Moderate Resolution Imaging Spectroradiometer Onboard Research Articles

Sentinel-3 SLSTR active fire (AF) detection and FRP daytime product - Algorithm description and global intercomparison to MODIS, VIIRS and landsat AF data

The Sea and Land Surface Temperature Radiometer (SLSTR) senses the Earth from onboard two concurrently operating European Copernicus Sentinel-3 (S3) satellites. As the Terra platform carrying the Moderate Resolution Imaging Spectroradiometer (MODIS) is reaching its end of life, the S3 Active Fire Detection and FRP products generated from data captured by S3 SLSTR are expected to soon become the main global active fire (AF) product for the mid-morning and evening low Earth orbit timeslots. The S3 night-time AF product issued by the European Space Agency (ESA) has been operational since March 2020, and here we report on the significant adjustments made to enable the generation of a complimentary daytime product. Similar to MODIS, SLSTR possesses two middle infrared channels, both a ‘standard’ (normal gain; S7) channel and a ‘fire’ (low-gain; F1) channel - but in contrast to MODIS by day even the ambient background land surface is often saturated in the SLSTR standard gain MIR (S7) channel. This saturation necessitates far greater use of the F1 channel data by day for active fire detection than by night, even though F1 has characteristics which make its data more challenging to combine with that from the other SLSTR thermal infrared channels. Here we report on the approaches used to combine S7 and F1 data for optimized daytime AF detection, and also detail the other algorithm adjustments found necessary to include in the daytime AF product algorithm. We compare the resulting daytime SLSTR AF product data to that generated from near-simultaneous views provided by MODIS onboard Terra. When both sensors detect the same active fire cluster at similar time, there is minimal bias shown between the two FRP retrievals (the ordinary least squares linear best fit between matched SLSTR and MODIS per-fire FRP matchups has a slope of 0.97). At the regional scale, the S3 product detects 70% of the AF pixels that the matching MODIS product reports, but also provides a further (16%) set of unique AF pixel detections. Regional FRP totals derived from SLSTR appear slightly lower than those from MODIS, and the OLS linear best fit between these regional FRP matchup datasets has a slope of 0.91. This is largely due to SLSTR performing less well in detecting the lowest FRP fires by day, whereas by night the S3 product performs a little better than MODIS due to the increased night-time use of S7 in the earlier AF pixel detection stages. Global fire mapping at a 0.25° grid cell resolution shows very similar daytime fire patterns and FRP totals from S3 and Terra MODIS, with SLSTR detecting around twice the number of AF pixels due to the algorithm being more effective at identifying low FRP pixels at the edges of fire clusters. Regional time series case studies also show very similar temporal patterns between S3 and Terra MODIS. Longer-term intercomparisons such as these will provide the knowledge necessary to use MODIS and SLSTR AF products together to analyse long-term AF trends. Comparing near simultaneous observations of fires by SLSTR and from the 30 m spatial resolution Landsat Operational Land Image (OLI) data, we find that once there are around 150 OLI active fire pixels detected within the area of an SLSTR pixel, the chances of that SLSTR pixel being classed as an active fire by the daytime algorithm rises to almost 100%. The daytime SLSTR AF Detection and FRP product based on the algorithm described herein has been fully operational since March 2022 and is available from the Sentinel-3 Science Hub (https://scihub.copernicus.eu/).

