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At least 109 records · Page 6

Identification of atmospheric structure by coherent microwave sounding

Two atmospheric probing experiments involving beyond-the-horizon propagation of microwave signals are reported. In the first experiment, Doppler-shift caused by the cross path wind is measured by a phase lock receiver with the common volume displaced in azimuth from the great circle. Variations in the measured Doppler shift values are explained in terms of variations in atmospheric structure. The second experiment makes use of the pseudorandom sounding signal used in a RAKE communication system. Both multipath delay and Doppler shift are provided by the receiver, permitting the cross section of the atmospheric layer structure to be deduced.

Birkemeier, W. P.↗

HAMSR - The High Altitude MMIC Sounding Radiometer

WAMSR is a millimeter wave atmospheric temperature and humidity sounder that utilizes state of the art technology to enable substantial reductions in size and mass while at the same time achieve improved measurement sensitivity and accuracy. It is the first such instrument to use receivers based entirely on newly developed monolithic microwave integrated circuit technology. Sponsored by the NASA Instrument Incubator Program, HAMSR has been under development for the past 2 112 years. The first science mission takes place in Florida this summer, where HAMSR is deployed on the NASA ER-2 during the CAMEX-4 hurricane field campaign and will provide core atmospheric soundings to a number of investigators. HAMSR represents the next generation of microwave sounders.

remote sensing↗

Observation of NO(x) Enhancement and Ozone Depletion in the Northern and Southern hemispheres after the October-November 2003 Solar Proton Events

The large solar storms in October-November 2003 produced enormous solar proton events (SPEs) where high energetic particles reached the Earth and penetrated into the middle atmosphere in the polar regions. At this time, the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) was observing the atmosphere in the 6-68 km altitude range. MIPAS observations of NO(x) (NO+NO2) and O3 of the period from 25 October to 14 November 2003 are the first global measurements of NO(x) species, covering both the summer (daylight) and winter (dark) polar regions during an SPE. Very large values of NO(x) in the upper stratosphere of 180 ppbv (parts per billion by volume) have been measured, and a large asymmetry in Northern and Southern polar cap NO(x) enhancements was found. Arctic mean polar cap (>60 deg) NO(x) enhancements of 20 to 70 ppbv between 40 to 60 km lasted for at least two weeks, while the Antarctic mean NO(x) enhancement was between 10 and 35 ppbv and was halved after two weeks. Ozone shows depletion signatures associated with both HO(x) (H+OH+HO2) and NO(x) enhancements but at different time scales. Arctic lower mesospheric (upper stratospheric) ozone is reduced by 50-70% (30-40%) for about two weeks The large solar storms in October-November 2003 produced after the SPEs. A smaller ozone depletion signal was observed in the Antarctic atmosphere. After the locally produced Arctic middle and upper stratospheric as well as mesospheric NO(x) enhancement, large amounts of NO(x) were observed until the end of December. These are explained by downward transport processes.

Lopez-Puertas, M.↗

Cloud and Thermodynamic Parameters Retrieved from Satellite Ultraspectral Infrared Measurements

Atmospheric-thermodynamic parameters and surface properties are basic meteorological parameters for weather forecasting. A physical geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiance observed with satellite ultraspectral infrared sounders has been developed and applied to the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric InfraRed Sounder (AIRS). The retrieved parameters presented herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, in-situ measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here, IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features with high vertical resolution from satellite ultraspectral sounder radiance spectra.

Zhou, Daniel K.↗

The Suomi National Polar-Orbiting Partnership (SNPP): Continuing NASA Research and Applications

The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).

remote sensing↗

Future hybrid infrared and microwave satellite sounding system - A theoretical analysis of its capability

The expected atmospheric sounding accuracy and the vertical resolution performance of the sounding system selected by NASA to fly aboard the Earth Observing System polar platform, the Atmospheric Infrared Sounder combined with the Advanced Microwave Sounding Unit, are evaluated under various weather conditions. The performance of the combined system is compared to that of current polar orbiting systems. The complementary nature of the IR component provides high vertical resolution, and the microwave information permits sounding through nonprecipitating clouds.

