Atmósfera

Comparison of meteorological indices for drought assessment and monitoring: A case study from the Tafna watershed, Northwestern Algeria

Djillali Fettam — 2025-05-28

Drought is a complex phenomenon that includes meteorological, agricultural, and hydrological aspects. It is characterized by an extended period of insufficient rainfall that adversely impacts civilization‘s economic, social, and environmental aspects. This study compares four meteorological indices, including the Standardized Precipitation Index (SPI), China-Z index (CZI), Modified China Z Index (MCZI), and Z-Score Index (ZSI), to identify the most suitable drought indices (DIs) for assessing drought in the Tafna watershed. Monthly rainfall data from 14 stations (1970-2019) were used to calculate drought events on 1-, 3-, and 12-month time scales. On the 1- and 3-month time scales, the frequency of total drought for SPI-1 and CZI-1 is higher than for MCZI-1 and ZSI-1. At the 12-month time scale, all DIs showed the same frequency of total drought for most stations. The highest Pearson correlation coefficient is observed between SPI-1 and CZI-1 on a 1-month scale, with values exceeding 0.939 across all stations. Additionally, 57 and 71% of stations exhibit the highest correlation between SPI and CZI, with coefficients exceeding 0.963 and 0.999 at 3- and 12-month scales, respectively. Most stations do not show any trend (increase or decrease) using the Mann-Kendall trend test in all index values at 1- and 3-month scales. On a 12-month scale, most stations showed an increase in the values of all DIs. The results reported in this study provide valuable insights that can enhance the management of water resources and improve preparedness for drought events in the Tafna watershed, particularly in the context of climate change.

Analysis of extreme precipitation in eastern China from 1960 to 2020 and future projections

Qin Guan — 2025-05-28

This study analyzes extreme precipitation in eastern China over the past 60 years through climatology and trend detection, with future projections using 10 indices. Data from 1310 meteorological stations and 20 CMIP6 models were employed to examine the spatiotemporal evolution of these indices from 1961 to 2020 during summer, both regionally and across eight major river basins. Key findings include: (1) the spatial distribution of extreme precipitation generally decreases from south to north and east to west. High-value centers for extreme precipitation are found south of the Yangtze River, while the maximum consecutive wet days decline from the southeast coast inland. (2) Extreme summer precipitation in eastern China increased over six decades, with intensity, 1-day max, heavy, extreme heavy precipitation, and very heavy rain days rising at 0.03, 0.11, 0.22, 0.13 mm yr^–1, and 0.02 d yr^–1, respectively. Trends show growth in the Yangtze River Basin and the northeast, but declines in the Hai and Yellow River basins, with decreases up to 0.50 mm yr^–1. (3) Multi-model ensemble simulations reliably capture summer extreme precipitation trends, indicating that by 2060, heavy and extreme precipitation amounts will increase by up to 10% under SSP-1.26. Higher carbon emissions will further accelerate this increase, particularly in the southeast rivers, the Pearl River, and the Yangtze River basins. These results provide important references for predicting extreme precipitation in eastern China.

Effect of green corridors on the mitigation of the urban heat island (UHI) in the district of Lince, Lima, Peru

Isabella Molina-Barrenechea — 2025-05-22

In Peru, various studies on canopy urban heat islands (CUHI) show their effects on the health and habitability of cities. In the case of Lima, various effects have been analyzed. However, the analysis of the mitigation mechanisms of urban heat islands is still limited. Therefore, information on the mitigation potential of such measures is also limited. The main objective of this work is to evaluate the effect of green corridors on Arequipa Avenue in the city of Lima with respect to the mitigation of CUHI. The work was carried out by recording temperatures and relative humidity between August and September 2022, using fixed stations, through determined observation points, and numerical atmospheric modelling. The results show that the maximum temperatures reached in areas without a corridor are higher than those in areas with a green corridor by up to 5.4 ºC. On the other hand, there are significant differences in the intensity of CUHI between areas inside and outside the corridor. CUHI values within the corridor, ranging from 0.4 to 0.6 ºC, are lower than those found outside, indicating the positive effect of the green corridors in mitigating the CUHI impact. The analysis of the data allows us to evaluate the effectiveness of this intervention proposed in the Strategic evaluation of measures to reduce the urban heat island in the Province of Lima, prepared by the Metropolitan Municipality of Lima.

