Advancements in the design and validation of an air pollution integrated assessment model for Spain

This paper describes the design and application of the Atmospheric Evaluation and Research Integrated model for Spain (AERIS). Currently, AERIS can provide concentration profiles of NO₂, O₃, SO₂, NH₃, PM, as a response to emission variations of relevant sectors in Spain. Results are calculated using transfer matrices based on an air quality modelling system (AQMS) composed by the WRF (meteorology), SMOKE (emissions) and CMAQ (atmospheric-chemical processes) models. The AERIS outputs were statistically tested against the conventional AQMS and observations, revealing a good agreement in both cases. At the moment, integrated assessment in AERIS focuses only on the link between emissions and concentrations. The quantification of deposition, impacts (health, ecosystems) and costs will be introduced in the future. In conclusion, the main asset of AERIS is its accuracy in predicting air quality outcomes for different scenarios through a simple yet robust modelling framework, avoiding complex programming and long computing times.     

Combining wind farms with concentrating solar plants to provide stable renewable power

We evaluate the extent to which a combination of wind power and concentrating solar power (CSP) may lead to stable and even baseload power by taking advantage of: 1) spatiotemporal balancing of solar and wind energy resources and 2) storage capabilities of CSP plants. A case study is conducted for the region of Andalusia in Spain. To this end, spatiotemporal variability of modeled CSP and wind capacity factors in a 3-km spatial resolution grid were analyzed based on principal component analysis (PCA) and canonical correlation analysis (CCA). Results reveal that renewable baseload power can be obtained in the study region by locating wind farms and CSP plants using balancing patterns derived from CCA and PCA. In addition, the power fluctuation reduction attained from these patterns was substantially higher than those obtained by interconnecting randomly-located wind farms and CSP plants across the study region. Results were particularly meaningful for the winter season. Upon considering storage capability of the CSP plants, results proved better. The main difference was a higher firm capacity value associated with spring and summer seasons. For the other seasons, the contribution of thermal storage capabilities of the CSP plants to stable power proved less relevant.     

Coastal trapped waves in the southern Caspian Sea

Previous studies reported coastal trapped waves (CTWs) in the Caspian Sea (CS). This study deals with the generation mechanisms, the temporal and spatial variability of CTWs in this area, and their transformations during propagation from the origin to the destination using recent measurements and high-resolution numerical simulations. CTWs are observed at all stations with periods of 2–6 days after northerly storms. The Absheron Peninsula, old Sefidrud delta, and Nur coasts were identified as the CTWs prone regions. The generation of CTWs in these locations was confirmed using numerical experiments. The propagation away from the generating location of CTWs was analyzed using a representative real wind storm. In the west part of the CS, the generation mechanism of CTWs is mainly similar to the barotropic Kelvin waves; in contrast, it is similar to the continental shelf waves in the southern shelves. The results can be used to study the contribution of generated CTWs to the transport of sediment and biological materials in all large lakes.     

Wind over complex terrain – Microscale modelling with two types of mesoscale winds at Nygårdsfjell

Nygårdsfjell, a complex terrain near Norwegian-Swedish border, is characterized by its significant wind resources. The feasibility of using mesoscale winds as input to microscale model is studied in this work. The main objective is to take into account the actual terrain effects on wind flow over complex terrain. First set of mesoscale winds are modelled with Weather Research and Forecasting (WRF) numerical tool whereas second set of mesoscale winds are taken from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) data system. WindSim, a computational fluid dynamics based numerical solver is used as microscale modelling tool. The results suggest that the performance of microscale model is largely dependent upon the quality of mesoscale winds as input. The proposed coupled models achieve improvements in wind speed modelling, especially during cold weather. WRF-WindSim coupling showed better results than MERRA-WindSim coupling in all three test cases, as root mean square error (RMSE) decreased by 70.9% for the February case, 61.5% for October and 14.4% for June case respectively. Raw mesoscale winds from the WRF model were also more correct than the mesoscale winds from MERRA data set when extracted directly at the wind turbine by decreasing the RMSE by 62.6% for the February case, 62.7% for October and 23.7% for June case respectively. The difference of RMSE values between the mesoscale winds directly at wind turbine versus the coupled meso-microscale model outputs are not conclusive enough to indicate any specific trend.     

WRF-LTNGDA: A lightning data assimilation technique implemented in the WRF model for improving precipitation forecasts

This study introduces WRF-LTNGDA, a lightning data assimilation technique implemented in the Weather Research and Forecasting (WRF) model. This technique employs lightning for improving the representation of convection by means of controlling the triggering of the model's convection parameterization scheme. The development and implementation of WRF-LTNGDA was carried out in a framework that could easily allow for its exploitation in real-time forecasting activities. The assimilation algorithm was evaluated over eight precipitation events that took place in Greece in the years 2010–2013. Results clearly show that lightning forcing has a positive impact on model performance. The conducted analysis revealed that the employment of WRF-LTNGDA induces statistically significant improvements in precipitation verification scores, especially for high rainfall accumulations. Separate examination of one of the eight case studies highlighted the overall better agreement between the modelled and observed spatial distribution of precipitation when lightning data assimilation was applied, than in the control simulation.     

