Identification and ranking of extraordinary rainfall events over northwest Italy: the role of Atlantic moisture

An objective identification and ranking of extraordinary rainfall events for Northwest Italy is established using time series of annual precipitation maxima for 1938–2002 at over 200 stations. Rainfall annual maxima are considered for five reference durations (1, 3, 6, 12, and 24 h). In a first step, a day is classified as an extraordinary rainfall day when a regional threshold calculated on the basis of a two-components extreme value distribution is exceeded for at least one of the stations. Second, a clustering procedure taking into account the different rainfall durations is applied to the identified 163 events. Third, a division into six clusters is chosen using Ward's distance criteria. It is found that two of these clusters include the seven strongest events as quantified from a newly developed measure of intensity which combines rainfall intensities and spatial extension. Two other clusters include the weakest 72% historical events. The obtained clusters are analyzed in terms of typical synoptic characteristics. The two top clusters are characterized by strong and persistent upper air troughs inducing not only moisture advection from the North Atlantic into the Western Mediterranean but also strong northward flow towards the southern Alpine ranges. Humidity transports from the North Atlantic are less important for the weaker clusters. We conclude that moisture advection from the North Atlantic plays a relevant role in the magnitude of the extraordinary events over Northwest Italy.

The central European floods of August 2002: Part 2 - Synoptic causes and considerations with respect to climatic change

In the first part of this paper (Ulbrich et al. 2003), we gave a description of the August 2002 rainfall events and the resultant floods, in particular of the flood wave of the River Elbe. The extreme precipitation sums observed in the first half of the month were primarily associated with two rainfall episodes. The first episode occurred on 6/7 August 2002. The main rainfall area was situated over Lower Austria, the south-western part of the Czech Republic and south-eastern Germany. A severe flash flood was produced in the Lower Austrian Waldviertel (`forest quarter’ ). The second episode on 11± 13 August 2002 most severely affected the Erz Mountains and western parts of the Czech Republic. During this second episode 312mm of rain was recorded between 0600GMT on 12 August and 0600GMT on 13 August at the Zinnwald weather station in the ErzMountains, which is a new 24-hour record for Germany. The flash floods resulting from this rainfall episode and the subsequent Elbe flood produced the most expensive weatherrelated catastrophe in Europe in recent decades. In this part of the paper we discuss the meteorological conditions and physical mechanisms leading to the two main events. Similarities to the conditions that led to the recent summer floods of the River Oder in 1997 and the River Vistula in 2001 will be shown. This will lead us to a consideration of trends in extreme rainfall over Europe which are found in numerical simulations of anthropogenic climate change.

The central European floods of August 2002: Part 1 - Rainfall periods and flood development

Record-breaking rainfall amounts and intensities were observed at several raingauges in central Europe during the first half of August 2002 (Fig. 1). They produced flash floods in small rivers in the Erz Mountains, the Bohemian Forest and in Lower Austria (see Fig. 2), followed by record-breaking floods of larger rivers fed from these areas. The Vltava submerged parts of the city of Prague on 13± 15 August, and subsequently the Elbe flooded parts of Dresden and further villages and towns located downstream. The gauge level of 9.40m measured at Dresden on 17 August 2002 is the highest level since 1275, exceeding the former maximum level of 8.77m recorded in 1845 (Grollmann and Simon 2002). Parts of the Danube catchment were also affected by severe flooding. There were 100 fatalities connected with the floods in central Europe, and the economic loss is estimated at 9 billion Euros for Germany (German government’s estimate), 3 billion Euros for Austria, and 2.5 billion Euros for the Czech Republic (estimates from Boyle 2002). The event thus replaced the European winter storm Lothar of December 1999 (Ulbrich et al. 2001) as the most expensive weather-related catastrophe in Europe in recent decades (see Cornford 2002). In this study, we give an overview of the exceptional rainfall experienced over wide areas on 12/13 August 2002, and the resulting floods. Further events during early August 2002, in particular the event on 6/7 August in Lower Austria, are briefly mentioned.

