Relevant bibliographies by topics / Daily maximum temperature

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Daily maximum temperature'

Author: Grafiati
Published: 5 June 2025
Last updated: 25 June 2025

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Journal articles on the topic "Daily maximum temperature"

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Goncharevskyi, S., and V. Martynyuk. "Daily temperature dynamics of human skin representative areas." Bulletin of Taras Shevchenko National University of Kyiv. Series: Problems of Physiological Functions Regulation 21, no. 2 (2016): 86–91. http://dx.doi.org/10.17721/2616_6410.2016.21.86-91.

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The main aim of our research was to study the temperature variation of representative are a soft the cranial part of the autonomic nervous system of the human skin during the day. The temperature of representative are a soft the thoracic autonomic nervous system we measured by infrared thermometer (Medisana FTO D-53340, with anaccuracy of 0.1 degree Celsius). During the study identified minimums and maximums temperatures for representative are as during the day: the hypothalamus – 13 (maximum), 3 (minimum) an hour, midbrain – 15 (maximum), 5 (minimum) an hour, pons- not found, the medulla oblongata – 9, 15 (maximum), 3.21 (minimum) an hour, the vagus nerve (right side) – 15 (maximum), 5 (at least) an hour, the vagus nerve (left side) – 15 (maximum), 21 (minimum) an hour. The presence of minimums and maximums temperature in representative areas indicates different activity related to their brain structures.
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Muna, Siti Umamah Naili. "Crop Insurance Model Based on Maximum Daily Rainfall and Maximum Daily Temperature Index." ASTONJADRO 12, no. 2 (2023): 599–612. http://dx.doi.org/10.32832/astonjadro.v12i2.13207.

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A loss insurance model of risk for agricultural commodities that considers maximum daily rainfall and maximum daily temperature is introduced in this paper. This model requires bivariate distribution of maximum daily rainfall and maximum daily temperature in a specific region. Characteristics of particular agricultural commodity is also needed in the region where the two variables are being insured. The bivariate distribution and commodity characteristics are combined to obtain exit. exit is a benchmark value that causes the total crop failure and gives full benefit claim to policyholder. The case study was demonstrated by using data on maximum daily rainfall and temperature in Dramaga Bogor from September to December during 38 years (1984-2021) . Data was collected from Jawa Barat Climatology Station. Frank Copula is better to represent the bivariate distribution of data. Furthermore, two scenarios had given the premiums as IDR 2 482 925 per hectare and IDR 1 495 660 per hectare. This crop insurance model based on maximum daily rainfall and maximum daily temperature index could be the basis for the next developing of crop insurance model.
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van Wijngaarden, W. A., and A. Mouraviev. "Seasonal and Annual Trends in Australian Minimum/Maximum Daily Temperatures." Open Atmospheric Science Journal 10, no. 1 (2016): 39–55. http://dx.doi.org/10.2174/1874282301610010039.

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Seasonal and annual trends in Australian minimum and maximum temperatures were studied. Records of daily minimum and maximum temperatures averaged over each month, extending as far back as 1856 were examined. Over 1/2 million monthly temperature values were retrieved from the Australian Bureau of Meteorology for 299 stations. Each station had an average of 89 years of observations. Significant step discontinuities affected the maximum temperature data in the 19th century when Stevenson screens were installed. The temperature trends were found after such spurious data were removed and averaged over all stations. The resulting trend in the minimum (maximum) daily temperature was 0.67 ± 0.19 (0.58 ± 0.26) oC per century for the period 1907-2014. Decadal fluctuations were evident in the maximum daily temperature with most of the increase occurring in the late 20th century. The minimum and maximum daily temperature trends were also found for the various seasons. The minimum daily temperature trend exceeded the maximum daily temperature trend for all seasons except during June to August. The largest increases in minimum temperature as well as the smallest maximum temperature increases were found for the region north of 30 oS latitude and east of 140 oE longitude. There was also evidence that urban stations had greater increases in maximum daily temperature than those located in a rural environment.
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Abdullah, Ahmad Makmom, Marzuki Ismail, Fong Si Yuen, Samsuri Abdullah, and Rasheida Elhadi. "The Relationship between Daily Maximum Temperature and Daily Maximum Ground Level Ozone Concentration." Polish Journal of Environmental Studies 26, no. 2 (2017): 517–23. http://dx.doi.org/10.15244/pjoes/65366.

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RAJ, Y. E. A. "On forecasting daily summer maximum temperature at Madras." MAUSAM 49, no. 1 (2021): 95–102. http://dx.doi.org/10.54302/mausam.v49i1.3602.

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Forecasting schemes based on statistical techniques have been developed to forecast daily summer (March-May) maximum temperatures of Madras. A set of optimal number of predictors were chosen from a large number of parameters by employing stepwise forward screening. Separate forecasting schemes for Madras city and airport, with lead time of 24 and 9 hr were developed from the data of 12 years and tested in an independent sample of 4 years. Maximum temperature of the previous day, normal daily maximum temperature, temperature advection index and morning zonal wind at Madras at 900 hPa level were among the predictors selected. The schemes yielded good results providing 77-87% correct, forecasts with skill scores of 0.29-0.57.
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DeGaetano, Arthur T., Keith L. Eggleston, and Warren W. Knapp. "A Method to Estimate Missing Daily Maximum and Minimum Temperature Observations." Journal of Applied Meteorology 34, no. 2 (1995): 371–80. http://dx.doi.org/10.1175/1520-0450-34.2.371.

