A Hybrid Regional Model for Predicting Ground Deformation Induced by Large-Section Tunnel Excavation

Due to the large number of finite element mesh generated,it is difficult to use full-scale model to simulate largesection underground engineering,especially considering the coupling effect.A regional model is attempted to achieve this simulation.A variable boundary condition method for hybrid regional model is proposed to realize the numerical simulation of large-section tunnel construction.Accordingly,the balance of initial ground stress under asymmetric boundary conditions achieves by applying boundary conditions step by step with secondary development ofDynaflowscripts,which is the key issue of variable boundary conditionmethod implementation.In this paper,Gongbei tunnel based on hybrid regional model involvingmulti-field coupling is simulated.Meanwhile,the variable boundary condition method for regional model is verified against model initialization and the ground deformation due to tunnel excavation is predicted via the proposed hybrid regional model.Compared with the monitoring data of actual engineering,the results indicated that the hybrid regional model has a good prediction effect.

Effect of Counter-Gradient in the Computation of Turbulent Fluxes of Heat and Moisture in a Regional Model

The counter-gradient terms in the computations of turbulent fluxes of heat and moisture have been included in the PBL parameterization of a regional model for monsoon prediction. Results show that inclusion of counter-gradient terms has a marginal impact in the prediction of large scale monsoon circulation and rainfall rates.

Assessing the Impact of Using Different Land Cover Classification in Regional Modeling Studies for the Manaus Area,Brazil

Land cover classification is one of the main components of the modern weather research and forecasting models, which can influence the meteorological variable, and in turn the concentration of air pollutants. In this study the impact of using two traditional land use classifications, the United States Geological Survey (USGS) and the Moderate-resolution Imaging Spectroradiometer (MODIS), were evaluated. The Weather Research and Forecasting model (WRF, version 3.2.1) was run for the period 18 - 22 August, 2014 (dry season) at a grid spacing of 3 km centered on the city of Manaus. The comparison between simulated and ground-based observed data revealed significant differences in the meteorological fields, for instance, the temperature. Compared to USGS, MODIS classification showed better skill in representing observed temperature for urban areas of Manaus, while the two files showed similar results for nearby areas. The analysis of the files suggests that the better quality of the simulations favorable to the MODIS file is straightly related to its better representation of urban class of land use, which is observed to be not adequately represented by USGS.

Characteristics of Anthropogenic Sulfate and Carbonaceous Aerosols over East Asia: Regional Modeling and Observation

The authors present spatial and temporal characteristics of anthropogenic sulfate and carbonaceous aerosols over East Asia using a 3-D coupled regional climate-chemistry-aerosol model, and compare the simulation with the limited aerosol observations over the region. The aerosol module consists of SO2, SO4^2-, hydrophobic and hydrophilic black carbon （BC） and organic carbon compounds （OC）, including emission, advections, dry and wet deposition, and chemical production and conversion. The simulated patterns of SO2 are closely tied to its emission rate, with sharp gradients between the highly polluted regions and more rural areas. Chemical conversion （especially in the aqueous phase） and dry deposition remove 60% and 30% of the total SO2 emission, respectively. The SO4^2- shows less horizontal gradient and seasonality than SO2, with wet deposition （60%） and export （27%） being two major sinks. Carbonaceous aerosols are spatially smoother than sulfur species. The aging process transforms more than 80% of hydrophobic BC and OC to hydrophilic components, which are removed by wet deposition （60%） and export （30%）. The simulated spatial and seasonal SO4^2-, BC and OC aerosol concentrations and total aerosol optical depth are generally consistent with the observations in rural areas over East Asia, with lower bias in simulated OC aerosols, likely due to the underestimation of anthropogenic OC emissions and missing treatment of secondary organic carbon. The results suggest that our model is a useful tool for characterizing the anthropogenic aerosol cycle and for assessing its potential climatic and environmental effects in future studies.

