During the presummer rainy season (April–June), southern China often experiences frequent occurrences of extreme rainfall, leading to severe flooding and inundations. To expedite the efforts in improving the quantitative precipitation forecast (QPF) of the presummer rainy season rainfall, the China Meteorological Administration (CMA) initiated a nationally coordinated research project, namely, the Southern China Monsoon Rainfall Experiment (SCMREX) that was endorsed by the World Meteorological Organization (WMO) as a research and development project (RDP) of the World Weather Research Programme (WWRP). The SCMREX RDP (2013–18) consists of four major components: field campaign, database management, studies on physical mechanisms of heavy rainfall events, and convection-permitting numerical experiments including impact of data assimilation, evaluation/improvement of model physics, and ensemble prediction. The pilot field campaigns were carried out from early May to mid-June of 2013–15. This paper: i) describes the scientific objectives, pilot field campaigns, and data sharing of SCMREX; ii) provides an overview of heavy rainfall events during the SCMREX-2014 intensive observing period; and iii) presents examples of preliminary research results and explains future research opportunities.
Study on the uncertainties in land surface models (LSMs) helps us understand the differences and errors in climate models. Meanwhile, uncertainty in model structure, derived from the many possible parameterization schemes for the same physical subprocess, is a primary source of land model uncertainties. To attribute structural errors and model parameterization scheme uncertainties, it is critical to identify the key subprocesses involved and investigate the interactions of these subprocesses on LSM behavior, which will ultimately help us identify the “optimal” parameterization schemes for various plant functional types, soil types, and different locations. Here, we conduct physical ensemble simulations for multiple sites from FLUXNET and then apply a variance‐based sensitivity analysis method to quantitatively assess the impacts of uncertainties in the parameterization schemes of subprocesses in the Noah with multiparameterization (Noah‐MP) LSM on model performance. The results show that three subprocesses—surface exchange coefficient, runoff and groundwater, and surface resistance to evaporation—have the most significant impacts on the performance of the simulated sensible heat flux, latent heat flux, and net absorbed radiation in the Noah‐MP LSM. The interaction between two subprocesses could contribute up to 50% of the variation in model performance for some sites, which highlights the need for taking into consideration the interactions of subprocesses to improve LSMs. Finally, a statistical optimal combination of the parameterization schemes is recommended for global land modeling, although it is noticed that the optimal schemes vary with regions and can be different even for neighboring sites.
SUMMARYA conservative constraint is presented for a new quasi-uniform overset (Yin-Yang) grid on the sphere. The Yin-Yang grid is a newly developed grid system in spherical geometry created by matching two notched latitudelongitude grids which are normal to each other. Global and local conservation is achieved with an interpolation algorithm that exactly guarantees that the fluxes on boundaries of the two grid components are identical. Several numerical experiments are shown to confirm the conservation in passive transport situations and shallow-water dynamical equations.
A numerical model for shallow-water equations has been built and tested on the Yin-Yang overset spherical grid. A high-order multimoment finite-volume method is used for the spatial discretization in which two kinds of so-called moments of the physical field [i.e., the volume integrated average (VIA) and the point value (PV)] are treated as the model variables and updated separately in time. In the present model, the PV is computed by the semi-implicit semi-Lagrangian formulation, whereas the VIA is predicted in time via a flux-based finite-volume method and is numerically conserved on each component grid. The concept of including an extra moment (i.e., the volume-integrated value) to enforce the numerical conservativeness provides a general methodology and applies to the existing semi-implicit semi-Lagrangian formulations. Based on both VIA and PV, the high-order interpolation reconstruction can only be done over a single grid cell, which then minimizes the overlapping zone between the Yin and Yang components and effectively reduces the numerical errors introduced in the interpolation required to communicate the data between the two components. The present model completely gets around the singularity and grid convergence in the polar regions of the conventional longitude-latitude grid. Being an issue demanding further investigation, the high-order interpolation across the overlapping region of the Yin-Yang grid in the current model does not rigorously guarantee the numerical conservativeness. Nevertheless, these numerical tests show that the global conservation error in the present model is negligibly small. The model has competitive accuracy and efficiency.
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