Showing papers in "Weather and climate extremes in 2017"

Variability and time series trend analysis of rainfall and temperature in northcentral Ethiopia: A case study in Woleka sub-basin

Abstract: Examining the spatiotemporal dynamics of meteorological variables in the context of changing climate, particularly in countries where rainfed agriculture is predominant, is vital to assess climate-induced changes and suggest feasible adaptation strategies. To that end, trend analysis has been employed to inspect the change of rainfall and temperature in northcentral Ethiopia using gridded monthly precipitation data obtained from Global Precipitation and Climate Centre (GPCC V7) and temperature data from Climate Research Unit (CRU TS 3.23) with 0.5° by 0.5° resolution from 1901 to 2014. Data have been analyzed using coefficient of variation, anomaly index, precipitation concentration index and Palmer drought severity index. Furthermore, Mann-Kendall test was used to detect the time series trend. The result revealed intra- and inter-annual variability of rainfall while Palmer drought severity index value proved the increasing trend of the number of drought years. Annual, belg and kiremt rainfall have decreased with a rate of 15.03, 1.93 and 13.12 mm per decade respectively. The declining trend for annual and kiremt rainfall was found to be statistically significant while that of belg was not significant. The rate of change of temperature was found to be 0.046, 0.067 and 0.026 °C per decade for mean, minimum and maximum respectively. The Mann-Kendall trend analysis test result revealed increasing trend for mean and minimum average temperatures through time significantly while the trend for maximum temperature exhibited a non-significant increasing trend. We recommend strategies designed in the agricultural sector have to take the declining and erratic nature of rainfall and increasing trend of temperature into consideration.

Understanding, modeling and predicting weather and climate extremes: Challenges and opportunities

Abstract: Weather and climate extremes are identified as major areas necessitating further progress in climate research and have thus been selected as one of the World Climate Research Programme (WCRP) Grand Challenges. Here, we provide an overview of current challenges and opportunities for scientific progress and cross-community collaboration on the topic of understanding, modeling and predicting extreme events based on an expert workshop organized as part of the implementation of the WCRP Grand Challenge on Weather and Climate Extremes. In general, the development of an extreme event depends on a favorable initial state, the presence of large-scale drivers, and positive local feedbacks, as well as stochastic processes. We, therefore, elaborate on the scientific challenges related to large-scale drivers and local-to-regional feedback processes leading to extreme events. A better understanding of the drivers and processes will improve the prediction of extremes and will support process-based evaluation of the representation of weather and climate extremes in climate model simulations. Further, we discuss how to address these challenges by focusing on short-duration (less than three days) and long-duration (weeks to months) extreme events, their underlying mechanisms and approaches for their evaluation and prediction.

Comparing smallholder farmers’ perception of climate change with meteorological data: A case study from southwestern Nigeria

Abstract: This paper examines smallholder farmers’ perceptions of climate change, climate variability and their impacts, and adaptation strategies adopted over the past three decades. We use ethnographic analysis, combined with Cumulative Departure Index (CDI), Rainfall Anomaly Index (RAI) analysis, and correlation analysis to compare farmers’ perceptions in Southwestern Nigeria with historical meteorological data, in order to assess the way farmers’ observations mirror the climatic trends. The results show that about 67% of farmers who participated had observed recent changes in climate. Perceptions of rural farmers on climate change and variability are consistent with the climatic trend analysis. RAI and CDI results illustrate that not less than 11 out of 30 years in each study site experienced lower-than-normal rainfall. Climatic trends show fluctuations in both early growing season (EGS) and late growing season (LGS) rainfall and the 5-year moving average suggests a reduction in rainfall over the 30 years. Climatic trends confirmed farmers’ perceptions that EGS and LGS precipitations are oscillating, that rainfall onset is becoming later, and EGS rainfall is reducing. Overall impacts of climate change on both crops and livestock appear to be highly negative, much more on maize (62.8%), yam (52.2%), poultry (67%) and cattle (63.2%). Years of farming experiences and level of income of farmers appear to have a significant relationship with farmers’ choice of adaptation strategies, with r≥0.60@ p

