Atmósfera (Journal)
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Population growth in Mexico and its impact on mitigation components of nationally determined contributions
Full text linkBy 2050, most of the population in Mexico will be between 44 and 50 years old. By 2100, the population is expected to decrease to 116 million, 9% less than in 2020. Mexico recently ratified its commitment to face the planetary climate crisis by updating its nationally determined contribution, increasing its goal of reducing greenhouse gases from 22% to 35% by 2030. The main goal of this article is to estimate carbon emissions in 2018 (pre-pandemic conditions) of selected mitigation components and compare them with estimated values for 2030, considering the population variation under a business-as-usual scenario. If growth takes place at an exponentially compounded rate, this projection exercise shows that by 2030, the transport sector (private and public) could reduce its CO2 emissions by 21%, the residential sector will increase its CO2 emissions by 4.1%, and the municipal waste sector would increase its methane emissions by 10%. It is advisable to quantify the differentiated impact of climate change on the lives of diverse population groups, and after evaluating the effectiveness of solutions that reduce the exposure of these groups to climate change, to enhance their role as agents of climate action in terms of decarbonization and/or resilience to its effects
Maximum daily precipitation in Iran (1979-2018)
Full text linkThis article deals with daily precipitation intensities. The maximum daily precipitation values were calculated for return periods of 10, 20, 50, and 100 years using the daily precipitation levels recorded at 42 meteorological stations between 1979 and 2018. Three extreme value probability distribution adjustments were used to do this: Weibull, Generalized Extreme Value, and Gumbel. While all fit the annual maximum daily rainfall series well, Weibull produces lower values than the other two distribution methods. The results show considerable differences between the Caspian fringe in the north, with values reaching 300 mm in Ramsar for a return period of 50 years, and some of the more arid eastern areas of the country, where values were less than 40 mm. An area near the Strait of Hormuz in the south was also identified as having high values. The maximum daily precipitation correlates positively with the annual total and negatively with altitude
Lightning-rainfall relationship in El Niño and La Niña events during the Indian summer monsoon over central India
Full text linkThe Indian summer monsoon rainfall (June-September) on a regional scale is critically important for agriculture and water management in India. The current study presents the lightning-rainfall relationship during El Niño (drought) and La Niña (flood) events in the Indian summer monsoon over central India. The results show that the flash count, Bowen ratio, surface maximum temperature, total heat flux, aerosol optical depth (AOD), sea surface temperature (SST), and Niño 3.4 index are increased by 36, 62, 19, 12, 46, 4.7%, and 0.3 ºC (warmer), whereas the rainfall is decreased by 15% during El Niño years with respect to normal years. The flash count, Bowen ratio, surface maximum temperature, and AOD are found to decrease by 15, 11, 3.5, and 11.1% during La Nina years, whereas the rainfall, total heat flux, SST, and Niño 3.4 index are found to increase by 2.4, 1.72, 0.36%, and –0.68 ºC (cooler) during La Niña years with respect to normal years. The increase in the flash count and the reduction in rainfall are associated with the warm phase of El Niño-Southern Oscillation (ENSO) (El Niño), which causes the weakening of the Indian summer monsoon. The decrease in flash count and increase in rainfall is due to the cold phase of ENSO (La Niña) and is associated with the strengthening of the Indian monsoon season. The increase in the number of break days and low-pressure systems also plays an important role in El Niño and La Niña years, respectively, over central India during the Indian summer monsoon
Why did numerical weather forecasting systems fail to predict the Hurricane Otis’s development?
