Science tools
decisionSupport
This is an R package that can be used to run decision analysis simulations. It is featured on my Holistic modeling website
This is an R package that can be used to run decision analysis simulations. It is featured on my Holistic modeling website
chillR
Here you can download my chillR R package. This is an extension to the R statistics software that offers some useful functions for calculating winter chill for temperate fruit trees. It also allow estimating chilling and heat requirements from long-term records of bloom dates and daily weather. The full method is described in the following papers:
Luedeling E, Kunz A and Blanke M, in press. Identification of chilling and heat requirements of cherry trees - a statistical approach. International Journal of Biometeorology. (Link to paper)
Luedeling E and Gassner A, 2012. Partial Least Squares Regression for analyzing walnut phenology in California. Agricultural and Forest Meteorology 158, 43-52. (Link to abstract)
Luedeling E, Kunz A and Blanke M, in press. Identification of chilling and heat requirements of cherry trees - a statistical approach. International Journal of Biometeorology. (Link to paper)
Luedeling E and Gassner A, 2012. Partial Least Squares Regression for analyzing walnut phenology in California. Agricultural and Forest Meteorology 158, 43-52. (Link to abstract)
Climate analogue analysis
I've been playing around a bit with climate analogue analysis. Some details of the procedure are outlined in a report I wrote for GIZ in 2011 (Download). Basically, the idea is that most future climates projected for a particular place of interest can already be found somewhere else at present. These are climate analogues. Such analogues can be useful in several ways:
And here's another example: Kaptumo in Kenya
As you can see, this is not particularly well-designed yet, and it clearly still needs work, but I think it provides an interesting perspective on climate change that is not so easily conveyed by simple climate projections. In the following paper, I have also used this methodology to evaluate climate change impacts on agroforestry parklands in the Sahel:
Luedeling E and Neufeldt H, 2012. Carbon sequestration potential of parkland agroforestry in the Sahel. Climatic Change 115, 443-461. (Link to paper)
There are still a lot of open questions regarding the usefulness of this methodology. Current procedures are only based on climate - important site factors like soil type are not included. Socioeconomic factors are also not considered, but might critically affect what land use options are feasible. It my be possible to include some of these factors in the future, but even then, climate analogues won't be silver bullets for adaptation. Given the scarcity of reliable climate change impact projections in many parts of the world, and the dearth of adequate systems models in many places, climate analogue nonetheless provides an interesting work-around for direct impact projection, and may fulfill useful functions in science and in adaptation planning.
- Environmental conditions at these analogue sites can provide clues about climate change impacts at the target site.
- Land management practices at analogue sites could be adaptation options for the target site.
- Potential adaptation options for the target site can be tested at analogue locations, which may go further at ensuring future viability than tests at the target site.
- Data from observations or experiments at target and a suite of climate analogue locations (for multiple climate scenarios) can be used to make robust systems models, which should then be valid for the range of climate scenarios that must plausibly be expected.
- Map of analogue locations: These show the location of the target site, as well as climate analogue locations for a suite of Global Climate Model projections.
- Link to open analogues in Google Earth
- Correspondence plots: these show how similar the climate at the analogue location is to the projected climate at the target site.
- Distance plots: These provide maps of climatic similarity of current climate in the region with the projected climate at the target site (the Google Earth link for these doesn't work currently - I need to look at this again).
- Analogue pathways: For multiple emissions scenarios and climate models, analogue locations are displayed as spatial representations of climate trajectories. Basically, all the dots are connected.
- Context graphs: These figures show data from various environmental GIS layers, which have been sampled at target and analogue locations. These are shown as boxplots, which represent the distributions over the 50 closest climate analogue locations (the 50 pixels with the smallest climatic distance to projected conditions). For the target location, the box is derived by sampling the 50 geographically closest locations. Red dots in these figures are the values for the actual analogue locations (where the climatic distance is minimized). Most of the context graphs in the example are crop yield potential maps from IAASA.
- Vulnerability evaluation: This is based on the context graph layers. First the procedure producing this figure compares potential yields for all listed crops among the context grids with the global maximum yields for the respective crops. This is based on the median of the distributions shown in the context graphs. The 5 crops with the highest ratios of yield potential to global maximum at the target sites are assumed to be the most suitable crops. For these the yield potential for all future scenarios is then divided by the potential under baseline climate. Where this ratio is 1.5 or greater (yield potential increasing by 50%), conditions are diagnosed as 'improving'. Where the ratio is 0.5 or less (yield decline by 50%), the site is labeled as highly vulnerable.
And here's another example: Kaptumo in Kenya
As you can see, this is not particularly well-designed yet, and it clearly still needs work, but I think it provides an interesting perspective on climate change that is not so easily conveyed by simple climate projections. In the following paper, I have also used this methodology to evaluate climate change impacts on agroforestry parklands in the Sahel:
Luedeling E and Neufeldt H, 2012. Carbon sequestration potential of parkland agroforestry in the Sahel. Climatic Change 115, 443-461. (Link to paper)
There are still a lot of open questions regarding the usefulness of this methodology. Current procedures are only based on climate - important site factors like soil type are not included. Socioeconomic factors are also not considered, but might critically affect what land use options are feasible. It my be possible to include some of these factors in the future, but even then, climate analogues won't be silver bullets for adaptation. Given the scarcity of reliable climate change impact projections in many parts of the world, and the dearth of adequate systems models in many places, climate analogue nonetheless provides an interesting work-around for direct impact projection, and may fulfill useful functions in science and in adaptation planning.