Trends In Minimum Temperatures Research Articles

Rice yield in response to climate trends and drought index in the Mun River Basin, Thailand

Rice yields in Thailand are among the lowest in Asia. In northeast Thailand where about 90% of rice cultivation is rain-fed, climate variability and change affect rice yields. Understanding climate characteristics and their impacts on the rice yield is important for establishing proper adaptation and mitigation measures to enhance productivity. In this paper, we investigate climatic conditions of the past 30years (1984–2013) and assess the impacts of the recent climate trends on rice yields in the Mun River Basin in northeast Thailand. We also analyze the relationship between rice yield and a drought indicator (Standardized Precipitation and Evapotranspiration Index, SPEI), and the impact of SPEI trends on the yield. Our results indicate that the total yield losses due to past climate trends are rather low, in the range of <50kg/ha per decade (3% of actual average yields). In general, increasing trends in minimum and maximum temperatures lead to modest yield losses. In contrast, precipitation and SPEI-1, i.e. SPEI based on one monthly data, show positive correlations with yields in all months, except in the wettest month (September). If increasing trends of temperatures during the growing season persist, a likely climate change scenario, there is high possibility that the yield losses will become more serious in future. In this paper, we show that the drought index SPEI-1 detects soil moisture deficiency and crop stress in rice better than precipitation or precipitation based indicators. Further, our results emphasize the importance of spatial and temporal resolutions in detecting climate trends and impacts on yields.

Observed warming over northern South America has an anthropogenic origin

We investigate whether the recently observed trends in daily maximum and minimum near-surface air temperature (Tmax and Tmin, respectively) over South America (SA) are consistent with the simulated response of Tmin and Tmax to anthropogenic forcing. Results indicate that the recently observed warming in the dry seasons is well beyond the range of natural (internal) variability. In the wet season the natural modes of variability explain a substantial portion of Tmin and Tmax variability. We demonstrate that the large-scale component of greenhouse gas (GHG) forcing is detectable in dry-seasonal warming. However, none of the global and regional climate change projections reproduce the observed warming of up to 0.6 K/Decade in Tmax in 1983–2012 over northern SA during the austral spring (SON). Thus, besides the global manifestation of GHG forcing, other external drivers have an imprint. Using aerosols-only forcing simulations, our results provide evidence that anthropogenic aerosols also have a detectable influence in SON and that the indirect effect of aerosols on cloud’s lifetime is more compatible with the observed record. In addition, there is an increasing trend in the observed incoming solar radiation over northern SA in SON, which is larger than expected from natural (internal) variability alone. We further show that in the dry seasons the spread of projected trends based on the RCP4.5 scenario derived from 30 CMIP5 models encompasses the observed area-averaged trends in Tmin and Tmax. This may imply that the observed excessive warming in the dry seasons serve as an illustration of plausible future expected change in the region.

Hydro-meteorological trends in the Gidabo catchment of the Rift Valley Lakes Basin of Ethiopia

The global and regional variability and changes of climate and stream flows are likely to have significant influence on water resource availability. The magnitude and impacts of climate variability and change differs spatially and temporally. This study examines the long term hydroclimatic changes, analyses of the hydro-climate variability and detect whether there exist significant trend or not in the Gidabo catchment, rift valley lakes basin of Ethiopia. Precipitation, temperature and stream flow time series data were used in monthly, seasonal and annual time scales. The precipitation and temperature data span is between 1982 and 2014 and that of stream flow is between 1976 and 2006. To detect trends the analysis were done by using Mann Kendal (MK), Sen's graphical method and to detect change point using the Pettit test. The comparison of trend analysis between MK trend test and Sen graphical method results depict mostly similar pattern. The annual rainfall trends exhibited a significant decrease by about 12 mm per year in the upstream, which is largely driven by the significant decrease in the peak season rainfall. The Pettit test revealed that the years 1997 and 2007 were the change points. It is noted that the rise of temperature over a catchment might have decreased the availability of soil moisture which resulted in less runoff. The temperature analyses also revealed that the catchment was getting warmer; particularly in the upstream. The minimum temperature trend showed a significant increase about 0.08°c per annum. There is generally a decreasing trend in stream flow. The monthly stream flow also exhibited a decreasing trend in February, March and September. The decline in annual and seasonal rainfall and the increase in temperature lead to more evaporation and directly affecting the stream flow negatively. This trend compounded with the growth of population and increasing demand for irrigation water exacerbates the competing demand for water resources. It thus calls for prudence in devising appropriate intervention in the planning and sustainable development of the basin water resources.

