# Presentation: 049352

## Aerosol radiative effects in the Met Office models

**Aerosol radiative effects in the Met Office models**

- Olivier Boucher, Nicolas Bellouin, Jim Haywood, Colin Johnson, Andy Jones, Jamie Rae, Shekar Reddy and Stephanie Woodward
- Met Office Hadley Centre, UK
- Johannes Quaas and Stefan Kinne
- MPI Meteorology, Hamburg, Germany

## Yoram Kaufman

## Outline

-  Introduction and model validation
-  Climate response to aerosol forcing
-  Black carbon radiative forcing and GWP
-  Aerosol indirect forcing from CERES and MODIS

## Met Office Unified Model: from NWP to climate

- UK 4km

- Regional
- 12km

- Global 40km
- 60 hour forecast twice/day
- 144 hour forecast twice/day
- +EPS 24member, 90km

**Climate projections**
- HadGEM1
- HadGEM2-AO
- HadGEM2-ES
- N96=1.8° resolution
- 38 levels

**Weather forecasts**

## HadGEM2 model validation

-  Aerosol optical depth
- Seasonal distributions against satellite retrievals
- Seasonal distributions against AERONET climatology
- Monthly averages against AERONET climatology
-  Vertical profile of aerosol extinction
- Against aircraft measurements
-  Radiative fluxes in clear-sky
- Against BSRN measurements
-  HadGEM2 averages are made of 10 simulated years using present-day emissions using its own meteorology.

- Increasingly demanding

- Analysis: N. Bellouin

## HadGEM1, HadGEM2, MISR and MODIS

**Aerosols included in HadGEM2:**
**Sulphate (revised)**
**Mineral dust (new)**
**Sea salt**
**Black carbon**
**Biomass-burning (revised)**
**Secondary organic (new climatology)**
**      ****– ****Global averages at 0.55 ********m –**
**                     ****DJF   MAM   JJA    SON**
**HadGEM1  0.079  0.068  0.080  0.072**
**HadGEM2  0.110  0.116  0.147  0.118**

- AOD at 0.55 m

## HadGEM1, HadGEM2, MISR and MODIS

- MODIS & MISR 2001
- Main patterns are reproduced.
- Continents are very clean in all seasons but summer (missing oxidation by O3, nitrate).
- African biomass burning seasonality too centred on summer.

- AOD at 0.55 m

## HadGEM2 and AERONET – Winter 

**Clean continents**

- Lack of biomass burning?

- AOD at 0.44 m

## HadGEM2 and AERONET – Summer

- Pretty good simulation overall

- AOD at 0.44 m

## HadGEM2 and AERONET – North America

- GSFC

- Boulder

- Rogers Dry Lake

## HadGEM2 and AERONET – Europe 

- Moldova

- Rome

- El Arenosillo

## HadGEM2 and AERONET – Northern Africa

- Banizoumbou

- Ilorin

- Cape Verde

## HadGEM2 and AERONET – Southern Africa

- Mongu

- Skukuza

- Ascension

## HadGEM2 and AERONET – South America

- Abracos Hill

- Sao Paulo

- Cordoba

## HadGEM2 and AERONET – Middle East &Asia 

- Anmyon

- Kanpur

- Solar Village

## HadGEM2 and AERONET – Pacific Ocean

- Hawaii

- Tahiti

- Nauru

## HadGEM2 and BAe-146 – DABEX and DODO

- Biomass-burning layer is above the mineral dust.
- The model simulates the vertical location right, aerosol loading generally underestimated.
- Mineral dust Ångström exponent is sensible, although not negative

## Radiative fluxes and diffuse fraction: BSRN

- Direct

- Diffuse

- Analysis: N. Bellouin, Data courtesy: M. Wild

## Radiative fluxes and diffuse fraction: BSRN

- BSRN                      HadGEM2 No aerosols                      HadGEM2 aerosols

- Direct

- Diffuse

- Analysis: N. Bellouin, Data courtesy: M. Wild

## Radiative fluxes and diffuse fraction: BSRN

- BSRN                      HadGEM2 No aerosols                      HadGEM2 aerosols

- Direct

- Diffuse

- Analysis: N. Bellouin, Data courtesy: M. Wild

## Radiative fluxes and diffuse fraction: BSRN

- BSRN                      HadGEM2 No aerosols                      HadGEM2 aerosols

- Direct

- Diffuse

- Analysis: N. Bellouin, Data courtesy: M. Wild

## Radiative fluxes and diffuse fraction: BSRN_x0003_

- BSRN                      HadGEM2 No aerosols                      HadGEM2 aerosols

- Direct

- Diffuse

- Analysis: N. Bellouin, Data courtesy: M. Wild

## A model: what for?

- Estimate aerosol direct/indirect effects
- 		==> climate response to aerosol forcings
- 		==> detection and attribution of climate change
- 		==> constrain the climate sensitivity
- 		==> understand climate feedbacks that involves aerosols
- 		==> constrain decadal forecasts for adaptation studies
- 		==> role of aerosols in mitigating climate change
- 		==> impact of aerosols on short-term weather forecasts

## Climate response to aerosol RFs in slab model experiments

- 1.01 K / Wm–2

- 0.86 K / Wm–2

- 0.71 K / Wm–2

- 1.00 K / Wm–2

- SO4

- BC

- CO2

- BB

- -3        -2        -1          0         1         2          3

- Climate response to aerosol RFs in slab model experiments

- Jones et al., JGR, submitted, 2007.

