In situ observed relationships between snow and ice surface skin temperatures and 2 m air temperatures in the Arctic

Abstract. To facilitate the construction of a satellite-derived 2 m air temperature (T2 m) product for the snow- and ice-covered regions in the Arctic, observations from weather stations are used to quantify the relationship between the T2 m and skin temperature (Tskin). Multiyear data records of simultaneous Tskin and T2 m from 29 different in situ sites have been analysed for five regions, covering the lower and upper ablation zone and the accumulation zone of the Greenland Ice Sheet (GrIS), sea ice in the Arctic Ocean, and seasonal snow-covered land in northern Alaska. The diurnal and seasonal temperature variabilities and the impacts from clouds and wind on the T2 m–Tskin differences are quantified. Tskin is often (85 % of the time, all sites weighted equally) lower than T2 m, with the largest differences occurring when the temperatures are well below 0 ∘C or when the surface is melting. Considering all regions, T2 m is on average 0.65–2.65 ∘C higher than Tskin, with the largest differences for the lower ablation area and smallest differences for the seasonal snow-covered sites. A negative net surface radiation balance generally cools the surface with respect to the atmosphere, resulting in a surface-driven surface air temperature inversion. However, Tskin and T2 m are often highly correlated, and the two temperatures can be almost identical (<0.5 ∘C difference), with the smallest T2–Tskin differences around noon and early afternoon during spring, autumn and summer during non-melting conditions. In general, the inversion strength increases with decreasing wind speeds, but for the sites on the GrIS the maximum inversion occurs at wind speeds of about 5 m s−1 due to the katabatic winds. Clouds tend to reduce the vertical temperature gradient, by warming the surface, resulting in a mean overcast T2 m–Tskin difference ranging from −0.08 to 1.63 ∘C, with the largest differences for the sites in the low-ablation zone and the smallest differences for the seasonal snow-covered sites. To assess the effect of using cloud-limited infrared satellite observations, the influence of clouds on temporally averaged Tskin has been studied by comparing averaged clear-sky Tskin with averaged all-sky Tskin. To this end, we test three different temporal averaging windows: 24 h, 72 h and 1 month. The largest clear-sky biases are generally found when 1-month averages are used and the smallest clear-sky biases are found for 24 h. In most cases, all-sky averages are warmer than clear-sky averages, with the smallest bias during summer when the Tskin range is smallest.

Download Full-text

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

Ocean Science Discussions ◽

10.5194/osd-9-1009-2012 ◽

2012 ◽

Vol 9 (2) ◽

pp. 1009-1043 ◽

Cited By ~ 1

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.

Download Full-text

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

10.5194/tc-2021-38 ◽

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.

Download Full-text

In-situ sounding of radiation flux profiles through the Arctic lower troposphere

10.5194/amt-2018-173 ◽

2018 ◽

Cited By ~ 1

Author(s):

Ralf Becker ◽

Marion Maturilli ◽

Rolf Philipona ◽

Klaus Behrens

Keyword(s):

Surface Composition ◽

Lower Troposphere ◽

Time Frame ◽

The Arctic ◽

Heating Rates ◽

Heterogeneous Terrain ◽

Near Surface ◽

Clear Sky ◽

Radiation Fluxes

Abstract. In-situ profiles of all four net radiation components were obtained at Ny Ålesund/Svalbard (78.9° N, 11.9° E) in the time frame May 04–21, 2015. Measurements could be performed using adapted high quality instrumentation classified as secondary standard carried by a tethered balloon system. Balloon lifted measurements of albedo under clear sky conditions demonstrate the altitude dependence of this parameter over heterogeneous terrain. Depending on the surface composition within the sensor's footprint, the albedo over predominantly snow covered surfaces was found to decrease to 53.4 % and 35.8 % compared to 73.1 % and 78.8 % measured with near surface references, respectively. Albedo profiles show an all-sky maximum at 150 m above surface level, and an averaged vertical change rate of −2.1 %/100 m (clear sky) and −3.4 %/100 m (overcast) above. Profiling of arctic low-level clouds reveals distinct vertical gradients in all radiation fluxes but longwave upward. Observed radiative cooling at cloud top with heating rates of −53 to −84 K/d in subsequent observations tend to be lower than suggested by 1-D simulations.