Historical and projected trends in temperature and precipitation extremes in Australia in observations and CMIP5

Abstract: This study expands previous work on climate extremes in Australia by investigating the simulation of a large number of extremes indices in the CMIP5 multi-model dataset and comparing them to multiple observational datasets over a century of observed data using consistent methods. We calculate 24 indices representing extremes of temperature and precipitation from 1911 to 2010 over Australia and show that there have been significant observed trends in temperature extremes associated with warming while there have been few significant observed trends in precipitation extremes. We compare the observed indices calculated from two mostly independent datasets with 22 CMIP5 models to determine how well global climate models are able to simulate observed climatologies, variability and trends. We find that generally temperature extremes are reasonably well simulated (climatology, variability and trend patterns) although the models tend to overestimate minimum temperature extremes and underestimate maximum temperature extremes. Some models stand out as being outliers and we exclude one model (INMCM4) entirely from the multi-model analysis as it simulates unrealistic minimum temperature extremes over the historical period. There is more spread between models for precipitation than temperature extremes but in most cases the observations sit within the model spread. Exceptions are consecutive wet days (CWD) where nearly all models overestimate the actual number of annual wet days and simple daily intensity (SDII) and one day precipitation maxima (Rx1day) where the models tend to underestimate precipitation intensity. However, some of these differences likely lie in observational uncertainty. Most models including the multi-model mean indicate that precipitation intensity has increased over the last century but the two observational datasets analysed disagree on the sign of change of precipitation intensity, one of them indicating a significant decrease. We use the CMIP5 simulations for two future Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5) to project changes in temperature and precipitation extremes across Australia. By the end of the century the number of cold temperature extremes substantially reduces and the number of warm temperature extremes substantially increases; changes scaling relative to the strength of emissions scenario. Changes in temperature extremes are often greatest in the tropics. While the results for precipitation extremes are less marked, simulations for the end of the century compared to present day indicate more periods of dryness while the most intense precipitation extremes increase substantially, with a separation becoming clear between emissions scenarios.

Characterization of future drought conditions in the Lower Mekong River Basin

Abstract: This study evaluates future changes to drought characteristics in the Lower Mekong River Basin using climate model projections. The Lower Mekong Basin (LMB), covering Thailand, Cambodia, Laos and Vietnam, is vulnerable to increasing droughts. Univariate analysis was employed in this study to compare drought characteristics associated with different return periods for the historical period 1964–2005 and future scenarios (RCP 4.5 2016–2057, RCP 4.5 2058–2099, RCP 8.5 2016–2057 and RCP 8.5 2058–2099). Because a single drought event is defined by several correlated characteristics, drought risk assessment by a multivariate analysis was deemed appropriate, and a multivariate analysis of droughts was conducted using copula functions to investigate the differences in the trivariate joint occurrence probabilities of the historical period and future scenarios. The Standardized Precipitation Index (SPI) was selected as the drought index because of its ability to detect and compare metrological droughts across time and space scales. Historical precipitation data from 1964 to 2005 and future precipitation projections from 2016 to 2099 for 15 global circulation models (GCMs) obtained from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset were employed. In all future scenarios, the Lower LMB and 3S subbasins were expected to experience more severe and intense droughts. The multivariate drought risk assessment revealed an increase in drought risks in the LMB. However, the Chi-Mun subbasin may experience an alleviation of future drought characteristics. Because the basin was expected to experience an increase in average monthly precipitation in most months, the variability in magnitude suggested that the LMB region requires adaptation strategies to address future drought occurrences.

