Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing
Abstract Effective assessment of potential climate impacts requires the ability to rapidly predict the time‐varying response of climate variables. This prediction must be able to consider different combinations of forcing agents at high resolution. Full‐scale ESMs are too computationally intensive t...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2025-01-01
|
| Series: | Journal of Advances in Modeling Earth Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2024MS004523 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832583477247082496 |
|---|---|
| author | Christopher B. Womack Paolo Giani Sebastian D. Eastham Noelle E. Selin |
| author_facet | Christopher B. Womack Paolo Giani Sebastian D. Eastham Noelle E. Selin |
| author_sort | Christopher B. Womack |
| collection | DOAJ |
| description | Abstract Effective assessment of potential climate impacts requires the ability to rapidly predict the time‐varying response of climate variables. This prediction must be able to consider different combinations of forcing agents at high resolution. Full‐scale ESMs are too computationally intensive to run large scenario ensembles due to their long lead times and high costs. Faster approaches such as intermediate complexity modeling and pattern scaling are limited by low resolution and invariant response patterns, respectively. We propose a generalizable framework for emulating climate variables to overcome these issues, representing the climate system through spatially resolved impulse response functions. We derive impulse response functions by directly deconvolving effective radiative forcing and near‐surface air temperature time series. This enables rapid emulation of new scenarios through convolution and derivation of other impulse response functions from any forcing to its response. We present results from an application to near‐surface air temperature based on CMIP6 data. We evaluate emulator performance across 5 CMIP6 experiments including the SSPs, demonstrating accurate emulation of global mean and spatially resolved temperature change with respect to CMIP6 ensemble outputs. Global mean relative error in emulated temperature averages 1.49% in mid‐century and 1.25% by end‐of‐century. These errors are likely driven by state‐dependent climate feedbacks, such as the non‐linear effects of Arctic sea ice melt. We additionally show an illustrative example of our emulator for policy evaluation and impact analysis, emulating spatially resolved temperature change for a 1,000 member scenario ensemble in less than a second. |
| format | Article |
| id | doaj-art-69a83a0f000641048946cd04aa161d03 |
| institution | Kabale University |
| issn | 1942-2466 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Journal of Advances in Modeling Earth Systems |
| spelling | doaj-art-69a83a0f000641048946cd04aa161d032025-01-28T13:21:09ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662025-01-01171n/an/a10.1029/2024MS004523Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative ForcingChristopher B. Womack0Paolo Giani1Sebastian D. Eastham2Noelle E. Selin3Department of Aeronautics and Astronautics Massachusetts Institute of Technology Cambridge MA USADepartment of Earth, Atmospheric, and Planetary Sciences Massachusetts Institute of Technology Cambridge MA USADepartment of Aeronautics Imperial College London Brahmal Vasudevan Institute for Sustainable Aviation London UKMassachusetts Institute of Technology Institute for Data, Systems, and Society Cambridge MA USAAbstract Effective assessment of potential climate impacts requires the ability to rapidly predict the time‐varying response of climate variables. This prediction must be able to consider different combinations of forcing agents at high resolution. Full‐scale ESMs are too computationally intensive to run large scenario ensembles due to their long lead times and high costs. Faster approaches such as intermediate complexity modeling and pattern scaling are limited by low resolution and invariant response patterns, respectively. We propose a generalizable framework for emulating climate variables to overcome these issues, representing the climate system through spatially resolved impulse response functions. We derive impulse response functions by directly deconvolving effective radiative forcing and near‐surface air temperature time series. This enables rapid emulation of new scenarios through convolution and derivation of other impulse response functions from any forcing to its response. We present results from an application to near‐surface air temperature based on CMIP6 data. We evaluate emulator performance across 5 CMIP6 experiments including the SSPs, demonstrating accurate emulation of global mean and spatially resolved temperature change with respect to CMIP6 ensemble outputs. Global mean relative error in emulated temperature averages 1.49% in mid‐century and 1.25% by end‐of‐century. These errors are likely driven by state‐dependent climate feedbacks, such as the non‐linear effects of Arctic sea ice melt. We additionally show an illustrative example of our emulator for policy evaluation and impact analysis, emulating spatially resolved temperature change for a 1,000 member scenario ensemble in less than a second.https://doi.org/10.1029/2024MS004523climate emulationGreen's functionresponse functionspatially explicittemperature emulation |
| spellingShingle | Christopher B. Womack Paolo Giani Sebastian D. Eastham Noelle E. Selin Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing Journal of Advances in Modeling Earth Systems climate emulation Green's function response function spatially explicit temperature emulation |
| title | Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing |
| title_full | Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing |
| title_fullStr | Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing |
| title_full_unstemmed | Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing |
| title_short | Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing |
| title_sort | rapid emulation of spatially resolved temperature response to effective radiative forcing |
| topic | climate emulation Green's function response function spatially explicit temperature emulation |
| url | https://doi.org/10.1029/2024MS004523 |
| work_keys_str_mv | AT christopherbwomack rapidemulationofspatiallyresolvedtemperatureresponsetoeffectiveradiativeforcing AT paologiani rapidemulationofspatiallyresolvedtemperatureresponsetoeffectiveradiativeforcing AT sebastiandeastham rapidemulationofspatiallyresolvedtemperatureresponsetoeffectiveradiativeforcing AT noelleeselin rapidemulationofspatiallyresolvedtemperatureresponsetoeffectiveradiativeforcing |