Download Full-text

Evaluation of 2-m Air Temperature and Surface Temperature from ERA5 and ERA-I Using Buoy Observations in the Arctic during 2010–2020

Remote Sensing ◽

10.3390/rs13142813 ◽

2021 ◽

Vol 13 (14) ◽

pp. 2813

Author(s):

Yining Yu ◽

Wanxin Xiao ◽

Zhilun Zhang ◽

Xiao Cheng ◽

Fengming Hui ◽

...

Keyword(s):

Surface Temperature ◽

Air Temperature ◽

The Arctic ◽

Sea Ice Concentration ◽

Weather Forecasts ◽

Ice Concentration ◽

Medium Range ◽

In Situ Observations ◽

Two Temperature

In data-sparse regions such as the Arctic, atmospheric reanalysis is one of the key tools for understanding rapid climate change at the regional and global scales. The utility of reanalysis datasets based on data assimilation is affected by their accuracy and biases. Therefore, it is important to evaluate their performance. Here, we conduct inter-comparisons of two temperature variables, namely, the 2-m air temperature (Ta) and the surface temperature (Ts), from the widely used ERA-I and ERA5 reanalysis datasets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) against in situ observations from three international buoy programs (i.e., the International Arctic Buoy Programme (IABP), the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC), and the Cold Regions Research and Engineering Laboratory (CRREL)) during 2010–2020 in the Arctic. Overall, the results show that both the ERA-I and ERA5 were well correlated with the buoy observations, with the highest correlation coefficient reaching 0.98. There were generally warm Ta biases for both ERA-I (2.27 ± 3.33 °C) and ERA5 (2.34 ± 3.22 °C) when compared with more than 3000 matching pairs of daily buoy observations. The warm Ta biases of both reanalysis datasets exhibited seasonal variations, reaching the maximum of 3.73 ± 2.84 °C in April and the minimum of 1.36 ± 2.51 °C in September. For Ts, both ERA-I and ERA5 exhibited good consistencies with the buoy observations, but have higher amplitude biases compared with those for Ta, with generally negative biases of −4.79 ± 4.86 °C for ERA-I and −4.11 ± 3.92 °C for ERA5. For both reanalysis datasets, the largest bias of Ts (−11.18 ± 3.08 °C) occurred in December, while the biases were rather small (less than −3 °C) in the warmer months (April to October). The cold Ts biases for ERA-I and ERA5 were probably overestimated due to the location of the surface temperature sensors on the buoys, which may have been affected by snow cover. Both the Ta and Ts biases varied for different buoy programs and different sea ice concentration conditions, yet they exhibited similar trends.

Download Full-text

Near-surface thermal stratification during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

10.5194/tc-2017-195 ◽

2017 ◽

Author(s):

Alden C. Adolph ◽

Mary R. Albert ◽

Dorothy K. Hall

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Skin Temperature ◽

Air Temperature ◽

The Arctic ◽

Cold Bias ◽

Near Surface ◽

Surface Temperatures ◽

In Situ Ir

Abstract. As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures, but in remote locations where few ground-based measurements exist, such as on the Greenland Ice Sheet, temperatures over large areas are assessed using remote sensing techniques. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June through 18 July 2015, near Summit Station in Greenland to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, thermochrons, and thermocouples; 2 m air temperature measured by a NOAA meteorological station; and a MODerate-resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in-situ, and this finding may account for apparent biases in previous surface temperature studies of MODIS products that used 2 m air temperature for validation. This inversion is present during summer months when incoming solar radiation and wind speed are both low. As compared to our in-situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface-temperature standard product has an RMSE of 1.0 °C, spanning a range of temperatures from −35 °C to −5 °C. For our study area and time series, MODIS surface temperature products agree with skin surface temperatures better than previous studies indicated, especially at temperatures below −20 °C where other studies found a significant cold bias. The apparent cold bias present in others’ comparison of 2 m air temperature and MODIS surface temperature is perhaps a result of the near-surface temperature inversion that our data demonstrate. Further investigation of how in-situ IR skin temperatures compare to MODIS surface temperature at lower temperatures (below −35 °C) is warranted to determine if this cold bias does indeed exist.