Study of the geomagnetic field's regional gradients in Chinese continent using three-dimensional surface Spline model

We combined domestic ground-based and satellite magnetic measurements to create a regional three-dimensional surface Spline(3DSS)gradient model of the main geomagnetic field over the Chinese continent.To improve the precision of the model,we considered the data gap between the ground and satellite data.We compared and analyzed the results of the Taylor polynomial,surface Spline,and CHAOS-6(the CHAMP,?rsted and SAC-C model of Earth’s magnetic field)gradient models.Results showed that the gradients in the south-north and east-west directions of the four models were consistent.The 3DSS model was able to express not only gradients at different altitudes,but also average gradients inside the research area.The two Spline models were able to capture more information on gradient anomalies than were the fitted models.Strong local anomalies were observed in northern Xinjiang,Beijing,and the junction area between Jiangsu and Zhejiang,and the total intensity F decreased whereas the altitude increased.The gradient decreased by 21.69%in the south-north direction and increased by 11.78%in the east-west direction.In addition,the altitude gradient turned from negative to positive while the altitude increased.The Spline model and the two fitted models differed mainly in the field sources they expressed and the modeling theory.

Short-term Photovoltaic Power Forecasting Using SOM-based Regional Modelling Methods

The inherent intermittency and uncertainty of photovoltaic(PV)power generation impede the development of grid-connected PV systems.Accurately forecasting PV output power is an effective way to address this problem.A hybrid forecasting model that combines the clustering of a trained self-organizing map(SOM)network and an optimized kernel extreme learning machine(KELM)method to improve the accuracy of short-term PV power generation forecasting are proposed.First,pure SOM is employed to complete the initial partitions of the training dataset;then the fuzzy c-means(FCM)algorithm is used to cluster the trained SOM network and the Davies-Bouldin index(DBI)is utilized to determine the optimal size of clusters,simultaneously.Finally,in each data partition,the clusters are combined with the KELM method optimized by differential evolution algorithm to establish a regional KELM model or combined with multiple linear regression(MR)using least squares to complete coefficient evaluation to establish a regional MR model.The proposed models are applied to one-hour-ahead PV power forecasting instances in three different solar power plants provided by GEFCom2014.Compared with other single global models,the root mean square errors(RMSEs)of the proposed regional KELM model are reduced by 52.06%in plant 1,54.56%in plant 2,and 51.43%in plant 3 on average.Such results demonstrate that the forecasting accuracy has been significantly improved using the proposed models.In addition,the comparisons between the proposed and existing state-of-the-art forecasting methods presented have demonstrated the superiority of the proposed methods.The forecasts of different methods in different seasons revealed the strong robustness of the proposed method.In four seasons,the MAEs and RMSEs of the proposed SF-KELM are generally the smallest.Moreover,the R2 value exceeds 0.9,which is the closest to 1.

Zoning Evaluation of Hourly Precipitation in High-resolution Regional Numerical Models over Hainan Island

This study assesses the performance of three high-resolution regional numerical models in predicting hourly rainfall over Hainan Island from April to October for the years from 2020 to 2022.The rainfall amount,frequency,intensity,duration,and diurnal cycle are examined through zoning evaluation.The results show that the China Meteor-ological Administration Guangdong Rapid Update Assimilation Numerical Forecast System(CMA-GD)tends to forecast a higher occurrence of light precipitation.It underestimates the late afternoon precipitation and the occurrence of short-duration events.The China Meteorological Administration Shanghai Numerical Forecast Model System(CMA-SH9)reproduces excessive precipitation at a higher frequency and intensity throughout the island.It overestimates rainfall during the late afternoon and midnight periods.The simulated most frequent peak times of rainfall in CMA-SH9 are 0-1 hour deviations from the observed data.The China Meteorological Administration Mesoscale Weather Numerical Forecasting System(CMA-MESO)displays a similar pattern to rainfall observations but fails to replicate reasonable structure and diurnal variation of frequency-intensity.It underestimates the occurrence of long-duration events and overestimates related rainfall amounts from midnight to early morning.Notably,significant discrepancies are observed in the predictions of the three models for areas with complex terrain,such as the central,southeastern,and southwestern regions of Hainan Island.

