Contrasting northern and southern European winter climate trends during the Last Interglacial

Paleoclimate reconstructions, pollen–climate calibration data, and cross-validation results.

Abstract. During the Last Interglacial period (~ 130–115 thousand years ago) the Arctic climate was warmer than today, and global mean sea level was probably more than 6.6 m higher. However, there are large discrepancies in the estimated contributions to this sea level change from various sources (the Greenland and Antarctic ice sheets and smaller ice caps). Here, we determine probabilistically the likely contribution of Greenland ice sheet melt to Last Interglacial sea level rise, taking into account ice sheet model parametric uncertainty. We perform an ensemble of 500 Glimmer ice sheet model simulations forced with climatologies from the climate model HadCM3, and constrain the results with palaeodata from Greenland ice cores. Our results suggest a 90% probability that Greenland ice melt contributed at least 0.6 m, but less than 10% probability that it exceeded 3.5 m, a value which is lower than several recent estimates. Many of these previous estimates, however, did not include a full general circulation climate model that can capture atmospheric circulation and precipitation changes in response to changes in insolation forcing and orographic height. Our combined modelling and palaeodata approach suggests that the Greenland ice sheet is less sensitive to orbital forcing than previously thought, and it implicates Antarctic melt as providing a substantial contribution to Last Interglacial sea level rise. Future work should assess additional uncertainty due to inclusion of basal sliding and the direct effect of insolation on surface melt. In addition, the effect of uncertainty arising from climate model structural design should be taken into account by performing a multi-climate-model comparison.

Abstract. The performance of the Rossby Centre regional climate model RCA4 is investigated for the Arctic CORDEX (COordinated Regional climate Downscaling EXperiment) region, with an emphasis on its suitability to be coupled to a regional ocean and sea ice model. Large biases in mean sea level pressure (MSLP) are identified, with pronounced too-high pressure centred over the North Pole in summer of over 5 hPa, and too-low pressure in winter of a similar magnitude. These lead to biases in the surface winds, which will potentially lead to strong sea ice biases in a future coupled system. The large-scale circulation is believed to be the major reason for the biases, and an implementation of spectral nudging is applied to remedy the problems by constraining the large-scale components of the driving fields within the interior domain. It is found that the spectral nudging generally corrects for the MSLP and wind biases, while not significantly affecting other variables, such as surface radiative components, two-metre temperature and precipitation.

Paleoclimate reconstructions, pollen–climate calibration data, and cross-validation results.

<p>We present here a novel application of state-of-the-art surge modeling on a past climate of special interest. The Last Interglacial (LIG; 125,000 years ago) was the latest instance of a climate (slightly) warmer than present: for this reason its study can inform on the response of several climate components to a climate state with partial resemblance to possible futures. Climate variables like temperature and precipitation have been extensively studied for the LIG. Here, we calculate for the first time the implications of the altered LIG atmospheric circulation (both in mean state and extremes) for storm surges along the global coastline. This presents particular interest since it is often claimed that a warmer climate may imply enhanced storminess in some ocean basins. We use sub-daily results from simulations of the LIG and of the pre-industrial periods with the climate model CESM1.2 (equipped with atmosphere module CAM5, with ca. 1 degree horizontal resolution) to force the Global Tide and Surge Model (GTSM) for 30-years at climate equilibrium conditions. We analyze patterns of storminess and of storm surges, and report on the anomalies in those metrics between the LIG and the pre-industrial climate. These results can help contextualize proxy-based reconstructions of storms of the LIG, as well as projections of storm surges in a future warmer climate. Finally, we also reconstruct tides of the LIG, aiming to provide useful constrains to paleo sea-level reconstructions.</p>

Abstract This study proposes a method to estimate the timing of human-induced climate change (HICC) emergence from internal climate variability (ICV) for hydrological impact studies based on climate model ensembles. Specifically, ICV is defined as the inter-member difference in a multi-member ensemble of a climate model in which human-induced climate trends have been removed through a detrending method. HICC is defined as the mean of multiple climate models. The intersection between HICC and ICV curves is defined as the time of emergence (ToE) of HICC from ICV. A case study of the Hanjiang River watershed in China shows that the temperature change has already emerged from ICV during the last century. However, the precipitation change will be masked by ICV up to the middle of this century. With the joint contributions of temperature and precipitation, the ToE of streamflow occurs about one decade later than that of precipitation. This implies that consideration for water resource vulnerability to climate should be more concerned with adaptation to ICV in the near-term climate (present through mid-century), and with HICC in the long-term future, thus allowing for more robust adaptation strategies to water transfer projects in China.