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.

Long-term trends in daily temperature extremes in Iraq

The existence of long-term persistence (LTP) in hydro-climatic time series can lead to considerable change in significance of trends. Therefore, past findings of climatic trend studies that did not consider LTP became a disputable issue. A study has been conducted to assess the trends in temperature and temperature extremes in Iraq in recent years (1965–2015) using both ordinary Mann-Kendal (MK) test; and the modified Mann-Kendall (m-MK) test, which can differentiate the multi-decadal oscillatory variations from secular trends. Trends in annual and seasonal minimum and maximum temperatures, diurnal temperature range (DTR), and 14 temperature-related extremes were assessed. MK test detected the significant increases in minimum and maximum temperature at all stations, where m-MK test detected at 86% and 80% of all stations, respectively. The temperature in Iraq is increasing 2 to 7 times faster than global temperature rise. The minimum temperature is increasing more (0.48–1.17°C/decade) than maximum temperature (0.25–1.01°C/decade). Temperature rise is higher in northern Iraq and in summer. The hot extremes particularly warm nights are increasing all over Iraq at a rate of 2.92–10.69days/decade, respectively. On the other hand, numbers of cold days are decreasing at some stations at a rate of −2.65 to −8.40days/decade. The use of m-MK test along with MK test confirms the significant increase in temperature and some of the temperature extremes in Iraq. This study suggests that trends in many temperature extremes in the region estimated in previous studies using MK test may be due to natural variability of climate, which empathizes the need for validation of the trends by considering LTP in time series.

Recent changes in monthly surface air temperature over Peru, 1964–2014

ABSTRACTThis study assessed changes in the maximum and minimum surface air temperatures across Peru during the period 1964–2014. For this purpose, we employed the most complete records of air temperature series that were also subjected to a rigorous quality control and homogenization protocol. Based on the homogenized series, we created a monthly gridded data set of maximum and minimum air temperatures at a 5 × 5 km grid spacing. The results suggest a general warming trend in surface air temperature across Peru, albeit with clear spatial and seasonal variation. Our results also reveal some differences in the detectable trends between maximum and minimum air temperatures. Maximum air temperature trends mainly increased during the austral summer (DJF), but cold season minimum air temperature trends showed an opposite pattern, with the strongest warming being recorded in the austral winter (JJA). In addition, maximum air temperature trends exhibited a clear elevation‐warming dependency, with the strongest warming recorded at highly elevated sites. On the contrary, this dependency is weakened for minimum air temperature trends, as lower magnitudes of change and even a cooling trend were observed at high elevations during most months of the year. For mean air temperature trends, there are no clear spatial and temporal seasonal differences across Peru.

Prediction of climate change in Brunei Darussalam using statistical downscaling model

Climate is changing and evidence suggests that the impact of climate change would influence our everyday lives, including agriculture, built environment, energy management, food security and water resources. Brunei Darussalam located within the heart of Borneo will be affected both in terms of precipitation and temperature. Therefore, it is crucial to comprehend and assess how important climate indicators like temperature and precipitation are expected to vary in the future in order to minimise its impact. This study assesses the application of a statistical downscaling model (SDSM) for downscaling General Circulation Model (GCM) results for maximum and minimum temperatures along with precipitation in Brunei Darussalam. It investigates future climate changes based on numerous scenarios using Hadley Centre Coupled Model, version 3 (HadCM3), Canadian Earth System Model (CanESM2) and third-generation Coupled Global Climate Model (CGCM3) outputs. The SDSM outputs were improved with the implementation of bias correction and also using a monthly sub-model instead of an annual sub-model. The outcomes of this assessment show that monthly sub-model performed better than the annual sub-model. This study indicates a satisfactory applicability for generation of maximum temperatures, minimum temperatures and precipitation for future periods of 2017–2046 and 2047–2076. All considered models and the scenarios were consistent in predicting increasing trend of maximum temperature, increasing trend of minimum temperature and decreasing trend of precipitations. Maximum overall trend of Tmax was also observed for CanESM2 with Representative Concentration Pathways (RCP) 8.5 scenario. The increasing trend is 0.014 °C per year. Accordingly, by 2076, the highest prediction of average maximum temperatures is that it will increase by 1.4 °C. The same model predicts an increasing trend of Tmin of 0.004 °C per year, while the highest trend is seen under CGCM3-A2 scenario which is 0.009 °C per year. The highest change predicted for the Tmin is therefore 0.9 °C by 2076. The precipitation showed a maximum trend of decrease of 12.7 mm year. It is also seen in the output using CanESM2 data that precipitation will be more chaotic with some reaching 4800 mm per year and also producing low rainfall about 1800 mm per year. All GCMs considered are consistent in predicting it is very likely that Brunei is expected to experience more warming as well as less frequent precipitation events but with a possibility of intensified and drastically high rainfalls in the future.

Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia

Most of the trend analysis that has been conducted has not considered the existence of a change point in the time series analysis. If these occurred, then the trend analysis will not be able to detect an obvious increasing or decreasing trend over certain parts of the time series. Furthermore, the lack of discussion on the possible factors that influenced either the decreasing or the increasing trend in the series needs to be addressed in any trend analysis. Hence, this study proposes to investigate the trends, and change point detection of mean, maximum and minimum temperature series, both annually and seasonally in Peninsular Malaysia and determine the possible factors that could contribute to the significance trends. In this study, Pettitt and sequential Mann–Kendall (SQ–MK) tests were used to examine the occurrence of any abrupt climate changes in the independent series. The analyses of the abrupt changes in temperature series suggested that most of the change points in Peninsular Malaysia were detected during the years 1996, 1997 and 1998. These detection points captured by Pettitt and SQ–MK tests are possibly related to climatic factors, such as El Nino and La Nina events. The findings also showed that the majority of the significant change points that exist in the series are related to the significant trend of the stations. Significant increasing trends of annual and seasonal mean, maximum and minimum temperatures in Peninsular Malaysia were found with a range of 2–5 °C/100 years during the last 32 years. It was observed that the magnitudes of the increasing trend in minimum temperatures were larger than the maximum temperatures for most of the studied stations, particularly at the urban stations. These increases are suspected to be linked with the effect of urban heat island other than El Nino event.

Analyzing snowfall variability over two locations in Kashmir, India in the context of warming climate

Present study focuses on examination snowfall variability over Gulmarg and Pahalgam of Kashmir Valley in India during past 31 years (1980–2010). Trends in temperature over the study area is also explored. Minimum and maximum temperature shows increasing trends which is consistent with increase in black carbon column mass density. Increase in black carbon mass density is attributed to urbanization over study area. Trends of minimum temperature is statistically significant. It is reported that snowfall over the Pahalgam shows decreasing trend except for the month of February and January. Pahalgam shows a significant decreasing trend in snowfall of about 48mm per decade during March. Pahalgam and Gulmarg show seasonal decreasing trends of snowfall of about 15mm and 1.8mm per decade, respectively. These decreasing trends in snowfall are consistent with decadal increasing trends of about 1.2°C and 0.8°C in minimum temperature over Pahalgam and Gulmarg, respectively. Seasonal snowfall over both the regions shows decreasing trend (insignificant). Results reported in this study show a decrease of about 24.16%±9.86% per degree increase in minimum temperature over Pahalgam. Changing characteristics of snowfall in the context of anthropogenic warming present major challenges to the tourism and socioeconomic aspects over the Valley.

Prevailing climatic trends and runoff response from Hindukush–Karakoram–Himalaya, upper Indus Basin

Abstract. Largely depending on the meltwater from the Hindukush–Karakoram–Himalaya, withdrawals from the upper Indus Basin (UIB) contribute half of the surface water availability in Pakistan, indispensable for agricultural production systems, industrial and domestic use, and hydropower generation. Despite such importance, a comprehensive assessment of prevailing state of relevant climatic variables determining the water availability is largely missing. Against this background, this study assesses the trends in maximum, minimum and mean temperatures, diurnal temperature range and precipitation from 18 stations (1250–4500 m a.s.l.) for their overlapping period of record (1995–2012) and, separately, from six stations of their long-term record (1961–2012). For this, a Mann–Kendall test on serially independent time series is applied to detect the existence of a trend, while its true slope is estimated using the Sen's slope method. Further, locally identified climatic trends are statistically assessed for their spatial-scale significance within 10 identified subregions of the UIB, and the spatially (field-) significant climatic trends are then qualitatively compared with the trends in discharge out of corresponding subregions. Over the recent period (1995–2012), we find warming and drying of spring (field-significant in March) and increasing early melt season discharge from most of the subregions, likely due to a rapid snowmelt. In stark contrast, most of the subregions feature a field-significant cooling within the monsoon period (particularly in July and September), which coincides well with the main glacier melt season. Hence, a decreasing or weakly increasing discharge is observed from the corresponding subregions during mid- to late melt season (particularly in July). Such tendencies, being largely consistent with the long-term trends (1961–2012), most likely indicate dominance of the nival but suppression of the glacial melt regime, altering overall hydrology of the UIB in future. These findings, though constrained by sparse and short observations, largely contribute in understanding the UIB melt runoff dynamics and address the hydroclimatic explanation of the Karakoram Anomaly.

