Geo-Hydrological Events and Temporal Trends in CAPE and TCWV over the Main Cities Facing the Mediterranean Sea in the Period 1979–2018

The Mediterranean region is regarded as the meeting point between Europe, Africa and the Middle East. Due to favourable climatic conditions, many civilizations have flourished here. Approximately, about half a billion people live in the Mediterranean region, which provides a key passage for trading between Europe and Asia. Belonging to the middle latitude zone, this region experiences high meteorological variability that is mostly induced by contrasting hot and cold air masses that generally come from the west. Due to such phenomenon, this region is subject to frequent intensive precipitation events. Besides, in this complex physiographic and orographic region, human activities have contributed to enhance the geo-hydrologic risk. Further, in terms of climate change, the Mediterranean is a hot spot, probably exposing it to future damaging events. In this framework, this research focuses on the analysis of precipitation related events recorded in the EM–DAT disasters database for the period 1979–2018. An increasing trend emerges in both event records and related deaths. Then a possible linkage with two meteorological variables was investigated. Significant trends were studied for CAPE (Convective Available Potential Energy) and TCWV (Total Column Water Vapor) data, as monthly means in 100 km2 cells for 18 major cities facing the Mediterranean Sea. The Mann–Kendall trend test, Sen’s slope estimation and the Hurst exponent estimation for the investigation of persistency in time series were applied. The research provides new evidence and quantification for the increasing trend of climate related disasters at the Mediterranean scale: recorded events in 1999–2018 are about four times the ones in 1979–1998. Besides, it relates this rise with the trend of two meteorological variables associated with high intensity precipitation events, which shows a statistically significative increasing trend in many of the analysed cities facing the Mediterranean Sea.

Epidemiological models based on meteorological variables to forewarn Alternaria blight of rapeseed-mustard

Alternaria blight [Alternaria brassicae (Berk.) Sacc.] is one of the most widespread and harmful maladies of rapeseed-mustard, causing yield loss up to 47 per cent. Meteorological parameters especially temperature, relative humidity and bright sunshine hours play major role in the development of Alternaria blight disease. Infection by the pathogen is highly influenced by meteorological conditions. A well-tested model based on meteorological variables is an efficient tool for forewarning this disease. Epidemiology of Alternaria blight of brassicas was investigated based on long term data during 2003-2018 crop seasons on the disease severity and meteorological variables, which was validated with data for two subsequent years. During this study, meteorological variable-based regression model of forewarning was developed for maximum severity (%) of Alternaria blight on leaves and pods for three locations viz., New Delhi, Hisar (Haryana) and Mohanpur (West Bengal)] in India. Validation of the forewarning models for maximum severity (%) of Alternaria blight proved the efficiency of the targeted forecasts.

Assessment of Meteorological Variables and Air Pollution Affecting COVID-19 Cases in Urban Agglomerations: Evidence from China

The 2019 novel coronavirus disease (COVID-19) has become a severe public health and social problem worldwide. A limitation of the existing literature is that multiple environmental variables have not been frequently elaborated, which is why the overall effect of the environment on COVID-19 has not been conclusive. In this study, we used generalized additive model (GAM) to detect the relationship between meteorological and air pollution variables and COVID-19 in four urban agglomerations in China and made comparisons among the urban agglomerations. The four urban agglomerations are Beijing-Tianjin-Hebei (BTH), middle reaches of the Yangtze River (MYR), Yangtze River Delta (YRD), and the Pearl River Delta (PRD). The daily rates of average precipitation, temperature, relative humidity, sunshine duration, and atmospheric pressure were selected as meteorological variables. The PM2.5, PM10, sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) contents were selected as air pollution variables. The results indicated that meteorological and air pollution variables tended to be significantly correlated. Moreover, the nature of the relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and meteorological and air pollution variables (i.e., linear or nonlinear) varied with urban agglomerations. Among the variance explained by GAMs, BTH had the highest value (75.4%), while MYR had the lowest value (35.2%). The values of the YRD and PRD were between the above two, namely 45.6% and 62.2%, respectively. The findings showed that the association between SARS-CoV-2 and meteorological and air pollution variables varied in regions, making it difficult to obtain a relationship that is applicable to every region. Moreover, this study enriches our understanding of SARS-CoV-2. It is required to create awareness within the government that anti-COVID-19 measures should be adapted to the local meteorological and air pollution conditions.

