Seasonal predictions based on two dynamical models

Abstract

Two dynamical models are used to perform a series of seasonal predictions. One model, referred to as GCM2, was designed as a general circulation model for climate studies, while the second one, SEF, was designed for numerical weather prediction. The seasonal predictions cover the 26‐year period 1969–1994. For each of the four seasons, ensembles of six forecasts are produced with each model, the six runs starting from initial conditions six hours apart. The sea surface temperature (SST) anomaly for the month prior to the start of the forecast is persisted through the three‐month prediction period, and added to a monthly‐varying climatological SST field.

The ensemble‐mean predictions for each of the models are verified independently, and the two ensembles are blended together in two different ways: as a simple average of the two models, denoted GCMSEF, and with weights statistically determined to minimize the mean‐square error (the Best Linear Unbiased Estimate (BLUE) method).

The GCMSEF winter and spring predictions show a Pacific/North American (PNA) response to a warm tropical SST anomaly. The temporal anomaly correlation between the zero‐lead GCMSEF mean‐seasonal predictions and observations of the 500‐hPa height field (Z₅₀₀) shows statistically significant forecast skill over parts of the PNA area for all seasons, but there is a notable seasonal variability in the distribution of the skill. The GCMSEF predictions are more skilful than those of either model in winter, and about as skilful as the better of the two models in the other seasons.

The zero‐lead surface air temperature GCMSEF forecasts over Canada are found to be skilful (a) over the west coast in all seasons except fall, (b) over most of Canada in summer, and (c) over Manitoba, Ontario and Quebec in the fall. In winter the skill of the BLUE forecasts is substantially better than that of the GCMSEF predictions, while for the other seasons the difference in skill is not statistically significant.

When the Z₅₀₀ forecasts are averaged over months two and three of the seasons (one‐month lead predictions), they show skill in winter over the north‐eastern Pacific, western Canada and eastern North America, a skill that comes from those years with strong SST anomalies of the El Niño/La Niña type. For the other seasons, predictions averaged over months two and three show little skill in Z₅₀₀ in the mid‐latitudes. In the tropics, predictive skill is found in Z₅₀₀ in all seasons when a strong SST anomaly of the El Niño/La Niña type is observed. In the absence of SST anomalies of this type, tropical forecast skill is still found over much of the tropics in months two and three of the northern hemisphere spring and summer, but not in winter and fall.     

Trends and low frequency variability of extra-tropical cyclone activity in the ensemble of twentieth century reanalysis

An objective cyclone tracking algorithm is applied to twentieth century reanalysis (20CR) 6-hourly mean sea level pressure fields for the period 1871–2010 to infer historical trends and variability in extra-tropical cyclone activity. The tracking algorithm is applied both to the ensemble-mean analyses and to each of the 56 ensemble members individually. The ensemble-mean analyses are found to be unsuitable for accurately determining cyclone statistics. However, pooled cyclone statistics obtained by averaging statistics from individual members generally agree well with statistics from the NCEP-NCAR reanalyses for 1951–2010, although 20CR shows somewhat weaker cyclone activity over land and stronger activity over oceans. Both reanalyses show similar cyclone trend patterns in the northern hemisphere (NH) over 1951–2010. Homogenized pooled cyclone statistics are analyzed for trends and variability. Conclusions account for identified inhomogeneities, which occurred before 1949 in the NH and between 1951 and 1985 in the southern hemisphere (SH). Cyclone activity is estimated to have increased slightly over the period 1871–2010 in the NH. More substantial increases are seen in the SH. Notable regional and seasonal variations in trends are evident, as is profound decadal or longer scale variability. For example, the NH increases occur mainly in the mid-latitude Pacific and high-latitude Atlantic regions. 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. European trends are also consistent with trends in the mean duration of wet spells derived from rain gauge data in Europe.     

Changes in temperature and precipitation extremes in the CMIP5 ensemble

Twenty-year temperature and precipitation extremes and their projected future changes are evaluated in an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), updating a similar study based on the CMIP3 ensemble. The projected changes are documented for three radiative forcing scenarios. The performance of the CMIP5 models in simulating 20-year temperature and precipitation extremes is comparable to that of the CMIP3 ensemble. The models simulate late 20th century warm extremes reasonably well, compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes. Simulated late 20th century precipitation extremes are plausible in the extratropics but uncertainty in extreme precipitation in the tropics and subtropics remains very large, both in the models and the observationally-constrained datasets. Consistent with CMIP3 results, CMIP5 cold extremes generally warm faster than warm extremes, mainly in regions where snow and sea-ice retreat with global warming. There are tropical and subtropical regions where warming rates of warm extremes exceed those of cold extremes. Relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation. The corresponding waiting times for late 20th century extreme precipitation events are reduced almost everywhere, except for a few subtropical regions. The CMIP5 planetary sensitivity in extreme precipitation is about 6 %/°C, with generally lower values over extratropical land.     

