Filters: Contacts: Michelle M. Irizarry-Ortiz (X)
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The South Florida Water Management District (SFWMD) and the U.S. Geological Survey (USGS) have evaluated projections of future droughts for south Florida based on climate model output from the Multivariate Adaptive Constructed Analogs (MACA) downscaled climate dataset from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The MACA dataset includes both Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5). A Portable Document Format (PDF) file is provided which presents boxplots of future overall drought-event characteristics based on 6-mo. and 12-mo. averaged balance anomaly timeseries derived from climate models downscaled by the MACA method assuming the Kruijt stomatal resistance curve...
The South Florida Water Management District (SFWMD) and the U.S. Geological Survey (USGS) have evaluated projections of future droughts for south Florida based on climate model output from the Multivariate Adaptive Constructed Analogs (MACA) downscaled climate dataset from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The MACA dataset includes both Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5). A Microsoft Excel workbook is provided which tabulates mean future (2056-95) anomalies derived from climate models downscaled by the MACA method assuming historical-standard stomatal resistance for four regions: (1) the entire South Florida Water Management District (SFWMD), (2) the Lower...
Categories: Data;
Tags: Florida,
Florida,
South Florida Water Management District,
Southern Florida,
climate,
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates projected future...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The South Florida Water Management District (SFWMD) and the U.S. Geological Survey (USGS) have evaluated projections of future droughts for south Florida based on climate model output from the Multivariate Adaptive Constructed Analogs (MACA) downscaled climate dataset from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The MACA dataset includes both Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5). A Portable Document Format (PDF) file is provided which presents hierarchical clustering summary plots showing model drought evaluation statistics based on future (2056-95) drought characteristics derived from climate models downscaled by the MACA method assuming historical-standard stomatal...
The South Florida Water Management District (SFWMD) and the U.S. Geological Survey (USGS) have evaluated projections of future droughts for south Florida based on climate model output from the Multivariate Adaptive Constructed Analogs (MACA) downscaled climate dataset from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The MACA dataset includes both Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5). A Portable Document Format (PDF) file is provided which presents scatterplots of the joint distributions of historical (1950-2005) and future (2056-95) drought-event characteristics (duration and intensity) based on 6-mo. and 12-mo. averaged balance anomaly timeseries derived from climate...
The South Florida Water Management District (SFWMD) and the U.S. Geological Survey (USGS) have evaluated projections of future droughts for south Florida based on climate model output from the Multivariate Adaptive Constructed Analogs (MACA) downscaled climate dataset from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The MACA dataset includes both Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5). A Portable Document Format (PDF) file is provided which presents scatterplots of the joint distributions of historical (1950-2005) and future (2056-95) drought-event characteristics (duration and intensity) based on 6-mo. and 12-mo. averaged balance anomaly timeseries derived from climate...
The South Florida Water Management District (SFWMD) and the U.S. Geological Survey (USGS) have evaluated projections of future droughts for south Florida based on climate model output from the Multivariate Adaptive Constructed Analogs (MACA) downscaled climate dataset from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The MACA dataset includes both Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5). A Microsoft Excel workbook is provided which tabulates mean future (2056-95) anomalies derived from climate models downscaled by the MACA method assuming the Kruijt stomatal resistance curve in the future for four regions: (1) the entire South Florida Water Management District (SFWMD),...
Categories: Data;
Tags: Florida,
Florida,
South Florida Water Management District,
Southern Florida,
climate,
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the periods 2020-59 (centered in the year 2040) and 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: ARF,
Florida,
Florida,
Florida,
Florida Flood Hub for Applied Research and Innovation,
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in 2040) or to the period 2050-89 (centered in the year 2070) as compared to the 1966-2005...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the periods 2020-59 (centered in the year 2040) and 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical...
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