9th Global Energy and Water Exchanges Open Science Conference, July 7-12, 2024. Sapporo, Japan

Impact assessment of climate changeon the blowing-snow events in Hokkaido
with a large ensemble meteorological dataset
大規模アンサンブル気候予測データによる北海道の吹雪イベントに対する気候変動の影響評価
Sugawara, K., M. Inatsu, and Y. Harada, 2024: Climate change assessment on blowing snow in Hokkaido
using a large ensemble dataset. Scientific Online Letters on the Atmosphere (SOLA), in press.

Kuniyasu Sugawara1, 2*, Masaru Inatsu2, Yusuke Harada1
1. Civil Engineering Research Institute for Cold Region (CERI), PWRI, Japan2. Hokkaido University

Blowing snow

1

• Snow particles are blown through the air with wind … Blowing snow
• Blowing snow without snowfall … Drifting snow

• Cause of traffic accidents on winter road

Visibility deterioration

Snowdrift

Photo by CERI

Photo by Hokkaido Regional Development BureauPurpose2• Climate change has affected the phenomena in the cryosphere.

• Some studies focused on a climatological change effect of blowing snow frequency.
(e.g., Greaves et al. 2023; Browne and Chen 2023)

Our purpose
To reveal the possible impact of climate change on the magnitude of blowing snow
events across a wide probability spectrum• Use a large number of ensemble meteorological dataset called d4PDF• Focus on the four sites in Hokkaido taking into account the historical record ofblowing snow intensity and diverse synoptic characteristics

Ensemble dataset | d4PDF

3

Database for Policy Decision-Making for Future Climate Change
Global experiment(60-km resolution)

Regional experiments(20-km resolution)(Mizuta et al. 2017; Fujita et al. 2019)

Ishii and Mori, 2020: d4PDF: large-ensemble and highresolution climate simulations for global warming risk
assessment. PEPS, 7, 58.

Regional experiments• Historical experiment (HIST run)
50 members• +2-K experiment(+2K run)
54 members
1 ensemble member contains 60-years simulated data.

Equivalent to …
1951−2010 (current climate)2040s (the RCP8.5 scenario)

d4PDF enables quantitative evaluation of phenomena occurring at low probability.

Severity of blowing snow

4

Snow transport rate 𝑄ℎ (kg m-1 h-1; STR)

𝑃 : snowfall (mm h-1)
𝑈10 : 10-m wind speed (m s-1)

4.4
𝑄ℎ = 5.12𝑃𝑈10 + 2.81 × 10−3 𝑈10

𝑄𝑓 : Snowfall term

Omiya et al. (2018); Takechi et al. (2023)

𝑄𝑑 : Drifting term

• 𝑄ℎ > 300 (kg m-1 h-1) corresponds to the hourly mean visibility of less than 50 m.
(Kajiya et al. 2004; Harada et al. 2023)

Hardly recognizing a lattice tower

Photo by Dr. Sakurai (CERI)

Severity of blowing snow

5Blowing snow can be identified by the following decision tree
(Takeuchi et al. 1986; Takechi et al. 2023)
𝑃 : Snowfall (mm h-1)

𝑃>0YesNo𝑇<2All of the following are met• 𝑇<2• 𝑈10 > 5 + 𝑇 + 3 𝐻(𝑇 + 3)
• 𝑇𝑚𝑎𝑥 < 2• 𝑡𝑠 ≤ 48
• 𝑆𝐷 > 0

𝑈10 : 10-m wind speed (m s-1)
𝑇 : Air temperature (℃)
𝑇𝑚𝑎𝑥 : Maximum temperature
after snowfall termination (℃)
𝑡𝑠 : Elapsed time from snowfall termination (h)𝑆𝐷 : Snow depth (cm)
𝐻 : Heaviside’s hyper function

𝑇 < 2 and𝑈10 > 5 + 𝑇 + 3 𝐻(𝑇 + 3)

Target sites and Data

6

Target sites : AMeDAS Haboro(H), Abashiri(A), Urakawa(U), and Iwamizawa(I)• Based on 10-year mean annual STR* 1 winter = November 1−March 31
Analyzed data
AMeDAS

d4PDF

Temperature(℃)

Observed data

2-m air temperatureWind speed(m s-1)

