Session | ||
WS#1 ID.32426: Calibration and Data Quality
| ||
Presentations | ||
Oral
ID: 323 / WS#1 ID.32426: 1 Oral Presentation Atmosphere, Climate & Carbon: 32426 - Calibration and Data Quality Assurance for Quantitative Remote Sensing On-obit Optical Sensor Radiometric Benchmark Transfer Calibration Technique 1Academy of Opto-Electronics,Chinese Academy of Sciences, China, People's Republic of; 2National Physical Laboratory (NPL), UK; 3National Institute of Metrology (NIM), China; 4European Space Agency, Noordwijk, The Netherlands To promote the radiometric quality of satellite remote sensing products and assure the comparability of product quality amongst multi-series satellites, we should build a continuous transfer chain from remote sensor to the radiometric reference standard, estimate those parameters characterizing sensor’s performance, and conduct quality controls on remote sensing data and products during sensor lifetime. However, when the sensor is on-orbit, its radiometric quality is usually hard to be traced to SI because of breakage of the reference transfer chain. The traditional field vicarious radiometric calibration method which uses ground target measurement value as radiometric reference, can be influenced by various uncertainties due to scaling effect, atmospheric condition, environment change, etc., so it is hard to reach high calibration accuracy. In pursuit of on-orbit optical sensor high-accuracy calibration and product quality consistence, we carried out the following exploratory work: Oral
ID: 205 / WS#1 ID.32426: 2 Oral Presentation Atmosphere, Climate & Carbon: 32426 - Calibration and Data Quality Assurance for Quantitative Remote Sensing Investigations into the Development of a Satellite-Based Aerosol Climate Data Record using ATSR-2, AATSR and AVHRR data 1Finnish Meteorological Institute (FMI), Finland; 2Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (RADI/CAS), Beijing, P.R. China Long-term aerosol data records provide information on changes in the aerosol properties due to both natural (meteorological, climatological, dust storm, fires) and anthropogenic effects (such as industrialization, urbanization and policy measures aimed at improvement of air quality). An often-used indicator for the aerosol burden is the aerosol optical depth (AOD), i.e. the column-integrated extinction coefficient. AOD can be monitored from satellites using radiometers, but instruments used for this purpose have a limited lifetime and often are not designed for aerosol monitoring. As part of the Aerosol-cci project, the Along Track Scanning Radiometer (ATSR-2) flying on the European Space Agency (ESA) ERS-2 satellite from 1995 to 2003 and the advanced ATSR (AATSR) flying on ESA’s ENVISAT (2002-2012) were used together to create a 17-years (1995-2012) global AOD data record over land and ocean (Popp et al., 2016). This data set is planned to be extended with AOD retrieved from the Sea and Land Surface Temperature Radiometer (SLSTR), an instrument similar to ATSR but with a backward instead of forward view, the first of which flies on Sentinel-3A launched in early 2016. However, this leaves a gap of about 4 years between the end of the AATSR and the start of the SLSTR data records. To fill this gap, we investigated the use of AOD data available from the application of the ALAD algorithm developed by RADI for AOD retrieval over land using data from the Advanced Very High Resolution Radiometer (AVHRR) (Xue et al., 2017). ALAD combines eight different AVHRR instruments to produce an AOD time series starting in 1983 (Xue et al., 2017). Hence, the ALAD AOD data set could also be used to extent the information from the ATSR data record backward from 1995 to 1983, provided that a satisfactory match can be obtained between the overlapping ATRS and AVHRR data sets. In this study we used ATSR AOD data produced with FMI’s Aerosol Dual View (ADV) algorithm (Kolmonen et al., 2016; Sogacheva et al., 2017) and ALAD data sets retrieved for the whole period from 1983 to 2014 over the North China Plain (NCP). In addition, MODIS-Terra AOD C6.1 data are used for comparison and ground-based sun photometer AOD data from AERONET (Holben et al., 1998) are used as reference. The validation versus AERONET shows the good performance of the AVHRR AOD up to about 0.5 and for ATSR up to about 1.3, which leads to large differences during high AOD episodes such as often