ALBERT

Description: The optical properties and chemical composition of PM1.0 (particulate with an aerodynamic diameter of less than 1.0 μm) particles in a suburban environment (Huairou) near the mega-city Beijing were measured during the HOPE-J3A (Haze Observation Project Especially for Jing-Jin-Ji Area) field campaign. The campaign covered the period November 2014 to January 2015 during the winter coal heating season. The average and standard deviations for the extinction, scattering, absorption coefficients, and the aerosol single scattering albedo (SSA) at λ = 470 nm during the measurement period were 201 ± 240, 164 ± 202, 37 ± 43 Mm-1, and 0.80 ± 0.08, respectively. The mean mass scattering (MSE) and absorption (MAE) efficiencies were 4.77 ± 0.01 and 0.87 ± 0.03 m2g-1, respectively. Highly time-resolved air pollution episodes clearly show the dramatic evolution of the PM1.0 size distribution, extensive optical properties (extinction, scattering, and absorption coefficients) and intensive optical properties (single scattering albedo and complex refractive index) during haze formation, development and decline. Time periods were classified into three different pollution levels (clear, slightly polluted, and polluted) for further analysis. It was found that: (1) The diurnal patterns of the aerosol extinction, scattering, absorption coefficients, and SSA differed for the three pollution classes. (2) The real and imaginary part of complex refractive index (CRI) increased, while the SSA decreased from clear to polluted days. (3) The relative contributions of organic and inorganic species to observed aerosol composition changed significantly from clear to polluted days: the organic mass fraction decreased (50 to 43 %) while the proportion of sulfates, nitrates, and ammonium increased strongly (34 to 44 %). (4) The fractional contribution of chemical components to extinction coefficients was calculated by using the modified IMPROVE algorithm. Organic mass was the largest contributor (58 %) to the total extinction of PM1.0. When the air quality deteriorated, the change of the relative contribution of sulfate aerosol to the total extinction was small, but the contribution of nitrate aerosol increased significantly (from 17 % on clear days to 23 % on polluted days). (5) The observed mass scattering efficiencies increased consistently with the pollution extent, however, the observed mass absorption efficiencies increased consistently with increasing mass concentration in slightly pollution conditions, but decreased under polluted conditions.

Description: Global reactive nitrogen (Nr) deposition to terrestrial ecosystems has increased dramatically since the industrial revolution. This is especially true in recent decades in China due to continuous economic growth. However, there are no comprehensive reports of both measured dry and wet Nr deposition across China. We therefore conducted a multiple-year study during the period mainly from 2010 to 2014 to monitor atmospheric concentrations of five major Nr species of gaseous NH3, NO2 and HNO3, and inorganic nitrogen (NH4+ and NO3−) in both particles and precipitation, based on a Nationwide Nitrogen Deposition Monitoring Network (NNDMN, covering 43 sites) in China. Wet deposition fluxes of Nr species were measured directly; dry deposition fluxes were estimated using airborne concentration measurements and inferential models. Our observations reveal large spatial variations of atmospheric Nr concentrations and dry and wet Nr deposition. The annual average concentrations (1.3–47.0 μg N m−3) and dry plus wet deposition fluxes (2.9–75.2 kg N ha−1 yr−1) of inorganic Nr species ranked by region as North China 〉 Southeast China 〉 Southwest China 〉 Northeast China 〉 Northwest China 〉 the Tibetan Plateau or by land use as urban 〉 rural 〉 background sites, reflecting the impact of anthropogenic Nr emission. Average dry and wet N deposition fluxes were 18.5 and 19.3 kg N ha−1 yr−1, respectively, across China, with reduced N deposition dominating both dry and wet deposition. Our results suggest atmospheric dry N deposition is equally important to wet N deposition at the national scale and both deposition forms should be included when considering the impacts of N deposition on environment and ecosystem health.

