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Ligtenberg S.R.M.,University Utrecht | van de Berg W.J.,University Utrecht | van den Broeke M.R.,University Utrecht | Rae J.G.L.,UK Met Office | van Meijgaard E.,KNMI
Climate Dynamics | Year: 2013

A regional atmospheric climate model with multi-layer snow module (RACMO2) is forced at the lateral boundaries by global climate model (GCM) data to assess the future climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS). Two different GCMs (ECHAM5 until 2100 and HadCM3 until 2200) and two different emission scenarios (A1B and E1) are used as forcing to capture a realistic range in future climate states. Simulated ice sheet averaged 2 m air temperature (T2m) increases (1.8-3.0 K in 2100 and 2.4-5.3 K in 2200), simultaneously and with the same magnitude as GCM simulated T2m. The SMB and its components increase in magnitude, as they are directly influenced by the temperature increase. Changes in atmospheric circulation around Antarctica play a minor role in future SMB changes. During the next two centuries, the projected increase in liquid water flux from rainfall and snowmelt, together 60-200 Gt year-1, will mostly refreeze in the snow pack, so runoff remains small (10-40 Gt year-1). Sublimation increases by 25-50 %, but remains an order of magnitude smaller than snowfall. The increase in snowfall mainly determines future changes in SMB on the AIS: 6-16 % in 2100 and 8-25 % in 2200. Without any ice dynamical response, this would result in an eustatic sea level drop of 20-43 mm in 2100 and 73-163 mm in 2200, compared to the twentieth century. Averaged over the AIS, a strong relation between ΔSMB and ΔT2m of 98 ± 5 Gt w.e. year-1 K-1 is found. © 2013 Springer-Verlag Berlin Heidelberg. Source


Van Der Schrier G.,KNMI | Van Oldenborgh G.J.,KNMI
Climate of the Past | Year: 2011

The Central Netherlands Temperature (CNT) is a monthly daily mean temperature series constructed from homogenized time series from the centre of the Netherlands. The purpose of this series is to offer a homogeneous time series representative of a larger area in order to study large-scale temperature changes. It will also facilitate a comparison with climate models, which resolve similar scales. From 1906 onwards, temperature measurements in the Netherlands have been sufficiently standardized to construct a high-quality series. Long time series have been constructed by merging nearby stations and using the overlap to calibrate the differences. These long time series and a few time series of only a few decades in length have been subjected to a homogeneity analysis in which significant breaks and artificial trends have been corrected. Many of the detected breaks correspond to changes in the observations that are documented in the station metadata. This version of the CNT, to which we attach the version number 1.1, is constructed as the unweighted average of four stations (De Bilt, Winterswijk/Hupsel, Oudenbosch/Gilze-Rijen and Gemert/Volkel) with the stations Eindhoven and Deelen added from 1951 and 1958 onwards, respectively. The global gridded datasets used for detecting and attributing climate change are based on raw observational data. Although some homogeneity adjustments are made, these are not based on knowledge of local circumstances but only on statistical evidence. Despite this handicap, and the fact that these datasets use grid boxes that are far larger then the area associated with that of the Central Netherlands Temperature, the temperature interpolated to the CNT region shows a warming trend that is broadly consistent with the CNT trend in all of these datasets. The actual trends differ from the CNT trend up to 30 %, which highlights the need to base future global gridded temperature datasets on homogenized time series. © Author(s) 2011. Source


Katsman C.A.,KNMI | Van Oldenborgh G.J.,KNMI
Geophysical Research Letters | Year: 2011

Over the period 2003-2010, the upper ocean has not gained any heat, despite the general expectation that the ocean will absorb most of the Earth's current radiative imbalance. Answering to what extent this heat was transferred to other components of the climate system and by what process(-es) gets to the essence of understanding climate change. Direct heat flux observations are too inaccurate to assess such exchanges. In this study we therefore trace these heat budget variations by analyzing an ensemble of climate model simulations. The analysis reveals that an 8-yr period without upper ocean warming is not exceptional. It is explained by increased radiation to space (45%), largely as a result of El Nio variability on decadal timescales, and by increased ocean warming at larger depths (35%), partly due to a decrease in the strength of the Atlantic meridional overturning circulation. Recently-observed changes in these two large-scale modes of climate variability point to an upcoming resumption of the upward trend in upper ocean heat content. Copyright 2011 by the American Geophysical Union. Source


In this paper the beneficial impacts of high-resolution (in space and time) wind and temperature observations from aircraft on very short-range numerical weather forecasting are presented. The observations are retrieved using the tracking and ranging radar from the air traffic control facility at Schiphol Airport, Amsterdam, the Netherlands. This enhanced surveillance radar tracks all aircraft in sight every 4 s, generating one million wind and temperature observations per day in a radius of 270 km around the radar. Nowcasting applications will benefit from improved three-dimensional wind fields. When these observations are assimilated into a numerical model with an hourly update cycle, the short-range three-dimensional wind field forecasts match the observations better than those from an operational forecast cycle, which is updated every 3 h. The positive impact on wind in the first hours of the forecast gradually turns into a neutral impact, when compared to other wind and temperature observations. The timeliness of the forecasts combined with the high resolution of the observations are the main reasons for the observed nowcasting benefits. All in all, the assimilation of high-resolution wind (and temperature) observations is found to be beneficial for nowcasting and short-range forecasts up to 2-3 h. © 2012 American Meteorological Society. Source


Wind climate in Northwest Europe is subject to long-term persistence (LTP), also called the Hurst phenomenon. Ignorance of LTP causes underestimation of climatic variability. The quantification of multi-year variability is important for the assessment of the uncertainty of future multi-year wind yields. Estimating LTP requires long homogeneous time series. Such series of wind observations are rare, but annual mean geostrophic wind speed (U) can be used instead. This study demonstrates a method to estimate the 10-year aggregated mean U for the near and the far future and its uncertainty in Northwest Europe. Time series of U were derived from daily sea level pressure from the European Climate Assessment Dataset. Minor inhomogeneities cannot be ruled out, but were shown to hardly affect the estimated Hurst exponent (Ĥ). A maximum likelihood method was adjusted to remove the biases in (Ĥ). The geostrophic wind speed over the North Sea, the British Isles and along the Scandinavian coast are characterised by statistically significant H between 0.58 and 0.74, (H = 0.5 implies no LTP). The additional affect of the parameter uncertainty is estimated in a Bayesian way and is highly dependent on the record length. The assessment of structural changes in future wind fields requires general circulation models. An ensemble of seventeen simulations (ESSENCE) with one single climate model (ECHAM5/MPI-OM) was used to evaluate structural trends and LTP. The estimated Ĥ in the ESSENCE simulations are generally close to 0.5 and not significant. Significant trends in U are found over large parts of the investigated domain, but the trends are small compared to the multi-year variability. Large decreasing trends are found in the vicinity of Iceland and increasing trends near the Greenland coast. This is likely related to the sea ice retreat within the ESSENCE simulations and the associated change in surface temperature gradients. © 2011 The Author(s). Source

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