Search NASA⌕ Search

SEARCH · Search NASA

Results for “Cloud Clearing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ARM shortwave spectrometers to study the clear-cloud transition zone and mixing processes

The proposed research is a collaborative effort between NASA/Goddard Space Flight Center and the Hebrew University of Jerusalem. While the NASA team focused on analyzing ground-based hyper-spectral radiance observations to understand cloud edge properties and their connection to mixing processes, the Hebrew University team tackled the problem through cloud modeling activities. By approximating the shortwave spectra in the cloud-clear transition zone as a linear combination of purely clear and purely cloudy spectra we can characterize the variations of cloud optical thickness and cloud droplet effective radius in the transition zone. When applying this method to the measurements of a ground-based shortwave spectroradiometer at the ARM’s SGP site, representing continental conditions, and MAGIC field campaign between Log Angeles, California and Honolulu, Hawaii, representing maritime scenarios, we found that cloud optical depth consistently decreases in both cases, but droplet size decreases much more substantially for the continental regime, suggesting different mixing processes for the continental and maritime conditions. The investigation and measurements of radiation clouds were coupled with a unique cloud modeling. A novel spectral bin microphysics was developed and implemented to the System of Atmospheric Modeling (SAM). In order to resolve cloud transition zones with high spatial gradients of microphysical variables a unique high resolution (10 m) was used in simulations. The model calculates droplet size distributions in each grid point. The model output was transferred to the NASA/GSFC team for utilization in radiative calculations and testing of both radiative algorithm and model representation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Evaluation and Assimilation of Cloud Cleared Radiances for AIRS in GEOS-5

The use of clear (cloud-free) channels for AIRS in GEOS-5 had shown positive impact on forecast skills in both hemispheres. However, improvements in forecast skills due to the assimilation of AIRS data are less impressive since the number of assimilated channels from AIRS is much larger than that from other Infrared sounders such as HIRS-3 onboard NOAA 15-17 satellites. This limitation of AIRS radiance data to improve the forecast skill is mainly due to the fact that channels capable of peaking below clouds are not used in the assimilation and yet those have highest vertical resolving capability of AIRS instrument are concentrated in the lower troposphere. On average, the percentage of AIRS footprints completely clear for all channels is less than 10%. The percentage of assimilated AIRS channel radiances however ranges from 100% for channels peaking in the upper stratosphere, above the cloud, to no more that 5% in the lower atmosphere due to cloud contamination. Our current ability to model and predict clouds accurately in global model, and to fully characterize and parameterize optical properties of cloud particles in radiative transfer model are the two major obstacles prohibiting us to use cloudy radiance directly in the assimilation. To further improve forecast skill using AIRS data, we ought to use the channels peaking below the clouds in the troposphere, which can be accomplished by assimilating cloud-cleared radiance. The cloud-cleared radiance data for AIRS used in this study were obtained from optimal cloud clearing procedures developed by researchers at CIMSS of University of Wisconsin at Madison to retrieve clear column radiances for all AIRS channels by collocating multi-band MODIS IR clear radiance observations with the AIRS cloudy radiances on a single footprint basis. Two adjacent AIRS cloudy footprints are used to retrieve one AIRS cloud-cleared radiance spectrum and no background information (first guess) is needed. To assimilate the cloud-cleared radiance data, the errors of the cloud-cleared radiances need to be addressed. The details of convolving AIRS radiances with MODIS spectral response function and comparison with MODIS-measured cloud-free radiance will be presented. The range of errors of cloud-cleared radiances for AIRS using collocated MODIS clear and near-by AIRS clear data will be shown. The NASA. global data assimilation model, GEOS-5, is used to evaluate and assimilate the cloud-cleared radiance for AIRS. The residues between the cloud-cleared brightness temperature and the simulated brightness temperature from background (i.e., OMFs) will be investigated. The quality control procedures will be documented based on error estimation and the OMFs. Finally, the impacts between assimilation of clear channel radiances and cloud-cleared radiances will be addressed.

Liu, Hui-chun↗
NASA NTRS2021

Precipitable Water Vapor Variation in the Clear-Cloud Transition Zone From the ARM Shortwave Spectrometer

A new technique to retrieve precipitable water vapor (PWV)amount in the clear-cloud transition zone using ground-based zenith spectral radiance is developed. The method uses zenith radiances at the water vapor band at 720 nm and adjacent non-absorbing band at 750 nm.Radiative transfer calculations show that the relative difference in zenith radiance between the two bands depends on PWV and the variations in cloud optical depth introduce a small change in the relative difference which is independent of PWV amount. This allows us to retrieve PWV variations in the cloud-clear transition zone for clouds over dark ocean surface. We applied this method to a Cu cloud case with zenith radiance observations by the Shortwave Array Spectroradiometer-Zenith (SASZe) during the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign. We found that there is about 10% change in PWV amount from known-cloudy region to known-clear sky in cloud edges.

