scholarly journals Seasonal variations of outlet glacier terminus position in Greenland

2013 ◽  
Vol 59 (216) ◽  
pp. 759-770 ◽  
Author(s):  
Kristin M. Schild ◽  
Gordon S. Hamilton
Keyword(s):  
Seasonal Variations ◽  
Spatial And Temporal Variability ◽  
Simple Relationship ◽  
Environmental Forcing ◽  
Outlet Glacier ◽  
Glacier Terminus ◽  
Air Temperatures ◽  
Spatial Differences ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractMany of Greenland’s marine-terminating outlet glaciers have undergone rapid retreat in the past decade, accompanied by accelerated flow and dynamic thinning. Superimposed on this pattern of retreat, these glaciers undergo seasonal variations in terminus position, corresponding roughly to wintertime advance and summertime retreat. We compiled near-daily time series of terminus position for five of Greenland’s largest outlet glaciers (Daugaard Jensen, Kangerdlugssuaq and Helheim glaciers in East Greenland, and Jakobshavn Isbræ and Rink Isbræ in West Greenland) using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. There are spatial differences in the timing of the onset of seasonal retreat among all the glaciers in our study, as well as variability in terminus behavior for individual glaciers from year to year. We examine whether this spatial and temporal variability is linked to above-freezing air temperatures or high sea surface temperatures, but find no simple relationship. Instead, we hypothesize that terminus geometry (ice thickness, subglacial topography, fjord bathymetry) exerts an important control on the response of marine-terminating glaciers to climate perturbations. Models for predicting outlet glacier response to climate change need to include this complex interaction between geometry and environmental forcing.

scholarly journals MODIS-Derived Spatially Complete Surface Albedo Products: Spatial and Temporal Pixel Distribution and Zonal Averages

2008 ◽  
Vol 47 (11) ◽  
pp. 2879-2894 ◽  
Author(s):  
Eric G. Moody ◽  
Michael D. King ◽  
Crystal B. Schaaf ◽  
Steven Platnick
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Temporal Distribution ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Qualitative Comparison ◽  
Annual Cycles ◽  
Satellite Platform ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Five years (2000–04) of spatially complete snow-free land surface albedo data have been produced using high-quality-flagged diffuse bihemispherical (white sky) and direct-beam directional hemispherical (black sky) land surface albedo data derived from observations taken by the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument aboard the NASA Terra satellite platform (MOD43B3, collection 4). In addition, a spatially complete snow-free aggregate albedo climatological product was generated. These spatially complete products were prepared using an ecosystem-dependent temporal interpolation technique that retrieves missing data within 3%–8% error. These datasets have already been integrated into research and operational projects that require snow-free land surface albedo. As such, this paper provides details regarding the spatial and temporal distribution of the filled versus the original MOD43B3 data. The paper also explores the intra- and interannual variation in the 5-yr data record and provides a qualitative comparison of zonal averages and annual cycles of the filled versus the original MOD43B3 data. The analyses emphasize the data’s inter- and intraannual variation and show that the filled data exhibit large- and small-scale phenological behavior that is qualitatively similar to that of the original MOD43B3. These analyses thereby serve to showcase the inherent spectral, spatial, and temporal variability in the MOD43B3 data as well as the ability of the fill technique to preserve these unique regional and pixel-level phenological characteristics.

scholarly journals Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations – Part 1: ATSR (1995–2011) and MODIS C6.1 (2000–2017)

2018 ◽  
Vol 18 (15) ◽  
pp. 11389-11407 ◽  
Author(s):  
Larisa Sogacheva ◽  
Gerrit de Leeuw ◽  
Edith Rodriguez ◽  
Pekka Kolmonen ◽  
Aristeidis K. Georgoulias ◽  
...  
Keyword(s):  
Time Series ◽  
Seasonal Variations ◽  
Eastern Coast ◽  
Deep Blue ◽  
Modis Aod ◽  
Yearly Average ◽  
Offset Correction ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference

