Associations between extreme precipitation and childhood hand, foot and mouth disease in urban and rural areas in Hefei, China

Background Understanding the relationship between extreme weather events and childhood hand, foot and mouth disease (HFMD) is important in the context of climate change. This study aimed to quantify the relationship between extreme precipitation and childhood HFMD in Hefei, China, and further, to explore whether the association varied across urban and rural areas. Methods Daily data on HFMD counts among children aged 0–14 years from 2010 January 1st to 2012 December 31st were retrieved from Hefei Center for Disease Control and Prevention. Daily data on mean temperature, relative humidity and precipitation during the same period were supplied by Hefei Bureau of Meteorology. We used a Poisson linear regression model combined with a distributed lag non-linear model to assess the association between extreme precipitation (≥ 90th precipitation) and childhood HFMD, controlling for mean temperature, humidity, day of week, and long-term trend. Results There was a statistically significant association between extreme precipitation and childhood HFMD. The effect of extreme precipitation on childhood HFMD was the greatest at six days lag, with a 5.12% (95% confident interval: 2.7–7.57%) increase of childhood HFMD for an extreme precipitation event versus no precipitation. Notably, urban children and children aged 0–4 years were particularly vulnerable to the effects of extreme precipitation. Conclusions Our findings indicate that extreme precipitation may increase the incidence of childhood HFMD in Hefei, highlighting the importance of protecting children from forthcoming extreme precipitation, particularly for those who are young and from urban areas.

On the detection of human influence in extreme precipitation over India

Climate change is expected to influence extreme precipitation which in turn might affect risks of pluvial flooding. Recent studies on extreme rainfall over India vary in their definition of extremes, scales of analyses and conclusions about nature of changes in such extremes. Fingerprint-based detection and attribution (D&A) offer a formal way of investigating the presence of anthropogenic signals in hydroclimatic observations. There have been recent efforts to quantify human effects in the components of the hydrologic cycle at large scales, including precipitation extremes. This study conducts a D&A analysis on precipitation extremes over India, considering both univariate and multivariate fingerprints, using a standardized probability-based index (SPI) from annual maximum one-day (RX1D) and five-day accumulated (RX5D) rainfall. The pattern-correlation based fingerprint method is used for the D&A analysis. Transformation of annual extreme values to SPI and subsequent interpolation to coarser grids are carried out to facilitate comparison between observations and model simulations. Our results show that in spite of employing these methods to address scale and physical processes mismatch between observed and model simulated extremes, attributing changes in regional extreme precipitation to anthropogenic climate change is difficult. At very high (95%) confidence, no signals are detected for RX1D, while for the RX5D and multivariate cases only the anthropogenic (ANT) signal is detected, though the fingerprints are in general found to be noisy. The findings indicate that model simulations may underestimate regional climate system responses to increasing human forcings for extremes, and though anthropogenic factors may have a role to play in causing changes in extreme precipitation, their detection is difficult at regional scales and not statistically significant. (C) 2015 Elsevier B.V. All rights reserved.

Uncertainties in future projections of extreme precipitation in the Indian monsoon region

Uncertainties in changes to the spatial distribution and magnitude of the heaviest extremes of daily monsoon rainfall over India are assessed in the doubled CO2 climate change scenarios in the IPCC Fourth Assessment Report. Results show diverse changes to the spatial pattern of the 95th and 99th subseasonal percentiles, which are strongly tied to the mean precipitation change during boreal summer. In some models, the projected increase in heaviest rainfall over India at CO2 doubling is entirely predictable based upon the surface warming and the Clausius–Clapeyron relation, a result which may depend upon the choice of convection scheme. Copyright © 2009 Royal Meteorological Society and Crown Copyright

Extreme precipitation and climate change: the potential impacts on flooding

Recent extreme precipitation events have caused widespread flooding to the UK. The prediction of the intensity of such events in a warmer climate is important for adaption strategies against future events. This study highlights the importance of using high-resolution models to predict these events. Using a high-resolution GCM it is shown that extreme precipitation events are predicted to become more frequent under the IPCC A1B warming scenario. It is also shown that current forecast models have difficulty in predicting the location, timing and intensity of small scale precipitation in areas with significant orography.

