Trends In Meteorological Variables Research Articles

Performance Evaluation of High-resolution Reanalysis Datasets Over North-central British Columbia

abstract Version 2.1 of Environment and Climate Change Canada’s Canadian Surface Reanalysis (CaSR), based on the Regional Deterministic Reforecast System (RDRS), was implemented in 2022 to provide temporally complete meteorological data over 1980–2018 covering Canada at 10 km spatial resolution. Similarly, the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Land (ERA5-Land) dataset at ∼9 km spatial resolution became available. To assess their performance in complex topography, this paper undertakes spatiotemporal inter-comparisons between the RDRS and ERA5-Land reanalysis products with station-based data across British Columbia’s Skeena and Nechako watersheds for 1980–2018. Results reveal persistent cold biases, ranging from −6.2°C to −1.6°C basin-wide, in reanalysis mean annual air temperatures relative to observations, but biases vary in both space and time. Conversely, reanalysis total annual precipitation shows wet biases, ranging from 25% to 59% basin-wide. Analyses generally show wetting trends for observations and ERA5-Land while RDRS exhibits drying trends. Reanalysis datasets achieve better agreement overall with observations over the Nechako Watershed, likely due to its denser network of meteorological stations and less complex terrain than the Skeena Watershed. Despite some deficiencies, the RDRS and ERA5-Land reanalyses remain particularly useful products to assess regional climate variability and climatic change given their generally skilful representation of spatial patterns and temporal trends in meteorological variables across the Nechako and Skeena watersheds.

Seed rain composition responds to climate change in a subtropical forest

Recent climate change has been shown to alter aspects of forest plant demography, such as growth and mortality, but less attention has been focused on how climate change alters the reproduction of plant populations through time. We hypothesized that the plant seed production would respond to climate change, and that the response would differ according to plant life form and functional traits. We tested this hypothesis by examining climate change from 2005 to 2020 and by determining the temporal trends of seed rain and seed production from plants with different life forms (e.g., herbs, vines, trees, palms) and of tree species with different statures as well as leaf, seed and wood traits during 2014-2020. We also tested the correlation between meteorological variables and time series of seed rain using cross correlation analysis. We found increasing wetness (lower vapor pressure deficit) through time but with decreasing minimum relative humidity, which is a pattern consistent with trends seen in many other parts of the world. During the study period, seed production of shrubs and relative contribution of woody vines to total seed rain decreased, while relative contribution of palms to total seed rain and tree species with more conservative leaf traits increased their contribution to total seed rain. Overall, these trends were well explained by the trends of meteorological variables and the responses of these life forms to climate change in previous studies. Additionally, the increasingly conservative leaf traits were also consistent with shifts in traits following recovery from disturbance. Our results suggest that a trait-based approach may help to unveil trends that are not readily apparent by examining seed counts alone. The compositional change found in the seed rain may indicate future shifts in forest species composition and should be incorporated into future studies of forest modelling and projections under climate change.

The impact of weather changes on air quality and health in Brazil

Background and Aim: Weather changes affect air quality that is also a leading contributor to disease burden. The current evidence on the relationship between weather changes and air pollution is mainly based on the environmental processes occurring in North America and Europe. As a response to this gap in knowledge, in this study, we quantified the past weather-related changes in ambient air pollution in Brazil over 16 years (2003-2018). Then we estimated the excess mortalities associated with this impact of long-term weather changes on air quality. Methods: We applied generalized additive models (GAMs) to fit adjusted (with meteorological variables) and unadjusted models. The difference of slopes estimated by the models without and with adjusting for these meteorological variables represents the impact of weather changes on pollutant trends, defined in our study as "weather penalty”. Results: Overall, ambient air pollution levels in Brazil during the period 2003-2018 have decreased in most of the Brazilian regions. We estimated significant trends in meteorological variables, indicating an increase in temperature, relative humidity, and wind speed in all Brazilian regions over the 16-study period. Our findings suggest that PM2.5 was the pollutant most impacted by weather changes. For the 16-year period of analysis, we estimated a weather penalty ranging from 1.58 μg/m−3 (CI 95%:1.25;1.91) to 0.41 μg/m−3 (CI 95%:0.28;0.53) among the different Brazilian regions. If weather parameters had remained constant, PM2.5 would have decreased by 1.10 µg/m3 (95%CI: 0.74; 1.46) in the South and by 2.25 µg/m3 (95%CI: 2.72; 1.79) in the Midwest. Over the 16-year study period, the weather impact on PM2.5 in Brazil was associated with over 6,500 excess deaths. Conclusions: The evidence of historical weather penalty should be of interest to policy makers to devise future strategies related to environmental health and climate change. Keywords: Air pollution, Climate Change, Long-term impact

