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 | This is a set of daily variables that would be useful for diagnosing temperature variability and the processes involved. Temperature variability, in particular hot extremes, are highly impactful events and it is important to be able to predict how these are changing. Is it also important to assess the representation of the processes that contribute to temperature variability in the models and compare this with observations as well as intercompare across models to understand differences in behavior in how they represent both present day variability as well as projected changes. This proposed opportunity consists of a high priority variable group that we consider to be of the highest priority but also a medium priority variable group that is still desirable but considered to be lower priority. |
| desirable_ensemble_size | 1000 |
| expected_impacts | These fields can be used to diagnose how the distribution of temperature variability, including extremes, is represented in models over the present day and to both intercompare models and to compare them with observations. The basic fields tas, tasmax, and tasmin are also often used in attribution studies to provide context for temperature extremes that have occurred in the real world and to diagnose how external forcings have contributed to changing the likelihood of temperature extremes. They can be used to quantify how temperature variability is projected to change in each model. We need to also go beyond simply evaluating and projecting temperature variability and also understand the processes involved. The surface energy balance fields and circulation related fields could be used to diagnose difference in the factors that are controlling temperature variability across models and future projected changes in these factors. The land variables can be used to understand how changing water limitations might be impacting on temperature variability and to quantify the relative roles of changes in evaporation from the bare ground versus from plants, which seems important given that the change in evapotranspiration from plants can rely on rather uncertain biophysical responses to CO2. |
| justification_of_resources | This opportunity requests daily tas, tasmin, and tasmax which are necessary to quantify temperature variability, identify extremes, and quantify impactful impacts over the course of the diurnal cycle e.g., hotter minimum temperatures at night can have significant health impacts. Circulation related variables are requested to diagnose the synoptic conditions associated with heatwaves and the associated temperature advection (zg, ua, va, ta) and zg and ta would also be useful to quantify mid-tropospheric moist static energy which has been used in theories of temperature variability and change (Zhang and Boos (2023) 10.1073/pnas.2215278120 and Byrne (2021) 10.1038/s41561-021-00828-8.). Quantities that are useful for examining how water limitations are impacting on heat extremes (e.g., huss and ps for quantifying vapor pressure deficit, evspsbl and its components (evspsblsoi and evspsblveg) to explore the impacts of changing evaporation and the relative roles of changing evaporation from soils and vegetation separately. Quantifies for diagnosing the surface energy balance (hfls, hfss, rlds, rlus, rsds, rsus). Quantities for diagnosing the changing water availability from the land surface (mrsos) and the contributions to that availability (precipitation (pr) and runoff (mrros and mrro). Quantities that could be useful in diagnosing the impacts of clouds and surface wind speed on the surface energy balance (rsdscs, rldscs, sfcWind) and for diagnosing the behavior of the atmospheric boundary layer (maxpblz, minpblz) Changes in temperature variability and in extremes are one of the most impactful impacts of climate change. It is important that we predict how this will change but also understand the processes involved and validate the models in this regard and this understanding can feed back into model development. |
| lead_theme | Atmosphere |
| minimum_ensemble_size | 1 |
| name | Diagnosing temperature variability and extremes |
| opportunity_id | 64 |
| technical_notes | Proposer states ensemble size of 3 is a reasonable number but the max available would be preferable, and 1 is still useful. |
| data_request_themes | Impacts & Adaptation, Atmosphere, Land & Land-Ice, Earth System |
| experiment_groups | temperature_variability_opportunity, highresmip2-ia, scenarios |
| mips | DCPP, DAMIP |
| time_subsets | 80ac3156-a698-11ef-914a-613c0433d878 |
| variable_groups | temperature_variability_daily_highpriority, temperature_variability_daily_lowpriority |