scholarly journals Medium-Term Increases in Ambient Grass Pollen Between 1994-1999 and 2016-2020 in a Subtropical Climate Zone

2021 ◽  
Vol 2 ◽  
Author(s):  
Beth Addison-Smith ◽  
Andelija Milic ◽  
Divya Dwarakanath ◽  
Marko Simunovic ◽  
Shanice Van Haeften ◽  
...  

Grass pollen is the major outdoor trigger of allergic respiratory diseases. Climate change is influencing pollen seasonality in Northern Hemisphere temperate regions, but many aspects of the effects on grass pollen remain unclear. Carbon dioxide and temperature rises could increase the distribution of subtropical grasses, however, medium term shifts in grass pollen in subtropical climates have not yet been analysed. This study investigates changes in grass pollen aerobiology in a subtropical city of Brisbane, Australia, between the two available monitoring periods, 1994-1999 and 2016-2020. Potential drivers of pollen change were examined including weather and satellite-derived vegetation indicators. The magnitude of the seasonal pollen index for grass showed almost a three-fold increase for 2016-2020 over 1994-1999. The number and proportion of high and extreme grass pollen days in the recent period increased compared to earlier monitoring. Statistically significant changes were also identified for distributions of CO2, satellite-derived seasonal vegetation health indices, and daily maximum temperatures, but not for minimum temperatures, daily rainfall, or seasonal fraction of green groundcover. Quarterly grass pollen levels were correlated with corresponding vegetation health indices, and with green groundcover fraction, suggesting that seasonal-scale plant health was higher in the latter period. The magnitude of grass pollen exposure in the subtropical region of Brisbane has increased markedly in the recent past, posing an increased environmental health threat. This study suggests the need for continuous pollen monitoring to track and respond to the possible effects of climate change on grass pollen loads.

Author(s):  
Myeong-Ho Yeo ◽  
Hoang-Lam Nguyen ◽  
Van-Thanh-Van Nguyen

Abstract The present study proposes a climate change assessment tool based on a statistical downscaling (SD) approach for describing the linkage between large-scale climate predictors and observed daily rainfall characteristics at a local site. The proposed SD of the daily rainfall process (SDRain) model is based on a combination of a logistic regression model for representing the daily rainfall occurrences and a nonlinear regression model for describing the daily precipitation amounts. A scaling factor (SR) and correction coefficient (CR) are suggested to improve the accuracy of the SDRain model in representing the variance of the observed daily precipitation amounts in each month without affecting the monthly mean precipitation. SDRain facilitates the construction of daily precipitation models for the current and future climate conditions. The tool is tested using the National Center for Environmental Prediction re-analysis data and the observed daily precipitation data available for the 1961–2001 period at two study sites located in two completely different climatic regions: the Seoul station in subtropical-climate Korea and the Dorval Airport station in cold-climate Canada. Results of this illustrative application have indicated that the proposed functions (e.g. logistic regression, SR, and CR) contribute marked improvement in describing daily precipitation amounts and occurrences. Furthermore, the comparison analyses show that the proposed SD method could provide more accurate results than those given by the currently popular SDSM method.


2010 ◽  
Vol 11 (1) ◽  
pp. 26-45 ◽  
Author(s):  
Nityanand Singh ◽  
Ashwini Ranade

