Dr. David R. Doelling Profile

Dr. David R. Doelling

Group Leader at NASA Langley Research Ctr

SPIE Involvement:

Author

Publications (37)

Proceedings Article | 4 October 2023 Presentation + Paper

Improved characterization of Libya-4 and Dome-C for consistent radiometric scaling between VIIRS sensors

David Doelling, Conor Haney, Prathana Khakurel, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan

Proceedings Volume 12685, 1268519 (2023) https://doi.org/10.1117/12.2677789

KEYWORDS: Atmospheric corrections, MODIS, Ozone, Absorption, Tunable filters, Sensors, Bidirectional reflectance transmission function, Imaging systems, Clouds, Aerosols

Read Abstract +

The NASA Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) product provides the scientific community observed TOA SW and LW fluxes for climate monitoring and climate model validation. To provide continuity for cloud retrievals between MODIS and VIIRS, the CERES project inter-calibrates MODIS and VIIRS utilizing coincident ray-matched radiance pairs over all-sky tropical ocean. The Aqua and Terra satellites have started drifting, thereby preventing any coincident tropical MODIS and VIIRS inter-calibration events. Similarly, no simultaneous nadir overpasses (SNOs) will exist between SNPP and NOAA satellites, which will fly in the same 1:30 PM orbit but positioned a half an orbit apart. The CERES project will utilize the Libya-4 and Dome-C invariant targets to radiometrically scale between MODIS and VIIRS reflective solar bands. This study has advanced the Libya-4 and Dome-C characterization by considering all angular conditions, improving clear-sky identification and atmospheric corrections. The BRDF for each VZA and RAA stratified angular bin is approximated using a 2^nd order regression with respect to cos(SZA). The clear-sky filtering utilized spatial homogeneity thresholds applied to channels not impacted by atmospheric parameters and additional angular bin specific dynamic filtering. Multiple sources of PW, ozone and aerosol optical depth are considered. The improved atmospheric characterization is evaluated by comparing the trendSE consistency across channels. For Libya-4 the 2.2μm and 0.91μm strong water vapor absorption bands, the trendSE was reduced by ~60% and ~80% by including the PW term. The Libya- 4 trendSE with atmospheric correction was reduced from within 2% to 1% for all channels except MODIS B17. The Dome-C 0.55mm and 0.65μm band trendSE was reduced by between 40% to 60% after accounting for ozone absorption. The Dome-C imager channel trendSE was reduced from within 2% to 1% by including atmospheric corrections. The Dome-C post-solstice ozone and PW daily variations are much smaller than prior to solstice. The Dome-C resulting post-solstice imager channel trendSE was reduced from 1% to 0.85% by including atmospheric corrections and closer to the 0.48μm band trendSE of 0.6%, which was not impacted by the atmosphere. Smaller trend_SE can be realized by limiting the large VZA observations over Libya-4 as well as utilizing only post-solstice observations over Dome-C.

Proceedings Article | 4 October 2023 Presentation + Paper

The impact of pixel size on the characterization of deep convective clouds for calibration

Conor Haney, David Doelling, Rajendra Bhatt, Prathana Khakurel, Benjamin Scarino, Arun Gopalan

Proceedings Volume 12685, 1268518 (2023) https://doi.org/10.1117/12.2677709

KEYWORDS: Reflectivity, Pixel resolution, Landsat, Clouds, Calibration, Image resolution, Imaging systems, Sensors, Spatial resolution

Read Abstract +

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, are used to estimate the broadband fluxes between CERES observations. This requires stable and consistent cross-platform imager visible channel calibration. The CERES project utilizes deep convective clouds (DCC) as an invariant Earth target to both monitor the stability of sensors and for radiometric scaling. GSICS, an international collaboration, is also evaluating and implementing the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the Aqua- MODIS or the NOAA-20 VIIRS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical DCC-identified pixel-level reflectances, which are aggregated as probability density functions (PDF). By assuming the monthly PDF shape is otherwise consistent in time excepting shifts in reflectance caused by changes in the sensor calibration, the imager stability is monitored. Radiometric scaling is accomplished by ratioing the sensor pair DCC PDF reflectance values. The success of the DCC methodology relies on consistent PDF distributions. The goal of this study is to determine the impact of pixel resolution on the DCC reflectance distribution. Single SNPP-VIIRS 750-m and Landsat 8 OLI 30-m granules are aggregated to degrade the pixel resolution from the native level. The DCC pixels are identified using a BT threshold. Most of the brightest DCC pixels are also the coldest, although there are exceptions. It was found that increasing the BT threshold exponentially increased the number of darker pixels. The pixel resolution did not seem to impact the DCC reflectance PDF distribution for pixel resolutions less than 3 km, which suggests that imagers of varying pixel resolutions may be radiometrically scaled to each other using DCC targets.

