Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model

A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

North Atlantic Oscillation response to transient greenhouse gas forcing and the impact on European winter climate: a CMIP2 multi-model assessment

This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO2) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO2, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5-10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970-1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO2 concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061 +/- 0.0036 hPa per %CO2. Although an increase of 0.61 hPa in NAO for a doubling in CO2 represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models' inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.

Quasi-biennial oscillation and tracer distributions in a coupled chemistry-climate model

[ 1] We have used a fully coupled chemistry-climate model (CCM), which generates its own wind and temperature quasi-biennial oscillation (QBO), to study the effect of coupling on the QBO and to examine the QBO signals in stratospheric trace gases, particularly ozone. Radiative coupling of the interactive chemistry to the underlying general circulation model tends to prolong the QBO period and to increase the QBO amplitude in the equatorial zonal wind in the lower and middle stratosphere. The model ozone QBO agrees well with Stratospheric Aerosol and Gas Experiment II and Total Ozone Mapping Spectrometer satellite observations in terms of vertical and latitudinal structure. The model captures the ozone QBO phase change near 28 km over the equator and the column phase change near +/- 15 degrees latitude. Diagnosis of the model chemical terms shows that variations in NOx are the main chemical driver of the O-3 QBO around 35 km, i.e., above the O-3 phase change.

Recent trends in sea level pressure in the Indian Ocean region

During the second half of the twentieth century the Indian Ocean exhibited a rapid rise in sea surface temperatures (SST). It has been argued - largely on the basis of experiments with atmospheric GCMs - that this rapid warming was an important cause of remote changes in climate, in particular an increasing trend in the North Atlantic Oscillation Index and decreases in African rainfall. Here however we present evidence that the Indian Ocean warming was associated with local increases in sea level pressure (SLP). These increases are inconsistent with results from experiments in which an atmospheric GCM is forced by historical SST, which show robust decreases in SLP. The clear discrepancy between the observed and simulated trends in SLP suggests that the response of some atmospheric GCMs to the Indian Ocean warming may not provide a reliable guide to the behaviour of the real world.

Arctic oscillation or North Atlantic oscillation?

The definition and interpretation of the Arctic oscillation (AO) are examined and compared with those of the North Atlantic oscillation (NAO). It is shown that the NAO reflects the correlations between the surface pressure variability at its centers of action, whereas this is not the case for the AO. The NAO pattern can be identified in a physically consistent way in principal component analysis applied to various fields in the Euro-Atlantic region. A similar identification is found in the Pacific region for the Pacific–North American (PNA) pattern, but no such identification is found here for the AO. The AO does reflect the tendency for the zonal winds at 35° and 55°N to anticorrelate in both the Atlantic and Pacific regions associated with the NAO and PNA. Because climatological features in the two ocean basins are at different latitudes, the zonally symmetric nature of the AO does not mean that it represents a simple modulation of the circumpolar flow. An increase in the AO or NAO implies strong, separated tropospheric jets in the Atlantic but a weakened Pacific jet. The PNA has strong related variability in the Pacific jet exit, but elsewhere the zonal wind is similar to that related to the NAO. The NAO-related zonal winds link strongly through to the stratosphere in the Atlantic sector. The PNA-related winds do so in the Pacific, but to a lesser extent. The results suggest that the NAO paradigm may be more physically relevant and robust for Northern Hemisphere variability than is the AO paradigm. However, this does not disqualify many of the physical mechanisms associated with annular modes for explaining the existence of the NAO.

Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model

A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

A pressure-jump time-resolved x-ray diffraction study of cubic-cubic transition kinetics in monoolein

In the past two decades, the geometric pathways involved in the transformations between inverse bicontinuous cubic phases in amphiphilic systems have been extensively theoretically modeled. However, little experimental data exists on the cubic-cubic transformation in pure lipid systems. We have used pressure-jump time-resolved X-ray diffraction to investigate the transition between the gyroid Q(II)(G) and double-diamond Q(II)(D) phases in mixtures of 1-monoolein in 30 wt% water. We find for this system that the cubic-cubic transition occurs without any detectable intermediate structures. In addition, we have determined the kinetics of the transition, in both the forward and reverse directions, as a function of pressure-jump amplitude, temperature, and water content. A recently developed model allows (at least in principle) the calculation of the activation energy for lipid phase transitions from such data. The analysis is applicable only if kinetic reproducibility is achieved, at least within one sample, and achievement of such kinetic reproducibility is shown here, by carrying out prolonged pressure-cycling. The rate of transformation shows clear and consistent trends with pressure-jump amplitude, temperature, and water content, all of which are shown to be in agreement with the effect of the shift in the position of the cubic-cubic phase boundary following a change in the thermodynamic parameters.

Pressure-jump X-ray studies of liquid crystal transitions in lipids

In this paper, we give an overview of our studies by static and time-resolved X-ray diffraction of inverse cubic phases and phase transitions in lipids. In 1, we briefly discuss the lyotropic phase behaviour of lipids, focusing attention on non-lamellar structures, and their geometric/topological relationship to fusion processes in lipid membranes. Possible pathways for transitions between different cubic phases are also outlined. In 2, we discuss the effects of hydrostatic pressure on lipid membranes and lipid phase transitions, and describe how the parameters required to predict the pressure dependence of lipid phase transition temperatures can be conveniently measured. We review some earlier results of inverse bicontinuous cubic phases from our laboratory, showing effects such as pressure-induced formation and swelling. In 3, we describe the technique of pressure-jump synchrotron X-ray diffraction. We present results that have been obtained from the lipid system 1:2 dilauroylphosphatidylcholine/lauric acid for cubic-inverse hexagonal, cubic-cubic and lamellar-cubic transitions. The rate of transition was found to increase with the amplitude of the pressure-jump and with increasing temperature. Evidence for intermediate structures occurring transiently during the transitions was also obtained. In 4, we describe an IDL-based 'AXCESS' software package being developed in our laboratory to permit batch processing and analysis of the large X-ray datasets produced by pressure-jump synchrotron experiments. In 5, we present some recent results on the fluid lamellar-Pn3m cubic phase transition of the single-chain lipid 1-monoelaidin, which we have studied both by pressure-jump and temperature-jump X-ray diffraction. Finally, in 6, we give a few indicators of future directions of this research. We anticipate that the most useful technical advance will be the development of pressure-jump apparatus on the microsecond time-scale, which will involve the use of a stack of piezoelectric pressure actuators. The pressure-jump technique is not restricted to lipid phase transitions, but can be used to study a wide range of soft matter transitions, ranging from protein unfolding and DNA unwinding and transitions, to phase transitions in thermotropic liquid crystals, surfactants and block copolymers.

The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.

Past and recent changes in the North Atlantic oscillation

The North Atlantic oscillation (NAO) is under current climate conditions the leading mode of atmospheric circulation variability over the North Atlantic region. While the pattern is present during the entire year, it is most important during winter, explaining a large part of the variability of the large-scale pressure field, being thus largely determinant for the weather conditions over the North Atlantic basin and over Western Europe. In this study, a review of recent literature on the basic understanding of the NAO, its variability on different time scales and driving physical mechanisms is presented. In particular, the observed NAO variations and long-term trends are put into a long term perspective by considering paleo-proxy evidence. A representative number of recently released NAO reconstructions are discussed. While the reconstructions agree reasonably well with observations during the instrumental overlapping period, there is a rather high uncertainty between the different reconstructions for the pre-instrumental period, which leads to partially incoherent results, that is, periods where the NAO reconstructions do not agree even in sign. Finally, we highlight the future need of a broader definition of the NAO, the assessment of the stability of the teleconnection centers over time, the analysis of the relations to other relevant variables like temperature and precipitation, as well as on the relevant processes involved

The role of air–sea coupling in the simulation of the Madden–Julian oscillation in the Hadley Centre model

