Sea level rise poses a significant threat to coastal communities, infrastructure, and ecosystems. Sea level rise is not uniform globally but is affected by a range of regional factors. In this paper, we calculate regional projections of 21st century sea level rise in Northern Europe, focusing on the British Isles, the Baltic, and the North Sea. The input to the regional sea level projection is a probabilistic projection of the major components global sea level budget. Local sea level rise is partly compensated by vertical land movement from glacial isostatic adjustment. We explore the uncertainties beyond the likely range provided by IPCC, including the risk and potential rate of marine ice sheet collapse. Our median 21st century relative sea level rise projection is 0.8 m near London and Hamburg, and a relative sea level drop of 0.1 m in the Bay of Bothnia (near Oulu, Finland). Considerable uncertainties remain in both the sea level budget, and in the regional expression of sea level rise. The greatest uncertainties are associated with Antarctic ice loss and uncertainties are skewed towards higher values, with the 95th percentile being characterized by an additional 0.9 m sea level rise above median projections.
Grinsted, Jevrejeva, Riva, Dahl-Jensen (2015), Sea level rise projections for Northern Europe under RCP8.5, Clim. Res., doi:10.3354/cr01309
We find that there is a considerable risk that existing high-end scenarios for sea level rise may be exceeded.
Data files with the RSL projection uncertainties for individual cities is attached below. In practice, the uncertainties are given as a cumulative density function of the RSL projection in each city. Some additional info such as the applied GIA rate, and derived quantities such as mean and standard deviation is given in the header to each file.
[Download data] Update 7Jul16: an earlier version of the file listed expected LSL instead of expected RSL in the header. This has been corrected.
The paper is part of a special issue on Effects of Extreme Global Warming in Northern Europe. In this issue there are some cases which highlight how difficult it will be to adapt to a 6 degree C warmer world, and when that would happen under different scenarios. For sea level rise i instead chose to focus on RCP8.5. The special issue has many contributions from our Centre for Regional change in the Earth System.
Trivia: all colormaps were generated using hslcolormap.
Global warming is causing sea levels to rise, primarily due to loss of land-based ice masses and thermal (steric) expansion of the world oceans. Sea level does not rise in a globally uniform manner, but varies in complex spatial patterns. This chapter reviews projections of the individual contributions to sea-level rise. These are used to assemble a mid-range scenario of a 0.70 ± 0.30-m sea-level rise over the twenty-first century (based on the SRES A1B scenario) and a high-end scenario of 1.10 m. The sea-level projection was regionalised to the Baltic Sea area by taking into account local dynamic sea-level rise and weighting the components of the sea-level budget by their static equilibrium fingerprint. This yields a mid-range Baltic Sea sea-level rise that is ~80 % of the global mean. Ongoing glacial isostatic adjustment (GIA) partly compensates for local sea-level rise in much of the region. For the mid-range scenario, this equates to a twenty-first century relative sea-level rise of 0.60 m near Hamburg and a relative sea-level fall of 0.35 m in the Bothnian Bay. The high-end scenario is characterised by an additional 0.5 m.
Note: This chapter has been superceded by newer probabilistic sea level projections using AR5 as the foundation. Please refer to this paper for more up to date information.
Grinsted, A. (2015). Projected Change—Sea Level. In Second Assessment of Climate Change for the Baltic Sea Basin (pp. 253-263). Springer International Publishing.
Effekter, klimatilpasning og sårbarhed, - med særligt fokus på Danmark
I have contributed to this report with an analysis of AR5 WG2 with a focus on Denmark. Only available in Danish.
Citation: Analyse af IPCC delrapport 2 - Effekter, klimatilpasning og sårbarhed : med særligt fokus på Danmark. / Christensen, Jen Hesselbjerg; Arnbjerg-Nielsen, Karsten; Grinsted, Aslak; Halsnæs, Kirsten; Jeppesen, Erik; Madsen, Henrik; Olesen, Jørgen Eivind; Porter, John Roy; Refsgaard, Jens Christian; Olesen, Martin.København : Miljøministeriet, Naturstyrelsen, 2014. 54 p.
