213 – Applications, Evaluation, and Improvement of Goddard Multi-scale Modeling System
Principal Investigator(s): B-W. Shen
To examine the impacts of resolved moist processes on the short-term and long-term climate simulations with the MMF.
204 – GMAO Core MERRA Research & Evaluation of Global Water Cycle in Reanalyses
Principal Investigator(s): J. Chen
The changes of observing system have significant impact on the temporal consistency of all reanalysis datasets. Especially when new observation types are introduced, the related discontinuities or jumps could be big obstacles for climate study.
MERRA is a global reanalysis dataset based on NASA GEOS5 data assimilation system. In 2011, we continued to investigate the impact of observing system changes on the MERRA dataset, especially the different characters of impact from individual observing system change events, namely the introduction of SSM/I in 1987 and NOAA15 ATOVS in 1998.
203 – Diurnal Variation of Tropospheric Trace Gas Amounts and Aerosol Optical Characteristics
Principal Investigator(s): M. Tzortziou
The project involves the development of a new ground-based network of highly accurate spectrometer systems (Pandora and Cleo instruments, Fig 1) and the development, optimization and validation of remote-sensing retrieval algorithms for obtaining new measurements of aerosol optical characteristics and tropospheric trace gas amounts and vertical distribution (NO2, O3, SO2, H2O, HCHO). The resulting data provide a unique dataset for bounding tropospheric photochemical models, and studying the evolution of tropospheric ozone, NO2, other trace gases, and aerosols and their impacts on climate and air quality. Measurements are applied to improve interpretation of current satellite observations and assess more effective design and observing strategies for future NASA satellite missions.
Task 202 – Ground-based Supersite/Network Measurements in Support of NASA/EOS Missions
Principal Investigator(s): Q. Ji
According to NASA’s Science Mission Directorate (SMD), "in order to study the Earth as a whole system and understand how it is changing, NASA develops and supports a large number of Earth observing missions. These missions provide Earth science researchers the necessary data to address key questions about global climate change." (http://science.nasa.gov/earth-science/missions). As a major component of the Earth Science Division of NASA/SMD, "the Earth Observing System (EOS) is a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans." (http://eospso.gsfc.nasa.gov). As the EOS follow-on, "the Decadal Survey will generate consensus recommendations from the Earth and environmental science and the applications communities regarding a systems approach to space-based Earth Science observations." (http://decadal.gsfc.nasa.gov). However, satellite observations alone is not sufficient to provide a complete understanding of the complex earth-atmosphere system. Extensive ground-based measurements and comprehensive modeling analysis are also indispensable parts in this endeavor.
200 – Global Land Data Assimilation System (GLDAS)
Principal Investigator(s): H. K. Beaudoing
Land surface states and fluxes influence the weather and climate through exchanges of energy, water, and momentum between land and atmosphere. The energy and water stored in land present persistence on diurnal, seasonal, and inter-annual time scales. Because these conditions (e.g. soil moisture, temperature, and snow) are integrated states, biases in forcing data (i.e. meteorological and land characteristics) and parameterizations (i.e. models) lead to incorrect estimates. We are working on deriving accurate surface conditions at global, high spatio-temporal resolutions, and near-real time to help improve weather forecast and prediction skills, water and energy budget studies, and water resource management applications.
148 – CloudSat-TRMM Intersection Processing
Principal Investigator(s): Shen-Shyang Ho
Before the launch of CloudSat in April 2006, the Ku-band (13.8 GHz) Precipitation Radar, PR, aboard the Tropical Rainfall Measurement Mission (TRMM) was the only spaceborne radar capable of making rainfall measurements. The TRMM PR is designed for precipitation measurements over the tropics and is capable of measuring most rain rates greater than 0.7 mm/h with its = 70 dB dynamic range. However, its 17 dB sensitivity effectively makes the PR unable to measure light rains with rain rates less than or equal 0.7 mm/h. Although the W-band (94 GHz) Cloud Profiling Radar, CPR, flown on CloudSat is designed for observing the vertical structure of clouds it is also capable of measuring light rains. The CPR’s light rain capability naturally complements the PR. In addition, the CloudSat CPR offers information about the cloud structure above the rain which is useful in providing better attenuation estimate for the PR.
