It is known that carbon dioxide emissions cause the Earth to warm, but no previous study has focused on examining how long it takes to reach maximum warming following a particular CO2 emission. Using conjoined results of carbon-cycle and physical-climate model intercomparison projects, we find the median time between an emission and maximum warming is 10.1 years, with a 90% probability range of 6.6–30.7 years.

The El Niño Southern Oscillation (ENSO) is Earth’s dominant source of interannual climate variability, but its response to global warming remains highly uncertain. To improve our understanding of ENSO’s sensitivity to external climate forcing, it is paramount to determine its past behaviour by using palaeoclimate data and model simulations. Palaeoclimate records show that ENSO has varied considerably since the Last Glacial Maximum (21,000 years ago) and some data sets suggest a gradual intensification of ENSO over the past ~6,000 years.

We analyzed volume change and mass balance of outlet glaciers of the northern Antarctic Peninsula over the period 2011 to 2013, using topographic data of high vertical accuracy and great spatial detail, acquired by bistatic radar interferometry of the TanDEM-X/TerraSAR-X satellite formation. The study area includes glaciers draining into the Larsen-A, Larsen Inlet, and Prince-Gustav-Channel embayments. After collapse of buttressing ice shelves in 1995 the glaciers became tidewater calving glaciers and accelerated, resulting in increased ice export.

Of the many processes contributing to long-term sea-level change, little attention has been paid to the large-scale contributions of salinity-driven halosteric changes. We evaluate observed and simulated estimates of long-term (1950-present) halosteric patterns and compare these to corresponding thermosteric changes. Spatially coherent halosteric patterns are visible in the historical record, and are consistent with estimates of long-term water cycle amplification.

The variation and control of soil organic carbon (SOC) and other nutrients in permafrost regions are critical for studying the carbon cycle and its potential feedbacks to climate change; however, they are poorly understood. Soil nutrients samples at depths of 0–10, 10–20, 20–30, and 30–40 cm, were sampled eight times in 2009 in alpine swamp meadow, alpine meadow and alpine steppe in permafrost regions of the central Qinghai-Tibetan Plateau.

The large uncertainty in soil carbon–climate feedback predictions has been attributed to the incorrect parameterization of decomposition temperature sensitivity and microbial carbon use efficiency. Empirical experiments have found that these parameters vary spatiotemporally, but such variability is not included in current ecosystem models. Here we use a thermodynamically based decomposition model to test the hypothesis that this observed variability arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions.

Widespread flooding occurred across northwest Europe during the winter of 2013/14, resulting in large socioeconomic damages. In the historical record, extreme hydrological events have been connected with intense water vapour transport. Here we show that water vapour transport has higher medium-range predictability compared with precipitation in the winter 2013/14 forecasts from the European Centre for Medium-Range Weather Forecasts. Applying the concept of potential predictability, the transport is found to extend the forecast horizon by 3 days in some European regions.