Description: This paper introduces and presents the Spatial Processes in HYdrology (SPHY) model (v2.0), its development background, its underlying concepts, and some typical applications. The SPHY model is developed using the best components of existing and well-tested simulation models, and is developed with the explicit aim to simulate terrestrial hydrology at flexible scales, under various land use and climate conditions. SPHY is a spatially distributed leaky bucket type of model, and is applied on a cell-by-cell basis. The model is written in the Python programming language using the PCRaster dynamic modelling framework. Compared to other hydrological models, that typically focus on the simulation of streamflow only, the SPHY model has several advantages: it (i) integrates most relevant hydrological processes, (ii) is setup modular, (iii) is easy adjustable and applicable, (iii) can easily be linked to remote sensing data, and (iv) can be applied for operational as well as strategic decision support. The most relevant hydrological processes that are integrated in the SPHY model are rainfall–runoff processes, cryosphere processes, evapotranspiration processes, the simulation of dynamic vegetational cover, lake/reservoir outflow, and the simulation of rootzone moisture contents. Studies in which the SPHY model was successfully applied and tested are described in this paper, and range from (i) real-time soil moisture predictions to support irrigation management in lowland areas, to (ii) detailed climate change impact studies in snow and glacier-fed river basins, to (iii) operational flow forecasting in mountainous catchments.

Description: This paper introduces and presents the Spatial Processes in HYdrology (SPHY) model (v2.0), its development background, its underlying concepts, and some example applications. SPHY has been developed with the explicit aim of simulating terrestrial hydrology on flexible scales, under various physiographical and hydroclimatic conditions, by integrating key components from existing and well-tested models. SPHY is a spatially distributed leaky bucket type of model, and is applied on a cell-by-cell basis. The model is written in the Python programming language using the PCRaster dynamic modeling framework. SPHY (i) integrates most hydrologic processes, (ii) has the flexibility to be applied in a wide range of hydrologic applications, and (iii) on various scales, and (iv) can easily be implemented. The most relevant hydrological processes that are integrated into the SPHY model are rainfall–runoff processes, cryosphere processes, evapotranspiration processes, the dynamic evolution of vegetation cover, lake/reservoir outflow, and the simulation of root-zone moisture contents. Studies in which the SPHY model was successfully applied and tested are described in this paper, including (i) real-time soil moisture predictions to support irrigation management in lowland areas, (ii) climate change impact studies in snow- and glacier-fed river basins, and (iii) operational flow forecasting in mountainous catchments.

Description: A Nationwide Nitrogen Deposition Monitoring Network (NNDMN) containing 43 monitoring sites was established in China to measure gaseous NH3, NO2, and HNO3 and particulate NH4+ and NO3− in air and/or precipitation from 2010 to 2014. Wet/bulk deposition fluxes of Nr species were collected by precipitation gauge method and measured by continuous-flow analyzer; dry deposition fluxes were estimated using airborne concentration measurements and inferential models. Our observations reveal large spatial variations of atmospheric Nr concentrations and dry and wet/bulk Nr deposition. On a national basis, the annual average concentrations (1.3–47.0 μg N m−3) and dry plus wet/bulk deposition fluxes (2.9–83.3 kg N ha−1 yr−1) of inorganic Nr species are ranked by land use as urban 〉 rural 〉 background sites and by regions as north China 〉 southeast China 〉 southwest China 〉 northeast China 〉 northwest China 〉 Tibetan Plateau, reflecting the impact of anthropogenic Nr emission. Average dry and wet/bulk N deposition fluxes were 20.6 ± 11.2 (mean ± standard deviation) and 19.3 ± 9.2 kg N ha−1 yr−1 across China, with reduced N deposition dominating both dry and wet/bulk deposition. Our results suggest atmospheric dry N deposition is equally important to wet/bulk N deposition at the national scale. Therefore, both deposition forms should be included when considering the impacts of N deposition on environment and ecosystem health.

Description: The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a testbed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas in September 2013. Measurements of backscattered solar radiation between 420–465 nm collected on four days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 molecules cm−2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.91 for the most polluted day). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.84, slope = 0.94). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