GIS-based climate variability and drought characterization in Ethiopia over three decades

Abstract: The climate variability and drought frequency over potential crop growing regions of Ethiopia during 1983−2012 were analysed. Data from 87 weather stations across the country were used for this analysis. Ethiopian agricultural activities are highly dependent on the long rainy season (June−September) rainfall, which accounts for 70% of the total annual rainfall. There was no significant change in rainfall during annual and the bimodal seasons during this period of study. However, there was significant change in the rainfall coefficient of variation. STARDEX precipitation indices provided a measure of intensity, frequency and proportion of total rainfall. Ninetieth percentile of rainfall, number of rainy days with rainfall >10 mm/day and the greatest 10 d total rainfall were increased over time at most of the stations. Among the major droughts, 1984−'85 drought was reported as the most severe drought with peak negative SPI value −3.68 in Wollo. The longest duration of drought lasted for 63 months in Borena Zone in southern Ethiopia during 1983−2012 period. Extreme maximum temperature (90th percentile) has increased over 45% of the weather stations, while, extreme minimum temperature (90th percentile) has increased 53% of the weather stations. Extreme maximum temperature events have been increasing during the seasons in Ethiopia, which is the real concern for agricultural and livestock activities, as these sectors significantly contribute to about 50% of GDP for the country. However, given the increasing response capacity of the government, as observed during 2002−'03 drought, environmental disaster is expected to be under control over time.

Evolution of mean, variance and extremes in 21st century temperatures

Abstract: Warming of the climate system can result in very large corresponding changes in the occurrence of climate extremes. Temperature extremes may occur due to a shift in the whole distribution, where there is an increase in the entire temperature probability distribution, or to changes in the shape of the distribution, such as an increase in variability causing a widening of the distribution. Understanding the precise characteristics of changes in temperature distributions in response to background warming is an important aspect of fully understanding changes in heat extremes and their associated impacts on human and ecosystem health. This study investigates projected 21st century changes in the characteristics of mean, maximum and minimum temperature on daily- and annual- timescales for various regions (Australia, Asia, Europe and North America) using data from seven models participating in the Coupled Model Intercomparison Phase 5 (CMIP5). Using the RCP8.5 experiment we show that an increase in mean temperature throughout the 21st century is a consistent feature of all models for each region. Changes in the variance of simulated temperatures are equivocal, with the sign and magnitude of variance changes in the 21st century varying in different models and regions. A quantile regression analysis demonstrates differences in upper and lower quantile slopes, relative to the mean, including a consistent skew in daily temperatures towards hot extremes. These potentially complex characteristics of temperature changes should not be overlooked, as temperature extremes are potentially more sensitive to changes in the variance and higher order moments than in the mean. Furthermore, a wider range of extreme temperature behaviour may have important consequences for various stakeholders, due to impacts on public health, agriculture and ecological systems.

Diagnosing conditional anthropogenic contributions to heavy Colorado rainfall in September 2013

Abstract: The Colorado floods of September 2013 caused severe damage and fatalities, and resulted from prolonged heavy rainfall unusual for that time of year – both in its record-breaking amounts and associated weather systems. We investigate the possible role of anthropogenic climate change in this extreme event. The unusual hydrometeorology of the event, however, challenges standard frameworks for attributing extreme events to anthropogenic climate change, because they typically struggle to simulate and connect the large-scale meteorology associated with local weather processes. Therefore we instead employ a part dynamical modelling- part observational- based event attribution approach, which simulates regional Colorado rainfall conditional on boundary conditions prescribed from the observed synoptic-scale meteorology in September 2013 – and assumes these conditions would have been similar in the absence of anthropogenic forcing. Using this ‘conditional event attribution’ approach we find that our regional climate model simulations indicate that anthropogenic drivers increased the magnitude of heavy northeast Colorado rainfall for the wet week in September 2013 by 30%, with the occurrence probability of a week at least that wet increasing by at least a factor of 1.3. By comparing the convective and large-scale components of rainfall, we find that this increase resulted in part from the additional moisture-carrying capacity of a warmer atmosphere – allowing more intense local convective rainfall that induced a dynamical positive feedback in the existing larger scale moisture flow – and also in part from additional moisture transport associated with larger scale circulation change. Our approach precludes assessment of changes in the frequency of the observed synoptic meteorological conditions themselves, and thus does not assess the effect of anthropogenic climate drivers on the statistics of heavy Colorado rainfall events. However, tailoring analysis tools to diagnose particular aspects of localized extreme weather events, conditional on the observed large-scale meteorology, can prove useful for diagnosing the physical effects of anthropogenic climate change on severe weather events – especially given large uncertainties in assessments of anthropogenic driven changes in atmospheric circulation.