The synergy of these two spaceborne radars possesses such a potential for benefiting the researches of cloud precipitation systems that it is only logical to pursue a combined product of the two. In this project, the main objective is the design and implementation of efficient and effective algorithm to extract the 2D-CloudSat-TRMM intersection data product.
146 – Analysis of OMI tropospheric NO2 data in relation to global lightning flash data
Principal Investigator(s): K.Pickering
This effort will be aimed at estimating NOx production from lightning through analysis of Aura/OMI tropospheric NO2 data. The second major data set to be utilized will be the World Wide Lightning Location Network (WWLLN) flash data. The OMI data (which have been retrieved especially for quantifying the lightning impact) and the WWLLN data will be allocated to the NASA Global Modeling Initiative (GMI) global grid. Analysis will be conducted on this grid to identify matches between major lightning events and the Aura/OMI overpass. Mean NOx production per flash will be computed for each grid cell.
145 – Model based study of DC-Baltimore Urban heat island
Principal Investigator(s): R. Murtugudde
This task provides additional support to look at the use of Terra and other data sets in the application of urban related impacts to the Chesapeake Bay environment within the context of the on-going CBFS. The impact of Urbanization, land use, and heat island effects on weather and climate is being studied in a dynamic downscaling framework for Regional Earth System Prediction. Urban areas are known to alter local temperature and winds due to differences in surface roughness, albedo, and surface sensible and latent heat fluxes. As the human population continues to grow we can also expect urban areas to expand and potentially affect weather and climate on a regional scale in some areas.
The Urban Heat Island (UHI) impact of DC-Baltimore on local precipitation is studied using WRF at 500m resolution. The various processes related to urban surfaces are simulated using an urban canopy model in combination with NOAH’s Land Surface Model. The heavy precipitation event that occurred on 13th-14th July 2010 in the DC-Baltimore area is analyzed.
140 and 141 – Earth Model-Human Model
Principal Investigator(s): E. Kalnay
Human population and consumption has grown significantly over the past few decades. The Earth’s natural resources were assumed to be practically infinite for the whole length of the history, but we are now realizing that they may be scarce. This has rung a bell for the policy makers, scientists, economists, and all other conscious individuals. Economic growth has reached an “uneconomic growth” phase. To cope with such issues, new fields of study like “ecological economics” are born. Several research groups around the globe have developed (mathematical) models to predict the future of human population and nature. Such models have helped scholars to understand and investigate possible scenarios for the future of life on our planet more thoroughly.
The most complete versions of such models incorporate population, climate, energy, and agriculture as main variables. However, some of these variables, like population, are taken as exogenous variables and therefore, the coupling between the variables is uni-directional. This means that, for example, increased population can affect climate by creating more pollution, but the climate change does not feed back on the population.
136 and 137 – Impact of satellite sensor calibration on the long-term trend of global aerosol products.
Principal Investigator(s): Z. Li
Aerosols influence both the transfer of short- and long-wave radiation through the processes of scattering and absorption; this is known as the aerosol direct effect. Accurate understand of the overall radiative forcing due to aerosols is further compounded due to their high spatiotemporal variability. Satellite observations on multiple platforms have been made since the late 1970s to measure aerosol loading and optical properties and have been used to constrain various types of models as well as in atmospheric reanalyses. However, inconsistencies exist between different satellite derived aerosol products which can result in discrepancies of up to 50% in aerosol optical depth (AOD), for example [Li et. al. 2009].
Li et. al. （2009）found that differences in satellite calibrations lead to the largest discrepancies in AOD, with cloud screening, aerosol model selection, and surface effects also contributing, albeit to lesser extents. Halthore et. al. [2008] note that, due to sensor performance degradation following launch, prelaunch calibrations are generally not valid. This is further confirmed by Xiong et. al. [2010]. Due to the weak radiometric signal of aerosols, high calibration accuracy and precision are needed as well as consistency across sensors in order to produce an accurate long-term aerosol climate data record time series [Li et. al. 2009; Cao et. al. 2008]. A linear change of -0.01/decade in aerosol optical thickness (AOT) is reported from nearly 25 years of global and monthly mean AVHRR aerosol observations [Zhao et. al. 2008].
In the current study, the impact of satellite sensor calibration on the long-term trend of global aerosol products will be assessed, with a specific focus on NASA’s MODIS instruments. Other sensors of interest to this study are NOAA’s AVHRR and NOAA/NASAs VIIRS instruments.
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