Richard P. Allan Environmental Systems Science Centre, University of Reading, UK
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Transcript of Richard P. Allan Environmental Systems Science Centre, University of Reading, UK
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Surface radiative fluxes: comparison of NWP/Climate models/reanalyses with
remote sensing estimates
Richard P. Allan
Environmental Systems Science Centre, University of Reading, UK
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Earth’s energy balance
Kiehl and Trenberth, 1997; Also IPCC 2007 tech. summary, p.94
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Determinants of surface radiation
Field Climatology Diurnal decadal change
Insolation
Cloud
Aerosol
Ozone
Water vapour
Temperature
Water vapour
Cloud
aerosol
GHG
SW
LW
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Methods of model surface flux evaluation
NWP/Climate model
Surface flux observations
Physics
Reanalyses
Satellite data
Conventional observations
RT modelsEmpirical models
Other models
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Ground Based ObservationsEvaluation of NWP/Climate models
ARM site ARM Model
Barrow ◊ ◊
Lamont + +
Darwin □ □
Manus * *
Peter Henderson et al.
Atm
osp
her
ic e
mis
sivi
ty
Column water vapour (cm)
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Bodas et al. (2008) J. Climate (see also e.g., Wild et al. (2001) J Climate, etc)
• Excellent time resolution
• Direct observations
• Scaling up issues• Poor spatial
coverage• Instrumental
uncertainty
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Empirical estimates
• Based on physics
• Use surface observations to calibrate– e.g. Prata (1996) QJ Royal Meteorol Soc
Clear-sky surface down longwave
Column integrated water vapour
Screen-level temperature
Atmospheric emissivity
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
NCEP clear and cloudy surface down longwave and Prata empirical estimate using observed T2m and column integrated water vapour
Niamey, Niger
Empirical formulas are valuable tools in understanding physical processes determining radiative flux variations
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
• Good quality clear-sky fluxes? Range in estimates of clear-sky surface net longwave radiation…
SRB (82 Wm-2) > NCEP (80 Wm-2) > ERA40 (73 Wm-2) > SSM/I empirical
Reanalyses
Allan (2006) JGR
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Robust relationship between clear-sky net surface LW flux (SNLc)
and column water vapour (CWV)
ERA40 NCEP
Allan (2006) JGR
dCWV (mm)
~1.3 Wm-2 mm-1
Clear ~1.5 Wm-2 mm-1
CWV (cm)
S
NL
(W
m-2)
Slingo et al (2008) JGR
Global: reanalyses Sahel, Africa: observations
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Interannual/Decadal changes: Homogeneity an issue
• Surface fluxes available globally on model grids• Observational basis through data assimilation• Model/observational errors; require validation• Changes in quality of observing system may
lead to spurious variability
Allan (2007) Tellus
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Reanalysis cloud properties unrealistic
Cloud components of surface fluxes poor
ERA40-ISCCP total cloud difference
ERA40 – satellite data (below)
Allan et al. (2004) JGR
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Remote sensing of surface fluxes
• Use satellite (and other) retrievals of important parameters (e.g. cloud, T, q)
• Input to radiative transfer codes
• Surface fluxes on model/satellite grids– e.g. ISCCP clouds/reanalysis atmosphere: Zhang et
al. (2004) JGR, Stackhouse et al (GEWEX), Pavlakis et al. (2004) Atmos Chem Phys
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Bodas et al. (2008) J. Climate
HadGAM1-Obs: Albedo net SW
Surface Down LW Column Water Vapour
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Spurious changes in ISCCP cloudsSurface fluxes: Issues with cloud-overlap, calibration and coverage/angular effects
Norris and Slingo (2008) FIAS
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Remote sensing of surface fluxese.g. surface longwave
What the surface sees
Cloud baseColumn water vapour
Tair
IR satellite
Cloud top
Tskin (when clear)
microwave satellites
Humidity temperature (when clear)
Cloud liquid water
precipitation, wind .
