Showing papers in "International Journal of Climatology in 2015"

Candidate Distributions for Climatological Drought Indices (SPI and SPEI)

Abstract: The Standardized Precipitation Index (SPI), a well-reviewed meteorological drought index recommended by the World Meteorological Organization (WMO), and its more recent climatic water balance variant, the Standardized Precipitation-Evapotranspiration Index (SPEI), both rely on selection of a univariate probability distribution to normalize the index, allowing for comparisons across climates. Choice of an improper probability distribution may impart bias to the index values, exaggerating or minimizing drought severity. This study compares a suite of candidate probability distributions for use in SPI and SPEI normalization using the 0.5° × 0.5° gridded Watch Forcing Dataset (WFD) at the continental scale, focusing on Europe. Several modifications to the SPI and SPEI methodology are proposed, as well as an updated procedure for evaluating SPI/SPEI goodness of fit based on the Shapiro-Wilk test. Candidate distributions for SPI organize into two groups based on their ability to model short-term accumulation (1-2 months) or long-term accumulation (>3 months). The two-parameter gamma distribution is recommended for general use when calculating SPI across all accumulation periods and regions within Europe, in agreement with previous studies. The generalized extreme value distribution is recommended when computing the SPEI, in disagreement with previous recommendations.

Crowdsourcing for climate and atmospheric sciences: current status and future potential

Abstract: Crowdsourcing is traditionally defined as obtaining data or information by enlisting the services of a (potentially large) number of people. However, due to recent innovations, this definition can now be expanded to include ‘and/or from a range of public sensors, typically connected via the Internet.’ A large and increasing amount of data is now being obtained from a huge variety of non-traditional sources – from smart phone sensors to amateur weather stations to canvassing members of the public. Some disciplines (e.g. astrophysics, ecology) are already utilizing crowdsourcing techniques (e.g. citizen science initiatives, web 2.0 technology, low-cost sensors), and while its value within the climate and atmospheric science disciplines is still relatively unexplored, it is beginning to show promise. However, important questions remain; this paper introduces and explores the wide-range of current and prospective methods to crowdsource atmospheric data, investigates the quality of such data and examines its potential applications in the context of weather, climate and society. It is clear that crowdsourcing is already a valuable tool for engaging the public, and if appropriate validation and quality control procedures are adopted and implemented, it has much potential to provide a valuable source of high temporal and spatial resolution, real-time data, especially in regions where few observations currently exist, thereby adding value to science, technology and society.

Influences of ENSO, NAO, IOD and PDO on seasonal precipitation regimes in the Yangtze River basin, China

Abstract: Teleconnections between El Nino/Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD) and Pacific Decadal Oscillation (PDO) and seasonal precipitation regimes over the Yangtze River basin have been analysed based on the rotated empirical orthogonal functions. Results show that ENSO is the leading driver of seasonal precipitation variability over the Yangtze River basin, and the spring precipitation has been influenced by the PDO and ENSO, the summer and autumn precipitation has been influenced by the ENSO and IOD, the winter precipitation has been influenced by the ENSO, IOD and NAO. Furthermore, changes for the seasonal occurrence and intensity of wet days linked to the ENSO, NAO, IOD and PDO indices have also been investigated to discover which is the dominant mechanism driving seasonal precipitation changes. And results indicated that the influences of ENSO, NAO, IOD and PDO on the seasonal occurrence and intensity of precipitation events are complex, such as that the negative PDO event at the same year tends to increase the spring occurrence of precipitation events in the southwestern part of the Yangtze River basin while the positive ENSO event a year earlier tends to increase the spring intensity of precipitation events in the east part of the Yangtze River basin.

Creating a topoclimatic daily air temperature dataset for the conterminous United States using homogenized station data and remotely sensed land skin temperature

Abstract: Gridded topoclimatic datasets are increasingly used to drive many ecological and hydrological models and assess climate change impacts. The use of such datasets is ubiquitous, but their inherent limitations are largely unknown or overlooked particularly in regard to spatial uncertainty and climate trends. To address these limitations, we present a statistical framework for producing a 30-arcsec (∼800-m) resolution gridded dataset of daily minimum and maximum temperature and related uncertainty from 1948 to 2012 for the conterminous United States. Like other datasets, we use weather station data and elevation-based predictors of temperature, but also implement a unique spatio-temporal interpolation that incorporates remotely sensed 1-km land skin temperature. The framework is able to capture several complex topoclimatic variations, including minimum temperature inversions, and represent spatial uncertainty in interpolated normal temperatures. Overall mean absolute errors for annual normal minimum and maximum temperature are 0.78 and 0.56 °C, respectively. Homogenization of input station data also allows interpolated temperature trends to be more consistent with US Historical Climate Network trends compared to those of existing interpolated topoclimatic datasets. The framework and resulting temperature data can be an invaluable tool for spatially explicit ecological and hydrological modelling and for facilitating better end-user understanding and community-driven improvement of these widely used datasets.