Download Full-text

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

10.5194/tc-2019-126 ◽

2019 ◽

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 ◽

Ice Surface ◽

Air Temperatures ◽

In Situ Observations ◽

The Arctic Region ◽

Snow And Ice

Abstract. The Arctic region is responding heavily to climate change, and yet, the air temperature of Arctic, ice covered areas is heavily under-sampled when it comes to in situ measurements, and large uncertainties exist in weather- and reanalysis products. This paper presents a method for estimating daily mean 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 developed using in situ observations and daily mean satellite ice surface skin temperatures combined with a seasonal variation to estimate daily T2m. The satellite derived T2m product including estimated uncertainties covers clear sky snow and ice surfaces in the Arctic region during the period 2000–2009. Comparison with independent in situ measured T2m gives average correlations of 95.5 % and 96.5 % and average root mean square errors of 3.47 °C and 3.19 °C for land ice and sea ice, respectively. 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 alternative to simulated air temperatures to be used for assimilation or global surface temperature reconstructions. A comparison between in situ T2m versus T2m from satellite and ERA-Interim shows that the T2m derived from satellite observations validate similar or better than ERA-Interim estimates in the Arctic.

Download Full-text

Implications of surface flooding on airborne estimates of snow depth on sea ice

The Cryosphere ◽

10.5194/tc-15-2819-2021 ◽

2021 ◽

Vol 15 (6) ◽

pp. 2819-2833

Author(s):

Anja Rösel ◽

Sinead Louise Farrell ◽

Vishnu Nandan ◽

Jaqueline Richter-Menge ◽

Gunnar Spreen ◽

...

Keyword(s):

Sea Ice ◽

Validation Studies ◽

Snow Depth ◽

The Arctic ◽

Airborne Radar ◽

Ice Thickness ◽

Sea Ice Thickness ◽

Thickness Measurements ◽

Snow And Ice

Abstract. Snow depth observations from airborne snow radars, such as the NASA's Operation IceBridge (OIB) mission, have recently been used in altimeter-derived sea ice thickness estimates, as well as for model parameterization. A number of validation studies comparing airborne and in situ snow depth measurements have been conducted in the western Arctic Ocean, demonstrating the utility of the airborne data. However, there have been no validation studies in the Atlantic sector of the Arctic. Recent observations in this region suggest a significant and predominant shift towards a snow-ice regime caused by deep snow on thin sea ice. During the Norwegian young sea Ice, Climate and Ecosystems (ICE) expedition (N-ICE2015) in the area north of Svalbard, a validation study was conducted on 19 March 2015. This study collected ground truth data during an OIB overflight. Snow and ice thickness measurements were obtained across a two-dimensional (2-D) 400 m × 60 m grid. Additional snow and ice thickness measurements collected in situ from adjacent ice floes helped to place the measurements obtained at the gridded survey field site into a more regional context. Widespread negative freeboards and flooding of the snowpack were observed during the N-ICE2015 expedition due to the general situation of thick snow on relatively thin sea ice. These conditions caused brine wicking into and saturation of the basal snow layers. This causes the airborne radar signal to undergo more diffuse scattering, resulting in the location of the radar main scattering horizon being detected well above the snow–ice interface. This leads to a subsequent underestimation of snow depth; if only radar-based information is used, the average airborne snow depth was 0.16 m thinner than that measured in situ at the 2-D survey field. Regional data within 10 km of the 2-D survey field suggested however a smaller deviation between average airborne and in situ snow depth, a 0.06 m underestimate in snow depth by the airborne radar, which is close to the resolution limit of the OIB snow radar system. Our results also show a broad snow depth distribution, indicating a large spatial variability in snow across the region. Differences between the airborne snow radar and in situ measurements fell within the standard deviation of the in situ data (0.15–0.18 m). Our results suggest that seawater flooding of the snow–ice interface leads to underestimations of snow depth or overestimations of sea ice freeboard measured from radar altimetry, in turn impacting the accuracy of sea ice thickness estimates.

Download Full-text

Snow-depth observations by adventurers traveling on Arctic sea ice

Annals of Glaciology ◽

10.3189/172756411795931552 ◽

2011 ◽

Vol 52 (57) ◽

pp. 369-376 ◽

Cited By ~ 12

Author(s):

Sebastian Gerland ◽

Christian Haas

Keyword(s):

