Panel B of Figure 2 demonstrates the robustness of the ensemble mean results to the variation in the climate data across the GCMs that define the bounds of potential changes in temperature and precipitation volatility. For each period, the poverty results from GCM 02, 06, and 08 were pooled to give a poverty distribution that considered climate data from GCMs where climate volatility increased and decreased the most. We continue to find that the mass of the poverty change distribution shifts rightward in the future relative to the 20<sup>th</sup> Century – although the shift is more marked than in panel A – implying that climate outcomes in the future will be more frequently poverty increasing.

The poverty distributions for the 20<sup>th</sup> and 21<sup>st</sup> Centuries that are based on the individual GCMs that characterize the upper and lower bounds of the climate volatility changes (panels C, D and E of Figure 2), demonstrate that we observe the shift in the probability mass in the more aggregated climate‐poverty results due to shifting median values, the interquartile range, or both. The use of individual GCMs also reveals the possibility of even larger poverty headcount changes. Poverty results based on GCM 02, 06, and 08 indicate that the years with the greatest poverty increases may see more than 2 percent of Tanzania’s total population – equivalent to nearly 700 thousand people – become impoverished.

In analyzing GCM 02, which shows the greatest increase in precipitation volatility as well as the largest decrease in temperature volatility (Table 2), we see that the median poverty value and the left tail of the distribution shift in the positive (poverty increasing) direction, and that the right tail of the distribution becomes substantially more positive (panel C, Figure 2). Analyzing GCM 06, which shows the greatest increase in temperature volatility (Table 2), we see that the right “whisker” of the poverty change distribution is higher for the 21<sup>st</sup> Century than in the 20<sup>th</sup> Century, , although the left tail and lower quartile both become more negative (panel D, Figure 2). This change in the distribution suggests that, in response to the greatest increase in temperature volatility, there are many more years with very large poverty increases. This highlights the potential importance of changes in climate volatility for poverty vulnerability, even when there is essentially no change in the median poverty value. For GCM 02 and GCM 06, the median poverty change increases by 0.26 and 0.07 percentage points of the national poverty rate, respectively. Based on Tanzania’s 2001 population, these 0.26 and 0.07 percentage point increases in the poverty rate would translate into 89.7 and 24.3 thousand additional poor.

The magnitudes of the extreme poverty increasing outcomes are also found to be greater in the future under GCM 06. In the 20<sup>th</sup> Century, the greatest predicted increase in poverty was of 880 thousand people (2.6 percent of the population), while in the 21<sup>st</sup> Century, the highest possible poverty increase was of 1.17 million people, equivalent to 3.4 percent of the Tanzanian population.

Alternatively, when analyzing GCM 08, which shows the largest decrease in precipitation volatility (Table 2), we see that the poverty distribution is contracted, with the median and right whisker being lower in the future than in the 20<sup>th</sup> Century (panel E, Figure 2). However, even though the median poverty change decreased for GCM 08, the mass of the poverty change distribution shifted rightward, with the first quartile value poverty change increasing by 0.21 percentage points of the poverty rate, and the third quartile value increasing by 0.04 percentage points. Nonetheless, the results of this GCM realization lie in contrast to those from the whole GCM ensemble and from the other boundaries of the ensemble‐envelope, highlighting the uncertainty in the impacts of climate volatility on poverty.

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