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Coherent Mechanistic Patterns of Tropical Land Hydroclimate Change

September 5th, 2023

Key Findings

  • To investigate future temperature extremes and connections with the hydrological cycle over land, the authors introduce a process-based method which organizes the spatial complexity by climatological aridity, and organizes the temporal complexity by daily soil moisture.
  • By showing data in a behavioral phase space (rather than in a map view), patterns become apparent which reveal physical mechanisms connecting soil moisture, latent heat flux (evaporation from soils and open water, along with transpiration from plants), and temperature extremes.
  • A consistent average critical soil moisture value is found in the models; below this value, moisture limitation exacerbates temperature extremes.
  • This compact new display highlights the repartitioning of rainfall toward fewer, stronger events in the future.
  • The process-oriented regimes revealed by this analysis help explain how land deviates from the ocean-based “wet-get wetter/dry-get-drier” paradigm.

Suqin Q. Duan, Kirsten L. Findell, and Stephan A. Fueglistaler. Geophysical Research Letters. DOI: 10.1029/2022GL102285

Accurate predictions of future changes in hydroclimate over land, in particular the magnitude and frequency of extreme heat, extreme rainfall, and droughts are of paramount importance for society. Gaps in our process-level understanding of land-atmosphere interactions remain, in particular with respect to the connection between changes in different types of extremes, and the connection between changes in local land-atmosphere interactions with the global-scale response of the hydrological cycle to climate forcings. The authors introduce a novel method that preserves the mechanistic local, daily-mean time scale understanding while substantially reducing the dimensionality of the global, time-varying problem in order to provide an integrated, big-picture perspective.

Predictions of hydroclimate changes (temperature, precipitation, evaporation, etc.) over land in a warming world rely largely on model simulations with often diverging results when presented in map view. The authors’ process-based method organizes the spatial complexity by climatological aridity, and organizes the temporal complexity by daily soil moisture (SM). This allows for the analysis of model predictions in a comprehensive yet compact display which clearly reveals the connections between variables and the mechanisms responsible for changes. Key results include the impact of SM limitation on elevated temperature extremes and the trend toward fewer but stronger rainfall events.

This compact display is an efficient new tool for intercomparisons between models. The remarkably clean results suggest quantitative theoretical advances are possible despite the complexity of the system. Improved understanding of the drivers of extreme temperatures will help shed light on future temperature extremes, and connections with the hydrological cycle over land.

Figure 1: (a) Schematic of the regimes of surface latent heat flux as a function of surface soil moisture. (b) Geographical pattern of climatological warm-season aridity index (AI) in the tropics sorted into percentiles. (c) Multi-model mean pre-industrial soil moisture overlain by a schematic of the regimes in the phase space of AI percentiles (separating locations based on climate) and daily soil moisture percentiles (separating days of relatively drier/moister conditions at a given location).


Figure 2: Multi-model mean changes in surface soil moisture (SM), latent heat flux, daily-maximum temperature, precipitation, and precipitation-minus-evaporation between the 4xCO2 and the pre-industrial control (piCtl) climate states, normalized by the mean tropical ocean warming. The normalization is conducted before averaging over models. Pink lines show the SM value of 20 kg/m2 in the piCtl (solid) and 4xCO2 (dashed) climate states.