Kalman filter improvement of the monthly smoothed Sunspot Number prediction
Source |
SIDC (RWC-Belgium)
|
Frequency |
Monthly
|
Format |
Plain text
|
Mail header |
Kalman filter improvement of the monthly smoothed Sunspot Number prediction
|
SIDC code |
kalfil
|
Issued: 2022 Mar
#--------------------------------------------------------------------#
# MONTHLY REPORT OF THE INTERNATIONAL SUNSPOT NUMBER #
# FROM THE SOLAR INFLUENCES DATA ANALYSIS CENTER (RWC-BELGIUM) #
#--------------------------------------------------------------------#
Kalman filter improvement of the monthly smoothed Sunspot Number prediction
by SIDC classical method (SM) and by the Combined method (CM).
Predictions of SM and CM methods were taken from http://www.sidc.be/products/ri
The last provisional value, calculated for August 2021:35.3(+-5%)
KFSM KFCM
2021 Sep 40 2021 Sep 41.2
Oct 43.3 Oct 46.6
Nov 45.5 Nov 49.8
Dec 52.8 (4) Dec 55.9 (5)
2022 Jan 59.7 (5) 2022 Jan 60.8 (5)
Feb 67.8 (7) Feb 65.2 (6)
Mar 76.6 (8) Mar 69.5 (8)
Apr 85.9 (10) Apr 74.3 (9)
May 95.2 (12) May 79 (10)
Jun 104 (14) Jun 83.7 (12)
Jul 114 (16) Jul 88.6 (13)
Aug 123 (18) Aug 92.8 (14)
Sep 134 (20) Sep 96.2 (16)
Oct 145 (23) Oct 97.7 (16)
Nov 159 (25) Nov 99.8 (17)
Dec 175 (29) Dec 102 (18)
2023 Jan 193 (32) 2023 Jan 103 (19)
Feb 212 (36) Feb 106 (20)
KFSM: Kalman filter prediction correction for SM. Standard deviation
of estimates errors are given in brackets.
KFCM: Kalman filter prediction correction for CM. Standard deviations
of estimates errors are given in brackets.
The improvement of the predictions is provided by applying an adaptive Kalman
filter to obtained medium-term predictions using the last six monthly mean
values of sunspot numbers, which cover the six months between the last available
value of the 13-month running mean (the starting point for the predictions)
and the current time. The proposed technique reduces stochastic component of
the last six monthly mean sunspot numbers that give significant information
about cycle evolution and provides effective estimate of sunspot activity
at the current time. This estimate becomes the new starting point for
the prediction updating that is shifted six month ahead in comparison with
the last observed 13-month running mean and provides an increase of prediction
accuracy for medium-term methods.
Correction technique was proposed by T. Podladchikova and R. Van der Linden and
improves medium term prediction methods as they are monthly updated using the last
available observations of smoothed sunspot numbers.
ref.: T. Podladchikova, R. Van der Linden, 2011: "A Kalman Filter Technique for Improving
Medium-Term Predictions of the Sunspot Number". Solar Physics. DOI: 10.1007/s11207-011-9899-y
#--------------------------------------------------------------------#
# Solar Influences Data analysis Center - RWC Belgium #
# Royal Observatory of Belgium #
# Fax : 32 (0) 2 373 0 224 #
# Tel.: 32 (0) 2 373 0 491 #
#--------------------------------------------------------------------#
# For more information, comments and suggestions write to #
# Ronald Van der Linden ronald@oma.be, #
# Tanya Podladchikova tatyana@oma.be #
#--------------------------------------------------------------------#
Kalman filter for the standard and combined methods
Issued: 2022 Mar
# MONTHLY REPORT OF THE INTERNATIONAL SUNSPOT NUMBER #
# FROM THE SOLAR INFLUENCES DATA ANALYSIS CENTER (RWC-BELGIUM) #
#--------------------------------------------------------------------#
Kalman filter improvement of the monthly smoothed Sunspot Number prediction
by McNish&Lincoln method (M&L). Predictions of M&L method were taken from
ftp://ftp.ngdc.noaa.gov/STP/space-weather/solar-data/solar-indices/sunspot-numbers/predicted
The last provisional value, calculated for August 2021:35.3(+-5%)
KFM&L
2021 Sep 38.4
Oct 42
Nov 45.2
Dec 51.3 (4)
2021 Jan 54.9 (5)
Feb 57.5 (6)
Mar 59.5 (7)
Apr 63.9 (8)
May 69.3 (10)
Jun 73.4 (11)
Jul 76.9 (12)
Aug 79.9 (13)
Sep 82.4 (14)
Oct 85.8 (15)
Nov 89.9 (17)
Dec 93.1 (18)
2023 Jan 95.5 (19)
Feb 99.5 (20)
KFM&L: Kalman filter prediction correction for McNish and Lincoln method.
Standard deviation of estimates errors are given in brackets.
The improvement of the predictions is provided by applying an adaptive Kalman
filter to obtained medium-term predictions using the last six monthly mean
values of sunspot numbers, which cover the six months between the last available
value of the 13-month running mean (the starting point for the predictions)
and the current time. The proposed technique reduces stochastic component of
the last six monthly mean sunspot numbers that give significant information
about cycle evolution and provides effective estimate of sunspot activity
at the current time. This estimate becomes the new starting point for
the prediction updating that is shifted six month ahead in comparison with
the last observed 13-month running mean and provides an increase of prediction
accuracy for medium-term methods.
Correction technique was proposed by T. Podladchikova and R. Van der Linden and
improves medium term prediction methods as they are monthly updated using the last
available observations of smoothed sunspot numbers.
ref.: T. Podladchikova, R. Van der Linden, 2011: "A Kalman Filter Technique for Improving
Medium-Term Predictions of the Sunspot Number". Solar Physics. DOI: 10.1007/s11207-011-9899-y
#--------------------------------------------------------------------#
# Solar Influences Data analysis Center - RWC Belgium #
# Royal Observatory of Belgium #
# Fax : 32 (0) 2 373 0 224 #
# Tel.: 32 (0) 2 373 0 491 #
#--------------------------------------------------------------------#
# For more information, comments and suggestions write to #
# Ronald Van der Linden ronald@oma.be, #
# Tanya Podladchikova tatyana@oma.be #
#--------------------------------------------------------------------#
Kalman filter for the McNish&Lincoln method