Articles | Volume 9, issue 2
https://doi.org/10.5194/esd-9-563-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-9-563-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
18 May 2018
Research article | Highlight paper |
| 18 May 2018
| 18 May 2018
Estimating sowing and harvest dates based on the Asian summer monsoon
Camilla Mathison
CORRESPONDING AUTHOR
Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
Chetan Deva
School of Earth and Environment, Institute for Climate and
Atmospheric Science, University of Leeds, Leeds, LS2 9AT, UK
Pete Falloon
Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
Andrew J. Challinor
School of Earth and Environment, Institute for Climate and
Atmospheric Science, University of Leeds, Leeds, LS2 9AT, UK
Viewed
Total article views: 7,158 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Nov 2017)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 5,817 | 1,196 | 145 | 7,158 | 148 | 121 |
- HTML: 5,817
- PDF: 1,196
- XML: 145
- Total: 7,158
- BibTeX: 148
- EndNote: 121
Total article views: 6,492 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 18 May 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 5,445 | 926 | 121 | 6,492 | 137 | 103 |
- HTML: 5,445
- PDF: 926
- XML: 121
- Total: 6,492
- BibTeX: 137
- EndNote: 103
Total article views: 666 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Nov 2017)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 372 | 270 | 24 | 666 | 11 | 18 |
- HTML: 372
- PDF: 270
- XML: 24
- Total: 666
- BibTeX: 11
- EndNote: 18
Viewed (geographical distribution)
Total article views: 7,158 (including HTML, PDF, and XML)
Thereof 6,659 with geography defined
and 499 with unknown origin.
Total article views: 6,492 (including HTML, PDF, and XML)
Thereof 5,987 with geography defined
and 505 with unknown origin.
Total article views: 666 (including HTML, PDF, and XML)
Thereof 666 with geography defined
and 0 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
25 citations as recorded by crossref.
- Spatial variations in crop growing seasons pivotal to reproduce global fluctuations in maize and wheat yields J. Jägermeyr & K. Frieler 10.1126/sciadv.aat4517
- Agricultural soybean and corn calendar based on moderate resolution satellite images for southern Brazil W. Becker et al. 10.5433/1679-0359.2020v41n5supl1p2419
- Improved air quality leads to enhanced vegetation growth during the COVID–19 lockdown in India R. Kashyap et al. 10.1016/j.apgeog.2022.102869
- Contrasting area and yield responses to extreme climate contributes to climate-resilient rice production in Asia N. Hosokawa et al. 10.1038/s41598-023-33413-7
- A global-scale relationship between crop yield anomaly and multiscalar drought index based on multiple precipitation data V. Hendrawan et al. 10.1088/1748-9326/ac45b4
- Global crop yields can be lifted by timely adaptation of growing periods to climate change S. Minoli et al. 10.1038/s41467-022-34411-5
- Delayed onset of the tropical Asian summer monsoon in CMIP6 can be linked to the cold bias over the Tibetan Plateau D. Hu et al. 10.1088/1748-9326/acff79
- New findings on impact of COVID lockdown over terrestrial ecosystems from LEO-GEO satellites N. Lele et al. 10.1016/j.rsase.2021.100476
- Crop-specific exposure to extreme temperature and moisture for the globe for the last half century N. Jackson et al. 10.1088/1748-9326/abf8e0
- Aligning the harvesting year in global gridded crop model simulations with that in census reports is pivotal to national-level model performance evaluations for rice T. Iizumi et al. 10.1016/j.eja.2021.126367
- Optimality-based modelling of wheat sowing dates globally S. Qiao et al. 10.1016/j.agsy.2023.103608
- Sensitivity of soybean planting date to wet season onset in Mato Grosso, Brazil, and implications under climate change M. Zhang et al. 10.1007/s10584-021-03223-9
- Integration of prognostic sowing and harvesting schemes to enhance crop dynamic growth simulation in Noah-MP-Crop model F. Wang et al. 10.1016/j.ecoinf.2024.102785
- Estimation of Spring Maize Planting Dates in China Using the Environmental Similarity Method M. Sheng et al. 10.3390/agronomy14010097
- Modelling cropping periods of grain crops at the global scale S. Minoli et al. 10.1016/j.gloplacha.2018.12.013
- Investigating the Capability of DOVE Satellite Temporal Data for Mapping Harvest Dates of Sugarcane Crop Types Using Fuzzy Model S. Pancholi & A. Kumar 10.1007/s12524-024-01927-w
- An improved framework for mapping and assessment of dynamics in cropping pattern and crop calendar from NDVI time series across a heterogeneous agro-climatic region R. Jeba et al. 10.1007/s10661-024-13270-1
- How Much Are Planting Dates for Maize Affected by the Climate Trend? Lessons for Scenario Analysis Using Land Surface Models M. Sheng et al. 10.3390/agronomy9060316
- Modeling the Global Sowing and Harvesting Windows of Major Crops Around the Year 2000 T. Iizumi et al. 10.1029/2018MS001477
- Implementation of sequential cropping into JULESvn5.2 land-surface model C. Mathison et al. 10.5194/gmd-14-437-2021
- Monsoon Asia Rice Calendar (MARC): a gridded rice calendar in monsoon Asia based on Sentinel-1 and Sentinel-2 images X. Zhao et al. 10.5194/essd-16-3893-2024
- Climate adaptive rice planting strategies diverge across environmental gradients in the Indo-Gangetic Plains A. Urfels et al. 10.1088/1748-9326/aca5a2
- High-Resolution History: Downscaling China’s Climate from the 20CRv2c Reanalysis R. Amato et al. 10.1175/JAMC-D-19-0083.1
- Versatile crop yield estimator Y. Sadeh et al. 10.1007/s13593-024-00974-4
- RICA: A rice crop calendar for Asia based on MODIS multi year data B. Mishra et al. 10.1016/j.jag.2021.102471
23 citations as recorded by crossref.
