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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Relationship between circum-Arctic atmospheric wave patterns and large-scale wildfires in boreal summer

Long-term assessment of severe wildfires and associated air pollution and related climate patterns in and around the Arctic is essential for assessing healthy human life status. To examine the relationships, we analyzed the National Aeronautics and Space Administration (NASA) modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Our investigation based on this state-of-the-art atmospheric reanalysis data reveals that 13 out of the 20 months with the highest PM2.5 (corresponding to the highly elevated organic carbon in the particulate organic matter [POM] form) monthly mean mass concentration over the Arctic for 2003–2017 were all in summer (July and August), during which POM of ⩾0.5 μg/cu. m and PM2.5 were positively correlated. This correlation suggests that high PM2.5 in the Arctic is linked to large wildfire contributions and characterized by significant anticyclonic anomalies (i.e. clockwise atmospheric circulation) with anomalous surface warmth and drier conditions over Siberia and subpolar North America, in addition to Europe. A similar climate pattern was also identified through an independent regression analysis for the July and August mean data between the same atmospheric variables and the sign-reversed Scandinavian pattern index. We named this pattern of recent atmospheric circulation anomalies the circum-Arctic wave (CAW) pattern as a manifestation of eastward group-velocity propagation of stationary Rossby waves (i.e. large-scale atmospheric waves). The CAW induces concomitant development of warm anticyclonic anomalies over Europe, Siberia, Alaska, and Canada, as observed in late June 2019. Surprisingly, the extended regression analysis of the 1980–2017 period revealed that the CAW pattern was not prominent before 2003. Understanding the CAW pattern under future climate change and global warming would lead to better prediction of co-occurrences of European heatwaves and large-scale wildfires with air pollution over Siberia, Alaska, and Canada in and around the Arctic in summer.

wildfire↗
NASA NTRS2020

Arctic Ocean Primary Productivity: The Response of Marine Algae to Climate Warming and Sea Ice Decline

Autotrophic single-celled algae living in sea ice (ice algae) and water column (phytoplankton) are the main primary producers in the Arctic Ocean. Through photosynthesis, they transform dissolved inorganic carbon into organic material. Consequently, primary production provides a key ecosystem service by providing energy to the entire food web in the oceans. Primary productivity is strongly dependent upon light availability and the presence of nutrients, and thus is highly seasonal in the Arctic. The melting and retreat of sea ice during spring are strong drivers of primary production in the Arctic Ocean and its adjacent shelf seas, owing to enhanced light availability and stratification (Barber et al. 2015; Leu et al. 2015; Ardyna et al. 2017). Recent studies have emphasized that primary production occurs under lower light conditions and earlier in the seasonal cycle than previously recognized (Randelhoff et al. 2020). Other studies suggest that increased nutrient supply have also influenced overall production (Henley et al. 2020; Lewis et al. 2020). Furthermore, while declines in Arctic sea ice extent over the past several decades (see essay Sea Ice) have contributed substantially to shifts in primary productivity throughout the Arctic Ocean, the response of primary production to sea ice loss has been both seasonally and spatially variable (e.g., Tremblay et al. 2015; Hill et al. 2018). Here we present satellite-based estimates of algal chlorophyll-a (occurring in all species of phytoplankton), based on ocean color, and subsequently provide calculated primary production estimates. These results are shown for ocean areas with less than 10% sea ice concentration and, therefore, do not include production by sea ice algae or under-ice phytoplankton blooms, which can be significant (e.g., Lalande et al. 2019).

K. E. Frey↗
NASA NTRSDate not supplied

The Influence of Sea ice on Arctic Cloud Properties: What Can We Learn by Applying a In Situ Observational Strategy to Satellite Data?

