Uncertainties in observations and climate projections for the North East India

NASA Astrophysics Data System (ADS)

Soraisam, Bidyabati; Karumuri, Ashok; D. S., Pai

2018-01-01

The Northeast-India has undergone many changes in climatic-vegetation related issues in the last few decades due to increased human activities. However, lack of observations makes it difficult to ascertain the climate change. The study involves the mean, seasonal cycle, trend and extreme-month analysis for summer-monsoon and winter seasons of observed climate data from Indian Meteorological Department (1° × 1°) and Aphrodite & CRU-reanalysis (both 0.5° × 0.5°), and five regional-climate-model simulations (LMDZ, MPI, GFDL, CNRM and ACCESS) data from AR5/CORDEX-South-Asia (0.5° × 0.5°). Long-term (1970-2005) observed, minimum and maximum monthly temperature and precipitation, and the corresponding CORDEX-South-Asia data for historical (1970-2005) and future-projections of RCP4.5 (2011-2060) have been analyzed for long-term trends. A large spread is found across the models in spatial distributions of various mean maximum/minimum climate statistics, though models capture a similar trend in the corresponding area-averaged seasonal cycles qualitatively. Our observational analysis broadly suggests that there is no significant trend in rainfall. Significant trends are observed in the area-averaged minimum temperature during winter. All the CORDEX-South-Asia simulations for the future project either a decreasing insignificant trend in seasonal precipitation, but increasing trend for both seasonal maximum and minimum temperature over the northeast India. The frequency of extreme monthly maximum and minimum temperature are projected to increase. It is not clear from future projections how the extreme rainfall months during JJAS may change. The results show the uncertainty exists in the CORDEX-South-Asia model projections over the region in spite of the relatively high resolution.

Sulfate Aerosol Control of Tropical Atlantic Climate over the Twentieth Century

NASA Technical Reports Server (NTRS)

Chang, C.-Y.; Chiang, J. C. H.; Wehner, M. F.; Friedman, A. R.; Ruedy, R.

2011-01-01

The tropical Atlantic interhemispheric gradient in sea surface temperature significantly influences the rainfall climate of the tropical Atlantic sector, including droughts over West Africa and Northeast Brazil. This gradient exhibits a secular trend from the beginning of the twentieth century until the 1980s, with stronger warming in the south relative to the north. This trend behavior is on top of a multi-decadal variation associated with the Atlantic multi-decadal oscillation. A similar long-term forced trend is found in a multimodel ensemble of forced twentieth-century climate simulations. Through examining the distribution of the trend slopes in the multimodel twentieth-century and preindustrial models, the authors conclude that the observed trend in the gradient is unlikely to arise purely from natural variations; this study suggests that at least half the observed trend is a forced response to twentieth-century climate forcings. Further analysis using twentieth-century single-forcing runs indicates that sulfate aerosol forcing is the predominant cause of the multimodel trend. The authors conclude that anthropogenic sulfate aerosol emissions, originating predominantly from the Northern Hemisphere, may have significantly altered the tropical Atlantic rainfall climate over the twentieth century

Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate.

PubMed

Omumbo, Judith A; Lyon, Bradfield; Waweru, Samuel M; Connor, Stephen J; Thomson, Madeleine C

2011-01-17

Whether or not observed increases in malaria incidence in the Kenyan Highlands during the last thirty years are associated with co-varying changes in local temperature, possibly connected to global changes in climate, has been debated for over a decade. Studies, using differing data sets and methodologies, produced conflicting results regarding the occurrence of temperature trends and their likelihood of being responsible, at least in part, for the increases in malaria incidence in the highlands of western Kenya. A time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, may help resolve the controversy. If significant temperature trends over the last three decades have occurred then climate should be included (along with other factors such as land use change and drug resistance) as a potential driver of the observed increases in malaria in the region. Over 30 years (1 January 1979 to 31 December 2009) of quality controlled daily observations ( > 97% complete) of maximum, minimum and mean temperature were used in the analysis of trends at Kericho meteorological station, sited in a tea growing area of Kenya's western highlands. Inhomogeneities in all the time series were identified and corrected. Linear trends were identified via a least-squares regression analysis with statistical significance assessed using a two-tailed t-test. These 'gold standard' meteorological observations were compared with spatially interpolated temperature datasets that have been developed for regional or global applications. The relationship of local climate processes with larger climate variations, including tropical sea surface temperatures (SST), and El Niño-Southern Oscillation (ENSO) was also assessed. An upward trend of ≈0.2°C/decade was observed in all three temperature variables (P < 0.01). Mean temperature variations in Kericho were associated with large-scale climate variations including tropical SST (r = 0.50; p < 0.01). Local rainfall was found to have inverse effects on minimum and maximum temperature. Three versions of a spatially interpolated temperature data set showed markedly different trends when compared with each other and with the Kericho station observations. This study presents evidence of a warming trend in observed maximum, minimum and mean temperatures at Kericho during the period 1979 to 2009 using gold standard meteorological observations. Although local factors may be contributing to these trends, the findings are consistent with variability and trends that have occurred in correlated global climate processes. Climate should therefore not be dismissed as a potential driver of observed increases in malaria seen in the region during recent decades, however its relative importance compared to other factors needs further elaboration. Climate services, pertinent to the achievement of development targets such as the Millennium Development Goals and the analysis of infectious disease in the context of climate variability and change are being developed and should increase the availability of relevant quality controlled climate data for improving development decisions. The malaria community should seize this opportunity to make their needs heard.

Variable Trends in High Peak Flow Generation Across the Swedish Sub-Arctic

NASA Astrophysics Data System (ADS)

Matti, B.; Dahlke, H. E.; Lyon, S. W.

2015-12-01

There is growing concern about increased frequency and severity of floods and droughts globally in recent years. Improving knowledge on the complexity of hydrological systems and their interactions with climate is essential to be able to determine drivers of these extreme events and to predict changes in these drivers under altered climate conditions. This is particularly true in cold regions such as the Swedish Sub-Arctic where independent shifts in both precipitation and temperature can have significant influence on extremes. This study explores changes in the magnitude and timing of the annual maximum daily flows in 18 Swedish sub-arctic catchments. The Mann-Kendall trend test was used to estimate changes in selected hydrological signatures. Further, a flood frequency analysis was conducted by fitting a Gumbel (Extreme Value type I) distribution whereby selected flood percentiles were tested for stationarity using a generalized least squares regression approach. Our results showed that hydrological systems in cold climates have complex, heterogeneous interactions with climate. Shifts from a snowmelt-dominated to a rainfall-dominated flow regime were evident with all significant trends pointing towards (1) lower flood magnitudes in the spring flood; (2) earlier flood occurrence; (3) earlier snowmelt onset; and (4) decreasing mean summer flows. Decreasing trends in flood magnitude and mean summer flows suggest permafrost thawing and are in agreement with the increasing trends in annual minimum flows. Trends in the selected flood percentiles showed an increase in extreme events over the entire period of record, while trends were variable under shorter periods. A thorough uncertainty analysis emphasized that the applied trend test is highly sensitive to the period of record considered. As such, no clear overall regional pattern could be determined suggesting that how catchments are responding to changes in climatic drivers is strongly influenced by their physical characteristics.

Observed SWE trends and climate analysis for Northwest Pacific North America: validation for future projection of SWE using the CRCM and VIC

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Bronaugh, D.; Rodenhuis, D.

2008-12-01

Observational databases of snow water equivalent (SWE) have been collected from Alaska, western US states and the Canadian provinces of British Columbia, Alberta, Saskatchewan, and territories of NWT, and the Yukon. These databases were initially validated to remove inconsistencies and errors in the station records, dates or the geographic co-ordinates of the station. The cleaned data was then analysed for historical (1950 to 2006) trend using emerging techniques for trend detection based on (first of the month) estimates for January to June. Analysis of SWE showed spatial variability in the count of records across the six month time period, and this study illustrated differences between Canadian and US (or the north and south) collection. Two different data sets (one gridded and one station) were then used to analyse April 1st records, for which there was the greatest spatial spread of station records for analysis with climate information. Initial results show spatial variability (in both magnitude and direction of trend) for trend results, and climate correlations and principal components indicate different drivers of change in SWE across the western US, Canada and north to Alaska. These results will be used to validate future predictions of SWE that are being undertaken using the Canadian Regional Climate Model (CRCM) and the Variable Infiltration Capacity (VIC) hydrologic model for Western Northern America (CRCM) and British Columbia (VIC).

Precipitation Indices as a Tool for Climate-Resilient Development in the Peruvian Andes

NASA Astrophysics Data System (ADS)

Chisolm, R. E.; McKinney, D. C.

2016-12-01

The local people living in the mountains of the Ancash Department in Peru have noticed changes in their water supply as climate change has altered precipitation patterns. They are seeking adaptation solutions to help guarantee the reliability of their water supply, but there has been very little analysis of historical data to evaluate and justify these adaptation solutions. In addition, Peru's Ministry of Economy and Finance now requires that climate change be part of the vulnerability assessment for all public investment project proposals, but there are currently no tools or methods of data analysis for including climate change in vulnerability assessments. Compounding the difficulties of considering climate change in the sustainability of development projects is the scarcity of climate data in the region and the difficulty of accessing existing data. To counteract this problem, the Peruvian government recommends using local people's perceptions of change as a proxy for gauged climate data. This work focuses on precipitation data analysis in the mountains of Ancash, Peru. The objectives of this analysis were to determine the accuracy of the local population's perceptions of climate change and to investigate how changes in precipitation patterns might impact public investment projects. The precipitation data analysis was compared to a local study of perceptions of change to determine whether or not these perceptions might be used in lieu of gauged climate data. It appears that people's perceptions of precipitation trends do not accurately reflect the trends observed in the gauged data. The methods of analysis were designed so that the results may be useful for public investment projects with a particular emphasis on agricultural projects. The data were analyzed for trends, seasonal patterns and variability. Dry spells were examined, and the results indicate that droughts during the rainy season have become more frequent and of longer duration. This could have significant impact on agricultural projects. It is likely that the current practice of relying exclusively on wet season rainfall to meet crop water requirements may not be sustainable in the future. Further analysis of climate data is needed to generate a regional climatic characterization that can be used for climate-resilient development projects.

Analysis of rainfall and temperature time series to detect long-term climatic trends and variability over semi-arid Botswana

NASA Astrophysics Data System (ADS)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.

2018-03-01

Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann-Kendall and Sen's Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.

[Temporal and spatial variations of extreme climatic events in Songnen Grassland, Northeast China during 1960-2014].

PubMed

Ma, Qi Yun; Zhang, Ji Quan; Lai, Quan; Zhang, Feng; Dong, Zhen Hua; A, Lu Si

2017-06-18

Fourteen extreme climatic indices related with main regional meteorological disasters and vegetation growth were calculated based on daily data from 13 meteorological stations during 1960-2014 in Songnen Grassland, Northeast China. Then, the variation trend and the spatial and temporal patterns of climatic extreme events were analyzed by using regression analysis, break trend analy-sis, Mann-Kendall test, Sen's slope estimator and moving t-test method. The results indicated that summer days (SU25), warm days (TX90P), warm nights (TN90P) and warm spell duration (WSDI) representing extremely high temperatures showed significant increasing trends (P<0.05). Meanwhile, frost days (FD0), cold days (TX10P), cold nights (TN10P) and cold spell duration indicator (CSDI) representing extremely low temperatures showed obviously decreasing trends. The magnitudes of changes in cold indices (FD0, TX10P, TN10P and CSDI) were clearly greater than those of warm indices (SU25, TX90P, TN90P and WSDI), and that changes in night indices were larger than those of day indices. Regional climate warming trend was obvious from 1970 to 2009, and the most occurrences of the abrupt changes in these indices were identified in this period. The extreme precipitation indices did not show obvious trend, in general, SDII and CDD experienced a slightly decreasing trend while RX5D, R95P, PRCPTOT and CWD witnessed a mildly increasing trend. It may be concluded that regional climate changed towards warming and slightly wetting in Songnen Grassland. The most sensitive region for extreme temperature was distributed in the south and north region. Additionally, the extreme temperature indices showed clearly spatial difference between the south and the north. As for the spatial variations of extreme precipitation indices, the climate could be characterized by becoming wetter in northern region, and getting drier in southern region, especially in southwestern region with a high drought risk.

Analysis of temporal and spatial trends of hydro-climatic variables in the Wei River Basin.

PubMed

Zhao, Jing; Huang, Qiang; Chang, Jianxia; Liu, Dengfeng; Huang, Shengzhi; Shi, Xiaoyu

2015-05-01

The Wei River is the largest tributary of the Yellow River in China. The relationship between runoff and precipitation in the Wei River Basin has been changed due to the changing climate and increasingly intensified human activities. In this paper, we determine abrupt changes in hydro-climatic variables and identify the main driving factors for the changes in the Wei River Basin. The nature of the changes is analysed based on data collected at twenty-one weather stations and five hydrological stations in the period of 1960-2010. The sequential Mann-Kendall test analysis is used to capture temporal trends and abrupt changes in the five sub-catchments of the Wei River Basin. A non-parametric trend test at the basin scale for annual data shows a decreasing trend of precipitation and runoff over the past fifty-one years. The temperature exhibits an increase trend in the entire period. The potential evaporation was calculated based on the Penman-Monteith equation, presenting an increasing trend of evaporation since 1990. The stations with a significant decreasing trend in annual runoff mainly are located in the west of the Wei River primarily interfered by human activities. Regression analysis indicates that human activity was possibly the main cause of the decline of runoff after 1970. Copyright © 2015. Published by Elsevier Inc.

Effects of urbanization on climate of İstanbul and Ankara

NASA Astrophysics Data System (ADS)

Karaca, Mehmet; Tayanç, Mete; Toros, Hüseyi˙n.

The purpose of this work is to study regional climate change and investigate the effects of urbanization on climates of two largest cities in Turkey: İstanbul and Ankara. Air temperature (mean, maximum and minimum) data of İstanbul and Ankara are analyzed to study regional climate change and to understand the possible effects of urbanization on the climate of these regions owing to industrialization and large flux of migration from rural parts of the country. For the trend analysis, linear regression and the sequential version of the Mann-Kendall test is used. A significant upward trend is found in the urban temperatures of southern İstanbul, which is the most highly populated and industrialized part of the city compared to its rural parts. Northern stations do not show any warming trend; instead, they have a cooling trend. Urbanization and industrialization in the southern part of İstanbul has a negative effect on regional cooling. In spite of Ankara's urban geometry and air pollution problem, the urban station in Ankara does not show any warming trend. A significant urban heat island intensity ( urban-rural) is not observed in Ankara.

Do climate model predictions agree with long-term precipitation trends in the arid southwestern United States?

NASA Astrophysics Data System (ADS)

Elias, E.; Rango, A.; James, D.; Maxwell, C.; Anderson, J.; Abatzoglou, J. T.

2016-12-01

Researchers evaluating climate projections across southwestern North America observed a decreasing precipitation trend. Aridification was most pronounced in the cold (non-monsoonal) season, whereas downward trends in precipitation were smaller in the warm (monsoonal) season. In this region, based upon a multimodel mean of 20 Coupled Model Intercomparison Project 5 models using a business-as-usual (Representative Concentration Pathway 8.5) trajectory, midcentury precipitation is projected to increase slightly during the monsoonal time period (July-September; 6%) and decrease slightly during the remainder of the year (October-June; -4%). We use observed long-term (1915-2015) monthly precipitation records from 16 weather stations to investigate how well measured trends corroborate climate model predictions during the monsoonal and non-monsoonal timeframe. Running trend analysis using the Mann-Kendall test for 15 to 101 year moving windows reveals that half the stations showed significant (p≤0.1), albeit small, increasing trends based on the longest term record. Trends based on shorter-term records reveal a period of significant precipitation decline at all stations representing the 1950s drought. Trends from 1930 to 2015 reveal significant annual, monsoonal and non-monsoonal increases in precipitation (Fig 1). The 1960 to 2015 time window shows no significant precipitation trends. The more recent time window (1980 to 2015) shows a slight, but not significant, increase in monsoonal precipitation and a larger, significant decline in non-monsoonal precipitation. GCM precipitation projections are consistent with more recent trends for the region. Running trends from the most recent time window (mid-1990s to 2015) at all stations show increasing monsoonal precipitation and decreasing Oct-Jun precipitation, with significant trends at 6 of 16 stations. Running trend analysis revealed that the long-term trends were not persistent throughout the series length, but depended on the period examined. Recent trends in Southwest precipitation are directionally consistent with anthropogenic climate change.

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Statistical significance of seasonal warming/cooling trends

NASA Astrophysics Data System (ADS)

Ludescher, Josef; Bunde, Armin; Schellnhuber, Hans Joachim

2017-04-01

The question whether a seasonal climate trend (e.g., the increase of summer temperatures in Antarctica in the last decades) is of anthropogenic or natural origin is of great importance for mitigation and adaption measures alike. The conventional significance analysis assumes that (i) the seasonal climate trends can be quantified by linear regression, (ii) the different seasonal records can be treated as independent records, and (iii) the persistence in each of these seasonal records can be characterized by short-term memory described by an autoregressive process of first order. Here we show that assumption ii is not valid, due to strong intraannual correlations by which different seasons are correlated. We also show that, even in the absence of correlations, for Gaussian white noise, the conventional analysis leads to a strong overestimation of the significance of the seasonal trends, because multiple testing has not been taken into account. In addition, when the data exhibit long-term memory (which is the case in most climate records), assumption iii leads to a further overestimation of the trend significance. Combining Monte Carlo simulations with the Holm-Bonferroni method, we demonstrate how to obtain reliable estimates of the significance of the seasonal climate trends in long-term correlated records. For an illustration, we apply our method to representative temperature records from West Antarctica, which is one of the fastest-warming places on Earth and belongs to the crucial tipping elements in the Earth system.

Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate

PubMed Central

2011-01-01

Background Whether or not observed increases in malaria incidence in the Kenyan Highlands during the last thirty years are associated with co-varying changes in local temperature, possibly connected to global changes in climate, has been debated for over a decade. Studies, using differing data sets and methodologies, produced conflicting results regarding the occurrence of temperature trends and their likelihood of being responsible, at least in part, for the increases in malaria incidence in the highlands of western Kenya. A time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, may help resolve the controversy. If significant temperature trends over the last three decades have occurred then climate should be included (along with other factors such as land use change and drug resistance) as a potential driver of the observed increases in malaria in the region. Methods Over 30 years (1 January 1979 to 31 December 2009) of quality controlled daily observations ( > 97% complete) of maximum, minimum and mean temperature were used in the analysis of trends at Kericho meteorological station, sited in a tea growing area of Kenya's western highlands. Inhomogeneities in all the time series were identified and corrected. Linear trends were identified via a least-squares regression analysis with statistical significance assessed using a two-tailed t-test. These 'gold standard' meteorological observations were compared with spatially interpolated temperature datasets that have been developed for regional or global applications. The relationship of local climate processes with larger climate variations, including tropical sea surface temperatures (SST), and El Niño-Southern Oscillation (ENSO) was also assessed. Results An upward trend of ≈0.2°C/decade was observed in all three temperature variables (P < 0.01). Mean temperature variations in Kericho were associated with large-scale climate variations including tropical SST (r = 0.50; p < 0.01). Local rainfall was found to have inverse effects on minimum and maximum temperature. Three versions of a spatially interpolated temperature data set showed markedly different trends when compared with each other and with the Kericho station observations. Conclusion This study presents evidence of a warming trend in observed maximum, minimum and mean temperatures at Kericho during the period 1979 to 2009 using gold standard meteorological observations. Although local factors may be contributing to these trends, the findings are consistent with variability and trends that have occurred in correlated global climate processes. Climate should therefore not be dismissed as a potential driver of observed increases in malaria seen in the region during recent decades, however its relative importance compared to other factors needs further elaboration. Climate services, pertinent to the achievement of development targets such as the Millennium Development Goals and the analysis of infectious disease in the context of climate variability and change are being developed and should increase the availability of relevant quality controlled climate data for improving development decisions. The malaria community should seize this opportunity to make their needs heard. PMID:21241505

Seasonal Responses of Terrestrial Ecosystem Water-use Efficiency to Climate Change

NASA Astrophysics Data System (ADS)

Huang, M.; Piao, S.; Zeng, Z.; Peng, S.; Ciais, P.; Cheng, L.; Mao, J.; Poulter, B.; Shi, X.; Yao, Y.; Yang, H.; Wang, Y.

2016-12-01

Ecosystem water-use efficiency (EWUE) is an indicator of carbon-water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET). Previous research suggests an increasing long-term trend in annual EWUE over many regions, and is largely attributed to the physiological effects of rising CO2. The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982-2008. The seasonal cycle for two variants of EWUE, water-use efficiency (WUE, GPP/ET) and transpiration-based WUE (WUEt, the ratio of GPP and transpiration), is analyzed from 0.5° gridded fields from four process-based models and satellite-based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite-based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite-based products. Trend analysis, based on process-model factorial simulations separating effects of climate, CO2 and nitrogen deposition (NDEP), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid- and high northern latitudes. In these regions, spring climate change has amplified the effect of CO2 in increasing WUE by more than 0.005 gC m-2 mm-1 yr-1 for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO2 and NDEP.

West African warming: Investigating Temperature Trends and their relation between Precipitation Trends over West African Sahel.

NASA Astrophysics Data System (ADS)

LY, M., Jr.

2014-12-01

It is now admitted that the West African region faces a lot of constraints due to the comprehensiveness of the high climate variability and potential climate change. This is mainly due to the lack of a large number of datasets and long-term records as summarized in the in the IPCC reports. This paper aims to provide improved knowledge and evidence on current and future climate conditions, for better manage climate variability over seasons and from year to year and strengthen the capacity to adapt to future climate change. In this regards, we analyse the evolution of some extreme temperature and precipitation indices over a large area of West Africa. Prior results show a general warming trend at individual stations throughout the region during the period from 1960 to 2010, namely negative trends in the number of cool nights, and positive trends in the number of warm days and length of warm spells. Trends in rainfall-related indices are not as uniform as the ones in temperatures, rather they display marked multi-decadal variability, as expected. To refine analyses of temperature variations and their relation to precipitation we investigated on cluster analysis aimed at distinguishing different sub-regions, such as continental and coastal, and relevant seasons, such as wet, dry/cold and dry warm. This will contribute to significantly lower uncertainties by developing better and more tailored temperature and precipitation trends to inform the user communities on climate related risks, as well as enhance their resilience to food insecurity and other climate related disasters.

Trends and Controls of inter-annual Variability in the Carbon Budget of Terrestrial Ecosystems

NASA Astrophysics Data System (ADS)

Cescatti, A.; Marcolla, B.

2014-12-01

The climate sensitivity of the terrestrial carbon budget will substantially affect the sign and strength of the land-climate feedbacks and the future climate trajectories. Current trends in the inter-annual variability of terrestrial carbon fluxes (IAV) may contribute to clarify the relative role of physical and biological controls of ecosystem responses to climate change. For this purpose we investigated how recent climate variability has impacted the carbon fluxes at long-term FLUXNET sites. Using a novel method, the IAV has been factored out in climate induced variability (physical control), variability due to changes in ecosystem functioning (biological control) and the interaction of the two terms. The relative control of the main climatic drivers (temperature, water availability) on the physical and biological sources of IAV has been investigated using both site level fluxes and global gridded products generated from the up-scaling of flux data. Results of this analysis highlight the fundamental role of precipitation trends on the pattern of IAV in the last 30 years. Our findings on the spatial/temporal trends of IAV have been finally confirmed using the signal derived from the global network of atmospheric CO2 concentrations measurements.

Assessing Climate Risk on Agricultural Production: Insights Using Retrospective Analysis of Crop Insurance and Climatic Trends

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Elias, E.; Eischens, A.; Shilts, M.; Rango, A.; Steele, R.

2017-12-01

The collaborative synthesis of existing datasets, such as long-term climate observations and farmers' crop insurance payments, can increase their overall collective value and societal application. The U.S. Department of Agriculture (USDA) Climate Hubs were created to develop and deliver science-based information and technologies to agricultural and natural resource managers to enable climate-informed decision-making. As part of this mission, Hubs work across USDA and other climate service agencies to synthesize existing information. The USDA Risk Management Agency (RMA) is responsible for overseeing the Federal crop insurance program which currently insures over $100 billion in crops annually. RMA hosts data describing the cause for loss (e.g. drought, wind, irrigation failure) and indemnity amount (i.e. total cost of loss) at multiple spatio-temporal scales (i.e. state, county, year, month). The objective of this paper is to link climate information with indemnities, and their associated cause of loss, to assess climate risk on agricultural production and provide regionally-relevant information to stakeholders to promote resilient working landscapes. We performed a retrospective trend analysis at the state-level for the American Southwest (SW). First, we assessed indemnity-only trends by cause of loss and crop type at varying temporal scales. Historical monthly weather data (i.e. precipitation and temperature) and long-term drought indices (e.g. Palmer Drought Severity Index) were then linked with indemnities and grouped by different causes of loss. Climatological ranks were used to integrate historical comparative intensity of acute and long-term climatic events. Heat and drought as causes of loss were most correlated with temperature and drought indicators, respectively. Across all SW states increasing indemnities were correlated with warmer conditions. Multiple statistical trend analyses suggest a framework is necessary to appropriately measure the biophysical signals in crop insurance trends taking into account spatio-temporal characteristics. Based on stakeholder feedback, we also developed a web-based information browser to visualize and assess indemnity trends providing useful and usable knowledge to support informed land management decisions and ecosystem resilience.

Assessing floods and droughts in the Mékrou River basin (West Africa): a combined household survey and climatic trends analysis approach

NASA Astrophysics Data System (ADS)

Markantonis, Vasileios; Farinosi, Fabio; Dondeynaz, Celine; Ameztoy, Iban; Pastori, Marco; Marletta, Luca; Ali, Abdou; Carmona Moreno, Cesar

2018-05-01

The assessment of natural hazards such as floods and droughts is a complex issue that demands integrated approaches and high-quality data. Especially in African developing countries, where information is limited, the assessment of floods and droughts, though an overarching issue that influences economic and social development, is even more challenging. This paper presents an integrated approach to assessing crucial aspects of floods and droughts in the transboundary Mékrou River basin (a portion of the Niger River basin in West Africa), combining climatic trends analysis and the findings of a household survey. The multivariable trend analysis estimates, at the biophysical level, the climate variability and the occurrence of floods and droughts. These results are coupled with an analysis of household survey data that reveals the behaviour and opinions of local residents regarding the observed climate variability and occurrence of flood and drought events, household mitigation measures, and the impacts of floods and droughts. Based on survey data analysis, the paper provides a per-household cost estimation of floods and droughts that occurred over a 2-year period (2014-2015). Furthermore, two econometric models are set up to identify the factors that influence the costs of floods and droughts to impacted households.

Satellite-based trends of solar radiation and cloud parameters in Europe

NASA Astrophysics Data System (ADS)

Pfeifroth, Uwe; Bojanowski, Jedrzej S.; Clerbaux, Nicolas; Manara, Veronica; Sanchez-Lorenzo, Arturo; Trentmann, Jörg; Walawender, Jakub P.; Hollmann, Rainer

2018-04-01

Solar radiation is the main driver of the Earth's climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990's is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out.

Human Land-Use Practices Lead to Global Long-Term Increases in Photosynthetic Capacity

NASA Technical Reports Server (NTRS)

Mueller, Thomas; Tucker, Compton J.; Dressler, Gunnar; Pinzon, Jorge E.; Leimgruber, Peter; Dubayah, Ralph O.; Hurtt, George C.; Boehning-Gaese, Katrin; Fagan, William F.

2014-01-01

Long-term trends in photosynthetic capacity measured with the satellite-derived Normalized Difference Vegetation Index (NDVI) are usually associated with climate change. Human impacts on the global land surface are typically not accounted for. Here, we provide the first global analysis quantifying the effect of the earth's human footprint on NDVI trends. Globally, more than 20% of the variability in NDVI trends was explained by anthropogenic factors such as land use, nitrogen fertilization, and irrigation. Intensely used land classes, such as villages, showed the greatest rates of increase in NDVI, more than twice than those of forests. These findings reveal that factors beyond climate influence global long-term trends in NDVI and suggest that global climate change models and analyses of primary productivity should incorporate land use effects.

Changes in Concurrent Risk of Warm and Dry Years under Impact of Climate Change

NASA Astrophysics Data System (ADS)

Sarhadi, A.; Wiper, M.; Touma, D. E.; Ausín, M. C.; Diffenbaugh, N. S.

2017-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena. The changing concurrence of multiple climatic extremes (warm and dry years) may result in intensification of undesirable consequences for water resources, human and ecosystem health, and environmental equity. The present study assesses how global warming influences the probability that warm and dry years co-occur in a global scale. In the first step of the study a designed multivariate Mann-Kendall trend analysis is used to detect the areas in which the concurrence of warm and dry years has increased in the historical climate records and also climate models in the global scale. The next step investigates the concurrent risk of the extremes under dynamic nonstationary conditions. A fully generalized multivariate risk framework is designed to evolve through time under dynamic nonstationary conditions. In this methodology, Bayesian, dynamic copulas are developed to model the time-varying dependence structure between the two different climate extremes (warm and dry years). The results reveal an increasing trend in the concurrence risk of warm and dry years, which are in agreement with the multivariate trend analysis from historical and climate models. In addition to providing a novel quantification of the changing probability of compound extreme events, the results of this study can help decision makers develop short- and long-term strategies to prepare for climate stresses now and in the future.

Climatic indicators over Catalonia during the last century

NASA Astrophysics Data System (ADS)

Busto, M.; Prohom, M.

2010-09-01

The Meteorological Service of Catalonia releases a yearly bulletin whose main objective is to try to detect climate trends over Catalonia during the last decades. Climate indicators are obtained from the analysis of historical daily air temperature, sea temperature and rainfall series. Those series have been first completed, analyzed for quality control and homogenized to ensure its final reliability. Regarding homogenization, monthly air temperature series have been tested and corrected according to the methodology proposed by Caussinus and Mestre (2004). For the two longest air temperature series, the calculated correction factors have been transferred to the daily values following Vincent et al. (2002) recommendations, while no significant inhomogeneities have been detected for precipitation series. The analysis of temperature trends, for the period 1950-2010, of 17 selected climatic series spread across the territory shows a common temperature increase between +0.19 to +0.24 °C/decade. This warming trend is uniform and no specific sub-regional trends are detected. Furthermore, the seasonal approach reveals that mean maximum temperature increases at a higher rate than mean minimum temperature. The summer temperature rise is the most significant, between +0.32 and +0.44 °C/decade, while autumn is the only season showing no significant positive trend. The summer maximum temperature shows the highest increase, exceeding +0.39 °C/decade in all the 17 series. The climatic extremes analysis of the longest Catalan series (Ebre Observatory in Roquetes, Tarragona, since 1905 and Fabra Observatory in Barcelona since 1913) reveals an increase in the number of summer days, tropical nights, minimum of maximum temperature, warm days and warm nights, and a decrease in the number of frost days, cold nights, cold days and cold spell duration indicator. Concerning precipitation, the only significant trend is the reduction of snow days. These trends were calculated according to the Expert Team on Climate Change Detection and Indices (ETCCDI). The sea temperature trend in l'Estartit (NE coast of Catalonia, Costa Brava) since 1974 shows a steady increment in all the measured levels (surface, -20 m, -50 m and -80 m) of +0,33 °C/decade on average. Temperature increment is maximum at -20 m, with +0.36 °C/decade variation. Moreover, there is an increase in the sea level of +3.35 cm/decade. CAUSSINUS, H. and MESTRE, O. (2004): Detection and correction of artificial shifts in climate series. Journal of the Royal Statistical Society Series C - Applied Statistics, 53, 405-425. VINCENT, L.A., ZHANG, X., BONSAL, B.R., HOGG, W.D. (2002): Homogenization of daily temperatures over Canada. Journal of Climate, 15, 1322-1334

Crop-climate relationships of cereals in Greece and the impacts of recent climate trends

NASA Astrophysics Data System (ADS)

Mavromatis, Theodoros

2015-05-01

Notwithstanding technological developments, agricultural production is still affected by uncontrollable factors, such weather and climate. Within this context, the present study aims at exploring the relative influence of growing season climate on the yields of major cereals (hard and soft wheat, maize, and barley) on a regional scale in Greece. To this end, crop-climate relationships and the impacts of climate trends over the period 1978-2005 were explored using linear regression and change point analysis (CPA). Climate data used include maximum (Tx) and minimum temperature (Tn), diurnal temperature range (Tr), precipitation (Prec), and solar radiation (Rad). Temperature effects were the most substantial. Yields reduced by 1.8-7.1 %/°C with increasing Tx and by 1.4-6.1 %/°C with decreasing Tr. The warming trends of Tn caused bilateral yield effects (from -3.7 to 8.4 %/°C). The fewer significantly increasing Rad and decreasing Prec anomalies were associated with larger yield decreases (within the range of 2.2 % MJ/m2/day (for maize) to 4.9 % MJ/m2/day (for hard wheat)) and smaller yield increases (from 0.04 to 1.4 %/mm per decade), respectively. Wheat and barley—the most vulnerable cereals—were most affected by the trends of extreme temperatures and least by Tr. On the contrary, solar radiation has proven to be the least affecting climate variable on all cereals. Despite the similarity in the direction of crop responses with both analyses, yield changes were much more substantial in the case of CPA analysis. In conclusion, regional climate change has affected Greek cereal productivity, in a few, but important for cereal production, regions. The results of this study are expected to be valuable in anticipating the effects of weather/climate on other warm regions worldwide, where the upper temperature limit for some cereals and further changes in climate may push them past suitability for their cultivation.

Seeing is Believing? An Examination of Perceptions of Local Weather Conditions and Climate Change Among Residents in the U.S. Gulf Coast.

