Sonia I. Seneviratne , Thierry Corti, Edouard L. Davin, Martin Hirschi, ⁎Eric B. Jaeger, Irene Lehner, Boris Orlowsky, Adriaan J. Teuling
Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland
Investigating soil moisture-climate interactions in a changing climate:
A review
Many complex land processes and feedbacks!
Some Preliminaries • “Evapotranspiration” = net effect of ground
evaporation and plant transpiration (mostly the latter)
• More than half of solar radiation used for land evapotranspiration
• Soil Moisture controls the partitioning of sensible and latent fluxes (Bowen Ratio) with implication on meteorology.
Clouds due to Plant Transpiration
• Dry Season in the Amazon Basin• Plants more active in Dry Season!
Role of Soil Moisture is 2-fold:
dS/dt = P – E – Rs – Rg dH/dt = Rn – λE – SH – G
Coupled through evapotranspiration term
Soil-Moisture affects climate through Δ Evapotranspiration (Latent heat flux)
Classic Conceptual Framework : 2 regimes
EF independent of soil moisture(e.g. Amazon in Summer)
No evaporation (e.g. Sahara)
Stron
g cou
pling
SM only affects climate in these transitional “hot spots” regions
1. strong SM-EVAP coupling2. large mean EVAP
*AGCM ensemble simulations from GLACE
WET: large EVAP, but not controlled by SM
DRY : EVAP controlled By Soil moisture, but mean too small
OBS evidence for different SM regimes
“SM limited” “ Transitional ” “Energy Limited”
Dry Mediterranean Temperate Forest Artic tundra
*Different Drivers of SM conspire to make similar EVAP in summer, despite different climates / land cover
Soil Moisture – Temperature Coupling
PotentialPositive feedback
Regions of strong SM-TEMP coupling
Transitional “hot spots” zonesWhere temperatureDepends on Soil-moisture
Radiation limited regimes
SM limited regimes
Soil Moisture – Precip Coupling
?? Don’t even know theCorrect sign here!
Regions of strong SM-Precip coupling
• In GLACE models, EVAP sensitivity appears to control both T and P coupling
• BUT significant inter-model variability • GLACE models may not be able to simulate negative SM-
Precip feedbacks found in CRM, RCM, and OBS
Other SM–climate interactions• Persistence (“memory”) of soil moisture anomalies
– SM acts as both water and energy storage– Potential implications for subseasonal/seasonal forecasting– Again depends on “hot spot” regions where coupling is strong
• Non-local and Large scale impacts- e.g. Advection of dry/hot air over negative SM anomalies - Apparently relevant for spread of European heat waves
• Soil Moisture – Albedo interaction – Soil moisture anomalies affect both bare-soil and vegetative albedo
• Interaction with Biogeochemical cycles– CO2 uptake by plants coupled with water loss via transpiration– Less water Less productive plants More CO2
Δ Soil Moisture in a warming world
Projected Decrease In precipitation in mid-Lat and sub-arid Regions
Drives SM decrease
* Note no change in SM in wet places in spite of increased Precip (“energy-limited” regime)
-Changes in Climate Variability Cannot be simply Derived from changesIn mean climate
- Again Mediterranean Hot Spot Clear
How SM can affect Climate Variability
Seasonal cycle
“Radiation-Limited”Wet regime
“SM-limited”Transitional regime
If a region shifts to a SM-limited regime and becomes a coupling “hot spot” then EVAP variability depends highly on SM and then SM is an important driver of TEMP (via Bowen Ratio)
Projected changes in SM-Temp coupling
Red = Soil moisture limited regime Blue = Radiation limited regime * Projected decrease in Precip causes Central Europe to switch from Blue to Red
Does SM-climate interactions amplify or damp Climate Variability?
• Wet soil moisture regime- EVAP is insensitive to soil moisture and has no effect
on CLIVAR• Transitional soil moisture regime
- EVAP very sensitive to soil moisture and significantly impacts climate
• Dry soil moisture regime– EVAP very sensitive to soil moisture, but very limited
If Climate changes from :Wet Transitional = Increased Climate VariabilityTransitional Dry = Decreased Climate Variability
Challenges and uncertainties • Significant divergence among models regarding SM–
Precipitation feedbacks – Still don’t know what sign is here, let alone magnitude!
• Evap sensitivity to soil moisture highly variable among LSMs
• Better Diagnostics to validate models• Coupling of key processes often more important to
climate prediction than absolute values of temp, evap, etc..
• How to assimilate disparate land data sets • More comprehensive ground network given land
heterogeneity
Challenges and uncertainties (cont.)
