ALBERT

Description: The purpose of this paper is to provide a method for perturbing Weather Generators (WGs) for future decades and to assess its effectiveness. Here the procedure is applied to the WG implemented within the UKCP09 package and assessed using data from a Regional Climate Model (RCM) simulation which provides a significant "climate change" between a control run period and a distant future. The WG is normally calibrated on observed data. For this study, data from an RCM control period (1961–1990) was used, then perturbed using the procedure. Because only monthly differences between the RCM control and scenario periods are used to perturb the WG, the direct daily RCM scenario may be considered as unseen data to assess how well the perturbation procedure reproduces the direct RCM simulations for the future.

Description: Two recently-available daily gridded datasets are used to investigate trends in Mediterranean temperature extremes since the mid-20th century. The underlying trends are found to be generally consistent with global trends of temperature and their extremes: cold extremes decrease and warm/hot extremes increase. This consistency is better manifested in the western part of the Mediterranean where changes are most pronounced since the mid-1970s. In the eastern part, a cooling is observed, with a near reversal in the last two decades. This inter-basin discrepancy is clearer in winter, while in summer changes are more uniform and the west-east difference is restricted to the rate of increase of warm/hot extremes, which is higher in central and eastern parts of the Mediterranean over recent decades. Linear regression and correlation analysis reveals some influence of major large-scale atmospheric circulation patterns on the occurrence of these extremes – both in terms of trend and interannual variability. These relationships are not, however, able to account for the most striking features of the observations – in particular the intensification of the increasing trend in warm/hot extremes, which is most evident over the last 15–20 yr in the Central and Eastern Mediterranean.

Description: Education in hydrology is changing rapidly due to diversification of students, emergent major scientific and practical challenges that our discipline must engage with, shifting pedagogic ideas and higher education environments, the need for students to develop new discipline specific and transferrable skills, and the advent of innovative technologies for learning and teaching. This paper focuses on new technologies in the context of learning and teaching in Physical Geography and reflects on the implications of our experiences for education in hydrology. We evaluate the experience of designing and trialling novel mobile technology-based field exercises and a virtual field tour for a Year 1 undergraduate Physical Geography module at a UK university. The new exercises are based on using and obtaining spatial data, operation of meteorological equipment (explained using an interactive DVD), and include introductions to global positioning systems (GPS) and geographical information systems (GIS). The technology and exercises were well received in a pilot study and subsequent rolling-out to the full student cohort (∼150 students). A statistically significant improvement in marks was observed following the redesign. Although the students enjoyed using mobile technology, the increased interactivity and opportunity for peer learning were considered to be the primary benefits by students. This is reinforced further by student preference for the new interactive virtual field tour over the previous "show-and-tell" field exercise. Despite the new exercises having many advantages, exercise development was not trivial due to the high start-up costs, the need for provision of sufficient technical support and the relative difficulty of making year-to-year changes (to the virtual field tour in particular). Our experiences are highly relevant to the implementation of novel learning and teaching technologies in hydrology education.

Description: Climate data for studies within the SWURVE (Sustainable Water: Uncertainty, Risk and Vulnerability in Europe) project, assessing the risk posed by future climatic change to various hydrological and hydraulic systems were obtained from the regional climate model HadRM3H, developed at the Hadley Centre of the UK Met Office. This paper gives some background to HadRM3H; it also presents anomaly maps of the projected future changes in European temperature, rainfall and potential evapotranspiration (PET, estimated using a variant of the Penman formula). The future simulations of temperature and rainfall, following the SRES A2 emissions scenario, suggest that most of Europe will experience warming in all seasons, with heavier precipitation in winter in much of western Europe (except for central and northern parts of the Scandinavian mountains) and drier summers in most parts of western and central Europe (except for the north-west and the eastern part of the Baltic Sea). Particularly large temperature anomalies (〉6°C) are projected for north-east Europe in winter and for southern Europe, Asia Minor and parts of Russia in summer. The projected PET displayed very large increases in summer for a region extending from southern France to Russia. The unrealistically large values could be the result of an enhanced hydrological cycle in HadRM3H, affecting several of the input parameters to the PET calculation. To avoid problems with hydrological modelling schemes, PET was re-calculated, using empirical relationships derived from observational values of temperature and PET.

Description: To aid assessments of the impact of climate change on water related activities in the case study regions (CSRs) of the EC-funded project SWURVE, estimates of uncertainty in climate model data need to be developed. This paper compares two methods for estimating uncertainty in annual surface temperature and precipitation for the period 2070–2099. Both combine probability distribution functions for global temperature increase and for scaling variables (i.e. the change in regional temperature/precipitation per degree of global annual average temperature change) to produce a probability distribution for regional temperature and precipitation. The methods differ in terms of the distribution used for the respective probability distribution function. For scaling variables, the first method assumes a uniform distribution, whilst the second method assumes a normal distribution. For the probability distribution function of global annual average temperature change, the first method uses a uniform distribution and the second uses a log-normal approximation to a distribution derived from Wigley and Raper, 2001. Although the methods give somewhat different ranges of change, they agree on how temperature and precipitation in each of the CSRs are likely to change relative to each other. For annual surface temperature, both methods predict increases in all CSRs, although somewhat less so for NW England (5th and 95th percentiles vary between 1.1–1.9°C to 3.8–5.7°C) and about 1.7–3.1°C to 5.3–8.6°C for the others. For precipitation, most probability distributions (except for NW England) show predominantly decreasing precipitation, particularly so for the Iberian CSR (5th and 95th percentiles vary from –29.3 to –44% to –9.6 to –4%).

