Aqua MODIS Research Articles

Chlorophyll a Concentration Distribution on the Mainland Coast of the Gulf of California, Mexico

Coastal zones are important areas for the development of diverse ecosystems. The analysis of chlorophyll a (Chl a), as an indicator of primary production in these regions, is crucial for the quantification of phytoplankton biomass, which is considered the main food chain base in the oceans and an indicator of the trophic state index. This variable is greatly important for the analysis of the oceanographic variability, and it is crucial for determining the tendencies of change in these areas with the objective of determining the effects on the ecosystem and the population dynamics of marine resources. In this study, we analysed the Chl a concentration distribution on the mainland coast of the Gulf of California based on the monthly data from July 2002 to July 2019, obtained from remote sensing (Moderate-Resolution Imaging Spectroradiometer Aqua (MODIS-Aqua) with a 9 km resolution). The results showed a clear distribution pattern of Chl a observed along this area with the maximum levels in March and minimum levels in August. A four-region characterisation on this area was used to make a comparison of the Chl a concentrations during warm and cold periods. The majority of the results were statistically significant. The spectral analysis in each of the four regions analysed in this study determined the following variation frequencies: annual, semi-annual, seasonal, and inter-annual; the last was related to the macroscale climatological phenomena El Niño-La Niña affecting the variability of the Chl a concentration in the study region.

Stability Assessment of OCO-2 Radiometric Calibration Using Aqua MODIS as a Reference

With three imaging grating spectrometers, the Orbiting Carbon Observatory-2 (OCO-2) measures high spectral resolution spectra ( λ / Δ λ ≈ 19,000) of reflected solar radiation within the molecular oxygen (O 2 ) A-band at 0.765 μ m and two carbon dioxide (CO 2 ) bands at 1.61 and 2.06 μ m. OCO-2 uses onboard lamps with a reflective diffuser, solar observations through a transmissive diffuser, lunar measurements, and surface targets for radiometric calibration and validation. Separating calibrator aging from instrument degradation poses a challenge to OCO-2. Here we present a methodology for trending the OCO-2 Build 8R radiometric calibration using OCO-2 nadir observations over eight desert sites and nearly simultaneous observations from Moderate Resolution Imaging Spectroradiometer (MODIS) with sensor viewing zenith angles of 15 ± 0.5 ∘ . For the O 2 A-band, this methodology is able to quantify a drift of −0.8 ± 0.1% per year and capture a small error in correcting the aging of the solar calibrator. For the other two OCO-2 bands, no measurable changes were seen, indicating less than 0.1% and less than 0.3% per year drift in the radiometric calibration of Band 2 and Band 3, respectively.

Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence

The similarity of mesoscale and submesoscale features observed in different ocean scalars indicates that they undergo some common non-linear processes. As a result of quasi-2D turbulence, complicated patterns of filaments, meanders, and eddies are recognized in remote sensing images. A data fusion method used to improve the quality of one ocean variable using another variable as a template is used here as an extrapolation technique to improve the coverage of daily Aqua MODIS Level-3 chlorophyll maps by using MODIS SST maps as a template. The local correspondence of SST and Chl-a multifractal singularities is granted due to the existence of a common cascade process which makes it possible to use SST data to infer Chl-a concentration where data are lacking. The quality of the inference of Level-4 Chl-a maps is assessed by simulating artificial clouds and comparing reconstructed and original data.

Trends of Climate Variables and Aerosol optical Depth in Thailand

This study analysed climate variables data in four stations over Thailand. Aerosol optical depth (AOD) obtained from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) were also used to determine climatic trends in the areas under focus. The linear regression, Mann-Kendall trend, and Sen’s slope tests were applied. Rain (R) gave higher values in July to October for most regions except in the Songkhla. Amount of R increased in all regions. Rainy season is caused by the Southwest monsoon, which is a normal occurrence in Thailand from June to September. However, this monsoon tended to begin earlier and last longer (May to October) than expected. Mean temperature (Tmean) values were found to be significantly higher from March to May and increased in all stations. The highest significant increases of annual Tmean were found in the North. There was no significant trend in annual R (Rainfall) at the 1% and 5% significance level in all stations. The AOD values were likely to increase in almost all stations. The highest significant increase of annual AOD was observed in Ubon Ratchathani.

