Meteorology, Volume 4, Issue 3 (September 2025) – 9 articles

A parameterization for the planetary boundary layer (PBL) based on the statistical theory of turbulence formulated by Geoffrey Ingram Taylor is derived to be applied in the Brazilian Global Atmospheric Model (BAM). The BAM model is the operational system employed by the National Institute for Space Research (INPE), Brazil, to produce numerical weather and climate predictions. A comparison of the BAM model simulations using Taylor’s parameterization is carried out against other three turbulent representations. The forecasting from different parameterizations with BAM is evaluated with the ERA-5 reanalysis. Predictions were performed on different initial conditions, representing two types of climate seasons: dry and wet seasons, for the Southern Hemisphere. The comparison shows that Taylor’s approach is competitive with other turbulence parameterizations, especially for the dry season. It must be highlighted that the forecasting over the Amazon region—one of the regions on the planet with the most intense rainfall, where Taylor’s approach provided more effective precipitation forecasting, a particularly challenging meteorological variable to predict. Full article

Wind gustiness at airports, which is generally determined using gust factors, is impactful across a range of considerations from piloting to airport planning. Yet advisory materials to help assess their quality and representativeness, particularly for aviators, are limited. To address this, a climatological analysis of both gust factors is conducted using Automated Surface Observing System (ASOS) wind observations. Data for multi-year periods at selected airports in the United States are used to assess their site representativeness and for turbulence attribution purposes. Both gust factors vary by direction in response to local terrain features and nearby obstructions and are generally not well correlated with each other. The meteorological gust factor is shown to be more responsive to local obstructions in proximity to the ASOS systems. Excluding lower gusts leads to a marked improvement in the correlation between the two gust factors. Due to ASOS’s siting limitations, attributing observed gustiness to turbulence from nearby terrain or structures is difficult. The gustiness is often localized and may not represent conditions across the full airport. Excluding lower gusts increases the aviation gust factor’s sensitivity to local obstructions. This suggests that obstructions may play a meaningful role in shaping the higher observed gust factors. The potential exists to provide pilots and other users of this data with site- and direction-specific metadata regarding observed gustiness, thereby improving situational awareness. Full article

This study examines wind speed trends based on seven mandatory pressure levels of the atmosphere for Brazil from 1980 to 2022 using radiosonde and climate reanalysis products. The results show that austral summer (DJF) and winter (JJA) wind speed trends are predominately influenced by upper tropospheric circulations in each reanalysis model. A vertical wind profile shows that the lowest wind speed trend changes occur below 500 hPa, while the largest wind speed trend tendencies develop in the upper troposphere (400–200 hPa). To further quantify this finding, a spatial profile of wind speed change is developed through a three-dimensional model. The model shows that two synoptic features are possibly controlling upper-level air trends across Brazil. During summer, decreased (increased) upper-level wind speeds across southern and northeastern (central-west and southeastern) Brazil are related to changes in temperature and geopotential heights occurring in proximity of the Bolivian high. This anticyclone gradually dissipates and the role of the subtropical jet stream affects upper-level wind trends across the subtropical latitudes of Brazil during winter. Finally, an upper-level wind analysis is also conducted to support the geographical findings shown in the three-dimensional wind trend model. The results provide a foundation for understanding how wind speeds vary not only from a vertical but also from a spatial (horizontal) perspective across Brazil. Full article

Accurate estimations of reference evapotranspiration (ETo) are critical for hydrologic studies, efficient crop irrigation, water resources management and sustainable development. The evaluation of an empirical method was carried out to estimate hourly ETo, utilizing short-wave radiation and relative humidity as a surrogate of vapor pressure deficit (VPD), calibrated under semi-arid conditions and validated for different climatic regimes (hyper-arid, arid, subhumid) using American Society of Civil Engineers Penman–Monteith (ASCE PM) (2005) values as a standard, for the state of California. For hyper-arid climatic conditions, the empirical method resulted in underestimation and had coefficient of determination (R²) values of 0.88–0.95 and root mean square error (RMSE) values of 0.062–0.115 mm h⁻¹. Hyper-arid climatic conditions correspond to lower R² and different relations between the vapor pressure deficit (VPD) and the relative humidity function (1/lnRH) that the empirical method utilizes. For the other climatic regimes (arid, semi-arid, subhumid), the empirical method performed satisfactorily. The RMSE was calculated for groups of empirical estimates corresponding to various wind velocity values, and it was satisfactory for >99% of wind speed values (u₂). The RMSE was also calculated for grouped values of the estimates of the empirical method corresponding to observed VPDs and was satisfactory for >97% of all observed values of VPD, except for hyper-arid stations (59% of u₂ and 60% of all observed values of VPD). Full article