observed over the NCP in the summer. However, during the winter, when AOD is often moderate, AVHRR provides better coverage. Part of the difference between AVHRR and ATSR AOD may be explained by the difference in wavelength between the ATSR- and AVHRR-retrieved AOD (550 nm and 630 nm, respectively). References Kolmonen, P., Sogacheva, L., Virtanen, T.H., de Leeuw, G. , and Kulmala, M.: The ADV/ASV AATSR aerosol retrieval algorithm: current status and presentation of a full-mission AOD data set, International Journal of Digital Earth, 9:6, 545-561, doi: 10.1080/17538947.2015.1111450, 2016. Popp, T., de Leeuw, G., Bingen, C., Brühl, C., Capelle, V., Chedin, A., Clarisse, L., Dubovik, O., Grainger, R., Griesfeller, J., Heckel, A., Kinne, S., Klüser, L., Kosmale, M., Kolmonen, P., Lelli, L., Litvinov, P., Mei, L., North, P., Pinnock, S., Povey, A., Robert, C., Schulz, M., Sogacheva, L., Stebel, K., Stein Zweers, D., Thomas, G., Tilstra, L.G., Vandenbussche, S., Veefkind, P., Vountas, M., and Xue, Y.: Development, production and evaluation of aerosol Climate Data Records from European satellite observations (Aerosol_cci), Remote Sens. 2016, 8, 421; doi:10.3390/rs8050421, 2016. Sogacheva, L., Kolmonen, P., Virtanen, T. H., Rodriguez, E., Saponaro, G., and de Leeuw, G.: Post-processing to remove residual clouds from aerosol optical depth retrieved using the Advanced Along Track Scanning Radiometer, Atmos. Meas. Tech., 10, 491-505, doi:10.5194/amt-10-491-2017, 2017. Xue, Y., He, X., de Leeuw, G., Mei, L., Che, Y., Rippin, W., Guang, J., Hu, Y. : Long-time series aerosol optical depth retrieval from AVHRR data over land in North China and Central Europe. Remote Sensing of Environment, 198: 471-489, 2017. Oral
ID: 179 / WS#1 ID.32426: 3 Oral Presentation Atmosphere, Climate & Carbon: 32426 - Calibration and Data Quality Assurance for Quantitative Remote Sensing Calibration, Validation and Retrievals on Satellite-based Microwave Instruments 1NSSC, China, People's Republic of; 2Earth and Environmental Sciences, Vanderbilt University, Nashville, US Different from the work last year, the paper develops a all-weather and all-day passive sub-millimeter precipitation retrievals algorithm for Microwave Humidity and Temperature Sounder (MWHTS) onboard the Chinese Feng Yun 3C (FY-3C) satellite. The retrieval algorithm employs a number of neural network estimators trained and evaluated using the validated global reference physical model NCEP/WRF/ARTS, and works for seawater. NCEP data per 6 hours are downloaded to run the Weather Research and Forecast model WRF, and derive the typical precipitation data from the whole world. The Atmospheric Radiative Transfer Simulator ARTS is feasible for performing simulations of atmospheric radiative transfer. Rain detection algorithm has been used to generate level 2 products. Retrievals are reliable for surface precipitation rate higher than 0.1 mm/h at 15km resolution, which is in good agreement with those retrieved using the Precipitation retrieval algorithm version 1(ATMP-1) for Advanced Technology Microwave Sounder (ATMS) aboard Suomi NPP satellite. Meanwhile, calibration and validation between similar instruments onboard different satellites are also important to ensure the validity of observations and accuracy of precipitation retrievals. In the ongoing work, we are going to carry out the calibration and validation among FY-3C MWHTS, FY-3B MWHS and ATMS,and some preliminary results can be shown in the conference materials. Oral
ID: 185 / WS#1 ID.32426: 4 Oral Presentation Atmosphere, Climate & Carbon: 32426 - Calibration and Data Quality Assurance for Quantitative Remote Sensing Progresses in Validating Satellite Products over Northern China Using Ground-based FTIR and MAX-DOAS Instruments in Xianghe and Xinglong Stations Institute of Atmospheric Physics, Chinese Academy of Sciences, China, People's Republic of A ground-based MAX-DOAS and a Bruker IFS 125HR have been deployed in Xianghe Station, Northern China, of the Institute of Atmospheric Physics, Chinese Academy of Sciences, and another Bruker IFS 125M has been installed in Xinglong Station. The MAX-DOAS has been running for more than ten years, providing a large number of high quality data of NO2, SO2, etc., for deriving their trends, and for validating the satellite products of OMI, GOME-2, and SCIMACHY. In Xianghe station, CIMEL sunphotometer, gas analyzers, automatic meteorological station, and a 100-meter tower can provide aerosol optical properties, air quality status, and meteorological conditions in the planet boundary layers. The two Bruker FTIR instruments in Xianghe and Xinglong stations aim at providing the greenhouse gas such as CO2, CH4, N2O, and for validating GOSAT, OCO-2, and TanSat products in future. The FTIR in Xinglong station has been operating for more than one year, and some data has been used for validation of GOSAT products. Some new progresses in validating satellite products over northern China using ground-based FTIR and MAX-DOAS instruments will be reported here. Poster