Primary productivity connects hilsa fishery in the Bay of Bengal

Tropical hilsa shad (Tenualosa ilisha) contributes significantly to the society and economy of Bangladesh, India and Myanmar, but little is known about their habitats across the life cycle and their relationship with environmental drivers. This study describes spatial and temporal variability of productivity in the Bay of Bengal (BoB) relating to hilsa fishery. Decadal data on net primary productivity, nutrients (i.e. nitrate, phosphate and silicate) and zooplankton were collected from Aqua MODIS, world ocean database and COPEPOD respectively with spatial resolution 1°×1°. Moreover, monthly abundance of phytoplankton, hilsa catch and long-term catch dynamics were analyzed to determine the associations between variables. The present study was extended over 3.568 million km2 area, of which 0.131–0.213 million km2 area characterized as the most productive with net primary production of >2,000 mg C/m2/day, 0.373–0.861 million km2 area as moderately productive with 500–2,000 mg C/m2/day, and 2.517–3.040 million km2 area as the least productive with <500 mg C/m2/day which were consistent with field verification data. In case of nutrients, the Ganges-Brahmaputra-Meghna (GBM) delta was rich in nitrate and phosphate than that of the Ayeyarwady delta, while silicate concentration persisted high all over the northern BoB including the deltas. A peak abundance of phytoplankton was observed in GBM delta during the months of August-November, when ~80% of total hilsa are harvested in Bangladesh annually. Variations in seasonal productivity linked with nutrients and phytoplankton abundance are important factors for predicting hilsa habitat and their migration patterns in the deltaic regions and shelf waters of BoB. These results can be useful in forecasting potential responses of the hilsa in BoB ecosystem to changing global ocean productivity.

Comparative evaluation of VIIRS daily snow cover product with MODIS for snow detection in China based on ground observations

Accurate spatiotemporal information of snow cover not only is important for investigating the mechanisms of climate change but also greatly contributes to hydrological modelling in mountainous regions. The Suomi-National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) (referred to as VNP) daily snow cover product is recently released and expected to take place of Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products in near future. As an important addition to the widely used MODIS products, there is also an urgent need for a reliable accuracy evaluation and comparison of VNP for future large-scale daily snow cover mapping. This study for the first time evaluates the accuracy of VNP daily snow cover data in China using daily snow depth observations from 330 stations. The accuracy of VNP data is generally good with the averaged CK (Cohen's Kappa) and FS (F-Score) as high as 0.72 and 0.75, respectively, but considerably decreases to 0.50 and 0.52 for the Tibetan Plateau. VNP shows slightly better accuracy than MODIS TERRA for stations outside the Tibetan Plateau owing to its higher spatial resolution, but its accuracy is lower than TERRA for those within the Tibetan Plateau possibly due to its longer time interval between ground observation and satellite overpass time. By contrast, VNP shows much better accuracy than MODIS AQUA in China including both outside and within the Tibetan Plateau. This study provides important implications for optimal use of VNP and MODIS daily snow cover products in China, which may further contribute to more accurate snow variation information for climate analysis and cryospheric hydrological modelling.