PubMed

Shao, Wanyun; Goidel, Kirby

2016-11-01

What role do objective weather conditions play in coastal residents' perceptions of local climate shifts and how do these perceptions affect attitudes toward climate change? While scholars have increasingly investigated the role of weather and climate conditions on climate-related attitudes and behaviors, they typically assume that residents accurately perceive shifts in local climate patterns. We directly test this assumption using the largest and most comprehensive survey of Gulf Coast residents conducted to date supplemented with monthly temperature data from the U.S. Historical Climatology Network and extreme weather events data from National Climatic Data Center. We find objective conditions have limited explanatory power in determining perceptions of local climate patterns. Only the 15- and 19-year hurricane trends and decadal summer temperature trend have some effects on perceptions of these weather conditions, while the decadal trend of total number of extreme weather events and 15- and 19-year winter temperature trends are correlated with belief in climate change. Partisan affiliation, in contrast, plays a powerful role affecting individual perceptions of changing patterns of air temperatures, flooding, droughts, and hurricanes, as well as belief in the existence of climate change and concern for future consequences. At least when it comes to changing local conditions, "seeing is not believing." Political orientations rather than local conditions drive perceptions of local weather conditions and these perceptions-rather than objectively measured weather conditions-influence climate-related attitudes. © 2016 Society for Risk Analysis.

Techniques for analyses of trends in GRUAN data

NASA Astrophysics Data System (ADS)

Bodeker, G. E.; Kremser, S.

2015-04-01

The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterized and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterized uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E).

Techniques for analyses of trends in GRUAN data

NASA Astrophysics Data System (ADS)

Bodeker, G. E.; Kremser, S.

2014-12-01

The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterised and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterised uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E).

Analysis on variability and trend in Antarctic sea ice albedo between 1983 and 2009

NASA Astrophysics Data System (ADS)

Seo, Minji; Kim, Hyun-cheol; Choi, Sungwon; Lee, Kyeong-sang; Han, Kyung-soo

2017-04-01

Sea ice is key parameter in order to understand the cryosphere climate change. Several studies indicate the different trend of sea ice between Antarctica and Arctic. Albedo is important factor for understanding the energy budget and factors for observing of environment changes of Cryosphere such as South Pole, due to it mainly covered by ice and snow with high albedo value. In this study, we analyzed variability and trend of long-term sea ice albedo data to understand the changes of sea ice over Antarctica. In addiction, sea ice albedo researched the relationship with Antarctic oscillation in order to determine the atmospheric influence. We used the sea ice albedo data at The Satellite Application Facility on Climate Monitoring and Antarctic Oscillation data at NOAA Climate Prediction Center (CPC). We analyzed the annual trend in albedo using linear regression to understand the spatial and temporal tendency. Antarctic sea ice albedo has two spatial trend. Weddle sea / Ross sea sections represent a positive trend (0.26% ˜ 0.04% yr-1) and Bellingshausen Amundsen sea represents a negative trend (- 0.14 ˜ -0.25%yr-1). Moreover, we performed the correlation analysis between albedo and Antarctic oscillation. As a results, negative area indicate correlation coefficient of - 0.3639 and positive area indicates correlation coefficient of - 0.0741. Theses results sea ice albedo has regional trend according to ocean. Decreasing sea ice trend has negative relationship with Antarctic oscillation, its represent a possibility that sea ice influence atmospheric factor.

Exploring the Link Between Streamflow Trends and Climate Change in Indiana, USA

NASA Astrophysics Data System (ADS)

Kumar, S.; Kam, J.; Thurner, K.; Merwade, V.

2007-12-01

Streamflow trends in Indiana are evaluated for 85 USGS streamflow gaging stations that have continuous unregulated streamflow records varying from 10 to 80 years. The trends are analyzed by using the non-parametric Mann-Kendall test with prior trend-free pre-whitening to remove serial correlation in the data. Bootstrap method is used to establish field significance of the results. Trends are computed for 12 streamflow statistics to include low-, medium- (median and mean flow), and high-flow conditions on annual and seasonal time step. The analysis is done for six study periods, ranging from 10 years to more than 65 years, all ending in 2003. The trends in annual average streamflow, for 50 years study period, are compared with annual average precipitation trends from 14 National Climatic Data Center (NCDC) stations in Indiana, that have 50 years of continuous daily record. The results show field significant positive trends in annual low and medium streamflow statistics at majority of gaging stations for study periods that include 40 or more years of records. In seasonal analysis, all flow statistics in summer and fall (low flow seasons), and only low flow statistics in winter and spring (high flow seasons) are showing positive trends. No field significant trends in annual and seasonal flow statistics are observed for study periods that include 25 or fewer years of records, except for northern Indiana where localized negative trends are observed in 10 and 15 years study periods. Further, stream flow trends are found to be highly correlated with precipitation trends on annual time step. No apparent climate change signal is observed in Indiana stream flow records.

Teleconnections in the Presence of Climate Change: A Case Study of the Annular Modes

NASA Astrophysics Data System (ADS)

Gerber, Edwin; Baldwin, Mark

2010-05-01

Long model integrations of future and past climates present a problem for defining teleconnection patterns through Empirical Orthogonal Function (EOF) or correlation analysis when trends in the underlying climate begin to dominate the covariance structure. Similar issues may soon appear in observations as the record becomes longer, especially if climate trends accelerate. The Northern and Southern Annular Modes provide a prime example, because the poleward shift of the jet streams strongly projects onto these patterns, particularly in the Southern Hemisphere. Climate forecasts of the 21st century by chemistry climate models provide a case study. Computation of the annular modes in these long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The new procedure involves two key changes. First, the global mean geopotential height is removed at each time step before computing anomalies. This is particularly important high in the atmosphere, where seasonal variations in geopotential height become significant, and filters out trends due to changes in the temperature structure of the atmosphere. Pattern definition can be very sensitive near the tropopause, as regions of the atmosphere that used to be more of stratospheric character begin to take on tropospheric characteristics as the tropopause rises. The second change is to define anomalies relative to a slowly evolving seasonal climatology, so that the covariance structure reflects internal variability. Once these changes are accounted for, it is found that the zonal mean variability of the atmosphere stays remarkably constant, despite significant changes in the baseline climate forecast for the rest of the century. This stability of the internal variability makes it possible to relate trends in climate to teleconnections.

Climatic Redistribution of Canada's Water Resources (CROCWR): An analysis of spatial and temporal hydrological trends and patterns in western Canada

NASA Astrophysics Data System (ADS)

Bawden, A. J.; Burn, D. H.; Prowse, T. D.

2012-12-01

Climate variability and change can have profound impacts on the hydrologic regime of a watershed. These effects are likely to be especially severe in regions particularly sensitive to changes in climate, such as the Canadian north, or when there are other stresses on the hydrologic regime, such as may occur when there are large withdrawals from, or land-use changes within, a watershed. A recent report of the Intergovernmental Panel on Climate Change (IPCC) stressed that future climate is likely to accelerate the hydrologic cycle and hence may affect water security in certain locations. For some regions, this will mean enhanced access to water resources, but because the effects will not be spatially uniform, other regions will experience reduced access. Understanding these patterns is critical for water managers and government agencies in western Canada - an area of highly contrasting hydroclimatic regimes and overlapping water-use and jurisdictional borders - as adapting to climate change may require reconsideration of inter-regional transfers and revised allocation of water resources to competing industrial sectors, including agriculture, hydroelectric production, and oil and gas. This research involves the detection and examination of spatial and temporal streamflow trends in western Canadian rivers as a response to changing climatic factors, including temperature, precipitation, snowmelt, and the synoptic patterns controlling these drivers. The study area, known as the CROCWR region, extends from the Pacific coast of British Columbia as far east as the Saskatchewan-Manitoba border and from the Canada-United States international border through a large portion of the Northwest Territories. This analysis examines hydrologic trends in monthly and annual streamflow for a collection of 34 hydrometric gauging stations believed to adequately represent the overall effects of climate variability and change on flows in western Canada by means of the Mann-Kendall non-parametric trend test. Large-scale spatial patterns are determined through examination of trends and contrasts between upper and lower reaches of individual sub-basins, as well as via analysis of streamflow redistributions within the CROCWR region as an entirety (i.e. north, south, east and/or west-moving patterns). Results are used to predict future implications of hydroclimatic variability and change on western Canada's water resources and recommend measures to be taken by water managers in response to these changes. This research is part of a larger hydroclimatic study that includes an analysis of the climatic drivers contributing to shifting flow regimes in western Canada as well as a study of the controlling synoptic patterns and teleconnections associated with changes in these driving forces.

Recent shifts in Himalayan vegetation activity trends in response to climatic change and environmental drivers

NASA Astrophysics Data System (ADS)

Mishra, N. B.; Mainali, K. P.

2016-12-01

Climatic changes along with anthropogenic disturbances are causing dramatic ecological impacts in mid to high latitude mountain vegetation including in the Himalayas which are ecologically sensitive environments. Given the challenges associated with in situ vegetation monitoring in the Himalayas, remote sensing based quantification of vegetation dynamics can provide essential ecological information on changes in vegetation activity that may consist of alternative sequence of greening and/or browning periods. This study utilized a trend break analysis procedure for detection of monotonic as well as abrupt (either interruption or reversal) trend changes in smoothed normalized difference vegetation index satellite time-series data over the Himalayas. Overall, trend breaks in vegetation greenness showed high spatio-temporal variability in distribution considering elevation, ecoregion and land cover/use stratifications. Interrupted greening was spatially most dominant in all Himalayan ecoregions followed by abrupt browning. Areas showing trend reversal and monotonic trends appeared minority. Trend type distribution was strongly dependent on elevation as majority of greening (with or without interruption) occurred at lower elevation areas at higher elevation were dominantly. Ecoregion based stratification of trend types highlighted some exception to this elevational dependence as high altitude ecoregions of western Himalayas showed significantly less browning compared to the ecoregions in eastern Himalaya. Land cover/use based analysis of trend distribution showed that interrupted greening was most dominant in closed needleleafed forest following by rainfed cropland and mosaic croplands while interrupted browning most dominant in closed to open herbaceous vegetation found at higher elevation areas followed by closed needleleafed forest and closed to open broad leafed evergreen forests. Spatial analysis of trend break timing showed that for majority of areas experiencing interrupted greening, break in trend occurred later compared to areas with interrupted browning where break trend was observed much earlier. These results have significant implications for environmental management in the context of climate change and ecosystem dynamics in the Himalayas.

Comparison of Mean Climate Trends in the Northern Hemisphere Between N.C.E.P. and Two Atmosphere-Ocean Model Forced Runs

NASA Technical Reports Server (NTRS)

Lucarini, Valerio; Russell, Gary L.; Hansen, James E. (Technical Monitor)

2002-01-01

Results are presented for two greenhouse gas experiments of the Goddard Institute for Space Studies Atmosphere-Ocean Model (AOM). The computed trends of surface pressure, surface temperature, 850, 500 and 200 mb geopotential heights and related temperatures of the model for the time frame 1960-2000 are compared to those obtained from the National Centers for Environmental Prediction observations. A spatial correlation analysis and mean value comparison are performed, showing good agreement. A brief general discussion about the statistics of trend detection is presented. The domain of interest is the Northern Hemisphere (NH) because of the higher reliability of both the model results and the observations. The accuracy that this AOM has in describing the observed regional and NH climate trends makes it reliable in forecasting future climate changes.

Impact of land-use and climatic changes on hydrology of the Himalayan Basin: A case study of the Kosi Basin

NASA Astrophysics Data System (ADS)

Sharma, Keshav Prasad

1997-10-01

Land-use and climatic changes are of major concern in the Himalayan region because of their potential impacts on a predominantly agriculture-based economy and a regional hydrology dominated by strong seasonality. Such concerns are not limited to any particular basin but exist throughout the region including the downstream plain areas. As a representative basin of the Himalayas, we studied the Kosi basin (54,000 km2) located in the mountainous area of the central Himalayan region. We analyzed climatic and hydrologic information to assess the impacts of existing and potential future land-use and climatic changes over the basin. The assessment of anthropogenic inputs showed that the population grew at a compound growth rate of about one percent per annum over the basin during the last four decades. The comparison of land-use data based on the surveys made in the 1960s, and the surveys of 1978-79 did not reveal noticeable trends in land-use change. Analysis of meteorological and hydrological trends using parametric and nonparametric statistics for monthly data from 1947 to 1993 showed some increasing tendency for temperature and precipitation. Statistical tests of hydrological trends indicated an overall decrease of discharge along mainstem Kosi River and its major tributaries. The decreasing trends of streamflow were more significant during low-flow months. Statistical analysis of homogeneity showed that the climatological as well as the hydrological trends were more localized in nature lacking distinct basinwide significance. Statistical analysis of annual sediment time series, available for a single station on the Kosi River did not reveal a significant trend. We used water balance, statistical correlation, and distributed deterministic modeling approaches to analyze the hydrological sensitivity of the basin to possible land-use and climatic changes. The results indicated a stronger influence of basin characteristics compared to climatic characteristics on flow regime. Among the climatic variables, hydrologic response was much more sensitive to changes in precipitation, and the response was more significant in the drier areas of the basin. Rapid retreat of glaciers due to potential global warming was shown to be as important as projected deforestation scenarios in regulating sediment flux over the basin.

Climatic trends over Ethiopia: regional signals and drivers

USGS Publications Warehouse

Jury, Mark R.; Funk, Christopher C.

2013-01-01

This study analyses observed and projected climatic trends over Ethiopia, through analysis of temperature and rainfall records and related meteorological fields. The observed datasets include gridded station records and reanalysis products; while projected trends are analysed from coupled model simulations drawn from the IPCC 4th Assessment. Upward trends in air temperature of + 0.03 °C year−1 and downward trends in rainfall of − 0.4 mm month−1 year−1 have been observed over Ethiopia's southwestern region in the period 1948-2006. These trends are projected to continue to 2050 according to the Geophysical Fluid Dynamics Lab model using the A1B scenario. Large scale forcing derives from the West Indian Ocean where significant warming and increased rainfall are found. Anticyclonic circulations have strengthened over northern and southern Africa, limiting moisture transport from the Gulf of Guinea and Congo. Changes in the regional Walker and Hadley circulations modulate the observed and projected climatic trends. Comparing past and future patterns, the key features spread westward from Ethiopia across the Sahel and serve as an early warning of potential impacts.

Sea-Level Trend Uncertainty With Pacific Climatic Variability and Temporally-Correlated Noise

NASA Astrophysics Data System (ADS)

Royston, Sam; Watson, Christopher S.; Legrésy, Benoît; King, Matt A.; Church, John A.; Bos, Machiel S.

2018-03-01

Recent studies have identified climatic drivers of the east-west see-saw of Pacific Ocean satellite altimetry era sea level trends and a number of sea-level trend and acceleration assessments attempt to account for this. We investigate the effect of Pacific climate variability, together with temporally-correlated noise, on linear trend error estimates and determine new time-of-emergence (ToE) estimates across the Indian and Pacific Oceans. Sea-level trend studies often advocate the use of auto-regressive (AR) noise models to adequately assess formal uncertainties, yet sea level often exhibits colored but non-AR(1) noise. Standard error estimates are over- or under-estimated by an AR(1) model for much of the Indo-Pacific sea level. Allowing for PDO and ENSO variability in the trend estimate only reduces standard errors across the tropics and we find noise characteristics are largely unaffected. Of importance for trend and acceleration detection studies, formal error estimates remain on average up to 1.6 times those from an AR(1) model for long-duration tide gauge data. There is an even chance that the observed trend from the satellite altimetry era exceeds the noise in patches of the tropical Pacific and Indian Oceans and the south-west and north-east Pacific gyres. By including climate indices in the trend analysis, the time it takes for the observed linear sea-level trend to emerge from the noise reduces by up to 2 decades.

Changing pattern of natural hazards due to extreme hydro-meteorological conditions (Apulia, southern Italy)

NASA Astrophysics Data System (ADS)

Polemio, Maurizio; Lonigro, Teresa

2013-04-01

Recent international researches have underlined the evidences of climate changes throughout the world. Among the consequences of climate change, there is the increase in the frequency and magnitude of natural disasters, such as droughts, windstorms, heat waves, landslides, floods and secondary floods (i.e. rapid accumulation or pounding of surface water with very low flow velocity). The Damaging Hydrogeological Events (DHEs) can be defined as the occurrence of one or more simultaneous aforementioned phenomena causing damages. They represent a serious problem, especially in DHE-prone areas with growing urbanisation. In these areas the increasing frequency of extreme hydrological events could be related to climate variations and/or urban development. The historical analysis of DHEs can support decision making and land-use planning, ultimately reducing natural risks. The paper proposes a methodology, based on both historical and time series approaches, used for describing the influence of climatic variability on the number of phenomena observed. The historical approach is finalised to collect phenomenon historical data. The historical flood and landslide data are important for the comprehension of the evolution of a study area and for the estimation of risk scenarios as a basis for civil protection purposes. Phenomenon historical data is useful for expanding the historical period of investigation in order to assess the occurrence trend of DHEs. The time series approach includes the collection and the statistical analysis of climatic and rainfall data (monthly rainfall, wet days, rainfall intensity, and temperature data together with the annual maximum of short-duration rainfall data, from 1 hour to 5 days), which are also used as a proxy for floods and landslides. The climatic and rainfall data are useful to characterise the climate variations and trends and to roughly assess the effects of these trends on river discharge and on the triggering of landslides. The time series approach is completed by tools to analyse simultaneously all data types. The methodology was tested considering a selected Italian region (Apulia, southern Italy). The data were collected in two databases: a damaging hydrogeological event database (1186 landslides and floods since 1918) and a climate database (from 1877; short-duration rainfall from 1921). A statistically significant decreasing trend of rainfall intensity and an increasing trend of temperature, landslides, and DHEs were observed. A generalised decreasing trend of short-duration rainfall was observed. If there is not an evident relationship between climate variability and the variability of DHE occurrences, the role of anthropogenic modifications (increasing use or misuse of flood- and landslide-prone areas) could be hypothesized to justify the increasing occurrences of floods and landslides.. This study identifies the advantages of a simplifying approach to reduce the intrinsic complexities of the spatial-temporal analysis of climate variability, permitting the simultaneous analysis of the modification of flood and landslide occurrences.

The long-term trends (1982-2006) in vegetation greenness of the alpine ecosystem in the Qinghai-Tibetan Plateau

USGS Publications Warehouse

Zhang, Li; Guo, Huadong; Wang, Cuizhen; Ji, Lei; Li, Jing; Wang, Kun; Dai, Lin

2014-01-01

The increased rate of annual temperature in the Qinghai-Tibetan Plateau exceeded all other areas of the same latitude in recent decades. The influence of the warming climate on the alpine ecosystem of the plateau was distinct. An analysis of alpine vegetation under changes in climatic conditions was conducted in this study. This was done through an examination of vegetation greenness and its relationship with climate variability using the Advanced Very High Resolution Radiometer satellite imagery and climate datasets. Vegetation in the plateau experienced a positive trend in greenness, with 18.0 % of the vegetated areas exhibiting significantly positive trends, which were primarily located in the eastern and southwestern parts of the plateau. In grasslands, 25.8 % of meadows and 14.1 % of steppes exhibited significant upward trends. In contrast, the broadleaf forests experienced a trend of degradation. Temperature, particularly summer temperature, was the primary factor promoting the vegetation growth in the plateau. The wetter and warmer climate in the east contributed to the favorable conditions for vegetation. The alpine meadow was mostly sensitive to temperature, while the steppes were sensitive to both temperature and precipitation. Although a warming climate was expected to be beneficial to vegetation growth in the alpine region, the rising temperature coupled with reduced precipitation in the south did not favor vegetation growth due to low humidity and poor soil moisture conditions.

Simulated trends of extreme climate indices for the Carpathian basin using outputs of different regional climate models

NASA Astrophysics Data System (ADS)

Pongracz, R.; Bartholy, J.; Szabo, P.; Pieczka, I.; Torma, C. S.

2009-04-01

Regional climatological effects of global warming may be recognized not only in shifts of mean temperature and precipitation, but in the frequency or intensity changes of different climate extremes. Several climate extreme indices are analyzed and compared for the Carpathian basin (located in Central/Eastern Europe) following the guidelines suggested by the joint WMO-CCl/CLIVAR Working Group on climate change detection. Our statistical trend analysis includes the evaluation of several extreme temperature and precipitation indices, e.g., the numbers of severe cold days, winter days, frost days, cold days, warm days, summer days, hot days, extremely hot days, cold nights, warm nights, the intra-annual extreme temperature range, the heat wave duration, the growing season length, the number of wet days (using several threshold values defining extremes), the maximum number of consecutive dry days, the highest 1-day precipitation amount, the greatest 5-day rainfall total, the annual fraction due to extreme precipitation events, etc. In order to evaluate the future trends (2071-2100) in the Carpathian basin, daily values of meteorological variables are obtained from the outputs of various regional climate model (RCM) experiments accomplished in the frame of the completed EU-project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). Horizontal resolution of the applied RCMs is 50 km. Both scenarios A2 and B2 are used to compare past and future trends of the extreme climate indices for the Carpathian basin. Furthermore, fine-resolution climate experiments of two additional RCMs adapted and run at the Department of Meteorology, Eotvos Lorand University are used to extend the trend analysis of climate extremes for the Carpathian basin. (1) Model PRECIS (run at 25 km horizontal resolution) was developed at the UK Met Office, Hadley Centre, and it uses the boundary conditions from the HadCM3 GCM. (2) Model RegCM3 (run at 10 km horizontal resolution) was developed by Giorgi et al. and it is available from the ICTP (International Centre for Theoretical Physics). Analysis of the simulated daily temperature datasets suggests that the detected regional warming is expected to continue in the 21st century. Cold temperature extremes are projected to decrease while warm extremes tend to increase significantly. Expected changes of annual precipitation indices are small, but generally consistent with the detected trends of the 20th century. Based on the simulations, extreme precipitation events are expected to become more intense and more frequent in winter, while a general decrease of extreme precipitation indices is expected in summer.

Seasonal responses of terrestrial ecosystem water-use efficiency to climate change.

PubMed

Huang, Mengtian; Piao, Shilong; Zeng, Zhenzhong; Peng, Shushi; Ciais, Philippe; Cheng, Lei; Mao, Jiafu; Poulter, Ben; Shi, Xiaoying; Yao, Yitong; Yang, Hui; Wang, Yingping

2016-06-01

Ecosystem water-use efficiency (EWUE) is an indicator of carbon-water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET). Previous research suggests an increasing long-term trend in annual EWUE over many regions and is largely attributed to the physiological effects of rising CO2 . The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982-2008. The seasonal cycle for two variants of EWUE, water-use efficiency (WUE, GPP/ET), and transpiration-based WUE (WUEt , the ratio of GPP and transpiration), is analyzed from 0.5° gridded fields from four process-based models and satellite-based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite-based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite-based products. Trend analysis, based on process-model factorial simulations separating effects of climate, CO2 , and nitrogen deposition (NDEP), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid- and high northern latitudes. In these regions, spring climate change has amplified the effect of CO2 in increasing WUE by more than 0.005 gC m(-2)  mm(-1)  yr(-1) for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO2, and NDEP. © 2015 John Wiley & Sons Ltd.

Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran

NASA Astrophysics Data System (ADS)

Ahani, Hossien; Kherad, Mehrzad; Kousari, Mohammad Reza; van Roosmalen, Lieke; Aryanfar, Ramin; Hosseini, Seyyed Mashaallah

2013-05-01

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955-2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann-Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.

Sensitivity analysis of monthly reference crop evapotranspiration trends in Iran: a qualitative approach

NASA Astrophysics Data System (ADS)

Mosaedi, Abolfazl; Ghabaei Sough, Mohammad; Sadeghi, Sayed-Hossein; Mooshakhian, Yousof; Bannayan, Mohammad

2017-05-01

The main objective of this study was to analyze the sensitivity of the monthly reference crop evapotranspiration (ETo) trends to key climatic factors (minimum and maximum air temperature ( T max and T min), relative humidity (RH), sunshine hours ( t sun), and wind speed ( U 2)) in Iran by applying a qualitative detrended method, rather than the historical mathematical approach. Meteorological data for the period of 1963-2007 from five synoptic stations with different climatic characteristics, including Mashhad (mountains), Tabriz (mountains), Tehran (semi-desert), Anzali (coastal wet), and Shiraz (semi-mountains) were used to address this objective. The Mann-Kendall test was employed to assess the trends of ETo and the climatic variables. The results indicated a significant increasing trend of the monthly ETo for Mashhad and Tabriz for most part of the year while the opposite conclusion was drawn for Tehran, Anzali, and Shiraz. Based on the detrended method, RH and U 2 were the two main variables enhancing the negative ETo trends in Tehran and Anzali stations whereas U 2 and temperature were responsible for this observation in Shiraz. On the other hand, the main meteorological variables affecting the significant positive trend of ETo were RH and t sun in Tabriz and T min, RH, and U 2 in Mashhad. Although a relative agreement was observed in terms of identifying one of the first two key climatic variables affecting the ETo trend, the qualitative and the quantitative sensitivity analysis solutions did never coincide. Further research is needed to evaluate this interesting finding for other geographic locations, and also to search for the major causes of this discrepancy.

The influence of ENSO, PDO and PNA on secular rainfall variations in Hawai`i

NASA Astrophysics Data System (ADS)

Frazier, Abby G.; Elison Timm, Oliver; Giambelluca, Thomas W.; Diaz, Henry F.

2017-11-01

Over the last century, significant declines in rainfall across the state of Hawai`i have been observed, and it is unknown whether these declines are due to natural variations in climate, or manifestations of human-induced climate change. Here, a statistical analysis of the observed rainfall variability was applied as first step towards better understanding causes for these long-term trends. Gridded seasonal rainfall from 1920 to 2012 is used to perform an empirical orthogonal function (EOF) analysis. The leading EOF components are correlated with three indices of natural climate variations (El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Pacific North American (PNA)), and multiple linear regression (MLR) is used to model the leading components with climate indices. PNA is the dominant mode of wet season (November-April) variability, while ENSO is most significant in the dry season (May-October). To assess whether there is an anthropogenic influence on rainfall, two methods are used: a linear trend term is included in the MLR, and pattern correlation coefficients (PCC) are calculated between recent rainfall trends and future changes in rainfall projected by downscaling methods. PCC results indicate that recent observed rainfall trends in the wet season are positively correlated with future expected changes in rainfall, while dry season PCC results do not show a clear pattern. The MLR results, however, show that the trend term adds significantly to model skill only in the dry season. Overall, MLR and PCC results give weak and inconclusive evidence for detection of anthropogenic signals in the observed rainfall trends.

Sustainability of winter tourism in a changing climate over Kashmir Himalaya.

PubMed

Dar, Reyaz Ahmad; Rashid, Irfan; Romshoo, Shakil Ahmad; Marazi, Asif

2014-04-01

Mountain areas are sensitive to climate change. Implications of climate change can be seen in less snow, receding glaciers, increasing temperatures, and decreasing precipitation. Climate change is also a severe threat to snow-related winter sports such as skiing, snowboarding, and cross-country skiing. The change in climate will put further pressure on the sensitive environment of high mountains. Therefore, in this study, an attempt has been made to know the impact of climate change on the snow precipitation, water resources, and winter tourism in the two famous tourist resorts of the Kashmir Valley. Our findings show that winters are getting prolonged with little snow falls on account of climate change. The average minimum and maximum temperatures are showing statistically significant increasing trends for winter months. The precipitation is showing decreasing trends in both the regions. A considerable area in these regions remains under the snow and glacier cover throughout the year especially during the winter and spring seasons. However, time series analysis of LandSat MODIS images using Normalized Difference Snow Index shows a decreasing trend in snow cover in both the regions from past few years. Similarly, the stream discharge, comprising predominantly of snow- and glacier-melt, is showing a statistically significant declining trend despite the melting of these glaciers. The predicted futuristic trends of temperature from Predicting Regional Climates for Impact Studies regional climate model are showing an increase which may enhance snow-melting in the near future posing a serious threat to the sustainability of winter tourism in the region. Hence, it becomes essential to monitor the changes in temperature and snow cover depletion in these basins in order to evaluate their effect on the winter tourism and water resources in the region.

Urban and peri-urban precipitation and air temperature trends in mega cities of the world using multiple trend analysis methods

NASA Astrophysics Data System (ADS)

Ajaaj, Aws A.; Mishra, Ashok K.; Khan, Abdul A.

2018-04-01

Urbanization plays an important role in altering local to regional climate. In this study, the trends in precipitation and the air temperature were investigated for urban and peri-urban areas of 18 mega cities selected from six continents (representing a wide range of climatic patterns). Multiple statistical tests were used to examine long-term trends in annual and seasonal precipitation and air temperature for the selected cities. The urban and peri-urban areas were classified based on the percentage of land imperviousness. Through this study, it was evident that removal of the lag-k serial correlation caused a reduction of approximately 20 to 30% in significant trend observability for temperature and precipitation data. This observation suggests that appropriate trend analysis methodology for climate studies is necessary. Additionally, about 70% of the urban areas showed higher positive air temperature trends, compared with peri-urban areas. There were not clear trend signatures (i.e., mix of increase or decrease) when comparing urban vs peri-urban precipitation in each selected city. Overall, cities located in dry areas, for example, in Africa, southern parts of North America, and Eastern Asia, showed a decrease in annual and seasonal precipitation, while wetter conditions were favorable for cities located in wet regions such as, southeastern South America, eastern North America, and northern Europe. A positive relationship was observed between decadal trends of annual/seasonal air temperature and precipitation for all urban and peri-urban areas, with a higher rate being observed for urban areas.

Evapotranspiration trends over the eastern United States during the 20th century

USGS Publications Warehouse

Kramer, Ryan J.; Bounoua, Lahouari; Zhang, Ping; Wolfe, Robert E.; Huntington, Thomas G.; Imhoff, Marc L.; Thome, Kurtis; Noyce, Genevieve L.

2015-01-01

Most models evaluated by the Intergovernmental Panel for Climate change estimate projected increases in temperature and precipitation with rising atmospheric CO2 levels. Researchers have suggested that increases in CO2 and associated increases in temperature and precipitation may stimulate vegetation growth and increase evapotranspiration (ET), which acts as a cooling mechanism, and on a global scale, may slow the climate-warming trend. This hypothesis has been modeled under increased CO2 conditions with models of different vegetation-climate dynamics. The significance of this vegetation negative feedback, however, has varied between models. Here we conduct a century-scale observational analysis of the Eastern US water balance to determine historical evapotranspiration trends and whether vegetation greening has affected these trends. We show that precipitation has increased significantly over the twentieth century while runoff has not. We also show that ET has increased and vegetation growth is partially responsible.

Twitter Analytics: Are the U.S. Coastal Regions Prepared for Climate Change in 2017?

NASA Astrophysics Data System (ADS)

Singleton, S. L.; Kumar, S.

2017-12-01

According to the U.S. National Climate Assessment, the Southeast Coast and Gulf Coast of the United States are particularly susceptible to sea level rise, heat waves, hurricanes and less accessibility to clean water due to climate change. This is because of the extreme variation of topography in these two regions. Preparation for climate change consequences can only occur with conversation, which is a method of bringing awareness to the issue. Over the past decade, social media has taken over the spectrum of information exchange in the United States. Social Network Analysis (SNA) is a field that is emerging with the growth in popularity of social media. SNA is the practice of analyzing trends in volume and opinion of a population of social media users. Twitter, one popular social media platform, is one of the largest microblogging sites in the world, and it provides an abundance of data related to the trending topics such as climate change. Twitter analytics is a type of SNA performed on data from the tweets of Twitter users. In this work, Twitter analytics is performed on the data generated from the Twitter users in the United States, who were talking about climate change, global warming and/or CO2, over the course of one year (July 2016 - June 2017). Specifically, a regional comparative analysis on the coastal U.S. regions was conducted to recognize which region(s) is/are falling behind on the conversation about climate change. Sentiment analysis was also performed to understand the trends in opinion about climate change that vary over time. Experimental results determined that the southeast coast of the United States is deficient in their discussion about climate change compared to the other coastal regions. Igniting the conversation about this issue in these regions will mitigate the disasters due to climate change by increasing awareness in the people of these regions so they can properly prepare.

Assessment of impacts of climate change on gender in the context of Nepal

NASA Astrophysics Data System (ADS)

Paudel, R.; Acharya, A.

2016-12-01

Climate change and its impact on gender in the context of Nepal has not been clearly understood due to lack of proper scientific research in terms of gender and climate change. Climate induced disasters such as droughts, floods, GLOFs, and landslides affect men and women differently. This study is conducted to analyze the scenario of gender equality, and impacts of climate change on gender in Nepal. This study also identifies gender based adaptation approaches through the use of observed climate data, and projected and modeled demographic data such as Adolescent Fertility Rate, Labor Force Participation Rate, and Maternal Mortality Ratio. The major tasks of this project include the calculation of Gender Inequality Index (GII), trend analysis and correlation between GII and temperature, that helps to evaluate the women vulnerability and identify the gender based adaptation interventions in Nepal. The required data on gender and temperature are obtained from World Bank and Department of Hydrology and Meteorology, Nepal. GII is calculated for almost 26 years starting from the year 1990 by utilizing a tool "Calculating the Indices using Excel" provided through the UNDP. The Reproductive Health Index (RHI), Empowerment Index (EI), and Labor Market Index (LMI) that are required to determine GII are also calculated through the use of same tool. The trend analysis shows that GII follows a decreasing trend indicating higher gender equality. The correlation analysis shows the temperature positively correlated with RHI (r=0.64), EI Female (r=0.61), and EI Male (r=0.73). In case of LMI, temperature is positively correlated with female (r=0.14) and negatively correlated with male (r=-0.57). The analysis depicts negative correlation (r=-0.68) between climate change and GII. This research will provide some valuable insights in the research relating to gender and climate change that could help gender advocates and policymakers in developing further plans for women empowerment.

A new statistical tool for NOAA local climate studies

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Meyers, J. C.; Hollingshead, A.

