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Xi Chen, Yongqin David Chen, and Zhicai Zhang

Abstract

To analyze the water budget under human influences in the Huaihe River plain region in China, the authors have developed a numerical modeling system that integrates water flux algorithms into a platform created by coupling a soil moisture model with the modular three-dimensional finite-difference groundwater flow model (MODFLOW). The modeling system is largely based on physical laws and employs a numerical method of the finite difference to simulate water movement and fluxes in a horizontally discretized watershed or field. The majority of model parameters carry physical significance and can be determined by field and laboratory measurements or derived from watershed characteristics contained in GIS and remote sensing data. Several other empirical parameters need to be estimated by model calibration. The numerical modeling system is calibrated in the Linhuanji catchment (2 560 km2) to estimate surface runoff, groundwater recharge, and groundwater loss for evapotranspiration and stream baseflow. Model validation is conducted at a small runoff experimental field (1.36 km2) in the Wuduogou Hydrological Experimental Station to test the model’s capability to simulate hydrological components and estimate water fluxes using observed stream stage and groundwater data, as well as lysimeter-measured precipitation recharge and groundwater loss. As proven by the promising results of model testing, this physically based and distributed-parameter model is a valuable contribution to the ever-advancing technology of hydrological modeling and water resources assessment.

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Zezong Chen, Longgang Zhang, Chen Zhao, Xi Chen, and Jianbo Zhong

Abstract

Wind sea and swell representing different weather conditions generally coexist in both open waters and coastal areas, which results in bimodal or multipeaked features in directional wave spectrum. Because they make wave parameters such as significant wave height and mean wave period of the mixed sea state less meaningful, the processes of separation and identification of wind sea and swell are crucial. Consistent wind sea and swell results can be obtained by a commonly used method based on wave age (WA) with the directional wave spectrum and wind velocity. However, the subjective dependence of wave age threshold selection and the required wind information restrict the application of this method. In this study, a practical method based on the overshoot phenomenon (OP) in wind-generated waves is proposed to extract wind sea and swell from the directional wave spectrum without any other meteorology information. Directional wave spectra derived from an S-band Doppler radar deployed on the coast of the South China Sea have been utilized as the datasets to investigate the performance of both methods. The proposed OP method is then validated by comparing it with the WA method and the verifying results are presented.

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Xi Cao, Tim Li, Melinda Peng, Wen Chen, and Guanghua Chen

Abstract

The effects of intraseasonal oscillation (ISO) of the western North Pacific (WNP) monsoon trough on tropical cyclone (TC) formation were investigated using the Advanced Research Weather Research and Forecasting (ARW) Model. A weak vortex was specified initially and inserted into the background fields containing climatological-mean anomalies associated with active and inactive phases of monsoon trough ISOs.

The diagnosis of simulations showed that monsoon trough ISO can modulate TC development through both dynamic and thermodynamic processes. The dynamic impact is attributed to the lower–midtropospheric large-scale vorticity associated with monsoon trough ISO. Interactions between cyclonic vorticity in the lower middle troposphere during the active ISO phase and a vortex lead to the generation of vortex-scale outflow at the midlevel, which promotes the upward penetration of friction-induced ascending motion and thus upward moisture transport. In addition, the low-level convergence associated with active ISO also helps the upward moisture transport. Both processes contribute to stronger diabatic heating and thus promote a positive convection–circulation–moisture feedback. On the other hand, the large-scale flow associated with inactive ISO suppresses upward motion near the core by inducing the midlevel inflow and the divergence forcing within the boundary layer, both inhibiting TC development. The thermodynamic impact comes from greater background specific humidity associated with active ISO that allows a stronger diabatic heating. Experiments that separated the dynamic and thermodynamic impacts of the ISO showed that the thermodynamic anomaly from active ISO contributes more to TC development, while the dynamic anomalies from inactive ISO can inhibit vortex development completely.

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Wen Wang, Wei Cui, Xiaoju Wang, and Xi Chen

Abstract

The Global Land Data Assimilation System (GLDAS) is an important data source for global water cycle research. Using ground-based measurements over continental China, the monthly scale forcing data (precipitation and air temperature) during 1979–2010 and model outputs (runoff, water storage, and evapotranspiration) during 2002–10 of GLDAS models [focusing on GLDAS, version 1 (GLDAS-1)/Noah and GLDAS, version 2 (GLDAS-2)/Noah] are evaluated. Results show that GLDAS-1 has serious discontinuity issues in its forcing data, with large precipitation errors in 1996 and large temperature errors during 2000–05. While the bias correction of the GLDAS-2 precipitation data greatly improves temporal continuity and reduces the biases, it makes GLDAS-2 precipitation less correlated with observed precipitation and makes it have larger mean absolute errors than GLDAS-1 precipitation for most months over the year. GLDAS-2 temperature data are superior to GLDAS-1 temperature data temporally and spatially. The results also show that the change rates of terrestrial water storage (TWS) data by GLDAS and the Gravity Recovery and Climate Experiment (GRACE) do not match well in most areas of China, and both GLDAS-1 and GLDAS-2 are not very capable of capturing the seasonal variation in monthly TWS change observed by GRACE. Runoff is underestimated in the exorheic basins over China, and runoff simulations of GLDAS-2 are much more accurate than those of GLDAS-1 for two of the three major river basins of China investigated in this study. Evapotranspiration is overestimated in the exorheic basins in China by both GLDAS-1 and GLDAS-2, whereas the overestimation of evapotranspiration by GLDAS-2 is less than that by GLDAS-1.

