scholarly journals Half-hourly changes in intertidal temperature at nine wave-exposed locations along the Atlantic Canadian coast: a 5.5-year study

2020 ◽  
Vol 12 (4) ◽  
pp. 2695-2703
Author(s):  
Ricardo A. Scrosati ◽  
Julius A. Ellrich ◽  
Matthew J. Freeman

Abstract. Intertidal habitats are unique because they spend alternating periods of submergence (at high tide) and emergence (at low tide) every day. Thus, intertidal temperature is mainly driven by sea surface temperature (SST) during high tides and by air temperature during low tides. Because of that, the switch from high to low tides and vice versa can determine rapid changes in intertidal thermal conditions. On cold-temperate shores, which are characterized by cold winters and warm summers, intertidal thermal conditions can also change considerably with seasons. Despite this uniqueness, knowledge on intertidal temperature dynamics is more limited than for open seas. This is especially true for wave-exposed intertidal habitats, which, in addition to the unique properties described above, are also characterized by wave splash being able to moderate intertidal thermal extremes during low tides. To address this knowledge gap, we measured temperature every half hour during a period of 5.5 years (2014–2019) at nine wave-exposed rocky intertidal locations spanning 415 km of the Atlantic coast of Nova Scotia, Canada. This data set is freely available from the figshare online repository (Scrosati and Ellrich, 2020a; https://doi.org/10.6084/m9.figshare.12462065.v1). We summarize the main properties of this data set by focusing on location-wise values of daily maximum and minimum temperature and daily SST, which we make freely available as a separate data set in figshare (Scrosati et al., 2020; https://doi.org/10.6084/m9.figshare.12453374.v1). Overall, this cold-temperate coast exhibited a wide annual SST range, from a lowest overall value of −1.8 ∘C in winter to a highest overall value of 22.8 ∘C in summer. In addition, the latitudinal SST trend along this coast experienced a reversal from winter (when SST increased southwards) to summer (when SST decreased southwards), seemingly driven by alongshore differences in summer coastal upwelling. Daily temperature maxima and minima were more extreme, as expected from their occurrence during low tides, ranging from a lowest overall value of −16.3 ∘C in winter to a highest overall value of 41.2 ∘C in summer. Daily maximum temperature in summer varied little along the coast, while daily minimum temperature in winter increased southwards. This data set is the first of its kind for the Atlantic Canadian coast and exemplifies in detail how intertidal temperature varies in wave-exposed environments on a cold-temperate coast.

2020 ◽  
Author(s):  
Ricardo A. Scrosati ◽  
Julius A. Ellrich ◽  
Matthew J. Freeman

Abstract. Intertidal habitats are unique because they spend alternating periods of submergence (at high tide) and emergence (at low tide) every day. Thus, intertidal temperature is mainly driven by sea surface temperature (SST) during high tides and by air temperature during low tides. Because of that, the switch from high to low tides and viceversa can determine rapid changes in intertidal thermal conditions. On cold-temperate shores, which are characterized by cold winters and warm summers, intertidal thermal conditions can also change considerably with seasons. Despite this uniqueness, knowledge on intertidal temperature dynamics is more limited than for open seas. This is especially true for wave-exposed intertidal habitats, which, in addition to the unique properties described above, are also characterized by wave splash being able to moderate intertidal thermal extremes during low tides. To address this knowledge gap, we measured temperature every half hour during a period of 5.5 years (2014–2019) at nine wave-exposed rocky intertidal locations along the Atlantic coast of Nova Scotia, Canada. This data set is freely available from the figshare online repository (Scrosati and Ellrich, 2020a; https://doi.org/10.6084/m9.figshare.12462065.v1). We summarize the main properties of this data set by focusing on location-wise values of daily maximum and minimum temperature and daily SST, which we make freely available as a separate data set in figshare (Scrosati et al., 2020; https://doi.org/10.6084/m9.figshare.12453374.v1). Overall, this cold-temperate coast exhibited a wide annual SST range, from a lowest overall value of −1.8 °C in winter to a highest overall value of 22.8 °C in summer. In addition, the latitudinal SST trend along this coast experienced a reversal from winter, when SST increased southwards, to summer, when SST decreased southwards, seemingly driven by alongshore differences in coastal upwelling. Daily temperature maxima and minima were more extreme, as expected from their occurrence during low tides, ranging from a lowest overall value of −16.3 °C in winter to a highest overall value of 41.2 °C in summer. Daily maximum temperature in summer varied little along the coast, while daily minimum temperature in winter increased southwards. This data set is the first of its kind for the Atlantic Canadian coast and exemplifies in detail how intertidal temperature varies in wave-exposed environments on a cold-temperate coast.