2011-12-01

The National Weather Services (NWS) Local Climate Analysis Tool (LCAT) is evolving out of a need to support and enhance the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) field offices' ability to efficiently access, manipulate, and interpret local climate data and characterize climate variability and change impacts. LCAT will enable NOAA's staff to conduct regional and local climate studies using state-of-the-art station and reanalysis gridded data and various statistical techniques for climate analysis. The analysis results will be used for climate services to guide local decision makers in weather and climate sensitive actions and to deliver information to the general public. LCAT will augment current climate reference materials with information pertinent to the local and regional levels as they apply to diverse variables appropriate to each locality. The LCAT main emphasis is to enable studies of extreme meteorological and hydrological events such as tornadoes, flood, drought, severe storms, etc. LCAT will close a very critical gap in NWS local climate services because it will allow addressing climate variables beyond average temperature and total precipitation. NWS external partners and government agencies will benefit from the LCAT outputs that could be easily incorporated into their own analysis and/or delivery systems. Presently we identified five existing requirements for local climate: (1) Local impacts of climate change; (2) Local impacts of climate variability; (3) Drought studies; (4) Attribution of severe meteorological and hydrological events; and (5) Climate studies for water resources. The methodologies for the first three requirements will be included in the LCAT first phase implementation. Local rate of climate change is defined as a slope of the mean trend estimated from the ensemble of three trend techniques: (1) hinge, (2) Optimal Climate Normals (running mean for optimal time periods), (3) exponentially-weighted moving average. Root mean squared error is used to determine the best fit of trend to the observations with the least error. The studies of climate variability impacts on local extremes use composite techniques applied to various definitions of local variables: from specified percentiles to critical thresholds. Drought studies combine visual capabilities of Google maps with statistical estimates of drought severity indices. The process of development will be linked to local office interactions with users to ensure the tool will meet their needs as well as provide adequate training. A rigorous internal and tiered peer-review process will be implemented to ensure the studies are scientifically-sound that will be published and submitted to the local studies catalog (database) and eventually to external sources, such as the Climate Portal.

Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

NASA Astrophysics Data System (ADS)

Liu, Meixian; Xu, Xianli; Sun, Alex

2015-07-01

Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

Climate change and human health: what are the research trends? A scoping review protocol

PubMed Central

Herlihy, Niamh; Bar-Hen, Avner; Verner, Glenn; Fischer, Helen; Sauerborn, Rainer; Depoux, Anneliese; Flahault, Antoine; Schütte, Stefanie

2016-01-01

Introduction For 28 years, the Intergovernmental Panel on Climate Change (IPCC) has been assessing the potential risks associated with anthropogenic climate change. Although interest in climate change and health is growing, the implications arising from their interaction remain understudied. Generating a greater understanding of the health impacts of climate change could be key step in inciting some of the changes necessary to decelerate global warming. A long-term and broad overview of the existing scientific literature in the field of climate change and health is currently missing in order to ensure that all priority areas are being adequately addressed. In this paper we outline our methods to conduct a scoping review of the published peer-reviewed literature on climate change and health between 1990 and 2015. Methods and analysis A detailed search strategy will be used to search the PubMed and Web of Science databases. Specific inclusion and exclusion criteria will be applied in order to capture the most relevant literature in the time frame chosen. Data will be extracted, categorised and coded to allow for statistical analysis of the results. Ethics and dissemination No ethical approval was required for this study. A searchable database of climate change and health publications will be developed and a manuscript will be complied for publication and dissemination of the findings. We anticipate that this study will allow us to map the trends observed in publications over the 25-year time period in climate change and health research. It will also identify the research areas with the highest volume of publications as well as highlight the research trends in climate change and health. PMID:28011805

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

Spatial and temporal variations of wind erosion climatic erosivity in the farming-pastoral zone of Northern China

NASA Astrophysics Data System (ADS)

Yue, Shuping; Yang, Ruixin; Yan, Yechao; Yang, Zhengwei; Wang, Dandan

2018-03-01

Wind erosion climatic erosivity is an important parameter to assess the possible effects of climatic conditions on wind erosion. In this paper, the wind erosion climatic factor (C-factor), which was used to quantify the wind erosion climatic erosivity, was calculated for the period 1960-2014 based on monthly meteorological data collected from 101 stations in the farming-pastoral zone of Northern China. The Mann-Kendall (M-K) test, trend analysis, and geostatistical analysis methods were used to explore the spatial and temporal characteristics of the wind erosion climatic erosivity in this region. The result suggests that the annual C-factor, with a maximum of 76.05 in 1969 and a minimum of 26.57 in 2007, has a significant decreasing trend over the past 55 years. Strong seasonality in the C-factor was found, with the highest value in spring, which accounts for a significant proportion of the annual C-factor (41.46%). However, the coefficient of variation of the seasonal C-factor reaches a maximum in winter and a minimum in spring. The mean annual C-factor varies substantially across the region. Areas with high values of the mean annual C-factor (C ≥ 100) are located in Ulanqab and Dingxi, while areas with low values (C ≤ 10) lie in Lanzhou, Linxia, Dingxi, Xining, and Chengde. Spatial analysis on the trend of the C-factor reveals that 81% of the stations show statistically significant decreases at a 90% confidence level. An examination of the concentration ratio of the C-factor shows that the wind erosion climatic erosivity is concentrated in spring, especially in April, which makes this period particularly important for implementing soil conservation measures.

Trend analysis of evapotranspiration over India: Observed from long-term satellite measurements

NASA Astrophysics Data System (ADS)

Goroshi, Sheshakumar; Pradhan, Rohit; Singh, Raghavendra P.; Singh, K. K.; Parihar, Jai Singh

2017-12-01

Owing to the lack of consistent spatial time series data on actual evapotranspiration ( ET), very few studies have been conducted on the long-term trend and variability in ET at a national scale over the Indian subcontinent. The present study uses biome specific ET data derived from NOAA satellite's advanced very high resolution radiometer to investigate the trends and variability in ET over India from 1983 to 2006. Trend analysis using the non-parametric Mann-Kendall test showed that the domain average ET decreased during the period at a rate of 0.22 mm year^{-1}. A strong decreasing trend (m = -1.75 mm year^{-1}, F = 17.41, P 0.01) was observed in forest regions. Seasonal analyses indicated a decreasing trend during southwest summer monsoon (m= -0.320 mm season^{-1} year^{-1}) and post-monsoon period (m= -0.188 mm season^{-1 } year^{-1}). In contrast, an increasing trend was observed during northeast winter monsoon (m = 0.156 mm season^{-1 } year^{-1}) and pre-monsoon (m = 0.068 mm season^{-1 } year^{-1}) periods. Despite an overall net decline in the country, a considerable increase ( 4 mm year^{-1}) was observed over arid and semi-arid regions. Grid level correlation with various climatic parameters exhibited a strong positive correlation (r >0.5) of ET with soil moisture and precipitation over semi-arid and arid regions, whereas a negative correlation (r -0.5) occurred with temperature and insolation in dry regions of western India. The results of this analysis are useful for understanding regional ET dynamics and its relationship with various climatic parameters over India. Future studies on the effects of ET changes on the hydrological cycle, carbon cycle, and energy partitioning are needed to account for the feedbacks to the climate.

Response of the groundwater system in the Guanzhong Basin (central China) to climate change and human activities

NASA Astrophysics Data System (ADS)

Wang, Wenke; Zhang, Zaiyong; Duan, Lei; Wang, Zhoufeng; Zhao, Yaqian; Zhang, Qian; Dai, Meiling; Liu, Huizhong; Zheng, Xiaoyan; Sun, Yibo

2018-03-01

The Guanzhong Basin in central China features a booming economy and has suffered severe drought, resulting in serious groundwater depletion in the last 30 years. As a major water resource, groundwater plays a significant role in water supply. The combined impact of climate change and intensive human activities has caused a substantial decline in groundwater recharge and groundwater levels, as well as degradation of groundwater quality and associated changes in the ecosystems. Based on observational data, an integrated approach was used to assess the impact of climate change and human activities on the groundwater system and the base flow of the river basin. Methods included: river runoff records and a multivariate statistical analysis of data including historical groundwater levels and climate; hydro-chemical investigation and trend analysis of the historical hydro-chemical data; wavelet analysis of climate data; and the base flow index. The analyses indicate a clear warming trend and a decreasing trend in rainfall since the 1960s, in addition to increased human activities since the 1970s. The reduction of groundwater recharge in the past 30 years has led to a continuous depletion of groundwater levels, complex changes of the hydro-chemical environment, localized salinization, and a strong decline of the base flow to the river. It is expected that the results will contribute to a more comprehensive management plan for groundwater and the related eco-environment in the face of growing pressures from intensive human activities superimposed on climate change in this region.

Temporal changes and variability in temperature series over Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Suhaila, Jamaludin

2015-02-01

With the current concern over climate change, the descriptions on how temperature series changed over time are very useful. Annual mean temperature has been analyzed for several stations over Peninsular Malaysia. Non-parametric statistical techniques such as Mann-Kendall test and Theil-Sen slope estimation are used primarily for assessing the significance and detection of trends, while a nonparametric Pettitt's test and sequential Mann-Kendall test are adopted to detect any abrupt climate change. Statistically significance increasing trends for annual mean temperature are detected for almost all studied stations with the magnitude of significant trend varied from 0.02°C to 0.05°C per year. The results shows that climate over Peninsular Malaysia is getting warmer than before. In addition, the results of the abrupt changes in temperature using Pettitt's and sequential Mann-Kendall test reveal the beginning of trends which can be related to El Nino episodes that occur in Malaysia. In general, the analysis results can help local stakeholders and water managers to understand the risks and vulnerabilities related to climate change in terms of mean events in the region.

ClimatePad: Enabling public exploration of climate data

NASA Astrophysics Data System (ADS)

Walsh, J. E.; Chapman, W. L.

2012-12-01

Informal learners interested in climate issues can find a wealth of information in the print and online media related to climate and climate change. Throughout these resources, the equal use of generic terms like 'global warming' and 'climate change' suggest a level of nuance in the science that is not easy to convey in this conventional media. Perhaps more than any other discipline, climate literacy has the most potential to be enhanced via the process of cognitive construction and reconstruction, rather than simple transmission of knowledge. Constructionism suggests that meaningful learning happens most effectively if the learner is actively engaged in constructing a product in the real world rather than absorbing information passively. Recent technological innovations have introduced mobile computing devices with sufficient power to do serious data analysis. The potential of these devices to augment climate literacy by turning citizens into scientists has yet to be exploited. We introduce ClimatePad, an iPad application that permits students and public to actively browse climate datasets, construct trends, plot time series, create composite differences and view animations of real-world climate data. Interactions with the ClimatePad permits varying the starting and ending dates of trends and differences. Climate analysis maps and animations can be customized with different color palettes, enticing the user to delve into and absorb the subtleties of the regional and temporal variations of the recent climate record. Finally, user-generated climate visualizations created with ClimatePad can be emailed to friends and shared via Facebook, entraining even more active learners.

Chronic groundwater decline: A multi-decadal analysis of groundwater trends under extreme climate cycles

NASA Astrophysics Data System (ADS)

Le Brocque, Andrew F.; Kath, Jarrod; Reardon-Smith, Kathryn

2018-06-01

Chronic groundwater decline is a concern in many of the world's major agricultural areas. However, a general lack of accurate long-term in situ measurement of groundwater depth and analysis of trends prevents understanding of the dynamics of these systems at landscape scales. This is particularly worrying in the context of future climate uncertainties. This study examines long-term groundwater responses to climate variability in a major agricultural production landscape in southern Queensland, Australia. Based on records for 381 groundwater bores, we used a modified Mann-Kendall non-parametric test and Sen's slope estimator to determine groundwater trends across a 26-year period (1989-2015) and in distinct wet and dry climatic phases. Comparison of trends between climatic phases showed groundwater level recovery during wet phases was insufficient to offset the decline in groundwater level from the previous dry phase. Across the entire 26-year sampling period, groundwater bore levels (all bores) showed an overall significant declining trend (p < 0.05) of an average 0.06 m year-1. Fifty-one bores (20%) exhibited significant declining groundwater levels (p < 0.05), 25 bores (10%) exhibited significant rising groundwater levels (p < 0.05), and 175 bores (70%) exhibited no significant change in groundwater levels (p > 0.05). Spatially, both declining and rising bores were highly clustered. We conclude that over 1989-2015 there is a significant net decline in groundwater levels driven by a smaller subset of highly responsive bores in high irrigation areas within the catchment. Despite a number of targeted policy interventions, chronic groundwater decline remains evident in the catchment. We argue that this is likely to continue and to occur more widely under potential climate change and that policy makers, groundwater users and managers need to engage in planning to ensure the sustainability of this vital resource.

Annual trend patterns of phytoplankton species abundance belie homogeneous taxonomical group responses to climate in the NE Atlantic upwelling.

PubMed

Bode, Antonio; Estévez, M Graciela; Varela, Manuel; Vilar, José A

2015-09-01

Phytoplankton is a sentinel of marine ecosystem change. Composed by many species with different life-history strategies, it rapidly responds to environment changes. An analysis of the abundance of 54 phytoplankton species in Galicia (NW Spain) between 1989 and 2008 to determine the main components of temporal variability in relation to climate and upwelling showed that most of this variability was stochastic, as seasonality and long term trends contributed to relatively small fractions of the series. In general, trends appeared as non linear, and species clustered in 4 groups according to the trend pattern but there was no defined pattern for diatoms, dinoflagellates or other groups. While, in general, total abundance increased, no clear trend was found for 23 species, 14 species decreased, 4 species increased during the early 1990s, and only 13 species showed a general increase through the series. In contrast, series of local environmental conditions (temperature, stratification, nutrients) and climate-related variables (atmospheric pressure indices, upwelling winds) showed a high fraction of their variability in deterministic seasonality and trends. As a result, each species responded independently to environmental and climate variability, measured by generalized additive models. Most species showed a positive relationship with nutrient concentrations but only a few showed a direct relationship with stratification and upwelling. Climate variables had only measurable effects on some species but no common response emerged. Because its adaptation to frequent disturbances, phytoplankton communities in upwelling ecosystems appear less sensitive to changes in regional climate than other communities characterized by short and well defined productive periods. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Trends and variations of pH and hardness in a typical semi-arid river in a monsoon climate region during 1985-2009.

PubMed

Hao, Shaonan; Li, Xuyong; Jiang, Yan; Zhao, Hongtao; Yang, Lei

2016-09-01

The rapid growth of urbanization and industrialization, along with dramatic climate change, has strongly influenced hydrochemical characteristics in recent decades in China and thus could cause the variation of pH and general total hardness of a river. To explore such variations and their potential influencing factors in a river of the monsoon climate region, we analyzed a long-term monitoring dataset of pH, SO4 (2-), NOx, general total hardness (GH), Mg(2+), Ca(2+), and Cl(-) in surface water and groundwater in the Luan River basin from 1985 to 2009. The nonparametric Seasonal Kendall trend test was used to test the long-term trends of pH and GH. Relationship between the affecting factors, pH and GH were discussed. Results showed that pH showed a decreasing trend and that GH had an increasing trend in the long-term. Seasonal variation of pH and GH was mainly due to the typical monsoon climate. Results of correlation analysis showed that the unit area usage amounts of chemical fertilizer, NO3 (-), and SO4 (2-) were negatively correlated with pH in groundwater. In addition, mining activity affected GH spatial variation. Acid deposition, drought, and increasing the use of chemical fertilizers would contribute to the acidification trend, and mining activities would affect the spatial variation of GH. Variations of precipitation and runoff in semi-arid monsoon climate areas had significant influences on the pH and GH. Our findings implied that human activities played a critical role in river acidification in the semi-arid monsoon climate region of northern China.

Trend analysis of watershed-scale precipitation over Northern California by means of dynamically-downscaled CMIP5 future climate projections.

PubMed

Ishida, K; Gorguner, M; Ercan, A; Trinh, T; Kavvas, M L

2017-08-15

The impacts of climate change on watershed-scale precipitation through the 21st century were investigated over eight study watersheds in Northern California based on dynamically downscaled CMIP5 future climate projections from three GCMs (CCSM4, HadGEM2-ES, and MIROC5) under the RCP4.5 and RCP8.5 future climate scenarios. After evaluating the modeling capability of the WRF model, the six future climate projections were dynamically downscaled by means of the WRF model over Northern California at 9km grid resolution and hourly temporal resolution during a 94-year period (2006-2100). The biases in the model simulations were corrected, and basin-average precipitation over the eight study watersheds was calculated from the dynamically downscaled precipitation data. Based on the dynamically downscaled basin-average precipitation, trends in annual depth and annual peaks of basin-average precipitation during the 21st century were analyzed over the eight study watersheds. The analyses in this study indicate that there may be differences between trends of annual depths and annual peaks of watershed-scale precipitation during the 21st century. Furthermore, trends in watershed-scale precipitation under future climate conditions may be different for different watersheds depending on their location and topography even if they are in the same region. Copyright © 2017 Elsevier B.V. All rights reserved.

Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

NASA Astrophysics Data System (ADS)

Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei

2017-09-01

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the "fluctuation threshold" which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (-2.59 to -15.89%). Followed by climatic fluctuations with a range of -2.60 to -4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented "trade-offs" among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (-2.11 to -12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

A Energy Balance Analysis of the Climate Sensitivity to Variations in the Rate of Upwelling in the World Oceans.

NASA Astrophysics Data System (ADS)

Morantine, Michael Creighton

The climate system of the Earth has been under investigation for many years, and the "Green-House Effect" has introduced a sense of urgency into the effort. The globally averaged temperature of the Earth undergoes what is commonly referred to as natural fluctuations in the climate signal. One effort of climate modellers is to isolate the responses of particular climate forcings in order to better understand each effect. The use of energy balance climate models (EBM's) has been one of the major tools in this respect. Studies conducted on the response of the environment to the "Green-House Effect" predict a warming trend. After experiencing such a trend in the early 1900's, however, the globally averaged temperature of the Earth began to decrease in the 1940's and continued this trend for approximately 20 years before resuming its trend of increase. It will be shown that a reduction of ~10% in the upwelling rate in the oceans could produce a decrease in the globally averaged temperature sufficient to explain this departure from the expected trend. The analysis of paleoclimatic indicators has produced strong evidence that the orbital forcing with periods of approximately 21000, 41000 and 93000 years predicted by the Milankovitch Theory is the primary cause of the glacial cycles known to have occurred on the Earth. However, there is a dynamic interaction between the environment and the ice caps that is not completely understood at this time. The paleoclimatic indicators available for the last deglaciation are abundant and well preserved (relative to the evidence of previous glacial periods), and analysis of the evidence indicates that during the most recent deglaciation a pulsation in the polar front occurred on such a small time scale that Milankovitch forcing is ruled out as a possible cause. It will be shown that an abrupt shutdown in the deep-water formation process which feeds the upwelling in the oceans could produce an influence of appropriate magnitude and time-scale to be the source of the dynamic interaction responsible for this abrupt climatic event. The process employed in the dimension reduction used in the formulation of lower-order EBM's will be illustrated through the development of the equations, pointing out the inherent assumptions which must be made when developing one- and two-dimensional models as they are required. One -, two- and three-dimensional energy balance models will be analyzed and the results of climate sensitivity to upwelling variations will be presented graphically for each case.

Sensitivity of intermittent streams to climate variations in the western United States

NASA Astrophysics Data System (ADS)

Eng, K.; Wolock, D.; Dettinger, M. D.

2014-12-01

There is a great deal of interest in streamflow changes caused by climate change because of the potential negative effects on aquatic biota and water supplies. Most previous studies have focused on perennial streams, and only a few studies have examined the effect of climate variability on intermittent streams. Our objective in this study was to evaluate the sensitivity of intermittent streams to historical variability in climate in the semi-arid regions of the western United States. This study was carried out at 45 intermittent streams that had a minimum of 45 years of daily-streamgage record by evaluating: (1) correlations among time series of flow metrics (number of zero-flow events, the average of the central 50% and largest 10% of flows) with climate, and (2) decadal changes in the seasonality and long-term trends of these flow metrics. Results showed strong associations between the low-flow metrics and historical changes in climate. The decadal analysis, in contrast, suggested no significant seasonal shifts or decade-to-decade trends in the low-flow metrics. The lack of trends or changes in seasonality is likely due to unchanged long-term patterns in precipitation over the time period examined.

Comparison of mean climate trends in the Northern Hemisphere between National Centers for Environmental Prediction and two atmosphere-ocean model forced runs

NASA Astrophysics Data System (ADS)

Lucarini, Valerio; Russell, Gary L.

2002-08-01

Results are presented for two greenhouse gas experiments of the Goddard Institute for Space Studies atmosphere-ocean model (AOM). The computed trends of surface pressure; surface temperature; 850, 500, and 200 mbar geopotential heights; and related temperatures of the model for the time frame 1960-2000 are compared with those obtained from the National Centers for Enviromental Prediction (NCEP) observations. The domain of interest is the Northern Hemisphere because of the higher reliability of both the model results and the observations. A spatial correlation analysis and a mean value comparison are performed, showing good agreement in terms of statistical significance for most of the variables considered in the winter and annual means. However, the 850 mbar temperature trends do not show significant positive correlation, and the surface pressure and 850 mbar geopotential height mean trends confidence intervals do not overlap. A brief general discussion about the statistics of trend detection is presented. The accuracy that this AOM has in describing the regional and NH mean climate trends inferred from NCEP through the atmosphere suggests that it may be reliable in forecasting future climate changes.

Statistical approach to the analysis of olive long-term pollen season trends in southern Spain.

PubMed

García-Mozo, H; Yaezel, L; Oteros, J; Galán, C

2014-03-01

Analysis of long-term airborne pollen counts makes it possible not only to chart pollen-season trends but also to track changing patterns in flowering phenology. Changes in higher plant response over a long interval are considered among the most valuable bioindicators of climate change impact. Phenological-trend models can also provide information regarding crop production and pollen-allergen emission. The interest of this information makes essential the election of the statistical analysis for time series study. We analysed trends and variations in the olive flowering season over a 30-year period (1982-2011) in southern Europe (Córdoba, Spain), focussing on: annual Pollen Index (PI); Pollen Season Start (PSS), Peak Date (PD), Pollen Season End (PSE) and Pollen Season Duration (PSD). Apart from the traditional Linear Regression analysis, a Seasonal-Trend Decomposition procedure based on Loess (STL) and an ARIMA model were performed. Linear regression results indicated a trend toward delayed PSE and earlier PSS and PD, probably influenced by the rise in temperature. These changes are provoking longer flowering periods in the study area. The use of the STL technique provided a clearer picture of phenological behaviour. Data decomposition on pollination dynamics enabled the trend toward an alternate bearing cycle to be distinguished from the influence of other stochastic fluctuations. Results pointed to show a rising trend in pollen production. With a view toward forecasting future phenological trends, ARIMA models were constructed to predict PSD, PSS and PI until 2016. Projections displayed a better goodness of fit than those derived from linear regression. Findings suggest that olive reproductive cycle is changing considerably over the last 30years due to climate change. Further conclusions are that STL improves the effectiveness of traditional linear regression in trend analysis, and ARIMA models can provide reliable trend projections for future years taking into account the internal fluctuations in time series. Copyright © 2013 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Suhaila, Jamaludin; Yusop, Zulkifli

2017-06-01

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 Niño and La Niña 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 Niño event.

Climate change and occurrence of diarrheal diseases: evolving facts from Nepal.

PubMed

Bhandari, G P; Gurung, S; Dhimal, M; Bhusal, C L

2012-09-01

Climate change is becoming huge threat to health especially for those from developing countries. Diarrhea as one of the major diseases linked with changing climate. This study has been carried out to assess the relationship between climatic variables, and malaria and to find out the range of non-climatic factors that can confound the relationship of climate change and human health. It is a Retrospective study where data of past ten years relating to climate and disease (diarrhea) variable were analyzed. The study conducted trend analysis based on correlation. The climate related data were obtained from Department of Hydrology and Meteorology. Time Series analysis was also being conducted. The trend of number of yearly cases of diarrhea has been increasing from 1998 to 2001 after which the cases remain constant till 2006.The climate types in Jhapa vary from humid to per-humid based on the moisture index and Mega-thermal based on thermal efficiency. The mean annual temperature is increasing at an average of 0.04 °C/year with maximum temperature increasing faster than the minimum temperature. The annual total rainfall of Jhapa is decreasing at an average rate of -7.1 mm/year. Statistically significant correlation between diarrheal cases occurrence and temperature and rainfall has been observed. However, climate variables were not the significant predictors of diarrheal occurrence. The association among climate variables and diarrheal disease occurrence cannot be neglected which has been showed by this study. Further prospective longitudinal study adjusting influence of non-climatic factors is recommended.

Using CHIRPS Rainfall Dataset to detect rainfall trends in West Africa

NASA Astrophysics Data System (ADS)

Blakeley, S. L.; Husak, G. J.

2016-12-01

In West Africa, agriculture is often rain-fed, subjecting agricultural productivity and food availability to climate variability. Agricultural conditions will change as warming temperatures increase evaporative demand, and with a growing population dependent on the food supply, farmers will become more reliant on improved adaptation strategies. Development of such adaptation strategies will need to consider West African rainfall trends to remain relevant in a changing climate. Here, using the CHIRPS rainfall product (provided by the Climate Hazards Group at UC Santa Barbara), I examine trends in West African rainfall variability. My analysis will focus on seasonal rainfall totals, the structure of the rainy season, and the distribution of rainfall. I then use farmer-identified drought years to take an in-depth analysis of intra-seasonal rainfall irregularities. I will also examine other datasets such as potential evapotranspiration (PET) data, other remotely sensed rainfall data, rain gauge data in specific locations, and remotely sensed vegetation data. Farmer bad year data will also be used to isolate "bad" year markers in these additional datasets to provide benchmarks for identification in the future of problematic rainy seasons.

Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing

NASA Astrophysics Data System (ADS)

Bałdysz, Zofia; Nykiel, Grzegorz; Figurski, Mariusz; Szafranek, Karolina; KroszczyńSki, Krzysztof

2015-08-01

The GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network (EPN) reprocessing performed by the Military University of Technology. For 58 stations Lomb-Scargle periodograms were performed in order to obtain information about the oscillations in ZTD time series. Seasonal components and linear trend were estimated using Least Square Estimation (LSE) and Mann—Kendall trend test was used to confirm the presence of a linear trend designated by LSE method. In order to verify the impact of the length of time series on trend value, comparison between 16 and 18 years were performed.

Future climate data from RCP 4.5 and occurrence of malaria in Korea.

PubMed

Kwak, Jaewon; Noh, Huiseong; Kim, Soojun; Singh, Vijay P; Hong, Seung Jin; Kim, Duckgil; Lee, Keonhaeng; Kang, Narae; Kim, Hung Soo

2014-10-15

Since its reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001-2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future.

Future Climate Data from RCP 4.5 and Occurrence of Malaria in Korea

PubMed Central

Kwak, Jaewon; Noh, Huiseong; Kim, Soojun; Singh, Vijay P.; Hong, Seung Jin; Kim, Duckgil; Lee, Keonhaeng; Kang, Narae; Kim, Hung Soo

2014-01-01

Since its reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001–2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future. PMID:25321875

Correlation analysis of tree growth, climate, and acid deposition in the Lake States.

Treesearch

Margaret R. Holdaway

1990-01-01

Describes research designed to detect subtle regional tree growth trends related to sulfate (SO4) deposition in the Lake States. Correlation methods were used to analyze climatic and SO4 deposition. Effects of SO4 deposition are greater on climatically stressed trees, especially pine species on dry sites, than on unstressed trees. Jack pine growth shows the...

Tertiary climatic change in the marginal northeastern Pacific Ocean

USGS Publications Warehouse

Addicott, W.O.

1969-01-01

Analysis of distributional patterns of shallow-water molluscan faunas of the middle latitudes of the marginal northeastern Pacific Ocean discloses a sharp reversal during the Miocene of the progressive climatic deterioration. A low point in the Tertiary cooling trend during the Oligocene was followed by climatic warming that culminated during the middle Miocene, as illustrated by a series of zoogeographic profiles.

Tertiary climatic change in the marginal northeastern pacific ocean.

PubMed

Addicott, W O

1969-08-08

Analysis of distributional patterns of shallow-water molluscan faunas of the middle latitudes of the marginal northeastern Pacific Ocean discloses a sharp reversal during the Miocene of the progressive climatic deterioration. A low point in the Tertiary cooling trend during the Oligocene was followed by climatic warming that culminated during the middle Miocene, as illustrated by a series of zoogeographic profiles.

Multidecadal Atlantic climate variability and its impact on marine pelagic communities

NASA Astrophysics Data System (ADS)

Harris, Victoria; Edwards, Martin; Olhede, Sofia C.

2014-05-01

A large scale analysis of sea surface temperature (SST) and climate variability over the North Atlantic and its interactions with plankton over the North East Atlantic was carried out to better understand what drives both temperature and species abundance. The spatio-temporal pattern of SST was found to correspond to known climate indices, namely the Atlantic Multidecadal Oscillation (AMO), the East Atlantic Pattern (EAP) and the North Atlantic Oscillation (NAO). The spatial influence of these indices is heterogeneous. Although the AMO is present across all regions, it is most strongly represented in the SST signal in the subpolar gyre region. The NAO instead is strongly weighted in the North Sea and the pattern of its influence is oscillatory in space with a wavelength of approximately 6000 km. Natural oscillations might obscure the influence of climate change effects, making it difficult to determine how much of the variation is attributable to longer term trends. In order to separate the influences of different climate signals the SST signals were decomposed in to spatial and temporal components using principal component analysis (PCA). A similar analysis is carried out on various indicator species of plankton: Calanus finmarchicus, Phytoplankton Colour Index and total copepod abundance, as well as phytoplankton and zooplankton communities. By comparing the two outputs it is apparent that the dominant driver is the recent warming trend, which has a negative influence on C. finmarchicus and total copepods, but has a positive one on phytoplankton colour. However natural oscillations also influence the abundance of plankton, in particular the AMO is a driver of diatom abundance. Fourier principal component analysis, an approach which is novel in terms of the ecological data, was used to analyse the behaviour of various communities averaged over space. The zooplankton community is found to be primarily influenced by climate warming trends. The analysis provides compelling evidence for the hypothesis that cold water species are gradually being replaced by more temperate species in the North Atlantic. This may have detrimental effects for the entire marine ecosystem, by affecting on organisms such as fish larva for example. The second group, a phytoplankton subset consisting primarily of diatom species, is primarily influenced by the AMO rather than the average temperature trend. This result highlights the importance of natural oscillations to certain functional groups, in particular those subgroups which are less directly metabolically affected by changes in temperature.

Climate Informed Low Flow Frequency Analysis Using Nonstationary Modeling

NASA Astrophysics Data System (ADS)

Liu, D.; Guo, S.; Lian, Y.

2014-12-01

Stationarity is often assumed for frequency analysis of low flows in water resources management and planning. However, many studies have shown that flow characteristics, particularly the frequency spectrum of extreme hydrologic events,were modified by climate change and human activities and the conventional frequency analysis without considering the non-stationary characteristics may lead to costly design. The analysis presented in this paper was based on the more than 100 years of daily flow data from the Yichang gaging station 44 kilometers downstream of the Three Gorges Dam. The Mann-Kendall trend test under the scaling hypothesis showed that the annual low flows had significant monotonic trend, whereas an abrupt change point was identified in 1936 by the Pettitt test. The climate informed low flow frequency analysis and the divided and combined method are employed to account for the impacts from related climate variables and the nonstationarities in annual low flows. Without prior knowledge of the probability density function for the gaging station, six distribution functions including the Generalized Extreme Values (GEV), Pearson Type III, Gumbel, Gamma, Lognormal, and Weibull distributions have been tested to find the best fit, in which the local likelihood method is used to estimate the parameters. Analyses show that GEV had the best fit for the observed low flows. This study has also shown that the climate informed low flow frequency analysis is able to exploit the link between climate indices and low flows, which would account for the dynamic feature for reservoir management and provide more accurate and reliable designs for infrastructure and water supply.

Misrepresentation of the IPCC CO2 emission scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manning, Martin; Edmonds, James A.; Emori, S.

2010-06-01

Estimates of recent fossil fuel CO2 emissions have been compared with the IPCC SRES (Special Report on Emission Scenarios) emission scenarios that had been developed for analysis of future climate change, impacts and mitigation. In some cases this comparison uses averages across subgroups of SRES scenarios and for one category of greenhouse gases (industrial sources of CO2). That approach can be misleading and cause confusion as it is inconsistent with many of the papers on future climate change projections that are based on a specific subset of closely scrutinized SRES scenarios, known as illustrative marker scenarios. Here, we show thatmore » comparison between recent estimates of fossil fuel emissions trends and the SRES illustrative marker scenarios leads to the conclusion that recent trends are not outside the SRES range. Furthermore, the recent economic downturn appears to have brought actual emission back toward the middle of the SRES illustrative marker scenarios. We also note that SRES emission scenarios are designed to reflect potential alternative long-term trends in a world without climate policy intervention and the trend in the resulting climate change is not sensitive to short-term fluctuations.« less

Climate change and livestock system in mountain: Understanding from Gandaki River basin of Nepal Himalaya.

NASA Astrophysics Data System (ADS)

Dahal, P.; Shrestha, N. S.; Krakauer, N.; Lakhankar, T.; Panthi, J., Sr.; Pradhanang, S.; Jha, A. K.; Shrestha, M.; Sharma, M.

2015-12-01

In recent years climate change has emerged as a source of vulnerability for agro-livestock smallholders in Nepal where people are mostly dependent on rain-fed agriculture and livestock farming for their livelihoods. There is a need to understand and predict the potential impacts of climate change on agro-livestock farmer to develop effective mitigation and adaptation strategies. To understand dynamics of this vulnerability, we assess the farmers' perceptions of climate change, analysis of historical and future projections of climatic parameters and try to understand impact of climate change on livestock system in Gandaki River Basin of Central Nepal. During the period of 1981-2012, as reported by the mountain communities, the most serious hazards for livestock system and agriculture are the increasing trend of temperature, erratic rainfall patterns and increase in drought. Poor households without irrigated land are facing greater risks and stresses than well-off people. Analysis of historical climate data also supports the farmer perception. Result shows that there is increasing trend of temperature but no consistent trend in precipitation but a notable finding is that wet areas are getting wetter and dry areas getting drier. Besides that, there is increase in percentage of warm days and nights with decrease in the cool nights and days. The magnitude of the trend is found to be higher in high altitude. Trend of wet days has found to be increasing with decreasing in rainy days. Most areas are characterized by increases in both severity and frequency of drought and are more evident in recent years. The summers of 2004/05/06/09 and winters of 2006/08/09 were the worst widespread droughts and have a serious impact on livestock since 1981. Future projected change in temperature and precipitation obtained from downscaling the data global model by regional climate model shows that precipitation in central Nepal will change by -8% to 12% and temperature will change by 1.9 0C to 3 0C in 2031-2060 compared to the baseline period 1970-2000. Since there will be an increase in temperature and most of the area will experience decreasing rainfall we can predict that there will be increasing vulnerability on livestock system in central Nepal in future which is already facing a serious impact.

Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll-a data.