EFFECTS OF METEOROLOGICAL VARIABLES ON Pinus caribaea GROWTH IN DIFFERENT AGES AT THE AMAZON REGION.

This study compares the impact of five meteorological variables on the diametric growth of Pinus caribaea var. hondurensis Barrett & Golfari in Vilhena, Rondônia. One thousand nine hundred sixty-eight trees were evaluated and classified at different ages: 600 trees were one year old; 600 trees were two years old; 768 trees were 13 years. The diameter measurement at the soil level (SL) was conducted in young stands between one and two years old. In the stand with 13 years old, the diameter was measured at 1.3 m (DCH). Using a Pressler borer, 50 increment cores were removed at DCH to measure the tree rings in LINTAB™ 6. The diametric growth was evaluated through the Periodic Increment (PI) for young stands and Current Annual Increment (CAI) for adult stands. The following variables were considered: average temperature (°C), precipitation (mm), solar radiation (Kj m-²), real evapotranspiration (mm), and maximum relative humidity (%). The Pearson Correlation Coefficient (r) proposed by Callegari-Jacques and the coefficient of variation (CV%) were used to establish the relationship between growth and meteorological variables. For young stands, the variables with higher positive correlation were real evapotranspiration and maximum relative humidity. However, the variable with a higher positive correlation in adult stands was average temperature, demonstrating a strong correlation until the sixth year of the species.

Epidemiological study of Colletotrichum spp. associated with Enterolobium cyclocarpum (Jacq.) Griseb. and Platymiscium pinnatum (Jacq.) Dugand in the Colombian Caribbean Region

Epidemiological analyzes of foliar diseases associated with Colletotrichum spp. in Enterolobium cyclocarpum and Platymiscium pinnatum were performed under field conditions and without any type of intervention. At the Universidad del Magdalena (Santa Marta, Colombia), four trees for each species and four equidistant monitoring sites per tree were established. The incidence and severity were recorded for 33 weeks (March to November 2016), including two follow-up periods: dry and rainy season. Disease development curves were elaborated. Moreover, the development rate (r) and the area under the disease progress curve (AUDPC) were calculated for each follow-up period. The effect of the meteorological variables was statistically analyzed by correlation and multiple regression. In E. cyclocarpum, the highest incidence and severity were recorded between September and November with 100 and 19.6%, respectively, showing a positive correlation with relative humidity and negative with average temperature, solar radiation and wind speed. In P. pinnatum, the maximum values of incidence and severity were observed between March and April with 68.9 and 1.3%, respectively. However, correlation analyzes did not support their relationship with the environmental factors. The r values during the dry months were 0.136 and 0.107 units week-1 and the AUDPCs were calculated at 51 and 4 units week-1 for E. cyclocarpum and P. pinnatum, respectively. In the rainy months, the r values were 0.187 and 0.016 units week-1 and the AUDPCs were 186 and 2 units week-1, respectively. In conclusion, the development of the disease varies according to the forest species, time of year and some meteorological variables.

