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We thank the authors (hereafter referred to as CCC) for providing us an opportunity to clarify some points of our original paper. CCC list in their abstract three “key points”that we respond to in this Reply. The first comment is the central one and the most developed. It deals mainly with discussion of features of methods of spectral analysis, mainly SSA. We have quoted the sub‐parts of that comment as items 1a to 1k. The replies to comments/key points 2 and 3 are shorter. We disagree with most of the comments by CCC and explain why. We conclude that we have successfully countered CCC's criticism and shown many of their points to be unsubstantiated. The main problem seems to reside in differences concerning the literature on Singular Spectral Analysis and our use of it. Much of our response to the comments can be found in textbooks and review papers on SSA and time series analysis; we quote extensively, both in our original paper and in this response to CCC, Golyandina and Zhigljavsky (2013).

Academics fly a lot: to research sites and archives, to conferences and workshops. Yet flying has many negative repercussions. Air travel has disproportionate climate impacts, and for reasons of time, money, and border security, produces many barriers for marginalized scholars, shaping who is able shows up at conferences and thus, who participates in the conversations that define a community of study. Forms of knowledge exchange that do not depend on aviation are thus urgently needed. E-conferences offer on such possibility. As scholars of media and energy, and as e-conference organizers and participants ourselves, we wrote this white paper to highlight what’s worked in the past, what hazards lie ahead for the future, and what potential gains could be won in the present. We hope our words will be useful to small conference organizers and professional associations alike. Our aim is not to end in-person meetings but rather to foster effective low-carbon alternatives that can help reduce the amount of travel necessary to participate in global knowledge communities. Meeting together in person is invaluable, but we can augment it with effective alternatives through critical reflection and smart design choices. We aim to spark further reflections and innovations in collaborative experiments in digital research exchange - or even other forms of scholarly community. We hope such experimentation continues long after the pandemic is over, and that its effects will shape the university for the better.

The Madden–Julian oscillation (MJO) identified by Madden and Julian in the early 1970s has been well recognized as the most prominent intraseasonal signal in the tropics. Its discovery and its relationship with other weather phenomena such as tropical cyclones (TCs) are among the most significant advancements in modern meteorology with broad and far-reaching impacts. The original study by Madden and Julian used radiosonde data on Canton Island, and their spectral analysis revealed the signal of a 40–50-day oscillation.It has come to our attention that an earlier study by Xie et al. published in a Chinese journal documented an oscillatory signal of a 45-day period using radiosonde data from several stations between 70° and 125°E in the tropics. The 40–50-day signal found by Xie et al. is strikingly evident without any filtering. Xie et al. identified that occurrences of TCs are correlated with the 40–50-day variation of low-level westerlies at these stations. The original figures in Xie et al.’s article were hand drawn. Their results are verified using data from a longer period of 1958–70. The 40–50-day oscillation in the monsoon westerlies and its relationship with the occurrence of TCs are confirmed and further expanded upon.This study serves the purpose of bringing recognition to the community of the identification of a 40–50-day signal published in Chinese in 1963 and the discovery of the correlation between MJO phases and TC genesis three decades earlier than studies on this subject published outside China.

S. Trivikrama Rao, Ph.D.There is scientific consensus that climate change has been contributing to rising surface temperatures, changing weather pattens, and extreme weather events leading to extre...

The STatistical Analogue Resampling Scheme (STARS) statistical approach was recently used to project changes of climate variables in Germany corresponding to a supposed degree of warming. We show by theoretical and empirical analysis that STARS simply transforms interannual gradients between warmer and cooler seasons into climate trends. According to STARS projections, summers in Germany will inevitably become dryer and winters wetter under global warming. Due to the dominance of negative interannual correlations between precipitation and temperature during the year, STARS has a tendency to generate a net annual decrease in precipitation under mean German conditions. Furthermore, according to STARS, the annual level of global radiation would increase in Germany. STARS can be still used, e.g., for generating scenarios in vulnerability and uncertainty studies. However, it is not suitable as a climate downscaling tool to access risks following from changing climate for a finer than general circulation model (GCM) spatial scale.

In his article Willems (Clim Chang 120(4):931–944, 2013) proposed a methodology to analyse extremes in rainfall series. When applying it to artificially generated, non-cyclic random variables we were able to detect cyclic behavior. Therefor we had a closer look on the methodology. Here we discuss our considerations, why this method generates cycles, depending on chosen subperiods and their coherence between detected cycle lengths. To verify these relationships some examples based on random data samples are given.