Shifting of agro‐climatic zones, their drought vulnerability, and precipitation and temperature trends in Pakistan

ABSTRACTAgro‐climatic classification helps to determine the different features of a region. This climatic classification provides a useful insight for a farmer to grow their crops according to the conditions of their region. This study identifies the shifting of moisture index from average values in different agro‐climatic zones of Pakistan. Unpredictable climate remains dominant over long periods. Observational data of precipitation and evapotranspiration were used to determine the agro‐climatic zone during the period 1951–2010. This study reveals that almost 87% of Pakistan is in extremely arid to semi‐arid zones, a 5% decrease in over the last 30 years (1981–2010). The largest decrease of 8% and increase of 5% were observed in the extremely arid and humid zones, respectively. The semi‐arid zone is more vulnerable to drought, while intensity and severity are greater in the extremely arid region. An agro‐climatic regional analysis identifies 1952, 1969, 2000, 2001 and 2002 as years when the most severe droughts were observed during the study period. The trends of precipitation and temperature were performed at 95% significance level on a monthly, seasonal and annual basis over the entire agro‐climatic zone of Pakistan during 1951–2014. The annual precipitation trends show a significant increase of 0.828 mm year−1 in arid regions, whereas the maximum temperature trends shows a significant increase of 0.014 °C year−1 and 0.018 °C year−1 in extremely arid and humid regions, respectively. The trend of minimum temperature shows an increase over the whole region, which may place pressure on the water demands of crops.

Local spatiotemporal variability and trends in rainfall and temperature in the central highlands of Ethiopia

ABSTRACTThis study evaluates recent spatiotemporal variability and trends in rainfall and temperature in the central highlands of Ethiopia by using monthly rainfall and temperature records. The monthly rainfall data are for 132 points of 10 × 10 km grids reconstructed from weather stations and meteorological satellite observations, which cover the period between 1983 and 2013. The monthly maximum and minimum temperatures are for the same points and girds, but cover the period 1981–2011. Linear regression is used to each of the 132 grid points to detect changes or trends in rainfall, maximum and minimum temperatures and the statistical significance of the trends is determined by the F-distribution test. These points were reclassified into the three districts (Woredas in Amharic) studied having different agroecologies by extraction techniques with ArcGIS 10.1 and converted into raster to generate surface data using simple krigging interpolation technique. Annual and June–September (Kiremt) rainfall exhibit statistically insignificant increasing trends in most of the grid points while March–May (Belg) rainfall shows significant decreasing trends. On the other hand, significant spatiotemporal variability in the maximum and minimum temperatures is observed across the study area. The warming trends in the maximum and minimum temperatures for Basona Werana and Efratana Gidim, respectively, are statistically significant at p = .05 and p = .01 levels. It is concluded that trends of rainfall and temperature vary considerably within the study area. This indicates the need for local-level analysis, and context-specific planning and implementation of climate change adaptation interventions.

Estimated influence of urbanization on surface warming in Eastern China using time‐varying land use data

ABSTRACTWe examine the urban effect on surface warming in Eastern China, where a substantial portion of the land area has undergone rapid urbanization in the last few decades. Daily surface air temperature records during the period 1971–2010 at 277 meteorological stations are used to investigate temperature changes. Owing to urban expansion, some of the stations formerly located in rural areas are becoming increasingly influenced by urban environments. To estimate the effect of this urbanization on observed surface warming, the stations are dynamically classified into urban and rural types based on the land use data for four periods, i.e. 1980, 1990, 2000 and 2010. After eliminating the temperature trend bias induced by time‐varying latitudinal distributions of urban and rural stations, the estimated urban‐induced trends in the daily minimum and mean temperature are 0.167 and 0.085 °C decade−1, accounting for 33.6 and 22.4% of total surface warming, respectively. The temperature difference between urban and rural stations indicates that urban heat island intensity has dramatically increased owing to rapid urbanization, and is highly correlated with the difference in fractional coverage of artificial surfaces between these two types of stations. This study highlights the importance of dynamic station classification in estimating the contribution of urbanization to long‐term surface warming over large areas.