PubMed

Mélin, F; Vantrepotte, V; Chuprin, A; Grant, M; Jackson, T; Sathyendranath, S

2017-12-15

In this work, trend estimates are used as indicators to compare the multi-annual variability of different satellite chlorophyll- a (Chl a ) data and to assess the fitness-for-purpose of multi-mission Chl a products as climate data records (CDR). Under the assumption that single-mission products are free from spurious temporal artifacts and can be used as benchmark time series, multi-mission CDRs should reproduce the main trend patterns observed by single-mission series when computed over their respective periods. This study introduces and applies quantitative metrics to compare trend distributions from different data records. First, contingency matrices compare the trend diagnostics associated with two satellite products when expressed in binary categories such as existence, significance and signs of trends. Contingency matrices can be further summarized by metrics such as Cohen's κ index that rates the overall agreement between the two distributions of diagnostics. A more quantitative measure of the discrepancies between trends is provided by the distributions of differences between trend slopes. Thirdly, maps of the level of significance P of a t -test quantifying the degree to which two trend estimates differ provide a statistical, spatially-resolved, evaluation. The proposed methodology is applied to the multi-mission Ocean Colour-Climate Change Initiative (OC-CCI) Chl a data. The agreement between trend distributions associated with OC-CCI data and single-mission products usually appears as good as when single-mission products are compared. As the period of analysis is extended beyond 2012 to 2015, the level of agreement tends to be degraded, which might be at least partly due to the aging of the MODIS sensor on-board Aqua. On the other hand, the trends displayed by the OC-CCI series over the short period 2012-2015 are very consistent with those observed with VIIRS. These results overall suggest that the OC-CCI Chl a data can be used for multi-annual time series analysis (including trend detection), but with some caution required if recent years are included, particularly in the central tropical Pacific. The study also recalls the challenges associated with creating a multi-mission ocean color data record suitable for climate research.

Substantial increase in concurrent droughts and heatwaves in the United States

PubMed Central

Mazdiyasni, Omid; AghaKouchak, Amir

2015-01-01

A combination of climate events (e.g., low precipitation and high temperatures) may cause a significant impact on the ecosystem and society, although individual events involved may not be severe extremes themselves. Analyzing historical changes in concurrent climate extremes is critical to preparing for and mitigating the negative effects of climatic change and variability. This study focuses on the changes in concurrences of heatwaves and meteorological droughts from 1960 to 2010. Despite an apparent hiatus in rising temperature and no significant trend in droughts, we show a substantial increase in concurrent droughts and heatwaves across most parts of the United States, and a statistically significant shift in the distribution of concurrent extremes. Although commonly used trend analysis methods do not show any trend in concurrent droughts and heatwaves, a unique statistical approach discussed in this study exhibits a statistically significant change in the distribution of the data. PMID:26324927

Substantial increase in concurrent droughts and heatwaves in the United States.

PubMed

Mazdiyasni, Omid; AghaKouchak, Amir

2015-09-15

A combination of climate events (e.g., low precipitation and high temperatures) may cause a significant impact on the ecosystem and society, although individual events involved may not be severe extremes themselves. Analyzing historical changes in concurrent climate extremes is critical to preparing for and mitigating the negative effects of climatic change and variability. This study focuses on the changes in concurrences of heatwaves and meteorological droughts from 1960 to 2010. Despite an apparent hiatus in rising temperature and no significant trend in droughts, we show a substantial increase in concurrent droughts and heatwaves across most parts of the United States, and a statistically significant shift in the distribution of concurrent extremes. Although commonly used trend analysis methods do not show any trend in concurrent droughts and heatwaves, a unique statistical approach discussed in this study exhibits a statistically significant change in the distribution of the data.

Effect of climatic variability on malaria trends in Baringo County, Kenya.

PubMed

Kipruto, Edwin K; Ochieng, Alfred O; Anyona, Douglas N; Mbalanya, Macrae; Mutua, Edna N; Onguru, Daniel; Nyamongo, Isaac K; Estambale, Benson B A

2017-05-25

Malaria transmission in arid and semi-arid regions of Kenya such as Baringo County, is seasonal and often influenced by climatic factors. Unravelling the relationship between climate variables and malaria transmission dynamics is therefore instrumental in developing effective malaria control strategies. The main aim of this study was to describe the effects of variability of rainfall, maximum temperature and vegetation indices on seasonal trends of malaria in selected health facilities within Baringo County, Kenya. Climate variables sourced from the International Research Institute (IRI)/Lamont-Doherty Earth Observatory (LDEO) climate database and malaria cases reported in 10 health facilities spread across four ecological zones (riverine, lowland, mid-altitude and highland) between 2004 and 2014 were subjected to a time series analysis. A negative binomial regression model with lagged climate variables was used to model long-term monthly malaria cases. The seasonal Mann-Kendall trend test was then used to detect overall monotonic trends in malaria cases. Malaria cases increased significantly in the highland and midland zones over the study period. Changes in malaria prevalence corresponded to variations in rainfall and maximum temperature. Rainfall at a time lag of 2 months resulted in an increase in malaria transmission across the four zones while an increase in temperature at time lags of 0 and 1 month resulted in an increase in malaria cases in the riverine and highland zones, respectively. Given the existence of a time lag between climatic variables more so rainfall and peak malaria transmission, appropriate control measures can be initiated at the onset of short and after long rains seasons.

Identify temporal trend of air temperature and its impact on forest stream flow in Lower Mississippi River Alluvial Valley using wavelet analysis

Treesearch

Ying Ouyang; Prem B. Parajuli; Yide Li; Theodor D. Leininger; Gary Feng

2017-01-01

Characterization of stream flow is essential to water resource management, water supply planning, environmental protection, and ecological restoration; while air temperature variation due to climate change can exacerbate stream flow and add instability to the flow. In this study, the wavelet analysis technique was employed to identify temporal trend of air temperature...

20th-Century Climate Change over Africa: Seasonal Variation in Hydroclimate Trends and Sahara Desert Extent

NASA Astrophysics Data System (ADS)

Nigam, S.; Thomas, N. P.

2017-12-01

Twentieth-century trends in seasonal temperature and precipitation over the African continent are analyzed from observational data sets and historical climate simulations. Given the agricultural economy of the continent, a seasonal perspective is adopted as it is more pertinent than an annual-average one which can mask off-setting but agriculturally-sensitive seasonal hydroclimate variations. Examination of linear trends in seasonal surface air temperature (SAT) shows that heat stress has increased in several regions, including Sudan and Northern Africa where largest SAT trends occur in the warm season. Broadly speaking, the northern continent has warmed more than the southern one in all seasons. Precipitation trends are varied but notable declining trends are found in the countries along the Gulf of Guinea, especially in the source region of Niger river in West Africa, and in the Congo river basin. Rainfall over the African Great Lakes - one of the largest freshwater repositories - has however increased. We show that the Sahara Desert has expanded significantly over the 20th century - by 12-20% depending on the season. The desert expanded southward in summer, reflecting retreat of the northern edge of the Sahel rainfall belt; and to the north in winter, indicating potential impact of the widening of the Tropics. Specific mechanisms driving the expansion in each season are investigated. Finally, this observational analysis is used to evaluate the state-of-the-art climate models from a comparison of the 20th-century hydroclimate trends with those manifest in historical climate simulations. The evaluation shows that modeling regional hydroclimate change over the Africa continent remains challenging.

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

Spatio-temporal Trends of Climate Variability in North Carolina

NASA Astrophysics Data System (ADS)

Sayemuzzaman, Mohammad

Climatic trends in spatial and temporal variability of maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tmean) and precipitation were evaluated for 249 ground-based stations in North Carolina for 1950-2009. The Mann-Kendall (MK), the Theil-Sen Approach (TSA) and the Sequential Mann-Kendall (SQMK) tests were applied to quantify the significance of trend, magnitude of trend and the trend shift, respectively. The lag-1 serial correlation and double mass curve techniques were used to address the data independency and homogeneity. The pre-whitening technique was used to eliminate the effect of auto correlation of the data series. The difference between minimum and maximum temperatures, and so the diurnal temperature range (DTR), at some stations was found to be decreasing on both an annual and a seasonal basis, with an overall increasing trend in the mean temperature. For precipitation, a statewide increasing trend in fall (highest in November) and decreasing trend in winter (highest in February) were detected. No pronounced increasing/decreasing trends were detected in annual, spring, and summer precipitation time series. Trend analysis on a spatial scale (for three physiographic regions: mountain, piedmont and coastal) revealed mixed results. Coastal zone exhibited increasing mean temperature (warming) trend as compared to other locations whereas mountain zone showed decreasing trend (cooling). Three main moisture components (precipitation, total cloud cover, and soil moisture) and the two major atmospheric circulation modes (North Atlantic Oscillation and Southern Oscillation) were used for correlative analysis purposes with the temperature (specifically with DTR) and precipitation trends. It appears that the moisture components are associated with DTR more than the circulation modes in North Carolina.

How well do CMIP5 climate simulations replicate historical trends and patterns of droughts?

DOE PAGES

Nasrollahi, Nasrin; AghaKouchak, Amir; Cheng, Linyin; ...

2015-04-26

Assessing the uncertainties and understanding the deficiencies of climate models are fundamental to developing adaptation strategies. The objective of this study is to understand how well Coupled Model Intercomparison-Phase 5 (CMIP5) climate model simulations replicate ground-based observations of continental drought areas and their trends. The CMIP5 multimodel ensemble encompasses the Climatic Research Unit (CRU) ground-based observations of area under drought at all time steps. However, most model members overestimate the areas under extreme drought, particularly in the Southern Hemisphere (SH). Furthermore, the results show that the time series of observations and CMIP5 simulations of areas under drought exhibit more variabilitymore » in the SH than in the Northern Hemisphere (NH). The trend analysis of areas under drought reveals that the observational data exhibit a significant positive trend at the significance level of 0.05 over all land areas. The observed trend is reproduced by about three-fourths of the CMIP5 models when considering total land areas in drought. While models are generally consistent with observations at a global (or hemispheric) scale, most models do not agree with observed regional drying and wetting trends. Over many regions, at most 40% of the CMIP5 models are in agreement with the trends of CRU observations. The drying/wetting trends calculated using the 3 months Standardized Precipitation Index (SPI) values show better agreement with the corresponding CRU values than with the observed annual mean precipitation rates. As a result, pixel-scale evaluation of CMIP5 models indicates that no single model demonstrates an overall superior performance relative to the other models.« less

Long-term trends of phosphorus concentrations in an artificial lake: Socio-economic and climate drivers.

PubMed

Vystavna, Yuliya; Hejzlar, Josef; Kopáček, Jiří

2017-01-01

European freshwater ecosystems have undergone significant human-induced and environmentally-driven variations in nutrient export from catchments throughout the past five decades, mainly in connection with changes in land-use, agricultural practice, waste water production and treatment, and climatic conditions. We analysed the relations among concentration of total phosphorus (TP) in the Slapy Reservoir (a middle reservoir of the Vltava River Cascade, Czechia), and socio-economic and climatic factors from 1963 to 2015. The study was based on a time series analysis, using conventional statistical tools, and the identification of breaking points, using a segmented regression. Results indicated clear long-term trends and seasonal patterns of TP, with annual average TP increasing up until 1991 and decreasing from 1992 to 2015. Trends in annual, winter and spring average TP concentrations reflected a shift in development of sewerage and sanitary infrastructure, agricultural application of fertilizers, and livestock production in the early 1990s that was associated with changes from the planned to the market economy. No trends were observed for average TP in autumn. The summer average TP has fluctuated with increased amplitude since 1991 in connection with recent climate warming, changes in thermal stratification stability, increased water flow irregularities, and short-circuiting of TP-rich inflow during high flow events. The climate-change-induced processes confound the generally declining trend in lake-water TP concentration and can result in eutrophication despite decreased phosphorus loads from the catchment. Our findings indicate the need of further reduction of phosphorus sources to meet ecological quality standards of the EU Water Framework Directive because the climate change may lead to a greater susceptibility of the aquatic ecosystem to the supply of nutrients.

Recent changes in ecologically-relevant streamflows in North America

NASA Astrophysics Data System (ADS)

Ficklin, D. L.; Abatzoglou, J. T.; Knouft, J.; Robeson, S. M.

2017-12-01

The streamflow regime is a primary regulator of the composition and functioning of freshwater ecosystems. Growth, behavior, and/or reproduction of most freshwater organisms are influenced in some way by the amount of water, including high and low flows, and seasonal fluctuations in water availability in a particular habitat. This work examines trends in ecologically-relevant measures of streamflows from 1980-2015 for over 3,000 streamflow gauges located throughout Canada and United States. Specifically, we examine trends in water year mean flow and variability, as well as trends in high (95th and 99th percentile), low (1st and 5th percentile), and 7- and 3-day maximum and minimum streamflows. The results indicate a clear regional delineation of significant increases of ecologically-relevant streamflows in the northern Central Plains/south-central Canada, upper Midwest (except Michigan and Wisconsin) and northeastern United States/southeastern Canada, while significant decreases are found throughout the southeastern and southwestern United States. The regional agreement between streamflow trends in regulated and unregulated watersheds indicate a widespread climatic influence that is not masked by human alteration of streamflows. We explore the degree to which climate factors explain both interannual variability and observed trends in streamflow to better elucidate the role of top-down climate drivers versus bottom-up land surface drivers on recent trends in ecologically-relevant streamflow. We also explore how these changes in streamflow are affecting water quality such as water temperature and sediment concentration. This type of analysis will aid in highlighting streamflow regions in the United States that are currently sensitive to changes in climate, but may also aid in understanding which regions may be sensitive to future climatic changes.

A New Perspective on Increasing Activity of Extratropical Disturbances: Spatial and Temporal Trends of Wave Activity

NASA Astrophysics Data System (ADS)

Hsu, P. C.; Hsu, H. H.

2016-12-01

Changes in extratropical disturbance behavior could play an important role in climate dynamics and be responsible for a part of climate-related damage. However, robust observational evidence for long-term trends in the activity is still lacking, and understanding of how it is linked with climate phenomena is limited. In this study, we define an accumulated perturbation index (API) to quantify the variation in some scalar quantities of atmospheric disturbances. API measures the areas (e.g., % of total surface area of Earth) where a certain perturbation quantity exceeds the long-term mean value plus 0.5 standard deviations. This index reflects more realistically the ensemble impacts of a climate perturbation and/or trend (such as global warming and ENSO) on the extratropical disturbances, even though its impact on different regions might vary from year to year due to stochastic processes. API represents an integrated activity of extratropical disturbances at a given time relative to a long time span. API is calculated for the 5-day running mean and 10-30-day stream function fluctuations during DJF and JJA. The analysis reveals an increasing trend in API and variance of stream function, especially in the Southern Hemisphere. The findings suggest that atmospheric extratropical disturbances have strengthened in widening areas during the past six decades, even though there might not be robust trends in wave activity at regional scales. Whether the observed trends in API are associated with certain climate patterns is under investigation. Impact of global warming is likely one of the major sources for the increasing activity. The future change in API under global warming scenarios will be further studied by analyzing the projection of the CMIP5 models.

Influence of climate variability on acute myocardial infarction mortality in Havana, 2001-2012.

PubMed

Rivero, Alina; Bolufé, Javier; Ortiz, Paulo L; Rodríguez, Yunisleydi; Reyes, María C

2015-04-01

Death from acute myocardial infarction is due to many factors; influences on risk to the individual include habits, lifestyle and behavior, as well as weather, climate and other environmental components. Changing climate patterns make it especially important to understand how climatic variability may influence acute myocardial infarction mortality. Describe the relationship between climate variability and acute myocardial infarction mortality during the period 2001-2012 in Havana. An ecological time-series study was conducted. The universe comprised 23,744 deaths from acute myocardial infarction (ICD-10: I21-I22) in Havana residents from 2001 to 2012. Climate variability and seasonal anomalies were described using the Bultó-1 bioclimatic index (comprising variables of temperature, humidity, precipitation, and atmospheric pressure), along with series analysis to determine different seasonal-to-interannual climate variation signals. The role played by climate variables in acute myocardial infarction mortality was determined using factor analysis. The Mann-Kendall and Pettitt statistical tests were used for trend analysis with a significance level of 5%. The strong association between climate variability conditions described using the Bultó-1 bioclimatic index and acute myocardial infarctions accounts for the marked seasonal pattern in AMI mortality. The highest mortality rate occurred during the dry season, i.e., the winter months in Cuba (November-April), with peak numbers in January, December and March. The lowest mortality coincided with the rainy season, i.e., the summer months (May-October). A downward trend in total number of deaths can be seen starting with the change point in April 2009. Climate variability is inversely associated with an increase in acute myocardial infarction mortality as is shown by the Bultó-1 index. This inverse relationship accounts for acute myocardial infarction mortality's seasonal pattern.

Recent trends in the frequency and duration of global floods

NASA Astrophysics Data System (ADS)

Najibi, Nasser; Devineni, Naresh

2018-06-01

Frequency and duration of floods are analyzed using the global flood database of the Dartmouth Flood Observatory (DFO) to explore evidence of trends during 1985-2015 at global and latitudinal scales. Three classes of flood duration (i.e., short: 1-7, moderate: 8-20, and long: 21 days and above) are also considered for this analysis. The nonparametric Mann-Kendall trend analysis is used to evaluate three hypotheses addressing potential monotonic trends in the frequency of flood, moments of duration, and frequency of specific flood duration types. We also evaluated if trends could be related to large-scale atmospheric teleconnections using a generalized linear model framework. Results show that flood frequency and the tails of the flood duration (long duration) have increased at both the global and the latitudinal scales. In the tropics, floods have increased 4-fold since the 2000s. This increase is 2.5-fold in the north midlatitudes. However, much of the trend in frequency and duration of the floods can be placed within the long-term climate variability context since the Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Pacific Decadal Oscillation were the main atmospheric teleconnections explaining this trend. There is no monotonic trend in the frequency of short-duration floods across all the global and latitudinal scales. There is a significant increasing trend in the annual median of flood durations globally and each latitudinal belt, and this trend is not related to these teleconnections. While the DFO data come with a certain level of epistemic uncertainty due to imprecision in the estimation of floods, overall, the analysis provides insights for understanding the frequency and persistence in hydrologic extremes and how they relate to changes in the climate, organization of global and local dynamical systems, and country-scale socioeconomic factors.

Climate Change Amplifications of Climate-Fire Teleconnections in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Mariani, Michela; Holz, Andrés.; Veblen, Thomas T.; Williamson, Grant; Fletcher, Michael-Shawn; Bowman, David M. J. S.

2018-05-01

Recent changes in trend and variability of the main Southern Hemisphere climate modes are driven by a variety of factors, including increasing atmospheric greenhouse gases, changes in tropical sea surface temperature, and stratospheric ozone depletion and recovery. One of the most important implications for climatic change is its effect via climate teleconnections on natural ecosystems, water security, and fire variability in proximity to populated areas, thus threatening human lives and properties. Only sparse and fragmentary knowledge of relationships between teleconnections, lightning strikes, and fire is available during the observed record within the Southern Hemisphere. This constitutes a major knowledge gap for undertaking suitable management and conservation plans. Our analysis of documentary fire records from Mediterranean and temperate regions across the Southern Hemisphere reveals a critical increased strength of climate-fire teleconnections during the onset of the 21st century including a tight coupling between lightning-ignited fire occurrences, the upward trend in the Southern Annular Mode, and rising temperatures across the Southern Hemisphere.

Sensitivity of intermittent streams to climate variations in the USA

USGS Publications Warehouse

Eng, Kenny; Wolock, David M.; Dettinger, Mike

2015-01-01

There is a great deal of interest in the literature on streamflow changes caused by climate change because of the potential negative effects on aquatic biota and water supplies. Most previous studies have primarily focused on perennial streams, and there have been only a few studies examining the effect of climate variability on intermittent streams. Our objectives in this study were to (1) identify regions of similar zero-flow behavior, and (2) evaluate the sensitivity of intermittent streams to historical variability in climate in the United States. This study was carried out at 265 intermittent streams by evaluating: (1) correlations among time series of flow metrics (number of zero-flow events, the average of the central 50% and largest 10% of flows) with climate (magnitudes, durations and intensity), and (2) decadal changes in the seasonality and long-term trends of these flow metrics. Results identified five distinct seasonality patterns in the zero-flow events. In addition, strong associations between the low-flow metrics and historical changes in climate were found. The decadal analysis suggested no significant seasonal shifts or decade-to-decade trends in the low-flow metrics. The lack of trends or changes in seasonality is likely due to unchanged long-term patterns in precipitation over the time period examined.

[Evolution of maize climate productivity and its response to climate change in Heilongjiang Province, China.

PubMed

Li, Xiu Fen; Zhao, Hui Ying; Zhu, Hai Xia; Wang, Ping; Wang, Qiu Jing; Wang, Ming; Li, Yu Guang

2016-08-01

Under the background of climate change, revealing the change trend and spatial diffe-rence of maize climate productivity in-depth and understanding the regularity of maize climatic resources utilization can provide scientific basis for the macro-decision of agricultural production in Heilongjiang Province. Based on the 1981-2014 meteorological data of 72 weather stations and the corresponding maize yield data in Heilongjiang Province, by the methods of step by step revisal, spatial interpolation and linear trend analysis, this paper studied the photosynthetic productivity (PP), light-temperature productivity (LTP), and climatic productivity (CP) of spring maize, and their temporal and spatial variation characteristics, main influencing factors and light energy utilization efficiency, and evaluated the maize climate productivities under different climate scenarios in the future. The results showed that during the study period, the mean PP, LTP and CP in Heilongjiang Province were 26558, 19953, 18742 kg·hm -2 , respectively. Maize PP, LTP and CP were high in plains and low in mountains, and gradually decreased from southwest to northeast. PP, LTP and CP presented significantly increasing trends, and the increase rates were 378, 723 and 560 kg·hm -2 ·(10 a) -1 , respectively. The increase of radiation and temperature had positive effect on maize production in Heilongjiang Province. The potential productivity of maize presented significant response to climate change. The decrease of solar radiation led to the decline of PP in western Songnen Plain, but the increased temperature compensated the negative effect of solar radiation, so the downward trend of LTP was slowed. The response to climate warming was particularly evident in North and East, and LTP was significantly increased, which was sensitive to the change of precipitation in southwest of Songnen Plain and part of Sanjiang Plain. The average ratio of maize actual yield to its climate productivity was only 24.1%, there was still 75.9% to be developed. In the future, the warm and wet climate would benefit the improvement of maize climate productivity, while the cold and dry climate would make an adverse impact.

Icehouse Effect: A Polar Autumn and Winter Cooling Trend

NASA Technical Reports Server (NTRS)

Wetzel, Peter J.

1999-01-01

The icehouse effect is a hypothesized polar climate trend toward cooling (or lack of warming) in response to greenhouse warming of adjacent lower latitudes. When greenhouse warmed air from lower latitudes moves over ice and snow, it generates a stronger, more stable, cappino, inversion than in a parallel case without greenhouse warming. Because the degree of decoupling between vertically adjacent air masses is directly dependent on the strength of the inversion, the capping inversion acts somewhat analogously to the walls and roof of the icehouse of generations past. What is inside the icehouse, namely the cold polar atmospheric boundary layer (ABL) air, is preserved by the "insulation" or decoupling, provided by the warm air aloft. Observations over the Arctic Ocean have shown an unexpected lack of any detectable surface warming trend over the past 40 years. This finding strongly contradicts climate model predictions that polar regions should show the strongest effect of greenhouse warming. It also stands in contrast to the consensus reached by the Intergovernmental Panel on Climate Change (IPCC), that human caused greenhouse warming is now detectable globally. One might ask: Are these Arctic observations wrong? Or, if right, is there a plausible physical explanation for them? The published observations mentioned above used about 50,000 soundings over the Arctic Ocean. Here I present a novel analysis of ALL available Arctic rawinsonde data north of 65N--a total of more than 1.1 million soundings. The analysis confirms the previously published result: There is indeed a slight climate-cooling trend in the vast majority of the data. Importantly, there are also select conditions (very strong and very weak stability of the ABL) which show a consistent, strong Arctic warming trend. It is the juxtaposition of these warming and cooling trends which defines a unique "icehouse signature" for which an explanation can be sought.

[Lake eutrophication modeling in considering climatic factors change: a review].

PubMed

Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

2012-11-01

Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

Impact of anthropogenic climate change and human activities on environment and ecosystem services in arid regions.

PubMed

Mahmoud, Shereif H; Gan, Thian Y

2018-08-15

The implications of anthropogenic climate change, human activities and land use change (LUC) on the environment and ecosystem services in the coastal regions of Saudi Arabia were analyzed. Earth observations data was used to drive land use categories between 1970 and 2014. Next, a Markov-CA model was developed to characterize the dynamic of LUC between 2014 and 2100 and their impacts on regions' climate and environment. Non-parametric change point and trend detection algorithms were applied to temperature, precipitation and greenhouse gases data to investigate the presence of anthropogenic climate change. Lastly, climate models were used to project future climate change between 2014 and 2100. The analysis of LUC revealed that between 1970 and 2014, built up areas experienced the greatest growth during the study period, leading to a significant monotonic trend. Urban areas increased by 2349.61km 2 between 1970 and 2014, an average increase of >53.4km 2 /yr. The projected LUC between 2014 and 2100 indicate a continued increase in urban areas and irrigated cropland. Human alteration of land use from natural vegetation and forests to other uses after 1970, resulted in a loss, degradation, and fragmentation, all of which usually have devastating effects on the biodiversity of the region. Resulting in a statistically significant change point in temperature anomaly after 1968 with a warming trend of 0.24°C/decade and a downward trend in precipitation anomaly of 12.2mm/decade. Total greenhouse gas emissions including all anthropogenic sources showed a statistically significant positive trend of 78,090Kt/decade after 1991. This is reflected in the future projection of temperature anomaly between 1900 and 2100 with a future warming trend of 0.19°C/decade. In conclusion, human activities, industrial revelation, deforestation, land use transformation and increase in greenhouse gases had significant implications on the environment and ecosystem services of the study area. Copyright © 2018 Elsevier B.V. All rights reserved.

Trends in Middle East climate extreme indices from 1950 to 2003

NASA Astrophysics Data System (ADS)

Zhang, Xuebin; Aguilar, Enric; Sensoy, Serhat; Melkonyan, Hamlet; Tagiyeva, Umayra; Ahmed, Nader; Kutaladze, Nato; Rahimzadeh, Fatemeh; Taghipour, Afsaneh; Hantosh, T. H.; Albert, Pinhas; Semawi, Mohammed; Karam Ali, Mohammad; Said Al-Shabibi, Mansoor Halal; Al-Oulan, Zaid; Zatari, Taha; Al Dean Khelet, Imad; Hamoud, Saleh; Sagir, Ramazan; Demircan, Mesut; Eken, Mehmet; Adiguzel, Mustafa; Alexander, Lisa; Peterson, Thomas C.; Wallis, Trevor

2005-11-01

A climate change workshop for the Middle East brought together scientists and data for the region to produce the first area-wide analysis of climate extremes for the region. This paper reports trends in extreme precipitation and temperature indices that were computed during the workshop and additional indices data that became available after the workshop. Trends in these indices were examined for 1950-2003 at 52 stations covering 15 countries, including Armenia, Azerbaijan, Bahrain, Cyprus, Georgia, Iran, Iraq, Israel, Jordan, Kuwait, Oman, Qatar, Saudi Arabia, Syria, and Turkey. Results indicate that there have been statistically significant, spatially coherent trends in temperature indices that are related to temperature increases in the region. Significant, increasing trends have been found in the annual maximum of daily maximum and minimum temperature, the annual minimum of daily maximum and minimum temperature, the number of summer nights, and the number of days where daily temperature has exceeded its 90th percentile. Significant negative trends have been found in the number of days when daily temperature is below its 10th percentile and daily temperature range. Trends in precipitation indices, including the number of days with precipitation, the average precipitation intensity, and maximum daily precipitation events, are weak in general and do not show spatial coherence. The workshop attendees have generously made the indices data available for the international research community.

Spaceborne estimated long-term trends (1980s - 2013) of albedo and melting season length over the Greenland ice sheet and linkages to climate drivers

NASA Astrophysics Data System (ADS)

Tedesco, M.; Stroeve, J. C.

2014-12-01

The length of the melting season and surface albedo modulate the amount of meltwater produced over the Greenland ice sheet. The two quantities are intimately connected through a suite of non-linear processes: for example, early melting can reduce the surface albedo (through constructive grain size metamorphism), hence affecting the surface energy balance and further increasing melting. Over the past years, several studies have highlighted increased melting concurring, with a decrease of mean surface albedo over Greenland. However, few studies have examined the duration of the melting season, its implication for surface processes and linkages to climate drivers. Moreover, the majority (if not all) of the studies assessing albedo trends from spaceborne data over Greenland have focused on the last decade or so (2000 - 2013) because they use data collected over the same period by the Moderate Resolution Imaging Spectroradiometer (MODIS). Here, we evaluate and synthesize long-term trends in the length of the melting season (1979 - 2013) derived from spaceborne microwave observations together with surface albedo trends for the period 1982 - 2013 using data from the Advanced Very High Resolution Radiometer (AVHRR). To our knowledge, this is the first time that trends in Greenland albedo and melt season length are discussed for the periods considered in this study. Our results point to a lengthening of the melting season as a consequence of earlier melt onset and later refreeze and to a decrease of mean albedo (1982 - 2013) over the Greenland ice sheet, with trends being spatially variable. To account for this spatial variability, the results of an analysis at regional scales over 12 different regions (defined by elevation and drainage systems) are also reported. The robustness of the results is evaluated by means of a comparative analysis of the results obtained from both AVHRR and MODIS when overlapping data are available (2000 - 2013). Lastly, because large-scale circulation patterns and climate drivers can impact the amount of meltwater produced over Greenland (hence impacting albedo), we discuss the observed trends in the context of North Atlantic Oscillation (NAO) and Greenland Blocking Index (GBI) using a combination of regional climate model outputs and re-analysis data.

Medieval Warm Period Archives Preserved in Limpet Shells (Patella Vulgata) From Viking Deposits, United Kingdom

NASA Astrophysics Data System (ADS)

Mobilia, M.; Surge, D.

2008-12-01

The Medieval Warm Period (700-1100 YBP) represents a recent period of warm climate, and as such provides a powerful comparison to today's continuing warming trend. However, the spatial and temporal variability inherent in the Medieval Warm Period (MWP) makes it difficult to differentiate between global climate trends and regional variability. The continued study of this period will allow for the better understanding of temperature variability, both regional and global, during this climate interval. Our study is located in the Orkney Islands, Scotland, which is a critical area to understand climate dynamics. The North Atlantic Oscillation and Gulf Stream heavily influence climate in this region, and the study of climate intervals during the MWP will improve our understanding of the behavior of these climate mechanisms during this interval. Furthermore, the vast majority of the climate archive has been derived from either deep marine or arctic environments. Studying a coastal environment will offer valuable insight into the behavior of maritime climate during the MWP. Estimated seasonal sea surface temperature data were derived through isotopic analysis of limpet shells (Patella vulgata). Analysis of modern shells confirms that growth temperature tracks seasonal variation in ambient water temperature. Preliminary data from MWP shells record a seasonal temperature range comparable to that observed in the modern temperature data. We will extend the range of temperature data from the 10th through 14th centuries to advance our knowledge of seasonal temperature variability during the late Holocene.

River catchment rainfall series analysis using additive Holt-Winters method

NASA Astrophysics Data System (ADS)

Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

Climate driven variability and detectability of temporal trends in low flow indicators for Ireland

NASA Astrophysics Data System (ADS)

Hall, Julia; Murphy, Conor; Harrigan, Shaun

2013-04-01

Observational data from hydrological monitoring programs plays an important role in informing decision makers of changes in key hydrological variables. To analyse how changes in climate influence stream flow, undisturbed river basins with near-natural conditions limited from human influences are needed. This study analyses low flow indicators derived from observations from the Irish Reference Network. Within the trend analysis approach the influence of individual years or sub-periods on the detected trend are analysed using sequential trend tests on all possible periods (of at least 10 years in length) by varying the start and end dates of records for various indicators. Results from this study highlight that the current standard approach using fixed periods to determine long term trends is not appropriate as statistical significance and direction of trends from short term records do not persist continuously over entire record and can be heavily influenced by extremes within the record. The importance of longer records in contextualising short term trends derived from fixed-periods influenced by natural annual, inter-annual and multi-decadal variability is highlighted. Due to the low signal (trend) to noise (variability) ratio, the apparent trends derived from the low flow indicators cannot be used as confident guides to inform future water resources planning and decision making on climate change. Infact, some derived trends contradict expected climate change impacts and even small changes in study design can change the outcomes to a high degree. Therefore it is important not only to evaluate the magnitude of trends derived from monitoring data but also when a trend of a certain magnitude in a given indicator will be detectable to inform decision making or what changes might be required to detect trends for a certain significance level. In this study, the influence of observed variance in the monitoring records on the expected detection times for trends with a fixed magnitude are presented. Depending on the indicator selected, the sample variance and trend magnitude very different detection time estimates are obtained and in most cases not within the time required for anticipatory adaptation in the water resources sector. Additionally, the minimum changes in low flow indicators required to be detectable are large and changes are unlikely to be statistically detectable for many years. This means that water management and planning for anticipated future climatic changes will be required to take place without these changes being formally statistically detectable.Waiting for these trends to become formally detectable with the traditional statistical methods might not be an option for water resources management. Within the monitoring network, a considerable difference is apparent between stations in terms of detection times and changes required for detection. The existence of flow monitoring stations showing short detection times for specific indicators confirms the potential for identifying stations that may be first responders to climate induced changes. Identifying sentinel stations can increase the ability to more effectively optimise the deployment of resources for monitoring the influences of climatic change in a hydrometric reference network.

Impact of land cover changes and climate on the main airborne pollen types in Southern Spain.

