Arctic Cloud Changes from Surface and Satellite Observations

2010 ◽  
Vol 23 (15) ◽  
pp. 4233-4242 ◽  
Author(s):  
Ryan Eastman ◽  
Stephen G. Warren
Keyword(s):  
Time Series ◽  
Satellite Data ◽  
Cloud Cover ◽  
The Arctic ◽  
Interannual Variations ◽  
Infrared Observation ◽  
Cloud Data ◽  
Surface Data ◽  
Avhrr Data ◽  
Very High

Abstract Visual cloud reports from land and ocean regions of the Arctic are analyzed for total cloud cover. Trends and interannual variations in surface cloud data are compared to those obtained from Advanced Very High Resolution Radiometer (AVHRR) and Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) satellite data. Over the Arctic as a whole, trends and interannual variations show little agreement with those from satellite data. The interannual variations from AVHRR are larger in the dark seasons than in the sunlit seasons (6% in winter, 2% in summer); however, in the surface observations, the interannual variations for all seasons are only 1%–2%. A large negative trend for winter found in the AVHRR data is not seen in the surface data. At smaller geographic scales, time series of surface- and satellite-observed cloud cover show some agreement except over sea ice during winter. During the winter months, time series of satellite-observed clouds in numerous grid boxes show variations that are strangely coherent throughout the entire Arctic.

scholarly journals Comparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY

2018 ◽  
Vol 11 (5) ◽  
pp. 2949-2965 ◽  
Author(s):  
Dunya Alraddawi ◽  
Alain Sarkissian ◽  
Philippe Keckhut ◽  
Olivier Bock ◽  
Stefan Noël ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapour ◽  
Satellite Data ◽  
Cloud Cover ◽  
Surface Albedo ◽  
Hydrological Cycle ◽  
Radiation Budget ◽  
The Arctic ◽  
Gnss Measurements ◽  
Gnss Time Series

Abstract. Atmospheric water vapour plays a key role in the Arctic radiation budget, hydrological cycle and hence climate, but its measurement with high accuracy remains an important challenge. Total column water vapour (TCWV) datasets derived from ground-based GNSS measurements are used to assess the quality of different existing satellite TCWV datasets, namely from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Atmospheric Infrared Sounder (AIRS) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The comparisons between GNSS and satellite data are carried out for three reference Arctic observation sites (Sodankylä, Ny-Ålesund and Thule) where long homogeneous GNSS time series of more than a decade (2001–2014) are available. We select hourly GNSS data that are coincident with overpasses of the different satellites over the three sites and then average them into monthly means that are compared with monthly mean satellite products for different seasons. The agreement between GNSS and satellite time series is generally within 5 % at all sites for most conditions. The weakest correlations are found during summer. Among all the satellite data, AIRS shows the best agreement with GNSS time series, though AIRS TCWV is often slightly too high in drier atmospheres (i.e. high-latitude stations during autumn and winter). SCIAMACHY TCWV data are generally drier than GNSS measurements at all the stations during the summer. This study suggests that these biases are associated with cloud cover, especially at Ny-Ålesund and Thule. The dry biases of MODIS and SCIAMACHY observations are most pronounced at Sodankylä during the snow season (from October to March). Regarding SCIAMACHY, this bias is possibly linked to the fact that the SCIAMACHY TCWV retrieval does not take accurately into account the variations in surface albedo, notably in the presence of snow with a nearby canopy as in Sodankylä. The MODIS bias at Sodankylä is found to be correlated with cloud cover fraction and is also expected to be affected by other atmospheric or surface albedo changes linked for instance to the presence of forests or anthropogenic emissions. Overall, the results point out that a better estimation of seasonally dependent surface albedo and a better consideration of vertically resolved cloud cover are recommended if biases in satellite measurements are to be reduced in the polar regions.

scholarly journals Comparison of total water vapour content in the Arctic derived from GPS, AIRS, MODIS and SCIAMACHY

2017 ◽  
Author(s):  
Dunya Alraddawi ◽  
Alain Sarkissian ◽  
Philippe Keckhut ◽  
Olivier Bock ◽  
Stefan Noël ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapour ◽  
Satellite Data ◽  
Cloud Cover ◽  
Surface Albedo ◽  
Radiation Budget ◽  
The Arctic ◽  
Gps Measurements ◽  
Data Set ◽  
Gps Time Series