Sea ice is declining because of anthropogenic climate change. This change alters many aspects of the Arctic climate system, including the way that the surface and atmosphere interact. Atmosphere-surface coupling processes represent an important cloud feedback mechanism that can alter the Arctic surface energy budget. For the Arctic, it has been hypothesized that a reduction in sea ice cover could lead to an increase in clouds. If this process were to occur as originally hypothesized, sea ice loss in all seasons would lead to an increase in clouds. Recent observational studies find a cloud response to sea ice loss in non-summer months and no cloud response in summer months. However, previous studies rely on inter-annual variability and reanalysis to control for the influence of meteorology, reducing the confidence in the resulting conclusions. We adopt a phenomenological, event-based approach that does not need to use meteorological reanalysis. The approach analyzes cloud properties derived from CALIPSO-CloudSat over sea ice and adjacent ice-free footprints by compositing individual satellite ground tracks that cross the Arctic sea ice edge. The underlying assumption, which we verify, is that footprints that are close to each other in space and time experience similar large-scale meteorological conditions. Our results show larger cloud fraction and more cloud liquid water over ice-free than over sea ice footprints and provide additional evidence for a seasonal dependence of cloud-sea ice coupling that is in line with previous work. We find a different result where the maximum cloud property differences between sea ice and ice-free ocean occurs in spring, not fall as earlier studies suggest. We argue that these cloud differences between sea ice and ice-free ocean are primarily caused by the influence of the surface type on the thermodynamic stability of the lower troposphere and not principally from an increase in surface evaporation. In addition, we explore the sensitivity of these results to marginal ice zone width, season, Atlantic vs. Pacific sector, and the cloud property dependence on the distance from the sea ice edge. Overall, our results provide further evidence that cloud-sea ice coupling processes are not offsetting the observed surface energy budget perturbation due to sea ice loss in summer; thus, the cloud response to declining sea ice appears to contribute to amplified Arctic warming.

Patrick C Taylor↗
NASA NTRSDate not supplied

Arctic Amplification: Process Drivers and Sources of Uncertainty

Arctic amplification (AA) is a coupled atmosphere-sea ice-ocean process. This understanding has evolved from the early concept of AA, as a consequence of snow ice line progressions, through more than a century of research that has clarified the relevant processes and driving mechanisms of AA. The predictions made by early modeling studies, namely the fall/winter maximum, bottom-heavy structure, the prominence of surface albedo feedback, and the importance of stable stratification have withstood the scrutiny of multi-decadal observations and more complex models. Yet, the uncertainty in Arctic climate projections is larger than in any other region of the planet, making the assessment of high-impact, near-term regional changes difficult or impossible. Reducing this large spread in Arctic climate projections requires a quantitative process understanding. This presentation synthesizes current knowledge of AA and describes a set of recommendations to guide future research. It briefly reviews the history of AA science, summarizes observed Arctic changes, discusses modeling approaches and feedback diagnostics, and assesses the current understanding of the most relevant feedbacks to AA. These sections culminate in a conceptual model of the fundamental physical mechanisms causing AA and a collection of recommendations to accelerate progress towards reduced uncertainty in Arctic climate projections. Our conceptual model highlights the need to account for local feedback and remote process interactions within the context of the annual cycle to constrain projected AA.

Patrick C Taylor↗
NASA NTRSDate not supplied

Non-Additivity of the Midlatitude Circulation Response to Regional Arctic Temperature Anomalies: The Role of the Stratosphere

Previous studies have documented the impact of the Arctic sea ice loss and associated warming on the midlatitude weather and climate, especially the influence of sea ice retreat over the Barents-Kara Sea on the North Atlantic and Europe regions. However, less attention has been given to other geographical locations over the Arctic, and to the linear additivity of the circulation response to regional Arctic sea ice loss and temperature anomalies. Using a simplified dry dynamical core model, we demonstrate that responses to regional Arctic temperature anomalies over the Barents-Kara Sea, Baffin Bay-Davis Strait-Labrador Sea, and East Siberia-Chukchi Sea, separately, cause similar equatorward shift of the tropospheric jet, but different stratospheric polar vortex responses. Furthermore, responses to regional Arctic temperature anomalies are not linearly additive, and the residual resembles a positive Northern Annular Mode-like structure. Additional targeted experiments highlight the stratospheric influence in the non-additivity of the midlatitude tropospheric response.

