scholarly journals Strengthening tropical influence on heat generating circulation over Australia through spring

2021 ◽  
Author(s):  
Roseanna C. McKay ◽  
Julie M. Arblaster ◽  
Pandora Hope
Keyword(s):  
Linear Regression Analysis ◽  
Seasonal Prediction ◽  
Southern Annular Mode ◽  
Maximum Temperature ◽  
Low Level ◽  
Tropical Variability ◽  
High Maximum ◽  
Maximum Temperatures ◽  
The Tropics ◽  
Spring Maximum

Abstract. Extreme maximum temperatures during Australian spring can have deleterious impacts on a range of sectors from health to wine grapes to planning for wildfires, but are relatively understudied compared to spring rainfall. Spring maximum temperatures in Australia have been rising over recent decades, and, as such, it is important to understand how Australian spring maximum temperatures develop. Australia’s climate is influenced by variability in the tropics and extratropics, but some of this influence impacts Australia differently from winter to summer, and, consequently, may have different impacts on Australia as spring evolves. Using linear regression analysis, this paper explores the atmospheric dynamics and remote drivers of high maximum temperatures over the individual months of spring. We find that the drivers of early spring maximum temperatures in Australia are more closely related to low-level wind changes, which in turn are more related to the Southern Annular Mode than variability in the tropics. By late spring, Australia’s maximum temperatures are proportionally more related to warming through subsidence than low-level wind changes, and more closely related to tropical variability. This increased relationship with the tropical variability is linked with the breakdown of the subtropical jet through spring and an associated change in tropically-forced Rossby wave teleconnections. However, much of the maximum temperature variability cannot be explained by either tropical or extratropical variability. An improved understanding of how the extratropics and tropics projects onto the mechanisms that drive high maximum temperatures through spring may lead to improved sub-seasonal prediction of high temperatures in the future.

scholarly journals MJO teleconnections to crop growing seasons

2020 ◽  
Vol 54 (3-4) ◽  
pp. 2203-2219 ◽  
Author(s):  
Weston Anderson ◽  
Ángel G. Muñoz ◽  
Lisa Goddard ◽  
Walter Baethgen ◽  
Xandre Chourio
Keyword(s):  
Soil Moisture ◽  
Daily Precipitation ◽  
Maximum Temperature ◽  
Growing Seasons ◽  
Air Temperatures ◽  
Summer Hemisphere ◽  
Leaf Level ◽  
Maximum Temperatures ◽  
The Tropics

AbstractWhile many Madden–Julian Oscillation (MJO) teleconnections are well documented, the significance of these teleconnections to agriculture is not well understood. Here we analyze how the MJO affects the climate during crop flowering seasons, when crops are particularly vulnerable to abiotic stress. Because the MJO is located in the tropics of the summer hemisphere and maize is a tropical, summer-grown crop, the MJO teleconnections to maize flowering seasons are stronger and more coherent than those to wheat, which tends to be grown in midlatitudes and flowers during the spring. The MJO significantly affects not only daily average precipitation and soil moisture, but also the probability of extreme precipitation, soil moisture and maximum temperatures during crop flowering seasons. The average influence on the probability of extreme daily precipitation, soil moisture, and maximum temperature events is roughly equal. On average the MJO modifies the probability of a 5th or 95th, 10th or 90th, and 25th or 75th percentile event by $$\sim $$∼ 2.5%, $$\sim $$∼ 4% and $$\sim $$∼ 7%, respectively. This means that an exceptionally dry (10th percentile) soil moisture value, for example, would become $$\sim $$∼ 40% more common (happening 14% of the time) during certain MJO phases. That the MJO can simultaneously dry soils and raise maximum air temperatures may be particularly damaging to crops because without available soil water during times of heat stress, plants are unable to transpire to cool leaf-level temperatures as a means of avoiding long-term damage. As a result, even though teleconnections from the MJO last only a few days to a week, they likely affect crop growth.

