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NASA NTRSDate not supplied

TPSAS-NF1676L-10726-DND

The principal component radiative transfer model PCRTM (Xu 2006) simulates spectral longwave radiance at a 0.5cm-1 resolution over the wavelengths (50-2760cm-1) using 280 principal components. The CERES product SSF containing CERES field-of-view (FOV) cloud properties based on MODIS pixel information are used as inputs. NASA GMAO(Global Modeling and Assimilation Office)Geos-4 temperature and humidity profiles, as well as SMOBA (Stratosphere Monitoring Ozone Blended Analysis) ozone profiles allow computations for five years (Jan 2001- Dec 2006) of FOV nadir spectral radiance. The approximately twice daily FOV PCRTM simulations along with CERES broadband measurements are time-space averaged to 10deg zonal monthly data. Analysis of monthly seasonal and deseasonalized interannual variability in terms of brightness temperature are presented. Comparison of interannual variability in the portions of the spectrum seen by the AIRS instrument are shown. Comparisons of spectral integrated PCRTM simulations to CERES broadband longwave radiance measurements are made. In order to study the sensitivity of the spatially and temporally averaged TOA spectrum to various atmospheric properties, we perturbed atmospheric and surface temperatures, humidity, cloud height, cloud fraction, and particle size. The sensitivity of the spectrum to these properties depends on region and seasons. Month to month variability of the longwave spectra to these perturbations is 10 to 20% of the global monthly mean perturbation response. In addition, it depends on time period and size of the area used for averaging spectra. In this poster, the magnitude of sensitivity variability and how the sensitivity changes depending on temporal and spatial scale of averaging will be discussed.

Fred G. Rose↗
NASA NTRS2010

Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

Ice, Cloud, and land Elevation Satellite (ICESat) / Geosciences Laser Altimeter System (GLAS) waveform data are used to estimate biomass and carbon on a 1.27 X 10(exp 6) square km study area in the Province of Quebec, Canada, below the tree line. The same input datasets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include non-stratified and stratified versions of a multiple linear model where either biomass or (biomass)(exp 0.5) serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial dry biomass estimates of up to 0.35 G, with a range of 4.94 +/- 0.28 Gt to 5.29 +/-0.36 Gt. The differences among model estimates are statistically non-significant, however, and the results demonstrate the degree to which carbon estimates vary strictly as a function of the model used to estimate regional biomass. Results also indicate that GLAS measurements become problematic with respect to height and biomass retrievals in the boreal forest when biomass values fall below 20 t/ha and when GLAS 75th percentile heights fall below 7 m.

Nelson, Ross F.↗
NASA NTRSDate not supplied

Forward and Inverse Models for Satellite Remote Sensors using Principal Component Analysis

Satellite remote sensors such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C make millions of observations each day with thousands of spectral channels for each observation; this poses challenges for efficiently inversion of the inherently large dataset as needed to retrieve atmospheric and surface properties. This presentation will illustrate the use of Principal Component Analysis (PCA) to speed up radiative transfer forward model calculations and to stabilize the inversion algorithms. A Principal Component-based radiative transfer model (PCRTM) developed at NASA Langley Research Center can simulate top of atmosphere (TOA) radiance or reflectance spectra from 50 cm-1 to 50000 cm-1 (200 m to 0.20 m quickly and accurately. PCRTM demonstrated very high accuracy relative to reference line-by-line radiative transfer models and it saves orders of magnitude computational time. Examples of the PCRTM model developed for hyperspectral sensors such as AIRS, CrIS, IASI, NAST-I, SHIS, CPF, TEMPO, SBG, OMI, and SCIAMACHY will be presented. In addition to using the PCRTM as forward model, the NASA Langley developed inversion algorithm also uses PCA to compress the state vector into a compressed dimension to speed up and stabilize the inversion process. Examples of retrieved atmospheric temperature, water vapor, CO2, CO, CH4, N2O, and O3 profiles, cloud properties (optical depth, size, phase, and height), and surface properties (surface emissivity spectra and skin temperatures) will be presented. This algorithm is being transitioned to the NASA Sounder SIPS and NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC).

