Methoden vergleichen

	Allgemeines Zirkulationsmodell	NDVI	Standardisierter Niederschlagsindex
Fachgebiet	Geophysik	Geophysik	Geophysik
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Entstehungsjahr	1975	1973	1993
Urheber	Syukuro Manabe and Richard Wetherald	Rouse, Haas, Schell, and Deering	Thomas McKee, Neil Doesken, and John Kleist
Typ	Deterministic coupled atmosphere-ocean simulation	Spectral index for vegetation assessment	Probabilistic drought indicator
Wegweisende Quelle	Manabe, S., & Wetherald, R. T. (1975). The effects of doubling the CO2 concentration on the climate of a general circulation model. Journal of the Atmospheric Sciences, 32(1), 3-15.	Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1973). Monitoring vegetation systems in the Great Plains with ERTS. Third Earth Resources Technology Satellite Symposium Proceedings, 1, 309-317.	McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Proceedings of the Eighth Conference on Applied Climatology, 179-184.
Aliasnamen	GCM, Global Climate Model	NDVI	SPI
Verwandt	3	3	3
Zusammenfassung	A General Circulation Model (GCM), also called a Global Climate Model, is a three-dimensional numerical representation of the Earth's atmosphere, oceans, ice, and land surface that simulates physical processes governing weather and climate. Pioneered by Manabe and Wetherald in 1975, GCMs are the primary tools for understanding past climate, projecting future climate change, and investigating climate sensitivity to greenhouse gases and other forcings.	The Normalized Difference Vegetation Index (NDVI) is a spectral index computed from satellite or aerial multispectral imagery that quantifies vegetation greenness and vigor. Introduced by Rouse and colleagues in 1973 using Landsat data, NDVI has become the most widely used remote sensing metric for vegetation monitoring, drought assessment, crop productivity forecasting, and land cover change detection.	The Standardized Precipitation Index (SPI) is a climate index that quantifies precipitation anomalies relative to historical norms, standardized to account for differences in precipitation climatology across regions. Introduced by McKee, Doesken, and Kleist in 1993, SPI has become a primary tool for drought detection and characterization, adopted by meteorological agencies worldwide for operational drought monitoring and early warning systems.