scholarly journals Radiative Fluxes at Barrow, Alaska: A Satellite View

2011 ◽  
Vol 24 (21) ◽  
pp. 5494-5505 ◽  
Author(s):  
Xiaolei Niu ◽  
Rachel T. Pinker
Keyword(s):  
Department Of Energy ◽  
Shortwave Radiation ◽  
Energy Budgets ◽  
High Latitudes ◽  
Radiative Fluxes ◽  
North Slope Of Alaska ◽  
Moderate Resolution ◽  
Atmospheric Radiation Measurement ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Satellite estimates of surface shortwave radiation (SWR) at high latitudes agree less with ground observations than at other locations; moreover, ground observations at such latitudes are scarce. The comprehensive observations of radiative fluxes made since 1977 by the Department of Energy Atmospheric Radiation Measurement (ARM) Program at the Barrow North Slope of Alaska (NSA) site are unique. They provide an opportunity to revisit accuracy estimates of remote sensing products at these latitudes, which are problematic because the melting of snow/ice and lower solar elevation make the satellite retrievals more difficult. A newly developed inference scheme for deriving SWR from the Moderate Resolution Imaging Spectroradiometer (MODIS; Terra and Aqua) that utilizes updated information on surface properties over snow and sea ice will be evaluated against these ground measurements and compared with other satellite and model products. Results show that the MODIS-based estimates are in good agreement with observations, with a bias of −5.3 W m−2 (−4% of mean observations) for the downward SWR, a bias of −5.3 W m−2 (−7%) for upward SWR, a bias of 1 (1%) for net SWR, and a bias of −0.001 (0%) for surface albedo. As such, the MODIS estimates of SWR can be useful for numerical model evaluations and for estimating the energy budgets at high latitudes.

scholarly journals Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

2018 ◽  
Author(s):  
Falguni Patadia ◽  
Robert Levy ◽  
Shana Mattoo
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Infrared Imaging ◽  
Gas Absorption ◽  
Shortwave Radiation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon Moderate Resolution Imaging Spectroradiometer (MODIS, onboard Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, onboard Suomi-NPP) sensors, use wavelength bands in “window” regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper we use High-resolution TRANsmission (HITRAN) database and Line-by-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are “similar”, they are different enough that applying MODIS specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases up to 0.07. As recent studies are attempting to create a long-term data record by joining multiple satellite datasets, including MODIS and VIIRS, the consistency of gas correction becomes even more crucial.

scholarly journals Evaluation of the Spatial and Temporal Uncertainties Distribution of Daily-Integrated Shortwave Downward Radiation Estimated from Polar-Orbiting Satellite Observation

2012 ◽  
Vol 29 (10) ◽  
pp. 1481-1491
Author(s):  
Yang Liu ◽  
Ronggao Liu
Keyword(s):  
East Asia ◽  
Satellite Observation ◽  
Shortwave Radiation ◽  
Wide Field ◽  
Wide Field Of View ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Polar Orbiting Satellite ◽  
Downward Radiation

Abstract The polar-orbiting satellite sensor, which can observe the entire Earth’s surface with good spatial and spectral resolution, is a potential tool for estimation of global downward shortwave radiation (DSR). However, it can only provide a couple of snapshots in one day, which should be extended to daily-integrated DSR in order to drive the ecosystem models. In this paper, the temporal and spatial uncertainties for estimating of daily-integrated DSR from instantaneous measurements of polar-orbiting satellites are evaluated using geostationary Geosynchronous Meteorological Satellite-5 (GMS-5) observations over East Asia. Those overpass times—including 1030, 1200, and 1330 local time (LT), which correspond to Terra/Moderate Resolution Imaging Spectroradiometer (MODIS), Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), and Aqua/MODIS—are evaluated. The combinations of multiobservations are also assessed. The results show that the daily-integrated DSR from polar-orbiting satellite observations of 1030, 1200, and 1330 underestimate solar radiation by 2.16% (0.46 MJ m−2), 5.44% (1.16 MJ m−2), and 5.54% (1.09 MJ m−2), with an RMSE of 2.05 MJ m−2 (12.92%), 2.50 MJ m−2 (13.33%), and 2.34 MJ m−2 (13.95%) in East Asia with large spatial and seasonal variations. In general, the bias is higher in the southern than in the northern part of East Asia. It is low in January, February, and March, then increases from April and reaches the maximum in June and July, and decreases rapidly to lower than 1.0 MJ m−2 in October. The uncertainties of daily-integrated DSR could be reduced by averaging multiday observations or combining of multitime observations. These uncertainties’ distributions are important for evaluation the usability of daily-integrated DSR from polar-orbiting satellite data and probably can be used for its calibration.