中尺度风资源数值模拟试验分析

应用中尺度数值模式模拟地区的风资源状况是一种比较先进的方法。该模拟成果对大范围区域风能资源的宏观评估和风电场宏观选址具有很好的参考价值。着重介绍了WRF(Weather Research and Forecast)数值模式模拟方法,并采用该模拟方法对近海风电场的风资源进行了模拟。     

江西“2010.6.19”特大暴雨水汽输送过程分析

利用NCEP（1°×1°）再分析资料、常规气象观测资料和WRF中尺度数值模式,对2010-06-19江西出现的历史罕见特大暴雨天气水汽输送的过程进行分析。结果表明：特大暴雨天气过程的水汽输送源地以南海和孟加拉湾为主,强降水落区在水汽输送带左侧风向切变线附近。暴雨过程是由两次强降水天气过程组成：一次是19日02：00江西南部和福建南部交界处的中尺度系统北抬形成的赣北暴雨;另一次是19日20：00由湖南中尺度气旋及其后续的中尺度系统东移造成的大范围暴雨。利用WRF数值模式对整层水汽输送进行高分辨力数值模拟发现,暴雨落区出现在整层水汽输送最大值区域和梯度最大处,且整层水汽输送方向为西南-东北走向。     

Evaluation of basidiomycetous fungi for pretreatment of contaminated soil

BACKGROUND: For most dioxin‐contaminated sawmill soils, combustion is recommended. However, the process may be inefficient if the soil has a high organic matter content. The use of saprotrophic basidiomycetous fungi is an alternative for pretreatment of this kind of soil. A total of 147 fungi were evaluated for their ability to grow in sawmill soil. From this screening, the best soil colonizing fungi were selected to study their enzyme activities and degradation of soil organic matter. Pine (Pinus sylvestris) bark was used as a co‐substrate to propagate the fungi into the soil. The activities of manganese peroxidase (MnP), laccase, endo‐1,4‐β‐glucanase, endo‐1,4‐β‐xylanase, and endo‐1,4‐β‐mannanase were analysed from the inocula and fungal treated soil. RESULTS: The screening revealed that 56 out of 147 fungi were able to grow in non‐sterile soil, and most of them were litter‐decomposing fungi (LDF). In pine bark cultures, the highest enzyme activities were observed with Phanerochaete velutina, which produced 5 U g^?1 of MnP. The activity of endo‐1,4‐β‐glucanase was generally higher than that of other hydrolytic enzymes. The highest carbon loss from soil with a high organic matter content was achieved by P. velutina (3.4%) and Stropharia rugosoannulata (2.4%). CONCLUSIONS: Many LDF, and in addition the white‐rot fungus P. velutina, are potential degraders of soil organic matter since they showed good growth and respiratory activity. Pine bark was a suitable lignocellulosic co‐substrate and a good promoter of MnP activity. Copyright © 2009 Society of Chemical Industry     

Effects of sea surface temperature accuracy on offshore wind resource assessment using a mesoscale model

Offshore wind simulations were performed with the Weather Research and Forecasting (WRF) model driven by three different sea surface temperature (SST) datasets for Japanese coastal waters to investigate the effect of the SST accuracies on offshore wind simulations. First, the National Centers for Environmental Prediction Final analysis (FNL) (1° × 1° grid resolution) and the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) (0.05° × 0.05° grid resolution) datasets were compared with in situ measurements. The results show a decrease in accuracy of these datasets toward the coast from the open ocean. Aiming at an improved accuracy of SST data, we developed a new high‐resolution SST dataset (0.02° × 0.02° grid resolution). The new dataset referred to as MOSST is based on the Moderate Resolution Imaging Spectroradiometer (MODIS) product, provided by the Japan Aerospace Exploration Agency (JAXA). MOSST was confirmed to be more accurate than FNL and OSTIA for the coastal waters. Then, WRF simulations were carried out for 1 year with a 2 km grid resolution and by using the FNL, OSTIA and MOSST datasets. The use of the OSTIA dataset for a WRF simulation was found to improve the accuracy when compared with the FNL dataset, and further improvement was obtained when the MOSST dataset was applied. The sensitivity of wind speed and wind energy density to SST is also discussed. We conclude that the use of an accurate SST is a key factor not only for realistic offshore wind simulations near the surface but also for accurate wind resource assessments at the hub height of wind turbines. Copyright © 2014 John Wiley & Sons, Ltd.     

不同物理参数化方案对黄河源区降雨模拟的适用性研究

为分析不同物理参数化方案在模拟黄河源区降水时的适用性,采用中尺度WRF模式中常用的5种微物理方案和3种积云对流方案进行组合,模拟黄河源区的一次降水过程,利用直方图曼哈顿距离相似度对模拟结果和实况降水空间分布进行对比,并分析各方案组合模拟的降水中心(河南站)逐小时降水分布和24h累积降水量,以得到WRF模式模拟黄河源区降水的最优方案配置,提高模拟精度。结果表明,WRF模式的各方案基本可以再现降水强度、中心和范围,基于Morrison方案的组合对降水的还原能力较好;就降水中心的降水时间序列和24h累积降水量来看,基于Morrison方案的组合与实际降水的一致性较好;Morrison微物理方案和Grell 3积云对流方案组合的模拟结果与实际降水的空间分布相似度最高,表明该方案组合是WRF模式模拟黄河源区降水过程的最优模拟方案。研究成果对于提高黄河源区降水模拟的精度有重要意义。