Abstract. Atmospheric water vapour plays a key role in the Arctic radiation budget, hydrological cycle and hence climate, but its measurement with high accuracy remains an important challenge. Total Column Water Vapour (TCWV) data set derived from ground-based GPS measurements are used to assess the quality of different existing satellite TCWV datasets, namely from the Moderate Resolution Imaging Spectrometer (MODIS), the Atmospheric Infrared System (AIRS), and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The comparisons between GPS and satellite data are carried out for three reference Arctic observation sites (Sodankyla, Ny-Alesund and Thule) where long homogeneous GPS time series are available. We select hourly GPS data that are coincident with overpasses of the different satellites over the 3 sites and then average them into monthly means that are compared with monthly mean satellite products for different seasons. The agreement between GPS and satellite time series is generally within 5 % at all sites for most conditions. The weakest correlations are found during summer. Among all the satellite data, AIRS shows the best agreement with GPS time series, though AIRS TCWV is often slightly too high in drier atmospheres (i.e. high latitude stations during fall and winter). SCIAMACHY TCWV data are generally drier than GPS measurements at all the stations during the summer. This study suggests that these biases are associated with cloud cover, especially at Ny-Alesund and Thule. The dry biases of MODIS and SCIAMACHY observations are most pronounced at Sodankyla during the snow season (from October to March). Regarding SCIAMACHY, this bias is possibly linked to the fact that the SCIAMACHY TCWV retrieval does not take accurately into account the variations in surface albedo, notably in the presence of snow with a nearby canopy as in Sodankyla. The MODIS bias at Sodankyla is found to be correlated with cloud cover fraction and is also expected to be affected by other atmospheric or surface albedo changes linked for instance to the presence of forests or anthropogenic emissions. Overall, the results point out that a better estimation of seasonally-dependent surface albedo and a better consideration of vertically-resolved cloud cover are recommended if biases in satellite measurements are to be reduced in polar regions.

scholarly journals Relationships between Arctic Sea Ice and Clouds during Autumn

2008 ◽  
Vol 21 (18) ◽  
pp. 4799-4810 ◽  
Author(s):  
Axel J. Schweiger ◽  
Ron W. Lindsay ◽  
Steve Vavrus ◽  
Jennifer A. Francis
Keyword(s):  
Sea Ice ◽  
Cloud Cover ◽  
Cloud Amount ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Simultaneous Increase ◽  
Temperature Structure ◽  
Infrared Observation ◽  
Near Surface ◽  
Subsequent Decrease

Abstract The connection between sea ice variability and cloud cover over the Arctic seas during autumn is investigated by analyzing the 40-yr ECMWF Re-Analysis (ERA-40) products and the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) Polar Pathfinder satellite datasets. It is found that cloud cover variability near the sea ice margins is strongly linked to sea ice variability. Sea ice retreat is linked to a decrease in low-level cloud amount and a simultaneous increase in midlevel clouds. This pattern is apparent in both data sources. Changes in cloud cover can be explained by changes in the atmospheric temperature structure and an increase in near-surface temperatures resulting from the removal of sea ice. The subsequent decrease in static stability and deepening of the atmospheric boundary layer apparently contribute to the rise in cloud level. The radiative effect of this change is relatively small, as the direct radiative effects of cloud cover changes are compensated for by changes in the temperature and humidity profiles associated with varying ice conditions.

