Data · dataset · 2026
How can we use MODIS land surface temperature to validate long-term urban model simulations?
Listed in National Center for Atmospheric Research
High spatial resolution urban climate modeling is essential for understanding urban climatology and predicting the human health impacts under climate change.
Description
Satellite thermal remote-sensing data are potential observational sources for urban climate model validation with comparable spatial scales, temporal consistency, broad coverage, and long-term archives. However, sensor view angle, cloud distribution, and cloud-contaminated pixels can confound comparisons between satellite land surface temperature (LST) and modeled surface radiometric temperature.
The impacts of sensor view angles on urban LST values are investigated and addressed. Three methods to minimize the confounding factors of clouds are proposed and evaluated using 10years of Moderate Resolution Imaging Spectroradiometer (MODIS) data and simulations from the High-Resolution Land Data Assimilation System (HRLDAS) over Greater Houston, Texas, U.S. For the satellite cloud mask (SCM) method, prior to comparison, the cloud mask for each MODIS scene is applied to its concurrent HRLDAS simulation.
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For the max/min temperature (MMT) method, the 50 warmest days and coolest nights for each data set are selected and compared to avoid cloud impacts. For the high clear-sky fraction (HCF) method, only those MODIS scenes that have a high percentage of clear-sky pixels are compared. The SCM method is recommended for validation of long-term simulations because it provides the largest sample size as well as temporal consistency with the simulations.
The MMT method is best for comparison at the extremes. And the HCF method gives the best absolute temperature comparison due to the spatial and temporal consistency between simulations and observations.
Links
Get the data
- Publisher page n2t.org/ark:/85065/d7d50nxj ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/how-can-we-use-modis-land-surface-temperature-to-valid… ↗
National Center for Atmospheric Research dataset page
landing page · from data ucar edu
Catalogue records · 1
- CKAN API data.ucar.edu/api/3/action/package_show?id=99e5c097-7233-42d4-acef-5211c93b9… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Climate model simulation 65% · Imaging 75% · Simulation 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | 99e5c097-7233-42d4-acef-5211c93b98f3 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[method].local:method:climate-model | enrichment · data ucar edu | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[method].local:method:simulation | enrichment · data ucar edu | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:imaging | enrichment · data ucar edu | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| description | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /notes |
| publication_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| title | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /title |
| updated_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 |