scholarly journals Remote Sensing of Atmospheric Water Vapor Using the Moderate Resolution Imaging Spectroradiometer

2005 ◽  
Vol 22 (3) ◽  
pp. 309-314 ◽  
Author(s):  
P. Albert ◽  
R. Bennartz ◽  
R. Preusker ◽  
R. Leinweber ◽  
J. Fischer
Keyword(s):  
Water Vapor ◽  
Great Plains ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water ◽  
Southern Great Plains ◽  
Moderate Resolution ◽  
Atmospheric Radiation Measurement ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces

Abstract This paper presents first validation results for an algorithm developed for the retrieval of integrated columnar water vapor from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the polar-orbiting Terra and Aqua platforms. The algorithm is based on the absorption of reflected solar radiation by atmospheric water vapor and allows the retrieval of integrated water vapor above cloud-free land surfaces. A comparison of the retrieved water vapor with measurements of the Microwave Water Radiometer at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for a 10-month period in 2002 showed an rms deviation of 1.7 kg m−2 and a bias of 0.6 kg m−2. A comparison with radio soundings in central Europe from July 2002 to April 2003 showed an rms deviation of 2 kg m−2 and a bias of −0.8 kg m−2.

scholarly journals Estimation of daily average downward shortwave radiation from MODIS data using principal components regression method: Fars province case study

2017 ◽  
Vol 31 (1) ◽  
pp. 23-34 ◽  
Author(s):  
Razieh Barzin ◽  
Amin Shirvani ◽  
Hossein Lotfi
Keyword(s):  
Regression Model ◽  
Aerosol Optical Depth ◽  
Principal Components ◽  
Shortwave Radiation ◽  
Fars Province ◽  
Principal Components Regression ◽  
Daily Average ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Downward shortwave radiation is a key quantity in the land-atmosphere interaction. Since the moderate resolution imaging spectroradiometer data has a coarse temporal resolution, which is not suitable for estimating daily average radiation, many efforts have been undertaken to estimate instantaneous solar radiation using moderate resolution imaging spectroradiometer data. In this study, the principal components analysis technique was applied to capture the information of moderate resolution imaging spectroradiometer bands, extraterrestrial radiation, aerosol optical depth, and atmospheric water vapour. A regression model based on the principal components was used to estimate daily average shortwave radiation for ten synoptic stations in the Fars province, Iran, for the period 2009-2012. The Durbin-Watson statistic and autocorrelation function of the residuals of the fitted principal components regression model indicated that the residuals were serially independent. The results indicated that the fitted principal components regression models accounted for about 86-96% of total variance of the observed shortwave radiation values and the root mean square error was about 0.9-2.04 MJ m−2 d−1. Also, the results indicated that the model accuracy decreased as the aerosol optical depth increased and extraterrestrial radiation was the most important predictor variable among all.

scholarly journals Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

scholarly journals A Climatological Assessment of Intense Desert Dust Episodes over the Broader Mediterranean Basin Based on Satellite Data

