Modelling of the nighttime nitrogen and sulfur chemistry in size resolved droplets of an orographic cloud

A chemistry module has been incorporated into a Lagrangian type model that computes the dynamics and microphysics of an orographical cloud formed in moist air flowing over the summit of Great Dun Fell (GDF) in England. The cloud droplets grow on a maritime aerosol which is assumed to be an external mixture of sea-salt particles and ammonium-sulfate particles. The dry particle radii are in the range 10 nm<r<1 µm. The gas-phase chemical reaction scheme considers reactions of nitrogen compounds that are important at night. The treatment of scavenging of gases into the aqueous phase in the model takes into account the different solubilities and accommodation coefficients. The chemistry in the aqueous phase focusses on the oxidation of S(IV) via different pathways.Sensitivity analyses have been performed to investigate deviations from gas-liquid equilibria according to Henry's law and also to study the influence of iron and of nitrogen compounds on the aqueous-phase oxidation of dissolved SO₂. When addressing these questions, special attention has been given to the dependence on the droplet size distribution and on the chemical composition of the cloud condensation nuclei on which the droplets have formed. It was found that the oxidation of S(IV) via a chain reaction of sulfur radicals can be important under conditions where H₂O₂ is low. However, major uncertainties remain with respect to the interaction of iron with the radical chain. It was shown that mixing of individual cloud droplets, which are not in equilibrium according to Henry's law, can result in a bulk sample in equilibrium with the ambient air. The dependence of the aqueous-phase concentrations on the size of the cloud droplets is discussed for iron, chloride and NO₃.     

Application of a Shape-Preserving Advection Scheme to the Moisture Equation in an E-grid Regional Forecast Model

This paper presents a methodology which is very useful to design shape-preserving advection finite difference scheme on general E-grid horizontal arrangement of variables through introducing a two-step shape-preserving positive definite advection scheme in the moisture equation of the LASG-REM (LASG regional E-grid eta-coordinate forecast model). By trial-forecasting six local heavy raincases, the efficiency of the shape-preserving advection scheme in practical application has been examined. The LASG-REM with the shape-preserving advection scheme has a good forecasting ability for local precipitation.     

变步长显式完全平方守恒差分格式

综合隐式完全平方守恒差分格式和显式瞬时平方守恒差分格式的优点，针对一类非线性发展方程构造了一种通过自动调节时间步长来保持平方守恒性的显式差分格式。它基于加小耗散的思想，但又与小耗散法有所不同。本文取的耗散项不是一般的人工耗散，而是取能够弥补由于时间离散所产生的截断误差的所谓（时间）协调耗散。因此，该格式具有较高的时间精度。在数值试验中，该类格式可取得满意的效果。     

中尺度暴雨云团发生发展前的一些征兆

利用湿有效能量方法找出了盛夏午后北京地区中尺度暴雨云团发生发展的一些征兆：（１）北京地区已贮存着大量能量；（２）湿有效能量正在北京地区积聚；（３）低层流场结构有利于出现强迫抬升；（４）北京地区与河套地区之间午后将出现非绝热加热形成的巨大水平温差。     

Modeling Atmospheric Chemistry: Interactions between Gas-Phase Species and Liquid Cloud/Aerosol Particles

For detailed modeling of atmospheric chemistry it is necessary to consider aqueous-phase reactions in cloud droplets and deliquesced aerosol particles. Often, the gas-phase concentration is in equilibrium with the aqueous phase. Then Henrys law can be used to describe the distribution between the phases provided that the Henrys law coefficient is known. In some cases, thermodynamic equilibrium will not be reached and it is necessary to use kinetic expressions of the rates involved. These rates depend on diffusion constants, accommodation coefficients, Henrys law coefficients, particle size distributions, and several other parameters. This review describes how these processes can be treated in computer modeling and how the necessary data can be obtained. Even though it is written primarily for use in modeling atmospheric chemistry, some parts will also be useful for waste water and pesticide control and in other areas where the distribution of chemicals between the aqueous and the gas phase is important.     