forward model↗
NASA NTRSDate not supplied

CERES Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_TRMM-PFM-VIRS_Beta1)

The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLOUD OVERLAP↗
NASA NTRS1981

Pioneer fly-by of Saturn and its rings

Results acquired by the imaging photopolarimeter on board Pioneer 11 during the spacecraft fly-by of Saturn and its rings on September 1, 1979 are reviewed. Analysis of the broadband photometry and polarimetry obtained of the Saturn atmosphere has been used to determine a cloud top height of 300 mb and a scale height of the aerosol distribution about 1/4 that of the ambient gas, and to point out differences between the forward scattering and belt and zone characteristics of the Saturn and Jupiter atmospheres. Images of Saturn's rings have been used to derive a profile of ring optical depth between 1.22 and 2.35 Saturn radii, and reveal new divisions and thin rings and azimuthal variations in the brightness of the A ring not observable from earth. Linear polarization observations of Titan in red and blue light reveal that the aerosols near the top of the atmosphere have radii less than about 0.09 micron and that the optical thickness of the small aerosol layer is about 0.6 above an effectively depolarizing surface, and indicate radii of 2845 + or - 25 km and 2880 + or - 22 km in red and blue light, respectively. Earth-based and spacecraft data are consistent with the formation of rings structures as a result of Poynting-Robertson drag and gravitational satellite resonances with the original ice and rock particles.

Gehrels, T.↗
NASA NTRS2003

Observations of Dust Using the NASA Geoscience Laser Altimeter System (GLAS): New New Measurements of Aerosol Vertical Distribution From Space

On January 12, 2003 NASA launched the first satellite-based lidar, the Geoscience Laser -Altimeter System (GLAS), onboard the ICESat spacecraft. The GLAS atmospheric measurements introduce a fundamentally new and important tool for understanding the atmosphere and climate. In the past, aerosols have only been studied from space using images gathered by passive sensors. Analysis of this passive data has lead to an improved understanding of aerosol properties, spatial distribution, and their effect on the earth's climate. However, these images do not show the aerosol's vertical distribution. As a result, a key piece of information has been missing. The measurements now obtained by GLAS will provide information on the vertical distribution of aerosols and clouds, and improve our ability to study their transport processes and aerosol-cloud interactions. Here we show an overview of GLAS, provide an update of its current status, and present initial observations of dust profiles. In particular, a strategy of characterizing the height profile of dust plumes over source regions will be presented.

Welton, Ellsworth↗
NASA NTRS2010

JMISR INteractive eXplorer

MISR (Multi-angle Imaging SpectroRadiometer) INteractive eXplorer (MINX) is an interactive visualization program that allows a user to digitize smoke, dust, or volcanic plumes in MISR multiangle images, and automatically retrieve height and wind profiles associated with those plumes. This innovation can perform 9-camera animations of MISR level-1 radiance images to study the 3D relationships of clouds and plumes. MINX also enables archiving MISR aerosol properties and Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power along with the heights and winds. It can correct geometric misregistration between cameras by correlating off-nadir camera scenes with corresponding nadir scenes and then warping the images to minimize the misregistration offsets. Plots of BRF (bidirectional reflectance factor) vs. camera angle for points clicked in an image can be displayed. Users get rapid access to map views of MISR path and orbit locations and overflight dates, and past or future orbits can be identified that pass over a specified location at a specified time. Single-camera, level-1 radiance data at 1,100- or 275- meter resolution can be quickly displayed in color using a browse option. This software determines the heights and motion vectors of features above the terrain with greater precision and coverage than previous methods, based on an algorithm that takes wind direction into consideration. Human interpreters can precisely identify plumes and their extent, and wind direction. Overposting of MODIS thermal anomaly data aids in the identification of smoke plumes. The software has been used to preserve graphical and textural versions of the digitized data in a Web-based database.

