Geoscience Reference
In-Depth Information
Max
Bright
Temp
Number of
observations
Occurrence
Occ+MBT
R
A
b
R
a
b
R
2000 September
206
0.61
6.08
14.7 -0.35
-5.84
270.0
0.61
October
203
0.58
4.96
3.3 -0.44
-6.95
325.7
0.59
November
207
0.41
5.80
66.1 -0.40 -12.93
546.6
0.45
December
206
0.41
7.03
43.0 -0.48 -20.94
777.4
0.58
2001 January
201
0.52
12.68
-103.0
-0.67
-31.62 1032.7
0.69
February
200
0.31
6.49
64.3
-0.66
-29.78
944.3
0.67
March
198
0.46
7.37
65.1 -0.49 -23.09
798.6
0.53
April
196
0.69
9.47
-15.0
-0.64
-15.80
550.7
0.71
May
193
0.66
7.40
17.9 -0.39
-8.12
297.9
0.66
June
198
7.55
4.3 -0.57
-7.90
238.6
0.66
0.67
July
196
0.69
8.29
3.4 -0.48
-4.69
167.5
0.69
August
197
0.38
4.24
9.6 -0.06
-0.37
33.7
0.38
Season 2000-2001
2401
0.78
8.22
3.7
-0.62
-17.25
619.3
0.81
Annual Pmm
167
0.81
11.87
-659.7 -0.40 -60.01
3729.6
0.82
Obs. = number of stations used
Occ = monthly occurrences of clouds possessing cold summits
MaxBrightTemp = monthly maximum brightness temperature
Occ+MBT = multiple regression with occurrences and MaxBrightTemp
r = correlation; a and b = coefficients of linear straight lines.
Table 3.2.
Correlation coefficients (r) between rainfall measured on the ground
and data produced by infrared GOES; coefficients with a value more
than 0.60 are highlighted in bold
Comparisons made between precipitation and infrared GOES satellite data in
Mato Grosso for the period from September 2000 to August 2001 show that rainfall
had a stronger correlation with clouds that had a cold summit (r = 0.78) than with
maximum temperatures (r = -0.62). Precipitation estimation by satellite has
therefore been slightly adapted in this region, a region that does not possess many
conventional climatological stations. If we think of the two different methods that
were introduced at the beginning of this section, the technique of precipitation
estimation by satellite favors the use of the first method, as the second method only
slightly increases multiple correlations (r = 0.82).