Analysis of extreme events: Large coverage drought and daily precipitation events in Jalisco, Mexico

José Pablo Vega-Camarena — 2025-05-22

The objectives of the present study are to analyze: (1) drought events with large coverage and their possible response to El Niño Southern Oscillation (ENSO) and (2) extreme daily precipitation (EDP) events, both during the 1980-2019 period considering daily precipitation data from climatological stations during the summer months (July-September) in the state of Jalisco, Mexico. For the first objective, a drought analysis was performed using the Standardized Precipitation Index (SPI) at time scales of three (SPI-3) and 12 months (SPI-12), calculating seasonal (July-September) and annual (January-December) series. For the second objective, an EDP event was defined by filtering records greater than 30 mm from the selected stations, then adjusting them to a probability distribution to obtain the 99th percentile (P99) of each series. Values above P99 were identified as EDP events. The results indicate that drought events with large coverage (SPI-12) occurred under La Niña conditions in the 1989-1990 and 2011-2012 periods, affecting 71.4 and 64.3% of the state, respectively, where the coastal region was the least affected. A total of 57 EDP events were identified, but no particular ENSO pattern was determined. The most frequent peak activity occurred in 1987, 1999, 2010, and 2013, representing 31.6%, concentrated in 11 out of 28 climatological stations. While ENSO influences are weaker in these regions, other drivers, such as tropical cyclones, need adaptive disaster preparedness measures. Strengthening early warning systems, improving urban drainage infrastructure, and updating zoning regulations can mitigate flood impacts, reduce economic losses, and protect lives.

Spatial variation of climate change indices in the state of Chiapas, Mexico

Celia de la Mora Orozco — 2025-05-13

Although climate change is evidenced by a steady increase in global temperature, several indicators have been defined and are represented by mathematical expressions called indices, which are identified, recorded, and compared to demonstrate variations in climate change. However, using these indices requires: (1) timely evaluation, and (2) determining their spatial variation over a given region. However, there are only a few studies on the spatial trend of these indices, which is important considering that the impacts of climate change, as well as the factors that determine them, are not spatially homogeneous. Therefore, information from the historical series (1969-2009) of 16 meteorological stations, distributed in Chiapas, Mexico, was used. To determine the spatial variation of the climatic indices, each index was associated with 25 environmental variables through multiple linear regressions defined by the stepwise procedure. According to the results, the environmental variables with the greatest significant influence (p < 0.001) were mean annual temperature, mean annual runoff, real evapotranspiration, mean minimum temperature, and mean annual isotherms. On the other hand, the variables not used in the models were: highest insolation in May, soil moisture regimes, hydrogeology, biotic provinces, and physiographic provinces. The results of multiple linear regression models defined high R² values (from 0.72 to 0.97), and the resulting mapping shows that each index defined a particular spatial variation. We conclude that, for the purpose of evidencing climate change, the process followed in this work can be used to determine the variation of this type of index in other regions.

Regionalization of precipitation in Guatemala in climatology and El Niño-Southern Oscillation in its Niño, Niña, and neutral phases

José Luis Argueta Mayorga — 2025-05-09

The regionalization of precipitation is a vital tool for understanding hydrological phenomena, particularly in the context of the El Niño-Southern Oscillation (ENSO) phases (El Niño, La Niña, neutral, and climatology) in Guatemala. This study introduces a novel framework that defines previously diffuse regional boundaries, revealing the dynamic nature of precipitation patterns across the country. The findings demonstrate how regional boundaries shift in response to ENSO phases, as well as under climatology and neutral conditions. These insights highlight the importance of considering dynamic regionalization to accurately analyze climatic impacts and precipitation variability, providing a foundation for more effective climate adaptation strategies.

Predictive models of incident solar radiation and its reflectance on surfaces with anti-weed screens

Francia Deyanira Gaytán-Martínez — 2025-04-21

In agriculture, the wavelengths of interest are UV A + B radiation and photosynthetically active radiation. Different techniques can be used by farmers to enhance radiation distribution on crops, with one alternative being the installation of polypropylene anti-weed nets. The analysis of the radiation balance can be performed using different predictive methods, which are a function of solar geometry, climate, and weather variables. The objective of this research was to develop multiple regression models for comparison with the Holt-Winters model in time series to analyze and estimate incident radiation and its reflectance on surfaces covered with white and black polypropylene anti-weed nets and soil without cover. The results indicate an increase in radiation and temperature between Julian days 116 and 273, decreasing significantly with cloud cover. The white polypropylene anti-weed nets reflected a higher amount of solar radiation. On the other hand, the multiple regression models presented better accuracy for the prediction of incident solar radiation and its reflectance compared to the Holt Winters time series model. However, each model provides a different analysis of radiation, so that they can be complementary in decision making for agricultural purposes.