优选土层锚杆围护体设计方案的计算机实现

介绍了土层锚杆围护体（包括墙体和锚杆支护结构）的方案优选计算机系统的功能和特色,讨论了其计算机实现方法,以及利用系统进行以工程要求和工程成本为目标的土层锚杆围护体设计方案优选的思路和方法     

Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud

ABSTRACT

The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (≥250-m) cropland maps lack precision in geo-location of individual farms and have low map accuracies. This also results in uncertainties in cropland areas calculated from such products. Thereby, the overarching goal of this study was to develop a high spatial resolution (30-m or better) baseline cropland extent product of South Asia for the year 2015 using Landsat satellite time-series big-data and machine learning algorithms (MLAs) on the Google Earth Engine (GEE) cloud computing platform. To eliminate the impact of clouds, 10 time-composited Landsat bands (blue, green, red, NIR, SWIR1, SWIR2, Thermal, EVI, NDVI, NDWI) were derived for each of the three time-periods over 12 months (monsoon: Days of the Year (DOY) 151–300; winter: DOY 301–365 plus 1–60; and summer: DOY 61–150), taking the every 8-day data from Landsat-8 and 7 for the years 2013–2015, for a total of 30-bands plus global digital elevation model (GDEM) derived slope band. This 31-band mega-file big data-cube was composed for each of the five agro-ecological zones (AEZ’s) of South Asia and formed a baseline data for image classification and analysis. Knowledge-base for the Random Forest (RF) MLAs were developed using spatially well spread-out reference training data (N = 2179) in five AEZs. The classification was performed on GEE for each of the five AEZs using well-established knowledge-base and RF MLAs on the cloud. Map accuracies were measured using independent validation data (N = 1185). The survey showed that the South Asia cropland product had a producer’s accuracy of 89.9% (errors of omissions of 10.1%), user’s accuracy of 95.3% (errors of commission of 4.7%) and an overall accuracy of 88.7%. The National and sub-national (districts) areas computed from this cropland extent product explained 80-96% variability when compared with the National statistics of the South Asian Countries. The full-resolution imagery can be viewed at full-resolution, by zooming-in to any location in South Asia or the world, at www.croplands.org and the cropland products of South Asia downloaded from The Land Processes Distributed Active Archive Center (LP DAAC) of National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS): https://lpdaac.usgs.gov/products/gfsad30saafgircev001/.     

Assessing global Sentinel-2 coverage dynamics and data availability for operational Earth observation (EO) applications using the EO-Compass

ABSTRACT

Sentinel-2 scenes are increasingly being used in operational Earth observation (EO) applications at regional, continental and global scales, in near-real time applications, and with multi-temporal approaches. On a broader scale, they are therefore one of the most important facilitators of the Digital Earth. However, the data quality and availability are not spatially and temporally homogeneous due to effects related to cloudiness, the position on the Earth or the acquisition plan. The spatio-temporal inhomogeneity of the underlying data may therefore affect any big remote sensing analysis and is important to consider. This study presents an assessment of the metadata for all accessible Sentinel-2 Level-1C scenes acquired in 2017, enabling the spatio-temporal coverage and availability to be quantified, including scene availability and cloudiness. Spatial exploratory analysis of the global, multi-temporal metadata also reveals that higher acquisition frequencies do not necessarily yield more cloud-free scenes and exposes metadata quality issues, e.g. systematically incorrect cloud cover estimation in high, non-vegetated altitudes. The continuously updated datasets and analysis results are accessible as a Web application called EO-Compass. It contributes to a better understanding and selection of Sentinel-2 scenes, and improves the planning and interpretation of remote sensing analyses.     

基于RegCM4.6的中国地区云对地表太阳辐射的影响研究

使用RegCM4.6区域气候模式，选取Emanuel和Mix（Grell+Emanuel）两种积云对流参数化方案，以2016年为例，分别对中国地区云短波辐射强迫及其涉及的物理量进行数值模拟，揭示其时空分布特征，并探究两种积云对流参数方案模拟效果的差异及其原因。结果表明：从季节平均来看，全国地表云短波辐射强迫均为负值，云对地表为冷却效应，冬季最小，春夏季较大。塔里木盆地四季均为辐射强迫低值区，夏季冷却效应最弱，辐射强迫绝对值低于40 W·m-2；全天空地表净短波辐射分布也呈显著季节差异，除夏季外均呈由南向北逐渐递减的分布趋势；晴空地表净短波辐射在横断山脉处和塔里木盆地处均比较低，其中春季最为明显；两个方案所得的季节空间分布特征大致相同，但在数值上存在差异。春季时全国大部分地区全天空地表净短波辐射通量差异最大，在55 W·m-2左右，晴空地表净短波辐射通量在青藏高原处差异在60W·m-2左右。