Search for: All records

Many chemical processes depend non‐linearly on temperature. Gravity‐wave‐induced temperature perturbations have been shown to affect atmospheric chemistry, but accounting for this process in chemistry‐climate models has been a challenge because many gravity waves have scales smaller than the typical model resolution. Here, we present a method to account for subgrid‐scale orographic gravity‐wave‐induced temperature perturbations on the global scale for the Whole Atmosphere Community Climate Model. Temperature perturbation amplitudesconsistent with the model's subgrid‐scale gravity wave parameterization are derived and then used as a sinusoidal temperature perturbation in the model's chemistry solver. Because of limitations in the parameterization, we explore scaling ofbetween 0.6 and 1 based on comparisons to altitude‐dependentdistributions of satellite and reanalysis data, where we discuss uncertainties. We probe the impact on the chemistry from the grid‐point to global scales, and show that the parameterization is able to represent mountain wave events as reported by previous literature. The gravity waves for example, lead to increased surface area densities of stratospheric aerosols. This increases chlorine activation, with impacts on the associated chemical composition. We obtain large local changes in some chemical species (e.g., active chlorine, NO_x, N₂O₅) which are likely to be important formore »comparisons to airborne or satellite observations, but the changes to ozone loss are more modest. This approach enables the chemistry‐climate modeling community to account for subgrid‐scale gravity wave temperature perturbations interactively, consistent with the internal parameterizations and are expected to yield more realistic interactions and better representation of the chemistry.

This paper provides a comprehensive derivation of the total energy equations for the atmospheric components of Earth System Models (ESMs). The assumptions and approximations made in this derivation are motivated and discussed. In particular, it is emphasized that closing the energy budget is conceptually challenging and hard to achieve in practice without resorting to ad hoc fixers. As a concrete example, the energy budget terms are diagnosed in a realistic climate simulation using a global atmosphere model. The largest total energy errors in this example are spurious dynamical core energy dissipation, thermodynamic inconsistencies (e.g., coupling parameterizations with the host model) and missing processes/terms associated with falling precipitation and evaporation (e.g., enthalpy flux between components). The latter two errors are not, in general, reduced by increasing horizontal resolution. They are due to incomplete thermodynamic and dynamic formulations. Future research directions are proposed to reconcile and improve thermodynamics formulations and conservation principles.

The Single Column Atmosphere Model (SCAM) is a single column model version of the Community Atmosphere Model (CAM). Here we describe the functionality and features of SCAM6, available as part of CAM6 in the Community Earth System Model, version 2 (CESM2). SCAM6 features a wide selection of standard cases, as well as the ability to easily configure a case specified by the user based on a particular point in a CAM 3‐D simulation. This work illustrates how SCAM6 reproduces CAM6 results for physical parameterizations, mostly of moisture and clouds. We demonstrate how SCAM6 can be used for model development through different physics selections, as well as with parameter sweep experiments to highlight the sensitivity of cloud properties to the specification of the vapor deposition process in the cloud microphysics. Furthermore, we use SCAM6 to illustrate the sensitivity of CAM6 cloud radiative properties and precipitation to variable drop number (cloud microphysics properties). Finally, we illustrate how SCAM6 can be used to explore critical emergent processes such as cloud feedbacks and show that CAM6 cloud responses to surface warming in stratus and stratocumulus regimes are similar to those in CAM5. CAM6 has a larger response in the shallow cumulus regime thanmore »CAM5. CAM6 cloud feedbacks in the shallow cumulus regime are sensitive to turbulence parameters. SCAM6 is thus a valuable tool for model development, evaluation, and scientific analy sis and an important part of the model hierarchy in Community Earth System Model, version 2.

We examine the response of the Community Earth System Model Versions 1 and 2 (CESM1 and CESM2) to abrupt quadrupling of atmospheric CO₂concentrations (4xCO2) and to 1% annually increasing CO₂concentrations (1%CO2). Different estimates of equilibrium climate sensitivity (ECS) for CESM1 and CESM2 are presented. All estimates show that the sensitivity of CESM2 has increased by 1.5 K or more over that of CESM1. At the same time the transient climate response (TCR) of CESM1 and CESM2 derived from 1%CO2 experiments has not changed significantly—2.1 K in CESM1 and 2.0 K in CESM2. Increased initial forcing as well as stronger shortwave radiation feedbacks are responsible for the increase in ECS seen in CESM2. A decomposition of regional radiation feedbacks and their contribution to global feedbacks shows that the Southern Ocean plays a key role in the overall behavior of 4xCO2 experiments, accounting for about 50% of the total shortwave feedback in both CESM1 and CESM2. The Southern Ocean is also responsible for around half of the increase in shortwave feedback between CESM1 and CESM2, with a comparable contribution arising over tropical ocean. Experiments using a thermodynamic slab‐ocean model (SOM) yield estimates of ECS that are in remarkable agreement with those from fully coupledmore »Earth system model (ESM) experiments for the same level of CO₂increase. Finally, we show that the similarity of TCR in CESM1 and CESM2 masks significant regional differences in warming that occur in the 1%CO2 experiments for each model.

The Community Earth System Model Version 2 (CESM2) has an equilibrium climate sensitivity (ECS) of 5.3 K. ECS is an emergent property of both climate feedbacks and aerosol forcing. The increase in ECS over the previous version (CESM1) is the result of cloud feedbacks. Interim versions of CESM2 had a land model that damped ECS. Part of the ECS change results from evolving the model configuration to reproduce the long‐term trend of global and regional surface temperature over the twentieth century in response to climate forcings. Changes made to reduce sensitivity to aerosols also impacted cloud feedbacks, which significantly influence ECS. CESM2 simulations compare very well to observations of present climate. It is critical to understand whether the high ECS, outside the best estimate range of 1.5–4.5 K, is plausible.