Meteorological Trends Research Articles

Simulating future energy consumption in office buildings using an ensemble of morphed climate data

Designers and policy makers use simulations to characterize building energy performance; depending on localized weather files—typically assembled from historically-measured weather data—to project the building’s behavior and energy use. However, changes in global climate and advances in climate science research reveal significant differences between historical meteorological trends and the patterns of current and future climate. The increasing variability and uncertainty associated with climate change will affect buildings in complex ways that depend on the interaction of buildings’ properties, human behavior, and climatic context. Previous studies developed and tested methods to create future climate files by modifying historical data, typically assuming a single model of global climate and a single emission scenario. The present study takes a more comprehensive approach, using an ensemble of fourteen Global Climate Models and two Representative Concentration Pathways to incorporate the uncertainty of future climate projections into building energy simulations. To understand the effects on buildings over their lifespan, a prototypical large office was tested in three different US cities (Boston, Miami and San Francisco) and three future time windows (2030, 2060 and 2090). Driven by increases in cooling energy, annual primary energy consumption increased by 2090 for all projected climate conditions tested, by up to 10% in the edge-case climate of San Francisco where cooling requirements had hitherto been minor. There was significant variability in results and drivers among the different locations and projections, emphasizing the need for specific modeling to support local design practices.

Statistics on typhoon landfalls in Vietnam: Can recent increases in economic damage be attributed to storm trends?

The Emergency Events Database (EM-DAT) indicates that the economic damage associated with storms has been rapidly growing in Vietnam. By contrast, the fatality rate due to storm-relevant disasters has been declining in recent decades. This study investigates whether typhoon trends have affected these outcomes. Best track data from the Japan Meteorological Agency (JMA) were examined to estimate central pressure and wind speed when typhoons made landfall. From 1977 to 2017, typhoons with wind speeds above 20 knots struck the country 105 times. A statistical analysis, which defined a storm's intensity using principal component analysis (PCA), revealed that Typhoon Doksuri in 2017 was the strongest among the collection, followed by Cecil in 1985, Xangsane in 2006, and Damrey in 2017. The worst storm in history, Typhoon Linda in 1997, claimed over 3500 lives in southern Vietnam, but was only ranked 37th, demonstrating that typhoon intensity is not always the determining factor of fatalities. Moreover, the analysis of variance (ANOVA) illustrates that none of the meteorological trends such as frequency, central pressure, wind speed, or storm intensity show any significant increase or decrease over the last four decades. However, landfall frequency has risen significantly, particularly in the northernmost part of the country where two large cities, Hanoi and Hai Phong, are located. A strong correlation was found between intensity and recent economic damage (r = 0.80) based on the proposed index of positive annual landfall storm intensity (PALSI). Given all of these factors, it is reasonable to attribute the expansion of disaster-related economic damage to economic development and the fundamental volatility of typhoons.

Analysis of fine particle pollution data measured at 29 US diplomatic posts worldwide

Fine particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) is the most commonly measured ambient air pollutant worldwide on account of its adverse health effects. In 2008 the US Embassy in Beijing started monitoring PM2.5 on the embassy premises to provide US citizens in the area with actionable health information related to ambient air pollution. By May 2019 the United States Department of State ambient air quality monitoring network had expanded to 43 cities in 27 countries. This provided a reliable source of near-real-time PM2.5 data to fill data gaps in previously under-served countries.This manuscript describes data analyses of seasonal, diurnal and meteorological trends which can be used for air quality planning and awareness in 29 of the embassies host cities. People living, working, traveling or considering relocating to those areas can gain a better understanding of the air quality they are exposed to. Potential explanations are offered for sites that deviate from expected trends: Addis Ababa experiences high PM2.5 during the rainy season probably due to widespread biomass burning and light winds; Manama has high PM2.5 throughout the day on summer weekends because widespread air conditioner usage causes coal-fired power plants to operate at high capacity to meet the electricity demand; Pristina experienced very high PM2.5 during winter weekend nights, which turned out to be very cold and stagnant periods and likely increased wood and coal combustion for home heating.Although Chinese sites consistently exceed the country's annual PM2.5 standards, analysis of long term trends confirm steady improvements in air quality. These improvements cannot be attributed to favorable meteorological conditions alone and are likely due to reductions of emissions. Since random forest-based machine learning methods explained >90% of the variability in PM2.5 concentrations at 21 locations, they can be used in conjunction with meteorological models for air quality forecasting.

