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Atmosphere, Volume 9, Issue 3 (March 2018)

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Cover Story (view full-size image) El Niño is a regional phenomenon in the tropical Pacific Ocean with global impacts. It is [...] Read more.
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Open AccessArticle Short-Term Changes in Weather and Space Weather Conditions and Emergency Ambulance Calls for Elevated Arterial Blood Pressure
Atmosphere 2018, 9(3), 114; https://doi.org/10.3390/atmos9030114
Received: 13 February 2018 / Revised: 15 March 2018 / Accepted: 18 March 2018 / Published: 20 March 2018
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Abstract
Circadian rhythm influences the physiology of the cardiovascular system, inducing diurnal variation of blood pressure. We investigated the association between daily emergency ambulance calls (EACs) for elevated arterial blood pressure during the time intervals of 8:00–13:59, 14:00–21:59, and 22:00–7:59 and weekly fluctuations of
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Circadian rhythm influences the physiology of the cardiovascular system, inducing diurnal variation of blood pressure. We investigated the association between daily emergency ambulance calls (EACs) for elevated arterial blood pressure during the time intervals of 8:00–13:59, 14:00–21:59, and 22:00–7:59 and weekly fluctuations of air temperature (T), barometric pressure, relative humidity, wind speed, geomagnetic activity (GMA), and high-speed solar wind (HSSW). We used the Poisson regression to explore the association between the risk of EACs and weather variables, adjusting for seasonality and exposure to CO, PM10, and ozone. An increase of 10 °C when T > 1 °C on the day of the call was associated with a decrease in the risk of EACs during the time periods of 14:00–21:59 (RR (rate ratio) = 0.78; p < 0.001) and 22:00–7:59 (RR = 0.88; p = 0.35). During the time period of 8:00–13:59, the risk of EACs was positively associated with T above 1 °C with a lag of 5–7 days (RR = 1.18; p = 0.03). An elevated risk was associated during 8:00–13:59 with active-stormy GMA (RR = 1.22; p = 0.003); during 14:00–21:59 with very low GMA (RR = 1.07; p = 0.008) and HSSW (RR = 1.17; p = 0.014); and during 22:00–7:59 with HSSW occurring after active-stormy days (RR = 1.32; p = 0.019). The associations of environmental variables with the exacerbation of essential hypertension may be analyzed depending on the time of the event. Full article
(This article belongs to the Section Biometeorology)
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Open AccessArticle New Surrogate Model for Wind Pressure Coefficients in a Schematic Urban Environment with a Regular Pattern
Atmosphere 2018, 9(3), 113; https://doi.org/10.3390/atmos9030113
Received: 30 January 2018 / Revised: 11 March 2018 / Accepted: 16 March 2018 / Published: 19 March 2018
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Abstract
Natural ventilation and the use of fans are recognized as sustainable design strategies to reduce energy use while reaching thermal comfort. A big challenge for designers is to predict ventilation rates of buildings in dense urban areas. One significant factor for calculating the
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Natural ventilation and the use of fans are recognized as sustainable design strategies to reduce energy use while reaching thermal comfort. A big challenge for designers is to predict ventilation rates of buildings in dense urban areas. One significant factor for calculating the ventilation rate is the wind pressure coefficient (Cp). Cp values can be obtained at a high cost, via real measurements, wind tunnel experiments, or high computational effort via computational fluid dynamic (CFD) simulation. A fast surrogate model to predict Cp for a schematic urban environment is required for the integration in building performance simulations. There are well-known surrogate models for Cp. The average surface pressure coefficient model integrated in EnergyPlus considers only a box-shaped building, without surrounding buildings. CpCalc, a surrogate model for Cp, considers only one height of neighbouring buildings. The Toegepast Natuurwetenschappelijk Onderzoek (TNO) Cp Generator model was available via web interface, and could include several box-shaped buildings in the surrounding area. These models are complex for fast integration in a natural ventilation simulation. For optimization processes, with thousands of simulation runs, speed is even more essential. Our study proposes a new surrogate model for Cp estimation based on data obtained from the TNO CP Generator model. The new model considers the effect of different neighbouring buildings in a simplified urban configuration, with an orthogonal street pattern, box-shaped buildings, and repetitive dimensions. The developed surrogate model is fast, and can easily be integrated in a dynamic energy simulation tool like EnergyPlus for optimization of natural ventilation in the urban areas. Full article
(This article belongs to the Special Issue Recent Advances in Urban Ventilation Assessment and Flow Modelling)
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Open AccessArticle Precipitation Extremes in Dynamically Downscaled Climate Scenarios over the Greater Horn of Africa
Atmosphere 2018, 9(3), 112; https://doi.org/10.3390/atmos9030112
Received: 11 November 2017 / Revised: 24 February 2018 / Accepted: 13 March 2018 / Published: 18 March 2018
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Abstract
This study first assesses the performance of regional climate models in the Coordinated Regional Climate Downscaling Experiment (CORDEX) in reproducing observed extreme precipitation indices over the Greater Horn of Africa (GHA) region during 1989–2005. The study then assesses projected changes in these extremes
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This study first assesses the performance of regional climate models in the Coordinated Regional Climate Downscaling Experiment (CORDEX) in reproducing observed extreme precipitation indices over the Greater Horn of Africa (GHA) region during 1989–2005. The study then assesses projected changes in these extremes during 2069–2098 compared to 1976–2005. The Regional Climate Model (RCM) simulations are made using two RCMs, with large-scale forcing from four CMIP5 Global limate Models(GCMs) under two Representative Concentration Pathways (RCP4.5 and RCP8.5). We found that RCM simulations have reasonably captured observed patterns of moderate precipitation extreme indices (MPEI). Pattern correlation coefficients between simulated and observed MPEI exceed 0.5 for all except the Simple Daily Intensity Index (SDII). However, significant overestimations or underestimations exist over localized areas in the region. Projected changes in Total annual Precipitation (PRCPTOT) and the annual number of heavy (>10 mm) and very heavy (>20 mm) precipitation days by 2069–2098 show a general north-south pattern, with decreases over the southern half and increases over the northern half of the GHA. These changes are often greatest over parts of Somalia, Eritrea, the Ethiopian highlands and southern Tanzania. Maximum one- and five-day precipitation totals over a year and SDII (ratio of PRCPTOT to rainy days) are projected to increase over a majority of the GHA, including areas where PRCPTOT is projected to decrease, suggesting fewer, but heavier rainy days in the future. Changes in the annual sum of daily precipitation above the 95th and 99th percentiles are statistically significant over a few locations, with the largest projected decrease/increase over Eritrea and northwestern Sudan/Somalia. Projected changes in Consecutive Dry Days (CDD) suggest longer periods of dryness over the majority of the GHA, except the central portions covering northern Uganda, southern South Sudan, southeastern Ethiopia and Somalia. Substantial increases in CDD are located over southern Tanzania and the Ethiopian highlands. The magnitude and the spatial extent of statistically-significant changes in all MPEI increase from RCP4.5 to RCP8.5, and the separation between positive and negative changes becomes clearer under RCP8.5. Full article
