Task 236
Hypo-G: Improved Hypoxia Modeling for Nutrient Control Decisions in the Gulf of Mexico
Principal Investigator(s):
M. Tzortziou
Sponsor(s):
S. Habib
Last Updated:
October 26, 2012 15:26:03
Description of Problem
The main objective of this project is to assess and transition the potential benefits of using NASA satellite data products within the EPA’s Gulf of Mexico Modeling Framework. The hypoxic zone in the Northern Gulf of Mexico forms each summer and can extend up to 80 miles offshore and stretch from the discharge of the Mississippi River westward to coastal waters of Texas. The size of the hypoxic zone varies considerably each year. In 2007, the size of the hypoxic zone was 20,500 km2 approximately the size of Massachusetts. The direct effects of hypoxia include fish kills, depletion of fisheries, and loss of habitat for less mobile animals such as crabs and mussels. The purpose of the EPA Gulf of Mexico Modeling and Monitoring project is to provide the scientific basis to guide a reduction in the frequency, duration, size, and degree of oxygen depletion in the northern Gulf of Mexico as outlined in the recently released Hypoxia Action Plan. The Gulf of Mexico Modeling Framework is a suite of coupled EPA models linking the deposition and transport of sediment and nutrients to subsequent bio-geo chemical processes and concentrations of dissolved oxygen in the coastal of waters of Louisiana and Texas. Use of NASA’s Earth Observations can potentially improve the accuracy of these models by providing more accurate inputs, thus enabling determination of best practices and strategies for managing the Mississippi/Achafalaya river basin. More information about the project can be found on the project’s website at: http://oas.gsfc.nasa.gov/Gulf/index.html
Scientific Objectives and Approach
Our approach to enhance the EPA’s Modeling Framework is divided into three components:
(a) Improvement of the precipitation input data, by using the NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA) and the NOAA/National Weather Service Multi-sensor Precipitation Estimator (MPE) products;
(b) Improvement of atmospheric constituent concentrations in EPA’s air quality/ deposition model, by using NASA MODIS, CALIPSO, and OMI data products;
(c) Improvement of the calculation of algal biomass, organic carbon and suspended solids within the water quality/eutrophication models, by using NASA MODIS and SeaWiFS ocean color data products.
The primary purpose of the EPA Gulf of Mexico Modeling Framework is to characterize the impacts of nutrient management actions, or proposed actions on the spatial and temporal characteristics of the Gulf hypoxic zone. The Modeling Framework is expected to play a significant role in determining best practices and improved strategies for incentivizing nutrient reduction strategies, including installation of on-farm structures to reduce sediment and nutrient runoff, use of cover crops and other agricultural practices, restoration of wetlands and riparian buffers, improved waste water treatment and decreased industrial nitrogen emissions. The use of NASA satellite data products in the models and for long term validation of the models has the potential to significantly increase the accuracy and therefore the utility of the model for the decision making described above.
Accomplishments
We evaluated the WRF (Weather and Research Forecasting) model precipitation estimates using gridded precipitation observation products from NOAA and NASA. Over the continental United States the NOAA/National Weather Service Multisensor Precipitation Estimator (MPE) product is used. MPE combines precipitation observations from over 6000 rain gauges, 160 Doppler radars, and multiple IR and microwave satellite sensors. MPE does not provide sufficient coverage over the Gulf of Mexico for the hypoxia project. Therefore, we also use the NASA TMPA product. While the primary data are from satellite microwave and infrared sensors, data from the TRMM precipitation radar and rain gauges are used for calibration. Validation results have shown good performance at monthly time scales and for detecting large daily events. TMPA has lower skill in specifying light rain events over short intervals.
We have also been using the Parameter-elevation Regressions on Independent Slopes Model (PRISM) to evaluate meteorological outputs from WRF (Fig. 1). PRISM interpolates between station-based observations of precipitation and other meteorological variables using a digitized elevation model and assuming that local differences in precipitation and temperature are primarily driven by differences in elevation, but accounting for other factors. Results from our preliminary comparisons between WRF output and PRISM data are presented in Shahid et al. [2010]. Relatively good overall agreement was found for both magnitude and location of precipitation over the Gulf of Mexico watershed area. However, the model seems to overestimate precipitation over Louisiana and Mississippi during the summer month. Further comparisons with satellite data will be used to suggest improvements to the model, including changing convective parameterization or cloud/precipitation microphysical scheme.
Because NO2 is the critical species in determining the nitrogen deposition, we are evaluating the CMAQ column amounts of NO2 using tropospheric column NO2 observations from the OMI sensor on NASA’s Aura satellite. Sulfate ion is typically the largest contributor to acidity, and SO2 gas is the precursor for sulfate. Thus, tropospheric column SO2 amounts derived from CMAQ are also compared with those measured by OMI.
Satellite derived measurements of the amount of organic matter present as particulate organic carbon (POC), chlorophyll, dissolved organic carbon (DOC) and total suspended solids (TSS) in surface waters of the Gulf of Mexico are critical for remote sensing monitoring of hypoxic conditions. We have been comparing these satellite products with output from the EPA’s Water Quality Fate and Transport Model (WASP, CE-QUAL-ICM) to assess how well the model is performing and suggest areas of improvement. Level 1 SeaWiFS and MODIS sensor data have been processed to level 2 using up-to-date versions of SeaDAS and IDL along with all the required masking. Measurements are processed using existing algorithms for chlorophyll, distributed by the NASA Ocean Biology Processing Group (OBPG), and for POC. Field measurements (e.g. Chl-a, DOC, POC, TSS concentrations) collected in the Gulf of Mexico by the EPA Gulf Breeze Lab are currently being applied to the validation and refinement of MODIS and SeaWiFS algorithms for improved estimates of biogeochemical variables in the study region.
Satellite and ground-based data have been compared with the estimates provided by the EPA’s Models before and after model modification resulting from evaluation with satellite data. Performance is measured with regard to improvements in the model estimates of precipitation, trace gas and aerosol, and water quality, as compared to the satellite data.
Task Figures
Fig. 1 – Model WRF estimates (left panels) and PRIS M measurements (right panels) of precipitation over the US, for January (upper panels) and July (lower panels) of 2006 (from Habib et al., 2010). |