Satellite estimates of the long-term trend in phytoplankton size classes in the coastal waters of north-western Bay of Bengal

The study presents long-term variability in satellite retrieved phytoplankton size classes (PSC) at two coastal sites, off Gopalpur and Visakhapatnam, in the north-western Bay of Bengal. The abundance-based models by Brewin et al. (2010) (B10) and Sahay et al. (2017) (S17), for retrieval of PSC (micro, nano, and picophytoplankton), from satellite data, were validated. Both the models performed well in the retrieval of nano and microphytoplankton. However, B10 performed poorly in retrieving picophytoplankton. The statistical analysis indicated better performance of the S17 model and hence was applied to Moderate Resolution Imaging Spectroradiometer onboard Aqua satellite (MODISA) data to understand the temporal (at monthly climatology) and spatial variability (from nearshore to offshore). The spatial distribution indicated nearshore dominance of micro and offshore dominance of picophytoplankton. In nearshore waters off Gopalpur, microphytoplankton dominated throughout the year except for months of south-west monsoon (June and July) where the dominance of picophytoplankton was observed. All PSC exhibited similar distribution at an annual scale with a primary peak during pre-monsoon (March and April) and a secondary peak during post-monsoon (September–November). However, microphytoplankton concentration during post-monsoon was higher off Gopalpur in comparison to Visakhapatnam. The higher microphytoplankton concentration during pre-monsoon was attributed to recurrent phytoplankton blooms. Whereas, post-monsoon increment could be attributed to enhanced phytoplankton growth by availing nutrients sourced from monsoonal precipitation induced terrigenous influx. The outcome of the present study recommends the use of the S17 model for satellite retrieval of PSC from the north-western Bay of Bengal.

Satellite Retrieved Spatio-temporal Variability of Phytoplankton Size Classes in the Arabian Sea

The long-term trend in satellite retrieved phytoplankton size classes (PSC) such as picophytoplankton (PP), nanophytoplankton (NP), and microphytoplankton (MP) was studied in the three zones falling under different ecological provinces in open ocean regions of the Arabian Sea. A regionally tuned three-component “abundance” model was used to compute PSC biomass from Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODISA) satellite data for the period of 17 years (2003 to 2019). The overall trend indicated the highest concentration of all PSC in the northern Arabian Sea (ARAB province) which gradually decreased to the southern region (MONS province). All PSC biomass showed a peak during the winter monsoon period in ARAB province attributed to the recurring algal bloom. The long-term temporal trend showed relatively lower concentration (most of the times PP > NP in ARAB. In contrast, MONS displayed PSC rank order as PP > NP > MP. A sharp decline in the concentration of MP biomass was observed during the onset of summer monsoon period in comparison with other PSC in MONS.

Monitoring bio-optical response of coastal waters surrounding the Indian subcontinent to atmospheric dust deposition using satellite data.

The paper investigates the impact of atmospheric dust deposition on ocean biological productivity in association with oceanic supply of nutrients over specific regions of the Arabian Sea (20°N, 69°E) and the Bay of Bengal (20°N, 87°E) during wintertime (November-March) from the year 2012 to 2017 using satellite-based observations. During winter, selected regions are characterized by higher Chlorophyll-a (Chl-a) and major oceanic vertical supply of nutrients. Moderate Resolution Imaging Spectroradiometer onboard Aqua space-platform is used to obtain Chl-a and aerosol optical depth (AOD) data. Blended Chl-a daily product from various satellite sensors is also used. There are a total of nine cases (seven cases of the Arabian Sea region and two cases of the Bay of Bengal region) where episodic Chl-a enhancements following high AOD values are observed. Chl-a maxima lag behind AOD maxima by 1 to 4days. Modern-Era Retrospective analysis for Research and Applications (Version-2) is used for AOD and dust deposition flux estimation. Estimated dust deposition flux ranges between 0.44 and 27.68mgm-2day-1.

A Simple Approximation for the Reflectance of a Thick Cloud in Gaseous Absorption Band and Its Application for the Cloud-Top Height Determination

This paper presents a new, simple, fast method to retrieve cloud altitude from measurements of light absorption in the strongest molecular band of oxygen (the A-band), centered at 761 nm, by the polarization and directionality of the earth’s reflectance sensor. First, we assess the validity of the method against synthetic spectra as a function of realistic cloud scenarios and satellite observation geometries. The retrieval error estimate amounts, on average, to less than 500 m. Second, the hurricane Ileana, overpassed the August 30, 2012, off the coasts west of Mexico and Southern California, is selected as test bed for the comparison of our retrievals against independent and nearly coincident cloud data inferred with the Moderate Resolution Imaging Spectroradiometer onboard Aqua and the Global Ozone Monitoring Experiment 2 onboard MetOp-A. We find that our approach can accurately reproduce the cloud height patterns, as long as the clouds are not thin cirrus.

