ResearchPad - weather https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Why do biting horseflies prefer warmer hosts? tabanids can escape easier from warmer targets]]> https://www.researchpad.co/article/elastic_article_14494 Blood-sucking horseflies (tabanids) prefer warmer (sunlit, darker) host animals and generally attack them in sunshine, the reason for which was unknown until now. Recently, it was hypothesized that blood-seeking female tabanids prefer elevated temperatures, because their wing muscles are quicker and their nervous system functions better at a warmer body temperature brought about by warmer microclimate, and thus they can more successfully avoid the host’s parasite-repelling reactions by prompt takeoffs. To test this hypothesis, we studied in field experiments the success rate of escape reactions of tabanids that landed on black targets as a function of the target temperature, and measured the surface temperature of differently coloured horses with thermography. We found that the escape success of tabanids decreased with decreasing target temperature, that is escape success is driven by temperature. Our results explain the behaviour of biting horseflies that they prefer warmer hosts against colder ones. Since in sunshine the darker the host the warmer its body surface, our results also explain why horseflies prefer sunlit dark (brown, black) hosts against bright (beige, white) ones, and why these parasites attack their hosts usually in sunshine, rather than under shaded conditions.

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<![CDATA[A case for Planetary Health/GeoHealth]]> https://www.researchpad.co/article/Nde3a46c2-5f2a-4a0f-9786-dd3e01de56f2

Abstract

Concern has been spreading across scientific disciplines that the pervasive human transformation of Earth's natural systems is an urgent threat to human health. The simultaneous emergence of “GeoHealth” and “Planetary Health” signals recognition that developing a new relationship between humanity and our natural systems is becoming an urgent global health priority—if we are to prevent a backsliding from the past century's great public health gains. Achieving meaningful progress will require collaboration across a broad swath of scientific disciplines as well as with policy makers, natural resource managers, members of faith communities, and movement builders around the world in order to build a rigorous evidence base of scientific understanding as the foundation for more robust policy and resource management decisions that incorporate both environmental and human health outcomes.

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<![CDATA[Insignificant QBO‐MJO Prediction Skill Relationship in the SubX and S2S Subseasonal Reforecasts]]> https://www.researchpad.co/article/N80d62339-fdd5-4539-8af8-fbb9aaf795dd

Abstract

The impact of the stratospheric quasi‐biennial oscillation (QBO) on the prediction of the tropospheric Madden‐Julian oscillation (MJO) is evaluated in reforecasts from nine models participating in subseasonal prediction projects, including the Subseasonal Experiment (SubX) and Subseasonal to Seasonal (S2S) projects. When MJO prediction skill is analyzed for December to February, MJO prediction skill is higher in the easterly phase of the QBO than the westerly phase, consistent with previous studies. However, the relationship between QBO phase and MJO prediction skill is not statistically significant for most models. This insignificant QBO‐MJO skill relationship is further confirmed by comparing two subseasonal reforecast experiments with the Community Earth System Model v1 using both a high‐top (46‐level) and low‐top (30‐level) version of the Community Atmosphere Model v5. While there are clear differences in the forecasted QBO between the two model top configurations, a negligible change is shown in the MJO prediction, indicating that the QBO in this model may not directly control the MJO prediction and supporting the insignificant QBO‐MJO skill relationship found in SubX and S2S models.

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<![CDATA[Solar Sources of Interplanetary Magnetic Clouds Leading to Helicity Prediction]]> https://www.researchpad.co/article/5c756547d5eed0c484cbd8e6