Atmosphere↗
NASA NTRSDate not supplied

Implementing Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) Cloud-Clearing Algorithm into the NASA GEOS: Focus on the 2017 Atlantic Tropical Cyclone Season

Numerical Weather Prediction (NWP) centers assimilate cloud-free infrared (IR) radiances because the assimilation of all-sky IR radiances is not yet operationally achievable. The cloud-clearing procedure offers a simpler, but effective strategy that produces cloud-affected radiances suitable for assimilation in partially cloudy regions. Several studies conducted by this team have demonstrated that IR Cloud-Cleared Radiances (CCRs), if thinned more aggressively than clear-sky radiances, can improve analysis and forecasts, particularly in meteorologically active areas. However, CCRs are not used by operational centers due partly to the thought that the process of cloud-clearing may affect latency and introduce difficult-to-control external dependencies. This study presents the results of implementing an Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) cloud-clearing procedure into the NASA Goddard Earth Observing System (GEOS) to demonstrate the portability of the procedure. The AIRS and CrIS cloud-clearing algorithms have been deprived of external dependencies, made customizable to any specific model, and the computational efficiency has been improved via parallelization. The revised AIRS and CrIS cloud-clearing algorithms allow a customized choice of channel selection, the use of a user-specified model's fields as first guess, and can perform in real time. Data assimilation experiments with the hybrid 4DEnVar GEOS system were successfully performed for the 2017 tropical cyclones (TC) season with a focus on three major hurricanes (Harvey, Irma, and Maria). This study shows that assimilation of locally-generated CCRs have a positive impact on both global skill and TC representation, compared to the assimilation of AIRS and CrIS clear-sky radiances, and a comparable or slightly improved impact compared to assimilation of CCRs produced by external sources, such as NASA's Distributed Active Archive Centers and NOAA’s Comprehensive Large Array-data Stewardship System. The customization and computational efficiency of the revised procedure would enable its usability in a real-time forecast context.

Niama Boukachaba↗
NASA NTRS2019

Impact of Assimilating Adaptively Thinned AIRS Cloud-Cleared Radiances in the GEOS

This work examines the assimilation of AIRS (Atmospheric Infrared Sounder) radiances from two points of view: the thinning strategy and the use of cloud-cleared radiances as opposed to clear-sky. Previous published work by this team, based on a very large set of Observing System Experiments performed with a 2014 3DVAR version of the GEOS (Goddard Earth Observing System), has shown that the assimilation of adaptively thinned AIRS cloud-cleared radiances (CCRs) improves the representation of tropical cyclones (TCs) without damaging the global forecast skill. The simple adaptive methodology is based on denser AIRS coverage in moving domains centered on TCs, and sparser coverage everywhere else. Subsequent experiments showed that the adaptive methodology produces good results also when applied to clear-sky CrIS (Cross-track Infrared Sounder) and IASI (Infrared Atmospheric Sounding Interferometer) radiances. In addition, the results indicate that the density of all hyperspectral data assimilated over meteorologically inactive areas is excessive, probably because of horizontal error correlation, suggesting that the global thinning should be more aggressive. More recent work focused on the polar regions has shown another positive impact of assimilating cloud-cleared AIRS radiances instead of clear-sky. The results show that high latitude atmospheric dynamics is very sensitive to the representation of the lower tropospheric temperature structure over the Arctic region. Specifically, assimilation of CCRs over areas that are data poor and also affected by broken stratus clouds, and as such minimally observed by AIRS clear-sky radiances, changes substantially the temperature structure over the Arctic low troposphere. Ingestion of CCRs over the region propagates, through hydrostatic adjustments, to mid-tropospheric geopotential height, allowing for better prediction of mid-latitude waves. In addition, adaptively thinned CCRs also improve the representation of mesoscale convective cyclones at high latitudes. An example of an Antarctic low is provided. Finally, recent ongoing work with the hybrid 4DenVAR GEOS, investigating the 2017 boreal TC season, has confirmed the previous results: namely that aggressively thinned cloud-cleared radiances improve TC structure with no loss of global skill.