The dynamic observation of dissolved organic matter in the Zhujiang (Pearl River) Estuary in China from space

The distributions of estuarine colored dissolved organic matter (CDOM) are the combined results of physicalbiogeochemical processes. Remote sensing is needed to monitor highly dynamically estuarine CDOM. Using in situ data from four seasonal cruises, an algorithm is developed to estimate CDOM absorption coefficient at 400 nm (aCDOM(400)) in the Zhujiang (Pearl River) Estuary (ZJE). The algorithm uses band ratios of Rrs(667)/Rrs(443) and Rrs(748)/Rrs(412). By applying it to moderate resolution imaging spectroradiometer onboard Aqua satellite (MODIS/Aqua) data from 2002 to 2014, seasonal climatology aCDOM(400) in the ZJE is calculated. CDOM distributions are majorly influenced by water discharge from the Zhujiang River and underwater topography. Along the section vertical to a water depth gradient, the seasonal aCDOM(400) exponentially decreased (y=aebx, b<0), but with great differences among seasons. Riverine fresh water is the primary source of CDOM in the ZJE. Fulvic acid fraction decreases with increasing salinity. Using developed algorithms, conservative CDOM mixing equation, and river discharge, effective riverine end-member concentration and flux of dissolved organic carbon (DOC) in summer and winter from 2002 to 2014 are first estimated from the MODIS/Aqua data. Both effective riverine end-member DOC concentration and flux are positively related to the river discharge, significantly in summer with R2 of 0.698 for concentration and 0.965 7 for flux.

Underway sampling of marine inherent optical properties on the Tara Oceans expedition as a novel resource for ocean color satellite data product validation

Developing and validating data records from operational ocean color satellite instruments requires substantial volumes of high quality in situ data. In the absence of broad, institutionally supported field programs, organizations such as the NASA Ocean Biology Processing Group seek opportunistic datasets for use in their operational satellite calibration and validation activities. The publicly available, global biogeochemical dataset collected as part of the two and a half year Tara Oceans expedition provides one such opportunity. We showed how the inline measurements of hyperspectral absorption and attenuation coefficients collected onboard the R/V Tara can be used to evaluate near-surface estimates of chlorophyll-a, spectral particulate backscattering coefficients, particulate organic carbon, and particle size classes derived from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODISA). The predominant strength of such flow-through measurements is their sampling rate—the 375 days of measurements resulted in 165 viable MODISA-to-in situ match-ups, compared to 13 from discrete water sampling. While the need to apply bio-optical models to estimate biogeochemical quantities of interest from spectroscopy remains a weakness, we demonstrated how discrete samples can be used in combination with flow-through measurements to create data records of sufficient quality to conduct first order evaluations of satellite-derived data products. Given an emerging agency desire to rapidly evaluate new satellite missions, our results have significant implications on how calibration and validation teams for these missions will be constructed.

Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

Cloud properties have been retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) over 12 years of continuous observations from Terra and over nine years from Aqua. Results include the spatial and temporal distribution of cloud fraction, the cloud top pressure and cloud top temperature, and the cloud optical thickness and effective radius of both liquid water and ice clouds. Globally, the cloud fraction derived by the MODIS cloud mask is ~ 67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, the cloud fraction over land is ~ 55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to afternoon deep convection. The coldest cloud tops (colder than 230 K) generally occur over Antarctica and the high clouds in the tropics. The cloud effective particle radius of liquid water clouds is significantly larger over ocean (mode 12-13 μm) than land (mode 10-11 μm), consistent with the variation in hygroscopic aerosol concentrations that provide cloud condensation nuclei necessary for cloud formation. We also find the effective radius to be 2-3 μm larger in the southern hemisphere than in the northern hemisphere, likely reflecting differences in sources of cloud condensation nuclei.

