scholarly journals A Method to Estimate Open Pack-Ice Thickness from Two-Day Sequences of Side-Lapping Satellite Images

1987 ◽  
Vol 9 ◽  
pp. 69-71 ◽  
Author(s):  
Uri Feldman
Keyword(s):  
Surface Wind ◽  
Microwave Remote Sensing ◽  
Surface Wind Speed ◽  
Ice Thickness ◽  
In Situ Observation ◽  
Pack Ice ◽  
Upper Limits ◽  
Ice Floes ◽  
Active Microwave Remote Sensing

A method to estimate open pack ice thickness drifting in a marginal ice zone (MIZ) is presented, The estimates are obtained from two-day sequences of sidelapping Landsat-1 MSS images and two-day sequences of wind field data by four steps: estimating the surface wind speed, estimating the angle of sea ice deflection, estimating three ratios between ice parameters and estimating the lower and upper limits of pack ice thickness. The method has been applied to six groups of open pack ice floes drifting in the MIZ of the Beaufort Sea during 1973–1975. In the absence of simultaneous in-situ observation, the results have not been tested, The method presented may be applied to any MIZ. Rather than using Landsat-1 MSS images, data from a high resolution active microwave remote sensing system should be employed in the future as its data will be independent of sun illumination and cloud cover.

scholarly journals A Method to Estimate Open Pack-Ice Thickness from Two-Day Sequences of Side-Lapping Satellite Images

1987 ◽  
Vol 9 ◽  
pp. 69-71
Author(s):  
Uri Feldman
Keyword(s):  
Surface Wind ◽  
Microwave Remote Sensing ◽  
Surface Wind Speed ◽  
Ice Thickness ◽  
In Situ Observation ◽  
Pack Ice ◽  
Upper Limits ◽  
Ice Floes ◽  
Active Microwave Remote Sensing

A method to estimate open pack ice thickness drifting in a marginal ice zone (MIZ) is presented, The estimates are obtained from two-day sequences of sidelapping Landsat-1 MSS images and two-day sequences of wind field data by four steps: estimating the surface wind speed, estimating the angle of sea ice deflection, estimating three ratios between ice parameters and estimating the lower and upper limits of pack ice thickness. The method has been applied to six groups of open pack ice floes drifting in the MIZ of the Beaufort Sea during 1973–1975. In the absence of simultaneous in-situ observation, the results have not been tested, The method presented may be applied to any MIZ. Rather than using Landsat-1 MSS images, data from a high resolution active microwave remote sensing system should be employed in the future as its data will be independent of sun illumination and cloud cover.

scholarly journals The sensitivity of landfast sea ice to atmospheric forcing in single-column model simulations: a case study at Zhongshan Station, Antarctica

2021 ◽  
Author(s):  
Fengguan Gu ◽  
Qinghua Yang ◽  
Frank Kauker ◽  
Changwei Liu ◽  
Guanghua Hao ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Zhongshan Station ◽  
Single Column ◽  
In Situ Observations

Abstract. Single-column sea ice models are used to focus on the thermodynamic evolution of the ice. Generally these models are forced by atmospheric reanalysis in absence of atmospheric in situ observations. Here we assess the sea ice thickness (SIT) simulated by a single-column model (ICEPACK) with in situ observations obtained off Zhongshan Station for the austral winter of 2016. In the reanalysis the surface air temperature is about 1 °C lower, the total precipitation is about 2 mm day−1 larger, and the surface wind speed is about 2 m s−1 higher compared to the in situ observations, respectively. Using sensitivity experiments we evaluate the simulation bias in sea ice thickness due to the uncertainty in the individual atmospheric forcing variables. We show that the unrealistic precipitation in the reanalysis leads to a bias of 14.5 cm in sea ice thickness and of 17.3 cm in snow depth. In addition, our data show that increasing snow depth works to gradually inhibits the growth of sea ice associated with thermal blanketing by the snow due to changing the vertical heat flux. Conversely, given suitable conditions, the sea ice thickness may grow suddenly when the snow load gives rise to flooding and leads to snow-ice formation. A potential mechanism to explain the different characteristics of the precipitation bias on snow and sea ice is discussed. The flooding process for landfast sea ice might cause different effect compared to pack ice, thus need to be reconsidered in ICEPACK. Meanwhile, the overestimation in surface wind speed in reanalysis is likely responsible for the underestimation in simulated snow depth, however this had little influence on the modelled ice thickness.

