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Data · dataset · 2026

A global gridded Thermal Deviation Index (TDI) dataset, 1940–2024

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Global Thermal Deviation Index (TDI) Dataset, 1940–2024The Thermal Deviation Index (TDI) is a dimensionless metric that quantifies how far ambient temperature deviates from optimal conditions for human economic activity, energy expenditure, asset integrity, and biological resource formation.

Description

Constructed from a four-parameter exponential function anchored to body temperature (36.5 °C), the freezing point of water (0 °C), and the thermal comfort optimum (22.5 °C), TDI transforms ambient temperature into a continuous, cumulative index of thermal deviation.

Unlike raw temperature, TDI can be accumulated over arbitrary time intervals, enabling the systematic tracking of weather-driven impacts on economic and ecological systems.This dataset provides the first publicly available global TDI product at full ERA5 native resolution. It comprises 1,038,240 grid cells at 0.25° × 0.25° spatial resolution, spanning 85 years from 1940 to 2024, derived from ERA5 hourly 2-m air temperature reanalysis data.

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Nine CSV files are provided under a CC BY 4.0 license:- Three gridded annual files: annual mean temperature, annual mean TDI, and annual cumulative TDI for all 1,038,240 grid cells (land and ocean), each with 85 annual columns.- Four daily statistics files: global, land-surface, United States, and China daily TDI aggregates (mean, max, min, standard deviation, confidence intervals, and percentiles; 31,047 days each).- One case-study file: 8,784 hourly temperature and TDI values for Namegata (Japan) and Fulton (United States) during 2024, demonstrating that locations with identical annual mean temperatures can exhibit substantially different TDI values.- One country name mapping table: UTF-8 to ASCII conversion for 167 country and territory names.All files are validated for internal consistency: zero missing values across all numeric fields, identical country-name assignments across gridded products, and boundary conditions verified to numerical precision.

The dataset supports climate impact assessment, ecological monitoring, climate model evaluation, and climate–economy research requiring spatially resolved, long-term thermal comfort metrics.Data citation: Cai, Y. (2026). Global Thermal Deviation Index (TDI) Dataset 1940–2024. figshare. doi.org/10.6084/m9.figshare.33012002

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Climate model simulation 65% · Tabular 65%
Provenance · 1 source records, 12 field assertions
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ScienceDB10.57760/sciencedb.435735 d agoJSON v1
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