Rosenzweig et al Crop Model Results

Rosenzweig and Iglesias (2006) provide a query-based database that returns estimates of the impact of prospective global warming, under alter

16. The entries in appendix table F.2 correspond to those in the final column of table 5.6 after shrinkage to take account of the ratio of net revenue to output.

17. The coefficient of variation is calculated as the square root of the sum of squared residuals of each of the six estimates from the average of the six, divided by the average (and reported in absolute value).

18. The coefficient of variation is increasingly misleading as the average value approaches zero. The high coefficient of variation for Turkey reflects this fact.

native climate scenarios and using alternative GCMs, on four major crops: wheat, rice, coarse grains (maize, barley, and others), and soybeans. The underlying research was developed in the 1990s by a team of agricultural scientists from 18 countries, who estimated compatible crop models at 125 agricultural sites using consistent climate change scenarios (see Rosenzweig et al. 1993, as discussed above; and Parry, Rosenzweig, and Liver-more 2005). The process-based dynamic crop growth models incorporate the effects of change in temperature, precipitation, and solar radiation; the effect of carbon fertilization from increased atmospheric concentrations of carbon dioxide; and crop management, particularly with respect to timing of planting and extent of fertilization and irrigation. The estimates are for three levels of adaptation: 1) no adaptation; 2) level 1 (L1): shifts in planting dates by less than one month, shifts to other available varieties and crops, and increased irrigation using existing systems; and 3) level 2 (L2): more intensive adaptations involving higher costs, including change in date of planting by more than one month; installation of new irrigation systems; and development of new varieties.

The GCMs and climate scenarios in the query system include three models with results for equilibrium carbon concentrations of 555 ppm (double preindustrial levels) and two "transient" model variants for expected conditions by the 2080s. For the transient model used here (HadCM3, Hadley Centre for Climate Prediction and Research Coupled Model 3), the IS95a scenario is used, which is the same as the IS92a "business as usual" scenario in the IPCC's Second Assessment Report of 1995.19 This scenario has a modestly lower path of rising emissions than the SRES A2 scenario in the Third Assessment Report of 2001, used for the projections in the first part of this study (see table 4.2). Thus, by 2040 fossil fuel and industrial process emissions stand at 12.66 gigatons of carbon equivalent (GtC) in IS92a and 15.01 GtC in SRES A2; by 2080 the comparison is 17.0 versus 22.97 GtC, respectively (IPCC 2001a, 801).

The equilibrium and transient models tend to generate relatively similar results at 555 ppm equilibrium and 731 ppm transient warming.20 This is presumably because ocean thermal lag means the ultimate equilibrium warming associated with any given atmospheric concentration of carbon is greater than will be observed at the date this concentration is first attained (see Cline 1992, 92).

19. Rosenzweig and Iglesias (2006) also report results for Hadley model HadCM2. However, these results show much greater divergence from the results of the other three models used here (GISS, GFDL, and UKMO) than do the results for HadCM3. The HadCM3 results, being more representative, are thus chosen for the analysis here. (For the regions shown in table 5.7, the sum of squared residuals of percent deviation from the average estimate from the other three models is 11,414 for HadCM2 but only 3,116 for HadCM3.)

20. See the color maps on the methodology page in Rosenzweig and Iglesias (2006).

Table 5.7 reports the results compiled in the Rosenzweig-Iglesias database for the impact of global warming by the 2080s on yields of the four major grains and oilseeds, again interpreting the equilibrium 555 ppm results as proxies for realized impact by the 2080s. These estimates are all for the moderate level of adaptation (L1) and full carbon fertilization effects. Analysis of the difference between results with and without carbon fertilization indicates that the Rosenzweig-Iglesias estimates place the carbon fertilization impact at about +17 percent by the 2080s.21 This impact is close to the 15 percent identified above as the proper target for carbon fertilization by this period on the basis of the recent free air concentration enrichment (FACE) field experiments.

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