A53F-0330
Is There a Link Between Tropical Sea Surface Temperature and Low Stratospheric Temperature?
Tropical convective clouds contribute to the radiative heating of the upper troposphere and low stratosphere and influence the dynamics of the Hadley and Walker circulations. Since convective processes are driven by the sea surface temperature (SST) it is natural to expect correlations between the SST and the low stratosphere temperature (Rosenlof and Reid, 2008). Water vapor can be lifted up by Deep Convective Clouds that penetrate into the low stratosphere (Aumann et al., 2008). We examine a possible link between the tropical SST and low stratospheric temperature using the high-cadence day and night measurements of temperature at 50 hPa, which are made by the AIRS Infrared sounder on Aqua spacecraft, and the Real Time SST records for 5-year period 2002-2007. The data are divided into four groups covering the West Pacific, East Pacific, Indian, and Atlantic oceans. The noise, oscillatory modes (such as the annual variation), and trends in the surface and stratospheric temperatures are identified using the Empirical Mode Decomposition (Huang and Wu, 2008). References: Aumann, H. H., A. Ruzmaikin and J. Teixeira, Geophys. Res. Letters, doi:10.1029.2008GRL034562, 2008. Huang, N, and Y. Wu, Rev. Geophys., 46, doi:10.1029/2007RG000228, 2008. Rosenlof, K. H. and G. Reid, J. Geophys. Research 113, D06107, 2008.
A53F-0331
Application of PCA using hyperspectral infrared sounder data to climate research
The application of Principle Component Analysis (PCA) to cloud-free hyperspectral sounder data provides insight into climate changes which may otherwise be masked by noise in the data. However, the most obvious change in the climate will be seen in clouds. We evaluate the sensitivity of the PCA eigenfunctions to the training data set under typical clear and cloudy conditions. We do this by creating nominally equivalent training sets by randomly selecting 10,000 near nadir spectra from the 100,000 spectra within 0.5 degrees of nadir collected by the Atmospheric Infrared Sounder each day. We then evaluate the correlation been equal rank eigenfunctions derived from different training sets.
A53F-0332
Intercomparison and Validation of AIRS, MODIS, and ASTER Land Surface Emissivity Products over the Namib and Kalahari Deserts in Southern Africa
Land surface emissivity is a critical parameter for retrieving land surface temperatures from spaceborne Thermal Infrared (TIR) measurements. Land Surface Temperature and Emissivity (LST&E) data are key parameters in global climate change studies that involve climate modeling, ice dynamic analyses, surface- atmosphere interactions and land use, land cover change. The errors in retrievals of atmospheric temperature and moisture profiles from hyperspectral infrared radiances, such as those from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite, are strongly dependent on using constant or inaccurate surface emissivities, particularly over arid and semi-arid regions where the variation in emissivity is large, both spatially and spectrally. LST&E products are available from spaceborne sensors such as AIRS, MODIS and ASTER at varying spatial, spectral, temporal resolutions, and using different retrieval algorithms. ASTER provides LST&E data with the highest spatial resolution (90 m), compared with AIRS (50 km) and MODIS (1 and 5 km). AIRS has the highest spectral sampling and both AIRS and MODIS acquire data at much higher temporal frequencies (every 2-3 days) compared with ASTER (every 16 days). In this paper we present validation and intercomparisons of AIRS, MODIS and ASTER emissivity products over the Namib and Kalahari deserts in Southern Africa. The Namib, Africa's second largest desert, and the Kalahari cover areas of 80,900 and 900, 000 km² respectively and consist of pure quartz, giving the sand a deep red color. The dunes provide excellent areas for validation as they have little or no vegetation, are spatially homogeneous with known composition, and have large spectral variations in TIR emissivity. MODIS and ASTER data will be upsampled to the AIRS spatial resolution, and then compared to the emissivities of in-situ sand samples collected at designated areas at Sossusvlei in the Namib dunes and Kgalagadi Transfrontier Park in the Kalahari. The directional hemispherical reflectance of the in-situ samples are measured in the lab using a Nicolet Fourier Transform Interferometer (FTIR), converted to emissivity using Kirchoff's law, and convolving to the appropriate sensor's spectral response functions. We present here some of the first quantitative results on the discrepancies between emissivity products from different sensors as a result of differences in spatial, spectral and temporal resolutions, and furthermore, comparisons with in-situ data will give a measure of the relative accuracy of the emissivity products - a critical aspect for the broad scientific community in deriving accurate land surface temperatures.