New experimental device for measuring electrical charge of precipitation particles

Rodolfo Guillermo Pereyra — 2025-04-11

A new approach is presented in this work to measure the electrical charge carried by precipitation particles and their corresponding fall velocity. The instrument represents an improved version of our previous device, with the primary goal of increasing the sampling rate of charged droplets to improve and make the statistical analysis of charged raindrops more robust. Additionally, the instrument incorporates a computational program for detecting individual raindrop passages, enabling automatic calculation of its electrical charge and fall velocity. To test the new device’s performance, it was simultaneously used with our previous instrument during a storm in Córdoba on November 21, 2023. It was observed that the latest instrument increased the sampling rate nearly fivefold compared to the old one. The results demonstrate a high degree of consistency across different devices, validating the reliability and reproducibility of the new device.

A quantitative study of extreme rainfall intensity and occurrence in northern Algeria

Ahmed Kheloufi Attou — 2025-04-08

This paper examines the characteristics associated with the spatiotemporal evolution of extreme precipitation, assesses its recurrence frequency, and predicts future return levels over northern Algeria. The study employs extreme precipitation indices in conjunction with the application of extreme value theory to a rainfall dataset spanning from 1982 to 2022. The study focused on modeling the index that demonstrated the highest percentage of significant positive trends at the α = 0.05 significance level. This was accomplished through the utilization of the Mann-Kendall test and the generalized extreme value distribution. Subsequently, the model was validated using the Kolmogorov-Smirnov fit test. The results revealed that the northeastern region of the study area experienced a more pronounced increase in rainfall intensity compared to the southern and western regions. Significant trends in precipitation intensity were observed over time. Notably, the index of days with rainfall exceeding 20 mm demonstrated the highest percentage of positive trends, with 88% of meteorological stations exhibiting an upward trend. Furthermore, a strong correlation was identified between the index of days with rainfall exceeding 20 mm and the very wet days index, particularly in the high plateaus and western region. This finding supports the hypothesis that extreme rainfall patterns are becoming more frequent in the region.

The influence of rainfall on the extinction coefficient and the meteorological optical range

Guillermo Montero-Martínez — 2025-04-03

The meteorological optical range (MOR) is an objective parameter for assessing atmospheric visibility. Data collected using optical disdrometers (PWS100) were used to analyze MOR estimates when extreme rainfalls occurred at two locations in Mexico: Chamela, on the Pacific coast, and Juriquilla, a continental sampling site. The performance of the disdrometer for rainfall estimation was found to be consistent and satisfactory when compared to rain gauges. Analyses based on rainfall rate (R) outcomes from tipping bucket rain gauge data showed that MOR measurements registered the most significant decreases during periods of highest R. The assessed coefficients for the extinction coefficient (σ) and R power-adjusted relationships are comparable to those obtained in previous studies, and the statistical performance of the fitted equations in modeling σ values is excellent. The equation coefficients for these mathematical expressions indicate that precipitation at the sampling sites is initiated from mixed (Bergeron-type) clouds, and it can be inferred that mixed-phase thunderstorms were predominant at the sampling sites during the chosen periods. Our findings indicate that MOR and σ are closely related to the large raindrop proliferation and the broadening of the raindrop size distribution (inferred from the increase of the median volume diameter). Despite the underestimation of small raindrops by the optical disdrometer, this study demonstrates the reliability of MOR estimates obtained with the PWS100 during rainfall events.

Variability of the Atlantic Niño: Impacts on precipitation in the state of Maranhão, Brazil

Thalita Mirian Santos Furtado — 2025-03-20

The study analyzed the influence of the Atlantic Niño on precipitation anomalies in Maranhão from 1980 to 2020. Using the Atlantic Niño index, 20 events were identified, predominantly with 2- to 8-year scales. A significant reduction was noted from the 2000s, likely due to the weakening of the Bjerknes feedback and the Atlantic Multidecadal Oscillation. However, events in 2019 and 2021 suggested that the negative phase of the Atlantic Multidecadal Oscillation may have contributed to the reactivation of the Atlantic Niño after 19 inactive years. The negative early termination event was “non-canonical”, with positive sea surface temperature anomalies in the North Tropical Atlantic and positive east winds. A relationship was found between the Atlantic Niño and the Atlantic Meridional Mode, influencing elements like sea surface temperature and interhemispheric winds, which in turn affected precipitation patterns in Maranhão. These findings highlight the complex climate interactions in the region, emphasizing the need to consider multiple factors, including local and remote climate modes, for understanding precipitation variability. The study underscores the importance of continuous monitoring and research on the Atlantic Niño and the Atlantic Meridional Mode to anticipate impacts on rainfall volume and distribution in Maranhão, aiding regional strategic planning.