Importance of resolution and model configuration when downscaling extreme precipitation

Dynamical downscaling is frequently used to investigate the dynamical variables of extra-tropical cyclones, for example, precipitation, using very high-resolution models nested within coarser resolution models to understand the processes that lead to intense precipitation. It is also used in climate change studies, using long timeseries to investigate trends in precipitation, or to look at the small-scale dynamical processes for specific case studies. This study investigates some of the problems associated with dynamical downscaling and looks at the optimum configuration to obtain the distribution and intensity of a precipitation field to match observations. This study uses the Met Office Unified Model run in limited area mode with grid spacings of 12, 4 and 1.5 km, driven by boundary conditions provided by the ECMWF Operational Analysis to produce high-resolution simulations for the Summer of 2007 UK flooding events. The numerical weather prediction model is initiated at varying times before the peak precipitation is observed to test the importance of the initialisation and boundary conditions, and how long the simulation can be run for. The results are compared to raingauge data as verification and show that the model intensities are most similar to observations when the model is initialised 12 hours before the peak precipitation is observed. It was also shown that using non-gridded datasets makes verification more difficult, with the density of observations also affecting the intensities observed. It is concluded that the simulations are able to produce realistic precipitation intensities when driven by the coarser resolution data.

Can reanalyses represent extreme precipitation over England and Wales?

A new generation of reanalysis products is currently being produced that provides global gridded atmospheric data spanning more than a century. Such data may be useful for characterising the observed long-term variability of extreme precipitation events, particularly in regions where spatial coverage of surface observations is limited, and in the pre-satellite era. An analysis of extreme precipitation events is performed over England and Wales, investigating the ability of Twentieth Century Reanalysis and ERA-Interim to represent extreme precipitation accumulations as recorded in the England and Wales Precipitation dataset on accumulation time-scales from 1 to 7 days. Significant correlations are found between daily precipitation accumulation observations and both reanalysis products. A hit-rate analysis indicates that the reanalyses have hit rates (as defined by an event above the 98th percentile) of approximately 40–65% for extreme events in both summer (JJA) and winter (DJF). This suggests that both ERA-Interim and Twentieth Century Reanalysis are difficult to use for representing individual extreme precipitation events over England and Wales.

The water vapour flux above Switzerland and its role in the August 2005 extreme precipitation and flooding

The water budget approach is applied to an atmospheric box above Switzerland (hereafter referred to as the “Swiss box”) to quantify the atmospheric water vapour flux using ECMWF ERA-Interim reanalyses. The results confirm that the water vapour flux through the Swiss box is highly temporally variable, ranging from 1 to 5 · 107 kg/s during settled anticyclonic weather, but increasing in size by a factor of ten or more during high speed currents of water vapour. Overall, Switzerland and the Swiss box “import” more water vapour than it “exports”, but the amount gained remains only a small fraction (1% to 5%) of the total available water vapour passing by. High inward water vapour fluxes are not necessarily linked to high precipitation episodes. The water vapour flux during the August 2005 floods, which caused severe damage in central Switzerland, is examined and an assessment is made of the computed water vapour fluxes compared to high spatio-temporal rain gauge and radar observations. About 25% of the incoming water vapour flux was stored in Switzerland. The computed water vapour fluxes from ECMWF data compare well with the mean rain gauge observations and the combined rain-gauge radar precipitation products.

Climatology of Vb cyclones, physical mechanisms and their impact on extreme precipitation over Central Europe

Cyclones, which develop over the western Mediterranean and move northeastward are a major source of extreme weather and known to be responsible for heavy precipitation over the northern side of the Alpine range and Central Europe. As the relevant processes triggering these so-called Vb events and their impact on extreme precipitation are not yet fully understood, this study focuses on gaining insight into the dynamics of past events. For this, a cyclone detection and tracking tool is applied to the ERA-Interim reanalysis (1979–2013) to identify prominent Vb situations. Precipitation in the ERA-Interim and the E-OBS data sets is used to evaluate case-to-case precipitation amounts and to assess consistency between the two data sets. Both data sets exhibit high variability in precipitation amounts among different Vb events. While only 23 % of all Vb events are associated with extreme precipitation, around 15 % of all extreme precipitation days (99 percentile) over the northern Alpine region and Central Europe are induced by Vb events, although Vb cyclones are rare events (2.3 per year). To obtain a better understanding of the variability within Vb events, the analysis of the 10 heaviest and lowest precipitation Vb events reveals noticeable differences in the state of the atmosphere. These differences are most pronounced in the geopotential height and potential vorticity field, indicating a much stronger cyclone for heavy precipitation events. The related differences in wind direction are responsible for the moisture transport around the Alps and the orographical lifting along the northern slopes of the Alps. These effects are the main reasons for a disastrous outcome of Vb events, and consequently are absent in the Vb events associated with low precipitation. Hence, our results point out that heavy precipitation related to Vb events is mainly related to large-scale dynamics rather than to thermodynamic processes.

