DAMOCLES - EU-kommissionens bidrag til IPY

De danske forskningsbevilligende myndigheder har i modsætning til en række andre lande indtil videre vist en påfaldende tilbageholdenhed i forbindelse med Det Internationale Polarår (IPY). Og det haster – IPY løber fra marts 2007- marts 2009

The impact of melt ponds on summertime microwave brightness temperatures and sea-ice concentrations

Sea-ice concentrations derived from satellite microwave brightness temperatures are less accurate during summer. In the Arctic Ocean the lack of accuracy is primarily caused by melt ponds, but also by changes in the properties of snow and the sea-ice surface itself. We investigate the sensitivity of eight sea-ice concentration retrieval algorithms to melt ponds by comparing sea-ice concentration with the melt-pond fraction. We derive gridded daily sea-ice concentrations from microwave brightness temperatures of summer 2009. We derive the daily fraction of melt ponds, open water between ice floes, and the ice-surface fraction from contemporary Moderate Resolution Spectroradiometer (MODIS) reflectance data. We only use grid cells where the MODIS sea ice concentration, which is the melt-pond fraction plus the ice-surface fraction, exceeds 90 %. For one group of algorithms, e.g., Bristol and Comiso bootstrap frequency mode (Bootstrap_f), sea-ice concentrations are linearly related to the MODIS melt-pond fraction quite clearly after June. For other algorithms, e.g., Near9OGHz and Comiso bootstrap polarization mode (Bootstrap_p), this relationship is weaker and develops later in summer. We attribute the variation of the sensitivity to the melt-pond fraction across the algorithms to a different sensitivity of the brightness temperatures to snow-property variations. We find an underestimation of the sea-ice concentration by between 14 % (Bootstrap_f) and 26 % (Bootstrap_p) for 100 % sea ice with a melt-pond fraction of 40 %. The underestimation reduces to 0 % for a melt pond fraction of 20 %. In presence of real open water between ice floes, the sea-ice concentration is overestimated by between 26 % (Bootstrap_f) and 14 % (Bootstrap_p) at 60 % sea-ice concentration and by 20 % across all algorithms at 80 % sea-ice concentration. None of the algorithms investigated performs best based on our investigation of data from summer 2009. We suggest that those algorithms which are more sensitive to melt ponds could be optimized more easily because the influence of unknown snow and sea-ice surface property variations is less pronounced

CryoSat - braste forventninger

I løbet af de seneste 30 år er både tykkelsen af den arktiske havis og udbredelsen, specielt om sommeren, mindsket. Gennemsnittet af den årlige udbredelse er mindsket med 8 % svarende til et areal på størrelse med Skandinavien (Danmark, Norge, Sverige og Finland), mens sommerudbredelsen er reduceret med 15-20 %. I 2005 målte man den mindste sommerudbredelse af den Arktiske havis nogensinde. Tykkelsen er reduceret med mindst 10-15 %

Explicitly determined sea ice emissivity and emission temperature over the Arctic for surface‐sensitive microwave channels

Data assimilation of satellite microwave measurements is one of the importantkeys to improving weather forecasting over the Arctic region. However, the useofsurface-sensitivemicrowave-soundingchannelmeasurementsfordataassim-ilation or retrieval has been limited, especially during winter, due to the poorlyconstrained sea ice emissivity. In this study, aiming at more use of those channelmeasurements in the data assimilation, we propose an explicit method for speci-fying the surface radiative boundary conditions (namely emissivity and emittinglayer temperature of snow and ice). These were explicitly determined with aradiativetransfermodelforsnowandiceandwithsnow/icephysicalparameters(i.e. snow/ice depths and vertical distributions of temperature, density, salinity,and grain size) simulated from the thermodynamically driven snow/ice growthmodel. We conducted 1D-Var experiments in order to examine whether thisapproach can help to use the surface-sensitive microwave temperature channelmeasurements over the Arctic sea ice region for data assimilation. Results showthat (1) the surface-sensitive microwave channels can be used in the 1D-Varretrieval, and (2) the specification of the radiative boundary condition at thesurface using the snow/sea ice emission model can significantly improve theatmospheric temperature retrieval, especially in the lower troposphere (500hPato surface). The successful retrieval suggests that useful information can beextracted from surface-sensitive microwave-sounding channel radiances oversea ice surfaces through the explicit determination of snow/ice emissivity andemitting layer temperature

Monitoring Arctic Sea Ice During One Year: Linearly Polarized GNSSReflectometry at the MOSAiC Campaign

Ponencia expuesta online en el 41st annual IGARSS (2021) celebrado en Bruselas del 12-16 de juli

Snow Property Controls on Modeled Ku-Band Altimeter Estimates of First-Year Sea Ice Thickness: Case Studies From the Canadian and Norwegian Arctic

Uncertainty in snow properties impacts the accuracy of Arctic sea ice thickness estimates from radar altimetry. On first-year sea ice (FYI), spatiotemporal variations in snow properties can cause the Ku-band main radar scattering horizon to appear above the snow/sea ice interface. This can increase the estimated sea ice freeboard by several centimeters, leading to FYI thickness overestimations. This article examines the expected changes in Ku-band main scattering horizon and its impact on FYI thickness estimates, with variations in snow temperature, salinity, and density derived from ten naturally occurring Arctic FYI Cases encompassing saline/nonsaline, warm/cold, simple/complexly layered snow (4–45 cm) overlying FYI (48–170 cm). Using a semi-empirical modeling approach, snow properties from these Cases are used to derive layer-wise brine volume and dielectric constant estimates, to simulate the Ku-band main scattering horizon and delays in radar propagation speed. Differences between modeled and observed FYI thickness are calculated to assess sources of error. Under both cold and warm conditions, saline snow covers are shown to shift the main scattering horizon above from the snow/sea ice interface, causing thickness retrieval errors. Overestimates in FYI thicknesses of up to 65% are found for warm, saline snow overlaying thin sea ice. Our simulations exhibited a distinct shift in the main scattering horizon when the snow layer densities became greater than 440 kg/m 3 , especially under warmer snow conditions. Our simulations suggest a mean Ku-band propagation delay for snow of 39%, which is higher than 25%, suggested in previous studies

Retrieval of Snow Depth on Arctic Sea Ice From Surface‐Based, Polarimetric, Dual‐Frequency Radar Altimetry

Snow depth on sea ice is an Essential Climate Variable and a major source of uncertainty in satellite altimetry‐derived sea ice thickness. During winter of the MOSAiC Expedition, the “KuKa” dual‐frequency, fully polarized Ku‐ and Ka‐band radar was deployed in “stare” nadir‐looking mode to investigate the possibility of combining these two frequencies to retrieve snow depth. Three approaches were investigated: dual‐frequency, dual‐polarization and waveform shape, and compared to independent snow depth measurements. Novel dual‐polarization approaches yielded r2 values up to 0.77. Mean snow depths agreed within 1 cm, even for data sub‐banded to CryoSat‐2 SIRAL and SARAL AltiKa bandwidths. Snow depths from co‐polarized dual‐frequency approaches were at least a factor of four too small and had a r2 0.15 or lower. r2 for waveform shape techniques reached 0.72 but depths were underestimated. Snow depth retrievals using polarimetric information or waveform shape may therefore be possible from airborne/satellite radar altimeters