Drought impacts and management in prairie and sandhills state parks

The combination of decreased water availability and increased temperatures can interfere with outdoor activities, particularly with surface water decline and the increased risk of wildfire. Drought is a longer-term climate trend, but there is a tendency toward short-term reactions only when a drought occurs. Policy mechanisms for drought, where present, are often left to managerial discretion because they are not needed every year, and lack specific indicators. Recreator choices contribute to adaptation and public lands managers also shape drought response by monitoring meteorological trends and managing resources wisely. Despite these trends, no singular recreational drought definition exists. To understand socio-environmental interactions from a management perspective, this study synthesizes interview findings to provide in-depth insight about drought monitoring, impacts, and management across a variety of ecological regions in Nebraska state parks. Collectively, the eight participating superintendents oversee more than 152 km2 of land, approximately 287 km2 of surface water, and more than 364 km of lakeshore. The emergent properties of drought in the recreation sector include a shortage of naturally available water needed for vegetation health and animal habitat, to support lake sports, to prevent permanent infrastructure damage, and maintain visitor volumes for economic stability. The study concludes with recommendations for increasing drought resilience within the sector.

Oscillation of meteorological trends and future scenario across southern Nigeria

Oscillation of meteorological trends and future scenario across southern Nigeria

Comparing farmers’ perceptions of climate change with meteorological data in three irrigated cropping zones of Punjab, Pakistan

Farmers’ perception about changing climate leads to farm-adaptive responses. Coherence between perceptions and meteorological trends leads to improved farm decisions. The objective of this study was to examine the degree of agreement between farmers’ perception and actual climate trends in three irrigated districts of Punjab province in Pakistan. The study also inquired the role of extension services and other factors affecting farmers’ perception. Using multistage sampling technique, a sample of 300 farmers was taken who were interviewed using pre-structured and field-tested questionnaire about their perceptions of climate change at farm. Climate data for 33 years regarding temperature and for 34 years for precipitation were obtained from meteorological stations in selected districts. It employed Mann–Kendall and Sen’s slope tests for trend analysis in climate time series and tested nonparametric association in cross-sectional data. The results revealed that farmers’ perception about precipitation trends do not match with actual trends mainly because of the way climate information is processed among farmers and scientific community. However, farmers’ perceptions about increase in temperature were in line with meteorological evidence across selected irrigated cropping zones. Extension services along with income and size of land holding were key factors affecting farmers’ perception about climate change. The study recommends bridging information gaps between scientific community and farmers about climate change.

Fuel economy assessment tool for auxiliary kite propulsion of merchant ship

A tool dedicated to assess fuel economy induced by kite propulsion has been developed. To produce reliable results, computations must be performed on a period over several years, for several routes and for several ships. In order to accurately represent the impact of meteorological trends variations on the exploitability of the kite towing concept, a time domain approach of the problem has been used. This tool is based on the weather database provided by the ECMWF. Two sailing strategies can be selected for assessing the performance of the kite system. For a given kite area, the simulation can be run either at constant speed or at constant engine power. A validation has been made, showing that predicted consumption is close from in-situ measurement. It shows an underestimation of 11.9% of the mean fuel consumption mainly due to auxiliary consumption and added resistance in waves that were not taken into account. To conclude, a case study is performed on a 2200 TEU container ship equipped with an 800m² kite on a transatlantic route between Halifax and Le Havre. Round trip simulations, performed over 5 years of navigation, show that the total economy predicted is of around 12% at a speed of 16 knots and around 6.5% at a speed of 19 knots.

