Back to opportunities | Category Index
These are the intended use-case/justification for one or multiple variable groups. Opportunities are linked to relevant experiment groups. Identifying opportunities helps to provide a structure to map variables against requirements. Each opportunity description will convey why this combination of variables and experiments is important and how they contribute to impact.
| Attribute | Value |
|---|---|
| description | Research on ongoing climate change creates awareness that we may be heading for uncharted territory regarding future environmental conditions. We are aware that climate models, applied to create projections of future climate, might be employed outside their calibrated range, raising questions regarding the degree of uncertainty in our expectations for the future. Greater understanding of how Earth's climate has changed in the past provides valuable context for its current and future changes. It is therefore valuable to study the record of past climate states and to aim to better understand the dynamics of the Earth System in the context of different past, present, and future background climates. This may provide an improved understanding of the envelope of potential future climates that we may head into, thereby creating a link between future and past (e.g., Burke et al., 2018). Paleoclimate research as proposed for CMIP7 will follow several routes. First, it involves a stock take of conventional climate model output that samples the state of various subsystems of the Earth System. Examples include ocean circulation and climate variables that influence and inform on the state of sea ice, ice sheets and permafrost. Beyond providing quantification of large-scale patterns and variability, this route will support understanding the status of tipping elements and evaluating the possibility of abrupt climate change. As a second route, we consider novel developments in paleoclimate modelling. Where modelling groups can do so, we invite employment of stable water and other isotope dynamics, enabling a more direct comparison of model output with the proxy-record. Furthermore, we acknowledge significant recent advances in paleodata assimilation. These allow us to systematically combine climate model output with paleoclimate proxy reconstructions to create probabilistic reanalyses of the past. Research using single models has provided large insights, for example in the Last Glacial Maximum (Osman et al, 2021), which are vital to underpin constraints on climate sensitivity. The next crucial step is similar work based on an ensemble of CMIP7 models. The combination of methods described above will provide us with a reflection on climate model performance against the glaciologic and geologic records. The approach will help us to better interpret any model-data discord. In combination with simulations from other MIPs (e.g. ScenarioMIP), the research will highlight where model sensitivity and model processes must be improved to better capture patterns and variability of climates significantly different from today. References: Burke, K. D., Williams, J. W., Chandler, M. A., Haywood, A. M., Lunt, D. J., and Otto-Bliesner, B. L.: Pliocene and Eocene provide best analogs for near-future climates, _P. Natl. Acad. Sci._ USA, 115, 13288–13293, https://doi.org/10.1073/pnas.1809600115, 2018. Osman, M.B., Tierney, J.E., Zhu, J. _et al._ Globally resolved surface temperatures since the Last Glacial Maximum. _Nature_ **599**, 239–244 (2021). https://doi.org/10.1038/s41586-021-03984-4 |
| expected_impacts | This data request aims at enabling the community to link model performance, and inferences on climate dynamics, across time scales - from past, to present, to future. We foresee the following use cases: 1. Studying the state of the ocean, including various ocean circulation patterns, across time scales, from the Last Interglacial, and even earlier time slices in PMIP, to the future. 2. The meridional overturning circulation (MOC) was different in the past and is projected to change in the future. Model dependency may be an issue and model parameterizations can lead to biases in projections. Having the upcoming CMIP7 models produce metrics relevant for sampling model dependency and model uncertainty in MOC, for as many simulations and experiments as possible, would allow us to make the most of the information contained in the past MOC reconstructions. 3. Understanding the performance of sea ice models in climate states that are significantly different from today is key to the quantification of various climate feedbacks. We request several additional sea ice metrics that will help to understand why sea ice models may show a different response to similar forcings. While our clear focus is on the PMIP-sponsored abrupt-127k simulation, we also aim to compare the results to DECK, historical and future scenarios. 4. Beyond the strong interest to gain an understanding of changes in the hydrological cycle under the impact of different climate forcings, from past to future, simulated stable water isotope output may support the interpretation of proxy records of past climates, which are often linked to isotope compositions. For recent climate, simulated isotopes can be compared to observational networks, providing an opportunity to compare skill of isotope-enabled climate models. 