Bithi De↗
NASA NTRS2012

Dynamics of Aboveground Phytomass of the Circumpolar Arctic Tundra During the Past Three Decades

Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.

Arctic tundra↗
NASA NTRS2014

Arctic Sea Ice in Transformation: A Review of Recent Observed Changes and Impacts on Biology and Human Activity

Sea ice in the Arctic is one of the most rapidly changing components of the global climate system. Over the past few decades, summer areal extent has declined over 30, and all months show statistically significant declining trends. New satellite missions and techniques have greatly expanded information on sea ice thickness, but many uncertainties remain in the satellite data and long-term records are sparse. However, thickness observations and other satellite-derived data indicate a 40 decline in thickness, due in large part to the loss of thicker, older ice cover. The changes in sea ice are happening faster than models have projected. With continued increasing temperatures, summer ice-free conditions are likely sometime in the coming decades, though there are substantial uncertainties in the exact timing and high interannual variability will remain as sea ice decreases. The changes in Arctic sea ice are already having an impact on flora and fauna in the Arctic. Some species will face increasing challenges in the future, while new habitat will open up for other species. The changes are also affecting peoples living and working in the Arctic. Native communities are facing challenges to their traditional ways of life, while new opportunities open for shipping, fishing, and natural resource extraction.

Sea Ice↗
NASA NTRS2016

Aircraft-Measured Indirect Cloud Effects from Biomass Burning Smoke in the Arctic and Subarctic

The incidence of wildfires in the Arctic and subarctic is increasing; in boreal North America, for example, the burned area is expected to increase by 200-300 over the next 50-100 years, which previous studies suggest could have a large effect on cloud microphysics, lifetime, albedo, and precipitation. However, the interactions between smoke particles and clouds remain poorly quantified due to confounding meteorological influences and remote sensing limitations. Here, we use data from several aircraft campaigns in the Arctic and subarctic to explore cloud microphysics in liquid-phase clouds influenced by biomass burning. Median cloud droplet radii in smoky clouds were 50 smaller than in background clouds. Based on the relationship between cloud droplet number (N(liq))/ and various biomass burning tracers (BBt/ across the multi-campaign dataset, we calculated the magnitude of subarctic and Arctic smoke aerosol-cloud interactions (ACI, where ACI = (1/3) x dln(N(liq))/dln(BBt)) to be 0.12 out of a maximum possible value of 0.33 that would be obtained if all aerosols were to nucleate cloud droplets. Interestingly, in a separate subarctic case study with low liquid water content (0.02 gm/ cu m) and very high aerosol concentrations (2000-3000 cu m) in the most polluted clouds, the estimated ACI value was only 0.06. In this case, competition for water vapor by the high concentration of CCN strongly limited the formation of droplets and reduced the cloud albedo effect, which highlights the importance of cloud feedbacks across scales. Using our calculated ACI values, we estimate that the smoke-driven cloud albedo effect may decrease shortwave radiative flux by 2 and 4 W/sq or more under some low and homogeneous cloud cover conditions in the subarctic, although the changes should be smaller in high surface albedo regions of the Arctic. We lastly show evidence to suggest that numerous northern latitude background Aitken particles can interact with combustion particles, perhaps impacting their properties as cloud condensation and ice nuclei. However, the influence of background particles on smoke-driven indirect effects is currently unclear.

Arctic↗
NASA NTRS2017

Comparison of Passive Microwave-Derived Early Melt Onset Records on Arctic Sea Ice