The role of air–sea coupling in the simulation of the Madden–Julian oscillation (MJO) is explored using two configurations of the Hadley Centre atmospheric model (AGCM), GA3.0, which differ only in F, a parameter controlling convective entrainment and detrainment. Increasing F considerably improves deficient MJO-like variability in the Indian and Pacific Oceans, but variability in and propagation through the Maritime Continent remains weak. By coupling GA3.0 in the tropical Indo-Pacific to a boundary-layer ocean model, KPP, and employing climatological temperature corrections, well resolved air–sea interactions are simulated with limited alterations to the mean state. At default F, when GA3.0 has a poor MJO, coupling produces a stronger MJO with some eastward propagation, although both aspects remain deficient. These results agree with previous sensitivity studies using AGCMs with poor variability. At higher F, coupling does not affect MJO amplitude but enhances propagation through the Maritime Continent, resulting in an MJO that resembles observations. A sensitivity experiment with coupling in only the Indian Ocean reverses these improvements, suggesting coupling in the Maritime Continent and West Pacific is critical for propagation. We hypothesise that for AGCMs with a poor MJO, coupling provides a “crutch” to artificially augment MJO-like activity through high-frequency SST anomalies. In related experiments, we employ the KPP framework to analyse the impact of air–sea interactions in the fully coupled GA3.0, which at default F shows a similar MJO to uncoupled GA3.0. This is due to compensating effects: an improvement from coupling and a degradation from mean-state errors. Future studies on the role of coupling should carefully separate these effects.

Propagation of the Madden-Julian Oscillation through the Maritime Continent and scale interaction with the diurnal cycle of precipitation

The convectively active part of the Madden-Julian Oscillation (MJO) propagates eastward through the warm pool, from the Indian Ocean through the Maritime Continent (the Indonesian archipelago) to the western Pacific. The Maritime Continent's complex topography means the exact nature of the MJO propagation through this region is unclear. Model simulations of the MJO are often poor over the region, leading to local errors in latent heat release and global errors in medium-range weather prediction and climate simulation. Using 14 northern winters of TRMM satellite data it is shown that, where the mean diurnal cycle of precipitation is strong, 80% of the MJO precipitation signal in the Maritime Continent is accounted for by changes in the amplitude of the diurnal cycle. Additionally, the relationship between outgoing long-wave radiation (OLR) and precipitation is weakened here, such that OLR is no longer a reliable proxy for precipitation. The canonical view of the MJO as the smooth eastward propagation of a large-scale precipitation envelope also breaks down over the islands of the Maritime Continent. Instead, a vanguard of precipitation (anomalies of 2.5 mm day^-1 over 10^6 km^2) jumps ahead of the main body by approximately 6 days or 2000 km. Hence, there can be enhanced precipitation over Sumatra, Borneo or New Guinea when the large-scale MJO envelope over the surrounding ocean is one of suppressed precipitation. This behaviour can be accommodated into existing MJO theories. Frictional and topographic moisture convergence and relatively clear skies ahead of the main convective envelope combine with the low thermal inertia of the islands, to allow a rapid response in the diurnal cycle which rectifies onto the lower-frequency MJO. Hence, accurate representations of the diurnal cycle and its scale interaction appear to be necessary for models to simulate the MJO successfully.

The Madden-Julian Oscillation and the diurnal cycle over the Maritime Continent: scale interactions and modelling

