Observed variability and trends in extreme temperature indices and rice–wheat productivity over two districts of Bihar, India—a case study

The purpose of this paper is to analyze the trends and variability in extreme temperature indices and its impact on rice–wheat productivity over two districts of Bihar, India, which is part of the middle Indo-Gangetic Basin. Mann–Kendall non-parametric test was employed for detection of trend and Sen slope was determined to quantify the magnitude of such trends. We have analyzed 10 extreme temperature indices for monthly and seasonally. The influence of extreme temperature indices on rice–wheat productivity was determined using correlation analysis. As far as Patna is concerned, if the number of cool days during September ≥10, the rice productivity will increase due to the availability of sufficient duration to fill up the grain. However, higher warm days during all the months except June will affect the productivity. A significant negative correlation was noticed between maximum value of minimum temperature during September and rice productivity. Highly significant positive correlation was noticed between number of cool days during September with rice productivity while it was highly significant negative correlation in the case of number of warm days during the same month. As far as Samastipur is concerned, a negative correlation was noticed between wheat productivity and maximum value of maximum temperature (TXx) during February, but not statistically significant. The higher temperature may affect the kernel weight and thereby yield. It is seen that a critical value of TXx ≥29.2 °C will be harmful to wheat crop during February. A significant positive correlation of number of cool nights with wheat productivity also supports the above relationship. The critical values of extreme temperature indices during rice and wheat growing months provide an indicator to assess the vulnerability of rice–wheat productivity to temperature for Patna and Samastipur districts and there is a need to prepare an adaptive strategy and also develop thermo-insensitive rice–wheat high yielding varieties suitable for this region to sustain rice–wheat productivity under projected climate change situation.     

Changes in extreme daily rainfall for São Paulo, Brazil

Significant positive trends are found in the evolution of daily rainfall extremes in the city of São Paulo (Brazil) from 1933 to 2010. Climatic indices including ENSO, PDO, NAO and the sea surface temperature at the coast near São Paulo explain 85 % of the increasing frequency of extremes during the dry season. During the wet season the climatic indices and the local sea surface temperature explain a smaller fraction of the total variance when compared to the dry season indicating that other factors such as the growth of the urban heat island and the role of air pollution in cloud microphysics need to be taken into account to explain the observed trends over the almost eight decades.     

Trends in extreme temperature indices in Huang-Huai-Hai River Basin of China during 1961–2014

Spatial and temporal characteristics of temperature extremes have been investigated in Huang-Huai-Hai (HHH) region based on the daily series of temperature observations from 162 meteorological stations. A total of 11 indices were used to assess the changes of temperature pattern. Linear trend analyses revealed that the daily maximum temperature (TXx) increased at α = 0.05 level with a magnitude of 0.15 °C per decade on the regional scale during the period of 1961–2014. More pronounced warming trend of the daily minimum temperature (TNn) was detected at a rate of 0.49 °C per decade (α = 0.01 level). Consequently, a decreasing trend of the temperature range of TXx and TNn (extreme temperature range) was observed. The frequency of hot days (TXf90) and annual average of warm events (warm spell duration indicator, WSDI) showed significant increasing trends, while that of cold nights (TNf10) and cold events (cold spell duration indicator, CSDI) showed opposite behaviors. Both warm winter (W-W) and hot summer (H-S) series displayed significant increasing trends at α = 0.01 confidence level. The cold winter (C-W) series showed a decreasing trend at α = 0.01 confidence level, while the cool summer (C-S) series showed a nonsignificant decreasing trend that is not passing the 90% confidence level (α = 0.1). Abrupt increments of warm­related extremes (TXx, TXf90, WSDI) have been detected since 1990s, and a steadily decreasing trend of cold related extremes (TNf10, CSDI) was found since 1970s. Ten hot summers out of 11 and nine warm winters out of 10 occurred after 1990s. Altitude has a large impact on spatial pattern of extreme temperature indices, and the urban heat island effect also has an impact on amplitude of variation in extreme temperature. Trend magnitudes are significantly larger at sites with high altitudes for warm­related indices (TXx, TXf90, WSDI), while those involving cold-related indices (TNn, TNf10) are remarkably larger for stations with low altitudes.     

