scholarly journals Forecasting maximum and minimum temperature over airports with special relevance to aviation in flight planning

MAUSAM ◽  
2021 ◽  
Vol 50 (2) ◽  
pp. 121-128
Author(s):  
R. SURESH
Keyword(s):  
Kalman Filtering ◽  
Adaptive Filtering ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Coastal Station ◽  
Flight Planning ◽  
Hot Weather ◽  
Auto Regression ◽  
Special Relevance ◽  
Better Than

Forecasting of maximum temperature and minimum temperature for aviation and non-aviation purpose has been attempted through auto regression and by employing the method of adaptive filtering and Kalman filtering during the hot weather season (March to May) over Madras. The filtering techniques have been outlined and the results are compared with the method of climatology and persistence. The Kalman filter using the model output of adaptive filtering. forecasts well the day-to-day variability of maximum and minimum temperature during hot weather season over Madras with an efficiency close to 90%. As the model performs reasonably well over Madras. a coastal station. the same has been tried over Trichy (300 km southwest of Madras), an inland airport station in Tamilnadu to ascertain its efficacy. The efficiency is better than 90% in predicting maximum and minimum temperature within an accuracy of 2°C).

scholarly journals On adaptive filtering for high dimensional systems under parameter uncertainty and its application to satellite data assimilation in oceanography

2016 ◽  
Vol 13 (2) ◽  
pp. 18-40
Author(s):  
S, Hoàng ◽  
R. Baraille ◽  
O. Talagrand ◽  
X. Carton ◽  
P.De Mey
Keyword(s):  
Kalman Filter ◽  
Kalman Filtering ◽  
Adaptive Filtering ◽  
Adaptive Filter ◽  
High Efficiency ◽  
Ocean Model ◽  
Numerical Estimation ◽  
Oceanic Circulation ◽  
Error Statistics ◽  
Better Than

In this paper, the adaptive filtering theory, recently proposed and developed the authors of present work [1-9] for stochastic, encountered in the field of data as simulation in meteorology and oceanography, is reviewed. Several important questions on numerical estimation og the gain matrix, model reduction, structural  choices for the gain, filter stability… are discussed. We show the connections of present approach with a standard Kalman filtering. Adaptive filter is implemented along with a Kalman filtering. Adaptive filter is implemented along with a Kalman filter and standard Newton relation method on the four-layer adiabatic Miami Isopycnical Co-ordinate Ocean Model (MICOM) to produce the estimate for the deep oceanic circulation using assimilate synthetic observations of surface height. Numerical results justify high efficiency of the adaptive filter whose performance is slightly better than that of a Kalman filter due to  impossibility to correctly specify the error statistics in a Kalman filter.

Comparison of Adaptive Factors in Kalman Filters on Navigation Results

2005 ◽  
Vol 58 (3) ◽  
pp. 471-478 ◽  
Author(s):  
Yuanxi Yang ◽  
Weiguang Gao
Keyword(s):  
Kalman Filtering ◽  
Adaptive Filtering ◽  
Kalman Filters ◽  
Variance Component ◽  
Kinematic Model ◽  
Component Ratio ◽  
Model Predictions ◽  
Comparison And Analysis ◽  
Better Than

The quality of kinematic navigation and positioning depends on the quality of the model describing the vehicle movements and the reliability of the observations. An adaptive Kalman filtering is introduced. Three kinds of adaptive factors based on the discrepancy between the geometrical positions and the kinematic model predictions and a variance component ratio between model predictions and observations are described. A new exponential adaptive factor is established. The theoretical curves of the adaptive factors are drawn and a practical example is given. The errors of four adaptive filtering results and the corresponding curves of the adaptive factors are also drawn. It is shown, by comparison and analysis, that all of the four adaptive factors can control the influences of the vehicle disturbances in movements on the navigation results. The results derived by the adaptive factor constructed by the variance component ratio are slightly better than those derived by other adaptive factors.

scholarly journals Spatiotemporal Evolution of Fractional Vegetation Cover and Its Response to Climate Change Based on MODIS Data in the Subtropical Region of China

2021 ◽  
Vol 13 (5) ◽  
pp. 913
Author(s):  
Hua Liu ◽  
Xuejian Li ◽  
Fangjie Mao ◽  
Meng Zhang ◽  
Di’en Zhu ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Distribution Area ◽  
Spatiotemporal Pattern ◽  
Climate Factors ◽  
Important Indicator ◽  
Fractional Vegetation Cover ◽  
Annual Minimum Temperature ◽  
Total Study Area