Huang, H.-L.↗

Evaluation of 2 1-D cloud models for the analysis of VAS soundings

Evaluation of the satellite Visual Infrared Spin Scan Radiometer Atmospheric Sounder (VISSR) has begun to document several of its critical shortcomings as far as numerical cloud models are concerned: excessive smoothing of thermal inversions; imprecise measurement of boundary layer moisture; and tendency to exaggerate atmospheric stability. The sensitivity of 1-D cloud models to their required inputs is stressed with special attention to those parameters obtained from atmospheric soundings taken by the VAS or rawinsonde. In addition to performing model experiments using temperature and moisture profiles having the general characteristics of VAS soundings, standard input sensitivity tests were made and 1-D model performance was compared with observations and the results of a 2-D model experiment using AVE/VAS data (Atmospheric Variability Experiment). Although very encouraging, the results are not sufficient to make any specific conclusions. In general, the VAS soundings are likely to be inadequate to provide the cloud base (and subcloud layer) information needed for inputs to current cumulus models. Above cloud base, the tendency to exaggerate the stability of the atmosphere requires solution before meaningful model experiments are run.

Emmitt, G. D.↗

Improved Determination of Surface and Atmospheric Temperatures Using Only Shortwave AIRS Channels

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. AIRS is a grating spectrometer with a number of linear arrays of detectors with each detector sensitive to outgoing radiation in a characteristic frequency v(sub i) with a spectral band pass delta v(sub i) of roughly v(sub i) /1200. AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm(exp -1) (15.38 gm) - 2665 cm(exp -1)' (3.752 micrometers). These spectral regions contain significant absorption features from two CO2 absorption bands, the 15 micrometer (longwave) CO2 band, and the 4.3 micrometer (shortwave) CO, absorption band. There are also two atmospheric window regions, the 12 micrometerm - 8 micrometer (longwave) window, and the 4.17 micrometer - 3.75 micrometer (shortwave) window. Historically, determination of surface and atmospheric temperatures from satellite observations was performed using primarily observations in the longwave window and CO2 absorption regions. One reason for this was concerns about the effects, during the day, of reflected sunlight and non-Local Thermodynamic Equilibrium (non-LTE) on the observed radiances in the shortwave portion of the spectrum. According to cloud clearing theory, more accurate soundings of both surface skin and atmospheric temperatures can be obtained under partial cloud cover conditions if one uses the longwave channels to determine cloud cleared radiances R(sub i) for all channels, and uses R(sub i) only from shortwave channels in the determination of surface and atmospheric temperatures. This procedure is now being used by the AIRS Science Team in preparation for the AIRS Version 6 Retrieval Algorithm. This paper describes how the effects on the radiances of solar radiation reflected by clouds and the Earth's surface, and also of non-LTE, are accounted for in the analysis of the data. Results are presented for both daytime and nighttime conditions showing improved surface and atmospheric soundings under partial cloud cover resulted from not using R(sub i) in the retrieval process for any longwave channels sensitive to cloud effects. This improvement is made possible because AIRS NEDT in the shortwave portion of the spectrum is extremely low.

Susskind,Joel↗

A new algorithm for tuning of computed radiances for HIRS2/MSU

Small biases of the order of 1 C exist in brightness temperatures computed for a number of atmospheric sounding channels using radiosonde reports of atmospheric temperature humidity profile compared to those of collocated HIRS2/MSU observations on TIROS N. These biases are attributed to errors in the computed atmospheric transmittances functions. Channel dependent empirical tuning coefficients were found such that the biases in the channel brightness temperatures are removed if the transmittances used to calculate these brightness temperatures are modified. Possible shortcomings of this method are that some of the bias errors may be due to instrumental calibration problems and that the part that is computational may not be of the form assumed in the equation used. Form of tuning was implemented in the calculation which has the potential of distinguishing between calibration and calculation errors and is also computationally faster and more easily vectorizable.

