Sea ice extent variability, a measure based on satellite-derived sea ice concentration measurements, has traditionally been used as an indicator to ev…Sea ice extent variability, a measure based on satellite-derived sea ice concentration measurements, has traditionally been used as an indicator to evaluate the impact of climate change on polar regions. However, concentration-based measurements of ice variability do not allow the discrimination of the relative contributions made by thermodynamic and dynamic processes, prompting the need to use sea ice drift products and develop methods to quantify changes in sea ice dynamics that would indicate trends in the ice characteristics. Here, we present a new method to automate the detection of rotational drift features in Antarctic sea ice from space at spatial and temporal scales comparable to that of polar weather. This analysis focusses on drift features in the Atlantic sector of the Southern Ocean in the period 2013-2020 using currently available satellite ice motion products from EUMETSAT OSI SAF. We observe a large discrepancy between cyclonic and anticyclonic drift features, with cyclonic features typically exhibiting larger drift intensity and spatial variability according to all products. The mean intensity of the 95th percentile of cyclonic features is 1.52.0 times larger for cyclonic features than anticyclonic features. The spatial variability of cyclonic features increased with intensity, indicating that the most intense cyclonic features are also the least homogenous. There is good agreement between products in detecting anticyclonic features; however, larger disagreement is evident for cyclonic features, with the merged product showing the most intense 95th percentile threshold and largest spatial variability, likely due to the more extended coverage of valid vorticity points. A time series analysis of the 95th percentile shows an abrupt intensification of cyclonic features from 2014-2017, which coincides with the record decline in Antarctic sea ice extent since winter of 2015. Our results indicate the need for systematic assessments of sea ice drift products against dedicated observational experiments in the weather-dominated Atlantic sector. Such information will allow us to confirm whether the detected increase in cyclonic vorticity is linked to rapidly changing atmospheric changes driven by sea ice dynamics and establish the measure of rotational sea ice drift as a potential indicator of weather-driven variability in Antarctic sea ice.more
Downward short- and longwave incoming irradiances play a key role in the radiation budget at the Earth's surface. Monitoring these parameters is essen…Downward short- and longwave incoming irradiances play a key role in the radiation budget at the Earth's surface. Monitoring these parameters is essential for understanding the basic mechanisms involved in climate change, such as the greenhouse effect, global dimming, and changes in cloud cover and precipitation. Geostationary satellite observations are important in the retrieval of irradiance at the surface, providing excellent spatial and temporal coverage. Three decentralized Satellite Application Facilities (SAFs) are currently operational in the European Organisation for the Exploitation of Meteorological Satellites (Eumetsat), involved in retrieving surface solar irradiance (SSI) and downward longwave irradiance (DLI) from Meteosat images. This study presents a common validation of these radiation products against ground data from eight stations covering four months representative of the annual declination variation. The overall conclusion is that the products of the different SAFs are comparable in terms of bias and standard deviation. The SSI is retrieved with a standard deviation of 80–100 W m−2 and negligible bias, and the DLI with a standard deviation of 25 W m−2 with a slight site-dependent bias.more
This review paper discusses how to develop, produce, sustain, and serve satellite climate data records (CDRs) in the context of transitioning research…This review paper discusses how to develop, produce, sustain, and serve satellite climate data records (CDRs) in the context of transitioning research to operation (R2O). Requirements and critical procedures of producing various CDRs, including Fundamental CDRs (FCDRs), Thematic CDRs (TCDRs), Interim CDRs (ICDRs), and climate information records (CIRs) are discussed in detail, including radiance/reflectance and the essential climate variables (ECVs) of land, ocean, and atmosphere. Major international CDR initiatives, programs, and projects are summarized. Societal benefits of CDRs in various user sectors, including Agriculture, Forestry, Fisheries, Energy, Heath, Water, Transportation, and Tourism are also briefly discussed. The challenges and opportunities for CDR development, production and service are also addressed. It is essential to maintain credible CDR products by allowing free access to products and keeping the production process transparent by making source code and documentation available with the dataset.more