Two long records of melt onset (MO) on Arctic sea ice from passive microwave brightness temperatures (Tbs) obtained by a series of satellite-borne instruments are compared. The Passive Microwave (PMW) method and Advanced Horizontal Range Algorithm (AHRA) detect the increase in emissivity that occurs when liquid water develops around snow grains at the onset of early melting on sea ice. The timing of MO on Arctic sea ice influences the amount of solar radiation absorbed by the ice-ocean system throughout the melt season by reducing surface albedos in the early spring. This work presents a thorough comparison of these two methods for the time series of MO dates from 1979through 2012. The methods are first compared using the published data as a baseline comparison of the publically available data products. A second comparison is performed on adjusted MO dates we produced to remove known differences in inter-sensor calibration of Tbs and masking techniques used to develop the original MO date products. These adjustments result in a more consistent set of input Tbs for the algorithms. Tests of significance indicate that the trends in the time series of annual mean MO dates for the PMW and AHRA are statistically different for the majority of the Arctic Ocean including the Laptev, E. Siberian, Chukchi, Beaufort, and central Arctic regions with mean differences as large as 38.3 days in the Barents Sea. Trend agreement improves for our more consistent MO dates for nearly all regions. Mean differences remain large, primarily due to differing sensitivity of in-algorithm thresholds and larger uncertainties in thin-ice regions.

sea ice↗
NASA NTRS2017

Variability and Trends in the Arctic Sea Ice Cover: Results from Different Techniques

Variability and trend studies of sea ice in the Arctic have been conducted using products derived from the same raw passive microwave data but by different groups using different algorithms. This study provides consistency assessment of four of the leading products, namely, Goddard Bootstrap (SB2), Goddard NASA Team (NT1), EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF 1.2), and Hadley HadISST 2.2 data in evaluating variability and trends in the Arctic sea ice cover. All four provide generally similar ice patterns but significant disagreements in ice concentration distributions especially in the marginal ice zone and adjacent regions in winter and meltponded areas in summer. The discrepancies are primarily due to different ways the four techniques account for occurrences of new ice and meltponding. However, results show that the different products generally provide consistent and similar representation of the state of the Arctic sea ice cover. Hadley and NT1 data usually provide the highest and lowest monthly ice extents, respectively. The Hadley data also show the lowest trends in ice extent and ice area at negative 3.88 percent decade and negative 4.37 percent decade, respectively, compared to an average of negative 4.36 percent decade and negative 4.57 percent decade for all four. Trend maps also show similar spatial distribution for all four with the largest negative trends occurring at the Kara/Barents Sea and Beaufort Sea regions, where sea ice has been retreating the fastest. The good agreement of the trends especially with updated data provides strong confidence in the quantification of the rate of decline in the Arctic sea ice cover.

Arctic↗
NASA NTRS2017

Understanding Arctic Surface Temperature Differences in Reanalyses

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. A review of surface temperature differences is presented with a particular focus on differences in contemporary reanalyses. An important consideration is the significant differences in Arctic surfaces, including the central Arctic Ocean, the Greenland Ice Sheet, and non-glaciated land. While there is significant correlation among reanalyses in annual time series, there is substantial disagreement in mean values. For the period 1980-2013, the trend in annual temperature ranges from 0.3 to 0.7K per decade. Over the central Arctic Ocean, differences in mean values and trends are larger. Most of the uncertainty is associated with winter months. This is likely associated with the constraint imposed by melting processes (i.e. 0 deg. Celsius), rather than seasonal changes to the observing system.

Sea Ic↗
NASA NTRS2021

Sensitivity of Low Tropospheric Arctic Temperatures to Assimilation of AIRS Cloud-Cleared Radiances: Impact on Mid-Latitude Waves

In this work, it is shown that the prediction of individual mid-latitude waves in a global forecast framework is sensitive to the initialization over the Arctic and may benefit from the assimilation of cloud-cleared radiances (CCRs) from the Atmospheric Infrared Sounder (AIRS), particularly in partially cloudy regions with active dynamics. This study shows that the assimilation of AIRS CCRs over the Arctic Ocean, providing more information than clear-sky radiances from areas affected by broken low-level stratus clouds, produces slightly cooler low-level temperatures and lower mid-tropospheric height through hydrostatic adjustment. In areas that are data void, as observed by clear-sky radiances, and dynamically active, the assimilation of CCRs provides valuable information that can improve the representation of individual baroclinic waves and their subsequent forecasts. The modifications induced by the assimilation of AIRS CCRs over the Arctic Ocean slightly modifies the geopotential height gradients between the Arctic and the mid-latitudes, leading to potential improvements in the forecast of individual baroclinic waves as is shown through a case study. The observing system experiment (OSE) is performed with the NASA Goddard Earth Observing System (GEOS) data assimilation and forecast system during boreal autumn 2014. AIRS CCRs are thinned to approximately one quarter the density of operationally assimilated AIRS radiances, consistent with their higher information content. Global, 6-hourly analyses are produced from 1 September to 10 November 2014 and 7-day forecasts are initialized at 0000 UTC daily. Since the CCR methodology is widely applicable, these findings are also relevant to other infrared sensors.