Spatial and temporal variation in daily temperature indices in summer and winter seasons over India (1969–2012)

Spatial and temporal variations in summer and winter extreme temperature indices are studied by using daily maximum and minimum temperatures data from 227 surface meteorological stations well distributed over India for the period 1969–2012. For this purpose, time series for six extreme temperature indices namely, hot days (HD), very hot days (VHD), extremely hot days (EHD), cold nights (CN), very cold nights (VCN), and extremely cold nights (ECN) are calculated for all the stations. In addition, time series for mean extreme temperature indices of summer and winter seasons are also analyzed. Study reveals high variability in spatial distribution of threshold temperatures of extreme temperature indices over the country. In general, increasing trends are observed in summer hot days indices and decreasing trends in winter cold night indices over most parts of the country. The results obtained in this study indicate warming in summer maximum and winter minimum temperatures over India. Averaged over India, trends in summer hot days indices HD, VHD, and EHD are significantly increasing (+1.0, +0.64, and +0.32 days/decade, respectively) and winter cold night indices CN, VCN, and ECN are significantly decreasing (−0.93, −0.47, and −0.15 days/decade, respectively). Also, it is observed that the impact of extreme temperature is higher along the west coast for summer and east coast for winter.

     

Detecting rainfall trends in twentieth century (1871–2006) over Orissa State, India

Climate change has affected the temperature and rainfall characteristics worldwide. However, the changes are not equal for all regions and have localized intensity and must be quantified locally to manage the natural resources. Orissa is an eastern state in India where agricultural activities mainly depends on the rainfall and thus face problems due to changing patterns of rainfall due to changing climate. In the present study, attempts were made to study temporal variation in monthly, seasonal and annual rainfall over the state during the period from 1871 to 2006. Long term changes in rainfall characteristics were determined by both parametric and non-parametric tests. The analysis revealed a long term insignificant decline trend of annual as well as monsoon rainfall, where as increasing trend in post-monsoon season over the state of Orissa. Rainfall during winter and summer seasons showed an increasing trend. Statistically monsoon rainfall can be considered as very dependable as the coefficient of variation is 14.2%. However, there is decreasing monthly rainfall trend in June, July and September, where as increasing trend in August. This trend is more predominant in last 10?year. Based on departure from mean, rainfall analysis also showed an increased number of dry years compared to wet years after 1950. This changing rainfall trend during monsoon months is major concern for the rain-fed agriculture. More over, this will affect hydro power generation and reservoir operation in the region.     

Documentary reconstruction of monsoon rainfall variability over western India, 1781–1860

Investigations into the climatic forcings that affect the long-term variability of the Indian summer monsoon are constrained by a lack of reliable rainfall data prior to the late nineteenth century. Extensive qualitative and quantitative meteorological information for the pre-instrumental period exists within historical documents, although these materials have been largely unexplored. This paper presents the first reconstruction of monsoon variability using documentary sources, focussing on western India for the period 1781–1860. Three separate reconstructions are generated, for (1) Mumbai, (2) Pune and (3) the area of Gujarat bordering the Gulf of Khambat. A composite chronology is then produced from the three reconstructions, termed the Western India Monsoon Rainfall reconstruction (WIMR). The WIMR exhibits four periods of generally deficient monsoon rainfall (1780–1785, 1799–1806, 1830–1838 and 1845–1857) and three of above-normal rainfall (1788–1794, 1813–1828 and 1839–1844). The WIMR shows good correspondence with a dendroclimatic drought reconstruction for Kerala, although agreement with the western Indian portion of the tree-ring derived Monsoon Asia Drought Atlas is less strong. The reconstruction is used to examine the long-term relationship between the El Nino-Southern Oscillation (ENSO) and monsoon rainfall over western India. This exhibits peaks and troughs in correlation over time, suggesting a regular long-term fluctuation. This may be an internal oscillation in the ENSO-monsoon system or may be related to volcanic aerosol forcings. Further reconstructions of monsoon rainfall are necessary to validate this. The study highlights uncertainties in existing published rainfall records for 1817–1846 for western India.     