The subtropical vegetation plays an important role in maintaining the structure and function of global ecosystems, and its contribution to the global carbon balance are receiving increasing attention. The fractional vegetation cover (FVC) as an important indicator for monitoring environment change, is widely used to analyze the spatiotemporal pattern of regional and even global vegetation. China is an important distribution area of subtropical vegetation. Therefore, we first used the dimidiate pixel model to extract the subtropical FVC of China during 2001–2018 based on MODIS land surface reflectance data, and then used the linear regression analysis and the variation coefficient to explore its spatiotemporal variations characteristics. Finally, the partial correlation analysis and the partial derivative model were used to analyze the influences and contributions of climate factors on FVC, respectively. The results showed that (1) the subtropical FVC had obvious spatiotemporal heterogeneity; the FVC high-coverage and medium-coverage zones were concentratedly and their combined area accounted for more than 70% of the total study area. (2) The interannual variation in the average subtropical FVC from 2001 to 2018 showed a significant growth trend. (3) In 76.28% of the study area, the regional FVC showed an increasing trend, and the remaining regional FVC showed a decreasing trend. However, the overall fluctuations in the FVC (increasing or decreasing) in the region were relatively stable. (4) The influences of climate factors to the FVC exhibited obvious spatial differences. More than half of all pixels exhibited the influence of the average annual minimum temperature and the annual precipitation had positive on FVC, while the average annual maximum temperature had negative on FVC. (5) The contributions of climate changes to FVC had obvious heterogeneity, and the average annual minimum temperature was the main contribution factor affecting the dynamic variations of FVC.

scholarly journals Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Evergreen Forest ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Study Region ◽  
Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

scholarly journals The effect of average temperature on suicide rates in five urban California counties, 1999–⁠2019: an ecological time series analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sierra Cheng ◽  
Rebecca Plouffe ◽  
Stephanie M. Nanos ◽  
Mavra Qamar ◽  
David N. Fisman ◽  
...  
Keyword(s):  
Public Health ◽  
Suicide Rate ◽  
Minimum Temperature ◽  
The United States ◽  
Additive Models ◽  
Maximum Temperature ◽  
Mortality Data ◽  
Average Temperature ◽  
Suicide Rates ◽  
Average Maximum

Abstract Background Suicide is among the top 10 leading causes of premature morality in the United States and its rates continue to increase. Thus, its prevention has become a salient public health responsibility. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. The purpose of the present study is to evaluate the association between average temperature and suicide rates in the five most populous counties in California using mortality data from 1999 to 2019. Methods Monthly counts of death by suicide for the five counties of interest were obtained from CDC WONDER. Monthly average, maximum, and minimum temperature were obtained from nCLIMDIV for the same time period. We modelled the association of each temperature variable with suicide rate using negative binomial generalized additive models accounting for the county-specific annual trend and monthly seasonality. Results There were over 38,000 deaths by suicide in California’s five most populous counties between 1999 and 2019. An increase in average temperature of 1 °C corresponded to a 0.82% increase in suicide rate (IRR = 1.0082 per °C; 95% CI = 1.0025–1.0140). Estimated coefficients for maximum temperature (IRR = 1.0069 per °C; 95% CI = 1.0021–1.0117) and minimum temperature (IRR = 1.0088 per °C; 95% CI = 1.0023–1.0153) were similar. Conclusion This study adds to a growing body of evidence supporting a causal effect of elevated temperature on suicide. Further investigation into environmental causes of suicide, as well as the biological and societal contexts mediating these relationships, is critical for the development and implementation of new public health interventions to reduce the incidence of suicide, particularly in the face increasing temperatures due to climate change.

scholarly journals Effects of Cropland Expansion on Temperature Extremes in Western India from 1982 to 2015

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 489
Author(s):  
Jinxiu Liu ◽  
Weihao Shen ◽  
Yaqian He
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Land Cover ◽  
Minimum Temperature ◽  
Negative Impact ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Western India

