Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UKMeteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern Africa.

Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 floods in Tewkesbury, UK

Two-dimensional flood inundation modelling is a widely used tool to aid flood risk management. In urban areas, the model spatial resolution required to represent flows through a typical street network often results in an impractical computational cost at the city scale. This paper presents the calibration and evaluation of a recently developed formulation of the LISFLOOD-FP model, which is more computationally efficient at these resolutions. Aerial photography was available for model evaluation on 3 days from the 24 to the 31 of July. The new formulation was benchmarked against the original version of the model at 20 and 40 m resolutions, demonstrating equally accurate simulation, given the evaluation data but at a 67 times faster computation time. The July event was then simulated at the 2 m resolution of the available airborne LiDAR DEM. This resulted in more accurate simulation of the floodplain drying dynamics compared with the coarse resolution models, although maximum inundation levels were simulated equally well at all resolutions tested.

A comparison of extra-tropical cyclones in recent re-analyses; ERA-Interim, NASA MERRA, NCEP CFSR and JRA-25

Extra-tropical cyclones are identified and compared using data from four recent re-analyses for the winter periods in both hemispheres. Results show the largest differences occur between the older lower resolution JRA25 re-analysis when compared with the newer high resolution re-analyses, in particular in the Southern Hemisphere (SH). Spatial differences between the newest re-analyses are small in both hemispheres and generally not significant except some common regions associated with cyclogenesis close to orography. Intensities are generally related to spatial resolution except NASA-MERRA which has larger intensities for several different measures. Matching storms between re-analyses shows the number matched between ERA-Interim and the other re-analyses are similar in the Northern Hemisphere (NH). In the SH the number matched between JRA25 and ERA-Interim is lower than in the NH, but for NASA-MERRA and NCEP-CFSR the number matched is similar to the NH. The mean separation of the identically same cyclones is typically less than 20 geodesic in both hemispheres for the latest re-analyses, whereas JRA25 compared with the other re-analyses has a broader distribution in the SH indicating greater uncertainty. The instantaneous intensity differences for matched storms shows narrow distributions for pressure while for winds and vorticity the distributions are much broader indicating larger uncertainty typical of smaller scale fields. Composite cyclone diagnostics show that cyclones are very similar between the re-analyses, with differences being related to the intensities, consistent with the intensity results. Overall, results show NH cyclones correspond well between re-analyses, with a significant improvement in the SH for the latest re-analyses, indicating a convergence between re-analyses for cyclone properties.

Changes in water vapor transports of the ascending branch of the tropical circulation

Recent studies have found contradicting results on whether tropical atmospheric circulation (TAC) has intensified or weakened in recent decades. We here re-investigate recent changes in TAC derived from moisture transports into the tropics using high temporal and spatial resolution reanalyses from ERA-interim. We found a significant strengthening of both, the lower level inward transports and the mid level outward transports over the recent two decades. However the signal in the total budget is weak, because strengthening of the in and outflow neutralize each other, at least to some extent. We found atmospheric humidity to be relatively stable, so suggest that the intensification is mainly caused by an intensification of the wind related circulation strength. The exact quantitative values were found to heavily depend on whether the calculations are based on mean or instantaneous values. We highlight the importance for using the instantaneous ones for transport calculations, as they represent the coincidence of high wind speeds and high atmospheric humidity.

Multi-satellite observed responses of precipitation and its extremes to interannual climate variability

The consistency of precipitation variability estimated from the multiple satellite-based observing systems is assessed. There is generally good agreement between TRMM TMI, SSM/I, GPCP and AMSRE datasets for the inter-annual variability of precipitation since 1997 but the HOAPS dataset appears to overestimate the magnitude of variability. Over the tropical ocean the TRMM 3B42 dataset produces unrealistic variabilitys. Based upon deseasonalised GPCP data for the period 1998-2008, the sensitivity of global mean precipitation (P) to surface temperature (T) changes (dP/dT) is about 6%/K, although a smaller sensitivity of 3.6%/K is found using monthly GPCP data over the longer period 1989-2008. Over the tropical oceans dP/dT ranges from 10-30%/K depending upon time-period and dataset while over tropical land dP/dT is -8 to -11%/K for the 1998-2008 period. Analyzing the response of the tropical ocean precipitation intensity distribution to changes in T we find the wetter area P shows a strong positive response to T of around 20%/K. The response over the drier tropical regimes is less coherent and varies with datasets, but responses over the tropical land show significant negative relationships over an interannual time-scale. The spatial and temporal resolutions of the datasets strongly influence the precipitation responses over the tropical oceans and help explain some of the discrepancy between different datasets. Consistency between datasets is found to increase on averaging from daily to 5-day time-scales and considering a 1o (or coarser) spatial resolution. Defining the wet and dry tropical ocean regime by the 60th percentile of P intensity, the 5-day average, 1o TMI data exhibits a coherent drying of the dry regime at the rate of -20%/K and the wet regime becomes wetter at a similar rate with warming.