The paper describes the hydrodynamic part of the coupled ice-ocean model that also includes the ecosystem predictive model. The Baltic Sea model is based on the Community Earth System Model (CESM from NCAR – National Centre for Atmospheric Research). CESM was adopted for the Baltic Sea as a coupled sea-ice model. It consists of the Community Ice CodE (CICE, model version 4.0) and the Parallel Ocean Program (POP, version 2.1). The models are linked through a coupler (CPL7), which is based on the Model Coupling Toolkit (MCT) library. The current horizontal resolution is about 2 km (1/48 degrees). The ocean model has 21 vertical levels and is forced by atmospheric fields from the European Centre for Medium Weather Forecast (ECMWF). A preliminary validation of the hydrodynamic module with in situ measurements and reanalysis from My Ocean ( http://www.myocean.eu ) has also been done. In the operational mode, 48-hour atmospheric forecasts provided by the UM model from the Interdisciplinary Centre for Mathematical and Computational Modelling of Warsaw University (ICM) are used. The variables presented on the website in real time for a 48-hour forecast are temperature, salinity, currents, sea surface height, ice thickness and ice coverage ( http://deep.iopan.gda.pl/CEMBaltic/newlay/index.php ). The embedded model of the marine ecosystem, like ice, is not taken into account in this paper.

An article by William D. Nordhaus (2010) in this journal examined the economic impacts by hurricanes in the USA, and the potential impacts of climate change on future hurricane damages. His analyses show that hurricane damages normalized over time for changes in GDP have increased significantly since the year 1900, at a rate of about 3.1% per year. Moreover, the results of Nordhaus show that hurricane damages increase with the ninth power of maximum wind speed, which is considerably higher than findings of other studies. We perform similar statistical analyses with different data series of hurricane damage, which are more accurately corrected for changes in exposure of assets over time. Our results do not indicate an upward trend in hurricane losses since 1900, which is in line with earlier studies, and indicates that climate change has not increased hurricane damage in the past. Moreover, although the relation between damage and maximum wind speed appears to be considerably higher than assumed by other studies, this elasticity is more likely to be the eighth-power of maximum wind speed. This finding is relevant since it implies that future climate change impacts on hurricane damage may be considerably lower than Nordhaus indicates.

We discuss a recently proposed model for the sawtooth oscillations of atmospheric carbon observed in ice age cores. The model at its simplest arises from a single reaction involving just two species, oceanic biomass and nutrient, and bears similarity to models which have been proposed to explain oscillations in glycolysis. We show that the sawtooth behaviour, and associated spiking of one of the constituents, is associated with the existence of a conservative nonlinear oscillator with an asymmetric potential at high values of the energy, and we give asymptotic descriptions of the solutions. We extend the analysis to a more complicated model which includes competition between planktonic species.

In 2001–2007 aerosols were measured in the coastal zone (11 campaigns) and over the open waters of the Gdansk Basin (southern Baltic) (5 campaigns). The marine aerosols contained nitrogen and sulphur compounds, which increased their acidity. This situation intensified during the cool months of the year, when fossil fuel emissions were higher, proportionate to energy and heat requirements. Irrespective of the season, these acidic aerosols were neutralized in the reaction with sea salt. The likelihood of sodium nitrate being formed increased at air humidities > 80% and nitrate concentrations > 30 nmol m− 3. Sodium sulphate was present in aerosols mostly in autumn and winter, with northerly advection, and at the highest wind speeds. The excess of free ammonia resulted in the formation of ammonium sulphate and ammonium nitrate in aerosols over the southern Baltic.

The impacts of climate change on the seasonality of low flows were analysed for 134 sub-catchments covering the River Rhine basin upstream of the Dutch-German border. Three seasonality indices for low flows were estimated, namely the seasonality ratio (SR), weighted mean occurrence day (WMOD) and weighted persistence (WP). These indices are related to the discharge regime, timing and variability in timing of low flow events respectively. The three indices were estimated from: (1) observed low flows; (2) simulated low flows by the semi-distributed HBV model using observed climate as input; (3) simulated low flows using simulated inputs from seven combinations of General Circulation Models (GCMs) and Regional Climate Models (RCMs) for the current climate (1964–2007); (4) simulated low flows using simulated inputs from seven combinations of GCMs and RCMs for the future climate (2063–2098) including three different greenhouse gas emission scenarios. These four cases were compared to assess the effects of the hydrological model, forcing by different climate models and different emission scenarios on the three indices. Significant differences were found between cases 1 and 2. For instance, the HBV model is prone to overestimate SR and to underestimate WP and simulates very late WMODs compared to the estimated WMODs using observed discharges. Comparing the results of cases 2 and 3, the smallest difference was found for the SR index, whereas large differences were found for the WMOD and WP indices for the current climate. Finally, comparing the results of cases 3 and 4, we found that SR decreases substantially by 2063–2098 in all seven sub-basins of the River Rhine. The lower values of SR for the future climate indicate a shift from winter low flows (SR > 1) to summer low flows (SR < 1) in the two Alpine sub-basins. The WMODs of low flows tend to be earlier than for the current climate in all sub-basins except for the Middle Rhine and Lower Rhine sub-basins. The WP values are slightly larger, showing that the predictability of low flow events increases as the variability in timing decreases for the future climate. From comparison of the error sources evaluated in this study, it is obvious that different RCMs/GCMs have a larger influence on the timing of low flows than different emission scenarios. Finally, this study complements recent analyses of an international project (Rhineblick) by analysing the seasonality aspects of low flows and extends the scope further to understand the effects of hydrological model errors and climate change on three important low flow seasonality properties: regime, timing and persistence.