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Abstract A method to estimate missing daily maximum and minimum temperatures is presented. Temperature estimates are based on departures from daily temperature normals at the three closest stations with similar observation times. Although applied to Cooperative Observer Network stations in the northeastern United States, the approach can be used with any network of stations possessing an adequate station density and period of record. Generally, 75% of the estimates for both daily maximum and minimum temperature are within 1.7°C of the observed value. Median absolute differences between estimated and observed minimum temperatures, however, tend to be greater than those associated with maximum temperatures. For minimum temperatures, median absolute differences are approximately 1.0°C, whereas for maximum temperatures these differences are near 0.5°C. The accuracy of the estimates is independent of observation time, geographic location, and observed temperature but is influenced somewhat by station density.
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Neumann, David W., Balaji Rajagopalan, and Edith A. Zagona. "Regression Model for Daily Maximum Stream Temperature." Journal of Environmental Engineering 129, no. 7 (2003): 667–74. http://dx.doi.org/10.1061/(asce)0733-9372(2003)129:7(667).

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Kundzewicz, Zbigniew W., and Damian Józefczyk. "Temperature-related climate extremes in the Potsdam observation record." Geografie 113, no. 4 (2008): 372–82. http://dx.doi.org/10.37040/geografie2008113040372.

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This paper examines temperature-related climate extremes in the unique long-term gapfree record at the Secular Meteorological Station in Potsdam. Increasing tendencies in daily minimum temperature in winter and daily maximum temperature in summer, as well as monthly means of daily minimum temperatures in winter months and of daily maximum temperatures in summer months are illustrated. Also the numbers of hot days and of summer days (with maximum daily temperature exceeding 30 °C and 25 °C, respectively) have been increasing. In agreement with warming of winter minimum temperatures, the numbers of frost days (with minimum daily temperature below 0 °C) and of ice days (with maximum daily temperature below 0 °C) have been decreasing. However, low correlation coefficient and huge scatter illustrate strong natural variability, so that the occurrence of extremes departs from the general underlying tendency.
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Serrano-Notivoli, Roberto, Santiago Beguería, and Martín de Luis. "STEAD: a high-resolution daily gridded temperature dataset for Spain." Earth System Science Data 11, no. 3 (2019): 1171–88. http://dx.doi.org/10.5194/essd-11-1171-2019.

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Abstract. Using 5520 observatories covering the whole territory of Spain (about 1 station per 90 km2 considering the whole period), a daily gridded maximum and minimum temperature was built covering a period from 1901 to 2014 in peninsular Spain and 1971 to 2014 in the Balearic and Canary Islands. A comprehensive quality control was applied to the original data, and the gaps were filled on each day and location independently. Using the filled data series, a grid of 5 km × 5 km spatial resolution was created by estimating daily temperatures and their corresponding uncertainties at each grid point. Four daily temperature indices were calculated to describe the spatial distribution of absolute maximum and minimum temperature, number of frost days and number of summer days in Spain. The southern plateau showed the maximum values of maximum absolute temperature and summer days, while the minimum absolute temperature and frost days reached their maximums at the northern plateau. The use of all the available information, the complete quality control and the high spatial resolution of the grid allowed for an accurate estimate of temperature that represents a precise spatial and temporal distribution of daily temperatures in Spain. The STEAD dataset is publicly available at https://doi.org/10.20350/digitalCSIC/8622 and can be cited as Serrano-Notivoli et al. (2019).
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Matthiessen, J. N., and M. J. Palmer. "Prediction of temperatures in cattle dung for estimating development times of coprophilous organisms." Bulletin of Entomological Research 78, no. 2 (1988): 235–40. http://dx.doi.org/10.1017/s0007485300013006.

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AbstractIn studies in Western Australia, temperatures in air and one- and two-litre pads of cattle dung set out weekly and ranging from one to 20 days old were measured hourly for 438 days over all seasons, producing 1437 day x dung-pad observations. Daily maximum temperatures (and hence thermal accumulation) in cattle dung pads could not be accurately predicted using meteorological data alone. An accurate predictor of daily maximum dung temperature, using multiple regression analysis, required measurement of the following factors: maximum air temperature, hours of sunshine, rainfall, a seasonal factor (the day number derived from a linear interpolation of day number from day 0 at the winter solstice to day 182 at the preceding and following summer solstices) and a dung-pad age-specific intercept term, giving an equation that explained a 91·4% of the variation in maximum dung temperature. Daily maximum temperature in two-litre dung pads was 0·6°C cooler than in one-litre pads. Daily minimum dung temperature equalled minimum air temperature, and daily minimum dung temperatures occurred at 05.00 h and maximum temperatures at 14.00 h for one-litre and 14.30 h for two-litre pads. Thus, thermal summation in a dung pad above any threshold temperature can be computed using a skewed sine curve fitted to daily minimum air temperature and the calculated maximum dung temperature.
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Dissertations / Theses on the topic "Daily maximum temperature"

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naz, saima. "Forecasting daily maximum temperature of Umeå." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-112404.

