Teaching a Climate Model to See Cities: New Urban Scheme Boosts ORCHIDEE’s Skill

Cities are the most radically transformed landscapes on Earth, yet some of the world’s most important climate models still treat them as if they were bare fields of dirt. That is the problem a team of French and Swiss researchers set out to solve. In a new study published in Geoscientific Model Development, Morgane Lalonde of ETH Zürich and colleagues at Sorbonne Université and Université Paris-Saclay describe how they built a brand-new urban scheme into ORCHIDEE, the land surface model developed at the Institut Pierre-Simon Laplace in France. The result is a model that finally understands what a city is made of, and it performs measurably better at the twenty urban sites where it was tested.

Land surface models are the bridge between the atmosphere and the ground in climate simulations. They calculate how sunlight, heat, and water move between the soil, the vegetation, and the air, and they feed those exchanges upward into the atmospheric component of a climate model. Historically, the models built for global circulation ran on grids tens to hundreds of kilometers wide, where a city was too small to matter. But computing power has changed the game. Global models are now pushing toward kilometer-scale grids, and regional models are running climate-length simulations over huge domains. At those resolutions, cities are no longer invisible specks; they are resolved features whose energy and water budgets can distort temperature, rainfall, and runoff if they are represented badly.

ORCHIDEE is a heavyweight in this world. It simulates coupled water, energy, and carbon cycles and serves as the land component of the IPSL climate model. Its architecture divides each grid cell into a mosaic of plant functional types, with separate soil columns for bare ground, high vegetation, and low vegetation. Until now, however, anything urban was simply assigned to the bare-soil category. That meant no reflective rooftops, no tall buildings stirring the wind, no concrete storing the afternoon sun, and no sealed asphalt blocking rain from soaking into the earth. The model could simulate a forest or a wheat field with sophistication, but a metropolis looked like a patch of exposed dirt.

The new scheme is deliberately parsimonious. Rather than adding an elaborate three-dimensional canyon geometry with separate energy budgets for roofs, walls, and roads, the team introduced a single urban tile, or PFT, into the existing mosaic. This tile carries urban-specific values for albedo, building height, thermal conductivity, and heat capacity, all of which can be prescribed from global or local datasets. The approach follows a lesson from the Urban-PLUMBER intercomparison project, which evaluated thirty urban land surface models and found that simpler slab schemes often outperform more complex ones, provided that vegetation, water availability, and imperviousness are represented realistically. Geometry, in other words, is not everything; what the surface is made of matters just as much.

The genuine novelty lies in how the scheme handles imperviousness. Most urban models treat sealed ground as a surface phenomenon: rain hits the pavement and runs off. Lalonde and colleagues went deeper, literally. Instead of splitting the urban tile into pervious and impervious sub-tiles, they modify the saturated hydraulic conductivity of the entire soil column beneath the city. Two options were tested. The first, called Urban1, slashes conductivity to ten percent of its reference value throughout the column, representing a heavily sealed city. The second, Urban2, scales the reduction linearly with the impervious fraction, so a city that is fifty-five percent sealed sees its conductivity cut proportionally. This single parameter change ripples through the whole hydrology: it suppresses infiltration, boosts surface runoff, reduces soil water storage, and limits the water available for evaporation, all through the model’s existing Richards-equation soil physics rather than any bolted-on machinery.

The thermal side of the scheme is equally consequential. Urban materials conduct and store heat very differently from soil. In grid cells where urban cover exceeds fifty percent, the model now prescribes a thermal conductivity of 3.24 watts per meter per kelvin and a heat capacity of 1890 kilojoules per cubic meter per kelvin, values borrowed from the Noah-MP land surface model. Compare that with the median thermal conductivity of natural soils in the study region, around 1.20 watts per meter per kelvin, and the physical implication is clear: cities soak up far more energy during the day and release it slowly through the night. That stored heat is the engine of the urban heat island, and the model now captures it.