5. Studying radiative and energetic balance of the Earth System across time scales will put ongoing anthropogenic climate change into perspective. Via the requested additional albedo and fx quantities, and by means of a quantification of changes in ocean heat content, we hope to contribute to analyzing Earth's climate in the context of its long-term response to various forcings. 6. Proxy system models underpin paleodata assimilation, which take output from climate models and determine what a proxy record would look like if it had seen that simulated climate. Lodging the output required to run these models would not only provide an advance in data model comparisons, but would allow multi-model reanalyses to be made. 7. Improved understanding of the state of the land cryosphere and of its future are of key interest in a changing climate. How much carbon may become released from melting permafrost? What are the stabilizing and destabilizing mechanisms that control sea level in a warm climate? These and other questions will be targeted from the viewpoint of paleoclimate research across time scales. |
| justification_of_resources | Most requested variables are part of the baseline data request and are assumed to be produced by modelling centers anyway. This is the case for most of the higher voluminous variables that go beyond the ocean surface and will help us to get a more detailed understanding of the ocean’s state and dynamics for climates significantly different from today. In some cases, we request variables that are beyond the baseline request. For some of them the definition process has been initiated. We believe that our request will lead to a modest increase of resources consumption in comparison to the overall CMIP7 data request. Below we justify required resources by outlining how requested variable groups are key to realize our proposed scientific goals and impacts. Gaining improved understanding of the cryosphere (snow, land ice, sea ice), and of its response to different climate drivers, necessitates detailed model output that relates to land ice, sea ice, permafrost, and albedo. For the latter we either request the model-diagnosed albedos of snow, ice, and snow/ice-free surfaces across land and ocean (down to the subgrid-scale level), or the respective radiative quantities to compute them. At the interface between modern and orbital time scales we necessitate some variables at higher temporal resolution than commonly done. This involves both top of the atmosphere radiative fluxes, and first order climate metrics, like surface temperature and rain fluxes, for performing calendar correction in simulations where the Earth's orbit differs from today. Understanding the state of the ocean, ocean dynamics, and related tipping points, necessitates availability not only of ocean state metrics (like heat, salt and volume transports and inventories), but also the relevant boundary conditions at the ocean surface, including continental runoff. There are parallels to other relevant CMIP7 opportunities, and hence variables requested by us have a value beyond paleoclimate research. A more direct comparison of model output to proxies, applications of CMIP model output in the framework of paleodata assimilation, and a more complete appreciation of slow adjustment processes in the Earth System necessitate variables that are a bit more specific than those typically requested for other CMIP7 opportunities. This involves extended information on various boundary conditions, but also refers to information on the state of the deep ocean. We note that there may be a benefit well beyond paleoclimate research. For example, simulated stable water isotopes may be compared to modern observational data sets and help to better understand hydrological transport processes in climate models. Since we would like to compare model performance in the PMIP sponsored abrupt-127k simulation also to climate states, it is necessary to provide the aforementioned types of model output also for other simulations than those typically grouped under the term “paleo”. |
| lead_theme | Ocean & Sea-Ice |
| minimum_ensemble_size | 1 |
| name | Paleoclimate research at the interface between past, present, and future |
| notes | For deck we are particularly interested in PI (plus historical), but we note that also for simulations that study the change of an abrupt or ramp CO2 forcing providing the requested additional variables will contribute to a better understanding of model dynamics in the framework of a rapidly changing climate. |
| opportunity_id | 51 |
| data_request_themes | Atmosphere, Land & Land-Ice, Ocean & Sea-Ice, Earth System |
| experiment_groups | pmip, picontrol, scenarios, historical |
| mips | PMIP |
| time_subsets | all |
| variable_groups | paleo_atmosphere, paleo_cryosphere_high_priority, paleo_cryosphere_low_priority, paleo_cryosphere_medium_priority, paleo_fx ... and 8 morepaleo_atmosphere, paleo_cryosphere_high_priority, paleo_cryosphere_low_priority, paleo_cryosphere_medium_priority, paleo_fx, paleo_land_atmosphere_surface, paleo_ocean, paleo_ocean_3D, paleo_ocean_transports, paleo_permafrost, paleo_radiation_fluxes, paleo_stable_isotopes, paleodata_assimilation |