Magnitude of climate variability during middle Pliocene warmth: a palaeoclimate modelling study

The nature and magnitude of climatic variability during the period of middle Pliocene warmth (ca 3.29–2.97 Ma) is poorly understood. We present a suite of palaeoclimate modelling experiments incorporating an advanced atmospheric general circulation model (GCM), coupled to a Q-flux ocean model for 3.29, 3.12 and 2.97 Ma BP. Astronomical solutions for the periods in question were derived from the Berger and Loutre BL2 astronomical solution. Boundary conditions, excluding sea surface temperatures (SSTs) which were predicted by the slab-ocean model, were provided from the USGS PRISM2 2°×2° digital data set. The model results indicate that little annual variation (0.5°C) in SSTs, relative to a ‘control’ experiment, occurred during the middle Pliocene in response to the altered orbital configurations. Annual surface air temperatures also displayed little variation. Seasonally, surface air temperatures displayed a trend of cooler temperatures during December, January and February, and warmer temperatures during June, July and August. This pattern is consistent with altered seasonality resulting from the prescribed orbital configurations. Precipitation changes follow the seasonal trend observed for surface air temperature. Compared to present-day, surface wind strength and wind stress over the North Atlantic, North Pacific and Southern Ocean remained greater in each of the Pliocene experiments. This suggests that wind-driven gyral circulation may have been consistently greater during the middle Pliocene. The trend of climatic variability predicted by the GCM for the middle Pliocene accords with geological data. However, it is unclear if the model correctly simulates the magnitude of the variation. This uncertainty is derived from, (a) the relative insensitivity of the GCM to perturbation in the imposed boundary conditions, (b) a lack of detailed time series data concerning changes to terrestrial ice cover and greenhouse gas concentrations for the middle Pliocene and (c) difficulties in representing the effects of ‘climatic history’ in snap-shot GCM experiments.

Evidence for long-term regional changes in precipitation on the East Coast Mountains in Mauritius

Global climate change and its impacts are being increasingly studied and precipitation trends are one of the measures of quantifying climate change especially in the tropics. This study uses daily rainfall data to determine if there are changes in the long-term trends in rainfall variability in the East Coast Mountains of Mauritius during the last few decades, and to investigate the factors influencing the trends in the inter-annual to inter-decadal rainfall variability. Statistical modelling has been used to investigate the trends in total seasonal rainfall, the number of rain days and the mean amount of rain per rainy days and the local, regional and large-scale factors that affect them on inter-annual to inter-decadal time scales. The strongest inter-decadal trend was found in the number of rain days for both rainfall seasons, and the other variables were found to have weak or insignificant trends. Both local factors, such as the surrounding sea surface temperatures and large-scale phenomena such as Indian Monsoon and the El Niño Southern Oscillation were found to influence rainfall patterns.

In-street wind direction variability in the vicinity of a busy intersection in central London

We present results from fast-response wind measurements within and above a busy intersection between two street canyons (Marylebone Road and Gloucester Place) in Westminster, London taken as part of the DAPPLE (Dispersion of Air Pollution and Penetration into the Local Environment; www.dapple.org.uk) 2007 field campaign. The data reported here were collected using ultrasonic anemometers on the roof-top of a building adjacent to the intersection and at two heights on a pair of lamp-posts on opposite sides of the intersection. Site characteristics, data analysis and the variation of intersection flow with the above-roof wind direction (θref) are discussed. Evidence of both flow channelling and recirculation was identified within the canyon, only a few metres from the intersection for along-street and across-street roof-top winds respectively. Results also indicate that for oblique rooftop flows, the intersection flow is a complex combination of bifurcated channelled flows, recirculation and corner vortices. Asymmetries in local building geometry around the intersection and small changes in the background wind direction (changes in 15-min mean θref of 5–10 degrees) were also observed to have profound influences on the behaviour of intersection flow patterns. Consequently, short time-scale variability in the background flow direction can lead to highly scattered in-street mean flow angles masking the true multi-modal features of the flow and thus further complicating modelling challenges.

Air flow influences on local climate: observed and simulated mean relationships for the United Kingdom

Synoptic-scale air flow variability over the United Kingdom is measured on a daily time scale by following previous work to define 3 indices: geostrophic flow strength, vorticity and direction. Comparing the observed distribution of air flow index values with those determined from a simulation with the Hadley Centre’s global climate model (HadCM2) identifies some minor systematic biases in the model’s synoptic circulation but demonstrates that the major features are well simulated. The relationship between temperature and precipitation from parts of the United Kingdom and these air flow indices (either singly or in pairs) is found to be very similar in both the observations and model output; indeed the simulated and observed precipitation relationships are found to be almost interchangeable in a quantitative sense. These encouraging results imply that some reliability can be assumed for single grid-box and regional output from this climate model; this applies only to those grid boxes evaluated here (which do not have high or complex orography), only to the portion of variability that is controlled by synoptic air flow variations, and only to those surface variables considered here (temperature and precipitation).