(This article belongs to the Special Issue Precipitation Variability and Change in Africa)
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Open AccessArticle Validation Study for an Atmospheric Dispersion Model, Using Effective Source Heights Determined from Wind Tunnel Experiments in Nuclear Safety Analysis
Atmosphere 2018, 9(3), 111; https://doi.org/10.3390/atmos9030111
Received: 14 February 2018 / Revised: 12 March 2018 / Accepted: 14 March 2018 / Published: 18 March 2018
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Abstract
For more than fifty years, atmospheric dispersion predictions based on the joint use of a Gaussian plume model and wind tunnel experiments have been applied in both Japan and the U.K. for the evaluation of public radiation exposure in nuclear safety analysis. The
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For more than fifty years, atmospheric dispersion predictions based on the joint use of a Gaussian plume model and wind tunnel experiments have been applied in both Japan and the U.K. for the evaluation of public radiation exposure in nuclear safety analysis. The effective source height used in the Gaussian model is determined from ground-level concentration data obtained by a wind tunnel experiment using a scaled terrain and site model. In the present paper, the concentrations calculated by this method are compared with data observed over complex terrain in the field, under a number of meteorological conditions. Good agreement was confirmed in near-neutral and unstable stabilities. However, it was found to be necessary to reduce the effective source height by 50% in order to achieve a conservative estimation of the field observations in a stable atmosphere. Full article
(This article belongs to the Section Air Quality)
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Open AccessArticle Wind Resource Assessment in the Southern Plains of the US: Characterizing Large-Scale Atmospheric Circulation with Cluster Analysis
Atmosphere 2018, 9(3), 110; https://doi.org/10.3390/atmos9030110
Received: 29 January 2018 / Revised: 27 February 2018 / Accepted: 13 March 2018 / Published: 16 March 2018
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Abstract
A new approach for wind resource assessment in the Southern Plains of the US is proposed here. This new approach establishes the baseline frequency of occurrence of large-scale atmospheric circulations (weather regimes) by cluster analysis, using 38-yr NCEP-NCAR reanalysis daily data from 1979–2016.
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A new approach for wind resource assessment in the Southern Plains of the US is proposed here. This new approach establishes the baseline frequency of occurrence of large-scale atmospheric circulations (weather regimes) by cluster analysis, using 38-yr NCEP-NCAR reanalysis daily data from 1979–2016. These baseline frequency values can help quantify the departure of wind resource from the long-term mean for a given month. In specific, two scenarios featuring favorable and unfavorable wind energy productions in the Callahan Divide Energy Center of Texas, US, are evaluated by the new approach of wind resource assessment in details. For the favorable scenario, it is found that the jet stream is configured to enhance the southwesterly flow over the Southern Plains, with a frequency of occurrence being nearly three times of the baseline frequency, whereas for the unfavorable scenario, the jet stream is found to suppress the low-level jet over the Southern Plains, with a frequency of occurrence being more than twice the baseline frequency. Hence, the new approach is proven to provide an objective and more efficient way in conducting wind resource assessment. Full article
(This article belongs to the Special Issue Energy Meteorology)
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Open AccessArticle Returning Tea Pruning Residue and Its Biochar Had a Contrasting Effect on Soil N2O and CO2 Emissions from Tea Plantation Soil
Atmosphere 2018, 9(3), 109; https://doi.org/10.3390/atmos9030109
Received: 16 February 2018 / Revised: 12 March 2018 / Accepted: 12 March 2018 / Published: 15 March 2018
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Abstract
A laboratory incubation experiment is conducted for 90 days under controlled conditions where either pruning residue or its biochar is applied to determine which application generates the lowest amount of greenhouse gas from tea plantation soil. To study the effect of incorporation depth
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A laboratory incubation experiment is conducted for 90 days under controlled conditions where either pruning residue or its biochar is applied to determine which application generates the lowest amount of greenhouse gas from tea plantation soil. To study the effect of incorporation depth on soil N2O and CO2 emissions, experiment 1 is performed with three treatments: (1) control; (2) tea pruning residue; and (3) residue biochar mixed with soil from two different depths (0–5 cm and 0–10 cm layers). In experiment 2, only the 0–10 cm soil layer is used to study the effect of surface application of tea pruning residue or its biochar on soil N2O and CO2 emissions compared with the control. The results show that biochar significantly increases soil pH, total C and C/N ratio in both experiments. The addition of pruning residue significantly increases soil total C content, cumulative N2O and CO2 emissions after 90 days of incubation. Converting pruning residue to biochar and its application significantly decreases cumulative N2O emission by 17.7% and 74.2% from the 0–5 cm and 0–10 cm soil layers, respectively, compared to their respective controls. However, biochar addition increases soil CO2 emissions for both the soil layers in experiment 1. Surface application of biochar to soil significantly reduces both N2O and CO2 emissions compared to residue treatment and the control in experiment 2. Our results suggest that converting pruning residue to biochar and its addition to soil has the potential to mitigate soil N2O emissions from tea plantation. Full article
(This article belongs to the Special Issue C and N Cycling and Greenhouse Gases Emission in Agroecosystem)
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Open AccessReview Approaches to Outdoor Thermal Comfort Thresholds through Public Space Design: A Review
Atmosphere 2018, 9(3), 108; https://doi.org/10.3390/atmos9030108
Received: 13 January 2018 / Revised: 7 March 2018 / Accepted: 9 March 2018 / Published: 14 March 2018
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Abstract
Based on the Köppen Geiger (KG) classification system, this review article examines existing studies and projects that have endeavoured to address local outdoor thermal comfort thresholds through Public Space Design (PSD). The review is divided into two sequential stages, whereby (1) overall existing
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Based on the Köppen Geiger (KG) classification system, this review article examines existing studies and projects that have endeavoured to address local outdoor thermal comfort thresholds through Public Space Design (PSD). The review is divided into two sequential stages, whereby (1) overall existing approaches to pedestrian thermal comfort thresholds are reviewed within both quantitative and qualitative spectrums; and (2) the different techniques and measures are reviewed and framed into four Measure Review Frameworks (MRFs), in which each type of PSD measure is presented alongside its respective local scale urban specificities/conditions and their resulting thermal attenuation outcomes. The result of this review article is the assessment of how current practices of PSD within three specific subcategories of the KG ‘Temperate’ group have addressed microclimatic aggravations such as elevated urban temperatures and Urban Heat Island (UHI) effects. Based upon a bottom-up approach, the interdisciplinary practice of PSD is hence approached as a means to address existing and future thermal risk factors within the urban public realm in an era of potential climate change. Full article