The Effect of High Maximum Temperatures upon the Longevity of Glossina submorsitans, Newst., and G. tachinoides, Westw.

1935 ◽  
Vol 26 (1) ◽  
pp. 103-113 ◽  
Author(s):  
T. A. M. Nash
Keyword(s):  
Critical Zone ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
Sudden Increase ◽  
Long Duration ◽  
Cent Mortality ◽  
High Maximum ◽  
Low Humidity ◽  
Maximum Temperatures ◽  
Very High

Newly Hatched Tsetse (0–1 day old).1. Neither species is affected by daily maximum temperatures of 95–102°F.2. Possibly the death of any weakly tsetse is accelerated by a temperature of 102·5°F.3. The critical zone for G. tachinoides is 103° to 105°F., but at the latter temperature 100 per cent. mortality is only assured if this maximum lasts for about 100 minutes.4. The critical zone for G. submorsitans is 103·5° to 106°F.5. If maintained for 60 minutes, 106°F. assures 100 per cent. mortality among young flies of both species.Old Tsetse (over 10 days old).6. The critical zone for G. tachinoides is 102° to 105·5°F.7. The critical zone for G. submorsitans is 102·5° to 106°F.8. The sudden increase in mortality among tsetse upon very hot days would appear to be directly due to the maximum temperature having entered the critical zone, and not to excessively low humidity or very high evaporation.9. The critical zone for old flies starts at about 1°F. lower than for newly hatched flies.10. G. tachinoides is rather more susceptible to high maximum temperatures than is G. submorsitans ; results also suggest that G. tachinoides cannot withstand an exposure of long duration at high temperatures as well as G. submorsitans.

scholarly journals The impact of climate change in wheat and barley yields in the Iberian Peninsula

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Virgílio A. Bento ◽  
Andreia F. S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Rita M. Cardoso ◽  
...  
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Model ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Historical Period ◽  
Early Winter ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Spring Maximum

AbstractThe impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies.

scholarly journals Projected Changes in Climate Extremes Using CMIP6 Simulations Over SREX Regions

2021 ◽  
Vol 5 (3) ◽  
pp. 481-497
Author(s):  
Mansour Almazroui ◽  
Fahad Saeed ◽  
Sajjad Saeed ◽  
Muhammad Ismail ◽  
Muhammad Azhar Ehsan ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Extreme Events ◽  
First Century ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
Temperature And Precipitation ◽  
Projected Change ◽  
Twenty First Century ◽  
Projected Changes ◽  
The Tropics

AbstractThis paper presents projected changes in extreme temperature and precipitation events by using Coupled Model Intercomparison Project phase 6 (CMIP6) data for mid-century (2036–2065) and end-century (2070–2099) periods with respect to the reference period (1985–2014). Four indices namely, Annual maximum of maximum temperature (TXx), Extreme heat wave days frequency (HWFI), Annual maximum consecutive 5-day precipitation (RX5day), and Consecutive Dry Days (CDD) were investigated under four socioeconomic scenarios (SSP1-2.6; SSP2-4.5; SSP3-7.0; SSP5-8.5) over the entire globe and its 26 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions. The projections show an increase in intensity and frequency of hot temperature and precipitation extremes over land. The intensity of the hottest days (as measured by TXx) is projected to increase more in extratropical regions than in the tropics, while the frequency of extremely hot days (as measured by HWFI) is projected to increase more in the tropics. Drought frequency (as measured by CDD) is projected to increase more over Brazil, the Mediterranean, South Africa, and Australia. Meanwhile, the Asian monsoon regions (i.e., South Asia, East Asia, and Southeast Asia) become more prone to extreme flash flooding events later in the twenty-first century as shown by the higher RX5day index projections. The projected changes in extremes reveal large spatial variability within each SREX region. The spatial variability of the studied extreme events increases with increasing greenhouse gas concentration (GHG) and is higher at the end of the twenty-first century. The projected change in the extremes and the pattern of their spatial variability is minimum under the low-emission scenario SSP1-2.6. Our results indicate that an increased concentration of GHG leads to substantial increases in the extremes and their intensities. Hence, limiting CO2 emissions could substantially limit the risks associated with increases in extreme events in the twenty-first century.

