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NASA NTRS1999

Impact of a Merged Precipitation Data on Global Soil Moisture Variability

Accurate soil moisture information has proved to be important to climate simulations and climate and weather forecasts. However, many difficulties exist that limit our understanding of soil moisture distribution and variability. One of them is the lack of accurate precipitation with appropriate spatial and temporal resolution. Precipitation as an input forcing to the land surface greatly influences soil moisture characteristics and variability. To improve precipitation data quality, an algorithm has been developed to generate a spatially and temporally continuous 3-hourly global precipitation data for the period of 1987 to present. This precipitation product is a combination of the precipitation from Special Sensor Microwave Imager (SSMI) with the Goddard Earth Observing System-1 Data Assimilation System (GEOS-1 DAS) employing a Physical-space Statistical Analysis System (PSAS). In this study we investigate the impact of this merged/analyzed precipitation data on the global soil moisture variability using an Off-line Land-surface GEOS Assimilation (OLGA) system. Two OLGA integrations starting from 1987 to 1993 are performed forced with the analyzed and GEOS-1 DAS precipitation respectively. We examine the spatial and temporal characteristics of soil moisture variability in response to the analyzed precipitation. The influence of this merged precipitation on the soil moisture variability and regional hydrological budget is estimated throughout the comparison with the results forced with the GEOS-1 DAS precipitation only. In the OLGA the sut@-grid scale horizontal heterogeneity is explicitly represented on the tile space. This provides a means to assess the role of the surface moisture heterogeneity in the interaction with the surface atmosphere and surface hydrological budget, and to validate OLGA results at tile space with in situ observation. ABRACOS (Anglo-Brazilian Amazonian Climate Observation Study), FIFE (First ISLSCP Field Experiment) I and HAPEX data will be used in the validation.

Yang, Runhua↗

NASA NTRS1999

Improving Reanalyses Using TRMM and SSM/I-Derived Precipitation and Total Precipitable Water Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of rainfall and total precipitable water (TPW) observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve these fields in reanalyses. The DAO has developed a "1+1"D procedure to assimilate 6-hr averaged rainfall and TPW into the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS. The "1+1" designation refers to one spatial dimension plus one temporal dimension. The scheme minimizes the least-square differences between the satellite-retrieved rain rates and those produced by the column model over the 6-hr analysis window. The control variables are analysis increments of moisture within the Incremental Analysis Update (IAU) framework of the GEOS DAS. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but differs in its choice of the control variable. Instead of estimating the initial condition at the beginning of the assimilation cycle, it estimates the constant IAU forcing applied over a 6-hr assimilation cycle. In doing so, it imposes the forecast model as a weak constraint in a manner similar to the variational continuous assimilation techniques. We present results from an experiment in which the observed rain rate and TPW are assumed to be "perfect". They show that assimilating the TMI and SSM/I-derived surface precipitation and TPW observations improves not only the precipitation and moisture fields but also key climate parameters directly linked to convective activities such as clouds, the outgoing longwave radiation, and the large-scale circulation in the tropics. In particular, assimilating these data types reduce the state-dependent systematic errors in the assimilated products. The improved analysis also leads to a better short-range forecast, but the impact is modest compared with improvements in the time-averaged fields. These results suggest that, in the presence of biases and other errors of the forecast model, it is possible to improve the time-averaged "climate content" in the assimilated data without comparable improvements in the short-range forecast skill. Results of this experiment provide a useful benchmark for evaluating error covariance models for optimal use of these data types.

Hou, Arthur Y.↗

NASA NTRS1999

Validation of the Land-Surface Energy Budget and Planetary Boundary Layer for Several Intensive field Experiments