Cloud-clearing↗
NASA NTRSDate not supplied

Overview of Large-Scale Transport into the Arctic in the Chemistry Climate Model Initiative (CCMI) Simulations

The transport of trace gases and aerosols is a major uncertainty in the modeling of Arctic tropospheric composition. Here we compare the large-scale midlatitude-to-Arctic transport properties among different models participating in the Chemistry Climate Modeling Initiative (CCMI). Among simulations of the recent past (1980-2010) we show that there are substantial (~30-45%) differences in transport to the Arctic free troposphere, as diagnosed through use of idealized tracers emitted over the Northern Hemisphere (NH) midlatitude surface and subject to prescribed uniform loss. In addition, we show that the spread among tracers with predominantly land-based sources is correlated with the spread in the location of the Hadley Cell edge, while the spread in tracers with zonally uniform sources is also related to differences in (parameterized) convection over oceans. Interestingly, comparisons with simulations constrained with analysis fields reveal similar, if not larger, transport differences, compared to the free-running simulations, indicating that caution should be taken when interpreting simulations constrained with analyzed winds. Finally, among simulations of the 21st century we show that models project a consistent, albeit small (~5-10%), increase in transport from the NH midlatitude surface to the Arctic upper troposphere.

Large-Scale Transpor↗
NASA NTRS2024

The Future of Arctic Fires: Leveraging Ongoing Activities, New Efforts, and International Cooperation

Fires in the Arctic region are gaining more attention and driving increased concern from the public, the scientific community, and policymakers. An increasing number of scientific projects, collaboration efforts, media coverage, and policy assessments have been and are being implemented and published regarding this emerging and important wildland fire phenomenon. In short, this increased activity comes from the recognition of increasing fire risk and activity close to, within, and impacting the Arctic. There is a need to integrate these numerous and expanding local, national, and international efforts to avoid redundant and overlapping efforts and to focus resources more efficiently. As a response, this report suggests short and long-term goals to respond to the growing fire risk and fire danger in the Arctic. All efforts call for more integrated international collaboration and greater recognition of the importance for Arctic communities to be collaborators and leaders.

Future↗
NASA NTRS2024

The Correlation Between Arctic Sea Ice, Cloud Phase and Radiation Using A-Train Satellites

Climate warming has a stronger impact on Arctic climate and sea ice cover (SIC) decline than previously thought. Better understanding and characterization of the relationship between sea ice and clouds and the implications for surface radiation is key to improving our confidence in Arctic climate projections. Here we analyze the relationship between sea ice, cloud phase and surface radiation over the Arctic, defined as north of 60° N, using active- and passive-sensor satellite observations from three different datasets. We find that all datasets agree on the climatology of and seasonal variability in total and liquid-bearing (liquid and mixed-phase) cloud covers. Similarly, our results show a robust relationship between decreased SIC and increased liquid-bearing clouds in the lowest levels (below 3 km) for all seasons (strongest in winter) but summer, while increased SIC and ice clouds are positively correlated in two of the three datasets. A refined map correlation analysis indicates that the relationship between SIC and liquid-bearing clouds can change sign over the Bering, Barents and Laptev seas, likely because of intrusions of warm air from low latitudes during winter and spring. Finally, the increase in liquid clouds resulting from decreasing SIC is associated with enhanced radiative cooling at the surface. Our findings indicate that the newly formed liquid clouds reflect more shortwave (SW) radiation back to space compared to the surface, generating a cooling effect of the surface, while their downward longwave (LW) radiation is similar to the upward LW surface emission, which has a negligible radiative impact on the surface. This overall cooling effect should contribute to dampening future Arctic surface warming as SIC continues to decline.