THE TEMPERATURES OF SURFACE FIRES IN JACK PINE BARREN: I. THE VARIATION IN TEMPERATURE WITH TIME

1966 ◽  
Vol 44 (10) ◽  
pp. 1285-1292 ◽  
Author(s):  
David W. Smith ◽  
John H. Sparling
Keyword(s):  
Jack Pine ◽  
Maximum Temperature ◽  
Surface Fires ◽  
Mean Temperature ◽  
The Mean ◽  
Maximum Temperatures

The temperatures of 18 fires in an open jack pine barren near Timmins, Ontario, have been recorded. The maximum temperature recorded was 545 °C, although in other determinations fire temperatures in excess of 1000 °C were reached. The mean temperature of all fires was 340.6 ± 133.2 °C. Three fires at 230, 345, and 545 °C were considered in detail.The maximum temperature of a fire was normally recorded at heights of 5 cm or 10 cm above the surface. Maximum temperatures of hotter fires usually occurred at greater heights than cooler ones. Duration and the temperature ("intensity") of the fire are important aspects of fire studies.

Potential predictability of Southwest US rainfall : role of tropical and high-latitude variability

2021 ◽  
pp. 1-45
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Seasonal Prediction ◽  
Seasonal Rainfall ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Potential Predictability ◽  
Subseasonal Variability ◽  
The Tropics

Abstract This study explores the potential predictability of Southwest US (SWUS) precipitation for the November-March season in a set of numerical experiments performed with the Whole Atmospheric Community Climate Model. In addition to the prescription of observed sea surface temperature and sea ice concentration, observed variability from the MERRA-2 reanalysis is prescribed in the tropics and/or the Arctic through nudging of wind and temperature. These experiments reveal how a perfect prediction of tropical and/or Arctic variability in the model would impact the prediction of seasonal rainfall over the SWUS, at various time scales. Imposing tropical variability improves the representation of the observed North Pacific atmospheric circulation, and the associated SWUS seasonal precipitation. This is also the case at the subseasonal time scale due to the inclusion of the Madden-Julian Oscillation (MJO) in the model. When additional nudging is applied in the Arctic, the model skill improves even further, suggesting that improving seasonal predictions in high latitudes may also benefit prediction of SWUS precipitation. An interesting finding of our study is that subseasonal variability represents a source of noise (i.e., limited predictability) for the seasonal time scale. This is because when prescribed in the model, subseasonal variability, mostly the MJO, weakens the El Niño Southern Oscillation (ENSO) teleconnection with SWUS precipitation. Such knowledge may benefit S2S and seasonal prediction as it shows that depending on the amount of subseasonal activity in the tropics on a given year, better skill may be achieved in predicting subseasonal rather than seasonal rainfall anomalies, and conversely.

Calorimetric determination of the effect of additives on cement hydration process

2013 ◽  
Vol 67 (2) ◽  
Author(s):  
Pavel Šiler ◽  
Josef Krátký ◽  
Iva Kolářová ◽  
Jaromír Havlica ◽  
Jiří Brandštetr
Keyword(s):  
Portland Cement ◽  
Silica Fume ◽  
Maximum Temperature ◽  
Granulated Blast Furnace Slag ◽  
Mineral Components ◽  
Maximum Temperatures ◽  
The Impact ◽  
Furnace Slag ◽  
Calorimetric Determination

AbstractPossibilities of a multicell isoperibolic-semiadiabatic calorimeter application for the measurement of hydration heat and maximum temperature reached in mixtures of various compositions during their setting and early stages of hardening are presented. Measurements were aimed to determine the impact of selected components’ content on the course of ordinary Portland cement (OPC) hydration. The following components were selected for the determination of the hydration behaviour in mixtures: very finely ground granulated blast furnace slag (GBFS), silica fume (microsilica, SF), finely ground quartz sand (FGQ), and calcined bauxite (CB). A commercial polycarboxylate type superplasticizer was also added to the selected mixtures. All maximum temperatures measured for selected mineral components were lower than that reached for cement. The maximum temperature increased with the decreasing amount of components in the mixture for all components except for silica fume. For all components, except for CB, the values of total released heat were higher than those for pure Portland cement samples.