The Maritime Continent archipelago, situated on the equator at 95-165E, has the strongest land-based precipitation on Earth. The latent heat release associated with the rainfall affects the atmospheric circulation throughout the tropics and into the extra-tropics. The greatest source of variability in precipitation is the diurnal cycle. The archipelago is within the convective region of the Madden-Julian Oscillation (MJO), which provides the greatest variability on intra-seasonal time scales: large-scale (∼10^7 km^2) active and suppressed convective envelopes propagate slowly (∼5 m s^-1) eastwards between the Indian and Pacific Oceans. High-resolution satellite data show that a strong diurnal cycle is triggered to the east of the advancing MJO envelope, leading the active MJO by one-eighth of an MJO cycle (∼6 days). Where the diurnal cycle is strong its modulation accounts for 81% of the variability in MJO precipitation. Over land this determines the structure of the diagnosed MJO. This is consistent with the equatorial wave dynamics in existing theories of MJO propagation. The MJO also affects the speed of gravity waves propagating offshore from the Maritime Continent islands. This is largely consistent with changes in static stability during the MJO cycle. The MJO and its interaction with the diurnal cycle are investigated in HiGEM, a high-resolution coupled model. Unlike many models, HiGEM represents the MJO well with eastward-propagating variability on intra-seasonal time scales at the correct zonal wavenumber, although the inter-tropical convergence zone's precipitation peaks strongly at the wrong time, interrupting the MJO's spatial structure. However, the modelled diurnal cycle is too weak and its phase is too early over land. The modulation of the diurnal amplitude by the MJO is also too weak and accounts for only 51% of the variability in MJO precipitation. Implications for forecasting and possible causes of the model errors are discussed, and further modelling studies are proposed.

Vertical structure and physical processes of the Madden-Julian oscillation: Linking hindcast fidelity to simulated diabatic heating and moistening

Many theories for the Madden-Julian oscillation (MJO) focus on diabatic processes, particularly the evolution of vertical heating and moistening. Poor MJO performance in weather and climate models is often blamed on biases in these processes and their interactions with the large-scale circulation. We introduce one of three components of a model-evaluation project, which aims to connect MJO fidelity in models to their representations of several physical processes, focusing on diabatic heating and moistening. This component consists of 20-day hindcasts, initialised daily during two MJO events in winter 2009-10. The 13 models exhibit a range of skill: several have accurate forecasts to 20 days' lead, while others perform similarly to statistical models (8-11 days). Models that maintain the observed MJO amplitude accurately predict propagation, but not vice versa. We find no link between hindcast fidelity and the precipitation-moisture relationship, in contrast to other recent studies. There is also no relationship between models' performance and the evolution of their diabatic-heating profiles with rain rate. A more robust association emerges between models' fidelity and net moistening: the highest-skill models show a clear transition from low-level moistening for light rainfall to mid-level moistening at moderate rainfall and upper-level moistening for heavy rainfall. The mid-level moistening, arising from both dynamics and physics, may be most important. Accurately representing many processes may be necessary, but not sufficient for capturing the MJO, which suggests that models fail to predict the MJO for a broad range of reasons and limits the possibility of finding a panacea.

Vertical structure and physical processes of the Madden-Julian oscillation: synthesis and summary

The "Vertical structure and physical processes of the Madden-Julian oscillation (MJO)" project comprises three experiments, designed to evaluate comprehensively the heating, moistening and momentum associated with tropical convection in general circulation models (GCMs). We consider here only those GCMs that performed all experiments. Some models display relatively higher or lower MJO fidelity in both initialized hindcasts and climate simulations, while others show considerable variations in fidelity between experiments. Fidelity in hindcasts and climate simulations are not meaningfully correlated. The analysis of each experiment led to the development of process-oriented diagnostics, some of which distinguished between GCMs with higher or lower fidelity in that experiment. We select the most discriminating diagnostics and apply them to data from all experiments, where possible, to determine if correlations with MJO fidelity hold across scales and GCM states. While normalized gross moist stability had a small but statistically significant correlation with MJO fidelity in climate simulations, we find no link with fidelity in medium-range hindcasts. Similarly, there is no association between timestep-to-timestep rainfall variability, identified from short hindcasts, and fidelity in medium-range hindcasts or climate simulations. Two metrics that relate precipitation to free-tropospheric moisture--the relative humidity for extreme daily precipitation, and variations in the height and amplitude of moistening with rain rate--successfully distinguish between higher- and lower-fidelity GCMs in hindcasts and climate simulations. To improve the MJO, developers should focus on relationships between convection and both total moisture and its rate of change. We conclude by offering recommendations for further experiments.