Assessment of changing trends of daily precipitation and temperature extremes in Bamako and Ségou in Mali from 1961- 2014

Abstract: In Mali the annual rainfall is highly variable, ranging from less than 200 mm–1 300 mm and its distribution is unevenly spread between north and south. Climate change threatens to increase air temperatures and evapotranspiration, increase the risk of intense rainstorms, and increase the risk of heat waves associated with drought. The objective of this study is to assess the change trends of daily temperature and precipitation extremes in Bamako and Segou in Mali during the period between 1961 and - 2014. Analyses of the changes in trends of daily temperature and precipitation extremes in two regions were studied by calculated extreme climate extreme indices series in RClimdex software. Trends in extreme indices were studied for 5 temperature and 4 precipitation series. Results showed a positive significant decrease of warming trends in cool days, cool nights, whereas warm extreme nights, day times and warm spells on the contrary showed positive significant increasing warming throughout the Segou region. In Bamako, temperature extreme showed an insignificant trend for negative extremes decreasing warming trends for cold nights and cold days while warm nights, warm days and warm spells showed insignificant positive trends over the period from 1961 to 2014. The results of precipitation extremes for Segou showed positive significant decrease in consecutive wet day and in extremely wet, whereas Maximum 5 day's precipitation showed positive insignificant increase and the total annual precipitation showed a positive insignificant decrease. In Bamako consecutive wet day, Maximum 5 day's precipitation and total annual precipitation showed positive insignificant decrease. Despite the small number of homogenous temperature and rainfall indices series, the study could present a proportion of significant extremes in Segou station averages trends. The study provided evidence that during the last 53 years; Segou was particularly affected by warm extremes based on night time indices rather than cold extremes based on day time indices.

Analysis of farmers’ adaptation to weather extremes in West African Sudan Savanna

Abstract: There have been recent incidences of weather extremes in the West African Sudan Savanna and farmers have responded through implementation of relevant adaptation strategies. For a deeper insight into farmers’ adaptation to climatic shocks, this study documents farmers’ perception of recent changes in the local climate, and identifies factors that influence the number and choice of strategies implemented. Interdependencies among strategies are explored and joint and marginal probabilities of adoption estimated. Upper East Ghana and Southwest Burkina Faso are used as the case study regions. These regions were selected due to extreme reliance of inhabitants on agriculture for sustenance, and their recent exposure to weather extremes. Through estimation of a Poisson regression and multivariate probit model to identify the major factors that influence the number and choice of strategies adopted, we discover that, limited access to credit, markets, and extension services, smaller cropland area, and low level of mechanization could impede effective adaptation to weather extremes. To enhance farmers’ adaptive capacity, policy makers and various stakeholders need to contribute towards improving farmers’ access to credit, markets, and extension services, and implement measures to promote mechanization.

Extreme value analysis of air pollution data and their comparison between two large urban regions of South America

Abstract: Sixteen years of hourly atmospheric pollutant data (1996–2011) in the Metropolitan Area of Sao Paulo (MASP), and seven years (2005–2011) of data measured in the Metropolitan Area of Rio de Janeiro (MARJ), were analyzed in order to study the extreme pollution events and their return period. In addition, the objective was to compare the air quality between the two largest Brazilian urban areas and provide information for decision makers, government agencies and civil society. Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD) were applied to investigate the behavior of pollutants in these two regions. Although GEV and GPD are different approaches, they presented similar results. The probability of higher concentrations for CO, NO, NO2, PM10 and PM2.5 was more frequent during the winter, and O3 episodes occur most frequently during summer in the MASP. On the other hand, there is no seasonally defined behavior in MARJ for pollutants, with O3 presenting the shortest return period for high concentrations. In general, Ibirapuera and Campos Elisios stations present the highest probabilities of extreme events with high concentrations in MASP and MARJ, respectively. When the regions are compared, MASP presented higher probabilities of extreme events for all analyzed pollutants, except for NO; while O3 and PM2.5 are those with most frequent probabilities of presenting extreme episodes, in comparison other pollutants.