A53F-0333
Spatial and Temporal Inter-Relationships Between Anomalies and Trends of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua
AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, fractional cloud cover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2002- August 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extra-tropical land surface skin temperatures, as well as pronounced El Nino – La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to validate the anomalies and trends of temperature profiles, cloud cover, and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 year period shown are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.
A53F-0334
Validation of Observed and Computed Clear Sky OLR using CERES and AIRS
For almost 50 years now, accurate, long term records of solar insolation, planetary albedo, and OLR have been collected to monitor climate change. We focused on comparing two methods of determining clear sky OLR. Clear sky OLR computed using the AER Inc.'s radiative transfer model and retrievals from AIRS shows excellent agreement with co-located CERES clear sky OLR observations. Calculations at the Department of Energy's Atmospheric Radiation Measurement (ARM) Program site in the U.S. Southern Great Plains (SGP) between September 2002 and February 2005 with both in-situ measurements and retrievals from AIRS agree with CERES observations to ~1 W/m2 with an uncertainty in the mean of ~1 W/m2. The AIRS retrieval based RRTM calculation comparisons to CERES OLR is extended to global coverage for four days of coincident measurements. Results are given by surfaces defined by the International Geosphere-Biosphere Programme (IGBP). Excluding observed discrepancies in daytime and high latitude surfaces, the globally averaged bias is ~1 W/m2 with an uncertainty in the mean ~0.4 W/m2.
A53F-0335
Retrieval of high spatial resolution soundings from hyperspectral infrared sounder measurements
Hyperspectral infrared (IR) sounders such as Atmospheric InfraRed Sounder (AIRS) onboard the NASA's Earth Observing System (EOS) Aqua platform and Infrared Atmospheric Sounding Interferometer (IASI) onboard the Europe's Metop-A satellite, provide unique capability of deriving global atmospheric temperature and moisture profiles with high vertical resolution and accuracy. The high spatial resolution soundings are needed for mesoscale forecast and other applications. Algorithms have been developed for single field-of- view (FOV) temperature and moisture profile retrievals from advanced IR sounders. Handling surface IR emissivities and clouds in the sounding retrieval process is essential. High spatial resolution soundings from AIRS have been evaluated with regional Weather and Research Forecasting (WRF) Model assimilation system. In addition, global surface IR emissivity spectra from AIRS have been developed for various applications (land surface temperature, trace gas, radiance assimilation over land, climate study etc.). Furthermore the results are systematically analyzed to evaluate data processing and retrieval algorithms for future hyperspectral infrared instruments, in particular the Cross-track Infrared Sounder (CrIS) on NPOESS satellites.
A53F-0336
Improved Spatial Distribution and Trends of Clouds Observed with the Atmospheric Infrared Sounder
Clouds are an important component of the Earth's radiation budget. Depending on their height and type they can either cool or warm the Earth's surface and atmosphere. Therefore it is important to have an accurate determination of cloud properties and where they are located to understand how Earth's climate is changing. The CO2 climatology used in the AIRS Version 5 retrieval algorithm assumes the CO2 abundance increases linearly with time but it neglects seasonal and spatial variations. Although a simple linearly varying CO2 climatology can remove spurious year-to-year trends it can cause spurious seasonal and spatial variations. We show that an improved CO2 climatology improves the retrieved AIRS cloud height and fraction. We also estimate the uncertainty in the AIRS Version 5 cloud parameters due to the simple CO2 climatology.
