SPOT: Open Source framework for scientific data repository and interactive visualization

SPOT is an open source and free visual data analytics tool for multi-dimensional data-sets. Its web-based interface allows a quick analysis of complex data interactively. The operations on data such as aggregation and filtering are implemented. The generated charts are responsive and OpenGL supported. It follows FAIR principles to allow reuse and comparison of the published data-sets. The software also support PostgreSQL database for scalability

Synthesis and evaluation of historical meridional heat transport from midlatitudes towards the Arctic

Meridional Energy Transport (MET), both in the atmosphere (AMET) and ocean (OMET), has significant impact on the climate in the Arctic. In this study, we quantify AMET and OMET at subpolar latitudes from six reanalyses datasets. We investigate the differences between the datasets and we check the coherence between MET and the Arctic climate variability from annual to interannual scales. The results indicate that, although the mean transport in all datasets agree well, the spatial distribution and temporal variations of AMET and OMET differ substantially among the reanalysis datasets. For the ocean, only after 2010 the low-frequency signals for all reanalyses products agree well. A further comparison with observed heat transports at 26.5° N and the subpolar Atlantic, and a high-resolution ocean model hindcast confirm that the OMET estimated from reanalyses are consistent with independent observations. For the atmosphere, the variations among reanalyses datasets are large. This can be attributed to differences in temperature transport. A further analysis of linkages between the Arctic climate variability and AMET shows that atmospheric reanalyses differ substantially from each other. Among all the chosen atmospheric products, ERA-Interim results are most consistent with results obtained with coupled climate models. For the ocean, ORAS4 and SODA3 agree well on the relation between OMET and sea ice concentration (SIC), while GLORYS2V3 deviates from those data sets. Our study suggests, since the reanalyses products are not designed for the quantification of energy transport, the AMET and OMET estimated from reanalyses should be used with great care, especially when studying variability and interactions between the Arctic and midlatitudes beyond annual time scales

Extended-range arctic sea ice forecast with convolutional long short-Term memory networks

Operational Arctic sea ice forecasts are of crucial importance to science and to society in the Arctic region. Currently, statistical and numerical climate models are widely used to generate the Arctic sea ice forecasts at weather time scales. Numerical models require near-real-Time input of relevant environmental conditions consistent with the model equations and they are computationally expensive. In this study, we propose a deep learning approach, namely convolutional long short-Term memory networks (ConvLSTM), to forecast sea ice in the Barents Sea at weather to subseasonal time scales. This is an unsupervised learning approach. It makes use of historical records and it exploits the covariances between different variables, including spatial and temporal relations. With input fields from reanalysis data, we demonstrate that ConvLSTM is able to learn the variability of the Arctic sea ice and can forecast regional sea ice concentration skillfully at weekly to monthly time scales. It preserves the physical consistency between predictors and predictands, and generally outperforms forecasts with climatology, persistence, and a statistical model. Based on the known sources of predictability, sensitivity tests with different climate fields as input for learning were performed. The impact of different predictors on the quality of the forecasts are evaluated and we demonstrate that the surface energy budget components have a large impact on the predictability of sea ice at weather time scales. This method is a promising way to enhance operational Arctic sea ice forecasting in the near future

Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model

In this study, we investigate uncertainties in a large eddy simulation of the atmosphere, employing modern uncertainty quantification methods that have hardly been used yet in this context. When analysing the uncertainty of model results, one can distinguish between uncertainty related to physical parameters whose values are not exactly known, and uncertainty related to modelling choices such as the selection of numerical discretization methods, of the spatial domain size and resolution, and the use of

Model-observation and reanalyses comparison at key locations for heat transport to the Arctic: Assessment of key lower latitude influences on the Arctic and their simulation