Land-surface processes in a data assimilation system influence the lower troposphere and must be properly represented. With the recent incorporation of the Mosaic Land-surface Model (LSM) into the GEOS Data Assimilation System (DAS), the detailed land-surface processes require strict validation. While global data sources can identify large-scale systematic biases at the monthly timescale, the diurnal cycle is difficult to validate. Moreover, global data sets rarely include variables such as evaporation, sensible heat and soil water. Intensive field experiments, on the other hand, can provide high temporal resolution energy budget and vertical profile data for sufficiently long periods, without global coverage. Here, we evaluate the GEOS DAS against several intensive field experiments. The field experiments are First ISLSCP Field Experiment (FIFE, Kansas, summer 1987), Cabauw (as used in PILPS, Netherlands, summer 1987), Atmospheric Radiation Measurement (ARM, Southern Great Plains, winter and summer 1998) and the Surface Heat Budget of the Arctic Ocean (SHEBA, Arctic ice sheet, winter and summer 1998). The sites provide complete surface energy budget data for periods of at least one year, and some periods of vertical profiles. This comparison provides a detailed validation of the Mosaic LSM within the GEOS DAS for a variety of climatologic and geographic conditions.

Bosilovich, Michael G.↗

NASA NTRS1998

Vertical Distribution of Saharan Dust from the Goddard Three Dimensional Transport Model: Comparison with LITE Data

Spatial distributions of Saharan dust are simulated by the Goddard 3D chemistry transport model driven by meteorological fields from the Goddard Earth Observing System Data Assimilation System, GEOS-2 DAS. An aerosol module accounts for gravitational settling and the aerosol source function is based on surface moisture content and wind speed. The simulated aerosol fields are compared with Total Ozone Mapping Spectrometer (TOMS) by P. Ginoux in this session. The main focus is how ventilation of the assimilation winds will impact the simulated aerosol vertical distribution. Excessive ventilation would transport too much aerosol in the upper troposphere and lead to errors in the long range transport as well as errors in any radiative forcing calculations derived from the simulated aerosol fields. Simulated aerosol fields using GEOS-1 DAS wind fields for September 1994 will be compared with lidar observations during the Lidar In-space Technology Experiment (LITE). The lidar return signal clearly delineates the vertical extent and horizontal variability of the aerosol layer allowing rigorous comparison with the simulated fields. A second focus is the simulation of aerosol scavenging due to moist processes. Three-dimensional precipitation fields can be derived from two possible sources: Assimilated precipitation fields from GEOS-DAS or fields obtained from the Special Sensor Microwave/imager (SSM/1). Of interest is the sensitivity of the modeled aerosol fields to the different precipitation fields driving the moist scavenging module.

Weaver, Clark J.↗

NASA NTRS1999

Assimilation of SeaWinds Scatterometer Data in the GEOS Data Assimilation System

The first SeaWinds scatterometer was launched in to space aboard the Quikscat satellite on June 19, 1999 at 7:15 p.m. PDT. Flying in a near polar orbit 800 km above the earth's surface, SeaWinds uses an advanced scatterometer design to measure surface wind velocity over 90 percent of the ice free oceans ever 24 hours. This first SeaWinds mission is designed to replace the NASA Scatterometer (NSCAT) which ceased providing wind velocity data when the ADEOS I satellite failed. A second SeaWinds is scheduled to be launched late in 2000 aboard ADEOS II. Previous scatterometer assimilation experiments conducted by the NASA Data Assimilation Office, using both ERS and NSCAT wind observations, have demonstrated considerable potential for this type of data to improve both atmospheric analyses and forecasts, however much of the smaller scale information content of the scatterometer data could not be taken into account in the early coarse resolution versions of the Goddard (GEOS) Data Assimilation System (DAS) or in operational data assimilation systems. In this paper, we will describe data assimilation experiments in which the new higher resolution versions of the GOES DAS are used to assimilate SeaWinds scatterometer winds. Following a brief discussion of the SeaWinds design and the methodology used to assimilate scatterometer data in the GOES DAS, the quality of the SeaWinds data and the impact of SeaWinds on GOES analyses and forecasts at different resolutions will be presented.