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The aim of this study is to get some approach which can help in improving the predictions of daily temperature of Umeå. Weather forecasts are available through various sources nowadays. There are various software and methods available for time series forecasting. Our aim is to investigate the daily maximum temperatures of Umeå, and compare the performance of some methods in forecasting these temperatures. Here we analyse the data of daily maximum temperatures and find the predictions for some local period using methods of autoregressive integrated moving average (ARIMA), exponential smoothing (ETS), and cubic splines.  The forecast package in R is used for this purpose and automatic forecasting methods available in the package are applied for modelling with ARIMA, ETS, and cubic splines. The thesis begins with some initial modelling on univariate time series of daily maximum temperatures. The data of daily maximum temperatures of Umeå from 2008 to 2013 are used to compare the methods using various lengths of training period. On the basis of accuracy measures we try to choose the best method. Keeping in mind the fact that there are various factors which can cause the variability in daily temperature, we try to improve the forecasts in the next part of thesis by using multivariate time series forecasting method on the time series of maximum temperatures together with some other variables. Vector auto regressive (VAR) model from the vars package in R is used to analyse the multivariate time series. Results: ARIMA is selected as the best method in comparison with ETS and cubic smoothing splines to forecast one-step-ahead daily maximum temperature of Umeå, with the training period of one year. It is observed that ARIMA also provides better forecasts of daily temperatures for the next two or three days. On the basis of this study, VAR (for multivariate time series) does not help to improve the forecasts significantly. The proposed ARIMA with one year training period is compatible with the forecasts of daily maximum temperature of Umeå obtained from Swedish Meteorological and Hydrological Institute (SMHI).
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Squintu, Antonello Angelo. "Daily temperature trends in Trentino Alto Adige over the last century." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8310/.

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Numerosi lavori apparsi sulla letteratura scientifica negli ultimi decenni hanno evidenziato come, dall’inizio del XX secolo, la temperatura media globale sia aumentata. Tale fenomeno si è fatto più evidente dagli anni ’80, infatti ognuno degli ultimi tre decenni risulta più caldo dei precedenti. L’Europa e l’area mediterranea sono fra le regioni in cui il riscaldamento risulta più marcato, soprattutto per le temperature massime (dal 1951 sono cresciute di +0.39 °C per decennio) che hanno mostrato trend maggiori delle minime. Questo comportamento è stato osservato anche a scala nazionale (+0.25°C/dec per le massime e +0.20°C/dec per le minime). Accanto all’aumento dei valori medi è stato osservato un aumento (diminuzione) degli eventi di caldo (freddo) estremo, studiati attraverso la definizione di alcuni indici basati sui percentili delle distribuzioni. Resta aperto il dibattito su quali siano le cause delle variazioni negli eventi estremi: se le variazioni siano da attribuire unicamente ad un cambiamento nei valori medi, quindi ad uno shift rigido della distribuzione, o se parte del segnale sia dovuto ad una variazione nella forma della stessa, con un conseguente cambiamento nella variabilità. In questo contesto si inserisce la presente tesi con l’obiettivo di studiare l’andamento delle temperature giornaliere sul Trentino-Alto-Adige a partire dal 1926, ricercando cambiamenti nella media e negli eventi estremi in due fasce altimetriche. I valori medi delle temperature massime e minime hanno mostrato un evidente riscaldamento sull’intero periodo specialmente per le massime a bassa quota (`0.13 ̆ 0.03 °C/dec), con valori più alti per la primavera (`0.22 ̆ 0.05 °C/dec) e l’estate (`0.17 ̆ 0.05 °C/dec). Questi trends sono maggiori dopo il 1980 e non significativi in precedenza. L’andamento del numero di giorni con temperature al di sopra e al di sotto delle soglie dei percentili più estremi (stimate sull’intero periodo) indica un chiaro aumento degli estremi caldi, con valori più alti per le massime ad alta quota ( fino a +26.8% per il 99-esimo percentile) e una diminuzione degli estremi freddi (fino a -8.5% per il primo percentile delle minime a bassa quota). Inoltre, stimando anno per anno le soglie di un set di percentili e confrontando i loro trend con quelli della mediana, si è osservato, unicamente per le massime, un trend non uniforme verso temperature più alte, con i percentili più bassi (alti) caratterizzati da trend inferiori (superiori) rispetto a quello della mediana, suggerendo un allargamento della PDF.
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Books on the topic "Daily maximum temperature"

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Cristea, Nicoleta. Wenatchee River temperature total maximum daily load study. Washington State Dept. of Ecology, Environmental Assessment Program, 2005.

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Irle, Pat. Teanaway temperature total maximum daily load: Submittal report. Washington State Dept. of Ecology, Water Quality Program, 2001.

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Pelletier, G. J. Wind River Watershed temperature total maximum daily load. Washington State Dept. of Ecology, Environmental Assessment Program, 2002.

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Cristea, Nicoleta. Wenatchee River temperature total maximum daily load study. Washington State Dept. of Ecology, 2005.

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Butkus, Steven R. Upper Chehalis River Basin temperature: Total maximum daily load. Washington State Dept. of Ecology, Water Quality Program, 1999.

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Pelletier, G. J. Stillaguamish River Watershed temperature total maximum daily load study. Washington State Dept. of Ecology, 2004.

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Butkus, Steven R. Upper Chehalis River Basin temperature: Total maximum daily load. Washington State Dept. of Ecology, Water Quality Program, 1999.

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Brock, Stephanie. Little Klickitat River Watershed temperature total maximum daily load. Environmental Assessment Program, 2002.

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Brock, Stephanie. Little Klickitat River Watershed temperature total maximum daily load. Environmental Assessment Program, 2002.

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Stohr, Anita J. M. Willapa River Watershed temperature total maximum daily load study. Washington State Dept. of Ecology, 2004.

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Book chapters on the topic "Daily maximum temperature"

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Matandirotya, Newton R., Dirk P. Cilliers, Roelof P. Burger, Christian Pauw, and Stuart J. Piketh. "Risks of Indoor Overheating in Low-Cost Dwellings on the South African Lowveld." In African Handbook of Climate Change Adaptation. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_123.

