IM Systems Group

Silver Spring, MD, United States

IM Systems Group

Silver Spring, MD, United States
Time filter
Source Type

Oreopoulos L.,NASA | Mlawer E.,Atmospheric and Environmental Research Inc. | Delamere J.,Atmospheric and Environmental Research Inc. | Delamere J.,Tech-X Corporation | And 16 more authors.
Journal of Geophysical Research: Atmospheres | Year: 2012

We present results from Phase I of the Continual Intercomparison of Radiation Codes (CIRC), intended as an evolving and regularly updated reference source for evaluation of radiative transfer (RT) codes used in global climate models and other atmospheric applications. CIRC differs from previous intercomparisons in that it relies on an observationally validated catalog of cases. The seven CIRC Phase I baseline cases, five cloud free and two with overcast liquid clouds, are built around observations by the Atmospheric Radiation Measurements program that satisfy the goals of Phase I, namely, to examine RT model performance in realistic, yet not overly complex, atmospheric conditions. Besides the seven baseline cases, additional idealized "subcases" are also employed to facilitate interpretation of model errors. In addition to quantifying individual model performance with respect to reference line-by-line calculations, we also highlight RT code behavior for conditions of doubled CO2, issues arising from spectral specification of surface albedo, and the impact of cloud scattering in the thermal infrared. Our analysis suggests that improvements in the calculation of diffuse shortwave flux, shortwave absorption, and shortwave CO2 forcing as well as in the treatment of spectral surface albedo should be considered for many RT codes. On the other hand, longwave calculations are generally in agreement with the reference results. By expanding the range of conditions under which participating codes are tested, future CIRC phases will hopefully allow even more rigorous examination of RT codes. © 2012 by the American Geophysical Union.

Bin O.,East Carolina University | Czajkowski J.,University of Pennsylvania | Li J.,Im Systems Group | Villarini G.,University of Iowa
Environmental and Resource Economics | Year: 2016

In this study we utilize a hedonic property price analysis to examine changes in the implicit price of water quality given housing market fluctuations over time. We analyze Martin County, Florida waterfront home sales from 2001 to 2010 accounting for the associated significant real estate fluctuations in this area through flexible econometric controls in space and time. We apply a segmented regression methodology to identify housing market price instability over time, interact water quality with these identified market segmentations, and embed these interactions within a spatial fixed effect model to further account for any spatial heterogeneity in the waterfront market. Results indicate that water quality improvement is associated with higher property values. We find no evidence that the economic downturn crowded out concern for the water quality in this area. We further impute an implicit prices of $2614, evaluated at the sample mean, for 1 % point increase in the water quality grade. © 2016 Springer Science+Business Media Dordrecht

Meyers P.C.,University of Maryland College Park | Ferraro R.R.,The Center for Satellite Applications and Research | Wang N.-Y.,Im Systems Group
Journal of Atmospheric and Oceanic Technology | Year: 2015

The Goddard profiling algorithm 2010 (GPROF2010) was revised for the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS; AMSR-E) instrument. The GPROF2010 land algorithm was developed for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), which observes slightly different central frequencies than AMSR-E. A linear transfer function was developed to convert AMSR-E brightness temperatures to their corresponding TMI frequency for raining and nonraining instantaneous fields of view (IFOVs) using collocated brightness temperature and TRMM precipitation radar (PR) measurements. Previous versions of the algorithm separated rain from surface ice, snow, and desert using a series of empirical procedures. These occasionally failed to separate raining and nonraining scenes, leading to failed detection and false alarms of rain. The new GPROF2010, version 2 (GPROF2010V2), presented here, prefaced the heritage screening procedures by referencing annual desert and monthly snow climatologies to identify IFOVs where rain retrievals were unreliable. Over a decade of satellite- and ground-based observations from the Interactive Multisensor Snow and Ice Mapping System (IMS) and AMSR-E allowed for the creation of a medium-resolution (0.25° × 0.25°) climatology of monthly snow and ice cover. The scattering signature of rain over ice and snow is not well defined because of complex emissivity signals dependent on snow depth, age, and melting, such that using a static climatology was a more stable approach to defining surface types. GPROF2010V2 was subsequently used for the precipitation environmental data record (EDR) for the AMSR2 sensor aboard the Global Change Observation Mission-Water 1 (GCOM-W1). © 2015 American Meteorological Society.