Bibliometric Analysis of Atmospheric Simulation Trends in Meteorology and Atmospheric Science Journals: Update

This study was designed to evaluate the global scientific output of simulation research in meteorology and atmospheric sciences for the past 16 years and to assess the characteristics of the atmospheric simulation research patterns, tendencies and methods in the papers, from leading countries and institutes. Data were based on the online version of Science Citation Index, Web of Science from 1992 to 2007. Articles referring to atmospheric simulation were assessed by exponential regression fitting the trend of publication outputs with r 2 = 0.9996, distribution of source countries, source institutes, source titles, author keywords, and keywords plus, and the four most cited articles in these years. By synthetic analysis of the three kinds of keywords, it was concluded that atmospheric simulation research related to ozone, climate, circulation, transport, parameterization and assimilation will be foci of atmospheric simulation research in the 21 st century.

Projection of Future Precipitation and Temperature Change over the Transboundary Koshi River Basin Using Regional Climate Model PRECIS

The Koshi river basin sustains the livelihoods of millions of people in the upstream and downstream areas of the basin. People rely on monsoon rainfall for agricultural production, hydropower generation and other livelihood activities. Climate change is expected to have serious implication on its environment. To reduce the adverse impacts of disasters and to better understand the implication of climate change for the sustainable development, initiative in this regard is necessary. Analysis of past meteorological trends and future climate projections can give us a sense of what to expect and how to prepare ourselves and manage available resources. In this paper, we have used a high-resolution climate model, viz., Providing REgional Climates for Impacts Studies (PRECIS), to project future climate scenario over the Koshi river basin for impact assessment. Three outputs of the Quantifying Uncertainties in Model Prediction (QUMP) simulations have been used to project the future climate. These simulations were selected from the 17-member Perturbed Physics Ensemble (PPE) using Hadley Centre Couple Model (HadCM3) based on the IPCC SRES A1B emission scenario. The future projections are analysed for three time slices 2011-2040 (near future), 2041-2070 (middle of the century) and 2071-2098 (distant future). Despite quantitative wet and cold bias, the model was able to resolve the seasonal pattern reasonably well. The model projects a decrease in rainfall in the near future and a progressive increase towards the end of the century. The projected change in rainfall is non-uniform, with increase over the southern plains and the middle mountains and decrease over the trans-Himalayan region. Simulation suggests that rainy days will be less frequent but more intense over the southern plains towards the end of the century. Further, the model projections indicate significant warming towards the end of the century. The rate of warming is slightly higher over the trans-Himalayan region during summer and over the southern plains during winter.

Impact of sowing time, hybrid and environmental conditions on the contamination of maize by emerging mycotoxins and fungal metabolites