Validation of the FALL3D ash dispersion model using observations of the 2010 Eyjafjallajökull volcanic ash clouds

During April-May 2010 volcanic ash clouds from the Icelandic Eyjafjallajökull volcano reached Europe causing an unprecedented disruption of the EUR/NAT region airspace. Civil aviation authorities banned all flight operations because of the threat posed by volcanic ash to modern turbine aircraft. New quantitative airborne ash mass concentration thresholds, still under discussion, were adopted for discerning regions contaminated by ash. This has implications for ash dispersal models routinely used to forecast the evolution of ash clouds. In this new context, quantitative model validation and assessment of the accuracies of current state-of-the-art models is of paramount importance. The passage of volcanic ash clouds over central Europe, a territory hosting a dense network of meteorological and air quality observatories, generated a quantity of observations unusual for volcanic clouds. From the ground, the cloud was observed by aerosol lidars, lidar ceilometers, sun photometers, other remote-sensing instru- ments and in-situ collectors. From the air, sondes and multiple aircraft measurements also took extremely valuable in-situ and remote-sensing measurements. These measurements constitute an excellent database for model validation. Here we validate the FALL3D ash dispersal model by comparing model results with ground and airplane-based measurements obtained during the initial 14e23 April 2010 Eyjafjallajökull explosive phase. We run the model at high spatial resolution using as input hourly- averaged observed heights of the eruption column and the total grain size distribution reconstructed from field observations. Model results are then compared against remote ground-based and in-situ aircraft-based measurements, including lidar ceilometers from the German Meteorological Service, aerosol lidars and sun photometers from EARLINET and AERONET networks, and flight missions of the German DLR Falcon aircraft. We find good quantitative agreement, with an error similar to the spread in the observations (however depending on the method used to estimate mass eruption rate) for both airborne and ground mass concentration. Such verification results help us understand and constrain the accuracy and reliability of ash transport models and it is of enormous relevance for designing future operational mitigation strategies at Volcanic Ash Advisory Centers.

Multimodel estimate of the global terrestrial water balance: setup and first results

Six land surface models and five global hydrological models participate in a model intercomparison project (WaterMIP), which for the first time compares simulation results of these different classes of models in a consistent way. In this paper the simulation setup is described and aspects of the multi-model global terrestrial water balance are presented. All models were run at 0.5 degree spatial resolution for the global land areas for a 15-year period (1985-1999) using a newly-developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm year-1 (60,000 to 85,000 km3 year-1) and simulated runoff ranges from 290 to 457 mm year-1 (42,000 to 66,000 km3 year-1). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically-based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degree-day approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between model are major sources of uncertainty. Climate change impact studies thus need to use not only multiple climate models, but also some other measure of uncertainty, (e.g. multiple impact models).

Morphometric analysis of aeolian bedforms in the Namib Sand Sea using ASTER data

The ASTER Global Digital Elevation Model (GDEM) has made elevation data at 30 m spatial resolution freely available, enabling reinvestigation of morphometric relationships derived from limited field data using much larger sample sizes. These data are used to analyse a range of morphometric relationships derived for dunes (between dune height, spacing, and equivalent sand thickness) in the Namib Sand Sea, which was chosen because there are a number of extant studies that could be used for comparison with the results. The relative accuracy of GDEM for capturing dune height and shape was tested against multiple individual ASTER DEM scenes and against field surveys, highlighting the smoothing of the dune crest and resultant underestimation of dune height, and the omission of the smallest dunes, because of the 30 m sampling of ASTER DEM products. It is demonstrated that morphometric relationships derived from GDEM data are broadly comparable with relationships derived by previous methods, across a range of different dune types. The data confirm patterns of dune height, spacing and equivalent sand thickness mapped previously in the Namib Sand Sea, but add new detail to these patterns.