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AbstractThe South African Lowveld is a region of land that lies between 150 and 2000 m above sea level. In summer the region is characterized by the maximum mean daily ambient temperature of 32 °C. The purpose of the study was to characterize indoor thermal environments in low-cost residential dwellings during summer seasons as climate is changing. Indoor and ambient air temperature measurements were performed at a 30-min temporal resolution using Thermochron iButtons in the settlement of Agincourt. 58 free running low-cost residential dwellings were sampled over the summer seasons of 2016 and 2017. Complementary ambient air temperature data were sourced from the South African Weather Service (SAWS). Data were transformed into hourly means for further analysis. It was found that hourly maximum mean indoor temperatures ranged between 27 °C (daytime) and 23 °C (nighttime) for both living rooms and bedrooms in summer 2016 while in 2017, maximum mean indoor temperatures ranged between 29 °C (daytime) and 26 °C (nighttime) in living rooms and bedrooms. Pearson correlations showed a positive association between indoor and ambient temperatures ranging between r = 0.40 (daytime) and r = 0.90 (nighttime). The association is weak to moderate during daytime because occupants apply other ventilation practices that reduce the relationship between indoor and ambient temperatures. The close association between nighttime ambient and indoor temperature can also be attributed to the effect of urban heat island as nighttime ambient temperature remain elevated; thus, influencing indoor temperatures also remain high. These findings highlight the potential threat posed by a rise in temperatures for low-cost residential dwellings occupants due to climate change. Furthermore, the high level of sensitiveness of dwellings to ambient temperature changes also indicates housing envelopes that have poor thermal resistance to withstand the Lowveld region’s harsh extreme heat conditions, especially during summer. The study findings suggest that a potential risk of indoor overheating exists in low-cost dwellings on the South African Lowveld as the frequency and intensity of heat waves rise. There is therefore a need to develop immediate housing adaptation interventions that mitigate against the projected ambient temperature rise for example through thermal insulation retrofits on the existing housing stock and passive housing designs for new housing stock.
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Dutta, Pulendra, and Arup Kumar Sarma. "Impact of Climate Change on Daily Maximum Temperature of the Brahmaputra River Basin." In Advances in Sustainability Science and Technology. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7535-5_2.

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Costa, Marco, Fernanda Catarina Pereira, and A. Manuela Gonçalves. "Improving Short-Term Forecasts of Daily Maximum Temperature with the Kalman Filter with GMM Estimation." In Computational Science and Its Applications – ICCSA 2021. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86973-1_39.

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Hays, Dirk B., Ilse Barrios-Perez, and Fatima Camarillo-Castillo. "Heat and Climate Change Mitigation." In Wheat Improvement. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90673-3_22.

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AbstractHigh temperature stress is a primary constraint to maximal yield in wheat, as in nearly all cultivated crops. High temperature stress occurs in varied ecoregions where wheat is cultivated, as either a daily chronic metabolic stress or as an acute episodic high heat shock during critical periods of reproductive development. This chapter focuses on defining the key biochemical processes regulating a plant’s response to heat stress while highlighting and defining strategies to mitigate stress and stabilize maximal yield during high temperature conditions. It will weigh the advantages and disadvantages of heat stress adaptive trait breeding strategies versus simpler integrated phenotypic selection strategies. Novel remote sensing and marker-assisted selection strategies that can be employed to combine multiple heat stress tolerant adaptive traits will be discussed in terms of their efficacy. In addition, this chapter will explore how wheat can be re-envisioned, not only as a staple food, but also as a critical opportunity to reverse climate change through unique subsurface roots and rhizomes that greatly increase wheat’s carbon sequestration.
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Khala, Mohamed, Naima El yanboiy, Ismail Elabbassi, et al. "CNN-LSTM Approach for Forecasting Daily Maximum and Minimum Temperatures: A Case Study of Southeast Morocco." In Information Systems Engineering and Management. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65014-7_39.

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Atesmen, M. Kemal. "Transient Heat Transfer During Seasonal Heating and Cooling of Earth’s Surface with Periodic Surface Temperature Fluctuations." In Case Studies in Transient Heat Transfer With Sensitivities to Governing Variables. ASME, 2023. http://dx.doi.org/10.1115/1.886786_ch22.

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Temperatures on Earth’s surface fluctuates daily and seasonally in a periodic fashion that affect temperatures on its surface and in its depths. In this chapter, we will investigate transient heat transfer from a semi-infinite surface with periodic surface temperature fluctuations with respect to an average annual temperature, Tave, and a maximum annual temperature, Tmax, as given in Equations 22-1.
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Burt, Stephen, and Tim Burt. "October." In Durham Weather and Climate since 1841. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780198870517.003.0013.

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Abstract Like September, October is another transitional month, and it ushers in shorter, cloudier days, more frequent rainfall, and lower temperatures. Furthermore, the mean daily maximum temperature can be expected to fall more than 5 °C during this month, there is increased precipitation, and autumn’s first air frosts can normally be expected before the month is out. This chapter examines the long-term records (averages and extremes) of temperature, precipitation, sunshine, barometric pressure, wind direction and speed, snowfall, and fog at Durham during the month of October. The chapter includes descriptive accounts and local photographs of notable weather events during the month.
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Bhattacharjee, Saurav, and Sabiha Raiyesha. "Analysis of Arima Model for Weather Forecasting in the Assam District." In Critical Approaches to Data Engineering Systems and Analysis. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2260-4.ch004.