This study provides an overview of South Carolina’s climatic trends and variability over the last century. Most studies nationally have focused on large-scale temperature and precipitation trends, but examination of regional and local trends are needed to monitor the significance of the state’s climate signal and advance our understanding of the complex physical controls on the region’s climate. The behavior of several climatic elements since the 1900s were evaluated for 66 sites in South Carolina and bordering states to determine the variability of the system on annual, seasonal and decadal scales, including the use of threshold approaches to assess climate patterns. Results from the bordering states were not directly discussed, but were included in the study for continuity.

Abstract. The performance of the Rossby Centre regional climate model RCA4 is investigated for the Arctic CORDEX region, with an emphasis on its suitability to be coupled to a regional ocean and sea-ice model. Large biases in mean sea level pressure (MSLP) are identified, with pronounced too high pressure centred over the North Pole in summer of over 5 hPa, and too low pressure in winter of a similar magnitude. These lead to biases in the surface winds, which will potentially lead to strong sea-ice biases in a future coupled system. The large scale circulation is believed to be the major reason for the biases, and an implementation of spectral nudging is applied to remedy the problems by constraining the large scale components of the driving fields within the interior domain. It is found that the spectral nudging generally corrects for the MSLP and wind biases, while not significantly affecting other variables such as surface radiative components, two metre temperature and precipitation.

Abstract The Western Arctic Linkage Experiment (WALE) is aimed at understanding the role of high-latitude terrestrial ecosystems in the response of the Arctic system to global change through collection and comparison of climate datasets and model results. In this paper, a spatiotemporal approach is taken to compare and validate model results from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) with commonly used analysis and reanalysis datasets for monthly averages of temperature and precipitation in 1992–2000 and for a study area at 55°–65°N, 160°–110°W in northwestern Canada and Alaska. Objectives include a quantitative assessment of similarity between datasets and climate model fields, and identification of geographic areas and seasons that are problematic in modeling, with potential causes that may aid in model improvement. These are achieved by application of algebraic similarity mapping, a simple yet effective method for synoptic analysis of many (here, 45) different spatial datasets, maps, and models. Results indicate a dependence of model–data similarity on seasonality, on climate variable, and on geographic location. In summary, 1) similarity of data and models is better for temperature than for precipitation; and 2) modeling of summer precipitation fields, and to a lesser extent, temperature fields, appears more problematic than that of winter fields. The geographic distribution of areas with best and worst agreement shifts throughout the year, with generally better agreement between maps and models in the northeastern and northern inland areas than in topographically complex and near-coastal areas. The study contributes to an understanding of the geographic complexity of the Arctic system and modeling its diverse climate.

In this study, we compare the diurnal variation in stratospheric ozone of the MACC (Monitoring Atmospheric Composition and Climate) reanalysis, ECMWF Reanalysis Interim (ERA-Interim), and the free-running WACCM (Whole Atmosphere Community Climate Model). The diurnal variation of stratospheric ozone results from photochemical and dynamical processes depending on altitude, latitude, and season. MACC reanalysis and WACCM use similar chemistry modules and calculate a similar diurnal cycle in ozone when it is caused by a photochemical variation. The results of the two model systems are confirmed by observations of the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) experiment and three selected sites of the Network for Detection of Atmospheric Composition Change (NDACC) at Mauna Loa, Hawaii (tropics), Bern, Switzerland (midlatitudes), and Ny-Ålesund, Svalbard (high latitudes). On the other hand, the ozone product of ERA-Interim shows considerably less diurnal variation due to photochemical variations. The global maxima of diurnal variation occur at high latitudes in summer, e.g., near the Arctic NDACC site at Ny-Ålesund, Svalbard. The local OZORAM radiometer observes this effect in good agreement with MACC reanalysis and WACCM. The sensed diurnal variation at Ny-Ålesund is up to 8% (0.4 ppmv) due to photochemical variations in summer and negligible during the dynamically dominated winter. However, when dynamics play a major role for the diurnal ozone variation as in the lower stratosphere (100–20 hPa), the reanalysis models ERA-Interim and MACC which assimilate data from radiosondes and satellites outperform the free-running WACCM. Such a domain is the Antarctic polar winter where a surprising novel feature of diurnal variation is indicated by MACC reanalysis and ERA-Interim at the edge of the polar vortex. This effect accounts for up to 8% (0.4 ppmv) in both model systems. In summary, MACC reanalysis provides a global description of the diurnal variation of stratospheric ozone caused by dynamics and photochemical variations. This is of high interest for ozone trend analysis and other research which is based on merged satellite data or measurements at different local time.