Members of the Department of Atmospheric and Oceanic Science and faculty affiliates from local government agencies, are involved in various aspects of Remote Sensing Research. Activities include development of inference techniques, algorithm implementation and evaluation, and use of remotely sensed information in climate modeling and research. Topics span terrestrial, oceanic, and atmospheric disciplines, and include research on retrieval of trace gases (e. g., ozone), greenhouse gases (e. g., water vapor), aerosols, modeling of surface processes, as well as inference of surface fluxes and properties, such as radiation, salinity, rainfall, net primary productivity, and sea level.

Satellite Inference of Stratospheric and Tropospheric Ozone

Ozone plays an important role in the radiative and chemical balance in the atmosphere. Ozone in the stratosphere filters out harmful ultraviolet radiation from reaching the earth, and high levels of ozone near ground level cause respiratory problems for people. In addition, ozone near the tropopause exerts considerable radiative forcing. Dr. Robert D. Hudson is developing algorithms for the derivation of the global picture for total ozone in both the stratosphere and troposphere, from measurents of the ultraviolet albedo of the earth. Instruments which currently measure these albedos are the Total Ozone Mapping Spectrometer (TOMS), the Solar Backscatter Ultraviolet Spectrometer (SBUV), and the Global Ozone Monitoring Experiment (GOME). Algorithms have been developed which retrieve tropospheric column ozone in the tropics, and daily near real-time images of the results are given at the Tropical Troposheric Ozone Home Page. This technique is currently being extended to the Mid-Atlantic region to examine high ground-level ozone events (smog).

Two major interferences in the derivation of total ozone are sulfur dioxide and clouds of aerosol particles. An algorithm was developed to remove these interferences from albedos obtained during periods of major volcanic eruptions, and information was obtained about the nature of the emitted gas and the rate of formation of the resulting sulfate aerosols, which are another major source of climate forcing. A new algorithm is currently being developed to separate the effects of ozone and aerosols on the measured albedos during non-volcanic periods. This algorithm will determine the aerosol type and optical depth. In addition there is a continuing study of improvements to the algorithms used by NASA and NOAA for the retrieval of operational ozone and related data products.

Satellite Inference of Temperature and Moisture

Dr. Owen E. Thompson is pursuing several investigations dealing with the quality and fidelity of temperature and moisture soundings inferred from radiation measurements collected by advanced satellite instruments, such as the Atmospheric Infrared Radiation Sounder (AIRS) or Infrared Temperature Sounder (ITS).

Remote Inference of Surface and Atmospheric Radiation

Earth's climate depends on its radiative balance, controlled by solar input, surface properties, and distribution of radiatively active gases, clouds, and aerosols in the atmosphere. Radiative fluxes are the forcing functions of the climate system and are responsible for the maintenance of atmospheric motions. The exchange of energy from radiation fluxes to other forms of energy, such as sensible and latent heat fluxes, occurs at the surface of the earth. Therefore, it is of interest, to have information on surface radiative fluxes and thier variability. This can enable scientists to improve parametrization of surface-atmosphere interactions, to validate climate models, and to better understand the hydrological cycle. The use of climate models for simulating plausible climate change scenarios, requires improved capabilities in respect to hydrologic modeling and in assessing the effects of increased greenhouse gases. Of special interest is the solar radiation in the visible part of the spectrum, namely, in the interval of 400-700 nm, known as the Photosynthetically Active Radiation (PAR). Information on the spatial and temporal distribution of photosynthetically active radiation (PAR), by control of the evapotranspiration process, is required for modeling the hydrological cycle and for estimating global oceanic and terrestrial net primary productivity (NPP).

Earth orbiting satellites are well suited to provide a global view of our climate. Professor Pinker and her associates in the Department of Atmospheric and Oceanic Science, Drs. I. Laszlo, G. Pandithurai, Xu Li, and graduate students, participate in several national and international projects, aimed at improving the understanding of the climate system. Examples of projects include the Global Energy and Water Experiment (GEWEX), the Earth Observing System (EOS) Program, the GEWEX Continental-scale International Project (GCIP), the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) Project, the NOAA/NASA PATHFINDER Project, and the Advanced Earth Observing Satellite (ADEOS)-II mission sponsored by the National Space Development Agency of Japan (NASDA). These activities are linked to efforts at other institutions.

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A close collaborative activity among the National Oceanic and Atmospheric Administration (NOAA)/National Environmental Satellite Data and Information Service (NESDIS), the NOAA National Center for Environmental Prediction (NCEP), and the Department of Atmospheric and Oceanic, University of Maryland is supporting the Global Energy and Water Cycle Experiment (GEWEX) Continental Scale International Project (GCIP). Information on surface radiative fluxes is produced in real time by NOAA/NESDIS, using information from the NCEP ETA model. The derived information is used in a wide range of applications, such as evaluation of numerical models, estimation of energy budgets, and snow melt modeling. A novel application is the use of the radiative fluxes as forcing functions in numerical weather prediction (NWP) models, such as the Land Data Assimilation System (LDAS) project. It is hoped that this approach will reduce the errors in the storage of soil moisture and energy which are often present in NWP models and which degrade the accuracy of forecasts.

The work on algorithm development for global scale inference of radiative fluxes is coordinated with the NASA Langley Research Center (LaRC), where the algorithms are implemented with the PATHFINDER International Cloud Climatology Project (ISCCP) data. At Maryland, special research effort is being placed on methodology improvements for dust and biomass burning scenarios, work that is linked to the EOS and (LBA) projects, and should benefit from the international Global Aerosol Climatology Project (GACP).

The Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) is an international research project led by Brazil. The world's tropical forests are under major stress of conversion to various forms of land use. Research is in progress towards the improvement of understanding the hydrologic cycle of this region. It is anticipated that spaceborne remote sensing capabilities will help to define the basin scale forcing functions, to determine how the basin functions as a regional entity.

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In the EOS Validation framework, an activity in a desert ecroachment zone in sub-Sahel Africa was undertaken, in collaboration with African scientists from the University of Ilorin, Nigeria. This is a climatically important region due to its location in a desert transition zone and because of the influence of the dusty Harmattan wind which is persistent for prolonged periods of time, and characterized by steady dusty conditions with high aerosol loading. Observations are made of surface radiative fluxes, as well as aerosol optical depth. The radiation observations are linked to the World Climate Research (WCRP) Baseline Surface Radiation Network (BSRN) activity, and aerosol data from this station are part of the (AERONET) network.

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Recently, a new CD-ROM was prepared which contains global scale information on the distribution of daily and monthly mean values of Surface and Top of the Atmosphere Shortwave Radiation Budget (SRB) Parameters, for the period July 1983 to August 1994. The derived values were produced at the University of Maryland, and are based on satellite observations and on ancillary data as available from the Global Energy and Water Cycle Experiment (GEWEX) ISCCP D1 product, at a nominal resolution of 2.5 degrees. Provided are: shortwave surface downward flux; shortwave surface upward flux; visible surface downward flux (Photosynthetically Active Radiation (PAR)); visible surface upward flux; shortwave top of the atmosphere net flux (down-up). The CD-ROM can be obtained by writing to: srb@atmos.umd.edu

More information is available at the Surface Radiation Budget Home Page

Remote Sensing of Rainfall

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Accurate and detailed precipitation observations are crucial for the complete understanding of the surface hydrology, interaction of the surface with the overlying atmosphere, and prediction of changes in water resources on time scales ranging from hourly to seasonal and annual. At many locations within the continental United States, radar and raingauge coverage is inadequate, as evidenced by the experimental Stage IV analyzed data from the National Environmental Prediction Center (NCEP). Moreover, radar and gauge data do not exist over the Gulf of Mexico and Northern regions of Mexico. Satellite estimates of precipitation play an important role in the collection and the use of precipitation data. They have proven to be quite useful in large scale climate applications, as produced for the Global Precipitation Climatology Project (GPCP), and have been applied to estimate rainfall for instantaneous and heavy precipitation events.

For high temporal and spatial resolution (about one hour and 10 km), estimates of rain from geostationary satellites represent the only plausible source of information. The most common techniques are based on infra-red observations, and they are most effective in tropical air masses which are dominated by deep convective rainfall. They tend to underestimate rainfall from warm top clouds, and overestimate precipitation from cold non-raining cirrus clouds, a problems that can prove to be serious for high spatial and temporal scales. A multi-spectral model was developed that seems to overcome many of these problems. It uses visible, near infrared and infrared observations from GOES satellites to identify both deep convective and "warm" precipitating clouds.

Remote Sensing of the Oceans

Observing the changing climate of the ocean presents a daunting observational challenge. One of the most exciting developments in climate research in recent years has been the introduction of satellite remote sensing observations to ocean studies. The ocean is a conducting medium and thus electromagnetic sensors are constrained to observe surface properties including: infrared and microwave emission (sea surface temperature), laser and microwave ranging (sea level), microwave reflectance (wave heights and surface wind stress), and brighness in the visible bands (phytoplankton concentration). Some of these surface observations allow us to infer subsurface properties of the ocean. For example, in the tropics, increases in sea level coincide with a deepening of the warm upper layer of the ocean (a 1cm rise roughly corresponds to a 2m deepening). In the very near future, satellite-based observations of time-dependent gravity will allow an additional direct measurement of the horizontal redistribution of mass. Scientists within the Department involved in research projects examining all of these data types include Drs. Carton, Wang, Subraminium, Murtugudde, Wajsowicz, and Chepurin.

Satellite Inference of Surface Chlorophyll, Primary Production and Carbon Fluxes

The Wide Field of view Sensor (SeaWiFS) which was launched during August 1997 has been providing unprecedented high quality data of surface ocean color. Several ocean color missions are now operational or planned by the United States and other countries such as India and Japan. Dr. Ragu Murtugudde is working on the simulation of surface distributions of chlorophyll to allow for the interpretation of remotely sensed ocean color in terms of subsurface ecosystem variability. Satellite data of ocean color have several applications such as its linkage to fisheries with a potential for forecasting fish locations. More importantly, global primary productions can be estimated for the first time from biomass inferred from SeaWiFS and other remotely sensed ocean color data. Research includes attempts to estimate surface CO₂ fluxes and their variability on seasonal-to-interannual time-scales. The overall goal is to determine the contribution of the marine ecosystem to the global carbon budget. Other satellite data such as precipitation from Tropical Rainfall Measuring Mission (TRMM) and winds from QuickScat are used extensively in this study.

Modelling Surface Energy Balances

The representation of surface processes in numerical models is critical in studies of climate change and variability; likewise, seasonal prediction relies on adequate characterization of land surface-atmosphere energy exchanges.

Dr. E. H. Berbery is examining the surface energy balances of operational models and evaluating them against ground and satellite information. His research is in close collaboration with respective Operational Centers, to help in their development of surface parameterizations.

The figure at left presents a comparison of downward shortwave radiation at the surface as estimated from satellites and the following two operational models: National Center for Environmental Prediction (NCEP) ETA model and the Canadian Meteorological Centre Global Multiscale Environmental (GEM) model. The Eta model seems to have an excess of downward shortwave radiation at the surface, which has to be compensated by other energy related processes. Further details on this subject can be found in:

More information can also be found at Dr. Berbery's GCIP page