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Journal articles on the topic 'Daily mean'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Smith, Brooks M. "Should "daily" Mean "daily" in TMDL." Proceedings of the Water Environment Federation 2007, no. 5 (2007): 756–65. http://dx.doi.org/10.2175/193864707786619387.

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2

Norton, B., and M. Abu-Ebeid. "Estimation of mean monthly daily total insolation from mean daily ambient temperature." International Journal of Ambient Energy 10, no. 3 (1989): 151–62. http://dx.doi.org/10.1080/01430750.1989.9675134.

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3

Weggel, J. Richard. "Maximum Daily Wind Gusts Related to Mean Daily Wind Speed." Journal of Structural Engineering 125, no. 4 (1999): 465–68. http://dx.doi.org/10.1061/(asce)0733-9445(1999)125:4(465).

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4

Brown, Shannon E., Kurt S. Pregitzer, David D. Reed, and Andrew J. Burton. "Predicting Daily Mean Soil Temperature from Daily Mean Air Temperature in Four Northern Hardwood Forest Stands." Forest Science 46, no. 2 (2000): 297–301. http://dx.doi.org/10.1093/forestscience/46.2.297.

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Abstract Soil temperature is very important in regulating ecosystem processes, yet it is often difficult and costly to measure. Most models that have endeavored to predict soil temperature have either a long time step or several complicated independent variables. Daily mean air and soil temperatures were measured from 1989-1997 in four northern hardwood sites along a 500 km latitudinal gradient in Michigan. These data were used to derive a simple method to predict daily mean soil temperature (depth of 15 cm) using the daily mean air temperature from the previous day and a cosine function of Ju

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5

Bristow, Keith L. "Prediction of daily mean vapor density from daily minimum air temperature." Agricultural and Forest Meteorology 59, no. 3-4 (1992): 309–17. http://dx.doi.org/10.1016/0168-1923(92)90099-p.

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6

MOOLEY, DA, and SS ARALIKATTI. "Regression equations between mean wind power density and mean hourly wind speed during the monsoon season." MAUSAM 36, no. 1 (2022): 33–38. http://dx.doi.org/10.54302/mausam.v36i1.1580.

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Utilising the hourly wind speed data of some selected Indian stations with good wind regime during the monsoon season, mean dally and monthly wind power density and mean daily and monthly wind speeds have been obtained for each day and for each month. From these, correlation coefficients between mean daily power density and cube of mean daily wind speed and also between mean monthly power density and cube of mean monthly wind speed have been computed for the monsoon months. These correlations are found to be consistently very high (> 0.92) and stable. In view of this very close and stable r

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7

Yang, Shimin, and Gary A. Davis. "Bayesian estimation of classified mean daily traffic." Transportation Research Part A: Policy and Practice 36, no. 4 (2002): 365–82. http://dx.doi.org/10.1016/s0965-8564(01)00008-8.

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8

Lucas, Mary, Martin Lee, Eric Oksenhendler, and Helen Chapel. "The ratio of mean daily IgG increment/mean daily dose in immunoglobulin replacement therapy in primary antibody deficiencies." Journal of Allergy and Clinical Immunology: In Practice 3, no. 6 (2015): 998–1000. http://dx.doi.org/10.1016/j.jaip.2015.07.001.

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9

Chinita, Maria J., Mark Richardson, João Teixeira, and Pedro M. A. Miranda. "Global mean frequency increases of daily and sub-daily heavy precipitation in ERA5." Environmental Research Letters 16, no. 7 (2021): 074035. http://dx.doi.org/10.1088/1748-9326/ac0caa.

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10

Chen, Bo, Witold F. Krajewski, Fan Liu, Weihua Fang, and Zongxue Xu. "Estimating instantaneous peak flow from mean daily flow." Hydrology Research 48, no. 6 (2017): 1474–88. http://dx.doi.org/10.2166/nh.2017.200.

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Abstract We revisited three traditional methods and proposed a slope-based method, which all require only mean daily flow (MDF) records as inputs, to estimate instantaneous peak flows (IPFs). We applied these methods to 144 basins in Iowa, USA, with drainage areas in the range 7–220,000 km2. This application involves ∼3,800 peak flow events triggered by snow-melting and rainfall over the period from 1997 to 2014. The results show that: using a sequence of MDF rather than just the maximum MDF improves the accuracy of estimating IPFs from MDFs; Sangal's method tends to overestimate, Fill and Ste

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11

Christy, John R., and S. James Drouilhet. "Variability in Daily, Zonal Mean Lower-Stratospheric Temperatures." Journal of Climate 7, no. 1 (1994): 106–20. http://dx.doi.org/10.1175/1520-0442(1994)007<0106:vidzml>2.0.co;2.

