Coupled climate models used for long-term future climate projections and seasonal or decadal predictions share a systematic and persistent warm sea surface temperature (SST) bias in the tropical ...Atlantic. This study attempts to better understand the physical mechanisms responsible for the development of systematic biases in the tropical Atlantic using the so-called Transpose-CMIP protocol in a multi-model context. Six global climate models have been used to perform seasonal forecasts starting both in May and February over the period 2000–2009. In all models, the growth of SST biases is rapid. Significant biases are seen in the first month of forecast and, by 6 months, the root-mean-square SST bias is 80% of the climatological bias. These control experiments show that the equatorial warm SST bias is not driven by surface heat flux biases in all models, whereas in the south-eastern Atlantic the solar heat flux could explain the setup of an initial warm bias in the first few days. A set of sensitivity experiments with prescribed wind stress confirm the leading role of wind stress biases in driving the equatorial SST bias, even if the amplitude of the SST bias is model dependent. A reduced SST bias leads to a reduced precipitation bias locally, but there is no robust remote effect on West African Monsoon rainfall. Over the south-eastern part of the basin, local wind biases tend to have an impact on the local SST bias (except in the high resolution model). However, there is also a non-local effect of equatorial wind correction in two models. This can be explained by sub-surface advection of water from the equator, which is colder when the bias in equatorial wind stress is corrected. In terms of variability, it is also shown that improving the mean state in the equatorial Atlantic leads to a beneficial intensification of the Bjerknes feedback loop. In conclusion, we show a robust effect of wind stress biases on tropical mean climate and variability in multiple climate models.
This study presents the version of the LMDZ global atmospheric model used as the atmospheric component of the Institut Pierre Simon Laplace coupled model (IPSL‐CM6A‐LR) to contribute to the 6th phase ...of the international Coupled Model Intercomparison Project (CMIP6). This LMDZ6A version includes original convective parameterizations that define the LMDZ “New Physics”: a mass flux parameterization of the organized structures of the convective boundary layer, the “thermal plume model,” and a parameterization of the cold pools created by reevaporation of convective rainfall. The vertical velocity associated with thermal plumes and gust fronts of cold pools are used to control the triggering and intensity of deep convection. Because of several shortcomings, the early version 5B of this New Physics was worse than the previous “Standard Physics” version 5A regarding several classical climate metrics. To overcome these deficiencies, version 6A includes new developments: a stochastic triggering of deep convection, a modification of the thermal plume model that allows the representation of stratocumulus and cumulus clouds in a unified framework, an improved parameterization of very stable boundary layers, and the modification of the gravity waves scheme targeting the quasi‐biennal oscillation in the stratosphere. These improvements to the physical content and a more well‐defined tuning strategy led to major improvements in the LMDZ6A version model climatology. Beyond the presentation of this particular model version and documentation of its climatology, the present paper underlines possible methodological pathways toward model improvement that can be shared across modeling groups.
Plain Language Summary
The improvement of global numerical models is essential for the anticipation of future climate changes. We present significant advances in the physical content of a particular atmospheric model which contributes to the simulations of the Coupled Model Intercomparison project CMIP that feed reports from the IPCC. We document in particular the improvements of the representation through “parameterizations” of convective and cloudy processes. The article emphasizes the importance of strengthening the formalization of the methodology of development and tuning of models, so that new physical ideas can be translated into effective improvement of the climate representation.
Key Points
The development strategy of the LMDZ6A global atmospheric circulation model is presented
Improvements with respect to previous versions are documented in the context of the Coupled Model Intercomparison Project, CMIP
The improvements are based on significant changes of the physics content as well as on a better controlled tuning strategy
Using successive versions of a global climate model, we show how convective transport to the free troposphere of the humidity evaporated at the surface or, reciprocally, entrainment of dry air from ...the free troposphere into the mixed layer, controls surface evaporative cooling and then sea surface temperature. This control is as important as the radiative effect of boundary layer clouds on radiation. Those aspects are shown to be improved when activating a mass flux representation of the organized structures of the convective boundary layer coupled to eddy diffusion, the so‐called “thermal plume model,” leading to an increased near‐surface drying compared to the use of turbulent diffusion alone. Controlling detrainment by air properties from just above the boundary layer allows the thermal plume model to be valid for both cumulus and stratocumulus regimes, improving the contrast in near‐surface humidity between the trade winds region and East Tropical oceans. Using pairs of stand‐alone atmospheric simulations forced by sea surface temperature and of coupled atmosphere‐ocean simulations, we show how the improvement of the surface fluxes that arise from this improved physics projects into an improvement of the representation of sea surface temperature patterns in the coupled model, and in particular into a reduction of the East Tropical Ocean warm bias. The work presented here led to the bias reduction in sea surface temperature in the Institute Pierre Simon Laplace coupled model, IPSL‐CM6A, developed recently for the 6th phase of the Coupled Model Intercomparison Project, CMIP6.
Plain Language Summary
Global numerical models used to anticipate the future of our climate under global warming still suffer from significant errors, some of which are shared among all models. Among those shared errors is the tendency to predict too warm sea surface temperature over the east part of the tropical ocean in the tropics. We show how a better representation of the vertical convective transport in the first km above sea surface improves the representation of transport of dry air from the free troposphere. The drying of the near surface increases evaporation at the surface, that in turn contributes to significantly cool the sea surface in those regions.