The impact of long-term weather changes on air quality in Brazil

In this study, we estimate the weather-related increases in ambient air pollution (CO, NO2, SO2, O3 and PM2.5) in Brazil between 2003 and 2018. The impact of long-term weather changes on each air pollutant was defined as “weather penalty”. Overall, ambient air pollution levels in Brazil during the period 2003–2018 have decreased in most of the Brazilian regions. We estimated significant trends in meteorological variables, indicating an increase in temperature, relative humidity, and wind speed in all Brazilian regions over the 16-study period. Our findings suggest that PM2.5 was the pollutant most impacted by weather changes. For the 16-year period of analysis, we estimated a weather penalty ranging from 1.58 μg/m−3 (CI 95%:1.25; 1.91) to 0.41 μg/m−3 (CI 95%:0.28; 0.53) among the different Brazilian regions. If weather parameters had remained constant, PM2.5 would have decreased by 1.10 μg/m3 (95%CI: 0.74; 1.46) in the South and by 2.25 μg/m3 (95%CI: 2.72; 1.79) in the Midwest. Over the 16-year study period, the weather impact on PM2.5 in Brazil was associated with over 6500 excess deaths.

Impacts and variability on the urban climate of Recife – Pernambuco, Brazil

The objective of this work was to identify monthly and annual oscillations and trends in meteorological variables: maximum and minimum air temperatures, precipitation, and relative humidity, number of rainy days, total sunshine, wind intensity and cloud cover. We used the theoretical probability distribution: Weibull, Log-normal and Logistics to adjust the values ​​of the variables mentioned above. The Kolmogorov-Smirnov test was used to verify the adjustment of the theoretical functions. The study of the spatial temporal behavior of rainfall and monthly, maximum and minimum temperatures, relative humidity, insolation, cloud cover and wind used was acquired from the National Institute of Meteorology, the data period comprising the series from 1962 to 2015. For The determination of the theoretical distributions of probability adjusted to the annual extremes of precipitation, maximum and minimum temperature of the air, total isolation and relative humidity, cloud cover and wind intensity, were used the maximum likelihood methods to estimate the parameters of the distributions. The Kolmogorov-Smirnov test was used to compare the fit and select the best theoretical distributions. The adjustments were also evaluated in graphs. Deforestation of native vegetation for the construction of districts, favelas and buildings above six floors, as well as high burnings, has contributed to the high rates of desertification, silting up rivers, streams, streams, wells, ponds, ponds and lagoons. Water table, causing extreme fluctuations in the contribution of meteorological elements and well-being in urban centers. The Weibull and Logistics distributions were the best fit for precipitation, insolation, relative humidity, minimum temperature and cloud coverage.

Temporal variability in extremes of daily precipitation, daily maximum and minimum temperature in Shaanxi, China

Trends in meteorological variables have become clear. However, temporal variations and climate oscillations are less clear, especially for extreme events. This study investigates temporal variations in extreme daily precipitation, extreme daily maximum and minimum temperature (Tmax and Tmin) during the last decades in Shaanxi Province, China, by a quantile perturbation method with a nonparametric bootstrap method testing significance. Six extreme variables, including precipitation (R95p and R99p), maximum temperature (TX95 and TX99), and minimum temperature extremes (TN5 and TN1), based on percentiles are examined. The results show extreme heavy-precipitation is prevailing during the 1950s, the 1980s, and the last decade. A systematic oscillation can be observed in the south. A cluster of high extremes of precipitation occurred with periods of 25–35 years. High extreme Tmax cluster every 30 years or so, and show a negative relationship with high extremes of precipitation. The fluctuations of extreme Tmin are inconsistent in time and space. Five climate indices are examined to investigate correlation between large-scale ocean-atmosphere conditions and the extreme meteorological variables. The results show ocean-atmosphere condition of the Pacific Ocean is the most effective driver of extreme heavy-precipitation and high temperature, and ocean-atmosphere conditions of the Arctic and the Indian Ocean have an impact on extreme low temperature.