The ecology of immature phases of Trichostrongyle nematodes: II. The effect of climatic factors on the availability of the infective larvae of Trichostrongylus retortaeformis to the host

Parasitology ◽  
1948 ◽  
Vol 39 (1-2) ◽  
pp. 26-38 ◽  
Author(s):  
H. D. Crofton
Keyword(s):  
Climatic Factors ◽  
Faecal Pellet ◽  
Cold Weather ◽  
Maximum Temperature ◽  
Infective Stage ◽  
Faecal Pellets ◽  
Infective Larvae ◽  
High Death ◽  
Maximum Temperatures ◽  
Rate Of Evaporation

1. Eggs and larvae of Trichostrongylus retortaeformis were used.2. The rate of hatching of eggs was shown to be mainly related to temperature. From November to March, when maximum temperatures were below 50° F., there was no hatching. When maximum temperatures of 50–55° F. occurred eggs hatched on or before the fifteenth day, but never during the first 8 days. Eggs hatched in 8 days or less when maximum temperatures of 60–80° F. occurred.3. When the rate of evaporation in the air was high, eggs still hatched and reached the infective stage, the grass blades reducing the rate of loss of moisture from the faecal pellet. Laboratory experiments show that eggs may not develop to the infective stage if the faecal pellets are on a grassless portion of the pasture. This is most likely to occur when the rate of evaporation is high and the temperature low.4. Hatching may be delayed by cold conditions, but some eggs remain viable for long periods and they hatch when the temperature rises. Eggs passed by the host in the autumn can survive a cold winter and hatch in the spring, but eggs passed during the coldest period die.5. During periods when the maximum temperature never exceeded 55° F., little or no migration of larvae occurred. When temperatures rose above 55° F. the number of larvae migrating increased; but rise of temperature was associated with increase in the rate of evaporation. High rates of evaporation reduced the number of larvae migrating on the grass blades.6. Some infective larvae died soon after exposure on grass plots, but a small number survived long periods. In cold weather some larvae were still alive after 20 weeks. A high death-rate occurred in warm weather. A large proportion of the larvae died during periods in which the rate of evaporation was high; in one of these periods 95% of the larvae were dead at the end of 4 weeks' exposure.7. The number of larvae on grass blades of a pasture was shown to be dependent, at any time, upon the climate at that time, and upon past conditions which had influenced hatching and survival:

scholarly journals Initiation of Boreal Summer Intraseasonal Oscillation: Dynamic Contribution by Potential Vorticity

2012 ◽  
Vol 140 (6) ◽  
pp. 1748-1760 ◽  
Author(s):  
Kyong-Hwan Seo ◽  
Eun-Ji Song
Keyword(s):  
Potential Vorticity ◽  
Intraseasonal Oscillation ◽  
Vertical Wind Shear ◽  
Boreal Summer ◽  
Dynamical Process ◽  
Initiation Mechanism ◽  
Middle Troposphere ◽  
Boreal Summer Intraseasonal Oscillation ◽  
Low Level ◽  
The Tropics