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Weather forecasting is a scientific method that involves the prediction of atmospheric conditions at a specific geographic location. The increased volatility over the last decade is owing to an enormous rise in water used for irrigation application throughout agricultural area, much of which evaporates, necessitating accurate forecasting in order to take essential safeguards. In this chapter, an attempt is made to predict the average temperature and maximum temperature through machine learning models. The daily temperature data from 1970 to 2022 were collected from the National Centre of Environmental Information (NCEI). The ARIMA model is used to predict the weather data sets of Tezpur, Assam. Previous conventional models are insufficient to predict forecasting precisely. So statistical models and auto-regressive models are programmed and compared.
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"Pacific Salmon: Ecology and Management of Western Alaska’s Populations." In Pacific Salmon: Ecology and Management of Western Alaska’s Populations, edited by David A. Beauchamp. American Fisheries Society, 2009. http://dx.doi.org/10.47886/9781934874110.ch5.

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<em>Abstract.</em>—Size-selective mortality is a dominant variable regulating the dynamics of salmon populations. Body size, growth rate, and energy state during one life stage influence survival during that and subsequent life stages. Therefore, simultaneously examining allometric processes, foraging, and thermal constraints on growth within and among life stages can provide a powerful analytical framework for identifying critical periods and sizes during the life cycle of salmon, and for understanding the processes that contribute to the specific ecological bottlenecks confronting different species or stocks of salmon. A bioenergetics model was used to simulate generalized growth responses to a factorial combination of body size, daily feeding rate, and prey energy density over a continuous range of temperatures (0–24oC). The results of these simulations indicated that: 1) smaller salmon benefit from higher potential scope for growth or activity than larger salmon, based on the different allometric relationships for maximum consumption, metabolism, and waste; 2) optimal temperatures for growth decline with increasing body size; 3) optimal temperatures for growth also decline as daily rations decline; 4) thermal tolerances (temperature thresholds beyond which weight loss will occur) also shift to cooler temperatures for larger salmon and when ration sizes decline; 5) increasing the composite energy density of the diet can increase both optimal growth temperature, and thermal tolerance, especially at larger body sizes; 6) after spawners enter freshwater, the amount of energy and days available to migrate, and successfully spawn at a given upstream location was very sensitive to ambient river temperature, and the swimming speed required to reach the spawning grounds. When placed in the context of climate variability, seasonal shifts in temperature, and food availability, these simulations suggest that growth will be more frequently limited by feeding rate (prey availability) and prey quality than by temperature, especially for smaller, younger life stages. Larger salmon should be more sensitive to temperature change, but reductions in optimal growth temperature and thermal tolerance would be magnified for all life stages, if either feeding rate or prey quality were to be reduced. Given intense size-selective mortality during one or more early life stages, this simulation framework could be adopted to identify the key factors limiting growth to critical sizes during critical periods in the life cycle of specific salmon stocks.
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Reza Reisi, Ali. "Modeling Based on Daily Data of PV Power Plants." In Advances in Solar Photovoltaic Energy Systems. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.1003234.

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Modeling performance characteristics is essential for the design and optimal operation of solar power plants. However, due to the influence of various factors on the performance of solar panels and data changes over time, determining an exact relationship between output power and weather conditions is still challenging. In this chapter, a hybrid method based on genetic programming will be presented for accurate modeling of solar power plant characteristics, which includes two steps. First, three points of open-circuit voltage, maximum power point, and short-circuit current are modeled as functions of atmospheric conditions. For this purpose, by using the modeling process based on genetic programming, relationships with high fit will be obtained for these three points in terms of cell temperature and radiation. Then, with the help of these equations, the voltage–current characteristics are modeled based on the circuit analysis methods and without the need for factory data. To evaluate the modeling for a 3 kW solar power plant, and based on the results, the effectiveness of the proposed method will be shown.
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Conference papers on the topic "Daily maximum temperature"

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Minarik, Martin, Vladimir Kiss, Martin Prcik, Jan Cimo, and Maros Turna. "IMPACT OF THE BUILT-UP AREA OF A CITY ON THE DIURNAL PATTERN OF TEMPERATURES DURING TROPICAL DAYS." In 24th SGEM International Multidisciplinary Scientific GeoConference 24. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/4.1/s19.54.

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Approximately 5% of the area of Slovakia is made up of built-up areas and courtyards. These represent land where buildings and courtyards, motorways, roads, local roads, railways, airports, and water structures are built. To compare the influence of the urbanized part of the country on the daily air temperature, the city of Nitra, located in the western part of Slovakia, was selected. Meteorological stations are in the territory of the city, from which air temperature data were obtained. For the comparison of the "non-urbanised" part, a meteorological station located in the experimental garden and a station located at the Nitra-Janikovce airport were selected. The summer months from 15 June to 15 September in 2021 and 2022 were selected for comparison. In both years, four periods of heat with temperatures above 30-degree Celzius lasting at least three days were recorded during this period. The onset of temperature after night-time cooling is about the same, but the station in the experimental garden has a delayed onset. Also, the maximum temperature at noon, even during the heat wave, did not reach the same value as at the other stations. The temperature drop arrives identically, but the temperatures in the city do not drop to the same level as the temperatures at the base stations in the evening. It is also interesting to compare the average temperature differences. For the most part, there are larger differences in temperatures between the stations in the city and the station in the experimental garden. The differences between the stations in the city and the station at the airport are noticeable, but not to that extent. Thus, our hypothesis is only partially confirmed. The built-up area affects the diurnal temperature course, especially when it cools down in the evening, but an area with a regularly mowed lawn does not have as much of a positive effect as the public thinks. From our comparison, the experimental garden comes out best, where all stages are represented, including trees and shrubs. These create a more suitable microclimate that better mitigates the effects of climate change.
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Vincent, Shubhashalini, Patrick J. Teevens, Sridhar Arumugam, and Len J. Krissa. "Internal Corrosion Predictive Modeling (ICPM) and Solids Deposition Predictive Modeling (SDPM) Using In-house Corrosion Model Software for a 30” X 44.15-Mile Natural Gas Pipeline." In CONFERENCE 2025. AMPP, 2025. https://doi.org/10.5006/c2025-00483.

