Showing papers in "Atmosfera in 2021"

Seven decades of climate change across Mexico

Abstract: Due to its geographical location, Mexico is one of the most vulnerable countries to climate change. However, we currently ignore the exact magnitude and particularities of past climate change in the Mexican territory and are missing a country-level spatially explicit analysis based on observed data. To fill this gap, I analyzed how temperature, precipitation and the water balance of Mexico changed over 1951-2017 at interannual and seasonal scales. My results show a clear national increment in temperature (+0.71 oC) but no modification in annual mean precipitation. At the seasonal scale, the wet season (June-November) had higher rainfall (+31 mm) and no change was detectable on the dry season (December-May). However, when the full water balance was seasonally accounted for (precipitation minus potential evapotranspiration), the trend resulted in a wetter wet season and a much drier dry season across the country. Regionally, seasonal changes in water balance were larger in the area surrounding the Gulf of Mexico and positive in the Yucatan Peninsula and the central highlands. My results help explaining the recent increase in drought, storms and intense rainfall across Mexico and suggest even more extreme seasonal weather in the future if climate change exacerbates.

The Negative Impact of Biomass Burning and the Orinoco Low-Level Jet on the Air Quality of the Orinoco River Basin

Abstract: Biomass burning (BB) is a common activity in developing countries and has been identified as a serious air pollution threat. The present work evaluates the air quality of the largest town in the extensive Colombian savannas (250,000 km2) for the first time, from measurements over three consecutive years (2017-2020). Although the air quality in Villavicencio is good in terms of PM10 and O3 for most of the year, the pollution levels for both pollutants exceed the World Health Organization recommended limits during the dry season (February to April). The combination of the Orinoco low-level jet (OLLJ) with the BB emissions from the Venezuelan and the Colombian savannas was identified as the main cause of the poor air quality episodes during the dry season in this city. Organic carbon derived from reanalysis was identified as the main component of the high PM10 concentrations during the dry season. However, mineral dust and sea salt particles were also found to play an important role in the poor air quality observed in Villavicencio and likely along the Orinoco river basin region. Finally, between November and March, the OLLJ was found to be an efficient mechanism for the transport of air pollutants from the Atlantic Ocean and the savannas regions in the Orinoco River Basin in Venezuela and Colombia towards southern regions of Colombia, and in some cases, Ecuador.

Performance evaluation of the WRF model in a tropical region: wind speed analysis at different sites

Abstract: In this study, the performance of the mesoscale Weather Research and Forecasting (WRF) model is evaluated using combinations of three Planetary Boundary Layer (PBL) and three Land Surface Model (LSM) schemes, in order to identify the optimal parameters for the determination of wind speed in a tropical region. The state of Bahia in Brazil is selected as the location for the case study and simulations are performed over a period of eight months between 2015 and 2016. This is done to ensure that the dry and rainy seasons at the three different experimental sites—Esplanada, Mucuri, and Mucugê—are well separated from each other. The results of the simulations are compared with the observational data obtained from three towers equipped with anemometers at heights of 80, 100, 120 and 150 m, strategically placed at each site. Overestimation of wind speed is observed in the simulations, despite similarities between the simulated and observed wind directions. In addition, the accuracies of simulations corresponding to sites that are closer to the ocean are observed to be lower—the most accurate wind speed estimates are obtained corresponding to Mucugê, which is located farthest from the ocean. Finally, analysis of the results obtained from each tower accounting for periods with higher and lower precipitation reveals that the combination of the PBL-YSU scheme with the LSM-RUC scheme yields the best results.