Air and near-surface ground temperatures, late-winter snow conditions, and characteristics of the vegetation cover and soil were measured across the forest–tundra transition in the uplands east of the Mackenzie Delta, Northwest Territories, in 2004–2010. Mean late-winter snow depth decreased northward from 73 cm in the subarctic boreal forest near Inuvik to 22 cm in low-shrub tundra. Annual near-surface ground temperatures decreased northward by 0.1–0.3 °C/km near the northern limit of trees, in association with an abrupt change in snow depth. The rate decreased to 0.01–0.06 °C/km in the tundra. The freezing season is twice as long as the thawing season in the region, so measured differences in the regional ground thermal regime were dominated by the contrast in winter surface conditions between forest and tundra.

Kirschbaum (Mitig Adapt Strat Glob Change 11:1151–1164, 2006) explores the climatic impact over time of temporarily sequestering carbon from the atmosphere. He concludes that temporary storage of carbon in the terrestrial biosphere “achieves effectively no climate-change mitigation”. His strongly worded statement begs for a response. This paper argues that Kirschbaum’s conclusion is an artifact of the specific perspective of his analysis and his choice of a definition for climate-change impact. Even temporary sinks put us on a lower path for climate change, a path that will not otherwise be accessible. For carbon sinks in the terrestrial biosphere, we argue that sooner is better and longer is better, but even known temporary sinks have value.

In the boreal forests of Alaska, recent changes in climate have influenced the exchange of trace gases, water, and energy between these forests and the atmosphere. These changes in the structure and function of boreal forests can then feed back to impact regional and global climates. In this manuscript, we examine the type and magnitude of the climate feedbacks from boreal forests in Alaska. Research generally suggests that the net effect of a warming climate is a positive regional feedback to warming. Currently, the primary positive climate feedbacks are likely related to decreases in surface albedo due to decreases in snow cover. Fewer negative feedbacks have been identified, and they may not be large enough to counterbalance the large positive feedbacks. These positive feedbacks are most pronounced at the regional scale and reduce the resilience of the boreal vegetation – climate system by amplifying the rate of regional warming. Given the recent warming in this region, the large variety of associated mechanisms that can alter terrestrial ecosystems and influence the climate system, and a reduction in the boreal forest resilience, there is a strong need to continue to quantify and evaluate the feedback pathways.

In Canada, glacial isostatic adjustment (GIA) is the dominant process to cause vertical motion of the land surface. A GIA model is presented herein that can be used to predict slope changes at given locations in North America where GIA is the primary cause for vertical motion. Uncertainty in Pleistocene ice cover and viscosity in the Earth’s mantle prevent one from picking a single GIA model from the literature to predict uplift rates in the region. Therefore, in this study, a range of mantle viscosity values as well as two different ice-loading histories are used in a forward model of the GIA process. The combination of viscosities and ice model that gives the best fit to recently available continuous and episodic GPS observations is assumed to provide the best prediction of slope changes in North America. This model can be used to quantify GIA-induced vertical deformation in local geomorphologic studies. We show that the predicted differential uplift rate in the Nelson River with respect to Lake Winnipeg reaches 1 mm/year over a 200 km distance using the model that best fits the GPS data whereas the ICE-5Gv1.2/VM2 model gives a slightly larger value. The difference in uplift rate between the northern and southern shore of Lake Michigan amounts up to 3 mm/year (slightly larger than the ICE-5Gv1.2/VM2 model), which could lead to a change in shorelines of tens of metres horizontally over a period of 100 years.

We present new temperature and precipitation reconstructions for the past 25 000 cal. years BP from across eastern Beringia based on a network of pollen diagrams, an updated modern pollen calibration database, and an improved methodology using the modern analogue technique (MAT). Time series show July temperatures were around 4 °C lower during full glacial and January temperatures were about 2 °C lower than present. Annual temperatures rose beginning around 16 000 cal. years BP, reaching a maximum around 12 000 cal. year BP. The warming was more rapid in southern Beringia. Annual precipitation varied by 250 mm during the past 25 000 cal. years BP. Maps of reconstructed precipitation patterns show increasingly drier conditions since 12 000 cal. years BP. that vary regionally, suggesting Holocene atmospheric circulation changes at multiple time and space scales. Orbitally forced seasonality changes during the late glacial and early Holocene resulted in reversed seasonal temperature reconstructions due to methodological constraints using the MAT and (or) non-analogue conditions. The magnitude of millennial-scale climate variability in this region was greater during the last glacial and late glacial periods than during the past 8000 years.