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Abstract The NACE SP0110-2018 WG-ICDA Standard Practice was applied for internal corrosion predictive modeling of a 30” X 44.15-mile natural gas pipeline using the Broadsword in-house software. Operational data for 25 Meter stations over 5 years were collected daily and averaged seasonally. A null point at mile 739.05 was identified where gas flows west through Station 1 and east through Station 2. ICPM results showed stable temperature and pressure profiles along the pipeline, with corrosion rates <1mpy and wall loss <2%. The average wall loss (%) as calculated from the ILI data was 1.2%, and the average wall loss predicted by the in-house software was 1.6%. Predominant corrosion products were Fe3O4 and FeCO3, indicating air-contaminated gas streams and CO2 corrosion at low rates. Solids deposition modeling revealed maximum accumulation in the first 60,000 ft due to low gas velocity. Cumulative corrosion product weight and volume were high upstream and decreased towards Station 2, highlighting susceptibility to localized corrosion with brine water contamination. Enhanced monitoring during low gas flow periods is recommended to prevent operational upsets leading to free water dropout. Regular water analysis on free water and pigging debris samples is crucial due to observed chloride content correlation with pitting corrosion frequency.
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Na, Qiang, Hua Li, Biao Cao, Zunjian Bian, Yongming Du, and Qinhuo Liu. "Estimation of Daily Mean, Maximum, and Minimum Land Surface Temperatures from Modis Data Using Machine Learning." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642782.

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Sharma, Amit, and Namrata Sengar. "Experimental Study of Steam Generation through Solar Parabolic Trough Collector for Prospective Use in Small Industries." In 22nd ISME International Conference on Recent Advances in Mechanical Engineering for Sustainable Development. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-c5wuq2.

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The solar parabolic trough collector technology is one of the most reliable technologies in the field of solar thermal. This is due to the fact that temperatures as high as 300-400°C can be achieved using this technology. This technology is used for hot water production, process steam requirement, power generation and many more. In the present work a thermal study on a parabolic trough collector is performed to observe the range of steam temperatures to be useful for small scale industry applications. The paper presents the steam temperatures, temperature profiles for the solar collector components and the solar radiation variation over the day. On the basis of several experiments it was found that in the parabolic trough collector the maximum pressure of 221 bar and the maximum steam temperature of around 374°C is achieved. From the experimental data obtained, the variation in temperatures with solar radiation on clear and intermittent cloud cover is discussed. From the results it can be concluded that this system may be used successfully for production of hot water and steam for use in many different industries such as dairy, textile, paper, timber, bricks, chemicals, plastics etc. Hot water and steam from solar system can be used in small scale industries for rose water making, cooking, drying, sterilization, food processing etc. In this paper a design for rose water making process through parabolic trough collector has been proposed. Keywords: Solar concentrator, parabolic trough, cylindrical parabolic collector, steam, temperature profile, industry applications.
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Mohan, Meera G., and Adarsh S. "Statistical Characterization of Maximum Temperature of Kerala, India." In 6th International Conference on Modeling and Simulation in Civil Engineering. AIJR Publisher, 2023. http://dx.doi.org/10.21467/proceedings.156.17.

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Temperature is an essential climate variable that significantly contributes to the characterization of Earth’s climate. The rise of temperature intensity is a major contribution that has resulted from natural as well as anthropogenic activities over the past few decades. India habitats an extraordinary variety of climatic regions making generalizations challenging. The study focuses on the statistical characteristics of daily maximum temperature of 8 stations namely, Kozhikode, Kannur, Alappuzha, Kochi (NAS), Punalur, Kottayam, Trivandrum city and Trivandrum Airport belonging to the state of Kerala, India. In order to explore the spatial and temporal behaviour of maximum temperature in Kerala, the variability of daily maximum temperature data from 1981 to 2020 (40 years) is analysed by looking at trend, stationarity, homogeneity, noise, and randomness. It was found that all the stations have an increasing stochastic trend with no noise and are heterogeneous and non-random in nature. The best fit probability distribution that suits the daily maximum temperature data for all the 8 stations were identified. The study aims to provide a knowledge base on the trend, pattern and variability of daily maximum temperatures of Kerala, India for better management of health, agriculture, irrigation, energy and ecology. Additionally, it will assist the state's policy makers and catastrophe management in reducing upcoming extreme temperature events.
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R. Daren Harmel, Clarence W. Richardson, Clayton L. Hanson, and Gregory L. Johnson. "SIMULATING MAXIMUM AND MINIMUM DAILY TEMPERATURE WITH THE NORMAL DISTRIBUTION." In 2001 Sacramento, CA July 29-August 1,2001. American Society of Agricultural and Biological Engineers, 2001. http://dx.doi.org/10.13031/2013.3512.

