scholarly journals Validation of Avhrr and Modis ice Surface temperature products using in Situ radiometers

2006 ◽  
Vol 44 ◽  
pp. 345-351 ◽  
Author(s):  
Ted A. Scambos ◽  
Terry M. Haran ◽  
Robert Massom
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Skin Temperature ◽  
Mixed Pixel ◽  
Clear Sky ◽  
Helicopter Flight ◽  
Ice Surface ◽  
Surface Skin Temperature ◽  
Ice Surface Temperature

AbstractShip-borne and airborne infrared radiometric measurements during the Arise cruise of September–October 2003 permitted in Situ validation Studies of two Satellite-based ice Surface Skin temperature algorithms: the AVHRR Polar Pathfinder Ice Surface Temperature and the MODIS Sea Ice Surface Temperature. Observations of Sea ice from the Aurora Australis Ship’s rail using a KT-19.82 radiometer were conducted between 25 September and 21 October during clear-sky overflights by AVHRR (41 passes) and MODIS (17 passes) on their respective Satellite platforms. Data from both Sensors Show highly linear fits to 1 min integrated radiometer Spot measurements, Spanning the range 245–270 K with a ±1.4˚C, 1σ (AVHRR) and ±1.0˚C (MODIS) variation relative to a 1: 1 relationship. There was no Significant offset. Helicopter observations made with a KT-19.85 radiometer on three dates (8, 19 and 20 October) provided more data (236 gridcell Sites total), but over a more limited Sea-ice Skin temperature range (252–268 K), with higher variation (±1.7˚C, 1σ) due to mixed-pixel issues. Comparison of MODIS and AVHRR algorithms directly, with both images acquired during a helicopter flight, indicates very high correlation and near-unity Slope for the two Satellite-based algorithms. Ship air-temperature data during the validation indicated moderate to Strong inversions over Sea ice under clear Skies. These formed and decayed rapidly (tens of minutes) as clouds moved out of and into the zenith area.

scholarly journals Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

2012 ◽  
Vol 9 (2) ◽  
pp. 1009-1043 ◽  
Author(s):  
G. Dybkjær ◽  
R. Tonboe ◽  
J. Høyer
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Temperature Data ◽  
Coupled Systems ◽  
The Arctic ◽  
In Situ Observation ◽  
Clear Sky ◽  
Ice Surface ◽  
Ice Surface Temperature

Abstract. The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions are prevailing during spring in the Arctic while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveal that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measures complicates the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.

scholarly journals Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

Ocean Science ◽  
2012 ◽  
Vol 8 (6) ◽  
pp. 959-970 ◽  
Author(s):  
G. Dybkjær ◽  
R. Tonboe ◽  
J. L. Høyer
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Temperature Data ◽  
Coupled Systems ◽  
The Arctic ◽  
In Situ Observation ◽  
Clear Sky ◽  
Ice Surface ◽  
Ice Surface Temperature

Abstract. The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions prevail during spring in the Arctic, while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveals that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measurements complicate the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic, the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.

scholarly journals Deriving Arctic 2 m air temperatures over snow and ice from satellite surface temperature measurements

2021 ◽  
Author(s):  
Pia Nielsen-Englyst ◽  
Jacob L. Høyer ◽  
Kristine S. Madsen ◽  
Rasmus T. Tonboe ◽  
Gorm Dybkjær ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Arctic Region ◽  
Satellite Observations ◽  
The Arctic ◽  
Clear Sky ◽  
Ice Surface ◽  
Air Temperatures ◽  
In Situ Observations ◽  
The Arctic Region

Abstract. The Arctic region is responding heavily to climate change, and yet, the air temperature of ice covered areas in the Arctic is heavily under-sampled when it comes to in situ measurements, resulting in large uncertainties in existing weather- and reanalysis products. This paper presents a method for estimating daily mean clear sky 2 meter air temperatures (T2m) in the Arctic from satellite observations of skin temperature, using the Arctic and Antarctic ice Surface Temperatures from thermal Infrared (AASTI) satellite dataset, providing spatially detailed observations of the Arctic. The method is based on a linear regression model, which has been tuned against in situ observations to estimate daily mean T2m based on clear sky satellite ice surface skin temperatures. The daily satellite derived T2m product includes estimated uncertainties and covers clear sky snow and ice surfaces in the Arctic region during the period 2000–2009, provided on a 0.25 degree regular latitude-longitude grid. Comparisons with independent in situ measured T2m show average biases of 0.30 °C and 0.35 °C and average root mean square errors of 3.47 °C and 3.20 °C for land ice and sea ice, respectively. The associated uncertainties are verified to be very realistic for both land ice and sea ice, using in situ observations. The reconstruction provides a much better spatial coverage than the sparse in situ observations of T2m in the Arctic, is independent of numerical weather prediction model input and it therefore provides an important supplement to simulated air temperatures to be used for assimilation or global surface temperature reconstructions. A comparison between in situ T2m versus T2m derived from satellite and ERA-Interim/ERA5 estimates shows that the T2m derived from satellite observations validate similar or better than ERA-Interim/ERA5 in the Arctic.

scholarly journals Estimation of thin Sea-ice thickness from NOAA AVHRR data in a polynya off the Wilkes Land coast, East Antarctica

2006 ◽  
Vol 44 ◽  
pp. 269-274 ◽  
Author(s):  
Takeshi Tamura ◽  
Kay I. Ohshima ◽  
Hiroyuki Enomoto ◽  
Kazutaka Tateyama ◽  
Atsuhiro Muto ◽  
...  
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Meteorological Data ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Flux Calculation ◽  
Ice Surface ◽  
Wilkes Land ◽  
Ice Surface Temperature

AbstractAntarctic coastal polynyas are major areas of intense ocean–atmosphere heat and moisture flux, and associated high Sea-ice production and dense-water formation. Their accurate detection, including an estimate of thin ice thickness, is therefore very important. In this paper, we apply a technique originally developed in the Arctic to an estimation of Sea-ice thickness using Us National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data and meteorological data in the Vincennes Bay polynya off Wilkes Land, East Antarctica. The method is based upon the heat-flux calculation using Sea-ice Surface temperature estimates from the Satellite thermal-infrared data combined with global objective analysis (European Centre for Medium-Range Weather Forecasts (ECMWF)) data. The validity of this method is assessed by comparing results with independent ice-surface temperature and ice-thickness data obtained during an Australian-led research cruise to the region in 2003. In thin-ice (polynya) regions, ice thicknesses estimated by the heat-flux calculation using AVHRR and ECMWF data Show reasonable agreement with those estimated by (a) applying the heat-flux calculation to in Situ radiation thermometer and meteorological data and (b) in Situ observations. The Standard deviation of the difference between the AVHRR-derived and in Situ data is ∽0.02 m. Comparison of the AVHRR ice-thickness retrievals with coincident Satellite passive-microwave polarization ratio data confirms the potential of the latter as a means of deriving maps of thin Sea-ice thickness on the wider Scale, uninterrupted by darkness and cloud cover.

Sea ice surface temperature product from MODIS

2004 ◽  
Vol 42 (5) ◽  
pp. 1076-1087 ◽  
Author(s):  
D.K. Hall ◽  
J.R. Key ◽  
K.A. Case ◽  
G.A. Riggs ◽  
D.J. Cavalieri
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Ice Surface ◽  
Ice Surface Temperature
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