Nelson, David L.↗
NASA NTRS1992

Lidar Studies of Extinction in Clouds in the ECLIPS Project

The Experimental Cloud Lidar Pilot Study (ECLIPS) project has now had two active phases in 1989 and 1991. A number of laboratories around the world have taken part in the study. The observations have yielded new data on cloud height and structure, and have yielded some useful new information on the retrieval of cloud optical properties, together with the uncertainties involved. Clouds have a major impact on the climate of the earth. They have the effect of reducing the mean surface temperature from 30 C for a cloudless planet to a value of about 15 C for present cloud conditions. However, it is not at all certain how clouds would react to a change in the planetary temperature in the event of climate change due to a radiative forcing from greenhouse gases. Clouds both reflect out sunlight (negative feedback) and enhance the greenhouse effect (positive feedback), but the ultimate sign of cloud feedback is unknown. Because of these uncertainties, campaigns to study clouds intensely were initiated. The International Satellite Cloud Climatology (ISCPP) and the FIRE Campaigns (cirrus and stratocumulus) are examples. The ECLIPS was set up similarly to the above experiments to obtain information specifically on cloud base, but also cloud top (where possible), optical properties, and cloud structure. ECLIPS was designed to allow as many laboratories as possible globally to take part to get the largest range of clouds. It involves observations with elastic backscatter lidar, supported by infrared fluxes at the ground and radiosonde data, as basic instrumentation. More complex experiments using beam filter radiometers, solar pyranometers, and satellite data and often associated with other campaigns were also encouraged to join ECLIPS. Two periods for observation were chosen, Sep. - Dec. 1989 and Apr. - Jul. 1992 into which investigators were requested to fit 30 days of observations. These would be either continuous, or arranged to coincide with NOAA satellite overpasses to obtain AVHRR data. The distribution of the ECLIPS international effort as in 1991 is shown. The main gaps in the global distribution are in the tropics and the Southern Hemisphere.

Martin, C.↗
NASA NTRSDate not supplied

Study the Vertical Structure and Transportation of the Extreme African Dust Storms using MERRA-2 Data

The Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2) provides the first long-term global reanalysis to assimilate space-based observations of aerosols and represents their interactions with other physical processes in the climate system. In this study, we have examined the variations of atmospheric aerosols for the last 20 years since 2002 using the sub-daily MERRA-2 data and found seven extreme African dust storms that were transported westward across the Atlantic Ocean from the Sahara, crossing 70o-80oW. In particular, the well-known ‘Godzilla’ dust storm occurred in June 2020, and its dust cloud, with the highest-on-record aerosol optical depths, was transported toward the Americas. This storm greatly degraded air quality over large areas of the Caribbean Basin and the United States. The air quality index reached unhealthy levels for sensitive groups in more than ten U.S. states. In our study, the vertical structure and transport characteristics of the dust layers during this extreme dust event are investigated. The geopotential height and temperature were found anomalously low (around 600 hPa) over the Atlantic Ocean off northwest Africa before the June 2020 dust storm. This anomalous circulation pattern was persistent for more than 12 days starting from around May 30, breaking the regular easterly waves that transport dust from the Sahara Desert to the west. To verify the data quality, daily MERRA-2 PM2.5 data were calculated and compared with PM2.5 observations from the U.S. Environmental Protection Agency (EPA) at several selected ground stations in Florida. We provide this case study to illustrate how to effectively use various MERRA-2 data services at Goddard Earth Sciences Data and Information Services Center (GES DISC) where MERRA-2 data are archived, hoping to help data users in exploring their own topics of interest using data services at GES DISC.

data management, reanalysis↗
NASA NTRS1995

Implementation of Combined Feather and Surface-Normal Ice Growth Models in LEWICE/X

