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.

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.

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.

A data-adaptive network design for the regional gravity field modelling using spherical radial basis functions

A high-precision regional gravity field model is significant in various geodesy applications.In the field of modelling regional gravity fields,the spherical radial basis functions(SRBFs)approach has recently gained widespread attention,while the modelling precision is primarily influenced by the base function network.In this study,we propose a method for constructing a data-adaptive network of SRBFs using a modified Hierarchical Density-Based Spatial Clustering of Applications with Noise(HDBSCAN)algorithm,and the performance of the algorithm is verified by the observed gravity data in the Auvergne area.Furthermore,the turning point method is used to optimize the bandwidth of the basis function spectrum,which satisfies the demand for both high-precision gravity field and quasi-geoid modelling simultaneously.Numerical experimental results indicate that our algorithm has an accuracy of about 1.58 mGal in constructing the gravity field model and about 0.03 m in the regional quasi-geoid model.Compared to the existing methods,the number of SRBFs used for modelling has been reduced by 15.8%,and the time cost to determine the centre positions of SRBFs has been saved by 12.5%.Hence,the modified HDBSCAN algorithm presented here is a suitable design method for constructing the SRBF data adaptive network.

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.

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.

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.

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.

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.

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.

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.

Projections of Wind Changes for 21st Century in China by Three Regional Climate Models

This paper examines the capability of three regional climate models (RCMs), i.e., RegCM3 (the International Centre for Theoretical Physics Regional Climate Model), PRECIS (Providing Regional Climates for Impacts Studies) and CMM5 (the fifth-generation Pennsylvania State University-the National Center for Atmospheric Research of USA, NCAR Mesoscale Model) to simulate the near-surface-layer winds (10 m above surface) all over China in the late 20th century. Results suggest that like global climate models (GCMs), these RCMs have the certain capability of imitating the distribution of mean wind speed and fail to simulate the greatly weakening wind trends for the past 50 years in the country. However, RCMs especially RegCM3 have the better capability than that of GCMs to simulate the distribution and change feature of mean wind speed. In view of their merits, these RCMs were used to project the variability of near-surface-layer winds over China for the 21st century. The results show that 1) summer mean wind speed for 2020-2029 will be lower compared to those in 1990-1999 in most area of China; 2) annual and winter mean wind speed for 2081-2100 will be lower than those of 1971-1990 in the whole China; and 3) the changes of summer mean wind speed for 2081-2100 are uncertain. As a result, although climate models are absolutely necessary for projecting climate change to come, there are great uncertainties in projections, especially for wind speed, and these issues need to be further explored.

SIMULATION OF PRESENT CLIMATE OVER EAST ASIA BY A REGIONAL CLIMATE MODEL

A 15-year simulation of climate over East Asia is conducted with the latest version of a regional climate model RegCM3 nested in one-way mode to the ERA40 Re-analysis data. The performance of the model in simulating present climate over East Asia and China is investigated. Results show that RegCM3 can reproduce well the atmospheric circulation over East Asia. The simulation of the main distribution patterns of surface air temperature and precipitation over China and their seasonal cycle/evolution, are basically agree with that of the observation. Meanwhile a general cold bias is found in the simulation. As for the precipitation, the model tends to overestimate the precipitation in northern China while underestimate it in southern China, particularly in winter. In general, the model has better performance in simulating temperature than precipitation.