Land Data Assimilation

Tristan Quaife, Emily Lines, Ian Davenport, Jon Styles, Philip Lewis Robert Gurney.

Rationale

• Satellite data one of the most powerful observational constraints on land surface models– Synoptic spatial and temporal coverage – Direct measure of energy leaving the system

Rationale

• Highly derived satellite ‘products’ often physically inconsistent with assumptions in LSMs and difficult to quantify uncertainty– Hence want to use low-level data (e.g. radiance)

• Most LSMs lack appropriate physical representation required for this– For example typically 1D turbid medium canopies

Land components of earth system models

• Developed to calculate the exchange of energy and water between the land surface and atmosphere

Radiation interactions withatm, veg. and soil

Groundwater andChannel flows

Precipitation &evaporation

Evapo-transpiration

• Developed for NWP – extended for other studies

• Fluxes added for carbon, nutrients, aerosols

Processes and timescales

• Diurnal– Radiation and water balance

• Seasonal– Phenology– Snow

• Centennial– Vegetation dynamics– Soil turnover

EO data

• Assimilation of EO data (cf state estimation) is relevant at diurnal and seasonal timescales…

• … for forecasting, seasonal forecasting, crop monitoring, carbon cycle …

• Models not developed with EO in mind • Canopy models simple

– Limited handling of canopy structure– Can’t simulate BRFs

International landscape

• UK Community model – JULES / TRIFFID• US Community model – CLM • Meteo-France – ISBA • ECMWF – [C/H]-TESSEL • EC-Earth community model also uses TESSEL

scheme

Concept• Build parsimonious land surface scheme

– Water, energy and carbon fluxes• Invest complexity in the necessary physics

to represent satellite observations correctly– Optical, thermal and passive microwave

• Embed in DA scheme as early as possible– EOLDAS/Particle Filter

Model concept

Soil column

Photosynthesis& Allocation

Interception& Evaporation

Vegetationprocesses

Soilprocesses

Carbon Water SW LW

Soil “skin” layer

Force restore water/heat

rr v tr r

W veg P E E Rt

2

2

1g g tr

w

w P E Et d

1 2

1

gg g g geq

w

w C CP E w wt d

22s

T sT C G T Tt

22

1s

T T Tt

Soil temperature

Soil & vegetation water

e.g. Noilhan and Planton (1989)

Force restore model

• The force restore approach predicts surface temperature & moisture for a small, finite depth

• Depth can be tuned to match the response of thermal and passive microwave sensors

• In this phase of project no plans to implement surface flows and routing

Heat fluxes

Niwot Ridge, 2002, day of year 151

Heat fluxes

Niwot Ridge, 2002, day of year 170

Problems with the 1D operator

• For any canopy that departs from 1D:– Cannot correctly describe the variation of path

length with viewing and illumination geometry– Does not predict viewed amount of bare soil or

how this varies with viewing geometry• Both of these are critical for correct modelling

of satellite signals from large parts of the Earth’s surface

Observation operator - GORT

Shaded crown

Illuminated crown

Illuminated soil

Shaded soil

Shaded crownIlluminated

crown

Illuminated soil

Shaded soil

Geometric Observation Operator

Short-wave partitioning

Short-wave partitioning

Short-wave partitioning

Short-wave partitioning

Metropolis-Hastings

α = min 1,P(B|u*)P(A)

P(B|u)P(A)

Draw z from U(0,1)

u+= u* if z≤αu if z> α

u*=u + random proposition

MCMC calibration (Oregon)PD

FPD

F

Leaf area index Soil brightness H/B ratio

Projected Crown Cover Crown shape Leaf chlorophyll

PDF – LAI vs. chlorophyll

Leaf area index

Leaf

chl

orop

hyll

PDF – Crown cover vs. shape

Crown shape

Crow

n co

ver

PDF – fapar vs. albedo

Albedo

fapa

r

Forward modelled BRF

Forward modelled BRF

Next steps - immediate

• Improve model integration– Currently using Euler integration…

• Couple GORT fully– Sun angle effects– Diffuse/direct– Interception of precipitation

Next steps – short term

• Data Assimilation framework– Particle Filter

• Assimilate optical data– MODIS, GlobAlbedo

• Comprehensive testing– Flux tower sites – Neon sites

Next steps – medium term

• Add photosynthesis model– Farquhar based

• Add allocation model– DALEC type

• More testing…• Implement on large scale…