Susskind, J.↗

TPSAS-NF1676L-12839-DND

Hyper-spectral remote sensors, such as Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI), provides top of atmospheric radiances with high information content on atmospheric and surface properties. In order to analyze these data in real time, fast, and accurate forward and inverse models are needed. We will describe a method of simultaneously retrieving atmospheric temperature, moisture, cloud, and surface properties using all available spectral channels without sacrificing computational speed. The method has been successfully applied to AIRS, IASI, and NAST-I data. By applying the same method to the current and future hyperspectral sounders, the derived products will have less errors due to biases introduced by different retrieval methods. We have compared the retrieved products to radiosondes, aircraft measurements and other validation dataset. Simulations have done to quantify retrieval errors associated with the retrievals. The essence of the method is to convert channel radiance spectra into super-channels by an Empirical Orthogonal Function (EOF) transformation. A Principal Component-based Radiative Transfer Model (PCRTM) developed at NASA Langley Research Center is used to calculate both the super-channel magnitudes and derivatives with respect to atmospheric profiles and other properties. The inversion algorithm is based on a non-linear Levenberg-Marquardt method with climatology covariance matrices and a priori information as constraints. One advantage of this approach is that it uses all information content from the hyper-spectral data so that the retrieval is less sensitive to instrument noise and eliminates the need for selecting a subset of the channels. The PCRTM forward model has also been used to performance end-to-end sensor performance simulations of the Climate Absolute Radiance and Refractivity Observatory (CLARREO).

Xu Liu↗

The use of polar-orbiting satellite sounding data to estimate rural maximum and minimum temperatures

Atmospheric sounding products from NOAA's polar-orbiting satellites were used to derive and test predictive equations of rural shelter-level maximum and minimum temperatures. Sounding data from both winter and summer months were combined with surface data from over 5300 cooperative weather stations in the continental United States to develop multiple linear regression equations. Separate equations were developed for both maximum and minimum temperature, using the three types of sounding retrievals (clear, partly cloudy, and cloudy). Clear retrieval models outperformed others, and maximum temperatures were more accurately predicted than minimums. Average standard deviations of observed rural shelter temperatures within sounding search areas were of similar magnitude to root-mean-square errors from satellite estimates for most clear and partly cloudy cases, but were significantly less for cloudy retrieval cases. Model validation for surrogate polar and tropical climatic regions showed success in application of the four clear retrieval models (maximum and minimum temperature, for both winter and summer). This indicates the potential adaptability of these models to estimates of rural shelter temperature in areas outside of the United States.

Johnson, Gregory L.↗

Atmospheric parameterization schemes for satellite cloud property retrieval during FIRE IFO 2

Satellite cloud retrieval algorithms generally require atmospheric temperature and humidity profiles to determine such cloud properties as pressure and height. For instance, the CO2 slicing technique called the ratio method requires the calculation of theoretical upwelling radiances both at the surface and a prescribed number (40) of atmospheric levels. This technique has been applied to data from, for example, the High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS) flown aboard the NOAA series of polar orbiting satellites and the High Resolution Interferometer Sounder (HIS). In this particular study, four NOAA-11 HIRS channels in the 15-micron region are used. The ratio method may be applied to various channel combinations to estimate cloud top heights using channels in the 15-mu m region. Presently, the multispectral, multiresolution (MSMR) scheme uses 4 HIRS channel combination estimates for mid- to high-level cloud pressure retrieval and Advanced Very High Resolution Radiometer (AVHRR) data for low-level (is greater than 700 mb) cloud level retrieval. In order to determine theoretical upwelling radiances, atmospheric temperature and water vapor profiles must be provided as well as profiles of other radiatively important gas absorber constituents such as CO2, O3, and CH4. The assumed temperature and humidity profiles have a large effect on transmittance and radiance profiles, which in turn are used with HIRS data to calculate cloud pressure, and thus cloud height and temperature. For large spatial scale satellite data analysis, atmospheric parameterization schemes for cloud retrieval algorithms are usually based on a gridded product such as that provided by the European Center for Medium Range Weather Forecasting (ECMWF) or the National Meteorological Center (NMC). These global, gridded products prescribe temperature and humidity profiles for a limited number of pressure levels (up to 14) in a vertical atmospheric column. The FIRE IFO 2 experiment provides an opportunity to investigate current atmospheric profile parameterization schemes, compare satellite cloud height results using both gridded products (ECMWF) and high vertical resolution sonde data from the National Weather Service (NWS) and Cross Chain Loran Atmospheric Sounding System (CLASS), and suggest modifications in atmospheric parameterization schemes based on these results.

