This page presents data to illustrate the attributable flooding in the greater Houston are during Hurricane Harvey as simulated by the Fathom Global hydraulical model in a geotiff file format. The model resolution is 30 meters (about 100 feet).

You are encourage to download this data and investigate your own neighborhood of interest. You can validate the baseline simulated "flood that was" against your own personal experience and compare to the "flood that might have been" had there not been a human interference in the climate system. A variety of scientific opinions as to this human effect are presented as detailed in the table below. You can also visualize the "flood that might be" under a pair of high risk scenarios of future climate change if a storm similar to Harvey were to occur again in a much warmer world.

The geotiff file format is not the same as a regular tif graphic files and standard graphic file viewers will not likely reveal much. However, there are free geotiff viewers such as QGIS or commercial viewers such as ArcGis. Be sure to "save as download" as the files are as large as 450MB.

Report broken links or other problems to Michael Wehner, LBNL mfwehner@lbl.gov

Figure 3 from our paper showing the South Houston/Pasadena neighborhoods

Simulation of the actual and counterfactual flood in the South Houston and Pasadena neighborhoods. a) The flood that was. b) The flood that might have been in the absence of climate change if human activies increased Harvey storm total precipitation by 7%. c) same as b) except precipitation increased by 38%. Units: meters. 999 denotes areas of permanent water.

Available data:

baseline.tif	The flood that was
0percent_human_effect.tif	The flood that was (same file with more descriptive name)
38percent_human_effect.tif	38% human increase in precipitation; Risser and Wehner best estimate in a small region; Upper bound of Wang et al.
24percent_human_effect.tif	24% human increase in precipitation; Risser and Wehner best estimate over entire region
20percent_human_effect.tif	20% human increase in precipitation; Wang et al. best estimate
19percent_human_effect.tif	19% human increase in precipitation; upper bound of von Oldenburg et al.
13percent_human_effect.tif	13% human increase in precipitation; lower bound of Wang et al.
8percent_human_effect.tif	8% human increase in precipitation; lower bound of von Oldenburg et al.
7percent_human_effect.tif	7% human increase in precipitation; lower bound of Risser and Wehner; Also lowest credible bound due to Clausius-Clapeyron scaling
1.5X_future_increase.tif	Hypothetical 50% increase in future precipitation
2X_future_increase.tif	Hypothetical doubling of future precipitation

Note for example, that a 38% increase means that the actual precipitation was 38% more than it would have been without climate change. Hence, in that simulation, precipitation was decreased by a factor of 1.0/1.38=0.72 as described in our paper.