Using rain-use efficiency to explore livestock production trends in rangelands in the Transkei, South Africa

We qualitatively describe the condition of communally managed rangelands in the Transkei, South Africa, using GIS and high resolution near-infrared imagery. Using livestock census data from 28 magisterial districts in the Transkei, we explored the trends in livestock biomass from 1923–1998. The area had been subjected to intensive herbivory by domestic livestock during that period, and the high livestock biomass had been blamed for the perceived degradation or ‘overgrazing’ of the region. Our assessment used the concept rain-use efficiency (RUE) (kg dry matter ha–1 mm–1) to determine whether there is evidence of change in the efficiency of the system to produce domestic livestock. We calculated RUE from annual livestock numbers and the mean annual rainfall for each district. We found no evidence of a decline in rain-use efficiency between the two assessment periods (1923–1944, 1945–1998). There was evidence of a shift in the ratio of sheep to goats between 1923 and 1998, with goat numbers increasing (greater than twofold) relative to sheep in eight districts. This trend may be associated with changes in the structure of vegetation. We conclude that this region is not showing evidence of system run down that affects domestic livestock production.

Comparison of TAMSAT and CPC rainfall estimates with raingauges, for southern Africa

Two different TAMSAT (Tropical Applications of Meteorological Satellites) methods of rainfall estimation were developed for northern and southern Africa, based on Meteosat images. These two methods were used to make rainfall estimates for the southern rainy season from October 1995 to April 1996. Estimates produced by both TAMSAT methods and estimates produced by the CPC (Climate Prediction Center) method were then compared with kriged data from over 800 raingauges in southern Africa. This shows that operational TAMSAT estimates are better over plateau regions, with 59% of estimates within one standard error (s.e.) of the kriged rainfall. Over mountainous regions the CPC approach is generally better, although all methods underestimate and give only 40% of estimates within 1 s.e. The two TAMSAT methods show little difference across a whole season, but when looked at in detail the northern method gives unsatisfactory calibrations. The CPC method does have significant overall improvements by building in real-time raingauge data, but only where sufficient raingauges are available.

A comparative performance analysis of TRMM 3B42 (TMPA) versions 6 and 7 for hydrological applications over Andean-Amazon river basins

The Tropical Rainfall Measuring Mission 3B42 precipitation estimates are widely used in tropical regions for hydrometeorological research. Recently, version 7 of the product was released. Major revisions to the algorithm involve the radar refl ectivity - rainfall rates relationship, surface clutter detection over high terrain, a new reference database for the passive microwave algorithm, and a higher quality gauge analysis product for monthly bias correction. To assess the impacts of the improved algorithm, we compare the version 7 and the older version 6 product with data from 263 rain gauges in and around the northern Peruvian Andes. The region covers humid tropical rainforest, tropical mountains, and arid to humid coastal plains. We and that the version 7 product has a significantly lower bias and an improved representation of the rainfall distribution. We further evaluated the performance of versions 6 and 7 products as forcing data for hydrological modelling, by comparing the simulated and observed daily streamfl ow in 9 nested Amazon river basins. We find that the improvement in the precipitation estimation algorithm translates to an increase in the model Nash-Sutcliffe effciency, and a reduction in the percent bias between the observed and simulated flows by 30 to 95%.

Flood risk and climate change: global and regional perspectives

A holistic perspective on changing rainfall-driven flood risk is provided for the late 20th and early 21st centuries. Economic losses from floods have greatly increased, principally driven by the expanding exposure of assets at risk. It has not been possible to attribute rain-generated peak streamflow trends to anthropogenic climate change over the past several decades. Projected increases in the frequency and intensity of heavy rainfall, based on climate models, should contribute to increases in precipitation-generated local flooding (e.g. flash flooding and urban flooding). This article assesses the literature included in the IPCC SREX report and new literature published since, and includes an assessment of changes in flood risk in seven of the regions considered in the recent IPCC SREX report—Africa, Asia, Central and South America, Europe, North America, Oceania and Polar regions. Also considering newer publications, this article is consistent with the recent IPCC SREX assessment finding that the impacts of climate change on flood characteristics are highly sensitive to the detailed nature of those changes and that presently we have only low confidence1 in numerical projections of changes in flood magnitude or frequency resulting from climate change.

