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The human consequences of drought are normally addressed in terms of Bwater scarcity^originating from human water use. In these terms, a common prediction to the next few decades is that population growth, not climate change, will be the dominant factor determining numbers living under such scarcity. Here we address the relative importance of increasing human caused extreme drought and increasing population for numbers of humans likely to be directly exposed in the future to such drought. Using the Standardized Precipitation Evapotranspiration Index (SPEI) in conjunction with an ensemble of 16 CMIP5 climate models we find that, by 2081-2100 under the high emissions scenario RCP 8.5, average worldwide monthly population exposed to extreme drought (SPEI < -2) will increase by 386.8 million to 472.3 million (+426.6% from the current 89.7 million). Anthropogenic climate change is responsible for approximately 230.0 million (59.5%) of that increase with population growth responsible for only 35.5 million (9.2%); the climate change-population growth interaction explains the remaining 121.1 million (31.4%). At the national level, 129 countries will experience increase in drought exposure mainly due to climate change alone; 23 countries primarily due to population growth; and 38 countries primarily due to the interaction between climate change and population growth. Given inherently large uncertainties, projections of future climate impacts should be accepted with caution especially those directed to the regional level, to future population trends, and, of course, where technological, social and security changes are possible.

Consistency and discrepancy of air-sea latent and sensible heat fluxes (LHF and SHF, respectively) in the Southern Ocean for current-day flux products are analyzed from climatology and interannual-to-decadal variability perspectives. Five flux products are examined, including the National Oceanography Centre, Southampton flux dataset version 2 (NOCS2), the National Centers for Environmental Prediction/Department of Energy Global Reanalysis 2 (NCEP-2), the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40), the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data version 3 (HOAPS-3), and the objectively analyzed air-sea fluxes (OAFlux).Comparisons suggest that most datasets show encouraging agreement in the spatial distribution of the annual-mean LHF, the meridional profile of the zonal-averaged LHF, the leading empirical orthogonal function (EOF) mode of the LHF and SHF, and the large-scale response of the LHF and SHF to the Antarctic Oscillation (AAO) and El Niñ o-Southern Oscillation (ENSO). However, substantial spatiotemporal discrepancies are noteworthy. The largest across-data scatter is found in the central Indian sector of the Antarctic Circumpolar Current (ACC) for the annual-mean LHF, and in the Atlantic and Indian sectors of the ACC for the annual-mean SHF, which is comparable to and even larger than their respective interannual variability. The zonal mean of the SHF varies widely across the datasets in the ACC. There is a large spread in the seasonal cycle for the LHF and SHF among the datasets, particularly in the cold season. The datasets show interannual variability of various amplitudes and decadal trends of different signs. The flux variability of the NOCS2 is substantially different from the other datasets. Possible attributions of the identified discrepancies for these flux products are discussed based on the availability of the input meteorological state variables.

To date, projections of human migration induced by sea-level change (SLC) largely suggest large-scale displacement away from vulnerable coastlines. However, results from our model of Bangladesh suggest counterintuitively that people will continue to migrate toward the vulnerable coastline irrespective of the flooding amplified by future SLC under all emissions scenarios until the end of this century. We developed an empirically calibrated agent-based model of household migration decision-making that captures the multi-faceted push, pull and mooring influences on migration at a household scale. We then exposed ∼4800 000 simulated migrants to 871 scenarios of projected 21st-century coastal flooding under future emissions pathways. Our model does not predict flooding impacts great enough to drive populations away from coastlines in any of the scenarios. One reason is that while flooding does accelerate a transition from agricultural to non-agricultural income opportunities, livelihood alternatives are most abundant in coastal cities. At the same time, some coastal populations are unable to migrate, as flood losses accumulate and reduce the set of livelihood alternatives (so-called ‘trapped’ populations). However, even when we increased access to credit, a commonly-proposed policy lever for incentivizing migration in the face of climate risk, we found that the number of immobile agents actually rose. These findings imply that instead of a straightforward relationship between displacement and migration, projections need to consider the multiple constraints on, and preferences for, mobility. Our model demonstrates that decision-makers seeking to affect migration outcomes around SLC would do well to consider individual-level adaptive behaviors and motivations that evolve through time, as well as the potential for unintended behavioral responses.