ID: 188 / WS#1 ID.32426: 5 Poster Atmosphere, Climate & Carbon: 32426 - Calibration and Data Quality Assurance for Quantitative Remote Sensing Preliminary Results of Optical Properties Intercomparison Study of the Nonspherical and Spherical Aggregates of Black Carbon Institute of Atmospherics, Chinese Academy of Sciences, China, People's Republic of Atmospheric aerosol optical remote sensing makes use of ultraviolet, visible and infrared sensors to collect information of the particles in atmosphere by detecting radiation scattered from targets. Black carbon (BC) is the most important light-absorbing aerosol in the current atmosphere because of its strong positive climate forcing from direct radiative and snow albedo effects. Both effects are significantly affected by BC optical properties. Observations have shown that BC particles have complex structures due to stochastic aggregating. Thus, a reliable remote sensing of BC aerosols and estimate of BC climatic effects requires accurate computations of optical properties for BC particles with complex structures. Currently most simulation methods employ single-sized spherical particle as primary spherule to construct the whole aggregates, this may introduce some extra uncertainty. In this study we use DDA method to compute optical properties of aggregates constructed by nonspherical and spherical particle with same structural parameters. Preliminary results are presented and show great differences exist between them, the results could be used for evaluating uncertainty introduced by particle modelling and calibrating results of remote sensing. Poster
ID: 321 / WS#1 ID.32426: 6 Poster Atmosphere, Climate & Carbon: 32426 - Calibration and Data Quality Assurance for Quantitative Remote Sensing Uncertainty Analysis of the Automated Radiometric Calibration over Baotou Cal&Val Site in China 1Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences; 2National Physical Laboratory, Hampton Road, Teddington, Middlesex, TW11 0LW, UK; 3National Institute of Metrology, Beijing, China The Baotou site is one of four instrumented sites being established as part of the Radiometric Calibration Network (RadCalNet). RadCalNet is an initiative of the CEOS WGCV. It has been designed to provide satellite operators with SI (Système International d'Unités)-traceable top-of-atmosphere (TOA) spectrally-resolved reflectances from a coordinated network of instrumented land-based test sites. An automated radiometric calibration system was established on the Baotou Cal&Val test site in China to provide an operational high-accuracy and high-stability vicarious calibration and validation site for high resolution remote sensing instruments. Poster
ID: 220 / WS#1 ID.32426: 7 Poster Atmosphere, Climate & Carbon: 32426 - Calibration and Data Quality Assurance for Quantitative Remote Sensing Tropospheric nitrogen dioxide retrieval from the TROPOMI instrument and ground-based MAX-DOAS validation University of Science and Technology of China, China, People's Republic of Here we applied our tropospheric nitrogen dioxide (NO2) retrieval algorithm, which was implemented for the Chinese Environmental trace gases Monitoring Instrument (EMI), to the TROPOspheric Monitoring Instrument (TROPOMI). Generally, the Differential Optical Absorption Spectroscopy (DOAS) technique was used to retrieve slant column densities (SCDs) of NO2, and air mass factor (AMF) are calculated for light path correction. The solar and viewing geometries, surface albedo and pressure, cloud properties, and modelled gas profile was used as input parameters for online AMF calculations. The tropospheric NO2 was estimated from the total column by using the modified reference sector method. Results show good agreements with independent ground-based MAX-DOAS measurements. |