- Spatial variations in crop growing seasons pivotal to reproduce global fluctuations in maize and wheat yields J. Jägermeyr & K. Frieler 10.1126/sciadv.aat4517
- Agricultural soybean and corn calendar based on moderate resolution satellite images for southern Brazil W. Becker et al. 10.5433/1679-0359.2020v41n5supl1p2419
- Improved air quality leads to enhanced vegetation growth during the COVID–19 lockdown in India R. Kashyap et al. 10.1016/j.apgeog.2022.102869
- Contrasting area and yield responses to extreme climate contributes to climate-resilient rice production in Asia N. Hosokawa et al. 10.1038/s41598-023-33413-7
- A global-scale relationship between crop yield anomaly and multiscalar drought index based on multiple precipitation data V. Hendrawan et al. 10.1088/1748-9326/ac45b4
- Global crop yields can be lifted by timely adaptation of growing periods to climate change S. Minoli et al. 10.1038/s41467-022-34411-5
- Delayed onset of the tropical Asian summer monsoon in CMIP6 can be linked to the cold bias over the Tibetan Plateau D. Hu et al. 10.1088/1748-9326/acff79
- New findings on impact of COVID lockdown over terrestrial ecosystems from LEO-GEO satellites N. Lele et al. 10.1016/j.rsase.2021.100476
- Crop-specific exposure to extreme temperature and moisture for the globe for the last half century N. Jackson et al. 10.1088/1748-9326/abf8e0
- Aligning the harvesting year in global gridded crop model simulations with that in census reports is pivotal to national-level model performance evaluations for rice T. Iizumi et al. 10.1016/j.eja.2021.126367
- Optimality-based modelling of wheat sowing dates globally S. Qiao et al. 10.1016/j.agsy.2023.103608
- Sensitivity of soybean planting date to wet season onset in Mato Grosso, Brazil, and implications under climate change M. Zhang et al. 10.1007/s10584-021-03223-9
- Integration of prognostic sowing and harvesting schemes to enhance crop dynamic growth simulation in Noah-MP-Crop model F. Wang et al. 10.1016/j.ecoinf.2024.102785
- Estimation of Spring Maize Planting Dates in China Using the Environmental Similarity Method M. Sheng et al. 10.3390/agronomy14010097
- Modelling cropping periods of grain crops at the global scale S. Minoli et al. 10.1016/j.gloplacha.2018.12.013
- Investigating the Capability of DOVE Satellite Temporal Data for Mapping Harvest Dates of Sugarcane Crop Types Using Fuzzy Model S. Pancholi & A. Kumar 10.1007/s12524-024-01927-w
- An improved framework for mapping and assessment of dynamics in cropping pattern and crop calendar from NDVI time series across a heterogeneous agro-climatic region R. Jeba et al. 10.1007/s10661-024-13270-1
- How Much Are Planting Dates for Maize Affected by the Climate Trend? Lessons for Scenario Analysis Using Land Surface Models M. Sheng et al. 10.3390/agronomy9060316
- Modeling the Global Sowing and Harvesting Windows of Major Crops Around the Year 2000 T. Iizumi et al. 10.1029/2018MS001477
- Implementation of sequential cropping into JULESvn5.2 land-surface model C. Mathison et al. 10.5194/gmd-14-437-2021
- Monsoon Asia Rice Calendar (MARC): a gridded rice calendar in monsoon Asia based on Sentinel-1 and Sentinel-2 images X. Zhao et al. 10.5194/essd-16-3893-2024
- Climate adaptive rice planting strategies diverge across environmental gradients in the Indo-Gangetic Plains A. Urfels et al. 10.1088/1748-9326/aca5a2
- High-Resolution History: Downscaling China’s Climate from the 20CRv2c Reanalysis R. Amato et al. 10.1175/JAMC-D-19-0083.1
Saved (final revised paper)
Discussed (final revised paper)
Latest update: 09 May 2025
Short summary
Sowing and harvest dates are a significant source of uncertainty within crop models. South Asia is one region with a large uncertainty. We aim to provide more accurate sowing and harvest dates than currently available and that are relevant for climate impact assessments. This method reproduces the present day sowing and harvest dates for most parts of India and when applied to two future periods provides a useful way of modelling potential growing season adaptations to changes in future climate.
Sowing and harvest dates are a significant source of uncertainty within crop models. South Asia...
Altmetrics
Final-revised paper
Preprint