Regional Finite-Fault Source Model for Development of Ground Motion Attenuation Relationship in Sichuan, China

The attenuation relationship of ground motion based on seismology has always been a front subject of engineering earthquake.Among them,the regional finite-fault source model is very important.In view of this point,the general characteristics of regional seism-tectonics,including the dip and depth of the fault plane,are emphasized.According to the statistics of regional seism-tectonics and focal mechanisms in Sichuan,China,and the sensitivity of estimated peak ground acceleration(PGA)attenuation is analyzed,and the dip angle is taken as an average of 70°.Based the statistics of the upper crustal structure and the focal depth of regional earthquakes,the bottom boundary of the sedimentary cover can be used as the upper limit for estimating the depth of upper-edge.The analysis shows that this value is sensitive to PGA.Based on the analysis of geometric relations,the corresponding calculation formula is used,and a set of concepts and steps for building the regional finite-fault source model is proposed.The estimation of source parameters takes into account the uncertainty,the geometric relationship among parameters and the total energy conservation.Meanwhile,a set of reasonable models is developed,which lay a foundation for the further study of regional ground motion attenuation based on seismology.

Identification of thermal front dynamics in the northern Malacca Strait using ROMS 3D-model

The thermal front in the oceanic system is believed to have a significant effect on biological activity.During an era of climate change,changes in heat regulation between the atmosphere and oceanic interior can alter the characteristics of this important feature.Using the simulation results of the 3D Regional Ocean Modelling System(ROMS),we identified the location of thermal fronts and determined their dynamic variability in the area between the southern Andaman Sea and northern Malacca Strait.The Single Image Edge Detection(SIED)algorithm was used to detect the thermal front from model-derived temperature.Results show that a thermal front occurred every year from 2002 to 2012 with the temperature gradient at the location of the front was 0.3°C/km.Compared to the years affected by El Ni?o and negative Indian Ocean Dipole(IOD),the normal years(e.g.,May 2003)show the presence of the thermal front at every selected depth(10,25,50,and 75 m),whereas El Ni?o and negative IOD during 2010 show the presence of the thermal front only at depth of 75 m due to greater warming,leading to the thermocline deepening and enhanced stratification.During May 2003,the thermal front was separated by cooler SST in the southern Andaman Sea and warmer SST in the northern Malacca Strait.The higher SST in the northern Malacca Strait was believed due to the besieged Malacca Strait,which trapped the heat and make it difficult to release while higher chlorophyll a in Malacca Strait is due to the freshwater conduit from nearby rivers(Klang,Langat,Perak,and Selangor).Furthermore,compared to the southern Andaman Sea,the chlorophyll a in the northern Malacca Strait is easier to reach the surface area due to the shallower thermocline,which allows nutrients in the area to reach the surface faster.

A zenith tropospheric delay correction model based on the regional CORS network

Tropospheric delay is a primary error source in earth observations and a variety of radio navigation technologies. In this paper, the relationship between zenith tropospheric delays and the elevation and longitude of stations is analyzed using the zenith tropospheric delay final products of International GNSS Service （IGS） stations from 2011. Two new models are proposed for estimating zenith tropospheric delays from regional CORS data without meteorological data. The proposed models are compared with the direct interpolation method and the remove-restore method using data from Guangxi CORS. The results show that the new models significantly improve the calculated precision. Finally, the root mean square （RMS） errors of the new models were used to estimate the surface precipitable water vapor （PWV） value at CORS station, which was determined to be less than 2 mm.

Numerical Simulations of Intense Meiyu Rainfall in 1991 over the Changjiang and Huaihe River Valleys by a Regional Climate Model with p-σ Incorporated Coordinate System

Based on the primitive equation model with p- σ incorporated coordinate system originally developed by Qian et al., a one-way nested fine mesh limited area model is developed. This model is nested with ECMWF T42 data to simulate the extra-intensive rainfall event occurring in the Changjiang and Huaihe River valleys in summer of 1991. The results show that the model has certain capacity to fairly reproduce the regional distribution and the movement of the main rainfall belts. Therefore it can be used as a regional climate model to simulate and predict the short-range regional climate changes.

