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Iredell, Lena

Publications and source records attributed to Iredell, Lena.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

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

We tested and evaluated Version-6.22 AIRS and Version-6.22 CrIS products on a single day, December 4, 2013, and compared results to those derived using AIRS Version-6. AIRS and CrIS Version-6.22 O3(p) and q(p) products are both superior to those of AIRS Version-6All AIRS and CrIS products agree reasonably well with each other. CrIS Version-6.22 T(p) and q(p) results are slightly poorer than AIRS over land, especially under very cloudy conditions. Both AIRS and CrIS Version-6.22 run now at JPL. Our short term plans are to analyze many common months at JPL in the near future using Version-6.22 or a further improved algorithm to assess the compatibility of AIRS and CrIS monthly mean products and their interannual differences. Updates to the calibration of both CrIS and ATMS are still being finalized. JPL plans, in collaboration with the Goddard DISC, to reprocess all AIRS data using a still to be finalized Version-7 retrieval algorithm, and to reprocess all recalibrated CrISATMS data using Version-7 as well.

CrIS ATMS↗
NASA NTRS2015

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.

CrIS ATMS↗
NASA NTRS2015

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

We have tested and evaluated Version-6.22 AIRS and Version-6.22 CrIS products on a single day, December 4, 2013, and compared results to those derived using AIRS Version-6. AIRS and CrIS Version-6.22 O3(p) and q(p) products are both superior to those of AIRS Version-6All AIRS and CrIS products agree reasonably well with each other CrIS Version-6.22 T(p) and q(p) results are slightly poorer than AIRS under very cloudy conditions. Both AIRS and CrIS Version-6.22 run now at JPL. Our short term plans are to analyze many common months at JPL in the near future using Version-6.22 or a further improved algorithm to assess the compatibility of AIRS and CrIS monthly mean products and their interannual differencesUpdates to the calibration of both CrIS and ATMS are still being finalized. JPL plans, in collaboration with the Goddard DISC, to reprocess all AIRS data using a still to be finalized Version-7 retrieval algorithm, and to reprocess all recalibrated CrISATMS data using Version-7 as well.

AIRS↗
NASA NTRS2015

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.

AIRS↗
NASA NTRS2015

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

A main objective of AIRS/AMSU on EOS is to provide accurate sounding products that are used to generate climate data sets. Suomi NPP carries CrIS/ATMS that were designed as follow-ons to AIRS/AMSU. Our objective is to generate a long term climate data set of products derived from CrIS/ATMS to serve as a continuation of the AIRS/AMSU products. We have modified an improved version of the operational AIRS Version-6 retrieval algorithm for use with CrIS/ATMS. CrIS/ATMS products are of very good quality, and are comparable to, and consistent with, those of AIRS.

Retrieval methodology↗
NASA NTRS2015

Diurnal Differences in OLR Climatologies and Anomaly Time Series

AIRS (Atmospheric Infrared Sounder) Version-6 OLR (Outgoing Long-Wave Radiation) matches CERES (Clouds and the Earth's Radiant Energy System) Edition-2.8 OLR very closely on a 1x1 latitude x longitude scale, both with regard to absolute values, and also with regard to anomalies of OLR. There is a bias of 3.5 watts per meter squared, which is nearly constant both in time and space. Contiguous areas contain large positive or negative OLR difference between AIRS and CERES are where the day-night difference of OLR is large. For AIRS, the larger the diurnal cycle, the more likely that sampling twice a day is inadequate. Lower values of OLRclr (Clear Sky OLR) and LWCRF (Longwave Cloud Radiative Forcing) in AIRS compared to CERES is at least in part a result of AIRS sampling over cold and cloudy cases.

Anomaly Time Series↗
NASA NTRS2015

Major Upgrades to the AIRS Version-6 Water Vapor Profile Methodology

Additional changes in Version-6.19 include all previous updates made to the q(p) retrieval since Version-6: Modified Neural-Net q0(p) guess above the tropopause Linearly tapers the neural net guess to match climatology at 70 mb, not at the top of the atmosphereChanged the 11 trapezoid q(p) perturbation functions used in Version-6 so as to match the 24 functions used in T(p) retrieval step. These modifications resulted in improved water vapor profiles in Version-6.19 compared to Version-6.Version-6.19 is tested for all of August 2013 and August 2014, as well for select other days. Before finalized and operational in 2016, the V-6.19 can be acquired upon request for limited time intervals.

Water Vapor Profile Methodology↗
NASA NTRS2015

CrIS/ATMS Retrievals Using the Latest AIRS/AMSU Retrieval Methodology

This research is being done under the NPP Science Team Proposal: Analysis of CrISATMS Using an AIRS Version 6-like Retrieval Algorithm Objective: Generate a long term CrISATMS level-3 data set that is consistent with that of AIRSAMSU Approach: Adapt the currently operational AIRS Science Team Version-6 Retrieval Algorithm, or an improved version of it, for use with CrISATMS data. Metric: Generate monthly mean level-3 CrISATMS climate data sets and evaluate the results by comparison of monthly mean AIRSAMSU and CrISATMS products, and more significantly, their inter-annual differences and, eventually, anomaly time series. The goal is consistency between the AIRSAMSU and CrISATMS climate data sets.