On the drivers of inter-annual and decadal rainfall variability in Queensland, Australia

Queensland experiences considerable inter-annual and decadal rainfall variability, which impacts water-resource management, agriculture and infrastructure. To understand the mechanisms by which large-scale atmospheric and coupled air–sea processes drive these variations, empirical orthogonal teleconnection (EOT) analysis is applied to 1900–2010 seasonal Queensland rainfall. Fields from observations and the 20th Century Reanalysis are regressed onto the EOT timeseries to associate the EOTs with large-scale drivers. In winter, spring and summer the leading, state-wide EOTs are highly correlated with the El Nino–Southern Oscillation (ENSO); the Inter-decadal Pacific Oscillation modulates the summer ENSO teleconnection. In autumn, the leading EOT is associated with locally driven, late-season monsoon variations, while ENSO affects only tropical northern Queensland. Examining EOTs beyond the first, southeastern Queensland and the Cape York peninsula emerge as regions of coherent rainfall variability. In the southeast, rainfall anomalies respond to the strength and moisture content of onshore easterlies, controlled by Tasman Sea blocking. The summer EOT associated with onshore flow and blocking has been negative since 1970, consistent with the observed decline in rainfall along the heavily populated coast. The southeastern Queensland EOTs show considerable multi-decadal variability, which is independent of large-scale drivers. Summer rainfall in Cape York is associated with tropical-cyclone activity.

Strategies: Revolution in climate prediction is both necessary and possible: A declaration at the World Modelling Summit for Climate Prediction

The impending threat of global climate change and its regional manifestations is among the most important and urgent problems facing humanity. Society needs accurate and reliable estimates of changes in the probability of regional weather variations to develop science-based adaptation and mitigation strategies. Recent advances in weather prediction and in our understanding and ability to model the climate system suggest that it is both necessary and possible to revolutionize climate prediction to meet these societal needs. However, the scientific workforce and the computational capability required to bring about such a revolution is not available in any single nation. Motivated by the success of internationally funded infrastructure in other areas of science, this paper argues that, because of the complexity of the climate system, and because the regional manifestations of climate change are mainly through changes in the statistics of regional weather variations, the scientific and computational requirements to predict its behavior reliably are so enormous that the nations of the world should create a small number of multinational high-performance computing facilities dedicated to the grand challenges of developing the capabilities to predict climate variability and change on both global and regional scales over the coming decades. Such facilities will play a key role in the development of next-generation climate models, build global capacity in climate research, nurture a highly trained workforce, and engage the global user community, policy-makers, and stakeholders. We recommend the creation of a small number of multinational facilities with computer capability at each facility of about 20 peta-flops in the near term, about 200 petaflops within five years, and 1 exaflop by the end of the next decade. Each facility should have sufficient scientific workforce to develop and maintain the software and data analysis infrastructure. Such facilities will enable questions of what resolution, both horizontal and vertical, in atmospheric and ocean models, is necessary for more confident predictions at the regional and local level. Current limitations in computing power have placed severe limitations on such an investigation, which is now badly needed. These facilities will also provide the world's scientists with the computational laboratories for fundamental research on weather–climate interactions using 1-km resolution models and on atmospheric, terrestrial, cryospheric, and oceanic processes at even finer scales. Each facility should have enabling infrastructure including hardware, software, and data analysis support, and scientific capacity to interact with the national centers and other visitors. This will accelerate our understanding of how the climate system works and how to model it. It will ultimately enable the climate community to provide society with climate predictions, which are based on our best knowledge of science and the most advanced technology.

Assessment of inter-examiner agreement and variability in the manual classification of auditory brainstem response

Abstract Background: The analysis of the Auditory Brainstem Response (ABR) is of fundamental importance to the investigation of the auditory system behaviour, though its interpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analysing the ABR, clinicians are often interested in the identification of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave latency) is a practical tool for the diagnosis of disorders affecting the auditory system. Significant differences in inter-examiner results may lead to completely distinct clinical interpretations of the state of the auditory system. In this context, the aim of this research was to evaluate the inter-examiner agreement and variability in the manual classification of ABR. Methods: A total of 160 ABR data samples were collected, for four different stimulus intensity (80dBHL, 60dBHL, 40dBHL and 20dBHL), from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). Four examiners with expertise in the manual classification of ABR components participated in the study. The Bland-Altman statistical method was employed for the assessment of inter-examiner agreement and variability. The mean, standard deviation and error for the bias, which is the difference between examiners’ annotations, were estimated for each pair of examiners. Scatter plots and histograms were employed for data visualization and analysis. Results: In most comparisons the differences between examiner’s annotations were below 0.1 ms, which is clinically acceptable. In four cases, it was found a large error and standard deviation (>0.1 ms) that indicate the presence of outliers and thus, discrepancies between examiners. Conclusions: Our results quantify the inter-examiner agreement and variability of the manual analysis of ABR data, and they also allows for the determination of different patterns of manual ABR analysis.