Proceedings Article | 4 October 2023 Presentation + Paper

Estimating bidirectional reflectance and monitoring stability of SNPP-VIIRS reflective solar bands using a deep neural network

Benjamin Scarino, David Doelling, Rajendra Bhatt, Conor Haney, Prathana Khakurel, Arun Gopalan, Xiaoxiong Xiong

Proceedings Volume 12685, 1268517 (2023) https://doi.org/10.1117/12.2677687

KEYWORDS: Reflectivity, Short wave infrared radiation, Neural networks, Clouds

Read Abstract +

Proceedings Article | 30 September 2022 Presentation + Paper

Additional characterization of Libya-4 in support of post-launch vicarious calibration of satellite imagers

David Doelling, Prathana Khakurel, Conor Haney, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan

Proceedings Volume 12232, 1223219 (2022) https://doi.org/10.1117/12.2633118

KEYWORDS: Clouds, Reflectivity, Imaging systems, Sensors, Photonic integrated circuits, Ozone, Aerosols, Atmospheric particles

Read Abstract +

Proceedings Article | 30 September 2022 Presentation + Paper

Evaluation of spectral band adjustment factors for cross-calibration of visible imagers

David Doelling, Conor Haney, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan, Prathana Khakurel

Proceedings Volume 12232, 122321A (2022) https://doi.org/10.1117/12.2633113

KEYWORDS: Reflectivity, Clouds, Sensors, Neodymium, Satellites, Imaging systems

Read Abstract +

The NASA Clouds and the Earth's Radiant Energy System (CERES) energy balanced and filled (EBAF) product provides top of atmosphere SW and LW fluxes for monitoring the Earth’s energy budget and to validate climate models. The current EBAF Ed4.1 products, based on the Terra and Aqua CERES instrument observed radiances, rely on MODIS cloud properties to determine the scene-selected angular distribution model used to convert the CERES radiances into fluxes. The CERES EBAF Ed4.2 product will be based on NOAA-20 CERES observations beginning with the data month of April 2022. A seamless transition of fluxes and clouds can only occur if the analogous MODIS and VIIRS channels are properly inter-calibrated. The spectral response functions (SRF) of these bands differ noticeably and will require scene-dependent spectral band adjustment factors (SBAF) for proper radiometric scaling between them. VIIRS I1 and M5 same-granule reflectance measurements provide the optimal opportunity to validate SBAFs over many surface and cloud conditions. The CERES project maintains SCIAMACHY-, GOME-2-, and Hyperion-based scene-stratified hyper-spectral reflectance measurements that can be convolved with sensor pair SRFs to compute the corresponding SBAFs. The SCIAMACHY 2^nd order and GOME-2 linear fit SBAFs were optimal in providing spatially uniform M5/I1 spectrally corrected reflectance ratios over all-sky tropical ocean scenes, which corrected both clear-sky and bright cloud reflectances simultaneously by varying the SBAF as a function of the reflectance. Dome-C and deep convective cloud (DCC) SBAFs had a small M5/I1 SBAF reflectance correction of ~1.03, whereas Libya-4 had a large M5/I1 SBAF reflectance correction of ~1.085. DCC, Dome-C and Libya-4 are spectrally uniform spatial targets with site M5/I1 reflectance ratio spatial homogeneity within 0.2%. The impact of cloud contamination from both the cloud tops and shadows over Libya-4 reduced the M5/I1 reflectance ratio. Over Dome-C, cloud contamination did not significantly shift the M5/I1 reflectance ratio. The Hyperion spectral reflectances are too coarse to be convolved with the narrow M5 SRF, which resulted in M5/I1 SBAFs that differed significantly from those based on SCIAMACHY and GOME-2.

SPIE Journal Paper | 10 January 2022 Open Access

Daily monitoring algorithms to detect geostationary imager visible radiance anomalies

David Doelling, Conor Haney, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan

JARS, Vol. 16, Issue 01, 014502, (January 2022) https://doi.org/10.1117/12.10.1117/1.JRS.16.014502

KEYWORDS: Calibration, Imaging systems, MODIS, Clouds, Reflectivity, Solids, Satellites, Sensors, Satellite imaging, Image resolution

Read Abstract +

The NASA Clouds and the Earth’s Radiant Energy System (CERES) project provides observed flux and cloud products for the climate science community. Geostationary satellite (GEO) imager measured clouds and broadband derived fluxes are incorporated in the CERES SYN1deg product to provide regional diurnal information in between Sun-synchronous Terra and Aqua CERES measurements. The recently launched GEO imagers with onboard calibration systems have active calibration teams that incrementally update the calibration in order to mitigate calibration drifts. However, short-term L1B radiance anomalies and calibration adjustment discontinuities may still exist in the record. To avoid any GEO cloud and flux artifacts in the CERES SYN1deg product, these calibration events must be addressed while scaling the GEO imagers to the Aqua-moderate resolution imaging spectroradiometer (MODIS) calibration reference. All-sky tropical ocean ray-matching (ATO-RM) and deep convective cloud invariant target (DCC-IT)-based monitoring algorithms are presented to detect calibration-driven daily anomalies in the GOES-16 Advanced Baseline Imager L1B visible (0.65 μm) radiance measurements. Sufficient daily ATO-RM sampling was obtained both by ray-matching GOES-16 with multiple MODIS and visible-infrared imaging radiometer suite imagers as well as by increasing the grid resolution. Optimized angular matching and outlier filtering were most effective in reducing the ATO-RM daily gain algorithm noise. The DCC-IT daily calibration algorithm utilized a larger domain and included more GOES-16 scan times. The DCC-IT daily gain uncertainty was reduced by normalizing the DCC regional reflectance on a regional, seasonal, and diurnal basis. The combination of ATO-RM and DCC-IT daily monitoring algorithms is shown to detect, with a high degree of confidence, daily GOES-16 L1B calibration-driven radiance anomalies >2.4 % , while keeping false positives at a minimum. Remarkably, the ATO-RM and DCC-IT daily gains are mostly within 0.5%. The ATO-RM and DCC-IT daily monitoring algorithms can be easily adapted to other GEO imagers and visible channels.