Abstract

This study identifies the solar origins of magnetic clouds that are observed at 1 AU and predicts the helical handedness of these clouds from the solar surface magnetic fields. We started with the magnetic clouds listed by the Magnetic Field Investigation (MFI) team supporting NASA's Wind spacecraft in what is known as the MFI table and worked backward in time to identify solar events that produced these clouds. Our methods utilize magnetograms from the Helioseismic and Magnetic Imager instrument on the Solar Dynamics Observatory spacecraft so that we could only analyze MFI entries after the beginning of 2011. This start date and the end date of the MFI table gave us 37 cases to study. Of these we were able to associate only eight surface events with clouds detected by Wind at 1 AU. We developed a simple algorithm for predicting the cloud helicity that gave the correct handedness in all eight cases. The algorithm is based on the conceptual model that an ejected flux tube has two magnetic origination points at the positions of the strongest radial magnetic field regions of opposite polarity near the places where the ejected arches end at the solar surface. We were unable to find events for the remaining 29 cases: lack of a halo or partial halo coronal mass ejection in an appropriate time window, lack of magnetic and/or filament activity in the proper part of the solar disk, or the event was too far from disk center. The occurrence of a flare was not a requirement for making the identification but in fact flares, often weak, did occur for seven of the eight cases.

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<![CDATA[Lowering barometric pressure induces neuronal activation in the superior vestibular nucleus in mice]]> https://www.researchpad.co/article/5c64489bd5eed0c484c2ea08

Weather changes accompanied by decreases in barometric pressure are suggested to trigger meteoropathy, i.e., weather-related pain. We previously reported that neuropathic pain-related behavior in rats is aggravated by lowering barometric pressure, and that this effect is abolished by inner ear lesions. These results suggest that mechanisms that increase vestibular neuronal activity may parallel those that contribute to meteoropathy generation. However, it remains unknown whether changes in barometric pressure activate vestibular neuronal activity. To address this issue, we used expression of c-Fos protein as a marker for neural activation. Male and female mice were placed in a climatic chamber, and the barometric pressure was lowered by 40 hPa, from 1013 hPa, for 50 min (LP stimulation). The total number of c-Fos-positive cells in the vestibular nuclei was counted bilaterally after LP stimulation. We also video-recorded mouse behaviors and calculated the total activity score during the LP stimulation. LP stimulation resulted in significant c-Fos expression in the superior vestibular nucleus (SuVe) of male and female mice. There was no effect of LP stimulation on the total activity score. These data show that distinct neurons in the SuVe respond to LP stimulation. Similar mechanisms may contribute to the generation of meteoropathy in humans.

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<![CDATA[Influence of vertical wind shear on wind- and rainfall areas of tropical cyclones making landfall over South Korea]]> https://www.researchpad.co/article/5c3d0173d5eed0c48403b75a

The wind- and rainfall areas of tropical cyclones (TCs) making landfall over South Korea were examined for the period 1998–2013 by using the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and Tropical Rainfall Measuring Mission (TRMM) 3B42 data. Here, the wind- and rainfall areas were defined as the regions where wind speeds and precipitation rates exceed 14 m s-1 and 80 mm day-1 within 1000 km from the TC center, respectively. In general, TCs show significantly asymmetric wind and rainfall structures, with strong vertical wind shear appearing over South Korea during the landfall period. The rainfall area significantly increases with environmental vertical wind shear while the wind area is not sensitive to it. Composite analyses of the cases of strong and weak vertical wind shear confirm that the increase of rainfall area is related to the asymmetric convection (rising/sinking motion in the downshear-left/upshear-right side) induced by the vertical wind shear. This work highlights the importance of local atmospheric environment in determining the area primarily affected by strong winds or heavy rainfall during TC landfalls.

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<![CDATA[On the use of local weather types classification to improve climate understanding: An application on the urban climate of Toulouse]]> https://www.researchpad.co/article/5c1ab816d5eed0c4840269c8

This paper proposes a method based on a local weather type classification approach to facilitate analysis and communication of climate information in local climate studies. Presented herein is an application to urban climatology in Toulouse, France, but the method can be used in other applied fields of climatology as well. To describe the climatic context of this urbanized area, the local weather types that explain the plurality of weather situations Toulouse faces are presented in depth. In order to show the potential for use of this approach, this information is applied to the study of changes in local weather types in terms of frequency and intensity within a series of future climate projections, a classic urban canopy and a series of atmospheric boundary layer analyses, and as a support for communication aimed to initiate urban climate awareness in urban planning practices. The proposed classification method has been coded in an R script and is provided as a supporting information file. The paper concludes that a systematic pre-study using this kind of climatic analysis is a good practice for performing climatic contextualization in local scale applied studies, both for scientific analysis and communication.