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T. Scott Rupp, Xi Chen, Mark Olson, and A. David McGuire

Abstract

Projected climatic warming has direct implications for future disturbance regimes, particularly fire-dominated ecosystems at high latitudes, where climate warming is expected to be most dramatic. It is important to ascertain the potential range of climate change impacts on terrestrial ecosystems, which is relevant to making projections of the response of the Earth system and to decisions by policymakers and land managers. Computer simulation models that explicitly model climate–fire relationships represent an important research tool for understanding and projecting future relationships. Retrospective model analyses of ecological models are important for evaluating how to effectively couple ecological models of fire dynamics with climate system models. This paper uses a transient landscape-level model of vegetation dynamics, Alaskan Frame-based Ecosystem Code (ALFRESCO), to evaluate the influence of different driving datasets of climate on simulation results. Our analysis included the use of climate data based on first-order weather station observations from the Climate Research Unit (CRU), a statistical reanalysis from the NCEP–NCAR reanalysis project (NCEP), and the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). Model simulations of annual area burned for Alaska and western Canada were compared to historical fire activity (1950–2000). ALFRESCO was only able to generate reasonable simulation results when driven by the CRU climate data. Simulations driven by the NCEP and MM5 climate data produced almost no annual area burned because of substantially colder and wetter growing seasons (May–September) in comparison with the CRU climate data. The results of this study identify the importance of conducting retrospective analyses prior to coupling ecological models of fire dynamics with climate system models. The authors’ suggestion is to develop coupling methodologies that involve the use of anomalies from future climate model simulations to alter the climate data of more trusted historical climate datasets.

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Chong Wu, Liping Liu, Xi Liu, Guocui Li, and Chao Chen

Abstract

In the summer of 2016, one phased-array radar and two polarimetric weather radars, representative of advancing radar technology in use in China, jointly collected data in the Foshan area to study severe convective storms in southern China. After an introduction to the technical characteristics and a verification of the radar calibration, the advantages of the abovementioned dual-polarization and phased-array radars are discussed in terms of an observational analysis of a supercell that occurred on 9 May 2016. The polarimetric signatures within the supercell are associated with specific microphysical processes that can reveal different stages of storm evolution. The hydrometeor classification algorithm is a more straightforward and useful method for nowcasting than conventional algorithms, which makes it favorable for further recommendation in China. During the mature and dissipating stages of this supercell, observations of the phased-array radar show detailed changes on short time scales that cannot be observed by parabolic-antenna radars. The initiation and mergers of new convective cells are found in the peak inflow region, and the formation and dissipation of the hook echo are associated with the relative intensities of inflow and outflow. The abovementioned results demonstrate that the phased-array radar and dual-polarization radars recently developed in China are powerful tools to better understand storm evolution for nowcasting and scientific studies.

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Linjiong Zhou, Shian-Jiann Lin, Jan-Huey Chen, Lucas M. Harris, Xi Chen, and Shannon L. Rees

Abstract

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a new variable-resolution global model with the ability to represent convective-scale features that serves as a prototype of the Next Generation Global Prediction System (NGGPS). The goal of this prediction system is to maintain the skill in large-scale features while simultaneously improving the prediction skill of convectively driven mesoscale phenomena. This paper demonstrates the new capability of this model in convective-scale prediction relative to the current operational Global Forecast System (GFS). This model uses the stretched-grid functionality of the Finite-Volume Cubed-Sphere Dynamical Core (FV3) to refine the global 13-km uniform-resolution model down to 4-km convection-permitting resolution over the contiguous United States (CONUS), and implements the GFDL single-moment 6-category cloud microphysics to improve the representation of moist processes. Statistics gathered from two years of simulations by the GFS and select configurations of the FV3-based model are carefully examined. The variable-resolution FV3-based model is shown to possess global forecast skill comparable with that of the operational GFS while quantitatively improving skill and better representing the diurnal cycle within the high-resolution area compared to the uniform mesh simulations. Forecasts of the occurrence of extreme precipitation rates over the southern Great Plains are also shown to improve with the variable-resolution model. Case studies are provided of a squall line and a hurricane to demonstrate the effectiveness of the variable-resolution model to simulate convective-scale phenomena.