Retrieval Methodology↗
NASA NTRS2015

Major Upgrades to the AIRS Version-6 Ozone Profile Methodology

This research is a continuation of part of what was shown at the last AIRS Science Team Meeting in the talk Improved Water Vapor and Ozone Profiles in SRT AIRS Version-6.X and the AIRS February 11, 2015 NetMeeting Further improvements in water vapor and ozone profiles compared to Version-6.AIRS Version-6 was finalized in late 2012 and is now operational. Version-6 contained many significant improvements in retrieval methodology compared to Version-5. However, Version-6 retrieval methodology used for the water vapor profile q(p) and ozone profile O3(p) retrievals is basically unchanged from Version-5, or even from Version-4. Subsequent research has made significant improvements in both water vapor and O3 profiles compared to Version-6. This talk will concentrate on O3 profile retrievals. Improvements in water vapor profile retrievals are given in a separate presentation.

Ozone↗
NASA NTRS2015

Major Upgrades to the AIRS Version-6 Water Vapor Profile Methodology

This research is a continuation of part of what was shown at the last AIRS Science Team Meeting and the AIRS 2015 NetMeeting. AIRS Version 6 was finalized in late 2012 and is now operational. Version 6 contained many significant improvements in retrieval methodology compared to Version 5. Version 6 retrieval methodology used for the water vapor profile q(p) and ozone profile O3(p) retrievals is basically unchanged from Version 5, or even from Version 4. Subsequent research has made significant improvements in both water vapor and O3 profiles compared to Version 6.

Version-6↗
NASA NTRS2014

Spatial Correlations of Anomalies of Tropospheric Temperature and Water Vapor, Cloud Cover, and OLR with the El Nino Index

In this presentation, we will show AIRS Version-6 area weighted anomaly time series over the time period September 2002 through August 2014 of atmospheric temperature and water vapor profiles as a function of height. These anomaly time series show very different behaviors in the stratosphere and in the troposphere. Tropical mean stratospheric temperature anomaly time series are very strongly influenced by the Quasi-Biennial Oscillation (QBO) with large anomalies that propagate downward from 1 mb to 100 mb with a period of about two years. AIRS stratospheric temperature anomalies are in good agreement with those obtained by MLS over a common period. Tropical mean tropospheric temperature profile anomalies appear to be totally disconnected from those of the stratosphere and closely follow El Nino La Nina activity.

Version-6↗
NASA NTRS2014

Global Distribution and Variability of Surface Skin and Surface Air Temperatures as Depicted in the AIRS Version-6 Data Set

In this presentation, we will briefly describe the significant improvements made in the AIRS Version-6 retrieval algorithm, especially as to how they affect retrieved surface skin and surface air temperatures. The global distribution of seasonal 1:30 AM and 1:30 PM local time 12 year climatologies of Ts,a will be presented for the first time. We will also present the spatial distribution of short term 12 year anomaly trends of Ts,a at 1:30 AM and 1:30 PM, as well as the spatial distribution of temporal correlations of Ts,a with the El Nino Index. It will be shown that there are significant differences between the behavior of 1:30 AM and 1:30 PM Ts,a anomalies in some arid land areas.

Retrieval algorithm↗
NASA NTRS2014

Cris-atms Retrievals Using an AIRS Science Team Version 6-like Retrieval Algorithm

CrIS is the infrared high spectral resolution atmospheric sounder launched on Suomi-NPP in 2011. CrISATMS comprise the IRMW Sounding Suite on Suomi-NPP. CrIS is functionally equivalent to AIRS, the high spectral resolution IR sounder launched on EOS Aqua in 2002 and ATMS is functionally equivalent to AMSU on EOS Aqua. CrIS is an interferometer and AIRS is a grating spectrometer. Spectral coverage, spectral resolution, and channel noise of CrIS is similar to AIRS. CrIS spectral sampling is roughly twice as coarse as AIRSAIRS has 2378 channels between 650 cm-1 and 2665 cm-1. CrIS has 1305 channels between 650 cm-1 and 2550 cm-1. Spatial resolution of CrIS is comparable to AIRS.

AIRS↗
NASA NTRS2014

Improved Methodology for Surface and Atmospheric Soundings, Error Estimates, and Quality Control Procedures: the AIRS Science Team Version-6 Retrieval Algorithm

The AIRS Science Team Version-6 AIRS/AMSU retrieval algorithm is now operational at the Goddard DISC. AIRS Version-6 level-2 products are generated near real-time at the Goddard DISC and all level-2 and level-3 products are available starting from September 2002. This paper describes some of the significant improvements in retrieval methodology contained in the Version-6 retrieval algorithm compared to that previously used in Version-5. In particular, the AIRS Science Team made major improvements with regard to the algorithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the cloud clearing and retrieval procedures; and 3) derive error estimates and use them for Quality Control. Significant improvements have also been made in the generation of cloud parameters. In addition to the basic AIRS/AMSU mode, Version-6 also operates in an AIRS Only (AO) mode which produces results almost as good as those of the full AIRS/AMSU mode. This paper also demonstrates the improvements of some AIRS Version-6 and Version-6 AO products compared to those obtained using Version-5.

Quality Control↗