The solsticial pause on Mars: 1. A planetary wave reanalysis

Large-scale planetary waves are diagnosed from an analysis of profiles retrieved from the Thermal Emission Spectrometer aboard the Mars Global Surveyor spacecraft during its scientific mapping phase. The analysis is conducted by assimilating thermal profiles and total dust opacity retrievals into a Mars global circulation model. Transient waves are largest throughout the northern hemisphere autumn, winter and spring period and almost absent during the summer. The southern hemisphere exhibits generally weaker transient wave behaviour. A striking feature of the low-altitude transient waves in the analysis is that they show a broad subsidiary minimum in amplitude centred on the winter solstice, a period when the thermal contrast between the summer hemisphere and the winter pole is strongest and baroclinic wave activity might be expected to be strong. This behaviour, here called the ‘solsticial pause,’ is present in every year of the analysis. This strong pause is under-represented in many independent model experiments, which tend to produce relatively uniform baroclinic wave activity throughout the winter. This paper documents and diagnoses the transient wave solsticial pause found in the analysis; a companion paper investigates the origin of the phenomenon in a series of model experiments.

Irreducible uncertainty in near-term climate projections

Model simulations of the next few decades are widely used in assessments of climate change impacts and as guidance for adaptation. Their non-linear nature reveals a level of irreducible uncertainty which it is important to understand and quantify, especially for projections of near-term regional climate. Here we use large idealised initial condition ensembles of the FAMOUS global climate model with a 1 %/year compound increase in CO2 levels to quantify the range of future temperatures in model-based projections. These simulations explore the role of both atmospheric and oceanic initial conditions and are the largest such ensembles to date. Short-term simulated trends in global temperature are diverse, and cooling periods are more likely to be followed by larger warming rates. The spatial pattern of near-term temperature change varies considerably, but the proportion of the surface showing a warming is more consistent. In addition, ensemble spread in inter-annual temperature declines as the climate warms, especially in the North Atlantic. Over Europe, atmospheric initial condition uncertainty can, for certain ocean initial conditions, lead to 20 year trends in winter and summer in which every location can exhibit either strong cooling or rapid warming. However, the details of the distribution are highly sensitive to the ocean initial condition chosen and particularly the state of the Atlantic meridional overturning circulation. On longer timescales, the warming signal becomes more clear and consistent amongst different initial condition ensembles. An ensemble using a range of different oceanic initial conditions produces a larger spread in temperature trends than ensembles using a single ocean initial condition for all lead times. This highlights the potential benefits from initialising climate predictions from ocean states informed by observations. These results suggest that climate projections need to be performed with many more ensemble members than at present, using a range of ocean initial conditions, if the uncertainty in near-term regional climate is to be adequately quantified.

Selective environmental stress caused by magmatic sulfur emissions from continental flood basalt eruptions

Several biotic crises during the past 300 million years have been linked to episodes of continental flood basalt volcanism, and in particular to the release of massive quantities of magmatic sulphur gas species. Flood basalt provinces were typically formed by numerous individual eruptions, each lasting years to decades. However, the environmental impact of these eruptions may have been limited by the occurrence of quiescent periods that lasted hundreds to thousands of years. Here we use a global aerosol model to quantify the sulphur-induced environmental effects of individual, decade-long flood basalt eruptions representative of the Columbia River Basalt Group, 16.5–14.5 million years ago, and the Deccan Traps, 65 million years ago. For a decade-long eruption of Deccan scale, we calculate a decadal-mean reduction in global surface temperature of 4.5 K, which would recover within 50 years after an eruption ceased unless climate feedbacks were very different in deep-time climates. Acid mists and fogs could have caused immediate damage to vegetation in some regions, but acid-sensitive land and marine ecosystems were well-buffered against volcanic sulphur deposition effects even during century-long eruptions. We conclude that magmatic sulphur from flood basalt eruptions would have caused a biotic crisis only if eruption frequencies and lava discharge rates had been high and sustained for several centuries at a time.