Abstract Characteristics of wet spells (WSs) and intervening dry spells (DSs) are extremely useful for water-related sectors. The information takes on greater significance in the wake of global climate change and climate-change scenario projections. The features of 40 parameters of the rainfall time distribution as well as their extremes have been studied for two wet and dry spells for 19 subregions across India using gridded daily rainfall available on 1° latitude × 1° longitude spatial resolution for the period 1951–2007. In a low-frequency-mode, intra-annual rainfall variation, WS (DS) is identified as a “continuous period with daily rainfall equal to or greater than (less than) daily mean rainfall (DMR) of climatological monsoon period over the area of interest.” The DMR shows significant spatial variation from 2.6 mm day−1 over the extreme southeast peninsula (ESEP) to 20.2 mm day−1 over the southern-central west coast (SCWC). Climatologically, the number of WSs (DSs) decreases from 11 (10) over the extreme south peninsula to 4 (3) over northwestern India as a result of a decrease in tropical and oceanic influences. The total duration of WSs (DSs) decreases from 101 (173) to 45 (29) days, and the duration of individual WS (DS) from 12 (18) to 7 (11) days following similar spatial patterns. Broadly, the total rainfall of wet and dry spells, and rainfall amount and rainfall intensity of actual and extreme wet and dry spells, are high over orographic regions and low over the peninsula, Indo-Gangetic plains, and northwest dry province. The rainfall due to WSs (DSs) contributes ∼68% (∼17%) to the respective annual total. The start of the first wet spell is earlier (19 March) over ESEP and later (22 June) over northwestern India, and the end of the last wet spell occurs in reverse, that is, earlier (12 September) from northwestern India and later (16 December) from ESEP. In recent years/decades, actual and extreme WSs are slightly shorter and their rainfall intensity higher over a majority of the subregions, whereas actual and extreme DSs are slightly (not significantly) longer and their rainfall intensity weaker. There is a tendency for the first WS to start approximately six days earlier across the country and the last WS to end approximately two days earlier, giving rise to longer duration of rainfall activities by approximately four days. However, a spatially coherent, robust, long-term trend (1951–2007) is not seen in any of the 40 WS/DS parameters examined in the present study.


2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.


2021 ◽  
Vol 9 (4) ◽  
pp. 377
Author(s):  
Dong Eun Lee ◽  
Jaehee Kim ◽  
Yujin Heo ◽  
Hyunjin Kang ◽  
Eun Young Lee

The impact of climatic variability in atmospheric conditions on coastal environments accompanies adjustments in both the frequency and intensity of coastal storm surge events. The top winter season daily maximum sea level height events at 20 tidal stations around South Korea were examined to assess such impact of winter extratropical cyclone variability. As the investigation focusses on the most extreme sea level events, the impact of climate change is found to be invisible. It is revealed that the measures of extreme sea level events—frequency and intensity—do not correlate with the local sea surface temperature anomalies. Meanwhile, the frequency of winter extreme events exhibits a clear association with the concurrent climatic indices. It was determined that the annual frequency of the all-time top 5% winter daily maximum sea level events significantly and positively correlates with the NINO3.4 and Pacific Decadal Oscillation (PDO) indices at the majority of the 20 tidal stations. Hence, this indicates an increase in extreme event frequency and intensity, despite localized temperature cooling. This contradicts the expectation of increases in local extreme sea level events due to thermal expansion and global climate change. During El Nino, it is suggested that northward shifts of winter storm tracks associated with El Nino occur, disturbing the sea level around Korea more often. The current dominance of interannual storm track shifts, due to climate variability, over the impact of slow rise on the winter extreme sea level events, implies that coastal extreme sea level events will change through changes in the mechanical drivers rather than thermal expansion. The major storm tracks are predicted to continue shifting northward. The winter extreme sea level events in the midlatitude coastal region might not go through a monotonic change. They are expected to occur more often and more intensively in the near future, but might not continue doing so when northward shifting storm tracks move away from the marginal seas around Korea, as is predicted by the end of the century.


2021 ◽  
Author(s):  
Cathryn Birch ◽  
Lawrence Jackson ◽  
Declan Finney ◽  
John Marsham ◽  
Rachel Stratton ◽  
...  

<p>Mean temperatures and their extremes have increased over Africa since the latter half of the 20th century and this trend is projected to continue, with very frequent, intense and often deadly heatwaves likely to occur very regularly over much of Africa by 2100. It is crucial that we understand the scale of the future increases in extremes and the driving mechanisms. We diagnose daily maximum wet bulb temperature heatwaves, which allows for both the impact of temperature and humidity, both critical for human health and survivability. During wet bulb heatwaves, humidity and cloud cover increase, which limits the surface shortwave radiation flux but increases longwave warming. It is found from observations and ERA5 reanalysis that approximately 30% of wet bulb heatwaves over Africa are associated with daily rainfall accumulations of more than 1 mm/day on the first day of the heatwave. The first ever pan-African convection-permitting climate model simulations of present-day and RCP8.5 future climate are utilised to illustrate the projected future change in heatwaves, their drivers and their sensitivity to the representation of convection. Compared to ERA5, the convection-permitting model better represents the frequency and magnitude of present-day wet bulb heatwaves than a version of the model with more traditional parameterised convection. The future change in heatwave frequency, duration and magnitude is also larger in the convective-scale simulation, suggesting CMIP-style models may underestimate the future change in wet bulb heat extremes over Africa. The main reason for the larger future change appears to be the ability of the model to produce larger anomalies relative to its climatology in precipitation, cloud and the surface energy balance.</p>