Interannual variations and trend of the production of inorganic carbon by coccolithophores in the arctic in 2002–2010 based on satellite data

2013 ◽  
Vol 49 (9) ◽  
pp. 871-878 ◽  
Author(s):  
D. A. Petrenko ◽  
E. V. Zabolotsikh ◽  
D. V. Pozdnyakov ◽  
F. Counillon ◽  
L. N. Karlin
Keyword(s):  
Satellite Data ◽  
Inorganic Carbon ◽  
The Arctic ◽  
Interannual Variations

scholarly journals Comparison and integration of ice-pack temperatures derived from AVHRR and passive microwave imagery

1993 ◽  
Vol 17 ◽  
pp. 372-378 ◽  
Author(s):  
J. Maslanik ◽  
J. Key
Keyword(s):  
Cloud Cover ◽  
Large Scale ◽  
Passive Microwave ◽  
The Arctic ◽  
First Year ◽  
Brightness Temperatures ◽  
Ice Surface ◽  
Ice Concentration ◽  
Avhrr Data ◽  
Sky Conditions

Co-located sets of AVHRR and SSM/I passive microwave imagery are used to estimate ice surface temperatures and to infer cloud cover in the Arctic. Physical temperatures are determined from the AVHRR data by modeling atmospheric and surface conditions. The resulting field-of-view temperatures are converted to ice surface skin temperatures by adjusting for ice concentration calculated using the SSM/I data. By selecting AVHRR-derived temperatures for clear sky conditions, “effective” emissivities of first-year and multi-year ice are calculated. Given these emissivities, microwave brightness temperatures, and proportions of first-year and multi-year ice as estimated using the NASA Team Algorithm, physical temperatures of the sea ice/snow surface are calculated that are, in theory, relatively independent of cloud conditions. The resulting ice temperatures are used to delineate a portion of the cloud cover in the AVHRR data. The advantages of this approach are that only a fairly small amount of AVHRR data are needed to calibrate the SSM/I imagery that can then be used to calculate a time-series of temperatures on a large scale.

scholarly journals On the decadal increase in the tropical mean outgoing longwave radiation for the period 1984-2000

2004 ◽  
Vol 4 (5) ◽  
pp. 1419-1425 ◽  
Author(s):  
D. Hatzidimitriou ◽  
I. Vardavas ◽  
K. G. Pavlakis ◽  
N. Hatzianastassiou ◽  
C. Matsoukas ◽  
...  
Keyword(s):  
Time Series ◽  
Outgoing Longwave Radiation ◽  
Cloud Cover ◽  
Longwave Radiation ◽  
Atmospheric Temperature ◽  
Tropical Region ◽  
Transfer Model ◽  
Cloud Data ◽  
Low Level ◽  
High Level

Abstract. In the present paper, we have calculated the outgoing longwave radiation at the top of the atmosphere (OLR at TOA) using a deterministic radiation transfer model, cloud data from ISCCP-D, and atmospheric temperature and humidity data from NCEP/NCAR reanalysis, for the seventeen-year period 1984-2000. We constructed anomaly time-series of the OLR at TOA, as well as of all of the key input climatological data, averaged in the tropical region between 20°N and 20°S. We compared the anomaly time-series of the model calculated OLR at TOA with that obtained from the ERBE S-10N (WFOV NF edition 2) non-scanner measurements. The model results display very similar seasonal and inter-annual variability as the ERBS data, and indicate a decadal increase of OLR at TOA of 1.9±0.2Wm-2/decade, which is lower than that displayed by the ERBS time-series (3.5±0.3Wm-2). Analysis of the inter-annual and long-term variability of the various parameters determining the OLR at TOA, showed that the most important contribution to the observed trend comes from a decrease in high-level cloud cover over the period 1984-2000, followed by an apparent drying of the upper troposphere and a decrease in low-level cloudiness. Opposite but small trends are introduced by a decrease in low-level cloud top pressure, an apparent cooling of the lower stratosphere (at the 50mbar level) and a small decadal increase in mid-level cloud cover.

scholarly journals Retrieval of aerosol optical depth over land surfaces from AVHRR data

2013 ◽  
Vol 6 (1) ◽  
pp. 2227-2251 ◽  
Author(s):  
L. Mei ◽  
Y. Xue ◽  
A. A. Kokhanovsky ◽  
W. von Hoyningen-Huene ◽  
G. de Leeuw ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Reflectance ◽  
Aerosol Retrieval ◽  
Avhrr Data ◽  
Land Surfaces ◽  
Very High

