How reliable are CMIP5 models in simulating dust optical depth?
<p>Dust aerosol plays an important role in the climate system by affecting the radiative and energy balances. Biases in dust modeling may result in biases in simulating global energy budget and regional climate. It is thus very important to understand how well dust is simulated in the Coup...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-08-01
|
| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/18/12491/2018/acp-18-12491-2018.pdf |
| _version_ | 1819077346176532480 |
|---|---|
| author | B. Pu B. Pu P. Ginoux |
| author_facet | B. Pu B. Pu P. Ginoux |
| author_sort | B. Pu |
| collection | DOAJ |
| description | <p>Dust aerosol plays an important role in the climate system by
affecting the radiative and energy balances. Biases in dust modeling may
result in biases in simulating global energy budget and regional climate. It
is thus very important to understand how well dust is simulated in the
Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Here seven
CMIP5 models using interactive dust emission schemes are examined against
satellite-derived dust optical depth (DOD) during 2004–2016.</p><p>It is found that multi-model mean can largely capture the global spatial
pattern and zonal mean of DOD over land in present-day climatology in MAM and
JJA. Global mean land DOD is underestimated by −25.2 % in MAM to
−6.4 % in DJF. While seasonal cycle, magnitude, and spatial pattern are
generally captured by the multi-model mean over major dust source regions such as
North Africa and the Middle East, these variables are not so well represented
by most of the models in South Africa and Australia. Interannual variations
in DOD are not captured by most of the models or by the multi-model mean.
Models also do not capture the observed connections between DOD and local
controlling factors such as surface wind speed, bareness, and precipitation.
The constraints from surface bareness are largely underestimated while the
influences of surface wind and precipitation are overestimated.</p><p>Projections of DOD change in the late half of the 21st century under the
Representative Concentration Pathways 8.5 scenario in which the multi-model
mean is compared with that projected by a regression model. Despite the
uncertainties associated with both projections, results show some
similarities between the two, e.g., DOD pattern over North Africa in DJF and
JJA, an increase in DOD in the central Arabian Peninsula in all seasons, and
a decrease over northern China from MAM to SON.</p> |
| first_indexed | 2024-12-21T18:55:44Z |
| format | Article |
| id | doaj.art-12059c4b63a94fed9db8619a4118f28d |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-12-21T18:55:44Z |
| publishDate | 2018-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-12059c4b63a94fed9db8619a4118f28d2022-12-21T18:53:37ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242018-08-0118124911251010.5194/acp-18-12491-2018How reliable are CMIP5 models in simulating dust optical depth?B. Pu0B. Pu1P. Ginoux2Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, New Jersey 08544, USANOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey 08540, USANOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey 08540, USA<p>Dust aerosol plays an important role in the climate system by affecting the radiative and energy balances. Biases in dust modeling may result in biases in simulating global energy budget and regional climate. It is thus very important to understand how well dust is simulated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Here seven CMIP5 models using interactive dust emission schemes are examined against satellite-derived dust optical depth (DOD) during 2004–2016.</p><p>It is found that multi-model mean can largely capture the global spatial pattern and zonal mean of DOD over land in present-day climatology in MAM and JJA. Global mean land DOD is underestimated by −25.2 % in MAM to −6.4 % in DJF. While seasonal cycle, magnitude, and spatial pattern are generally captured by the multi-model mean over major dust source regions such as North Africa and the Middle East, these variables are not so well represented by most of the models in South Africa and Australia. Interannual variations in DOD are not captured by most of the models or by the multi-model mean. Models also do not capture the observed connections between DOD and local controlling factors such as surface wind speed, bareness, and precipitation. The constraints from surface bareness are largely underestimated while the influences of surface wind and precipitation are overestimated.</p><p>Projections of DOD change in the late half of the 21st century under the Representative Concentration Pathways 8.5 scenario in which the multi-model mean is compared with that projected by a regression model. Despite the uncertainties associated with both projections, results show some similarities between the two, e.g., DOD pattern over North Africa in DJF and JJA, an increase in DOD in the central Arabian Peninsula in all seasons, and a decrease over northern China from MAM to SON.</p>https://www.atmos-chem-phys.net/18/12491/2018/acp-18-12491-2018.pdf |
| spellingShingle | B. Pu B. Pu P. Ginoux How reliable are CMIP5 models in simulating dust optical depth? Atmospheric Chemistry and Physics |
| title | How reliable are CMIP5 models in simulating dust optical depth? |
| title_full | How reliable are CMIP5 models in simulating dust optical depth? |
| title_fullStr | How reliable are CMIP5 models in simulating dust optical depth? |
| title_full_unstemmed | How reliable are CMIP5 models in simulating dust optical depth? |
| title_short | How reliable are CMIP5 models in simulating dust optical depth? |
| title_sort | how reliable are cmip5 models in simulating dust optical depth |
| url | https://www.atmos-chem-phys.net/18/12491/2018/acp-18-12491-2018.pdf |
| work_keys_str_mv | AT bpu howreliablearecmip5modelsinsimulatingdustopticaldepth AT bpu howreliablearecmip5modelsinsimulatingdustopticaldepth AT pginoux howreliablearecmip5modelsinsimulatingdustopticaldepth |