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Mori, Hiroyuki, and Akira Takahashi. "Hybrid intelligent system for daily maximum temperature forecasting in smart grids." In 2011 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2011. http://dx.doi.org/10.1109/iscas.2011.5937947.

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Bajpai, Animesh, Yashaswa Shukla, and Mohit Ranjan Panda. "Comparative analysis of daily maximum temperature & heatwave using MLP and LSTM." In 2024 International Conference on Emerging Systems and Intelligent Computing (ESIC). IEEE, 2024. http://dx.doi.org/10.1109/esic60604.2024.10481543.

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Lin, Qirong, Qiaoqiao Wang, Guilin Zhang, Yu Shi, Hongxia Liu, and Lijun Deng. "Maximum daily load forecasting based on support vector regression considering accumulated temperature effect." In 2018 Chinese Control And Decision Conference (CCDC). IEEE, 2018. http://dx.doi.org/10.1109/ccdc.2018.8408035.

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Lee, Soo Bong, Dalgeun Lee, Jongpil Kim, and Jinyoung Kim. "Development and Validation of a Daily Maximum Temperature Estimation Algorithm Using Landsat-8." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8518682.

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Reports on the topic "Daily maximum temperature"

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Osadchyi, V., O. Skrynyk, V. Sidenko, et al. ClimUAd: Ukrainian gridded daily air temperature (min, max, mean) and atmospheric precipitation data (1946-2020). Ukrainian Hydrometeorological Institute (UHMI), Kyiv, Ukraine, 2024. http://dx.doi.org/10.15407/uhmi.report.03.

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The dataset contains observation based long gridded time series of daily minimum, maximum and mean air temperature and atmospheric precipitation for Ukraine, covering the period of 1946-2020. The dataset was built through the thorough historical climate data processing, which included all mandatory steps: data rescue/digitization of missing values and/or periods in station time series from paper sources, their quality control and homogenization, and interpolation on 0.1o * 0.1o grid. The station data comprised daily values of 178 meteorological stations of Ukraine. The quality control, homogenization and gridding were performed by means of the well established and widely used software INQC, Climatol and MISH, respectively.
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Ruosteenoja, Kimmo. Applicability of CMIP6 models for building climate projections for northern Europe. Finnish Meteorological Institute, 2021. http://dx.doi.org/10.35614/isbn.9789523361416.

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In this report, we have evaluated the performance of nearly 40 global climate models (GCMs) participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). The focus is on the northern European area, but the ability to simulate southern European and global climate is discussed as well. Model evaluation was started with a technical control; completely unrealistic values in the GCM output files were identified by seeking the absolute minimum and maximum values. In this stage, one GCM was rejected totally, and furthermore individual output files from two other GCMs. In evaluating the remaining GCMs, the primary tool was the Model Climate Performance Index (MCPI) that combines RMS errors calculated for the different climate variables into one index. The index takes into account both the seasonal and spatial variations in climatological means. Here, MCPI was calculated for the period 1981—2010 by comparing GCM output with the ERA-Interim reanalyses. Climate variables explored in the evaluation were the surface air temperature, precipitation, sea level air pressure and incoming solar radiation at the surface. Besides MCPI, we studied RMS errors in the seasonal course of the spatial means by examining each climate variable separately. Furthermore, the evaluation procedure considered model performance in simulating past trends in the global-mean temperature, the compatibility of future responses to different greenhouse-gas scenarios and the number of available scenario runs. Daily minimum and maximum temperatures were likewise explored in a qualitative sense, but owing to the non-existence of data from multiple GCMs, these variables were not incorporated in the quantitative validation. Four of the 37 GCMs that had passed the initial technical check were regarded as wholly unusable for scenario calculations: in two GCMs the responses to the different greenhouse gas scenarios were contradictory and in two other GCMs data were missing from one of the four key climate variables. Moreover, to reduce inter-GCM dependencies, no more than two variants of any individual GCM were included; this led to an abandonment of one GCM. The remaining 32 GCMs were divided into three quality classes according to the assessed performance. The users of model data can utilize this grading to select a subset of GCMs to be used in elaborating climate projections for Finland or adjacent areas. Annual-mean temperature and precipitation projections for Finland proved to be nearly identical regardless of whether they were derived from the entire ensemble or by ignoring models that had obtained the lowest scores. Solar radiation projections were somewhat more sensitive.
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Wright, Wendy, M. Gregory, and Aaron Rinehart. Fixed station water quality monitoring at Cape Hatteras National Seashore: 2010 data summary. National Park Service, 2012. https://doi.org/10.36967/2190306.

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In 2005 the National Park Service (NPS) Southeast Coast Network (SECN) Inventory and Monitoring Program began collecting water-quality data in the estuarine waters near Cape Hatteras National Seashore (CAHA) as part the NPS Vital Signs monitoring program. The continuous monitoring data station is located at a dock at the Ocracoke Village boat ramp. This station collects pH, dissolved oxygen, temperature, salinity, conductivity, turbidity and water level data every 30 minutes. Additional water quality measurements are made by SECN staff and include monthly measurements of water clarity conditions, nutrients, and chlorophyll a levels. This report summarizes data collected during 2010. Monthly water quality sampling indicated good water clarity, good to fair chlorophyll levels, good dissolved oxygen and fair levels of both nitrogen and phosphorus in the vicinity of Ocracoke Island during 2010. Dissolved oxygen levels briefly dropped below 2 mg/L several times during a brief three day period between November 4 and November 6. Values ranged from 0.13 mg/L during this period in November to 13.22 mg/L during February. Mean monthly values ranged from to 11.4 mg/L in February to 5.6 mg/L during September. Mean daily values were generally higher during the cooler winter months and dipped to their lowest level during late summer and fall. pH values ranged from 7.58 in January to 9.05 in May. Mean monthly pH levels range from 7. 9 to 8.2 and did not exhibit any discernible seasonal variation during 2010. Turbidity levels ranged from near 0 NTUs across all months to maximum reading readings of 238 NTUs and 346 NTUs in May and June, respectively. Daily mean values were generally higher during late spring and lowest in the summer months.
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Rinehart, Aaron, M. Gregory, and Wendy Wright. Fixed-station water-quality monitoring at Cape Hatteras National Seashore: 2012 data summary. National Park Service, 2013. https://doi.org/10.36967/2195212.