The Offset Elliptical Normal (OEN) mixture model represents the seasonal–diurnal surface wind vector for wind engineering design applications. This study upgrades the parameterization of OEN by accounting for changes in format of the global database of surface observations, improving performance by eliminating manual supervision and extending the scope of the model to include skewness. The previous coordinate transformation of binned speed and direction, used to evaluate the joint probability distributions of the wind vector, is replaced by direct kernel density estimation. The slow process of sequentially adding additional components is replaced by initializing all components together using fuzzy clustering. The supervised process of sequencing each mixture component through time is replaced by a fully automated unsupervised process using pattern matching. Previously reported departures from normal in the tails of the fuzzy-demodulated OEN orthogonal vectors are investigated by directly fitting the bivariate skew generalized t distribution, showing that the small observed skew is likely real but that the observed kurtosis is an artefact of the demodulation process, leading to a new Offset Skew Normal mixture model. The supplied open-source R scripts fully automate parametrization for locations in the NCEI Integrated Surface Hourly global database of wind observations. Full article

In an ensemble prediction system, each member performs differently from each other for individual cases. To adaptively (not only statistically) calibrate or post-process raw ensemble forecasts and produce more reliable and accurate forecast products case by case, it is necessary to understand how individual ensemble members behave inside an ensemble cloud. For example, how (randomly or orderly) does an individual member’s relative performance (including the best and worst members) vary with location and time? To quantify and understand these variations, this study proposes the “Performance Rank Variation Score (PRVS)” to measure the degree of ensemble member’s relative performance variation (the “motion” of members). The PRVS was applied to four real cases (representing the winter, spring, summer, and fall seasons) from the NCEP global ensemble forecast system (GEFS). Many interesting results were observed, which are otherwise hard to elucidate without this new score. At the same time, based on the revealed results, possible ensemble post-processing strategies are discussed for future developments, where a new concept of “transformed ensemble” was demonstrated as an example. Full article

Quantifying long-term variations in the cloud liquid water path (LWP) is crucial to obtain a better understanding of the processes relevant to cloud–climate feedback. The 12-year (2013–2024) time series of LWP values obtained from ground-based measurements by the RPG-HATPRO radiometer near the Gulf of Finland is analysed, and the linear trends of the LWP for different sampling subsets of data are assessed. These subsets include all-hour, daytime, and night-time measurements. Two different approaches have been used for trend assessment, which produced similar results. Statistically significant linear trends have been detected for most data subsets. The most pronounced general trend over the period 2013–2024 has been detected for the daytime LWP, and it constitutes −0.0011 ± 0.00015 kg m⁻² yr⁻¹. This trend is driven mainly by the daytime LWP trend for the warm season (May–July, −0.0014 ± 0.00015 kg m⁻² yr⁻¹), which is considerably larger than the trend for the cold season (November–January, −0.00064 ± 0.00026 kg m⁻² yr⁻¹). Additionally, the analysis shows that the absolute number of clear-sky measurements decreased approximately by a factor of 4 if the years 2013 and 2024 are compared. Full article

The Standardized Precipitation Index (SPI) is widely used to determine drought severity worldwide. However, inconsistencies exist regarding its application in warm, humid tropical climatic zones. Originally developed for temperate regions with a continental climate, the index may not adequately reflect drought conditions in tropical environments where rainfall regimes differ substantially. This study identifies the following two principal reasons why the traditional calculation method fails to characterize drought severity in tropical domains: first, the marked humidity contrast between the consistently humid rainy season and the rest of the year, and second, the diverse drought types in tropical regions, which include both long-term and short-term events. Using data from meteorological stations in Mexico’s humid tropics and comparing them with temperate regions, the study demonstrates significant discrepancies between SPI-based drought classifications and actual precipitation patterns. Our analysis shows that the abundant precipitation during the rainy season causes biases in longer time scales integrated into multivariate drought indices. Considerations are established for adapting the SPI for decision makers who monitor drought in humid tropics, with specific recommendations on time scale limits to avoid biases. This work contributes to more accurate drought monitoring in tropical regions by addressing the unique climatic characteristics of these environments. Full article

The São Francisco River provides water for agriculture, urban areas, and hydroelectric power generation, benefiting millions of people in Brazil. Its Basin supports various species, some of which are endemic and rely on its unique habitats for survival. Currently, monitoring maximum air temperature in the São Francisco River Basin is limited due to sparse weather stations. This study proposes three linear regression models to estimate maximum air temperature using satellite-derived land surface temperature from the Aqua’s moderate resolution imaging spectroradiometer across the Basin’s three main biomes: Caatinga, Cerrado, and Mata Atlântica. With over 94,000 paired observations of ground and satellite data, the models showed good performance, accounting for 46% to 54% of temperature variation. Cross-validation confirmed reliable estimates with errors below 2.7 °C. The findings demonstrate that satellite data can improve air temperature monitoring in areas with limited ground observations and suggest that the proposed biome-specific models could assist in environmental management and water resource planning in the São Francisco River Basin. This includes providing more informed policies for climate adaptation and sustainable development or analyzing variations in maximum air temperature in arid and semi-arid regions to contribute to desertification mitigation strategies in the São Francisco River Basin. Full article