PubMed

García-Mozo, Herminia; Oteros, Jose Antonio; Galán, Carmen

2016-04-01

Airborne pollen concentrations strongly correlate with flowering intensity of wind-pollinated species growing at and around monitoring sites. The pollen spectrum, and the variations in its composition and concentrations, is influenced by climatic features and by available nutritional resources but it is also determined by land use and its changes. The first factor influence is well known on aerobiological researches but the impact of land cover changes has been scarcely studied until now. This paper reports on a study carried out in Southern Spain (Córdoba city) examining airborne pollen trends over a 15-year period and it explores the possible links both to changes in land use and to climate variations. The Seasonal-Trend Decomposition procedure based on Loess (STL) which decomposes long-term data series into smaller seasonal component patterns was applied. Trends were compared with recorded changes in land use at varying distances from the city in order to determine their possible influence on pollen-count variations. The influence of climate-related factors was determined by means of non-parametric correlation analysis. The STL method proved highly effective for extracting trend components from pollen time series, because their features vary widely and can change quickly in a short term. Results revealed mixed trends depending on the taxa and reflecting fluctuations in land cover and/or climate. A significant rising trend in Olea pollen counts was observed, attributable both to the increasing olive-growing area but also to changes in temperature and rainfall. Poaceae pollen concentrations also increased, due largely to an expansion of heterogeneous agricultural areas and to an increase in pollen season length positively influenced by rainfall and temperature. By contrast, the significant declining trend observed for pollen from ruderal taxa, such as Amaranthaceae, Rumex, Plantago and Urticaceae, may be linked to changes in urban planning strategies with a higher building pressure. Copyright © 2016. Published by Elsevier B.V.

Human Influence on Tropical Cyclone Intensity

NASA Technical Reports Server (NTRS)

Sobel, Adam H.; Camargo, Suzana J.; Hall, Timothy M.; Lee, Chia-Ying; Tippett, Michael K.; Wing, Allison A.

2016-01-01

Recent assessments agree that tropical cyclone intensity should increase as the climate warms. Less agreement exists on the detection of recent historical trends in tropical cyclone intensity.We interpret future and recent historical trends by using the theory of potential intensity, which predicts the maximum intensity achievable by a tropical cyclone in a given local environment. Although greenhouse gas-driven warming increases potential intensity, climate model simulations suggest that aerosol cooling has largely canceled that effect over the historical record. Large natural variability complicates analysis of trends, as do poleward shifts in the latitude of maximum intensity. In the absence of strong reductions in greenhouse gas emissions, future greenhouse gas forcing of potential intensity will increasingly dominate over aerosol forcing, leading to substantially larger increases in tropical cyclone intensities.

Hot spots, hot moments and time-span of changes in drivers and their responses on carbon cycling in Europe

NASA Astrophysics Data System (ADS)

Tomelleri, E.; Forkel, M.; Fuchs, R.; Jung, M.; Mahecha, M. D.; Reichstein, M.; Weber, U.

2012-12-01

The objective of this study is to provide a complete quantitative assessment of the annual to decadal variability, hotspots of changes and the temporal magnitude of regional trends and variability for the main drivers of carbon cycle like climate and land use and their responses for Europe. For this purpose we used an harmonized climatic data set (ERA Interim and WATCH) and an historical land-use change reconstruction (HILDAv1, Fuchs in prep.). Both the data sets cover the period 1900-2010 and have a 0.25 deg spatial resolution. As driver response we used two different empirically up-scaled GPP fields: the first (MTE) obtained by the application of model trees (Jung et al. 2009) and a second (LUE) based on a light use efficiency model (Tomelleri in prep.). Both the approaches are based on the up-scaling of Fluxnet observations. The response fields have monthly temporal resolution and are limited to the period 1982-2011. We estimated break-points in time series of driver and response variables based on the method of Bai and Perron (2003) to identify changes in trends. This method was implemented in Verbesselt et al. 2010 and applied by deJong et al. 2011 to detect phenological and abrupt changes and trends in vegetation activity based on satellite-derived vegetation index time series. The analysis of drivers and responses allowed to identify the dominant factors driving the biosphere-atmosphere carbon exchange. The synchronous analysis of climatic drivers and land use change allowed us to explain most of the temporal and spatial variability showing that in the regions and time period where the most land use change occurred the climatic drivers are not sufficient to explain trends and oscillation in carbon cycling. The comparison of our analysis for the up-scaling methods shows some agreement: we found inconsistency in the spatial and temporal patterns in regions where the Fluxnet network is less dense. This can be explained by the conceptual difference in the up-scaling methods: while one is on pixel basis (MTE) the other (LUE) is up-scaling model parameters by bioclimatic regions. Our study shows the value of up-scaling methods for understanding the spatial-temporal variability of carbon cycling and how these are a valuable tool for spatial and temporal analysis. Furthermore, the use of climatic drivers and land-use change demonstrated the need of taking natural and anthropogenic drivers into consideration for explaining trends and oscillations. Possibly a further analysis including detailed management practices for forestry and agriculture would help in explaining the remaining variance. References: Bai, J., Perron, P.: Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 2003. Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model. Biogeosciences, 6, 2009. Verbesselt, J., Hyndman, R., Newnham, G., Culvenor, D.: Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment,114(1), 2010. de Jong, R., Verbesselt, J., Schaepman, M.E., Bruin, S.: Trend changes in global greening and browning: contribution of short-term trends to longer-term change. Global Change Biology, 18, 2011.

Attribution of trends in global vegetation greenness from 1982 to 2011

NASA Astrophysics Data System (ADS)

Zhu, Z.; Xu, L.; Bi, J.; Myneni, R.; Knyazikhin, Y.

2012-12-01

Time series of remotely sensed vegetation indices data provide evidence of changes in terrestrial vegetation activity over the past decades in the world. However, it is difficult to attribute cause-and-effect to vegetation trends because variations in vegetation productivity are driven by various factors. This study investigated changes in global vegetation productivity first, and then attributed the global natural vegetation with greening trend. Growing season integrated normalized difference vegetation index (GSI NDVI) derived from the new GIMMS NDVI3g dataset (1982-2011was analyzed. A combined time series analysis model, which was developed from simper linear trend model (SLT), autoregressive integrated moving average model (ARIMA) and Vogelsang's t-PST model shows that productivity of all vegetation types except deciduous broadleaf forest predominantly showed increasing trends through the 30-year period. The evolution of changes in productivity in the last decade was also investigated. Area of greening vegetation monotonically increased through the last decade, and both the browning and no change area monotonically decreased. To attribute the predominant increase trend of productivity of global natural vegetation, trends of eight climate time series datasets (three temperature, three precipitation and two radiation datasets) were analyzed. The attribution of trends in global vegetation greenness was summarized as relaxation of climatic constraints, fertilization and other unknown reasons. Result shows that nearly all the productivity increase of global natural vegetation was driven by relaxation of climatic constraints and fertilization, which play equally important role in driving global vegetation greenness.; Area fraction and productivity change fraction of IGBP vegetation land cover classes showing statistically significant (10% level) trend in GSI NDVIt;

Trend Estimation and Regression Analysis in Climatological Time Series: An Application of Structural Time Series Models and the Kalman Filter.

NASA Astrophysics Data System (ADS)

Visser, H.; Molenaar, J.

1995-05-01

The detection of trends in climatological data has become central to the discussion on climate change due to the enhanced greenhouse effect. To prove detection, a method is needed (i) to make inferences on significant rises or declines in trends, (ii) to take into account natural variability in climate series, and (iii) to compare output from GCMs with the trends in observed climate data. To meet these requirements, flexible mathematical tools are needed. A structural time series model is proposed with which a stochastic trend, a deterministic trend, and regression coefficients can be estimated simultaneously. The stochastic trend component is described using the class of ARIMA models. The regression component is assumed to be linear. However, the regression coefficients corresponding with the explanatory variables may be time dependent to validate this assumption. The mathematical technique used to estimate this trend-regression model is the Kaiman filter. The main features of the filter are discussed.Examples of trend estimation are given using annual mean temperatures at a single station in the Netherlands (1706-1990) and annual mean temperatures at Northern Hemisphere land stations (1851-1990). The inclusion of explanatory variables is shown by regressing the latter temperature series on four variables: Southern Oscillation index (SOI), volcanic dust index (VDI), sunspot numbers (SSN), and a simulated temperature signal, induced by increasing greenhouse gases (GHG). In all analyses, the influence of SSN on global temperatures is found to be negligible. The correlations between temperatures and SOI and VDI appear to be negative. For SOI, this correlation is significant, but for VDI it is not, probably because of a lack of volcanic eruptions during the sample period. The relation between temperatures and GHG is positive, which is in agreement with the hypothesis of a warming climate because of increasing levels of greenhouse gases. The prediction performance of the model is rather poor, and possible explanations are discussed.

Trend analysis of long-term temperature time series in the Greater Toronto Area (GTA)

NASA Astrophysics Data System (ADS)

Mohsin, Tanzina; Gough, William A.

2010-08-01

As the majority of the world’s population is living in urban environments, there is growing interest in studying local urban climates. In this paper, for the first time, the long-term trends (31-162 years) of temperature change have been analyzed for the Greater Toronto Area (GTA). Annual and seasonal time series for a number of urban, suburban, and rural weather stations are considered. Non-parametric statistical techniques such as Mann-Kendall test and Theil-Sen slope estimation are used primarily for the assessing of the significance and detection of trends, and the sequential Mann test is used to detect any abrupt climate change. Statistically significant trends for annual mean and minimum temperatures are detected for almost all stations in the GTA. Winter is found to be the most coherent season contributing substantially to the increase in annual minimum temperature. The analyses of the abrupt changes in temperature suggest that the beginning of the increasing trend in Toronto started after the 1920s and then continued to increase to the 1960s. For all stations, there is a significant increase of annual and seasonal (particularly winter) temperatures after the 1980s. In terms of the linkage between urbanization and spatiotemporal thermal patterns, significant linear trends in annual mean and minimum temperature are detected for the period of 1878-1978 for the urban station, Toronto, while for the rural counterparts, the trends are not significant. Also, for all stations in the GTA that are situated in all directions except south of Toronto, substantial temperature change is detected for the periods of 1970-2000 and 1989-2000. It is concluded that the urbanization in the GTA has significantly contributed to the increase of the annual mean temperatures during the past three decades. In addition to urbanization, the influence of local climate, topography, and larger scale warming are incorporated in the analysis of the trends.

Statistical evaluation of rainfall time series in concurrence with agriculture and water resources of Ken River basin, Central India (1901-2010)

NASA Astrophysics Data System (ADS)

Meshram, Sarita Gajbhiye; Singh, Sudhir Kumar; Meshram, Chandrashekhar; Deo, Ravinesh C.; Ambade, Balram

2017-12-01

Trend analysis of long-term rainfall records can be used to facilitate better agriculture water management decision and climate risk studies. The main objective of this study was to identify the existing trends in the long-term rainfall time series over the period 1901-2010 utilizing 12 hydrological stations located at the Ken River basin (KRB) in Madhya Pradesh, India. To investigate the different trends, the rainfall time series data were divided into annual and seasonal (i.e., pre-monsoon, monsoon, post-monsoon, and winter season) sub-sets, and a statistical analysis of data using the non-parametric Mann-Kendall (MK) test and the Sen's slope approach was applied to identify the nature of the existing trends in rainfall series for the Ken River basin. The obtained results were further interpolated with the aid of the Quantum Geographic Information System (GIS) approach employing the inverse distance weighted approach. The results showed that the monsoon and the winter season exhibited a negative trend in rainfall changes over the period of study, and this was true for all stations, although the changes during the pre- and the post-monsoon seasons were less significant. The outcomes of this research study also suggest significant decreases in the seasonal and annual trends of rainfall amounts in the study period. These findings showing a clear signature of climate change impacts on KRB region potentially have implications in terms of climate risk management strategies to be developed during major growing and harvesting seasons and also to aid in the appropriate water resource management strategies that must be implemented in decision-making process.

Research on trend of warm-humid climate in Central Asia

NASA Astrophysics Data System (ADS)

Gong, Zhi; Peng, Dailiang; Wen, Jingyi; Cai, Zhanqing; Wang, Tiantian; Hu, Yuekai; Ma, Yaxin; Xu, Junfeng

2017-07-01

Central Asia is a typical arid area, which is sensitive and vulnerable part of climate changes, at the same time, Central Asia is the Silk Road Economic Belt of the core district, the warm-humid climate change will affect the production and economic development of neighboring countries. The average annual precipitation, average anneal temperature and evapotranspiration are the important indexes to weigh the climate change. In this paper, the annual precipitation, annual average temperature and evapotranspiration data of every pixel point in Central Asia are analyzed by using long-time series remote sensing data to analyze the trend of warm and humid conditions. Finally, using the model to analyzed the distribution of warm-dry trend, the warm-wet trend, the cold-dry trend and the cold-wet trend in Central Asia and Xinjiang area. The results showed that most of the regions of Central Asia were warm-humid and warm-dry trends, but only a small number of regions showed warm-dry and cold-dry trends. It is of great significance to study the climatic change discipline and guarantee the ecological safety and improve the ability to cope with climate change in the region. It also provide scientific basis for the formulation of regional climate change program. The first section in your paper

Abrupt climate change and extinction events

NASA Technical Reports Server (NTRS)

Crowley, Thomas J.

1988-01-01

There is a growing body of theoretical and empirical support for the concept of instabilities in the climate system, and indications that abrupt climate change may in some cases contribute to abrupt extinctions. Theoretical indications of instabilities can be found in a broad spectrum of climate models (energy balance models, a thermohaline model of deep-water circulation, atmospheric general circulation models, and coupled ocean-atmosphere models). Abrupt transitions can be of several types and affect the environment in different ways. There is increasing evidence for abrupt climate change in the geologic record and involves both interglacial-glacial scale transitions and the longer-term evolution of climate over the last 100 million years. Records from the Cenozoic clearly show that the long-term trend is characterized by numerous abrupt steps where the system appears to be rapidly moving to a new equilibrium state. The long-term trend probably is due to changes associated with plate tectonic processes, but the abrupt steps most likely reflect instabilities in the climate system as the slowly changing boundary conditions caused the climate to reach some threshold critical point. A more detailed analysis of abrupt steps comes from high-resolution studies of glacial-interglacial fluctuations in the Pleistocene. Comparison of climate transitions with the extinction record indicates that many climate and biotic transitions coincide. The Cretaceous-Tertiary extinction is not a candidate for an extinction event due to instabilities in the climate system. It is quite possible that more detailed comparisons and analysis will indicate some flaws in the climate instability-extinction hypothesis, but at present it appears to be a viable candidate as an alternate mechanism for causing abrupt environmental changes and extinctions.

Effects of climate change on soil moisture over China from 1960-2006

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Liu, J.

2009-01-01

Soil moisture is an important variable in the climate system and it has sensitive impact on the global climate. Obviously it is one of essential components in the climate change study. The Integrated Biosphere Simulator (IBIS) is used to evaluate the spatial and temporal patterns of soil moisture across China under the climate change conditions for the period 1960-2006. Results show that the model performed better in warm season than in cold season. Mean errors (ME) are within 10% for all the months and root mean squared errors (RMSE) are within 10% except winter season. The model captured the spatial variability higher than 50% in warm seasons. Trend analysis based on the Mann-Kendall method indicated that soil moisture in most area of China is decreased especially in the northern China. The areas with significant increasing trends in soil moisture mainly locate at northwestern China and small areas in southeastern China and eastern Tibet plateau. ?? 2009 IEEE.

Analysis of trends in climate, streamflow, and stream temperature in north coastal California

USGS Publications Warehouse

Madej, Mary Ann; Medley, C. Nicholas; Patterson, Glenn; Parker, Melanie J.

2011-01-01

As part of a broader project analyzing trends in climate, streamflow, vegetation, salmon, and ocean conditions in northern California national park units, we compiled average monthly air temperature and precipitation data from 73 climate stations, streamflow data from 21 river gaging stations, and limited stream temperature data from salmon-bearing rivers in north coastal California. Many climate stations show a statistically significant increase in both average maximum and average minimum air temperature in early fall and midwinter during the last century. Concurrently, average September precipitation has decreased. In many coastal rivers, summer low flow has decreased and summer stream temperatures have increased, which affects summer rearing habitat for salmonids. Nevertheless, because vegetative cover has also changed during this time period, we cannot ascribe streamflow changes to climate change without first assessing water budgets. Although shifts in the timing of the centroid of runoff have been documented in snowmelt-dominated watersheds in the western United States, this was not the case in lower elevation coastal rivers analyzed in this study.

Deciphering the expression of climate change within the Lower Colorado River basin by stochastic simulation of convective rainfall

NASA Astrophysics Data System (ADS)

Bliss Singer, Michael; Michaelides, Katerina

2017-10-01

In drylands, convective rainstorms typically control runoff, streamflow, water supply and flood risk to human populations, and ecological water availability at multiple spatial scales. Since drainage basin water balance is sensitive to climate, it is important to improve characterization of convective rainstorms in a manner that enables statistical assessment of rainfall at high spatial and temporal resolution, and the prediction of plausible manifestations of climate change. Here we present a simple rainstorm generator, STORM, for convective storm simulation. It was created using data from a rain gauge network in one dryland drainage basin, but is applicable anywhere. We employ STORM to assess watershed rainfall under climate change simulations that reflect differences in wetness/storminess, and thus provide insight into observed or projected regional hydrologic trends. Our analysis documents historical, regional climate change manifesting as a multidecadal decline in rainfall intensity, which we suggest has negatively impacted ephemeral runoff in the Lower Colorado River basin, but has not contributed substantially to regional negative streamflow trends.

0.1 Trend analysis of δ18O composition of precipitation in Germany: Combining Mann-Kendall trend test and ARIMA models to correct for higher order serial correlation

NASA Astrophysics Data System (ADS)

Klaus, Julian; Pan Chun, Kwok; Stumpp, Christine

2015-04-01

Spatio-temporal dynamics of stable oxygen (18O) and hydrogen (2H) isotopes in precipitation can be used as proxies for changing hydro-meteorological and regional and global climate patterns. While spatial patterns and distributions gained much attention in recent years the temporal trends in stable isotope time series are rarely investigated and our understanding of them is still limited. These might be a result of a lack of proper trend detection tools and effort for exploring trend processes. Here we make use of an extensive data set of stable isotope in German precipitation. In this study we investigate temporal trends of δ18O in precipitation at 17 observation station in Germany between 1978 and 2009. For that we test different approaches for proper trend detection, accounting for first and higher order serial correlation. We test if significant trends in the isotope time series based on different models can be observed. We apply the Mann-Kendall trend tests on the isotope series, using general multiplicative seasonal autoregressive integrate moving average (ARIMA) models which account for first and higher order serial correlations. With the approach we can also account for the effects of temperature, precipitation amount on the trend. Further we investigate the role of geographic parameters on isotope trends. To benchmark our proposed approach, the ARIMA results are compared to a trend-free prewhiting (TFPW) procedure, the state of the art method for removing the first order autocorrelation in environmental trend studies. Moreover, we explore whether higher order serial correlations in isotope series affects our trend results. The results show that three out of the 17 stations have significant changes when higher order autocorrelation are adjusted, and four stations show a significant trend when temperature and precipitation effects are considered. Significant trends in the isotope time series are generally observed at low elevation stations (≤315 m a.s.l.). Higher order autoregressive processes are important in the isotope time series analysis. Our results show that the widely used trend analysis with only the first order autocorrelation adjustment may not adequately take account of the high order autocorrelated processes in the stable isotope series. The investigated time series analysis method including higher autocorrelation and external climate variable adjustments is shown to be a better alternative.

Homogeneity of a Global Multisatellite Soil Moisture Climate Data Record

NASA Technical Reports Server (NTRS)

Su, Chun-Hsu; Ryu, Dongryeol; Dorigo, Wouter; Zwieback, Simon; Gruber, Alexander; Albergel, Clement; Reichle, Rolf H.; Wagner, Wolfgang

2016-01-01

Climate Data Records (CDR) that blend multiple satellite products are invaluable for climate studies, trend analysis and risk assessments. Knowledge of any inhomogeneities in the CDR is therefore critical for making correct inferences. This work proposes a methodology to identify the spatiotemporal extent of the inhomogeneities in a 36-year, global multisatellite soil moisture CDR as the result of changing observing systems. Inhomogeneities are detected at up to 24 percent of the tested pixels with spatial extent varying with satellite changeover times. Nevertheless, the contiguous periods without inhomogeneities at changeover times are generally longer than 10 years. Although the inhomogeneities have measurable impact on the derived trends, these trends are similar to those observed in ground data and land surface reanalysis, with an average error less than 0.003 cubic meters per cubic meter per year. These results strengthen the basis of using the product for long-term studies and demonstrate the necessity of homogeneity testing of multisatellite CDRs in general.

Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mao, Jiafu; Shi, Xiaoying; Ricciuto, Daniel M.

Here, we examined natural and anthropogenic controls on terrestrial evapotranspiration (ET) changes from 1982-2010 using multiple estimates from remote sensing-based datasets and process-oriented land surface models. A significant increased trend of ET in each hemisphere was consistently revealed by observationally-constrained data and multi-model ensembles that considered historic natural and anthropogenic drivers. The climate impacts were simulated to determine the spatiotemporal variations in ET. Globally, rising CO 2 ranked second in these models after the predominant climatic influences, and yielded a decreasing trend in canopy transpiration and ET, especially for tropical forests and high-latitude shrub land. Increased nitrogen deposition slightly amplifiedmore » global ET via enhanced plant growth. Land-use-induced ET responses, albeit with substantial uncertainties across the factorial analysis, were minor globally, but pronounced locally, particularly over regions with intensive land-cover changes. Our study highlights the importance of employing multi-stream ET and ET-component estimates to quantify the strengthening anthropogenic fingerprint in the global hydrologic cycle.« less

Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends

DOE PAGES

Mao, Jiafu; Shi, Xiaoying; Ricciuto, Daniel M.; ...

2015-09-08

Here, we examined natural and anthropogenic controls on terrestrial evapotranspiration (ET) changes from 1982-2010 using multiple estimates from remote sensing-based datasets and process-oriented land surface models. A significant increased trend of ET in each hemisphere was consistently revealed by observationally-constrained data and multi-model ensembles that considered historic natural and anthropogenic drivers. The climate impacts were simulated to determine the spatiotemporal variations in ET. Globally, rising CO 2 ranked second in these models after the predominant climatic influences, and yielded a decreasing trend in canopy transpiration and ET, especially for tropical forests and high-latitude shrub land. Increased nitrogen deposition slightly amplifiedmore » global ET via enhanced plant growth. Land-use-induced ET responses, albeit with substantial uncertainties across the factorial analysis, were minor globally, but pronounced locally, particularly over regions with intensive land-cover changes. Our study highlights the importance of employing multi-stream ET and ET-component estimates to quantify the strengthening anthropogenic fingerprint in the global hydrologic cycle.« less

Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

NASA Technical Reports Server (NTRS)

Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

2014-01-01

Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3 decades. OGI mainly showed late trends in the Southern Hemisphere of Africa while GSL was reversed from reduced GSL trends (1982-1999) to prolonged trends (2000-2010). In Australia, GSL exhibited considerable interannual variation, but the consistent trend lacked presence in most regions. Finally, the proportion of pixels with significant trends was less than I% in most of climate regions although it could be as large as 10%.

Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

2014-05-01

Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3 decades. OGI mainly showed late trends in the Southern Hemisphere of Africa while GSL was reversed from reduced GSL trends (1982-1999) to prolonged trends (2000-2010). In Australia, GSL exhibited considerable interannual variation, but the consistent trend lacked presence in most regions. Finally, the proportion of pixels with significant trends was less than 1 % in most of climate regions although it could be as large as 10 %.

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

NASA Technical Reports Server (NTRS)

Molnar, Gyula; Susskind, Joel

2008-01-01

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Analysis of long-term changes in extreme climatic indices: a case study of the Mediterranean climate, Marmara Region, Turkey

NASA Astrophysics Data System (ADS)

Abbasnia, Mohsen; Toros, Hüseyin

2018-05-01

This study aimed to analyze extreme temperature and precipitation indices at seven stations in the Marmara Region of Turkey for the period 1961-2016. The trend of temperature indices showed that the warm-spell duration and the numbers of summer days, tropical nights, warm nights, and warm days have increased, while the cold-spell duration and number of ice days, cool nights, and cool days have decreased across the Marmara Region. Additionally, the diurnal temperature range has slightly increased at most of the stations. A majority of stations have shown significant warming trends for warm days and warm nights throughout the study area, whereas warm extremes and night-time based temperature indices have shown stronger trends compared to cold extremes and day-time indices. The analysis of precipitation indices has mostly shown increasing trends in consecutive dry days and increasing trends in annual rainfall, rainfall intensity for inland and urban stations, especially for stations in Sariyer and Edirne, which are affected by a fast rate of urbanization. Overall, a large proportion of study stations have experienced an increase in annual precipitation and heavy precipitation events, although there was a low percentage of results that was significant. Therefore, it is expected that the rainfall events will tend to become shorter and more intense, the occurrence of temperature extremes will become more pronounced in favor of hotter events, and there will be an increase in the atmospheric moisture content over the Marmara Region. This provides regional evidence for the importance of ongoing research on climate change.

Evaluating the patterns of spatiotemporal trends of root zone soil moisture in major climate regions in East Asia

NASA Astrophysics Data System (ADS)

Zohaib, Muhammad; Kim, Hyunglok; Choi, Minha

2017-08-01

Root zone soil moisture (RZSM) is a crucial variable in land-atmosphere interactions. Evaluating the spatiotemporal trends and variability patterns of RZSM are essential for discerning the anthropogenic and climate change effects on the regional and global hydrological cycles. In this study, the trends of RZSM, computed by the exponential filter from the European Space Agency's Climate Change Initiative soil moisture, were evaluated in major climate regions of East Asia from 1982 to 2014. Moreover, the trends of RZSM were compared to the trends of precipitation (P), skin temperature (Tskin), and actual evapotranspiration (AET) to investigate how they influence the RZSM trends in each climate region. Drying trends were predominant in arid and continental regions, whereas wetting trends were found in the tropical and temperate regions. The increasing trends of Tskin and AET cause drying in arid and continental regions, whereas in tropical regions, these cause wetting trends, which might be due to convective P. In temperate regions, despite decreasing P and increasing Tskin, the RZSM trend was increasing, attributed to the intensive irrigation activities in these regions. This is probably the first time to analyze the long-term trends of RZSM in different climate regions. Hence, the results of this study will improve our understanding of the regional and global hydrological cycles. Despite certain limitations, the results of this study may be useful for improving and developing climate models and predicting long-term vast scale natural disasters such as drought, dust outbreaks, floods, and heat waves.

Analyzing the contribution of climate change to long-term variations in sediment nitrogen sources for reservoirs/lakes.

PubMed

Xia, Xinghui; Wu, Qiong; Zhu, Baotong; Zhao, Pujun; Zhang, Shangwei; Yang, Lingyan

2015-08-01

We applied a mixing model based on stable isotopic δ(13)C, δ(15)N, and C:N ratios to estimate the contributions of multiple sources to sediment nitrogen. We also developed a conceptual model describing and analyzing the impacts of climate change on nitrogen enrichment. These two models were conducted in Miyun Reservoir to analyze the contribution of climate change to the variations in sediment nitrogen sources based on two (210)Pb and (137)Cs dated sediment cores. The results showed that during the past 50years, average contributions of soil and fertilizer, submerged macrophytes, N2-fixing phytoplankton, and non-N2-fixing phytoplankton were 40.7%, 40.3%, 11.8%, and 7.2%, respectively. In addition, total nitrogen (TN) contents in sediment showed significant increasing trends from 1960 to 2010, and sediment nitrogen of both submerged macrophytes and phytoplankton sources exhibited significant increasing trends during the past 50years. In contrast, soil and fertilizer sources showed a significant decreasing trend from 1990 to 2010. According to the changing trend of N2-fixing phytoplankton, changes of temperature and sunshine duration accounted for at least 43% of the trend in the sediment nitrogen enrichment over the past 50years. Regression analysis of the climatic factors on nitrogen sources showed that the contributions of precipitation, temperature, and sunshine duration to the variations in sediment nitrogen sources ranged from 18.5% to 60.3%. The study demonstrates that the mixing model provides a robust method for calculating the contribution of multiple nitrogen sources in sediment, and this study also suggests that N2-fixing phytoplankton could be regarded as an important response factor for assessing the impacts of climate change on nitrogen enrichment. Copyright © 2015 Elsevier B.V. All rights reserved.

Climate change and human health: what are the research trends? A scoping review protocol.

PubMed

Herlihy, Niamh; Bar-Hen, Avner; Verner, Glenn; Fischer, Helen; Sauerborn, Rainer; Depoux, Anneliese; Flahault, Antoine; Schütte, Stefanie

2016-12-23

For 28 years, the Intergovernmental Panel on Climate Change (IPCC) has been assessing the potential risks associated with anthropogenic climate change. Although interest in climate change and health is growing, the implications arising from their interaction remain understudied. Generating a greater understanding of the health impacts of climate change could be key step in inciting some of the changes necessary to decelerate global warming. A long-term and broad overview of the existing scientific literature in the field of climate change and health is currently missing in order to ensure that all priority areas are being adequately addressed. In this paper we outline our methods to conduct a scoping review of the published peer-reviewed literature on climate change and health between 1990 and 2015. A detailed search strategy will be used to search the PubMed and Web of Science databases. Specific inclusion and exclusion criteria will be applied in order to capture the most relevant literature in the time frame chosen. Data will be extracted, categorised and coded to allow for statistical analysis of the results. No ethical approval was required for this study. A searchable database of climate change and health publications will be developed and a manuscript will be complied for publication and dissemination of the findings. We anticipate that this study will allow us to map the trends observed in publications over the 25-year time period in climate change and health research. It will also identify the research areas with the highest volume of publications as well as highlight the research trends in climate change and health. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Indicators of climate change for the African continent derived from radiosondes

NASA Astrophysics Data System (ADS)

Añel, J. A.; Gimeno, L.; Tesouro, M.; de La Torre, L.; Nieto, R.; Ribera, P.; García, R.; Hernández, E.

2003-04-01

Here we study the interannual variability of different parameters calculated from radiosonde data in the African continent. Data used in the analysis were a subset of the National Climatic Data Center Upper Air Digital Files of the National Oceanic and Atmospheric Administration (USA) (CARDS). This work show the climatic trends in the studied region during the period and from 1973 to 1998). Results show that radiosonde stations were useful for this analysis in the African continent. Main oscillations and the relationship with the Northern Annular Mode and El Niño-Southern Oscillation were also studied.

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

NASA Astrophysics Data System (ADS)

Belihu, Mamuye; Abate, Brook; Tekleab, Sirak; Bewket, Woldeamlak

2018-04-01

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.

Trend and uncertainty analysis of simulated climate change impacts with multiple GCMs and emission scenarios

USDA-ARS?s Scientific Manuscript database

Impacts of climate change on hydrology, soil erosion, and wheat production during 2010-2039 at El Reno in central Oklahoma, USA, were simulated using the Water Erosion Prediction Project (WEPP) model. Projections from four GCMs (CCSR/NIES, CGCM2, CSIRO-Mk2, and HadCM3) under three emissions scenari...

Quantifying the impacts of climatic trend and fluctuation on crop yields in northern China.

PubMed

Qiao, Jianmin; Yu, Deyong; Liu, Yupeng

2017-10-01

Climate change plays a critical role in crop yield variations, which has attracted a great deal of concern worldwide. However, the mechanisms of how climatic trend and fluctuations affect crop yields are not well understood and need to be further investigated. Thus, using the GIS-based Environmental Policy Integrated Climate (EPIC) model, we simulated the yields of major crops (i.e., wheat, maize, and rice) and evaluated the impacts of climatic factors on crop yields in the Agro-Pastoral Transitional Zone (APTZ) of northern China between 1980 and 2010. The partial least squares regression model was used to assess the contribution rates of climatic factors (i.e., precipitation, photosynthetically active radiation (PAR), minimum temperature (T min ), maximum temperature (T max )) to the variation of crop yields. The Breaks for Additive Season and Trend (BFAST) model was adopted to decompose the climate factors into trend and fluctuation components, and the relative contributions of climate trend and fluctuation were then evaluated. The results indicated that the contributions of climatic factors to yield variations of wheat, maize, and rice were 31.7, 37.7, and 23.1%, respectively. That is, climate change had larger impacts on maize than wheat and rice. More cultivated areas were significantly and positively correlated with precipitation than with other climatic factors due to the limited precipitation in the APTZ. Also, climatic trend component had positive impacts on crop yields in the whole region, whereas the climate fluctuation was associated mainly with the areas where the crop yields decreased. This study helps improve our understanding of the mechanisms of climate change impacts on crop yields, and provides useful scientific information for designing regional-scale strategies of adaptation to climate change.

Open data mining for Taiwan's dengue epidemic.

PubMed

Wu, ChienHsing; Kao, Shu-Chen; Shih, Chia-Hung; Kan, Meng-Hsuan

2018-07-01

By using a quantitative approach, this study examines the applicability of data mining technique to discover knowledge from open data related to Taiwan's dengue epidemic. We compare results when Google trend data are included or excluded. Data sources are government open data, climate data, and Google trend data. Research findings from analysis of 70,914 cases are obtained. Location and time (month) in open data show the highest classification power followed by climate variables (temperature and humidity), whereas gender and age show the lowest values. Both prediction accuracy and simplicity decrease when Google trends are considered (respectively 0.94 and 0.37, compared to 0.96 and 0.46). The article demonstrates the value of open data mining in the context of public health care. Copyright © 2018 Elsevier B.V. All rights reserved.

Assessment of climate change downscaling and non-stationarity on the spatial pattern of a mangrove ecosystem in an arid coastal region of southern Iran

NASA Astrophysics Data System (ADS)

Etemadi, Halimeh; Samadi, S. Zahra; Sharifikia, Mohammad; Smoak, Joseph M.

2016-10-01

Mangrove wetlands exist in the transition zone between terrestrial and marine environments and have remarkable ecological and socio-economic value. This study uses climate change downscaling to address the question of non-stationarity influences on mangrove variations (expansion and contraction) within an arid coastal region. Our two-step approach includes downscaling models and uncertainty assessment, followed by a non-stationary and trend procedure using the Extreme Value Analysis (extRemes code). The Long Ashton Research Station Weather Generator (LARS-WG) model along with two different general circulation model (GCMs) (MIRH and HadCM3) were used to downscale climatic variables during current (1968-2011) and future (2011-2030, 2045-2065, and 2080-2099) periods. Parametric and non-parametric bootstrapping uncertainty tests demonstrated that the LARS-WGS model skillfully downscaled climatic variables at the 95 % significance level. Downscaling results using MIHR model show that minimum and maximum temperatures will increase in the future (2011-2030, 2045-2065, and 2080-2099) during winter and summer in a range of +4.21 and +4.7 °C, and +3.62 and +3.55 °C, respectively. HadCM3 analysis also revealed an increase in minimum (˜+3.03 °C) and maximum (˜+3.3 °C) temperatures during wet and dry seasons. In addition, we examined how much mangrove area has changed during the past decades and, thus, if climate change non-stationarity impacts mangrove ecosystems. Our results using remote sensing techniques and the non-parametric Mann-Whitney two-sample test indicated a sharp decline in mangrove area during 1972,1987, and 1997 periods ( p value = 0.002). Non-stationary assessment using the generalized extreme value (GEV) distributions by including mangrove area as a covariate further indicated that the null hypothesis of the stationary climate (no trend) should be rejected due to the very low p values for precipitation ( p value = 0.0027), minimum ( p value = 0.000000029) and maximum ( p value = 0.00016) temperatures. Based on non-stationary analysis and an upward trend in downscaled temperature extremes, climate change may control mangrove development in the future.