Experimental observations have shown that discrete rime ice growths called feathers, which grow in approximately the direction of water droplet impingement, play an important role in the growth of ice on accreting surfaces for some thermodynamic conditions. An improved physical model of ice accretion has been implemented in the LEWICE 2D panel-based ice accretion code maintained by the NASA Lewis Research Center. The LEWICE/X model of ice accretion explicitly simulates regions of feather growth within the framework of the LEWICE model. Water droplets impinging on an accreting surface are withheld from the normal LEWICE mass/energy balance and handled in a separate routine; ice growth resulting from these droplets is performed with enhanced convective heat transfer approximately along droplet impingement directions. An independent underlying ice shape is grown along surface normals using the unmodified LEWICE method. The resulting dual-surface ice shape models roughness-induced feather growth observed in icing wind tunnel tests. Experiments indicate that the exact direction of feather growth is dependent on external conditions. Data is presented to support a linear variation of growth direction with temperature and cloud water content. Test runs of LEWICE/X indicate that the sizes of surface regions containing feathers are influenced by initial roughness element height. This suggests that a previous argument that feather region size is determined by boundary layer transition may be incorrect. Simulation results for two typical test cases give improved shape agreement over unmodified LEWICE.

Matthew T Velazquez↗
NASA NTRS1980

Deep convection on day 261 of GATE

The structural features of the deep convection observed on September 18, 1974, day 261 of the GARP Atlantic Tropical Experiment (GATE), as the ridge axis of a 700 mb wave passed the center of the GATE B-scale network are reported. Satellite and aircraft maps indicate the presence of clouds penetrating above 2.5 km into the middle troposphere organized in bands about 9 km apart and aligned roughly along the direction of the wind shear in the cloud layer. Radar echoes corresponding to cumulus convection of lifetime, peak height and peak rainfall rates on the orders of 30 min, 6 km and 1.3 mm/h, respectively, were observed to triple in number density as convergence at 950 hPa increased from 1.5 to 3 x 10 to the -5th/sec. The structural features of the radar echoes indicate that the day was similar to a mesoscale precipitation feature of Leary and Houe (1979), with the cluster consisting of many echoes appearing in succession. Data from aircraft penetrations of the deep convection reveal downdrafts accompanying the precipitation and updrafts immediately to their south. Shipboard and rawinsonde observations show that the convective downdrafts brought down air of low pseudo-equivalent potential temperature, with local surface convergence of up to 0.001/sec. Mean wind shears through the cloud layer to the top of a main cloud layer are found to be only 75% greater than those of Malkus (1958) for the Caribbean, with shears just above the cloud base several factors larger.

Warner, C.↗
NASA NTRS1993

Electric field measurements in the vicinity of noctilucent clouds and PMSE

We report mesospheric electronic field structure in the vicinity of noctilucent clouds (NLC) and polar mesospheric summer echoes (PMSEs) measured on the DECIMALS-B rocket payload launched during the international rocket-radar campaign NLC-91 from Esrange, Sweden on August 10, 1991. Unusually large vertical E- fields, E(sub Z), about 100-300 mV/m on ascent and greater than 1 V/m on descent were detected at 82.5-84.5 km. The region of the large E(sub Z) was clearly limited by the NLC layer on the bottom and by the distinctly separated PMSE layer on the top. A narrow negative peak in the E(sub Z) height profile observed on ascent in the lower part of the NLC layer was apparently caused by the interaction of the field mill with impacting NLC particles possibly carrying negative charge. If the impact signature is due to single particles, their size is estimated to at least 0.5 microns and their concentration about 10(exp -4)/cu cm locally. Based on the light-scattering properties of NLC such massive particles can only be a minor part of the NLC population.

Zadorozhny, Alexander M.↗
NASA NTRS2016

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations: 2. Retrieval Evaluation

An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (MODIS) observations is assessed in comparison with the operational retrieval products from MODIS on the Aqua satellite (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the Afternoon Constellation (A-Train) with Aqua. The results show that OE-IR cloud optical thickness (tau) and effective radius (r(sub eff)) retrievals perform best for ice clouds having 0.5 < tau< 7 and r(sub eff) < 50microns. For global ice clouds, the averaged retrieval uncertainties of tau and r(sub eff) are 19% and 33%, respectively. For optically thick ice clouds with tau larger than 10, however, the tau and r(sub eff) retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48km. Relatively large h uncertainty (e.g., > 1km) occurs for tau < 0.5. Analysis of 1month of the OE-IR retrievals shows large tau and r(sub eff) uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent tau and h retrievals. However, obvious differences between the OE-IR and the MODIS Collection 6 r(sub eff) are found.

