Regional Feedbacks Between the Ocean and the Atmosphere in the North Atlantic (A21D-0083)LuAnne Thompson1, Maylis Garcia, Kathryn A. Kelly1, James Booth2,31University of Washington, Seattle, USA, 2NASA GISS, New York, USA, 3Columbia University, New York, USA,
Email: [email protected]
IntroductionRegional seasonal feedbacks from stored heat in the ocean to the atmosphere is investigated using observations. Previous work (Dong and Kelly, 2004)) shows that low frequency heat content is negatively correlated with net surface heat flux (positive heat flux into the ocean) in the Gulf Stream with heat content leading by 4 months. When the ocean is warm (cold), the flux is heat is to (from) the atmosphere. We investigate whether ocean heat content feedbacks to the atmosphere in other regions of the North Atlantic by using observationally constrained surface flux fields (OAFlux) and altimetry sea surface height (SSH) as a proxy for upper ocean heat content from 1993 to 2009. Because the bulk of the heat content in the ocean is shielded from the atmosphere during the summer, we surmised that the coupling may change with the seasons. To determine whether this is true, we examine the relationship between time series for each month of the year in both SSH and surface flux of heat. We also speculate on the processes at work that allow the ocean to influence the atmosphere in specific regions as specific times of the year.
Data sources: monthly averages of all quantities
Example: SSH and Qnet over the Gulf Stream
ReferencesDong, S., K. A. Kelly, 2004: Heat Budget in the Gulf Stream Region: The Importance of Heat Storage and Advection. J. Phys. Oceanogr., 34, 1214–1231. Timlin, M. S., M. A. Alexander, and C. Deser, 2002: On the reemergence of North Atlantic SST anomalies. J. Climate, 15, 9, 2707-2712. Minobe, S., Masato M., A. Kuwano-Yoshida, H. Tokinaga, S.-P. Xie, 2010: Atmospheric Response to the Gulf Stream: Seasonal Variations. J. Climate, 23, 3699–3719. Yu, L., and R. A. Weller, 2007: Objectively Analyzed air-sea heat Fluxes for the global oce-free oceans (1981–2005). Bull. Ameri. Meteor. Soc., 88, 527–539.
Predictions from turbulent fluxes: differences in summer
This project is supported by the NASA Physical Oceanography Program Ocean Surface Topography Science Team
Mechanisms for feedbacks
Persistence and linkages between SSH/heat content and Qturb in the Gulf Stream: lagged correlations
Figure 1. SSH (in cm) on December 27, 1995. Gulf Stream region is defined by yellow box.
Interannual SSH and -Qturb
SS
H (
m)
-Qturb (W
att m
-2)
SSH leads Qturb by 5 months with a correlation of -0.53 significant at 95% (a warm ocean leads to heat flux out of the ocean).
Seasonal relationship between SSH and Qturb
SS
H (
m)
Figure 3. The blue lines show separate time series of anomalous SSH and –Qturb, for each month of the year. The SSH times series are very similar to each other while Qturb time series are not. The red lines show October SSH, and November –Qturb. The correlation between SSH and Qturb for these month is -0.43 and is significant at 95%.
SSH/Heat contentautocorrelation
Qturb
autocorrelation
White areas have insignificant correlations. SSH/Heat content is much more persistent than Qturb. The negative correlation indicates that a warmer ocean is correlated with heat flux out of the ocean. November and December Qturb
can be predicted by heat content in the previous 4-11 months.