Trends in mean and extreme precipitation in the Mount Kenya region from observations and reanalyses

Land and water management in semi-arid regions requires detailed information on precipitation distribution, including extremes, and changes therein. Such information is often lacking. This paper describes statistics of mean and extreme precipitation in a unique data set from the Mount Kenya region, encompassing around 50 stations with at least 30 years of data. We describe the data set, including quality control procedures and statistical break detection. Trends in mean precipitation and extreme indices calculated from these data for individual rainy seasons are compared with corresponding trends in reanalysis products. From 1979 to 2011, mean precipitation decreased at 75% of the stations during the ‘long rains’ (March to May) and increased at 70% of the stations during the ‘short rains’ (October to December). Corresponding trends are found in the number of heavy precipitation days, and maximum of consecutive 5-day precipitation. Conversely, an increase in consecutive dry days within both main rainy seasons is found. However, trends are only statistically significant in very few cases. Reanalysis data sets agree with observations with respect to interannual variability, while correlations are considerably lower for monthly deviations (ratios) from the mean annual cycle. While some products well reproduce the rainfall climatology and some the spatial trend pattern, no product reproduces both.

Characterisation of extreme winter precipitation in Mediterranean coastal sites and associated anomalous atmospheric circulation patterns

We present an analysis of daily extreme precipitation events for the extended winter season (October–March) at 20 Mediterranean coastal sites covering the period 1950–2006. The heavy tailed behaviour of precipitation extremes and estimated return levels, including associated uncertainties, are derived applying a procedure based on the Generalized Pareto Distribution, in combination with recently developed methods. Precipitation extremes have an important contribution to make seasonal totals (approximately 60% for all series). Three stations (one in the western Mediterranean and the others in the eastern basin) have a 5-year return level above 100 mm, while the lowest value (estimated for two Italian series) is equal to 58 mm. As for the 50-year return level, an Italian station (Genoa) has the highest value of 264 mm, while the other values range from 82 to 200 mm. Furthermore, six series (from stations located in France, Italy, Greece, and Cyprus) show a significant negative tendency in the probability of observing an extreme event. The relationship between extreme precipitation events and the large scale atmospheric circulation at the upper, mid and low troposphere is investigated by using NCEP/NCAR reanalysis data. A 2-step classification procedure identifies three significant anomaly patterns both for the western-central and eastern part of the Mediterranean basin. In the western Mediterranean, the anomalous southwesterly surface to mid-tropospheric flow is connected with enhanced moisture transport from the Atlantic. During ≥5-year return level events, the subtropical jet stream axis is aligned with the African coastline and interacts with the eddy-driven jet stream. This is connected with enhanced large scale ascending motions, instability and leads to the development of severe precipitation events. For the eastern Mediterranean extreme precipitation events, the identified anomaly patterns suggest warm air advection connected with anomalous ascent motions and an increase of the low- to mid-tropospheric moisture. Furthermore, the jet stream position (during ≥5-year return level events) supports the eastern basin being in a divergence area, where ascent motions are favoured. Our results contribute to an improved understanding of daily precipitation extremes in the cold season and associated large scale atmospheric features.

On the roles of the northeast cold surge, the Borneo vortex, the Madden-Julian Oscillation, and the Indian Ocean Dipole during the extreme 2006/2007 flood in southern Peninsular Malaysia

The mid-December 2006 to late January 2007 flood in southern Peninsular Malaysia was the worst flood in a century and was caused by three extreme precipitation episodes. These extreme precipitation events were mainly associated with strong northeasterly winds over the South China Sea. In all cases, the northeasterlies penetrated anomalously far south and followed almost a straight trajectory. The elevated terrain over Sumatra and southern Peninsular Malaysia caused low-level convergence. The strong easterly winds near Java associated with the Rossby wave-type response to Madden-Julian Oscillation (MJO) inhibited the counter-clockwise turning of the northeasterlies and the formation of the Borneo vortex, which, in turn, enhanced the low-level convergence over the region. The abrupt termination of the Indian Ocean Dipole (IOD) in December 2006 played a secondary role as warmer equatorial Indian Ocean helped in the MJO formation.

Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores

The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5A degrees x 2.5A degrees grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO - June to October), non-monsoon season (JFMAMND - January to May, November, December) and for the entire year (''Annual''). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5A degrees grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.