Use of Weather Variables to Quantify Sorghum Ergot Potential in South Africa

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.

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

10.5194/essd-2020-161 ◽

2020 ◽

Author(s):

Ricardo A. Scrosati ◽

Julius A. Ellrich ◽

Matthew J. Freeman

Keyword(s):

Minimum Temperature ◽

High Tide ◽

Thermal Conditions ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Measured Temperature ◽

Data Set ◽

Intertidal Habitats

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.

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

Earth System Science Data ◽

10.5194/essd-12-2695-2020 ◽

2020 ◽

Vol 12 (4) ◽

pp. 2695-2703

Author(s):

Ricardo A. Scrosati ◽

Julius A. Ellrich ◽

Matthew J. Freeman

Keyword(s):

Minimum Temperature ◽

High Tide ◽

Thermal Conditions ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Measured Temperature ◽

Data Set ◽

Intertidal Habitats

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.

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TIN-Copula bias correction of climate modeled daily maximum temperature in the MENA region

10.5194/egusphere-egu21-1988 ◽

2021 ◽

Author(s):

Georgia Lazoglou ◽

George Zittis ◽

Panos Hadjinicolaou ◽

Jos Lelieveld

Keyword(s):

Hot Spot ◽

Maximum Temperature ◽

Daily Maximum Temperature ◽

Dependence Structure ◽

Daily Maximum ◽

Model Output ◽

Mena Region ◽

Data Set ◽

Variable Nature ◽

Copula Method

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.

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Changes of Extreme Temperature and Its Influencing Factors in Shiyang River Basin, Northwest China

Atmosphere ◽

10.3390/atmos11111171 ◽

2020 ◽

Vol 11 (11) ◽

pp. 1171

Author(s):

Junju Zhou ◽

Jumei Huang ◽

Xi Zhao ◽

Li Lei ◽

Wei Shi ◽

...

Keyword(s):

Global Warming ◽

River Basin ◽

Minimum Temperature ◽

Extreme Temperature ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Extreme Temperatures ◽

Shiyang River Basin

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.

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Detecting climate change in Ukraine: trends, prediction and extreme events

10.5194/egusphere-egu21-6197 ◽

2021 ◽

Author(s):

Anna Bohushenko ◽

Sergiy Stepanenko ◽

Inna Khomenko

Keyword(s):

Spatial Distribution ◽

Minimum Temperature ◽

Precipitation Amount ◽

Maximum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Minimum Value ◽

Maximum Value ◽

Temperature Indices ◽

Consecutive Dry Days

In this study the trends and variations in 25 extreme temperature and precipitation indices defined by ETCCDI, are examined using trend method, probability distribution analysis and spatial statistics for periods of 71 to 137 years for 16 stations evenly distributed in Ukraine. Data on the indices were obtained from www.ecad.eu. Since 1981, temperature has increased by about 1&#186;C in all stations in question relative to the period of 1945-1980. Analysis of the temperature indices indicates that during the 20th and the beginning of the 21th century there is significant warming which is particularly pronounced in annual mean and annual maximum temperatures. Occurrence of more summer days, warm days and tropical nights and warm spell duration reached the record highest level, and conversely occurrence of frost and ice days, cold days and cold spell duration fall to a record low for the last three decades in the most of study territory. Since 1981, precipitation amount has grown by 30-50 mm relative to the period of 1945-1980 for the most of Ukrainian territory, except Uzhhorod and Uman where precipitation amount has remained the same. For Ukraine average, an increase in maximum daily and maximum 5 days precipitation amount, the maximum number of consecutive wet days, heavy and very heavy precipitation days, and a decrease in the maximum number of consecutive dry days are observed for the last three decades. The analysis of the spatial distribution of trend of precipitation and temperature indices showed that there are large differences between regions of Ukraine, and coherence of spatial distribution of trends of various indices is low. Spectral analysis and harmonic regression techniques were used to derive simulated and predicted (2019-2050) values of annual precipitation and annual mean temperature and four indices such as maximum value of daily maximum temperature, minimum value of daily minimum temperature, the highest 1-day precipitation amount and maximum number of consecutive dry days for some stations such as Kerch (the Crimean Peninsula), Kyiv (situated in north-central Ukraine along the Dnieper River), Lubny (Dnieper Lowland), Lviv and Shepetivka (Podillia Upland), Uzhhorod (Transcarpathia), Uman (Dnieper Upland). Annual mean temperature and maximum value of daily maximum temperature were predicted to increase by 0.33&#176;C per decade in the period of 2019-2050 with respect to 1981-2018, while minimum value of daily minimum temperature was predicted to grow slightly faster (by 0.43- 0.63&#186;C per decade). Precipitation was predicted to increase for the stations in question by 20-66 mm up to 2050 relative to 1981-2018 and conversely maximum number of consecutive dry days will slightly decline except Lubny where increase in an aridity index was predicted. In the next three decades changes in maximum daily precipitation will be various: in Shepetivka and Kyiv such precipitation will be decreased and in other stations increasement in such precipitation will be up to 6 mm till 2050 with respect to 1981-2018.