Extreme rainfall variability in Australia: Patterns, drivers and predictability

Leading patterns of observed monthly extreme rainfall variability in Australia are examined using an Empirical Orthogonal Teleconnection (EOT) method. Extreme rainfall variability is more closely related to mean rainfall variability during austral summer than in winter. The leading EOT patterns of extreme rainfall explain less variance in Australia-wide extreme rainfall than is the case for mean rainfall EOTs. We illustrate that, as with mean rainfall, the El Niño-Southern Oscillation (ENSO) has the strongest association with warm-season extreme rainfall variability, while in the cool-season the primary drivers are atmospheric blocking and the subtropical ridge. The Indian Ocean Dipole and Southern Annular Mode also have significant relationships with patterns of variability during austral winter and spring. Leading patterns of summer extreme rainfall variability have predictability several months ahead from Pacific sea surface temperatures (SSTs) and as much as a year in advance from Indian Ocean SSTs. Predictability from the Pacific is greater for wetter than average summer months than for months that are drier than average, whereas for the Indian Ocean the relationship has greater linearity. Several cool-season EOTs are associated with mid-latitude synoptic-scale patterns along the south and east coasts. These patterns have common atmospheric signatures denoting moist onshore flow and strong cyclonic anomalies often to the north of a blocking anti-cyclone. Tropical cyclone activity is observed to have significant relationships with some warm season EOTs. This analysis shows that extreme rainfall variability in Australia can be related to remote drivers and local synoptic-scale patterns throughout the year.

The three-dimensional morphology of simulated and observed convective storms over southern England

A set of high-resolution radar observations of convective storms has been collected to evaluate such storms in the UK Met Office Unified Model during the DYMECS project (Dynamical and Microphysical Evolution of Convective Storms). The 3-GHz Chilbolton Advanced Meteorological Radar was set up with a scan-scheduling algorithm to automatically track convective storms identified in real-time from the operational rainfall radar network. More than 1,000 storm observations gathered over fifteen days in 2011 and 2012 are used to evaluate the model under various synoptic conditions supporting convection. In terms of the detailed three-dimensional morphology, storms in the 1500-m grid-length simulations are shown to produce horizontal structures a factor 1.5–2 wider compared to radar observations. A set of nested model runs at grid lengths down to 100m show that the models converge in terms of storm width, but the storm structures in the simulations with the smallest grid lengths are too narrow and too intense compared to the radar observations. The modelled storms were surrounded by a region of drizzle without ice reflectivities above 0 dBZ aloft, which was related to the dominance of ice crystals and was improved by allowing only aggregates as an ice particle habit. Simulations with graupel outperformed the standard configuration for heavy-rain profiles, but the storm structures were a factor 2 too wide and the convective cores 2 km too deep.

The impacts of European and Asian anthropogenic sulphur dioxide emissions on Sahel rainfall

In this study, the atmospheric component of a state-of-the-art climate model (HadGEM2-ES) has been used to investigate the impacts of regional anthropogenic sulphur dioxide emissions on boreal summer Sahel rainfall. The study focuses on the transient response of the West African monsoon (WAM) to a sudden change in regional anthropogenic sulphur dioxide emissions, including land surface feedbacks, but without sea surface temperature (SST) feedbacks. The response occurs in two distinct phases: 1) fast adjustment of the atmosphere on a time scale of days to weeks (up to 3 weeks) through aerosol-radiation and aerosol-cloud interactions with weak hydrological cycle changes and surface feedbacks. 2) adjustment of the atmosphere and land surface with significant local hydrological cycle changes and changes in atmospheric circulation (beyond 3 weeks). European emissions lead to an increase in shortwave (SW) scattering by increased sulphate burden, leading to a decrease in surface downward SW radiation which causes surface cooling over North Africa, a weakening of the Saharan heat low and WAM, and a decrease in Sahel precipitation. In contrast, Asian emissions lead to very little change in sulphate burden over North Africa, but they induce an adjustment of the Walker Circulation which leads again to a weakening of the WAM and a decrease in Sahel precipitation. The responses to European and Asian emissions during the second phase exhibit similar large scale patterns of anomalous atmospheric circulation and hydrological variables, suggesting a preferred response. The results support the idea that sulphate aerosol emissions contributed to the observed decline in Sahel precipitation in the second half of the twentieth century.