Cross-Calibration of Terra and Aqua MODIS Using RadCalNet

Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard the Terra and Aqua spacecraft have been successfully operating for nearly two decades and providing complementary observations of the Earth's land, ocean, and atmosphere. Although the two MODIS instruments view the entire Earth's surface once every 2-3 days, simultaneous views between them are limited due to their varying orbits. Therefore, the intercomparison between these two instruments has been previously performed using a transfer instrument [such as Advanced Very-high-resolution Radiometer (AVHRR)] or using lunar measurements normalized using a common model, such as the USGS Robotic Lunar Observatory (ROLO). In recent years RadCalNet, a Committee on Earth Observation Satellites (CEOS) initiative, has provided SI-traceable Top-of-Atmosphere (TOA) reflectances from a coordinated network of instrumented land-based sites. RadCalNet facilitates a unique mechanism to perform cross-calibration of instruments by minimizing the uncertainties associated with overpass time differences. In this letter, the near-simultaneous TOA reflectance measurements from the Railroad Valley (RRV), US (RVUS) are used as a transfer to compare the on-orbit observations for the Terra and Aqua MODIS reflective solar bands (RSBs). Near-nadir overpasses from January 2013 to January 2019 are processed and matched up with near-simultaneous RadCalNet measurements. Results show that the visible (VIS)/near-infrared response (NIR) bands agree to within 2%, and the short-wave infrared (SWIR) bands agree to within 5%. Also discussed in this letter are the future efforts that will be undertaken to expand this comparison to include other instruments, other sites, and both nadir- and off-nadir views after compensation for bidirectional reflectance distribution function (BRDF) effects.

Mathematical Models Selection on the Total Suspended Solid Mapping using Reflective Satellite Image Data

Ujung Pangkah Gresik is a reasonably dynamic area in the growth of turbidity levels in coastal beaches. As an area that has the estuary of the River Bengawan Solo, then Ujung Pangkah each year will experience the sedimentation process, one of which is the result of the movement of the river flow. This study aims to find the best mathematical model as an illustration of the total dynamics of the dissolved solids occurring in the area. The method used is a linear regression analysis of several selected models such as linear model, exponent, logarithm, polynomial degree 2, polynomial degree 3 and power model. The independent variable used in this research is the reflectance value of the Aqua Modis Level 2 from satellite imagery at wavelength 412 nm, 531 nm, and 645 nm. The results obtained from this study are the ability of Aqua Modis satellite imagery in mapping the total suspended solids, besides that it can also be used to predict changes in the total value of suspended solids by calculating remote sensing algorithms that produce optimal mathematical models, where the model used is the polynomial model degree 3 and the logarithmic model based on choosing a high correlation value of the model that is 0.75 obtained at a wavelength of 645 nanometers

Compositing the Minimum NDVI for Daily Water Surface Mapping

Capturing high frequency water surface dynamics via optical remote sensing is important for understanding hydro-ecological processes over seasonally flooded wetlands. However, it is a difficult task due to the presence of clouds on satellite images. This study proposed the MODerate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) Minimum Value Composite (MinVC) algorithm to generate daily water surface data at a 250-m resolution. The algorithm selected pixelwise minimum values from the combined daily Terra and Aqua MODIS NDVI data within a 15-day moving window. Consisting mainly of cloud and water surface information, the MinVC NDVI data were segmented for water surfaces over the Poyang Lake, China (2000–2017) by using an edge detection model. The water surface mapping result was strongly correlated with the Landsat based result (R2 = 0.914, root mean square error, RMSE = 223.7 km2), the cloud free MODIS image based result (R2 = 0.824, RMSE = 356.7 km2), the recent Landsat-MODIS image fusion based result (R2 = 0.765, RMSE = 403 km2), and the hydrodynamic modeling result (R2 = 0.799). Compared to the equivalent eight-day MOD13 NDVI based on the Constraint View-Angle Maximum Value Composite (CV-MVC) algorithm, the daily MinVC NDVI highlighted water bodies by generating spatially homogenous water surface information. Consequently, the algorithm provided spatially and temporally continuous data for calculating water submersion times and trends in water surface area, which contribute to a better understanding of hydro-ecological processes over seasonally flooded wetlands. Within the framework of sensor intercalibration, the algorithm can be extended to incorporate multiple sensor data for improved water surface mapping.