Malaria incidence trends and their association with climatic variables in rural Gwanda, Zimbabwe, 2005-2015.

PubMed

Gunda, Resign; Chimbari, Moses John; Shamu, Shepherd; Sartorius, Benn; Mukaratirwa, Samson

2017-09-30

Malaria is a public health problem in Zimbabwe. Although many studies have indicated that climate change may influence the distribution of malaria, there is paucity of information on its trends and association with climatic variables in Zimbabwe. To address this shortfall, the trends of malaria incidence and its interaction with climatic variables in rural Gwanda, Zimbabwe for the period January 2005 to April 2015 was assessed. Retrospective data analysis of reported cases of malaria in three selected Gwanda district rural wards (Buvuma, Ntalale and Selonga) was carried out. Data on malaria cases was collected from the district health information system and ward clinics while data on precipitation and temperature were obtained from the climate hazards group infrared precipitation with station data (CHIRPS) database and the moderate resolution imaging spectro-radiometer (MODIS) satellite data, respectively. Distributed lag non-linear models (DLNLM) were used to determine the temporal lagged association between monthly malaria incidence and monthly climatic variables. There were 246 confirmed malaria cases in the three wards with a mean incidence of 0.16/1000 population/month. The majority of malaria cases (95%) occurred in the > 5 years age category. The results showed no correlation between trends of clinical malaria (unconfirmed) and confirmed malaria cases in all the three study wards. There was a significant association between malaria incidence and the climatic variables in Buvuma and Selonga wards at specific lag periods. In Ntalale ward, only precipitation (1- and 3-month lag) and mean temperature (1- and 2-month lag) were significantly associated with incidence at specific lag periods (p < 0.05). DLNM results suggest a key risk period in current month, based on key climatic conditions in the 1-4 month period prior. As the period of high malaria risk is associated with precipitation and temperature at 1-4 month prior in a seasonal cycle, intensifying malaria control activities over this period will likely contribute to lowering the seasonal malaria incidence.

Climatic and chemical drivers of trends in DOC in northern surface waters in Europa and North America

NASA Astrophysics Data System (ADS)

de Wit, Heleen A.; Monteith, Don T.; Stoddard, John L.

2016-04-01

Concentrations of DOC in boreal surface waters have increased to levels that create challenges for water treatment plants, and that potentially impact lake habitat through increased anoxia and thermal mixing, and productivity. Aquatic transport of DOC from land to oceans is likely to increase, even if runoff patterns would remain stable. Reduced acid deposition appears to be a dominant driver behind the increase in DOC concentrations, through increasing organic matter solubility. We hypothesize that the higher solubility of organic matter makes DOC more susceptible to climate change. Here, we present trends in DOC from circa 500 lakes and streams in subarctic, boreal and temperate headwater catchments in Europe (UK, Fennoscandia, Czech Republic, Slovakia) and North America (Northeastern US, Ontario, Atlantic Canada) from 1990 until 2012; an extension of the trend analysis presented in Monteith et al. (2007). The water chemical data stem from national monitoring networks, assembled by the ICP Waters network. Sampling frequencies vary from 1 to 52 samples per year. Climate data were obtained from Climate Research Unit in the UK. Trends were calculated using the Mann-Kendall test and the Sen-slope estimator. We test 1) if DOC responds to changes in the rate of decline in acid deposition, and 2) if trends in temperature and precipitation affect trends and variability in DOC. Positive trends dominate: the median (±2.5% quartile) of the absolute and relative DOC trends is +0.06 (+0.36 to -0.02) mg C L-1 yr-1 and +1.4 (+4.7 to -0.9) % yr-1, respectively. Overall, the trends do not level off when comparing 1990-2004, and 1998-2012, except in the UK and Atlantic Canada. These two regions are strongly impacted by seasalt deposition but may also experience stronger warming than elsewhere. The response of DOC to changes in SO4 (expressed as trend ratios) is stronger in 1998-2012 than in 1990-2004. We will explore whether this changing relates to increasing dominance of drivers, such as temperature or precipitation, and will present multivariate models of DOC trends in relation to climate and deposition. References Monteith DT, Stoddard JL, Evans CD, de Wit HA, Forsius M, Hogasen T, Wilander A, Skjelkvale BL, Jeffries DS, Vuorenmaa J, Keller B, Kopacek J, Vesely J (2007) Dissolved organic carbon trends resulting from changes in atmospheric deposition chemistry. Nature 450(7169): 537-540

Circumpolar analysis of the Adélie Penguin reveals the importance of environmental variability in phenological mismatch

USGS Publications Warehouse

Youngflesh, Casey; Jenouvrier, Stephanie; Li, Yun; Ji, Rubao; Ainley, David G.; Ballard, Grant; Barbraud, Christophe; Delord, Karine; Dugger, Catherine; Emmerson, Loiuse M.; Fraser, William R.; Hinke, Jefferson T.; Lyver, Phil O'B.; Olmastroni, Silvia; Southwell, Colin J.; Trivelpiece, Susan G.; Trivelpiece, Wayne Z.; Lynch, Heather J.

2017-01-01

Evidence of climate-change-driven shifts in plant and animal phenology have raised concerns that certain trophic interactions may be increasingly mismatched in time, resulting in declines in reproductive success. Given the constraints imposed by extreme seasonality at high latitudes and the rapid shifts in phenology seen in the Arctic, we would also expect Antarctic species to be highly vulnerable to climate-change-driven phenological mismatches with their environment. However, few studies have assessed the impacts of phenological change in Antarctica. Using the largest database of phytoplankton phenology, sea-ice phenology, and Adélie Penguin breeding phenology and breeding success assembled to date, we find that, while a temporal match between Penguin breeding phenology and optimal environmental conditions sets an upper limit on breeding success, only a weak relationship to the mean exists. Despite previous work suggesting that divergent trends in Adélie Penguin breeding phenology are apparent across the Antarctic continent, we find no such trends. Furthermore, we find no trend in the magnitude of phenological mismatch, suggesting that mismatch is driven by interannual variability in environmental conditions rather than climate-change-driven trends, as observed in other systems. We propose several criteria necessary for a species to experience a strong climate-change-driven phenological mismatch, of which several may be violated by this system.

Satellite-based Monitoring of global Precipitation using the PERSIANN system: from Weather- to Climate-scales with some application examples

NASA Astrophysics Data System (ADS)

Switzer, A.; Yap, W.; Lauro, F.; Gouramanis, C.; Dominey-Howes, D.; Labbate, M.

2016-12-01

This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.

Satellite-based Monitoring of global Precipitation using the PERSIANN system: from Weather- to Climate-scales with some application examples

NASA Astrophysics Data System (ADS)

Sorooshian, S.; Nguyen, P.; Hsu, K. L.

2017-12-01

This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.

Temperature trends and Urban Heat Island intensity mapping of the Las Vegas valley area

NASA Astrophysics Data System (ADS)

Black, Adam Leland

Modified urban climate regions that are warmer than rural areas at night are referred to as Urban Heat Islands or UHI. Islands of warmer air over a city can be 12 degrees Celsius greater than the surrounding cooler air. The exponential growth in Las Vegas for the last two decades provides an opportunity to detect gradual temperature changes influenced by an increasing presence of urban materials. This thesis compares ground based thermometric observations and satellite based remote sensing temperature observations to identify temperature trends and UHI areas caused by urban development. Analysis of temperature trends between 2000 and 2010 at ground weather stations has revealed a general cooling trend in the Las Vegas region. Results show that urban development accompanied by increased vegetation has a cooling effect in arid climates. Analysis of long term temperature trends at McCarran and Nellis weather stations show 2.4 K and 1.2 K rise in temperature over the last 60 years. The ground weather station temperature data is related to the land surface temperature images from the Landsat Thematic Mapper to estimate and evaluate urban heat island intensity for Las Vegas. Results show that spatial and temporal trends of temperature are related to the gradual change in urban landcover. UHI are mainly observed at the airport and in the industrial areas. This research provides useful insight into the temporal behavior of the Las Vegas area.

Analysis on the Climate Change Characteristics of Dianchi Lake Basin under the Background of Global Warming

NASA Astrophysics Data System (ADS)

Zhenyu, Yu; Luo, Yi; Yang, Kun; Qiongfei, Deng

2017-05-01

Based on the data published by the State Statistical Bureau and the weather station data, the annual mean temperature, wind speed, humidity, light duration and precipitation of Dianchi Lake in 1990 ~ 2014 were analysed. Combined with the population The results show that the climatic changes in Dianchi Lake basin are related to the climatic change in the past 25 years, and the correlation between these factors and the main climatic factors are analysed by linear regression, Mann-Kendall test, cumulative anomaly, R/S and Morlet wavelet analysis. Population, housing construction area growth and other aspects of the correlation trends and changes in the process, revealing the population expansion and housing construction area growth on the climate of the main factors of the cycle tendency of significant impact.

An analysis of surface air temperature trends and variability along the Andes

NASA Astrophysics Data System (ADS)

Franquist, Eric S.

Climate change is difficult to study in mountainous regions such as the Andes since steep changes in elevation cannot always be resolved by climate models. However, it is important to examine temperature trends in this region as rises in surface air temperature are leading to the melting of tropical glaciers. Local communities rely on the glacier-fed streamflow to get their water for drinking, irrigation, and livestock. Moreover, communities also rely on the tourism of hikers who come to the region to view the glaciers. As the temperatures increase, these glaciers are no longer in equilibrium with their current climate and are receding rapidly and decreasing the streamflow. This thesis examines surface air temperature from 858 weather stations across Ecuador, Peru, and Chile in order to analyze changes in trends and variability. Three time periods were studied: 1961--1990, 1971--2000, and 1981--2010. The greatest warming occurred during the period of 1971--2000 with 92% of the stations experiencing positive trends with a mean of 0.24°C/decade. There was a clear shift toward cooler temperatures at all latitudes and below elevations of 500 m during the most recent time period studied (1981--2010). Station temperatures were more strongly correlated with the El Nino Southern Oscillation (ENSO), than the Pacific Decadal Oscillation (PDO), and the Southern Annular Mode (SAM). A principal component analysis confirmed ENSO as the main contributor of variability with the most influence in the lower latitudes. There were clear multidecadal changes in correlation strength for the PDO. The PDO contributed the most to the increases in station temperature trends during the 1961--1990 period, consistent with the PDO shift to the positive phase in the middle of this period. There were many strong positive trends at individual stations during the 1971--2000 period; however, these trends could not fully be attributed to ENSO, PDO, or SAM, indicating anthropogenic effects of greenhouse gas emissions as the most likely cause.

Long-term rise of the Water Table in the Northeast US: Climate Variability, Land-Use Change, or Angry Beavers?

NASA Astrophysics Data System (ADS)

Boutt, D. F.

2011-12-01

The scientific evidence that humans are directly influencing the Earth's natural climate is increasingly compelling. Numerous studies suggest that climate change will lead to changes in the seasonality of surface water availability thereby increasing the need for groundwater development to offset those shortages. Research suggests that the Northeast region of the U.S. is experiencing significant changes to its' natural climate and hydrologic systems. Previous analysis of a long-term regional compilation of the water table response to the last 60 years of climate variability in New England documented a wide range of variability. The investigation evaluated the physical mechanisms, natural variability and response of aquifers in New England using 100 long term groundwater monitoring stations with 20 or more years of data coupled with 67 stream gages, 75 precipitation stations, and 43 temperature stations. Groundwater trends were calculated as normalized anomalies and analyzed with respect to regional compiled precipitation, temperature, and streamflow anomalies to understand the sensitivity of the aquifer systems to change. Interestingly, a trend and regression analysis demonstrate that water level fluctuations are producing statistically significant results with increasing water levels over at least the past thirty years at most (80 out of 100) well sites. In this contribution we investigate the causal mechanisms behind the observed ground water level trends using site-by-site land-use change assessments, cluster analysis, and spatial analysis of beaver populations (a possible proxy for beaver activity). Regionally, average annual precipitation has been slightly increasing since 1900, with 95% of the stations having statistically significant positive trends. Despite this, no correlation is observed between the magnitude of the annual precipitation trends and the magnitude of the groundwater level changes. Land-use change throughout the region has primarily taken place in and around existing urban centers with an overall increase in the percentage of forested land. Individual analysis of well sites in areas with documented land-use change from agriculture and forested land cover to urban land use suggests a positive correlation with increasing water levels. Recently, beaver populations been begun to rise that has led to local increases in wetland areas. These regions also show a high positive correlation to the magnitude of water table rise. Local factors such as land-use change and beaver activity appear to overprint and mask the impact of consistent increases in annual precipitation. Rising water tables have major implications for not only water management but also the agriculture, forestry, fishing, and tourism industries as they all depend on the quantity and quality of water resources of the region.

The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

NASA Astrophysics Data System (ADS)

Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

2016-12-01

Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection capabilities of existing sensors.

Space-time analysis of snow cover change in the Romanian Carpathians (2001-2016)

NASA Astrophysics Data System (ADS)

Micu, Dana; Cosmin Sandric, Ionut

2017-04-01

Snow cover is recognized as an essential climate variable, highly sensitive to the ongoing climate warming, which plays an important role in regulating mountain ecosystems. Evidence from the existing weather stations located above 800 m over the last 50 years points out that the climate of the Romanian Carpathians is visibly changing, showing an ongoing and consistent warming process. Quantifying and attributing the changes in snow cover on various spatial and temporal scales have a great environmental and socio-economic importance for this mountain region. The study is revealing the inter-seasonal changes in the timing and distribution of snow cover across the Romanian Carpathians, by combining gridded snow data (CARPATCLIM dataset, 1961-2010) and remote sensing data (2001-2016) in specific space-time assessment at regional scale. The geostatistical approach applied in this study, based on a GIS hotspot analysis, takes advantage of all the dimensions in the datasets, in order to understand the space-time trends in this climate variable at monthly time-scale. The MODIS AQUA and TERRA images available from 2001 to 2016 have been processed using ArcGIS for Desktop and Python programming language. All the images were masked out with the Carpathians boundary. Only the pixels with snow have been retained for analysis. The regional trends in snow cover distribution and timing have been analysed using Space-Time cube with ArcGIS for Desktop, according with Esri documentation using the Mann-Kendall trend test on every location with data as an independent bin time-series test. The study aimed also to assess the location of emerging hotspots of snow cover change in Carpathians. These hotspots have been calculated using Getis-Ord Gi* statistic for each bin using Hot Spot Analysis implemented in ArcGIS for Desktop. On regional scale, snow cover appear highly sensitive to the decreasing trends in air temperatures and land surface temperatures, combined with the decrease in seasonal precipitation, especially at lower elevations in all the three divisions of the Romanian Carpathians (generally below 1,700-1,800 m). The space-time patterns of snow cover change are dominated by a significant decreasing trend of snow days and earlier spring snow melt. The key findings of this study provides robust indication of a decreasing snow trends across the Carpathian Mountain region and could provide valuable spatial and temporal snow information for other related research fields as well as for an effective environmental monitoring in the mountain ecosystems of the Carpathian region

[Correlation analysis on normalized difference vegetation index (NDVI) of different vegetations and climatic factors in Southwest China].

PubMed

Zhang, Yuan-Dong; Zhang, Xiao-He; Liu, Shi-Rong

2011-02-01

Based on the 1982-2006 NDVI remote sensing data and meteorological data of Southwest China, and by using GIS technology, this paper interpolated and extracted the mean annual temperature, annual precipitation, and drought index in the region, and analyzed the correlations of the annual variation of NDVI in different vegetation types (marsh, shrub, bush, grassland, meadow, coniferous forest, broad-leaved forest, alpine vegetation, and cultural vegetation) with corresponding climatic factors. In 1982-2006, the NDVI, mean annual temperature, and annual precipitation had an overall increasing trend, and the drought index decreased. Particularly, the upward trend of mean annual temperature was statistically significant. Among the nine vegetation types, the NDVI of bush and mash decreased, and the downward trend was significant for bush. The NDVI of the other seven vegetation types increased, and the upward trend was significant for coniferous forest, meadow, and alpine vegetation, and extremely significant for shrub. The mean annual temperature in the areas with all the nine vegetation types increased significantly, while the annual precipitation had no significant change. The drought index in the areas with marsh, bush, and cultural vegetation presented an increasing trend, that in the areas with meadow and alpine vegetation decreased significantly, and this index in the areas with other four vegetation types had an unobvious decreasing trend. The NDVI of shrub and coniferous forest had a significantly positive correlation with mean annual temperature, and that of shrub and meadow had significantly negative correlation with drought index. Under the conditions of the other two climatic factors unchanged, the NDVI of coniferous forest, broad-leaved forest, and alpine vegetation showed the strongest correlation with mean annual temperature, that of grass showed the strongest correlation with annual precipitation, and the NDVI of mash, shrub, grass, meadow, and cultural vegetation showed the strongest correlation with drought index. There existed definite correlations among the climatic factors. If the correlations among the climatic factors were ignored, the significant level of the correlations between NDVI and climatic factors would be somewhat reduced.

The Relationships Between the Trends of Mean and Extreme Precipitation

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Lau, William K.-M.

2017-01-01

This study provides a better understanding of the relationships between the trends of mean and extreme precipitation in two observed precipitation data sets: the Climate Prediction Center Unified daily precipitation data set and the Global Precipitation Climatology Program (GPCP) pentad data set. The study employs three kinds of definitions of extreme precipitation: (1) percentile, (2) standard deviation and (3) generalize extreme value (GEV) distribution analysis for extreme events based on local statistics. Relationship between trends in the mean and extreme precipitation is identified with a novel metric, i.e. area aggregated matching ratio (AAMR) computed on regional and global scales. Generally, more (less) extreme events are likely to occur in regions with a positive (negative) mean trend. The match between the mean and extreme trends deteriorates for increasingly heavy precipitation events. The AAMR is higher in regions with negative mean trends than in regions with positive mean trends, suggesting a higher likelihood of severe dry events, compared with heavy rain events in a warming climate. AAMR is found to be higher in tropics and oceans than in the extratropics and land regions, reflecting a higher degree of randomness and more important dynamical rather than thermodynamical contributions of extreme events in the latter regions.

Exploiting Synoptic-Scale Climate Processes to Develop Nonstationary, Probabilistic Flood Hazard Projections

NASA Astrophysics Data System (ADS)

Spence, C. M.; Brown, C.; Doss-Gollin, J.

2016-12-01

Climate model projections are commonly used for water resources management and planning under nonstationarity, but they do not reliably reproduce intense short-term precipitation and are instead more skilled at broader spatial scales. To provide a credible estimate of flood trend that reflects climate uncertainty, we present a framework that exploits the connections between synoptic-scale oceanic and atmospheric patterns and local-scale flood-producing meteorological events to develop long-term flood hazard projections. We demonstrate the method for the Iowa River, where high flow episodes have been found to correlate with tropical moisture exports that are associated with a pressure dipole across the eastern continental United States We characterize the relationship between flooding on the Iowa River and this pressure dipole through a nonstationary Pareto-Poisson peaks-over-threshold probability distribution estimated based on the historic record. We then combine the results of a trend analysis of dipole index in the historic record with the results of a trend analysis of the dipole index as simulated by General Circulation Models (GCMs) under climate change conditions through a Bayesian framework. The resulting nonstationary posterior distribution of dipole index, combined with the dipole-conditioned peaks-over-threshold flood frequency model, connects local flood hazard to changes in large-scale atmospheric pressure and circulation patterns that are related to flooding in a process-driven framework. The Iowa River example demonstrates that the resulting nonstationary, probabilistic flood hazard projection may be used to inform risk-based flood adaptation decisions.

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data

PubMed Central

Scanlon, Bridget R.; Zhang, Zizhan; Save, Himanshu; Sun, Alexander Y.; van Beek, Ludovicus P. H.; Wiese, David N.; Reedy, Robert C.; Longuevergne, Laurent; Döll, Petra; Bierkens, Marc F. P.

2018-01-01

Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002–2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤−0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km3/y, whereas most models estimate decreasing trends (−71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km3/y) but negative for models (−450 to −12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. PMID:29358394

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data.

PubMed

Scanlon, Bridget R; Zhang, Zizhan; Save, Himanshu; Sun, Alexander Y; Müller Schmied, Hannes; van Beek, Ludovicus P H; Wiese, David N; Wada, Yoshihide; Long, Di; Reedy, Robert C; Longuevergne, Laurent; Döll, Petra; Bierkens, Marc F P

2018-02-06

Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002-2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤-0.5 km 3 /y) and increasing (≥0.5 km 3 /y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km 3 /y, whereas most models estimate decreasing trends (-71 to 11 km 3 /y). Land water storage trends, summed over all basins, are positive for GRACE (∼71-82 km 3 /y) but negative for models (-450 to -12 km 3 /y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. Copyright © 2018 the Author(s). Published by PNAS.

Quantifying the effect of trend, fluctuation, and extreme event of climate change on ecosystem productivity.

PubMed

Liu, Yupeng; Yu, Deyong; Su, Yun; Hao, Ruifang

2014-12-01

Climate change comprises three fractions of trend, fluctuation, and extreme event. Assessing the effect of climate change on terrestrial ecosystem requires an understanding of the action mechanism of these fractions, respectively. This study examined 11 years of remotely sensed-derived net primary productivity (NPP) to identify the impacts of the trend and fluctuation of climate change as well as extremely low temperatures caused by a freezing disaster on ecosystem productivity in Hunan province, China. The partial least squares regression model was used to evaluate the contributions of temperature, precipitation, and photosynthetically active radiation (PAR) to NPP variation. A climatic signal decomposition and contribution assessment model was proposed to decompose climate factors into trend and fluctuation components. Then, we quantitatively evaluated the contributions of each component of climatic factors to NPP variation. The results indicated that the total contribution of the temperature, precipitation, and PAR to NPP variation from 2001 to 2011 in Hunan province is 85 %, and individual contributions of the temperature, precipitation, and PAR to NPP variation are 44 % (including 34 % trend contribution and 10 % fluctuation contribution), 5 % (including 4 % trend contribution and 1 % fluctuation contribution), and 36 % (including 30 % trend contribution and 6 % fluctuation contribution), respectively. The contributions of temperature fluctuation-driven NPP were higher in the north and lower in the south, and the contributions of precipitation trend-driven NPP and PAR fluctuation-driven NPP are higher in the west and lower in the east. As an instance of occasionally triggered disturbance in 2008, extremely low temperatures and a freezing disaster produced an abrupt decrease of NPP in forest and grass ecosystems. These results prove that the climatic trend change brought about great impacts on ecosystem productivity and that climatic fluctuations and extreme events can also alter the ecosystem succession process, even resulting in an alternative trajectory. All of these findings could improve our understanding of the impacts of climate change on the provision of ecosystem functions and services and can also provide a basis for policy makers to apply adaptive measures to overcome the unfavorable influence of climate change.

Evaluation of empirical relationships between extreme rainfall and daily maximum temperature in Australia

NASA Astrophysics Data System (ADS)

Herath, Sujeewa Malwila; Sarukkalige, Ranjan; Nguyen, Van Thanh Van

2018-01-01

Understanding the relationships between extreme daily and sub-daily rainfall events and their governing factors is important in order to analyse the properties of extreme rainfall events in a changing climate. Atmospheric temperature is one of the dominant climate variables which has a strong relationship with extreme rainfall events. In this study, a temperature-rainfall binning technique is used to evaluate the dependency of extreme rainfall on daily maximum temperature. The Clausius-Clapeyron (C-C) relation was found to describe the relationship between daily maximum temperature and a range of rainfall durations from 6 min up to 24 h for seven Australian weather stations, the stations being located in Adelaide, Brisbane, Canberra, Darwin, Melbourne, Perth and Sydney. The analysis shows that the rainfall - temperature scaling varies with location, temperature and rainfall duration. The Darwin Airport station shows a negative scaling relationship, while the other six stations show a positive relationship. To identify the trend in scaling relationship over time the same analysis is conducted using data covering 10 year periods. Results indicate that the dependency of extreme rainfall on temperature also varies with the analysis period. Further, this dependency shows an increasing trend for more extreme short duration rainfall and a decreasing trend for average long duration rainfall events at most stations. Seasonal variations of the scale changing trends were analysed by categorizing the summer and autumn seasons in one group and the winter and spring seasons in another group. Most of 99th percentile of 6 min, 1 h and 24 h rain durations at Perth, Melbourne and Sydney stations show increasing trend for both groups while Adelaide and Darwin show decreasing trend. Furthermore, majority of scaling trend of 50th percentile are decreasing for both groups.

Trend of annual temperature and frequency of extreme events in the MATOPIBA region of Brazil

NASA Astrophysics Data System (ADS)

Salvador, Mozar de A.; de Brito, J. I. B.

2017-06-01

During the 1980s, a new agricultural frontier arouse in Brazil, which occupied part of the states of Maranhão, Tocantins, Piauí, and Bahia. Currently, this new frontier is known as the MATOPIBA region. The region went through intense transformations in its social and environmental characteristics, with the emergence of extensive areas of intensive agriculture and large herds. The purpose of this research was to study the climatic variabilities of temperature in the MATOPIBA region through extreme climate indexes of ClimAp tool. Data from 11 weather stations were analyzed for yearly air temperature (maximum and minimum) in the period of 1970 to 2012. To verify the trend in the series, we used methods of linear regression analysis and Kendall-tau test. The annual analysis of maximum and minimum temperatures and of the temperature extremes indexes showed a strong positive trend in practically every series (with p value less than 0.05). These results indicated that the region went through to a significant heating process in the last 3 decades. The indices of extreme also showed a significant positive trend in most of the analyzed stations, indicating a higher frequency of warm days during the year.

Remotely Sensed Spatio-Temporal Variability of Snow Cover in Himalayan Region with Perspective of Climate Change

NASA Astrophysics Data System (ADS)

Dhakal, S.; Ojha, S.

2017-12-01

Climate change and its impact of water resource have gained tremendous attention among scientific committee, governments and other stakeholders since last couple of decades, especially in Himalayan region. In this study, we purpose remotely sensed measurements to monitor snow cover, both spatially and temporal, and assess climate change impact on water resource. The snow cover data from MODIS satellite (2000-2010) have been used to analyze some climate change indicators. In particular, the variability in the maximum snow extent with elevations, its temporal variability (8-day, monthly, seasonal and annual), its variation trend and its relation with temperature have been analyzed. The snow products used in this study are the maximum snow extent and fractional snow covers, which come in 8-day temporal and 500m and 0.05 degree spatial resolutions, respectively. The results showed a tremendous potential of the MODIS snow product for studying the spatial and temporal variability of snow as well as the study of climate change impact in large and inaccessible regions like the Himalayas. The snow area extent (SAE) (%) time series exhibits similar patterns during seven hydrological years, even though there are some deviations in the accumulation and melt periods. The analysis showed relatively well inverse relation between the daily mean temperature and SAE during the melting period. Some important trends of snow fall are also observed. In particular, the decreasing trend in January and increasing trend in late winter and early spring may be interpreted as a signal of a possible seasonal shift. However, it requires more years of data to verify this conclusion.

Recent climate hiatus revealed dual control by temperature and drought on the stem growth of Mediterranean Quercus ilex.

PubMed

Lempereur, Morine; Limousin, Jean-Marc; Guibal, Frédéric; Ourcival, Jean-Marc; Rambal, Serge; Ruffault, Julien; Mouillot, Florent

2017-01-01

A better understanding of stem growth phenology and its climate drivers would improve projections of the impact of climate change on forest productivity. Under a Mediterranean climate, tree growth is primarily limited by soil water availability during summer, but cold temperatures in winter also prevent tree growth in evergreen forests. In the widespread Mediterranean evergreen tree species Quercus ilex, the duration of stem growth has been shown to predict annual stem increment, and to be limited by winter temperatures on the one hand, and by the summer drought onset on the other hand. We tested how these climatic controls of Q. ilex growth varied with recent climate change by correlating a 40-year tree ring record and a 30-year annual diameter inventory against winter temperature, spring precipitation, and simulated growth duration. Our results showed that growth duration was the best predictor of annual tree growth. We predicted that recent climate changes have resulted in earlier growth onset (-10 days) due to winter warming and earlier growth cessation (-26 days) due to earlier drought onset. These climatic trends partly offset one another, as we observed no significant trend of change in tree growth between 1968 and 2008. A moving-window correlation analysis revealed that in the past, Q. ilex growth was only correlated with water availability, but that since the 2000s, growth suddenly became correlated with winter temperature in addition to spring drought. This change in the climate-growth correlations matches the start of the recent atmospheric warming pause also known as the 'climate hiatus'. The duration of growth of Q. ilex is thus shortened because winter warming has stopped compensating for increasing drought in the last decade. Decoupled trends in precipitation and temperature, a neglected aspect of climate change, might reduce forest productivity through phenological constraints and have more consequences than climate warming alone. © 2016 John Wiley & Sons Ltd.

Spatiotemporal variability of temperature and precipitation in Gansu Province (Northwest China) during 1951-2015

NASA Astrophysics Data System (ADS)

Wen, Xiaohu; Wu, Xiaoqing; Gao, Meng

2017-11-01

Climate change is potentially challenging the sustainable development in many parts of the world, especially the semi-arid and arid regions on the earth. Northwest China (NWC) is one of the most arid areas in East Asia, and Gansu Province is located at the important climate transition zone in NWC. Spatiotemporal variability of both temperature and precipitation were analyzed based on the daily observation dataset at 29 meteorological stations over Gansu during 1951-2015. The Mann-Kendall trend test was utilized to detect monotonic trends in extreme climate indices, mean temperature, and total precipitation. The results revealed that the warming trends were statistically significant at most stations in Gansu, especially at the high altitude stations; however, the change trends in annual and seasonal precipitation over Gansu were not significant as expected. Furthermore, the 29 stations were spatially grouped using hierarchical clustering method. The regional-averaged temperature anomalies also showed a significant warming trend beginning at the end of 1970s. Spatial variations were also observed in the annual and seasonal precipitation over Gansu. In general, precipitation increased in the western part of Gansu while decreased in the eastern part. Additionally, the wavelet analyses revealed that the teleconnection between large scale circulation and summer precipitation varied not only from region to region, but also was different at different time scale and different time periods. Analysis of large-scale atmospheric circulation changes showed that a strengthening anticyclonic circulation, increasing geopotential height and rapid warming over the Eurasian continent were considered to be attributable to climate change in Gansu and even in NWC.

Beyond climate envelopes: effects of weather on regional population trends in butterflies.

PubMed

WallisDeVries, Michiel F; Baxter, Wendy; Van Vliet, Arnold J H

2011-10-01

Although the effects of climate change on biodiversity are increasingly evident by the shifts in species ranges across taxonomical groups, the underlying mechanisms affecting individual species are still poorly understood. The power of climate envelopes to predict future ranges has been seriously questioned in recent studies. Amongst others, an improved understanding of the effects of current weather on population trends is required. We analysed the relation between butterfly abundance and the weather experienced during the life cycle for successive years using data collected within the framework of the Dutch Butterfly Monitoring Scheme for 40 species over a 15-year period and corresponding climate data. Both average and extreme temperature and precipitation events were identified, and multiple regression was applied to explain annual changes in population indices. Significant weather effects were obtained for 39 species, with the most frequent effects associated with temperature. However, positive density-dependence suggested climatic independent trends in at least 12 species. Validation of the short-term predictions revealed a good potential for climate-based predictions of population trends in 20 species. Nevertheless, data from the warm and dry year of 2003 indicate that negative effects of climatic extremes are generally underestimated for habitat specialists in drought-susceptible habitats, whereas generalists remain unaffected. Further climatic warming is expected to influence the trends of 13 species, leading to an improvement for nine species, but a continued decline in the majority of species. Expectations from climate envelope models overestimate the positive effects of climate change in northwestern Europe. Our results underline the challenge to include population trends in predicting range shifts in response to climate change.

Measurements of the Solar Spectral Irradiance Variability over Solar Cycles 21 to 24

NASA Astrophysics Data System (ADS)

Woods, T. N.

2017-12-01

The solar irradiance is the primary natural energy input into Earth's atmosphere and climate system. Understanding the long-term variations of the solar spectral irradiance (SSI) over time scales of the 11-year solar activity cycle and longer is critical for most Sun-climate research topics. There are satellite measurements of the SSI since the 1970s that contribute to understanding the solar cycle variability over Solar Cycles 21 to 24. A limiting factor for the accuracy of these results is the uncertainties for the instrument degradation corrections, for which there are fairly large corrections relative to the amount of solar cycle variability at some wavelengths. A summary of these satellite SSI measurements, which are primarily in the ultraviolet and only recently in the visible and near infrared, will be presented. Examining SSI trends using a new analysis technique is helping to identify some uncorrected instrumental trends, which once applied to the SSI trends has the potential to provide more accurate solar cycle variability results. This new technique examines the SSI trends at different levels of solar activity to provide long-term trends in a SSI record, and one of the most common components of these derived long-term trends is a downward trend that we attribute to being most likely from uncorrected instrument degradation. Examples of this analysis will be presented for some of the satellite SSI measurements to demonstrate this new technique and how it has potential to improve the understanding of solar cycle variability and to clarify the uncertainties of the trends.

Influence of Wave Energetics on Nearshore Storms and Adjacent Shoreline Morphology

NASA Astrophysics Data System (ADS)

Wadman, H. M.; McNinch, J. E.; Hanson, J.