Climate of the Carpathian Region in the period 1961–2010: climatologies and trends of 10 variables

Abstract: The Carpathians are the longest mountain range in Europe and a geographic barrier between Central Europe, Eastern Europe, and the Balkans. To investigate the climate of the area, the CARPATCLIM project members collected, quality-checked, homogenized, harmonized, and interpolated daily data for 16 meteorological variables and many derived indicators related to the period 1961–2010. The principal outcome of the project is the Climate Atlas of the Carpathian Region, hosted on a dedicated website (www.carpatclim-eu.org) and made of high-resolution daily grids (0.1° × 0.1°) of all variables and indicators at different time steps. In this article, we analyze the spatial and temporal variability of 10 variables: minimum, mean, and maximum temperature, daily temperature range, precipitation, cloud cover, relative sunshine duration, relative humidity, surface air pressure, and wind speed at 2 m. For each variable, we present the gridded climatologies for the period 1961–2010 and discuss the linear trends both on an annual and seasonal basis. Temperature was found to increase in every season, in particular in the last three decades, confirming the trends occurring in Europe; wind speed decreased in every season; cloud cover and relative humidity decreased in spring, summer, and winter, and increased in autumn, while relative sunshine duration behaved in the opposite way; precipitation and surface air pressure showed no significant trend, though they increased slightly on an annual basis. We also discuss the correlation between the variables and we highlight that in the Carpathian Region positive and negative sunshine duration anomalies are highly correlated to the corresponding temperature anomalies during the global dimming (1960s and 1970s) and brightening (1990s and 2000s) periods.

Trends in extreme daily rainfall and temperature indices over South Asia

Abstract: Over the last few decades, weather and climate extremes have become a major focus of researchers, the media and general public due to their damaging effects on human society and infrastructure. Trends in indices of climate extremes are studied for the South Asian region using high-quality records of daily temperature and precipitation observations. Data records from 210 (265) temperature (precipitation) observation stations are analysed over the period 1971-2000 (1961-2000). Spatial maps of station trends, time series of regional averages and frequency distribution analysis form the basis of this study. Due to the highly diverse geography of the South Asian region, the results are also described for some specific regions, such as the island of Sri Lanka; the tropical region (excluding Sri Lanka); the Greater Himalayas above 35°N, the Eastern Himalayas (Nepal) and the Thar Desert. Generally, changes in the frequency of temperature extremes over South Asia are what one would expect in a warming world; warm extremes have become more common and cold extremes less common. The warming influence is greater in the Eastern Himalayas compared with that in the Greater Himalayas. The Thar Desert also shows enhanced warming, but increases are mostly less than in the Eastern Himalayas. Changes in the indices of extreme precipitation are more mixed than those of temperature, with spatially coherent changes evident only at relatively small scales. Nevertheless, most extreme precipitation indices show increases in the South Asia average, consistent with globally averaged results. The indices trends are further studied in the context of Atmospheric Brown Clouds (ABCs) over the region. Countries falling within the ABC hotspot namely Indo-Gangetic Plain (IGP) have shown a different behaviour on the trends of extreme indices compared with the parts outside this hotspot. IGP has increased temperature and decreased rainfall and tally closely with the actual trends.

Spatio‐temporal characteristics of the recent rainfall recovery in West Africa

Abstract: Using daily (monthly) rainfall data from 167 (254) stations across West Africa with at least 80% data availability for the 31-year period 1980–2010 and the gridded African Rainfall Climatology Version 2 (ARC2) for the period 1983–2010, linear trends in yearly and monthly rainfall totals were investigated. Measures of the Expert Team on Climate Change Detection and Indices (ETCCDI) and two rainy season onset and retreat definitions were employed to assess the corresponding trends in frequency and intensity of daily rainfall and changes to monsoon season length. A rotated Empirical Orthogonal Function analysis yielded two homogeneous rainfall regions, the Sahel and Guinea Coast, in terms of interannual to decadal rainfall variability, and this led to analysis of station data and Standardised Precipitation Index for the two regions. Results show that the majority of stations in the Sahel between the West Coast and 15°E shows a statistically significant positive rainfall trend for annual totals. The August–October period exhibits the largest rainfall recovery in the Sahel and the date of the retreat of the rainy season significantly moved later into the year by 2 days decade−1. The recovery is reflected both in more rainy days associated with longer wet spell duration and more extreme rainfall events. Trends along the Guinea Coast are weak and non-significant except for extreme rainfall related indices. This missing significance is partly related to the hiatus in rainfall increase in the 1990s, but also to the larger interannual rainfall variability. However, the tendency towards a more intense second rainy season suggests a later withdrawal of rains from the West African subcontinent. ARC2 trends are broadly consistent where ground calibration was undertaken, but are dubious for Nigeria and Ghana, and especially for the Guinea, Jos and Cameroon Line highlands due to missing gauge data.

Recent seasonal asymmetric changes in the NAO (a marked summer decline and increased winter variability) and associated changes in the AO and Greenland Blocking Index

Abstract: Recent changes are found in the means and variability of the North Atlantic Oscillation (NAO) index. There has been a sustained significant recent decrease in the summer NAO since the 1990s and, at the same time, a striking increase in variability of the winter – especially December – NAO that resulted in three of five (two of five) record high (record low) NAO Decembers occurring during 2004–2013 in the 115-year record. These NAO changes are related to an increasing trend in the Greenland Blocking Index (GBI, high pressure over Greenland) in summer and a more variable GBI in December. The enhanced early winter NAO variability originates mainly at the southern node of the NAO but is also related to the more variable GBI in December. Transition seasons (spring and autumn) have remained relatively unchanged over the last 30 years. These results are corroborated using several NAO indices. The Arctic Oscillation (AO) index, although strongly correlated with the NAO, does not show the recent sustained significant summer decrease, but it does show enhanced early winter variability. These recent observed changes are not present in the current generation of global climate models, although the latest process studies do offer insight into their causes. We invoke several plausible climate forcings and feedbacks to explain the recent NAO changes.