CCR↗
NASA NTRS2018

Impact of Assimilating Cloud-Cleared and Adaptively Thinned Infrared Hyperspectral Data on Tropical Cyclones in a Global Data Assimilation and Forecast Framework

A simple adaptive thinning methodology for Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder (CrIS) and Infrared Atmospheric Sounding Interferometer (IASI) radiances is evaluated through a combination of Observing System Experiments (OSEs) and adjoint methodologies. In addition, the impact of cloud-cleared radiances for AIRS is also evaluated. The OSEs are performed with the NASA Goddard Earth Observing System (GEOS, version 5) data assimilation and forecast model. The adaptive strategy uses a denser coverage in a moving domain centered around tropical cyclones (TCs), sparser everywhere else.The OSEs consist of three sets of data assimilation runs that cover the period from September 1st to 10 November 2014, with the first 20 days discarded for spin-up. All sets assimilate conventional and satellite observations used operationally. In addition, one ingests clear-sky AIRS, CrIS, and IASI radiances at different densities, another AIRS cloud-cleared radiances, and CrIS and IASI clear-sky radiances, and the third adaptively thinned AIRS, CrIS and IASI radiances. Daily 10-day forecasts are initialized from all these analyses and evaluated with focus on TCs over the Atlantic and the Pacific.Evidence is provided that this simple TC-centered adaptive radiance thinning strategy, in full agreement with previous theoretical studies, increases the global forecast skill and improves tropical cyclone representation and intensity forecast. In addition, the impact of AIRS cloud-cleared radiances is demonstrated to be particularly strong on TCs. The implications are that cloud-cleared radiances, if thinned more aggressively than the currently used clear-sky radiances, could be operationally used with large gain in TC forecasting and no loss of global skill.

Reale, Oreste↗
NASA NTRS2012

A Study of Global Cirrus Cloud Morphology with AIRS Cloud-clear Radiances (CCRs)

Version 6 (V6) AIRS cloud-clear radiances (CCR) are used to derive cloud-induced radiance (Tcir=Tb-CCR) at the infrared frequencies of weighting functions peaked in the middle troposphere. The significantly improved V 6 CCR product allows a more accurate estimation of the expected clear-sky radiance as if clouds are absent. In the case where strong cloud scattering is present, the CCR becomes unreliable, which is reflected by its estimated uncertainty, and interpolation is employed to replace this CCR value. We find that Tcir derived from this CCR method are much better than other methods and detect more clouds in the upper and lower troposphere as well as in the polar regions where cloud detection is particularly challenging. The cloud morphology derived from the V6 test month, as well as some artifacts, will be shown.

Wu, Dong L.↗
NASA NTRS2019

Impact of Assimilating AIRS Cloud Cleared Radiances on the Analysis and Forecast of Polar Lows

Previous work by this team (Reale et al. 2018) has found that the current assimilation of AIRS (Atmospheric InfraRed Sounder) radiances on a regularly spaced thinning grid is suboptimal, probably because of horizontal error correlation over meteorologically inactive areas. Moreover, cloud-cleared radiances appear to be a better product than clear-sky radiances, but need to be assimilated at a much lower density globally, because of the higher information content. Specifically: 1. Assimilation of AIRS cloud-cleared radiances at a density of about one quarter of the clear-sky radiances improves global forecast skill; 2. An adaptive thinning strategy assimilating cloud-cleared radiances at reduced density globally except around tropical cyclones (TCs), leads to substantial improvement in the structure and intensity forecast of TCs without damaging global skill.

Polar Low↗
NASA NTRS2018

Impact of Assimilating AIRS Cloud-Cleared Radiances on Atmospheric Dynamics and Polar Low Representation at High Latitudes

This study explores the sensitivity of planetary boundary layer height and related atmospheric dynamics to the assimilation of cloud-cleared AIRS (Atmospheric Infrared Sounder) radiances in the Goddard Earth Observing System (GEOS, version 5) data assimilation and forecast system during the boreal fall 2014 season using observing system experiments (OSEs). Examined here are comparisons between the current, operational approach of assimilating AIRS clear-sky radiances against the assimilation of cloud-cleared radiances (CCR). In polar regions, assimilation of AIRS CCRs is particularly beneficial because of the sparsity of conventional observations and the prevalence of extended low-level stratus cloud cover, which limit the ingestion of clear-sky data. Assimilation of hyperspectral infrared information from AIRS over the Arctic region slightly modifies the lower midtropospheric temperature structure, which in turn contributes to adjustments in geopotential height, affecting the baroclinic instability properties over the entire hemisphere and explaining the overall improvement in global forecast skill. In addition, it is shown that the assimilation of CCRs benefits the representation of convectively-driven small-scale cyclones at high latitudes in the same way as previously noted for tropical cyclones. Specifically, assimilation of CCRs create a temperature dipole over the top of meteorologically active and strongly convective systems such as polar, arctic, and antarctic lows, which helps constrain the analyzed representation of their scale and vertical structure.

