1. Surface Fluxes and Model Error An introduction
John Mitchell, with contributions from Keith Williams and Pat Hyder
WDAC, Galway, May 2014
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2. Context From WMAC report
- WDAC3 to address surface fluxes with inputs from reanalysis, GEWEX and SURFA and SOLAS communities
4th WGNE Workshop on Systematic Errors in Weather and Climate Models (April 2013)
Key recommendation from the workshop summary report:
“The lack of and/or inaccessibility to some key observations remains a major challenge. These include surface fluxes (especially over the oceans), and observations in polar and tropical regions. Additional efforts in these areas are required.”
Also “Update on Surface Fluxes- GCOS/WCRP AOP for Climate, 2012.
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3. Errors in climate model surface air temperature (CMIP1, DJF, no flux adjustment)
IPCC TAR,2001
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4. Climate models- errors in surface temperature.
Figure 8.2. (a) Observed climatological annual mean SST and, over land, surface air temperature (labelled contours) and the multi-model mean error in these temperatures, simulated minus observed (colour-shaded contours). (b) Size of the typical model error, as gauged by the root-mean-square error in this temperature, computed over all AOGCM simulations available in the MMD at PCMDI. The Hadley Centre Sea Ice and Sea Surface Temperature (HadISST; Rayner et al., 2003) climatology of SST for 1980 to 1999 and the Climatic Research Unit (CRU; Jones et al., 1999) climatology of surface air temperature over land for 1961 to 1990 are shown here. The model results are for the same period in the 20th-century simulations. In the presence of sea ice, the SST is assumed to be at the approximate freezing point of seawater (–1.8°C). Results for individual models can be seen in the Supplementary Material, Figure S8.1.
IPCC,2007
Climate models- errors in surface temperature.
Flato, et al; IPCC, 2013
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5. Biases in TOA radiation in climate models (Wm-2)
Solar
Solar LW
Temperature bias
Net
Marotze et al, IPCC, 2013
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6. Surface fluxes: Why do we care?
Coupled NWP
Day 3 forecast SST bias
Surface fluxes: Why do we care?
100yr mean SST bias MetOffice Weather and climate model
Coupled NWP
Day 14 forecast SST bias
SST biases are a key issue for coupled modelling on climate and, increasingly, NWP timescales.
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7. Importance of surface fluxes
Most of the bias in ocean heat content (and therefore SSTs) can be associated with the surface flux biases from the atmosphere.
Coupled model
SST bias
Coupled model heat content
bias
Atmosphere-only
Surface flux
Pat Hyder
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8. Existing radiative/turbulent datasets over the ocean are inconsistent with each other
Approach – cf Trenberth and Caron , 2001
TOA fluxes - CERES-EBAF– anchored by long term change in ocean heat content
SPACE
Divergence-ERA analyses
ATMOSPHERE
Radiative transfer modelling to get - radiative surface flux flux
SURFACE
Residual- turbulent fluxes
John Edwards & Pat Hyder
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9. Model bias: Latent + sensible
So have used:
TOA radiation & Divergence  Total Surface Flux
TOA radiation & Divergence & Surface radiation  Turbulent Surface Flux
Model bias: Total
Model bias: Longwave
Model bias: Shortwave
Model bias: Latent + sensible
Pat Hyder (MO), net flux estimate from Chun-lei Liu and Richard Allen
at Reading University under NERC DEEP-C project
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10. Zonal mean net ocean heat flux in reanalyses and obs. products
Josey et al. (2013) : Global zonal mean net air-sea heat flux from various datasets:
NCEP-1 (red dashed),
ERA-40 (red solid),
NCEP CFSR (blue solid),
Trenberth residual (black dashed),
NOC1.1a (green solid),
NOC1.1 (grey solid),
NOC2 (grey dash-dot),
UWM/COADS( green dashed),
OAFlux/ISCCP (purple solid),
COREv2 (purple dashed).
Note the ~20W/m2 spread,
probably underestimates uncertainty
Range of global means ~ -2 to 33 W/m2
Josey, S. A., S. Gulev and L. Yu, 2013

11. Fluxes over Land Downward solar fluxes at the surface
BSRN
ISCCP-FD
Model
Model evaluation against BSRN sites:
Bodas-Salcedo et al. (2008)
Models have been evaluated, improved and are now performing fairly well against the observations which exist over mid-latitude land.
Primary requirement is for more observations over the ocean.
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12. Moisture fluxes over mid latitude land in summer
Untangling strong feedbacks between
Temperature
Soil moisture
Evaporation
Boundary layer cloud
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13. CONCLUDING REMARKS Some issues in comparing model and observed fluxes
Point vs area fluxes
Natural temporal variability
Shortcomings of re-analyses
Nevertheless
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14. CONCLUDING REMARKS
Some issues in comparing model and observed fluxes
Point vs area fluxes
Natural temporal variability
Shortcomings of re-analyses
but
We still need direct radiative & turbulent flux obs which are consistent with each other
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