Flood vulnerability, local perception and gender role judgment using multivariate analysis: A problem-based “participatory action to Future Skill Management” to cope with flood impacts

Abstract: Flood impacts and social vulnerability are substantial threats for the sustainable development of the developing world. This study focuses on some particular points of flood impacts and the local concept towards existing management capacity. Additionally, significant focus was given to gender roles and how they may impact measures that aim towards reducing flood risks. Both qualitative and quantitative techniques were applied during the research, in order to understand the perception of the char-land communities on natural hazards, social crisis, resource accessibility, climatic uncertainty and the gender role to cope with flood consequences. Concurrently the questionnaire survey and focus group discussion (FGD) was performed among the local people. This study revealed that majority of the people was directly threatened by the destructive consequences of flood hazards, which in turn, badly influenced the household economies, alongside its education, security and infrastructural prospects. Some decades ago, the application of indigenous techniques was deemed successful as the communities managed to effectively reduce the risk involved with potential floods. However, now the solution is no longer clear as it is disturbed by external climate components. Results showed the vulnerability of the local communities in terms of knowledge, resource access, communication system, proper information dissemination, health, and livelihood. The gender variability is believed to have significant value in terms of flood disaster risk reduction, household development, and family caring activities. Principal component analysis (PCA) and cluster analysis (CA) has clearly identified the gender role in the char-land community. The women's activities are profoundly focused in terms of the flood risk management, and the families generally do not properly appreciate the value of women and their role. However, the problem-based “Participatory Action to Future Skill Management (PFM)” for flood risk reduction in the char-land area can ensure to knowledge empowerment and capacity builds up, to achieve community resilience and sustainability in adverse climate conditions. The government should take appropriate actions in order to figure out the basic problem, and should issue focused policy practices among the char-land communities to bring them in sustainable trends.

Intervention pathways towards improving the resilience of pastoralists: A study from Borana communities, southern Ethiopia

Abstract: Building resilient communities towards recurrent droughts is increasingly becoming an important element in development endeavours, particularly among communities vulnerable to shocks and stresses. Despite decades of remarkable efforts made by governmental and non-governmental organization, the resilience capacity of pastoralists in Ethiopia remains poor. The aim of this study is to test the statistical relationships among the resilience dimensions that emerged through community consultations, and to identify the intervention pathways for effective resilience building efforts. Data were collected from 1058 randomly sampled households in Arero and Dhas districts of Borana Zone, Southern Ethiopia. The data were collected through interviewer administered structured questionnaire and observational checklist. Principal component analyses were done to develop composite scores of the different resilience dimensions. Structural equation model (SEM) verified the theoretical model. The SEM also revealed that resilience towards impact of recurrent droughts was multi-dimensional and showed statistically significant (p

The spatial distribution of rainfall extremes and the influence of El Nino Southern Oscillation

Abstract: Extreme rainfall does not occur in spatial isolation. Rainfall occurs in a region, and within that region nearby locations are likely to experience similar impacts due to spatial dependence. While univariate extreme value models provide the easiest statistical modelling approach to rainfall extremes, practitioners and researchers adopting statistical models without spatial dependence are liable to underestimate potential impacts. To minimise the adverse impacts of extreme rainfall, an understanding of the extreme precipitation field is required. To highlight how a spatial model with dependence compares with univariate models of extremes, a max-stable model is fitted to the daily annual maximum rainfall in a case study region of South East Queensland, Australia. This case study region was selected as it can be used to illustrate how climate drivers, such as El Nino Southern Oscillation (ENSO), can affect the extreme precipitation field and subsequently the distribution of spatial random variables. In adopting a max-stable model it is possible to produce simulations of the daily annual maximum rainfall field. These simulations can be used to inform urban planning strategies. This includes showing that the probability of a historical flash flood occurring was much higher given the strong La Nina phase of ENSO compared with an El Nino phase. The results presented aim to shift the dialogue from a univariate discussion to a discussion about how models of spatial extremes with dependence can be used to better understand the probability of extreme rainfall events and account for the influence of ENSO.