Atlas, Robert↗

NASA NTRS2000

The Impact of Withholding Observations from TOMS or SBUV Instruments on the GEOS Ozone Data Assimilation System

In a data assimilation system (DAS), model forecast atmospheric fields, observations and their respective statistics are combined in an attempt to produce the best estimate of these fields. Ozone observations from two instruments are assimilated in the Goddard Earth Observing System (GEOS) ozone DAS: the Total Ozone Mapping Spectrometer (TOMS) and the Solar Backscatter Ultraviolet (SBUV) instrument. The assimilated observations are complementary; TOMS provides a global daily coverage of total column ozone, without profile information, while SBUV measures ozone profiles and total column ozone at nadir only. The purpose of this paper is to examine the performance of the ozone assimilation system in the absence of observations from one of the instruments as it can happen in the event of a failure of an instrument or when there are problems with an instrument for a limited time. Our primary concern is for the performance of the GEOS ozone DAS when it is used in the operational mode to provide near real time analyzed ozone fields in support of instruments on the Terra satellite. In addition, we are planning to produce a longer term ozone record by assimilating historical data. We want to quantify the differences in the assimilated ozone fields that are caused by the changes in the TOMS or SBUV observing network. Our primary interest is in long term and large scale features visible in global statistics of analysis fields, such as differences in the zonal mean of assimilated ozone fields or comparisons with independent observations, While some drifts in assimilated fields occur immediately, after assimilating just one day of different observations, the others develop slowly over several months. Thus, we are also interested in the length of time, which is determined from time series, that is needed for significant changes to take place.

Stajner, Ovanka↗

NASA NTRS2000

1DVAR Analysis of Temperature and Humidity using GPS Radio Occulation Data

The Global Positioning System (GPS) enables positioning with a very small receiver. The signals transmitted by the GPS satellites are sensitive to the atmosphere and can be used to perform soundings with the radio occultation technique (e.g., Kursinski et al., 1997). The GPS signal can be converted to refractivity N via the Abel transform. The refractivity can then be related to atmospheric pressure P, temperature T, and water vapor partial pressure P (sub w) the GPS measurement, (between 0.5 and 1.5 km), its self-calibration, and it's nearly all-weather capabilities make it a good candidate for use in data assimilation systems (DAS) and numerical weather prediction (NWP). In order to demonstrate its usefulness in a DAS or NWP system, a first step is to assess its impact oil the analysis. A one-dimensional variational off-line analysis (1DVAR), meaning the data are not assimilated 'In the 3D DAS, constitutes a starting approach to which further enhancements can be made. The chosen observable to be analyzed in this study is the refractivity. One way to extract temperature (humidity) from the refractivity, is to assume a humidity (temperature) profile. One variable may then be retrieved without any a priori information. The 1DVAR approach used here resolves the ambiguity problem raised in the interpretation of these data. It enables retrieving these two atmospheric variables at a reasonable computing cost.

Poli, Paul↗

NASA NTRS2001

Mixing in the Extratropical Stratosphere: Model-measurements Comparisons using MLM Diagnostics

We evaluate transport processes in the extratropical lower stratosphere for both models and measurements with the help of equivalent length diagnostic from the modified Lagrangian-mean (MLM) analysis. This diagnostic is used to compare measurements of long-lived tracers made by the Cryogenic Limb Array Etalon Spectrometer (CLAES) on the Upper Atmosphere Research Satellite (UARS) with simulated tracers. Simulations are produced in Chemical and Transport Models (CTMs), in which meteorological fields are taken from the Goddard Earth Observing System Data Assimilation System (GEOS DAS), the Middle Atmosphere Community Climate Model (MACCM2), and the Geophysical Fluid Dynamics Laboratory (GFDL) "SKYHI" model, respectively. Time series of isentropic equivalent length show that these models are able to capture major mixing and transport properties observed by CLAES, such as the formation and destruction of polar barriers, the presence of surf zones in both hemispheres. Differences between each model simulation and the observation are examined in light of model performance. Among these differences, only the simulation driven by GEOS DAS shows one case of the "top-down" destruction of the Antarctic polar vortex, as observed in the CLAES data. Additional experiments of isentropic advection of artificial tracer by GEOS DAS winds suggest that diabatic movement might have considerable contribution to the equivalent length field in the 3D CTM diagnostics.

