Intercomparison of methods of coupling between convection and large‐scale circulation: 2. Comparison over nonuniform surface conditions

Abstract

As part of an international intercomparison project, the weak temperature gradient (WTG) and damped gravity wave (DGW) methods are used to parameterize large-scale dynamics in a set of cloudresolving models (CRMs) and single column models (SCMs). The WTG or DGW method is implemented using a configuration that couples a model to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. We investigated the sensitivity of each model to changes in SST, given a fixed reference state. We performed a systematic comparison of the WTG and DGW methods in different models, and a systematic comparison of the behavior of those models using the WTG method and the DGW method. The sensitivity to the SST depends on both the large-scale parameterization method and the choice of the cloud model. In general, SCMs display a wider range of behaviors than CRMs. All CRMs using either the WTG or DGW method show an increase of precipitation with SST, while SCMs show sensitivities which are not always monotonic. CRMs using either the WTG or DGW method show a similar relationship between mean precipitation rate and column-relative humidity, while SCMs exhibit a much wider range of behaviors. DGW simulations produce large-scale velocity profiles which are smoother and less topheavy compared to those produced by the WTG simulations. These large-scale parameterization methods provide a useful tool to identify the impact of parameterization differences on model behavior in the presence of two-way feedback between convection and the large-scale circulation.

Reexamining the Nonlinear Moisture‐Precipitation Relationship Over the Tropical Oceans

“…Many studies have used the exponential curve derived by Bretherton et al () from the version 5 SSM/I product as the simplified moisture‐convection relationship in simple models of tropical atmosphere or as the basis of model evaluation (Adames, ; Adames & Kim, ; Bretherton & Khairoutdinov, ; Daleu et al, ; Liu & Wang, ; Sobel & Maloney, ). We strongly suggest that the exponential curve derived from the version 7 SSM/I and SSMIS products should be utilized for future studies.…”

“…For example, a few recent theoretical studies of the Madden‐Julian Oscillation (MJO) used the coefficients a d and P r obtained by Bretherton et al () (e.g., Adames & Kim, ; Liu & Wang, ; Sobel & Maloney, ). The Bretherton et al () exponential curve has also served as a constraint on numerical model simulations (e.g., Bretherton & Khairoutdinov, ; Daleu et al, ). In Daleu et al (), the curve of Bretherton et al () was used as a reference against which the moisture‐convection relationship in a series of single‐column model simulations was evaluated.…”

“…The Bretherton et al () exponential curve has also served as a constraint on numerical model simulations (e.g., Bretherton & Khairoutdinov, ; Daleu et al, ). In Daleu et al (), the curve of Bretherton et al () was used as a reference against which the moisture‐convection relationship in a series of single‐column model simulations was evaluated.…”

Could Machine Learning Break the Convection Parameterization Deadlock?

“…In fact, most of the intermodel spread in equilibrium climate sensitivity can be traced back to the representation of clouds (Schneider et al, ). Convective schemes exhibit systematic biases in the vertical structure of heating and moistening, precipitation intensity, and cloud cover (Daleu et al, , ). These errors, in turn, feed back onto larger‐scale circulations, deteriorating general circulation model (GCM) simulations, and prediction skill (Bony et al, ).…”

“…MCS and the impact of shear are, however, crucial for correct representation of rainfall and radiative feedback (Cao & Zhang, ; Houze, ; Moncrieff, ; Moncrieff et al, , ; Tan et al, ). Finally, another challenge is that climate sensitivity is strongly related to the interaction between deep and shallow convection (Bony et al, ), and the coupling between clouds, convection, and the large‐scale circulation, which is currently poorly captured by parameterized convection (Bony et al, ; Daleu et al, ; Hohenegger & Stevens, ; Nie et al, ).…”