Atmospheric temperature / water vapour
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
• Comparisons of NWP model and satellite estimates of:
Cloud liquid waterWater vapour
• Indirect evaluation of surface fluxes– Parameters important
for surface LW (and SW) radiation
– Allan et al. (2008) QJRMS
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Constraining model (based on remote sensing estimates) using surface/satellite observations
Work with:
Nicky Chalmers & Robin Hogan
Mo
del
v G
ER
B/M
SG
Mo
del
v A
RM
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
RADAGAST/AMMA case study
1200GMT, 8 March 2006
RADAGAST project: http://radagast.nerc-essc.ac.uk
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Shortwave fluxes Longwave fluxes
• Diurnal cycle in surface fluxes– Solar/geometry; Temperature response; Atmosphere response
• Daily variability– Advection of air-masses; Aerosol cloud effects
• Important to simulate in models• Important to correct for in remote sensing estimates
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Radiative transfer models underestimate the solar absorption in the atmosphere during March 2006 dust storm
Slingo et al. (2006) GRL, 33, L24817
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Special issue on RADAGAST
under review for JGR-Atmospheres (A. Slingo et al.)
Using surface observations (and models) improves understanding of physical processes;
An indirect method of model evaluation
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Evaluating model climate change responses
CMIP3
CMIP3 volcanic
NCEP ERA40
SSM/I-derived~ +0.7 Wm-2 decade-1
∆SNLc (Wm-2)
Changes in clear-sky surface net longwave flux in coupled climate models, reanalyses and empirical estimates
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Linear fit
dSNLc/dTs ~ 3.5±1.5 Wm-2K-1
dCWV/dTs ~ 3.0±1.0 mm K-1
CMIP3 non-volcanic CMIP3 volcanic
Reanalyses/ Obs AMIP3
Models, reanalyses and observations show increased surface net downward longwave with warming due to increased water vapour
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Increases in water vapour enhance clear-sky longwave radiative cooling of atmosphere to the surface
This is offset by enhanced absorption of shortwave radiation by water vapour
Changes in greenhouse gases, aerosol and cloud alter this relationship…
Tropical oceans
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Sensitivity test: tropical oceans
Clear-sky Longwave shortwave
TOA SFC ATM ATM
1K increase in tropospheric T, constant RH
Greenhouse gas changes from 1980 to 2000 assuming different rates of warming
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Conclusions
• Evaluation of surface fluxes in models crucial but problematic (climatology, diurnal cycle, trends)
• Surface observations:– Excellent time-resolution– Upscaling issues, spatial coverage poor
• Reanalyses limitations: clouds/variability• Remote sensing estimates
– Good spatial (and temporal) coverage– Measure accurately quantities important for surface fluxes; need
to consider variety of time-scales
• Analysis of surface/satellite data can help to improve physical processes in models better surface fluxes
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Evaluation of diurnal cycle in NWP model using surface observations
Milton et al. (2008) JGR accepted
Niamey ARM station
(RADAGAST/AMMA)
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Diurnal effects: near surface temperature
Night Day
Temperature Temperature
Alti
tude
Alti
tude
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Near surface temperature:
diurnal cycle error
Missing physics?
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
• Diurnal skin temperature effects are also apparent for oceans (clear, calm conditions)
Allan (2000) J.Climate
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
• Surface downward LW sensitive to moisture changes in lowest levels and temperature changes close to the surface
Sensitivity of surface downwelling LW to temperature and moisture changes in 50 hPa vertical levels
1K temperature increase; moisture increased to conserve Relative Humidity
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Window region crucial in determining changes in surface net LW flux
Spectral signatude of clear-sky surface net longwave radiation
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Increased moisture enhances atmospheric radiative cooling to surface
ERA40 NCEP
Allan (2006) JGR 111, D22105
SNLc = clear-sky surface net down longwave radiation
CWV = column integrated water vapour
dCWV (mm)
~1.4 Wm-2 mm-1
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Evaluation of climate model sensitivity
SNLc = clear-sky surface net down longwave radiation
CWV = column integrated water vapour
dSNLc/dCWV ~ 1 ─ 1.5 W kg-1
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
• Also true for unique meteorological environments (e.g. Niamey, Radagast project, Slingo et al.)– Here water vapour & temperature anti-correlated over the seasonal cycle
Clear ~1.5 Wm-2 mm-1
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Impact of clouds on surface LW radiation
Smaller cloud LW effect in cloudy deep tropics due to water vapour path
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Surface cloud LW effect:observations and NWP model
- Higher water path: smaller cloud effect
- More cloud, lower/warmer cloud-base: higher cloud effect
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Dimming to brightening simulated in HadGEM1 climate model (Bodas et al.)
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Direct evaluation of models using surface observations
Allan (2000) J Climate
Barrow, Alaska
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
Bodas et al. (2008) J. Climate
[email protected] © University of Reading 2007www.nerc-essc.ac.uk/~rpa
SST
Water vapour
Clear net LW down at surface
Testing climate model simulations of current variability (tropical oceans)