cloud optics↗
NASA NTRSDate not supplied

CERES) Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_Terra-FM2-MODIS_Edition2C)

The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLOUD OVERLAP↗
NASA NTRS1992

Groundbased near-IR observations of the surface of Venus

We present images of the nightside of Venus taken in the near-infrared windows at 1.0, 1.1, 1.18, 1.28, 1.31, and 2.3 microns with the new infrared camera/spectrometer IRIS on the Anglo-Australian Telescope. These data were taken in spectral-mapping mode. This technique involves scanning the telescope perpendicular to the slit, while collecting spectra at successive slit positions across the planet. We produce data cubes with one spectral and two spatial dimensions. Images can be extracted over any wavelength regions. Each image has square pixels of 0.8 inch resolution. We reduced the scattered light from the sunlit crescent in images extracted from each window by subtracting images taken on either side of the window, where the Venus atmosphere is opaque. Unlike the short wavelength windows, which reveal thermal contrasts that originate primarily from the surface and deep atmosphere, the emission in the 2.3 microns window is produced at much higher altitudes (30-40 km). Emission contrasts seen near 2.3 microns are associated with horizontal variations in the cloud optical depths, and have rotation periods of about six days. We detect large contrasts in infrared emission (20-40 percent) across the disc of Venus in the 1.0-, 1.1-, 1.18-, 1.28-, and 1.31-micron images. Contrasts at these wavelengths may be due to a combination of variations in the optical depths of the overlying sulfuric acid clouds and differences in surface emission. Comparison with the 2.3-micron images show that the patterns seen in the 1.28- and 1.31-micron windows are consistent with cloud optical depth variations alone and require no contribution from the surface. However, images at 1.0, 1.1, and 1.8 microns from July 1991 show a dark feature having a contrast that increases with decreasing wavelength. This behavior is contrary to that expected of cloud absorption. Images taken on three successive days in October show another dark feature that is stationary with respect to the surface. These regions of lower emission correspond closely to the high-altitude surface regions of Beta Regio and Aphrodite Terra. The images can potentially reveal the near-infrared emissiveity of the surface of Venus, thereby complementing Magellan radar reflectivity and ground based radio emissivity measurements. The contrast ratio between highlands and plains is much smaller than would be expected for blackbody radiation from the surface along. Unlike at radio wavelengths, where the atmosphere is essentially transparent, at near-infrared wavelengths the atmosphere emits, absorbs, and scatters radiation, and can modify the observed topographically induced contrasts. The additional radiation from the atmosphere reduces the contrast, and further modification would be expected if terrain at different altitudes has different emissivities. A fit to our data therefore requires, and may constrain, a model of the lowest scale height of the atmosphere.

Meadows, V. S.↗
NASA NTRS2009

Antennas Lower Cost of Satellite Access

Whether for scientific inquiry, weather forecasting, or public safety, the world relies upon the data gathered by satellite remote sensing. Some of NASA s most valuable work is in its remote sensing capabilities - the ability to retrieve data acquired at great distances - affording a height and scope not available from the ground. NASA satellites in low Earth orbit (LEO) monitor ocean health by taking large-scale pictures of phytoplankton blooms and measuring surface temperatures; snap photographs of full hurricanes from above, teaching researchers about how these giant storms form; and capture images of cloud formation and air pollution, all allowing researchers to further develop understanding of the planet s health. NASA remote sensing satellites also monitor shifts in the Earth s crust, analyze wind patterns around the world to develop efficient wind energy, help people around the world recover from natural disasters, and monitor diminishing sea ice levels. Just as researchers are more heavily relying on this data from space to conduct their work, the instruments carried on satellites are getting more sophisticated and capable of capturing increasingly complex and accurate measurements. The satellites are covering larger areas, from farther away, and generating more and more valuable data. The ground-based receivers for this wealth of satellite data have grown increasingly capable of handling greater bandwidth and higher power levels. They have also become less expensive, through a NASA research partnership, with the creation of a high-rate X-band data receiver system that is now in widespread use around the globe.