Mcgrath-Spangler, E. L.↗
NASA NTRS2019

Advances Towards Ingestion of Multi-Instrument Cloud-Cleared Infrared Radiances in a Global Data Assimilation and Forecast Framework

The progress towards the assimilation of hyperspectral infrared radiances affected by clouds in the NASA GEOS system is presented. After positive published results describing the assimilation of adaptively thinned AIRS cloud-cleared radiances in the 3DVAR GEOS, this team has then successfully tested adaptively thinned CrIS and IASI data as well, and then moved to assimilation in a hybrid 4DEnVAR configuration. The latest effort is focused on the creation of a portable, customizable version of the cloud-clearing algorithm that is being tailored for the hybrid 4DEnVAR system.

Reale, Oreste↗
NASA NTRS2006

Retrieved Surface Emissivity Impact of New Cloud-Clearing Channel Set

A viewgraph presentation on a proposed new cloud clearing channel set to improve land products and validate surface emissivity is given. The topics include: 1) Methodology; 2) Channel Selection; 3) Temperature Statistics; 4) 850 hPa Temperature Variability; 5) Status of Surface Retrieval; 6) Emissivity at 9 micrometers; 7) Emissivity Spectra; 8) Ha Megev (Israel); 9) Egypt One; 10) Salonga National Park, Zaire; 11) HaGolan (Israel/Syria); 12) Emissivity at 3.75 micrometers; 13) Improving Surface Retrieval; 14) Work Needed for V5 Delivery; 15) Effects of MODIS Emissivity; 16) Channel Selection; 17) 500 hPa Temperature Variability; 18) 850 hPa Temperature Variability; and 19) 850 hPa Temperature Differences;

Atmospheric Infrared Sounder (AIRS)↗
NASA NTRS2021

Sensitivity of Low Tropospheric Arctic Temperatures to Assimilation of AIRS Cloud-Cleared Radiances: Impact on Mid-Latitude Waves

In this work, it is shown that the prediction of individual mid-latitude waves in a global forecast framework is sensitive to the initialization over the Arctic and may benefit from the assimilation of cloud-cleared radiances (CCRs) from the Atmospheric Infrared Sounder (AIRS), particularly in partially cloudy regions with active dynamics. This study shows that the assimilation of AIRS CCRs over the Arctic Ocean, providing more information than clear-sky radiances from areas affected by broken low-level stratus clouds, produces slightly cooler low-level temperatures and lower mid-tropospheric height through hydrostatic adjustment. In areas that are data void, as observed by clear-sky radiances, and dynamically active, the assimilation of CCRs provides valuable information that can improve the representation of individual baroclinic waves and their subsequent forecasts. The modifications induced by the assimilation of AIRS CCRs over the Arctic Ocean slightly modifies the geopotential height gradients between the Arctic and the mid-latitudes, leading to potential improvements in the forecast of individual baroclinic waves as is shown through a case study. The observing system experiment (OSE) is performed with the NASA Goddard Earth Observing System (GEOS) data assimilation and forecast system during boreal autumn 2014. AIRS CCRs are thinned to approximately one quarter the density of operationally assimilated AIRS radiances, consistent with their higher information content. Global, 6-hourly analyses are produced from 1 September to 10 November 2014 and 7-day forecasts are initialized at 0000 UTC daily. Since the CCR methodology is widely applicable, these findings are also relevant to other infrared sensors.

Cloud-clearing↗
NASA NTRSDate not supplied

Assimilation of Hyperspectral Infrared Radiances from the Cloud-Clearing Methodology: Results from the 2017 Atlantic Tropical Cyclone Season

Assimilation of cloud-affected radiances has the potential to dramatically improve numerical weather prediction systems, as has already been widely shown by use of all-sky microwave radiances. Assimilation of cloudy infrared (IR) radiances, however, lags far behind and only clear-sky radiances are used operationally, leaving data voids in dynamically sensitive areas, such as around tropical cyclones. This team has previously shown the positive benefit of assimilating cloud-cleared IR radiances from hyperspectral sensors (CCRs) and in this work applies the cloud-clearing methodology to generate fully customizable CCRs using an algorithm designed to be portable and reduce latency. These data are successfully assimilated in the Goddard Earth Observing System (GEOS) data assimilation system (DAS) for the 2017 Atlantic Hurricane season.