Typhoon activity and some important parameters in the South China Sea

Abstract: This study aims to statistically describe temporal and spatial variations of sea surface temperature (SST), latent heat flux (LHF), sensible heat flux (SHF), and precipitation rate with typhoon activity over the South China Sea. The correlations of the parameters and their connections with the physical phenomena are clearly presented. This is fundamental to predict a typhoon's intensity and track. The effects were investigated from 1991 to 2011 based on archived data from the National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP-NCAR) and the number of typhoons were sourced from the International Best Track Archive for Climate Stewardship (IBTrACS). The results showed that most typhoons occurred in August and September, which was related to high temperature in the summer season and the southwest monsoon in the area. The maximum mean values of SST in May and June were related to the East Asian Monsoon. The average values of LHF were highest in July, and the mean values of SHF were highest in July and August. SHF varied gradually at different months compared with LHF. In addition, the average of precipitation rate was highest in November, which can be related to the northeasterly winter monsoon. The relationships of the aforementioned parameters were obtained using Pearson's correlation analysis. Moreover, the highest and lowest mean values of the parameters in different areas were considered, and their spatial relationships were analyzed.

Drivers of 2016 record Arctic warmth assessed using climate simulations subjected to Factual and Counterfactual forcing

Abstract: A suite of historical atmospheric model simulations is described that uses a hierarchy of global boundary forcings designed to inform research on the detection and attribution of weather and climate-related extremes. In addition to experiments forced by actual variations in sea surface temperature, sea ice concentration, and atmospheric chemical composition (so-called Factual experiments); additional (Counterfactual) experiments are conducted in which the boundary forcings are adjusted by removing estimates of long-term climate change. A third suite of experiments are identical to the Factual runs except that sea ice concentrations are set to climatological conditions (Clim-Polar experiments). These were used to investigate the cause for extremely warm Arctic surface temperature during 2016. Much of the magnitude of surface temperature anomalies averaged poleward of 65°N in 2016 (3.2 ± 0.6 °C above a 1980–89 reference) is shown to have been forced by observed global boundary conditions. The Factual experiments reveal that at least three quarters of the magnitude of 2016 annual mean Arctic warmth was forced, with considerable sensitivity to assumptions of sea ice thickness change. Results also indicate that 30–40% of the overall forced Arctic warming signal in 2016 originated from drivers outside of the Arctic. Despite such remote effects, the experiments reveal that the extreme magnitude of the 2016 Arctic warmth could not have occurred without consideration of the Arctic sea ice loss. We find a near-zero probability for Arctic surface temperature to be as warm as occurred in 2016 under late-19th century boundary conditions, and also under 2016 boundary conditions that do not include the depleted Arctic sea ice. Results from the atmospheric model experiments are reconciled with coupled climate model simulations which lead to a conclusion that about 60% of the 2016 Arctic warmth was likely attributable to human-induced climate change.

Detecting the effect of urban land use on extreme precipitation in the Netherlands

Abstract: A notable increase in heavy precipitation has been observed over the Netherlands in recent decades. The aim of this study was to assess the influences of urban land use on these extreme precipitation patterns. Significant differences between an earlier multi-decadal period and a recent period were found in the Netherlands between 1961 and 2014. The significant changes in different indices indicate that severe precipitation events were not distributed homogeneously across the study area. The precipitation probability and distribution were assessed using the block maxima approach by comparing observations from urban and rural areas at different timescales. The possible effects of land use on extreme precipitation were assessed by quantifying the differences between urban and rural rain gauge stations according to the spatial gridding method. This study shows that urban land use may have affected the extreme precipitation patterns across the Netherlands. The data from all the categorized stations show that urban areas receive more intense extreme precipitation than do rural areas. Relative to other areas in the Netherlands, the urban areas in the western populated regions of the country exhibit prominent urban land use influences on the extreme precipitation patterns.

