Background: The observation of low levels of weed pollens following a freeze and an early autumn snowfall in Denver, Colorado led to this analysis of meteorologic variables and pollen counts.
Objective: The purpose of this study was to examine, in depth, the relationship between observed pollen counts and a selection of independent meteorologic variables.
Methods: We prospectively studied in 1991 daily high and low temperature, relative humidity, precipitation, barometric pressure, percent sunshine, wind velocity and direction, tree, grass, and weed pollen, as well as dates of the first frost/freeze. Similar data were retrospectively analyzed for 1987-1990.
Results: Correlation coefficients for the prospective data were as high as .611 for high temperature and cottonwood and .718 for high temperature and maple (P < .001). High and low temperature showed strong correlations with the combined weed counts (.598 and .628, respectively, P < .001).
Conclusions: Denver weed pollens appear impacted more by temperature and less by precipitation and humidity, while the converse is true for tree and grass pollen. However, weed pollen, especially sage, may appreciably rebound after freezing temperatures. While separate meteorologic variables may have high correlations with specific pollen counts in a given year, such effect is not consistent and varies from year to year.
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Glob Chang Biol
January 2025
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.
Terrestrial vegetation is a key component of the Earth system, regulating the exchange of carbon, water, and energy between land and atmosphere. Vegetation affects soil moisture dynamics by absorbing and transpiring soil water, thus modulating land-atmosphere interactions. Moreover, changes in vegetation structure (e.
View Article and Find Full Text PDFSci Rep
January 2025
Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany.
The global burden of dengue disease is escalating under the influence of climate change, with India contributing a third of the total. The non-linearity and regional heterogeneity inherent in the climate-dengue relationship and the lack of consistent data makes it difficult to make useful predictions for effective disease prevention. The current study investigates these non-linear climate-dengue links in Pune, a dengue hotspot region in India with a monsoonal climate and presents a model framework for predicting both the near-term and future dengue mortalities.
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January 2025
Department of Geography, Hong Kong Baptist University, Hong Kong SAR 999077, China.
Brown carbon (BrC) has been recognized as an important light-absorbing carbonaceous aerosol, yet understanding of its influence on regional climate and air quality has been lacking, mainly due to the ignorance of regional coupled meteorology-chemistry models. Besides, assumptions about its emissions in previous explorations might cause large uncertainties in estimates. Here, we implemented a BrC module into the WRF-Chem model that considers source-dependent absorption and avoids uncertainties caused by assumptions about emission intensities.
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January 2025
Guangzhou Huadu district drainage management center, Guangzhou 510800, China.
Rapid urbanization has significantly altered surface landscape configurations, leading to complex urban climates. While much attention has been focused on impervious surfaces' impact on extreme precipitation, a critical gap remains in understanding how various 2D urban landscape components influence extreme precipitation across different durations. Through an analysis of the non-stationarity and spatiotemporal variations in extreme precipitation across the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1990 to 2020, we constructed the non-stationary Generalized Additive Models for Location Scale and Shape (GAMLSS) model by introducing six urban landscape structural metrics as explanatory variables for each of the 27 meteorological stations in the GBA.
View Article and Find Full Text PDFJ Therm Biol
January 2025
School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Private Bag X3, Wits, 2050, South Africa. Electronic address:
Questionnaires exploring tourists' perceptions of ideal climatic conditions are argued to be a more suitable data source for the development of tourism climate indices than the utilization and integration of expert opinion and pre-established thresholds. This assumes that those tourist respondents can accurately quantify meteorological conditions at a given point in time, and effectively discriminate between meteorological thresholds of suitable and unsuitable conditions. For variables such as rainfall and sunshine hours, this assumption is fairly reasonable.
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