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12

Karakoti, Indira, Prasun Kumar Das, and S. K. Singh. "Predicting monthly mean daily diffuse radiation for India." Applied Energy 91, no. 1 (2012): 412–25. http://dx.doi.org/10.1016/j.apenergy.2011.10.012.

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13

von Bloh, W., M. C. Romano, and M. Thiel. "Long-term predictability of mean daily temperature data." Nonlinear Processes in Geophysics 12, no. 4 (2005): 471–79. http://dx.doi.org/10.5194/npg-12-471-2005.

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Abstract. We quantify the long-term predictability of global mean daily temperature data by means of the Rényi entropy of second order K2. We are interested in the yearly amplitude fluctuations of the temperature. Hence, the data are low-pass filtered. The obtained oscillatory signal has a more or less constant frequency, depending on the geographical coordinates, but its amplitude fluctuates irregularly. Our estimate of K2 quantifies the complexity of these amplitude fluctuations. We compare the results obtained for the CRU data set (interpolated measured temperature in the years 1901-2003 wi

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14

Ma, Yuting, and Peter Guttorp. "Estimating daily mean temperature from synoptic climate observations." International Journal of Climatology 33, no. 5 (2012): 1264–69. http://dx.doi.org/10.1002/joc.3510.

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15

De Jong, R. "Soil water modelling using daily and mean‐daily data derived from historical monthly values*." Atmosphere-Ocean 23, no. 3 (1985): 254–66. http://dx.doi.org/10.1080/07055900.1985.9649228.

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16

SHEKH, A. M., M. S. KULSHRESHTHA, H. R. PATEL, and R. S. PARMAR. "Relationship of mean temperatures with screen temperatures." MAUSAM 49, no. 1 (2021): 21–26. http://dx.doi.org/10.54302/mausam.v49i1.3595.

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An attempt has been made to study the variation in daily mean temperatures obtained from maximum and minimum temperatures and that obtained from hourly temperatures recorded by the automatic weather station at the Agrometeorological Observatory, Anand (Gujarat).  The mean temperatures obtained from the records of daily maximum and minimum temperatures were higher and fluctuated from -1.5 to 1.5 °C during the months of September to May as compared to the respective values obtained from hourly temperatures recorded by the automatic weather station. However, during May to September, t

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17

L.O.Onundi, Otuogba Philips, and Oumarou M.B. "AN IMPROVEMENT ON THE SOBOYEJO AND NIGERIAN METEOROLOGICAL AGENCY WIND ISOPLETHS MAPS." Continental J. Engineering Sciences 4 (July 22, 2009): 12–19. https://doi.org/10.5281/zenodo.833693.

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The paper reviewed the useful details of the Soboyejo Isopleths map for wind speeds and the Nigerian Meteorological Agency wind Documentation maps produced for Nigeria. The research work discovered some discrepancies in the interpretations given to the data produced by the Agency. Efforts were made to correct the wrong interpretations and a factor that varies from 7.86 to 11.67 was recommended to conveniently convert the daily mean produced by the Nigerian Meteorological Agency to the yearly mean produced by Soboyejo. Alternatively, the researchers decided to find a homogeneous mathematical re

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18

Frick, Claudia, Heiko Steiner, Alex Mazurkiewicz, et al. "Central European high-resolution gridded daily data sets (HYRAS): Mean temperature and relative humidity." Meteorologische Zeitschrift 23, no. 1 (2014): 15–32. http://dx.doi.org/10.1127/0941-2948/2014/0560.

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19

Kenigsberg, D. V., Yu M. Salamatina, O. A. Prokhorov, and S. I. Kuzikov. "Convergence of daily mean coordinates of precise positioning methods." IOP Conference Series: Earth and Environmental Science 929, no. 1 (2021): 012014. http://dx.doi.org/10.1088/1755-1315/929/1/012014.

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Abstract As part of the research of modern movements of the Earth’s crust, an analysis of 7 high-precision methods for calculating GNSS positions was carried out for the convergence of their daily mean coordinates. Based on Euclidean distances, regular and maximal discrepancies between coordinates of different methods are given. According to the coordinates in the ITRF, 5 methods are stood out with regular coordinate discrepancies <1 mm, and individual maximum discrepancies up to 30 mm. The other two methods have regular discrepancies in coordinates up to 2 cm, and the maximum differences r

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20

Davis, Gary A. "Accuracy of Estimates of Mean Daily Traffic: A Review." Transportation Research Record: Journal of the Transportation Research Board 1593, no. 1 (1997): 12–16. http://dx.doi.org/10.3141/1593-02.