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<![CDATA[Estimating lake ice thickness in Central Ontario]]> https://www.researchpad.co/article/5c12cf58d5eed0c484914431

Lakes are a key geographical feature in Canada and have an impact on the regional climate. In the winter, they are important for recreational activities such as snowmobiling and ice fishing and act as part of an important supply route for northern communities. The ability to accurately report lake ice characteristics such as thickness is vital, however, it is underreported in Canada and there is a lack of lake ice thickness records for temperate latitude areas such as Central Ontario. Here, we evaluate the application of previously developed temperature models and RADARSAT-2 for estimating lake ice thickness in Central Ontario and provide insight into the regions long term ice thickness variability. The ALS Environmental Science Shallow Water Ice Profiler (SWIP) was used for validation of both temperature and radar-based models. Results indicate that the traditional approach that uses temperatures to predict ice thickness during ice growth has low RMSE values of 2.3 cm and correlations of greater than 0.9. For ice decay, similar low RMSE values of 2.1 cm and high correlations of 0.97 were found. Using RADARSAT-2 to estimate ice thickness results in R2 values of 0.6 (p < 0.01) but high RMSE values of 11.7 cm. Uncertainty in the RADARSAT-2 approach may be linked to unexplored questions about scattering mechanisms and the interaction of radar signal with mid-latitude lake ice. The application of optimized temperature models to a long-term temperature record revealed a thinning of ice cover by 0.81 cm per decade.

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<![CDATA[The Dependence of the Peak Velocity of High-Speed Solar Wind Streams as Measured in the Ecliptic by ACE and the STEREO satellites on the Area and Co-latitude of Their Solar Source Coronal Holes]]> https://www.researchpad.co/article/5c02177bd5eed0c484347c91

Abstract

We study the properties of 115 coronal holes in the time range from August 2010 to March 2017, the peak velocities of the corresponding high‐speed streams as measured in the ecliptic at 1 AU, and the corresponding changes of the Kp index as marker of their geoeffectiveness. We find that the peak velocities of high‐speed streams depend strongly on both the areas and the co‐latitudes of their solar source coronal holes with regard to the heliospheric latitude of the satellites. Therefore, the co‐latitude of their source coronal hole is an important parameter for the prediction of the high‐speed stream properties near the Earth. We derive the largest solar wind peak velocities normalized to the coronal hole areas for coronal holes located near the solar equator and that they linearly decrease with increasing latitudes of the coronal holes. For coronal holes located at latitudes 60°, they turn statistically to zero, indicating that the associated high‐speed streams have a high chance to miss the Earth. Similarly, the Kp index per coronal hole area is highest for the coronal holes located near the solar equator and strongly decreases with increasing latitudes of the coronal holes. We interpret these results as an effect of the three‐dimensional propagation of high‐speed streams in the heliosphere; that is, high‐speed streams arising from coronal holes near the solar equator propagate in direction toward and directly hit the Earth, whereas solar wind streams arising from coronal holes at higher solar latitudes only graze or even miss the Earth.