DOWNLOAD PAPER

Proceedings Article | 12 September 2021 Presentation + Paper

Optimized MODIS channel selection to improve the NASA CERES FluxByCloudTyp product fluxes

David Doelling, Moguo Sun, Forrest Wrenn

Proceedings Volume 11859, 118590F (2021) https://doi.org/10.1117/12.2600060

KEYWORDS: MODIS, Clouds, Satellites, Reflectivity, Climatology, Imaging systems, Ocean optics, Visible radiation, Satellite imaging, Carbon dioxide

Read Abstract +

Proceedings Article | 1 August 2021 Presentation + Paper

Improving the CERES SYN cloud and flux products by identifying GOES-17 scan anomalies using a convolutional neural network

Benjamin Scarino, David Doelling, Konstantin Khlopenkov, William Smith, Michele Nordeen

Proceedings Volume 11829, 1182904 (2021) https://doi.org/10.1117/12.2594637

KEYWORDS: Clouds, Image processing, Satellites, Satellite imaging, Inspection, Earth observing sensors, Imaging systems, Visualization, Convolutional neural networks, Detection and tracking algorithms

Read Abstract +

Proceedings Article | 1 August 2021 Presentation + Paper

Additional characterization of Dome-C to improve its use as an invariant visible calibration target

David Doelling, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan, David Rutan, Ryan Scott, Conor Haney

Proceedings Volume 11829, 118290D (2021) https://doi.org/10.1117/12.2594294

KEYWORDS: Ozone, Reflectivity, MODIS, Calibration, Clouds, Absorption, Sensors, Imaging systems, Sensor calibration, Atmospheric modeling

Read Abstract +

SPIE Journal Paper | 7 August 2020

Clouds and the Earth’s Radiant Energy System strategy for intercalibrating the new-generation geostationary visible imagers

Rajendra Bhatt, David Doelling, Conor Haney, Douglas Spangenberg, Benjamin Scarino, Arun Gopalan

JARS, Vol. 14, Issue 03, 032410, (August 2020) https://doi.org/10.1117/12.10.1117/1.JRS.14.032410

KEYWORDS: Calibration, Clouds, Reflectivity, Imaging systems, Bidirectional reflectance transmission function, Short wave infrared radiation, Satellites, Sun, Sensors

Read Abstract +

Proceedings Article | 10 October 2019 Presentation + Paper

An automated algorithm to detect MODIS, VIIRS and GEO sensor L1B radiance anomalies

David Doelling, Conor Haney, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan

Proceedings Volume 11151, 111511T (2019) https://doi.org/10.1117/12.2533246

KEYWORDS: Clouds, Climatology, Image segmentation

Read Abstract +

Proceedings Article | 9 September 2019 Paper

Advances in utilizing tropical deep convective clouds as a stable target for on-orbit calibration of satellite imager reflective solar bands

Rajendra Bhatt, David Doelling, Benjamin Scarino, Arun Gopalan, Conor Haney

Proceedings Volume 11127, 111271H (2019) https://doi.org/10.1117/12.2530636

KEYWORDS: Reflectivity, Clouds, Short wave infrared radiation, Calibration, Satellites, Imaging systems, Satellite imaging, Earth observing sensors, Bidirectional reflectance transmission function, Radio optics

Read Abstract +

Tropical deep convective clouds (DCC) are proven to be an excellent Earth invariant target for post-launch radiometric assessment of satellite imagers. The success of the DCC technique (DCCT) relies on a large ensemble of identified DCC pixels that are collectively analyzed as a stable reflectance reference. The near-Lambertian reflectance of DCC, as well as their high signal-to-noise ratio, location near the tropopause above most of the atmospheric water vapor and aerosol, and availability across the globe make them an ideal target for radiometric scaling of geostationary (GEO) and low-earth orbiting (LEO) satellites. The DCCT has been successfully applied to calibrate reflective solar bands (with wavelengths < 1 µm) of numerous GEO and LEO imagers. The DCC reflectivity in VIS-NIR is mainly a function of cloud optical depth, and the DCCT provides a stable monthly statistical mode that can be tracked over time for monitoring the radiometric stability of the sensor. However, at shortwave infrared (SWIR) wavelengths, the DCC reflectance is affected by both cloud particle size and cloud optical depth. The DCCT for SWIR bands is found to be most sensitive to the BRDF and brightness temperature, resulting in large seasonal cycles of DCC reflectivity that make the implementation of the DCCT more challenging. The key to improving the DCCT at SWIR wavelengths is proper characterization of the DCC reflectance as a function of viewing and solar angular conditions. This paper presents channel-specific seasonal BRDF models for SWIR bands based on five years of SNPP-VIIRS DCC measurements. The seasonal BRDFs are effective in reducing the temporal variability of the DCC time series by up to 65% when applied to both Aqua-MODIS and NPP-VIIRS SWIR bands. The use of seasonal BRDF models for radiometric stability assessment and absolute inter-calibration of the MODIS and SNPPVIIRS SWIR bands is discussed in the paper. In addition, the modification of the baseline DCCT for daily monitoring of the radiometric stability of the GEO imager L1B radiances is also illustrated. The DCCT is capable of detecting daily GOeS-16 L1B radiance anomalies with a magnitude greater than ±3% for bands 2 and 3, and ±4% shift for band 1 with 3σ significance.