Regional characterization of ENSO effects on the seasonal rainfall of Sinaloa, Mexico

César Enrique Romero Higareda — 2025-03-11

Rainfall seasonality is of paramount relevance for the northwestern Mexican ecosystems. Among other factors, it is annually driven by the North American Monsoon. An outstanding yet irregular and changing factor that affects rainfall seasonality is the El Niño Southern Oscillation (ENSO) and its two phases, El Niño and La Niña, which can change the seasonal rainfall patterns. Here, we characterized spatially seasonal rainfall patterns of three physiographic regions of Sinaloa and adjacent states in northwestern Mexico. The covariances between El Niño and La Niña phases and their respective summer and winter rainfall amounts were estimated in each station within their regions. The magnitude of covariance was also differentiated among regions and characterized spatially. A multivariate analysis was performed to attain a simultaneous perspective of the rainfall-related variables. We detected differences among regions for the measured rainfall-related variables; altitude and longitude explained most of its spatial variation. Winter rainfall increased in all stations of El Niño and La Niña occurrence. El Niño decreased rainfall in most stations for summer, whilst La Niña increased rainfall in summer. Summer rainfall covariance with El Niño and La Niña was differentiated among regions. Latitude and longitude were correlated with the covariation between El Niño and La Niña and winter rainfall. Altitude correlated to the interaction of summer rainfall and La Niña and El Niño. Multivariate analysis segregated regions on the variation of winter, annual rainfall, number of rainfall events, and rainfall seasonality.

Impact assessment of 3D-var data assimilation on simulation of tropical cyclones using WRF

Pragnya Makar — 2025-03-03

The combination of data from the Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) satellites provide measurements in frequency channels 23-183 GHz, which allow the estimation of vertical profiles of atmospheric temperature and humidity. These measurements play a significant role in numerical weather prediction models, improving initial conditions during tropical cyclone development. In the present study, measurements from AMSU-A and MHS have been assimilated in the Weather Research and Forecasting (WRF) model through the 3D-variational (3D-var) data assimilation technique using the Gridpoint Statistical Interpolation (GSI) analysis system. The assimilation impact has been assessed on super cyclonic storm Amphan and severe cyclonic storm Nisarga, which formed over the Bay of Bengal (BoB) and the Arabian Sea (AS), respectively. To investigate their impact, a series of experiments are conducted with and without assimilation of AMSU-A and MHS observations from each day’s initial condition for both cyclones. The track and landfall errors of all the experiments are computed against the best track position provided by the India Meteorological Department (IMD). The results indicate that the assimilation of AMSU-A and MHS observations led to an improvement in track errors of about 11 to 35% for Amphan and 6 to 20% for Nisarga for 12 to 72 h lead times. Furthermore, the assimilation of AMSU-A and MHS observations helped to improve the simulation of landfall position and time. The evaluation of maximum sustained surface wind, central pressure, and rainfall against the observations demonstrates the positive impact of the assimilated observations on the performance of the WRF model.

A case study of the sea/land breeze diurnal cycle in the Peninsula and Gulf of Nicoya, Costa Rica: Interactions with local and regional processes

Natali Mora — 2025-02-25

The presence of sea breeze (SB) is analyzed at nine meteorological stations in the northwest of Costa Rica (Peninsula and Gulf of Nicoya, GF); two from the Ticosonde-NAME experiment, University of Costa Rica, and seven from the National Meteorological Institute, for the period from July 1 to September 16, 2004. An objective detection algorithm for SB is applied to hourly data from the stations and sea surface temperature (SST). The algorithm uses temperature gradient and wind direction. Pinilla and Guacalillo stations show 64% of SB on the 78 days analyzed. Liberia (20 km inland) presents 44.9% of SB associated with weak synoptic winds from the east. Puntarenas presents doubtful cases due to wind errors, while the other stations do not present complete records. Some of the non-SB days are dominated, on one hand, by strong synoptic flow from the northeast associated with the low-level Caribbean jet that in turn coincides with the periods of reduced rainfall or mid-summer drought and, on the other hand, by synoptic flow from the southwest associated with the passage of weather systems in the western Caribbean. The algorithm shows a good ability to detect SB despite the poor spatial resolution of SST. Consistent with a typical SB circulation, precipitation at almost all stations is characterized by coastal convective activity and precipitation in the late afternoon and evening hours. The results are encouraging for their potential application to artisanal fishing, agriculture, tourism, and regional air quality, as there are very active ports in the Gulf of Nicoya (Puntarenas and Caldera), points of intense movement of tourist and commercial ships that negatively impact environmental conditions.