Trends and variability of storminess in the Northeast Atlantic region, 1874–2007

This article builds on the previous studies on storminess conditions in the northeast North Atlantic–European region. The period of surface pressure data analyzed is extended from 1881–1998 to 1874–2007. The seasonality and regional differences of storminess conditions in this region are also explored in more detail. The results show that storminess conditions in this region have undergone substantial decadal or longer time scale fluctuations, with considerable seasonal and regional differences. The most notable differences are seen between winter and summer, and between the North Sea area and other parts of the region. In particular, winter storminess shows an unprecedented maximum in the early 1990s in the North Sea area and a steady upward trend in the northeastern part of the region, while it appears to have declined in the western part of the region. In summer, storminess appears to have declined in most parts of this region. In the transition seasons, the storminess trend is characterized by increases in the northern part of the region and decreases in the southeastern part, with increases in the north being larger in spring. In particular, the results also show that the earliest storminess maximum occurred in summer (around 1880), while the latest storminess maximum occurred in winter (in the early 1990s). Looking at the annual metrics alone (as in previous studies), one would conclude that the latest storminess maximum is at about the same level as the earliest storminess maximum, without realizing that this is comparing the highest winter storminess level with the highest summer storminess level in the period of record analyzed, while winter and summer storminess conditions have undergone very different long-term variability and trends. Also, storminess conditions in the NE Atlantic region are found to be significantly correlated with the simultaneous NAO index in all seasons but autumn. The higher the NAO index, the rougher the NE Atlantic storminess conditions, especially in winter and spring.     

Detection of external influence on trends of atmospheric storminess and northern oceans wave heights

The atmospheric storminess as inferred from geostrophic wind energy and ocean wave heights have increased in boreal winter over the past half century in the high-latitudes of the northern hemisphere (especially the northeast North Atlantic), and have decreased in more southerly northern latitudes. This study shows that these trend patterns contain a detectable response to anthropogenic and natural forcing combined. The effect of external influence is found to be strongest in the winter hemisphere, that is, in the northern hemisphere in January–March and in the southern hemisphere in July–September. However, the simulated response to anthropogenic and natural forcing combined, which was obtained directly from climate models in the case of geostrophic wind energy and indirectly via an empirical downscaling procedure in the case of ocean wave heights, is significantly weaker than the magnitude of the observed changes in these parameters.     

Evaluation of proxy-based millennial reconstruction methods

A range of existing statistical approaches for reconstructing historical temperature variations from proxy data are compared using both climate model data and real-world paleoclimate proxy data. We also propose a new method for reconstruction that is based on a state-space time series model and Kalman filter algorithm. The state-space modelling approach and the recently developed RegEM method generally perform better than their competitors when reconstructing interannual variations in Northern Hemispheric mean surface air temperature. On the other hand, a variety of methods are seen to perform well when reconstructing surface air temperature variability on decadal time scales. An advantage of the new method is that it can incorporate additional, non-temperature, information into the reconstruction, such as the estimated response to external forcing, thereby permitting a simultaneous reconstruction and detection analysis as well as future projection. An application of these extensions is also demonstrated in the paper.     

Intercomparison of interannual variability and potential predictability: an AMIP diagnostic subproject

 The inter-annual variability and potential predictability of 850 hPa temperature (T ₈₅₀), 500 hPa geopotential (φ₅₀₀) and 300 hPa stream function (ψ₃₀₀) simulated by the models participating in the Atmospheric Model Intercomparison Project (AMIP) are examined. The total inter-annual variability is partitioned into a potentially predictable component which arises from the forcing implied by the prescribed SST and sea-ice evolution, or from sources internal to the simulated climate, and an unpredictable low frequency component induced by “weather noise”. There is wide variation in the ability to simulate observed inter-annual variability, both total and weather-noise induced. A majority of models under simulate seasonal mean φ₅₀₀ variability in DJF and JJA and over simulate ψ₃₀₀ variability in JJA. All but one model simulates less T ₈₅₀ total inter-annual variability than in the analysed data. There is little apparent connection between gross model characteristics and the corresponding ability to simulate observed variability, with the possible exceptions of resolution. Received: 7 July 1996 / Accepted: 8 January 1998     

The impact of combined ENSO and PDO on the PNA climate: a 1,000-year climate modeling study

This study analyzes the atmospheric response to the combined Pacific interannual ENSO and decadal–interdecadal PDO variability, with a focus on the Pacific-North American (PNA) sector, using a 1,000-year long integration of the Canadian Center for Climate Modelling and Analysis (CCCma) coupled climate model. Both the tropospheric circulation and the North American temperature suggest an enhanced PNA-like climate response and impacts on North America when ENSO and PDO variability are in phase. The anomalies of the centers of action for the PNA-like pattern are significantly different from zero and the anomaly pattern is field significant. In association with the stationary wave anomalies, large stationary wave activity fluxes appear in the mid-high latitudes originating from the North Pacific and flowing downstream toward North America. There are significant Rossby wave source anomalies in the extratropical North Pacific and in the subtropical North Pacific. In addition, the axis of the Pacific storm track shifts southward with the positive PNA. Atmospheric heating anomalies associated with ENSO variability are confined primarily to the tropics. There is an anomalous heating center over the northeast Pacific, together with anomalies with the same polarity in the tropical Pacific, for the PDO variability. The in-phase combination of ENSO and PDO would in turn provide anomalous atmospheric energy transports towards North America from both the Tropical Pacific and the North Pacific, which tends to favor the occurrence of stationary wave anomalies and would lead to a PNA-like wave anomaly structure. The modeling results also confirm our analysis based on the observational record in the twentieth century.