Proceedings Article | 23 October 2018 Paper

Advances in utilizing deep convective cloud targets to inter-calibrate geostationary reflective solar band imagers with well calibrated imagers

Conor Haney, David Doelling, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan

Proceedings Volume 10781, 107810Z (2018) https://doi.org/10.1117/12.2324786

KEYWORDS: Calibration, MODIS, Imaging systems, Clouds, Reflectivity, Visible radiation, Satellites, Sensors

Read Abstract +

The CERES project utilizes geostationary-derived broadband measurements to infer the regional diurnal flux in between CERES instantaneous measurements to estimate the daily-averaged flux. The geostationary (GEO) imager radiances must be calibrated to the same reference to ensure spatial and temporal consistency of cloud properties and fluxes across the contiguous GEO domains. In order to place all of the GEO visible imagers on the same radiometric scale, the CERES project inter-calibrates the GEO imagers with Aqua-MODIS using multiple independent approaches. The primary inter-calibration approach relies on coincident, ray-matched GEO and MODIS radiance pairs over all-sky tropical ocean scenes (ATO). Another ray-matching approach was recently developed to take advantage of the visible spectral uniformity and near-Lambertian reflectance of deep convective clouds (DCC). The success of the DCC raymatching (DCC-RM) approach has been demonstrated by comparing the calibration with the ATO ray-matching (ATORM) approach for the 0.65-μm GEO and MODIS bands.

Now that many of the recently launched GEO imagers have multiple reflective solar band channels, the DCCRM algorithm is being modified to inter-calibrate those channels as well, especially for the SWIR bands. The spectral uniformity of the DCC over the SWIR bands is not uniform, given that the ice particle absorption is a function of wavelength. New Spectral Band Adjustment Factor (SBAF) strategies will need to be developed. DCC-RM is also wellsuited to inter-calibrate historical near-broadband visible GEO imagers. DCC are spectrally flat across the visible spectrum, which reduces the SBAF uncertainty between two ray-matched sensors. Applying the DCC-RM technique on historical GEO imagers is challenging due to the coarser pixel and temporal resolution of the ISCCP B1U formatted dataset.

The ATO-RM and DCC-RM calibration methods were applied to multiple visible bands on Himawari-8 using MODIS as the calibration reference. The Aqua-MODIS and Himawari-8 calibration difference was less than 0.4% for wavelengths less than 1 µm and for the Terra-MODIS 0.65-μm channel. Other channel combinations would need further examination to obtain consistent ATO and DCC gain results. The ATO-RM and DCC-RM calibration methods were also applied to GOES-8 in the ISCCP B1U format with NOAA-14 AVHRR as the calibration reference. The GOES-8 ATO and DCC calibration gain difference was within 0.15%. The agreement between ATO and DCC gains provides confidence in both methods.

Proceedings Article | 7 September 2018 Presentation + Paper

Enhancements to the open access spectral band adjustment factor online calculation tool for visible channels

Benjamin Scarino, David Doelling, Arun Gopalan, Thad Chee, Rajendra Bhatt, Conor Haney

Proceedings Volume 10764, 1076418 (2018) https://doi.org/10.1117/12.2321118

KEYWORDS: Calibration, Reflectivity, MODIS, Clouds, Sensors, Satellites, Visible radiation

Read Abstract +

With close to 40 years of satellite observations, from which, cloud, land-use, and aerosol parameters can be measured, inter-consistent calibrations are needed to normalize retrievals across satellite records. Various visible-sensor inter-calibration techniques have been developed that utilize radiometrically stable Earth targets, e.g., deep convective clouds and desert/polar ice pseudo-invariant calibration sites. Other equally effective, direct techniques for intercalibration between satellite imagers are simultaneous nadir overpass comparisons and ray-matched radiance pairs. Combining independent calibration results from such varied techniques yields robust calibration coefficients, and is a form of self-validation. One potential source of significant error when cross-calibrating satellite sensors, however, are the often small but substantial spectral discrepancies between comparable bands, which must be accounted for. As such, visible calibration methods rely on a Spectral Band Adjustment Factor (SBAF) to account for the spectral-responsefunction-induced radiance differences between analogous imagers. The SBAF is unique to each calibration method as it is a function of the Earth-reflected spectra. In recent years, NASA Langley pioneered the use of SCIAMACHY-, GOME-2-, and Hyperion-retrieved Earth spectra to compute SBAFs. By carefully selecting hyperspectral footprints that best represent the conditions inherent to an inter-calibration technique, the uncertainty in the SBAF is greatly reduced. NASA Langley initially provided the Global Space-based Inter-calibration System processing and research centers with online SBAF tools, with which users select conditions to best match their calibration criteria. This article highlights expanded SBAF tool capabilities for visible wavelengths, with emphasis on spectral range filtering for the purpose of separating scene conditions for the channel that the SBAF is needed based on the reflectance values of other bands. In other words, spectral filtering will enable better scene-type selection for bands where scene determination is difficult without information from other channels, which should prove valuable to users in the calibration community.