Performance evaluation of random forest and boosted tree in rainfall-runoff process modeling for sub-basins of Lake Urmia

Zeinab Bigdeli — 2025-02-21

This study aimed to develop rainfall-runoff (P-Q) modeling using machine learning models in the sub-basins of Lake Urmia, Iran. In this research, chronological records of hydrological parameters and meteorological inputs at a regional scale were analyzed using Random Forest (RF) and Boosted Tree (BT) heuristic methods. This study compared the performance of these two models for the Urmia Basin over the period from 1976 to 2019. The results showed that the RF model provided better estimates in Akhula, Daryan, and Ghermez Gol stations in the eastern sub-basin and Miandoab, Pole Ozbak, Abajalu Sofla, Nezam Abad, and Pole Bahramlu stations in the western sub-basin. In contrast, the BT model performed better at Pole Senikh, Shishvan, Gheshlagh Amir, Shirin Kandi, and Khormazard stations in the eastern sub-basin and Babarud, Keshtiban, and Yalghoz Aghaj stations in the western sub-basin. Additionally, the time series analysis showed changes in yearly rainfall frequency and a decreasing trend in flow discharge in most years. These findings highlight a significant reduction in inflow to Lake Urmia over the past 43 years, with a particularly sharp decline in recent years.

Changes in surface air temperature for Mediterranean climate in Turkey

Buket Mesta — 2025-01-28

Local climate influences of inland water bodies, complex topography, and surrounding seas cause temperate, arid, and continental climate properties to prevail with local variations in different parts of Turkey. The intra-regional variability of environmental factors creates uncertainties and challenges in climate modeling. Multi-model ensemble analysis is suggested to be used to characterize the uncertainties and minimize the generalization error in projections. This study is part of a research on climate change impacts in Turkey, focusing on the impacts on surface air temperature through a multi-model ensemble analysis of high-resolution climate models. The ensemble set comprises 12 EURO-CORDEX RCMs and two models from the Japan Meteorological Research Institute (MRI). Firstly, historical model data are validated with temperature records from 59 meteorological stations. Furthermore, changes in temperature climatology in the future in short- (2020-2030), medium- (2031-2050), and long-term (2051-2100) horizons are analyzed and compared with the precipitation changes. In the ensemble, two MRI models (MRI-AGCM, NHRCM) and two CORDEX RCMs nested in the HadGEM2-ES (RCA4 and CCLM4-8-17) perform best to replicate the spatial variability of climatology. The 14-member ensemble projects a gradual increase in the temperature up to 4.5 and 6.6 ºC under RCP4.5 and RCP8.5 scenarios, respectively. The projections agree on an inverse relationship between temperature and precipitation changes. More substantial impacts are projected in inland compared to coastal regions.

Air quality in the Metropolitan Zone of the Valley of Puebla: Comparative evaluation of CAMS and persistence forecasts

Javier Omar Castillo-Miranda — 2025-01-08

Background on air quality in the Metropolitan Zone of the Valley of Puebla shows that suspended particles smaller than 10 micrometers (PM₁₀) and smaller than 2.5 micrometers (PM_2.5) represent a health risk. Puebla’s automatic air quality monitoring system measures PM₁₀ and PM_2.5at five stations in the municipalities of Puebla and Coronango. These measurements allow for determining the Air and Health Index according to the NOM-172-SEMARNAT-2019 standard for these pollutants. The advancement of global pollutant modeling techniques represents an opportunity for air quality management in areas with scarce terrestrial measurements. However, it is necessary to validate global forecasts with ground measurements from georeferenced monitoring stations to reduce uncertainties and determine reliability. The Copernicus Atmospheric Monitoring Service (CAMS) forecast allows atmospheric pollution exploration processes in the study region. This study presents an analysis of the CAMS forecast against the Persistence forecast. The results show that the persistence forecast performs better than the CAMS forecast in general, both for PM₁₀ and for PM_2.5. However, using the CAMS forecast for a preliminary evaluation of the prediction of PM_2.5is feasible due to its acceptable values in the comparison criteria of the dichotomous statistics ACCURACY, probability of detection (POD), false alarm rate (FAR), probability of false detection (POFD), success ratio (SR), threat score (TS), equitable threat score (ETS), Heidke skill score (HSS), and odds ratio skill score (ORSS). This work provides valuable insights to both the population and decision-makers, aiding in the enhancement of air quality management and public health strategies.