Ma, Jun↗

NASA NTRS2002

Stratospheric Analysis and Forecasting in the Northern Winter of 1999/2000: The NASA DAO's GEOS-3 System

An evaluation is presented of the performance in the northern winter 1999/2000 of the GEOS-3 troposphere-stratosphere data assimilation system (DAS). The impacts of the two main input data types are assessed: upper-air soundings (sondes) provide wind and temperature information and satellite-based (Tiros Operational Vertical Sounders: TOVS) give estimates of the thermal structure. It is shown that in the low stratosphere (300-70hPa) the analyses are generally slightly warmer than the sonde data, but colder than the TOVS data; this relationship reverses between 70 and 10 hPa. There are geographical biases, related to the spatial and temporal coverage of the observation types and to the statistical weights assigned to them in the DAS. Forecasts show a tendency to reduce zonal asymmetries in the atmospheric flow and to suppress stratospheric temperature minima. In the DAS, the analysis increments compensate for this, but it leads to important biases in the multi-day forecasts. The analysis increments are as large as the diabatic forcing in the lower polar stratosphere, indicating a substantial model bias. The results provide important insights into the roles of different data types and the circulation model in producing accurate analyses for studies of polar chemistry and physical processes.

Pawson, Steven↗

NASA NTRS2002

Sensitivity of Assimilated Tropical Tropospheric Ozone to the Meteorological Analyses

Tropical tropospheric ozone fields from two different experiments performed with an off-line ozone assimilation system developed in NASA's Data Assimilation Office (DAO) are examined. Assimilated ozone fields from the two experiments are compared with the collocated ozone profiles from the Southern Hemispheric Additional Ozonesondes (SHADOZ) network. Results are presented for 1998. The ozone assimilation system includes a chemistry-transport model, which uses analyzed winds from the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The two experiments use wind fields from different versions of GEOS DAS: an operational version of the GEOS-2 system and a prototype of the GEOS-4 system. While both versions of the DAS utilize the Physical-space Statistical Analysis System and use comparable observations, they use entirely different general circulation models and data insertion techniques. The shape of the annual-mean vertical profile of the assimilated ozone fields is sensitive to the meteorological analyses, with the GEOS-4-based ozone being closest to the observations. This indicates that the resolved transport in GEOS-4 is more realistic than in GEOS-2. Remaining uncertainties include quantification of the representation of sub-grid-scale processes in the transport calculations, which plays an important role in the locations and seasons where convection dominates the transport.

Hayashi, Hiroo↗

NASA NTRS2003

Local and Remote Sources of Precipitation during the 1993 Midwestern United States Flood

During June and July of 1993, devastating and persistent rainfall caused substantial damage in the Midwest United States primarily focused on the Mississippi River Basin. Above noma1 springtime rains primed the region for flooding. The resulting wet soil was thought to be a major source of water for the heavy summer precipitation. On the other hand, northward moisture transport was extremely intense during the summer. In this study, we have implemented passive tracers to diagnose the geographic source of water for precipitation, called Water Vapor Tracers (WVT), into the NASA Data Assimilation Office (DAO) Data Assimilation System (DAS). The WVT diagnostics can produce detailed budgets of the geographical sources of water that precipitates in any region, and they consider physical and dynamical tendencies at the model time step. The 1993 summer has been reanalyzed with the new WVT diagnostics to better understand the local and remote source of water for precipitation during the flood. Because the DAS also uses observations of water in the atmospheric hydrologic budget, we will also evaluate the impact of the observations on the local and remote sources of water in the DAS.

Bosilovich, Michael↗

NASA NTRS2004

Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth's Radiant Energy System Instrument on the Terra Satellite: Methodology - Part 1

The Clouds and Earth's Radiant Energy System (CERES) provides coincident global cloud and aerosol properties together with reflected solar, emitted terrestrial longwave and infrared window radiative fluxes. These data are needed to improve our understanding and modeling of the interaction between clouds, aerosols and radiation at the top of the atmosphere, surface, and within the atmosphere. This paper describes the approach used to estimate top-of-atmosphere (TOA) radiative fluxes from instantaneous CERES radiance measurements on the Terra satellite. A key component involves the development of empirical angular distribution models (ADMs) that account for the angular dependence of Earth's radiation field at the TOA. The CERES Terra ADMs are developed using 24 months of CERES radiances, coincident cloud and aerosol retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from the Global Modeling and Assimilation Office (GMA0) s Goddard Earth Observing System DAS (GEOS-DAS V4.0.3) product. Scene information for the ADMs is from MODIS retrievals and GEOS-DAS V4.0.3 properties over ocean, land, desert and snow, for both clear and cloudy conditions. Because the CERES Terra ADMs are global, and far more CERES data is available on Terra than was available from CERES on the Tropical Rainfall Measuring Mission (TRMM), the methodology used to define CERES Terra ADMs is different in many respects from that used to develop CERES TRMM ADMs, particularly over snow/sea-ice, under cloudy conditions, and for clear scenes over land and desert.