Description: Education in hydrology is changing rapidly due to diversification of students, emergent major scientific and practical challenges that our discipline must engage with, shifting pedagogic ideas and higher education environments, the need for students to develop new discipline specific and transferrable skills, and the advent of innovative technologies for learning and teaching. This paper focuses on new technologies in the context of learning and teaching in Physical Geography and reflects on the implications of our experiences for education in hydrology. We evaluate the experience of designing and trialling novel mobile technology-based field exercises and a virtual field trip for a Year 1 undergraduate Physical Geography module at a UK university. The new exercises are based on using and obtaining spatial data, operation of meteorological equipment (explained using an interactive DVD), and include introductions to global positioning systems (GPS) and geographical information systems (GIS). The technology and exercises were well received in a pilot study and subsequent rolling-out to the full student cohort (∼150 students). A statistically significant improvement in marks was observed following the redesign. Although the students enjoyed using mobile technology, the increased interactivity and opportunity for peer learning were considered to be the primary benefits by students. This is reinforced further by student preference for the new interactive virtual field trip over the previous "show-and-tell" field exercise. Despite the new exercises having many advantages, exercise development was not trivial due to the high start-up costs, the need for provision of sufficient technical support and the relative difficulty of making year-to-year changes (to the virtual field trip in particular). We believe our experiences are directly relevant to the implementation of such novel learning and teaching technologies in hydrology education.

Description: The CRUTEM4 (Climatic Research Unit Temperature version 4) land-surface air temperature dataset is one of the most widely used records of the climate system. Here we provide an important additional dissemination route for this dataset: online access to monthly, seasonal and annual data values and timeseries graphs via Google Earth. This is achieved via an interface written in Keyhole Markup Language (KML) and also provides access to the underlying weather station data used to construct the CRUTEM4 dataset. A mathematical description of the construction of the CRUTEM4 dataset (and its predecessor versions) is also provided, together with an archive of some previous versions and a recommendation for identifying the precise version of the dataset used in a particular study. The CRUTEM4 dataset used here is available from doi:10.5285/EECBA94F-62F9-4B7C-88D3-482F2C93C468.

Description: The CRUTEM4 (Climatic Research Unit Temperature, version 4) land-surface air temperature data set is one of the most widely used records of the climate system. Here we provide an important additional dissemination route for this data set: online access to monthly, seasonal and annual data values and time series graphs via Google Earth. This is achieved via an interface written in Keyhole Markup Language (KML) and also provides access to the underlying weather station data used to construct the CRUTEM4 data set. A mathematical description of the construction of the CRUTEM4 data set (and its predecessor versions) is also provided, together with an archive of some previous versions and a recommendation for identifying the precise version of the data set used in a particular study. The CRUTEM4 data set used here is available from doi:10.5285/EECBA94F-62F9-4B7C-88D3-482F2C93C468.

Description: HadISDH is a near-global land surface specific humidity monitoring product providing monthly means from 1973 onwards over large-scale grids. Presented herein to 2012, annual updates are anticipated. HadISDH is an update to the land component of HadCRUH, utilising the global high-resolution land surface station product HadISD as a basis. HadISD, in turn, uses an updated version of NOAA's Integrated Surface Database. Intensive automated quality control has been undertaken at the individual observation level, as part of HadISD processing. The data have been subsequently run through the pairwise homogenisation algorithm developed for NCDC's US Historical Climatology Network monthly temperature product. For the first time, uncertainty estimates are provided at the grid-box spatial scale and monthly timescale. HadISDH is in good agreement with existing land surface humidity products in periods of overlap, and with both land air and sea surface temperature estimates. Widespread moistening is shown over the 1973–2012 period. The largest moistening signals are over the tropics with drying over the subtropics, supporting other evidence of an intensified hydrological cycle over recent years. Moistening is detectable with high (95%) confidence over large-scale averages for the globe, Northern Hemisphere and tropics, with trends of 0.089 (0.080 to 0.098) g kg−1 per decade, 0.086 (0.075 to 0.097) g kg−1 per decade and 0.133 (0.119 to 0.148) g kg−1 per decade, respectively. These changes are outside the uncertainty range for the large-scale average which is dominated by the spatial coverage component; station and grid-box sampling uncertainty is essentially negligible on large scales. A very small moistening (0.013 (−0.005 to 0.031) g kg−1 per decade) is found in the Southern Hemisphere, but it is not significantly different from zero and uncertainty is large. When globally averaged, 1998 is the moistest year since monitoring began in 1973, closely followed by 2010, two strong El Niño years. The period in between is relatively flat, concurring with previous findings of decreasing relative humidity over land.

Description: Measurements of wind strength and direction abstracted from European ships' logbooks during the recently finished CLIWOC project have been used to produce the first gridded Sea Level Pressure (SLP) reconstruction for the 1750–1850 period over the North Atlantic based solely on marine data. The reconstruction is based on a spatial regression analysis calibrated by using data taken from the ICOADS database. An objective methodology has been developed to select the optimal calibration period and spatial domain of the reconstruction by testing several thousands of possible models. The finally selected area, limited by the performance of the regression equations and by the availability of data, covers the region between 28° N and 52° N close to the European coast and between 28° N and 44° N in the open Ocean. The results provide a direct measure of the strength and extension of the Azores High during the 101 years of the study period. The comparison with the recent land-based SLP reconstruction by Luterbacher et al. (2002) indicates the presence of a common signal. The interannual variability of the CLIWOC reconstructions is rather high due to the current scarcity of abstracted wind data in the areas with best response in the regression. Guidelines are proposed to optimize the efficiency of future abstraction work.