Titlow, James↗

Mechanisms Regulating Deep Moist Convection and Sea-Surface Temperatures of the Tropics

Despite numerous previous studies, two relationships between deep convection and the sea-surface temperature (SST) of the tropics remain unclear. The first is the cause for the sudden emergence of deep convection at about 28 deg SST, and the second is its proximity to the highest observed SST of about 30 C. Our analysis provides a rational explanation for both by utilizing the Improved Meteorological (IMET) buoy data together with radar rainfall retrievals and atmospheric soundings provided by the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE). The explanation relies on the basic principles of moist convection as enunciated in the Arakawa-Schubert cumulus parameterization. Our analysis shows that an SST range of 28-29 C is necessary for "charging" the atmospheric boundary layer with sufficient moist static energy that can enable the towering convection to reach up to the 200 hPa level. In the IMET buoy data, the changes in surface energy fluxes associated with different rainfall amounts show that the deep convection not only reduces the solar flux into the ocean with a thick cloud cover, but it also generates downdrafts which bring significantly cooler and drier air into the boundary-layer thereby augmenting oceanic cooling by increased sensible and latent heat fluxes. In this way, the ocean seasaws between a net energy absorber for non-raining and a net energy supplier for deep-convective raining conditions. These processes produce a thermostat-like control of the SST. The data also shows that convection over the warm pool is modulated by dynamical influences of large-scale circulation embodying tropical easterly waves (with a 5-day period) and MJOs (with 40-day period); however, the quasi-permanent feature of the vertical profile of moist static energy, which is primarily maintained by the large-scale circulation and thermodynamical forcings, is vital for both the 28 C SST for deep convection and its upper limit at about 30 C.

Sud, Y. C.↗

Two Decades of Atmospheric and Surface Temperature, Water Vapor, and Cloud Trends Derived from Satellite Remote Sensors

Satellite remote sensor such as Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI) provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

remote sensing↗

GeoSTAR - A Microwave Sounder for Geostationary Satellites

GeoSTAR represents a new approach to microwave atmospheric sounding that is now under development. It has capabilities similar to sensors currently operating on low earth orbiting weather satellites but is intended for deployment in geostationary orbit - where it will complement future infrared sounders and enable all-weather temperature and humidity soundings and rain mapping. The required spatial resolution of 50 km or better dictates an aperture of 4 meters or more at a sounding frequency of 50 GHz, which is difficult to achieve with a real aperture system - this is the reason why it has until now not been possible to put a microwave sounder on a geostationary platform. GeoSTAR is instead based on a synthetic aperture imaging approach. Among the advantages of such a system are that there are no moving parts, and the size of the aperture is easily expandable to meet future needs. A ground based prototype of GeoSTAR is currently under development in an effort led by the Jet Propulsion Laboratory.

aperture synthesis↗

Windsonde Atmospheric Profile during CoURAGE 2024-2025 at Kent Island.

This is the atmospheric sounding data using Sparv Windsond S1 lower-atmosphere profiling instruments ( https://sparv.io/products/windsond-s1) . These data are taken weekly (twice weekly and twice daily during the two CoURAGE IOPs in February and July 2025). Lower-atmosphere conditions, generally between the surface and 5km altitude, are recorded. The variables include pressure, height, temperature, dew-point temperature, wind speed, and wind direction.

air_temperature↗

Windsonde Atmospheric Profile during CoURAGE 2024-2025 at Baltimore.

This is the atmospheric sounding data using Sparv Windsond S1 lower-atmosphere profiling instruments ( https://sparv.io/products/windsond-s1) . These data are taken weekly (twice weekly and twice daily during the two CoURAGE IOPs in February and July 2025). Lower-atmosphere conditions, generally between the surface and 5km altitude, are recorded. The variables include pressure, height, temperature, dew-point temperature, wind speed, and wind direction.

air_temperature↗