A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Physics, Khulna University of Engineering and Technology. Shibendra Shekher Sikder, Department of Physics, Khulna University of Engineering and Technology, for his cooperation and inspiration during this work.
ABSTRACT
Introduction
Composite temperature anomalies in La Niña years are almost opposite to El Niño composites:. negative temperature anomalies associated with La Niña events lasted from the current monsoon season to the following year's pre-monsoon season. The importance of the warming trends of the lowest annual temperature for the urban heat island effect is also discussed.
Literature Review
Different Seasons
- Pre -monsoon
- Winter season
- Dry Bulb Temperature (DBT)
- Wet Bulb Temperature (WBT)
- Measurement of wet and dry bulb temperature
- Surface Temperature
- Highest temperature
- Lowest Temperatures
When people refer to the temperature of the air, they are usually referring to its DBT. In the case of the lowest temperature recorded, there is a strong north-south gradient across the peninsula and also to the northwest.
Weather Research & Forecasting (WRF) Model
- Microphysics schemes in WRF-ARW Model
- Kessler Scheme
- Lin et al. Scheme
- WSM 3-class scheme
- Ferrier scheme
- WRF Single-moment 6-class (WSM6) scheme
- Thompson Scheme
- WRF double moment 5-class (WDM5) scheme
- WRF double-moment 6-class (WDM6) scheme
- Cumulus Parameterization
- Kain-Fritsch (KF) scheme
- Betts-Miller-Janjic (BMJ) scheme
- Planetary Boundary Layer (PBL) Parameterizations
- Yonsei University (YSU) scheme
- Mercator Projection
- Arakawa Staggered C-Grid
The influence of the small-scale eddies on large-scale atmospheric circulations can be included in the model equations. The development of the Mercator projection marked a major breakthrough in nautical cartography of the 16th century.
Methodology
- Model Setup
- Model Domain and Configuration
- Root Mean Square Error (RMSE)
- Mean Absolute Error (MAE)
- Coefficient of Correlation (CC)
Root Mean Square Error (RMSE) (also called root mean square deviation, RMSD) is a frequently used measure of the difference between values predicted by a model and the values actually observed from the environment being modeled. The MAE measures the average size of the errors in a set of forecasts without considering their direction. The MAE is the average over the verification sample of the absolute values of the differences between the forecast and the corresponding observation.
As the name suggests, the mean absolute error is an average of the absolute errors, where is the prediction and is the true value. The ratio between the explained variation and the total variation is called the coefficient of determination. If there is zero explained variation (ie the total variation is completely unexplained), this ratio is 0.
If there is no unexplained variation (ie, all the total variation is explained), the ratio is 1. The total variation of Y is defined as ( Y Y )2; that is, the sum of the squares of the deviations of the value of Y from the mean of Y. Y 0 1 and the measure of dispersion around the regression line Yon X is given by the quantity.
Results & Discussion
- Distribution of Observed and Simulated temperature in March 2010-2013
- Distribution of Observed and Simulated temperature in May 2010-2013
- Distribution of Observed and Simulated temperature of March 2014
- Distribution of Observed and Simulated temperature in April2014
- Distribution of Observed and Simulated temperature in May 2014
The simulated 107-day average temperature in April 2011 is found to be maximum in the west-northwest region of the country (Fig.4.1.3d). The simulated monthly average temperature is found to be minimum in the south-eastern region of the country and its value is 23.48oC in the Cox's Bazar region. The simulated 107-day average temperature in April 2012 was found to be maximum in the western part of the country (Fig.4.1.3c).
The simulated monthly average temperature is found minimum in the south-south-eastern region of the country and its value is 23.1oC at Kutubdia region. The monthly average temperature in April is found maximum at Jessore, Khulna, Mongla and Khepupara regions and its value is 29.4oC at Jessore. The minimum monthly average temperature is found in northwestern and northeastern regions of the country and the minimum observed temperature at.
The simulated average temperature of 107 days in April 2013 is maximum in the western region of the country (Fig. 4.1.4d). The simulated average temperature of 107 days in May 2011 has the maximum in the western region of the country (Fig. 4.1.5d). The simulated average temperature of 107 days in May 2012 has the maximum in the western region of the country (Fig. 4.1.6c).
The simulated 107 day average temperature in May 2013 is found to be maximum in the western northwestern region of the country (Fig.4.1.6d). The monthly average temperature is found minimum in the north-west and north-east regions and the average temperature increased from north-east part of the country to south-west region.
Root Mean Square Error (RMSE) of Temperature .1 RMSE of Temperature for March 2010-2013
- RMSE of Temperature for April 2010-2013
- RMSE of Temperature for May 2010-2013
- RMSE of Temperature for March 2014
- RMSE of Temperature for April 2014
- RMSE of Temperature for May 2014
The RMSE of the March 2012 temperature is found to be maximum (Fig. 4.2.1c) in the south-southeast region and in the Bhola region and its value is 4.79oC. RMSE of temperature is found minimum in Bogra, Rajshahi, Ishurdi, Tangail and Mymensingh regions and its value is 1.13oC in Bogra. The monthly mean RMSE of temperature increases from the central region to the southeastern region of the country.
