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Yuhe Song and Tao Tang

Abstract

The Turkel-Zwas-type schemes employ coarse grids to discretize the terms associated with the fast gravity-inertia waves and use fine grids to treat the terms associated with the slow Rossby waves. The ratio of the coarse and fine grids is an integer, p>1, and one can use time steps nearly p times larger than those allowed by the Courant-Friedrich-Lewy condition for the usual explicit leapfrog scheme. This paper investigates the Turkel-Zwas-type schemes with three spatial grids-namely, A (unstaggered), B, and C grids (staggered)-for two-dimensional shallow-water equations. A new method that uses the Laplace transform is introduced to solve the two-dimensional phase solutions. Comparisons of the three grids with coarse and fine-grid resolutions are made. One realistic model problem is tested to verify the linear analysis results. The test shows that the Turkel-Zwas-type schemes can be used for a larger time step in some practical simulations.

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Cheng Tao, Yunyan Zhang, Qi Tang, Hsi-Yen Ma, Virendra P. Ghate, Shuaiqi Tang, Shaocheng Xie, and Joseph A. Santanello

Abstract

Using the 9-yr warm-season observations at the Atmospheric Radiation Measurement Southern Great Plains site, we assess the land–atmosphere (LA) coupling in the North American Regional Reanalysis (NARR) and two climate models: hindcasts with the Community Atmosphere Model version 5.1 by Cloud-Associated Parameterizations Testbed (CAM5-CAPT) and nudged runs with the Energy Exascale Earth System Model Atmosphere Model version 1 Regionally Refined Model (EAMv1-RRM). We focus on three local convective regimes and diagnose model behaviors using the local coupling metrics. NARR agrees well with observations except a slightly warmer and drier surface with higher downwelling shortwave radiation and lower evaporative fraction. On clear-sky days, it shows warmer and drier early-morning conditions in both models with significant underestimates in surface evaporation by EAMv1-RRM. On the majority of the ARM-observed shallow cumulus days, there is no or little low-level clouds in either model. When captured in models, the simulated shallow cumulus shows much less cloud fraction and lower cloud bases than observed. On the days with late-afternoon deep convection, models tend to present a stable early-morning lower atmosphere more frequently than the observations, suggesting that the deep convection is triggered more often by elevated instabilities. Generally, CAM5-CAPT can reproduce the local LA coupling processes to some extent due to the constrained early-morning conditions and large-scale winds. EAMv1-RRM exhibits large precipitation deficits and warm and dry biases toward mid-to-late summers, which may be an amplification through a positive LA feedback among initial atmosphere and land states, convection triggering and large-scale circulations.

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C. Zhang, S. Xie, C. Tao, S. Tang, T. Emmenegger, J. D. Neelin, K. A. Schiro, W. Lin, and Z. Shaheen

Abstract

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program User Facility produces ground-based long-term continuous unique measurements for atmospheric state, precipitation, turbulent fluxes, radiation, aerosol, cloud, and the land surface, which are collected at multiple sites. These comprehensive datasets have been widely used to calibrate climate models and are proven to be invaluable for climate model development and improvement. This article introduces an evaluation package to facilitate the use of ground-based ARM measurements in climate model evaluation. The ARM data-oriented metrics and diagnostics package (ARM-DIAGS) includes both ARM observational datasets and a Python-based analysis toolkit for computation and visualization. The observational datasets are compiled from multiple ARM data products and specifically tailored for use in climate model evaluation. In addition, ARM-DIAGS also includes simulation data from models participating the Coupled Model Intercomparison Project (CMIP), which will allow climate-modeling groups to compare a new, candidate version of their model to existing CMIP models. The analysis toolkit is designed to make the metrics and diagnostics quickly available to the model developers.

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Jinyuan Xin, Yuesi Wang, Yuepeng Pan, Dongsheng Ji, Zirui Liu, Tianxue Wen, Yinghong Wang, Xingru Li, Yang Sun, Jie Sun, Pucai Wang, Gehui Wang, Xinming Wang, Zhiyuan Cong, Tao Song, Bo Hu, Lili Wang, Guiqian Tang, Wenkang Gao, Yuhong Guo, Hongyan Miao, Shili Tian, and Lu Wang

Abstract

Based on a network of field stations belonging to the Chinese Academy of Sciences (CAS), the Campaign on Atmospheric Aerosol Research network of China (CARE-China) was recently established as the country’s first monitoring network for the study of the spatiotemporal distribution of aerosol physical characteristics, chemical components, and optical properties, as well as aerosol gaseous precursors. The network comprises 36 stations in total and adopts a unified approach in terms of the instrumentation, experimental standards, and data specifications. This ongoing project is intended to provide an integrated research platform to monitor online PM2.5 concentrations, nine-size aerosol concentrations and chemical component distributions, nine-size secondary organic aerosol (SOA) component distributions, gaseous precursor concentrations (including SO2, NOx, CO, O3, and VOCs), and aerosol optical properties. The data will be used to identify the sources of regional aerosols, the relative contributions from nature and anthropogenic emissions, the formation of secondary aerosols, and the effects of aerosol component distributions on aerosol optical properties. The results will reduce the levels of uncertainty involved in the quantitative assessment of aerosol effects on regional climate and environmental changes and ultimately provide insight into how to mitigate anthropogenic aerosol emissions in China. The present paper provides a detailed description of the instrumentation, methodologies, and experimental procedures used across the network, as well as a case study of observations taken from one station and the distribution of main components of aerosol over China during 2012.

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