India has experienced extensive land cover and land use change (LCLUC). However, there is still limited empirical research regarding the impact of LCLUC on climate extremes in India. Here, we applied statistical methods to assess how cropland expansion has influenced temperature extremes in India from 1982 to 2015 using a new land cover and land use dataset and ECMWF Reanalysis V5 (ERA5) climate data. Our results show that during the last 34 years, croplands in western India increased by ~33.7 percentage points. This cropland expansion shows a significantly negative impact on the maxima of daily maximum temperature (TXx), while its impacts on the maxima of daily minimum temperature and the minima of daily maximum and minimum temperature are limited. It is estimated that if cropland expansion had not taken place in western India over the 1982 to 2015 period, TXx would likely have increased by 0.74 (±0.64) °C. The negative impact of croplands on reducing the TXx extreme is likely due to evaporative cooling from intensified evapotranspiration associated with croplands, resulting in increased latent heat flux and decreased sensible heat flux. This study underscores the important influences of cropland expansion on temperature extremes and can be applicable to other geographic regions experiencing LCLUC.

Observations on 287 thunder-storms made at highfield house, near Nottingham, during the last nine years

1851 ◽  
Vol 5 ◽  
pp. 957-957
Keyword(s):  
Minimum Temperature ◽  
Maximum Temperature ◽  
Tabular Form ◽  
The Hours ◽  
The Mean ◽  
Atmospheric Phenomena ◽  
Rotatory Motion

The thunder-storms referred to in this communication are recorded in a tabular form., arranged according to their dates. In this table are given the date; the hour of the commencement of the storm; the mean height of the barometer to tenths of an inch; whether it is rising, stationary, or falling; the direction of the wind before the storm, during its continuance, and after its cessation; the maximum temperature on the day of the storm and on the day after; the minimum temperature on the night before and on the night after; and general remarks on the storms. This table is followed by remarks on particular storms recorded in it. In conclusion the author gives the results of his observations with reference to the number of storms in each year; the number in each month, with the hours at which they mostly occur in particular months; the number that have occurred with a rising, stationary, or falling barometer; the number in respect to the direction of the wind and of the current in which the storms moved; the number of storms that have occurred at the various heights of the maximum, and also of the minimum thermometer; the number in which the peculiar breeze that suddenly springs up on the commencement of thunder-storms has been well marked; the change in the direction of some of these storms, and indications of rotatory motion; and finally, the different atmospheric phenomena which have accompanied these storms.

Effect of environment factors on milk production and lactation length under different seasons in crossbred cattle

2015 ◽  
Author(s):  
S.S. Mote ◽  
D.S. Chauhan* and Nilotpal Ghosh1
Keyword(s):  
Milk Yield ◽  
Minimum Temperature ◽  
Summer Season ◽  
Climatic Variables ◽  
Coefficient Of Determination ◽  
Maximum Temperature ◽  
Temperature Minimum ◽  
Crossbred Cattle ◽  
Lactation Length ◽  
Significant Regression

The study was undertaken to evaluate the effect of different macro climatic variables on lactation milk yield and lactation length of Holdeo (Holstein Friesian x Deoni) crossbred cattle. Milk data of 145 Holdeo crossbred cows with 619 lactation records and the meteorological data over a period of 15 years (1995-2009) were obtained from Cattle Cross Breeding Project, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani and University Meteorological Observatory, respectively. It was observed that maximum temperature has significant correlation with lactation milk yield; whereas maximum temperature, minimum temperature, sunshine hours and wind speed have significant correlation with lactation length. Regression analysis indicated that all the climatic variables except minimum temperature exhibited significant regression results with lactation milk yield, and maximum temperature, minimum temperature and maximum humidity have significant regression results with lactation length. All the climatic variables considered in the study accounted for 75 % and 65 % direct variation on lactation milk yield and lactation length, respectively, as verified by the value of coefficient of determination (R2). It was observed that lactation milk yield (1136.56 + 21.04 kg.) and lactation length (295.29 + 5.51 days) were highest among the cows calved during winter season as compared to rainy and summer season. All the climatic variables considered in the study accounted for 57% , 56 % and 48 % direct variation on milk yield and 68% , 53 % and 46 % direct variation on lactation length in rainy, winter and summer season, respectively, as verified by the value of coefficient of determination (R2). This research indicated that crossbred cows were sensitive to seasonal changes on their lactation performance. The optimum ranges of temperature; humidity and THI for better performance of crossbred in subtropical region of India were found to be 19-26 oC, 52-66 % and 65-68 %, respectively.

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