Studies on changes and cause of the minimum air temperature in Songnen Plain of China during 1961–2010

In this study, we took Songnen Plain of China as the study area, collected the observed minimum air temperature, the minimum air temperature reanalysis data (ERA-40), and the minimum land surface temperature from 1961 to 2010, the nighttime land surface temperature (MOD11A2) from 2000 to 2010. Further, with the obtained and processed data, we analyzed the mechanism and impact of land use change on minimum air temperature within the recent 50years in the Songnen Plain of China using climate tendency rate, Observation Minus Reanalysis (OMR) and spatial analysis methods. The analysis results can be summarized as follows. (1) The areas of agricultural land, built up, unused land, and forest land have increased and the areas of grassland and water have decreased from 1960 to 2010. In particular, the areas of unused land and built up have increased significantly with about 22 times and 9 times respectively compared with their areas in 1960. (2) During 1961–2010, with the land use change in the Songnen Plain, the maximum air temperature and diurnal temperature range trend has decreased, the minimum air temperature trend has increased, and impact of land use change on minimum air temperature trend is greater than maximum air temperature trend. (3) The unused land has the highest minimum air temperature, nighttime land surface temperature, and minimum land surface temperature than any other land uses, and all corresponding temperature is lower in the agricultural land and the lowest in the forestland. (4) The conversion from any other land uses to the unused land will result in the increasing of the temperature and to the agricultural land and forest land will cause the decreasing of the temperature.

Seasonal and Annual Trends in Australian Minimum/Maximum Daily Temperatures

Seasonal and annual trends in Australian minimum and maximum temperatures were studied. Records of daily minimum and maximum temperatures averaged over each month, extending as far back as 1856 were examined. Over 1/2 million monthly temperature values were retrieved from the Australian Bureau of Meteorology for 299 stations. Each station had an average of 89 years of observations. Significant step discontinuities affected the maximum temperature data in the 19th century when Stevenson screens were installed. The temperature trends were found after such spurious data were removed and averaged over all stations. The resulting trend in the minimum (maximum) daily temperature was 0.67 ± 0.19 (0.58 ± 0.26) oC per century for the period 1907-2014. Decadal fluctuations were evident in the maximum daily temperature with most of the increase occurring in the late 20th century. The minimum and maximum daily temperature trends were also found for the various seasons. The minimum daily temperature trend exceeded the maximum daily temperature trend for all seasons except during June to August. The largest increases in minimum temperature as well as the smallest maximum temperature increases were found for the region north of 30 oS latitude and east of 140 oE longitude. There was also evidence that urban stations had greater increases in maximum daily temperature than those located in a rural environment.

Climate perceptions of local communities validated through scientific signals in Sikkim Himalaya, India.

Sikkim, a tiny Himalayan state situated in the north-eastern region of India, records limited research on the climate change. Understanding the changes in climate based on the perceptions of local communities can provide important insights for the preparedness against the unprecedented consequences of climate change. A total of 228 households in 12 different villages of Sikkim, India, were interviewed using eight climate change indicators. The results from the public opinions showed a significant increase in temperature compared to a decade earlier, winters are getting warmer, water springs are drying up, change in concept of spring-water recharge (locally known as Mul Phutnu), changes in spring season, low crop yields, incidences of mosquitoes during winter, and decrease in rainfall in last 10years. In addition, study also showed significant positive correlations of increase in temperature with other climate change indicators viz. spring-water recharge concept (R (2)=0.893), warmer winter (R (2)=0.839), drying up of water springs (R (2)=0.76), changes in spring season (R (2)=0.68), low crop yields (R (2)=0.68), decrease in rainfall (R (2)=0.63), and incidences of mosquitoes in winter (R (2)=0.50). The air temperature for two meteorological stations of Sikkim indicated statistically significant increasing trend in mean minimum temperature and mean minimum winter temperature (DJF). The observed climate change is consistent with the people perceptions. This information can help in planning specific adaptation strategies to cope with the impacts of climate change by framing village-level action plan.

