A 1-km hourly air-temperature model for 13 northeastern U.S. states using remotely sensed and ground-based measurements

Keyphrases

• Ground Measurements 100%
• Air Temperature Model 100%
• Hourly Air Temperature 100%
• Northeastern US 100%
• US States 100%
• NLDAS 100%
• Heat Wave 66%
• Root Mean Square Error 66%
• Social Vulnerability 66%
• Model Prediction 33%
• Air Temperature 33%
• Future Health 33%
• Vegetated Surface 33%
• Spatial Resolution 33%
• Land Surface Temperature 33%
• Statistical Model 33%
• Health Studies 33%
• Satellite-based 33%
• Health Relevance 33%
• Weak Association 33%
• High Temporal Resolution 33%
• Ambient Air Temperature 33%
• Meteorological Station 33%
• Validation Scheme 33%
• External Data 33%
• Square Grid 33%
• Inverse Distance Weighted Interpolation Method 33%
• Spatially Weighted 33%
• Mid-Atlantic United States 33%
• Northeast Atlantic 33%
• Dynamic Variation 33%
• Well Model 33%
• Temperature Estimates 33%
• Temperature-based Method 33%
• Within-day 33%
• Spatial Cross-validation 33%
• Mesonet 33%
• Weighted Root Mean Square 33%
• Weather Underground 33%
• Hourly Model 33%
• Xgboost Machine Learning Algorithm 33%

Earth and Planetary Sciences

• United States of America 100%
• Air Temperature 100%
• Ground-Based Measurement 100%
• Data Assimilation 75%
• Heat Wave 50%
• Root-Mean-Square Error 50%
• Vegetation 25%
• Ambient Air 25%
• Interpolation 25%
• Spatial Resolution 25%
• Land Surface Temperature 25%
• Machine Learning 25%
• United States 25%
• Standard Deviation 25%
• Weather Stations 25%
• Xgboost 25%