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In 2005 the National Park Service (NPS) Southeast Coast Network (SECN) Inventory and Monitoring Program began collecting water-quality data in the estuarine waters near Cape Hatteras National Seashore (CAHA) as part the NPS Vital Signs monitoring program. The continuous-monitoring data station is located at a dock at the Ocracoke Village boat ramp. This station collects pH, dissolved oxygen, temperature, salinity, conductivity, turbidity and water-level data every 30 minutes. Additional water-quality measurements are made by SECN staff and include monthly measurements of water-clarity conditions, nutrients, and chlorophyll a levels. Methods used are adapted from the water-quality monitoring program established by the National Estuarine Research Reserve Program. The Cape Hatteras National Seashore fixed-station water-quality monitoring site is part of the SECN estuarine water and sediment quality monitoring efforts, which routinely collects data in the vicinity of seven coastal parks located along the southeastern U.S. coast. Information collected by this monitoring program will be used to help managers make better-informed decisions by understanding trends and variability related to water-quality conditions in park waters. This report presents data from the 2012 sampling year at Cape Hatteras National Seashore. Monthly water-quality data collected at the Southeast Coast Network site near Cape Hatteras National Seashore during 2012 reflect good to fair conditions throughout the year, with water-clarity rating good in the spring and early summer and fair in the late summer. Dissolved inorganic nitrogen and phosphorus indicated good conditions when available. Chlorophyll a levels rated fair during the late summer months, and good in June and October. Data were not available for the first five months, and last two months of the year. Mean monthly dissolved oxygen levels were good throughout the entire year, ranging from a high of 9.6 mg/L in February to a low of 6.4 mg/L in July and August. No daily average dissolved oxygen levels dipped below 5 mg/L. Mean monthly pH values ranged from a low of 7.9 in January to a high of 8.3 in June with very little variability throughout the year. Monthly mean turbidity values were highest during April at 18.9 NTUs. The lowest individual turbidity reading for any given month was ≤ 2.2 NTUs and a maximum reading of 175.4 NTUs was recorded in September. Water temperatures in 2012 were similar to those in 2011. The monthly mean high in July was 28.5 ºC (83.3 ºF) and 28.1 ºC (82.3 ºF) for 2012 and 2011, respectively. The lowest monthly average for both years occurred in January with 2012 readings approximately 5 ºC (9 ºF) degrees higher.
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Stumpf, Stacy, Laura Ploughe, Christopher Calvo, Laura Ploughe, Stacy Stumpf, and Christopher Calvo. Long-term trend in the aquatic macroinvertebrate community of the Mancos River at Mesa Verde National Park: Aquatic macroinvertebrate monitoring 2008-2019. National Park Service, 2024. http://dx.doi.org/10.36967/2306058.

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The Southern Colorado Plateau Inventory and Monitoring Network monitors status and long-term trends in the aquatic macroinvertebrate community and associated habitat in order to track changes in the ecological integrity of stream ecosystems. This report investigates changes in key aquatic macroinvertebrate community indices and physical habitat metrics collected from two long-term monitoring sites on the Mancos River in Mesa Verde National Park, Colorado. Results suggest that both monitoring sites have experienced periods of thermal and hydrologic stress. These stresses occur concurrently and are reflected in key metrics describing the aquatic community of the Mancos River. Daily stream temperature maxima were in exceedance of the State of Colorado?s aquatic life use water quality standard during the summer and fall months (June?September) across several years (2010?2014). These thermal exceedances match timing of low stream flows on the river. Sensitive taxa such as Trichoptera and taxa assigned as intolerant to perturbation exhibited significant negative trends in abundance, as did Trichoptera richness. These declines are likely attributed to thermal and hydrologic stress. Data analyzed using the state of Colorado?s multi-metric index indicate that both monitoring sites showed signs of impairment over the course of this study (2008?2019). Multiple index metrics contributed to impairment and support trend analyses demonstrating that declines in sensitive intolerant taxa, Ephemeroptera, Plecoptera and Trichoptera taxa (EPT) and clingers (trichopteran habit) contributed to the overall impairment of monitoring sites. As the effects of climate change increase over the coming decades, future management action on the river should include monitoring of thermal and hydrologic stress to better understand community responses to those stresses as well as their effects on the outcome of future management actions.
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October Mean Daily Maximum Temperatures. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2010. http://dx.doi.org/10.4095/300979.

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July Mean Daily Maximum Temperatures. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2010. http://dx.doi.org/10.4095/301079.

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January Mean Daily Maximum Temperatures. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2010. http://dx.doi.org/10.4095/301082.

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April Mean Daily Maximum Temperatures. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2010. http://dx.doi.org/10.4095/301220.

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