An improved Terra–Aqua MODIS snow cover and Randolph Glacier Inventory 6.0 combined product (MOYDGL06*) for high-mountain Asia between 2002 and 2018

Abstract. Snow is a significant component of the ecosystem and water resources in high-mountain Asia (HMA). Therefore, accurate, continuous, and long-term snow monitoring is indispensable for the water resources management and economic development. The present study improves the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites 8 d (“d” denotes “day”) composite snow cover Collection 6 (C6) products, named MOD10A2.006 (Terra) and MYD10A2.006 (Aqua), for HMA with a multistep approach. The primary purpose of this study was to reduce uncertainty in the Terra–Aqua MODIS snow cover products and generate a combined snow cover product. For reducing underestimation mainly caused by cloud cover, we used seasonal, temporal, and spatial filters. For reducing overestimation caused by MODIS sensors, we combined Terra and Aqua MODIS snow cover products, considering snow only if a pixel represents snow in both the products; otherwise it is classified as no snow, unlike some previous studies which consider snow if any of the Terra or Aqua product identifies snow. Our methodology generates a new product which removes a significant amount of uncertainty in Terra and Aqua MODIS 8 d composite C6 products comprising 46 % overestimation and 3.66 % underestimation, mainly caused by sensor limitations and cloud cover, respectively. The results were validated using Landsat 8 data, both for winter and summer at 20 well-distributed sites in the study area. Our validated adopted methodology improved accuracy by 10 % on average, compared to Landsat data. The final product covers the period from 2002 to 2018, comprising a combination of snow and glaciers created by merging Randolph Glacier Inventory version 6.0 (RGI 6.0) separated as debris-covered and debris-free with the final snow product MOYDGL06*. We have processed approximately 746 images of both Terra and Aqua MODIS snow containing approximately 100 000 satellite individual images. Furthermore, this product can serve as a valuable input dataset for hydrological and glaciological modelling to assess the melt contribution of snow-covered areas. The data, which can be used in various climatological and water-related studies, are available for end users at https://doi.org/10.1594/PANGAEA.901821 (Muhammad and Thapa, 2019).

Imprints of atmospheric waves on the Black Sea surface in data of ocean color scanners

Data from MERIS onboard Envisat and MODIS onboard Terra and Aqua for 15–16 May 2010 were used to study powerful imprints of atmospheric gravity waves (AGWs) on the western part the Black Sea surface. Two cold fronts crossed the sea following the warm front and caused the AGWs which modulated the sea surface. Imprints of AGWs appeared as stripes of alternating brightness, they had crest length more than a hundred kilometers and wavelength of units of kilometers. Wave amplitude of AGWs imprints, evaluated by a 90%-depth of light penetration into the sea at 490 nm z90, the value inverse to the diffuse attenuation coefficient Kd_490, was units of decimeterxs. MODIS 250-m data of remote sensing reflectance, wind components and atmospheric pressure near the sea surface were obtained by processing the top of atmosphere data with the SeaDAS software package. Negative correlations of fluctuations of z90 with fluctuations of wind stress and atmospheric pressure were found on the transects of more than ten kilometers. The impact of wind stress on the origination of AGW imprints was found to be determinant, while the impact of atmospheric pressure was not more than units of percent.

Comparison of the MODIS and VIIRS Thermal Emissive Band Radiometric Calibration

Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) are major instruments for Earth science observations. Nearly 40 MODIS scientific products and a wide range of VIIRS environmental data records are produced using their global observations. The consistency of the MODIS and VIIRS calibrated data is important for the study of Earth science. This article assesses the calibration consistency of the Aqua MODIS and VIIRS thermal emissive band (TEB) data. To remove the impact of the mismatched relative spectral response (RSR) on the comparisons, the simultaneous nadir observation data from the cross-track infrared sounder (CrIS) and the infrared atmospheric sounding interferometer (IASI) are used as references in two different methods to independently verify the consistency. The comparisons of the MODIS and VIIRS TEB calibrated data show that the brightness temperature (BT) differences for comparable bands between MODIS and VIIRS are in general within 0.2 K for BT larger than 230 K. The differences of all comparable MODIS and VIIRS TEBs are consistent over time. MODIS measurements agree better with N20 VIIRS than with Suomi National Polar-orbiting Partnership (S-NPP) VIIRS. The S-NPP VIIRS measurements are higher than N20 VIIRS, within 0.1 K for long-wave infrared (LWIR) bands and 0.3 K for band M13.