Blue-Action Work Package 2 (WP2) focuses on lower latitude drivers of Arctic change, with a focus on the influence of the Atlantic Ocean and atmosphere on the Arctic. In particular, warm water travels from the Atlantic, across the Greenland-Scotland ridge, through the Norwegian Sea towards the Arctic. A large proportion of the heat transported northwards by the ocean is released to the atmosphere and carried eastward towards Europe by the prevailing westerly winds. This is an important contribution to northwestern Europe's mild climate. The remaining heat travels north into the Arctic. Variations in the amount of heat transported into the Arctic will influence the long term climate of the Northern Hemisphere. Here we assess how well the state of the art coupled climate models estimate this northwards transport of heat in the ocean, and how the atmospheric heat transport varies with changes in the ocean heat transport. We seek to improve the ocean monitoring systems that are in place by introducing measurements from ocean gliders, Argo floats and satellites. These state of the art computer simulations are evaluated by comparison with key trans-Atlantic observations. In addition to the coupled models ‘ocean-only’ evaluations are made. In general the coupled model simulations have too much heat going into the Arctic region and the transports have too much variability. The models generally reproduce the variability of the Atlantic Meridional Ocean Circulation (AMOC) well. All models in this study have a too strong southwards transport of freshwater at 26°N in the North Atlantic, but the divergence between 26°N and Bering Straits is generally reproduced really well in all the models. Altimetry from satellites have been used to reconstruct the ocean circulation 26°N in the Atlantic, over the Greenland Scotland Ridge and alongside ship based observations along the GO-SHIP OVIDE Section. Although it is still a challenge to estimate the ocean circulation at 26°N without using the RAPID 26°N array, satellites can be used to reconstruct the longer term ocean signal. The OSNAP project measures the oceanic transport of heat across a section which stretches from Canada to the UK, via Greenland. The project has used ocean gliders to great success to measure the transport on the eastern side of the array. Every 10 days up to 4000 Argo floats measure temperature and salinity in the top 2000m of the ocean, away from ocean boundaries, and report back the measurements via satellite. These data are employed at 26°N in the Atlantic to enable the calculation of the heat and freshwater transports. As explained above, both ocean and atmosphere carry vast amounts of heat poleward in the Atlantic. In the long term average the Atlantic ocean releases large amounts of heat to the atmosphere between the subtropical and subpolar regions, heat which is then carried by the atmosphere to western Europe and the Arctic. On shorter timescales, interannual to decadal, the amounts of heat carried by ocean and atmosphere vary considerably. An important question is whether the total amount of heat transported, atmosphere plus ocean, remains roughly constant, whether significant amounts of heat are gained or lost from space and how the relative amount transported by the atmosphere and ocean change with time. This is an important distinction because the same amount of anomalous heat transport will have very different effects depending on whether it is transported by ocean or the atmosphere. For example the effects on Arctic sea ice will depend very much on whether the surface of the ice experiences anomalous warming by the atmosphere versus the base of the ice experiencing anomalous warming from the ocean. In Blue-Action we investigated the relationship between atmospheric and oceanic heat transports at key locations corresponding to the positions of observational arrays (RAPID at 26°N, OSNAP at ~55N, and the Denmark Strait, Iceland-Scotland Ridge and Davis Strait at ~67N) in a number of cutting edge high resolution coupled ocean-atmosphere simulations. We split the analysis into two different timescales, interannual to decadal (1-10 years) and multidecadal (greater than 10 years). In the 1-10 year case, the relationship between ocean and atmosphere transports is complex, but a robust result is that although there is little local correlation between oceanic and atmospheric heat transports, Correlations do occur at different latitudes. Thus increased oceanic heat transport at 26°N is accompanied by reduced heat transport at ~50N and a longitudinal shift in the location of atmospheric flow of heat into the Arctic. Conversely, on longer timescales, there appears to be a much stronger local compensation between oceanic and atmospheric heat transport i.e. Bjerknes compensation

Impacts of Arctic sea ice on cold season atmospheric variability and trends estimated from observations and a multi-model large ensemble

To examine the atmospheric responses to Arctic sea ice variability in the Northern Hemisphere cold season (from October to the following March), this study uses a coordinated set of large-ensemble experiments of nine atmospheric general circulation models (AGCMs) forced with observed daily varying sea ice, sea surface temperature, and radiative forcings prescribed during the 1979–2014 period, together with a parallel set of experiments where Arctic sea ice is substituted by its climatology. The simulations of the former set reproduce the near-surface temperature trends in reanalysis data, with similar amplitude, and their multimodel ensemble mean (MMEM) shows decreasing sea level pressure over much of the polar cap and Eurasia in boreal autumn. The MMEM difference between the two experiments allows isolating the effects of Arctic sea ice loss, which explain a large portion of the Arctic warming trends in the lower troposphere and drive a small but statistically significant weakening of the wintertime Arctic Oscillation. The observed interannual covariability between sea ice extent in the Barents–Kara Seas and lagged atmospheric circulation is distinguished from the effects of confounding factors based on multiple regression, and quantitatively compared to the covariability in MMEMs. The interannual sea ice decline followed by a negative North Atlantic Oscillation–like anomaly found in observations is also seen in the MMEM differences, with consistent spatial structure but much smaller amplitude. This result suggests that the sea ice impacts on trends and interannual atmospheric variability simulated by AGCMs could be underestimated, but caution is needed because internal atmospheric variability may have affected the observed relationship

Chromatic periodic activity down to 120 MHz in a Fast Radio Burst

Fast radio bursts (FRBs) are extragalactic astrophysical transients whose brightness requires emitters that are highly energetic, yet compact enough to produce the short, millisecond-duration bursts. FRBs have thus far been detected between 300 MHz and 8 GHz, but lower-frequency emission has remained elusive. A subset of FRBs is known to repeat, and one of those sources, FRB 20180916B, does so with a 16.3 day activity period. Using simultaneous Apertif and LOFAR data, we show that FRB 20180916B emits down to 120 MHz, and that its activity window is both narrower and earlier at higher frequencies. Binary wind interaction models predict a narrower periodic activity window at lower frequencies, which is the opposite of our observations. Our detections establish that low-frequency FRB emission can escape the local medium. For bursts of the same fluence, FRB 20180916B is more active below 200 MHz than at 1.4 GHz. Combining our results with previous upper-limits on the all-sky FRB rate at 150 MHz, we find that there are 3-450 FRBs/sky/day above 50 Jy ms at 90% confidence. We are able to rule out the scenario in which companion winds cause FRB periodicity. We also demonstrate that some FRBs live in clean environments that do not absorb or scatter low-frequency radiation.Comment: 50 pages, 14 figures, 3 tables, submitte

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands

Scenarios of future changes in small scale precipitation extremes for the Netherlands are presented. These scenarios are based on a new approach whereby changes in precipitation extremes are set proportional to the change in water vapor amount near the surface as measured by the 2m dew point temperature. This simple scaling framework allows the integration of information derived from: (i) observations, (ii) a new unprecedentedly large 16 member ensemble of simulations with the regional climate model RACMO2 driven by EC-Earth, and (iii) short term integrations with a non-hydrostatic model Harmonie. Scaling constants are based on subjective weighting (expert judgement) of the three different information sources taking also into account previously published work. In all scenarios local precipitation extremes increase with warming, yet with broad uncertainty ranges expressing incomplete knowledge of how convective clouds and the atmospheric mesoscale circulation will react to climate change