Aqua: AIRS, AMSU, HSB, AMSR-E, CERES, MODIS

This brochure provides an overview of the Aqua spacecraft, instruments, science, and data products Aqua, Latin for water, is a NASA Earth Science satellite mission named for the large amount of information that the mission is collecting about the Earth's water cycle, including evaporation from the oceans, water vapor in the atmosphere, clouds, precipitation, soil moisture, sea ice, land ice, and snow cover on the land and ice. Additional variables also measured by Aqua include radiative energy fluxes, aerosols, vegetation cover on the land, phytoplankton and dissolved organic matter in the oceans, and air, land, and water temperatures. Note: this guide was produced before Aqua was launched; for the most recent information on Aqua, go to http://aqua.nasa.gov. Educational levels: Undergraduate lower division, Undergraduate upper division, Graduate or professional, Informal education

Land and cryosphere products from Suomi NPP VIIRS: overview and status

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team's evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS

Determination of atmospheric moisture structure and infrared cooling rates from high resolution MAMS radiance data

This program has applied Multispectral Atmospheric Mapping Sensor (MAMS) high resolution data to the problem of monitoring atmospheric quantities of moisture and radiative flux at small spatial scales. MAMS, with 100-m horizontal resolution in its four infrared channels, was developed to study small scale atmospheric moisture and surface thermal variability, especially as related to the development of clouds, precipitation, and severe storms. High-resolution Interferometer Sounder (HIS) data has been used to develop a high spectral resolution retrieval algorithm for producing vertical profiles of atmospheric temperature and moisture. The results of this program are summarized and a list of publications resulting from this contract is presented. Selected publications are attached as an appendix

Sea surface temperatures from VAS MSI data

A procedure is developed for estimating sea surface temperatures from multispectral image data acquired from the VISSR atmospheric sounder on the geostationary GOES satellites. Theoretical regression equations for two and three infrared window channels are empirically tuned using clear field of view satellite radiances matched with reports of SST from NOAA fixed environmental buoys. The empirical regression equations are then used to produce daily regional analyses of SST. Monthly mean SST's for the western North Atlantic and the eastern equatorial Pacific during March and July 1982 were produced for use in the SST Intercomparison Workshop Series. Workshop results showed VAS SST's have a scatter of 0.8-1.0 C and a slight warm bias with respect to the other measurements of SST. The VAS SST's show no discernible bias in the region of El Chichon volcanic aerosol cloud

The Use of Neural Networks in Identifying Error Sources in Satellite-Derived Tropical SST Estimates

An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors causing the errors of GOES SST products in the tropical Pacific. The accuracy of SST estimates is also improved by the model. The root mean square error (RMSE) for the daily SST estimate is reduced from 0.58 K to 0.38 K and mean absolute percentage error (MAPE) is 1.03%. For the hourly mean SST estimate, its RMSE is also reduced from 0.66 K to 0.44 K and the MAPE is 1.3%

The role of water vapor in climate. A strategic research plan for the proposed GEWEX water vapor project (GVaP)

The proposed GEWEX Water Vapor Project (GVaP) addresses fundamental deficiencies in the present understanding of moist atmospheric processes and the role of water vapor in the global hydrologic cycle and climate. Inadequate knowledge of the distribution of atmospheric water vapor and its transport is a major impediment to progress in achieving a fuller understanding of various hydrologic processes and a capability for reliable assessment of potential climatic change on global and regional scales. GVap will promote significant improvements in knowledge of atmospheric water vapor and moist processes as well as in present capabilities to model these processes on global and regional scales. GVaP complements a number of ongoing and planned programs focused on various aspects of the hydrologic cycle. The goal of GVaP is to improve understanding of the role of water vapor in meteorological, hydrological, and climatological processes through improved knowledge of water vapor and its variability on all scales. A detailed description of the GVaP is presented

An operational analysis of Lake Surface Water Temperature

Operational analyses of Lake Surface Water Temperature (LSWT) have many potential uses including improvement of numerical weather prediction (NWP) models on regional scales. In November 2011, LSWT was included in the Met Office Operational Sea Surface Temperature and Ice Analysis (OSTIA) product, for 248 lakes globally. The OSTIA analysis procedure, which has been optimised for oceans, has also been used for the lakes in this first version of the product. Infra-red satellite observations of lakes and in situ measurements are assimilated. The satellite observations are based on retrievals optimised for Sea Surface Temperature (SST) which, although they may introduce inaccuracies into the LSWT data, are currently the only near-real-time information available. The LSWT analysis has a global root mean square difference of 1.31 K and a mean difference of 0.65 K (including a cool skin effect of 0.2 K) compared to independent data from the ESA ARC-Lake project for a 3-month period (June to August 2009). It is demonstrated that the OSTIA LSWT is an improvement over the use of climatology to capture the day-to-day variation in global lake surface temperatures

Sensitivity of North American monsoon rainfall to multisource sea surface temperatures in MM5

In this article, four continually processed sea surface temperature (SST) datasets, including the Reynolds SST (RYD), the global final analysis of skin temperature at oceans (FNL), and two Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua SSTs retrieved from thermal infrared imagery (TIR) and midinfrared imagery (MIR), were compared. The results show variations from each other. In comparison with the RYD SST, the FNL data have -0.5° ∼ 0.5°C perturbations, while the TIR and MIR SSTs possess larger deviations of -2° ∼ 1°C, mainly due to algorithm and/or sensor differences in these SST datasets. A regional model, the fifth-generation Pennsylvania State University-Na tional Center for Atmospheric Research (Penn State-NCAR) Mesoscale Model (MM5), was used to investigate whether model atmospheric predictions, especially those concerning precipitation during the North American monsoon season, are sensitive to these SST variations. A comparison of rainfall, atmospheric height, temperature, and wind fields produced by model results, reanalysis data, and observations indicates that, at monthly scale, the model shows changes in the simulations for three consecutive years; in particular, rainfall amounts, timing, and even patterns vary at some specific regions. Forced by the MODIS Aqua midinfrared SST (MIR), which includes large regions with SST values lower than the conventional Reynolds SST, the MM5 rain field predictions show reduced errors over land and oceans compared to when the model is forced by other SST data. Specifically, rainfall estimates are improved over the offshore of southern Mexico, the Gulf of Mexico, the coastal regions of southern and eastern Mexico, and the southwestern U.S. monsoon active region, but only slightly improved over the monsoon core and the high-elevated Great Plains. Using MIR SST data, one is also capable of improving geopotential height and temperature fields in comparison wit he reanalysis data. © 2005 American Meteorological Society

Low-level water vapor fields from the VISSR atmospheric sounder (VAS) split window channels at 11 and 12 microns

A series of high-resolution water vapor fields were derived from the 11 and 12 micron channels of the VISSR Atmospheric Sounder (VAS) on GOES-5. The low-level tropospheric moisture content was separated from the surface and atmospheric radiances by using the differential adsorption across the 'split window' along with the average air temperature from imbedded radiosondes. Fields of precipitable water are presented in a time sequence of five false color images taken over the United States at 3-hour intervals. Vivid subsynoptic and mesoscale patterns evolve at 15 km horizontal resolution over the 12-hour observing period. Convective cloud formations develop from several areas of enhanced low-level water vapor, especially where the vertical water vapor gradient relatively strong. Independent verification at radiosonde sites indicates fairly good absolute accuracy, and the spatial and temporal continuity of the water vapor features indicates very good relative accuracy. Residual errors are dominated by radiometer noise and unresolved clouds