2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>


Significance As in 2020 and 2021, this projected growth will be driven by the ongoing expansion of the oil and gas sector, and related investment and state revenues. These rising revenues will support the government’s ambitious national development plans, which include both increased social and infrastructure spending. Impacts The government will prioritise enhancing the oil and gas investment framework. Investment into joint oil and gas infrastructure with Suriname will benefit the growing oil industry in both countries. The expansionary fiscal policy may lead to a rise in inflation, leading to further calls for wage increases. In the medium term, strong growth in the oil and gas sector could lead to increased climate change activism in the country.


Author(s):  
Rengui Jiang ◽  
Jiancang Xie ◽  
Fawen Li ◽  
Honghong Liu ◽  
Bin Li

2008 ◽  
Vol 8 (2) ◽  
pp. 7781-7804 ◽  
Author(s):  
K.-J. Liao ◽  
E. Tagaris ◽  
K. Manomaiphiboon ◽  
C. Wang ◽  
J.-H. Woo ◽  
...  

Abstract. Impacts of uncertain climate forecasts on future regional air quality are investigated using downscaled MM5 meteorological fields from the NASA GISS and MIT IGSM global climate models and the CMAQ model in 2050 in the continental US. Three future climate scenarios: high-extreme, low-extreme and base, are developed for regional air quality simulations. GISS, with the IPCC A1B scenario, is used for the base case. IGSM results, in the form of probabilistic distributions, are used to perturb the base case climate to provide 0.5th and 99.5th percentile climate scenarios. Impacts of the extreme climate scenarios on concentrations of summertime fourth-highest daily maximum 8-h average ozone are predicted to be up to 10 ppbv (about one-eighth of the current NAAQS of ozone) in some urban areas, though average differences in ozone concentrations are about 1–2 ppbv on a regional basis. Differences between the extreme and base scenarios in annualized PM2.5 levels are very location dependent and predicted to range between −1.0 and +1.5 μg m−3. Future annualized PM2.5 is less sensitive to the extreme climate scenarios than summertime peak ozone since precipitation scavenging is only slightly affected by the extreme climate scenarios examined. Relative abundances of biogenic VOC and anthropogenic NOx lead to the areas that are most responsive to climate change. Such areas may find that climate change can significantly offset air quality improvements from emissions reductions, particularly during the most severe episodes.


2021 ◽  
Vol 9 ◽  
Author(s):  
Lara Valderrama ◽  
Salvador Ayala ◽  
Carolina Reyes ◽  
Christian R. González

The extreme north of Chile presents a subtropical climate permissive of the establishment of potential disease vectors. Anopheles (Ano.) pseudopunctipennis is distributed from the south of the United States to the north of Argentina and Chile, and is one of the main vectors of malaria in Latin America. Malaria was eradicated from Chile in 1945. Nevertheless, the vector persists in river ravines of the Arica and Tarapacá regions. The principal effect of climate change in the north of Chile is temperature increase. Precipitation prediction is not accurate for this region because records were erratic during the last century. The objective of this study was to estimate the current and the projected distribution pattern of this species in Chile, given the potential impact due to climate change. We compiled distributional data for An. (Ano.) pseudopunctipennis and constructed species distribution models to predict the spatial distribution of this species using the MaxEnt algorithm with current and RCP 4.5 and 8.5 scenarios, using environmental and topographic layers. Our models estimated that the current expected range of An. (Ano.) pseudopunctipennis extends continuously from Arica to the north of Antofagasta region. Furthermore, the RCP 4.5 and 8.5 projected scenarios suggested that the range of distribution of An. (Ano.) pseudopunctipennis may increase in longitude, latitude, and altitude limits, enhancing the local extension area by 38 and 101%, respectively, and local presence probability (>0.7), from the northern limit in Arica y Parinacota region (18°S) to the northern Antofagasta region (23°S). This study contributes to geographic and ecologic knowledge about this species in Chile, as it represents the first local study of An. (Ano.) pseudopunctipennis. The information generated in this study can be used to inform decision making regarding vector control and surveillance programs of Latin America. These kinds of studies are very relevant to generate human, animal, and environmental health knowledge contributing to the “One Health” concept.


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