Indications of a Decrease in the Depth of Deep Convective Cores with Increasing Aerosol Concentration During the CACTI Campaign

An aerosol indirect effect on deep convective cores (DCCs), by which increasing aerosol concentration increases cloud-top height via enhanced latent heating and updraft velocity, has been proposed in many studies. However, the magnitude of this effect remains uncertain due to aerosol measurement limitations, modulation of the effect by meteorological conditions, and difficulties untangling meteorological and aerosol effects on DCCs. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in 2018-19 produced concentrated aerosol and cloud observations in a location with frequent DCCs, providing an opportunity to examine the proposed aerosol indirect effect on DCC depth in a rigorous and robust manner. For periods throughout the campaign with well mixed boundary layers, we analyze relationships that exist between aerosol variables (condensation nuclei concentration >10 nm, 0.4% cloud condensation nuclei concentration, 55-1000 nm aerosol concentration, and aerosol optical depth) and meteorological variables [level of neutral buoyancy (LNB), convective available potential energy, mid-level relative humidity, and deep layer vertical wind shear] with the maximum radar echo top height and cloud-top temperature (CTT) of DCCs. Meteorological variables such as LNB and deep-layer shear are strongly correlated with DCC depth. LNB is also highly correlated with three of the aerosol variables. After accounting for meteorological correlations, increasing values of the aerosol variables (with the exception of one formulation of AOD) are generally correlated at a statistically significant level with a warmer CTT of DCCs. Therefore, for the study region and period considered, increasing aerosol concentration is mostly associated with a decrease in DCC depth.

Evaluation of the Influence between Local Meteorology and Air Quality in Beijing Using Generalized Additive Models

Previous studies have confirmed the inextricable connection between meteorological factors and air pollutants. This study presents the complex nonlinear relationship between meteorological variables and four major air pollutants under high-concentration air pollution in Beijing. The generalized additive model combined with marginal effects is used for quantitative analysis. After controlling the confounding factors such as long-term trends, seasonality and spatio-temporal deviation, the final fitting results exhibit that temperature, relative humidity and visibility are the most significant meteorological variables associating with PM2.5 concentration, and the marginal effect reaches 80%, −23% and 270%, respectively. Temperature and relative humidity are the most significant variables for SO2, and the marginal effect reaches 15% and 7%. The most significant variables for O3 are temperature and solar radiation, with marginal effect of up to 70% and 8%. Atmospheric pressure and temperature results in a positive effect on CO, and the marginal effect can reach 18% and 80%. All these indicate that local meteorological variables are a significant driving factor for air quality in Beijing. Other variables, such as wind speed, visibility, and precipitation, display some influence on air pollutants, but have less explanatory power in the model. Overall, our study provides a better understanding of the relationship between local meteorological variables and air quality, as well as an insight into how climate change affects air quality.

Strong regulation of daily variations in nighttime surface urban heat islands by meteorological variables across global cities

Knowledge of the day-to-day dynamics of surface urban heat island (SUHI) as well as their underlying determinants is crucial to a better design of effective heat mitigation. However, there remains a lack of a globally comprehensive investigation of the responsiveness of SUHI variations to meteorological variables. Based on the MODIS LSTs and auxiliary data in 2017, here we investigated 10,000+ cities worldwide to reveal day-to-day SUHI intensity (SUHII) variations (termed as SUHIIdv) in response to meteorological variables using Google Earth Engine. We found that: (1) meteorological variables related to the thermal admittance, e.g., precipitation, specific humidity and soil moisture (represented by daily temperature range in rural area, DTRr), reveal a larger regulation on SUHIIdv than those related to the air conditions (e.g., wind speed and near-surface air temperature) over a global scale. (2) Meteorological regulations on SUHIIdv can differ greatly by background climates. The control of specific humidity on SUHIIdv is significantly strengthened in arid zones, while that of wind speed is weakened prominently in equatorial zones. SUHIIdv is more sensitive to soil moisture in cities with higher background temperatures. (3) All meteorological variables, except that related to soil moisture (DTRr), show larger impact on SUHIIdv with antecedent precipitation over the global scale. Precipitation is observed to mitigate the SUHIIdv globally, and such effects are even more pronounced in equatorial and arid zones. We consider that our findings should be helpful in enriching the knowledge of SUHI dynamics on multiple timescales.