Category: Archive

238 – Quantifying Systematic Errors and Total Uncertainties in Satellite-based Precipitation Measurements
Principal Investigator(s): Y. Tian

Recent evaluations of TRMM-era multi-sensor precipitation products have helped raise the priority of developing improved over-land retrieval algorithms in preparation for the GPM era. An example of recent work evaluating TRMM-era multi-sensor precipitation products (Tian and Peters-Lidard, 2007) has documented systematic biases in overland retrievals related to land surface states—in this case the presence of inland water bodies. Physical precipitation retrievals rely on accurate characterization of the microwave radiometric properties of the land surface. Therefore it is critical to understand how the land surface states can affect these properties, and how we can accurately model these properties, specifically, surface microwave emissivity at various frequencies.

236 – Hypo-G: Improved Hypoxia Modeling for Nutrient Control Decisions in the Gulf of Mexico
Principal Investigator(s): M. Tzortziou

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

235 – Arctic and Southern Ocean Sea Ice
Principal Investigator(s): S. L. Farrell

The work being conducted under this project is in support of NASA’s Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) scheduled for launch in 2016. ICESat-2 is a follow-on to the ICESat mission, which operated between 2003 and 2009. ICESat-2 will provide sustained monitoring of changes in ice-sheet mass balance, and Arctic and Southern Ocean sea ice volume. The goals under this ICESat-2 Science Definition Team (SDT) project are to derive the Level 1 and 2 sea ice science requirements and measurement accuracies, and to determine the optimum spatial sampling strategy for profiling the complex sea ice environment of the Arctic and Southern Oceans.

234 – Aerosol Remote Sensing
Principal Investigator(s): M. Petrenko

The effects of atmospheric aerosols on the air quality, the hydrological cycle, and climate are still poorly understood. During the past decade, there have been increased efforts to employ satellite remote-sensing approaches in measuring aerosols in order to complement measurements from ground-based systems. However, because of the differences in the sensor measurement characteristics and algorithms used for aerosol retrievals, the products are often inconsistent, making it difficult to derive objective measures of aerosol amounts and properties. Therefore, it has become necessary to conduct integrated analysis of aerosol measurements acquired with different types of instrumentation, in order to narrow down the uncertainties that delay improvements in the knowledge of the different aerosol impacts. The purpose of this project is to provide an approach and a unified framework for inter-comparison and validation of aerosol measurements from different sensors and instruments, including ground-based, airborne, and spaceborne, obtained at different locations and time around the globe.

231 – Microphysical Processes of Atmospheric Convective Systems
Principal Investigator(s): T. Iguchi

Cloud microphysics focuses on the physical processes on the scale from μm to cm orders in clouds. Not only it decides features of precipitation from clouds attributed to convective systems, but also it has a large impact on the overall structure of the system through heating or cooling by the water phase conversion and radiation process. Exact representation of cloud microphysics is thus an important subject of numerical studies for cloud and convective systems. We propose the development of the numerical model package to investigate a role of the cloud microphysics for the atmospheric convective systems.

230 – Joint Aerosol-Monsoon Experiment
Principal Investigator(s): C. Li

Atmospheric aerosols, through interaction with clouds and alteration of the radiation, may influence the Asian Monsoon system, a critical component in the water cycle for this most populated continent of the world. Climate modeling studies of the aerosol-cloud-water cycle require detailed information about aerosol distribution and properties, which are highly variable and necessitate intense field deployments.

226 – Development of the Land Information System (LIS) Framework
Principal Investigator(s): K. Harrison

NASA’s Land Information System (LIS) is a high performance land surface modeling and data assimilation system. LIS supports global water cycle research, as land surface models predict key variables of the water cycle, including terrestrial water, energy, and biogeophysical states. This task involves adding functionality to LIS through the addition of advanced algorithms to maximize the utilization of available data and science. Recent extensions to LIS include a new optimization and uncertainty analysis subsystem (LIS-OPT/UE). The optimization and uncertainty modeling algorithms in LIS allow for use of satellite (and other) data for parameter estimation and probabilistic prediction. These new capabilities will improve land surface prediction and therefore global water cycle prediction.

224a – A Land Data Assimilation System for Famine Early Warning
Principal Investigator(s): S. Yatheendradas

The overarching goal was to demonstrate improved accuracy in runoff, stream flow, and flood monitoring and simulation that result from the combination of NASA infrastructure of snow data (MODIS) and model (LIS), with operational NOAA National Weather Service (NWS) River Forecast System (NWSRFS) Decision Support Tools (DST). The objectives were to engineer and integrate NASA satellite- and model-derived land surface products, through the Land Information System (LIS), into NWSRFS DST component models. The specific science question we investigated is whether adjusting modeled snow area with MODIS estimates improves modeled streamflow.

221 – Optical Properties Of Mineral Dust Aerosol
Principal Investigator(s): R. Hansell

To conduct testing of the MODIS Characterization Support Team’s (MCST) updated calibration approaches for collection 6 Level-1B Terra/Aqua MODIS data using NASA Goddard’s Deep Blue aerosol retrieval algorithm. Also to investigate the optical properties of mineral dust aerosol between the near to thermal IR using global aerosol field measurements combined with analysis of model data to help advance ground and satellite-based remote sensing applications and column energetic studies.