(This article belongs to the Section Biometeorology)
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Open AccessArticle Detecting Coastline Change with All Available Landsat Data over 1986–2015: A Case Study for the State of Texas, USA
Atmosphere 2018, 9(3), 107; https://doi.org/10.3390/atmos9030107
Received: 6 December 2017 / Revised: 6 March 2018 / Accepted: 6 March 2018 / Published: 14 March 2018
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Abstract
Coastline change often results from social and natural factors, such as human activities in the coastal zone, long-term and short-term sea level change, hurricane occurrences, subsequent recovery, and so on. Tracking coastline change is essential to deepen our understanding of coastal responses to
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Coastline change often results from social and natural factors, such as human activities in the coastal zone, long-term and short-term sea level change, hurricane occurrences, subsequent recovery, and so on. Tracking coastline change is essential to deepen our understanding of coastal responses to these factors. Such information is also required for land use planning and sustainable development of coastal zones. In this context, we aimed to collect all available Landsat data (TM: Thematic Mapper, ETM+: Enhanced Thematic Mapper Plus and OLI: Operational Land Imager) over 1986–2015 for tracking the coastline dynamic and estimating its change rate in the State of Texas, USA. First, the land vs. water maps at an annual scale were derived from the satellite images. The border between land and water represents the coastline in this study. Second, the annual land area was obtained to characterize the coastline dynamic and a linear regression model was used for estimating the change rate. We also analyzed the potential driving factors of the observed coastline change. The results reveal that the coastline in the State of Texas changed at a rate of −0.154 ± 0.063 km2/year from 1986 to 2015, which indicates that the coastline has mainly experienced an erosion over the past three decades. Specifically, 52.58% of the entire coastline retreated to the land while a 47.42% portion advanced to the ocean. Long-term sea level rise can result in the erosion of coastline. Hurricane occurrences can explain the relatively strong coastline erosion. Besides, significant difference between the coastline change rate with a higher curvature and a lower curvature was observed. This study establishes a general method for detecting coastline change at large spatial and long-term temporal scales, by using remote sensing that can give fundamental information on coastline change. This is important for making scientific and reasonable policies of sustainable development of coastal zones. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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Open AccessArticle Evaluations of WRF Sensitivities in Surface Simulations with an Ensemble Prediction System
Atmosphere 2018, 9(3), 106; https://doi.org/10.3390/atmos9030106
Received: 26 January 2018 / Revised: 9 March 2018 / Accepted: 9 March 2018 / Published: 13 March 2018
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Abstract
This paper investigates the sensitivities of the Weather Research and Forecasting (WRF) model simulations to different parameterization schemes (atmospheric boundary layer, microphysics, cumulus, longwave and shortwave radiations and other model configuration parameters) on a domain centered over the inter-mountain western United States (U.S.).
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This paper investigates the sensitivities of the Weather Research and Forecasting (WRF) model simulations to different parameterization schemes (atmospheric boundary layer, microphysics, cumulus, longwave and shortwave radiations and other model configuration parameters) on a domain centered over the inter-mountain western United States (U.S.). Sensitivities are evaluated through a multi-model, multi-physics and multi-perturbation operational ensemble system based on the real-time four-dimensional data assimilation (RTFDDA) forecasting scheme, which was developed at the National Center for Atmospheric Research (NCAR) in the United States. The modeling system has three nested domains with horizontal grid intervals of 30 km, 10 km and 3.3 km. Each member of the ensemble system is treated as one of 48 sensitivity experiments. Validation with station observations is done with simulations on a 3.3-km domain from a cold period (January) and a warm period (July). Analyses and forecasts were run every 6 h during one week in each period. Performance metrics, calculated station-by-station and as a grid-wide average, are the bias, root mean square error (RMSE), mean absolute error (MAE), normalized standard deviation and the correlation between the observation and model. Across all members, the 2-m temperature has domain-average biases of −1.5–0.8 K; the 2-m specific humidity has biases from −0.5–−0.05 g/kg; and the 10-m wind speed and wind direction have biases from 0.2–1.18 m/s and −0.5–4 degrees, respectively. Surface temperature is most sensitive to the microphysics and atmospheric boundary layer schemes, which can also produce significant differences in surface wind speed and direction. All examined variables are sensitive to data assimilation. Full article
(This article belongs to the Special Issue WRF Simulations at the Mesoscale: From the Microscale to Macroscale)
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Open AccessArticle Spatio-Temporal Pattern Estimation of PM2.5 in Beijing-Tianjin-Hebei Region Based on MODIS AOD and Meteorological Data Using the Back Propagation Neural Network
Atmosphere 2018, 9(3), 105; https://doi.org/10.3390/atmos9030105
Received: 29 January 2018 / Revised: 7 March 2018 / Accepted: 9 March 2018 / Published: 13 March 2018
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Abstract
With the economic growth and increasing urbanization in the last three decades, the air quality over China has continuously degraded, which poses a great threat to human health. The concentration of fine particulate matter (PM2.5) directly affects the mortality of people
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With the economic growth and increasing urbanization in the last three decades, the air quality over China has continuously degraded, which poses a great threat to human health. The concentration of fine particulate matter (PM2.5) directly affects the mortality of people living in the polluted areas where air quality is poor. The Beijing-Tianjin-Hebei (BTH) region, one of the well organized urban regions in northern China, has suffered with poor air quality and atmospheric pollution due to recent growth of the industrial sector and vehicle emissions. In the present study, we used the back propagation neural network model approach to estimate the spatial distribution of PM2.5 concentration in the BTH region for the period January 2014–December 2016, combining the satellite-derived aerosol optical depth (S-DAOD) and meteorological data. The results were validated using the ground PM2.5 data. The general method including all PM2.5 training data and 10-fold cross-method have been used for validation for PM2.5 estimation (R2 = 0.68, RMSE = 20.99 for general validation; R2 = 0.54, RMSE = 24.13 for cross-method validation). The study provides a new approach to monitoring the distribution of PM2.5 concentration. The results discussed in the present paper will be of great help to government agencies in developing and implementing environmental conservation policy. Full article
(This article belongs to the Section Aerosols)
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Open AccessArticle Verification of High-Resolution Medium-Range Precipitation Forecasts from Global Environmental Multiscale Model over China during 2009–2013