2008-12-01

Large-scale climatic forcings (such as NAO and ENSO) are known to induce fluctuations in regional storm frequency and intensity. Morphology-based studies have traditionally focused on individual storms and their influence on the nearshore coastal wave regime and shoreline response. Few studies have attempted to link long-term observed changes in shoreline position, beach, and nearshore morphology with large-scale climatic forcings that influence regional storm patterns. In order to predict the response of coastlines to future sea level rise and climate change, we need to understand how changes in the frequency of storms affecting nearshore regions (nearshore storms) may influence trends in shoreline position and nearshore morphology. Nearly 30 years of wave data (deep and shallow) collected off of Duck, NC are examined for trends in storm frequency and/or intensity. Changes in shoreline position and shoreface elevation, as observed from monthly beach transects over the same period, are also investigated in light of the observed trends in hydrodynamic forcings. Our preliminary analysis was unable to identify any consistent linear trends (increases or decreases) in frequency or intensity over the ~30-year time period in either the offshore wave heights or the nearshore storm record. These data might suggest that previous observations of recent increases in storm intensity and frequency, speculated to be due to climate change, might be spatially limited. Future analyses will partition the contributions from individual wind sea and swell events in order to better identify long-term trends in wave energetics from the various wave generation regions in the Atlantic. At this location, offshore wave height and the nearshore storm record are dominated by seasonal fluctuations and a strong interdecadal- to decadal periodicity. Previous research in Duck, NC has suggested that changes in shoreline position and shoreface elevations are related both to seasonal trends as well as "storm groupiness". Our analyses support these findings, but also identify interdecadal- to decadal trends in the nearshore morphology. Despite these fluctuations, the overall position of the shoreline and elevation of the shoreface shows little net change over the 30 years investigated. We hypothesize that the interdecadal- to decadal periodicity in the morphology is driven largely by the influences of large-scale climatic forcings on the nearshore wave regime as reflected in the storm record. We also explore the relationship between morphological periodicity, storm and wave height periodicity, and climatic fluctuations.

Response of groundwater level and surface-water/groundwater interaction to climate variability: Clarence-Moreton Basin, Australia

NASA Astrophysics Data System (ADS)

Cui, Tao; Raiber, Matthias; Pagendam, Dan; Gilfedder, Mat; Rassam, David

2018-03-01

Understanding the response of groundwater levels in alluvial and sedimentary basin aquifers to climatic variability and human water-resource developments is a key step in many hydrogeological investigations. This study presents an analysis of groundwater response to climate variability from 2000 to 2012 in the Queensland part of the sedimentary Clarence-Moreton Basin, Australia. It contributes to the baseline hydrogeological understanding by identifying the primary groundwater flow pattern, water-level response to climate extremes, and the resulting dynamics of surface-water/groundwater interaction. Groundwater-level measurements from thousands of bores over several decades were analysed using Kriging and nonparametric trend analysis, together with a newly developed three-dimensional geological model. Groundwater-level contours suggest that groundwater flow in the shallow aquifers shows local variations in the close vicinity of streams, notwithstanding general conformance with topographic relief. The trend analysis reveals that climate variability can be quickly reflected in the shallow aquifers of the Clarence-Moreton Basin although the alluvial aquifers have a quicker rainfall response than the sedimentary bedrock formations. The Lockyer Valley alluvium represents the most sensitively responding alluvium in the area, with the highest declining (-0.7 m/year) and ascending (2.1 m/year) Sen's slope rates during and after the drought period, respectively. Different surface-water/groundwater interaction characteristics were observed in different catchments by studying groundwater-level fluctuations along hydrogeologic cross-sections. The findings of this study lay a foundation for future water-resource management in the study area.

Productivity and phenological responses of natural vegetation to present and future inter-annual climate variability across semi-arid river basins in Chile.

PubMed

Glade, Francisco E; Miranda, Marcelo D; Meza, Francisco J; van Leeuwen, Willem J D

2016-12-01

Time series of vegetation indices and remotely sensed phenological data offer insights about the patterns in vegetation dynamics. Both are useful sources of information for analyzing and monitoring ecosystem responses to environmental variations caused by natural and anthropogenic drivers. In the semi-arid region of Chile, climate variability and recent severe droughts in addition to land-use changes pose threats to the stability of local ecosystems. Normalized difference vegetation index time series (2000-2013) data from the moderate resolution imaging spectroradiometer (MODIS) was processed to monitor the trends and patterns of vegetation productivity and phenology observed over the last decade. An analysis of the relationship between (i) vegetation productivity and (ii) precipitation and temperature data for representative natural land-use cover classes was made. Using these data and ground measurements, productivity estimates were projected for two climate change scenarios (RCP2.6 and RCP8.5) at two altitudinal levels. Results showed negative trends of vegetation productivity below 2000 m a.s.l. and positive trends for higher elevations. Phenology analysis suggested that mountainous ecosystems were starting their growing period earlier in the season, coinciding with a decreased productivity peak during the growing season. The coastal shrubland/grassland land cover class had a significant positive relation with rainfall and a significant negative relation with temperature, suggesting that these ecosystems are vulnerable to climate change. Future productivity projections indicate that under an RCP8.5 climate change scenario, productivity could decline by 12% in the period of 2060-2100, leading to a severe vegetation degradation at lower altitudes and in drier areas.

Variability of temperature properties over Kenya based on observed and reanalyzed datasets

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Gao, Chujie; Sagero, Phillip Obaigwa

2017-08-01

Updated information on trends of climate extremes is central in the assessment of climate change impacts. This work examines the trends in mean, diurnal temperature range (DTR), maximum and minimum temperatures, 1951-2012 and the recent (1981-2010) extreme temperature events over Kenya. The study utilized daily observed and reanalyzed monthly mean, minimum, and maximum temperature datasets. The analysis was carried out based on a set of nine indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The trend of the mean and the extreme temperature was determined using Mann-Kendall rank test, linear regression analysis, and Sen's slope estimator. December-February (DJF) season records high temperature while June-August (JJA) experiences the least temperature. The observed rate of warming is + 0.15 °C/decade. However, DTR does not show notable annual trend. Both seasons show an overall warming trend since the early 1970s with abrupt and significant changes happening around the early 1990s. The warming is more significant in the highland regions as compared to their lowland counterparts. There is increase variance in temperature. The percentage of warm days and warm nights is observed to increase, a further affirmation of warming. This work is a synoptic scale study that exemplifies how seasonal and decadal analyses, together with the annual assessments, are important in the understanding of the temperature variability which is vital in vulnerability and adaptation studies at a local/regional scale. However, following the quality of observed data used herein, there remains need for further studies on the subject using longer and more data to avoid generalizations made in this study.

Long-term trends of surface ozone and its influencing factors at the Mt Waliguan GAW station, China - Part 1: Overall trends and characteristics

NASA Astrophysics Data System (ADS)

Xu, Wanyun; Lin, Weili; Xu, Xiaobin; Tang, Jie; Huang, Jianqing; Wu, Hao; Zhang, Xiaochun

2016-05-01

Tropospheric ozone is an important atmospheric oxidant, greenhouse gas and atmospheric pollutant at the same time. The oxidation capacity of the atmosphere, climate, human and vegetation health can be impacted by the increase of the ozone level. Therefore, long-term determination of trends of baseline ozone is highly needed information for environmental and climate change assessment. So far, studies on the long-term trends of ozone at representative sites are mainly available for European and North American sites. Similar studies are lacking for China and many other developing countries. Measurements of surface ozone were carried out at a baseline Global Atmospheric Watch (GAW) station in the north-eastern Tibetan Plateau region (Mt Waliguan, 36°17' N, 100°54' E, 3816 m a.s.l.) for the period of 1994 to 2013. To uncover the variation characteristics, long-term trends and influencing factors of surface ozone at this remote site in western China, a two-part study has been carried out, with this part focusing on the overall characteristics of diurnal, seasonal and long-term variations and the trends of surface ozone. To obtain reliable ozone trends, we performed the Mann-Kendall trend test and the Hilbert-Huang transform (HHT) analysis on the ozone data. Our results confirm that the mountain-valley breeze plays an important role in the diurnal cycle of surface ozone at Waliguan, resulting in higher ozone values during the night and lower ones during the day, as was previously reported. Systematic diurnal and seasonal variations were found in mountain-valley breezes at the site, which were used in defining season-dependent daytime and nighttime periods for trend calculations. Significant positive trends in surface ozone were detected for both daytime (0.24 ± 0.16 ppbv year-1) and nighttime (0.28 ± 0.17 ppbv year-1). The largest nighttime increasing rate occurred in autumn (0.29 ± 0.11 ppbv year-1), followed by spring (0.24 ± 0.12 ppbv year-1), summer (0.22 ± 0.20 ppbv year-1) and winter (0.13 ± 0.10 ppbv year-1), respectively. The HHT spectral analysis identified four different stages with different positive trends, with the largest increase occurring around May 2000 and October 2010. The HHT results suggest that there were 2-4a, 7a and 11a periodicities in the time series of surface ozone at Waliguan. The results of this study can be used for assessments of climate and environment change and in the validation of chemistry-climate models.

Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

NASA Astrophysics Data System (ADS)

Safavi, Hamid R.; Sajjadi, Sayed Mahdi; Raghibi, Vahid

2017-10-01

Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971-2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015-2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nasrollahi, Nasrin; AghaKouchak, Amir; Cheng, Linyin

Assessing the uncertainties and understanding the deficiencies of climate models are fundamental to developing adaptation strategies. The objective of this study is to understand how well Coupled Model Intercomparison-Phase 5 (CMIP5) climate model simulations replicate ground-based observations of continental drought areas and their trends. The CMIP5 multimodel ensemble encompasses the Climatic Research Unit (CRU) ground-based observations of area under drought at all time steps. However, most model members overestimate the areas under extreme drought, particularly in the Southern Hemisphere (SH). Furthermore, the results show that the time series of observations and CMIP5 simulations of areas under drought exhibit more variabilitymore » in the SH than in the Northern Hemisphere (NH). The trend analysis of areas under drought reveals that the observational data exhibit a significant positive trend at the significance level of 0.05 over all land areas. The observed trend is reproduced by about three-fourths of the CMIP5 models when considering total land areas in drought. While models are generally consistent with observations at a global (or hemispheric) scale, most models do not agree with observed regional drying and wetting trends. Over many regions, at most 40% of the CMIP5 models are in agreement with the trends of CRU observations. The drying/wetting trends calculated using the 3 months Standardized Precipitation Index (SPI) values show better agreement with the corresponding CRU values than with the observed annual mean precipitation rates. As a result, pixel-scale evaluation of CMIP5 models indicates that no single model demonstrates an overall superior performance relative to the other models.« less

Trends in atmospheric evaporative demand in Great Britain using high-resolution meteorological data

NASA Astrophysics Data System (ADS)

Robinson, Emma L.; Blyth, Eleanor M.; Clark, Douglas B.; Finch, Jon; Rudd, Alison C.

2017-02-01

Observations of climate are often available on very different spatial scales from observations of the natural environments and resources that are affected by climate change. In order to help bridge the gap between these scales using modelling, a new dataset of daily meteorological variables was created at 1 km resolution over Great Britain for the years 1961-2012, by interpolating coarser resolution climate data and including the effects of local topography. These variables were used to calculate atmospheric evaporative demand (AED) at the same spatial and temporal resolution. Two functions that represent AED were chosen: one is a standard form of potential evapotranspiration (PET) and the other is a derived PET measure used by hydrologists that includes the effect of water intercepted by the canopy (PETI). Temporal trends in these functions were calculated, with PET found to be increasing in all regions, and at an overall rate of 0.021 ± 0.021 mm day-1 decade-1 in Great Britain. PETI was found to be increasing at a rate of 0.019 ± 0.020 mm day-1 decade-1 in Great Britain, but this was not statistically significant. However, there was a trend in PETI in England of 0.023 ± 0.023 mm day-1 decade-1. The trends were found to vary by season, with spring PET increasing by 0.043 ± 0.019 mm day-1 decade-1 (0.038 ± 0.018 mm day-1 decade-1 when the interception correction is included) in Great Britain, while there is no statistically significant trend in other seasons. The trends were attributed analytically to trends in the climate variables; the overall positive trend was predominantly driven by rising air temperature, although rising specific humidity had a negative effect on the trend. Recasting the analysis in terms of relative humidity revealed that the overall effect is that falling relative humidity causes the PET to rise. Increasing downward short- and longwave radiation made an overall positive contribution to the PET trend, while decreasing wind speed made a negative contribution to the trend in PET. The trend in spring PET was particularly strong due to a strong decrease in relative humidity and increase in downward shortwave radiation in the spring.

Human influence on tropical cyclone intensity.

PubMed

Sobel, Adam H; Camargo, Suzana J; Hall, Timothy M; Lee, Chia-Ying; Tippett, Michael K; Wing, Allison A

2016-07-15

Recent assessments agree that tropical cyclone intensity should increase as the climate warms. Less agreement exists on the detection of recent historical trends in tropical cyclone intensity. We interpret future and recent historical trends by using the theory of potential intensity, which predicts the maximum intensity achievable by a tropical cyclone in a given local environment. Although greenhouse gas-driven warming increases potential intensity, climate model simulations suggest that aerosol cooling has largely canceled that effect over the historical record. Large natural variability complicates analysis of trends, as do poleward shifts in the latitude of maximum intensity. In the absence of strong reductions in greenhouse gas emissions, future greenhouse gas forcing of potential intensity will increasingly dominate over aerosol forcing, leading to substantially larger increases in tropical cyclone intensities. Copyright © 2016, American Association for the Advancement of Science.

Sensitivity of bud burst in key tree species in the UK to recent climate variability and change

NASA Astrophysics Data System (ADS)

Abernethy, Rachel; Cook, Sally; Hemming, Deborah; McCarthy, Mark

2017-04-01

Analysing the relationship between the changing climate of the UK and the spatial and temporal distribution of spring bud burst plays an important role in understanding ecosystem functionality and predicting future phenological trends. The location and timing of bud burst of eleven species of trees alongside climatic factors such as, temperature, precipitation and hours of sunshine (photoperiod) were used to investigate: i. which species' bud burst timing experiences the greatest impact from a changing climate, ii. which climatic factor has the greatest influence on the timing of bud burst, and iii. whether the location of bud burst is influenced by climate variability. Winter heatwave duration was also analysed as part of an investigation into the relationship between temperature trends of a specific winter period and the following spring events. Geographic Information Systems (GIS) and statistical analysis tools were used to visualise spatial patterns and to analyse the phenological and climate data through regression and analysis of variance (ANOVA) tests. Where there were areas that showed a strong positive or negative relationship between phenology and climate, satellite imagery was used to calculate a Normalised Difference Vegetation Index (NDVI) and a Leaf Area Index (LAI) to further investigate the relationships found. It was expected that in the north of the UK, where bud burst tends to occur later in the year than in the south, that the bud bursts would begin to occur earlier due to increasing temperatures and increased hours of sunshine. However, initial results show that for some species, the bud burst timing tends to remain or become later in the year. Interesting results will be found when investigating the statistical significance between the changing location of the bud bursts and each climatic factor.

Spring onset variations and long-term trends from new hemispheric-scale products and remote sensing

NASA Astrophysics Data System (ADS)

Dye, D. G.; Li, X.; Ault, T.; Zurita-Milla, R.; Schwartz, M. D.

2015-12-01

Spring onset is commonly characterized by plant phenophase changes among a variety of biophysical transitions and has important implications for natural and man-managed ecosystems. Here, we present a new integrated analysis of variability in gridded Northern Hemisphere spring onset metrics. We developed a set of hemispheric temperature-based spring indices spanning 1920-2013. As these were derived solely from meteorological data, they are used as a benchmark for isolating the climate system's role in modulating spring "green up" estimated from the annual cycle of normalized difference vegetation index (NDVI). Spatial patterns of interannual variations, teleconnections, and long-term trends were also analyzed in all metrics. At mid-to-high latitudes, all indices exhibit larger variability at interannual to decadal time scales than at spatial scales of a few kilometers. Trends of spring onset vary across space and time. However, compared to long-term trend, interannual to decadal variability generally accounts for a larger portion of the total variance in spring onset timing. Therefore, spring onset trends identified from short existing records may be aliased by decadal climate variations due to their limited temporal depth, even when these records span the entire satellite era. Based on our findings, we also demonstrated that our indices have skill in representing ecosystem-level spring phenology and may have important implications in understanding relationships between phenology, atmosphere dynamics and climate variability.

An 'Observational Large Ensemble' to compare observed and modeled temperature trend uncertainty due to internal variability.

NASA Astrophysics Data System (ADS)

Poppick, A. N.; McKinnon, K. A.; Dunn-Sigouin, E.; Deser, C.

2017-12-01

Initial condition climate model ensembles suggest that regional temperature trends can be highly variable on decadal timescales due to characteristics of internal climate variability. Accounting for trend uncertainty due to internal variability is therefore necessary to contextualize recent observed temperature changes. However, while the variability of trends in a climate model ensemble can be evaluated directly (as the spread across ensemble members), internal variability simulated by a climate model may be inconsistent with observations. Observation-based methods for assessing the role of internal variability on trend uncertainty are therefore required. Here, we use a statistical resampling approach to assess trend uncertainty due to internal variability in historical 50-year (1966-2015) winter near-surface air temperature trends over North America. We compare this estimate of trend uncertainty to simulated trend variability in the NCAR CESM1 Large Ensemble (LENS), finding that uncertainty in wintertime temperature trends over North America due to internal variability is largely overestimated by CESM1, on average by a factor of 32%. Our observation-based resampling approach is combined with the forced signal from LENS to produce an 'Observational Large Ensemble' (OLENS). The members of OLENS indicate a range of spatially coherent fields of temperature trends resulting from different sequences of internal variability consistent with observations. The smaller trend variability in OLENS suggests that uncertainty in the historical climate change signal in observations due to internal variability is less than suggested by LENS.

O the Interpretation of Climatic Change from the Fossil Record: Climatic Change in Central and Eastern United States for the Past 2000 Years Estimated from Pollen Data.

NASA Astrophysics Data System (ADS)

Gajewski, Konrad J.

Pollen records from varved-lake sediments at seven locations in the northeastern United States record late Holocene climate changes over the past 1000-2000 years. Simplification of pollen diagrams by principal component analysis documents that climate changes affect vegetation at all sites, and not just at "sensitive" sites or ecotones. All seven pollen records show a long-term trend, medium frequency oscillations and higher frequency fluctuations. The between-site similarity of the trend and the coherency of the medium frequency oscillations demonstrates the importance of climate forcing to vegetation change at these scales. Response of vegetation to a climatic change is quite rapid, and depends not only on the nature of the climate fluctuation, but also on the pre-existing state of the vegetation. Multiple regression and canonical correlation techniques were used to calculate calibration functions from a spatial network of modern pollen and climate data. When analyzed at comparable scales, the spatial distribution of pollen assemblages in northeastern United States are related both to summer temperature and annual precipitation. Although summer temperature and annual precipitation are coupled, this coupling is not so strong as to negate the use of univariate calibration models. Over the 2000-year period of time, a gradual summer cooling of about 1.0(DEGREES)C/1000 years has occurred. Superimposed on the long-term trend are medium frequency temperature fluctuations of amplitude about 0.5(DEGREES)C that persist for several centuries. Annual precipitation is relatively constant, except for a period of increased rainfall from 600 years ago to the present in southern Maine.

On the variability of cold region flooding

NASA Astrophysics Data System (ADS)

Matti, Bettina; Dahlke, Helen E.; Lyon, Steve W.

2016-03-01

Cold region hydrological systems exhibit complex interactions with both climate and the cryosphere. Improving knowledge on that complexity is essential to determine drivers of extreme events and to predict changes under altered climate conditions. This is particularly true for cold region flooding where independent shifts in both precipitation and temperature can have significant influence on high flows. This study explores changes in the magnitude and the timing of streamflow in 18 Swedish Sub-Arctic catchments over their full record periods available and a common period (1990-2013). The Mann-Kendall trend test was used to estimate changes in several hydrological signatures (e.g. annual maximum daily flow, mean summer flow, snowmelt onset). Further, trends in the flood frequency were determined by fitting an extreme value type I (Gumbel) distribution to test selected flood percentiles for stationarity using a generalized least squares regression approach. Results highlight shifts from snowmelt-dominated to rainfall-dominated flow regimes with all significant trends (at the 5% significance level) pointing toward (1) lower magnitudes in the spring flood; (2) earlier flood occurrence; (3) earlier snowmelt onset; and (4) decreasing mean summer flows. Decreasing trends in flood magnitude and mean summer flows suggest widespread permafrost thawing and are supported by increasing trends in annual minimum daily flows. Trends in selected flood percentiles showed an increase in extreme events over the full periods of record (significant for only four catchments), while trends were variable over the common period of data among the catchments. An uncertainty analysis emphasizes that the observed trends are highly sensitive to the period of record considered. As such, no clear overall regional hydrological response pattern could be determined suggesting that catchment response to regionally consistent changes in climatic drivers is strongly influenced by their physical characteristics.

[Organization, availability and possibility of analysis of disaster data of climate related origin and its impacts on health].

PubMed

Xavier, Diego Ricardo; Barcellos, Christovam; Barros, Heglaucio da Silva; Magalhães, Monica de Avelar Figueiredo Mafra; Matos, Vanderlei Pascoal de; Pedroso, Marcel de Moraes

2014-09-01

The occurrence of disasters is often related to unforeseeable able natural processes. However, the analysis of major databases may highlight seasonal and long-term trends, as well as some spatial patterns where risks are concentrated. In this paper the process of acquiring and organizing climate-related disaster data collected by civil protection institutions and made available by the Brazilian Climate and Health Observatory is described. Preliminary analyses show the concentration of disasters caused by heavy rainfall events along the Brazilian coastline especially during the summer. Droughts have longer duration and extent, affecting large areas of the south and northeast regions of the country. These data can be used to analyze and monitor the impact of extreme climatic events on health, as well as identify the vulnerability and climate deteminants.

Dominance of climate warming effects on recent drying trends over wet monsoon regions

NASA Astrophysics Data System (ADS)

Park, Chang-Eui; Jeong, Su-Jong; Ho, Chang-Hoi; Park, Hoonyoung; Piao, Shilong; Kim, Jinwon; Feng, Song

2017-09-01

Understanding changes in background dryness over land is key information for adapting to climate change because of its critical socioeconomic consequences. However, causes of continental dryness changes remain uncertain because various climate parameters control dryness. Here, we verify dominant climate variables determining dryness trends over continental eastern Asia, which is characterized by diverse hydroclimate regimes ranging from arid to humid, by quantifying the relative effects of changes in precipitation, solar radiation, wind speed, surface air temperature, and relative humidity on trends in the aridity index based on observed data from 189 weather stations for the period of 1961-2010. Before the early 1980s (1961-1983), change in precipitation is a primary condition for determining aridity trends. In the later period (1984-2010), the dominant climate parameter for aridity trends varies according to the hydroclimate regime. Drying trends in arid regions are mostly explained by reduced precipitation. In contrast, the increase in potential evapotranspiration due to increased atmospheric water-holding capacity, a secondary impact of warming, works to increase aridity over the humid monsoon region despite an enhanced water supply and relatively less warming. Our results show significant drying effects of warming over the humid monsoon region in recent decades; this also supports the drying trends over warm and water-sufficient regions in future climate.

Supporting Climatic Trends of Corn and Soybean Production in the USA

NASA Astrophysics Data System (ADS)

Mishra, V.; Cherkauer, K. A.; Verdin, J. P.

2010-12-01

The United States of America (USA) is a major source of corn and soybeans, producing about 39 percent of the world’s corn and 50 percent of world’s soybean supply. The north central states, including parts of the Midwestern US and the Great Plains form what is commonly described as the “Corn Belt” and consist of the most productive grain growing region in the United States. Changes in climate, including precipitation and temperature, are being observed throughout the world, and the Corn Belt region of the US is not immune posing a potential threat to global food security. We conducted a retrospective analysis of observed climate variables and crop production statistics to evaluate if observed climatic trends are having a positive or negative effect on corn and soybean production in the US. We selected climate indices based on gridded daily precipitation, maximum and minimum air temperature data from the National Climatic Data Center (NCDC) for the period of 1920-2009 and for 13 states in the Corn Belt region. We used the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) for different periods overlapping the important seasons for crop growths, such as the planting (April-May), grain-filling (June-August), and harvesting (September -October) seasons. We estimated the seasonal average of maximum and minimum daily temperatures to identify the historic trends and variability in air temperature during the key crop-growth seasons. Extreme warm temperatures can affect crop growth and yields adversely; therefore, cumulative maximum air temperature above the 90th percentiles (e.g. Cumulative Heat Index) was estimated for each growing period. We evaluated historic trends and variability of areal extents of severe or extreme droughts along with the areal extents facing the high cumulative heat stress. Our results showed that climatic extremes (e.g. droughts and heat stress) that occurred during the period of June - August (JJA), affected the yields of corn and soybeans most severely. High moisture and low heat stress during the JJA period favored crop yields, while low moisture and high heat conditions during the planting season (April-May) increased yields. Results also indicated that this part of the US is trending towards lower heat stress and drought extents, and higher moisture conditions during the JJA period. Therefore, in future, if the present trends persist, we expect the climate will more supportive of increased corn and soybean yields.

Assessing the impacts of climate change and nitrogen deposition on Norway spruce (Picea abies L. Karst) growth in Austria with BIOME-BGC.

PubMed

Eastaugh, Chris S; Pötzelsberger, Elisabeth; Hasenauer, Hubert

2011-03-01

The aim of this paper is to determine whether a detectable impact of climate change is apparent in Austrian forests. In regions of complex terrain such as most of Austria, climatic trends over the past 50 years show marked geographic variability. As climate is one of the key drivers of forest growth, a comparison of growth characteristics between regions with different trends in temperature and precipitation can give insights into the impact of climatic change on forests. This study uses data from several hundred climate recording stations, interpolated to measurement sites of the Austrian National Forest Inventory (NFI). Austria as a whole shows a warming trend over the past 50 years and little overall change in precipitation. The warming trends, however, vary considerably across certain regions and regional precipitation trends vary widely in both directions, which cancel out on the national scale These differences allow the delineation of 'climatic change zones' with internally consistent climatic trends that differ from other zones. This study applies the species-specific adaptation of the biogeochemical model BIOME-BGC to Norway spruce (Picea abies (L.) Karst) across a range of Austrian climatic change zones, using input data from a number of national databases. The relative influence of extant climate change on forest growth is quantified, and compared with the far greater impact of non-climatic factors. At the national scale, climate change is found to have negligible effect on Norway spruce productivity, due in part to opposing effects at the regional level. The magnitudes of the modeled non-climatic influences on aboveground woody biomass increment increases are consistent with previously reported values of 20-40 kg of added stem carbon sequestration per kilogram of additional nitrogen deposition, while climate responses are of a magnitude difficult to detect in NFI data.

Late Cenozoic Climate Change and its Implications on the Denudation of Orogen Syntaxes

NASA Astrophysics Data System (ADS)

Mutz, Sebastian; Ehlers, Todd

2017-04-01

The denudation history of active orogens is often interpreted in the context of modern climate gradients. Despite the influence of climatic conditions on erosion rates, information about paleoclimate evolution is often not available and thus not considered when denudation histories are interpreted. In this study, we analyze output from paleoclimate simulations conducted with ECHAM5-wiso at T159 (ca. 80x80km) resolution. Specifically, we analyze simulations of pre-industrial (PI, pre-1850), Mid-Holocene (MH, ca. 6ka), Last Glacial Maximum (LGM, ca. 21ka) and Pliocene (PLIO, ca. 3ka) climates and focus on a selection of orogen syntaxes as study regions (e.g. Himalaya, SE Alaska, Cascadia, and Central Andes). For the selected region, we carry out a cluster analysis using a hybrid of hierarchical and k-means clustering procedures using mean annual temperature (MAT), temperature amplitude, mean annual precipitation (MAP), precipitation amplitude and u-wind and v-wind in different months to provide a general overview of paleoclimates in the study regions. Additionally, we quantify differences between paleoclimates by applying two-group linear discrimination analyses to the simulation output for a similar selection of variables. Results indicate the largest differences to the PI climate are observed for the LGM and PLIO climates in the form of widespread cooling and reduced precipitation in the LGM and warming and enhanced precipitation during the PLIO. These global trends can be observed for most locations in the investigated areas, but the strength varies regionally and the trends in precipitation are less uniform than trends in temperatures. The LGM climate shows the largest deviation in annual precipitation from the PI climate, and shows enhanced precipitation in the temperate Andes, and coastal regions for both SE Alaska and the US Pacific Northwest Pacific. Furthermore, LGM precipitation is reduced in the western Himalayas and enhanced in the eastern Himalayas, resulting in a shift of the wettest regional climates eastward along the orogen towards the eastern syntax. The cluster-analysis results also suggest more climatic variability across latitudes east of the Andes in the PLIO climate than in other time-slice experiments conducted here. Results from the discriminant analysis show that the quantified differences in climate and the relative contribution to these differences by each of the analyzed parameters are highly variable in space for each of the paleoclimates. Taken together, these results highlight significant changes in Late Cenozoic regional climatology over active orogens on time scales ranging from glacial cycles to geologic. As a result, future interpretation of recent and paleo denudation rates in these areas from sediment flux inventories, cosmogenic radionuclides, or low-temperature thermochronology techniques warrant careful consideration of these changes.

Lemonade's the Name, Simulation's the Game.

ERIC Educational Resources Information Center

Friel, Susan

1983-01-01

Provides a detailed description of Lemonade, a business game designed to introduce elementary and secondary students to the basics of business; i.e., problem solving strategies, hypothesis formulation and testing, trend analysis, prediction, comparative analysis, and effects of such factors as advertising and climatic conditions on sales and…

Impact of climate change on potential evapotranspiration (case study: west and NW of Iran)

NASA Astrophysics Data System (ADS)

Dinpashoh, Y.; Jahanbakhsh-Asl, S.; Rasouli, A. A.; Foroughi, M.; Singh, V. P.

2018-04-01

Potential evapotranspiration (ET0) is one of the main elements when computing agricultural irrigation requirements and scheduling. All climatic parameters as well as ET0 are influenced by climate change. The aim of this study is trend analysis of monthly and annual ET0 time series in the west and NW of Iran. Values of ET0 are estimated at 36 selected stations, using the FAO-56 Penman-Monteith (FAO-56 PM) method. Then, the non-parametric Mann-Kendall (MK) method was used to detect trends. The slopes of trend lines are estimated using Sen's estimator approach. Results showed that about 86%of the monthly ET0 time series had upward trends of which 35.6 and 43% were significant at 0.01 and 0.05 levels, respectively, 47.4% exhibited a significant upward trend at the 10% level. In contrast, less than 0.7% of the whole monthly ET0 time series showed a significant downward trend (α < 0.01). Only 1.1% of the monthly ET0 time series had significant downward trends (α < 0.10). The strongest positive upward trend (significant at the 0.01 level) was detected in August at the Kermanshah station. However, the strongest negative downward trend belonged to the Khodabandeh station. The steepest upward and downward monthly ET0 slopes were observed at Maragheh and Khodabandeh stations. The magnitude of trends for these two stations are estimated as 2.33 and - 2.01 mm/year, respectively. On an annual timescale, above 94% of the stations had upward trend slopes. About 67% of the total stations exhibited significant trends at the 10% level. Very few sites (2.7%) showed downward annual ET0 trends (α < 0.10). At the annual scale, the first three strongest upward trends belonged to the Kermanshah, Urmia, and Tabriz stations, respectively (α < 0.01). It can be concluded that ET0 in the west and NW of Iran have an increasing trend for most of the stations. Therefore, it is important to use water in a prudent manner in this area.

Population trends influence species ability to track climate change.

PubMed

Ralston, Joel; DeLuca, William V; Feldman, Richard E; King, David I

2017-04-01

Shifts of distributions have been attributed to species tracking their fundamental climate niches through space. However, several studies have now demonstrated that niche tracking is imperfect, that species' climate niches may vary with population trends, and that geographic distributions may lag behind rapid climate change. These reports of imperfect niche tracking imply shifts in species' realized climate niches. We argue that quantifying climate niche shifts and analyzing them for a suite of species reveal general patterns of niche shifts and the factors affecting species' ability to track climate change. We analyzed changes in realized climate niche between 1984 and 2012 for 46 species of North American birds in relation to population trends in an effort to determine whether species differ in the ability to track climate change and whether differences in niche tracking are related to population trends. We found that increasingly abundant species tended to show greater levels of niche expansion (climate space occupied in 2012 but not in 1980) compared to declining species. Declining species had significantly greater niche unfilling (climate space occupied in 1980 but not in 2012) compared to increasing species due to an inability to colonize new sites beyond their range peripheries after climate had changed at sites of occurrence. Increasing species, conversely, were better able to colonize new sites and therefore showed very little niche unfilling. Our results indicate that species with increasing trends are better able to geographically track climate change compared to declining species, which exhibited lags relative to changes in climate. These findings have important implications for understanding past changes in distribution, as well as modeling dynamic species distributions in the face of climate change. © 2016 John Wiley & Sons Ltd.

On the definition and identifiability of the alleged "hiatus" in global warming.

PubMed

Lewandowsky, Stephan; Risbey, James S; Oreskes, Naomi

2015-11-24

Recent public debate and the scientific literature have frequently cited a "pause" or "hiatus" in global warming. Yet, multiple sources of evidence show that climate change continues unabated, raising questions about the status of the "hiatus". To examine whether the notion of a "hiatus" is justified by the available data, we first document that there are multiple definitions of the "hiatus" in the literature, with its presumed onset spanning a decade. For each of these definitions we compare the associated temperature trend against trends of equivalent length in the entire record of modern global warming. The analysis shows that the "hiatus" trends are encompassed within the overall distribution of observed trends. We next assess the magnitude and significance of all possible trends up to 25 years duration looking backwards from each year over the past 30 years. At every year during the past 30 years, the immediately preceding warming trend was always significant when 17 years (or more) were included in the calculation, alleged "hiatus" periods notwithstanding. If current definitions of the "pause" used in the literature are applied to the historical record, then the climate system "paused" for more than 1/3 of the period during which temperatures rose 0.6 K.

Identification of potential impacts of climate change and anthropogenic activities on streamflow alterations in the Tarim River Basin, China.