Monthly rainfall prediction using wavelet regression and neural network: an analysis of 1901–2002 data,Assam, India

Rainfall is a principal element of the hydrological cycle and its variability is important from both the scientific as well as practical point of view. Wavelet regression (WR) technique is proposed and developed to analyze and predict the rainfall forecast in this study. The WR model is improved combining two methods, discrete wavelet transform and linear regression model. This study uses rainfall data from 21 stations in Assam, India over 102 years from 1901 to 2002. The calibration and validation performance of the models is evaluated with appropriate statistical methods. The root mean square errors (RMSE), N-S index, and correlation coefficient (R) statistics were used for evaluating the accuracy of the WR models. The accuracy of the WR models was then compared with those of the artificial neural networks (ANN) models. The results of monthly rainfall series modeling indicate that the performances of wavelet regression models are found to be more accurate than the ANN models.     

Statistical characteristics,trends, and variability of rainfall in Shanxi province,China, during the period 1957–2019

Theoretical and Applied Climatology - Under the background of global warming, an analysis of the trend and variability of rainfall time series on various timescales is very important for...     

Observed changes in daily temperature and precipitation indices for southern Québec, 1960–2005

Abstract

Trends and variations in daily temperature and precipitation indices in southern Québec are examined for the period 1960–2005. The indices are based on daily temperature and daily precipitation which have been recently adjusted at 53 climatological stations. The adjustments were made for site relocation, changes in observing programs, known instrument changes and measurement program deficiencies. The results show that the surface air temperature has increased in southern Québec over 1960–2005. Significant warming is evident in the western, southern and central parts of the province but the increasing trends become smaller toward the east. The warming is greater during the winter although many significant increasing trends are found in the summer. The analysis of the temperature extremes strongly indicates the occurrence of more nights with extreme high temperatures in all seasons. The temperature indices also suggest an increase in the number of thaw/frost days during the winter (days with maximum temperature above 0°C and minimum temperature below 0°C), a decrease in the length of the frost season, an increase in the length of the growing season, a decrease in heating degree days and an increase in cooling degree days. The precipitation indices show an increase in the annual total rainfall although many stations indicate decreasing trends during the summer. The number of days with rain has increased over the region whereas the number of days with snow and the total snow amounts have decreased over the past 46 years.     

Past to future extreme events in Liverpool Bay: model projections from 1960–2100

Knowledge of the likely future wind, wave and surge climate in Liverpool Bay is of importance for coastal flood defence management. We examine a 140-year time series (1960–2100) of wind and wave model projections at the WaveNet buoy location in Liverpool Bay and also of surge model projection at two ports in Liverpool Bay, namely Liverpool and Heysham. To this end we use model projections from the UK Climate Projections 09 (UKCP09) programme. We use a medium emissions scenario ensemble from the HadCM3 climate model sensitivity tests. A continental shelf model (CS3) with ~12 km resolution was used to separately simulate the waves and the surge. The models are forced by hourly wind and pressure data from the Met Office (Hadley Centre) regional climate model (RCM). Swell wave boundary conditions are generated over the full Atlantic using global climate model (GCM) winds. Analysis of significant changes in the statistics over time shows that there is little change in extreme wave and surge conditions in Liverpool Bay. Although there is a slight increase in the severity of the most extreme events, the frequency of extreme wind and wave events is slightly reduced, while the frequency of extreme surge events slightly increases over the 140-year period. From the model projections, we find that the trends in the local wind are directly reflected in the wave field within Liverpool Bay. The trends in the skew surge projections deviate slightly from those in the wind patterns.     

The hourly gale record from Valentia Observatory,SW Ireland 1874–2008 and some observations on extreme wave heights in the NE Atlantic

The sustained hourly gale record from Valentia Observatory, SW Ireland over the time period from 1874–2006 shows very significant variations including high values in the 1920s, 1940s, 1960s and 1980s but a decline since then down to the lowest recorded levels at present. Most gales occur in winter and in particular in December and January. An analysis of the wind duration and speed data shows that there has been increased variability in the duration of gales over the last 20 years and despite an overall decline in mean wind speed there is no indication that gale strengths have changed in any systematic way. This gale data is strongly in contrast to the outputs and predictions from the various scenarios in the ECHAM4 models which predict at worst no changes in cyclonicity of depressions below 1,000 hPa but significant increases in cyclonicity of severe depressions below 940 hPa. At present the actual data is running contrary to the model outcomes at Valentia and elsewhere in Ireland. The sustained gales have given rise to wave heights in excess of 30 m and this documentary evidence is verified by more recent satellite and marine buoy data.     