Atmosphere 2018, 9(3), 104; https://doi.org/10.3390/atmos9030104
Received: 9 December 2017 / Revised: 15 February 2018 / Accepted: 3 March 2018 / Published: 13 March 2018
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Abstract
Accurate and timely precipitation forecasts are a key factor for improving hydrological forecasts. Therefore, it is fundamental to evaluate the skill of Numerical Weather Prediction (NWP) for precipitation forecasting. In this study, the Global Environmental Multi-scale (GEM) model, which is widely used around
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Accurate and timely precipitation forecasts are a key factor for improving hydrological forecasts. Therefore, it is fundamental to evaluate the skill of Numerical Weather Prediction (NWP) for precipitation forecasting. In this study, the Global Environmental Multi-scale (GEM) model, which is widely used around Canada, was chosen as the high-resolution medium-term prediction model. Based on the forecast precipitation with the resolution of 0.24° and taking regional differences into consideration, the study explored the forecasting skill of GEM in nine drought sub-regions around China. Spatially, GEM performs better in East and South China than in the inland areas. Temporally, the model is able to produce more precise precipitation during flood periods (summer and autumn) compared with the non-flood season (winter and spring). The forecasting skill variability differs with regions, lead time and season. For different precipitation categories, GEM for trace rainfall and little rainfall performs much better than moderate rainfall and above. Overall, compared with other prediction systems, GEM is applicable for the 0–96 h forecast, especially for the East and South China in flood season, but improvement for the prediction of heavy and storm rainfall and for the inland areas should be focused on as well. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Remarkable Impacts of Indian Ocean Sea Surface Temperature on Interdecadal Variability of Summer Rainfall in Southwestern China
Atmosphere 2018, 9(3), 103; https://doi.org/10.3390/atmos9030103
Received: 2 February 2018 / Revised: 4 March 2018 / Accepted: 5 March 2018 / Published: 13 March 2018
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Abstract
During the boreal summer from June to August, rainfall in Southwestern China shows substantial interdecadal variabilities on timescales longer than 10 years. Based on observational analyses and numerical modeling, we investigated the characteristics of interdecadal Southwestern China summer rainfall (SWCSR) and its dynamic
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During the boreal summer from June to August, rainfall in Southwestern China shows substantial interdecadal variabilities on timescales longer than 10 years. Based on observational analyses and numerical modeling, we investigated the characteristics of interdecadal Southwestern China summer rainfall (SWCSR) and its dynamic drivers. We find that the SWCSR is markedly impacted by the interdecadal Indian Ocean basin mode (ID-IOBM) of the sea surface temperature (SST), which may induce anomalous inter-hemispheric vertical circulation. During the cold phase of the ID-IOBM, an enhanced lower-level divergence and upper-level convergence exist over the tropical Indian Ocean. The simultaneous lower-level outflow anomalies further converge over the Indo-China peninsula, resulting in an anomalous ascending motion and a lower-level cyclone that contribute to strengthening the eastward moisture transport from the Bay of Bengal to Southwestern China. The joint effects of the anomalous ascending motion and the above-normal moisture transport play a key role in increasing the SWCSR. In summers during the warm phase of the ID-IOBM, the situation is approximately the same, but with opposite polarity. After the beginning of the 1970s, the impacts of interdecadal Indian Ocean dipole (ID-IOD) on SWCSR is strengthening. The anomalous vertical circulation associated with the positive (negative) phase of ID-IOD is in favor of decreased (increased) rainfall in SWC. However, the impacts of ID-IOD on SWCSR is relatively weak before the 1970s, indicating that the ID-IOD is the secondary driver of the interdecadal variability of SWCSR. Modeling results also indicate that the ID-IOBM of SST anomalies is the main driver of interdecadal variability of SWCSR. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessReview Exchange Processes in the Atmospheric Boundary Layer Over Mountainous Terrain
Atmosphere 2018, 9(3), 102; https://doi.org/10.3390/atmos9030102
Received: 29 January 2018 / Revised: 17 February 2018 / Accepted: 19 February 2018 / Published: 12 March 2018
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Abstract
The exchange of heat, momentum, and mass in the atmosphere over mountainous terrain is controlled by synoptic-scale dynamics, thermally driven mesoscale circulations, and turbulence. This article reviews the key challenges relevant to the understanding of exchange processes in the mountain boundary layer and
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The exchange of heat, momentum, and mass in the atmosphere over mountainous terrain is controlled by synoptic-scale dynamics, thermally driven mesoscale circulations, and turbulence. This article reviews the key challenges relevant to the understanding of exchange processes in the mountain boundary layer and outlines possible research priorities for the future. The review describes the limitations of the experimental study of turbulent exchange over complex terrain, the impact of slope and valley breezes on the structure of the convective boundary layer, and the role of intermittent mixing and wave–turbulence interaction in the stable boundary layer. The interplay between exchange processes at different spatial scales is discussed in depth, emphasizing the role of elevated and ground-based stable layers in controlling multi-scale interactions in the atmosphere over and near mountains. Implications of the current understanding of exchange processes over mountains towards the improvement of numerical weather prediction and climate models are discussed, considering in particular the representation of surface boundary conditions, the parameterization of sub-grid-scale exchange, and the development of stochastic perturbation schemes. Full article
(This article belongs to the Special Issue Atmospheric Processes over Complex Terrain)
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Open AccessArticle Assessment of the Performance of Three Dynamical Climate Downscaling Methods Using Different Land Surface Information over China
Atmosphere 2018, 9(3), 101; https://doi.org/10.3390/atmos9030101
Received: 22 December 2017 / Revised: 22 February 2018 / Accepted: 7 March 2018 / Published: 11 March 2018
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Abstract
This study aims to assess the performance of different dynamical downscaling methods using updated land surface information. Particular attention is given to obtaining high-resolution climate information over China by the combination of an appropriate dynamical downscaling method and updated land surface information. Two