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A location’s mean daily traffic (MDT) is the expected traffic volume on a “typical” day, and AASHTO’s Guidelines for Traffic Monitoring Programs identifies 22 different uses for estimates of MDT. The problem of quantifying the “precision and bias” of short-count estimates of MDT is reviewed, with particular attention to the different sources of estimation errors. It is argued that early attempts to estimate the likely error of short-count estimates did not include errors from using incorrect seasonal or day-of-week adjustment factors. It is also indicated that incorrect adjustment can produce

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21

Langholz, H. "A Simple Model for Predicting Daily Mean Soil Temperatures." Journal of Agronomy and Crop Science 163, no. 5 (1989): 312–18. http://dx.doi.org/10.1111/j.1439-037x.1989.tb00773.x.

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22

REVFEIM, K. "On the relationship between radiation and mean daily sunshine." Agricultural and Forest Meteorology 86, no. 3-4 (1997): 183–91. http://dx.doi.org/10.1016/s0168-1923(97)00013-0.

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23

Tsonis, Anastasios A., Xinnong Pan, Geli Wang, and Catherine Nicolis. "On the min–max estimation of mean daily temperatures." Climate Dynamics 53, no. 3-4 (2019): 1981–89. http://dx.doi.org/10.1007/s00382-019-04757-6.

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24

Jiang, Yingni. "Estimation of monthly mean daily diffuse radiation in China." Applied Energy 86, no. 9 (2009): 1458–64. http://dx.doi.org/10.1016/j.apenergy.2009.01.002.

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25

Fill, Heinz Dieter, and Alexandre Arns Steiner. "Estimating Instantaneous Peak Flow from Mean Daily Flow Data." Journal of Hydrologic Engineering 8, no. 6 (2003): 365–69. http://dx.doi.org/10.1061/(asce)1084-0699(2003)8:6(365).

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26

CRISP, D. T. "Simplified methods of estimating daily mean stream water temperature." Freshwater Biology 23, no. 3 (1990): 457–62. http://dx.doi.org/10.1111/j.1365-2427.1990.tb00287.x.

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27

Göçken, Mustafa, and Aslı Boru. "Integrating metaheuristics and ANFIS for daily mean temperature forecasting." International Journal of Global Warming 9, no. 1 (2016): 110. http://dx.doi.org/10.1504/ijgw.2016.074326.

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28

Bednorz, Ewa, and Leszek Kolendowicz. "Summer mean daily air temperature extremes in Central Spitsbergen." Theoretical and Applied Climatology 113, no. 3-4 (2012): 471–79. http://dx.doi.org/10.1007/s00704-012-0798-4.

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29

Geerts, B. "Empirical estimation of the monthly-mean daily temperature range." Theoretical and Applied Climatology 74, no. 3-4 (2003): 145–65. http://dx.doi.org/10.1007/s00704-002-0715-3.

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30

Wang, Dongdong, Shunlin Liang, Tao He, Yunyue Yu, Crystal Schaaf, and Zhuosen Wang. "Estimating daily mean land surface albedo from MODIS data." Journal of Geophysical Research: Atmospheres 120, no. 10 (2015): 4825–41. http://dx.doi.org/10.1002/2015jd023178.

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31

Zaiki, Masumi, Keiji Kimura, and Takehiko Mikami. "A statistical estimate of daily mean temperature derived from a limited number of daily observations." Geophysical Research Letters 29, no. 18 (2002): 39–1. http://dx.doi.org/10.1029/2001gl014378.

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32

Dall'Amico, M., and M. Hornsteiner. "A simple method for estimating daily and monthly mean temperatures from daily minima and maxima." International Journal of Climatology 26, no. 13 (2006): 1929–36. http://dx.doi.org/10.1002/joc.1363.

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33

Uzun, Sezgin. "The Effect of Temperature and Mean Cumulative Daily Light Intensity on Fruiting Behavior of Greenhouse-grown Tomato." Journal of the American Society for Horticultural Science 132, no. 4 (2007): 459–66. http://dx.doi.org/10.21273/jashs.132.4.459.

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Determinations were made of the effect of mean daily temperature and cumulative daily light intensity related to planting date on fruiting behavior of greenhouse-grown tomato (Lycopersicon esculentum Mill.). Time to first flowering (FT), flower bud number per cluster (BN/C), fruit number per cluster (FN/C), mean fruit weight, fruit growth period (FGP), and fruit production rate (FPR) in tomato were plotted against mean daily temperature (11 to 28 °C) and mean cumulative daily light intensity (2 to 8 MJ·m−2·d−1) obtained from different planting dates. The FT was negatively related to mean daily

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34

Muijen, M., I. M. Marks, J. Connolly, B. Audini, and G. McNamee. "The Daily Living Programme." British Journal of Psychiatry 160, no. 3 (1992): 379–84. http://dx.doi.org/10.1192/bjp.160.3.379.

