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At least 19 records

AIRS-Only Product in Giovanni for Exploring Up-to-Date AIRS Observation and Comparing with AIRS+AMSU Product

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of processing, archiving, and distribution services for the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002 for global observations of the atmospheric state. Giovanni, a Web-based application developed by the GES DISC, provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Most important AIRS variables, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases, are available in Giovanni. AIRS is an instrument suite comprised of a hyperspectral infrared instrument (AIRS) and two multichannel microwave instruments, the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB). As HSB ceased operation in the very early stages of the AIRS mission, the AIRS project operates two parallel retrieval algorithms: one using both IR and MW measurements (AIRS+AMSU) and the other using only IR measurements (AIRS-only), which covers most of the mission duration. The AIRS+AMSU product is better quality, and the variables in Giovanni are from this product. However, generation of the AIRS+AMSU product has been suspended since the AMSU instrument anomaly occurred in late September 2016. To continue exploring up-to-date AIRS observations, the same set of variables from the AIRS-only product have been added to Giovanni by the GES DSIC. This will also support comparison of AIRS-only with AIRS+AMSU retrievals. In this presentation, we demonstrate the visualization of the AIRS-only product and plots/statistics of comparison with AIRS+AMSU product using Giovanni.

AIRS↗

Infrared remote sensing in the presence of clouds with AIRS-AMSU-HSB

The Atmospheric Infrared Sounder (AIRS) and its two companion instruments (AMSU) and (HSB) are designed to provide atmospheric temperature and humidity profiles with radiosonde accuracty. The performance of AIRS since launch on Aqua has been exceptional indicating that it will meet or exceed its objectives.

AIRS EOS spectrometers infrared temperature sounde↗

Comparative Results of AIRS AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

The AIRS Science Team Version 6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRSAMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrISATMS is the only scheduled follow on to AIRSAMSU. The objective of this research is to prepare for generation of a long term CrISATMS level-3 data using a finalized retrieval algorithm that is scientifically equivalent to AIRSAMSU Version-7.

AIRS↗

Analysis of CrIS ATMS and AIRS AMSU Data Using Scientifically Equivalent Retrieval Algorithms

Monthly mean August 2014 Version-6.28 AIRS and CrIS products agree well with OMPS and CERES, and reasonably well with each other. Version-6.28 CrIS total precipitable water is biased dry compared to AIRS. AIRS and CrIS Version-6.36 water vapor products are both improved compared to Version-6.28. Version-6.36 AIRS and CrIS total precipitable water also shows improved agreement with each other. AIRS Version-6.36 total ozone agrees even better with OMPS than does AIRS Version-6.28, and gives reasonable results during polar winter where OMPS does not generate products. CrIS and ATMS are high spectral resolution IR and Microwave atmospheric sounders currently flying on the SNPP satellite, and are also scheduled for flight on future NPOESS satellites. CrIS/ATMS have similar sounding capabilities to those of the AIRS/AMSU sounder suite flying on EOS Aqua. The objective of this research is to develop and implement scientifically equivalent AIRS/AMSU and CrIS/ATMS retrieval algorithms with the goal of generating a continuous data record of AIRS/AMSU and CrIS/ATMS level-3 data products with a seamless transition between them in time. To achieve this, monthly mean AIRS/AMSU and CrIS/ATMS retrieved products, and more importantly their interannual differences, should show excellent agreement with each other. The currently operational AIRS Science Team Version-6 retrieval algorithm has generated 14 years of level-3 data products. A scientifically improved AIRS Version-7 retrieval algorithm is expected to become operational in 2017. We see significant improvements in water vapor and ozone in Version-7 retrieval methodology compared to Version-6.We are working toward finalization and implementation of scientifically equivalent AIRS/AMSU and CrIS/ATMS Version-7 retrieval algorithms to be used for the eventual processing of all AIRS/AMSU and CrIS/ATMS data. The latest version of our retrieval algorithm is Verison-6.36, which includes almost all the improvements we want in Version-7. Version-6.28 has been used to process both AIRS and CrIS data for August 2014. This poster compares August 2014 monthly mean Version-6.28 AIRS/AMSU and CrIS/ATMS products with each other, and also with monthly mean products obtained using AIRS Version-6. AIRS and CrIS results using Version-6.36 are presented for April 15, 2016. These demonstrate further improvements since Version-6.28. The new results also show improved agreement of Version-6.36 AIRS and CrIS products with each other. Version-6.36 is not yet optimized for CrIS ozone products.