Proceedings Article | 29 September 2017 Presentation + Paper

The use of deep convective clouds to uniformly calibrate the next generation of geostationary reflective solar imagers

David Doelling, Rajendra Bhatt, Conor Haney, Arun Gopalan, Benjamin Scarino

Proceedings Volume 10423, 1042319 (2017) https://doi.org/10.1117/12.2278676

KEYWORDS: Imaging systems, Calibration, Clouds, Satellites, MODIS, Sensor calibration, Shortwaves, Climatology, Satellite imaging, Detection and tracking algorithms

Read Abstract +

Proceedings Article | 30 August 2017 Presentation + Paper

Utilizing the precessing orbit of TRMM to produce hourly corrections of geostationary infrared imager data with the VIRS sensor

Benjamin Scarino, David Doelling, Conor Haney, Kristopher Bedka, Patrick Minnis, Arun Gopalan, Rajendra Bhatt

Proceedings Volume 10403, 104030H (2017) https://doi.org/10.1117/12.2273883

KEYWORDS: Calibration, Infrared imaging, Satellites, MODIS, Remote sensing

Read Abstract +

Accurate characterization of the Earth’s radiant energy is critical for many climate monitoring and weather forecasting applications. For example, groups at the NASA Langley Research Center rely on stable visible- and infraredchannel calibrations in order to understand the temporal/spatial distribution of hazardous storms, as determined from an automated overshooting convective top detection algorithm. Therefore, in order to facilitate reliable, climate-quality retrievals, it is important that consistent calibration coefficients across satellite platforms are made available to the remote sensing community, and that calibration anomalies are recognized and mitigated. One such anomaly is the infrared imager brightness temperature (BT) drift that occurs for some Geostationary Earth Orbit satellite (GEOsat) instruments near local midnight. Currently the Global Space-Based Inter-Calibration System (GSICS) community uses the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) sensor as a common reference to uniformly calibrate GEOsat IR imagers. However, the combination of IASI, which has a 21:30 local equator crossing time (LECT), and hyperspectral Atmospheric Infrared Sounder (AIRS; 01:30 LECT) observations are unable to completely resolve the GEOsat midnight BT bias. The precessing orbit of the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS), however, allows sampling of all local hours every 46 days. Thus, VIRS has the capability to quantify the BT midnight effect observed in concurrent GEOsat imagers. First, the VIRS IR measurements are evaluated for long-term temporal stability between 2002 and 2012 by inter-calibrating with Aqua-MODIS. Second, the VIRS IR measurements are assessed for diurnal stability by inter-calibrating with Meteosat-9 (Met-9), a spin-stabilized GEOsat imager that does not manifest any diurnal dependency. In this case, the Met-9 IR imager is first adjusted with the official GSICS calibration coefficients. Then VIRS is used as a diurnal calibration reference transfer to produce hourly corrections of GEOsat IR imager BT. For the 9 three-axis stabilized GEO imagers concurrent with VIRS, the midnight effect increased the BT on average by 0.5 K (11 μm) and 0.4 K (12 μm), with a peak at ~01:00 local time. As expected, the spin-stabilized GEOsats revealed a smaller diurnal temperature cycle (mostly < 0.2 K) with inconsistent peak hours.

SPIE Journal Paper | 28 January 2017

Characterizing response versus scan-angle for MODIS reflective solar bands using deep convective clouds

Rajendra Bhatt, David Doelling, Amit Angal, Xiaoxiong Xiong, Benjamin Scarino, Arun Gopalan, Conor Haney, Aisheng Wu

JARS, Vol. 11, Issue 01, 016014, (January 2017) https://doi.org/10.1117/12.10.1117/1.JRS.11.016014

KEYWORDS: MODIS, Reflectivity, Calibration, Photonic integrated circuits, Clouds, Sensors, Mirrors, Satellites, Short wave infrared radiation, Satellite imaging

Read Abstract +

Proceedings Article | 18 October 2016 Paper

Development of image processing method to detect noise in geostationary imagery

Konstantin Khlopenkov, David Doelling

Proceedings Volume 10004, 100041S (2016) https://doi.org/10.1117/12.2241544

KEYWORDS: Image processing, Satellites, Satellite imaging, Data processing, Clouds, Visible radiation, Infrared imaging, Imaging systems, Calibration, Image analysis

Read Abstract +

Proceedings Article | 19 September 2016 Presentation + Paper

The calibration of the DSCOVR EPIC multiple visible channel instrument using MODIS and VIIRS as a reference