Abstract. Aerosol optical depth (AOD) patterns and interannual and seasonal variations over China are discussed based on the AOD retrieved from the Along-Track Scanning Radiometer (ATSR-2, 1995–2002), the Advanced ATSR (AATSR, 2002–2012) (together ATSR) and the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite (2000–2017). The AOD products used were the ATSR Dual View (ADV) v2.31 AOD and the MODIS/Terra Collection 6.1 (C6.1) merged dark target (DT) and deep blue (DB) AOD product. Together these datasets provide an AOD time series for 23 years, from 1995 to 2017. The difference between the AOD values retrieved from ATSR-2 and AATSR is small, as shown by pixel-by-pixel and monthly aggregate comparisons as well as validation results. This allows for the combination of the ATSR-2 and AATSR AOD time series into one dataset without offset correction. ADV and MODIS AOD validation results show similar high correlations with the Aerosol Robotic Network (AERONET) AOD (0.88 and 0.92, respectively), while the corresponding bias is positive for MODIS (0.06) and negative for ADV (−0.07). Validation of the AOD products in similar conditions, when ATSR and MODIS/Terra overpasses are within 90 min of each other and when both ADV and MODIS retrieve AOD around AERONET locations, show that ADV performs better than MODIS in autumn, while MODIS performs slightly better in spring and summer. In winter, both ADV and MODIS underestimate the AERONET AOD. Similar AOD patterns are observed by ADV and MODIS in annual and seasonal aggregates as well as in time series. ADV–MODIS difference maps show that MODIS AOD is generally higher than that from ADV. Both ADV and MODIS show similar seasonal AOD behavior. The AOD maxima shift from spring in the south to summer along the eastern coast further north. The agreement between sensors regarding year-to-year AOD changes is quite good. During the period from 1995 to 2006 AOD increased in the southeast (SE) of China. Between 2006 and 2011 AOD did not change much, showing minor minima in 2008–2009. From 2011 onward AOD decreased in the SE of China. Similar patterns exist in year-to-year ADV and MODIS annual AOD tendencies in the overlapping period. However, regional differences between the ATSR and MODIS AODs are quite large. The consistency between ATSR and MODIS with regards to the AOD tendencies in the overlapping period is rather strong in summer, autumn and overall for the yearly average; however, in winter and spring, when there is a difference in coverage between the two instruments, the agreement between ATSR and MODIS is lower. AOD tendencies in China during the 1995–2017 period will be discussed in more detail in Part 2 (a following paper: Sogacheva et al., 2018), where a method to combine AOD time series from ADV and MODIS is introduced, and combined AOD time series are analyzed.

scholarly journals Effects of Spring–Neap Tidal Cycle on Spatial and Temporal Variability of Satellite Chlorophyll-A in a Macrotidal Embayment, Ariake Sea, Japan

2020 ◽  
Vol 12 (11) ◽  
pp. 1859
Author(s):  
Mengmeng Yang ◽  
Joaquim I. Goes ◽  
Hongzhen Tian ◽  
Elígio de R. Maúre ◽  
Joji Ishizaka
Keyword(s):  
Chlorophyll A ◽  
Temporal Variability ◽  
Tidal Cycle ◽  
Ocean Color ◽  
Spatial And Temporal Variability ◽  
Ariake Sea ◽  
Chl A ◽  
Moderate Resolution ◽  
Spatio Temporal ◽  
Moderate Resolution Imaging Spectroradiometer

We investigated the spatio-temporal variability of chlorophyll-a (Chl-a) and total suspended matter (TSM) associated with spring–neap tidal cycles in the Ariake Sea, Japan. Our study relied on significantly improved, regionally-tuned datasets derived from the ocean color sensor Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua over a 16-year period (2002–2017). The results revealed that spring–neap tidal variations in Chl-a and TSM within this macrotidal embayment (the Ariake Sea) are clearly different regionally and seasonally. Generally, the spring–neap tidal variability of Chl-a in the inner part of the Ariake Sea was controlled by TSM for seasons other than summer, whereas it was controlled by river discharge for summer. On the other hand, the contribution of TSM to the variability of Chl-a was not large for two areas in the middle of Ariake Sea where TSM was not abundant. This study demonstrates that ocean color satellite observations of Chl-a and TSM in the macrotidal embayment offer strong advantages for understanding the variations during the spring–neap tidal cycle.