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Assessing the Spatial Distribution of Biodiversity in a Changing Temperature Pattern: The Case of Catalonia, Spain

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16204026 ◽

2019 ◽

Vol 16 (20) ◽

pp. 4026 ◽

Cited By ~ 1

Author(s):

Diego Varga ◽

Mariona Roigé ◽

Josep Pintó ◽

Marc Saez

Keyword(s):

Land Use ◽

Minimum Temperature ◽

Maximum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Temperature Pattern ◽

Explanatory Variables ◽

Number Of Species ◽

Protected Natural Areas ◽

Planning Processes

The impacts that climate change and land-use dynamics have on biodiversity are already visible in the distribution and behaviour of a large number of species. By using a Bayesian framework, including land-use, meteorological, topography and other variables as explanatory variables, such as distance to roads and urban centres, we modeled a number of species within each cell of a regular lattice for Catalonia, Spain, in the period of 2004 to 2010. We estimated a slight increase in daily maximum temperature and a more significant increase in minimum temperature (a 5-year increase of 0.159 °C in maximum temperature, and an increase of 0.332 °C in minimum temperature). The estimation shows that the total number of species was greater than expected in the cells where land use was not urban—38.4%, in forests and 55.2% in mixed forests. Finally, we observed that most invasive species are found in areas where the minimum temperature is expected to increase. Our study can help with making important recommendations as to where, when and how future threats could affect specie distribution and the kind of planning processes needed for when protected natural areas will be unable to continue to support all the species they were designed to protect.

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Long-Term Maximum and Minimum Temperature Projections Over Metro Vancouver, Canada

Frontiers in Earth Science ◽

10.3389/feart.2021.742840 ◽

2021 ◽

Vol 9 ◽

Author(s):

Chuyin Tian ◽

Guohe Huang ◽

Yanli Liu ◽

Denghua Yan ◽

Feng Wang ◽

...

Keyword(s):

Seasonal Variability ◽

Minimum Temperature ◽

General Circulation ◽

Energy Requirement ◽

General Circulation Models ◽

Maximum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Climate Projections ◽

