The pseudo-global-warming (PGW) approach: methodology, software package PGW4ERA5 v1.1, validation, and sensitivity analyses

Abstract

Abstract. The term “pseudo-global warming” (PGW) refers to a simulation strategy in regional climate modeling. The strategy consists of directly imposing large-scale changes in the climate system on a control regional climate simulation (usually representing current conditions) by modifying the boundary conditions. This differs from the traditional dynamic downscaling technique where output from a global climate model (GCM) is used to drive regional climate models (RCMs). The PGW climate changes are usually derived from a transient global climate model (GCM) simulation. The PGW approach offers several benefits, such as lowering computational requirements, flexibility in the simulation design, and avoiding biases from global climate models. However, implementing a PGW simulation is non-trivial, and care must be taken not to deteriorate the physics of the regional climate model when modifying the boundary conditions. To simplify the preparation of PGW simulations, we present a detailed description of the methodology and provide the companion software PGW4ERA5 facilitating the preparation of PGW simulations. In describing the methodology, particular attention is devoted to the adjustment of the pressure and geopotential fields. Such an adjustment is required when ensuring consistency between thermodynamical (temperature and humidity) changes on the one hand and dynamical changes on the other hand. It is demonstrated that this adjustment is important in the extratropics and highly essential in tropical and subtropical regions. We show that climate projections of PGW simulations prepared using the presented methodology are closely comparable to traditional dynamic downscaling for most climatological variables.

Application of the Pseudo‐Global Warming Approach in a Kilometer‐Resolution Climate Simulation of the Tropics

“…The initial and boundary conditions of the PGW simulation are obtained following Brogli et al. (2023) using the software PGW4ERA5 v1.1 by adding the mean climate change signal (so‐called climate deltas) for temperature, relative humidity, horizontal wind and sea and land surface temperature to the ERA5 boundary conditions of the CTRL simulation period. The climate deltas are a function of latitude, longitude, pressure and month, and represent the mean annual cycle of the spatial change pattern between two climate states, that is, here between a historical and a future scenario climatology.…”

“…The output of the MPI‐ESM is obtained as daily mean values from the CMIP6 output group CFday (on a regular latitude‐longitude grid but on the native vertical coordinate) and aggregated into monthly means. Since this output group was intended for the Cloud Feedback Model Intercomparison Project (Webb et al., 2017) it is provided at fine vertical resolution which is desirable to accurately represent the difference in warming across the trade‐wind inversion (see Brogli et al., 2023, Figure 5 and corresponding discussion). The obtained changes are displayed in Figures S1–S5 of Supporting Information .…”

“…Usually, a historical control simulation and a future scenario simulation are compared to extract the climate change signal. An alternative to this dynamical downscaling approach is the pseudo‐global warming (PGW) approach (Adachi & Tomita, 2020; Brogli et al., 2023) in which reanalysis boundary conditions are used for both the control and the scenario simulation. The climate change signal is obtained by imposing large‐scale changes in the climate system on the reanalysis boundary fields of the scenario simulation.…”

“…The climate change signal is obtained by imposing large‐scale changes in the climate system on the reanalysis boundary fields of the scenario simulation. Doing so has the advantage that the biases from the GCM run do not enter the limited‐area simulation, and that relatively short simulation periods can be used (Brogli et al., 2023). The PGW approach has extensively been applied in the mid‐latitudes (Brogli et al., 2019; Kröner et al., 2017; Rasmussen et al., 2011; Sato et al., 2007; Schär et al., 1996; Wu & Lynch, 2000).…”

Application of the Pseudo-Global Warming Approach in a Kilometer-Resolution Climate Simulation of the Tropics

“…Usually, a historical control simulation and a future scenario simulation are compared to extract the climate change signal. An alternative to this dynamical downscaling approach is the pseudo-global warming (PGW) approach (Adachi & Tomita, 2020;Brogli et al, 2023) in which reanalysis boundary conditions are used for both the control and the scenario simulation. The climate change signal is obtained by imposing large-scale changes in the climate system on the reanalysis boundary fields of the scenario simulation.…”