Ice thickness variability in the Arctic Ocean between 1954–1990, results from a coupled ocean-ice-atmosphere column model

The interannual variation of the Arctic Ocean ice thickness during the period 1954–1990 is investigated by using a coupled ocean-ice-atmosphere column model. The model is forced by poleward energy flux in the atmosphere from NCEP/NCAR reanalysis data, ice export from satellite observations, cloudiness, and precipitation observed at the Russian North Pole drift stations. During the period 1977–1986 the model ice thickness decreased from 3.2 m to 2.0 m. The decrease is mainly caused by extra melting due to larger poleward energy flux in summer, and reduced ice growth in winter as a result of both increased cloudiness and energy flux. Precipitation and ice export are of less importance. A sensitivity study shows that the NCEP/NCAR data is accurate enough with respect to stochastic errors to ensure that the thinning is not caused by forcing errors. It is also shown that the poleward energy flux during summer is the dominant factor for regulating the ice thickness. The column model gives different results compared to other model studies using 2D ice models, especially towards the end of the period. Possible reasons for this disparity are discussed.     

Global warming and rainfall oscillation in the 5–10 yr band in Western Europe and Eastern North America

From joint wavelet analysis of long-wavelength baroclinic Rossby waves and SST anomalies in the 5–10?yr band in the North and tropical Atlantic, and Reduced Rainfall Height (RRH) in Western Europe and Eastern North America, some key mechanisms involved in the interannual rainfall variability are highlighted. Systematic work has been undertaken to highlight the resonance of long planetary waves in the tropical oceans. Quasi-stationary Waves (QSWs) are produced resulting from the combination of gravitational forces and trade wind stress or ENSO events to compensate for energy lost in the resonator and, above all, to produce a strong modulated output current at the open end, contributing to the western boundary currents. Gravitational forces are resulting from the topography of the surface of the ocean at the antinodes, the dimension of the basin and the wavelength of planetary waves involved in the resonance being of the same order of magnitude. Remote resonances occur at critical latitudes, nearly 40°N and 40°S, forming QSWs the role of which is crucial in the functioning of sub-tropical gyres. In the North Atlantic subtropical gyre, an 8-yr period QSW appears to have a decisive role in the interannual rainfall variability. The pattern of SST anomalies depends on buoyancy of the advected layer associated with this QSW, which is controlled by the amplitude and the phase of long-period sub-harmonics. Rainfall oscillation in Western Europe has occurred for some decades and extended as the dipole formed by SST anomalies on both antinodes became unbalanced, due to the emergence of the advected layer further north. Since then cyclonic or anticyclonic conditions are prevailing at midlatitudes, depending on the polarity. Strengthening of RRH anomalies in Eastern North America is attributed to the buoyancy of the advected layer that re-circulates along the sub-tropical gyre, which evidences the excitation of long-period sub-harmonics, too. Frequency of exceptional events increased in areas heavily exposed to RRH anomalies, subject to oceanic influences even during extreme events, as this occurs in the north of France. Changes in rainfall patterns is attributed to global warming, i.e. the resonance of long-period sub-harmonics associated with solar magnetic cycles whose amplitude has increased drastically at the end of the second millennium, not including the possible contribution of greenhouse gas emissions whose impact on climate is non-resonant.     

Spatial and temporal variability of precipitation indices during 1961–2010 in Hunan Province,central south China

Based on daily precipitation records at 75 meteorological stations in Hunan Province, central south China, the spatial and temporal variability of precipitation indices is analyzed during 1961–2010. For precipitation extremes, most of precipitation indices suggest that both the amount and the intensity of extreme precipitation are increasing, especially the mean precipitation amount on a wet day, showing a significant positive trend. Meanwhile, both of the monthly rainfall heterogeneity and the contribution of the days with the greatest rainfall show an upward trend. When it comes to rainfall erosivity, most of this province is characterized by high values of annual rainfall erosivity. Although the directions of trends in annual rainfall erosivity at most stations are upward, only 6 of the 75 stations have significant trends. Furthermore, the spatial and temporal variation of dryness/wetness has been assessed by the standardized precipitation index (SPI). The principal component analysis (PCA) was applied to the SPI series computed on 24-month time scales. The results demonstrated a noticeable spatial variability with three subregions characterized by different trends: a remarkable wet tendency prevails in the central and southern areas, while the northern areas are dominated by a remarkable dry tendency.