Abstract. The Advanced Very High Resolution Radiometer (AVHRR) radiance data provide a global, long-term, consistent time series having high spectral and spatial resolution and thus being valuable for the retrieval of surface spectral reflectance, albedo and surface temperature. Long term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. These data have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land and land surface albedo are challenging because of the information content of the measurement is limited and the inversion of these data products being ill defined. Solving the radiative transfer equations requires additional information and knowledge to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 μm and 2.1 μm, which has been identified in Moderate Resolution Imaging Spectroradiometer (MODIS) data. Next, following the MODIS dark target approach, the surface reflectance at 0.64 μm was obtained. The comparison of the estimated surface reflectance at 0.64 μm with MODIS reflectance products (MOD09) shows a strong correlation (R = 0.7835). Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to Advanced Very High Resolution Radiometer (AVHRR) data. A simplified Look-Up Table (LUT) method, adopted from Bremen AErosol Retrieval (BAER) algorithm, was used in the retrieval. The Aerosol Optical Depth (AOD) values retrieved from AVHRR with this method compare favourably with ground-based measurements, with a correlation coefficient R = 0.861 and Root Mean Square Error (RMSE) = 0.17. This method can be easily applied to other satellite instruments which do not have a 2.1 μm channel, such as those currently planned to geostationary satellites.

scholarly journals Correction of CCI cloud data over the Swiss Alps using ground-based radiation measurements

2018 ◽  
Vol 11 (7) ◽  
pp. 4153-4170
Author(s):  
Fanny Jeanneret ◽  
Giovanni Martucci ◽  
Simon Pinnock ◽  
Alexis Berne
Keyword(s):  
Satellite Data ◽  
Cloud Cover ◽  
Swiss Alps ◽  
Shortwave Radiation ◽  
Data Sets ◽  
Cloud Detection ◽  
Tree Model ◽  
Validation Data ◽  
Cloud Data ◽  
Mountainous Regions

Abstract. The validation of long-term cloud data sets retrieved from satellites is challenging due to their worldwide coverage going back as far as the 1980s. A trustworthy reference cannot be found easily at every location and every time. Mountainous regions present a particular problem since ground-based measurements are sparse. Moreover, as retrievals from passive satellite radiometers are difficult in winter due to the presence of snow on the ground, it is particularly important to develop new ways to evaluate and to correct satellite data sets over elevated areas. In winter for ground levels above 1000 m (a.s.l.) in Switzerland, the cloud occurrence of the newly released cloud property data sets of the ESA Climate Change Initiative Cloud_cci Project (Advanced Very High Resolution Radiometer afternoon series (AVHRR-PM) and Moderate-Resolution Imaging Spectroradiometer (MODIS) Aqua series) is 132 to 217 % that of surface synoptic (SYNOP) observations, corresponding to a rate of false cloud detections between 24 and 54 %. Furthermore, the overestimations increase with the altitude of the sites and are associated with particular retrieved cloud properties. In this study, a novel post-processing approach is proposed to reduce the amount of false cloud detections in the satellite data sets. A combination of ground-based downwelling longwave and shortwave radiation and temperature measurements is used to provide independent validation of the cloud cover over 41 locations in Switzerland. An agreement of 85 % is obtained when the cloud cover is compared to surface synoptic observations (90 % within ± 1 okta difference). The validation data are then co-located with the satellite observations, and a decision tree model is trained to automatically detect the overestimations in the satellite cloud masks. Cross-validated results show that 62±13 % of these overestimations can be identified by the model, reducing the systematic error in the satellite data sets from 14.4±15.5 % to 4.3±2.8 %. The amount of errors is lower, and, importantly, their distribution is more homogeneous as well. These corrections happen at the cost of a global increase of 7±2 % of missed clouds. Using this model, it is possible to significantly improve the cloud detection reliability in elevated areas in the Cloud_cci AVHRR-PM and MODIS-Aqua products.

scholarly journals A Survey of Changes in Cloud Cover and Cloud Types over Land from Surface Observations, 1971–96

2007 ◽  
Vol 20 (4) ◽  
pp. 717-738 ◽  
Author(s):  
Stephen G. Warren ◽  
Ryan M. Eastman ◽  
Carole J. Hahn
Keyword(s):  
Cloud Cover ◽  
Convective Cloud ◽  
The Arctic ◽  
Positive Trend ◽  
Interannual Variations ◽  
Total Cloud Cover ◽  
Northern Asia ◽  
The North ◽  
Trade Offs ◽  
The North Atlantic Oscillation