Loeb, N. G.↗

NASA NTRS2008

Developments in Test Facility and Data Networking for the Altitude Test Stand at the John C. Stennis Space Center, MS - A General Overview

May 2007, NASA's Constellation Program selected John C Stennis Space Center (SSC) near Waveland Mississippi as the site to construct an altitude test facility for the developmental and qualification testing of the Ares1 upper stage (US) engine. Test requirements born out of the Ares1 US propulsion system design necessitate exceptional Data Acquisition System (DAS) design solutions that support facility and propellant systems conditioning, test operations control and test data analysis. This paper reviews the new A3 Altitude Test Facility's DAS design requirements for real-time deterministic digital data, DAS technology enhancements, system trades, technology validation activities, and the current status of this system's new architecture. Also to be discussed will be current network technologies to improve data transfer.

Hebert, Phillip W., Sr.↗

NASA NTRS2006

Correction for Thermal EMFs in Thermocouple Feedthroughs

A straightforward measurement technique provides for correction of thermal-electromotive-force (thermal-EMF) errors introduced by temperature gradients along the pins of non-thermocouple-alloy hermetic feedthrough connectors for thermocouple extension wires that must pass through bulkheads. This technique is an alternative to the traditional technique in which the thermal-EMF errors are eliminated by use of custom-made multipin hermetic feedthrough connectors that contain pins made of the same alloys as those of the thermocouple extension wires. One disadvantage of the traditional technique is that it is expensive and time-consuming to fabricate multipin custom thermocouple connectors. In addition, the thermocouple-alloy pins in these connectors tend to corrode easily and/or tend to be less rugged compared to the non-thermocouple-alloy pins of ordinary connectors. As the number of thermocouples (and thus pins) is increased in a given setup, the magnitude of these disadvantages increases accordingly. The present technique is implemented by means of a little additional hardware and software, the cost of which is more than offset by the savings incurred through the use of ordinary instead of thermocouple connectors. The figure schematically depicts a typical measurement setup to which the technique is applied. The additional hardware includes an isothermal block (made of copper) instrumented with a reference thermocouple and a compensation thermocouple. The reference thermocouple is connected to an external data-acquisition system (DAS) through a two-pin thermocouple-alloy hermetic feedthrough connector, but this is the only such connector in the apparatus. The compensation thermocouple is connected to the DAS through two pins of the same ordinary multipin connector that connects the measurement thermocouples to the DAS.

Ziemke, Robert A.↗

NASA NTRS2011

A Data System for a Rapid Evaluation Class of Subscale Aerial Vehicle

A low cost, rapid evaluation, test aircraft is used to develop and test airframe damage diagnosis algorithms at Langley Research Center as part of NASA's Aviation Safety Program. The remotely operated subscale aircraft is instrumented with sensors to monitor structural response during flight. Data is collected for good and compromised airframe configurations to develop data driven models for diagnosing airframe state. This paper describes the data acquisition system (DAS) of the rapid evaluation test aircraft. A PC/104 form factor DAS was developed to allow use of Matlab, Simulink simulation code in Langley's existing subscale aircraft flight test infrastructure. The small scale of the test aircraft permitted laboratory testing of the actual flight article under controlled conditions. The low cost and modularity of the DAS permitted adaptation to various flight experiment requirements.