A53F-0337
AIRS Data Service at NASA Goddard Earth Sciences Data and Information Services (GES DISC) and Its Application to Climate Change Study
The Atmospheric Infrared Sounder (AIRS) instrument suite is designed to observe and characterize the entire
atmospheric column from the surface to the top of the atmosphere in terms of surface emissivity and
temperature, atmospheric temperature and humidity profiles, cloud amount and height, and the spectral
outgoing infrared radiation on a global scale. It is comprised of a space-based hyperspectral infrared
instrument (AIRS) and two multichannel microwave instruments, the Advanced Microwave Sounding Unit
(AMSU-A) and the Humidity Sounder for Brazil (HSB). The AIRS instrument suite is one of several instruments
onboard the Earth Observing System (EOS) Aqua spacecraft launched May 4, 2002 and has been providing
global coverage ever since. A six-year record of these data are available from the GES DISC.
The AIRS Data Support Team at the GES DISC provides data support to assist others in understanding,
retrieving, and extracting information from the AIRS/AMSU/HSB data products. Various AIRS data products
(Level-1B, Level-2 and Level-3) are available from the GES DISC. In addition, the GES DISC provides a
range of value added services such as data search and access services, subsetting and format conversion
services, online data visualization and analysis services.
Because number of years has passed since its operation started, the amount of data has reached a certain
level of maturity where we can address the climate change study utilizing the AIRS data. In this presentation,
we would like to list various services we provide and to demonstrate how to utilize/apply the existing service to
long-term and short term variability study.
http://disc.gsfc.nasa.gov/AIRS/
A53F-0338
Land Surface Emissivity Comparisons for IASI Window Channels in the NCEP Global Data Assimilation System
The land surface emissivity for the Infrared Atmospheric Sounding Interferometer (IASI) is computed using the IR emissivity data base in Community Radiative Transfer Model (CRTM) and the Naval Research Laboratory (NRL) index emissivity model. However, for IASI window channels, the observations under clear conditions can be also used to retrieve the surface emissivity directly since the needed correction for atmospheric absorption is minimal and can be done fairly accurate using the atmospheric profiles from the National Centers for Environmental Prediction (NCEP) global data assimilation (GDAS) and forecast system (GFS). This retrieval is used as "truth". Our studies characterize the root mean square errors and standard deviation errors from two methods according to surface types in GFS land surface model. It is found that larger emissivity differences are found over desert for 8.3-9.2µm. Also, the simulated brightness temperatures are shown the larger uncertainty from the two emissivity methods.
A53F-0339
Hyperspectral Radiance Time-Series from AIRS for Climate Observations
The AIRS hyperspectral sensor on the EOS-Aqua platform has been operating for more than 6 years, giving us the first long-term hyperspectral infrared time-series. This time series will be continued for 15+ years by the IASI sensor on METOP and CrIS on NPP/NPOESS. Given the extremely high stability of the AIRS sensor, very small changes in the earth's outgoing radiation can be detected that are hard to track via complicated ill-posed inverse retrieval schemes. We examine the AIRS hyperspectral time series for clear scenes over ocean, which has signal-to-noises of well below 0.01K/year. Most easily distinguished in the tropics are changes in carbon-dioxide forcing in the mid-troposphere, along with temperature changes in the upper troposphere and stratosphere in the higher latitudes. Progress in the cross-validation of AIRS with IASI required to extend this series will also be discussed.
