Impact of water-storage parametrization on evaporation from urban areas using the new urban surface model TERRA-MLU
Bibliographic record
Abstract
Evaporation from the urban impervious surface could have a considerable impact on the surface energy and moisture balance on rainy days. In particular, the ever increasing urbanization could alter the interaction between evaporation from the surface and precipitation within the urban climate (change) in the future. However, uncertainty exists within the determination of water storage parameters for the impervious surface, and hydrological parameters of the soil for the natural fraction in urban environments. In order to investigate the water balance over urban areas in more detail, TERRA-MLU, a new urban surface-flux parameterization, is applied over Toulouse city centre during the CAPITOUL campaign during 2004.\n\nThe new urban parameterization covers a direct implementation of urban characteristics in TERRA_ML, Soil-Vegetation-Atmosphere Transfer model of COSMO. Besides anthropogenic heat, specific dynamic, radiative and thermal parameters including roughness length, heat capacity, conductivity, albedo and emissivity are assigned for the urban land-cover. A bluff-roughness thermal roughness length parametrization is used. New surface-layer transfer coefficients are adopted which can deal with very small thermal roughness lengths typical for urban surfaces. An new impervious water storage parameterization is introduced as well.\n\nTERRA-MLU is evaluated 'offline' for Marseille, Toulouse, Basel and Vancouver. Sensitivity analysis at the Toulouse site demonstrates that the maximum impervious water storage needs to be equal or less than 1kg/m^2 if one only considers evaporation at a potential rate from the impervious surface. Furthermore, results are improved by implementing a storage form parameter that accounts for the reduction of evaporative surface fraction in case of small water content on the impervious surface. An offline sensitivity analysis is performed to estimate the maximum water storage and the storage form parameter. At last, it is found that the rooting depth of the vegetation needs to be described carefully in urban environments with large trees in order not to underestimate the latent heat during summer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".