In this research, the climatological characteristics of total column ozone (ToZ) over Irene, South Africa (25.5º S, 28.1º E), are studied using both ground-based and satellite observations. Satellite data from the Total Ozone Mapping Spectrometer (TOMS) from November 1978 to May 1993; the Global Ozone Monitoring Experiment-1 (GOME-1) from August 1995 to June 2003; the Earth Probe Total Ozone Monitoring Spectrometer (EP-TOMS) from January 1997 to December 2005; the Microwave Limb Sounder from October 2004 to April 2013; the Ozone Monitoring Interferometer (OMI) from October 2004 to December 2013; the Global Ozone Monitoring Experiment-2 (GOME-2) from January 2007 to December 2013; and the Infrared Atmospheric Sounding Interferometer (IASI) from June 2008 to December 2011, were used in this study together with ground-based measurement from a Dobson instrument (August 1989 to December 2011). The seven satellite and ground-based instruments used for this study were selected as they provide long term ozone monitoring data. Satellite observations were collected when they overpass Irene and showed that ToZ replicated the expected behavior of spring maximum and autumn minimum. When compared with other satellite data sets, TOMS ToZ data displayed values approximately 8 DU higher overall but showed good general agreement with measurements from the ground-based Dobson instrument. The OMI instrument had the best agreement with the Dobson instrument as the measurements are within 5 DU for all seasons. The result of trend trend analysis of ozone over Irene shows a significant decrease of ~8 DU in total ozone from 1978 to 1993 with a gradual recovery and increase of ~2 DU in total ozone from 1995 to 2005 as measured by both GOME-1 and EPTOMS. An increase of approximately 7-9 DU is observed in measurements from OMI and IASI thereby illustrating the gradual recovery of the ozone layer. EPTOMS also showed good agreement with the Dobson instrument. GOME-1 and GOME-2 reveal underestimation of ozone while IASI overestimated ozone for the first half of the year. Between 1995 and 2005, both EPTOMS and GOME-1 data showed a gradual increase in column ozone of approximately 2 DU which has increased to approximately 7 DU in the last decade as measured by OMI, GOME-2 and IASI satellites. The result obtained showed a very strong correlation (~97%) between the variation in OMI-Dobson and GOME-2-Dobson and (~85%) between the variation in EPTOMS-Dobson and GOME-1-Dobson.

We present concentrations of dissolved total carbon (TC) and organic carbon (OC) in rainwater samples collected in 2016 in the southern part of Mexico City in a preliminary study. TC ranged from 10 to 25 mgC L–1 and OC – reported as non-purgable organic carbon (NPOC) – varied between 2.5 and 20 mgC L–1. NPOC concentrations were higher in samples collected between May and July and a change in the ratio of NPOC/TC was detected for the second part of the campaign (i.e., August-October). 1H NMR analysis indicated presence of aldehydes, carboxylic and other oxygenated hydrocarbons in the precipitation. An evaluation of air mass back-trajectories suggested no relationship between the organic contents and wind directions. Carbon contents were originated from sources within the basin of Mexico and higher pH of rainwater during the passage of air masses indicates that the sources causing rain neutralization are located in northern parts of the city.

At the end of the 1980´s particulates and sulfur dioxide (SO2) were the main atmospheric pollutants in the Mexico City Metropolitan Zone (MCMZ). To reduce emissions, fuel oil was replaced by natural gas at power plants located inside Mexico City. Currently, SO2 levels do not exceed its air quality standard; however, acid rain is present with a high contribution of sulfate (SO42–). In this study, spatial and temporal variations in the chemical composition of rain in Mexico City between 2003 and 2014 were analyzed. Major ions (Na+, NH4+, K+, Mg2+, Ca2+, SO42–, NO3– and Cl–), pH, and electrical conductivity (EC) were analyzed weekly at 16 sampling stations located in the MCMZ. The pH decreased from north to south, with the lowest annual volume weighted mean (VWM) of 4.16 in 2006. Annual ion concentrations were, in decreasing order: NH4+, SO42 –, NO3– and Ca2+ for the entire study period at most of the sampling sites. The highest values for wet atmospheric deposition (kg/ha) were found in the Western area and were the maximum in 2007. Wet deposition had major levels for SO42– and NO3– of 24 and 20 kg/ha, respectively, and were similar to the levels registered in the USA in 2013 and 2014. Considering that external emission sources play a decisive role in acid rain within the City, it is necessary to establish strategies for the emission reductions of acid rain precursors from upwind sources.