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Patients with a serious mental illness requiring admission were randomised to home care or standard hospital care. Over the initial 18 months, 60 patients entered each group and were studied for a mean of 10 months. Home care reduced hospital use by 80%, with patients being admitted for a mean of 14 days, compared with 72 days for the standard group, but this bed-saving made no difference in direct treatment costs. Home care offers individualised treatment, and many patients require continuing support with the emphasis on areas such as finances and housing.

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35

Li, Qianmei, Qingyou He, and Chuqun Chen. "Retrieval of Daily Mean VIIRS SST Products in China Seas." Remote Sensing 13, no. 24 (2021): 5158. http://dx.doi.org/10.3390/rs13245158.

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Sea surface temperature (SST) is one of the most important factors in regulating air-sea heat flux and, thus, climate change. Most of current global daily SST products are derived from one or two transient measurements of polar-orbiting satellites, which are not the same to daily mean SST values. In this study, high-temporal-resolution SST measurements (32–40 snapshots per day) from a geostationary satellite, FengYun-4A (FY–4A), are used to analyze the diurnal variation of SST in China seas. The results present a sinusoidal pattern of the diurnal variability in SST, with the maximum value at 1

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36

Wang, Rehua, Yongjun Lin, Mao Chen, et al. "Effects of Daily Mean Temperature on Daily Hospital Admissions for Coronary Artery Disease: A Retrospective Study." Risk Management and Healthcare Policy Volume 17 (January 2024): 269–77. http://dx.doi.org/10.2147/rmhp.s444451.

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37

Shabuj, Mohammad Kamrul Hassan, Shadeka Chowdhury Moni, Chandan Kumar Shaha, Sanjoy Kumar Shaha, Abdul Mannan, and Md Shahidullah. "Gentamicin in Newborn Sepsis: Once Daily Dose versus Twice Daily Dose." Bangladesh Medical Research Council Bulletin 43, no. 2 (2018): 82–86. http://dx.doi.org/10.3329/bmrcb.v43i2.35188.

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Gentamicin is commonly used as first line drug in neonatal sepsis. It is usually used in combination with other drugs. It is a nephrotoxic and an ototoxic drug. Long term use causes renal failure and hearing impairment. Its efficacy depends on the peak concentration, and its toxicity is related to the trough concentration. There is no set protocol of using gentamicin in neonate in Bangladesh, whether it should be used once daily or twice, it is till debatable in this perspective. In daily practice, it is not followed up trough and peak concentration of gentamicin, so it is not known the renal

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38

Sertel, E., H. K. Cigizoglu, and D. U. Sanli. "Estimating Daily Mean Sea Level Heights Using Artificial Neural Networks." Journal of Coastal Research 243 (May 2008): 727–34. http://dx.doi.org/10.2112/06-742.1.

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39

Hussein, Maged M. A. "Mean Daily Variability of Energy Fluxes Above Alexandria Eastern Harbor." ATHENS JOURNAL OF SCIENCES 8, no. 3 (2021): 183–98. http://dx.doi.org/10.30958/ajs.8-3-2.

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Mean daily variability of latent heat (E), sensible heat (H), net long wave (Lwnet), net short wave, and net flux of surface heat balance were estimated from hourly sea surface water temperature (SST) and meteorological time series obtained for three months during summer season (2019) in Alexandria Eastern Harbor (AEH), Egypt. Latent and sensible heat were not in phase and had their maximum 181.12 W/m2 (5:00 PM), 16.5 W/m2 (5:00 AM) and minimum 103.64 W/m2 (8:00 AM), -12.14 W/m2 (3:00 PM), resulting in Bowen ration of -0.11 and 0.09, respectively. The loss of heat by evaporation therefore pred

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40

Pires, J. C. M., F. G. Martins, S. I. V. Sousa, M. C. M. Alvim-Ferr, and M. C. Pereira. "Prediction of the Daily Mean PM10 Concentrations Using Linear Models." American Journal of Environmental Sciences 4, no. 5 (2008): 445–53. http://dx.doi.org/10.3844/ajessp.2008.445.453.

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41

Yoon, Sanghoo. "Generating high resolution of daily mean temperature using statistical models." Journal of the Korean Data and Information Science Society 27, no. 5 (2016): 1215–24. http://dx.doi.org/10.7465/jkdi.2016.27.5.1215.