Source record↗
NASA NTRS2014

The Atmospheric Infrared Sounder Version 6 Cloud Products

The version 6 cloud products of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) instrument suite are described. The cloud top temperature, pressure, and height and effective cloud fraction are now reported at the AIRS field-of-view (FOV) resolution. Significant improvements in cloud height assignment over version 5 are shown with FOV-scale comparisons to cloud vertical structure observed by the CloudSat 94 GHz radar and the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). Cloud thermodynamic phase (ice, liquid, and unknown phase), ice cloud effective diameter D(sub e), and ice cloud optical thickness (τ) are derived using an optimal estimation methodology for AIRS FOVs, and global distributions for 2007 are presented. The largest values of tau are found in the storm tracks and near convection in the tropics, while D(sub e) is largest on the equatorial side of the midlatitude storm tracks in both hemispheres, and lowest in tropical thin cirrus and the winter polar atmosphere. Over the Maritime Continent the diurnal variability of tau is significantly larger than for the total cloud fraction, ice cloud frequency, and D(sub e), and is anchored to the island archipelago morphology. Important differences are described between northern and southern hemispheric midlatitude cyclones using storm center composites. The infrared-based cloud retrievals of AIRS provide unique, decadal-scale and global observations of clouds over portions of the diurnal and annual cycles, and capture variability within the mesoscale and synoptic scales at all latitudes.

infrared instruments↗
NASA NTRS2001

The Vertical Error Characteristics of GOES-derived Winds: Description and Impact on Numerical Weather Prediction

Errors in the height assignment of some satellite-derived winds exist because the satellites sense radiation emitted from a finite layer of the atmosphere rather than a specific level. Potential problems in data assimilation may arise because the motion of a measured layer is often represented by a single-level value. In this research, cloud and water vapor motion winds that are derived from the Geostationary Operational Environmental Satellites (GOES winds) are compared to collocated rawinsonde observations (RAOBs). An important aspect of this work is that in addition to comparisons at each assigned height, the GOES winds are compared to the entire profile of the collocated RAOB data to determine the vertical error characteristics of the GOES winds. The impact of these results on numerical weather prediction is then investigated. The comparisons at individual vector height assignments indicate that the error of the GOES winds range from approx. 3 to 10 m/s and generally increase with height. However, if taken as a percentage of the total wind speed, accuracy is better at upper levels. As expected, comparisons with the entire profile of the collocated RAOBs indicate that clear-air water vapor winds represent deeper layers than do either infrared or water vapor cloud-tracked winds. This is because in cloud-free regions the signal from water vapor features may result from emittance over a thicker layer. To further investigate characteristics of the clear-air water vapor winds, they are stratified into two categories that are dependent on the depth of the layer represented by the vector. It is found that if the vertical gradient of moisture is smooth and uniform from near the height assignment upwards, the clear-air water vapor wind tends to represent a relatively deep layer. The information from the comparisons is then used in numerical model simulations of two separate events to determine the forecast impacts. Four simulations are performed for each case: 1) A control simulation that assimilates no satellite wind data, 2) assimilation of all GOES winds according to their assigned single level height, 3) assimilation of all GOES winds spread over multiple levels, and 4) assimilation of all GOES winds spread over multiple levels, but with variations in the vertical influence of clear-air water vapor winds based on the moisture profile in the model. In the first case, a strong mid-latitude cyclone is present and the use of the satellite data results in improved storm tracks during the initial approx. 36 h forecast period. This is because the satellite data improves the analysis of the environment into which the storm progresses. Statistics for mean wind vector and height differences show that, with the exception of the height field at later times in the first case, the use of GOES winds improves the simulation with time. The simulation results suggest that it is beneficial to spread the GOES wind information over multiple levels, particularly when the moisture profile is used to define the vertical influence.

Rao, P. Anil↗