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<![CDATA[Identification of Climatic Factors Affecting the Epidemiology of Human West Nile Virus Infections in Northern Greece]]> https://www.researchpad.co/article/5989db3cab0ee8fa60bd50b4

Climate can affect the geographic and seasonal patterns of vector-borne disease incidence such as West Nile Virus (WNV) infections. We explore the association between climatic factors and the occurrence of West Nile fever (WNF) or West Nile neuro-invasive disease (WNND) in humans in Northern Greece over the years 2010–2014. Time series over a period of 30 years (1979–2008) of climatic data of air temperature, relative humidity, soil temperature, volumetric soil water content, wind speed, and precipitation representing average climate were obtained utilising the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-Interim) system allowing for a homogeneous set of data in time and space. We analysed data of reported human cases of WNF/WNND and Culex mosquitoes in Northern Greece. Quantitative assessment resulted in identifying associations between the above climatic variables and reported human cases of WNF/WNND. A substantial fraction of the cases was linked to the upper percentiles of the distribution of air and soil temperature for the period 1979–2008 and the lower percentiles of relative humidity and soil water content. A statistically relevant relationship between the mean weekly value climatic anomalies of wind speed (negative association), relative humidity (negative association) and air temperature (positive association) over 30 years, and reported human cases of WNF/WNND during the period 2010–2014 could be shown. A negative association between the presence of WNV infected Culex mosquitoes and wind speed could be identified. The statistically significant associations could also be confirmed for the week the WNF/WNND human cases appear and when a time lag of up to three weeks was considered. Similar statistically significant associations were identified with the weekly anomalies of the maximum and minimum values of the above climatic factors. Utilising the ERA-Interim re-analysis methodology it could be shown that besides air temperature, climatic factors such as soil temperature, relative humidity, soil water content and wind speed may affect the epidemiology of WNV.

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<![CDATA[Application of the PJ and NPS evaporation duct models over the South China Sea (SCS) in winter]]> https://www.researchpad.co/article/5989db50ab0ee8fa60bdbd8f

The detection of duct height has a significant effect on marine radar or wireless apparatus applications. The paper presents two models to verify the adaptation of evaporation duct models in the SCS in winter. A meteorological gradient instrument used to measure evaporation ducts was fabricated using hydrological and meteorological sensors at different heights. An experiment on the adaptive characteristics of evaporation duct models was carried out over the SCS. The heights of the evaporation ducts were measured by means of log-linear fit, Paulus-Jeske (PJ) and Naval Postgraduate School (NPS) models. The results showed that NPS model offered significant advantages in stability compared with the PJ model. According the collected data computed by the NPS model, the mean deviation (MD) was -1.7 m, and the Standard Deviation (STD) of the MD was 0.8 m compared with the true value. The NPS model may be more suitable for estimating the evaporation duct height in the SCS in winter due to its simpler system characteristics compared with meteorological gradient instruments.

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<![CDATA[Effect of climate on incidence of respiratory syncytial virus infections in a refugee camp in Kenya: A non-Gaussian time-series analysis]]> https://www.researchpad.co/article/5989db5cab0ee8fa60be0257

Respiratory syncytial virus (RSV) is one of the major causes of acute lower respiratory tract infections (ALRTI) in children. Children younger than 1 year are the most susceptible to RSV infection. RSV infections occur seasonally in temperate climate regions. Based on RSV surveillance and climatic data, we developed statistical models that were assessed and compared to predict the relationship between weather and RSV incidence among refugee children younger than 5 years in Dadaab refugee camp in Kenya. Most time-series analyses rely on the assumption of Gaussian-distributed data. However, surveillance data often do not have a Gaussian distribution. We used a generalized linear model (GLM) with a sinusoidal component over time to account for seasonal variation and extended it to a generalized additive model (GAM) with smoothing cubic splines. Climatic factors were included as covariates in the models before and after timescale decompositions, and the results were compared. Models with decomposed covariates fit RSV incidence data better than those without. The Poisson GAM with decomposed covariates of climatic factors fit the data well and had a higher explanatory and predictive power than GLM. The best model predicted the relationship between atmospheric conditions and RSV infection incidence among children younger than 5 years. This knowledge helps public health officials to prepare for, and respond more effectively to increasing RSV incidence in low-resource regions or communities.