The effect of the Madden-Julian Oscillation on station rainfall and river level in the Fly River system, Papua New Guinea

The Madden-Julian oscillation (MJO) is the dominant mode of intraseasonal variability in tropical rainfall on the large scale, but its signal is often obscured in individual station data, where effects are most directly felt at the local level. The Fly River system, Papua New Guinea, is one of the wettest regions on Earth and is at the heart of the MJO envelope. A 16 year time series of daily precipitation at 15 stations along the river system exhibits strong MJO modulation in rainfall. At each station, the difference in rainfall rate between active and suppressed MJO conditions is typically 40% of the station mean. The spread of rainfall between individual MJO events was small enough such that the rainfall distributions between wet and dry phases of the MJO were clearly separated at the catchment level. This implies that successful prediction of the large-scale MJO envelope will have a practical use for forecasting local rainfall. In the steep topography of the New Guinea Highlands, the mean and MJO signal in station precipitation is twice that in the satellite Tropical Rainfall Measuring Mission 3B42HQ product, emphasizing the need for ground-truthing satellite-based precipitation measurements. A clear MJO signal is also present in the river level, which peaks simultaneously with MJO precipitation input in its upper reaches but lags the precipitation by approximately 18 days on the flood plains.

Seasonal intercomparison of observational rainfall datasets over India during the southwest monsoon season

The Indian monsoon is an important component of Earth's climate system, accurate forecasting of its mean rainfall being essential for regional food and water security. Accurate measurement of the rainfall is essential for various water-related applications, the evaluation of numerical models and detection and attribution of trends, but a variety of different gridded rainfall datasets are available for these purposes. In this study, six gridded rainfall datasets are compared against the India Meteorological Department (IMD) gridded rainfall dataset, chosen as the most representative of the observed system due to its high gauge density. The datasets comprise those based solely on rain gauge observations and those merging rain gauge data with satellite-derived products. Various skill scores and subjective comparisons are carried out for the Indian region during the south-west monsoon season (June to September). Relative biases and skill metrics are documented at all-India and sub-regional scales. In the gauge-based (land-only) category, Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of water resources (APHRODITE) and Global Precipitation Climatology Center (GPCC) datasets perform better relative to the others in terms of a variety of skill metrics. In the merged category, the Global Precipitation Climatology Project (GPCP) dataset is shown to perform better than the Climate Prediction Center Merged Analysis of Precipitation (CMAP) for the Indian monsoon in terms of various metrics, when compared with the IMD gridded data. Most of the datasets have difficulty in representing rainfall over orographic regions including the Western Ghats mountains, in north-east India and the Himalayan foothills. The wide range of skill scores seen among the datasets and even the change of sign of bias found in some years are causes of concern. This uncertainty between datasets is largest in north-east India. These results will help those studying the Indian monsoon region to select an appropriate dataset depending on their application and focus of research.