Mycotoxins and other fungal metabolites represent the most insidious safety risks to cereal food and the feed chain. Optimising agronomic practices is one of the main strategies adopted to minimise the contents of these undesirable substances in grain-based commodities. The aim of this study was to investigate the effect of the combination of sowing times and hybrids on the occurrence of emerging mycotoxins and fungal metabolites in maize. Field experiments were carried out in 2 sowing times (early vs late) and 3 maize hybrids were compared in the 2014 and 2015 growing seasons. Overall, 37 fungal metabolites produced by Fusarium and Alternaria species were detected. Apart from fumonisins type B (FBs), other metabolites produced by Fusarium verticillioides and F. proliferatum, such as fumonisins type A, fusaric acid, bikaverin and fusaproliferin, were also detected in all of the samples. Fusarin C was found in 61% of the samples. Deoxynivalenol (DON), deoxynivalenol-3-glucoside, culmorin and zearalenone, all of which are produced prevalently by Fusarium graminearum and F. culmorum, were found in all the samples. Their contents were clearly affected by the meteorological trend: the highest contamination was detected in the 2014 growing season, which was characterised by abundant rainfall and lower temperatures from flowering to maize ripening. Among the mycotoxins produced by other Fusarium species, aurofusarin was found to clearly be associated with DON, while moniliformin and beauvericin followed the same behaviour as the FBs. A late sowing time significantly increased the FBs and fumonisin- associated mycotoxins in both growing seasons. The increase in contamination with the delay of sowing was more pronounced in the 2015 growing season, as the environmental conditions were less favourable to the infection of other Fusarium species. The effect of sowing time on DON and DON-associated mycotoxins produced conflicting results for the two growing seasons, because contamination by these metabolites depends more on the conditions that occur during maize flowering than those that occur during ripening. A clearer hybrid susceptibility was observed for these compounds. Other metabolites, such as enniatins, equisetin, T-2 and HT-2 toxins and Alternaria toxins, were always found in traces. The occurrence of these metabolites seems to be influenced less by the considered agronomic practices. The results, obtained under naturally-infected field conditions, underline the key role that the sowing date and hybrid susceptibility play in influencing, in a variable way, the contamination of mycotoxins produced by different Fusarium species in maize subjected to different meteorological conditions. The content of mycotoxins produced by Fusarium spp. section Liseola is more directly and steadily related to late sowing time, while the contamination of mycotoxins associated to Fusarium spp. section Discolor depend more strongly on the environmental conditions at maize flowering and on hybrid susceptibility.

Local weather is associated with rates of online searches for musculoskeletal pain symptoms

Weather conditions are commonly believed to influence musculoskeletal pain, however the evidence for this is mixed. This study aimed to examine the relationship between local meteorological conditions and online search trends for terms related to knee pain, hip pain, and arthritis. Five years of relative online search volumes for these terms were obtained for the 50 most populous cities in the contiguous United States, along with corresponding local weather data for temperature, relative humidity, barometric pressure, and precipitation. Methods from the climate econometrics literature were used to assess the casual impact of these meteorological variables on the relative volumes of searches for pain. For temperatures between -5°C and 30°C, search volumes for hip pain increased by 12 index points, and knee pain increased by 18 index points. Precipitation had a negative effect on search volumes for these terms. At temperatures >30°C, search volumes for arthritis related pain decreased by 7 index points. These patterns were not seen for pain searches unrelated to the musculoskeletal system. In summary, selected local weather conditions are significantly associated with online search volumes for specific musculoskeletal pain symptoms. We believe the predominate driver for this to be the relative changes in physical activity levels associated with meteorological conditions.

Perceived and measured climate variability and change in semi-arid environments in Tanzania: experiences from Iramba and Meatu Districts

This paper combines farmers' perceptions of climate variability and change and meteorological data trends to generate empirical evidence to broaden an understanding of the phenomena. The results show an agreement on changing rainfall patterns. Bad years described by drought frequencies, temperature, and dry spell have increased since the 1970s. Crop growing period has decreased by one month in Meatu and by more than a month in Iramba. As hypothesised, the Mann-Whitney U test shows similar men and women's perceptions at 5% level of significance (P value = 0.701). Similarly, the Kruskal-Wallis H test indicates that the poor, not so poor and the rich have the same perceptions (P value = 0.281). These results have implications on crop and livestock production systems and on livelihoods more generally. We conclude that climate variability and change manifestations overlap, making it a complex phenomena perceived equally by men, women, the poor and non-poor. This is understood holistically by combining farmers' perceptions and meteorological data trends to inform adaptation strategies related decision making.

