Abstract:
Downscaled climate and hydrology projections, along with the corresponding historical observations, were acquired from UC Lawrence Livermore National Laboratory’s web service. One-sixteenth scale Coupled Model Intercomparison Project phase 5 (CMIP5) projection sets of selected hydrological variables were acquired for all available runs of emissions paths RCP4.5 and RCP8.5. Chosen variables and parameters of the projections were shown to be most capable of predicting future trends in freshwater inflows along the Texas Gulf Coast, while allowing for the region’s seasonal specific precipitation trends.
Selected variables: average surface air temperature, baseflow, rainfall rate, runoff , soil moisture layer 1, actual evapotranspiration, potential evapotranspiration, and relative humidity.
Basin selection: Along-coast differences in climate are represented by differences in small coastal drainage basins surrounding Houston (northeast) and Kingsville (southwest). Along-coast differences in riverine inflows will be represented by the Sabine-Neches Rivers (northeast) and the Nueces River (southwest). Differences related to the size of drainage basins will be represented by the Lavaca River and the Brazos River, both of which discharge along the central Texas coast.
Representative basins: Houston area: Outlet cell: 29.812500,-95.062500 (Trib area ~10856 km^2) Latitude bounds: (29.5, 30.75) Longitude bounds: (-96.125, -95.0) Area within bounds: ~15039 km^2 Kingsville area: Outlet cell: 27.312500,-97.562500 (Trib area ~11479 km2) Latitude bounds: (27.125, 28.0) Longitude bounds: (-99.0, -97.5) Area within bounds: ~14387 km^2 Sabine-Neches: Outlet cell: 29.812500,-93.937500 (Trib area ~55454 km2) Latitude bounds: (29.75, 33.375) Longitude bounds: (-96.5, -93.125) Area within bounds: ~128880 km^2 Nueces: Outlet cell: 28.5625, -96.5625 (Trib area approx..40977 km2) Latitude bounds: (27.625, 30.125) Longitude bounds: (-100.5, -97.375) Area within bounds: ~84586 km^2 Lavaca: Outlet cell: 28.5625, -96.5625 (Trib area ~7083 km^2) Latitude bounds: (28.5, 29.75) Longitude bounds: (-97.25, -96.375) Area within bounds: ~11814 km^2 Brazos: Outlet cell: 30.4375, -96.3125 (Trib area ~ 102771 km^2); Latitude bounds: (30.375, 34.625) Longitude bounds: (-103.875, -96.25) Area within bounds: ~337,877 km^2. The dataset includes five R dataframes (.RData) and plots for each model run/location/variable combination, specifying the quantiles (10th to 90th) for each location and model run (.Bdf); the sum or average function for each location and model run (sRCP); a timeseries for each location and model run (.tsdf), quantiles (0:5:100) (.qnts), and daily to annual averaged values (.aRCP). Also included are a listing of the 32 numerical models considered and the code used to source and analyze the data.
Suggested Citation:
Nielsen-Gammon, John and Alison A. Tarter. 2023. Texas climate, climate change, and impacts on inflows to bays and estuaries evaluated through the use of hydrologic model simulations driven by downscaled global climate model simulations and projections. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/qhkhp60n
Purpose:
Multiple anthropogenic and natural forces affect freshwater inflows to Texas nearshore waters. Statewide, the demand for freshwater continues to increase. Rising air temperatures are leading to increased water temperatures and increased potential evapotranspiration, which along with increased water diversions contribute to increased salinity. Though much uncertainty surrounds future climate conditions, model projections can aid in future resource management decisions.
Methods:
The information used here is based on global climate model (GCM) output from the Coupled Model Intercomparison Project phase 5 (CMIP5) that has been downscaled using the Localized Constructed Analog (LOCA) method. This statistical downscaling aligns certain properties of the GCM to the historical observations while providing estimates of climate variables at high spatial resolution. The local observations constitute the Livneh gridded data set (Livneh et al, 2013; Livneh et al, 2015) of daily maximum and minimum temperatures and precipitation over the period 1950-2005. Weather patterns analogous to the daily GCM simulations in the area were used to infer patterns of temperature and precipitation. The downscaled temperature and precipitation were constrained to have similar long-term average values as well as similar temporal variability, so that historical downscaled values were a good representation of observed climate. Projections are shown for both RCP 4.5 and RCP 8.5, where RCP stands for Representative Concentration Pathway. RCP 4.5 assumes substantial climate action and is a plausible best-case scenario. RCP 8.5 is a sort of worst-case scenario and can be used to identify the climate change signal, as the magnitude of the change is so large it can be distinguished from random distributional changes over short periods. Model output from individual runs of 32 GCM models were downscaled to produce sets of LOCA-VIC output for RCP 4.5 and RCP 8.5 projections. Focus ess place on the nine models that best represent Texas climate conditions (BCC_CSM1.1, CCSM4, CNRM-CM5, CSIRO-Mk3.6.0, GFDL-ESM2M, IPSL-CM5A-LR, MIROC5, MRI-CGCM3, NorESM1-M). All meteorological and hydrological variables were aggregated to a monthly time scale and averaged or summed over each drainage basin, and model output was displayed as annual time series, smoothed time series, or time series percentiles. The annual time series show the sequence of annual average or annual total values from individual climate model simulations. Their noisiness reflects the variability of the weather from year to year as represented by the simulations. Smoothed time series were used to show climate change with weather variability removed. The projections from individual models were also aggregated and summarized for the historical period (1950-2009) and the future period (2025-2084). Note that the plotted air temperature, soil moisture layer, dew accumulation, and relative humidity data are averages, while the plotted baseflow, potential evapotranspiration, actual evapotranspiration, runoff, and rainfall rate variables are sums.
The Livneh gridded dataset is available at ftp://livnehpublicstorage.colorado.edu/public/Livneh.2013.CONUS.Dataset/ or A spatially comprehensive, meteorological data set for Mexico, the U.S., and southern Canada (NCEI Accession 0129374) https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.nodc:0129374
Provenance and Historical References:
Livneh, Ben, E. A. Rosenberg, C. Lin, B. Nijssen, V. Mishra, K. M. Andreadis, E. P. Maurer, and D. P. Lettenmaier (2013). A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States: Update and Extensions. J. Climate 26(13), 9384-9392. https://doi.org/10.1175/JCLI-D-12-00508.1.
Ben Livneh, T. J. Bohn, D. W. Pierce, F. Munoz-Arriola, B. Nijssen, R. Vose, D. R. Cayan, and L. Brekke (2015). A spatially comprehensive, hydrometeorological data set for Mexico, the U.S., and Southern Canada 1950–2013. Sci Data 2, 150042 (2015). https://doi.org/10.1038/sdata.2015.42
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