Nitrous oxide fluxes over establishing biofuel crops: Characterization of temporal variability using the cross‐wavelet analysis

AbstractEmissions of nitrous oxide (N2O) over croplands are a major source of greenhouse gases to the atmosphere. The precise accounting of sources of N2O is essential to national and global budgets, as well as the understanding of the spatial and temporal relationships with environmental variables such as rainfall, air and soil temperature, and soil moisture. The objective of this work was to investigate the temporal correlations of N2O fluxes with soil and air temperatures, as well as soil moisture. N2O fluxes were measured over four biofuel crops in Central Illinois during their establishment phase. Measurements were carried out from 2009 to 2011 using a trace gas analyzer (TGA) with tunable laser technology. Measurements of concentrations of N2O and CO2 were taken at the center of four plots of maize/soybean rotation, miscanthus (Miscanthus × giganteus), switchgrass (Panicum virgatum) and a mixture of native prairie plants. Cumulative fluxes indicate an average emission of nitrogen via N2O fluxes on the order of 1.5 kg N ha−1 year−1, in agreement with chamber measurements previously reported for the site. N2O fluxes were associated with peaks in soil and air temperature, and soil moisture, particularly during spring and winter thaws. Cross‐wavelet analysis was used to investigate the correlation between N2O fluxes and those variables. Results indicate that N2O fluxes and meteorological variables have significant covariance in time scales ranging from 4 to 32 days. In addition, temporal delays of 1–8 days were found in those relationships. Cross‐wavelet patterns were similar when relating N2O fluxes with soil temperature, air temperature and soil moisture. The temporal patterns of fluxes and environmental variables reported here support the modeling of emissions and highlight the importance of considering the timing of fluxes in relation to trends in meteorological variables.

Environmental and Anthropogenic Degradation of Vegetation in the Sahel from 1982 to 2006

There is a great deal of debate on the extent, causes, and even the reality of land degradation in the Sahel. Investigations carried out before approximately 2000 using remote sensing data suggest widespread reductions in biological productivity, while studies extending beyond 2000 consistently reveal a net increase in vegetation production, strongly related to the recovery of rainfall following the extreme droughts of the 1970s and 1980s, and thus challenging the notion of widespread, long-term, subcontinental-scale degradation. Yet, the spatial variations in the rates of vegetation recovery are not fully explained by rainfall trends. It is hypothesized that, in addition to rainfall, other meteorological variables and human land use have contributed to vegetation dynamics. Throughout most of the Sahel, the interannual variability in growing season ΣNDVIgs (measured from satellites, used as a proxy of vegetation productivity) was strongly related to rainfall, humidity, and temperature (mean r2 = 0.67), but with rainfall alone was weaker (mean r2 = 0.41). The mean and upper 95th quantile (UQ) rates of change in ΣNDVIgs in response to climate were used to predict potential ΣNDVIgs—that is, the ΣNDVIgs expected in response to climate variability alone, excluding any anthropogenic effects. The differences between predicted and observed ΣNDVIgs were regressed against time to detect any long-term (positive or negative) trends in vegetation productivity. Over most of the Sahel, the trends did not significantly depart from what is expected from the trends in meteorological variables. However, substantial and spatially contiguous areas (~8% of the total area of the Sahel) were characterized by negative, and, in some areas, positive trends. To explore whether the negative trends were human-induced, they were compared with the available data of population density, land use, and land biophysical properties that are known to affect the susceptibility of land to degradation. The spatial variations in the trends of the residuals were partly related to soils and tree cover, but also to several anthropogenic pressures.

Diurnal and seasonal changes in near‐surface humidity in a complex orography

AbstractChanges in near‐surface humidity are evaluated in relation to changes in other meteorological variables such as air temperature, precipitation, and sunshine duration for a 31 year period (1981–2011) using hourly time series recorded in Switzerland. Trends in meteorological variables are analyzed at the seasonal and subdaily scale, and changes in water vapor are tested for Clausius‐Clapeyron scaling. Results show a marked seasonality of climatic changes with a trend toward warmer, clearer, and drier near‐surface atmosphere strengthening from January to June. During this period considerable negative trends in relative humidity are detected. An abrupt shift in climatic trends occurs during the month of July, after which warming trends are considerably smaller and relative humidity remains constant or increases. An evaluation of reanalysis products demonstrates strong consistency with station observations and when combined with teleconnection indices supports the hypothesis that shifts in the general circulation patterns rather than local feedbacks are the principal drivers of observed seasonality of climate change. However, local feedbacks can play a role in enhancing summer humidity and convective activity (lightning and evening precipitation). Subdaily changes are significant with more pronounced daytime trends of temperature and humidity during spring and the opposite during summer. The strong seasonality and diurnal variability of changes in near‐surface meteorology over the last three decades in Switzerland warns against climate change impact assessments at local scale that consider uniform changes in air temperature and assume Clausius‐Clapeyron scaling for near‐surface humidity.