A very unusual precipitation event associated with the 2015 floods in Jakarta: an analysis of the meteorological factors

Abstract: “The 2–days precipitation event over Jakarta in February 2015 was very unusual, the highest in the 135–year long historical records with a return period more than 60 years in the current climate. An intensified monsoon with an unusual northerly winds leading to this event is described. The 2015 event has become about 2.2 times more likely due to the trend towards more extreme precipitation.”

Evaluating the MSG satellite Multi-Sensor Precipitation Estimate for extreme rainfall monitoring over northern Tunisia

Abstract: Knowledge and evaluation of extreme precipitation is important for water resources and flood risk management, soil and land degradation, and other environmental issues. Due to the high potential threat to local infrastructure, such as buildings, roads and power supplies, heavy precipitation can have an important social and economic impact on society. At present, satellite derived precipitation estimates are becoming more readily available. This paper aims to investigate the potential use of the Meteosat Second Generation (MSG) Multi-Sensor Precipitation Estimate (MPE) for extreme rainfall assessment in Tunisia. The MSGMPE data combine microwave rain rate estimations with SEVIRI thermal infrared channel data, using an EUMETSAT production chain in near real time mode. The MPE data can therefore be used in a now-casting mode, and are potentially useful for extreme weather early warning and monitoring. Daily precipitation observed across an in situ gauge network in the north of Tunisia were used during the period 2007–2009 for validation of the MPE extreme event data. As a first test of the MSGMPE product's performance, very light to moderate rainfall classes, occurring between January and October 2007, were evaluated. Extreme rainfall events were then selected, using a threshold criterion for large rainfall depth (>50 mm/day) occurring at least at one ground station. Spatial interpolation methods were applied to generate rainfall maps for the drier summer season (from May to October) and the wet winter season (from November to April). Interpolated gauge rainfall maps were then compared to MSGMPE data available from the EUMETSAT UMARF archive or from the GEONETCast direct dissemination system. The summation of the MPE data at 5 and/or 15 min time intervals over a 24 h period, provided a basis for comparison. The MSGMPE product was not very effective in the detection of very light and light rain events. Better results were obtained for the slightly more moderate and moderate rain event classes in terms of percentage of detected events, correlation coefficient, and ratio bias. The results for extreme events were mixed, with high pixel correlations of R=0.75 achieved for some events, while for other events the correlation between satellite and ground observation was rather weak. MPE data for northern Tunisia seem more reliable during the summer season and for larger event scales. The MSGMPE data have demonstrated to be very informative for early warning purposes, but need to be combined with other near real time data or information to give reliable and quantitative estimates of extreme rainfall.

Extreme temperature differences in the city of Lahti, southern Finland: Intensity, seasonality and environmental drivers

Abstract: The extremes of month-specific spatial temperature differences were studied for a first time in the high-latitude city of Lahti and its surroundings in southern Finland. During the 2-year observation period (6/14–5/16), the largest momentary temperature difference, 11.1 °C, was detected in February, and the smallest, 6.2 °C, in April. The impacts of various environmental factors during the extreme situations were estimated by site-specific analysis of the warmest and coldest observation sites and a stepwise multiple linear regression model including all the 8 observation sites. The extreme temperature differences were characterised by inversions especially in winter and spring, the warmest site being the hill-top location in Kivistonmaki. In summer the role of urban heating was more apparent, and the temperature was the highest in the relatively low-lying city centre. In autumn the heating impact of the relatively warm Lake Vesijarvi caused the largest temperature differences with harbour as the warmest site. The weather during all of the momentary extreme situations was calm and in the majority of the situations also clear. The impact of cloud cover was less critical than that of wind speed in reducing spatial temperature differences. The momentary extreme situations existed at night or at dawn, with one exception: only in January, during the cold weather period dominated by high pressure, the delayed break of inversion in the vicinity of Lake Vesijarvi caused the extreme temperature difference to exist in the afternoon, reflecting for its part the substantial stabilising impact of seasonal ice cover on Lake Vesijarvi.