scholarly journals Evaluation of cloud effects on air temperature estimation using MODIS LST based on ground measurements over the Tibetan Plateau

2016 ◽  
Author(s):  
Hongbo Zhang ◽  
Fan Zhang ◽  
Guoqing Zhang ◽  
Xiaobo He ◽  
Lide Tian
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Estimation Accuracy ◽  
Daily Maximum ◽  
The Tibetan Plateau ◽  
Cloud Detection ◽  
Air Temperatures ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data have played a significant role in estimating the air temperature (Tair) due to the sparseness of ground measurements, especially for remote mountainous areas. Generally, two types of air temperatures are studied including daily maximum (Tmax) and minimum (Tmin) air temperatures. MODIS daytime and nighttime LST are often used as proxies for estimating Tmax and Tmin, respectively. The Tibetan Plateau (TP) has a high daily cloud cover fraction (> 45 %). The presence of clouds can affect the relationship between Tair and LST and can further affect the estimation accuracies. This study comprehensively analyzes the effects of clouds on Tair estimation based on MODIS LST using detailed half-hourly ground measurements and daily meteorological station observations collected from over the TP. Comparisons made between in-situ cloudiness observations and MODIS claimed clear-sky records show that erroneous rates of MODIS nighttime cloud detection are obviously higher than those achieved in daytime. Our validation of the MODIS LST values under different cloudiness constraining conditions shows that the accuracy of MODIS nighttime LST is severely affected by undetected clouds. Large errors introduced by undetected clouds are found to significantly affect the Tmin estimations based on nighttime LST through cloud effect tests. However, clouds are mainly found to affect Tmax estimation by affecting the essential relationship between Tmax and daytime LST. The obviously larger errors of Tmax estimation than those of Tmin could be attributed to larger MODIS daytime LST errors resulting from higher degrees of daytime LST heterogeneity within MODIS pixel than those of nighttime LST. Constraining all four MODIS observations per day to non-cloudy observations can efficiently screen samples to build a strong fit of Tmin estimation using MODIS nighttime LST. The present study reveals the effects of clouds on Tair estimation through MODIS LST and will thus help improve the estimation accuracy levels while alleviating the problems associated with severe data sparseness over the TP.

scholarly journals Monitoring ice break-up on the Mackenzie River using MODIS data

2015 ◽  
Vol 9 (3) ◽  
pp. 2783-2820
Author(s):  
P. Muhammad ◽  
C. Duguay ◽  
K.-K. Kang
Keyword(s):  
Drainage Basin ◽  
Geographic Location ◽  
Ice Melt ◽  
Air Temperatures ◽  
Moderate Resolution ◽  
Level 3 ◽  
Break Up ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Channel Constriction ◽  
Mackenzie River

Abstract. This study involves the analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 500 m snow products (MOD/MYD10A1), complemented with 250 m Level 1B data (MOD/MYD02QKM), to monitor ice cover during the break-up period on the Mackenzie River, Canada. Results from the analysis of data for 13 ice seasons (2001–2013) show that first day ice-off dates are observed between days of year (DOY) 115–125 and end DOY 145–155, resulting in average melt durations of about 30–40 days. Floating ice transported northbound could therefore generate multiple periods of ice-on and ice-off observations at the same geographic location. During the ice break-up period, ice melt was initiated by in situ (thermodynamic) melt over the drainage basin especially between 61–61.8° N (75–300 km). However, ice break-up process north of 61.8° N was more dynamically driven. Furthermore, years with earlier initiation of the ice break-up period correlated with above normal air temperatures and precipitation, whereas later ice break-up period was correlated with below normal precipitation and air temperatures. MODIS observations revealed that ice runs were largely influenced by channel morphology (islands and bars, confluences and channel constriction). It is concluded that the numerous MODIS daily overpasses possible with the Terra and Aqua polar orbiting satellites, provide a powerful means for monitoring ice break-up processes at multiple geographical locations simultaneously along the Mackenzie River.

