Ciencias de la Tierra Sólida
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Ciencias de la Atmósfera, Hidrosfera y Cambio Climático
Ciencias de la Tierra Sólida
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Impacto de la Geofísica en el Desarrollo Sostenible
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Instrumentación Geofísica y Desarrollo Tecnológico
Ciencias de la Atmósfera, Hidrosfera y Cambio Climático
Ciencias de la Tierra Sólida
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Impacto de la Geofísica en el Desarrollo Sostenible
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Enlaces de Referencias
Automatic detection and classification of Spread-F in ionograms using convolutional neural network
(Elsevier, 2025-05-30) Yacoub, Moheb; Pacheco, Edgardo E.; Abdelwahab, Moataz; De la Jara, César; Mahrous, Ayman
Equatorial spread-F (ESF) is an irregularity caused by plasma instabilities on the night side that causes signal degradation and disruptions to the GNSS signals. Ionosondes could detect ESF as it appears as a diffused echo in the ionogram images. This study proposes a Convolutional Neural Network (CNN) model that can automatically detect ESF within the ionogram images and classify its type. The model has been trained using 2646 manually labeled ionograms from the Low Latitude Ionospheric Sensor Network (LISN) VIPIR Ionosondes in South America. The data used to train the model was measured from 2019 to 2024. The model was able to classify the testing images into six categories: Clear class, frequency spread-F (FSF), range spread-F (RSF), mixed spread-F (MSF), strong spread-F (SSF), and Unidentified class. It demonstrated high classification accuracy within the extracted test subset and a further random test, showcasing robustness and consistency in detection accuracy across all classes. Furthermore, the model performance has been evaluated and compared with other baseline models: VGG16, VGG19, ResNet18, and Inception-V3 in the same environment. Additionally, a comparison with published models is provided. Our model showed a higher consistency in classification accuracy across all classes compared to the mentioned models.
Informe Técnico Nº PpR/El Niño-IGP/2026-01
(Instituto Geofísico del Perú, 2026-02-24) Instituto Geofísico del Perú
En el corto plazo, la persistencia de ondas Kelvin cálidas frente a la costa peruana podría favorecer un incremento adicional de la TSM, particularmente en marzo, cuando estacionalmente se alcanzan los valores más altos del año. En la región norte, este calentamiento podría favorecer procesos de acoplamiento océano–atmósfera, que podrían incrementar la ATSM y mantener lluvias intensas en la zona norte del Perú, principalmente. Sin embargo, debido a la estacionalidad, dicho acoplamiento no debería extenderse más allá de abril o mayo. A una escala mayor, los modelos de NMME pronostican el desarrollo de un evento El Niño costero y luego, basado en el RONI, un evento El Niño en el Pacífico central a partir de junio. Sin embargo, la presencia de la barrera de predictibilidad limita la confiabilidad de los pronósticos más allá de abril.
Assessing environmental and anthropogenic drivers for the occurrence and extent of fires in high Andean Grasslands
(Taylor & Francis, 2025-12-18) Gutierrez Flores, Ivon; Mercado, Angela; Zubieta Barragán, Ricardo; Beltrán, Pablo; Oyague, Eduardo
The grasslands of the southern Andes are critical ecosystems for the rural population, but they have been significantly affected by fires. While fire ignitions are anthropogenic, their occurrence and spread are shaped by climatic, vegetational, and topographic factors. This study identified the main environmental and human drivers of fire occur rence and extent in high Andean grasslands. We developed generalized linear models with 14 and 22 variables for the fire occurrence and extent model, respectively. Various metrics (e.g. AIC, AUC, pseudo-R²) were applied to validate the best-performing model and assess its performance. Our findings suggest that elevation, maximum temperature, soil adjusted vegetation index, and topographic position index are the primary drivers of fire occurrence. For fire extent, grass cover, elevation, topographic position index, and rock cover were the most influential factors. The models explained 21% and 60% of the variability in fire occurrence and extent, respectively. This study identifies key environmental factors influencing fire occurrence and extent, providing valuable insights for improving fire management strategies, particularly in fire-prone ecosystems such as grasslands. Since the temperature was a contributing factor to fire occurrence, this highlights the importance of prevention and reduction strategies in the context of climate change.
Characterization of the Optical Properties of Biomass-Burning Aerosols in Two High Andean Cities, Huancayo and La Paz, and Their Effect on Radiative Forcing
(MDPI, 2025-10-25) Victoria Barros, César; Estevan Arredondo, René
Atmospheric aerosols are known to alter the Earth’s radiative balance and influence climate. However, accurately quantifying the magnitude of aerosol-induced radiative forcing remains challenging. We characterize optical properties of biomass-burning (BB) and non-biomass-burning (NB) aerosols and quantify BB aerosol radiative forcing at two AERONET (AErosol RObotic NETwork) sites in Huancayo (Peru) and La Paz (Bolivia) during 2015–2021. From AERONET data, we derive aerosol optical depth (AOD), Ångström exponent (AE), single-scattering albedo (SSA), and asymmetry parameter (ASY). We then employ the SBDART model to calculate aerosol radiative forcing (ARF) on monthly and multiannual timescales. BB aerosols peak in September (AOD: 0.230 at Huancayo; 0.235 at La Paz), while NB aerosols reach maxima in September at Huancayo (0.109) and November at La Paz (0.104). AE values exceeding unity for BB aerosols indicate fine-mode dominance. Huancayo exhibited the highest BB ARF in November: +16.4 W m−2 at the top of the atmosphere (TOA), –18.6 W m−2 at the surface (BOA), and +35.1 W m−2 within the atmospheric column (ATM). This was driven by elevated AOD and high scattering efficiency. At La Paz, where SSA data was only available for September, BBARF values were also significant (+15.16 at TOA, –17.52 at BOA, and +32.73 W m−2 within the ATM). This result underscores the importance of quantifying the ARF, particularly over South America where data is scarce.
Simulating Stratiform Precipitation With Embedded Convection in High‐Elevation Valleys Using LES: The Role of Topographic Detail
(John Wiley and Sons, 2025-12-16) Chávez, Steven Paul; Flores Rojas, José Luis; Takahashi, Ken; Silva Vidal, Yamina
Precipitation dynamics in high‐elevation valleys of the central Andes are strongly modulated by complex terrain, which alters local circulation and cloud development. Here, we use the Cloud Model 1 (CM1) in large‐eddy simulation (LES) mode with a two‐moment microphysics scheme to examine the role of topographic detail on the spatial distribution of precipitation in the Mantaro Valley, Peru. Three terrain resolutions (450, 1,050, and 1,650 m) were tested under identical thermodynamic conditions derived from in situ soundings. In all cases, anabatic winds transported moisture upslope, but the fine‐resolution case generated larger amounts of ice, snow, and graupel within vortical structures, yielding rainfall that matched Ka‐band radar reflectivity profiles. In contrast, smoother terrains delayed cloud formation by 30–60 min and reduced ice‐phase particle production, confining precipitation to the eastern slopes. Wind vortex analysis revealed smaller upper level eddies (above 2 km AGL) in the high‐resolution case, promoting enhanced mixing and hydrometeor growth. These results demonstrate that subtle variations in terrain detail critically influence convection and stratiform precipitation processes in Andean valleys, underscoring the need for subkilometer representation of topography in high‐mountain rainfall modeling.