Next Issue
Previous Issue

Table of Contents

Atmosphere, Volume 9, Issue 3 (March 2018)

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Cover Story (view full-size image) El Niño is a regional phenomenon in the tropical Pacific Ocean with global impacts. It is [...] Read more.
View options order results:
result details:
Displaying articles 1-36
Export citation of selected articles as:
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
PDF Full-text (1148 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
PDF Full-text (11666 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
PDF Full-text (26835 KB) | HTML Full-text | XML Full-text | Supplementary Files
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
[...] Read more.
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)
Figures

Figure 1

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
PDF Full-text (13276 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
PDF Full-text (5435 KB) | HTML Full-text | XML Full-text
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.
[...] Read more.
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)
Figures

Figure 1

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
PDF Full-text (1492 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
Cited by 3 | PDF Full-text (18289 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
Cited by 1 | PDF Full-text (7463 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
PDF Full-text (4162 KB) | HTML Full-text | XML Full-text
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.).
[...] Read more.
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)
Figures

Figure 1

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
PDF Full-text (2968 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1a

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
PDF Full-text (12447 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
Cited by 1 | PDF Full-text (26168 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
Cited by 3 | PDF Full-text (1081 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
PDF Full-text (5959 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
Figures

Figure 1

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
PDF Full-text (117 KB) | HTML Full-text | XML Full-text
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)
Back to Top