Wind climate estimation using WRF model output: method and model sensitivities over the sea

Abstract: High-quality tall mast and wind lidar measurements over the North and Baltic Seas are used to validate the wind climatology produced from winds simulated by the Weather, Research and Forecasting (WRF) model in analysis mode. Biases in annual mean wind speed between model and observations at heights around 100 m are smaller than 3.2% at offshore sites, except for those that are affected by the wake of a wind farm or the coastline. These biases are smaller than those obtained by using winds directly from the reanalysis. We study the sensitivity of the WRF-simulated wind climatology to various model setup parameters. The results of the year-long sensitivity simulations show that the long-term mean wind speed simulated by the WRF model offshore in the region studied is quite insensitive to the global reanalysis, the number of vertical levels, and the horizontal resolution of the sea surface temperature used as lower boundary conditions. Also, the strength and form (grid vs spectral) of the nudging is quite irrelevant for the mean wind speed at 100 m. Large sensitivity is found to the choice of boundary layer parametrization, and to the length of the period that is discarded as spin-up to produce a wind climatology. It is found that the spin-up period for the boundary layer winds is likely larger than 12 h over land and could affect the wind climatology for points offshore for quite a distance downstream from the coast.

Towards identifying areas at climatological risk of desertification using the Köppen–Geiger classification and FAO aridity index

Abstract: Over the past decades, a continuous rise in global air temperatures resulted in significant changes in the global hydrological cycle. Regionally increased frequencies of extreme weather events and changes in the regional extent of drylands resulted in new areas at risk of desertification, a complex process driven by socio-economic and climate-related factors. Although desertification is not confined to drylands, they are the most vulnerable to land degradation processes. To investigate possible changes in climate patterns over the past 60 years, we couple the information obtained from the Koppen–Geiger (KG) climate classification and the FAO aridity index (AI), providing an overview of the most evident global changes in climate regimes from 1951–1980 to 1981–2010 and focussing on the modifications of the extent of drylands. KG and AI indicators have been computed on a 0.5° × 0.5° global grid using precipitation data from the Full Data Reanalysis (v6.0) of the Global Precipitation Climatology Centre, and mean temperature and potential evapotranspiration data from the Climate Research Unit of the University of East Anglia (CRUTSv3.20). Both KG and AI show that the arid areas globally increased between 1951–1980 and 1981–2010, but decreased on average in the Americas. North-Eastern Brazil, Southern Argentina, the Sahel, Zambia and Zimbabwe, the Mediterranean area, North-Eastern China and Sub-Himalayan India have been identified as areas with a significant increase of drylands extent. An analysis of the scientific literature gives evidence that most of the areas identified are effectively undergoing desertification, thus confirming the validity of AI and KG to highlight the areas under risk of desertification. We also discuss the global decrease of cold areas, the progressive change from continental to temperate climate in Central Europe, the shift from tundra to continental climate in Alaska, Canada and North-Eastern Russia and the widening of the tropical belt.

Observed changes in southwest monsoon rainfall over India during 1901–2011

Abstract: The trends and epochal variability of southwest monsoon over the country as a whole and four homogeneous regions are examined using monthly rainfall data (1901-2011) of 640 political districts of India. The district rainfall data is computed from station rainfall data. The same station data is used to analyse the trends in the frequency of rainfall events of different intensities for examining extreme rainfall events. The existence of the multidecadal epochal variability of rainfall is clearly established in the all-India monsoon rainfall as well as monsoon rainfall over the four homogenous regions. However, over different homogenous regions, the phases of multidecadal variability are found to be different. Principal component analysis brings out Northeast India (NEI) rainfall as more dominant mode for all-India rainfall. Signi cant decrease in southwest monsoon rainfall over NEI is observed during the post 1950 period. Decreasing trends are also observed over the monsoon core region during the post-1950 period. Over these regions, monsoon rainfall has increased signi cantly during the pre-1950 period. It has been shown that the decreasing trend in monsoon rainfall during the post 1950 period is the result of multidecadal epochal variability. Geographical regions that experienced signi cant changes in the frequency of days of rainfall with different intensities are also identi ed. Signi cant change/turning points are also detected in the southwest monsoon rainfall. Frequency of moderate rainfall events (5mm fdaily rainfall 100mm) or very heavy rain (daily rainfall >150mm) during the southwest monsoon season. Climatic shift or change point in monsoon rainfall in India is also detected by an established statistical test.

