Using Satellite Data and Fully Coupled Regional Hydrologic, Ecological and Atmospheric Models to Study Complex Coastal Environmental Processes Funded by NASA Interdisciplinary Science Program PI: 1 Zong-Liang Yang Co-PI: 1 Guo-Yue Niu 1 David Maidment 2 Paul Montagna 1 James McClelland 3 Hongjie Xie 1 Postdoc: Bryan Hong, Yongsheng Xu 1 University of Texas at Austin 2 Texas A&M University-Corpus Christi 3 University of Texas at San Antonio

Objectives Improve our understanding of how linked upland and estuarine ecosystems respond to combined changes in the hydrological and nutrient cycles that result from changes in climate and land use/land cover (LULC). Integrate research expertise from a diversity of fields that includes climate modeling, remote sensing analysis, biogeochemical cycling in watersheds, surface hydrology and estuary ecology.

Key Science Questions 1)What is the relationship between global climate forcing and seasonal-to-interannual climate variability and extreme storm events over the Gulf Coast region? (Yang/Niu/Jiang) 2)What are the spatial patterns in LULC as defined by satellite data in the Gulf Coast region? (Xie/Hong) 3)How does riverine nutrient export to Gulf Coast estuaries vary with LULC patterns and hydrologic conditions? (Maidment/McClelland) 4)What is the relationship between the frequency of extreme events in the hydrologic and nutrient cycles and the mean productivity and the resiliency of productivity in Gulf Coast estuaries? (McClelland/Montagna) 5)Can we use the answers to the questions above to predict the response of Gulf Coast estuaries to future climate perturbations? (All)

Deliverables 1)Develop a nested regional atmospheric modeling system augmented with satellite remote sensing data to predict high-resolution spatial and temporal hydrometeorological variables for the Gulf Coast region. 2)Characterize two biologically distinct watersheds in the semi-arid region of Central and South Central Texas, the Nueces River watershed and the San Antonio/Guadalupe watershed using modeling data, existing satellite observations, existing water quality data and new fieldwork. 3)Provide an assessment of the uncertainties related to data products and modeling in order to derive confidence values for the model’s predictive capabilities.

A Systematic Assessment of Temperature and Precipitation Changes under Different Future Emissions Scenarios in Texas

Data WCRP CMIP3 dataset WCRP CMIP3 dataset 16 global climate models16 global climate models Three emission scenarios (A1B, A2, B1)Three emission scenarios (A1B, A2, B1) A1B39 simulationsA1B39 simulations A237 simulationsA237 simulations B136 simulationsB136 simulations Precipitation and temperature (monthly)Precipitation and temperature (monthly) Statistical downscaling with bias-correctionStatistical downscaling with bias-correction

Present-day Evaluation (temperature and precipitation) NCDC NARR

Temperature projections

Projected probability distributions of surface temperature changes in the period of 2070–2099 relative to means by different climate models over Texas

Projected annual surface temperature anomalies in the period of 2070–2099 over Texas under different scenarios (A2, A1B and B1)

Projected surface temperature changes in winter (DJF) and summer (JJA)

95% Confidence intervals for surface temperature changes between 2070–2099 and 1971–2000 under A1B Scenario

Projected precipitation changes

Projected precipitation changes (%) under A2, A1B and B1 scenarios between and for winters (DJF) and summers (JJA)

Projected monthly precipitation anomalies over individual five regions in Texas

Trends of precipitation anomalies relative to 1971–2000 year after applying wavelet analysis

RMSE for precipitation RMSE for precipitation (mm/day)

Dynamically downscaled precipitation in the Guadalupe River Basin

Summary Texas is getting warmer (2-5 º C by the end of this century); more warming in the north than in the south.Texas is getting warmer (2-5 º C by the end of this century); more warming in the north than in the south. Overall decreasing trend of precipitation. Decreasing precipitation in the winter (5-15%), and increasing precipitation in the summer (5%).Overall decreasing trend of precipitation. Decreasing precipitation in the winter (5-15%), and increasing precipitation in the summer (5%). Downscaled precipitation (and other variables) at 3- hourly and fine-spatial scales are needed for hydrological studies. Bias correction must be made to precipitation before it is used to drive hydrological models.Downscaled precipitation (and other variables) at 3- hourly and fine-spatial scales are needed for hydrological studies. Bias correction must be made to precipitation before it is used to drive hydrological models.

Taylor Plot of Precipitation