Qturb
SS
H
Figure 6. Analysis using Qturb gives larger regions of high predictive skill in summer. White lines indicate high correlation regions. Also shown is the climatological sensible heat flux with zero contour in black. Regions where sensible heat flux is positive, planetary boundary layers are stable
Observational Analysis variables Source Comment
Sea surface height (SSH) Monthly maps of sea level anomaly from Ssalto/Duacs1/3° x 1/3°, Mercator grid
Used as proxy for upper ocean heat content
Turbulent heat flux Qturb
And net suface heat flux Qnet
OAflux: Objectively Analyzed air-sea fluxes for the Global Oceans (Yu and Weller, 2007)
Both fluxes are positive for warming the ocean. Qturb is the sum of the latent and sensible heat flux. Qnet also include net longwave and short wave fluxes
Mixed-layer depth 1 degree monthly mixed-layer climatology WOA 01
Lagged correlations between SSH and Qturb
Qturb
SS
H
SSH
Qtu
rb
Linkages between SSH/heat content and Qnet throughout the BasinFigure 4. We smoothed both Qnet and SSH with a 3o Gaussian smoother. Lagged correlations performed at locations shown in Figure 5. Shown are only negative correlations for points labeled in Figure 6. Note that regions A, B and C show correlations between Qnet and the previous years SSH.
Qnet
SS
H
Figure 5. We look for locations where for a particular month of the year Qne is significantly negatively correlated with SSH for 4 consecutive months (the bands in the above figure). Regions with high predictive skill are outlined in white and overlie the climatological Qnet for that month of the year. The zero contour for Qnet is in black. The regions of high correlations differ from month to month. Also marked are the locations for analysis shown in Figure 4.
• December, January, and February heat flux (points A, B and L) in the vicinity of the Gulf Stream can be predicted by summer through fall heat content. The deep winter mixed-layer allows the atmosphere to access heat stored in the previous seasons (Timlin et al, 2002).
• May heat flux (point E) off of the Northwest coast of Africa is the location of the Benguala upwelling that peaks in May. The boundary layers are stable (see regions of positive sensible heat flux in July and August in Figure 6.), and stored heat is brought into contact with the atmosphere.
• In August (point H), the Florida Current delivers heat originating in the tropics to the region of the ocean off the East Coast of the United States and the atmosphere is relatively quiet giving rise significant deep heating of the atmosphere by the ocean.
• In July, the planetary boundary layer is stable (point G) and the surface atmosphere is decoupled from the troposphere. The ocean forced heat fluxes can be felt in the planetary boundary layer.
Location A B C D E F G H I J K L
Qnet explained by SSH
36 27 19 18 10 10 10 10 15 16 16 36
Fraction of Qnet variance explained by SSH
25% 24% 21% 15% 41% 21% 27% 24% 22% 20% 16% 23%
Mean Qnet -299 -241 -39 -8 108 97 159 66 -26 -165 -202 -251
Size of feedback (Watts/m2)
Conclusions• The two-decade long satellite altimeter record allows quantification of the role of variability in heat content in
driving changes in the atmosphere. The persistence of heat content over that of SST allows longer lead times for prediction of Qnet.
• Lag correlations of separate time series of SSH and Qnet for each month of the year demonstrate that regionally and at specific times of the year the ocean heat content (SSH) has predictive skill for the Qnetfor a season or more and the stored heat in the ocean can be released back to the atmosphere. The SSH explains between 20% and 40% of the variance of Qnet locally. The results are similar when Qturb is used.
• Linkages to the atmosphere are suggested by the work of Minobe et al (2010) who examined the climatological cloud cover and precipitation over the Gulf Stream. They identify two loci of activity at two different times of the year:
In summer, the Florida Current (see August and point H), the Gulf Stream forces the formation ofupper level clouds by deep heating. In winter (see December, January and point A), the Gulf Stream forces low level convergence that leads to mid-level clouds. In summer, Minobe et al (2010) show low level clouds (see July point G) north of the Gulf Stream in the region of stable boundary layers, but they do not discuss the linkages of the low level clouds to the ocean.
• Our results suggest that there might be interannual changes in cloud properties forced by surface fluxes linked to heat content.
• Future work:Examination of seasonal coupling in other ocean basinsExamination of the relationship of interannual cloud cover to surface fluxes and stored heat in the
ocean.Examination of the relationships discussed here in coupled climate models
Monthly SSH and -Qturb
AB C D
Figure 2. Monthly SSH and Qturb were averaged over the yellow box in Figure 1. Note that -Qturb is plotted. Monthly and low passed time series are shown.
KJI
HG
FE
L
Qtu
rb
-Qturb (W
att m
-2)