European degree‐day climatologies and trends for the period 1951–2011

Abstract: The global increase of temperature, together with more frequent severe winters and summer heat waves may lead to a change in energy consumption and agricultural production. Cooling, heating, and growing degree-days (CDD, HDD, and GDD), respectively, are used to quantify the energy needed to condition or heat buildings, and to study the growing season. Using a new dataset made of 4023 daily TN–TM–TX series for the period 2001–2011 and 3897 monthly TM homogenized series for the period 1951–2011, we computed CDD, HDD, GDD, and Winkler Index (WI) for Europe. We developed a model that correlates degree-days calculated with daily TN–TM–TX data with degree-days obtained by monthly TM data, in the overlapping period 2001–2011. A set of parameters for each station was then applied to the corresponding 1951–2011 monthly records. We interpolated the parameters and the reconstructed degree-day series onto a European 0.25° × 0.25° grid: with these gridded parameters, one can estimate the degree-days for any European location if only monthly TM is available. We present maps of HDD, CDD, GDD, and WI for the period 1951–2010. To validate them, we run a comparison in the Carpathian area using an independent dataset (from the CARPATCLIM project). The regional records show high correlations, especially for HDD (r > 0.99) and WI (r > 0.98). Subsequently, we performed a linear trend analysis on European and regional basis. HDD showed a significant decrease almost everywhere in Europe, whereas CDD, GDD, and WI showed a significant increase in particular in the last 30 years in the Mediterranean region. Moreover, WI indicated that new areas in France and central Europe became suitable for grape cultivation in the last decades.

Comparative analysis of the ability of a set of CMIP3 and CMIP5 global climate models to represent precipitation in South America

Abstract: The purpose of this study is to evaluate the ability of two sets of global climate models (GCMs) derived from the Coupled Model Intercomparison Projects Phase 3 (CMIP3) and Phase 5 (CMIP5) to represent the summer, winter, and annual precipitation mean patterns in South America south of the equator and in three particular sub-regions, between years 1960 and 1999. Different metrics (relative bias, spatial correlation, RMSE, and relative errors) were calculated and compared between both projects to determine if there has been improvement from CMIP3 to CMIP5 models in the representation of regional rainfall. Results from this analysis indicate that for the analysed seasons, precipitation simulated by both CMIP3 and CMIP5 models' ensembles exhibited some differences. In DJF, the relative bias over Amazonia, central South America, eastern Argentina, and Uruguay is reduced in CMIP5 compared with CMIP3. In JJA, the same occurs in some areas of Amazonia. Annual precipitation is also better represented by the CMIP5 than CMIP3 GCMs as they underestimate precipitation to a lesser extent, although in NE Brazil the overestimation values are much larger in CMIP5 than in CMIP3 analysis. In line with previous studies, the multi-model ensembles show the best representation of the observed patterns in most seasons and regions. Only in some cases, single GCMs [MIROC3.2(hires) – CMIP3– and MIROC4h – CMIP5] presented better results than the ensemble. The high horizontal resolution of these models suggests that this could be a relevant issue for a more adequate estimation of rainfall at least in the analysed regions.

Shamals and climate variability in the Northern Arabian/Persian Gulf from 1973 to 2012

Abstract: This paper presents key results from analysis of surface meteorological observations collected in the Northern Arabian/Persian Gulf (N Gulf; Kuwait, Bahrain, and NE Saudi Arabia), which spans a 40-years period (1973–2012). The first part of this study analyzes climate variability in the N Gulf, and relates them to teleconnection patterns (North Atlantic Oscillation, El Nino Southern Oscillation, and Indian Ocean Dipole). Results of the analysis indicate that during the study period the climate in the region experienced a general trend of increase in temperature (0.8°C), decrease in barometric pressure (1 mbar), reduction in humidity (6%), and decrease in visibility (9%). Significant correlations were found between the three teleconnection patterns and the meteorological conditions suggesting that seasonal variabilities in air temperature, barometric pressure, and precipitation are closely related to the teleconnection patterns. The second part of this study examines the 40-year variability of Shamal events (strong NW winds that commonly generate significant dust storms). The data suggests that on average Shamal events occur at a rate of 10 events year–1 with 85% of the events occurring during the summer and winter. The number of these events has increased in the past 14 years of the study period. These events resulted in abrupt changes in meteorological conditions: an increase in wind speed of 2.7 m s–1, a decrease in visibility of 1.7 km, and reduction in humidity of 4.3%. Seasonal variations in temperature (an increase in temperature during summer of 0.8°C, and a decrease of 1.5°C during winter) and barometric pressure (a decrease in barometric pressure during summer of 0.6 mbar and an increase of 7.8 mbar during winter) were observed during Shamal events.

Projections of climate change in the Mediterranean Basin by using downscaled global climate model outputs

Abstract: The Mediterranean Basin is one of the regions that shall be affected most by the impacts of the future climate changes on hydrology and water resources. In this study, projected future changes in mean air temperature and precipitation climatology and inter-annual variability over the Mediterranean region were studied. For performing this aim, the future changes in annual and seasonal averages for the future period of 2070-2100 with respect to the period from 1970 to 2000 were investigated. Global climate model outputs of the World Climate Research Program's Coupled Model Intercomparison Project Phase 3 multi-model dataset were used in this work. Intergovernmental Panel on Climate Change SRES A2, A1B and B1 emission scenarios' outputs were used in future climate model projections. Future surface mean air temperatures of the larger Mediterranean basin increase mostly in summer and least in winter, and precipitation amounts decrease in all seasons at almost all parts of the basin. Future climate signals for air temperature and total precipitation values are much larger than the inter-model standard deviation. Inter-annual temperature variability increases evidently in summer season and decreases in the northern part of the domain in the winter season, while precipitation variability increases in almost all parts of domain. Probability distribution functions are found to be shifted and flattened for future period compared to the reference period. This indicates that the occurrence of frequency and intensity of high temperatures and heavy precipitation events will likely increase in the future period.