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<![CDATA[Projected Influences of Changes in Weather Severity on Autumn-Winter Distributions of Dabbling Ducks in the Mississippi and Atlantic Flyways during the Twenty-First Century]]> https://www.researchpad.co/article/5989da83ab0ee8fa60b9b725

Projected changes in the relative abundance and timing of autumn-winter migration are assessed for seven dabbling duck species across the Mississippi and Atlantic Flyways for the mid- and late 21st century. Species-specific observed relationships are established between cumulative weather severity in autumn-winter and duck population rate of change. Dynamically downscaled projections of weather severity are developed using a high-resolution regional climate model, interactively coupled to a one-dimensional lake model to represent the Great Lakes and associated lake-effect snowfall. Based on the observed relationships and downscaled climate projections of rising air temperatures and reduced snow cover, delayed autumn-winter migration is expected for all species, with the least delays for the Northern Pintail and the greatest delays for the Mallard. Indeed, the Mallard, the most common and widespread duck in North America, may overwinter in the Great Lakes region by the late 21st century. This highlights the importance of protecting and restoring wetlands across the mid-latitudes of North America, including the Great Lakes Basin, because dabbling ducks are likely to spend more time there, which would impact existing wetlands through increased foraging pressure. Furthermore, inconsistency in the timing and intensity of the traditional autumn-winter migration of dabbling ducks in the Mississippi and Atlantic Flyways could have social and economic consequences to communities to the south, where hunting and birdwatching would be affected.

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<![CDATA[Model Development for Risk Assessment of Driving on Freeway under Rainy Weather Conditions]]> https://www.researchpad.co/article/5989da27ab0ee8fa60b81135

Rainy weather conditions could result in significantly negative impacts on driving on freeways. However, due to lack of enough historical data and monitoring facilities, many regions are not able to establish reliable risk assessment models to identify such impacts. Given the situation, this paper provides an alternative solution where the procedure of risk assessment is developed based on drivers’ subjective questionnaire and its performance is validated by using actual crash data. First, an ordered logit model was developed, based on questionnaire data collected from Freeway G15 in China, to estimate the relationship between drivers’ perceived risk and factors, including vehicle type, rain intensity, traffic volume, and location. Then, weighted driving risk for different conditions was obtained by the model, and further divided into four levels of early warning (specified by colors) using a rank order cluster analysis. After that, a risk matrix was established to determine which warning color should be disseminated to drivers, given a specific condition. Finally, to validate the proposed procedure, actual crash data from Freeway G15 were compared with the safety prediction based on the risk matrix. The results show that the risk matrix obtained in the study is able to predict driving risk consistent with actual safety implications, under rainy weather conditions.

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<![CDATA[Heat in the southeastern United States: Characteristics, trends, and potential health impact]]> https://www.researchpad.co/article/5989db5cab0ee8fa60bdfdde

High summer temperatures in extratropical areas have an impact on the public’s health, mainly through heat stress, high air pollution concentrations, and the transmission of tropical diseases. The purpose of this study is to examine the current characteristics of heat events and future projections of summer apparent temperature (AT)–and associated health concerns–throughout the southeastern United States. Synoptic climatology was used to assess the atmospheric characteristics of extreme heat days (EHDs) from 1979–2015. Ozone concentrations also were examined during EHDs. Trends in summer-season AT over the 37-year period and correlations between AT and atmospheric circulation were determined. Mid-century estimates of summer AT were calculated using downscaled data from an ensemble of global climate models. EHDs throughout the Southeast were characterized by ridging and anticyclones over the Southeast and the presence of moist tropical air masses. Exceedingly high ozone concentrations occurred on EHDs in the Atlanta area and throughout central North Carolina. While summer ATs did not increase significantly from 1979–2015, summer ATs are projected to increase substantially by mid-century, with most the Southeast having ATs similar to that of present-day southern Florida (i.e., a tropical climate). High ozone concentrations should continue to occur during future heat events. Large urban areas are expected to be the most affected by the future warming, resulting from intensifying and expanding urban heat islands, a large increase in heat-vulnerable populations, and climate conditions that will be highly suitable for tropical-disease transmission by the Aedes aegypti mosquito. This nexus of vulnerability creates the potential for heat-related morbidity and mortality, as well as the appearance of disease not previously seen in the region. These effects can be attenuated by policies that reduce urban heat (e.g., cool roofs and green roofs) and that improve infrastructure (e.g. emergency services, conditioned space).