Conor Haney, David Doelling, Patrick Minnis, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan

Proceedings Volume 9972, 99720P (2016) https://doi.org/10.1117/12.2238010

KEYWORDS: Calibration, MODIS, Satellites, Environmental sensing, Climatology, Clouds, Sensors, Error analysis, Visible radiation, Ultraviolet radiation

Read Abstract +

Proceedings Article | 19 September 2016 Presentation + Paper

Assessment of MODIS on-orbit calibration using a deep convective cloud technique

Qiaozhen Mu, Aisheng Wu, Tiejun Chang, Amit Angal, Daniel Link, Xiaoxiong Xiong, David Doelling, Rajendra Bhatt

Proceedings Volume 9972, 997210 (2016) https://doi.org/10.1117/12.2237047

KEYWORDS: MODIS, Calibration, Clouds, Sensors, Diffusers, Reflectivity, Short wave infrared radiation, Mirrors, Absorption, Infrared radiation

Read Abstract +

Proceedings Article | 2 May 2016 Paper

Global space-based inter-calibration system reflective solar calibration reference: from Aqua MODIS to S-NPP VIIRS

Xiaoxiong Xiong, Amit Angal, James Butler, Changyong Cao, David Doelling, Aisheng Wu, Xiangqian Wu

Proceedings Volume 9881, 98811D (2016) https://doi.org/10.1117/12.2224320

KEYWORDS: Calibration, MODIS, Sensors, Reflectivity, Bidirectional reflectance transmission function, Sensor calibration, Diffusers, Sensor performance, Domes, Satellites

Read Abstract +

Proceedings Article | 2 May 2016 Paper

Response versus scan-angle corrections for MODIS reflective solar bands using deep convective clouds

Rajendra Bhatt, Amit Angal, David Doelling, Xiaoxiong Xiong, Aisheng Wu, Conor Haney, Benjamin Scarino, Arun Gopalan

Proceedings Volume 9881, 98811L (2016) https://doi.org/10.1117/12.2223809

KEYWORDS: MODIS, Calibration, Reflectivity, Clouds, Diffusers, Mirrors, Sensors, Photonic integrated circuits, Distributed interactive simulations, Neodymium

Read Abstract +

Proceedings Article | 8 September 2015 Paper

Toward consistent radiometric calibration of the NOAA AVHRR visible and near-infrared data record

Rajendra Bhatt, David Doelling, Benjamin Scarino, Arun Gopalan, Conor Haney

Proceedings Volume 9607, 960703 (2015) https://doi.org/10.1117/12.2186816

KEYWORDS: Calibration, Sensors, Satellites, MODIS, Clouds, Near infrared, Sensor calibration, Absorption, Scattering, Backscatter

Read Abstract +

Proceedings Article | 26 September 2014 Paper

Calibrating historical IR sensors using GEO and AVHRR infrared tropical mean calibration models

Benjamin Scarino, David Doelling, Patrick Minnis, Arun Gopalan, Conor Haney, Rajendra Bhatt

Proceedings Volume 9218, 92180H (2014) https://doi.org/10.1117/12.2061993

KEYWORDS: Calibration, Infrared imaging, Satellites, Imaging systems, Infrared sensors, Infrared radiation, Sensors, Satellite imaging, Data modeling, Climatology

Read Abstract +

Long-term, remote-sensing-based climate data records (CDRs) are highly dependent on having consistent, wellcalibrated satellite instrument measurements of the Earth’s radiant energy. Therefore, by making historical satellite calibrations consistent with those of today’s imagers, the Earth-observing community can benefit from a CDR that spans a minimum of 30 years. Most operational meteorological satellites rely on an onboard blackbody and space looks to provide on-orbit IR calibration, but neither target is traceable to absolute standards. The IR channels can also be affected by ice on the detector window, angle dependency of the scan mirror emissivity, stray-light, and detector-to-detector striping. Being able to quantify and correct such degradations would mean IR data from any satellite imager could contribute to a CDR. Recent efforts have focused on utilizing well-calibrated modern hyper-spectral sensors to intercalibrate concurrent operational IR imagers to a single reference. In order to consistently calibrate both historical and current IR imagers to the same reference, however, another strategy is needed. Large, well-characterized tropical-domain Earth targets have the potential of providing an Earth-view reference accuracy of within 0.5 K. To that effort, NASA Langley is developing an IR tropical mean calibration model in order to calibrate historical Advanced Very High Resolution Radiometer (AVHRR) instruments. Using Meteosat-9 (Met-9) as a reference, empirical models are built based on spatially/temporally binned Met-9 and AVHRR tropical IR brightness temperatures. By demonstrating the stability of the Met-9 tropical models, NOAA-18 AVHRR can be calibrated to Met-9 by matching the AVHRR monthly histogram averages with the Met-9 model. This method is validated with ray-matched AVHRR and Met-9 bias difference time series. Establishing the validity of this empirical model will allow for the calibration of historical AVHRR sensors to within 0.5 K, and thereby establish a climate-quality IR data record.