Evaluation of extreme climate events using a regional climate model for China

Abstract: Extreme climate events over China at the end of the 21st century (2080–2099) are investigated using the regional climate model RegCM4. Model performance is validated through comparison between observations and simulations over the period 1985–2005. The results show that RegCM4 can satisfactorily reproduce the spatial distribution of extreme climate events over China. The model simulates temperature extremes more accurately than precipitation. Under the RCP8.5 (high emission) scenario, the number of frost days decreases, and both the heat wave duration index and the growing season length increase dramatically towards the end of the 21st century. Changes in extreme temperature become increasingly pronounced from South to North China, with the most significant changes occurring on the Tibetan Plateau (TP). The proportion of heavy precipitation generally increases, except on the southern TP. The number of very heavy precipitation days increases by 25–50% in Northwest and East China. In winter, the number of consecutive dry days (CDD) decreases in North China and increases in South China. The greatest increases in CDD are found in June, July and August (JJA) in Southwest China. In a future that follows this scenario, drought events may be aggravated in Southwest China, and decrease in North China. In contrast, when repeating these projections under the assumption of the RCP4.5 scenario for emissions, the frequency of extreme climate events is reduced. These results suggest that reductions in greenhouse gas emissions may mitigate the effects of climate change over the coming decades.

Trend analysis of rainfall in four meteorological subdivisions of southern India using nonparametric methods and discrete wavelet transforms

Abstract: In recent times, trend analysis and change point detection in hydroclimatic variables receiving significant attention due to climate change and its socioeconomic consequences. In this study, long-term trends of rainfall in four subdivisions of southern India namely Kerala, Tamil Nadu, North Interior (NI) Karnataka and Telangana regions are analysed using linear regression, nonparametric Mann–Kendall (MK) test and Sen's slope estimator methods. Trend analysis of annual rainfall time series shows an increasing trend in three subdivisions – Tamil Nadu, NI Karnataka and Telangana, and a decreasing trend in Kerala subdivision. Further the sequential change in trend of annual and seasonal rainfalls in the four subdivisions is conducted using sequential MK (SQMK) method. The SQMK analysis shows an early divergence of progressive and retrograde modes of post-monsoon rainfall of Kerala and winter rainfall of Telangana subdivisions. Further it is observed that among different seasonal rainfalls, the post-monsoon rainfall of Kerala subdivision shows a statistically significant increase in the recent past. Then the trend analysis based on discrete wavelet transform (DWT) in conjunction with SQMK method is performed on the post-monsoon rainfall time series of Kerala subdivision, and the results show that there is a dominancy of short-term periodicity of less than a decade in the subdivision.

The alleviating trend of drought in the Huang-Huai-Hai Plain of China based on the daily SPEI

Abstract: Drought is a major natural hazard that can have devastating impacts on regional agriculture, water resources and the environment. To assess the variability and pattern of drought characteristics in the Huang-Huai-Hai (HHH) Plain, the daily Standardized Precipitation Evapotranspiration Index (SPEI) is developed based on daily meteorological data in this study. The daily SPEI data are used, including Annual Total Drought Severity (ATDS), Annual Total Drought Duration (ATDD) and Annual Drought Frequency (ADF), which were calculated from 1981 to 2010 at 28 meteorological stations. We used the indices (ATDS, ATDD and ADF), Hovmoller diagrams and the reliable no parameter statistical methods of the Mann–Kendall test to assess the variability and pattern of drought characteristics for the period from 1981 to 2010 in the HHH plain. The results suggested that severe drought occurred in the 1980s, the late 1990s and the early 2000s, severe drought events occurred in 1981, 1986, 1997 and 2002. Decreasing trends for both ATDS and ATDD were found, and the drought situation did not worsen under global warming during the past 30 years, and the drought situation is alleviating in the entire HHH plain. The northeast and southwest regions of the HHH plain have suffered from more severe drought, and the north region is prone to drought. The results of the study can provide a scientific understanding for the adoption of countermeasures of regional defence against drought and also may serve as a reference point for drought hazard vulnerability analysis.

Heat and cold waves trends in the Carpathian Region from 1961 to 2010

Abstract: The past two decades of the 20th century and the first of the 21st century have been characterized by global temperature rise and increased frequency of weather-induced extreme events such as floods, droughts, heavy rainfall, and heat waves. We investigated the heat and the cold waves in the Carpathian Region, an area whose rich biosphere is endangered by extreme events. We used the daily minimum (TN) and maximum (TX) temperature data collected in the framework of the CARPATCLIM project. Such high-resolution (0.1° × 0.1°) gridded data range from January 1961 to December 2010. In this study, a heat wave occurs when temperature is above the 90th percentile for at least five consecutive days and a cold wave occurs when temperature is below the 10th percentile for at least five consecutive days. The percentiles have been computed over the baseline period 1971–2000. We distinguish between night-time and daytime events and we discuss heat (and cold) waves considering at least five consecutive night and days with temperature above (below) the selected percentile. For each heat or cold wave event, we assigned duration, severity, and intensity. For these parameters and for frequency, we performed linear trend analysis for the period 1961–2010. The trends have been computed on an annual and seasonal basis and tested for statistical significance. Different spatial patterns of heat and cold waves characterize the Carpathian Region: heat wave events show general increase in all the parameters considered, while cold wave events show a decrease in all the variables West to the Carpathians and an increase North–East to the Carpathians. We also compiled a list of the most relevant heat waves that hit the Carpathian Region from 1961 to 2010: out of seven events, four occurred from 2000 to 2010. Instead, the 1960s and the 1980s have been the decades most hit by severe cold waves.