scholarly journals Retrieval of column-integrated water vapour from MODIS and analysis of its monthly and seasonal variability over several typical cities in China

MAUSAM ◽  
2021 ◽  
Vol 67 (3) ◽  
pp. 571-576
Author(s):  
ZHANG JINYE ◽  
CHENG CHUNFU ◽  
ZHU JINRONG ◽  
YU XIULI
Keyword(s):  
Water Vapour ◽  
Global Climate ◽  
Low Cost ◽  
Precipitable Water ◽  
Spatial And Temporal Variability ◽  
Precipitable Water Vapour ◽  
Integrated Water Vapour ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Good Tracer

Column-integrated water vapour also called Precipitable Water Vapour (PWV), is one of the main parameters influencing the global climate change. Due to its high spatial and temporal variability PWV has been found to be a good tracer of atmospheric motions. Retrieving PWV from Moderate Resolution Imaging Spectroradiometer (MODIS) data has the merits of high spatial resolution and low cost. In this paper, an algorithm for retrieving PWV using several MODIS near-IR channels data is first presented. Six typical cities in China with different climate are selected for study. These are Beijing, Shanghai, Guangzhou, Chengdu, Wuhan and Lanzhou. The variations of PWV in recent13 years (2001-2013) over six cities have been analyzed. The study brings out an increasing trend of annual average of water vapour over these cities in recent 13 years. The results also indicate that PWV reaches the highest value in summer, decreases in autumn, further decrease in spring, and is lowest in winter. PWV in summer over the six cities have been increasing in recent 13 years, but PWV in autumn and winter have been decreasing over inland cities, such as Wuhan and Beijing. Possible reasons for such observed trends are given in this paper.  

Developing an Index to Measure Urban Heat Island Effect Using Satellite Land Skin Temperature and Land Cover Observations

2012 ◽  
Vol 25 (18) ◽  
pp. 6193-6201 ◽  
Author(s):  
Menglin S. Jin
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Skin Temperature ◽  
Heat Island ◽  
Air Temperatures ◽  
Screen Level ◽  
Moderate Resolution ◽  
Urban Heat ◽  
Weather Stations ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract A new index of calculating the intensity of urban heat island effects (UHI) for a city using satellite skin temperature and land cover observations is recommended. UHI, the temperature difference between urban and rural regions, is traditionally identified from the 2-m surface air temperatures (i.e., the screen-level temperature T2m) measured at a pair of weather stations sited in urban and rural locations. However, such screen-level UHI is affected by the location, distance, and geographic conditions of the pair of weather stations. For example, choosing a different pair of rural and city sites leads to a different UHI intensity for the same city, due to the high heterogeneity of the urban surface temperature. To avoid such uncertainty, satellite-observed surface skin temperature measurements (i.e., skin level temperature Tskin) is recommended to record UHI, known as skin-level UHI or UHIskin. This new index has advantages of high spatial resolution and aerial coverage to better record UHI intensity than T2m. An assessment of skin-level UHI from 10 yr of the National Aeronautics and Space Administration (NASA)’s Moderate Resolution Imaging Spectroradiometer (MODIS) observations reveals that skin-level UHI has a strong UHI signal during the day and at night. In addition, there are significant diurnal and seasonal variations in skin-level UHI. Furthermore, the skin-level UHI is stronger during the day and summer (July) than during nighttime and winter. This new index is important for more uniformly assessing UHIs over cities around the globe. Nevertheless, whether the seasonality and diurnal variations revealed in this work using skin-level UHI index are valid over desert cities, such as Phoenix, Arizona, need to be examined.

scholarly journals Threefold increase in marine-terminating outlet glacier retreat rates across the Atlantic Arctic: 1992–2010