Citation: Jevrejeva, Grinsted, Moore (2014), Upper limit for sea level projections by 2100, Environ. Res. Lett. 9 104008 doi:10.1088/1748-9326/9/10/104008
The IPCC did not provide an upper limit or worst case scenario for sea level rise this century, but only a likely range of future sea level rise. In IPCC jargon "likely range" means that there is 33% chance that sea level rise will fall outside this range, and thus the IPCC high-end estimate is not a worst case scenario. I have criticized how this was communicated by the IPCC, because I thought that it was pretty clear that it would be misunderstood thus. The main uncertainty is the future rate of ice sheet mass loss and in particular the risk of a collapse of parts of the Antarctic ice sheet. This is particular challenging to model, and IPCC write that a collapse may cause sea level to rise faster than the 'likely range', but also that this risk is essentially impossible to model (paraphrased). In order to quantify the risk we therefore had to look to other lines of evidence, and here we looked at an expert elicitation which quantified the subjective uncertainty within the community of ice-sheet experts. We combined this with the IPCC numbers for the other contributions to sea level rise. The strength of this approach is that this is not just our view of the uncertainty but a snapshot of the community uncertainty. We also note that the peak in our estimate of the uncertainty distribution is very consistent with the likely range from the IPCC. The result is similar to the worst case estimate obtained by cherry-picking the worst case published result for each contributor to sea level rise (ocean expansion, glacier melt, ice-sheet melt, ground water pumping), and adding them up. This cherry picked scenario does not have a probability attached to it. Nevertheless it is useful because it strengthens our assertion that other lines of evidence are needed to justify a larger sea level rise this century.
It may seem like an alarmist paper, but really it is the opposite because we are arguing that even faster rates of sea level rise are improbable. We note that sea level rise does not stop in 2100.
Shortly, it is primarily useful as a tool in adaptation planning. There may be certain critical infrastructure where it is wise to take the worst-case into account in the planning. Consider the Delta works, or the Thames Barrier. We note that large national climate reports have provided such high end scenarios. The UK has a high-plus-plus scenario in their UKCP09 report which is accompanied by these words: "we provide the scenario as some users may find it useful to aid contingency planning". This is exactly how this unlikely scenario is useful. Our high end scenario of 1.8m (=6 feet) is very close to the highest scenario of 6.6ft adopted in the US NCA2014 report. Our result justify this 6.6ft choice for the highest scenario.
Any value for the upper-limit would meet opposition. Some would see it as overly alarmist, and others would argue that things could go a lot worse. We believe that with the methods we use, we fairly represent the broader community uncertainty.
For the ice sheet contribution we used a shap-shot of the expert uncertainty from 2012 (Bamber & Aspinall, 2013). Since then several studies have found that parts of Antarctica is already collapsing. This new knowledge may alter expert opinion (as we note in the paper), but we can only speculate by how much. This has led Joe Romm at Think Progress to argue that our study therefore "vastly* underestimates" worst case sea level rise. However, domain experts are ahead of the game, and ice sheet experts have long considered the possibility of a collapse. It is important to realize that the expert elicitation we used did not only ask for a best estimate, but asked each scientist to give a confidence interval. And it is clear from their responses that they did consider this possibility.
The new studies do not really inform on how fast that might happen, and I believe that the high-end would not change much if the same experts were asked the same question now. I speculate that these new studies will have a greater effect on what experts consider to be the most likely value, than the tail.
* Note the thinkprogress piece has since been amended to remove "vastly" from the headline.
The use of time-lapse camera systems is becoming an increasingly popular method for data acquisition. The camera setup is often cost-effective and simple, allowing for a large amount of data to be accumulated over a variety of environments for relatively minimal effort. The acquired data can, with the correct post-processing, result in a wide range of useful quantitative and qualitative information in remote and dangerous areas. The post-processing requires a significant amount of steps to transform images into meaningful and comparable data, such as velocity data. To the best of our knowledge at present a complete, openly available package that encompasses georeferencing, georectification and feature tracking of terrestrial, oblique images is still absent. This study presents a complete, yet adaptable, open-source package developed in MATLAB, that addresses and combines each of these post-processing steps into one complete suite in the form of an "Image GeoRectification and Feature Tracking" (ImGRAFT: http://imgraft.glaciology.net) toolbox. The toolbox, can also independently produce other useful outputs, such as viewsheds, georectified and orthorectified images. ImGRAFT is primarily focused on terrestrial oblique images, for which there are currently limited post-processing options available. In this study we illustrate ImGRAFT for glaciological applications on a small outlet glacier Engabreen, Norway.