A REGIONAL MODEL STUDY OF THE VARIATIONS AND DISTRIBUTIONS OF OZONE AND ITS PRECURSORS ON EASTERN ASIA AND WEST PACIFIC OCEAN REGIONS

A simulated study of mechanism for variations and distributions of ozone and its precursors was made by using the three-dimensional regional Eulerian model.The results showed that the ozone production was controlled by NO,but there is a complicated nonlinear relation between them.The photochemical reactions controlled by solar radiation are the determinative factors affecting the variations of the surface ozone and its precursors.The relations of ozone and CO, PAN were studied.We compared the simulated and observed results during the PEM-WEST A in order to better under- stand the photochemical processes of ozone and its precursors.

GPS-based regional ionospheric models and their suitability in Antarctica

There are a number of ionospheric models available for research and application, such as the polynomial model, generalized trigonometric series function model, low degree spherical harmonic function model, adjusted spherical harmonic function model, and spherical cap harmonic function analysis. Using observations from more than 40 continuously operating stations across Antarctica in 2010, ifve models are compared with regard to their precision and applicability to polar regions. The results show that all the models perform well in Antarctica with 0.1 TECU of residual mean value and 2 TECU of root mean square error.

A coupled regional Arctic sea ice-ocean model:configuration and application

A regional sea ice-ocean coupled model for the Arctic Ocean was developed, based on the MlTgcm ocean circulation model and classical Hibler79 type two category thermodynamics-dynamics sea ice model.The sea ice dynamics and thermodynamics were considered based on Viscous-Plastic（VP） and Winton three-layer models,respectively.A detailed configuration of coupled model has been introduced.Special attention has been paid to the model grid setup,subgrid paramerization,ice-ocean coupling and open boundary treatment.The coupled model was then applied and two test run examples were presented.The first model run was a climatology simulation with 10 years（1992—2002） averaged NCAR/NCEP reanalysis data as atmospheric forcing.The second model run was a seasonal simulation for the period of 1992—2007.The atmospheric forcing was daily NCAR/NCEP reanalysis.The climatology simulation captured the general pattern of the sea ice thickness distribution of the Arctic,i.e.,the thickest sea ice is situated around the Canada Archipelago and the north coast of the Greenland. For the second model run,the modeled September Sea ice extent anomaly from 1992—2007 was highly correlated with the observations,with a linear correlation coefficient of 0.88.The minimum of the Arctic sea ice area in the September of 2007 was unprecedented.The modeled sea ice area and extent for this minimum was overestimated relative to the observations.However,it captured the general pattern of the sea ice retreat.

A regional suspended load yield estimation model for ungauged watersheds

Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applicability of these models. Therefore, data reduction techniques(DRTs), e.g., principal component analysis(PCA), Gamma test(GT), and stepwise regression(SR), have been used to select the most effective variables. The artificial neural network(ANN) and multiple linear regression(MLR) are also common tools for SLY modeling. We conducted this study(1) to obtain the most effective variables influencing SLY through DRTs including PCA, GT, and SR, and then, to use them as input data for ANN and MLR; and(2) to provide the best SLY models. Accordingly, we used 14 physiographic, climatic, and hydrologic parameters from 42 watersheds in the Hyrcanian forest region(in northern Iran). The most effective variables as determined through DRTs as well as the original data sets were used as the input data for ANN and MLR in order to provide an SLY model. The results indicated that the SLY models provided by ANN performed much better than the MLR models, and the GT-ANN model was the best. The determination of coefficient,relative error, root mean square error, and bias were 99.9%, 26%, 323 t/year, and 6 t/year in the calibration period, and 70%, 43%, 456 t/year, and 407 t/year in the validation period, respectively. Overall, selecting the main factors that influence SLY and using artificial intelligence tools can be useful for water resources managers to quickly determine the behavior of SLY in ungauged watersheds.

