Retrieved Products from Simulated Hyperspectral Observations of a Hurricane

Retrievals were run using the AIRS Science Team Version-6 AIRS Only retrieval algorithm, which generates a Neural-Net first guess (T(sub s))(sup 0), (T(p))(sup 0), and (q(p))(sup 0) as a function of observed AIRS radiances. AIRS Science Team Neural-Net coefficients performed very well beneath 300 mb using the simulated radiances. This means the simulated radiances are very realistic. First guess and retrieved values of T(p) above 300 mb were biased cold, but both represented the model spatial structure very well. QC'd T(p) and q(p) retrievals for all experiments had similar accuracies compared to their own truth fields, and were roughly consistent with results obtained using real data. Spatial coverage of retrievals, as well as the representativeness of the spatial structure of the storm, improved dramatically with decreasing size of the instrument's FOV. We sent QC'd values of T(p) and q(p) to Bob Atlas at AOML for use as input to OSSE Data Assimilation experiments

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.

SRT Status and Plans for Version-7

The AIRS Science Team Version-6 retrieval algorithm is currently producing level-3 Climate Data Records (CDRs) from AIRS that have been proven useful to scientists in understanding climate processes. CDRs are gridded level-3 products which include all cases passing AIRS Climate QC. SRT has made significant further improvements to AIRS Version-6. Research is continuing at SRT toward the development of AIRS Version-7. At the last Science Team Meeting, we described results using SRT AIRS Version-6.19. SRT Version-6.19 is now an official build at JPL called 6.2. SRTs latest version is AIRS Version-6.22. We have also adapted AIRS Version-6.22 to run with CrISATMS. AIRS Version-6.22 and CrIS Version- 6.22 both run now on JPL computers, but are not yet official builds. The main reason for finalization of Version-7, and using it in the relatively near future for the future processing and reprocessing of old AIRS data, is to produce even better CDRs for use by climate scientists. For this reason all results shown in this talk use only AIRS Climate QC

Preliminary Assessment of the Accuracy of CrIS/ATMS Retrievals Generated at SRT Using an AIRS "Version-6-like" Retrieval Algorithm

No abstract availabl

The "Palliative Care Quality of Life Instrument (PQLI)" in terminal cancer patients

BACKGROUND: This paper describes the development of a new quality of life instrument in advanced cancer patients receiving palliative care. METHODS: The Palliative Care Quality of Life Instrument incorporates six multi-item and one single-item scale. The questionnaire was completed at baseline and one-week after. The final sample consisted of 120 patients. RESULTS: The average time required to complete the questionnaire, in both time points, was approximately 8 minutes. All multi-item scales met the minimal standards for reliability (Cronbach's alpha coefficient ≥.70) either before or during palliative treatment. Test-retest reliability in terms of Spearman-rho coefficient was also satisfactory (p < 0.05). Validity was demonstrated by inter-item correlations, comparisons with ECOG performance status, factor analysis, criterion-related validation, and correlations with the Assessment of Quality of Life in Palliative Care Instrument (AQEL), and the European Organisation for Research and Treatment of Cancer (EORTC) Core Quality of Life Questionnaire (QLQ-C30, version 3.0). CONCLUSION: The PQLI is a reliable and valid measure for the assessment of quality of life in patients with advanced stage cancer

Retrieved Products from Simulated Hyperspectral Observations of a Hurricane

This research uses GCM derived products, with 1 km spatial resolution and sampled every 10 minutes, over a moving area following the track of a simulated severe Atlantic storm. Model products were aggregated over sounder footprints corresponding to 13 km in LEO, 2 km in LEO, and 5 km in GEO sampled every 72 minutes. We simulated radiances for instruments with AIRS-like spectral coverage, spectral resolution, and channel noise, using these aggregated products as the truth, and analyzed them using a slightly modified version of the operational AIRS Version-6 retrieval algorithm. Accuracy of retrievals obtained using simulated AIRS radiances with a 13 km footprint was similar to that obtained using real AIRS data. Spatial coverage and accuracy of retrievals are shown for all three sounding scenarios. The research demonstrates the potential significance of flying Advanced AIRS-like instruments on future LEO and GEO missions

Progress Towards AIRS Science Team Version-7 at SRT

The AIRS Science Team Version-6 retrieval algorithm is currently producing level-3 Climate Data Records (CDRs) from AIRS that have been proven useful to scientists in understanding climate processes. CDRs are gridded level-3 products which include all cases passing AIRS Climate QC. SRT has made significant further improvements to AIRS Version-6. At the last Science Team Meeting, we described results using SRT AIRS Version-6.22. SRT Version-6.22 is now an official build at JPL called 6.2.4. Version-6.22 results are significantly improved compared to Version-6, especially with regard to water vapor and ozone profiles. We have adapted AIRS Version-6.22 to run with CrIS/ATMS, at the Sounder SIPS which processed CrIS/ATMS data for August 2014. JPL AIRS Version-6.22 uses the Version-6 AIRS tuning coefficients. AIRS Version-6.22 has at least two limitations which must be improved before finalization of Version-7: Version-6.22 total O3 has spurious high values in the presence of Saharan dust over the ocean; and Version-6.22 retrieved upper stratospheric temperatures are very poor in polar winter. SRT Version-6.28 addresses the first concern. John Blaisdell ran the analog of AIRS Version-6.28 in his own sandbox at JPL for the 14th and 15th of every month in 2014 and all of July and October for 2014. AIRS Version-6.28a is hot off the presses and addresses the second concern

Accuracy of Geophysical Parameters Derived from AIRS/AMSU as a Function of Fractional Cloud Cover

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. HSB failed in February 2005, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC in April 2005 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm

CrIS - ATMS Retrievals Using an AIRS Science Team Version 6-Like Retrieval Algorithm

No abstract availabl