Plant Disease ◽  
1998 ◽  
Vol 82 (1) ◽  
pp. 26-29 ◽  
Author(s):  
N. W. McLaren ◽  
B. C. Flett

Quantification of resistance to ergot requires that the observed ergot severity within a sorghum line be compared with expected ergot severity (ergot potential) to compensate for differences in environmental favorability for the disease among flowering dates and seasons. The ergot potential required to induce the onset of disease is referred to as the ergot breakdown point of that line. In earlier studies, the ergot potential of a specific flowering date was defined as the mean ergot severity in all sorghum heads over all lines in the nursery which commenced flowering on that date in a genetically broad-based sorghum nursery. In this study, results of field trials enabled accurate prediction of ergot potential by using a multiple regression analysis which included three weather variables—namely, pre-flowering minimum temperature (mean of days 23 to 27 pre-flowering), mean daily maximum temperature, and mean daily maximum relative humidity (mean of days 1 to 5 post-flowering; R2 = 0.90; P = 0.91E-5). Evaluation of predicted and observed ergot severity in an independent data set gave an index of agreement of d = 0.94 and R2 = 0.84 (P = 0.106E-4), showing that ergot severity, assuming the presence of viable inoculum, can be accurately predicted. Low pre-flowering minimum temperature was associated with reduced pollen viability, which appeared to be the primary factor predisposing lines to ergot.


Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1171
Author(s):  
Junju Zhou ◽  
Jumei Huang ◽  
Xi Zhao ◽  
Li Lei ◽  
Wei Shi ◽  
...  

The increase in the frequency and intensity of extreme weather events around the world has led to the frequent occurrence of global disasters, which have had serious impacts on the society, economic and ecological environment, especially fragile arid areas. Based on the daily maximum temperature and daily minimum temperature data of four meteorological stations in Shiyang River Basin (SRB) from 1960 to 2015, the spatio-temporal variation characteristics of extreme temperature indices were analyzed by means of univariate linear regression analysis, Mann–Kendall test and correlation analysis. The results showed that the extreme temperatures warming indices and the minimum of daily maximum temperature (TXn) and the minimum of daily minimum temperature (TNn) of cold indices showed an increasing trend from 1960 to 2016, especially since the 1990s, where the growth rate was fast and the response to global warming was sensitive. Except TXn and TNn, other cold indices showed a decreasing trend, especially Diurnal temperature (DTR) range, which decreased rapidly, indicating that the increasing speed of daily min-temperature were greater than of daily max-temperature in SRB. In space, the change tendency rate of the warm index basically showed an obvious altitude gradient effect that decreased with the altitude, which was consistent with Frost day (FD0) and Cool nights (TN10p) in the cold index, while Ice days (ID0) and Cool days (TX10p) are opposite. The mutation of the cold indices occurred earlier than the warm indices, illustrating that the cold indices in SRB were more sensitive to global warming. The change in extreme temperatures that would have a significant impact on the vegetation and glacier permafrost in the basin was the result of the combined function of different atmospheric circulation systems, which included the Arctic polar vortex, Western Pacific subtropical high and Qinghai-tibet Plateau circulation.


Water ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 3506
Author(s):  
Gandomè Mayeul Leger Davy Quenum ◽  
Francis Nkrumah ◽  
Nana Ama Browne Klutse ◽  
Mouhamadou Bamba Sylla

Climate variability and change constitute major challenges for Africa, especially West Africa (WA), where an important increase in extreme climate events has been noticed. Therefore, it appears essential to analyze characteristics and trends of some key climatological parameters. Thus, this study addressed spatiotemporal variabilities and trends in regard to temperature and precipitation extremes by using 21 models of the Coupled Model Intercomparison Project version 6 (CMIP6) and 24 extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). First, the CMIP6 variables were evaluated with observations (CHIRPS, CHIRTS, and CRU) of the period 1983–2014; then, the extreme indices from 1950 to 2014 were computed. The innovative trend analysis (ITA), Sen’s slope, and Mann–Kendall tests were utilized to track down trends in the computed extreme climate indices. Increasing trends were observed for the maxima of daily maximum temperature (TXX) and daily minimum temperature (TXN) as well as the maximum and minimum of the minimum temperature (TNX and TNN). This upward trend of daily maximum temperature (Tmax) and daily minimum temperature (Tmin) was enhanced with a significant increase in warm days/nights (TX90p/TN90p) and a significantly decreasing trend in cool days/nights (TX10p/TN10p). The precipitation was widely variable over WA, with more than 85% of the total annual water in the study domain collected during the monsoon period. An upward trend in consecutive dry days (CDD) and a downward trend in consecutive wet days (CWD) influenced the annual total precipitation on wet days (PRCPTOT). The results also depicted an upward trend in SDII and R30mm, which, additionally to the trends of CDD and CWD, could be responsible for localized flood-like situations along the coastal areas. The study identified the 1970s dryness as well as the slight recovery of the 1990s, which it indicated occurred in 1992 over West Africa.