An Input–Output Ex Ante Regional Model to Assess the Short-Term Net Effects of the 16 April 2016 Earthquake in Ecuador

The 16 April 2016 earthquake in Ecuador exposed the significant weaknesses concerning the methodological designs to compute—from an economic standpoint—the consequences of a natural hazard-related disaster for productive exchanges and the accumulation of capital in Ecuador.This study addressed one of these challenges with an innovative ex ante model to measure the partial and net short-term effects of a natural hazard-related catastrophe from an interregional perspective,with the 16 April 2016 earthquake serving as a case study.In general,the specified and estimated model follows the approach of the extended Miyazawa model,which endogenizes consumption demand in a standard input–output model with the subnational interrelations and resulting multipliers.Due to the country’s limitations in its regional account records the input–output matrices for each province of Ecuador had to be estimated,which then allowed transactions carried out between any two sectors within or outside a given province to be identified by means of the RAS method.The estimations provide evidence that the net short-term impact on the national accounts was not significant,and under some of the simulated scenarios,based on the official information with respect to earthquake management,the impact may even have had a positive effect on the growth of the national product during 2016.

Multi-Year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model (RegCM_NCC) Part Ⅱ:The Experimental Seasonal Prediction

A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM） provides the boundary and initial conditions for driving the regional climate model （RegCM_NCC）. The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme （TKE） and an improved land process model （LPM）. The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part Ⅰ. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model＇s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM_NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast （1991-2000） for summer （June-August）, the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM_NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient （ACC） are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM_NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM-NCC were made. The results are basically reasonable compared with the observations.

Multi-year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model (RegCM_NCC). Part Ⅰ: Sensitivity Study

A modified version of the NCAR/RegCM2 has been developed at the National Climate Center （NCC）, China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year （2001 to 2004） prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process paraxneterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme （MFS） and Betts-Miller scheme （BM） for convective precipitation, the LPMI （land surface process model I） and LPMII （land surface process model Ⅱ） for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE （turbulent kinetic energy） scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 （RegCM_NCC） has been set up for climate simulations and seasonal predictions.

Simulation of Effects of Land Use Change on Climate in China by a Regional Climate Model

Climate effects of land use change in China as simulated by a regional climate model (RegCM2) are investigated. The model is nested in one-way mode within a global coupled atmosphere-ocean model (CSIRO R21L9 AOGCM). Two multi-year simulations, one with current land use and the other with potential vegetation cover, are conducted. Statistically significant changes of precipitation, surface air temperature, and daily maximum and daily minimum temperature are analyzed based on the difference between the two simulations. The simulated effects of land use change over China include a decrease of mean annual precipitation over Northwest China, a region with a prevalence of arid and semi-arid areas; an increase of mean annual surface air temperature over some areas; and a decrease of temperature along coastal areas. Summer mean daily maximum temperature increases in many locations, while winter mean daily minimum temperature decreases in East China and increases in Northwest China. The upper soil moisture decreases significantly across China. The results indicate that the same land use change may cause different climate effects in different regions depending on the surrounding environment and climate characteristics.

Climate Change due to Greenhouse Effects in China as Simulated by a Regional Climate Model

Impacts of greenhouse effects (2 × CO2) upon climate change over China as simulated by a regional climate model over China (RegCM / China) have been investigated. The model was based on RegCM2 and was nested to a global coupled ocean-atmosphere model (CSIRO R21L9 AOGCM model). Results of the control run (1 × CO2) indicated that simulations of surface air temperature and precipitation in China by RegCM are much better than that by the global coupled model because of a higher resolution. Results of sensitive experiment by RegCM with 2 × CO2 showed that the surface air temperature over China might increase remarkably due to greenhouse effect, especially in winter season and in North China. Precipitation might also increase in most parts of China due to the CO2 doubling. Key words Regional climate model - Greenhouse effect This research was supported by National Key Programme for Developing Basic Sciences (G1998040900 — Part I), Chinese Academy of Sciences Key Program KZCX2-203 and KZ981-B1-108.