Diagnosing eclipse-induced wind changes

Responses in surface winds to solar eclipses have an almost mystical status but are difficult to detect in observations because of their transient nature. High spatial resolution (approx. 1.5 km grid) meteorological models now provide a new technique for their investigation. Measurements from the southern UK meteorological network during the 11 August 1999 total solar eclipse are compared with a high-resolution model ignorant of the lunar shadow’s influence. Differences between the model output and measurements at the eclipse time show transient eclipse zone temperature decreases of up to 3 degrees C, which also depressed the day’s maximum temperature compared with the model prediction. Coherent responses in temperature, and wind speed and direction measurements are detected in the inland cloud-free region (from 51 to 52 degrees N and −2 to 0 degrees E). A mean regional wind speed decrease of 0.7 m s−1 during the maximum eclipse hour is apparent with a mean anticlockwise wind direction change of 17 degrees; no such changes occurred in the model output. Such regional circulation changes are consistent with Clayton’s 1901 cold-cored eclipse cyclone hypothesis, which may be related to the anecdotal ‘eclipse wind’.

European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset

Vegetation distribution and state have been measured since 1981 by the AVHRR (Advanced Very High Resolution Radiometer) instrument through satellite remote sensing. In this study a correction method is applied to the Pathfinder NDVI (Normalized Difference Vegetation Index) data to create a continuous European vegetation phenology dataset of a 10-day temporal and 0.1° spatial resolution; additionally, land surface parameters for use in biosphere–atmosphere modelling are derived. The analysis of time-series from this dataset reveals, for the years 1982–2001, strong seasonal and interannual variability in European land surface vegetation state. Phenological metrics indicate a late and short growing season for the years 1985–1987, in addition to early and prolonged activity in the years 1989, 1990, 1994 and 1995. These variations are in close agreement with findings from phenological measurements at the surface; spring phenology is also shown to correlate particularly well with anomalies in winter temperature and winter North Atlantic Oscillation (NAO) index. Nevertheless, phenological metrics, which display considerable regional differences, could only be determined for vegetation with a seasonal behaviour. Trends in the phenological phases reveal a general shift to earlier (−0.54 days year−1) and prolonged (0.96 days year−1) growing periods which are statistically significant, especially for central Europe.

A comparison of models for estimating the riverine export of nitrogen from large watersheds

We evaluated the accuracy of six watershed models of nitrogen export in streams (kg km2 yr−1) developed for use in large watersheds and representing various empirical and quasi-empirical approaches described in the literature. These models differ in their methods of calibration and have varying levels of spatial resolution and process complexity, which potentially affect the accuracy (bias and precision) of the model predictions of nitrogen export and source contributions to export. Using stream monitoring data and detailed estimates of the natural and cultural sources of nitrogen for 16 watersheds in the northeastern United States (drainage sizes = 475 to 70,000 km2), we assessed the accuracy of the model predictions of total nitrogen and nitrate-nitrogen export. The model validation included the use of an error modeling technique to identify biases caused by model deficiencies in quantifying nitrogen sources and biogeochemical processes affecting the transport of nitrogen in watersheds. Most models predicted stream nitrogen export to within 50% of the measured export in a majority of the watersheds. Prediction errors were negatively correlated with cultivated land area, indicating that the watershed models tended to over predict export in less agricultural and more forested watersheds and under predict in more agricultural basins. The magnitude of these biases differed appreciably among the models. Those models having more detailed descriptions of nitrogen sources, land and water attenuation of nitrogen, and water flow paths were found to have considerably lower bias and higher precision in their predictions of nitrogen export.

Connecting mean field models of neural activity to EEG and fMRI data

Progress in functional neuroimaging of the brain increasingly relies on the integration of data from complementary imaging modalities in order to improve spatiotemporal resolution and interpretability. However, the usefulness of merely statistical combinations is limited, since neural signal sources differ between modalities and are related non-trivially. We demonstrate here that a mean field model of brain activity can simultaneously predict EEG and fMRI BOLD with proper signal generation and expression. Simulations are shown using a realistic head model based on structural MRI, which includes both dense short-range background connectivity and long-range specific connectivity between brain regions. The distribution of modeled neural masses is comparable to the spatial resolution of fMRI BOLD, and the temporal resolution of the modeled dynamics, importantly including activity conduction, matches the fastest known EEG phenomena. The creation of a cortical mean field model with anatomically sound geometry, extensive connectivity, and proper signal expression is an important first step towards the model-based integration of multimodal neuroimages.