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Jan-Huey Chen, Shian-Jiann Lin, Linjiong Zhou, Xi Chen, Shannon Rees, Morris Bender, and Matthew Morin

Abstract

A new global model using the GFDL nonhydrostatic Finite-Volume Cubed-Sphere Dynamical Core (FV3) coupled to physical parameterizations from the National Centers for Environmental Prediction’s Global Forecast System (NCEP/GFS) was built at GFDL, named fvGFS. The modern dynamical core, FV3, has been selected for the National Oceanic and Atmospheric Administration’s Next Generation Global Prediction System (NGGPS) due to its accuracy, adaptability, and computational efficiency, which brings a great opportunity for the unification of weather and climate prediction systems. The performance of tropical cyclone (TC) forecasts in the 13-km fvGFS is evaluated globally based on 363 daily cases of 10-day forecasts in 2015. Track and intensity errors of TCs in fvGFS are compared to those in the operational GFS. The fvGFS outperforms the GFS in TC intensity prediction for all basins. For TC track prediction, the fvGFS forecasts are substantially better over the northern Atlantic basin and the northern Pacific Ocean than the GFS forecasts. An updated version of the fvGFS with the GFDL 6-category cloud microphysics scheme is also investigated based on the same 363 cases. With this upgraded microphysics scheme, fvGFS shows much improvement in TC intensity prediction over the operational GFS. Besides track and intensity forecasts, the performance of TC genesis forecast is also compared between the fvGFS and operational GFS. In addition to evaluating the hit/false alarm ratios, a novel method is developed to investigate the lengths of TC genesis lead times in the forecasts. Both versions of fvGFS show higher hit ratios, lower false alarm ratios, and longer genesis lead times than those of the GFS model in most of the TC basins.

Open access
Mei Hong, Dong Wang, Ren Zhang, Xi Chen, Jing-Jing Ge, and Dandan Yu

Abstract

Abnormal activity of the western Pacific subtropical high (WPSH) may result in extreme weather events in East Asia. However, because the relationship between the WPSH and other components of the East Asian summer monsoon (EASM) system is unknown, it is still difficult to forecast such abnormal activity. The delay-relevant method is used to study 2010 data for abnormal weather and it is concluded that the Indian monsoon latent heat flux, the Somali low-level jet, and the Tibetan high activity index can significantly affect anomalies in the WPSH in the EASM system. By combining genetic algorithms and statistical–dynamical reconstruction theory, a nonlinear statistical–dynamical model of the WPSH and these three influencing factors was objectively reconstructed from actual 2010 data and a dynamically extended forecasting experiment was carried out. To further test the forecasting performance of the reconstructed model, further experiments using data from nine abnormal WPSH years and eight normal WPSH years were performed for comparison. All the results suggest that the forecasts of the subtropical high area index, the Indian monsoon latent heat flux, the Somali low-level jet, and the Tibetan high activity index all have good performance in the short and medium terms (<25 days). Not only is the forecasting trend accurate, but the mean absolute percentage error is ≤9%. This work suggests new areas of research into the association between the WPSH and EASM systems and provides a new method for the prediction of the WPSH area index.

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Aaron D. Kennedy, Xiquan Dong, Baike Xi, Shaocheng Xie, Yunyan Zhang, and Junye Chen

Abstract

Atmospheric states from the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the North American Regional Reanalysis (NARR) are compared with data from the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site, including the ARM continuous forcing product and Cloud Modeling Best Estimate (CMBE) soundings, during the period 1999–2001 to understand their validity for single-column model (SCM) and cloud-resolving model (CRM) forcing datasets. Cloud fraction, precipitation, and radiation information are also compared to determine what errors exist within these reanalyses. For the atmospheric state, ARM continuous forcing and the reanalyses have good agreement with the CMBE sounding information, with biases generally within 0.5 K for temperature, 0.5 m s−1 for wind, and 5% for relative humidity. Larger disagreements occur in the upper troposphere (p < 300 hPa) for temperature, humidity, and zonal wind, and in the boundary layer (p > 800 hPa) for meridional wind and humidity. In these regions, larger errors may exist in derived forcing products. Significant differences exist for vertical pressure velocity, with the largest biases occurring during the spring upwelling and summer downwelling periods. Although NARR and MERRA share many resemblances to each other, ARM outperforms these reanalyses in terms of correlation with cloud fraction. Because the ARM forcing is constrained by observed precipitation that gives the adequate mass, heat, and moisture budgets, much of the precipitation (specifically during the late spring/early summer) is caused by smaller-scale forcing that is not captured by the reanalyses. While reanalysis-based forcing appears to be feasible for the majority of the year at this location, it may have limited usage during the late spring and early summer, when convection is common at the ARM SGP site. Both NARR and MERRA capture the seasonal variation of cloud fractions (CFs) observed by ARM radar–lidar and Geostationary Operational Environmental Satellite (GOES) with high correlations (0.92–0.78) but with negative biases of 14% and 3%, respectively. Compared to the ARM observations, MERRA shows better agreement for both shortwave (SW) and longwave (LW) fluxes except for LW-down (due to a negative bias in water vapor): NARR has significant positive bias for SW-down and negative bias for LW-down under clear-sky and all-sky conditions. The NARR biases result from a combination of too few clouds and a lack of sufficient extinction by aerosols and water vapor in the atmospheric column. The results presented here represent only one location for a limited period, and more comparisons at different locations and longer periods are needed.

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