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

Latest issue

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                                 #
#--------------------------------------------------------------------#

Archive

Kalman filter for the standard and combined methods

Latest issue

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                                 #
#--------------------------------------------------------------------#

Archive

Kalman filter for the McNish&Lincoln method