To test the scheme, the team ran standalone simulations at twenty urban flux tower sites drawn from the harmonized Urban-PLUMBER dataset, spanning thirteen countries and climates from tropical Singapore to dry Phoenix and continental Europe. Each simulation was spun up for forty years until soil moisture and temperature reached equilibrium, then run over twelve to sixteen years of observations, with fluxes computed every thirty minutes. The benchmark was the old bare-soil treatment of cities. The verdict, measured by mean absolute error against tower observations, was unambiguous: the new Urban1 configuration reduced the average error in latent heat flux from 30.3 to 27.3 watts per square meter and in sensible heat flux from 41.9 to 36.9 watts per square meter across all sites. At sites with more than fifty percent impervious cover, the gains were larger still, with sensible heat error falling from 46.3 to 38.2 watts per square meter.

The detailed physics behind those numbers is telling. At the reference site of AU-Preston in Melbourne, the urban configurations reproduced the observed summer sensible heat flux far better than the old scheme, both during the day and at night. The improved daytime heat storage, driven by the higher thermal conductivity, left less energy to be dumped into the atmosphere as sensible heat, cutting a summer overestimation that reached a median bias of 77 watts per square meter in the bare-soil runs down to roughly 14 to 18 watts per square meter in the urban runs. Nocturnal sensible heat, which cities keep elevated by releasing stored warmth, also improved in both seasons. Not everything was fixed: daytime sensible heat remained underestimated in winter, and latent heat stayed generally underestimated in summer, likely because the scheme lacks active urban vegetation, irrigation, and anthropogenic heat from traffic and buildings, which can reach nearly 93 watts per square meter at highly urbanized sites like Seoul’s Jungnang district.

The hydrological results reveal both the promise and the limits of the new imperviousness parameterization. Under the strong Urban1 hypothesis, annual surface runoff roughly doubled at most stations, and the balance flipped so that surface runoff exceeded subsurface runoff at fifteen of the twenty sites, exactly the signature urbanization leaves on real catchments. But the moderate Urban2 option produced smaller and sometimes non-monotonic responses, and the simulated reduction in subsurface runoff sits awkwardly with observational studies showing that urban groundwater recharge can actually increase, thanks to leaking pipes and irrigation. The authors are candid that without runoff or soil moisture observations at the tower sites, the water-budget analysis remains a sensitivity assessment rather than a validation.

What comes next is where the story gets ambitious. The team plans convection-permitting simulations over Paris at resolutions below three kilometers, where cities are explicitly resolved and an inaccurate urban energy balance would feed wrong signals straight into the atmosphere. They also intend to add anthropogenic heat fluxes, refine the thermal parameters against measured data, embed active vegetation with seasonal phenology inside the urban tile, and exploit datasets like WUDAPT and the Copernicus Urban Atlas to make albedo, building height, and imperviousness vary across real cityscapes. Notably, most Earth system models contributing to CMIP still ignore cities altogether, a gap that becomes untenable as climate risk assessments increasingly focus on the built environment. A computationally cheap, physically grounded urban tile that works from the neighborhood scale to the globe is exactly the kind of tool that can close it, and ORCHIDEE now has one.

Subject of Research: Development and benchmarking of a new urban land surface scheme with imperviousness-dependent soil hydraulics in the ORCHIDEE 2.2 land surface model

Article Title: Benchmarking a new urban scheme in the ORCHIDEE 2.2 land surface model

Article References: Lalonde, M., Bastin, S., Oudin, L., Arboleda-Obando, P. F., & Ducharne, A. (2026). Benchmarking a new urban scheme in the ORCHIDEE 2.2 land surface model. Geoscientific Model Development, 19(19), 9463-9488. https://doi.org/10.5194/gmd-19-9463-2026

Image Credits: AI Generated

DOI: 10.5194/gmd-19-9463-2026

Keywords: ORCHIDEE, land surface model, urban climate, imperviousness, saturated hydraulic conductivity, surface energy balance, Urban-PLUMBER, sensible heat flux, latent heat flux, urban hydrology, convection-permitting simulations, Geoscientific Model Development