Parameterization of the Dry Convective Boundary Layer Based on a Mass Flux Representation of Thermals

Hourdin, F.; Couvreux, Fleur; Menut, Laurent

doi:10.1175/1520-0469(2002)059<1105:potdcb>2.0.co;2

Cited by 106 publications

(129 citation statements)

References 36 publications

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“…LMDz-SP uses also a local approach to parameterize vertical diffusion, but the Emanuel (1991) scheme parameterizes deep convection. LMDz-NP uses a combination of the Yamada (1983) scheme and the thermal plume model of Hourdin et al (2002) to simulate atmospheric mixing in the boundary layer. Atmospheric transport by deep convection is parameterized according to Emanuel (1991).…”

Section: Three Different Versions Of Lmdz: Lmdz-td Lmdz-sp and Lmdz-npmentioning

confidence: 99%

“…These LMDz versions differ only by the physical parameterizations they use. Two parameterizations of vertical diffusion (Louis, 1979;Yamada, 1983), one parameterization of the thermals (Hourdin et al, 2002) and two deep convection schemes (Tiedtke, 1989;Emanuel, 1991) are tested in three different versions of LMDz. As the impact of model parameterizations can be different when either assimilating surface data or satellite column data, we evaluate this impact for three observational systems: two surface networks and one data set of GOSAT retrievals.…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations

Locatelli¹,

Bousquet²,

Saunois³

et al. 2015

Atmos. Chem. Phys.

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Abstract. With the densification of surface observing networks and the development of remote sensing of greenhouse gases from space, estimations of methane (CH 4 ) sources and sinks by inverse modeling are gaining additional constraining data but facing new challenges. The chemical transport model (CTM) linking the flux space to methane mixing ratio space must be able to represent these different types of atmospheric constraints for providing consistent flux estimations.Here we quantify the impact of sub-grid-scale physical parameterization errors on the global methane budget inferred by inverse modeling. We use the same inversion setup but different physical parameterizations within one CTM. Two different schemes for vertical diffusion, two others for deep convection, and one additional for thermals in the planetary boundary layer (PBL) are tested. Different atmospheric methane data sets are used as constraints (surface observations or satellite retrievals).At the global scale, methane emissions differ, on average, from 4.1 Tg CH 4 per year due to the use of different sub-grid-scale parameterizations. Inversions using satellite total-column mixing ratios retrieved by GOSAT are less impacted, at the global scale, by errors in physical parameterizations. Focusing on large-scale atmospheric transport, we show that inversions using the deep convection scheme of Emanuel (1991) derive smaller interhemispheric gradients in methane emissions, indicating a slower interhemispheric exchange. At regional scale, the use of different sub-grid-scale parameterizations induces uncertainties ranging from 1.2 % (2.7 %) to 9.4 % (14.2 %) of methane emissions when using only surface measurements from a background (or an extended) surface network. Moreover, spatial distribution of methane emissions at regional scale can be very different, depending on both the physical parameterizations used for the modeling of the atmospheric transport and the observation data sets used to constrain the inverse system. When using only satellite data from GOSAT, we show that the small biases found in inversions using a coarser version of the transport model are actually masking a poor representation of the stratosphere-troposphere methane gradient in the model. Improving the stratosphere-troposphere gradient reveals a larger bias in GOSAT CH 4 satellite data, which largely amplifies inconsistencies between the surface and satellite inversions. A simple bias correction is proposed. The results of this work provide the level of confidence one can have for recent methane inversions relative to physical parameterizations included in CTMs.

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Section: Three Different Versions Of Lmdz: Lmdz-td Lmdz-sp and Lmdz-npmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations

Locatelli¹,

Bousquet²,

Saunois³

et al. 2015

Atmos. Chem. Phys.

View full text Add to dashboard Cite

show abstract

“…Briefly, it solves for monthly surface CH 4 emissions for the different categories of sources and sinks and for 11 large regions (10 land regions + 1 ocean), using monthly mean observations at up to 68 surface stations from the NOAA/ESRL, CSIRO and IPSL/LSCE surface monitoring networks. The offline version LMDZt version 3 of the LMDZ-GCM, nudged to analysed winds (Uppala, 2005), is used to model atmospheric transport (Hourdin and Talagrand, 2006;Hourdin et al, 2002). Prior emissions are taken from inventories (Matthews and Fung, 1987;Olivier and Berdowski, 2001;van der Werf et al, 2006).…”

Section: Inversion Modelsmentioning

confidence: 99%

Source attribution of the changes in atmospheric methane for 2006–2008

et al. 2011

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“…In this approach, the convection is represented by splitting the atmospheric column in two compartments: one associated with the concentrated buoyant updrafts (or thermal plumes) that rise from the surface and the other one with compensating subsidence around those plumes. This approach was developed independently by two teams and since adopted in several groups (Hourdin et al, 2002;Soares et al, 2004;Siebesma et al, 2007;Pergaud et al, 2009;Angevine et al, 2010;Neggers et al, 2009;Neggers, 2009;Hourdin et al, 2013b). It has been shown in particular to open the way to quite accurate representation of cumulus clouds that form at the top of convective thermal plumes (Rio and Hourdin, 2008;Jam et al, 2013).…”

Section: F Hourdin Et Al: Convective Transport In the Boundary Layementioning

confidence: 99%

Parameterization of convective transport in the boundary layer and its impact on the representation of the diurnal cycle of wind and dust emissions

et al. 2015

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Abstract. We investigate how the representation of the boundary layer in a climate model impacts the representation of the near-surface wind and dust emission, with a focus on the Sahel/Sahara region. We show that the combination of vertical turbulent diffusion with a representation of the thermal cells of the convective boundary layer by a mass flux scheme leads to realistic representation of the diurnal cycle of wind in spring, with a maximum near-surface wind in the morning. This maximum occurs when the thermal plumes reach the low-level jet that forms during the night at a few hundred meters above surface. The horizontal momentum in the jet is transported downward to the surface by compensating subsidence around thermal plumes in typically less than 1 h. This leads to a rapid increase of wind speed at surface and therefore of dust emissions owing to the strong nonlinearity of emission laws. The numerical experiments are performed with a zoomed and nudged configuration of the LMDZ general circulation model coupled to the emission module of the CHIMERE chemistry transport model, in which winds are relaxed toward that of the ERA-Interim reanalyses. The new set of parameterizations leads to a strong improvement of the representation of the diurnal cycle of wind when compared to a previous version of LMDZ as well as to the reanalyses used for nudging themselves. It also generates dust emissions in better agreement with current estimates, but the aerosol optical thickness is still significantly underestimated.

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Parameterization of the Dry Convective Boundary Layer Based on a Mass Flux Representation of Thermals

Cited by 106 publications

References 36 publications

Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations

Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations

Source attribution of the changes in atmospheric methane for 2006–2008

Parameterization of convective transport in the boundary layer and its impact on the representation of the diurnal cycle of wind and dust emissions

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