We report on results of an intercomparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from satellite pa…We report on results of an intercomparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from satellite passive microwave (PMW) observations. For this we use SIC estimated from > 350 images acquired in the visible-near-infrared frequency range by the joint National Aeronautics and Space Administration (NASA) and United States Geological Survey (USGS) Landsat sensor during the years 2003-2011 and 2013-2015. Conditions covered are late winter/early spring in the Northern Hemisphere and from late winter through fall freeze-up in the Southern Hemisphere. Among the products investigated are the four products of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) and European Space Agency (ESA) Climate Change Initiative (CCI) algorithms SICCI-2 and OSI450. We stress the importance to consider intercomparison results across the entire SIC range instead of focusing on overall mean differences and to take into account known biases in PMW SIC products, e.g., for thin ice. We find superior linear agreement between PMW SIC and Landsat SIC for the 25 and the 50 km SICCI-2 products in both hemispheres. We discuss quantitatively various uncertainty sources of the evaluation carried out. First, depending on the number of mixed ocean-ice Landsat pixels classified erroneously as ice only, our Landsat SIC is found to be biased high. This applies to some of our Southern Hemisphere data, promotes an overly large fraction of Landsat SIC underestimation by PMW SIC products, and renders PMW SIC products overestimating Landsat SIC particularly problematic. Secondly, our main results are based on SIC data truncated to the range 0 % to 100 %. We demonstrate using non-truncated SIC values, where possible, can considerably improve linear agreement between PMW and Landsat SIC. Thirdly, we investigate the impact of filters often used to clean up the final products from spurious SIC over open water due to weather effects and along coastlines due to land spillover. Benefiting from the possibility to switch on or off certain filters in the SICCI-2 and OSI-450 products, we quantify the impact land spillover filtering can have on evaluation results as shown in this paper.more
The present work is aimed at gaining more knowledge on the nature of the relation between land surface temperature (LST) as a biophysical parameter, w…The present work is aimed at gaining more knowledge on the nature of the relation between land surface temperature (LST) as a biophysical parameter, which is related to the coupled effect of the energy and water cycles, and fire activity over Bulgaria, in the Eastern Mediterranean. In the ecosystems of this area, prolonged droughts and heat waves create preconditions in the land surface state that increase the frequency and intensity of landscape fires. The relationships between the spatial–temporal variability of LST and fire activity modulated by land cover types and Soil Moisture Availability (SMA) are quantified. Long-term (2007–2018) datasets derived from geostationary MSG satellite observations are used: LST retrieved by the LSASAF LST product; fire activity assessed by the LSASAF FRP-Pixel product. All fires in the period of July–September occur in days associated with positive LST anomalies. Exponential regression models fit the link between LST monthly means, LST positive anomalies, LST-T2 (as a first proxy of sensible heat exchange with atmosphere), and FRP fire characteristics (number of detections; released energy FRP, MW) at high correlations. The values of biophysical drivers, at which the maximum FRP (MW) might be expected at the corresponding probability level, are identified. Results suggest that the biophysical index LST is sensitive to the changes in the dynamics of vegetation fire occurrence and severity. Dependences are found for forest, shrubs, and cultivated LCs, which indicate that satellite IR retrievals of radiative temperature is a reliable source of information for vegetation dryness and fire activity.more
Site-specific satellite-derived hourly global horizontal irradiance is compared with that obtained from extrapolation and interpolation of values meas…Site-specific satellite-derived hourly global horizontal irradiance is compared with that obtained from extrapolation and interpolation of values measured by ground-based weather stations. A national assessment of three satellite models and two ground-based techniques is described. A number of physiographic factors are examined to allow identification of the optimal resource. The chief influences are determined as: factors associated with latitude; terrain ruggedness; and weather station clustering/density. Whilst these factors act in combination, weather station density was found to be fundamental for a country like the UK, with its ever-changing weather. The decision between satellite and ground-based irradiance data based on accuracy is not straightforward. It depends on the exactitude of the selected satellite model and the concentration of pyranometric stations.more