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Land Surface Hydrology and the Earth System

Land Surface Hydrology and the Earth System Christopher Taylor Eleanor Blyth Doug Clark Richard Harding Centre for Ecology and Hydrology, Wallingford Nic Gedney Hadley Centre Dave Lawrence CGAM, University of Reading. Land Surface Hydrology and the Earth System.

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Land Surface Hydrology and the Earth System

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  1. Land Surface Hydrology and the Earth System Christopher Taylor Eleanor Blyth Doug Clark Richard HardingCentre for Ecology and Hydrology, WallingfordNic GedneyHadley CentreDave LawrenceCGAM, University of Reading

  2. Land Surface Hydrology and the Earth System • Role of land surface in hydrological cycle • Impacts of variability (spatial and temporal) on atmosphere • Modelling • requirements • point processes • sensitivities of soil hydrology in GCM • horizontal complexity • Conclusions

  3. Atmosphere Precipitation Evaporation Soil moisture store Runoff Ocean Role of land surface in hydrological cycle • After rain/snow, surface hydrology determines when water available for evaporation back into atmosphere, or runoff into ocean • Continental regions, surface evaporation is important part of atmospheric moisture budget, + controls diurnal heating • Potential for feedbacks between soil wetness and atmosphere

  4. Temporal Variability Impact of Interactive Soil Moisture on Climate Variability in GCM - North America RH spectrum: interactive soil moisture experiment RH spectrum: prescribed soil moisture experiment Delworth and Manabe (1993) Soil moisture-atmosphere interactions increase variability of atmosphere and modify time scales of variability

  5. Temporal Variability Impact of Improved Surface Description on Sahelian Weather Systems in GCM • Introduced more realistic controls on evaporation: • diurnal timescale - stomatal conductance • daily timescale – soil drainage and bare soil evaporation • Affected diurnal and synoptic weather systems Power spectra of rainfall - Sahel Taylor and Clark, QJRMS, 2001

  6. ~2000 km Spatial Variability Patterns of soil moisture in Sahel inferred from Meteosat Red (warm): soil surface dried Blue (cool): recent rain Taylor et al, QJRMS, 2003 Rainfall variability at range of scales produces surface heterogeneity

  7. Impacts of Spatial Variability on Atmosphere: Convective Scale Annual Rainfall 1992 (HAPEX-Sahel) Extreme gradients rain can develop over series of storms Not random, nor forced by topography Soil moisture feedback: memory of past storms retained in soil moisture + atmospheric humidity gradients Feedbacks appear even at 10km! Taylor and Lebel, MWR, 1998

  8. Impacts of Spatial Variability on Atmosphere: Convective Scale A Sahelian squall line approaching • Use cloud-resolving model to show that rainfall from organised convective systems very sensitive to surface variability • Dynamical feedbacks at scale of individual convective cells reinforce soil moisture variability, particularly when surface length scales matches convective cell length scale Rainfall increase Wet patch Rainfall decrease Clark et al, QJRMS, 2003

  9. Impacts of Spatial Variability on Atmosphere: Synoptic Scale 1000 km Satellite analysis shows that wet and dry patches occur at large scale. Composite “hotspot” Southerlies Atmospheric analyses suggest: higher temperatures lower surface pressure Anomaly TIR [C] vortex develops subsequent rainfall modulated Northerlies Degrees longitude Taylor et al, submitted QJRMS

  10. Modelling of Surface Hydrology • Land surface hydrology schemes need to partition: • net radiation into sensible and latent heat • rainfall into evaporation, runoff, storage • Requires modelling of: • controls on evaporation - stomatal opening • pathways of water (+ snow) through vegetation canopy, soil and landscape • These processes complex + not always well understood at large scale • Parameters not universal but depend on: • soil properties • vegetation properties • topography • These properties vary widely over globe.

  11. Obs. MOSES + snow/canopy processes Standard MOSES Essery and Clark, GPC 2003 Runoff Modelling point processes: need for complexity Example of interception of snow by forest canopy in Swedish catchment. Simple model, moisture rapidly recycled to atmosphere Adding complexity, model runoff is enhanced and delayed Month of year

  12. Evaporative fraction Runoff (mm/day) Gedney et al JClim 2000 Critical soil moisture Scaled soil moisture Scaled soil moisture Comparison of Surface Schemes Within GCMs 4 GCMs run, each with 2 versions of own surface scheme Diagnosis over Amazonia (similar results elsewhere): (i) Evaporative fraction increases to “critical point”, tends to flatten off for wetter soils (ii) Runoff response quite different in different schemes (iii) Models occupy characteristic soil moisture regimes, some unrealistic – partly due to forcing (precip) Soil moisture state is closely linked to runoff at critical point in scheme

  13. Soil moisture stress in Unified Model Large parts of world are either very dry (purple) or very wet (red) Not v. realistic Extreme soil moisture states can produce positive feedbacks on precip. to exacerbate problem Using alternative soil hydrology parameterisation (incl. greater runoff at critical point), reduce number of extreme points Still left with unrealistic soil moisture where precip. poor

  14. Horizontal versus vertical complexity Surface schemes tended to focus on vertical processes (e.g. evaporation) Can be compared with field observations But landscape has obvious horizontal complexity Comparison of impact of complexity in vertical (soil type) with horizontal (topography) Suggests that horizontal complexity at least as important Blyth, IAHS 2001

  15. Sub-grid variability GCM grid cell Sub-grid variations in near-surface moisture due to recent rain - large variability in direct evaporation from soil - large variability in drainage rates Soil moisture using mean rainfall Sub-grid rainfall distribution assumed “True” surface soil moisture Day of year Compare length-scale of forcing on surface simulations Taylor and Blyth JGR 2000

  16. Concluding Remarks • Land surface hydrology plays important role in earth system • Modelling requires: • appropriate complexity and scale • realistic forcing • Use of new global datasets (for parameters and validation) will produce better models

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