Description: Large-scale climatic forcing is impacting oceanic biogeochemical cycles and is expected to influence the water-column distribution of trace gases, including methane and nitrous oxide. Our ability as a scientific community to evaluate changes in the water-column inventories of methane and nitrous oxide depends largely on our capacity to obtain robust and accurate concentration measurements that can be validated across different laboratory groups. This study represents the first formal international intercomparison of oceanic methane and nitrous oxide measurements whereby participating laboratories received batches of seawater samples from the subtropical Pacific Ocean and the Baltic Sea. Additionally, compressed gas standards from the same calibration scale were distributed to the majority of participating laboratories to improve the analytical accuracy of the gas measurements. The computations used by each laboratory to derive the dissolved gas concentrations were also evaluated for inconsistencies (e.g., pressure and temperature corrections, solubility constants). The results from the intercomparison and intercalibration provided invaluable insights into methane and nitrous oxide measurements. It was observed that analyses of seawater samples with the lowest concentrations of methane and nitrous oxide had the lowest precisions. In comparison, while the analytical precision for samples with the highest concentrations of trace gases was better, the variability between the different laboratories was higher: 36 % for methane and 27 % for nitrous oxide. In addition, the comparison of different batches of seawater samples with methane and nitrous oxide concentrations that ranged over an order of magnitude revealed the ramifications of different calibration procedures for each trace gas. Finally, this study builds upon the intercomparison results to develop recommendations for improving oceanic methane and nitrous oxide measurements, with the aim of precluding future analytical discrepancies between laboratories.

Description: A high spatial resolution of the Precipitable Water Vapor (PW V) in the atmosphere is a key requirement for the short-scale weather forecasting and climate research. The aim of this work is to derive temporally-differenced maps of the spatial distribution of PWV by analyzing the atmospheric delay "noise" in Interferometric Synthetic Aperture Radar (InSA R). A time series maps of differential PW V were obtained by processing a set of ENVISAT ASAR images cover the area of Southern California, USA from 06 October 2007 to 29 November 2008. To get a more accurate PW V, the component of dry delay is calculated by using ERA-Interim reanalysis products. In addition, the ERA-Interim was used to compute the conversion factors required to convert the zenith wet delay to water vapor. The InSA R-derived differential PW V maps were calibrated by means of the GPS PW V measurements over the study area. We validated our results against the measurements of PW V derived from the MEdium Resolution Imaging Spectrometer (MERIS) which is located together with ASAR sensor onboard the ENVISAT satellite. Our comparative results show strong spatial correlations between the two data sets. The difference maps have Gaussian distributions with mean values close to zero and standard deviations below 2 mm. The advantages of the InSAR technique is that it provides water vapor distribution with a spatial resolution as fine as 20 m and an accuracy of ~2 mm. Such a high spatial resolution maps of PW V could lead to much greater accuracy in meteorological understanding and quantitative precipitation forecasts.

Description: The European Academy of Wind Energy (eawe), representing universities and institutes with a significant wind energy programme in 14 countries, has discussed the long-term research challenges in wind energy. In contrast to research agendas addressing short- to medium-term research activities, this eawe document takes a longer-term perspective, addressing the scientific knowledge base that is required to develop wind energy beyond the applications of today and tomorrow. In other words, this long-term research agenda is driven by problems and curiosity, addressing basic research and fundamental knowledge in 11 research areas, ranging from physics and design to environmental and societal aspects. Because of the very nature of this initiative, this document does not intend to be permanent or complete. It shows the vision of the experts of the eawe, but other views may be possible. We sincerely hope that it will spur an even more intensive discussion worldwide within the wind energy community.

Description: Meltwater delivered to the bed of the Greenland Ice Sheet is a driver of variable ice-motion through changes in effective pressure and enhanced basal lubrication. Ice surface velocities have been shown to respond rapidly both to meltwater production at the surface and to drainage of supraglacial lakes, suggesting efficient transfer of meltwater from the supraglacial to subglacial hydrological systems. Although considerable effort is currently being directed towards improved modelling of the controlling surface and basal processes, modelling the temporal and spatial evolution of the transfer of melt to the bed has received less attention. Here we present the results of spatially distributed modelling for prediction of moulins and lake drainages on the Leverett Glacier in Southwest Greenland. The model is run for the 2009 and 2010 ablation seasons, and for future increased melt scenarios. The temporal pattern of modelled lake drainages are qualitatively comparable with those documented from analyses of repeat satellite imagery. The modelled timings and locations of delivery of meltwater to the bed also match well with observed temporal and spatial patterns of ice surface speed-ups. This is particularly true for the lower catchment (