Building structures constitute obstacles for the entrance and distribution of marine aerosol in the atmosphere of Havana City (tropical coastal climate). Due to the shielding effect caused by building structures, a considerable decrease in chloride deposition is determined at a short distance from the sea. Heavier and larger-sized chloride aerosol particles can settle down in the vicinity of breaking waves. The annual average wind speed showed significant influence in increasing chloride deposition at the exposure site close to the sea, where the effect of building structures is negligible and the predicted levels of corrosivity of the atmosphere are high, very high and extreme. Air temperature was the main climatic factor influencing chloride deposition (when temperature decreases, chloride deposition increases). Penetration of marine aerosol is eight times lower in Havana City with respect to other sites without obstacles. Airborne salinity distribution inside the city is different than outside the city.

The spatial analysis of the wet spell probability over the Indian region has been carried out using daily gridded (0.5º × 0.5º) rainfall data of 1971-2005 during the summer monsoon period, i.e. June-September. A threshold was applied to the weekly cumulative rainfall to convert the rainfall data into wet spell information. A Markov chain model was employed to estimate the initial and conditional probabilities of the wet spell for each grid and the spatio-temporal distribution of the wet spells probabilities was analyzed. The probability maps were able to capture the summer monsoon scenario over the Indian region, representing the onset, progression and withdrawal of monsoon rainfall. Higher wet spell probability was observed over the west coast and northeastern parts of India, i.e., the initial probability was maximum over these regions. However, lower probability values were observed in West Rajasthan, Gujarat and southern India. A threshold of 80% of the maximum initial probability was used to standardize the spatially-variable probability information, and a week with more than the threshold values was considered as a probable wet week. The duration of the longest probable wet spell was highest along the west coast and in northeastern India, whereas it was lowest in western and southern India. The start and duration of the longest spell of the probable wet week can be used for rainfed-agricultural planning, i.e., the start of sowing/planting, selection of crops and varieties based on their length of growing period, optimum harvesting period to avoid wet spell, etc. 

Wildfires impact both ecosystems and human welfare, being carbon monoxide and PM2.5 particles the most critical emissions affecting human health. The impact of a fire in the Tepozteco National Park, in the state of Morelos, Mexico was evaluated on its potential to produce health impacts on the surrounding inhabitants. Surrounding population centers are located at around 2000 m from the area affected by the wildfire, which occurred in a natural protected natural area. HYSPLIT simulations to estimate pollutant trajectories were conducted along with a dispersion simulation to determine pollutant concentrations as a function of distance to the centers of population. The results show that the inhabitants of adjacent communities were not subject to significant risk levels according to national and international regulations, because the dispersion trajectory of the pollutants did not impact such populations. In Mexico, it is necessary to prioritize prevention, monitoring, and mitigation measures of human-induced wildfires. It is recommended to increase the coverage of the monitoring network of Morelos to include the Tepoztlán Municipality, due to the high frequency of fires and the growing urbanization in the zone.

Land surface processes play a critical role in governing the surface energy partitioning and the atmospheric circulation within a climate system. Improper representations of present land state, particularly spatially specific fields such as land cover, topographical and biophysical parameters contribute to the uncertainty in the model’s weather simulations extending from local to regional scales. The present study investigates the impact of superior land surface datasets on the performance of the Weather Research and Forecasting (WRF) model in simulating micrometeorological/near-surface weather, particularly sensible variables such as temperature, relative humidity, solar radiation and wind speed. The hypothesis is that the updated land surface datasets would help in improving micrometeorological forecasts over the domain comprising of Punjab, Haryana and Uttarakhand states in India. A land use land cover (LULC) dataset derived from Advanced Wide Field Sensor (AWiFS); an elevation dataset from the Shuttle Radar Topography Mission (SRTM), and a Leaf Area Index (LAI) based on the Moderate Resolution Imaging Spectroradiometer (MODIS), are used in model initialization. Performance evaluation of the model’s simulation is done for controlled (default) and modified land boundary conditions with in situ weather from a network of automatic weather stations (AWS) operated by the Indian Space Research Organization (ISRO). In the modified run, the model more closely captured the temporal evolution of surface level temperature, relative humidity, wind speed, surface pressure and solar radiation. Improvement in 24-hr forecast ranges from 15 to 30% for these near-surface weather variables. Further testing of the model’s performance on its capability to forecast 8-day micrometeorological weather variables revealed that the modified run gave consistent results. The average RMSE values for minimum and maximum temperature, wind speed, relative humidity and precipitation are 2.5 and 3 ºC, 2 m s–1, 18% and 3.5 mm, respectively. The modification helped in increasing the lead-time of the model’s forecast by reducing the propagation error. Thus, this study emphasizes the fact that improved representation of land surface parameters has a definite effect on weather simulations at local to regional scales. For a country like India, where the feedback mechanisms between land and atmosphere are more prominent due to inherent climatic characteristics, it is critical to concentrate and improve on the inputs that represent the initial land state. 