AIRS↗

Estimating Sampling Biases and Measurement Uncertainties of AIRS-AMSU-A Temperature and Water Vapor Observations Using MERRA Reanalysis

We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be +/- 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and greater than 30% dry over mid-latitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.

MERRA↗

Team 2: AIRS Only Retrieval

This slide presentation makes the case for the retrieval of data from the Atmospheric Infrared Sounder (AIRS) Advanced Microwave Sounding Unit (AMSU). AIRS only retrieval is not only a risk reduction for failure of AMSU, but also important because NWP centers are reluctant to assimilate AMSU twice.

cloudy regression↗

Expanding NASA's Land, Atmosphere Near Real-Time Capability for EOS (LANCE)

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) is a virtual system that provides near real-time EOS data and imagery to meet the needs of scientists and application users interested in monitoring a wide variety of natural and man-made phenomena in near real-time. Over the last year: near real-time data and imagery from MOPITT, MISR, OMPS and VIIRS (Land and Atmosphere), the Fire Information for Resource Management System (FIRMS) has been updated and LANCE has begun the process of integrating the Global NRT flood, and Black Marble products. In addition, following the AMSU-A2 instrument anomaly in September 2016, AIRS-only products have replaced the NRT level 2 AIRS+AMSU products. This presentation provides a brief overview of LANCE, describes the new products that are recently available and contains a preview of what to expect in LANCE over the coming year.

NASA Lance↗

Analysis of CrIS-ATMS Data Using an AIRS Science Team Version 6 - Like Retrieval Algorithm

CrIS/ATMS is flying on NPP and is scheduled to fly on JPSS-1. CrIS/ATMS has roughly equivalent capabilities to AIRS/AMSU. The AIRS Science Team Version 6 retrieval algorithm is currently producing very high quality level-3 Climate Data Records (CDR's) that will be critical for understanding climate processes AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS AMSU. I have been asked by Ramesh Kakar if CrIS/ATMS can be counted on to adequately continue the AIRS/AMSU CDRs beyond 2020, or is something better needed? This research is being done to answer that question. A minimum requirement to obtain a yes answer is that CrIS/ATMS be analyzed using an AIRS Version 6 - like algorithm. NOAA is currently generating CrIS/ATMS products using 2 algorithms: IDPS and NUCAPS

Retrieval Algorithm↗

Note on the Effect of Horizontal Gradients for Nadir-Viewing Microwave and Infrared Sounders

Passive microwave and infrared nadir sounders such as the Advanced Microwave Sounding Unit A (AMSU-A) and the Atmospheric InfraRed Sounder (AIRS), both flying on NASA s EOS Aqua satellite, provide information about vertical temperature and humidity structure that is used in data assimilation systems for numerical weather prediction and climate applications. These instruments scan cross track so that at the satellite swath edges, the satellite zenith angles can reach approx. 60 deg. The emission path through the atmosphere as observed by the satellite is therefore slanted with respect to the satellite footprint s zenith. Although radiative transfer codes currently in use at operational centers use the appropriate satellite zenith angle to compute brightness temperature, the input atmospheric fields are those from the vertical profile above the center of the satellite footprint. If horizontal gradients are present in the atmospheric fields, the use of a vertical atmospheric profile may produce an error. This note attempts to quantify the effects of horizontal gradients on AIRS and AMSU-A channels by computing brightness temperatures with accurate slanted atmospheric profiles. We use slanted temperature, water vapor, and ozone fields from data assimilation systems. We compare the calculated slanted and vertical brightness temperatures with AIRS and AMSU-A observations. We show that the effects of horizontal gradients on these sounders are generally small and below instrument noise. However, there are cases where the effects are greater than the instrument noise and may produce erroneous increments in an assimilation system. The majority of the affected channels have weighting functions that peak in the upper troposphere (water vapor sensitive channels) and above (temperature sensitive channels) and are unlikely t o significantly impact tropospheric numerical weather prediction. However, the errors could be significant for other applications such as stratospheric analysis. Gradients in ozone and tropospheric temperature appear to be well captured by the analyses. In contrast, gradients in upper stratospheric and mesospheric temperature as well as upper tropospheric humidity are less well captured. This is likely due in part to a lack of data to specify these fields accurately in the analyses. Advanced new sounders, like AIRS, may help to better specify these fields in the future.