Full text linkHurricane Otis (HO) occurred in the eastern tropical Pacific (ETP), intensifying rapidly and unexpectedly, making landfall near Acapulco at 06:25 UTC on October 25, 2023 as a category five hurricane. Official and unofficial national weather forecasts (NWF) failed to predict HO’s development, trajectory, and intensification. To analyze the reasons for the failure of the NWF, we conducted two experiments using the Weather Research and Forecasting (WRF) model, with Global Forecast System (GFS) and fifth-generation ECMWF atmospheric reanalysis (ERA5) data as initial condition (IC). Our results showed that some fields in the GFS data, such as relative humidity, convective available potential energy, and even sea surface temperature, were more favorable for the development and intensification of the disturbance compared to ERA5. However, the three-dimensional structure of the wind field in the ETP in GFS did not contribute to the initial development of HO. Additionally, we explored the WRF’s sensitivity to different model configurations to simulate the trajectory and intensity of the hurricane using a coupled ocean-atmosphere system composed of WRF and a three-dimensional upper-ocean circulation model based on Price-Weller-Pinkel. Our numerical experiments involve modifications in the IC, cumulus parameterizations (CP), roughness coefficients, spatial resolutions, different time steps, and an idealized coupled model. The sensitivity test reveals the significance of the CP scheme, where the Kain-Fritsch was the only one that helped simulate the HO properly, altogether with increased spatial resolution. Furthermore, ocean-atmosphere coupling improves the prediction of the landfall time and location of the HO. However, no experiment captured the intensity or rapid intensification of HO
Time series trend analysis of rainfall and temperature over Kolkata and surrounding region
Full text linkStudies of temperature and rainfall long-term variability in the context of climate change are important, particularly in regions where rainfed agriculture is predominant. Long-term trends of temperature and rainfall have been determined for Kolkata, India (a tropical region) using gridded monthly data from the Global Precipitation and Climate Centre (GPCC v. 7) with 0.5º × 0.5º resolution for the period 1901 to 2014. Precipitation concentration index, coefficient of variation, and rainfall anomaly have been calculated and Palmer drought severity index has been analyzed. Furthermore, the Mann-Kendall test and Sen’s slope estimate have been used to detect time series trend. Annual temperature and rainfall have increased at a rate of 0.0082ºC yr–1 and 0.03 mm yr–1, respectively. Most months show statistically significant increasing trends for temperature and rainfall. Rainfall with high precipitation concentration index (16-20) has been observed for the period 1951-1975 and 1976-2000. The number of years with dry conditions has increased. However, the intensity of dryness is very close to zero. The information from this study will be helpful for farmers to plan for resilient farming
Spatiotemporal distributions of ultraviolet radiation from OMI orbital data and relationships with total O3 and total NO2
Full text linkUltraviolet radiation (UVR) plays a key role in the photochemistry of the atmosphere, through absorption or dispersion processes by its constituents (ozone, cloudiness, aerosols, and pollutants in the troposphere). Quantifying UVR in a spatial-temporal way and knowing its relationships with modulating variables is important for Rio Grande do Sul State, a region with one of Brazil’s highest skin neoplasms rates. Ultraviolet radiation data for the region, acquired by the Ozone Monitoring Instrument (OMI) for the period 2006 to 2020, and expressed in terms of erythemal daily dose (EDD), was used in this study, with the objective of quantifying UVR incidence and its stability in time and spatial distribution. Our results show that for this study area the radiation varies from 3300 to 3700 J m–2, with a latitudinal gradient of 66.7 J m–2 per degree, with maxima recorded in December (6028 J m–2, summer) and minima in June (1123 J m–2, winter). A long-term decreasing trend of 29.76% (z value = –2) was observed in the area, while 6.19% of the area had an increasing trend (z value = 5). During the studied period of 15 years, occurrences of high values of EDD were negatively correlated with total O3 as the dominant relationship. Positive or negative correlations with total NO2 were also recorded, depending on the investigated season or region
Synoptic characteristics of the spatial variability of spring dust storms over Saudi Arabia