On-Orbit Spatial Characterization of MODIS With ASTER Aboard the Terra Spacecraft

This letter presents a novel approach for on-orbit characterization of MODerate resolution Imaging Spectroradiometer (MODIS) band-to-band registration (BBR) using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra spacecraft. The spatial resolution of ASTER spectral bands is much higher than that of MODIS, making it feasible to characterize MODIS on-orbit BBR using their simultaneous observations. The ground target selected for on-orbit MODIS BBR characterization in this letter is a water body, which is a uniform scene with high signal contrast relative to its neighbor areas. A key step of this approach is to accurately localize the measurements of each MODIS band in an ASTER measurement plane coordinate (AMPC). The ASTER measurements are first interpolated and aggregated to simulate the measurements of each MODIS band. The best measurement match between ASTER and each MODIS band is obtained when the measurement difference reaches its weighted minimum. The position of each MODIS band in the AMPC is then used to calculate the BBR. The results are compared with those derived from MODIS onboard Spectro-Radiometric Calibration Assembly. They are in good agreement, generally less than 0.1 MODIS pixel. This approach is useful for other sensors without onboard spatial characterization capability.

MODIS Onboard Blackbody Function and Performance

Two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments are currently in orbit, making continuous global observations in visible to long-wave infrared wavelengths. Compared to heritage sensors, MODIS was built with an advanced set of onboard calibrators, providing sensor radiometric, spectral, and spatial calibration and characterization during on-orbit operation. For the thermal emissive bands (TEB) with wavelengths from 3.7 to 14.4 mum, a v-grooved blackbody (BB) is used as the primary calibration source. The BB temperature is accurately measured each scan (1.47 s) using a set of 12 temperature sensors traceable to the National Institute of Standards and Technology (NIST) temperature standards. The onboard BB is nominally operated at a fixed temperature, 290 K for Terra MODIS and 285 K for Aqua MODIS, to compute the TEB linear calibration coefficients. Periodically, its temperature is varied from 270 K (instrument ambient) to 315 K in order to evaluate and update the nonlinear calibration coefficients. This paper describes MODIS onboard BB functions with emphasis on on-orbit operation and performance. It examines the BB temperature uncertainties under different operational conditions and their impact on TEB calibration and data product quality. The temperature uniformity of the BB is also evaluated using TEB detector responses at different operating temperatures. On-orbit results demonstrate excellent short-term and long-term stability for both the Terra and Aqua MODIS onboard BB. The on-orbit BB temperature uncertainty is estimated to be 10 mK for Terra MODIS at 290 K and 5 mK for Aqua MODIS at 285 K, thus meeting the TEB design specifications. In addition, there has been no measurable BB temperature drift over the entire mission of both Terra and Aqua MODIS.

On the Use of CloudSat and MODIS Data for Estimating Hurricane Intensity

This letter presents preliminary results concerning the use of new observations from the A-Train Constellation for testing a new technique of remotely sensing hurricane intensity from space based on modeling a hurricane as a balanced, convectively neutral vortex. The key observational requirements are simultaneous, accurate measurements of cloud-top height, cloudtop temperature, and cloud profiling information across the center of the storm, although there are ways to bypass the need for cloud-top temperature. In this letter, the Moderate Resolution Imaging Spectroradiometer onboard Aqua provides an estimation of the cloud-top temperature, and the near-simultaneous CloudSat observations provide the essential cloud-top height and cloud profiling information. Initial results indicate that the new technique is a promising method for estimating storm intensity when compared post facto to the best track database. Potential uncertainties and room for further refinement of the technique are discussed.