2017 ◽  
Vol 58 (74) ◽  
pp. 72-91 ◽  
Author(s):  
J. Rachel Carr ◽  
Chris. R. Stokes ◽  
Andreas Vieli
Keyword(s):  
Barents Sea ◽  
Glacier Retreat ◽  
Spatial And Temporal Variability ◽  
Remotely Sensed Data ◽  
Position Change ◽  
Outlet Glacier ◽  
Novaya Zemlya ◽  
Air Temperatures ◽  
Franz Josef Land ◽  
North Atlantic Climate

ABSTRACTAccelerated discharge through marine-terminating outlet glaciers has been a key component of the rapid mass loss from Arctic glaciers since the 1990s. However, glacier retreat and its climatic controls have not been assessed at the pan-Arctic scale. Consequently, the spatial and temporal variability in the magnitude of retreat, and the possible drivers are uncertain. Here we use remotely sensed data acquired over 273 outlet glaciers, located across the entire Atlantic Arctic (i.e. areas potentially influenced by North Atlantic climate and/or ocean conditions, specifically: Greenland, Novaya Zemlya, Franz Josef Land and Svalbard), to demonstrate high-magnitude, accelerating and near-ubiquitous retreat between 1992 and 2010. Overall, mean retreat rates increased by a factor of 3.5 between 1992 and 2000 (−30.5 m a−1) and 2000–10 (−105.8 m a−1), with 97% of the study glaciers retreating during the latter period. The Retreat was greatest in northern, western and south-eastern Greenland and also increased substantially on the Barents Sea coast of Novaya Zemlya. Glacier retreat showed no significant or consistent relationship with summer air temperatures at decadal timescales. The rate of frontal position change showed a significant, but weak, correlation with changes in sea-ice concentrations. We highlight large variations in retreat rates within regions and suggest that fjord topography plays an important role. We conclude that marine-terminating Arctic outlet glaciers show a common response of rapid and accelerating retreat at decadal timescales.

scholarly journals Evaluation of cloud effects on air temperature estimation using MODIS LST based on ground measurements over the Tibetan Plateau

2016 ◽  
Vol 16 (21) ◽  
pp. 13681-13696 ◽  
Author(s):  
Hongbo Zhang ◽  
Fan Zhang ◽  
Guoqing Zhang ◽  
Xiaobo He ◽  
Lide Tian
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Estimation Accuracy ◽  
Daily Maximum ◽  
The Tibetan Plateau ◽  
Cloud Detection ◽  
Air Temperatures ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime land surface temperature (LST) data are often used as proxies for estimating daily maximum (Tmax) and minimum (Tmin) air temperatures, especially for remote mountainous areas due to the sparseness of ground measurements. However, the Tibetan Plateau (TP) has a high daily cloud cover fraction (> 45 %), which may affect the air temperature (Tair) estimation accuracy. This study comprehensively analyzes the effects of clouds on Tair estimation based on MODIS LST using detailed half-hourly ground measurements and daily meteorological station observations collected from the TP. It is shown that erroneous rates of MODIS nighttime cloud detection are obviously higher than those achieved in daytime. Large errors in MODIS nighttime LST data were found to be introduced by undetected clouds and thus reduce the Tmin estimation accuracy. However, for Tmax estimation, clouds are mainly found to reduce the estimation accuracy by affecting the essential relationship between Tmax and daytime LST. The errors of Tmax estimation are obviously larger than those of Tmin and could be attributed to larger MODIS daytime LST errors that result from higher degrees of LST heterogeneity within MODIS pixel compared to those of nighttime LST. Constraining MODIS observations to non-cloudy observations can efficiently screen data samples for accurate Tmin estimation using MODIS nighttime LST. As a result, the present study reveals the effects of clouds on Tmax and Tmin estimation through MODIS daytime and nighttime LST, respectively, so as to help improve the Tair estimation accuracy and alleviate the severe air temperature data sparseness issues over the TP.

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