Global to city scale urban anthropogenic heat flux: model and variability

The large scale urban consumption of energy (LUCY) model simulates all components of anthropogenic heat flux (QF) from the global to individual city scale at 2.5 × 2.5 arc-minute resolution. This includes a database of different working patterns and public holidays, vehicle use and energy consumption in each country. The databases can be edited to include specific diurnal and seasonal vehicle and energy consumption patterns, local holidays and flows of people within a city. If better information about individual cities is available within this (open-source) database, then the accuracy of this model can only improve, to provide the community data from global-scale climate modelling or the individual city scale in the future. The results show that QF varied widely through the year, through the day, between countries and urban areas. An assessment of the heat emissions estimated revealed that they are reasonably close to those produced by a global model and a number of small-scale city models, so results from LUCY can be used with a degree of confidence. From LUCY, the global mean urban QF has a diurnal range of 0.7–3.6 W m−2, and is greater on weekdays than weekends. The heat release from building is the largest contributor (89–96%), to heat emissions globally. Differences between months are greatest in the middle of the day (up to 1 W m−2 at 1 pm). December to February, the coldest months in the Northern Hemisphere, have the highest heat emissions. July and August are at the higher end. The least QF is emitted in May. The highest individual grid cell heat fluxes in urban areas were located in New York (577), Paris (261.5), Tokyo (178), San Francisco (173.6), Vancouver (119) and London (106.7). Copyright © 2010 Royal Meteorological Society

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

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.

An assessment of the impact of local processes on dust lifting in martian climate models

Simulation of the lifting of dust from the planetary surface is of substantially greater importance on Mars than on Earth, due to the fundamental role that atmospheric dust plays in the former’s climate, yet the dust emission parameterisations used to date in martian global climate models (MGCMs) lag, understandably, behind their terrestrial counterparts in terms of sophistication. Recent developments in estimating surface roughness length over all martian terrains and in modelling atmospheric circulations at regional to local scales (less than O(100 km)) presents an opportunity to formulate an improved wind stress lifting parameterisation. We have upgraded the conventional scheme by including the spatially varying roughness length in the lifting parameterisation in a fully consistent manner (thereby correcting a possible underestimation of the true threshold level for wind stress lifting), and used a modification to account for deviations from neutral stability in the surface layer. Following these improvements, it is found that wind speeds at typical MGCM resolution never reach the lifting threshold at most gridpoints: winds fall particularly short in the southern midlatitudes, where mean roughness is large. Sub-grid scale variability, manifested in both the near-surface wind field and the surface roughness, is then considered, and is found to be a crucial means of bridging the gap between model winds and thresholds. Both forms of small-scale variability contribute to the formation of dust emission ‘hotspots’: areas within the model gridbox with particularly favourable conditions for lifting, namely a smooth surface combined with strong near-surface gusts. Such small-scale emission could in fact be particularly influential on Mars, due both to the intense positive radiative feedbacks that can drive storm growth and a strong hysteresis effect on saltation. By modelling this variability, dust lifting is predicted at the locations at which dust storms are frequently observed, including the flushing storm sources of Chryse and Utopia, and southern midlatitude areas from which larger storms tend to initiate, such as Hellas and Solis Planum. The seasonal cycle of emission, which includes a double-peaked structure in northern autumn and winter, also appears realistic. Significant increases to lifting rates are produced for any sensible choices of parameters controlling the sub-grid distributions used, but results are sensitive to the smallest scale of variability considered, which high-resolution modelling suggests should be O(1 km) or less. Use of such models in future will permit the use of a diagnosed (rather than prescribed) variable gustiness intensity, which should further enhance dust lifting in the southern hemisphere in particular.

Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation–climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America – 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

Use of fused airborne scanning laser altimetry and digital map data for urban flood modelling

Flood modelling of urban areas is still at an early stage, partly because until recently topographic data of sufficiently high resolution and accuracy have been lacking in urban areas. However, Digital Surface Models (DSMs) generated from airborne scanning laser altimetry (LiDAR) having sub-metre spatial resolution have now become available, and these are able to represent the complexities of urban topography. The paper describes the development of a LiDAR post-processor for urban flood modelling based on the fusion of LiDAR and digital map data. The map data are used in conjunction with LiDAR data to identify different object types in urban areas, though pattern recognition techniques are also employed. Post-processing produces a Digital Terrain Model (DTM) for use as model bathymetry, and also a friction parameter map for use in estimating spatially-distributed friction coefficients. In vegetated areas, friction is estimated from LiDAR-derived vegetation height, and (unlike most vegetation removal software) the method copes with short vegetation less than ~1m high, which may occupy a substantial fraction of even an urban floodplain. The DTM and friction parameter map may also be used to help to generate an unstructured mesh of a vegetated urban floodplain for use by a 2D finite element model. The mesh is decomposed to reflect floodplain features having different frictional properties to their surroundings, including urban features such as buildings and roads as well as taller vegetation features such as trees and hedges. This allows a more accurate estimation of local friction. The method produces a substantial node density due to the small dimensions of many urban features.