Arctic climate↗
NASA NTRS2023

Quantification of Discharge-Specific Effects on Dissolved Organic Matter Export From Major Arctic Rivers From 1982 Through 2019

Long-term increases in Arctic river discharge have been well documented, and observations in the six largest Arctic rivers show strong positive correlations between dissolved organic carbon (DOC) concentration, river discharge, and chromophoric dissolved organic matter (CDOM) content. Here, observations of DOC and CDOM collected from 2009-2019 by the Arctic Great Rivers Observatory were used to estimate chromophoric DOC (CDOC) concentrations in the Kolyma, Lena, Mackenzie, Ob’, Yenisey, and Yukon Rivers. All rivers but the Mackenzie showed significant positive correlations between annual watershed runoff and the proportion of the DOC that is chromophoric. Historical estimates of DOC and CDOC export were calculated for 1982-2019 by extrapolating the DOC and CDOC concentration – discharge relationships from 2009-2019 as a hindcast modeled estimate. For the six rivers combined, modeled DOC and CDOC export increased, but CDOC increased faster than total DOC. The Lena and Ob’ Rivers showed significant increases in DOC export individually, with annual trends of 39.1 and 20.4 Gg C yr -1 respectively. November-April (winter) DOC and CDOC export increased in all rivers but the Yenisey, with the hindcast winter Kolyma export increasing by more than 20% per decade. There were no significant trends in discharge or associated DOC and CDOC fluxes during the observational period from 2009-2019; only when hindcasted values driven by changes in river discharge were analyzed did trends in DOC and CDOC emerge. This demonstrates how shifting seasonal distributions and increases in discharge can drive changes in DOC and CDOC concentrations and export, independent of other environmental factors.

carbon cycle↗
NASA NTRS1974

The application of ERTS imagery to monitoring Arctic sea ice

The author has identified the following significant results. Because of the effect of sea ice on the heat balance of the Arctic and because of the expanding economic interest in arctic oil and minerals, extensive monitoring and further study of sea ice is required. The application of ERTS data for mapping ice is evaluated for several arctic areas, including the Bering Sea, the eastern Beaufort Sea, parts of the Canadian Archipelago, and the Greenland Sea. Interpretive techniques are discussed, and the scales and types of ice features that can be detected are described. For the Bering Sea, a sample of ERTS-1 imagery is compared with visual ice reports and aerial photography from the NASA CV-990 aircraft. The results of the investigation demonstrate that ERTS-1 imagery has substantial practical application for monitoring arctic sea ice. Ice features as small as 80-100 m in width can be detected, and the combined use of the visible and near-IR imagery is a powerful tool for identifying ice types. Sequential ERTS-1 observations at high latitudes enable ice deformations and movements to be mapped. Ice conditions in the Bering Sea during early March depicted in ERTS-1 images are in close agreement with aerial ice observations and photographs.

Barnes, J. C.↗
NASA NTRS1976

Study of Arctic sea ice drift from L-band synthetic aperture radar

As part of the Arctic Ice Dynamics Joint Experiment (AIDJEX) several repetitive coverages of L-band (25 cm wavelength) side-looking airborne radar images have been flown over coastal areas of Alaska and a test area in the Arctic. These images allow the analysis of sea ice and its drift. Radar is particularly suited for the mapping and interpretation of Arctic sea ice due to independence from sunlight and the capability to penetrate clouds. Ice floes and leads can be readily identified on the radar images. Measurement of ice floe drift is based on the transformation of radar image coordinates into a geocentric coordinate system using inertial guidance data from the survey aircraft. The paper will demonstrate an example of Arctic ice drift measurements from L-band synthetic aperture radar imagery with an absolute accuracy of about 5%. The conclusions are of particular value in view of planned spaceborne side-looking radar missions in polar orbits.

Leberl, F.↗