Sun B.,Im Systems Group | Sun B.,The Center for Satellite Applications and Research | Reale A.,The Center for Satellite Applications and Research | Seidel D.J.,National Oceanic and Atmospheric Administration | Hunt D.C.,University Corporation for Atmospheric Research
Journal of Geophysical Research: Atmospheres | Year: 2010

Collocated global atmospheric temperature, humidity, and refractivity profiles from radiosondes and from Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation data for April 2008 to October 2009 are compared for two purposes. The first is to quantify the error characteristics of 12 radiosonde types flown in the global operational network, as a function of height and for both day and nighttime observations, for each of the three variables. The second is to determine the effects of imperfect temporal and spatial collocation on the radiosonde-COSMIC differences, for application to the general problem of satellite calibration and validation using in situ sounding data. Statistical analyses of the comparisons reveal differences among radiosonde types in refractivity, relative humidity, and radiation-corrected temperature data. Most of the radiosonde types show a dry bias, particularly in the upper troposphere, with the bias in daytime drier than in nighttime. Weather-scale variability, introduced by collocation time and distance mismatch, affects the comparison of radiosonde and COSMIC data by increasing the standard deviation errors, which are generally proportional to the size of the time and distance mismatch within the collocation window of 6 h and 250 km considered. Globally, in the troposphere (850-200 hPa), the collocation mismatch impacts on the comparison standard deviation errors for temperature are 0.35 K per 3 h and 0.42 K per 100 km and, for relative humidity, are 3.3% per 3 h and 3.1% per 100 km, indicating an approximate equivalence of 3 h to 100 km in terms of mismatch impact. Copyright 2010 by the American Geophysical Union.

Chen R.,Im Systems Group | Cao C.,The Center for Satellite Applications and Research
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2011

The 30 years of observations from High-Resolution Infrared Radiation Sounder (HIRS) aboard NOAA series of satellites have been widely used in numerical weather prediction and climate studies. However, there are significant discrepancies in the HIRS measurements between different satellites. The HIRS data from NOAA satellites series need to be recalibrated to establish an accurate and consistent temporal series before it can be used for climate changing detection. To ensure the consistency and reduce the uncertainties for the climate studies of clouds using NOAA HIRS data, this study explores the spectral calibration of longwave CO 2 channels for the HIRS on board of NOAA series of satellites using the hyper-spectral IASI radiance measurements from MetOp satellite as reference. The HIRS measurements from each NOAA satellite are compared with the recalibrated HIRS measurements from the successive satellite at Simultaneous-Nadir-Overpass (SNO) locations. For the satellites after NOAA 15, the comparison between the HIRS measurements and the matched IASI measurements at SNO locations is also displayed. A preliminary analysis of the intersatellite biases is performed to quantify the spectral causes of the biases for HIRS channels 4. By removing these biases, our method shows the potential to recalibrate the HIRS on board of the NOAA series of satellites and make the HIRS measurements traceable to the IASI measurements with improved spectral calibration. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Seidel D.J.,National Oceanic and Atmospheric Administration | Sun B.,Im Systems Group | Pettey M.,Im Systems Group | Reale A.,The Center for Satellite Applications and Research
Journal of Geophysical Research: Atmospheres | Year: 2011

The drift of radiosonde balloons during their ascent has generally been considered a negligible factor in applications involving radiosonde observations. However, several applications envisioned for observations from the Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) require estimates of balloon drift. This study presents a comprehensive global climatology of radiosonde balloon drift distance and ascent time, based on 2 years of data from 419 stations, with particular attention to GRUAN stations. Typical drift distances are a few kilometers in the lower troposphere, ∼5 km in the midtroposphere, ∼20 km in the upper troposphere, and ∼50 km in the lower stratosphere, although there is considerable variability due to variability in climatological winds. Drift distances tend to increase with height above the surface, be larger in midlatitudes than in the tropics, be larger in winter than in summer, and vary with wind (and consequent balloon drift) direction. Most estimates of elapsed time from balloon launch to various pressure levels, due to vertical balloon rise, have median values ranging from about 5 min at 850 hPa to about 1.7 h at 10 hPa, with ranges of about 20% of median values. Observed elapsed times exceed those estimated using assumed 5 or 6 m/s rise rates. Copyright 2011 by the American Geophysical Union.

Chang T.,Im Systems Group | Wu X.,National Oceanic and Atmospheric Administration
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2012

The increasing need for accuracy in Advanced Very High Resolution Radiometer (AVHRR) radiance products requires a precise calibration of the instrument response. One concern is the error in the on-board calibration radiance, which combines the on-board black body (BB) imperfection effect and the temperature measurement error. The BB imperfection effect includes the radiance reduction due to the non-perfect BB (emissivity less than 1) and the reflection of the instrument and Earth scene environment through the BB. In addition, discriminating the temperature measurement error and BB imperfection is difficult due to insufficient on-board measurement information. In this work, an effective emissivity is used to analyze the on-board BB calibration radiance. The error in the effective emissivity is evaluated using an inter-comparison approach, from the difference in radiance retrieved by AVHHR IR channels and the spectral radiance measured by the Infrared Atmospheric Sounding Interferometer (IASI) on the same satellite, MetOp-A. Two AVHRR IR channels (channels 4 and 5) are covered by the IASI spectrum and homogenous Earth scenes with brightness temperatures close to the on-board BB temperature are selected to evaluate the calibration radiance error. It is found that this error is 0.30% for channel 4 and 0.33% for channel 5. The correction of the calibration radiance provides the possibility to correct the errors due to other effects, such as the offset and nonlinearity in instrument response. The Earth scene brightness temperature dependent bias will be discussed and the source of the error will be discussed. © 2012 SPIE.