Citation: Messerli, A. and Grinsted, A. (2015), Image GeoRectification And Feature Tracking toolbox: ImGRAFT, Geosci. Instrum. Method. Data Syst., 4, 23-34, doi:10.5194/gi-4-23-2015 [PDF]
We use 1277 tide gauge records since 1807 to provide an improved global sea level reconstruction and analyse the evolution of sea level trend and acceleration. In particular we use new data from the polar regions and remote islands to improve data coverage and extend the reconstruction to 2009. There is a good agreement between the rate of sea level rise (3.2 ± 0.4 mm/yr) calculated from satellite altimetry and the rate of 3.1 ± 0.6 mm/yr from tide gauge based reconstruction for the overlapping time period (1993–2009). The new reconstruction suggests a linear trend of 1.9 ± 0.3 mm/yr during the 20th century, with 1.8 ± 0.5 mm/yr since 1970. Regional linear trends for 14 ocean basins since 1970 show the fastest sea level rise for the Antarctica (4.1 ± 0.8 mm/yr) and Arctic (3.6 ± 0.3 mm/yr). Choice of GIA correction is critical in the trends for the local and regional sea levels, introducing up to 8 mm/yr uncertainties for individual tide gauge records, up to 2 mm/yr for regional curves and up to 0.3–0.6 mm/yr in global sea level reconstruction. We calculate an acceleration of 0.02 ± 0.01 mm·yr-2 in global sea level (1807–2009). In comparison the steric component of sea level shows an acceleration of 0.006 mm·yr− 2 and mass loss of glaciers accelerates at 0.003 mm·yr-2 over 200 year long time series.
Jevrejeva, S., Moore, J. C., Grinsted, A., Matthews, A. P., & Spada, G. (2014). Trends and acceleration in global and regional sea levels since 1807. Global and Planetary Change, 113, 11-22. doi:10.1016/j.gloplacha.2013.12.004
We review the two main approaches to estimating sea level rise over the coming century: physically plausible models of reduced complexity that exploit statistical relationships between sea level and climate forcing, and more complex physics-based models of the separate elements of the sea level budget. Previously, estimates of future sea level rise from semiempirical models were considerably larger than those from process-based models. However, we show that the most recent estimates of sea level rise by 2100 using both methods have converged, but largely through increased contributions and uncertainties in process-based model estimates of ice sheets mass loss. Hence, we focus in this paper on ice sheet flow as this has the largest potential to contribute to sea level rise. Progress has been made in ice dynamics, ice stream flow, grounding line migration, and integration of ice sheet models with high-resolution climate models. Calving physics remains an important and difficult modeling issue. Mountain glaciers, numbering hundreds of thousands, must be modeled by extensive statistical extrapolation from a much smaller calibration data set. Rugged topography creates problems in process-based mass balance simulations forced by regional climate models with resolutions 10–100 times larger than the glaciers. Semiempirical models balance increasing numbers of parameters with the choice of noise model for the observations to avoid overfitting the highly autocorrelated sea level data. All models face difficulty in separating out non-climate-driven sea level rise (e.g., groundwater extraction) and long-term disequilibria in the present-day cryosphere-sea level system.
Moore, J. C., A. Grinsted, T. Zwinger, and S. Jevrejeva (2013), Semiempirical and process-based global sea level projections, Rev. Geophys., 51, 484–522, doi:10.1002/rog.20015.