Study and Analysis of Meteorological Effect on Shanghai Sheshan National Tourist Resorts in Shanghai

In this paper, the main meteorological disasters in the Sheshan National Tourist and Vacation Areas are analyzed by using the climate data from 1955 to 2014, such as average temperature, relative humidity, wind speed, insolation duration. The influences of meteorological parameters on this area are studied with the climate comfort evaluation and meteorological disaster climate trend. It is found that the major meteorological disasters in this area including fog, typhoon, storm, wind, thunderstorms and high temperature, were occurred in different periods with higher frequency from May to October. Nineteen comfortable ten-day periods in a year are suitable for tourist activities, during March and May, late September and the end of December. And seventeen ten-day periods in a year are not suitable for tourist activities, from January to February and from June to the middle of September. Some suggestions for tourism weather service on the basis of these results are listed in the conclusion.

Nitrogen efficiency in oats on grain yield with stability

ABSTRACT Nitrogen (N) is the nutrient most absorbed by the oat crop. Unfavorable climate conditions decrease its efficiency, generating instability and reduction in yield. The objective of this study was to improve N use efficiency in oat grain yield by the economic value of the product and of the input and by models that scale the stability, considering systems of succession of high and reduced residual-N release in favorable and unfavorable years for cultivation. The study was conducted in the years 2013, 2014 and 2015 in two systems of succession (soybean/oat, maize/oat) in randomized blocks with eight replicates, using the N-fertilizer doses of 0, 30, 60 and 120 kg ha-1. The N-fertilizer dose for maximum economic efficiency in oats should be considered based on the meteorological trends of the cultivation year. N use optimization by models that determine the stability is an innovative proposal to increase fertilization efficiency on the yield. The N-fertilizer dose of 60 kg ha-1 promotes greater efficiency with predictability and yield, regardless of the agricultural year and the system of succession.

Long-term meteorological trends in the Naiman County of northern China

The annual trends of six meteorological variables (precipitation, evaporation, relative humidity, sunshine hours, and wind-speed and air temperature) were analyzed by wavelet analyses and mutation analyses of Mann-Kendall method based on daily average data observed from Naiman National automatic meteorological station from 1970 to 2014. Results indicated: (1) The ranges of annual mean precipitation, evaporation, relative humidity, daily sunshine hours, wind-speed and air temperature were 213∼567 mm, 1408∼2192 mm, 46%∼58%, 7∼9 h, 2.7∼3.8 m/s and 5.8∼8.6°C, respectively. (2) Air temperature and daily sunshine hours had increased by 0.29°C /10a and 0.11h/10a (P<0.01) respectively over 45 years (1970∼2014); (3) Wavelet analysis indicated that wind-speed had a long cycle (26 years); the cycle for daily sunshine hours was somewhat shorter (18 years); evaporation had no obviously cycle; and the other three variables had both shorter and longer cycles. (4) Mutation analysis determined six meteorological parameters that differed from each other, e.g., evaporation had a mutation from low to high occurred in 2001; relative humidity had a mutation from high to low occurred in 2000; daily sunshine hours had a mutation from low to high occurred in 1993.

Detection of trends in surface ozone in the presence of climate variability

AbstractTrends in trace atmospheric constituents can be driven not also by trends in their (precursor) emissions but also by trends in meteorology. Here we use ground‐level ozone as an example to highlight the extent to which unforced, low‐frequency climate variability can drive multidecadal trends. Using output from six experiments of the Geophysical Fluid Dynamics Laboratory chemistry‐climate model (CM3), we demonstrate that 20 year trends in surface ozone driven by climate variability alone can be as large as those forced by changes in ozone precursor emissions or by anthropogenic climate change. We highlight regions and seasons where surface ozone is strongly influenced by climate variability and thus where a given forced trend may be more difficult to detect. A corollary is that this approach identifies regions and seasons of low variability, where measurement sites may be most effectively deployed to detect a particular trend driven by changing precursor emissions. We find that the representative concentration pathways 4.5 (RCP4.5) and RCP8.5 forced surface ozone trends in most locations emerge over background variability during the first half of the 21st century. Ozone trends are found to respond mostly to changes in emissions of ozone precursors and unforced climate variability, with a comparatively small impact from anthropogenic climate change. Thus, attempts to attribute observed trends to regional emissions changes require consideration of internal climate variability, particularly for short record lengths and small forced trends.