## Dust and sea-salt response: burden

**SO4**

**BB**

**CO2**

**BC**

- HadGEM2-AML slab model experiments

- Jones et al., JGR, submitted, 2007.

## Dust response: emissions vs SMC

**SO4**

**BB**

**CO2**

**BC**

## Dust response: emissions vs 10-m wind speed

**SO4**

**BB**

**CO2**

**BC**

## Dust and sea-salt response: burden

**SO4**

**BB**

**CO2**

**BC**

- HadGEM2-AML slab model experiments

- Jones et al., JGR, submitted, 2007.

## Dust and sea-salt response: sea-ice

**SO4**

**BB**

**CO2**

**BC**

## Dust and sea-salt response:  10-m wind speed

**SO4**

**BB**

**CO2**

**BC**

## Changes in dust emissions from 2000 to 2100

- Woodward et al.,
- GRL, 2005

- Bare soil fraction

- Atmospheric dust load
- (kg m-2)

## BC in HadGEM2 experiments

- Burden

- Burden from UK emissions

- Direct RF

## Direct radiative forcing by regional BC emissions

- Reddy and Boucher
- GRL, 2007

- Results from LMDZ

## BC atmospheric transport and radiative forcings

**Residence times**

**Atmospheric ****burden (6.97x10****-2**** Tg)**

- Reddy and
- Boucher
- GRL, 2007

- LMDZ

## Global warming potentials of black carbon

***Direct GWP (100 years) by black carbon is in the range of 400 to 700 with little dependence on the region of emission.***

- {

**HADGEM2**

**LMDZ**

## BC deposition on snow and ice

**Radiative forcing from change in snow/ice albedo due to BC deposition ranges from +0.04 to +0.24 Wm****-2****.**
**BC deposition to north to 60****o****N and south to 60****o****S is 5-10 mg.m****-2**** with an annual deposition of 0.2 Tg.**

_**Assumptions**_
** ****RF = 0.1 Wm****-2**
** **
** ****Apportion to source regions according to how much BC is deposited north to 60°N and south to 60°S. **

## Global warming potentials of black carbon

***European BC has a total (direct+indirect) GWP which is more than a factor of 2 larger than that for global emissions.***

- {

**HADGEM2**

## Snow albedo

- Parametrisation from Wiscombe and Warren (1980)

- Single scattering co-albedo

- Snow albedo for direct radiation (SZA=60°)

## Aerosol RF from MODIS and CERES

- Quaas et al., JGR, submitted, 2007.

- 0) Download 5 years of colocated CERES albedo (20 km) and MODIS aerosol (1°x1°) and cloud (20 km) properties!
- 1) Divide the globe into regions
- 2) Fit the CERES albedo as a function of AOD, f, fliq, fxCOD (sigmoidal fit) using a subset of the data.
- 3) Derive statistical relationships between AOD and various cloud properties for each region and season
- 3) Attribute the statistical increase in scene albedo with AOD to the aerosol direct, first indirect and a residual effect using the sigmoidal fit and some algebra
- 4) Use Bellouin et al. (2005) to separate natural and anthropogenic aerosols and estimate the aerosol RF
- 5) Integrate the RF over time and space

## Aerosol RF from MODIS and CERES

****** ****ln N****d**** / ******** ln ********a**

****** ****ln f / ******** ln ********a**

****** ****ln L / ******** ln ********a**

- Quaas et al., JGR, submitted, 2007.

**??**

- 1st aerosol indirect effect

- 2nd aerosol indirect effect + ??
- See Kaufman et al. JGR 2005

## Aerosol RF

- _Aerosol direct effect_

- Quaas et al., JGR, submitted, 2007.

- _Aerosol first indirect effect_

- Direct RF= -0.9 ± 0.2 Wm-2
- 		larger over land

- First indirect RF = -0.2 ± 0.1 Wm-2
- Larger over the ocean

- Sigmoidal fit

- Statistical
- relationships

## Comparison of aerosol optical depth with MODIS (08/2003)

**Analysis run with recent upgrades (ev65)**

**Forecast run (eupr)**

- Morcrette, Benedetti, Boucher and the GEMS participants, BAMS, submitted, 2007.

- ECMWF IFS model

## Slide 43

## OLR Errors & Saharan Dust

- _Conclusion:_ OLR errors over the Western Sahara at 1200 UTC during May-August 2004 can be explained by the failure to include the strong greenhouse effect of high amounts of desert dust in the model
- ...see Haywood et al. (2004) JGR