8.3.2 The Mathematical Simulation of the Influence of Initial
Parameters Random Uncertainties on the Exactness of the
Surface Temperature Retrieval T s
Calculating characteristics of the mathematical model reaction to randomly
specified uncertainties of values regulating the model is demanded for studying the
uncertainties’ impact on the exactness of remote retrieving of the surface temperature.
The approach based on Eqs. 8.14 and 8.15 is used for estimating the uncertainty
DT s
j
j, namely on the multiple modeling values Da 0 including in the Eq. 8.14 and
obeing to normal distribution with the zeroth mean value and fixed dispersion (the
mean square deviation is used in the computer program «Tsrnd» inspite the dispersion). Equations 8.7 and 8.8 are applied for calculating values T s .
Statistical characterisitics of uncertainties DT s , might be obtained in the program
with modeling uncertainty for every parameter separately or any combination of
parameters «Tsrnd». After specifying the needed set of parameters and their statistical characteristics 1,000 values of every parameter uncertainty are simulated with
the standard subprogram RND (random number digitizer), and the uncertainty DT s
j
j
is calculated, then statistical characteristics of the DT s
j
j are found. The following
values are the output on the screen:
– hystogram of the uncertainties DT s
j
j;
– statistical characteristics of the DT s
j
j.
and in file:
– numbers of every uncertainty values for plotting the histogram;
– statistical characteristics of the DT s
j
j.
8.4 Practice 7
8.4.1 Objectives
1. To study theoretical basis of the remore retrieving of the surface temperature.
2. To study basis of mathematical simulation of physical processes described with
the approach of statistical modeling and probability characteristics.
3. To obtain practical knowledge of applying the Monte-Carlo method for simulation of physical processes (case studies of initial data uncertainties’ impact on
the exactness of the remote surface temperature retrieval).
4. To compare application of two approaches (“deterministical” and “statistical”
with the Monte-Carlo method) for estimation of the initial data uncertainty
impact on the exactness of the remote surface temperature retrieval
5. To obtain numerical characteristics determining initial data uncertainties impact
on the exactness of the remote surface temperature retrieval as a result of
operating with computer numerical experiments.
78
8 Study of Depending the Uncertainty of the Remote Surface Temperature
Parameters Random Uncertainties on the Exactness of the
Surface Temperature Retrieval T s
Calculating characteristics of the mathematical model reaction to randomly
specified uncertainties of values regulating the model is demanded for studying the
uncertainties’ impact on the exactness of remote retrieving of the surface temperature.
The approach based on Eqs. 8.14 and 8.15 is used for estimating the uncertainty
DT s
j
j, namely on the multiple modeling values Da 0 including in the Eq. 8.14 and
obeing to normal distribution with the zeroth mean value and fixed dispersion (the
mean square deviation is used in the computer program «Tsrnd» inspite the dispersion). Equations 8.7 and 8.8 are applied for calculating values T s .
Statistical characterisitics of uncertainties DT s , might be obtained in the program
with modeling uncertainty for every parameter separately or any combination of
parameters «Tsrnd». After specifying the needed set of parameters and their statistical characteristics 1,000 values of every parameter uncertainty are simulated with
the standard subprogram RND (random number digitizer), and the uncertainty DT s
j
j
is calculated, then statistical characteristics of the DT s
j
j are found. The following
values are the output on the screen:
– hystogram of the uncertainties DT s
j
j;
– statistical characteristics of the DT s
j
j.
and in file:
– numbers of every uncertainty values for plotting the histogram;
– statistical characteristics of the DT s
j
j.
8.4 Practice 7
8.4.1 Objectives
1. To study theoretical basis of the remore retrieving of the surface temperature.
2. To study basis of mathematical simulation of physical processes described with
the approach of statistical modeling and probability characteristics.
3. To obtain practical knowledge of applying the Monte-Carlo method for simulation of physical processes (case studies of initial data uncertainties’ impact on
the exactness of the remote surface temperature retrieval).
4. To compare application of two approaches (“deterministical” and “statistical”
with the Monte-Carlo method) for estimation of the initial data uncertainty
impact on the exactness of the remote surface temperature retrieval
5. To obtain numerical characteristics determining initial data uncertainties impact
on the exactness of the remote surface temperature retrieval as a result of
operating with computer numerical experiments.
78
8 Study of Depending the Uncertainty of the Remote Surface Temperature