Loss of a lake system in a megacity: The impact of urban expansion on seasonal meteorology in Mexico City

AbstractThe Mexico City Metropolitan Area (MCMA) has undergone significant urban expansion in a closed basin that once supported a large lacustrine system. While urbanization has been mentioned as a factor in observed meteorological trends, a systematic study of the effects of land use‐land cover change (LULCC) on seasonal meteorology is lacking. In this study, we utilize the Weather Research and Forecasting (WRF) system to determine the spatiotemporal changes in near‐surface air temperature, precipitation, and boundary layer conditions induced by the modern‐day urban landscape relative to presettlement conditions. We capture the MCMA extent through an improved Landsat‐based multicategory urban classification and therefore account for intraurban spatial heterogeneity and further conduct additional experiments to examine the sensitivity to anthropogenic heating within WRF. We find that accounting for these factors produced the best simulations of thermal conditions, with RMSE values less than 1.5°C at all measurement stations, and an improved diurnal cycle of air temperature and precipitation. We then assessed the impacts of LULCC in the MCMA, finding that thermal changes were largest during daytime hours, with temperature increasing, on average, by more than 4°C. Furthermore, we utilize these simulations to mechanistically link the built environment‐induced increase in air temperature to simulated increases in rainfall during the evening hours. To our knowledge, this study provides the first dynamical and thermodynamical evidence to support the rainfall enhancements documented through observations in the MCMA and link it quantitatively to the warming effects associated with urbanization. These results have important implications for understanding the meteorological conditions leading to widespread urban flooding in the MCMA.

Pastoralist Perceptions on Climate Change and Variability in Kajiado in Relation to Meteorology Evidence

This study provides an overview of changing climatic conditions in Kajiado County based on analysis of climatic data and perception of pastoralist on key climatic variables. It collates the two sources of knowledge on climate change, indicating the consistency and inconsistency between the two. Rainfall and temperature data of the study area for a period of 43 years (1970-2013) was collected from Kenya Meteorological Service, organized and analyzed using Microsoft excel. The perception of Maasai pastoralist to climate change was determined using questionnaires, focus group discussions and key informant interview. Result shows that rainfall trend in Kajiado County have a high variability level (CV %) of 27.5% for Kajiado North, 21.5% for Kajiado West, 26.4% for Kajiado East and 25.2% for Kajiado Central. Although, there is no significant change for rainfall over the study period, result on perception revealed that 83% of respondent perceive that rainfall amount is reducing in the last 30years. However, perception of pastoralist about years of extreme drought corroborates the meteorological trend of years with very low rainfall. A rise in minimum temperature (1.410C), maximum temperature (0.470C) and average temperature (0.940C) occurred between 1970 and 2013. This agrees with the perception of 81% of Maasai pastoralist, which perceived that temperature has been increasing in the last 30 years. Overall, the results of this study are in line with recent trend of global warming in the region as reported by the latest Intergovernmental panel on Climate Change (IPCC 2014) report. DOI: 10.5901/ajis.2016.v5n1p37

Multiyear applications of WRF/Chem over continental U.S.: Model evaluation, variation trend, and impacts of boundary conditions