Full text linkStatistical and synoptic studies of spring dust storms over the Arabian Peninsula (AP) were performed using surface observations from 27 surface stations and meteorological data from the NCEP/NCAR reanalysis data set for the period 1978-2008. The study showed that, spatially, the northern and eastern AP are the regions most affected by dust storms and that, temporally, the study period can be divided into two subperiods: before and after 1995, with a pronounced increase before 1995 and a smooth increase (decrease) after 1995 with respect to dust (dust storms) types. The synoptic study reveals three main atmospheric systems: frontal systems over the northern region, Red Sea Trough (RST)-related systems over the western region, and thermal low systems over the eastern region. Additionally, the synoptic study shows that all the atmospheric systems are associated with a favorable pressure (geopotential) gradient area and that the shape and strength of the maximum wind and upper-layer atmospheric regimes are suitable for completely integrating the atmospheric layers. Moreover, the southern thermal low is a common synoptic component of dust-related atmospheric systems, but its effect is particularly pronounced in the atmospheric system of the eastern region
El Niño-Southern Oscillation diversity and its relationship with the North Atlantic Oscillation – Atmospheric anomalies response over the North Atlantic and the Pacific
Full text linkTo explore the impacts of El Niño-Southern Oscillation (ENSO) on the North Atlantic Oscillation (NAO), the linear correlation among the indices of each oscillation was investigated. The indices Niño 1+2, Niño 3, Niño 3.4, Niño 4, ONI, SOI, BEST, TNI and MEI were used to represent the ENSO, besides the NAO index. The analysis considers the ENSO diversity in its spatial structure. The results show that when years with Eastern Pacific (EP) La Niña events were omitted, the linear correlation increased concerning other scenarios. This means that NAO responses for the Central Pacific (CP) ENSO tend to be linear, but seemingly they are not so for EP ENSO, which explains why the ENSO/NAO relationship has been difficult to identify and predict. The TNI-NAO relationship had the highest correlation values, followed by NAO-El Niño 4, whilst NAO/El Niño 1+2 and NAO/El Niño 3 showed the lowest coefficients. The results also confirmed that the atmospheric dynamics over the North Atlantic have a more linear teleconnection to the West and Central Pacific than to the Eastern Pacific. Changes in deep convection, atmospheric circulation, and vorticity are discussed like possible mechanisms that trigger the changes in impacts over the North Atlantic and other locations. The composite anomalies map also showed the contrast in the effects of both events and the importance of considering those differences when modeling ocean dynamics
Geocoding and spatiotemporal modeling of long-term PM2.5 and NO2 exposure in the Mexican Teachers’ Cohort
Full text linkEpidemiological studies on air pollution in Mexico often use the environmental concentrations of pollutants as measured by monitors closest to the home of participants as exposure proxies, yet this approach does not account for the space gradients of pollutants and ignores intra-city human mobility. This study aimed to develop high-resolution spatial and temporal models for predicting long-term exposure to PM2.5 and NO2 in ~16 500 participants from the Mexican Teachers’ Cohort study. We geocoded the home and work addresses of participants, and used secondary source information on geographical and meteorological variables as well as other pollutants to fit two generalized additive models capable of predicting monthly PM2.5 and NO2 concentrations during the 2004-2019 period. Both models were evaluated through 10-fold cross-validation, and showed high predictive accuracy with out-of-sample data and no overfitting (CV-RMSE = 0.102 for PM2.5 and CV-RMSE = 4.497 for NO2). Participants were exposed to a monthly average of 24.38 (6.78) µg m–3 of PM2.5 and 28.21 (8.00) ppb of NO2 during the study period. These models offer a promising alternative for estimating PM2.5 and NO2 exposure with high spatiotemporal resolution for epidemiological studies in the Mexico City Metropolitan Area
Climate regionalization of Santa Cruz province, Argentina
Full text linkClimate regionalization is essential for characterizing spatial and temporal climatic variability, producing meteorological forecasts, analyzing trends at different scales, and determining the climatic impact on human activities. The aim was to propose a climatic regionalization for Santa Cruz province, based on gridded rainfall and temperature data (period 1995 to 2014), and subsequent characterization. We applied the non-hierarchical k-means clustering method to monthly accumulated rainfall and monthly average temperature databases to achieve this goal. The Thornthwaite classification modified by Feddema was used to classify each cluster. Results from this study showed that Santa Cruz province is divided into 11 climatic regions based on rainfall and temperature. The driest and warmest regions are located in the center and northeast of the province and the most humid and coldest ones in the south and southwest. Regionalization is an important component of many applied climate studies and it can be used in other studies related to agriculture, energy production, water resource management, extreme weather events, and climate change, among others. This regionalization in particular can be used to examine the impacts of climate change in regional studies of climatic scale reduction in Santa Cruz province. It can also be essential in the study of drought and its impacts, and contributes to a better understanding of the climatic phenomena that condition drought