Understanding convective storms in a tropical, high-altitude location with in-situ meteorological observations and GPS-derived water vapor

Abstract: We investigate convective storms over the Sabana de Bogota, a high-altitude and densely populated area in the Colombian tropical Andes. Convective events are identified using infrared satellite images and in-situ precipitation data. As expected, convection shows a strong early-afternoon peak during the two rainy seasons. Previous studies hypothesize that early-afternoon westerly winds and their moisture advection from the warmer Magdalena Valley are the main explanatory mechanism for intense storms. We find that early-afternoon westerlies are present in 78% of the rainy season days, but convective events develop in only 26% of the days. Thus, although westerlies seem necessary for convection due to the convergence they generate, they only occasionally generate storms, and are therefore not a good predictor. Furthermore, reanalysis data indicate that precipitable water vapor (PWV) at the Magdalena Valley is anomalously low during convective days, suggesting that moisture converges locally instead of being advected from the west. Based on composites of surface wind speed, air temperature, pressure and GPS-derived PWV, we identify the most prominent signals associated to deep convection: a weaker than average wind speed throughout the morning, higher than normal values of surface air temperature towards noon, followed by an anomalous steep increase of PWV and wind speed. These features indicate that convection results from a strong diurnal forcing facilitated by convergence of westerly winds, combined with sufficient water vapor convergence, with a timescale of about 3 hours. This highlights the relevance of high temporal resolution monitoring of PWV offered by Global Navigational Satellite System stations.

Application of network theory to study spatio-temporal evolution in the weekend effect in urban areas

Abstract: The occurrence of higher ground-level O3 concentrations on weekends rather than on weekdays, despite reduced anthropogenic activity in urban areas, is known as the O3 weekend effect (OWE). Here, we present an approach to analyse OWE spatio-temporal variations in urban areas, integrated by the trend, prediction and network representation. We used data from ten monitoring sites geographically distributed within the Mexico City Metropolitan Area (MCMA) recorded during 1994-2018. The OWE occurrence within the MCMA ranged typically between 40 and 60 % of the total weeks per year. The annual differences between weekday and weekend O3 peaks (magnitudes) showed were most significant on Sundays. Naive, Linear and Auto-regressive Integrated Moving Average models were tested for predicting the OWE annual occurrences and magnitudes. There was no single model that outperformed significantly for predicting OWE at all sites. The proposed concept of generalised OWE (GOWE) implies that at least half of the sites under study exhibited simultaneous OWE occurrence. GOWE is represented as a network and its integration with prediction models is useful to determinate the OWE spread over the MCMA in the following years. The GOWE occurrence showed an increasing trend interpreted as the spread of VOC-limited conditions over most of the MCMA. Predicted data suggest that, with the current emission control policies, the GOWE will continue occurring. The integrated methodology presented permits the acquisition of valuable insights into the design of potential air quality control strategies.

The mid-summer drought spatial variability over Mesoamerica

Abstract: The region that includes southern Mexico and Central America is known as Mesoamerica. The annual cycle of precipitation characteristic of the Pacific slope of this region presents a bimodal distribution on summertime, with two maxima and a relative intraseasonal minimum, known as the Mid-Summer Drought (MSD). In this study, the small-scale (tens of kilometers) variability of the MSD is analyzed. Numerical simulations are performed using the regional climate model RegCM4 over a Mesoamerican domain for a six-year period. ERA Interim reanalysis data is used as initial and lateral boundary conditions. The domain is subdivided into smaller areas and the average annual cycle of precipitation distribution is computed for each of them. The MSD pattern is found to present a high spatial variability in the intensity of its two maxima and even the total absence of its characteristic minimum. Such behavior is attributed to soil-atmosphere and terrain topography interactions that are better resolved with a regional climate model.