2011 ◽  
Vol 50 (8) ◽  
pp. 1654-1665 ◽  
Author(s):  
Ron F. Hopkinson ◽  
Daniel W. McKenney ◽  
Ewa J. Milewska ◽  
Michael F. Hutchinson ◽  
Pia Papadopol ◽  
...  

AbstractOn 1 July 1961, the climatological day was redefined to end at 0600 UTC at all principal climate stations in Canada. Prior to that, the climatological day at principal stations ended at 1200 UTC for maximum temperature and precipitation and 0000 UTC for minimum temperature and was similar to the climatological day at ordinary stations. Hutchinson et al. reported occasional larger-than-expected residuals at 50 withheld stations when the Australian National University Spline (ANUSPLIN) interpolation scheme was applied to daily data for 1961–2003, and it was suggested that these larger residuals were in part due to the existence of different climatological days. In this study, daily minimum and maximum temperatures at principal stations were estimated using hourly temperatures for the same climatological day as local ordinary climate stations for the period 1953–2007. Daily precipitation was estimated at principal stations using synoptic precipitation data for the climatological day ending at 1200 UTC, which, for much of the country, was close to the time of the morning observation at ordinary climate stations. At withheld principal stations, the climatological-day adjustments led to the virtual elimination of large residuals in maximum and minimum temperature and a marked reduction in precipitation residuals. Across all 50 withheld stations the climatological day adjustments led to significant reductions, by around 12% for daily maximum temperature, 15% for daily minimum temperature, and 22% for precipitation, in the residuals reported by Hutchinson et al.


Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 489
Author(s):  
Jinxiu Liu ◽  
Weihao Shen ◽  
Yaqian He

India has experienced extensive land cover and land use change (LCLUC). However, there is still limited empirical research regarding the impact of LCLUC on climate extremes in India. Here, we applied statistical methods to assess how cropland expansion has influenced temperature extremes in India from 1982 to 2015 using a new land cover and land use dataset and ECMWF Reanalysis V5 (ERA5) climate data. Our results show that during the last 34 years, croplands in western India increased by ~33.7 percentage points. This cropland expansion shows a significantly negative impact on the maxima of daily maximum temperature (TXx), while its impacts on the maxima of daily minimum temperature and the minima of daily maximum and minimum temperature are limited. It is estimated that if cropland expansion had not taken place in western India over the 1982 to 2015 period, TXx would likely have increased by 0.74 (±0.64) °C. The negative impact of croplands on reducing the TXx extreme is likely due to evaporative cooling from intensified evapotranspiration associated with croplands, resulting in increased latent heat flux and decreased sensible heat flux. This study underscores the important influences of cropland expansion on temperature extremes and can be applicable to other geographic regions experiencing LCLUC.


2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.


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 ◽  
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>


2021 ◽  
Author(s):  
Georgia Lazoglou ◽  
George Zittis ◽  
Panos Hadjinicolaou ◽  
Jos Lelieveld

<p>Over the last decades, the use of climate models in the projection and assessment of future climate conditions, both on global and regional scales, has become common practice. However, inevitable biases between the simulated model output and observed conditions remain, mainly due to the variable nature of the atmospheric system, and limitations in representing sub-grid-scale processes that need to be parameterized. The present study aims to test a new approach for increasing the accuracy of daily climate model output. We apply the recently introduced TIN-Copula statistical method to the results of a state-of-the-art global Earth System Model (Hadley Centre Global Environmental Model version 3 - HadGEM3). The TIN-Copula approach is a combination of Triangular Irregular Networks and Copulas that focuses on modeling the whole dependence structure of the studied variables. The study area of the current application is the Middle East and North Africa (MENA) region, a prominent global climate change hot-spot. Considering the lack of accurate and consistent observational records in the MENA, we used the ERA5 reanalysis dataset as a reference. The results of the study reveal that the TIN-Copula method significantly improves the simulation of maximum temperature, both on annual and seasonal time scales. Specifically, the HadGEM3 model tends to overestimate the ERA5 temperature data in the major part of the MENA region. This overestimation is mainly evident for the lower values of the studied data sets during all seasons, while in summer the overestimation is found in the whole data set. However, after the use the TIN-Copula method, the differences between the simulated maximum temperature and the ERA5 data were minimized in more than the 85% of the studied grids.</p>


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