Simulated crop yield — an indicator of climate variability

Biological production of plants is a complex variable, which integrates summer weather conditions. To assess summer climate variability over the last century, the concept of the meteorologically possible yield (MPY) can be used, which expresses the highest yield under existing meteorological conditions, not limited by soil quality (except its hydrological properties) or management. The MPY for early and late varieties of potato were computed with a potato-production model (POMOD) for three localities in Estonia for periods of 83-106 years. The computed yields were compared with cumulative meteorological factors and a set of the North Atlantic Oscillation indices. Significant polynomial relationships between the MPY and the cumulative meteorological elements appeared for all localities, whereas linear regression was significant only for the western coastal zone. The dual relationships, the continuously high variance around a polynomial relationship and the changes in the MPY series variability not expressible as single factors, indicate that MPY gives qualitatively new information about climatic variability in a synthesis of different factors. Correlations between the NAO index of some late autumn and winter months and MPY values were significant, albeit weak. The highest, negative correlations, expressing the effects of anticyclonic patterns, proceeded from the previous November. Positive correlations were identified for January only for a late variety of potato at an inland station.

Authors

Publication Details

Journal
Työväentutkimus Vuosikirja
Published
2024-12-12
DOI
https://doi.org/10.60910/dgpe-ww0j
Citations
10
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.28

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simulated crop yield — an indicator of climate variability

J. Kadaja, Triin Saue
10 citations
Työväentutkimus Vuosikirja
Climate variability and models
0.28
article

Simulated crop yield — an indicator of climate variability

J. Kadaja, Triin Saue
article en
10 citations

Abstract

Biological production of plants is a complex variable, which integrates summer weather conditions. To assess summer climate variability over the last century, the concept of the meteorologically possible yield (MPY) can be used, which expresses the highest yield under existing meteorological conditions, not limited by soil quality (except its hydrological properties) or management. The MPY for early and late varieties of potato were computed with a potato-production model (POMOD) for three localities in Estonia for periods of 83-106 years. The computed yields were compared with cumulative meteorological factors and a set of the North Atlantic Oscillation indices. Significant polynomial relationships between the MPY and the cumulative meteorological elements appeared for all localities, whereas linear regression was significant only for the western coastal zone. The dual relationships, the continuously high variance around a polynomial relationship and the changes in the MPY series variability not expressible as single factors, indicate that MPY gives qualitatively new information about climatic variability in a synthesis of different factors. Correlations between the NAO index of some late autumn and winter months and MPY values were significant, albeit weak. The highest, negative correlations, expressing the effects of anticyclonic patterns, proceeded from the previous November. Positive correlations were identified for January only for a late variety of potato at an inland station.

Työväentutkimus VuosikirjaVol. 14(1)
Eesti Teadusfondi
Climate action
Openalex Percentile: Top 48%
Climate variability and models
0.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.