Hogge, Edward F.↗

NASA NTRS2008

The GEOS-5 Data Assimilation System-Documentation of Versions 5.0.1, 5.1.0, and 5.2.0

This report documents the GEOS-5 global atmospheric model and data assimilation system (DAS), including the versions 5.0.1, 5.1.0, and 5.2.0, which have been implemented in products distributed for use by various NASA instrument team algorithms and ultimately for the Modem Era Retrospective analysis for Research and Applications (MERRA). The DAS is the integration of the GEOS-5 atmospheric model with the Gridpoint Statistical Interpolation (GSI) Analysis, a joint analysis system developed by the NOAA/National Centers for Environmental Prediction and the NASA/Global Modeling and Assimilation Office. The primary performance drivers for the GEOS DAS are temperature and moisture fields suitable for the EOS instrument teams, wind fields for the transport studies of the stratospheric and tropospheric chemistry communities, and climate-quality analyses to support studies of the hydrological cycle through MERRA. The GEOS-5 atmospheric model has been approved for open source release and is available from: http://opensource.gsfc.nasa.gov/projects/GEOS-5/GEOS-5.php.

M. M. Rienecker↗

NASA NTRS2014

Status of the NASA GMAO Observing System Simulation Experiment

An Observing System Simulation Experiment (OSSE) is a pure modeling study used when actual observations are too expensive or difficult to obtain. OSSEs are valuable tools for determining the potential impact of new observing systems on numerical weather forecasts and for evaluation of data assimilation systems (DAS). An OSSE has been developed at the NASA Global Modeling and Assimilation Office (GMAO, Errico et al 2013). The GMAO OSSE uses a 13-month integration of the European Centre for Medium- Range Weather Forecasts 2005 operational model at T511/L91 resolution for the Nature Run (NR). Synthetic observations have been updated so that they are based on real observations during the summer of 2013. The emulated observation types include AMSU-A, MHS, IASI, AIRS, and HIRS4 radiance data, GPS-RO, and conventional types including aircraft, rawinsonde, profiler, surface, and satellite winds. The synthetic satellite wind observations are colocated with the NR cloud fields, and the rawinsondes are advected during ascent using the NR wind fields. Data counts for the synthetic observations are matched as closely as possible to real data counts, as shown in Figure 2. Errors are added to the synthetic observations to emulate representativeness and instrument errors. The synthetic errors are calibrated so that the statistics of observation innovation and analysis increments in the OSSE are similar to the same statistics for assimilation of real observations, in an iterative method described by Errico et al (2013). The standard deviations of observation minus forecast (xo-H(xb)) are compared for the OSSE and real data in Figure 3. The synthetic errors include both random, uncorrelated errors, and an additional correlated error component for some observational types. Vertically correlated errors are included for conventional sounding data and GPS-RO, and channel correlated errors are introduced to AIRS and IASI (Figure 4). HIRS, AMSU-A, and MHS have a component of horizontally correlated error. The forecast model used by the GMAO OSSE is the Goddard Earth Observing System Model, Version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) DAS. The model version has been updated to v. 5.13.3, corresponding to the current operational model. Forecasts are run on a cube-sphere grid with 180 points along each edge of the cube (approximately 0.5 degree horizontal resolution) with 72 vertical levels. The DAS is cycled at 6-hour intervals, with 240 hour forecasts launched daily at 0000 UTC. Evaluation of the forecasting skill for July and August is currently underway. Prior versions of the GMAO OSSE have been found to have greater forecasting skill than real world forecasts. It is anticipated that similar forecast skill will be found in the updated OSSE.

OSSE↗

NASA NTRS2015

Improving Forecast Skill by Assimilation of AIRS Cloud Cleared Radiances RiCC

ECMWF, NCEP, and GMAO routinely assimilate radiosonde and other in-situ observations along with satellite IR and MW Sounder radiance observations. NCEP and GMAO use the NCEP GSI Data Assimilation System (DAS).GSI DAS assimilates AIRS, CrIS, IASI channel radiances Ri on a channel-by-channel, case-by-case basis, only for those channels i thought to be unaffected by cloud cover. This test excludes Ri for most tropospheric sounding channels under partial cloud cover conditions. AIRS Version-6 RiCC is a derived quantity representative of what AIRS channel i would have seen if the AIRS FOR were cloud free. All values of RiCC have case-by-case error estimates RiCC associated with them. Our experiments present to the GSI QCd values of AIRS RiCC in place of AIRS Ri observations. GSI DAS assimilates only those values of RiCC it thinks are cloud free. This potentially allows for better coverage of assimilated QCd values of RiCC as compared to Ri.

Forecast Skill↗