The biogeophysical climatic impacts of anthropogenic land use change during the Holocene

The first agricultural societies were established around 10 ka BP and had spread across much of Europe and southern Asia by 5.5 ka BP with resultant anthropogenic deforestation for crop and pasture land. Various studies (e.g. Joos et al., 2004; Kaplan et al., 2011; Mitchell et al., 2013) have attempted to assess the biogeochemical implications for Holocene climate in terms of increased carbon dioxide and methane emissions. However, less work has been done to examine the biogeophysical impacts of this early land use change. In this study, global climate model simulations with Hadley Centre Coupled Model version 3 (HadCM3) were used to examine the biogeophysical effects of Holocene land cover change on climate, both globally and regionally, from the early Holocene (8 ka BP) to the early industrial era (1850 CE). Two experiments were performed with alternative descriptions of past vegetation: (i) one in which potential natural vegetation was simulated by Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) but without land use changes and (ii) one where the anthropogenic land use model Kaplan and Krumhardt 2010 (KK10; Kaplan et al., 2009, 2011) was used to set the HadCM3 crop regions. Snapshot simulations were run at 1000-year intervals to examine when the first signature of anthropogenic climate change can be detected both regionally, in the areas of land use change, and globally. Results from our model simulations indicate that in regions of early land disturbance such as Europe and south-east Asia detectable temperature changes, outside the normal range of variability, are encountered in the model as early as 7 ka BP in the June–July–August (JJA) season and throughout the entire annual cycle by 2–3 ka BP. Areas outside the regions of land disturbance are also affected, with virtually the whole globe experiencing significant temperature changes (predominantly cooling) by the early industrial period. The global annual mean temperature anomalies found in our single model simulations were −0.22 at 1850 CE, −0.11 at 2 ka BP, and −0.03 °C at 7 ka BP. Regionally, the largest temperature changes were in Europe with anomalies of −0.83 at 1850 CE, −0.58 at 2 ka BP, and −0.24 °C at 7 ka BP. Large-scale precipitation features such as the Indian monsoon, the Intertropical Convergence Zone (ITCZ), and the North Atlantic storm track are also impacted by local land use and remote teleconnections. We investigated how advection by surface winds, mean sea level pressure (MSLP) anomalies, and tropospheric stationary wave train disturbances in the mid- to high latitudes led to remote teleconnections.

Understanding the rapid summer warming and changes in temperature extremes since the mid-1990s over Western Europe

Analysis of observations indicates that there was a rapid increase in summer (June-August, JJA) mean surface air temperature (SAT) since the mid-1990s over Western Europe. Accompanying this rapid warming are significant increases in summer mean daily maximum temperature, daily minimum temperature, annual hottest day temperature and warmest night temperature, and an increase in frequency of summer days and tropical nights, while the change in the diurnal temperature range (DTR) is small. This study focuses on understanding causes of the rapid summer warming and associated temperature extreme changes. A set of experiments using the atmospheric component of the state-of-the-art HadGEM3 global climate model have been carried out to quantify relative roles of changes in sea surface temperature (SST)/sea ice extent (SIE), anthropogenic greenhouse gases (GHGs), and anthropogenic aerosols (AAer). Results indicate that the model forced by changes in all forcings reproduces many of the observed changes since the mid-1990s over Western Europe. Changes in SST/SIE explain 62.2% ± 13.0% of the area averaged seasonal mean warming signal over Western Europe, with the remaining 37.8% ± 13.6% of the warming explained by the direct impact of changes in GHGs and AAer. Results further indicate that the direct impact of the reduction of AAer precursor emissions over Europe, mainly through aerosol-radiation interaction with additional contributions from aerosol-cloud interaction and coupled atmosphere-land surface feedbacks, is a key factor for increases in annual hottest day temperature and in frequency of summer days. It explains 45.5% ± 17.6% and 40.9% ± 18.4% of area averaged signals for these temperature extremes. The direct impact of the reduction of AAer precursor emissions over Europe acts to increase DTR locally, but the change in DTR is countered by the direct impact of GHGs forcing. In the next few decades, greenhouse gas concentrations will continue to rise and AAer precursor emissions over Europe and North America will continue to decline. Our results suggest that the changes in summer seasonal mean SAT and temperature extremes over Western Europe since the mid-1990s are most likely to be sustained or amplified in the near term, unless other factors intervene.

A high-order arbitrarily unstructured finite-volume model of the global atmosphere: tests solving the shallow-water equations

Simulations of the global atmosphere for weather and climate forecasting require fast and accurate solutions and so operational models use high-order finite differences on regular structured grids. This precludes the use of local refinement; techniques allowing local refinement are either expensive (eg. high-order finite element techniques) or have reduced accuracy at changes in resolution (eg. unstructured finite-volume with linear differencing). We present solutions of the shallow-water equations for westerly flow over a mid-latitude mountain from a finite-volume model written using OpenFOAM. A second/third-order accurate differencing scheme is applied on arbitrarily unstructured meshes made up of various shapes and refinement patterns. The results are as accurate as equivalent resolution spectral methods. Using lower order differencing reduces accuracy at a refinement pattern which allows errors from refinement of the mountain to accumulate and reduces the global accuracy over a 15 day simulation. We have therefore introduced a scheme which fits a 2D cubic polynomial approximately on a stencil around each cell. Using this scheme means that refinement of the mountain improves the accuracy after a 15 day simulation. This is a more severe test of local mesh refinement for global simulations than has been presented but a realistic test if these techniques are to be used operationally. These efficient, high-order schemes may make it possible for local mesh refinement to be used by weather and climate forecast models.