Numerical simulations of intense tropical storms

A high resolution general circulation model has been used to study intense tropical storms. A five-year-long global integration with a spatial resolution of 125 km has been analysed. The geographical and seasonal distribution of tropical storms agrees remarkably well with observations. The structure of individual storms also agrees with observations, but the storms are generally more extensive in coverage and less extreme than the observed ones. A few additional calculations have also been done by a very high resolution limited-area version of the same model, where the boundary conditions successively have been interpolated from the global model. These results are very realistic in many details of the structure of the storms including simulated rain-bands and an eye structure. The global model has also been used in another five-year integration to study the influence of greenhouse warming. The sea surface temperatures have been taken from a transient climate change experiment carried out with a low resolution coupled ocean-atmosphere model. The result is a significant reduction in the number of hurricanes, particularly in the Southern Hemisphere. Main reasons for this can be found in changes in the largescale circulation, i.e. a weakening of the Hadley circulation, and a more intense warming of the upper tropical troposphere. A similar effect can be seen during warm ENSO events, where fewer North Atlantic hurricanes have been reported.

Realistic mean field forward predictions for the integration of co-registered EEG/fMRI

Brain activity can be measured non-invasively with functional imaging techniques. Each pixel in such an image represents a neural mass of about 105 to 107 neurons. Mean field models (MFMs) approximate their activity by averaging out neural variability while retaining salient underlying features, like neurotransmitter kinetics. However, MFMs incorporating the regional variability, realistic geometry and connectivity of cortex have so far appeared intractable. This lack of biological realism has led to a focus on gross temporal features of the EEG. We address these impediments and showcase a "proof of principle" forward prediction of co-registered EEG/fMRI for a full-size human cortex in a realistic head model with anatomical connectivity, see figure 1. MFMs usually assume homogeneous neural masses, isotropic long-range connectivity and simplistic signal expression to allow rapid computation with partial differential equations. But these approximations are insufficient in particular for the high spatial resolution obtained with fMRI, since different cortical areas vary in their architectonic and dynamical properties, have complex connectivity, and can contribute non-trivially to the measured signal. Our code instead supports the local variation of model parameters and freely chosen connectivity for many thousand triangulation nodes spanning a cortical surface extracted from structural MRI. This allows the introduction of realistic anatomical and physiological parameters for cortical areas and their connectivity, including both intra- and inter-area connections. Proper cortical folding and conduction through a realistic head model is then added to obtain accurate signal expression for a comparison to experimental data. To showcase the synergy of these computational developments, we predict simultaneously EEG and fMRI BOLD responses by adding an established model for neurovascular coupling and convolving "Balloon-Windkessel" hemodynamics. We also incorporate regional connectivity extracted from the CoCoMac database [1]. Importantly, these extensions can be easily adapted according to future insights and data. Furthermore, while our own simulation is based on one specific MFM [2], the computational framework is general and can be applied to models favored by the user. Finally, we provide a brief outlook on improving the integration of multi-modal imaging data through iterative fits of a single underlying MFM in this realistic simulation framework.

Sensitivities of a cyclone detection and tracking algorithm: individual tracks and climatology

Northern Hemisphere cyclone activity is assessed by applying an algorithm for the detection and tracking of synoptic scale cyclones to mean sea level pressure data. The method, originally developed for the Southern Hemisphere, is adapted for application in the Northern Hemisphere winter season. NCEP-Reanalysis data from 1958/59 to 1997/98 are used as input. The sensitivities of the results to particular parameters of the algorithm are discussed for both case studies and from a climatological point of view. Results show that the choice of settings is of major relevance especially for the tracking of smaller scale and fast moving systems. With an appropriate setting the algorithm is capable of automatically tracking different types of cyclones at the same time: Both fast moving and developing systems over the large ocean basins and smaller scale cyclones over the Mediterranean basin can be assessed. The climatology of cyclone variables, e.g., cyclone track density, cyclone counts, intensification rates, propagation speeds and areas of cyclogenesis and -lysis gives detailed information on typical cyclone life cycles for different regions. The lowering of the spatial and temporal resolution of the input data from full resolution T62/06h to T42/12h decreases the cyclone track density and cyclone counts. Reducing the temporal resolution alone contributes to a decline in the number of fast moving systems, which is relevant for the cyclone track density. Lowering spatial resolution alone mainly reduces the number of weak cyclones.