Atmósfera (Journal)
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Seven decades of climate change across Mexico
Get PDFDue 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 UNAM-droplet freezing assay: An evaluation of the ice nucleating capacity of the sea-surface microlayer and surface mixed layer in tropical and subpolar waters (edited by Dr. Michel Grutter)
No full textIce nucleating particles (INPs) in the atmosphere are necessary to generate ice crystals in mixed-phase clouds, a crucial component for precipitation development. The sources and composition of INPs are varied: from mineral dust derived from continental erosion to bioaerosols resulting from bubble bursting at the ocean surface. The performance of a home-built droplet freezing assay (DFA) device for quantifying the ice nucleating abilities of water samples via immersion freezing has been validated against both published results and analyses of samples from sea surface microlayer (SML) and bulk surface water (BSW) from the Gulf of Mexico (GoM) and Saanich Inlet, off Vancouver Island (VI), Canada. Even in the absence of phytoplankton blooms, all the samples contained INPs at moderate concentrations, ranging from 6.0 × 101 to 1.1 × 105 L–1 water. The freezing temperatures (i.e., T50, the temperature at which 50% of the droplets freeze) of the samples decreased in order of VI SML > GoM BSW > GoM SML, indicating that the higher-latitude coastal waters have a greater potential to initiate cloud formation and precipitation
Carbon monoxide emissions assessment by using satellite and modeling data: Central Mexico case study
Get PDFThis 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
New approach for local C-band weather radar precipitation calibration
Get PDFWeather 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 = ARb) 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
Meteorological data assimilation for air quality modeling with WRF-Chem: Central Mexico case study
Get PDFMeteorological data assimilation from surface observations (PREPBUFR) and satellite radiance (BUFR) provided by the National Centers for Environmental Prediction (NCEP) is carried out to determine their possible influence on chemical variables concentrations such as ozone (O3), obtained from air quality modeling over central Mexico using the photochemical Weather Research and Forecasting Model with Chemistry (WRF-Chem) during a bad-pollution event due to high O3 concentrations in the Mexico City Metropolitan Area on May 1-4, 2013. For this, the Weather Research and Forecasting Data Assimilation (WRFDA) module was adapted to run with WRF-Chem, and the 3DVAR assimilation technique (which is implemented in the WRFDA) was selected. Six study cases were defined taking into account the combination of the data source type with the assimilation process start times (00:00 and 12:00 UTC). Results indicate that independently of these factors, data assimilation modifies in general the meteorological variables (temperature and wind) initial conditions to obtain a better agreement between model simulations and observations, although statistics results are even higher when the process starts at 12:00 UTC using a combination of PREPBUFR and BUFR data (PB+RD cases). It was also verified that there is an influence on O3 concentrations since the statistical metrics obtained for the different experiments carried out are modified; however, it is insufficient to considerably improve the chemical variable model performance
A study of trends for Mexico City ozone extremes: 2001-2014
Get PDFWe analyze trends of high values of tropospheric ozone over Mexico City based on data corresponding to the years 2001-2014. The data consists of monthly maxima ozone concentrations based on 29 monitoring stations. Due to the large presence of missing data, we consider the monthly maxima based on five well identified geographical zones. We assess time trends based on a statistical model that assumes that these observations follow an extreme value distribution, where the location parameter changes in time accordingly to a regression model. In addition, we use Bayesian methods to estimate simultaneously a zonal and an overall time-trend parameter along with the shape and scale parameters of the Generalized Extreme Value distribution. We compare our results to a model that is based on a normal distribution. Our analyses show some evidence of decaying ozone levels for the monthly maxima during the period of study
The mid-summer drought spatial variability over Mesoamerica
Get PDFThe 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
Wind profile analysis for selected tropical cyclones over the South China Sea based on dropsonde measurements
Get PDFVertical wind profiles of selected tropical cyclones over the South China Sea are studied for the first time using dropsonde measurements by a fixed-wing aircraft of the Hong Kong Government. They are studied in two aspects which have not been conducted before for storms over the South China Sea. First the strengthening and weakening of the tropical cyclones are analyzed based on the radial wind profiles, namely, inflow and outflow, particularly over the atmospheric boundary layer. Second, the vertical wind profiles are fitted using the commonly considered wind profile models reported in the literature and compared with stipulations in Hong Kong and Chinese structural design codes. This would have significant contributions to wind engineering applications in the region. The results are unique for tropical cyclones over South China Sea and would serve as useful reference for the studies of tropical cyclones in this ocean basin
Relationship between precipitation anomalies and multivariate ENSO index through wavelet coherence analysis
Get PDFA better understanding of the local and regional spatio-temporal variability of past precipitation is needed to contextualize climate change research. Monthly precipitation data from 59 stations in the state of Zacatecas, Mexico were transformed into standardized monthly precipitation anomalies for the period 1976-2010 (34 years). Cluster analysis of the new time series was used to identify regions with similar precipitation regimes. Power spectrum analysis was carried out to identify important frequencies. Wavelet coherence analysis was performed to detect significant relations between each of the regional mean standardized anomalies of the monthly precipitation (SAMP) time series and the Multivariate El Niño Southern Oscillation Index (MEI). Three regions were identified: semi-arid, highlands and canyons. In all the three regional SAMP series, the 0.5-, 1-, 2- and 3-year frequencies are present in the power spectrum; the highlands and canyons regions showed important frequencies of 13 and 12 years, respectively. The 3-year frequencies may be linked to El Niño Southern Oscillation phenomenon. Three periods with significant correlation between regional SAMP time series and the MEI were identified: 1993 to 2003 for the semi-arid region, 1995 to 2003 for the highlands region and 1988 to 2003 for the canyons region. The results suggest that precipitation anomalies vary over time and according to regions. The results also strongly indicate that precipitation is modulated by the MEI
Analysis and selection of optimal sites for wind farms: case study, region north of Mexico
Get PDFThe analytic hierarchy analysis process allowed establishing a hierarchical model of a target function under a set of criteria aimed at choosing the best sites for the installation of wind farms in the north of Mexico. In this study, a large number of known and estimated criteria of diverse types (technical, economic, environmental, and social) were used, based on preliminary studies and information that allowed for the identification of the most relevant variables. The process simplifies a complex problem into simpler ones that can be analyzed independently, facilitating the efforts of decision takers since it allows envisaging the feasible alternatives. Once the most weighty and relevant variables were obtained, each variable was transformed into feasibility maps, and through the technique of map algebra coupled to a geographic information system, the sites were assessed in feasibility percentages in a general map fulfilling the set of imposed variables. The best scenarios for the location of a wind farm corresponded to the southern part of the state of Coahuila. The multicriteria analyses focused on decision-making within the planning process and characterization of feasible sites for a wind farm, are tools that optimize the selection of different variables, favoring the most relevant for the project by considering decision elements that are difficult to assess or quantify