Proceedings Article | 25 September 2014 Paper

Development of 2D deconvolution method to repair blurred MTSAT-1R visible imagery

Konstantin Khlopenkov, David Doelling, Arata Okuyama

Proceedings Volume 9218, 92181Q (2014) https://doi.org/10.1117/12.2061121

KEYWORDS: Point spread functions, Clouds, Satellites, Sensors, Mirrors, Deconvolution, Imaging systems, Visible radiation, Satellite imaging, Convolution

Read Abstract +

Proceedings Article | 23 September 2013 Paper

An initial assessment of the VIIRS onboard calibration using DCC and desert referenced to the Aqua-MODIS calibration

Rajendra Bhatt, David Doelling, Benjamin Scarino, Arun Gopalan, Conor Haney

Proceedings Volume 8866, 88660K (2013) https://doi.org/10.1117/12.2024271

KEYWORDS: Calibration, MODIS, Clouds, Climatology, Imaging systems, Satellites, Atmospheric modeling, Visible radiation, Scattering, Environmental sensing

Read Abstract +

Proceedings Article | 15 October 2012 Paper

Using SCIAMACHY to improve corrections for spectral band differences when transferring calibration between visible sensors

Benjamin Scarino, David Doelling, Daniel Morstad, Rajendra Bhatt, Arun Gopalan, Constantine Lukashin, Patrick Minnis

Proceedings Volume 8510, 85100Q (2012) https://doi.org/10.1117/12.929767

KEYWORDS: Calibration, MODIS, Absorption, Sensors, Clouds, Visible radiation, Imaging systems, Oceanography, Water, Sensor calibration

Read Abstract +

The advent of well-calibrated and well-characterized visible sensors, such as the MODerate resolution Imaging Spectroradiometer (MODIS), has allowed the opportunity to cross-calibrate other contemporary, un-calibrated visible sensors. Most of the operational geostationary-Earth-orbit satellite (GEOsat) visible sensors do not have a direct means of on-orbit calibration, and the cross-calibration of MODIS with GEOsats is plagued by the differences in the sensor spectral response functions (SRFs). Spectral band adjustment factors (SBAFs) are needed to correct for the solar flux and inter-band gaseous absorption discrepancies that are caused by SRF differences, which are sometimes significant. In addressing this problem, this manuscript describes a spectral band correction technique that employs Envisat SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) hyper-spectral radiances to derive pseudo-radiance, or equivalent-radiance, values for the MODIS and GEOsat sensors over the calibration targets, which include a desert, deep convective clouds, and a MODIS-with-GEOsat ray-matching ocean domain. The regressions from these equivalent-radiance comparisons constitute the necessary adjustment factor. The regressions of MODIS and GEOsat pseudo-radiance values are well-behaved, with small standard error and offsets, for spectral bands that are similar. When comparing narrowband to broadband, however, the correction difference between deep convective and maritime stratus clouds can be as large as 6%. New scene-selection criteria are investigated to derive spectral band adjustment factors that are dependent on the calibration-target domains, which reduces this uncertainty. Application of these SBAFs, which are validated for accuracy using ray-matched SCIAMACHY and GEOstat radiances, is shown to bring independently derived absolute calibrations to within 1% agreement, or better, with one-another. These spectral band adjustment factors are critical for obtaining accurate and consistent absolute calibration among multiple independent and scene-dependent inter-calibration techniques given that the variation of the SBAFs as a function of scene type can be close to 8% for a narrowband-to-broadband correction.

Proceedings Article | 14 September 2011 Paper

The CERES calibration strategy of the geostationary visible channels for CERES cloud and flux products

Daniel Morstad, David Doelling, Rajendra Bhatt, Benjamin Scarino

Proceedings Volume 8153, 815316 (2011) https://doi.org/10.1117/12.894650

KEYWORDS: Calibration, Sensors, MODIS, Clouds, Satellites, Bidirectional reflectance transmission function, Reflectivity, Climatology, Sensor calibration, Instrument modeling

Read Abstract +

The Clouds and Earth's Radiant Energy System (CERES) project has greatly improved the understanding of the role of clouds and energy cycles in global climate studies. CERES flux and cloud properties rely on not only CERES broadband fluxes and MODIS cloud properties but also on operational geostationary (GOES, METEOSAT, MTSAT) derived fluxes and clouds, which are acquired between CERES measurements such to properly account for the diurnal cycle. The high quality of the CERES products is dependent on a consistent radiometric calibration of the un-calibrated geostationary visible sensors and MODIS. To achieve this consistency, the calibration of a reference sensor must be transferred to the other instruments. Historically, Terra-MODIS and Aqua-MODIS, both of which employ solar diffusers, have been regarded as having a well-calibrated visible channel (650 nm). Recent analysis has revealed the Aqua-MODIS instrument to be more stable than the MODIS instrument onboard the Terra satellite. For this reason, Aqua-MODIS has been chosen as the reference sensor whereas Terra-MODIS adjustments can be used to put the instrument on the same radiometric scale as Aqua-MODIS. The ray-matching technique is used to transfer the calibration of the well-calibrated MODIS instrument to the un-calibrated GEO sensors. Additionally, empirically derived models for pseudo-invariant test sites and deep convective clouds (DCC) have been developed and applied for monitoring and validating the GEO calibration. Multiple pseudo-invariant test site and DCC absolute calibration methodologies are compared. Latest results show that GOES-13 response has drifted 5-6 percent in its first 15 months of operation. The Aqua/Terra-MODIS crosscalibration trends are in agreement with calibration trends obtained from pseudo-invariant test sites and DCC. These results are in preparation for CERES Edition4 products, which will include updated geostationary calibration coefficients and cloud retrieval improvements.