Sea Ice ◽

Arctic Ocean ◽

Snow Depth ◽

Arctic Basin ◽

Arctic Sea Ice ◽

The Arctic ◽

Ice Thickness ◽

Snow Thickness ◽

Snow And Ice

AbstractSnow depth is a key parameter for assessing the sea-ice mass budget in the Arctic and for the surface energy balance at the atmosphere–snow–ice–ocean interfaces. However, scientific expeditions to the high Arctic Ocean are rare, and for large parts of the year no snow and ice data are collected in situ in most regions. Therefore any additional in situ observations of snow depth are of interest to the scientific community. Arctic adventurers and tourists are among the most frequent visitors to the Arctic Ocean and North Pole. If properly trained and carefully adhering to standard protocols, they could collect valuable snow-depth data from large regions. Here we analyse such data from four Arctic basin ski traverses carried out between 1994 and 2007. Individual datasets show characteristic regional differences of snow thickness, which provide invaluable information for the validation of models and satellite data. the observations were made applying a continuously upgraded observation guideline scheme. Earlier observations were based on a relatively broad view of easily observable snow and ice parameters. Improvements included requirements of more detailed snow-thickness surveys in order to observe the spatial variability over varying sea-ice surfaces in a better way. Possibilities for, and limitations of, ice-thickness estimates and measurements are also discussed. Often, assessment of ice thickness is more problematic since measurements are either time-consuming or biased, meaning that possibilities for collecting large datasets are limited.

Download Full-text

Metabolic response to wind of downy chicks of Arctic-breeding shorebirds(Scolopacidae)

Journal of Experimental Biology ◽

10.1242/jeb.205.22.3435 ◽

2002 ◽

Vol 205 (22) ◽

pp. 3435-3443 ◽

Cited By ~ 1

Author(s):

George S. Bakken ◽

Joseph B. Williams ◽

Robert E. Ricklefs

Keyword(s):

Wind Speed ◽

Air Temperature ◽

Heat Production ◽

Metabolic Response ◽

Evaporative Cooling ◽

Thermal Conductance ◽

The Arctic ◽

Evaporative Water ◽

Near Surface ◽

Wind Speeds

SUMMARYWind is a significant factor in the thermoregulation of chicks of shorebirds on the Arctic tundra. We investigated the effect of wind at speeds typical of near-surface conditions (0.1-3 ms-1) on metabolic heat production, evaporative cooling and thermal conductance of 1- to 3- week-old downy scolopacid chicks (least sandpiper Calidris minutilla;short-billed dowitcher Limnodromus griseus; whimbrel Numenius phaeopus). Body mass ranged from 9 to 109 g. To accurately measure the interacting effects of air temperature and wind speed, we used two or more air temperatures between 15° and 30°C that produced cold stress at all wind speeds, but allowed chicks to maintain normal body temperature(approximately 39°C). Thermal conductance increased by 30-50% as wind speed increased from 0.1 to 3 ms-1. Conductance in these chicks is somewhat lower than that of 1-day-old mallard ducklings of similar mass, but higher than values reported for downy capercaillie and Xantus' murrelet chicks, as well as for adult shorebirds. Evaporative water loss was substantial and increased with mass and air temperature. We developed a standard operative temperature scale for shorebird chicks. The ratio of evaporative cooling to heat production varied with wind speed and air temperature.

Download Full-text

In situ observed relationships between skin temperatures and 2 m air temperatures in the Arctic

10.5194/tc-2018-150 ◽

2018 ◽

Cited By ~ 2

Author(s):

Pia Nielsen-Englyst ◽

Jacob L. Høyer ◽

Kristine S. Madsen ◽

Gorm Dybkjær ◽

Rasmus Tonboe ◽

...

Keyword(s):

Greenland Ice Sheet ◽

The Arctic ◽

Seasonal Temperature ◽

Air Temperatures ◽

Combined Use ◽

Two Temperatures ◽

Highly Correlated ◽

The Relationship ◽

Skin Temperatures

Abstract. To facilitate the combined use of traditional 2 m air temperature (T2m) observations from weather stations in the Arctic and skin temperature (Tskin) observations from satellites the relationship between high latitude snow and ice Tskin and T2m is quantified. Multiyear data records of simultaneous Tskin and T2m from 20 different in situ sites have been analysed, covering the Greenland Ice Sheet (GrIS), sea ice in the Arctic Ocean, and coastal snow covered land in North Alaska. The diurnal and seasonal temperature variabilities and the impacts from clouds and wind on the T2m-Tskin differences are quantified. Considering all stations, T2m is on average 1.37 °C warmer than Tskin, with the largest differences at the GrIS stations (mean of diff. of 1.64 °C). Tskin and T2m are often highly correlated, and the two temperatures are almost identical (

Download Full-text