This study deals with the evaluation of the Weather Research and Forecast (WRF) model’s parameterization schemes when used for global horizontal irradiation (GHI) forecasts, to assess the feasibility of solar energy utilization. The study area is the southeastern Anatolia (SEA) region of Turkey, with favorable weather conditions for solar energy generation. The results indicate that the values in the hourly output of GHI in the model were overestimated for all configurations at all stations compared to observations. The relative mean bias error values at five stations for all configurations vary between 10-21% for clear-sky and 17-30% for partly-cloudy conditions. Similarly, the relative RMSE values at the five stations vary between 20-39% for clear sky and 41-70% for partly-cloudy conditions. However, there are noticeable differences among the various configurations of the WRF parameterizations.

Noise, especially continuous noise, is an important factor that affects the velocity dealiasing of Doppler weather radars. A challenge in the design of dealiasing algorithm is how to effectively suppress noise. Therefore, a novel anti-noise dealiasing algorithm (AND) for Doppler velocities was proposed in this paper. In comparison with traditional methods, the AND utilizes a new separation-restoration noise suppression scheme, which can significantly reduce the interference of noise on dealiasing without losing data. This algorithm utilizes three fitting curves as references to correct ambiguous echoes, and it can further suppress residual noise and dynamically match wind fields at varying scales. The AND has been applied to the CINRAD-SA network of operational radars in China, achieving a better performance on noisy echoes, isolated echoes, typhoon echoes, and tornado echoes.

Thunderstorms are one of the most devastating mesoscale severe weather phenomena, which play an important role in the occurrence of rainfall activity over a region. Therefore, in the present study an attempt has been made to identify the relationship between thunderstorm days (Thn), rainy days (Thr) and rainfall amounts (Trr) for 294 meteorological stations spreading over India, by means of published data (climatological normals) from the India Meteorological Department (IMD) for four periods, 1951-1980, 1961-1990, 1971-2000, and 1981-2010. The analysis has revealed a sharp decrease in the frequency of Thn, while Thr and Trr showed a slight decline. A significant correlation between Thn, Thr and Trr has been observed. Monthly analysis has exhibited a dual peak in the occurrence of Thn and single peak in rainfall activity; however, a time lag of one month in their peak occurrence was detected. These results show that the Indian summer monsoon affects significantly the thunderstorm activity over India. Seasonal analysis suggests that Thn, Thr and Trr are maximum during the monsoon season, while minimum during winters. Apart from this, Thn and Thr, and Thn and Trr have demonstrated a negative relationship during the monsoon, which may be anomalously due to decreasing temperature in India during that season. In addition, the spatial annual and seasonal pattern of the occurrence of Thn, Thr and Trr shows almost a similar pattern during 1951-1980. However, a sharp decline in the frequency of Thn has been observed during subsequent periods over all parts of the country. Likewise, a slight decline in the frequency of Thr and Trr has been observed over India, except in the northeast, where an increasing trend in rainfall activity has been observed. The computed ratio between Thn and Thr (R) has been found maximum during the pre-monsoon, whereas the ratio between Trr and Thn (RTR) during the monsoon season. Regional analysis of Thn, Thr and Trr revealed a wide range of variations in the occurrence of these parameters month after month. It is believed that the results presented in this study will be useful for weather forecasters, aircraft pilots, agriculturists and planners.

