments reproduce the observed EDW below 5000 m in winter but fail to capture the observed EDW above 4500 m in spring. Further analysis suggests that the simulated EDW during winter is mainly caused by the SAF, and the clear-sky downward longwave radiation (LWclr) plays a secondary role in shaping EDW. The models’ inability in simulating EDW during spring is closely related to the SAF and the surface cloud radiative forcing (CRFs). Furthermore, the magnitude and structure of the simulated EDW are sensitive to the choice of CPs. Different CPs generate diverse snow cover fractions, which can modulate the simulated SAF and its effect on EDW. Also, the CPs show great influence on the LWclr via altering the low-level air temperature. Additionally, the mechanism for different temperature changes among the experiments varies with altitudes during summer and autumn, as the diverse temperature changes appear to be caused by the LWclr for the low altitudes while by the SAF for the middle-high altitudes.

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“…1). The configurations of these simulations are summarized in Table 1, and a detailed description of the model setup can be found in Niu et al (2020).…”

Section: Model and Sensitivity Experimentsmentioning

confidence: 99%

The performance of CORDEX-EA-II simulations in simulating seasonal temperature and elevation-dependent warming over the Tibetan Plateau

et al. 2021

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“…The large spread in simulations of present-day climate demonstrates uncertainties that should be associated with simulated projections (Woldemeskel et al 2016), particularly in the case of precipitation, which is highly variable. Recently, considerable progress has been achieved in high resolution climate modeling, for example in dynamical downscaling over multiple CORDEX (Coordinated Regional Climate Downscaling Experiment) domains (e.g., Jacob et al 2012;Wang et al 2016;Gao and Chen 2017;Ge et al 2019;Giorgi 2019;Niu et al 2019;Tapiador et al 2020). These high-resolution simulations have the advantages of improved representation of orographic features, increased spatial resolution, optimized atmospheric forcing, and a detailed land-surface scheme.…”

Section: Introductionmentioning

confidence: 99%

Historical and future climates over the upper and middle reaches of the Yellow River Basin simulated by a regional climate model in CORDEX

et al. 2021

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Despite the importance of the Yellow River to China, climate change for the middle reaches of the Yellow River Basin (YRB) has been investigated far less than for other regions. This work focuses on future changes in mean and extreme climate of the YRB for the near-term (2021–2040), mid-term (2041–2060), and far-term (2081–2100) future, and assesses these with respect to the reference period (1986–2005) using the latest REgional MOdel (REMO) simulations, driven by three global climate models (GCMs) and assuming historical and future [Representative Concentration Pathway (RCP) 2.6 and 8.5] forcing scenarios, over the CORDEX East Asia domain at 0.22° horizontal resolution. The results show that REMO reproduces the historical mean climate state and selected extreme climate indices reasonably well, although some cold and wet biases exist. Increases in mean temperature are strongest for the far-term in winter, with an average increase of 5.6 °C under RCP 8.5. As expected, the future temperatures of the warmest day (TXx) and coldest night (TNn) increase and the number of frost days (FD) declines considerably. Changes to mean temperature and FD depend on elevation, which could be explained by the snow-albedo feedback. A substantial increase in precipitation (34%) occurs in winter under RCP 8.5 for the far-term. Interannual variability in precipitation is projected to increase, indicating a future climate with more extreme events compared to that of today. Future daily precipitation intensity and maximum 5-day precipitation would increase and the number of consecutive dry days would decline under RCP 8.5. The results highlight that pronounced warming at high altitudes and more intense rainfall could cause increased future flood risk in the YRB, if a high GHG emission pathway is realized.

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“…Both RegCM and WRF simulate realistic patterns over TP but have large wet biases over the western Pacific and the Indian Ocean (Figures 3i and 3k). Such oceanic biases can be partly related to RCMs' cumulus parameterization schemes triggering precipitation too easily (Niu et al, 2019;Yu et al, 2020) and can be reduced by applying some convection suppression criteria (e.g., Zou et al, 2014). However, Niu et al (2019) also showed that none of the widely used cumulus parameterization schemes in WRF can remove the excessive precipitation over ocean.…”

Section: Precipitation Climatology and Seasonal Cyclementioning

confidence: 99%

“…Such oceanic biases can be partly related to RCMs' cumulus parameterization schemes triggering precipitation too easily (Niu et al, 2019;Yu et al, 2020) and can be reduced by applying some convection suppression criteria (e.g., Zou et al, 2014). However, Niu et al (2019) also showed that none of the widely used cumulus parameterization schemes in WRF can remove the excessive precipitation over ocean. Hence, other factors such as the moisture flux errors from the lateral boundary conditions over ocean (Wang & Yang, 2008) might also be important for these precipitation biases.…”

Section: Precipitation Climatology and Seasonal Cyclementioning

confidence: 99%

Multiscale Simulation of Precipitation Over East Asia by Variable Resolution CAM‐MPAS

Liang

Yang

Wang

et al. 2021

J Adv Model Earth Syst

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This study evaluates the precipitation over East Asia simulated by the variable resolution CAM‐MPAS featuring the Model for Prediction Across Scales (MPAS) atmospheric dynamical core coupled with the physics parameterizations of the Community Atmosphere Model (CAM) version 5.4. Two CAM‐MPAS experiments, one with a global quasi‐uniform resolution mesh of 120 km (MPAS‐UR) and the other with a variable resolution mesh of 30–120 km refined over East Asia (MPAS‐VR), are conducted from 1989 to 2005 following the Atmospheric Model Intercomparison Project protocol. Two regional climate model simulations at ∼25 km resolution from the Coordinated Regional Downscaling Experiment East Asia second plan are also analyzed for comparison. Results show that CAM‐MPAS performs better than the selected regional models in simulating the precipitation climatology over East Asia. Compared with MPAS‐UR, MPAS‐VR with refinement over East Asia better simulates the precipitation over and around the Tibetan Plateau (TP), the upper‐level circulation, the precipitation frequency and intensity in various regions of China, and the interannual precipitation pattern associated with the East Asian summer monsoon. Both decreased grid spacing and the use of finer‐scale terrain information contribute to the improvements in MPAS‐VR relative to MPAS‐UR. However, decreased grid spacing is more essential for simulating the precipitation magnitude over TP and the location of peak precipitation south of TP, likely due to the better resolved physical and dynamical processes associated with orographic precipitation. The 30–120 km CAM‐MPAS model is shown to be a promising tool for precipitation simulation over East Asia.

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On the sensitivity of seasonal and diurnal precipitation to cumulus parameterization over CORDEX-EA-II

Cited by 22 publications

References 78 publications

The performance of CORDEX-EA-II simulations in simulating seasonal temperature and elevation-dependent warming over the Tibetan Plateau

The performance of CORDEX-EA-II simulations in simulating seasonal temperature and elevation-dependent warming over the Tibetan Plateau

Historical and future climates over the upper and middle reaches of the Yellow River Basin simulated by a regional climate model in CORDEX

Multiscale Simulation of Precipitation Over East Asia by Variable Resolution CAM‐MPAS

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