Investigation of discrepancies in satellite rainfall estimates over Ethiopia

Tropical Applications of Meteorology Using Satellite and Ground-Based Observations (TAMSAT) rainfall estimates are used extensively across Africa for operational rainfall monitoring and food security applications; thus, regional evaluations of TAMSAT are essential to ensure its reliability. This study assesses the performance of TAMSAT rainfall estimates, along with the African Rainfall Climatology (ARC), version 2; the Tropical Rainfall Measuring Mission (TRMM) 3B42 product; and the Climate Prediction Center morphing technique (CMORPH), against a dense rain gauge network over a mountainous region of Ethiopia. Overall, TAMSAT exhibits good skill in detecting rainy events but underestimates rainfall amount, while ARC underestimates both rainfall amount and rainy event frequency. Meanwhile, TRMM consistently performs best in detecting rainy events and capturing the mean rainfall and seasonal variability, while CMORPH tends to overdetect rainy events. Moreover, the mean difference in daily rainfall between the products and rain gauges shows increasing underestimation with increasing elevation. However, the distribution in satellite–gauge differences demon- strates that although 75% of retrievals underestimate rainfall, up to 25% overestimate rainfall over all eleva- tions. Case studies using high-resolution simulations suggest underestimation in the satellite algorithms is likely due to shallow convection with warm cloud-top temperatures in addition to beam-filling effects in microwave- based retrievals from localized convective cells. The overestimation by IR-based algorithms is attributed to nonraining cirrus with cold cloud-top temperatures. These results stress the importance of understanding re- gional precipitation systems causing uncertainties in satellite rainfall estimates with a view toward using this knowledge to improve rainfall algorithms.

Extension of the TAMSAT satellite-based rainfall monitoring over Africa and from 1983 to present

Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) rainfall monitoring products have been extended to provide spatially contiguous rainfall estimates across Africa. This has been achieved through a new, climatology-based calibration, which varies in both space and time. As a result, cumulative estimates of rainfall are now issued at the end of each 10-day period (dekad) at 4-km spatial resolution with pan-African coverage. The utility of the products for decision making is improved by the routine provision of validation reports, for which the 10-day (dekadal) TAMSAT rainfall estimates are compared with independent gauge observations. This paper describes the methodology by which the TAMSAT method has been applied to generate the pan-African rainfall monitoring products. It is demonstrated through comparison with gauge measurements that the method provides skillful estimates, although with a systematic dry bias. This study illustrates TAMSAT’s value as a complementary method of estimating rainfall through examples of successful operational application.

Climate change projections and selected impacts for Vietnam

In September 2013, the 5th Assessment Report (5AR) of the International Panel on Climate Change (IPCC) has been released. Taking the 5AR cli-mate change scenarios into account, the World Bank published an earli-er report on climate change and its impacts on selected hot spot re-gions, including Southeast Asia. Currently, dynamical and statistical-dynamical downscaling efforts are underway to obtain higher resolution and more robust regional climate change projections for tropical South-east Asia, including Vietnam. Such initiatives are formalized under the World Meteorological Organization (WMO) Coordinated Regional Dynamic Downscaling Experiment (CORDEX) East Asia and Southeast Asia and also take place in climate change impact projects such as the joint Vietnam-ese-German project “Environmental and Water Protection Technologies of Coastal Zones in Vietnam (EWATEC-COAST)”. In this contribution, the lat-est assessments for changes in temperature, precipitation, sea level, and tropical cyclones (TCs) under the 5AR Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 are reviewed. Special emphasis is put on changes in extreme events like heat waves and/or heavy precipita-tion. A regional focus is Vietnam south of 16°N. A continued increase in mean near surface temperature is projected, reaching up to 5°C at the end of this century in northern Vietnam un-der the high greenhouse-gas forcing scenario RCP8.5. Overall, project-ed changes in annual precipitation are small, but there is a tendency of more rainfall in the boreal winter dry season. Unprecedented heat waves and an increase in extreme precipitation events are projected by both global and regional climate models. Globally, TCs are projected to decrease in number, but an increase in intensity of peak winds and rain-fall in the inner core region is estimated. Though an assessment of changes in land-falling frequency in Vietnam is uncertain due to difficul-ties in assessing changes in TC tracks, some work indicates a reduction in the number of land-falling TCs in Vietnam. Sea level may rise by 75-100 cm until the end of the century with the Vietnamese coastline experienc-ing 10-15% higher rise than on global average. Given the large rice and aquaculture production in the Mekong and Red River Deltas, that are both prone to TC-related storm surges and flooding, this poses a challenge to foodsecurity and protection of coastal population and assets.