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<![CDATA[Size Matters: What Are the Characteristic Source Areas for Urban Planning Strategies?]]> https://www.researchpad.co/article/5989da70ab0ee8fa60b948b6

Urban environmental measurements and observational statistics should reflect the properties generated over an adjacent area of adequate length where homogeneity is usually assumed. The determination of this characteristic source area that gives sufficient representation of the horizontal coverage of a sensing instrument or the fetch of transported quantities is of critical importance to guide the design and implementation of urban landscape planning strategies. In this study, we aim to unify two different methods for estimating source areas, viz. the statistical correlation method commonly used by geographers for landscape fragmentation and the mechanistic footprint model by meteorologists for atmospheric measurements. Good agreement was found in the intercomparison of the estimate of source areas by the two methods, based on 2-m air temperature measurement collected using a network of weather stations. The results can be extended to shed new lights on urban planning strategies, such as the use of urban vegetation for heat mitigation. In general, a sizable patch of landscape is required in order to play an effective role in regulating the local environment, proportional to the height at which stakeholders’ interest is mainly concerned.

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<![CDATA[Analyzing Personal Happiness from Global Survey and Weather Data: A Geospatial Approach]]> https://www.researchpad.co/article/5989da71ab0ee8fa60b94e49

Past studies have shown that personal subjective happiness is associated with various macro- and micro-level background factors, including environmental conditions, such as weather and the economic situation, and personal health behaviors, such as smoking and exercise. We contribute to this literature of happiness studies by using a geospatial approach to examine both macro and micro links to personal happiness. Our geospatial approach incorporates two major global datasets: representative national survey data from the International Social Survey Program (ISSP) and corresponding world weather data from the National Oceanic and Atmospheric Administration (NOAA). After processing and filtering 55,081 records of ISSP 2011 survey data from 32 countries, we extracted 5,420 records from China and 25,441 records from 28 other countries. Sensitivity analyses of different intervals for average weather variables showed that macro-level conditions, including temperature, wind speed, elevation, and GDP, are positively correlated with happiness. To distinguish the effects of weather conditions on happiness in different seasons, we also adopted climate zone and seasonal variables. The micro-level analysis indicated that better health status and eating more vegetables or fruits are highly associated with happiness. Never engaging in physical activity appears to make people less happy. The findings suggest that weather conditions, economic situations, and personal health behaviors are all correlated with levels of happiness.

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<![CDATA[Exploring the link between multiscale entropy and fractal scaling behavior in near-surface wind]]> https://www.researchpad.co/article/5989db50ab0ee8fa60bdbf81