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This study aims to assess the performance of different dynamical downscaling methods using updated land surface information. Particular attention is given to obtaining high-resolution climate information over China by the combination of an appropriate dynamical downscaling method and updated land surface information. Two group experiments using two land surface datasets are performed, including default Weather Research and Forecasting (WRF) land surface data (OLD) and accurate dynamically accordant MODIS data (NEW). Each group consists of three types of experiments for the summer of 2014, including traditional continuous integration (CT), spectral nudging (SN), and re-initialization (Re) experiments. The Weather Research and Forecasting (WRF) model is used to dynamically downscale ERA-Interim (reanalysis of the European Centre for Medium-Range Weather Forecast, ECMWF) data with a grid spacing of 30 km over China. The simulations are evaluated via comparison with observed conventional meteorological variables, showing that the CT method, which notably overestimates 2 m temperature and underestimates 2 m relative humidity across China, performs the worst; the SN and Re runs outperform the CT method, and the Re shows the smallest RMSE (root means square error). A comparison of observed and simulated precipitation shows that the SN simulation is closest to the observed data, while the CT and Re simulations overestimate precipitation south of the Yangtze River. Compared with the OLD group, the RMSE values of temperature and relative humidity are significantly improved in CT and SN, and there is smaller improved in Re. However, obvious improvements in precipitation are not evident. Full article
(This article belongs to the Special Issue Regional Climate Modeling)
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Open AccessEditorial Madden–Julian Oscillation
Atmosphere 2018, 9(3), 100; https://doi.org/10.3390/atmos9030100
Received: 7 March 2018 / Revised: 9 March 2018 / Accepted: 9 March 2018 / Published: 11 March 2018
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Abstract
The Madden–Julian Oscillation (MJO) is the most important mode of tropical intraseasonal variability. [...] Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
Open AccessArticle Evaluation of Lightning Forecasting Based on One Lightning Parameterization Scheme and Two Diagnostic Methods
Atmosphere 2018, 9(3), 99; https://doi.org/10.3390/atmos9030099
Received: 24 November 2017 / Revised: 7 February 2018 / Accepted: 7 March 2018 / Published: 10 March 2018
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Abstract
Lightning forecasting is a vital item in server convective system short-time forecasting. However, lightning parameterization in mesoscale numerical prediction models is still in its early stages of development. Several lightning parameterization schemes are implemented in the Weather Research and Forecasting (WRF) model. Data
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Lightning forecasting is a vital item in server convective system short-time forecasting. However, lightning parameterization in mesoscale numerical prediction models is still in its early stages of development. Several lightning parameterization schemes are implemented in the Weather Research and Forecasting (WRF) model. Data assimilation can provide a more accurate initial field, which could be useful for subsequent lightning forecasting. To evaluate its effect on lightning forecasting, a severe convective case that influenced Jiangsu and Anhui Province on 5 June 2009 is utilized and a series of experiments are conducted including assimilating radar reflectivity and lightning location network data via the three-dimensional variational (3DVar) method. Results show that data assimilation can effectively improve reflectivity forecasting and subsequent lightning forecasting. Lightning forecasting based on the PR92 lightning parameterization scheme, which is based on the convective cloud top height, offers a weaker magnitude forecast. The diagnostic method based on reflectivity and temperature has some spatial displacement. The potential forecast provided by lightning threat indexes produced an improvement in Anhui Province, while in other regions, it is located further east than the observation. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessArticle Theoretical Urban Heat Island Circulation in the Temperature Inversion Profile
Atmosphere 2018, 9(3), 98; https://doi.org/10.3390/atmos9030098
Received: 19 January 2018 / Revised: 3 March 2018 / Accepted: 7 March 2018 / Published: 9 March 2018
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Abstract
The characteristics of urban heat island (UHI) circulation are analytically expressed as functions of the surface temperature in both temperature inversion and non-temperature inversion (NTI) profiles, in which the temperature declines with increasing altitudes. To identify how the inversion layer affects UHI circulation,
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The characteristics of urban heat island (UHI) circulation are analytically expressed as functions of the surface temperature in both temperature inversion and non-temperature inversion (NTI) profiles, in which the temperature declines with increasing altitudes. To identify how the inversion layer affects UHI circulation, two temperature profiles are specified to be nearly similar except within the temperature inversion layer. Theoretical calculations suggest that the UHI circulation in the temperature inversion case is weaker and lower than in the NTI case and that there is no significant difference between the two cases. When the inversion layer thickness is fixed, the relative size difference between the weakening inversion intensity and the strengthening temperature influence above the inversion lid controls the decrease or increase in UHI circulation. Full article
(This article belongs to the Section Biometeorology)
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Open AccessArticle Stable Isotopic Characteristics and Influencing Factors in Precipitation in the Monsoon Marginal Region of Northern China
Atmosphere 2018, 9(3), 97; https://doi.org/10.3390/atmos9030097
Received: 1 January 2018 / Revised: 16 February 2018 / Accepted: 6 March 2018 / Published: 8 March 2018
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Abstract
Based on stable hydrogen and oxygen isotope data (δ18O, δD) and meteorological observation data for complete hydrological annual precipitation from 2016 to 2017 in the monsoon marginal region of northern China (Fengxiang and Ningwu), the isotopic characteristics of precipitation and the
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Based on stable hydrogen and oxygen isotope data (δ18O, δD) and meteorological observation data for complete hydrological annual precipitation from 2016 to 2017 in the monsoon marginal region of northern China (Fengxiang and Ningwu), the isotopic characteristics of precipitation and the sources of water vapor in these two regions combined were studied. The results showed that δ18O and δD values in the wet season (June through September) were higher than in the dry season (October to May of the following year) in Fengxiang and Ningwu. The intercept and slope of the meteoric water line in the two regions were somewhat low, revealing that the water vapor in the rainfall comes mainly from the tropical ocean. On a synoptic scale, significantly positive correlations among dry season precipitation, δ18O, and temperature manifested temperature effects, but in the wet season, the temperature effect was not significant. On a monthly scale, a relationship did not exist between the change in trend of the average value of monthly weighted δ18O in precipitation and the average temperature change value in the two regions. However, in the wet season, significantly negative relationships can be found between the average monthly weighted δ18O in precipitation and rainfall amount, which indicated a remarkable rainout effect. Further investigation revealed that continuous precipitation made the values of δ18O and δD more negative under the same source of water vapor (the rainout effect). Because the annual rainfall in the monsoon marginal region of Northern China is mainly made up of monsoon rainfall, the oxygen isotope index of geological and biological records, such as stalagmites and tree rings, which inherit meteoric water isotope information, can be used to reconstruct past rainfall changes in northern China. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Weather Radar Data Compression Based on Spatial and Temporal Prediction
Atmosphere 2018, 9(3), 96; https://doi.org/10.3390/atmos9030096
Received: 6 February 2018 / Revised: 6 March 2018 / Accepted: 6 March 2018 / Published: 8 March 2018