Precipitation bias variability versus various gauges under different climatic conditions over the Third Pole Environment (TPE) region

Abstract: An international programme dedicated to the study of the Third Pole Environment (TPE) is now developing. The TPE region is centred on the Tibetan Plateau and concerns the interests of the surrounding countries and regions. To improve input for hydrological research, we collected precipitation data on 241 meteorological stations across the TPE region; these data were obtained from various countries, thus including various types of gauges. Employing the procedure recommended by the World Meteorological Organization (WMO), a full version of bias adjustment was applied to the data, including adjustments for wind-induced error, wetting loss, evaporation loss and trace amount for each station. The results reveal that the average annual precipitation has increased considerably from a minimum of 4 mm to a maximum of 409 mm with an overall mean of 27% from the adjustment, the largest bias being found in the Chinese standard precipitation gauge (CSPG) which was used in the central TPE region. In addition, the bias shows variable spatial and temporal patterns in different climate zones throughout this area. It is expected that this study and its results will be beneficial for hydrological and climatic studies over the TPE region.

Projected changes in temperature and precipitation in ten river basins over China in 21st century

Abstract: Present and future climate change information is required to develop adaptation and mitigation strategies at national and international levels. This study assessed the simulated surface air temperature (SAT) and precipitation (PR) over China from 24 models involved in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The reliability ensemble average (REA) is applied to project the SAT and PR change under representative concentration pathway (RCP) scenarios over China in the 21st century. The results show that most CMIP5 models tend to underestimate SAT and overestimate PR in China. Models generally agree better with the observed SAT than PR. For SAT, the ensemble prediction shows that warming is expected all over China for all RCPs. The warming trend from 2006 to 2099 in China is 0.87 ± 0.14 °C 100 year−1, 2.47 ± 0.48 °C 100 year−1, 5.85 ± 0.73 °C 100 year−1 for RCP 2.6, RCP 4.5 and RCP 8.5, respectively. Northern regions experience more warming than southern regions. The Songhua River basin warms the most, considering the ten studied basins for RCP 4.5 and RCP 8.5. Under RCP 2.6, the largest warming trend occurs in the Huaihe River basin. For PR, the spatial pattern of PR change has zonal characteristics. The girds with the maximum linear trend, i.e. >7.5 mm decade−1, are concentrated in the upper Yangtze River basin. For temporal scale, PR in China is also projected to increase during the 21st century by 4.89 ± 2.30% 100 year−1, 8.67 ± 6.27% 100 year−1 and 13.39 ± 12.58% 100 year−1 for RCP 2.6, RCP 4.5 and RCP 8.5, respectively. PR tends to decrease in the Yangtze River basin, Southeast River Drainage and Pearl River basin during the early period (2011–2030) for all RCPs, largely increase thereafter. However, uncertainties are unavoidable for SAT and PR projections. The PR uncertainty exceeds the temperature uncertainty. More studies regarding the analysis of narrowing uncertainties are essential for a better understanding of climate change.

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

Abstract: 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.

Drivers of North Atlantic Polar Front jet stream variability

Abstract: Polar front jet stream variability is responsible for instances of extreme weather and is crucial for regional climate change. The North Atlantic Polar Front jet stream is of particular significance to the heavily populated areas of western Europe and eastern North America as storm track variability, atmospheric modes of variability such as the North Atlantic Oscillation (NAO), temperature and rainfall are all intimately linked with jet stream changes. Although seasonal and interannual variability are often attributed to internal variability, there are several possible drivers of polar front jet stream changes that are reviewed in this study. Cryospheric effects from sea-ice extent and snow cover, oceanic effects from North Atlantic sea-surface temperatures and tropical influences such as the El-NiA±o Southern Oscillation, and stratospheric effects due to stratospheric circulation variability, solar variability, volcanic eruptions and the Quasi-Biennial Oscillation are all identified in the literature as factors that impact on the Atlantic Polar Front jet stream. These drivers of jet stream variability can oppose or reinforce one another, and there are some indications of possible nonlinear interactions between them. We also review the modelling of jet stream variability. While a consensus has now been reached that some observed drivers can be reproduced in climate models, we conclude that improved understanding of more recently identified drivers of the Atlantic extratropical jet stream is crucial for making progress in regional climate predictions on all timescales from months to decades ahead. © 2015 Royal Meteorological Society.