Joiner, J.↗

An Anomaly Correlation Skill Score for the Evaluation of the Performance of Hyperspectral Infrared Sounders

With the availability of very accurate forecasts, the metric of accuracy alone for the evaluation of the performance of a retrieval system can produce misleading results. A useful characterization of the quality of a retrieval system and its potential to contribute to an improved weather forecast is its skill, which we define as the ability to make retrievals of geophysical parameters which are closer to the truth than the six hour forecast, when the truth differs significantly from the forecast. We illustrate retrieval skill using one day of AMSU and AIRS data with three different retrieval algorithms, which result in retrievals for more than 90% of the potential retrievals under clear and cloudy conditions. Two of the three algorithms have better than 1 K rms "RAOB quality" accuracy on the troposphere, but only one has skill between 900 and 100 mb. AIRS was launched on the EOS Aqua spacecraft in May 2002 into a 705 km polar sun-synchronous orbit with accurately maintained 1:30 PM ascending node. Essentially uninterrupted data are freely available since September 2002.

retrieval↗

Results from CrIS/ATMS Obtained Using an "AIRS Version-6 Like" Retrieval Algorithm

AIRS and CrIS Version-6.22 O3(p) and q(p) products are both superior to those of AIRS Version-6.Monthly mean August 2014 Version-6.22 AIRS and CrIS products agree reasonably well with OMPS, CERES, and witheach other. JPL plans to process AIRS and CrIS for many months and compare interannual differences. Updates to thecalibration of both CrIS and ATMS are still being finalized. We are also working with JPL to develop a joint AIRS/CrISlevel-1 to level-3 processing system using a still to be finalized Version-7 retrieval algorithm. The NASA Goddard DISCwill eventually use this system to reprocess all AIRS and recalibrated CrIS/ATMS. .

CrIS ATMS↗

Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

AIRS AMSU↗

Using Microwave and Infrared Radiances from Off-Nadir Pixels: Application of Radiative Transfer to Slanted Line-of-Sight and Comparisons with NASA EOS Aqua Data

The passive infrared and microwave nadir sounders such as (A)TOVS observe the atmosphere from a polar orbit by directing their scan pointed at the ground up to about 49 degrees from nadir. Except for the pixels located right on the satellite ground track, the radiance measurements collected by these instruments characterize hence atmospheric emission paths which are slanted with respect to the zenithal direction at the ground. At the outer swath edges, the deviations from nadir reach about 60 degrees in terms of Satellite Zenith Angle (SZA). The radiative transfer codes used in operational Numerical Weather Prediction applications make the appropriate corrections to account for the extra path induced by the non-zero SZA. However, no corrections are made to account for the fact that the atmospheric profiles along the slanted line-of-sight (LOS) are different from the vertical because of horizontal gradients in the atmosphere. Using NASA EOS Aqua satellite's orbits, zenith and azimuth angles, as well as three-dimensional fields of temperature, water vapor, and ozone produced by the NASA Global Modeling and Assimilation Office, we extracted slanted atmospheric profiles for actual soundings performed by the AIRS and AMSU-A instruments onboard EOS Aqua. We will present the results of our study comparing the calculated brightness temperatures along slanted LOS and vertical LOS with AIRS and AMSU-A observations.

Poli, Paul↗