A Significant Population Signal in Iranian Temperature Records

We assembled daily maximum and minimum temperature records for 31 stations throughout Iran over the period 1961–2010. As with many other areas of the world, we found that both the maximum and minimum temperatures were increasing overall with the minimum temperatures increasing twice as fast as the maximum temperatures. We gathered population data for the stations near the beginning and end of the temperature records and found in all seasons and for both the maximum and minimum temperatures the magnitude of population growth positively influenced the temperature trends. However, unlike so many other studies, we found the strongest population growth signal in the winter for the maximum temperatures. We found evidence that this winter-season population-temperature signal is related snow cover. Our results illustrate that any number of processes are involved in explaining trends in historical maximum and minimum temperature records.

Temperature and precipitation regional climate series over the central Pyrenees during 1910–2013

ABSTRACTQuality controlled homogenized regional anomaly series of temperature and precipitation are obtained for the central Pyrenees for the period 1910–2013. A 0.1 °C decade−1 positive trend is found for minimum and maximum annual temperature exceeding the significance level of 0.05 for the whole studied period. A significant warming is found in all seasons except boreal spring in minimum temperature and winter in maximum temperature. The annual regional precipitation anomaly series shows a high inter‐annual variability and a slightly negative non‐significant trend of −0.6% decade−1. Non‐significant negative trends of precipitation are found in all seasons for the whole period examined. Considering the recent period 1970–2013, values of temperature trends are generally higher than those obtained for the whole period. For this latest period, all maximum temperature trends are significant while only the minimum temperature trend in winter is non‐significant. Spring is the season that presents the greatest warming, with 0.9 °C decade−1 for maximum temperature and 0.4 °C decade−1 for minimum temperature. Evaluating the same period for precipitation anomalies, trends in the annual, winter and summer series remain negative, while spring and autumn trends are positive although non‐significant. This series represents the longest homogenized climate data set available for the central Pyrenees region, including the newly recovered period 1910–1949, offering new possibilities for climate analysis and paleoclimate proxy calibration.

Geo-spatial analysis of temporal trends of temperature and its extremes over India using daily gridded (1°×1°) temperature data of 1969–2005

Daily gridded (1°×1°) temperature data (1969–2005) were used to detect spatial patterns of temporal trends of maximum and minimum temperature (monthly and seasonal), growing degree days (GDDs) over the crop-growing season (kharif, rabi, and zaid) and annual frequencies of temperature extremes over India. The direction and magnitude of trends, at each grid level, were estimated using the Mann–Kendall statistics (α = 0.05) and further assessed at the homogeneous temperature regions using a field significance test (α=0.05). General warming trends were observed over India with considerable variations in direction and magnitude over space and time. The spatial extent and the magnitude of the increasing trends of minimum temperature (0.02–0.04 °C year−1) were found to be higher than that of maximum temperature (0.01–0.02 °C year−1) during winter and pre-monsoon seasons. Significant negative trends of minimum temperature were found over eastern India during the monsoon months. Such trends were also observed for the maximum temperature over northern and eastern parts, particularly in the winter month of January. The general warming patterns also changed the thermal environment of the crop-growing season causing significant increase in GDDs during kharif and rabi seasons across India. The warming climate has also caused significant increase in occurrences of hot extremes such as hot days and hot nights, and significant decrease in cold extremes such as cold days and cold nights.

TREND OF AIR TEMPERATURE IN THE STATE OF PARANÁ, BRAZIL (TENDÊNCIA DA TEMPERATURA DO AR NO ESTADO DO PARANÁ, BRASIL)

Considering the importance of climatologic series and the local temperature variability analyses, this study aimed to evaluate the trend of maximum and minimum air temperature in the State of Paraná, Brazil. It were used daily data for the period 1980 to 2009 of 28 locations. The trend magnitude was obtained through linear regression and statistical significance using the Mann-Kendall non-parametric test. The spatial distribution of changes found was represented in geo-referenced maps elaborated through the ARCGIS v.10.0 with the spline interpolation method. The results revealed that the State of Paraná presents great variability in air temperature changes, with differences between places ranging from reductions of 0.5 reductions to increases of 0.6 °C/decade. These increases occurred mainly during the winter and the spring and reductions in the autumn. It was not possible to define simultaneity between the trends due to different changes found, which may be related to local factors such as relief, vegetation and regional activities.