AbstractMultiyear applications of an online‐coupled meteorology‐chemistry model allow an assessment of the variation trends in simulated meteorology, air quality, and their interactions to changes in emissions and meteorology, as well as the impacts of initial and boundary conditions (ICONs/BCONs) on simulated aerosol‐cloud‐radiation interactions over a period of time. In this work, the Weather Research and Forecasting model with Chemistry version 3.4.1 (WRF/Chem v. 3.4.1) with the 2005 Carbon Bond mechanism coupled with the Volatility Basis Set module for secondary organic aerosol formation (WRF/Chem‐CB05‐VBS) is applied for multiple years (2001, 2006, and 2010) over continental U.S. This work also examines the changes in simulated air quality and meteorology due to changes in emissions and meteorology and the model's capability in reproducing the observed variation trends in species concentrations from 2001 to 2010. In addition, the impacts of the chemical ICONs/BCONs on model predictions are analyzed. ICONs/BCONs are downscaled from two global models, the modified Community Earth System Model/Community Atmosphere model version 5.1 (CESM/CAM v5.1) and the Monitoring Atmospheric Composition and Climate model (MACC). The evaluation of WRF/Chem‐CB05‐VBS simulations with the CESM ICONs/BCONs for 2001, 2006, and 2010 shows that temperature at 2 m (T2) is underpredicted for all three years likely due to inaccuracies in soil moisture and soil temperature, resulting in biases in surface relative humidity, wind speed, and precipitation. With the exception of cloud fraction, other aerosol‐cloud variables including aerosol optical depth, cloud droplet number concentration, and cloud optical thickness are underpredicted for all three years, resulting in overpredictions of radiation variables. The model performs well for O3 and particulate matter with diameter less than or equal to 2.5 (PM2.5) for all three years comparable to other studies from literature. The model is able to reproduce observed annual average trends in O3 and PM2.5 concentrations from 2001 to 2006 and from 2006 to 2010 but is less skillful in simulating their observed seasonal trends. The 2006 and 2010 results using CESM and MACC ICONs/BCONs are compared to analyze the impact of ICONs/BCONs on model performance and their feedbacks to aerosol, clouds, and radiation. Comparing to the simulations with MACC ICONs/BCONs, the simulations with the CESM ICONs/BCONs improve the performance of O3 mixing ratios (e.g., the normalized mean bias for maximum 8 h O3 is reduced from −17% to −1% in 2010), PM2.5 in 2010, and sulfate in 2006 (despite a slightly larger normalized mean bias for PM2.5 in 2006). The impacts of different ICONs/BCONs on simulated aerosol‐cloud‐radiation variables are not negligible, with larger impacts in 2006 compared to 2010.

Mycotoxin occurrence in maize produced in Northern Italy over the years 2009–2011: focus on the role of crop related factors

The occurrence of mycotoxins associated with Fusarium spp. and Aspergillus flavus in Northern Italy, and the role of cropping systems, were investigated on 140 field samples collected over the years 2009–2011. Samples were analysed for fumonisins B 1 and B 2 (FBs), aflatoxins B 1 , B 2 , G 1 and G 2 (AFs), deoxynivalenol (DON) and zearalenone (ZEN) using validated analytical methods. Information on: maize hybrid, preceding crop, tillage applied, mineral nutrition, pest and disease control, severity of European Corn Borer (ECB) attack, sowing and harvesting dates, kernel moisture at harvesting and longitude of the sampled province, were also collected. During this period there were distinct differences in FBs and AFs concentrations between years and geographic origins, and very low contamination with DON and ZEN was always found. The incidence of AFs exceeded 75% across all samples, and was almost 100% for FBs. The meteorological trends were quite different in the 3 years surveyed. 2009 was the coldest in June and the warmest in August, 2010 the most humid, and in 2011 cold weather occurred during flowering and dry conditions during ripening. The run of a logistic equation with the backward stepwise approach selected three parameters, (seeding week, ECB severity and longitude of sampling province) to predict AFB 1 contamination and four parameters (year, sowing week, ECB severity and longitude of sampling province) to predict FB contamination. The internal validation gave good results, with 76% correct predictions. The probability of harvesting maize with more than 5 µg kg -1 of AFB 1 varied between 86 and 5%, and the probability of harvesting maize with more than 4,000 µg kg -1 of FBs varied between 81 and 2%, respectively, for conducive and non-conducive environments. Therefore, considerable variability was found even if a limited area and only 3 years were considered.