Climate and biome simulations for the past 21,000 years

This paper reports on a set of paleoclimate simulations for 21, 16, 14, 11 and 6 ka (thousands of years ago) carried out with the Community Climate Model, Version 1 (CCM1) of the National Center for Atmospheric Research (NCAR). This climate model uses four interactive components that were not available in our previous simulations with the NCAR CCM0 (COHMAP, 1988Science, 241, 1043–1052; Wright et al., 1993Global Climate Since the Last Glocial Maximum, University of Minnesota Press, MN): soil moisture, snow hydrology, sea-ice, and mixed-layer ocean temperature. The new simulations also use new estimates of ice sheet height and size from ( Peltier 1994, Science, 265, 195–201), and synchronize the astronomically dated orbital forcing with the ice sheet and atmospheric CO2 levels corrected from radiocarbon years to calendar years. The CCM1 simulations agree with the previous simulations in their most general characteristics. The 21 ka climate is cold and dry, in response to the presence of the ice sheets and lowered CO2 levels. The period 14–6 ka has strengthened northern summer monsoons and warm mid-latitude continental interiors in response to orbital changes. Regional differences between the CCM1 and CCM0 simulations can be traced to the effects of either the new interactive model components or the new boundary conditions. CCM1 simulates climate processes more realistically, but has additional degrees of freedom that can allow the model to ‘drift’ toward less realistic solutions in some instances. The CCM1 simulations are expressed in terms of equilibrium vegetation using BIOME 1, and indicate large shifts in biomes. Northern tundra and forest biomes are displaced southward at glacial maximum and subtropical deserts contract in the mid-Holocene when monsoons strengthen. These vegetation changes could, if simulated interactively, introduce additional climate feedbacks. The total area of vegetated land remains nearly constant through time because the exposure of continental shelves with lowered sea level largely compensates for the land covered by the expanded ice sheets.

How do I know if my forecasts are better? Using benchmarks in Hydrological ensemble prediction

The skill of a forecast can be assessed by comparing the relative proximity of both the forecast and a benchmark to the observations. Example benchmarks include climatology or a naïve forecast. Hydrological ensemble prediction systems (HEPS) are currently transforming the hydrological forecasting environment but in this new field there is little information to guide researchers and operational forecasters on how benchmarks can be best used to evaluate their probabilistic forecasts. In this study, it is identified that the forecast skill calculated can vary depending on the benchmark selected and that the selection of a benchmark for determining forecasting system skill is sensitive to a number of hydrological and system factors. A benchmark intercomparison experiment is then undertaken using the continuous ranked probability score (CRPS), a reference forecasting system and a suite of 23 different methods to derive benchmarks. The benchmarks are assessed within the operational set-up of the European Flood Awareness System (EFAS) to determine those that are ‘toughest to beat’ and so give the most robust discrimination of forecast skill, particularly for the spatial average fields that EFAS relies upon. Evaluating against an observed discharge proxy the benchmark that has most utility for EFAS and avoids the most naïve skill across different hydrological situations is found to be meteorological persistency. This benchmark uses the latest meteorological observations of precipitation and temperature to drive the hydrological model. Hydrological long term average benchmarks, which are currently used in EFAS, are very easily beaten by the forecasting system and the use of these produces much naïve skill. When decomposed into seasons, the advanced meteorological benchmarks, which make use of meteorological observations from the past 20 years at the same calendar date, have the most skill discrimination. They are also good at discriminating skill in low flows and for all catchment sizes. Simpler meteorological benchmarks are particularly useful for high flows. Recommendations for EFAS are to move to routine use of meteorological persistency, an advanced meteorological benchmark and a simple meteorological benchmark in order to provide a robust evaluation of forecast skill. This work provides the first comprehensive evidence on how benchmarks can be used in evaluation of skill in probabilistic hydrological forecasts and which benchmarks are most useful for skill discrimination and avoidance of naïve skill in a large scale HEPS. It is recommended that all HEPS use the evidence and methodology provided here to evaluate which benchmarks to employ; so forecasters can have trust in their skill evaluation and will have confidence that their forecasts are indeed better.

Do US macroeconomic forecasters exaggerate their differences?

Application of the Bernhardt et al. (Journal of Financial Economics 2006; 80(3): 657–675) test of herding to the calendar-year annual output growth and inflation forecasts suggests forecasters tend to exaggerate their differences, except at the shortest horizon, when they tend to herd. We consider whether these types of behaviour can help to explain the puzzle that professional forecasters sometimes make point predictions and histogram forecasts which are mutually inconsistent.

Variability and trends in England and Wales precipitation

The England and Wales precipitation (EWP) dataset is a homogeneous time series of daily accumulations from 1931 to 2014, composed from rain gauge observations spanning the region. The daily regional-average precipitation statistics are shown to be well described by a Weibull distribution, which is used to define extremes in terms of percentiles. Computed trends in annual and seasonal precipitation are sensitive to the period chosen, due to large variability on interannual and decadal timescales. Atmospheric circulation patterns associated with seasonal precipitation variability are identified. These patterns project onto known leading modes of variability, all of which involve displacements of the jet stream and storm-track over the eastern Atlantic. The intensity of daily precipitation for each calendar season is investigated by partitioning all observations into eight intensity categories contributing equally to the total precipitation in the dataset. Contrary to previous results based on shorter periods, no significant trends of the most intense categories are found between 1931 and 2014. The regional-average precipitation is found to share statistical properties common to the majority of individual stations across England and Wales used in previous studies. Statistics of the EWP data are examined for multi-day accumulations up to 10 days, which are more relevant for river flooding. Four recent years (2000, 2007, 2008 and 2012) have a greater number of extreme events in the 3-and 5-day accumulations than any previous year in the record. It is the duration of precipitation events in these years that is remarkable, rather than the magnitude of the daily accumulations.