Changes in Land Use in the Lombok River Basin and Their Impacts on River Basin Management Sustainability

Sustainable management in water resources development strategies depends on the knowledge of phenomena of changes in land use in the river basin as a significant tool in understanding the interactions of environment and human activities. Changes that occur within a certain period on the land cover or land use impacts the basin characteristics, which will ultimately affect river basin management. This paper studies the change of land use in the Lombok river basin in Indonesia based on the Moderate Resolution Imaging Spectroradiometer (MODIS) land use/land cover data version 6 from the years of 2001, 2010, and 2016 which were derived using MODIS Terra and Aqua reflectance supervised classification data. Land use data was then classified into fifteen land use categories according to SWAT classification. QGIS and MapWindow software were applied to analyse the features of land use in the study area, and the SWAT simulation model was applied to simulate the impacts of changing land use in the sub-basin. The study concludes that areas with occurrences of changes in land use impacted the river runoff in the sub-basin. Analysis of river basin land use, when combined with simulation in water resources management, will contribute to optimal and sustainable river basin planning.

ANALYSIS OF UTILIZATION CHLOROPHYLL-A CONCENTRATION DATA FROM REMOTE SENSING IMAGERY TO SUPPORT MARITIME SECURITY OPERATIONS (CASE STUDIES IN THE ARAFURA SEA)

Indonesia is the largest archipelago in the world with a vast ocean area and the richness of the fish. It allows theoccurrence of crime at sea, for example, is a crime of theft of fish and other marine resources. Indonesia in theregard Indonesian Navy confronted with various obstacles, among others, the limitation of the number of patrolboats that are not proportional to the extent of waters that should be on the cover as well as the limitations ofthe available budget for operational activities in the framework of the implementation of law enforcementoperations related crime at sea. With the limitation of that than required effectiveness and efficiency inoperations to crime at sea can still be implemented and the richness of the sea remains awake.The utilization ofremote sensing satellite technology capable of delivering information quickly with a broad scope. This researchuse the MODIS Aqua Image data Level 2 to detect the distributions of chlorophyll-a concentration which is anindicator of the fertility of the waters of an area the area is closely connected with the fisheries through theimplementations process of bottom-up areas with transparent high fertility rate is an area that's prone to fishtheft crime occurred. From the result of the data processing MODIS-Aqua Satellite image pattern time andlocation of the concentration of chlorophyll-a and verified by VMS data indicate that there is a close relationshipwhere a times and areas with a high concentration of chlorophyll observed a lot of fishing activity, so it is used inthis research can be used as supporting data in determining the direction and timing of the operation inparticular operations against crimes the theft of fish, finally the marine security operations could become moreeffective and efficient and success can be further improved.Keywords: Sea area, chlorophyll-a, effective and efficient.

Surface Temperature of the Planet Earth from Satellite Data

The Intergovernmental Panel on Climate Change regular scientific assessments of global warming is based on measurements of air temperature from weather stations, buoys or ships. More specifically, air temperature annual means are estimated from their integration into climate models, with some areas (Africa, Antarctica, seas) being clearly underrepresented. Present satellites allow estimation of surface temperature for a full coverage of our planet with a sub-daily revisit frequency and kilometric resolution. In this work, a simple methodology is developed that allows estimating the surface temperature of Planet Earth with MODIS Terra and Aqua land and sea surface temperature products, as if the whole planet was reduced to a single pixel. The results, through a completely independent methodology, corroborate the temperature anomalies retrieved from climate models and show a linear warming trend of 0.018 ± 0.007 °C/yr.