E L Mcgrath-Spangler↗
NASA NTRS2019

Impact of Assimilating AIRS Cloud-Cleared Radiances on Atmospheric Dynamics and Boundary Layer Height at High Latitudes

High latitude weather forecasts, on scales ranging from mesoscale to synoptic, present difficulties due, in part, to the sparsity of conventional observations. In addition, the prevalence of extended low-level stratus cloud cover limits the use of infrared data, which are operationally assimilated only in areas unaffected by clouds. Use of cloud-cleared AIRS (Atmospheric Infrared Sounder) radiances (AIRS CCR), allows the assimilation of infrared information in cloudy regions, permitting data ingestion in regions usually undersampled. This study explores the sensitivity of planetary boundary layer height and related atmospheric dynamics to the assimilation of these data in the Goddard Earth Observing System (GEOS, version 5) data assimilation and forecast system during the boreal fall 2014 season using observing system experiments (OSEs). Examined here are comparisons between the current, operational approach of assimilating AIRS clear-sky radiances against the assimilation of CCR. Assimilation of hyperspectral infrared information from AIRS over the Arctic region slightly modifies the lower midtropospheric temperature structure, which in turn contributes to adjustments in geopotential height, affecting the baroclinic instability properties over the entire hemisphere and explaining the overall improvement in global forecast skill.

McGrath-Spangler, E. L.↗
NASA NTRS2022

Impact of Assimilating Adaptively Thinned AIRS Cloud-Cleared Radiances on the Analysis of Polar Lows and Mediterranean Sea Tropical-Like Cyclone in a Global Modeling and Data Assimilation Framework

Polar lows, and mesoscale convective cyclones bearing resemblance to tropical cyclones but originating outside of the tropics, are storms that are challenging to represent accurately in global analyses and models because of their small size, rapid growth at subsynoptic scales, occurrence in data poor oceanic regions, and difficulties in objectively validating them in analysis. Building on previous positive results obtained with respect to the representation of tropical cyclones (TCs) in a global model, a set of observing system experiments (OSEs) performed using the NASA Goddard Earth Observing System (GEOS, version 5) are investigated, focusing on three case studies—a polar low in the Sea of Okhotsk, a polar low in the Southern Ocean, and a Mediterranean Sea tropical-like cyclone that occurred during the boreal fall season of 2014. Experiments assimilating adaptively thinned cloud-cleared hyperspectral infrared radiances from the Atmospheric Infrared Sounder (AIRS) instrument on board the NASA Aqua satellite, with higher density in the vicinity of each storm and its pre-cyclogenesis environment, and lower density elsewhere, demonstrate a positive impact on the analyzed representation of each storm. The adaptive thinning experiments improve the storm intensity and structure, including vertical alignment, depth, symmetry, strength, and compactness of warm core compared to the reference experiments. The results suggest that jet-level processes associated with extremely strong horizontal velocity gradients as represented in the model analysis can be useful to locate dynamically active regions of the extratropical atmosphere where denser data coverage is likely to improve the analyzed representation of polar lows and other similar marine mesoscale convective cyclones.

global modeling↗
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↗
NASA NTRS2007

Improved AIRS/AMSU Surface and Atmospheric Soundings Under Partial Cloud Cover Using an AIRS Only Cloud Clearing Approach

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. This paper describes the latest scientific advances made in the AIRS Science Team Version 5.0 retrieval algorithm. Starting in early 2007, the Goddard DAAC will use this algorithm to analyze near real time AIRS/AMSU observations. These products are then made available to the scientific community for research purposes. The products include twice daily measurements of the Earth's three dimensional global temperature, water vapor, and ozone distribution as well as cloud cover. In addition, accurate twice daily measurements of the earth's land and ocean temperatures are derived and reported. Scientists use this important set of observations for two major uses. They provide important information for climate studies of global and regional variability and trends of different aspects of the earth's atmosphere. They also provide information for researchers to improve the skill of weather forecasting. A very important new product of the AIRS Version 5 algorithm is accurate case-by-case error estimates of the retrieved products. This heightens their utility for use in both weather and climate applications. These error estimates are also used directly for quality control of the retrieved products.

Susskind, Dr. Joel↗