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Abstract Arboviruses transmitted mainly byAedes(Stegomyia)aegyptiandAe. albopictus, including dengue, chikungunya, and Zika viruses, and yellow fever virus in urban settings, pose an escalating global threat. Existing risk maps, often hampered by surveillance biases, may underestimate or misrepresent the true distribution of these diseases and do not incorporate epidemiological similarities despite shared vector species. We address this by generating new global environmental suitability maps forAedes-borne arboviruses using a multi-disease ecological niche model with a nested surveillance model fit to a dataset of over 21,000 occurrence points. This reveals a convergence in suitability around a common global distribution with recent spread of chikungunya and Zika closely aligning with areas suitable for dengue. We estimate that 5.66 (95% confidence interval 5.64-5.68) billion people live in areas suitable for dengue, chikungunya and Zika and 1.54 (1.53-1.54) billion people for yellow fever. We find large national and subnational differences in surveillance capabilities with higher income more accessible areas more likely to detect, diagnose and report viral diseases, which may have led to overestimation of risk in the United States and Europe. When combined with estimates of uncertainty, these suitability maps can be used by ministries of health to target limited surveillance and intervention resources in new strategies against these emerging threats. 

TRISH (Tree-Ring Integrated System for Hydrology), a new web-based tool for reconstruction of water-balance variables from tree-ring proxies is described. The tool makes use of a mapping application, a global water balance model and R-based reconstruction software. Long time series of water balance variables can be reconstructed by regression or analog statistical methods from tree-ring data uploaded by the user or available in TRISH as previously uploaded public datasets. A predictand hydroclimatic time series averaged or summed over a river basin or arbitrary polygon can be generated interactively by clicking on the map. Control over reconstruction modeling includes optional lagging of predictors, transformation of predictand, and reduction of predictors by principal component analysis. Output includes displayed and downloadable graphics, statistics, and time series. The two-stage reconstruction approach in TRISH allows assessment of the strength of the hydroclimatic signal in individual chronologies in addition to providing a reconstruction based on the tree-ring network. TRISH facilitates the testing of sensitivity of reconstructions to modeling choices and allows a user to explore hydrologic reconstruction in ungauged basins. The R software for reconstruction is available for running offline in the RStudio development environment. TRISH is an open-science resource designed to be shared broadly across the Earth Science research community and to engage water resource management.