Category: Archive

124 – Evaluating Potential for Satellite Observations to Improve Soil NOx Emissions Estimates by Satellite/Emissions/Photochemical Model Intercomparison
Principal Investigator(s): S. Ehrman

Soil NOx emissions contribute to the tropospheric NO2 column. Soil bacteria produce NO through the processes of nitrification and denitrification. Field experiments, model simulations [e.g., Davidson et al., 1998] and satellite observations indicate that NO emissions pulse following rain on dry soils, particularly after recent application of fertilizer. Satellite-based observations have been instrumental in determining the magnitude of soil NOx emissions. Globally, soil emissions of NO contribute perhaps 5-10 Tg N per year to the global NOx budget. Jaeglé et al. [2004, 2005] and Bertram et al. [2005] estimated the soil NOx source using top-down approaches based on satellite data from the GOME and SCIAMACHY instruments, respectively. Their results suggest that biospheric models underestimate soil NOx emissions by a factor of 2. The increasingly high resolution of satellite data makes it possible to constrain emission sources over smaller and smaller regions. Reducing uncertainties in this source is an active area of research.

121 &139 – Global Floods and Landslides
Principal Investigator(s): R. Adler, H. Wu

The objective is to develop, test and apply a global system for estimating floods and landslides using satellite precipitation information, other satellite data and hydrological models.

116 – Automating Boundary Layer Detection for Aerosol Lidar
Principal Investigator(s): Z. Li

During March and April 2008, the ICEALOT research cruise traveled into the ice-free Arctic as far as 81° N. The campaign observed many properties of the 2008 Arctic haze, including the aerosol backscatter with altitude that was provided by an MPLNET lidar instrument. Because of the shared focus between many instruments, the lidar backscatter profiles came with a greater context of observations with which to validate conclusions about the chemistry and transport of the Arctic haze. The observations were also supported by satellite data from CALIPSO and MODIS, and by trajectory modeling. This information was valuable for studying the behavior of the planetary boundary layer over the marine Arctic and the transport of aerosol plumes into it from the midlatitudes. With several potential sources of validation, the cruise observations were also useful for evaluating methods to detect the planetary boundary layer in lidar profiles.

115 – The Global Reservoir and Lake Monitoring System: Enhancing the USDA/FAS DSS with NASA, NRL and ESA Satellite Radar Altimeter Data
Principal Investigator(s): C. Birkett (ESSIC/UMD)

This program aims to enhance and expand a satellite-based, near-real time, reservoir and lake water-level monitoring system. This system is on-line, operational, existing within the US Department of Agriculture (USDA) decision support system (DSS) through the cooperative USDA/NASA Global Agricultural Monitoring (GLAM) program. Current lake level products stem from the NASA/CNES TOPEX/Poseidon (archival 1992-2002), NASA/CNES Jason-1 (post 2002 and near real time), NASA/CNES Jason-2/OSTM (post 2008) and the US Naval Research Lab’s GFO (post 2000) missions. The primary user is the Office of Global Analysis (OGA) within the USDA Foreign Agricultural Service (FAS). The FAS utilize the products for irrigation potential considerations and as general indicators of drought and high-water conditions. The monitoring system thus has relevance to water resources management and agriculture efficiency applications at both the national and international level.

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 inputs to study of the water cycle, including terrestrial water, energy, and biogeophysical states. This project involves adding functionality to LIS through its coupling to other physical models and 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 and support of radiative transfer model coupling. These extensions allow us to more fully exploit satellite data to advance science and address agency goals. The coupling of a radiative transfer model to LIS moves us more towards direct assimilation of satellite data into land surface models. 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. New algorithms/coupled models hold potential for improving predictions. They need to be added into LIS and fully tested on real problems to assess resulting improvement and identification of areas that would benefit from further research.

114 – Using a Cloud-resolving Model to Simulate Lightning NOx Production During the TC4 Experiment
Principal Investigator(s): K. Cummins

Lightning NOx production is the largest uncertainty related to the overall global NOx budget. Cloud-resolved chemistry simulations for observed thunderstorms can be used to make estimates of average NOx production per flash. Lightning and airborne chemistry observations are available from the Stratospheric-Climate Links with Emphasis on the Upper Troposphere and Lower Stratosphere (SCOUT-O3) and Aerosol and Chemical Transport in Tropical Convection (ACTIVE) field campaign. Therefore, it is useful to simulate a convective event from SCOUT-O3/ACTIVE, in particular a tropical thunderstorm over the Tiwi Islands located north of Darwin, Australia, on 16 November 2005. NOx production from lightning throughout the storm duration can lead to the formation of ozone downwind of the storm anvil following storm dissipation.

Ozone production downwind of thunderstorms has a large impact on the upper tropospheric ozone budget. We will be testing the hypothesis from the literature that on average a tropical flash may make less NOx than a midlatitude flash and the application of a new lightning flash rate parameterization scheme in the Hector storm simulation.

113 – Does Management Matter? Assessing the Effects of Charcoal Production and Management on Woodland Regeneration in Senegal
Principal Investigator(s): K. Wurster

In much of Sub-Saharan Africa, more than 75% of a rapidly growing urban population depends on charcoal as their primary source of energy for cooking. The high demand for charcoal has led many to believe that charcoal harvesting catalyzes widespread deforestation. The Senegalese government and international donors have initiated projects within protected areas to combat deforestation and created land management plans to sustainably harvest charcoal. To date, the effects of forest management techniques on forest sustainability are still in question. This research uses a multiphase approach integrating satellite analysis with field surveys to assess the effect of varying forest management strategies on forest regeneration and sustainability after charcoal harvesting.

109 – NASA Decision Support: Monitoring Air Quality Effects of Anthropogenic Emissions Reductions and Estimating Emissions from Natural Sources
Principal Investigator(s): D. Allen

An accurate specification of anthropogenic and natural emissions is crucial for determining the impact of emission perturbations on air quality. However, lightning-NO emissions, a substantial contributor to tropospheric NO2 columns over the United States during the summertime, are not included in the Community Multiscale Air Quality (CMAQ) model used by the Environmental Protection Agency. A goal of this project is to add lightning-NO emissions to CMAQ. Simulations with lightning-NO emissions will provide more accurate estimates of nitrogen deposition and will be useful for top down estimates of anthropogenic emissions. A second goal of this project is to use tropospheric nitrogen dioxide (NO2) columns retrieved from the Ozone Monitoring Instrument aboard NASA’s Aura satellite to refine emissions of nitric oxide (NO) by microbial activity in soils calculated by the Biogenic Emission Inventory System (BEIS) that is used within the EPA’s Community Multiscale Air Quality Model (CMAQ). The lightning-NO portion of this project is supported under this Grant.

ESSIC generated materials pertaining to research, reports, education, and general information and overview purposes can be found within the Publications section. (A brief description of