An Inherent Optical Properties Data Processing System for Achieving Consistent Ocean Color Products From Different Ocean Color Satellites

AbstractWe used field measurements and multimission satellite data to evaluate how well an inherent optical properties (IOPs) data processing system performed at correcting the residual error of the atmospheric correction in satellite remote sensing reflectance (Rrs) and how well the system simultaneously minimized intermission biases between different remote sensing systems. We developed the IOPs data processing system as a semianalytical algorithm called IDAS. Our results show that IDAS generates accurate and consistent IOPs products from two ocean color missions: Sea‐viewing Wide Field‐of‐View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer Aqua (MODISA). Specifically, with “high‐quality” SeaWiFS and MODISA Rrs data, IDAS provided temporally consistent IOPs products for the oligotrophic open ocean resulting in an annual mean intermission difference of less than 3%, which is significantly lower than what a quasi‐analytical algorithm (QAA) provided. We used IDAS to generate a long time series of bb(555) from the Northwest Atlantic Subtropical Gyre using SeaWiFS (1998 to 2002) and MODISA (2003 to 2017) images. Our results show that the IDAS‐derived annual bb(555) decreased monotonically by 2.81% per decade from 1998 to 2017. Comparing the IDAS‐generated annual trend for bb(555) to the same data processed with the QAA algorithm, we found that the QAA results differed because of impacts of the residual errors of the atmospheric correction and intermission biases. The differences in the annual trends existed despite the same temporal changing patterns of in situ particulate organic carbon existing in the Sargasso Sea and in the satellite chlorophyll‐a concentration in the Northwest Atlantic Subtropical Gyre.

Methodology development for calibration assessment using quasi-deep convective clouds with application to Aqua MODIS TEB.

Deep convective clouds (DCC) are identified by using a combination of brightness temperature (BT) and visible reflectance thresholds. Moreover, it is common practice to use daytime DCC measurements for the calibration assessment of reflective solar and longwave infrared (LWIR) bands. The DCC cold core is suitable for the MODIS Thermal Emissive Bands (TEB) calibration assessment; more specifically, for the offset effect in the quadratic calibration function. However, the reflected solar radiance in the daytime DCC measurements affects the midwave infrared (MWIR) bands. Thus, an assessment over low BT measurements is not applicable to these bands. Because of this, a quasi-DCC (qDCC) technique is developed for the MWIR bands calibration assessment. The feasibility of using nighttime DCC measurements is demonstrated by comparing the DCC and daytime qDCC techniques. A DCC normalization method is also developed to remove the DCC fluctuation impact and enhance the assessment accuracy. The DCC measurements' distribution is asymmetrical for all TEB, and their BT ranges fluctuate around 20 K. An empirical model is developed and applied to normalize the measurements over DCC to a reference temperature. After the normalization, the DCC and qDCC measurements' distributions are close to symmetrical and Gaussian in shape. These improvements are applied to the Aqua MODIS instrument. The calibration stability, noise performance, and consistency are evaluated for all Aqua MODIS TEB. Lastly, the Aqua MODIS formatter reset effect on the calibration offset bias between two mirror sides is analyzed, and a calibration coefficient correction is proposed for future calibration improvements.

Reconstruction Of Missing Information In Satellite Imagery Using STS-CNN

Reconstruction of missing information in any satellite imagery is very important. Without correct information it is very difficult to identify the area in remote sensing images. In general, there are three different types of noises in satellite imagery such as dead pixels and thick cloud cover. The Failure in Instruments such as Aqua MODIS BAND-6 instrument and ETM+ SLC (Scan Line Corrector)-off condition will lead to missing of information. The existing model consists of Double weighted low rank model Algorithm which is a time taking and less efficient model. In this paper, reconstruction of information in satellite image got done using STS-CNN (Spatial-Temporal-Spectral Convolution Neural Network), which is very efficient and uses faster network for reconstruction of information in satellite imagery.

Long-term chlorophyll-a dynamics in tropical coastal waters of the western Bay of Bengal.

