Showing papers by "Gilbert P. Compo published in 2014"

Continental heat anomalies and the extreme melting of the Greenland ice surface in 2012 and 1889

Abstract: Recent decades have seen increased melting of the Greenland ice sheet. On 11 July 2012, nearly the entire surface of the ice sheet melted; such rare events last occurred in 1889 and, prior to that, during the Medieval Climate Anomaly. Studies of the 2012 event associated the presence of a thin, warm elevated liquid cloud layer with surface temperatures rising above the melting point at Summit Station, some 3212 m above sea level. Here we explore other potential factors in July 2012 associated with this unusual melting. These include (1) warm air originating from a record North American heat wave, (2) transitions in the Arctic Oscillation, (3) transport of water vapor via an Atmospheric River over the Atlantic to Greenland, and (4) the presence of warm ocean waters south of Greenland. For the 1889 episode, the Twentieth Century Reanalysis and historical records showed similar factors at work. However, markers of biomass burning were evident in ice cores from 1889 which may reflect another possible factor in these rare events. We suggest that extreme Greenland summer melt episodes, such as those recorded recently and in the late Holocene, could have involved a similar combination of slow climate processes, including prolonged North American droughts/heat waves and North Atlantic warm oceanic temperature anomalies, together with fast processes, such as excursions of the Arctic Oscillation, and transport of warm, humid air in Atmospheric Rivers to Greenland. It is the fast processes that underlie the rarity of such events and influence their predictability.

Pacific Walker Circulation variability in coupled and uncoupled climate models

Abstract: There is still considerable uncertainty concerning twentieth century trends in the Pacific Walker Circulation (PWC). In this paper, observational datasets, coupled (CMIP5) and uncoupled (AGCM) model simulations, and additional numerical sensitivity experiments are analyzed to investigate twentieth century changes in the PWC and their physical mechanisms. The PWC weakens over the century in the CMIP5 simulations, but strengthens in the AGCM simulations and also in the observational twentieth century reanalysis (20CR) dataset. It is argued that the weakening in the CMIP5 simulations is not a consequence of a reduced global convective mass flux expected from simple considerations of the global hydrological response to global warming, but is rather due to a weakening of the zonal equatorial Pacific sea surface temperature (SST) gradient. Further clarification is provided by additional uncoupled atmospheric general circulation model simulations in which the ENSO-unrelated and ENSO-related portions of the observed SST changes are prescribed as lower boundary conditions. Both sets of SST forcing fields have a global warming trend, and both sets of simulations produce a weakening of the global convective mass flux. However, consistent with the strong role of the zonal SST gradient, the PWC strengthens in the simulations with the ENSO-unrelated SST forcing, which has a strengthening zonal SST gradient, despite the weakening of the global convective mass flux. Overall, our results suggest that the PWC strengthened during twentieth century global warming, but also that this strengthening was partly masked by a weakening trend associated with ENSO-related PWC variability.

Web-Based Reanalysis Intercomparison Tools (WRIT) for Analysis and Comparison of Reanalyses and Other Datasets

Abstract: While atmospheric reanalysis datasets are widely used in climate science, many technical issues hinder comparing them to each other and to observations. The reanalysis fields are stored in diverse file architectures, data formats, and resolutions. Their metadata, such as variable name and units, can also differ. Individual users have to download the fields, convert them to a common format, store them locally, change variable names, regrid if needed, and convert units. Even if a dataset can be read via the Open-Source Project for a Network Data Access Protocol (commonly known as OPeNDAP) or a similar protocol, most of this work is still needed. All of these tasks take time, effort, and money. Our group at the Cooperative Institute for Research in the Environmental Sciences at the University of Colorado and affiliated colleagues at the NOAA's Earth System Research Laboratory Physical Sciences Division have expertise both in making reanalysis datasets available and in creating web-based climate analysis tool...

Is the storminess in the Twentieth Century Reanalysis really inconsistent with observations? A reply to the comment by Krueger et al. (2013b)

Abstract: In a recent study of trends and low frequency variability of extra-tropical cyclone activity in the ensemble of Twentieth Century Reanalyses, we concluded that “For the North Atlantic-European region and southeast Australia, the 20CR cyclone trends are in agreement with trends in geostrophic wind extremes derived from in-situ surface pressure observations”. This conclusion has been challenged by Krueger et al. (Clim Dyn, submitted, 2013b), because a recent study (doi: 10.1175/JCLI-D-12-00309.1 , by the same lead author) comparing annual 95th percentiles (P95) of geostrophic wind speed (geo-wind) derived from surface pressure observations and from the 20CR found that “20CR-geostrophic storminess deviates to a large extent from the observation-based curve” in the period prior to 1950. In this reply, we show that our conclusion is valid; and we clarify that several factors contribute to the reported inconsistencies between the 20CR and observation-based geo-wind extremes. These include the choice of index that is used to represent the temporal variation of extremes (e.g., annual vs. seasonal percentiles), the use of different sampling intervals (6-hourly vs. 3-hourly), and the presence of very large errors in the observations that were not identified, corrected, or excluded in any of the previous studies of observation-based geo-wind extremes. We show that the time series of consecutive seasonal P95 geo-winds derived from the observations and from 20CR are in good agreement back to about 1893, with some deviation earlier when the observations (especially digitized data) remain limited and are more uncertain. We find that the correlation between the 20CR and observation-based geo-wind extremes (P95) time series for the full 134-year record is highly significant statistically, with and without the correction or exclusion of the newly identified erroneous SLP values. The agreement between 20CR and observations is further improved after the correction or exclusion of these erroneous values.

Downwelling longwave flux over Summit, Greenland, 2010–2012: Analysis of surface‐based observations and evaluation of ERA‐Interim using wavelets

Abstract: This study analyzes the downwelling longwave radiation (DLW) over the Greenland Ice Sheet (GrIS) using surface-based observations from Summit Station (72°N, 38°W; 3210 m) and the European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim) DLW fields. Since surface-based observations are sparse in the Arctic, the accuracy of including reanalyses for spatial context is assessed. First, the DLW at Summit is reported, including the significant time scales of variability using time-frequency decomposition (wavelet analysis). A new method for evaluating reanalyses is then introduced that also uses wavelet analysis. ERA-Interim DLW performs reasonably well at Summit, but because it includes too many thin clouds and too few thick clouds, it is biased low overall. The correlation between the observations and ERA-Interim drops from r2 > 0.8 to near 0 for time series reconstructed from time scales less than ~4 days. These low correlations and additional analyses suggest that the spatial resolution of the data sets is a factor in representing variability on short time scales. The bias is low across all time scales and is thus likely tied to cloud generation processes in the model rather than the spatial representation of the atmosphere across the GrIS. The exception is autumn, when ERA-Interim overestimates the influence of clouds at time scales of 1 and 4 weeks. The spatial distribution of cloud influence on the DLW across the GrIS indicates that Summit is located in a transition zone with respect to cloud properties. The gradient across this transition zone is steepest near Summit in autumn, so the spatial characteristics of the atmosphere near Summit may contribute to the ERA-Interim bias during this time.