Proceedings Article | 4 November 2010 Paper

The characterization of deep convective cloud albedo as a calibration target using MODIS reflectances

David Doelling, Gang Hong, Dan Morstad, Rajendra Bhatt, Arun Gopalan, Xiaoxiong Xiong

Proceedings Volume 7862, 78620I (2010) https://doi.org/10.1117/12.869577

KEYWORDS: Calibration, MODIS, Clouds, Satellites, Convection, Sensors, Absorption, Visible radiation, Sun, Bidirectional reflectance transmission function

Read Abstract +

Proceedings Article | 13 October 2008 Paper

Near-real time cloud retrievals from operational and research meteorological satellites

Patrick Minnis, Louis Nguyen, Rabindra Palikonda, Patrick Heck, Douglas Spangenberg, David Doelling, J. Kirk Ayers, William Smith, Mandana Khaiyer, Qing Trepte, Lance Avey, Fu-Lung Chang, Chris Yost, Thad Chee, Sun-Mack Szedung

Proceedings Volume 7107, 710703 (2008) https://doi.org/10.1117/12.800344

KEYWORDS: Clouds, Satellites, MODIS, Calibration, Satellite imaging, Imaging systems, Earth observing sensors, Infrared imaging, Meteorological satellites, Reflectivity

Read Abstract +

Proceedings Article | 24 September 2007 Paper

The calibration of AVHRR visible dual gain using Meteosat-8 for NOAA-16 to 18

David Doelling, Donald Garber, Lance Avey, Louis Nguyen, Patrick Minnis

Proceedings Volume 6684, 668409 (2007) https://doi.org/10.1117/12.736080

KEYWORDS: Calibration, MODIS, Satellites, Clouds, Imaging systems, Visible radiation, Sensors, Image resolution, Nano opto mechanical systems, Vegetation

Read Abstract +

Proceedings Article | 26 October 2004 Paper

Rapid technique to cross-calibrate satellite imager visible channels

Louis Nguyen, David Doelling, Patrick Minnis, J. Ayers

Proceedings Volume 5542, (2004) https://doi.org/10.1117/12.560138

KEYWORDS: Calibration, Satellites, Sensors, Satellite imaging, Imaging systems, MODIS, Visible radiation, Earth observing sensors, Clouds, Infrared imaging

Read Abstract +

Proceedings Article | 26 October 2004 Paper

On the use of deep convective clouds to calibrate AVHRR data

David Doelling, Louis Nguyen, Patrick Minnis

Proceedings Volume 5542, (2004) https://doi.org/10.1117/12.560047

KEYWORDS: Calibration, Clouds, Satellites, MODIS, Reflectivity, Sensors, Visible radiation, Infrared radiation, Atmospheric modeling, Phase modulation

Read Abstract +

Proceedings Article | 16 February 2004 Paper

CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua

Patrick Minnis, David Young, Sunny Sun-Mack, Patrick Heck, David Doelling, Qing Trepte

Proceedings Volume 5235, (2004) https://doi.org/10.1117/12.511210

KEYWORDS: Clouds, MODIS, Satellites, Imaging systems, Calibration, Infrared radiation, Climatology, Atmospheric modeling, Particles, Satellite imaging

Read Abstract +

Proceedings Article | 12 December 2001 Paper

Simulation and correction of Triana-viewed Earth radiation budget with ERBE data

Patrick Minnis, Jianping Huang, David Doelling, Francisco Valero

Proceedings Volume 4540, (2001) https://doi.org/10.1117/12.450681

KEYWORDS: Satellites, Reflectivity, Data modeling, Clouds, Earth's atmosphere, Scanners, Solids, Sun, Radiometry, Solar radiation

Read Abstract +

Proceedings Article | 1 September 1990 Paper

Time dependence of the earth's radiation fields determined from ERBS and NOAA-9 satellites

Edwin Harrison, Patrick Minnis, Bruce Barkstrom, Bruce Wielicki, Gary Gibson, Frederick Denn, David Doelling, David Young

Proceedings Volume 1299, (1990) https://doi.org/10.1117/12.21380

KEYWORDS: Clouds, Satellites, Scanners, Shortwaves, Environmental sensing, Radiation effects, Climatology, Solar radiation, Spatial resolution, Calibration

Read Abstract +

Proceedings Article | 1 September 1990 Paper

Examination of the use of narrowband radiances for earth radiation budget studies

David Young, David Doelling, Patrick Minnis, Edwin Harrison

Proceedings Volume 1299, (1990) https://doi.org/10.1117/12.21381

KEYWORDS: Clouds, Humidity, Tantalum, Satellites, Infrared radiation, Data conversion, Data modeling, Data centers, Error analysis, Absorption

Read Abstract +

Showing 5 of 37 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years