What: International experts and attendees from several countries of Central America, Mexico, the Caribbean (CAM), and South America (SA) met to discuss regional issues on climate variability and climate change to learn the use of the non-hydrostatic version of the International Center for Theoretical Physics (ICTP) RegCM4.6 model, and to establish a regional modeling scientific community for understanding the physics of climate processes and the generation of regional climate change scenarios.When: 14-18 November 2016.Where: Center for Geophysical Research (CIGEFI in Spanish) and School of Physics, University of Costa Rica (UCR), San José, Costa Rica.

We conducted the first research in the Czech Republic to measure ventilation and ammonia (NH3) emission rates in a naturally ventilated animal building (dairy farm) during a five-day measurement period in June, combined with a three-month (May-July) monitoring of NH3 concentration and dry deposition at 12 locations along horizontal gradients from the dairy farm up to the distance of 400 m. Passive diffusion-tube samplers were used to measure monthly NH3 concentrations. Moisture (H2O) balance was used to determine ventilation rates of the dairy farm. Continuous measurements of gas concentrations (NH3), temperature and relative humidity inside and outside the building were performed. The air exchange rate was 4.8 h–1 and the emission rate was 43.2 NH3 g cow–1 d–1 for building. The emission rate was 126% of what was obtained using emission factors from the Czech national inventory (34.2 g cow–1 d–1). NH3 concentrations and dry deposition fluxes decreased exponentially with distance from the dairy farm. Between May and July, mean predicted dry deposition fluxes ranged from 0.28 to 0.03 µg NH3 m–2 s–1 at a distance of 50 and 400 m from the source, respectively. Dry NH3 deposition over the nearest 400 m from the source accounted for 11.5% of daily emissions. The results confirm the short-range dispersion of NH3 emitted from a point source found in other studies, but it may not be the same in other situations, since dispersion of NH3 is dependent on the surrounding land-cover and on the number of animals in a barn.

The first ever long-term measurement of black carbon (BC) aerosols over an urban location at the central Indo-Gangetic Plain (IGP) is presented. Both short- and long-term variations in BC during the period 2009-2013 are discussed with specific emphasis on variation in BC sources, meteorology, trend and possible transport pathways across the IGP. High BC mass loading was noted with a 5-yr composite mean (± SD) of 11.8 (± 8.6) µg m–3, having strong and consistent seasonal variations (median: 8.8; range: 1.4-48.0 µg m–3). Winter (21.5 ± 9.9µ gm–3) and post-monsoon (17.4 ± 10.2 µg m–3) specific rises in BC mass were consistent with the increase in household emissions, and from agricultural residue burning. The BC mass concentration was mostly influenced by local sources, while sudden change in BC was consistent with the change in Delta-C, indicating emissions primarily from biomass burning. Beside sources, atmospheric boundary layer height was noted to considerably influence short-term variations in BC concentration. A statistically significant monotonic increasing trend in BC concentration (0.9 µg m–3 yr–1) was computed along with its 95% uncertainty bounds (0.38-1.52 µ gm–3 yr–1). Increase in BC concentration was consistent with a rise in BC sources across the IGP and over India. Furthermore, clear evidence of local and regional scale transport of BC aerosols was found using the particle Lagrangian model.

This study presents the main differences between classical cold fronts, subtropical fronts and baroclinic troughs, as well as a climatology of these systems along the coast of Brazil. Regarding the seasonality of these systems, classical cold fronts are more frequent in winter followed by spring, subtropical fronts in spring, and baroclinic troughs in spring and summer. In southeastern Brazil, these three kinds of systems are responsible for about 40% (60%) of the total precipitation during the rainy (dry) season.

This study presents an analysis of the summertime mesoscale convective systems (MCSs) that developed in northwestern Mexico during the strong ENSO events of 1997-1999. From the analysis of geostationary data, results indicate that the largest number of MCSs was associated with the 1997 El Niño event throughout a longer active period. During the La Niña event of 1999 fewer MCSs were observed, which had developed over a shorter active period. The occurrence of the MCSs is linked to the location of the ridge and the anti-cyclonic anomalies at 500 hPa and 200 hPa, respectively.