Greenland precipitation trends in a long-term instrumental climate context (1890-2012): evaluation of coastal and ice core records

Abstract: Here, we present an analysis of monthly, seasonal, and annual long-term precipitation time-series compiled from coastal meteorological stations in Greenland and Greenland Ice Sheet (GrIS) ice cores (including three new ice core records from ACT11D, Tunu2013, and Summit2010). The dataset covers the period from 1890 to 2012, a period of climate warming. For approximately the first decade of the new millennium (2001-2012) minimum and maximum mean annual precipitation conditions are found in Northeast Greenland (Tunu2013 c. 120mm water equivalent (w.e.) year(-1)) and South Greenland (Ikerasassuaq: c. 2300mm w.e. year(-1)), respectively. The coastal meteorological stations showed on average increasing trends for 1890-2012 (3.5mm w.e. year(-2)) and 1961-2012 (1.3mm w.e. year(-2)). Years with high coastal annual precipitation also had a: (1) significant high number of precipitation days (r(2) = 0.59); and (2) high precipitation intensity measured as 24-h precipitation (r(2) = 0.54). For the GrIS the precipitation estimated from ice cores increased on average by 0.1mm w.e. year(-2) (1890-2000), showing an antiphase variability in precipitation trends between the GrIS and the coastal regions. Around 1960 a major shift occurred in the precipitation pattern towards wetter precipitation conditions for coastal Greenland, while drier conditions became more prevalent on the GrIS. Differences in precipitation trends indicate a heterogeneous spatial distribution of precipitation in Greenland. An Empirical Orthogonal Function analysis reveals a spatiotemporal cycle of precipitation that is linked instantaneously to the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation and with an approximate to 6 years lag time response to the Greenland Blocking Index.

Long‐term variability of the East African ‘short rains’ and its links to large‐scale factors

Abstract: This study utilizes a new 139-year rainfall record for East Africa to evaluate the relationship between the ‘short rains’ of October–November and four tropical indices. These indices include the zonal winds at the surface and 200 mb over the central equatorial Indian Ocean, Nino 3.4 and the Indian Ocean Zonal Mode (IOZM). The relationships with these indices are time dependent, as are the relationships among the indices. These change markedly on a decadal timescale, consistent with regime changes indicated by other authors, and the links to El Nino-Southern Oscillation (ENSO) and the IOZM appear to be weaker than those suggested by previous studies. The zonal winds show the strongest and most consistent relationships with October–November rainfall. However, the relationships are very different for wet and dry years, and the zonal winds play a stronger role in producing wet conditions. Further, several factors appear to act in tandem to produce extremely wet years, but appear to act largely independently in producing drought. The links to drought have been markedly weaker since 1982. These links were also very weak roughly between 1920 and 1960, when apparently the Walker cell over the Indian Ocean was very weak and the Pacific Walker cell particularly strong. At that time, ENSO appeared to drive most of the variability of October–November rainfall, interannual variability was weak, and the rainfall was below average during most of that period. When the zonal circulation in the Indian Ocean sector became well-developed c. 1961 and the Pacific cell weakened, both the rainfall and its interannual variability markedly increased. Overall, this study stresses the time dependence of the various relationships with East African October–November rainfall. This has strong implications for seasonal forecasting.

Variability of extreme precipitation over Yunnan Province, China 1960-2012

Abstract: This study investigated spatial and temporal variations of extreme precipitation over Yunnan Province during 1960–2012. On the basis of a dataset from 120 meteorological stations covering the region, ten precipitation indices derived from daily precipitation were computed and analysed. Our results indicate the precipitation indices showed spatially complex trends. Most precipitation indices present increasing trends in western Yunnan and decreasing trends in eastern Yunnan. The western, southern and central regions experienced an increase in consecutive dry days (CDDs) and decrease in consecutive wet days (CWDs). In addition, a widespread increase was also found in precipitation intensity over Yunnan. On a region-wide scale, a weak decrease was observed in total precipitation, accompanied by an increase in precipitation intensity. CDDs tended to be prolonged while the CWDs tended to be shortened. The days with precipitation amounts totaling more than 10 mm and maximum 5-day precipitation amount had decreasing but not significant trends. In contrast, insignificant increases were found for the maximum 1-day precipitation and annual total precipitation exceeding 95th and 99th percentiles. The contribution of extreme precipitation to total precipitation increased during 1960–2012. Overall, occurrences of extreme precipitation are more concentrated in time. The weakening of the Asian summer monsoon strength and local topography had contribution to the variations of extreme precipitation over Yunnan. However, the forcing mechanisms are very complicated and need to be studied in subsequent work.

Changes in climate extreme events in China associated with warming

Abstract: The science that humans are the cause of global warming, and that the associated climate change would lead to serious changes in climate extreme events, food production, freshwater resources, biodiversity, human mortality, etc. is unequivocal. After several political negotiations, a 2 °C warming has been considered to be the benchmark for such damaging changes. However, an increasing amount of scientific research indicates that higher levels of warming are increasingly likely. What would the world be like if such higher levels of warming occurred? This study aims to provide information for better politically driven mitigation through an investigation of the changes in temperature- and precipitation-based extreme indices using CMIP5 (coupled model intercomparison project phase 5) simulations of a warming of 1, 2, and 3 °C in China. Warming simulations show more dramatic effects in China compared with the global average. In general, the results show relatively small change signals in climate extreme events in China at 1 °C, larger anomalies at 2 °C, and stronger and more extended anomalies at 3 °C. Changes in the studied temperature indices indicate that warm events would be more frequent and stronger in the future, and that cold events would be reduced and weakened. For changes in the precipitation indices, extreme precipitation generally increases faster than total wet-day precipitation, and China will experience more intensified extreme precipitation events. Furthermore, the risk of flooding is projected to increase, and the dry conditions over northern China are projected to be mitigated. In certain regions, particularly Southwest China, the risks of both drought and flood events would likely increase despite the decreased total precipitation in the future. Uncertainties mainly derived from inter-model and scenario variabilities are attached to these projections, but a high model agreement can be generally observed in the likelihood of these extreme changes.

