Home » Travis Swaim » Page 139

Author: Travis Swaim

245

245 – Develop Satellite Snow Data Assimilation Capabilities into the NASA Land Information System (LIS) to Support NWS Hydrologic Applications
Principal Investigator(s): Y. Liu

Accurate snow estimation during snow accumulation and melting periods is essential for various hydrologic and water resources applications in snow-impacted areas. However, estimates of snow water equivalent (SWE) from current land surface models typically contain errors due to poor model physics in representing the snow processes and other sources of uncertainties. Satellite-derived snow products, albeit subject to errors themselves, hold great potential for improving snow estimates if properly assimilated into the models. This project represents a collaborative effort between NASA GSFC and the National Operational Hydrologic Remote Sensing Center (NOHRSC) of the National Weather Service, which aims to develop snow data assimilation (DA) capabilities in LIS to integrate MODIS fraction snow cover area (fSCA) products into several land surface models to improve snow prediction over the Alaska and Afghanistan domains. The developed snow DA capability will be transferred to NOHRSC to support their hydrologic operations.

Read More »

241

241 – Interactive processes between cloud-precipitation, land-surface, radiation, and aerosol processes
Principal Investigator(s): T. Matsui

Aerosols, cloud, and precipitation processes play major roles in describing earth’s energy and water budget and cycle. Thus, understanding of these processes and interactions via in-situ observations, satellite remote sensing, and state-of-art numerical modeling is essential for atmospheric scientists. However, links between satellite observations and modeling have been always untied, because assumptions in geophysical parameters are usually different between them. Thus, a new tool must be developed to overcome such issue, and facilitate modeling development using satellite observations.

Read More »

240

240 – Aerosol Characterization and Radiative Forcing Assessment Using Satellite Data and Models
Principal Investigator(s): H. Yu

Aerosols affect the Earth’s energy budget directly by scattering and absorbing radiation and indirectly by acting as cloud condensation nuclei and, thereby, affecting cloud properties. Aerosols can be transported thousands of miles downwind, thereby having important implications for climate change and air quality on a wide range of scales. Enhanced new satellite passive sensors introduced in the last decade, the emerging measurements of aerosol vertical distributions from space-borne lidars provided the opportunity to attempt measurement-based characterization of aerosol and assessment of aerosol radiative forcing. Such satellite-based methods can play a role in extending temporal and spatial scale of field campaigns and evaluating and constraining model simulations. On the other hand, model simulations and measurements from field campaigns can provide essential parameters that satellites don’t observe. The overall goal of this research is to characterize aerosol distributions and assess the aerosol radiative forcing through an integration of multiple satellite observations and model simulations.

Read More »

239

239 – HIMALA: Climate Impacts on Glaciers in the Himalayan Region
Principal Investigator(s): M. Tzortziou

Glaciers are the largest reservoir of freshwater on Earth supporting one third of the world’s population. Himalayas possess one of the largest resources of snow and ice, which act as a freshwater reservoir for more than 1.3 billion people. Monitoring glaciers is important to assess the overall health of this reservoir. Glaciers and snowfields also form potential hazards in the Himalayas, and in similarly glacierised regions of the world. Water resources will be affected by climate change as well as population growth, changing economic activity, land use change, rapid urbanization and inefficient water use. National governments have limited capacity to determine and accurately predict possible impacts to water resources due to scarcity of hydrometeorological data, limited technical capacity, and the transboundary nature of many major river systems. This has also led to recent controversies surrounding the fate of Himalayan glacier melt, which highlight the need for further glaciological and hydrological research in this region.

The HIMALA project aims at developing a system that will aid populations at risk on early warning of floods, droughts and other water and climate-induced natural hazards in the Himalayan region. Among our main goals are to: (i) introduce the use of NASA Earth Science products and models to the International Center for Integrated Mountain Development (ICIMOD) and its member countries, through collaboration with USAID (the United States Agency for International Development) and USGS (the U.S. Geological Survey), (ii) enhance the decision making capacity of ICIMOD and its member countries for management of water resources (floods, agricultural water) in the short (snow, rainfall) and the long-term (glaciers), and (iii) provide projections of climate change impacts on water resources through 2100 using the IPCC models.

Read More »

238

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

Determining the uncertainties in precipitation measurements by satellite remote sensing is of fundamental importance to many applications. These uncertainties result mostly from the interplay of systematic errors and random errors. Although many satellite-based global precipitation datasets are routinely produced, a quantitative, global picture of their error characteristics is lacking.

Read More »

237

237 – Data Assimilation of AMSR-E Soil Moisture Retrievals and Analysis of Soil Moisture Spatial Variability
Principal Investigator(s): B. Li

Recent studies on the assimilation of Advanced Microwave Scanning Radiometer (AMSR-E) derived soil moisture retrievals focus on extracting anomaly signals embedded in the sensor data to improve the anomaly detection of land surface models. Utilizing only anomaly information does not address the issue of model bias, an issue which poses a challenge for most assimilation methods. Models are often biased due to uncertainties in the input parameters and deficiencies in model physics. In particular, the bias in the simulated soil moisture fields has a substantial impact on the estimation of land surface processes such as evapotranspiration (ET) and runoff since they are calculated based on the absolute value of soil moisture.

In contrast to anomaly information, the actual value of AMSR-E retrievals represents the spatial mean, and can be used to reduce model bias. Recognizing the need and the potential, an ensemble Kalman filter with a mass conservation constraint was developed to assimilate the actual value of AMSR-E retrievals without any scaling or preprocessing. This scheme uses different updating equations for the upper and lower two layers so that the bias in the upper two layers can be reduced using a conventional updating scheme while the lower two layers are updated through an equation conserving the mass within each soil column.

Read More »

236

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.

Read More »

235

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 strategy for sampling the complex sea ice environment of the Arctic and Southern Oceans.

Read More »