3.0 Starting the IDV for the first time
5.0.0 Introduction to the Color Table Editor
6.1.0 Core IDV
6.1.2 Major Components
6.1.3 IDV Architectural Overview
6.1.4 Data Package
6.1.5 Data Choices
184.108.40.206 PS‑1: BIOPHYSICAL PRODUCTION POTENTIAL
- Image 1: Light response curves of maize leaves at several temperatures (de Wit et
- Image 2: Light response curves of maize leaves at several temperatures (de Wit et
I = C3‑crops in cool and temperate climates;
II = C3‑crops in warm climates;
III = C4‑crops in warm climates;
IV = C4‑crops in cool climates.
- Image 3: Maximum Assimilation Algorithm Interface.
220.127.116.11 PS‑2: WATER-LIMITED PRODUCTION POTENTIAL
- Image 1: Leaves have microscopic mouths aka stomata.
- Image 2: Photosynthesis at leaf-level during which a major portion of incoming solar energy (light) is used in vaporizing water, and only a small portion (3%) is used in the actual photo-chemical reactions in carbon-hydrate (glucose) production.
- Image 3: Flow diagram of a routine to calculate PS-1/PS-2. Substitution of cf(water) with a dynamically calculated variable extends the analysis of production situation PS-1 to an analysis of situation PS-2.
- Image 4: Gross Rate of CO2 Reduction Algorithm Interface.
- Image 5: Gross Rate Assimilate Production Algorithm Interface.
- Image 1: Agricultural Areas based on CORINE land cover 2000 of Andalucia with map of Spain in the subset.
- Image 2: Rainfed Sunflower Map in (Fractions, %) per Km2, Andalucia.
- Image 3: General Crop Calendar Practiced in Andalucia.
18.104.22.168.0 Study area
7.0.2 Forecasting regional food/fiber production levels
- Image 1: Theoretical illustration of factors influencing variability of regional agricultural productivity (arbitrary units).
- Image 2: Time trend for Zimbabwe based on yield statistics provided by two independent sources.
- Image 3: Time trend for Iran based on yield statistics for two land-use systems (rainfed and irrigated wheat).
22.214.171.124 Does vegetation growth in Africa follow El Niño?
- Image 1: Climatic impacts of warm El Niño events (Oct-Mar). Source: FAO's El Niño Primer. last accessed: 29-10-2009.
- Image 2: Scientific activities to answer: Does biomass in Africa follow El Niño?
- Image 3: Troup's SOI Calculation (1887-1989 base period). Source: The Long Paddock-Website. Last accessed: 01-05-2009.
- Image 4: Normal Ocean Temperatures, Vertical Cross-Section Pacific Ocean, 3D iso-surface at 29 degrees celsius
- Image 5: Ocean Temperatures, Vertical Cross-Section Pacific Ocean, from top-to-bottom: El Niño, Normal, and La Niña conditions
- Image 6: NDVI Difference (El Niño vs. La Niña years), Map-View Africa. Red indicates less biomass during typical El Niño events (and more during typical La Niña events), green indicates no biomass difference between El Niño vs. La Niña events, and blue indicates more biomass during typical El Niño events (and less during typical La Niña events). White indicates data gaps; absence of data (missing) can be either due to waterbody, cloudcover or other (unknown) reasons.
- Image 7: NDVI Difference (El Niño vs. La Niña years), Cross-Section East Africa (transect depicted in previous figure, North-South is here plotted from left-right).
- Image 8: Box & Whisker Diagram for Karoi, Zimbabwe.
- Image 9: Box & Whisker Diagram for Naivasha, Kenya
- Image 10: Box & Whisker Diagram for Narok, Kenya.
- Image 11: Hypothesis test results for Karoi, Zimbabwe.
- Image 12: Hypothesis test results for Naivasha, Kenya.
- Image 13: Hypothesis test results for Narok, Kenya.
Time Animation Widget