NDVI and vegetation phenology dynamics under the influence of sunshine duration on the Tibetan plateau

Abstract: Climate change has significantly influenced vegetation dynamics on the Tibetan Plateau (TP). Past research mainly focused on vegetation responses to temperature variation and water stress, but the influence of sunshine duration on NDVI and vegetation phenology on the TP is not well understood. In this study, NDVI time series from 1982–2008 were used to retrieve spatiotemporal vegetation dynamics on the TP. Empirical orthogonal function (EOF) analysis was conducted to understand the spatiotemporal variations of NDVI. The Start of Season (SOS) was estimated from NDVI time series with a local threshold method. The first EOF, accounting for 35.1% of NDVI variations on the TP, indicates that NDVI variations are larger in areas with shorter sunshine duration. The needle-leaved forest and shrub in the southeastern TP are more sensitive to sunshine duration anomalies (p < 0.01) than broad-leaved forest, steppe, and meadow due to spatial and altitudinal distribution of sunshine duration and vegetation types. The decrease in sunshine duration for the growing season on the TP has resulted in a decreased NDVI trend in some areas of southeastern TP (p ranging from 0.32-0.05 with threshold ranging from 0.05 to 0.25) in spite of the overall NDVI increase. SOS dynamics in most parts of the TP were mainly related to temperature variability, with precipitation and sunshine duration playing a role in a few regions. This study enhances our understanding of vegetation responses to climatic change on the TP.

Elevation‐dependent relationships between climate change and grassland vegetation variation across the Qinghai‐Xizang Plateau

Abstract: As one of the most sensitive regions to climate change, the Qinghai-Xizang Plateau has been widely investigated as one unity for impacts of climate change on alpine grassland. However, previous findings might be confounded by distinct climate sensitivities at different elevations and different regional climates between Qinghai Province and Xizang Province, which lie at the two sides of Tanggula Mountains. In this study, we explored change trends of grassland vegetation, temperature and precipitation in growing season from 1982 to 2011, and elevation-dependent effects of climate change on grassland vegetation in the two provinces separately. The plateau grassland greenness gained improvement under climate warming and wetting during the past 30 years, especially in Qinghai Province. Temperature increased significantly with a warming magnitude of more than 1.5 degrees C over the plateau grassland. The interannual change of precipitation showed contrary trends between the two provinces. The main climate factor driving the grassland vegetation variation varied between the two provinces, with temperature being the main factor in Qinghai Province and precipitation being the main factor in Xizang Province. In particular, a more significant correlation between climate change and grassland vegetation variation was found at higher elevations, which reveals higher climate sensitivity in higher elevation areas of the plateau.

A new catalogue of tropical cyclones of the northern Bay of Bengal and the distribution and effects of selected landfalling events in Bangladesh

Abstract: Tropical cyclones devastate large areas, take numerous lives and damage extensive property in Bangladesh. Research on landfalling tropical cyclones affecting Bangladesh has primarily focused on events occurring since AD 1960 with limited work examining earlier historical records. We rectify this gap by developing a new tropical cyclone catalogue that maximizes the use of available sources. The catalogue consists of 304 tropical cyclones that occurred between AD 1000 and AD 2009 and made landfall along the coasts of Bangladesh, eastern India and Myanmar. One hundred and ninety-three events directly struck Bangladesh between AD 1484 and AD 2009, although the precise landfall location of six events is unknown. Of the remaining 187 events, Cox's Bazar, Chittagong, Noakhali, Barisal and Khulna were struck by 30, 46, 19, 41 and 51 tropical cyclones, respectively. There is a paucity of data about tropical cyclones before AD 1900 and this increases the further back in time we go. Inconsistencies in reported storm surge height, wind speed and exaggerations in the reporting of deaths are identified and discussed. Some 20 72 509 human deaths in Bangladesh are associated with 71 tropical cyclones that occurred between AD 1484 and AD 2009. Between AD 1923 and AD 2009, 11 tropical cyclones caused 94 35 000 people to become homeless and between AD 1961 and AD 2009, 10 tropical cyclones resulted in economic damage of over US$ 4.6 billion. Analysis of the deaths and damage associated with tropical cyclones in AD 1970, AD 1991 and AD 2007 indicates that while the number of deaths decreased between events, economic damage and the number of people made homeless increased. There are positive and significant correlations between increasing storm surge height and increasing human fatalities (r = 0.60, p < 0.01) and increasing human injuries and greater wind speed (r = 0.45, p < 0.01). Despite our best efforts, the catalogue is incomplete. As such, we suggest further ‘deep’ archival research coupled with regional geological studies of palaeostorm events to gain a more sophisticated understanding of the hazard. Our results have implications for both risk assessment and disaster risk reduction.