Satellite precipitation product assessment and correction technique selection at sub-basin scale for maximum annual events. Case study: Acaponeta River basin

Edith Bonilla-López — 2025-01-07

Satellite precipitation products (SPP) are increasingly being used for detailed hydrological studies due to scarce and discontinuous precipitation observations at different spatial and temporal scales. However, to evaluate its full utility, it is necessary to assess and correct the bias between estimated and observed precipitation (OP). The aim of this paper is to evaluate the CHIRPSv2.0 product for maximum annual events and different climatological conditions based on in-situ observations, using statistical metrics and selecting from linear scaling (LS), local intensity scaling (LOCI) and power transformation (PT) the appropriate bias correction technique (CT), at point and sub-basin scale, improving the maximum annual precipitation records for the period 2001-2020 in the Acaponeta River basin, Mexico. Previous applications of bias CT have focused on broader temporal scales rather than specific maximum events. Differences in the performance of the correction methods were identified between point and sub-basin scales. PT presented a good performance at the point scale, in contrast to percentual bias (PBIAS), which resulted in a great overestimation at the sub-basin scale in the upper zone for the average and dry years, while for the wet year, it overestimated in the lower part. Although LS and LOCI generally observed a good PBIAS reduction at the gauge stations, LS overestimated at the sub-basin scale overall. LOCI showed better SPP corrections in the middle and lower zones and a wider range of overestimation for the upper basins in the middle and wet years. The corrected annual maximum estimated values for the revised period are useful for hydrological analysis in the context of flood risk assessment.

Diurnal to seasonal meteorological cycles along an equatorial Andean elevational gradient

Luis Silva — 2025-01-07

The climate of the Andean equatorial mountains has a pronounced spatiotemporal variability, which, coupled with limited meteorological monitoring, hampers our understanding of the regional and local atmospheric processes that govern this variability. To deepen our understanding of this region’s climate, we analyzed diurnal to seasonal meteorological patterns of the main meteorological variables: precipitation, air temperature, relative humidity, incident solar radiation, and wind speed and direction. We used a unique 10-year high-resolution dataset from March 2013 to February 2023 along an elevation gradient located in southern Ecuador. Our analyses reveal a trimodal regime of precipitation; two wet seasons are associated with convective processes influenced by the position of the Intertropical Convergence Zone (ITCZ) over the study area during the equinoxes, and the less humid season is due to the intensification of the Walker circulation, which produces subsidence over the study area. The relative humidity shows distinct daily and seasonal variations, reaching minimum daily values around noon when the air temperature is the highest, and an annual minimum in November. Incident solar radiation reaches its maximum values around the equinoxes when sunlight is almost perpendicular, which produces greater heating on the surface and, hence, a more humid atmosphere. The meridional displacement of the ITCZ around the year influences the climate, increasing humidity from March to May and wind speed from April to July. Our research reveals significant differences between diurnal and seasonal meteorological cycles, highlighting the importance of altitude, topography, and wind patterns in the climate dynamics of the equatorial Andes.

Satellite-based analysis of climate oscillations: Implications for precipitation in an arid watershed in Mexico

David Eduardo Guevara-Polo — 2025-01-07

Climate oscillations are known to have an important influence on weather patterns across the world. While the impact of El Niño Southern Oscillation (ENSO) has been well documented, there is a scarcity of studies examining the effects of the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). This study uses satellite data to confirm that ENSO significantly influences precipitation in the Nazas-Aguanaval watershed from October to March, as evidenced by Spearman correlation coefficients. In contrast, the PDO influence is registered during specific months (January, March, November and December), while AMO impacts precipitations during April-June, November, and December. These results were corroborated using ANOVA, reinforcing the influence of ENSO and indicating a limited impact of PDO and AMO on this watershed. Finally, a linear model was developed to estimate monthly precipitation anomalies based on the phase of these three indices for the different sub-basins. Notably, monthly precipitation anomalies ranged between 140% and –78% in dry months. Our results demonstrate the influence of climate oscillations in precipitation in the Nazas-Aguanaval watershed and the usefulness of satellite data for conducting these analyses. Likewise, we set a starting point for investigating the implications of climate oscillation phases for water management and drought disaster prevention.