Chang T.,Im Systems Group | Cao C.,National Oceanic and Atmospheric Administration
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2011

Instrument self-emission and nonlinear response play important roles in satellite thermal infrared radiometers, and can affect the accuracy of Earth scene radiance retrieval if uncorrected. This paper presents a simplified self-emission model for infrared radiometers and analyzes the interrelationships between the instrument selfemission, detector nonlinearity, and calibration intercept and slope variations using MetOp-A/HIRS prelaunch characterization data. HIRS is a traditional cross-track line scanning radiometer in the infrared and visible spectrum, including 12 long wave infrared channels (669-1529cm -1), 7 short wave infrared channels (2188- 2657cm -1), and 1 visible channel, with beamsplitters and a rotating filter wheel assembly consisting of 20 spectral filters separates individual channels. The warm filters and other in-path components generate selfemission which becomes the majority of the total radiance falling on the detector. The pre-launch TV data allow us to evaluate the self-emission using the simplified model. It was found that the self-emission contributions at the detectors are in the range of 95% to 97%. The self-emission fluctuates with the instrument temperature and causes the variation in instrument response, including the variations of intercept and the instrument gain. The quantification of these variations provides guideline for on-orbit calibration algorithm improvement. The selfemission model is improved and its impact on MetOp-A/HIRS on-orbit calibration and Earth scene retrieval are also assessed. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Zhu Y.,Im Systems Group | Derber J.C.,National Oceanic and Atmospheric Administration | James Purser R.,Im Systems Group | Ballish B.A.,Im Systems Group | And 2 more authors.
Monthly Weather Review | Year: 2015

Various studies have noted that aircraft temperature data have a generally warm bias relative to radiosonde data around 200 hPa. In this study, variational aircraft temperature bias correction is incorporated in the Gridpoint Statistical Interpolation analysis system at the National Centers for Environmental Prediction. Several bias models, some of which include information about aircraft ascent/descent rate, are investigated. The results show that the aircraft temperature bias correction cools down the atmosphere analysis around 200 hPa, and improves the analysis and forecast fits to the radiosonde data. Overall, the quadratic aircraft ascent/descent rate bias model performs better than other bias models tested here, followed closely by the aircraft ascent/descent rate bias model. Two other issues, undocumented in previous studies, are also discussed in this paper. One is the bias correction of aircraft report (AIREP) data. Unlike Aircraft Meteorological Data Relay (AMDAR) data, where unique corrections are applied for each aircraft, bias correction is applied indiscriminately (without regard to tail numbers) to all AIREP data. The second issue is the problem of too many aircraft not reporting time in seconds, or too infrequently, to be able to determine accurate vertical displacement rates. In addition to the finite-difference method employed to estimate aircraft ascent/descent rate, a tensioned-splines method is tested to obtain more continuously smooth aircraft ascent/descent rates and mitigate the missing time information. © 2015 American Meteorological Society.

Zhang H.,University of Maryland Baltimore County | Zhang H.,Im Systems Group | Hoff R.M.,University of Maryland Baltimore County | Kondragunta S.,College Park | And 2 more authors.
Atmospheric Measurement Techniques | Year: 2013

Aerosol optical depth (AOD) in the western United States is observed independently by both the (Geostationary Operational Environmental Satellites) GOES-East and GOES-West imagers. The GASP (GOES Aerosol/Smoke Product) aerosol optical depth retrieval algorithm treats each satellite as a unique sensor and thus obtains two separate aerosol optical depth values at the same time for the same location. The TOA (the top of the atmosphere) radiances and the associated derived optical depths can be quite different due to the different viewing geometries with large difference in solar-scattering angles. In order to fully exploit the simultaneous observations and generate consistent AOD retrievals from the two satellites, the authors develop a new "hybrid" aerosol optical depth retrieval algorithm that uses data from both satellites. The algorithm uses both GOES-East and GOES-West visible channel TOA reflectance and daily average AOD from GOES Multi-Angle Implementation of Atmospheric Correction (GOES-MAIAC) on low AOD days (AOD less than 0.3), when diurnal variation of AOD is low, to retrieve surface BRDF (Bidirectional Reflectance Distribution Function). The known BRDF shape is applied on subsequent days to retrieve BRDF and AOD. The algorithm is validated at three AERONET sites over the western US. The AOD retrieval accuracy from the "hybrid" technique using the two satellites is similar to that from one satellite over UCSB (University of California Santa Barbara) and Railroad Valley, Nevada. Improvement of the accuracy is observed at Boulder, Colorado. The correlation coefficients between the GOES AOD and AERONET AOD are in the range of 0.67 to 0.81. More than 74% of AOD retrievals are within the error of ±(0.05+0.15τ) compared to AERONET AOD. The hybrid algorithm has more data coverage compared to the single satellite retrievals over surfaces with high surface reflectance. For single observation areas the number of valid AOD data increases from the use of two-single satellite algorithms by 5-80% for the three sites. With the application of the new algorithm, consistent AOD retrievals and better retrieval coverages can be obtained using the data from the two GOES satellite imagers. © Author(s) 2013. CC Attribution 3.0 License.

Loading IM Systems Group collaborators
Loading IM Systems Group collaborators