Key Points
Nonlocal vertical transport by boundary layer thermals controls near‐surface humidity and in turn evaporative cooling over tropical oceans
Mass flux convective parameterization dries the near‐surface air more than a diffusive approach, reinforcing surface evaporation
The tropical SST biases in the IPSL‐CM6A‐LR coupled model are reduced by improving representation of boundary layer convection and tuning
Despite decades of efforts and improvements in the representation of processes as well as in model resolution, current global climate models still suffer from a set of important, systematic biases in ...sea surface temperature (SST), not much different from the previous generation of climate models. Many studies have looked at errors in the wind field, cloud representation or oceanic upwelling in coupled models to explain the SST errors. In this paper we highlight the relationship between latent heat flux (LH) biases in forced atmospheric simulations and the SST biases models develop in coupled mode, at the scale of the entire intertropical domain. By analyzing 22 pairs of forced atmospheric and coupled ocean-atmosphere simulations from the CMIP5 database, we show a systematic, negative correlation between the spatial patterns of these two biases. This link between forced and coupled bias patterns is also confirmed by two sets of dedicated sensitivity experiments with the IPSL-CM5A-LR model. The analysis of the sources of the atmospheric LH bias pattern reveals that the near-surface wind speed bias dominates the zonal structure of the LH bias and that the near-surface relative humidity dominates the east–west contrasts.
Light and water use by vegetation at the ecosystem level, are key components for understanding the carbon and water cycles particularly in regions with high climate variability and dry climates such ...as Africa. The objective of this study is to examine recent trends over the last 30 years in Light Use Efficiency (LUE) and inherent Water Use Efficiency (iWUE*) for the major biomes of Africa, including their sensitivities to climate and CO2. LUE and iWUE* trends are analyzed using a combination of NOAA-AVHRR NDVI3g and fAPAR3g, and a data-driven model of monthly evapotranspiration and Gross Primary Productivity (based on flux tower measurements and remote sensing fAPAR, yet with no flux tower data in Africa) and the ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) process-based land surface model driven by variable CO2 and two different gridded climate fields. The iWUE* data product increases by 10%–20% per decade during the 1982–2010 period over the northern savannas (due to positive trend of vegetation productivity) and the central African forest (due to positive trend of vapor pressure deficit). In contrast to the iWUE*, the LUE trends are not statistically significant. The process-based model simulations only show a positive linear trend in iWUE* and LUE over the central African forest. Additionally, factorial model simulations were conducted to attribute trends in iWUE and LUE to climate change and rising CO2 concentrations. We found that the increase of atmospheric CO2 by 52.8 ppm during the period of study explains 30%–50% of the increase in iWUE* and >90% of the LUE trend over the central African forest. The modeled iWUE* trend exhibits a high sensitivity to the climate forcing and environmental conditions, whereas the LUE trend has a smaller sensitivity to the selected climate forcing.
Few studies have evaluated land surface models for African ecosystems. Here we evaluate the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process‐based model for the interannual ...variability (IAV) of the fraction of absorbed active radiation, the gross primary productivity (GPP), soil moisture, and evapotranspiration (ET). Two ORCHIDEE versions are tested, which differ by their soil hydrology parameterization, one with a two‐layer simple bucket and the other a more complex 11‐layer soil‐water diffusion. In addition, we evaluate the sensitivity of climate forcing data, atmospheric CO2, and soil depth. Beside a very generic vegetation parameterization, ORCHIDEE simulates rather well the IAV of GPP and ET (0.5 < r < 0.9 interannual correlation) over Africa except in forestlands. The ORCHIDEE 11‐layer version outperforms the two‐layer version for simulating IAV of soil moisture, whereas both versions have similar performance of GPP and ET. Effects of CO2 trends, and of variable soil depth on the IAV of GPP, ET, and soil moisture are small, although these drivers influence the trends of these variables. The meteorological forcing data appear to be quite important for faithfully reproducing the IAV of simulated variables, suggesting that in regions with sparse weather station data, the model uncertainty is strongly related to uncertain meteorological forcing. Simulated variables are positively and strongly correlated with precipitation but negatively and weakly correlated with temperature and solar radiation. Model‐derived and observation‐based sensitivities are in agreement for the driving role of precipitation. However, the modeled GPP is too sensitive to precipitation, suggesting that processes such as increased water use efficiency during drought need to be incorporated in ORCHIDEE.
Key Points
High sensitivity of grassland fluxes to climate compared to closed forestsCO2 and variable soil depth are small effect on the IAV of GPP and ETRelationship between carbon flux IAV and T2m temperature is weak and negative
AMMA-MODEL INTERCOMPARISON PROJECT Hourdin, Frédéric; Musat, Ionela; Guichard, Françoise ...
Bulletin of the American Meteorological Society,
01/2010, Volume:
91, Issue:
1
Journal Article
Peer reviewed
Open access
The African Monsoon Multidisciplinary Analyses-Model Intercomparison Project (AMMA-MIP) was developed within the framework of the AMMA project. It is a relatively light intercomparison and evaluation ...exercise of both global and regional atmospheric models, focused on the study of the seasonal and intraseasonal variations of the climate and rainfall over the Sahel. Taking advantage of the relative zonal symmetry of the West African climate, one major target of the exercise is the documentation of a meridional cross section made of zonally averaged (10°W–10°E) outputs. This paper presents the motivations and design of the exercise, and it discusses preliminary results and further extensions of the project.
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