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Abstract
The transmission and storage of weather radar products will be an important problem for future weather radar applications. The aim of this work is to provide a solution for real-time transmission of weather radar data and efficient data storage. By upgrading the capabilities
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The transmission and storage of weather radar products will be an important problem for future weather radar applications. The aim of this work is to provide a solution for real-time transmission of weather radar data and efficient data storage. By upgrading the capabilities of radar, the amount of data that can be processed continues to increase. Weather radar compression is necessary to reduce the amount of data for transmission and archiving. The characteristics of weather radar data are not considered in general-purpose compression programs. The sparsity and data redundancy of weather radar data are analyzed. A lossless compression of weather radar data based on prediction coding is presented, which is called spatial and temporal prediction compression (STPC). The spatial and temporal correlations in weather radar data are utilized to improve the compression ratio. A specific prediction scheme for weather radar data is given, while the residual data and motion vectors are used to replace the original values for entropy coding. After this, the Level-II product from CINRAD SA is used to evaluate STPC. Experimental results show that the STPC achieves a better performance than the general-purpose compression programs, with the STPC yield being approximately 26% better than the next best approach. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessArticle Optimisation of Heat Loss through Ventilation for Residential Buildings
Atmosphere 2018, 9(3), 95; https://doi.org/10.3390/atmos9030095
Received: 28 January 2018 / Revised: 5 March 2018 / Accepted: 6 March 2018 / Published: 8 March 2018
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Abstract
This study presents the results of research on heat loss from various types of residential buildings through ventilation systems. Experimental research was done to analyse the effectiveness of ventilation systems of different types and determine the parameters of air discharged via the ventilation
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This study presents the results of research on heat loss from various types of residential buildings through ventilation systems. Experimental research was done to analyse the effectiveness of ventilation systems of different types and determine the parameters of air discharged via the ventilation ducts. A model of heat loss from the discharge of exhaust air outside through air ducts has since been developed. Experiments were conducted on three experimental systems of building ventilation: gravitational, mechanical, and supply-exhaust ventilation systems with heat recovery. The proposed model dependencies were used to chart the daily fluctuations of the optimum multiplicity of air exchange for precise control of the parameters of mechanical ventilation systems in residential buildings. This study proves that natural ventilation in residential buildings fulfils its function only by increasing the air flow into the building, and that this incurs significant heat loss from buildings during the heating season. Full article
(This article belongs to the Special Issue Recent Advances in Urban Ventilation Assessment and Flow Modelling)
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Open AccessPerspective What Does It Mean to Be El Niño Ready?
Atmosphere 2018, 9(3), 94; https://doi.org/10.3390/atmos9030094
Received: 3 January 2018 / Revised: 4 March 2018 / Accepted: 5 March 2018 / Published: 7 March 2018
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Abstract
Once an El Niño event has been forecast, government warnings and news headlines highlight the need for society to get ready for the potential impacts of the event, whether drought, flood, heatwave, disease outbreak, or water shortage. The notion of readiness for a
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Once an El Niño event has been forecast, government warnings and news headlines highlight the need for society to get ready for the potential impacts of the event, whether drought, flood, heatwave, disease outbreak, or water shortage. The notion of readiness for a climate-, water- or weather-related hazard or disaster is a fuzzy term, subject to a wide range of conflicting perceptions. Not every government sees El Niño as a direct threat to the wellbeing of its citizens. In this paper, we conceptualize readiness and identify reasons that some governments do not as well as cannot prepare for El Niño’s foreseeable consequences. Central among those reasons are its characteristics: quasi-periodicity, event variability, difficulties with onset forecasting, and the fact that El Niño and its “teleconnections” are influenced by numerous other oceanic and atmospheric oscillations. As a result, there is no universally accepted approach to or reliable measure of readiness. The concept is often discussed qualitatively in terms of “shades of readiness”, such as hardly ready, somewhat ready, almost ready, and absolutely ready. Although El Niño is still difficult to forecast, the existing knowledge about it can provide usable information for decision makers to choose whether to pursue strategic or tactical disaster risk reduction policies. Full article
(This article belongs to the Special Issue El Niño Southern Oscillation (ENSO))
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Open AccessArticle Long-Term Analysis of Aerosol Optical Depth over the Huaihai Economic Region (HER): Possible Causes and Implications
Atmosphere 2018, 9(3), 93; https://doi.org/10.3390/atmos9030093
Received: 13 December 2017 / Revised: 21 February 2018 / Accepted: 2 March 2018 / Published: 4 March 2018
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Abstract
The quality of air is increasingly affecting regional climate and human activity. Collection 6 aerosol products retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite were validated based on CE-318 sun photometric data to analyze their applicability in the Huaihai economic
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The quality of air is increasingly affecting regional climate and human activity. Collection 6 aerosol products retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite were validated based on CE-318 sun photometric data to analyze their applicability in the Huaihai economic region (HER) at the Xuzhou and Shouxian sites. The spatio-temporal variations of aerosol optical depth (AOD) were also analyzed over HER from 2000 to 2016, with analyses of the correlation with potential driving factors, including meteorology, vegetation and human factors. HER is an economic cooperation organization with multiple industrial structures, containing coal resource-based cities, a national transportation hub and agricultural and high-altitude areas, which shows regional differences in AOD. The results suggest that MODIS Terra AOD products show good agreement with ground observations, with correlation coefficients of above 0.84 in HER, and the main pollutants for high AOD values are fine particles (the mean Ångström exponent was 1.16). The average annual change in AOD varied with a weak growth trend over the past 17 years, while a transition in 2012 made the tendency change from upward to downward due to the extensive cooperation of cities in the joint prevention and control of the deterioration of the ecological environment. The largest monthly mean AOD value appeared in June, which resulted from significant agricultural residue burning. The spatial distribution of multi-year average AOD occurred with a banded high-value center, extending from the north-west to the south-east. The high aerosol loadings were located in resource-based cities, and industrially developed and south-eastern coastal areas, whereas the regions with relatively low AOD in HER were distributed in the southern agricultural and northern high-altitude areas. The AOD value in the western, northern, and eastern coastal areas of HER showed a significant increasing trend, while no area exhibited a decreasing trend. The average wind speed has the largest negative correlation with the AOD value in terms of the natural driving factors, and GDP (gross domestic product) was more positively correlated with AOD with respect to the human factors, in comparison with population density. Full article