Metro Vancouver

Evident climate change has been observed and projected in observation records and General Circulation Models (GCMs), respectively. This change is expected to reshape current seasonal variability; the degree varies between regions. High-resolution climate projections are thereby necessary to support further regional impact assessment. In this study, a gated recurrent unit-based recurrent neural network statistical downscaling model is developed to project future temperature change (both daily maximum temperature and minimum temperature) over Metro Vancouver, Canada. Three indexes (i.e., coefficient of determinant, root mean square error, and correlation coefficient) are estimated for model validation, indicating the developed model’s competitive ability to simulate the regional climatology of Metro Vancouver. Monthly comparisons between simulation and observation also highlight the effectiveness of the proposed downscaling method. The projected results (under one model set-up, WRF-MPI-ESM-LR, RCP 8.5) show that both maximum and minimum temperature will consistently increase between 2,035 and 2,100 over the 12 selected meteorological stations. By the end of this century, the daily maximum temperature and minimum temperature are expected to increase by an average of 2.91°C and 2.98°C. Nevertheless, with trivial increases in summer and significant rises in winter and spring, the seasonal variability will be reduced substantially, which indicates less energy requirement over Metro Vancouver. This is quite favorable for Metro Vancouver to switch from fossil fuel-based energy sources to renewable and clean forms of energy. Further, the cold extremes’ frequency of minimum temperature will be reduced as expected; however, despite evident warming trend, the hot extremes of maximum temperature will become less frequent.

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Evaluation of the AR4 Climate Models’ Simulated Daily Maximum Temperature, Minimum Temperature, and Precipitation over Australia Using Probability Density Functions

Journal of Climate ◽

10.1175/jcli4253.1 ◽

2007 ◽

Vol 20 (17) ◽

pp. 4356-4376 ◽

Cited By ~ 381

Author(s):

S. E. Perkins ◽

A. J. Pitman ◽

N. J. Holbrook ◽

J. McAneney

Keyword(s):

Probability Density ◽

Minimum Temperature ◽

Climate Models ◽

Quantitative Measure ◽

Probability Density Functions ◽

Maximum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Density Functions ◽

Coupled Climate Models

Abstract The coupled climate models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change are evaluated. The evaluation is focused on 12 regions of Australia for the daily simulation of precipitation, minimum temperature, and maximum temperature. The evaluation is based on probability density functions and a simple quantitative measure of how well each climate model can capture the observed probability density functions for each variable and each region is introduced. Across all three variables, the coupled climate models perform better than expected. Precipitation is simulated reasonably by most and very well by a small number of models, although the problem with excessive drizzle is apparent in most models. Averaged over Australia, 3 of the 14 climate models capture more than 80% of the observed probability density functions for precipitation. Minimum temperature is simulated well, with 10 of the 13 climate models capturing more than 80% of the observed probability density functions. Maximum temperature is also reasonably simulated with 6 of 10 climate models capturing more than 80% of the observed probability density functions. An overall ranking of the climate models, for each of precipitation, maximum, and minimum temperatures, and averaged over these three variables, is presented. Those climate models that are skillful over Australia are identified, providing guidance on those climate models that should be used in impacts assessments where those impacts are based on precipitation or temperature. These results have no bearing on how well these models work elsewhere, but the methodology is potentially useful in assessing which of the many climate models should be used by impacts groups.

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Spatiotemporal Changes in Temperature and Precipitation in West Africa. Part I: Analysis with the CMIP6 Historical Dataset

Water ◽

10.3390/w13243506 ◽

2021 ◽

Vol 13 (24) ◽

pp. 3506

Author(s):

Gandomè Mayeul Leger Davy Quenum ◽

Francis Nkrumah ◽

Nana Ama Browne Klutse ◽

Mouhamadou Bamba Sylla

Keyword(s):

West Africa ◽

Minimum Temperature ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Upward Trend ◽

Extreme Climate ◽

Temperature And Precipitation ◽

Extreme Indices

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.

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Impact of Aligning Climatological Day on Gridding Daily Maximum–Minimum Temperature and Precipitation over Canada

Journal of Applied Meteorology and Climatology ◽

10.1175/2011jamc2684.1 ◽

2011 ◽

Vol 50 (8) ◽

pp. 1654-1665 ◽

Cited By ~ 100

Author(s):

Ron F. Hopkinson ◽

Daniel W. McKenney ◽

Ewa J. Milewska ◽

Michael F. Hutchinson ◽

Pia Papadopol ◽

...

Keyword(s):

Minimum Temperature ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Daily Minimum ◽

Temperature And Precipitation ◽

Daily Data ◽

National University ◽

Maximum Temperatures

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.

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