A53F-0340
Assimilation of High Peaking AIRS Channels in 15micron CO2 Band Using GEOS-5 and Validation
The use of AIRS channels peaking in upper stratosphere with their tails of weighting function extended to Mesosphere were prohibited in NASA's global data assimilation system, GOES-5, due to large biases in the background temperatures. These biases are evident in the residual statistics (differences between observed and simulated brightness temperatures from background) for the high peaking channels in 15-micron CO2 band. The comparison of GEOS-5 temperatures with those retrieved from AURA MLS instrument also confirmed these biases. The data assimilation is challenging at locations where observations are sparse, and background biases are large. The challenging is further enhanced by bias correction for observations. The GEOS-5 uses variational bias correction for radiance observations. The advantages of this method are that it's adaptive, bias estimates are updated for every analysis cycle and consistent with all components in the analysis. The disadvantages are that it does not work well at locations where observations are sparse, and it is prone to include systematic errors of the NWP models into the analysis through bias correction. To avoid aliasing background biases into the analysis, the bias correction for these high peaking channels were turn off in GEOS-5. The comparison of the assimilation results with the bias correction turned on and off for these high peaking channels will be presented. The advantages of assimilating these channels with bias correction turned off will be demonstrated by using other independent data sets such as AURA MLS, and GPS RO data.
A53F-0341
Analysis of Co-located Ground- and Space-based Infrared Atmospheric Measurements: AERI, AIRS, CERES, MODIS
Sets of clear-sky, co-located, down-looking infrared data, from the NASA AQUA space-based Atmospheric Infrared Sounder (AIRS) and the Clouds and the Earth's Radiant Energy System (CERES), have been paired with the DOE Southern Great Plains (SGP) ground-based, up-looking Atmospheric Emitted Radiance Interferometer (AERI). Only 26 cases are included in this study, the 8% of the available 2005 AIRS acquisitions at SGP that were defined as cloud free. These data sets have then been simulated using the MODTRAN® 5 (MOD5) radiative transfer code with auxiliary 'truth' data as input. Since MOD5 is unaffiliated with any of the instruments, its use as a transfer agent among the instrument suites provides important algorithm validation. Of particular interest is the impact, if any, of the Ground Sampling Distance (GSD) of AIRS, CERES and MODIS (13, 26 and 0.5 km, respectively) vs. the soda-straw up-looking mode of AERI. The sensitivity of the larger GSDs on measurements of outgoing long wave radiation (OLR) is an important question for next-stage climate monitoring. In addition to the coincident SGP 'ground truth' data (vertical profile sondes and AERONET measurements) and MODIS products, the AURA Ozone Monitoring Instrument (OMI) has also augmented the available 'truth' input parameters. Initial calculations with MOD5 have replicated both the AERI and AIRS measurements to within 1% RMS. Preliminary calculations of the CERES long wave radiances suggest that differences will fall well within 3%. While these results are not sufficiently precise for specific instrument algorithms, they suggest some confidence in the generic use of MODTRAN® 5 as an integration tool for Climate Change studies.
A53F-0342
Surface-based trace gas retrievals at Dome C, Antarctica, in validation of AIRS
Total column amounts of CO and HNO3 are retrieved from 19 surface-based measurements of downwelling infrared radiance at Dome C, Antarctica. The measurements were made in clear skies with the Polar Atmospheric Emitted Radiance Interferometer (PAERI) in December 2003 and January 2004. In addition, sensitivity studies for retrievals of other trace gases were performed. The CO amounts are used to validate retrievals derived from data taken by the Atmospheric Infrared Sounder (AIRS). Surface measurements of CO and CH4 made at South Pole station are compared to both retrievals. The retrieved CO amounts (averaging 4.5 x 1017 molecule/cm2) are found to be approximately half those of AIRS and about 20% larger than those measured at South Pole. The retrieved HNO3 total column amounts range from 1.3 to 1.9 x 1016 molecule/cm2; the mean surface estimate is 139 pptv. The sensitivity studies suggest that retrievals of CH4 and N2O amounts are possible from PAERI spectra, and that upper limits can be set for SO2, NH3, and NO2 amounts. These comparisons will help improve satellite -based retrievals of trace gases over polar ice sheets using infrared spectra.