(This article belongs to the Special Issue Aerosol Optical Properties: Models, Methods & Measurements)
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Open AccessArticle On-Road Air Quality Associated with Traffic Composition and Street-Canyon Ventilation: Mobile Monitoring and CFD Modeling
Atmosphere 2018, 9(3), 92; https://doi.org/10.3390/atmos9030092
Received: 1 February 2018 / Revised: 24 February 2018 / Accepted: 24 February 2018 / Published: 2 March 2018
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Abstract
Mobile monitoring and computational fluid dynamics (CFD) modeling are complementary methods to examine spatio-temporal variations of air pollutant concentrations at high resolutions in urban areas. We measured nitrogen oxides (NOx), black carbon (BC), particle-bound polycyclic aromatic hydrocarbons (pPAH), and particle number
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Mobile monitoring and computational fluid dynamics (CFD) modeling are complementary methods to examine spatio-temporal variations of air pollutant concentrations at high resolutions in urban areas. We measured nitrogen oxides (NOx), black carbon (BC), particle-bound polycyclic aromatic hydrocarbons (pPAH), and particle number (PN) concentrations in a central business district using a mobile laboratory. The analysis of correlations between the measured concentrations and traffic volumes demonstrate that high emitting vehicles (HEVs) are deterministically responsible for poor air quality in the street canyon. The determination coefficient (R2) with the HEV traffic volume is the largest for the pPAH concentration (0.79). The measured NOx and pPAH concentrations at a signalized intersection are higher than those on a road between two intersections by 24% and 25%, respectively. The CFD modeling results reveal that the signalized intersection plays a role in increasing on-road concentrations due to accelerating and idling vehicles (i.e., emission process), but also plays a countervailing role in decreasing on-road concentrations due to lateral ventilation of emitted pollutants (i.e., dispersion process). It is suggested that the number of HEVs and street-canyon ventilation, especially near a signalized intersection, need to be controlled to mitigate poor air quality in a central business district of a megacity. Full article
(This article belongs to the Special Issue Recent Advances in Urban Ventilation Assessment and Flow Modelling)
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Open AccessArticle Analysis and Comparison of Shading Strategies to Increase Human Thermal Comfort in Urban Areas
Atmosphere 2018, 9(3), 91; https://doi.org/10.3390/atmos9030091
Received: 13 November 2017 / Revised: 23 February 2018 / Accepted: 27 February 2018 / Published: 1 March 2018
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Abstract
With the expected increase in warmer conditions caused by climate change, heat-related illnesses are becoming a more pressing issue. One way that humans can protect themselves from this is to seek shade. The design of urban spaces can provide individuals with a variety
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With the expected increase in warmer conditions caused by climate change, heat-related illnesses are becoming a more pressing issue. One way that humans can protect themselves from this is to seek shade. The design of urban spaces can provide individuals with a variety of ways to obtain this shade. The objective of this study was to perform a detailed evaluation and comparison of three shading strategies that could be used in an urban environment: shade from a building, from a tree, and from an umbrella. This was done through using field measurements to calculate the impact of each strategy on a thermal comfort index (Comfort Formula (COMFA)) in two urban settings during sunny days of the summer of 2013 and 2014 in London, Canada. Building shade was found to be the most effective cooling strategy, followed by the tree strategy and the umbrella strategy. As expected, the main determinant of this ranking was a strategy’s ability to block incoming shortwave radiation. Further analysis indicated that changes in the convective loss of energy and in longwave radiation absorption had a smaller impact that caused variations in the strategy effectiveness between settings. This suggests that under non-sunny days, these rankings could change. Full article
(This article belongs to the Special Issue Urban Design and City Microclimates)
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Open AccessArticle A Statistical Investigation of the Impact of the Indian Monsoon on the Eastern Mediterranean Circulation
Atmosphere 2018, 9(3), 90; https://doi.org/10.3390/atmos9030090
Received: 30 November 2017 / Revised: 21 February 2018 / Accepted: 23 February 2018 / Published: 1 March 2018
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Abstract
The Indian summer monsoon (ISM) is a prominent feature of the summer circulation in the Northern Hemisphere (NH) and has been found to modulate the weather and climate conditions in many remote regions. This study investigates the most recurrent patterns of summertime midlatitude
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The Indian summer monsoon (ISM) is a prominent feature of the summer circulation in the Northern Hemisphere (NH) and has been found to modulate the weather and climate conditions in many remote regions. This study investigates the most recurrent patterns of summertime midlatitude circulation, over the eastern Mediterranean (EM) and also globally, that are most associated with the ISM. Monthly data of 44 summers from the ERA40 dataset are used and two multidimensional statistical methods, the Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA), are implemented. The ISM is found to be related to subsidence anomalies in the middle and more extendedly in the upper troposphere over the central and eastern Mediterranean and with an Etesian-like pattern regarding the field of the lower troposphere winds. An equatorial Rossby wave pattern, extending westward from an ISM heat source up to EM and N. Africa, was identified to be associated with the variability of ISM. The observed relationship between the ISM and the EM circulation features can be attributed to this equatorial Rossby wave response to the monsoon forcing. CCA implementation revealed the interconnection of the aforementioned PCA results with an ISM action center over the northern Arabian Sea and the monsoon trough region. Full article
(This article belongs to the Special Issue Advances in Atmospheric Physics: Selected Papers from CEST2017)
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Open AccessEditorial Air Quality Monitoring and Forecasting
Atmosphere 2018, 9(3), 89; https://doi.org/10.3390/atmos9030089
Received: 27 February 2018 / Revised: 28 February 2018 / Accepted: 28 February 2018 / Published: 1 March 2018
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Abstract
Air quality forecasting is a vital tool for local health and air managers to make informed decisions on mitigation measures to reduce public exposure risk.[...] Full article
(This article belongs to the Special Issue Air Quality Monitoring and Forecasting) Printed Edition available
Open AccessArticle Automatic Analysis of Trough Lines Based on Curvature Tracing
Atmosphere 2018, 9(3), 88; https://doi.org/10.3390/atmos9030088
Received: 7 November 2017 / Revised: 10 February 2018 / Accepted: 12 February 2018 / Published: 1 March 2018