Carbon monoxide emissions assessment by using satellite and modeling data: Central Mexico case study

Abstract: This paper quantifies and reduces the differences in emissions from the 2008 inventory with respect to the real ones through the use of satellite observations and modeling. Carbon monoxide column comparisons from the Infrared Atmospheric Sounding Interferometer (IASI) satellite data were made against columns obtained from the WRF-Chem model, during February 2011. The analysis was carried out at the satellite passage local time (approximately 10:00 LT) over Mexico City. The 2008 National Emissions Inventory generated by the Mexican Ministry of Environment and Natural Resources was utilized. An inversion method was applied to the modeled and observed column data. With the above, scaling factors were obtained for five regions and the concentration from the model domain boundaries, which were used to update the emissions. These were used in modeling and the result was compared with surface measurements. For Mexico City and the Metropolitan Area, a scaling factor equal to 0.43 was obtained when using the 2008 emissions inventory; for Toluca, Morelos and Puebla, a less than one factor was estimated, while for Hidalgo and the concentration from model boundaries it was close to two. The model performance was improved by an increment in the agreement index and a reduction on the mean square error when the updated CO emissions were used.

Evaluating reanalysis and satellite-based precipitation at regional scale: A case study in southern Mexico

Abstract: Accurate precipitation data is essential for any hydrometeorological study, particularly for calibration and simulation of hydrological models In this paper, we evaluate the precipitation of two different reanalysis products (the ERA5 and GLDAS), and two satellite-based precipitation products (TRMM 3B42 and CHIRPS) over the La Sierra river basins in Southern Mexico, on regional and daily time scales, from 2008 to 2010 We compare the collocated gridded precipitation data against in-situ precipitation measurements in each gauge station, as well as the mean areal precipitation (MAP) over the catchments in the study area for the different products The Pearson correlation coefficient, the root mean square error, and the multiplicative bias metrics suggest that CHIRPS and ERA5 are the highest quality precipitation products over the study area CHIRPS performs better on the grid to point comparison, estimating better precipitation events from 10-50 mm, above 100 mm, and for all the values without threshold ERA5 does better for precipitation from 0-10 and 50-100 mm These two datasets also have better performance on representing the spatial rainfall variability according to the mean annual precipitation and MAP analysis, showing statistical values close to each other

Characterization of particulate matter in iron ore mining region of Itabira, Minas Gerais, Brazil

Abstract: Itabira has in its territory the largest complex of opencast mining in the world, which is located close to residential areas of the city. The air quality-monitoring network installed in the city is the main source of particulate matter emission data. However, these air quality stations only cover the areas near the mines and does not measure fine particulate matter. Thus, a first field campaign was carried out to characterize the particulate matter in the city and to compare the Hi-Vol data from air quality stations with the dichotomous air sampler data. Results of trajectories cluster analysis showed a long-range transport of aerosols during the sampling days from northeast (84% of the trajectories), east-southeast (12%) and south-southwest (3%) directions. Regarding to the meteorological conditions during the sampling days, negative correlations were seen between coarse particulate matter from mostly air quality stations and all meteorological parameters (but temperature). Results of the X-ray fluorescence and principal component analyses showed that the main trace elements in the coarse and fine modes are Iron and Sulfur, associated with emissions from mining activities, air mass transport from regional iron and steelmaking industry activities, vehicle emissions, local and regional biomass burning and natural biogenic emissions. This work represents the first assessment of source apportionment done in the city. Comparisons with other studies for some Brazilian larger cities showed that Itabira has comparable contributions of sulfur, iron and elements, such as copper, selenium, chromium, nickel, vanadium and lead.

Emission inventory point source visualization on Google Earth and integrated with HYSPLIT model (edited by Dr. Luisa Molina)

Abstract: Emissions inventories are fundamental tools in the management and research of air pollution, climate change, and other relevant areas of knowledge. This work shows how the Mexico national emissions inventory for criteria pollutants was transferred from an Excel file to a structured and standardized one based on Extensible Markup Language (XML), following the Keyhole Markup Language (KML) standard and the United States Environmental Protection Agency consolidated emissions reporting schema using a Python script (provided as supplementary material). We also show how once in the KML format, the results are compatible with Google Earth and any Geographic Information System (GIS) platforms. The KML format may also allow emissions inventory models to interoperate with Chemical Transport Models (CTM) that would be able to read/write XML files for research and public environmental management policy. As an example, we used Google Earth to engage the point source data and the dispersion of a hypothetical release for that point source modeled using the Hybrid Single Particle Lagrangian Integrated Trajectory developed by the National Oceanic and Atmospheric Administration (HYSPLIT-NOAA), whose outputs also can be displayed on Google Earth. Finally, the KML files outputs from the inventory and HYSPLIT-NOAA model can be visualized on any computer platform and mobile applications that incorporate Google Earth.

