A Robust Test for OLS Trends in Daily Temperature Data

2015 ◽  
Author(s):  
Jamal Munshi
Keyword(s):  
Temperature Data ◽  
Daily Temperature ◽  
Robust Test

scholarly journals Estimation of seasonal boundaries using temperature data: a case of northwest part of Bangladesh

2020 ◽  
Vol 6 (1) ◽  
pp. 50-62
Author(s):  
Syed Mustafizur Rahman ◽  
Syed Mahbubur Rahman ◽  
Md. Shuzon Ali ◽  
Md. Abdullah Al Mamun ◽  
Md. Nezam Uddin
Keyword(s):  
Spectral Analysis ◽  
Crop Productivity ◽  
Temperature Data ◽  
Daily Temperature ◽  
Temperature Cycle ◽  
Local Climate ◽  
Higher Power ◽  
Cycle Plays ◽  
Maximum Temperatures ◽  
Harmonic Analyses

Abstract Seasons are the divisions of the year into months or days according to the changes in weather, ecology and the intensity of sunlight in a given region. The temperature cycle plays a major role in defining the meteorological seasons of the year. This study aims at investigating seasonal boundaries applying harmonic analysis in daily temperature for the duration of 30 years, recorded at six stations from 1988 to 2017, in northwest part of Bangladesh. Year by year harmonic analyses of daily temperature data in each station have been carried out to observe temporal and spatial variations in seasonal lengths. Periodic nature of daily temperature has been investigated employing spectral analysis, and it has been found that the estimated periodicities have higher power densities of the frequencies at 0.0027 and 0.0053 cycles/day. Some other minor periodic natures have also been observed in the analyses. Using the frequencies between 0.0027 to 0.0278 cycles/day, the observed periodicities in spectral analysis, harmonic analyses of minimum and maximum temperatures have found four seasonal boundaries every year in each of the stations. The estimated seasonal boundaries for the region fall between 19-25 February, 19-23 May, 18-20 August and 17-22 November. Since seasonal variability results in imbalance in water, moisture and heat, it has the potential to significantly affect agricultural production. Hence, the seasons and seasonal lengths presented in this research may help the concerned authorities take measures to reduce the risks for crop productivity to face the challenges arise from changing climate. Moreover, the results obtained are likely to contribute in introducing local climate calendar.

scholarly journals The Association between the Frequency of Rhegmatogenous Retinal Detachment and Atmospheric Temperature

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Dong Yoon Kim ◽  
Hyeseong Hwang ◽  
Jae-Hyung Kim ◽  
Byung Gil Moon ◽  
Sung Min Hyung ◽  
...  
Keyword(s):  
Retinal Detachment ◽  
Rhegmatogenous Retinal Detachment ◽  
Experimental Studies ◽  
Atmospheric Temperature ◽  
Temperature Data ◽  
Daily Temperature ◽  
University Hospital ◽  
Daily Temperature Range ◽  
Temperature Range ◽  
Monthly Average

Rhegmatogenous retinal detachment (RRD) frequency was observed to be higher with an increase in the daily temperature range. This showed that a wide daily range of temperature, rather than the absolute value of the temperature, is associated with the occurrence of RRD. Purpose. To investigate the association between the frequency of rhegmatogenous retinal detachment (RRD) and the atmospheric temperature. Method. A retrospective review of consecutive eyes that had undergone primary RRD surgery from 1996 to 2016 at Chungbuk National University Hospital was conducted. Temperature data (highest, lowest, and mean daily temperatures and daily temperature range) in Chungbuk Province were obtained from the Korean Meteorological Administration database. We investigated the relationship between the daily temperature range and the frequency of RRD surgery. We also analyzed the association between various temperature data and the frequency of RRD surgery. Result. There were 1,394 RRD surgeries from 1996 to 2016. Among them, 974 eyes were included in this study. The monthly average number of RRD operations showed a bimodal peak (in April and October) throughout the year. With the same tendency as the frequency of RRD, the monthly average of the daily temperature range over 1 year also showed a bimodal peak in April and October. There was a significant positive correlation between the monthly average of the daily temperature range and the number of RRD surgeries (r = 0.297, P<0.001). However, there were no associations between RRD frequency and the mean temperature, highest temperature, and lowest temperature. Conclusion. The higher the daily temperature range, the higher was the RRD frequency observed. We speculated that dynamic changes in temperature during the day may affect degrees in chorioretinal adhesion and liquefaction of the vitreous, which may eventually result in retinal detachment. Therefore, further experimental studies on the correlation between temperature changes and retinal detachment are needed.

scholarly journals Evaluation of NASA satellite- and assimilation model-derived long-term daily temperature data over the continental US

2008 ◽  
Vol 148 (10) ◽  
pp. 1574-1584 ◽  
Author(s):  
Jeffrey W. White ◽  
Gerrit Hoogenboom ◽  
Paul W. Stackhouse ◽  
James M. Hoell
Keyword(s):  
Temperature Data ◽  
Daily Temperature ◽  
Assimilation Model

scholarly journals Automation: A Step toward Improving the Quality of Daily Temperature Data Produced by Climate Observing Networks*

2009 ◽  
Vol 26 (7) ◽  
pp. 1246-1260 ◽  
Author(s):  
Christopher A. Fiebrich ◽  
Kenneth C. Crawford
Keyword(s):  
Data Quality ◽  
Observation Time ◽  
Temperature Data ◽  
Daily Temperature ◽  
National Weather Service ◽  
Climate Record ◽  
Daily Data ◽  
Oklahoma Mesonet ◽  
Weather Service

Abstract The research documented in this manuscript demonstrates that undeniable differences exist between values of daily temperature recorded by the National Weather Service Cooperative Observer Program network and data recorded by the Oklahoma Mesonet. Because of this fact, a transition to automated observations would have the effect of changing the climate record for Oklahoma. However, the change to automated observations would produce an improvement in overall data quality. A sampling of daily data from the two networks was compared for closely spaced station pairs for the period 1 January 2003 through 31 December 2005. As a result, a host of observer errors were discovered (including transcription errors, incorrectly resetting the manual sensors, and delaying the observation time). These errors created large daily differences that sometimes exceeded 5°C between the two datasets. More than 55% of the paired observations were found to differ by more than 1°C.

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