Parameter sensitivity analysis and optimization for a satellite-based evapotranspiration model across multiple sites using Moderate Resolution Imaging Spectroradiometer and flux data

2017 ◽  
Vol 122 (1) ◽  
pp. 230-245 ◽  
Author(s):  
Kun Zhang ◽  
Jinzhu Ma ◽  
Gaofeng Zhu ◽  
Ting Ma ◽  
Tuo Han ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Parameter Sensitivity ◽  
Parameter Sensitivity Analysis ◽  
Flux Data ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

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.

scholarly journals Consequences of the 2019 Greenland Ice Sheet Melt Episode on Albedo

2021 ◽  
Vol 13 (2) ◽  
pp. 227
Author(s):  
Arthur Elmes ◽  
Charlotte Levy ◽  
Angela Erb ◽  
Dorothy K. Hall ◽  
Ted A. Scambos ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Surface Albedo ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Energy Budget ◽  
Landsat 8 ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Seasonal Snow Cover

In mid-June 2019, the Greenland ice sheet (GrIS) experienced an extreme early-season melt event. This, coupled with an earlier-than-average melt onset and low prior winter snowfall over western Greenland, led to a rapid decrease in surface albedo and greater solar energy absorption over the melt season. The 2019 melt season resulted in significantly more melt than other recent years, even compared to exceptional melt years previously identified in the moderate-resolution imaging spectroradiometer (MODIS) record. The increased solar radiation absorbance in 2019 warmed the surface and increased the rate of meltwater production. We use two decades of satellite-derived albedo from the MODIS MCD43 record to show a significant and extended decrease in albedo in Greenland during 2019. This decrease, early in the melt season and continuing during peak summer insolation, caused increased radiative forcing of the ice sheet of 2.33 Wm−2 for 2019. Radiative forcing is strongly influenced by the dramatic seasonal differences in surface albedo experienced by any location experiencing persistent and seasonal snow-cover. We also illustrate the utility of the newly developed Landsat-8 albedo product for better capturing the detailed spatial heterogeneity of the landscape, leading to a more refined representation of the surface energy budget. While the MCD43 data accurately capture the albedo for a given 500 m pixel, the higher spatial resolution 30 m Landsat-8 albedos more fully represent the detailed landscape variations.

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