The long-term distribution of in situ optically active substances (OAS), accuracy assessment of satellite retrieved chlorophyll-a (chl-a) and its long-term trend has been carried out at a coastal site of the north-western Bay of Bengal. The temporal distribution of chl-a, total suspended matter (TSM) and absorption due to coloured dissolved organic matter at 440nm (aCDOM440) discerned a common peak during southwest monsoon season (August-October). Chl-a also showed a prominent peak during pre-southwest monsoon period (March-April). The spatial variability of TSM and aCDOM440 was maximum during southwest monsoon, whereas in the case of chl-a, it was during pre-southwest monsoon. The accuracy assessment of chl-a retrieved from Moderate Resolution Imaging Spectroradiometer-Aqua (MODISA), Ocean Colour Monitor-2 (OCM-2) and Visible Infrared Imager Radiometer Suite (VIIRS) showed overestimation in nearshore waters. The error in satellite measurement of chl-a was within the range of 33 to 51%. The chl-a retrieved from MODISA was most accurate as indicated by statistical analysis. The long-term trend in satellite chl-a clearly indicated bi-modal distribution with a primary peak during pre-southwest monsoon attributed to recurrent phytoplankton bloom that was mostly confined to nearshore waters. Whereas, the secondary peak in chl-a, during the end of southwest monsoon, spreads far offshore.

Evaluation of MODIS and VIIRS cloud-gap-filled snow-cover products for production of an Earth science data record

Abstract. MODerate resolution Imaging Spectroradiometer (MODIS) cryosphere products have been available since 2000 – following the 1999 launch of the Terra MODIS and the 2002 launch of the Aqua MODIS – and include global snow-cover extent (SCE) (swath, daily, and 8 d composites) at 500 m and ∼5 km spatial resolutions. These products are used extensively in hydrological modeling and climate studies. Reprocessing of the complete snow-cover data record, from Collection 5 (C5) to Collection 6 (C6) and Collection 6.1 (C6.1), has provided improvements in the MODIS product suite. Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Collection 1 (C1) snow-cover products at a 375 m spatial resolution have been available since 2011 and are currently being reprocessed for Collection 2 (C2). Both the MODIS C6.1 and the VIIRS C2 products will be available for download from the National Snow and Ice Data Center beginning in early 2020 with the complete time series available in 2020. To address the need for a cloud-reduced or cloud-free daily SCE product for both MODIS and VIIRS, a daily cloud-gap-filled (CGF) snow-cover algorithm was developed for MODIS C6.1 and VIIRS C2 processing. MOD10A1F (Terra) and MYD10A1F (Aqua) are daily, 500 m resolution CGF SCE map products from MODIS. VNP10A1F is the daily, 375 m resolution CGF SCE map product from VIIRS. These CGF products include quality-assurance data such as cloud-persistence statistics showing the age of the observation in each pixel. The objective of this paper is to introduce the new MODIS and VIIRS standard CGF daily SCE products and to provide a preliminary evaluation of uncertainties in the gap-filling methodology so that the products can be used as the basis for a moderate-resolution Earth science data record (ESDR) of SCE. Time series of the MODIS and VIIRS CGF products have been developed and evaluated at selected study sites in the US and southern Canada. Observed differences, although small, are largely attributed to cloud masking and differences in the time of day of image acquisition. A nearly 3-month time-series comparison of Terra MODIS and S-NPP VIIRS CGF snow-cover maps for a large study area covering all or parts of 11 states in the western US and part of southwestern Canada reveals excellent correspondence between the Terra MODIS and S-NPP VIIRS products, with a mean difference of 11 070 km2, which is ∼0.45 % of the study area. According to our preliminary validation of the Terra and Aqua MODIS CGF SCE products in the western US study area, we found higher accuracy of the Terra product compared with the Aqua product. The MODIS CGF SCE data record beginning in 2000 has been extended into the VIIRS era, which should last at least through the early 2030s.