The RMSE of temperature for the 107-day forecast in May 2012 is highest in the Southeast region and its value is 7.13oC in the Bhola region. The RMSE of temperature for the 107-day forecast in May 2013 is highest in the South-East and North regions and its value is 4.64oC in Bhola. The monthly mean RMSE of the simulated temperature is lowest in the southwestern region of the country.
The RMSE of simulated temperature is found to be minimum in the western region of the country. RMSE of temperature in April 107 days prediction is found significant maximum in South East region and its value at Teknaf is 6.74oC. The monthly mean RMSE of temperature is found minimum in Khepupara, Hatiya and Sandwip regions and its value is 0.83oC at Hatiya.
Mean Absolute Error (MAE) of Temperature .1 MAE of Temperature for March 2010-2013
- MAE of Temperature for April 2010-2013
- MAE of Temperature for May 2010-2013
- MAE of Temperature for March 2014
- MAE of Temperature for April 2014
The MAE of simulated temperature is found to be minimum in the northeastern region of the country and its value is 0.91oC at Srimangal. The MAE for temperature in April is found maximum in the South East region and its value is 4.72oC in Cox's Bazar region. The MAE for the temperature in April 2012 is found maximum in the south-southeast region and its value is 5.54oC at Bhola.
The MAE of temperature is found maximum in the southeast region and its value is 4.43oC at Cox's Bazar region. The MAE of temperature in May is found maximum in the south-southeast region and its value is 6.50oC at Cox's Bazar. The MAE of temperature in May is found maximum in the south-southeast region and its value is 6.93oC at Bhola.
In the central region, the mean MAE of temperature is maximum at Dhaka and its value is 1.62oC. The MAE of temperature is found in the maximum west-northwest region and its value is 2.88oC at Rajshahi. The MAE of temperature is found to be maximum in the north-northwest region and its value is 2.81oC at Rajshahi.
Correlation Coefficient (CC) between observed and simulated Temperature .1 Distribution of CC between observed and simulated temperature of March 2014
- Distribution of CC between observed and simulated temperature in April2014 The CC between observed and simulated temperature in April 2014 for 24, 48, 72 hours and
- Distribution of CC between observed and simulated temperature in May 2014 The CC between observed and simulated temperature in May 2014 for 24, 48, 72 hours and
The MAE of temperature for a 72-hour forecast (Fig. 4.3.6c) is found as a minimum in the southern region and its value is 0.67oC at Hatiya. The CC of temperature is minimum simulated in the northeastern region and its value is 0.53 at Sylhet. The minimum value of the CC is found in the southeastern and northeastern regions and its value is 0.12 at Teknaf.
CC between observed and simulated April 2014 hourly temperature is found maximum in West-Northwest and South-South regions and 107 days predicted by CC is found maximum in West-Northwest region of the country. CC distribution between observed and simulated 24-hour temperature for May 2014 is found maximum (Fig. 4.4.3a) in west-northwest region and its value is 0.82 in Chuadanga and Rajshahi region. The distribution of CC between the observed and simulated 48-hour temperature for May 2014 is found to be maximum (Fig. 4.4.3b) in the west-northwest and northeast regions and the maximum value is 0.72 in Chuadanga.
The distribution of CC between observed and 48-h simulated temperature for May 2014 is maximum (Fig. 4.4.3c) in the west-northwest and northeast regions, and its value is 0.78 at Chuadanga. Distribution of CC between observed and 107 days predicted temperature for May 2014 is maximum (Fig. 4.4.3d) in the west-northwest regions and its value is 0.66 at Dinajpur. From the analysis of CC between observed and simulated temperature in May 2014 for hours and 107 days prediction, it is found that CC is maximum in the west-northwest region and the minimum value is found in the central to south-southeast regions.
Conclusions
The observed monthly mean temperature is minimum in the northwestern region, but the forecast temperature for 107 days is minimum in the south-southeast and northeastern regions and the difference is within 5-6oC in the southeastern region. The correlation coefficients (CC) between observed and simulated temperature are found at a maximum for 24-hour lead-time forecasts in the month of March. The 107-day predicted monthly average temperature in May is found maximum in the west-northwest region of the country, while the observed temperature is found maximum in the south-west region.
For the 107-day forecast, the model simulated minimum monthly mean temperature is in the southeastern region of the country, but the observed minimum temperature is in the northeastern region. The RMSE distribution of temperature for the 107-day forecast stations is lowest in the central part of the country and increases in the surrounding areas during the 2010–2014 pre-monsoon season. In the central to southwestern region, the RMSE is the lowest for the 24, 48, and 72 h streamflow time forecasts in March, April, and May 2014, respectively.
The value of RMSE is less than 1oC in this region and it increases in the northwest and southeast regions. For 24-hour lead time forecast in March 2014, the CC is found greater than 0.92 throughout, except southeastern and northeastern regions of the country. As the time of the season progresses and also the forecast time increases, the CC decreases across the country and this decrease is significant in the southeastern region of the country.
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