Abstract
AbstractThis work is motivated by the identification of the land‐atmosphere interactions as one of the key sources of uncertainty in climate change simulations. It documents new developments in related processes, namely, boundary layer/convection/clouds parameterizations and land surface parameterization in the Earth System Model of the Institut Pierre Simon Laplace (IPSL). Simulations forced by prescribed oceanic conditions are produced with different combinations of atmospheric and land surface parameterizations. They are used to explore the sensitivity to the atmospheric physics and/or soil physics of major biases in the near surface variables over continents, the energy and moisture coupling established at the soil/atmosphere interface in not too wet (energy limited) and not too dry (moisture limited) soil moisture regions also known as transition or “hot‐spot” regions, the river runoff at the outlet of major rivers. The package implemented in the IPSL‐Climate Model for the Phase 6 of the Coupled Models Intercomparison Project (CMIP6) allows us to reduce several biases in the surface albedo, the snow cover, and the continental surface air temperature in summer as well as in the temperature profile in the surface layer of the polar regions. The interactions between soil moisture and atmosphere in hotspot regions are in better agreement with the observations. Rainfall is also significantly improved in volume and seasonality in several major river basins leading to an overall improvement in river discharge. However, the lack of consideration of floodplains and human influences in the model, for example, dams and irrigation, impacts the realism of simulated discharge.
Highlights
Earth's climate and its evolution are determined by interactions between the ocean, the atmosphere, ice caps, and land surfaces under the external solar forcing and the atmospheric composition
The main model modifications between the “new physics” and 6A are the revision of the eddy diffusion Yamada (1983) 1.5 order turbulent scheme already implemented in the new physics, the introduction of a stochastic triggering designed to make the frequency of occurrence of new convective systems within a mesh aware of the grid cell size (Rochetin, Couvreux, et al, 2014; Rochetin, Grandpeix, et al, 2014), a modification of the thermal plume model for the representation of stratocumulus clouds (Hourdin et al, 2019), the introduction of the latent heat release associated with water freezing, and a new parameterization of non orographic gravity waves targeting the representation of the quasi‐biennial oscillation (QBO)
Investigating the minimum and maximum daily temperature shows a widespread warm bias of daily minimum temperature over the midlatitude (Figure 8). This bias is present over the whole year for the AP physical package used for CMIP5, and only in JJA for the 6A package used for CMIP6, it is very marginally sensitive to the land surface scheme. This is consistent with the reduction of the turbulent mixing in the PBL for the stable boundary layers obtained with the 6A atmospheric physics and with the results of Wei et al (2017), which suggested that a bias in the simulated PBL mixing could very likely contribute to the temperature bias common to most of the models that participated to CMIP5 with Atmospheric Model Intercomparison Project (AMIP) experiments
Summary
Earth's climate and its evolution are determined by interactions between the ocean, the atmosphere, ice caps, and land surfaces under the external solar forcing and the atmospheric composition For these reasons, numerical models need to couple all these components of the system when they are used for running climate projections to anticipate the impacts of climate change. Numerical models need to couple all these components of the system when they are used for running climate projections to anticipate the impacts of climate change In this general framework, the land surface‐atmosphere interactions strongly modulate the regional climate (e.g., Seneviratne et al, 2010); they control climate hazards, and their consequences (Jaeger & Seneviratne, 2011; Miralles et al, 2014) impact the freshwater discharge into the oceans and, in turn, the thermohaline circulation (Peterson et al, 2002). The results are summarized, and directions for further improvements are presented
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