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Abstract
To solve the problems that arise in traditional automatic methods for trough line analysis with regard to low processing efficiency and analytical accuracy, an automatic method for trough line analysis was proposed in this study, comprising the following steps. Firstly, the curvature of
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To solve the problems that arise in traditional automatic methods for trough line analysis with regard to low processing efficiency and analytical accuracy, an automatic method for trough line analysis was proposed in this study, comprising the following steps. Firstly, the curvature of contour lines was calculated using geopotential height field data to extract tracing start points, and candidate and non-candidate trough points were classified and recognized based on their curvature and relative positions. Afterwards, among the candidates, the eligible trough points were connected from tracing start point. Finally, the automatically analyzed trough lines were obtained after some post-processing steps. The experimental results indicate that the method is able to effectively identify meteorological trough lines, and that its performance is superior to some previous analysis methods of trough line in terms of analytical accuracy and processing speed. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessArticle Assessment of Bacterial Aerosol in a Preschool, Primary School and High School in Poland
Atmosphere 2018, 9(3), 87; https://doi.org/10.3390/atmos9030087
Received: 31 January 2018 / Revised: 19 February 2018 / Accepted: 23 February 2018 / Published: 27 February 2018
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Abstract
The issue of healthy educational buildings is a global concern because children are particularly at risk of lung damage and infection caused by poor indoor air quality (IAQ). This article presents the results of a preliminary study of the concentration and size distribution
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The issue of healthy educational buildings is a global concern because children are particularly at risk of lung damage and infection caused by poor indoor air quality (IAQ). This article presents the results of a preliminary study of the concentration and size distribution of bacterial aerosol in three educational buildings: a preschool, primary school, and high school. Sampling was undertaken in the classrooms with an Andersen six-stage impactor (with aerodynamic cut-off diameters of 7.0, 4.7, 3.3, 2.1, 1.1 and 0.65 μm) during spring 2016 and 2017, as well as the outside of the buildings. After incubation, bioaerosol particles captured on nutrient media on Petri dishes were quantitatively evaluated and qualitatively identified. The highest average concentration of bacterial aerosol was inside the primary school building (2205 CFU/m3), whereas the lowest average concentration of indoor culturable bacteria was observed in the high school building (391 CFU/m3). Using the obtained data, the exposure dose (ED) of the bacterial aerosol was estimated for children attending each educational level. The most frequently occurring species in the sampled bacterial aerosol were Gram-positive cocci in the indoor environment and Gram-positive rod-forming endospores in the outdoor environment. Full article
(This article belongs to the Special Issue Indoor Air Pollution)
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Open AccessArticle Evaluation of Analysis by Cross-Validation. Part I: Using Verification Metrics
Atmosphere 2018, 9(3), 86; https://doi.org/10.3390/atmos9030086
Received: 5 September 2017 / Revised: 20 February 2018 / Accepted: 24 February 2018 / Published: 27 February 2018
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Abstract
We examine how passive and active observations are useful to evaluate an air quality analysis. By leaving out observations from the analysis, we form passive observations, and the observations used in the analysis are called active observations. We evaluated the surface air quality
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We examine how passive and active observations are useful to evaluate an air quality analysis. By leaving out observations from the analysis, we form passive observations, and the observations used in the analysis are called active observations. We evaluated the surface air quality analysis of O3 and PM2.5 against passive and active observations using standard model verification metrics such as bias, fractional bias, fraction of correct within a factor of 2, correlation and variance. The results show that verification of analyses against active observations always give an overestimation of the correlation and an underestimation of the variance. Evaluation against passive or any independent observations display a minimum of variance and maximum of correlation as we vary the observation weight, thus providing a mean to obtain the optimal observation weight. For the time and dates considered, the correlation between (independent) observations and the model is 0.55 for O3 and 0.3 for PM2.5 and for the analysis, with optimal observation weight, increases to 0.74 for O3 and 0.54 for PM2.5. We show that bias can be a misleading measure of evaluation and recommend the use of a fractional bias such as the modified normalized mean bias (MNMB). An evaluation of the model bias and variance as a function of model values also show a clear linear dependence with the model values for both O3 and PM2.5. Full article
(This article belongs to the Special Issue Air Quality Monitoring and Forecasting) Printed Edition available
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Open AccessArticle Evaluating the Sensitivity of the Mass-Based Particle Removal Calculations for HVAC Filters in ISO 16890 to Assumptions for Aerosol Distributions
Atmosphere 2018, 9(3), 85; https://doi.org/10.3390/atmos9030085
Received: 25 January 2018 / Revised: 22 February 2018 / Accepted: 23 February 2018 / Published: 26 February 2018
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Abstract
High efficiency particle air filters are increasingly being recommended for use in heating, ventilating, and air-conditioning (HVAC) systems to improve indoor air quality (IAQ). ISO Standard 16890-2016 provides a methodology for approximating mass-based particle removal efficiencies for PM1, PM2.5,
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High efficiency particle air filters are increasingly being recommended for use in heating, ventilating, and air-conditioning (HVAC) systems to improve indoor air quality (IAQ). ISO Standard 16890-2016 provides a methodology for approximating mass-based particle removal efficiencies for PM1, PM2.5, and PM10 using size-resolved removal efficiency measurements for 0.3 µm to 10 µm particles. Two historical volume distribution functions for ambient aerosol distributions are assumed to represent ambient air in urban and rural areas globally. The goals of this work are to: (i) review the ambient aerosol distributions used in ISO 16890, (ii) evaluate the sensitivity of the mass-based removal efficiency calculation procedures described in ISO 16890 to various assumptions that are related to indoor and outdoor aerosol distributions, and (iii) recommend several modifications to the standard that can yield more realistic estimates of mass-based removal efficiencies for HVAC filters, and thus provide a more realistic representation of a greater number of building scenarios. The results demonstrate that knowing the PM mass removal efficiency estimated using ISO 16890 is not sufficient to predict the PM mass removal efficiency in all of the environments in which the filter might be used. The main reason for this insufficiency is that the assumptions for aerosol number and volume distributions can substantially impact the results, albeit with some exceptions. Full article
(This article belongs to the Special Issue Indoor Air Pollution)
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