In-situ automatic observations of ice thickness of seas

2012 ◽  
Vol 19 (3) ◽  
pp. 583-592 ◽  
Author(s):  
Yinke Dou ◽  
Xiaomin Chang
Keyword(s):  
Sea Ice ◽  
New Technologies ◽  
Capacitive Sensor ◽  
Automatic Monitoring ◽  
Ice Thickness ◽  
In Situ Observation ◽  
Glacier Surface ◽  
Sea Ice Thickness ◽  
Surface Ice

Abstract Ice thickness is one of the most critical physical indicators in the ice science and engineering. It is therefore very necessary to develop in-situ automatic observation technologies of ice thickness. This paper proposes the principle of three new technologies of in-situ automatic observations of sea ice thickness and provides the findings of laboratory applications. The results show that the in-situ observation accuracy of the monitor apparatus based on the Magnetostrictive Delay Line (MDL) principle can reach ±2 mm, which has solved the “bottleneck” problem of restricting the fine development of a sea ice thermodynamic model, and the resistance accuracy of monitor apparatus with temperature gradient can reach the centimeter level and research the ice and snow substance balance by automatically measuring the glacier surface ice and snow change. The measurement accuracy of the capacitive sensor for ice thickness can also reach ±4 mm and the capacitive sensor is of the potential for automatic monitoring the water level under the ice and the ice formation and development process in water. Such three new technologies can meet different needs of fixed-point ice thickness observation and realize the simultaneous measurement in order to accurately judge the ice thickness.

scholarly journals Numerical Simulation of Near-Surface Wind during a Severe Wind Event in a Complex Terrain by Multisource Data Assimilation and Dynamic Downscaling

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
De Zhang ◽  
Luyuan Chen ◽  
Feimin Zhang ◽  
Juan Tan ◽  
Chenghai Wang
Keyword(s):  
Wind Speed ◽  
Data Assimilation ◽  
Surface Wind ◽  
Wrf Model ◽  
Surface Wind Speed ◽  
Dynamic Downscaling ◽  
Near Surface ◽  
Wind Event ◽  
Weak Wind

Accurate forecast and simulation of near-surface wind is a great challenge for numerical weather prediction models due to the significant transient and intermittent nature of near-surface wind. Based on the analyses of the impact of assimilating in situ and Advanced Tiros Operational Vertical Sounder (ATOVS) satellite radiance data on the simulation of near-surface wind during a severe wind event, using the new generation mesoscale Weather Research and Forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation system, the dynamic downscaling of near-surface wind is further investigated by coupling the microscale California Meteorological (CALMET) model with the WRF and its 3DVAR system. Results indicate that assimilating in situ and ATOVS radiance observations strengthens the airflow across the Alataw valley and triggers the downward transport of momentum from the upper atmosphere in the downstream area of the valley in the initial conditions, thus improving near-surface wind simulations. Further investigations indicate that the CALMET model provides more refined microtopographic structures than the WRF model in the vicinity of the wind towers. Although using the CALMET model achieves the best simulation of near-surface wind through dynamic downscaling of the output from the WRF and its 3DVAR assimilation, the simulation improvements of near-surface wind speed are mainly within 1 m s−1. Specifically, the mean improvement proportions of near-surface wind speed are 64.8% for the whole simulation period, 58.7% for the severe wind period, 68.3% for the severe wind decay period, and 75.4% for the weak wind period. The observed near-surface wind directions in the weak wind conditions are better simulated in the coupled model with CALMET downscaling than in the WRF and its 3DVAR system. It is concluded that the simulation improvements of CALMET downscaling are distinct when near-surface winds are weak, and the downscaling effects are mainly manifested in the simulation of near-surface wind directions.

An Inverse Model for Sea Ice Thickness Retrieval Using Active Microwave Remote Sensing

PIERS Online ◽  
2008 ◽  
Vol 4 (8) ◽  
pp. 896-900 ◽  
Author(s):  
Yu Jen Lee ◽  
Wee Keong Lim ◽  
Hong Tat Ewe ◽  
Hean Teik Chuah
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Microwave Remote Sensing ◽  
Inverse Model ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Active Microwave Remote Sensing

scholarly journals Remote sensing of sea ice: advances during the DAMOCLES project

2012 ◽  
Vol 6 (6) ◽  
pp. 1411-1434 ◽  
Author(s):  
G. Heygster ◽  
V. Alexandrov ◽  
G. Dybkjær ◽  
W. von Hoyningen-Huene ◽  
F. Girard-Ardhuin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Estimation Method ◽  
Satellite Observations ◽  
Microwave Emission ◽  
The Arctic ◽  
Ice Thickness ◽  
In Situ Observation ◽  
Microwave Emissivity

