Comparative Influence of Snow and SST Variability on Extratropical Climate in Northern Winter

Fanglin YangRSIS/CPC_NCEP

Arun Kumar CPC/NCEP

NOAA’s 27th Climate Diagnostics and Prediction

Workshop , October 2002

Motivitations

Compared to remote tropical SST forcing, how important is local snow anomaly in modulating mid-latitude climate variability?

In mid-latitudes, air-sea interaction is one way. Is snow-air interaction also one-way?

In extreme cases, for instance, in ENSO years, how snow and local temperature anomalies interact with each other?

GCM Experiments (NCEP GSM T42L28)

SST

Specification

Snow

Specification

#

Runs

Period of

Integration

SST_SNO Observed Predicted 3 1950-1999

SST_CSNO Observed Climatology 3 1950-1999

CSST_SNO Climatology predicted 1 150 years

CSST_CSNO Climatology Climatology 1 150 years

Model Fidelity, σ(Ts) in DJF Observation, CAMS Simulation: SST_SNO

Model Fidelity, σ(Z200) in DJF

NCEP/DOE R2 Simulation: SST_SNO

Snow Depth Climatology in DJF

Both are averages for 1979-1987. For model, assumed snow density 300 kg m-3 Both are averages for 1979-1987. For model, assumed snow density 300 kg m-3

Obs: SMMR Simulation: SST_SNO

Comparative Impact

Snow vs SST

Analysis of Standard Deviations in DJF

Δ { σ(Ts) } in DJF

Impact of Snow Variability

Impact of SST Variability

Δ { σ(Z200) } in DJF

Impact of Snow Variability

Impact of SST Variability

Δ {σ(Ts), 30°N-60°N} in DJF

Impact of Snow Variability

Impact of SST Variability

Rotated EOFs of Z200 in DJF, Atmospheric Modes

SST_SNO SST_CSNO

EOF 1, 11.6%

EOF 2, 11.2%

EOF 3, 9.6%

EOF 4, 7.3%

EOF 1, 13.7%

EOF 4, 8.1%

EOF 2, 10.7%

EOF 5, 7.5%

Composite Analysis for Extreme Cases

Impact of Snow Anomaly on the response of Mid-Latitude Climate to

Tropical SST Forcing in ENSO Years

Composite Sfc Temp Anomalies in ENSO Years

CAMS

SST_SNO

SST_CSNO

SST_SNO - SST_CSNO

Yang et al., J Climate, 2001

Composite Z500 Anomaly in ENSO Years

SST_SNO

SST_CSNO

Regression of Z200 and Ts with Nino 3.4 Index

SST_CSNOZ200

SST_SNOZ200

SST_CSNOTs

SST_SNOTs

Why the the variability (Anomalies) of surface air temperature is larger in the

runs with interactive snow?

Snow variation can lead to many land surface and atmospheric quantities to change, such as surface

temperature, latent and sensible heat fluxes, surface albedo, cloud cover and so on. These changes also feed back to snow variation (Grossman et al. 1994). Among all these feedbacks, we found snow-albedo feedback is the most effective one in explaining our

GCM results.

SurfaceAlbedo

Surface DownwardSolar

σ in DJF from SST_SNO, Snow-Albedo Feedback

Snow Depth

Surface Upward Solar

Zonal Mean σ in DJF from SST_SNO

Why the greatest impact of snow on sfc temperature variability is found in the mid-latitudes?

El Niño warmer SST

warm phase PNA pattern

higher surface air temperature

less snow

smaller surface albedomore downward solar radiation

Amplification by Snow-Albedo Feedback

Conclusion: Comparative Impact of Snow and SST, DJF, Mid-

Latitide

Sfc & Lower Tropospheric Temperature

Upper Tropospheric Temperature

Large-scale Circulation

Characteristics

Snow larger smaller

Smaller

(re-order internal modes)

Local;

Snow-albedo feedback etc

TropicalSST

smaller Larger larger Remote;

teleconnection

Conclusion: Mid-Latitude Air-Sea and Air-Snow Interactions at Seasonal time scales

Near Surface Temperature

Upper Tropospheric Temperature

Large-scale Circulation

Mechanism

Air-Snow Large small Small(re-order internal modes)

Snow-albedo feedback amplifies near surface temperature variability

Air-Sea Large Small Small(re-order internal modes)

Reduction in Thermal damping of near surface temperature Variability by surface energy fluxes