Role of clouds and land-atmosphere coupling in midlatitude continental summer warm biases and climate change amplification in CMIP5 simulations

Chéruy, F.; Dufresne, Jean‐Louis; Hourdin, F.; Ducharne, Agnès

doi:10.1002/2014gl061145

Cited by 102 publications

(133 citation statements)

References 26 publications

(32 reference statements)

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“…The calculation is adapted to monthly data following Dirmeyer et al (2013) and Cheruy et al (2014) regions, meaning that the soil moisture is the dominant factor that controls the variations of E (Fig. 9a, b).…”

Section: Impact Of Wtd On Land-atmosphere Couplingmentioning

confidence: 99%

Impact of a shallow groundwater table on the global water cycle in the IPSL land–atmosphere coupled model

et al. 2017

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125°S-60°S) are significantly impacted by the WT, showing a decrease in air temperature (−0.5 K over mid-latitudes and −1 K over tropics) and an increase in precipitation. The latter can be explained by more vigorous updrafts due to an increased meridional temperature gradient between the equator and higher latitudes, which transports more water vapour upward, causing a positive precipitation change in the ascending branch. Over the West African Monsoon and Australian Monsoon regions, the precipitation changes in both intensity (increases) and location (poleward). The more intense convection and the change of the large-scale dynamics are responsible for this change. Transition zones, such as the Mediterranean area and central North America, are also impacted, with strengthened convection resulting from increased ET.

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Section: Impact Of Wtd On Land-atmosphere Couplingmentioning

confidence: 99%

Impact of a shallow groundwater table on the global water cycle in the IPSL land–atmosphere coupled model

et al. 2017

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“…Together with the evaporative fraction and the cloud radiative properties (e.g. Cheruy et al, 2014;Lindvall and Svenson, 2014), the parameterization of the soil Figure 8. The LMDZOR simulations (annual mean) for EXP 8m (left) and the differences between EXP 8m,LT,TP (Table 4) and EXP 8m (right) for (a) soil thermal conductivity, (b) soil heat capacity, (c) soil thermal inertia, (d) soil heat diffusivity, (e, f) surface temperature, (g, h) daily maximum temperature, (i, j) daily minimum temperature, (k, l) latent heat flux, and (m, n) sensible heat flux.…”

Section: The Impact Of the Soil Thermodynamics On The Temperature Varmentioning

confidence: 99%

The improvement of soil thermodynamics and its effects on land surface meteorology in the IPSL climate model

2016

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Abstract. This paper describes the implementation of an improved soil thermodynamics in the hydrological module of Earth system model (ESM) developed at the Institut Pierre Simon Laplace (IPSL) and its effects on land surface meteorology in the IPSL climate model. A common vertical discretization scheme for the soil moisture and for the soil temperature is adopted. In addition to the heat conduction process, the heat transported by liquid water into the soil is modeled. The thermal conductivity and the heat capacity are parameterized as a function of the soil moisture and the texture. Preliminary tests are performed in an idealized 1-D (one-dimensional) framework and the full model is then evaluated in the coupled land-atmospheric module of the IPSL ESM. A nudging approach is used in order to avoid the timeconsuming long-term simulations required to account for the natural variability of the climate. Thanks to this nudging approach, the effects of the modified parameterizations can be modeled. The dependence of the soil thermal properties on moisture and texture lead to the most significant changes in the surface energy budget and in the surface temperature, with the strongest effects on the surface energy budget taking place over dry areas and during the night. This has important consequences on the mean surface temperature over dry areas and during the night and on its short-term variability. The parameterization of the soil thermal properties could therefore explain some of the temperature biases and part of the dispersion over dry areas in simulations of extreme events such as heat waves in state-of-the-art climate models.

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“…For example, models that have positive temperature biases in the historical 116 period have been shown to project larger increases in temperatures (Cheruy et al 2014) 117 because they generally overestimate incoming shortwave radiation due to 118 misrepresentation of cloudiness. Furthermore, biases in L-A coupling strength can have 119 an important impact on models' future projections.…”

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confidence: 99%

Uncertainties in Future Projections of Summer Droughts and Heat Waves over the Contiguous United States

Herrera-Estrada

Sheffield

2017

J. Climate

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24 25Droughts and heat waves have important impacts on multiple sectors including water 26 resources, agriculture, electricity generation, and public health, so it is important to 27 understand how they will be affected by climate change. However, there is large 28 uncertainty in the projected changes of these extreme events from climate models. We 29 compare historical biases in models against their future projections to understand and 30 attempt to constrain these uncertainties. Historical biases in precipitation, near-surface air 31 temperature, evapotranspiration, and a land-atmospheric coupling metric are calculated 32 Similarly, it is challenging to predict greenhouse gas emissions because they depend on 85 human development and mitigation efforts. Uncertainty from climate models occurs 86 because they include different sets of physical processes, use different parameterizations, 87 or have different spatial and vertical resolutions, even though they share significant 88 components and seek to solve the same general physical equations (Knutti et al. 2013). 89 90The work presented here focuses on the uncertainty in future projections of droughts and 91 heat waves derived from the diversity of climate models in CMIP5, and seeks to 92 5 constrain it by using information on the models' historical biases. These biases are 93 calculated using observationally constrained model output for key variables of the land 94 surface, near-surface atmosphere, and their interactions, which are important in 95 representing and controlling the occurrence of droughts, heat waves, and their feedbacks. 96Land-atmospheric (L-A) coupling is one of the main physical processes examined. This 97 represents how much influence the land surface has on the lower part of the atmosphere 98 and vice versa. The type of coupling determines whether a region is water-limited 99

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Role of clouds and land-atmosphere coupling in midlatitude continental summer warm biases and climate change amplification in CMIP5 simulations

Cited by 102 publications

References 26 publications

Impact of a shallow groundwater table on the global water cycle in the IPSL land–atmosphere coupled model

Impact of a shallow groundwater table on the global water cycle in the IPSL land–atmosphere coupled model

The improvement of soil thermodynamics and its effects on land surface meteorology in the IPSL climate model

Uncertainties in Future Projections of Summer Droughts and Heat Waves over the Contiguous United States

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