Corrected to a 10-m data
based on observed data

10-m wind speed

Snowfall(mm h-1)

Time difference of snow depth(1 cm of snow = 1 mm of water)

Precipitation of snow

* d4PDF data was extracted by the inverse distance weighting method

Bias correction (month by month)7• Temperature … Offsetting the mean and factoring the standard deviation(Wilby et al. 2004)

𝑇： d4PDF data (historical/+2-K)
𝑇𝑜 ：Observed data𝑇𝑚,ℎ ：d4PDF in historical experiment
Overbar ( ̅ ) : Monthly climatology
𝜎[]： Monthly standard deviation

𝜎 𝑇𝑜𝑇෠ = 𝑇𝑜 +(𝑇 − 𝑇𝑚,ℎ )𝜎 𝑇𝑚,ℎ• Wind speed and precipitation of snow … Quantile delta mapping(QDM; Cannon et al. 2015)𝑥ො𝑚,𝑝 = 𝑥𝑚,𝑝 ⋅HIST run𝑥ො𝑚,ℎ = 𝑥𝑚,ℎ ⋅𝐹𝑜−1 [𝐹𝑚,𝑝 [𝑥𝑚,𝑝 ]]𝐹: Cumulative distribution function(In this study … gamma function)−1 [𝐹𝐹𝑚,ℎ𝑚,𝑝 [𝑥𝑚,𝑝 ]]𝐹𝑜−1 𝐹𝑚,ℎ 𝑥𝑚,ℎ−1 𝐹𝐹𝑚,ℎ𝑚,ℎ 𝑥𝑚,ℎ= 𝐹𝑜−1 𝐹𝑚,ℎ 𝑥𝑚,ℎSubscripts
𝑜: Observed data𝑚, 𝑝: Modeled data in a projected period(+2-K climate)𝑚, ℎ: Modeled data in a historical period(current climate)Estimation of snow cover

8• The presence of snow cover was diagnosed based on the degree-days method(Kominami et al. 2005; Inatsu et al. 2016)
𝑆𝐷 : Daily snow depth (cm)𝑇ത : Daily mean temperature (℃)
𝑑𝑆𝐷= −𝛼𝑆𝐷 − 𝛽𝐻 𝑆𝐷 ⋅ 𝑇ത 𝑇ത + 𝑆𝐹
𝑆𝐹 : Daily snowfall (cm)𝑑𝑡
𝛼 : Compaction rate of snow cover (2% day-1)
Compaction

MeltingSnowfall• 𝛽 value was estimated for 10 winter seasons
based on the observation.

• Snow depth estimation: daily

𝛽 : Daily snow melt above 0 ℃ (cm ℃-1 day-1)
𝐻(⋅) : Heaviside’s hyper function

StationHaboro
Abashiri
Urakawa
Iwamizawa

Interpolated into hourly data to estimate hourly STR.

𝛽 (cm ℃-1 day-1)
1.45
1.78
3.87
2.50

Hourly STR

9Severe events became rarer in
response to global warming.

However…
the risk of traffic accidents dueto blowing snow would remain.

HIST+2KAMeDAS

Monthly maximum 𝑄ℎ (ensemble mean)
Future climate (compared to current climate)• Almost halved in Urakawa• In the other sites, the reduction exhibitedseasonality

HaboroUrakawa
Abashiri

Iwamizawa

10Drifting term (𝑄𝑑 )11
Future climate (+2K run)
• Drifting would be reduced at all sites• The seasonality in drifting’s reduction wasoverall consistent with the seasonality in total
STR.

HaboroUrakawa
Abashiri
Iwamizawa

HIST run+2K runSnow-covered duration (SCD) and STR

12In Urakawa …
• SCD was 30 days shorter than the other sites.
(HIST run)
• SCD would decrease to 20.3 days (+2K run)

HaboroUrakawaAbashiri
Iwamizawa
HIST run+2K runConclusion

13• We have estimated the impact of climate change on blowing snow intensity (STR)
across a wide probability spectrum in four targeted sites of Haboro, Abashiri,
Urakawa, and Iwamizawa in Hokkaido using d4PDF.
• We found severe blowing snow events would become rarer in response to global
warming.
• The blowing snow at Urakawa was most declined than any other sites.
This reduction would be related to the decrease in the snow-covered duration (SCD).