Uncertainty in weather and climate prediction

Following Lorenz's seminal work on chaos theory in the 1960s, probabilistic approaches to prediction have come to dominate the science of weather and climate forecasting. This paper gives a perspective on Lorenz's work and how it has influenced the ways in which we seek to represent uncertainty in forecasts on all lead times from hours to decades. It looks at how model uncertainty has been represented in probabilistic prediction systems and considers the challenges posed by a changing climate. Finally, the paper considers how the uncertainty in projections of climate change can be addressed to deliver more reliable and confident assessments that support decision-making on adaptation and mitigation

Scale interactions on diurnal toseasonal timescales and their relevanceto model systematic errors

Examples of current research into systematic errors in climate models are used to demonstrate the importance of scale interactions on diurnal,intraseasonal and seasonal timescales for the mean and variability of the tropical climate system. It has enabled some conclusions to be drawn about possible processes that may need to be represented, and some recommendations to be made regarding model improvements. It has been shown that the Maritime Continent heat source is a major driver of the global circulation but yet is poorly represented in GCMs. A new climatology of the diurnal cycle has been used to provide compelling evidence of important land-sea breeze and gravity wave effects, which may play a crucial role in the heat and moisture budget of this key region for the tropical and global circulation. The role of the diurnal cycle has also been emphasized for intraseasonal variability associated with the Madden Julian Oscillation (MJO). It is suggested that the diurnal cycle in Sea Surface Temperature (SST) during the suppressed phase of the MJO leads to a triggering of cumulus congestus clouds, which serve to moisten the free troposphere and hence precondition the atmosphere for the next active phase. It has been further shown that coupling between the ocean and atmosphere on intraseasonal timescales leads to a more realistic simulation of the MJO. These results stress the need for models to be able to simulate firstly, the observed tri-modal distribution of convection, and secondly, the coupling between the ocean and atmosphere on diurnal to intraseasonal timescales. It is argued, however, that the current representation of the ocean mixed layer in coupled models is not adequate to represent the complex structure of the observed mixed layer, in particular the formation of salinity barrier layers which can potentially provide much stronger local coupling between the atmosphere and ocean on diurnal to intraseasonal timescales

Atmospheric response to observed intraseasonal tropical sea surface temperature anomalies

The major tropical convective and circulation features of the intraseasonal or Madden-Julian Oscillation (MJO) are simulated as a passive response to observed MJO sea surface temperature (SST) anomalies in an atmospheric general circulation model (AGCM), strengthening the case for ocean-atmosphere interactions being central to MJO dynamics. However, the magnitude of the surface fluxes diagnosed from the MJO cycle in the AGCM, that would feed back onto the ocean in a coupled system, are much weaker than in observations. The phasing of the convective-dynamical model response to the MJO SST anomalies and the associated surface flux anomalies is too fast compared to observations of the (potentially) coupled system, and would act to damp the SST anomalies

Observed Changes in the Lifetime and Amplitude of the Madden–Julian Oscillation Associated with Interannual ENSO Sea Surface Temperature Anomalies

The Madden-Julian Oscillation (MJO) is analysed using the reanalysis zonal wind and satellite outgoing longwave radiation-based indices of Wheeler and Hendon for the 1974-2005 period. The average life time of MJO events varies with season, being 36 days for events whose central date occurs in December, and 48 days for events in September. The life time of the MJO in the equinoctial seasons (March-May and October-December) is also dependent on the state of the El Nino-Southern Oscillation (ENSO). During October-December it is only 32 days under El Nino conditions, increasing to 48 days under La Nina conditions, with similar values in northern spring. This difference is due to faster eastward propagation of the MJO convective anomalies through the Maritime Continent and western Pacific during El Nino, consistent with theoretical arguments concerning equatorial wave speeds. The analysis is extended back to 1950 by using an alternative definition of the MJO based on just the zonal wind component of the Wheeler and Hendon indices. A rupture in the amplitude of the MJO is found in 1975, at the same time as the well known rupture in the ENSO time series, that has been associated with the Pacific Decadal Oscillation. The mean amplitude of the MJO is 16% larger in the post-rupture period (1976-2005) compared to the pre-rupture period (1950-1975). Before the 1975 rupture, the amplitude of the MJO is a maximum (minimum) under El Nino (La Nina) conditions during northern winter, and a minimum (maximum) under El Nino (La Nina) conditions during northern summer. After the rupture, this relationship disappears. When the MJO-ENSO relationship is analysed using all year round data, or a shorter data set, as in some previous studies, no relationship is found