2021 ◽  
Vol 13 (15) ◽  
pp. 2895
Author(s):  
Maria Gavrouzou ◽  
Nikolaos Hatzianastassiou ◽  
Antonis Gkikas ◽  
Christos J. Lolis ◽  
Nikolaos Mihalopoulos
Keyword(s):  
Mediterranean Basin ◽  
Eastern Mediterranean ◽  
Mean Value ◽  
Early Spring ◽  
Dust Aerosol ◽  
Ozone Monitoring Instrument ◽  
Central Mediterranean ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other aerosol types (such as Sea Salt and Biomass Burning) by applying threshold values on key aerosol optical properties describing their loading, size and absorptivity, namely Aerosol Optical Depth (AOD), Aerosol Index (AI) and Ångström Exponent (α). The algorithm operates on a daily and 1° × 1° geographical cell basis over the 15-year period 2005–2019. Daily gridded spectral AOD data are taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua Collection 6.1, and are used to calculate the α data, which are then introduced into the algorithm, while AI data are obtained by the Ozone Monitoring Instrument (OMI) -Aura- Near-UV aerosol product OMAERUV dataset. The algorithm determines the occurrence of Dust Aerosol Episode Days (DAEDs), whenever high loads of DA (higher than their climatological mean value plus two/four standard deviations for strong/extreme DAEDs) exist over extended areas (more than 30 pixels or 300,000 km2). The identified DAEDs are finally grouped into Dust Aerosol Episode Cases (DAECs), consisting of at least one DAED. According to the algorithm results, 166 (116 strong and 50 extreme) DAEDs occurred over the MB during the study period. DAEDs are observed mostly in spring (47%) and summer (38%), with strong DAEDs occurring primarily in spring and summer and extreme ones in spring. Decreasing, but not statistically significant, trends of the frequency, spatial extent and intensity of DAECs are revealed. Moreover, a total number of 98 DAECs was found, primarily in spring (46 DAECs) and secondarily in summer (36 DAECs). The seasonal distribution of the frequency of DAECs varies geographically, being highest in early spring over the eastern Mediterranean, in late spring over the central Mediterranean and in summer over the western MB.

scholarly journals 250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou

2021 ◽  
Vol 13 (5) ◽  
pp. 920
Author(s):  
Zhongting Wang ◽  
Ruru Deng ◽  
Pengfei Ma ◽  
Yuhuan Zhang ◽  
Yeheng Liang ◽  
...  
Keyword(s):  
Mixing Model ◽  
Blue Band ◽  
Aerosol Retrieval ◽  
Aerosol Distribution ◽  
Medium Resolution ◽  
Fine Spatial Resolution ◽  
Yearly Average ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ).

scholarly journals New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hirofumi Hashimoto ◽  
Weile Wang ◽  
Jennifer L. Dungan ◽  
Shuang Li ◽  
Andrew R. Michaelis ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Seasonal Patterns ◽  
Optical Remote Sensing ◽  
Amazon Forest ◽  
Evergreen Forests ◽  
Geostationary Satellites ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
New Generation

AbstractAssessing the seasonal patterns of the Amazon rainforests has been difficult because of the paucity of ground observations and persistent cloud cover over these forests obscuring optical remote sensing observations. Here, we use data from a new generation of geostationary satellites that carry the Advanced Baseline Imager (ABI) to study the Amazon canopy. ABI is similar to the widely used polar orbiting sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), but provides observations every 10–15 min. Our analysis of NDVI data collected over the Amazon during 2018–19 shows that ABI provides 21–35 times more cloud-free observations in a month than MODIS. The analyses show statistically significant changes in seasonality over 85% of Amazon forest pixels, an area about three times greater than previously reported using MODIS data. Though additional work is needed in converting the observed changes in seasonality into meaningful changes in canopy dynamics, our results highlight the potential of the new generation geostationary satellites to help us better understand tropical ecosystems, which has been a challenge with only polar orbiting satellites.

scholarly journals Real-Time Detection of Daytime and Night-Time Fire Hotspots from Geostationary Satellites

2021 ◽  
Vol 13 (9) ◽  
pp. 1627
Author(s):  
Chermelle B. Engel ◽  
Simon D. Jones ◽  
Karin J. Reinke
Keyword(s):  
Real Time ◽  
Infrared Imaging ◽  
Night Time ◽  
Clear Link ◽  
Radiative Power ◽  
Biogeographical Region ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Fire Radiative Power

This paper introduces an enhanced version of the Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) algorithm. The algorithm runs in real-time and operates over 24 h to include both daytime and night-time detections. The algorithm was executed and tested on 12 months of Himawari-8 data from 1 April 2019 to 31 March 2020, for every valid 10-min observation. The resulting hotspots were compared to those from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). The modified BRIGHT hotspots matched with fire detections in VIIRS 96% and MODIS 95% of the time. The number of VIIRS and MODIS hotspots with matches in the coincident modified BRIGHT dataset was lower (at 33% and 46%, respectively). This paper demonstrates a clear link between the number of VIIRS and MODIS hotspots with matches and the minimum fire radiative power considered.

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