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42

Xu, Jiyao, Wenbin Wang, and Hong Gao. "The longitudinal variation of the daily mean thermospheric mass density." Journal of Geophysical Research: Space Physics 118, no. 1 (2013): 515–23. http://dx.doi.org/10.1029/2012ja017918.

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43

Reddy, T. A., S. Jumpa, and G. Y. Saunier. "Effective daily mean position of the sun for solar ponds." Solar Energy 37, no. 1 (1986): 75–77. http://dx.doi.org/10.1016/0038-092x(86)90110-6.

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44

Garen, David C., Gregory L. Johnson, and Clayton L. Hanson. "MEAN AREAL PRECIPITATION FOR DAILY HYDROLOGIC MODELING IN MOUNTAINOUS REGIONS." Journal of the American Water Resources Association 30, no. 3 (1994): 481–91. http://dx.doi.org/10.1111/j.1752-1688.1994.tb03307.x.

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45

Potter, Kenneth N., and Jimmy R. Williams. "Predicting Daily Mean Soil Temperatures in the EPIC Simulation Model." Agronomy Journal 86, no. 6 (1994): 1006–11. http://dx.doi.org/10.2134/agronj1994.00021962008600060014x.

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46

Pavan, V., R. Tomozeiu, C. Cacciamani, and M. Di Lorenzo. "Daily precipitation observations over Emilia-Romagna: mean values and extremes." International Journal of Climatology 28, no. 15 (2008): 2065–79. http://dx.doi.org/10.1002/joc.1694.

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47

Real, António C., José Borges, and Carlos B. Oliveira. "Estimation of daily mean temperatures: an accurate method for the Douro Valley." Ciência e Técnica Vitivinícola 33, no. 2 (2018): 167–76. http://dx.doi.org/10.1051/ctv/20183302167.

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Air temperature data from many locations worldwide are only available as series of daily minima and maxima temperatures. Historically, several different approaches have been used to estimate the actual daily mean temperature, as only in the last two or three decades automatic thermometers are able to compute its actual value. The most common approach is to estimate it by averaging the daily minima and maxima. When only daily minima and maxima are available, an alternative approach, proposed by Dall’Amico and Hornsteiner in 2006, uses the two daily extremes together with next day minima tempera

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48

Joshi, Chandan, B. Sobha, and Vishwas Deep Joshi. "Search for Correlation between Solar Flare Count and Mean Solar Magnetic Field." Proceedings of the International Astronomical Union 13, S340 (2018): 77–78. http://dx.doi.org/10.1017/s1743921318001953.

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AbstractAn investigation for search of correlation between the daily observations of mean magnetic field and daily flare count number in different class is studied here. The daily observations for mean magnetic field presented here are taken by Wilcox Solar observatory and daily flare count in different X-ray class is provided by National Centers For Environmental Information.

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49

Benseñor, IJM, PA Lotufo, D. Mion-Jr, and MA Martins. "Blood Pressure Behaviour in Chronic Daily Headache." Cephalalgia 22, no. 3 (2002): 190–94. http://dx.doi.org/10.1046/j.1468-2982.2002.00340.x.

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The objective was to examine the association between high blood pressure (BP) and chronic daily headache using 24-h ambulatory blood pressure monitorization (24-h ABPM). This was a cross sectional study in an out-patient clinic. Women were selected among patients referred for first evaluation, 62 with chronic daily headache and 57 without chronic daily headache. The main outcome measures were mean office systolic and diastolic blood pressure (BP), mean systolic and diastolic daytime and night-time BP and BP load, and mean systolic and diastolic nocturnal fall. Office systolic BP was 138.2 mmHg

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50

Walters, Kellie J., Sean Tarr, and Roberto G. Lopez. "Modeling purple basil, sage, spearmint, and sweet basil responses to daily light integral and mean daily temperature." PLOS ONE 18, no. 11 (2023): e0294905. http://dx.doi.org/10.1371/journal.pone.0294905.

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Mean daily temperature (MDT) and daily light integral (DLI) can interact to influence growth and development of plants. Our objectives were to determine 1) the extent DLI and MDT influence growth and development of purple basil ‘Dark Opal’ (Ocimum basilicum), sage ‘Extrakta’ (Salvia officinalis), spearmint ‘Spanish’ (Mentha spicata), and sweet basil ‘Nufar’ (Ocimum basilicum) and 2) the influence on purple basil color. Young plants were transplanted into hydroponic systems in five greenhouse compartments with MDT set points of 23, 26, 29, 32, or 35°C and DLIs from 5 to 19 mol·m‒2·d‒1, respecti

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