Global meteorological influences on the record UK rainfall of winter 2013-14

The UK experienced record average rainfall in winter 2013–14, leading to widespread and prolonged flooding. The immediate cause of this exceptional rainfall was a very strong and persistent cyclonic atmospheric circulation over the North East Atlantic Ocean. This was related to a very strong North Atlantic jet stream which resulted in numerous damaging wind storms. These exceptional meteorological conditions have led to renewed questions about whether anthropogenic climate change is noticeably influencing extreme weather. The regional weather pattern responsible for the extreme UK winter coincided with highly anomalous conditions across the globe. We assess the contributions from various possible remote forcing regions using sets of ocean–atmosphere model relaxation experiments, where winds and temperatures are constrained to be similar to those observed in winter 2013–14 within specified atmospheric domains. We find that influences from the tropics were likely to have played a significant role in the development of the unusual extra-tropical circulation, including a role for the tropical Atlantic sector. Additionally, a stronger and more stable stratospheric polar vortex, likely associated with a strong westerly phase of the stratospheric Quasi-Biennial Oscillation (QBO), appears to have contributed to the extreme conditions. While intrinsic climatic variability clearly has the largest effect on the generation of extremes, results from an analysis which segregates circulation-related and residual rainfall variability suggest that emerging climate change signals made a secondary contribution to extreme rainfall in winter 2013–14

Modelling the Madden Julian Oscillation

The MJO has long been an aspect of the global climate that has provided a tough test for the climate modelling community. Since the 1980s there have been numerous studies of the simulation of the MJO in atmospheric general circulation models (GCMs), ranging from Hayashi and Golder (1986, 1988) and Lau and Lau (1986), through to more recent studies such as Wang and Schlesinger (1999) and Wu et al. (2002). Of course, attempts to reproduce the MJO in climate models have proceeded in parallel with developments in our understanding of what the MJO is and what drives it. In fact, many advances in understanding the MJO have come through modeling studies. In particular, failure of climate models to simulate various aspects of the MJO has prompted investigations into the mechanisms that are important to its initiation and maintenance, leading to improvements both in our understanding of, and ability to simulate, the MJO. The initial focus of this chapter will be on modeling the MJO during northern winter, when it is characterized as a predominantly eastward propagating mode and is most readily seen in observations. Aspects of the simulation of the MJO will be discussed in the context of its sensitivity to the formulation of the atmospheric model, and the increasing evidence that it may be a coupled ocean-atmosphere phenomenon. Later, we will discuss the challenges regarding the simulation of boreal summer intraseasonal variability, which is more complex since it is a combination of the eastward propagating MJO and the northward propagation of the tropical convergence zone. Finally some concluding remarks on future directions in modeling the MJO and its relationship with other timescales of variability in the tropics will be made

Ambitious partnership needed for reliable climate prediction.

Current global climate models struggle to represent precipitation and related extreme events, with serious implications for the physical evidence base to support climate actions. A leap to kilometre-scale models could overcome this shortcoming but requires collaboration on an unprecedented scale

The role of the basic state in the ENSO-monsoon relationship and implications for predictability

The impact of systematic model errors on a coupled simulation of the Asian Summer monsoon and its interannual variability is studied. Although the mean monsoon climate is reasonably well captured, systematic errors in the equatorial Pacific mean that the monsoon-ENSO teleconnection is rather poorly represented in the GCM. A system of ocean-surface heat flux adjustments is implemented in the tropical Pacific and Indian Oceans in order to reduce the systematic biases. In this version of the GCM, the monsoon-ENSO teleconnection is better simulated, particularly the lag-lead relationships in which weak monsoons precede the peak of El Nino. In part this is related to changes in the characteristics of El Nino, which has a more realistic evolution in its developing phase. A stronger ENSO amplitude in the new model version also feeds back to further strengthen the teleconnection. These results have important implications for the use of coupled models for seasonal prediction of systems such as the monsoon, and suggest that some form of flux correction may have significant benefits where model systematic error compromises important teleconnections and modes of interannual variability

The role of tropical-extratropical interaction and synoptic variability in maintaining the South Pacific Convergence Zone in CMIP5 models

The South Pacific Convergence Zone (SPCZ) is simulated as too zonal a feature in current generation climate models, including those in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). This zonal bias induces errors in tropical convective heating, with subsequent effects on global circulation. The SPCZ structure, particularly in the subtropics, is governed by the tropical-extratropical interaction between transient synoptic systems and the mean background state. However, the fidelity of synoptic-scale interactions as simulated by CMIP5 models has not yet been evaluated. In this study, analysis of synoptic variability in the simulated subtropical SPCZ reveals that the basic mechanism of tropical-extratropical interaction is generally well simulated, with storms approaching the SPCZ along comparable trajectories to observations. However, there is a broad spread in mean precipitation and its variability across the CMIP5 ensemble. Inter-model spread appears to relate to a biased background state in which the synoptic waves propagate. In particular, the region of mean negative zonal stretching deformation or "storm graveyard" in the upper troposphere?a feature previously determined to play a key role in SPCZ-storm interactions?is typically displaced in CMIP5 models to the northeast of its position in reanalysis data, albeit with individual model graveyards displaying a pronounced (25 degree) longitudinal spread. From these findings, we suggest that SPCZs simulated by CMIP5 models are not simply too zonal; rather, in models the subtropical SPCZ manifests a diagonal tilt similar to observations while SST biases force an overly zonal tropical SPCZ, resulting in a more disjointed SPCZ than observed