as Madden Julian Oscillation, ENSO, Arctic Oscillation,
North Atlantic Oscillation and PDO (for more details, see
Sect. 11.2).
There are only a few studies that examined the changes in
WD activity (e.g. frequency) in a changing climate. For
example, Ridley et al. (2013) have investigated the future
projection of WD frequencies and the associated winter
snowfall using two simulations of regional climate model,
HadRM3 (i.e., HadRM3-H and HadRM3-E). HadRM3-H
projected an increased occurrence of WDs and an increase in
total winter snowfall by 2100, whereas HadRM3-E did not
indicate any significant future change in snowfall or
30
40
50
60
70
80
90
1958
1966
1974
1982
1990
1998
2006
2014
Std. dev. of GPHSV
ERA40
ERA Interim
Fig. 7.3 Time-series of standard deviations of daily filtered (4–15 days band-pass) index (in gpm units) computed for every DJFMA season using
200 hPa geopotential anomalies averaged over the region 58° E–62° E and 32° N–36° N, from ERA-40 (1958–2002) and ERA-Interim (1979–
2015) datasets. Adapted by permission from Krishnan et al. (2019)
Fig. 7.4 Time-series of standard deviation of daily filtered (4–15 days
band-pass) index (in gpm units) computed for every DJFMA season
using upper-level geopotential anomalies at 200 hPa averaged over the
region bounded by 58° E–62° E and 32° N–36° N, from the HIST
(orange), HISTNAT (blue) and RCP4.5 (red) experiments. A 5-year
moving average has been applied on the time-series. The first two
experiments (HIST and HISTNAT) are for the twentieth-century period
1900–2005. The HIST experiment includes both natural and anthropogenic forcing, whereas the HISTNAT includes only natural forcing.
The third experiment is performed in continuation with HIST into the
twenty-first century period 2006–2095, following the Representative
Concentration Pathway 4.5 (RCP4.5) scenario. Adapted by permission
from Krishnan et al. (2019)
150
S. Patwardhan et al.
North Atlantic Oscillation and PDO (for more details, see
Sect. 11.2).
There are only a few studies that examined the changes in
WD activity (e.g. frequency) in a changing climate. For
example, Ridley et al. (2013) have investigated the future
projection of WD frequencies and the associated winter
snowfall using two simulations of regional climate model,
HadRM3 (i.e., HadRM3-H and HadRM3-E). HadRM3-H
projected an increased occurrence of WDs and an increase in
total winter snowfall by 2100, whereas HadRM3-E did not
indicate any significant future change in snowfall or
30
40
50
60
70
80
90
1958
1966
1974
1982
1990
1998
2006
2014
Std. dev. of GPHSV
ERA40
ERA Interim
Fig. 7.3 Time-series of standard deviations of daily filtered (4–15 days band-pass) index (in gpm units) computed for every DJFMA season using
200 hPa geopotential anomalies averaged over the region 58° E–62° E and 32° N–36° N, from ERA-40 (1958–2002) and ERA-Interim (1979–
2015) datasets. Adapted by permission from Krishnan et al. (2019)
Fig. 7.4 Time-series of standard deviation of daily filtered (4–15 days
band-pass) index (in gpm units) computed for every DJFMA season
using upper-level geopotential anomalies at 200 hPa averaged over the
region bounded by 58° E–62° E and 32° N–36° N, from the HIST
(orange), HISTNAT (blue) and RCP4.5 (red) experiments. A 5-year
moving average has been applied on the time-series. The first two
experiments (HIST and HISTNAT) are for the twentieth-century period
1900–2005. The HIST experiment includes both natural and anthropogenic forcing, whereas the HISTNAT includes only natural forcing.
The third experiment is performed in continuation with HIST into the
twenty-first century period 2006–2095, following the Representative
Concentration Pathway 4.5 (RCP4.5) scenario. Adapted by permission
from Krishnan et al. (2019)
150
S. Patwardhan et al.