Rainfall uncertainty and water availability: Elements for planning water allocation to users in irrigation districts of Mexico. Study case: Irrigation District 041, Yaqui River

Abstract: The aim of this work is to present a protocol for analyzing readily available climatic and hydrological information on watersheds, in order to achieve a rational planning of irrigation water allocation under rainfall uncertainty conditions. We present as case study the Yaqui River watershed and Irrigation District (ID) No. 041 in the state of Sonora, Mexico. The watershed is divided into three sub-watersheds that drain into three reservoirs. Our findings indicate a strong dependence of water availability on the reservoirs, conditioned by El Nino phenomenon. In addition, rainfall-runoff relationships indicate the capability to produce a runoff for each sub-watershed and the differentiated impact of El Nino. The three sub-watersheds require about the same amount of antecedent rainfall for initiating the runoff (5 mm). A standardized precipitation index (SPI) highlights the dynamics of dry and wet spells and the impact on the planted area within the irrigation district. Overall, the functional relationships between El Nino, the SPI, and the planted area in the irrigation district may serve for planning purposes under climate uncertainty scenarios.

New approach for local C-band weather radar precipitation calibration

Abstract: Weather radar calibration is a topic of great current interest because it is useful for various hydrological applications. Several methods have been developed for adjusting the relation between reflectivity data Z and rainfall intensity R (Z/R) because droplet size distributions in different storm events are unknown and highly variable in time and space. The present study developed and tested a new space and time window-based procedure for optimal local calibration of weather radar using Z/R relations and applying it to convective and stratiform storms in the lower Grijalva river basin in Mexico. Improving rain estimates from the Sabancuy, Campeche radar is essential because it monitors this basin, which is prone to floods. The resulting estimates of the optimal power-law (Z = AR b ) window-based procedure (OP) are compared with those of the default Marshall and Palmer (MP) relation using the observed rain gauge records. The appropriate window was selected using a criterion that considers factors affecting the free fall of raindrops. For most of the storms tested, metrics for the OP models showed better values than those calculated for the MP ones. The best MP performance is when using smooth calibration data, achieving similar metric results to that of the OP. The proposed observed calibration method could be useful to improve the default MP model estimates at any weather radar with similar characteristics to the ones analyzed in this work. The resulting Z/R relations could improve precipitation radar estimates for hydrologic model inputs.

Assessment of the accuracy of open-circuit respiration chambers for measuring enteric methane emissions in cattle

Abstract: Ruminants are the main source of methane emissions from the agricultural sector. Emission inventories and mitigation strategies require reliable technics of measurement. The respiration chamber methodology is a precise approach for measuring enteric methane emissions in cattle. A set of experiments was carried out to validate two respiration chambers for measuring enteric methane emissions of cattle. The chambers were calibrated considering three main components: the methane analyzer, the air duct and air extraction system, and the chamber itself, by evaluating linearity and response time of the analyzer, plateau variability and high purity methane recoveries in chambers. Recovery test calculations carried out after releasing high purity methane into the chambers gave calibration factors of 0.95 ± 0.05 and 1.03 ± 0.03 for the complete system of respirations chambers one and two, respectively, with corresponding uncertainties of 4.87 and 2.49%. Thus, the respiration chambers for enteric methane measurements of cattle at the University of Yucatan, Mexico function with precision and accuracy. This technique can be used to establish methane inventories and methane mitigation strategies in cattle.