Trends of surface ozone concentrations in germany and their connections with changes in meteorological variables

Changes in daily mean and daily maximum surface ozone concentrations, temperature, and relative humidity are evaluated based on the data of long-term observations (from 11 to 16 years) carried out at eight German stations. For all stations the trends of daily mean surface ozone concentration are statistically significant and positive. The trend values are different and generally range from 0 to 10% per 10 years. The trends of the maximum daily concentration are, on average, approximately 1.5 times less. Noticeable part of trends of the surface ozone concentration is connected with the trends of meteorological variables: temperature, relative humidity, and air mass transport direction. After the account of the influence of the trends of meteorological variables, the trends of the surface ozone concentration at most stations substantially decrease. The highest trend values of daily mean and daily maximum surface ozone concentrations are observed in a cold season; in a warm season, the trend values are much lower, at some stations they are statistically insignificant. A conclusion is made that for a correct revealing of reasons of long-term changes in the surface ozone concentration one should take into account changes in meteorological factors influencing its formation.

Climatic influences on streamflow timing in the headwaters of the Mackenzie River Basin

The Mann–Kendall non-parametric test for trend is used to explore the trend behaviour of nine measures of the timing of runoff. The relationship between trends in timing measures and trends in meteorological variables are investigated using partial correlation analysis. The relationships between six climate indices and trends in the timing measures are also examined. The analysis is conducted for 26 streamflow gauging stations from three sub-watersheds of the Mackenzie River Basin in northern Canada. The results reveal that for several of the timing measures, many more trends are identified than can be expected to occur by chance. The spring freshet is observed to be occurring earlier with this timing shift appearing particularly strong in headwater catchments. Based on the partial correlation analysis, it is plausible to attribute some of the observed trends to trends in meteorological variables. Timing of runoff is affected by the Pacific Decadal Oscillation (PDO), the North Atlantic Oscillation (NAO), the North Pacific (NP) index and the Atlantic Multidecadal Oscillation (AMO) but not by the El Niño-Southern Oscillation (ENSO) or the Arctic Oscillation (AO).

Hydrological trends and variability in the Liard River basin / Tendances hydrologiques et variabilité dans le basin de la rivière Liard

A study of the trends and variability of hydrological variables was conducted for natural streamflow gauging stations within the Liard River basin in northern Canada. Trends were investigated using the Mann-Kendall test, with an approach that corrects for serial correlation. The field significance of the results was evaluated using a bootstrap resampling approach. The relationships between trends in hydrological variables and both meteorological variables and a large-scale oceanic and atmospheric process were investigated using correlation analysis. The results reveal more trends in some hydrological variables than are expected to occur by chance. The observed trends are related to both trends in meteorological variables and a large-scale oceanic and atmospheric process.

A Comparison of Trends in Hydrological Variables for Two Watersheds in the Mackenzie River Basin

A study of trends and variability of hydrological variables was conducted for natural streamflow gauging stations within two watersheds that are important sources of flow within the Mackenzie River Basin. A comparison was made between trend results for the Liard River Basin and for the Athabasca River Basin. These basins represent a north-south transect of high elevation headwater basins within the Mackenzie River system and are significant since they produce 34% of the annual flow, while occupying only 24% of the total drainage area. Trend analysis was conducted using the Mann-Kendall test with an approach that corrects for serial correlation. The global (or field) significance of the results for each watershed was evaluated using a bootstrap resampling approach. The relationships between trends in hydrological variables and trends in meteorological variables were investigated using partial correlation analysis. The results reveal more trends in some hydrological variables than are expected to occur by chance. In general, both basins exhibit an increase in winter flows and some increase in spring runoff. These increased flows are somewhat offset by decreases (not field significant) in summertime flow. Almost 50% of the stations used in the analysis show an increasing trend in annual minimum flows. Other differences in trend responses are noted for the two watersheds and possible explanations for the differences are hypothesized.

Detection of hydrologic trends and variability

This paper describes the development and application of a procedure that identifies trends in hydrologic variables. The procedure utilizes the Mann–Kendall non-parametric test to detect trends, a permutation approach to estimate the test distribution, and accounts for the correlation structure in the data in determining the significance level of the test results. The research investigates 18 hydrologic variables that reflect different parts of the hydrologic cycle. The hydrologic variables are analyzed for a network of 248 Canadian catchments that are considered to reflect natural conditions. A selection of catchments identified to have trends in hydrologic variables is studied further to investigate the presence of trends in meteorological variables and the relationship between the hydrologic and the meteorological response to climatic change. It is concluded that a greater number of trends are observed than are expected to occur by chance. There are differences in the geographic location of significant trends in the hydrologic variables investigated implying that impacts are not spatially uniform.