The equivalency between the power law behavior of Multiscale Entropy (MSE) and of power spectra opens a promising path for interpretation of complex time-series, which is explored here for the first time for atmospheric fields. Additionally, the present manuscript represents a new independent empirical validation of such relationship, the first one for the atmosphere. The MSE-fractal relationship is verified for synthetic fractal time-series covering the full range of exponents typically observed in the atmosphere. It is also verified for near-surface wind observations from anemometers and CFSR re-analysis product. The results show a ubiquitous β ≈ 5/3 behavior inside the inertial range. A scaling break emerges at scales around a few seconds, with a tendency towards 1/f noise. The presence, extension and fractal exponent of this intermediate range are dependent on the particular surface forcing and atmospheric conditions. MSE shows an identical picture which is consistent with the turbulent energy cascade model: viscous dissipation at the small-scale end of the inertial range works as an information sink, while at the larger (energy-containing) scales the multiple forcings in the boundary layer act as widespread information sources. Another scaling transition occurs at scales around 1–10 days, with an abrupt flattening of the spectrum. MSE shows that this transition corresponds to a maximum of the new information introduced, occurring at the time-scales of the synoptic features that dominate weather patterns. At larger scales, a scaling regime with flatter slopes emerges extending to scales larger than 1 year. MSE analysis shows that the amount of new information created decreases with increasing scale in this low-frequency regime. Additionally, in this region the energy injection is concentrated in two large energy peaks: daily and yearly time-scales. The results demonstrate that the superposition of these periodic signals does not destroy the underlying scaling behavior, with both periodic and fractal terms playing an important role in the observed wind time-series.

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<![CDATA[Plant Distribution Data Show Broader Climatic Limits than Expert-Based Climatic Tolerance Estimates]]> https://www.researchpad.co/article/5989db42ab0ee8fa60bd7344

Background

Although increasingly sophisticated environmental measures are being applied to species distributions models, the focus remains on using climatic data to provide estimates of habitat suitability. Climatic tolerance estimates based on expert knowledge are available for a wide range of plants via the USDA PLANTS database. We aim to test how climatic tolerance inferred from plant distribution records relates to tolerance estimated by experts. Further, we use this information to identify circumstances when species distributions are more likely to approximate climatic tolerance.

Methods

We compiled expert knowledge estimates of minimum and maximum precipitation and minimum temperature tolerance for over 1800 conservation plant species from the ‘plant characteristics’ information in the USDA PLANTS database. We derived climatic tolerance from distribution data downloaded from the Global Biodiversity and Information Facility (GBIF) and corresponding climate from WorldClim. We compared expert-derived climatic tolerance to empirical estimates to find the difference between their inferred climate niches (ΔCN), and tested whether ΔCN was influenced by growth form or range size.

Results

Climate niches calculated from distribution data were significantly broader than expert-based tolerance estimates (Mann-Whitney p values << 0.001). The average plant could tolerate 24 mm lower minimum precipitation, 14 mm higher maximum precipitation, and 7° C lower minimum temperatures based on distribution data relative to expert-based tolerance estimates. Species with larger ranges had greater ΔCN for minimum precipitation and minimum temperature. For maximum precipitation and minimum temperature, forbs and grasses tended to have larger ΔCN while grasses and trees had larger ΔCN for minimum precipitation.

Conclusion

Our results show that distribution data are consistently broader than USDA PLANTS experts’ knowledge and likely provide more robust estimates of climatic tolerance, especially for widespread forbs and grasses. These findings suggest that widely available expert-based climatic tolerance estimates underrepresent species’ fundamental niche and likely fail to capture the realized niche.

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<![CDATA[Quantification of Local Warming Trend: A Remote Sensing-Based Approach]]> https://www.researchpad.co/article/5989da25ab0ee8fa60b80498

Understanding the warming trends at local level is critical; and, the development of relevant adaptation and mitigation policies at those levels are quite challenging. Here, our overall goal was to generate local warming trend map at 1 km spatial resolution by using: (i) Moderate Resolution Imaging Spectroradiometer (MODIS)-based 8-day composite surface temperature data; (ii) weather station-based yearly average air temperature data; and (iii) air temperature normal (i.e., 30 year average) data over the Canadian province of Alberta during the period 1961–2010. Thus, we analysed the station-based air temperature data in generating relationships between air temperature normal and yearly average air temperature in order to facilitate the selection of year-specific MODIS-based surface temperature data. These MODIS data in conjunction with weather station-based air temperature normal data were then used to model local warming trends. We observed that almost 88% areas of the province experienced warming trends (i.e., up to 1.5°C). The study concluded that remote sensing technology could be useful for delineating generic trends associated with local warming.

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