In order to extract the intrinsic information of climatic time series from background red noise, in this paper, we will first give an analytic formula on the distribution of Haar wavelet power spectra of red noise in a rigorous statistical framework. After that, by comparing the difference of wavelet power spectra of real climatic time series and red noise, we can extract intrinsic features of climatic time series. Finally, we use our method to analyze Arctic Oscillation (AO) which is a key aspect of climate variability in the Northern Hemisphere, and discover a great change in fundamental properties of the AO, commonly called a regime shift or tripping point.
Zhihua Zhang, John C. Moore, Aslak Grinsted, Int. J. Wavelets Multiresolut Inf. Process. 12, 1450020 (2014) [11 pages] doi:10.1142/S0219691314500209
Detection and attribution of past changes in cyclone activity is hampered by biased cyclone records due to changes in observational capabilities. Here we relate a new homogeneous record of Atlantic tropical cyclone activity based on storm surge statistics from tide gauges to changes in global temperature patterns. We examine 10 competing hypotheses using non-stationary generalized extreme value analysis with different predictors (North Atlantic Oscillation, Southern Oscillation, Pacific Decadal Oscillation, Sahel rainfall, Quasi-Biennial Oscillation, Radiative Forcing, Main Development Region temperatures and its anomaly, global temperatures, and gridded temperatures). We find that gridded temperatures, Main Development Region, and global average temperature explain the observations best. The most extreme events are especially sensitive to temperature changes, and we estimate a doubling of Katrina magnitude events associated with the warming over the 20th century. The increased risk depends on the spatial distribution of the temperature rise with highest sensitivity from tropical Atlantic, Central America and the Indian Ocean. Statistically downscaling 21st century warming patterns from 6 climate models results in a 2-7 fold increase in the frequency of Katrina magnitude events for a 1°C rise in global temperature (using BNU-ESM; BCC-CSM-1-1; CanESM2; HadGEM2-ES; INM-CM4; NorESM1-M).
Aslak Grinsted, John C. Moore, and Svetlana Jevrejeva (2013), Projected Atlantic hurricane surge threat from rising temperatures, PNAS, doi:10.1073/pnas.1209980110
Comment & reply.
Kennedy et al wrote a comment to this paper questioning whether the Katrina benchmark as defined in the paper is appropriate given that our closest tide gauge at Pensacola was 162 km from highest high water mark left. However the highest high water mark records are set by very short lived events and we initially apply a 24 hour average to all records. This low pass filter removes these highly localized extremes and the Pensacola record becomes much more representative of the larger scale disturbances in sea level. It is therefore an apples to orange comparison to compare high water marks to our surge record. We demonstrate this to be the case in our reply to Kennedy et al. here. See also this page for further details on our processing choices.
The surge index record used in this paper is based on six long high resolution tide gauge records (see map) from the US Atlantic and Gulf coasts.
Table 2 shows how well different predictors are able to explain past surge variability. Temperatures and even just a plain linear trend is better than many other commonly proposed predictors. The sensitivity is given per degC or per century.
I asses the feasibility of multi-variate scaling relationships to estimate glacier volume from glacier inventory data. Scaling laws are calibrated against volume observations optimized for the specific purpose of estimating total global glacier ice volume. I find that adjustments for continentality and elevation range improve skill of area-volume scaling. These scaling relationships are applied to each record in the Randolph Glacier Inventory which is the first globally complete inventory of glaciers and ice caps. I estimate that the total volume of all glaciers in the world is 0.35±0.07 m sea level equivalent, including ice sheet peripheral glaciers. This is substantially less than a recent state-of-the-art estimate. Area volume scaling bias issues for large ice masses, and incomplete inventory data are offered as explanations for the difference.
Citation: Grinsted, A. (2013): An estimate of global glacier volume, The Cryosphere, 7, 141–151, doi:10.5194/tc-7-141-2013
More details on the study can be found under this link where I discuss:
Figure caption: The volume fraction stored in all the glaciers larger than a given area. Dark cyan shows the results of this study, and thin bright cyan excluding regions with many glacier complexes in RGI v2. The distribution from Huss and Farinotti (2012) is shown in green.
This figure shows that ~85% of the global glacier volume is stored in ~1000 largest RGI glacier complexes (>100 km2). In the paper I suggest that we can improve the glacier estimate through detailed studies of those complexes.