Abstract. In the Arctic, global warming is particularly pronounced so that we need to monitor its development continuously. On the other hand, the vast and hostile conditions make in situ observation difficult, so that available satellite observations should be exploited in the best possible way to extract geophysical information. Here, we give a résumé of the sea ice remote sensing efforts of the European Union's (EU) project DAMOCLES (Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies). In order to better understand the seasonal variation of the microwave emission of sea ice observed from space, the monthly variations of the microwave emissivity of first-year and multi-year sea ice have been derived for the frequencies of the microwave imagers like AMSR-E (Advanced Microwave Scanning Radiometer on EOS) and sounding frequencies of AMSU (Advanced Microwave Sounding Unit), and have been used to develop an optimal estimation method to retrieve sea ice and atmospheric parameters simultaneously. In addition, a sea ice microwave emissivity model has been used together with a thermodynamic model to establish relations between the emissivities from 6 GHz to 50 GHz. At the latter frequency, the emissivity is needed for assimilation into atmospheric circulation models, but is more difficult to observe directly. The size of the snow grains on top of the sea ice influences both its albedo and the microwave emission. A method to determine the effective size of the snow grains from observations in the visible range (MODIS) is developed and demonstrated in an application on the Ross ice shelf. The bidirectional reflectivity distribution function (BRDF) of snow, which is an essential input parameter to the retrieval, has been measured in situ on Svalbard during the DAMOCLES campaign, and a BRDF model assuming aspherical particles is developed. Sea ice drift and deformation is derived from satellite observations with the scatterometer ASCAT (62.5 km grid spacing), with visible AVHRR observations (20 km), with the synthetic aperture radar sensor ASAR (10 km), and a multi-sensor product (62.5 km) with improved angular resolution (Continuous Maximum Cross Correlation, CMCC method) is presented. CMCC is also used to derive the sea ice deformation, important for formation of sea ice leads (diverging deformation) and pressure ridges (converging). The indirect determination of sea ice thickness from altimeter freeboard data requires knowledge of the ice density and snow load on sea ice. The relation between freeboard and ice thickness is investigated based on the airborne Sever expeditions conducted between 1928 and 1993.

Dependence of mesoscale patterns of Trade-wind clouds on environmental conditions: an investigation using satellite and in-situ observations

2020 ◽  
Author(s):  
Sandrine Bony ◽  
Hauke Schulz ◽  
Jessica Vial ◽  
Bjorn Stevens ◽  
Keyword(s):  
Meteorological Data ◽  
Surface Wind ◽  
Cloud Amount ◽  
Surface Wind Speed ◽  
Trade Wind ◽  
Shallow Convection ◽  
Western Atlantic ◽  
Near Surface ◽  
Cloud Patterns

<p>Trade-wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as Flowers, Fish, Gravel and Sugar. By using 19 years of satellite and meteorological data, we show that these four patterns can be identified objectively from satellite observations, and that on daily and interannual timescales, the near-surface wind speed and the strength of the lower-tropospheric stability discriminate the occurrence of the different organization patterns. Moreover, we point out a tight relationship between cloud patterns, low-level cloud amount and cloud-radiative effects. The EUREC4A field study taking place upwind of Barbados in Jan-Feb 2020 offers an opportunity to investigate these relationships from an in-situ and process-oriented perspective. Preliminary results will be discussed.</p>

Estimating the surface wind speed over drifting pack ice from surface weather charts

1979 ◽  
Vol 16 (4) ◽  
pp. 421-429 ◽  
Author(s):  
Uri Feldman ◽  
Philip J. Howarth ◽  
John A. Davies
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Pack Ice ◽  
Surface Weather

scholarly journals Evaluation of Global Reanalysis Land Surface Wind Speed Trends to Support Wind Energy Development Using In Situ Observations

2021 ◽  
Vol 60 (1) ◽  
pp. 33-50
Author(s):  
Wenxin Fan ◽  
Yi Liu ◽  
Adrian Chappell ◽  
Li Dong ◽  
Rongrong Xu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Land Surface ◽  
Turning Point ◽  
Surface Wind ◽  
Energy Resource ◽  
Surface Wind Speed ◽  
Wind Speeds ◽  
Global Reanalysis

AbstractGlobal reanalysis products are important tools across disciplines to study past meteorological changes and are especially useful for wind energy resource evaluations. Studies of observed wind speed show that land surface wind speed declined globally since the 1960s (known as global terrestrial stilling) but reversed with a turning point around 2010. Whether the declining trend and the turning point have been captured by reanalysis products remains unknown so far. To fill this research gap, a systematic assessment of climatological winds and trends in five reanalysis products (ERA5, ERA-Interim, MERRA-2, JRA-55, and CFSv2) was conducted by comparing gridcell time series of 10-m wind speed with observational data from 1439 in situ meteorological stations for the period 1989–2018. Overall, ERA5 is the closest to the observations according to the evaluation of climatological winds. However, substantial discrepancies were found between observations and simulated wind speeds. No reanalysis product showed similar change to that of the global observations, although some showed regional agreement. This discrepancy between observed and reanalysis land surface wind speed indicates the need for prudence when using reanalysis products for the evaluation and prediction of winds. The possible reasons for the inconsistent wind speed trends between reanalysis products and observations are analyzed. The results show that wind energy production should select different products for different regions to minimize the discrepancy with observations.

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