Abstract From a dataset of weather observations from land stations worldwide, about 5400 stations were selected as having long periods of record with cloud-type information; they cover all continents and many islands. About 185 million synoptic reports were analyzed for total cloud cover and the amounts of nine different cloud types, for the 26-yr period 1971–96. Monthly and seasonal averages were formed for day and night separately. Time series of total-cloud-cover anomalies for individual continents show a large decrease for South America, small decreases for Eurasia and Africa, and no trend for North America. The largest interannual variations (2.7%) are found for Australia, which is strongly influenced by ENSO. The zonal average trends of total cloud cover are positive in the Arctic winter and spring, 60°–80°N, but negative in all seasons at most other latitudes. The global average trend of total cloud cover over land is small, −0.7% decade−1, offsetting the small positive trend that had been found for the ocean, and resulting in no significant trend for the land–ocean average. Significant regional trends are found for many cloud types. The night trends agree with day trends for total cloud cover and for all cloud types except cumulus. Cirrus trends are generally negative over all continents. A previously reported decline in total cloud cover over China and its neighbors appears to be largely attributable to high and middle clouds. Global trends of the cloud types exhibit trade-offs, with convective cloud types increasing at the expense of stratiform clouds, in both the low and middle levels. Interannual variations over Europe, particularly of nimbostratus, are well correlated with the North Atlantic Oscillation; significant correlations are also found across northern Asia. Interannual variations in many parts of the Tropics are well correlated with an ENSO index. Little correlation was found with an index of smoke aerosol, in seven regions of seasonal biomass burning. In the middle latitudes of both hemispheres, seasonal anomalies of cloud cover are positively correlated with surface temperature in winter and negatively correlated in summer, as expected if the direction of causality is from clouds to temperature.

scholarly journals Reconstruction and analysis of erythemal UV radiation time series from Hradec Králové (Czech Republic) over the past 50 years

2017 ◽  
Author(s):  
Klára Čížková ◽  
Kamil Láska ◽  
Ladislav Metelka ◽  
Martin Staněk
Keyword(s):  
Time Series ◽  
Czech Republic ◽  
Uv Radiation ◽  
Total Ozone ◽  
Cloud Cover ◽  
Radiation Doses ◽  
Total Ozone Column ◽  
Ozone Column ◽  
Radiation Time ◽  
Very High

Abstract. This paper evaluates the variability of erythemal ultraviolet (EUV) radiation from Hradec Králové (Czech Republic) in the period 1964–2013. The EUV radiation time series was reconstructed using a radiative transfer model and additional empirical relationships with the root mean square error of 9.9 %. The reconstructed time series documented the increase in EUV radiation doses in the 1980s and the 1990s (up to 15 % per decade), which is linked to the steep decline in total ozone (10 % per decade). The changes of cloud cover were the major factor affecting the EUV radiation doses especially in the 1960s, 1970s, and at the beginning of the new millennium. The mean annual EUV radiation doses in the decade 2004–2013 declined by 5 %. The factors affecting the EUV radiation doses differed also according to the chosen integration period (daily, monthly, and annually): solar zenith angle was the most important for daily doses, cloud cover for their monthly means, and the annual means of EUV radiation doses were most influenced by total ozone column. The number of days with very high EUV radiation doses increased by 22 % per decade, the increase was statistically significant in all seasons except autumn. The occurrence of the days with very high EUV doses was influenced mostly by low total ozone column (82 % of days), clear-sky or partly cloudy conditions (74 % of days) and by increased surface albedo (19 % of days). The principal component analysis documented that the occurrence of days with very high EUV radiation doses was much affected by the positive phase of North Atlantic Oscillation with an Azores High promontory reaching over central Europe. In the stratosphere, a strong Arctic circumpolar vortex and also the meridional inflow of ozone-poor air from the south-west were favorable for the occurrence of days with very high EUV radiation doses. This is the first analysis of the relationship between the high EUV radiation doses and macro-scale circulation patterns, and therefore more attention should be given also to other dynamical variables that may affect the solar UV radiation on the Earth surface.

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