Transient response of the global mean warming rate and its spatial variation

Abstract: The Earth has warmed over the past century. The warming rate (amount of warming over a given period) varies in time and space. Observations show a recent increase in global mean warming rate, which is initially maintained in model projections, but which diverges substantially in future depending on the emissions scenario followed. Scenarios that stabilize forcing lead to much lower warming rates, as the rate depends on the change in forcing, not the amount. Warming rates vary spatially across the planet, but most areas show a shift toward higher warming rates in recent decades. The areal distribution of warming rates is also changing shape to include a longer tail in recent decades. Some areas of the planet are already experiencing extreme warming rates of about 1 °C/decade. The fat tail in areal distribution of warming rates is pronounced in model runs when the forcing and global mean warming rate is increasing, and indicates a climate state more prone to regime transitions. The area-proportion of the Earth displaying warming/cooling trends is shown to be directly related to the global mean warming rate, especially for trends of length 15 years and longer. Since the global mean warming rate depends on the forcing rate, the proportion of warming/cooling trend areas in future also depends critically on the choice of future forcing scenario.

Simulation of extreme temperature over Odisha during May 2015

Abstract: An extreme temperature event (heat wave) over the state of Odisha was unique as it lasted for about 2 weeks in the 3rd and 4th weeks of May 2015. There was a similar severe heat wave in western and central Odisha in the month of April 1998. The interesting feature of the recent episodic heat wave is that it prevailed in the late pre-monsoon season with wider spread in the state of Odisha. Around 12–15 cities experienced a daily maximum temperature of over 45 °C during the strong heat wave period, and 25th −27th May was declared as the red box zone. In this study, we first analysed the intense summer temperature of 2015 May using India Meteorological Department observations of daily maximum temperature. The observed heat wave phenomenon was then simulated using the Weather Research and Forecast Model (WRFV3) at 2-km horizontal resolution to assess its ability to forecast such a rare event. The observational analysis clearly indicated that this episodic event was unique both in terms of intensity, geographical spread and duration. An optimized configuration of the WRF model is proposed and implemented for the simulation of the episodic heat wave phenomenon (daily maximum temperature) over the state of Odisha. The time-ensemble simulation of the temperature is shown to be in close agreement with the station-scale observations.

Regional decision-makers as potential users of Extreme Weather Event Attribution - Case studies from the German Baltic Sea coast and the Greater Paris area

Abstract: Extreme Event Attribution has raised increasing attention in climate science in the last years. It means to judge the extent to which certain weather-related extreme events have changed due to human influences on climate with probabilistic statements. Extreme Event Attribution is often anticipated to spur more than just scientific ambition. It is able to provide answers to a commonly asked questions after extreme events, namely, ‘can we blame it on climate change’ and is assumed to support decision-making of various actors engaged in climate change mitigation and adaptation. More in-depth research is widely lacking about who these actors are; in which context they can make use of it; and what requirements they have, to be able to actually apply Extreme Event Attribution. We have therefore addressed these questions with two empirical case studies looking at regional decision-makers who deal with storm surge risks in the German Baltic Sea region and heat waves in the Greater Paris area. Stakeholder interviews and workshops reveal that fields of application and requirements are diverse, difficult to explicitly identify, and often clearly associated with stakeholders' specific mandate, the hazard background, and the regional socio-economic setting. Among the considered stakeholders in the Baltic Sea region, Extreme Event Attribution is perceived to be most useful to awareness-raising, in particular for climate change mitigation. They emphasised the importance of receiving understandable information - and that, rather later, but with smaller uncertainties than faster, but with higher uncertainties. In the Paris case, we typically talked to people engaged in adaptation with expertise in terms of climate science, but narrowly defined mandates which is typical for the Paris-centred political system with highly specialised public experts. The interviewees claimed that Extreme Event Attribution is most useful to political leverage and public discourses. If novel information like this is not sorted out a priori, it needs to be clearly linked to impacts, preferably as monetary values lost. These examples underline the significance of conducting case-specific stakeholder mappings and consultation. Overall, our studies can thereby provide methods and exemplary empirical evidence to support developing useful services from Extreme Event Attribution for targeted groups of users.