Abstract Potential vorticity (PV) thinking conceptually connects the upper-level (upper troposphere in the extratropics and middle troposphere for the tropics) dynamical process to the lower-level process. Here, the initiation mechanism of the boreal summer intraseasonal oscillation (BSISO) in the tropics is investigated using PV thinking. The authors demonstrate that the midtropospheric PV anomaly produces a dynamical environment favorable for the BSISO initiation. Under seasonal easterly vertical wind shear, the PV anomaly enhances low-level convergence and upward motion at its western edge. Tropical PV forcing in the middle troposphere produces balanced mass and circulation fields that spread horizontally and vertically so that its effect can reach even the lowest troposphere. The downward influence of the midtropospheric PV forcing is one of the key aspects of the PV thinking. Direct piecewise PV inversions confirm that the anomalous lower-level zonal wind and its convergence necessary for the initiation of BSISO convection do not arise solely from the response to the lower-level PV forcing but from the summed contribution by PV forcing at all levels. About 50% of the low-level circulation variations result from PV forcing from 700 to 450 hPa, with the largest contribution from the 600–650-hPa PV anomalies for the convection initiation region over the western Indian Ocean. The current study is compared with and incorporated into the thermodynamic recharge process and the frictional moisture flux convergence mechanism for the BSISO initiation. This study is the first qualitative application of the PV thinking approach that reveals the BSISO dynamics.

scholarly journals Verification of surface minimum, mean, and maximum temperature forecasts in Calabria for summer 2008

2011 ◽  
Vol 11 (2) ◽  
pp. 487-500 ◽  
Author(s):  
S. Federico
Keyword(s):  
Forecast Error ◽  
Background Field ◽  
Horizontal Resolution ◽  
Atmospheric Modeling ◽  
Forecast Skill ◽  
Maximum Temperature ◽  
Model Forecast ◽  
Maximum Temperatures ◽  
Analysis Error ◽  
The Impact

Abstract. Since 2005, one-hour temperature forecasts for the Calabria region (southern Italy), modelled by the Regional Atmospheric Modeling System (RAMS), have been issued by CRATI/ISAC-CNR (Consortium for Research and Application of Innovative Technologies/Institute for Atmospheric and Climate Sciences of the National Research Council) and are available online at http://meteo.crati.it/previsioni.html (every six hours). Beginning in June 2008, the horizontal resolution was enhanced to 2.5 km. In the present paper, forecast skill and accuracy are evaluated out to four days for the 2008 summer season (from 6 June to 30 September, 112 runs). For this purpose, gridded high horizontal resolution forecasts of minimum, mean, and maximum temperatures are evaluated against gridded analyses at the same horizontal resolution (2.5 km). Gridded analysis is based on Optimal Interpolation (OI) and uses the RAMS first-day temperature forecast as the background field. Observations from 87 thermometers are used in the analysis system. The analysis error is introduced to quantify the effect of using the RAMS first-day forecast as the background field in the OI analyses and to define the forecast error unambiguously, while spatial interpolation (SI) analysis is considered to quantify the statistics' sensitivity to the verifying analysis and to show the quality of the OI analyses for different background fields. Two case studies, the first one with a low (less than the 10th percentile) root mean square error (RMSE) in the OI analysis, the second with the largest RMSE of the whole period in the OI analysis, are discussed to show the forecast performance under two different conditions. Cumulative statistics are used to quantify forecast errors out to four days. Results show that maximum temperature has the largest RMSE, while minimum and mean temperature errors are similar. For the period considered, the OI analysis RMSEs for minimum, mean, and maximum temperatures vary from 1.8, 1.6, and 2.0 °C, respectively, for the first-day forecast, to 2.0, 1.9, and 2.6 °C, respectively, for the fourth-day forecast. Cumulative statistics are computed using both SI and OI analysis as reference. Although SI statistics likely overestimate the forecast error because they ignore the observational error, the study shows that the difference between OI and SI statistics is less than the analysis error. The forecast skill is compared with that of the persistence forecast. The Anomaly Correlation Coefficient (ACC) shows that the model forecast is useful for all days and parameters considered here, and it is able to capture day-to-day weather variability. The model forecast issued for the fourth day is still better than the first-day forecast of a 24-h persistence forecast, at least for mean and maximum temperature. The impact of using the RAMS first-day forecast as the background field in the OI analysis is quantified by comparing statistics computed with OI and SI analyses. Minimum temperature is more sensitive to the change in the analysis dataset as a consequence of its larger representative error.

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