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.

Assimilation of stratospheric ozone from MIPAS into a global general-circulation model: The September 2002 vortex split

Ozone and temperature profiles from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) have been assimilated, using three-dimensional variational assimilation, into a stratosphere troposphere version of the Met Office numerical weather-prediction system. Analyses are made for the month of September 2002, when there was an unprecedented split in the southern hemisphere polar vortex. The analyses are validated against independent ozone observations from sondes, limb-occultation and total column ozone satellite instruments. Through most of the stratosphere, precision varies from 5 to 15%, and biases are 15% or less of the analysed field. Problems remain in the vortex and below the 60 hPa. level, especially at the tropopause where the analyses have too much ozone and poor agreement with independent data. Analysis problems are largely a result of the model rather than the data, giving confidence in the MIPAS ozone retrievals, though there may be a small high bias in MIPAS ozone in the lower stratosphere. Model issues include an excessive Brewer-Dobson circulation, which results both from known problems with the tracer transport scheme and from the data assimilation of dynamical variables. The extreme conditions of the vortex split reveal large differences between existing linear ozone photochemistry schemes. Despite these issues, the ozone analyses are able to successfully describe the ozone hole split and compare well to other studies of this event. Recommendations are made for the further development of the ozone assimilation system.

Global climate and ocean circulation on an aquaplanet ocean-atmosphere general circulation model

A low resolution coupled ocean-atmosphere general circulation model OAGCM is used to study the characteristics of the large scale ocean circulation and its climatic impacts in a series of global coupled aquaplanet experiments. Three configurations, designed to produce fundamentally different ocean circulation regimes, are considered. The first has no obstruction to zonal flow, the second contains a low barrier that blocks zonal flow in the ocean at all latitudes, creating a single enclosed basin, whilst the third contains a gap in the barrier to allow circumglobal flow at high southern latitudes. Warm greenhouse climates with a global average air surface temperature of around 27C result in all cases. Equator to pole temperature gradients are shallower than that of a current climate simulation. Whilst changes in the land configuration cause regional changes in temperature, winds and rainfall, heat transports within the system are little affected. Inhibition of all ocean transport on the aquaplanet leads to a reduction in global mean surface temperature of 8C, along with a sharpening of the meridional temperature gradient. This results from a reduction in global atmospheric water vapour content and an increase in tropical albedo, both of which act to reduce global surface temperatures. Fitting a simple radiative model to the atmospheric characteristics of the OAGCM solutions suggests that a simpler atmosphere model, with radiative parameters chosen a priori based on the changing surface configuration, would have produced qualitatively different results. This implies that studies with reduced complexity atmospheres need to be guided by more complex OAGCM results on a case by case basis.

Performance of the OPA/ARPEGE-T21 global ocean-atmosphere coupled model

The climatology of the OPA/ARPEGE-T21 coupled general circulation model (GCM) is presented. The atmosphere GCM has a T21 spectral truncation and the ocean GCM has a 2°×1.5° average resolution. A 50-year climatic simulation is performed using the OASIS coupler, without flux correction techniques. The mean state and seasonal cycle for the last 10 years of the experiment are described and compared to the corresponding uncoupled experiments and to climatology when available. The model reasonably simulates most of the basic features of the observed climate. Energy budgets and transports in the coupled system, of importance for climate studies, are assessed and prove to be within available estimates. After an adjustment phase of a few years, the model stabilizes around a mean state where the tropics are warm and resemble a permanent ENSO, the Southern Ocean warms and almost no sea-ice is left in the Southern Hemisphere. The atmospheric circulation becomes more zonal and symmetric with respect to the equator. Once those systematic errors are established, the model shows little secular drift, the small remaining trends being mainly associated to horizontal physics in the ocean GCM. The stability of the model is shown to be related to qualities already present in the uncoupled GCMs used, namely a balanced radiation budget at the top-of-the-atmosphere and a tight ocean thermocline.

Prediction of global and local model quality in CASP8 using the ModFOLD server

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0-an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/.

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.