PubMed

Xue, Lianqing; Yang, Fan; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Chi, Yixia; Yang, Guang

2017-08-15

Understanding contributions of climate change and human activities to changes in streamflow is important for sustainable management of water resources in an arid area. This study presents quantitative analysis of climatic and anthropogenic factors to streamflow alteration in the Tarim River Basin (TRB) using the double mass curve method (DMC) and the Budyko methods. The time series (1960~2015) are divided into three periods: the prior impacted period (1960~1972) and the two post impacted periods, 1973~1986 and 1987~2015 with trend analysis. Our results suggest that human activities played a dominant role in deduction in the streamflow in TRB with contribution of 144.6% to 120.68% during the post impacted period I and 228.68% to 140.38% during the post impacted period II. Climatic variables accounted for 20.68%~44.6% of the decrease during the post impacted period I and 40.38% ~128.68% during the post impacted period II. Sensitivity analysis indicates that the streamflow alteration was most sensitive to changes in landscape parameters. The aridity index and all the elasticities showed an obvious increasing trend from the upstream to the downstream in the TRB. Our study suggests that it is important to take effective measures for sustainable development of eco-hydrological and socio-economic systems in the TRB.

Population trends influence species ability to track climate change

Treesearch

Joel Ralston; William V. DeLuca; Richard E. Feldman; David I. King

2016-01-01

Shifts of distributions have been attributed to species tracking their fundamental climate niches through space. However, several studies have now demonstrated that niche tracking is imperfect, that species' climate niches may vary with population trends, and that geographic distributions may lag behind rapid climate change. These reports of imperfect niche...

Trend analysis of the aerosol optical depth from fusion of MISR and MODIS retrievals over China

NASA Astrophysics Data System (ADS)

Guo, Jing; Gu, Xingfa; Yu, Tao; Cheng, Tianhai; Chen, Hao

2014-03-01

Atmospheric aerosol plays an important role in the climate change though direct and indirect processes. In order to evaluate the effects of aerosols on climate, it is necessary to have a research on their spatial and temporal distributions. Satellite aerosol remote sensing is a developing technology that may provide good temporal sampling and superior spatial coverage to study aerosols. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) have provided aerosol observations since 2000, with large coverage and high accuracy. However, due to the complex surface, cloud contamination, and aerosol models used in the retrieving process, the uncertainties still exist in current satellite aerosol products. There are several observed differences in comparing the MISR and MODIS AOD data with the AERONET AOD. Combing multiple sensors could reduce uncertainties and improve observational accuracy. The validation results reveal that a better agreement between fusion AOD and AERONET AOD. The results confirm that the fusion AOD values are more accurate than single sensor. We have researched the trend analysis of the aerosol properties over China based on nine-year (2002-2010) fusion data. Compared with trend analysis in Jingjintang and Yangtze River Delta, the accuracy has increased by 5% and 3%, respectively. It is obvious that the increasing trend of the AOD occurred in Yangtze River Delta, where human activities may be the main source of the increasing AOD.

Frequency Analysis of Extreme Sub-Daily Precipitation under Stationary and Non-Stationary Conditions across Two Contrasting Hydroclimatic Environments

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Goodrich, D. C.; Keefer, T.

2017-12-01

Observed sub-daily precipitation intensities from contrasting hydroclimatic environments in the USA are used to evaluate temporal trends and to develop Intensity-Duration Frequency (IDF) curves under stationary and nonstationary climatic conditions. Analyses are based on observations from two United States Department of Agriculture (USDA)-Agricultural Research Service (ARS) experimental watersheds located in a semi-arid and a temperate environment. We use an Annual Maximum Series (AMS) and a Partial Duration Series (PDS) approach to identify temporal trends in maximum intensities for durations ranging from 5- to 1440-minutes. A Bayesian approach with Monte Carlo techniques is used to incorporate the effect of non-stationary climatic assumptions in the IDF curves. The results show increasing trends in observed AMS sub-daily intensities in both watersheds whereas trends in the PDS observations are mostly positive in the semi-arid site and a mix of positive and negative in the temperate site. Stationary climate assumptions lead to much lower estimated sub-daily intensities than those under non-stationary assumptions with larger absolute differences found for shorter durations and smaller return periods. The risk of failure (R) of a hydraulic structure is increased for non-stationary effects over those of stationary effects, with absolute differences of 25% for a 100-year return period (T) and a project life (n) of 100 years. The study highlights the importance of considering non-stationarity, due to natural variability or to climate change, in storm design.

Determining Water Quality Trends in the Sacramento-San Joaquin Delta Watershed in the Face of Climate Change

NASA Astrophysics Data System (ADS)

Kynett, K.; Azimi-Gaylon, S.; Doidic, C.

2014-12-01

The Sacramento-San Joaquin Delta and Suisun Marsh (Delta) is the largest estuary on the West Coast of the Americas and is a resource of local, State, and national significance. The Delta is simultaneously the most critical component of California's water supply, a primary focus of the state's ecological conservation measures, and a vital resource deeply imperiled by degraded water quality. Delta waterbodies are identified as impaired by salinity, excess nutrients, low dissolved oxygen, pathogens, pesticides, heavy metals, and other contaminants. Climate change is expected to exacerbate the impacts of existing stressors in the Delta and magnify the challenges of managing this natural resource. A clear understanding of the current state of the watershed is needed to better inform scientists, decision makers, and the public about potential impacts from climate change. The Delta Watershed Initiative Network (Delta WIN) leverages the ecological benefits of healthy watersheds, and enhances, expands and creates opportunities for greater watershed health by coordinating with agencies, established programs, and local organizations. At this critical junction, Delta WIN is coordinating data integration and analysis to develop better understanding of the existing and emerging water quality concerns. As first steps, Delta WIN is integrating existing water quality data, analyzing trends, and monitoring to fill data gaps and to evaluate indicators of climate change impacts. Available data will be used for trend analysis; Delta WIN will continue to monitor where data is incomplete and new questions arise. Understanding how climate change conditions may affect water quality will be used to inform efforts to build resilience and maintain water quality levels which sustain aquatic life and human needs. Assessments of historical and new data will aid in recognition of potential climate change impacts and in initiating implementation of best management practices in collaboration with State and local agencies. Ultimately, Delta WIN can inform responsive science and adaptive management in other estuaries and critical natural resource areas facing times of change.

The measurement of climate change using data from the Advanced Very High Resolution and Along Track Scanning Radiometers

NASA Astrophysics Data System (ADS)

Lawrence, S. P.; Llewellyn-Jones, D. T.; Smith, S. J.

2004-08-01

Global sea-surface temperature is an important indicator of climate change, with the ability to reflect warming/cooling climate trends. The detection of such trends requires rigorous measurements that are global, accurate, and consistent. Space instruments can provide the means to achieve these required attributes in sea-surface temperature data. Analyses of two independent data sets from the Advanced Very High Resolution and Along Track Scanning Radiometers series of space sensors during the period 1985 to 2000 reveal trends of increasing global temperature with magnitudes of 0.09°C and 0.13°C per decade, respectively, closely matching that expected due to current levels of greenhouse gas exchange. In addition, an analysis based upon singular value decomposition, allowing the removal of El Niño in order to examine areas of change other than the tropical Pacific region, indicates that the 1997 El Niño event affected sea-surface temperature globally. The methodology demonstrated here can be applied to other data sets, which cover long time series observations of geophysical observations in order to characterize long-term change. The conclusion is that satellite sea-surface temperature provides an important means to quantify and explore the processes of climate change.

Climate science: Breaks in trends

NASA Astrophysics Data System (ADS)

Pretis, Felix; Allen, Myles

2013-12-01

Global temperature rise since industrialization has not been uniform. A statistical analysis suggests that past changes in the rate of warming can be directly attributed to human influences, from economic downturns to the regulations of the Montreal Protocol.

Surface-Atmosphere Moisture Interactions in the Frozen Ground Regions of Eurasia.

PubMed

Ford, Trent W; Frauenfeld, Oliver W

2016-01-18

Climate models simulate an intensifying Arctic hydrologic cycle in response to climatic warming, however the role of surface-atmosphere interactions from degrading frozen ground is unclear in these projections. Using Modern-Era Retrospective Analysis for Research and Applications (MERRA) data in high-latitude Eurasia, we examine long-term variability in surface-atmosphere coupling as represented by the statistical relationship between surface evaporative fraction (EF) and afternoon precipitation. Changes in EF, precipitation, and their statistical association are then related to underlying permafrost type and snow cover. Results indicate significant positive trends in July EF in the Central Siberian Plateau, corresponding to significant increases in afternoon precipitation. The positive trends are only significant over continuous permafrost, with non-significant or negative EF and precipitation trends over isolated, sporadic, and discontinuous permafrost areas. Concurrently, increasing EF and subsequent precipitation are found to coincide with significant trends in May and June snowmelt, which potentially provides the moisture source for the observed enhanced latent heating and moisture recycling in the region. As climate change causes continuous permafrost to transition to discontinuous, discontinuous to sporadic, sporadic to isolated, and isolated permafrost disappears, this will also alter patterns of atmospheric convection, moisture recycling, and hence the hydrologic cycle in high-latitude land areas.

A perspective on nonstationarity and water management

USGS Publications Warehouse

Hirsch, R.M.

2011-01-01

This essay offers some perspectives on climate-related nonstationarity and water resources. Hydrologists must not lose sight of the many sources of nonstationarity, recognizing that many of them may be of much greater magnitude than those that may arise from climate change. It is paradoxical that statistical and deterministic approaches give us better insights about changes in mean conditions than about the tails of probability distributions, and yet the tails are very important to water management. Another paradox is that it is difficult to distinguish between long-term hydrologic persistence and trend. Using very long hydrologic records is helpful in mitigating this problem, but does not guarantee success. Empirical approaches, using long-term hydrologic records, should be an important part of the portfolio of research being applied to understand the hydrologic response to climate change. An example presented here shows very mixed results for trends in the size of the annual floods, with some strong clusters of positive trends and a strong cluster of negative trends. The potential for nonstationarity highlights the importance of the continuity of hydrologic records, the need for repeated analysis of the data as the time series grow, and the need for a well-trained cadre of scientists and engineers, ready to interpret the data and use those analyses to help adjust the management of our water resources.

Climatic change controls productivity variation in global grasslands

PubMed Central

Gao, Qingzhu; Zhu, Wenquan; Schwartz, Mark W.; Ganjurjav, Hasbagan; Wan, Yunfan; Qin, Xiaobo; Ma, Xin; Williamson, Matthew A.; Li, Yue

2016-01-01

Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate-induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2–71.2% during 1982–2011. Climate change contributed significantly to long-term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long-term controlled experiments and multi-model ensembles to reduce uncertainties and explain mechanisms. PMID:27243565

Spatiotemporal trends in mean temperatures and aridity index over Rwanda

NASA Astrophysics Data System (ADS)

Muhire, I.; Ahmed, F.

2016-01-01

This study aims at quantifying the trends in mean temperatures and aridity index over Rwanda for the period of 1961-1992, based on analysis of climatic data (temperatures, precipitations, and potential evapotranspiration). The analysis of magnitude and significance of trends in temperatures and aridity index show the degree of climate change and mark the level of vulnerability to extreme events (e.g., droughts) in different areas of the country. The study reveals that mean temperatures increased in most parts of the country, with a significant increase observed in the eastern lowlands and in the southwestern parts. The highlands located in the northwest and the Congo-Nile crest showed a nonsignificant increase in mean temperatures. Aridity index increased only in March, April, October, and November, corresponding with the rainy seasons. The remaining months of the year showed a decreasing trend. At an annual resolution, the highlands and the western region showed a rise in aridity index with a decreasing pattern over the eastern lowlands and the central plateau. Generally, the highlands presented a nonsignificant increase in mean temperatures and aridity index especially during the rainy seasons. The eastern lowlands showed a significant increase in mean temperatures and decreasing trends in aridity index. Therefore, these areas are bound to experience more droughts, leading to reduced water and consequent decline in agricultural production. On the other hand, the north highlands and southwest region will continue to be more productive.

Long-term analysis and appropriate metrics of climate change in Mongolia

NASA Astrophysics Data System (ADS)

Jamiyansharav, Khishigbayar

This study addresses three important issues related to long-term climate change study in Mongolia. Mongolia is one of the biggest land-locked countries in Asia and 75--80 percent of the land is rangeland, which is highly vulnerable to climate change. Climate will affect many sectors critical to the country's economic, social, and ecological welfare. Therefore, it is regionally and globally important to evaluate climate change in Mongolia. Chapter 1 discusses the qualitative and descriptive study on exposure characteristics of the 17 Mongolian meteorological stations, which are part of the Global Climate Observing Network (GCON). The global average temperature anomalies are based in part on the GCON stations' meteorological data. To document the possible exposures surrounding the weather stations, the Mongolian meteorological stations were surveyed during July--August 2005. From the total 17 stations, 47 percent were determined strongly influenced by urban character landscape, 41 percent received some anthropogenic influences, and 12 percent had very little to no anthropogenic influences. Even though the Mongolian meteorological stations' exposure characteristics are better than the European and North American stations' the strict adherence in following WMO guidelines is important and urgently needed. Chapter 2 evaluates the long-term (1961--2005) trends in seasonal and annual surface mean, maximum, minimum temperatures and precipitation. Furthermore, this study compares the long-term mean temperature trends with decadal (1998--2007) trends. This chapter also discusses the extreme climate indices on spatial and temporal scales. According to the results, the long-term linear temperature trends show a clear increasing trend whereas the decadal trends show the decreasing trend mostly in winter and spring. The analysis of extreme indices (1961--2001) indicate that most of the stations frost and icing days are decreased and summer days, tropical nights, monthly maximum value of daily minimum, maximum temperatures and growing season length are increased. Precipitation indices varied substantially and there were no unified temporal and spatial pattern. In addition to that, I am suggesting effective temperature as an appropriate metric to evaluate surface heat change because it counts not only air temperature but also surface humidity. Chapter 3 discusses a case study of grazing intensity on surface energy budgets. To evaluate the land atmospheric interactions over the grassland area depending on the different grazing intensity I conducted the case study over the Shortgrass Steppe Long-Term Ecological Research site on Northern Great Plains of US to imply the findings in semiarid shortgrass steppe of Mongolia. The study site has much of similarities with Mongolian shortgrass steppe and has more frequent, high quality data. This study evaluates the impact of grazing on microclimate and energy budgets in a dry (163 mm) and two near-normal (262 and 260 mm) precipitation years based on continuously measured 20 minute interval data. This study helps to describe surface energy partitioning in semi-arid grasslands that has long history of grazing. The main finding of the study is grazing has a potential impact on the energy partitioning under conditions of higher water availability, but not during dry conditions.

Assessment of short- and long-term memory in trends of major climatic variables over Iran: 1966-2015

NASA Astrophysics Data System (ADS)

Mianabadi, Ameneh; Shirazi, Pooya; Ghahraman, Bijan; Coenders-Gerrits, A. M. J.; Alizadeh, Amin; Davary, Kamran

2018-02-01

In arid and semi-arid regions, water scarcity is the crucial issue for crop production. Identifying the spatial and temporal trends in aridity, especially during the crop-growing season, is important for farmers to manage their agricultural practices. This will become especially relevant when considering climate change projections. To reliably determine the actual trends, the influence of short- and long-term memory should be removed from the trend analysis. The objective of this study is to investigate the effect of short- and long-term memory on estimates of trends in two aridity indicators—the inverted De Martonne (ϕ IDM ) and Budyko (ϕ B ) indices. The analysis is done using precipitation and temperature data over Iran for a 50-year period (1966-2015) at three temporal scales: annual, wheat-growing season (October-June), and maize-growing season (May-November). For this purpose, the original and the modified Mann-Kendall tests (i.e., modified by three methods of trend free pre-whitening (TFPT), effective sample size (ESS), and long-term persistence (LTP)) are used to investigate the temporal trends in aridity indices, precipitation, and temperature by taking into account the effect of short- and long-term memory. Precipitation and temperature data were provided by the Islamic Republic of Iran Meteorological Organization (IRIMO). The temporal trend analysis showed that aridity increased from 1966 to 2015 at the annual and wheat-growing season scales, which is due to a decreasing trend in precipitation and an increasing trend in mean temperature at these two timescales. The trend in aridity indices was decreasing in the maize-growing season, since precipitation has an increasing trend for most parts of Iran in that season. The increasing trend in aridity indices is significant in Western Iran, which can be related to the significantly more negative trend in precipitation in the West. This increasing trend in aridity could result in an increasing crop water requirement and a significant reduction in the crop production and water use efficiency. Furthermore, the modified Mann-Kendall tests indicated that unlike temperature series, precipitation, ϕ IDM , and ϕ B series are not affected by short- and long-term memory. Our results can help decision makers and water resource managers to adopt appropriate policy strategies for sustainable development in the field of irrigated agriculture and water resources management.

Northern Hemisphere climate trends in reanalysis and forecast model predictions: The 500 hPa annual means

NASA Astrophysics Data System (ADS)

Bordi, I.; Fraedrich, K.; Sutera, A.

2010-06-01

The lead time dependent climates of the ECMWF weather prediction model, initialized with ERA-40 reanalysis, are analysed using 44 years of day-1 to day-10 forecasts of the northern hemispheric 500-hPa geopotential height fields. The study addresses the question whether short-term tendencies have an impact on long-term trends. Comparing climate trends of ERA-40 with those of the forecasts, it seems that the forecast model rapidly loses the memory of initial conditions creating its own climate. All forecast trends show a high degree of consistency. Comparison results suggest that: (i) Only centers characterized by an upward trend are statistical significant when increasing the lead time. (ii) In midilatitudes an upward trend larger than the one observed in the reanalysis characterizes the forecasts, while in the tropics there is a good agreement. (iii) The downward trend in reanalysis at high latitudes characterizes also the day-1 forecast which, however, increasing lead time approaches zero.

Comparison of climate related changes in two Arctic fjords, Hornsund and Porsanger

NASA Astrophysics Data System (ADS)

Aniskiewicz, Paulina; Stramska, Małgorzata

2017-04-01

In the Arctic zone the climate change is amplified in comparison to globally averaged trends, and the observed trends are variable spatially. Our research is focused on two Artic fjords: Porsanger and Horsund. Porsanger fjord is located in the coastal waters of the Barents Sea. Hornsund is one of fjords located in the western part of Svalbard archipelago. In this presentation we have used data provided by the Norwegian Meteorological Institute for three meteorological stations. Two of them are located in the Porsanger fjord (Lakselv - in the inner part, Honningsvåg - in the outer zone). The third station provides data from the Hornsund fjord. Using these data we have estimated the 33-year trends (1983-2015) of air temperature and relative humidity in each station using linear regression analysis (statistically significant at 95In the inner part of the Porsanger fjord (Lakselv) the multiyear trend of increasing annual mean air temperature has been estimated at 0.006°C per year. The monthly trends were statistically significant in May, September and November. The strongest seasonal warming has been observed in spring and autumn. The trends of increasing annual mean humidity was about 0.2In Hornsund the air temperature trend (0.2°C per year) is significantly larger than in Porsanger. The trends of air temperature were statistically significant for eight months (except March, April, June and July) and three seasons (besides spring). The trends of relative humidity were not statistically significant. Thanks to this research we can discuss how atmospheric conditions and climate related trends change in time and seasons of the year in two different Arctic regions. The project has been financed from the funds of the Leading National Research Centre (KNOW) received by the Centre for Polar Studies for the period 2014-2018. This work was also funded by the Norway Grants (NCBR contract No. 201985, project NORDFLUX). Partial support comes from the Institute of Oceanology (IO PAN).

Impacts of global change on the concentrations and dilution of combined sewer overflows in a drinking water source.

PubMed

Jalliffier-Verne, Isabelle; Leconte, Robert; Huaringa-Alvarez, Uriel; Madoux-Humery, Anne-Sophie; Galarneau, Martine; Servais, Pierre; Prévost, Michèle; Dorner, Sarah

2015-03-01

This study presents an analysis of climate change impacts on a large river located in Québec (Canada) used as a drinking water source. Combined sewer overflow (CSO) effluents are the primary source of fecal contamination of the river. An analysis of river flowrates was conducted using historical data and predicted flows from a future climate scenario. A spatio-temporal analysis of water quality trends with regard to fecal contamination was performed and the effects of changing flowrates on the dilution of fecal contaminants were analyzed. Along the river, there was a significant spatial trend for increasing fecal pollution downstream of CSO outfalls. Escherichia coli concentrations (upper 95th percentile) increased linearly from 2002 to 2012 at one drinking water treatment plant intake. Two critical periods in the current climate were identified for the drinking water intakes considering both potential contaminant loads and flowrates: local spring snowmelt that precedes river peak flow and extra-tropical storm events that occur during low flows. Regionally, climate change is expected to increase the intensity of the impacts of hydrological conditions on water quality in the studied basin. Based on climate projections, it is expected that spring snowmelt will occur earlier and extreme spring flowrates will increase and low flows will generally decrease. High and low flows are major factors related to the potential degradation of water quality of the river. However, the observed degradation of water quality over the past 10 years suggests that urban development and population growth may have played a greater role than climate. However, climate change impacts will likely be observed over a longer period. Source water protection plans should consider climate change impacts on the dilution of contaminants in addition to local land uses changes in order to maintain or improve water quality. Copyright © 2014 Elsevier B.V. All rights reserved.

Aerosol optical depth trend over the Middle East

NASA Astrophysics Data System (ADS)

Klingmueller, Klaus; Pozzer, Andrea; Metzger, Swen; Abdelkader, Mohamed; Stenchikov, Georgiy; Lelieveld, Jos

2016-04-01

We use the combined Dark Target/Deep Blue aerosol optical depth (AOD) satellite product of the Moderate-resolution Imaging Spectroradiometer (MODIS) collection 6 to study trends over the Middle East between 2000 and 2015. Our analysis corroborates a previously identified positive AOD trend over large parts of the Middle East during the period 2001 to 2012. By relating the annual AOD to precipitation, soil moisture and surface wind, being the main factors controlling the dust cycle, we identify regions where these attributes are significantly correlated to the AOD over Saudi Arabia, Iraq and Iran. The Fertile Crescent turns out to be of prime importance for the AOD trend over these countries. Using multiple linear regression we show that AOD trend and interannual variability can be attributed to the above mentioned dust cycle parameters, confirming that the AOD increase is predominantly driven by dust. In particular, the positive AOD trend relates to a negative soil moisture trend. This suggests that increasing temperature and decreasing relative humidity in the last decade have promoted soil drying, leading to increased dust emissions and AOD; consequently an AOD increase is expected due to climate change. Based on simulations using the ECHAM/MESSy atmospheric chemistry-climate model (EMAC), we interpret the correlations identified in the observational data in terms of causal relationships.

Is climate change intensifying the drying-trend in the Caribbean?

NASA Astrophysics Data System (ADS)

Herrera, D. A.; Ault, T.; Fasullo, J.; Carrillo, C. M.

2017-12-01

Since 1950, the Caribbean (11ºN-25ºN; 85ºW-60ºW) has seen a significant drying trend characterized by several recent droughts, some of them contemporaneous with El Niño events. Moreover, the most recent drought from 2013 to 2016 was both the most severe and widespread event since at least 1950, and was associated with high temperatures, likely driven in part by climate change. This work examines the role of increased evaporative demand resulting from warmer temperatures on the drying trend observed in the Caribbean since 1950, using observations and model simulations. Large-scale dynamics associated with drought are also analyzed using sea surface temperature, geopotential height, wind, and precipitation anomalies, as well as radiative fluxes anomalies. Furthermore, land surface model soil moisture and high-resolution self-calibrated Palmer Drought Severity Index (scPDSI) datasets are used to quantify drought severity at local scales. The anthropogenic contribution to drought severity is estimated as the difference between the scPDSI calculated using linearly-detrended temperatures, and the scPDSI computed with the observed trend, with unadjusted precipitation, net radiation, and wind speed. Soil moisture anomalies driven by climate change are derived by comparing a large ensemble of forced simulations against a pre-industrial control. The resulting analysis indicates that anthropogenic forcing has intensified the drying trend in the Caribbean by -0.4 scPDSI-units over 60 years, and has increased the dry-land area by 10%. These findings are consistent with observed potential evapotranspiration (PET) anomalies, which are 30% higher than PET-anomalies estimated using detrended temperatures. These results suggest that climate change is already increasing the risk of drought in the Caribbean by enhancing the atmospheric demand of moisture through temperature, and provide insights into the role of climate change in future drought risk in the region.

Spatial patterns and recent trends in the climate of tropical rainforest regions.

PubMed

Malhi, Yadvinder; Wright, James

2004-03-29

We present an analysis of the mean climate and climatic trends of tropical rainforest regions over the period 1960-1998, with the aid of explicit maps of forest cover and climatological databases. Until the mid-1970s most regions showed little trend in temperature, and the western Amazon experienced a net cooling probably associated with an interdecadal oscillation. Since the mid-1970s, all tropical rainforest regions have experienced a strong warming at a mean rate of 0.26 +/- 0.05 degrees C per decade, in synchrony with a global rise in temperature that has been attributed to the anthropogenic greenhouse effect. Over the study period, precipitation appears to have declined in tropical rainforest regions at a rate of 1.0 +/- 0.8% per decade (p < 5%), declining sharply in northern tropical Africa (at 3-4% per decade), declining marginally in tropical Asia and showing no significant trend in Amazonia. There is no evidence so far of a decline in precipitation in eastern Amazonia, a region thought vulnerable to climate-change-induced drying. The strong drying trend in Africa suggests that this should be a priority study region for understanding the impact of drought on tropical rainforests. We develop and use a dry-season index to study variations in the length and intensity of the dry season. Only African and Indian tropical rainforests appear to have seen a significant increase in dry-season intensity. In terms of interannual variability, the El Niño-Southern Oscillation (ENSO) is the primary driver of temperature variations across the tropics and of precipitation fluctuations for large areas of the Americas and southeast Asia. The relation between ENSO and tropical African precipitation appears less direct.

Climate change and human health: Spatial modeling of water availability, malnutrition, and livelihoods in Mali, Africa

USGS Publications Warehouse

Jankowska, Marta M.; Lopez-Carr, David; Funk, Chris; Husak, Gregory J.; Chafe, Z.A.

2012-01-01

This study develops a novel approach for projecting climate trends in the Sahel in relation to shifting livelihood zones and health outcomes. Focusing on Mali, we explore baseline relationships between temperature, precipitation, livelihood, and malnutrition in 407 Demographic and Health Survey (DHS) clusters with a total of 14,238 children, resulting in a thorough spatial analysis of coupled climate-health dynamics. Results suggest links between livelihoods and each measure of malnutrition, as well as a link between climate and stunting. A ‘front-line’ of vulnerability, related to the transition between agricultural and pastoral livelihoods, is identified as an area where mitigation efforts might be usefully targeted. Additionally, climate is projected to 2025 for the Sahel, and demographic trends are introduced to explore how the intersection of climate and demographics may shift the vulnerability ‘front-line’, potentially exposing an additional 6 million people in Mali, up to a million of them children, to heightened risk of malnutrition from climate and livelihood changes. Results indicate that, holding constant morbidity levels, approximately one quarter of a million children will suffer stunting, nearly two hundred thousand will be malnourished, and over one hundred thousand will become anemic in this expanding arid zone by 2025. Climate and health research conducted at finer spatial scales and within shorter projected time lines can identify vulnerability hot spots that are of the highest priority for adaptation interventions; such an analysis can also identify areas with similar characteristics that may be at heightened risk. Such meso-scale coupled human-environment research may facilitate appropriate policy interventions strategically located beyond today’s vulnerability front-line.

Seasonal and interannual variations of atmospheric CO2 and climate

USGS Publications Warehouse

Dettinger, M.D.; Ghil, M.

1998-01-01

Interannual variations of atmospheric CO2 concentrations at Mauna Loa are almost masked by the seasonal cycle and a strong trend; at the South Pole, the seasonal cycle is small and is almost lost in the trend and interannual variations. Singular-spectrum analysis (SSA) issued here to isolate and reconstruct interannual signals at both sites and to visualize recent decadal changes in the amplitude and phase of the seasonal cycle. Analysis of the Mauna Loa CO2 series illustrates a hastening of the CO2 seasonal cycle, a close temporal relation between Northern Hemisphere (NH) mean temperature trends and the amplitude of the seasonal CO2 cycle, and tentative ties between the latter and seasonality changes in temperature over the NH continents. Variations of the seasonal CO2 cycle at the South Pole differ from those at Mauna Loa: it is phase changes of the seasonal cycle at the South Pole, rather than amplitude changes, that parallel hemispheric and global temperature trends. The seasonal CO2 cycles exhibit earlier occurrences of the seasons by 7 days at Mauna Loa and 18 days at the South Pole. Interannual CO2 variations are shared at the two locations, appear to respond to tropical processes, and can be decomposed mostly into two periodicities, around (3 years)-1 and (4 years)-1, respectively. Joint SSA analyses of CO2 concentrations and tropical climate indices isolate a shared mode with a quasi-triennial (QT) period in which the CO2 and sea-surface temperature (SST) participation are in phase opposition. The other shared mode has a quasi-quadrennial (QQ) period and CO2 variations are in phase with the corresponding tropical SST variations throughout the tropics. Together these interannual modes exhibit a mean lag between tropical SSTs and CO2 variations of about 6-8 months, with SST leading. Analysis of the QT and QQ signals in global gridded SSTs, joint SSA of CO2 and ??13C isotopic ratios, and SSA of CO2 and NH-land temperatures indicate that the QT variations in CO2 mostly reflect upwelling variations in the eastern tropical Pacific. QQ variations are dominated by the CO2 signature of terrestrial-ecosystem response to global QQ climate variations. Climate variations associated with these two interannual components of tropical variability have very different effects on global climate and, especially, on terrestrial ecosystems and the carbon cycle.

Individual contributions of climate and vegetation change to soil moisture trends across multiple spatial scales.

PubMed

Feng, Huihui

2016-09-07

Climate and vegetation change are two dominating factors for soil moisture trend. However, their individual contributions remain unknown due to their complex interaction. Here, I separated their contributions through a trajectory-based method across the global, regional and local scales. Our results demonstrated that climate change accounted for 98.78% and 114.64% of the global drying and wetting trend. Vegetation change exhibited a relatively weak influence (contributing 1.22% and -14.64% of the global drying and wetting) because it occurred in a limited area on land. Regionally, the impact of vegetation change cannot be neglected, which contributed -40.21% of the soil moisture change in the wetting zone. Locally, the contributions strongly correlated to the local environmental characteristics. Vegetation negatively affected soil moisture trends in the dry and sparsely vegetated regions and positively in the wet and densely vegetated regions. I conclude that individual contributions of climate and vegetation change vary at the global, regional and local scales. Climate change dominates the soil moisture trends, while vegetation change acts as a regulator to drying or wetting the soil under the changing climate.

Recent decadal trends in Iberian water vapour: GPS analysis and WRF process study

NASA Astrophysics Data System (ADS)

Miranda, Pedro M. A.; Nogueira, Miguel; Semedo, Alvaro; Benevides, Pedro; Catalao, Joao; Costa, Vera

2016-04-01

A 24-year simulation of the recent Iberian climate, using the WRF model at 9km resolution forced by ERA-Interim reanalysis (1989-2012), is analysed for the decadal evolution of the upwelling forcing coastal wind and for column integrated Precipitable water vapour (PWV). Results indicate that, unlike what was found by Bakun et al. (2009) for the Peruvian region, a statistically significant trend in the upwelling favourable (northerly) wind has been accompanied by a corresponding decrease in PWV, not only inland but also over the coastal waters. Such increase is consistent with a reinforced northerly coastal jet in the maritime boundary layer contributing to atmospheric Ekman pumping of dry continental air into the coastal region. Diagnostics of the prevalence of the Iberian thermal low following Hoinka and Castro (2003) also show a positive trend in its frequency during an extended summer period (April to September). These results are consistent with recent studies indicating an upward trend in the frequency of upwelling in SW Iberia (Alves and Miranda 2013), and may be relevant for climate change applications as an increase in coastal upwelling (Miranda et al 2013) may lead to substantial regional impacts in the subtropics. The same analysis with ERA-Interim reanalysis data, which was used to force the WRF simulations, does not reveal the same signal in PWV, and indeed correlates poorly with the GPS observations, indicating that the data assimilation process makes the water vapour data in reanalysis unusable for climate change purposes. The good correlation between the WRF simulated data and GPS observations allow for a detailed analysis of the processes involved in the evolution of the PWV field. Akcnowledgements: Study done within FCT Grant RECI/GEO-MET/0380/2012, financially supported by FCT Grant UID/ GEO/50019/2013-IDL Alves JMR, Miranda PMA (2013) Variability of Iberian upwelling implied by ERA-40 and ERA-Interim reanalyses, Tellus A 2013, http://dx.doi.org/10.3402/tellusa.v65i0.19245. Bakun et al (2010) Greenhouse gas, upwelling-favorable winds, and the future of coastal ocean upwelling ecosystems, Global Change Biology, doi: 10.1111/j.1365-2486.2009.02094.x Hoinka KP, Castro M (2003) The Iberian Peninsula thermal low. QJRMS, 129, 1491- 1511, doi: 10.1256/qj.01.189. Miranda et al (2013) Climate change and upwelling: response of Iberian upwelling to atmospheric forcing in a regional climate scenario. Climate Dynamics, doi: 10.1007/s00382-012-1442-9.

A hydrologic and archeologic study of climate change in Al Ain, United Arab Emirates

NASA Astrophysics Data System (ADS)

Jorgensen, Donald G.; Yasin al-Tikiriti, Walid

2003-01-01

Aridity trends established for Al Ain, United Arab Emirates, for the past 4500 years correlate with the trends of increased well depths and declining groundwater levels. Depth of wells found at archeologic sites at Hili near Al Ain were correlated to groundwater levels. Trends of declining groundwater levels were related to trends of increasing aridity (climate change). The increasing aridity had a pronounced affect on man's development in Al Ain area as well. For example, nonirrigation farming could not be successfully sustained at the end of the Bronze Age. This thwarted the economic development until the falaj (a water conveyance structure) was introduced in the Iron Age. The aridity trends in Al Ain correspond to contemporaneous aridity trends noted in Mesopotamia and the Dead Sea area, as well as the Middle East, Mediterranean, and northern Africa, in general. Other global climatic changes that are contemporaneous with climate change at Al Ain have been noted. The increased aridity (desertification) trends at Al Ain are contemporaneous with increased atmospheric CO 2 trends as reported by Indermuhle et al. [Nature (398) 121].

Isolating the Effects of the Warming Trend from the General Climate Change in Water Resources: California Case

NASA Astrophysics Data System (ADS)

Wang, J.; Yin, H.; Chung, F.

2008-12-01

While the population growth, the future land use change, and the desire for better environmental preservation and protection are adding up pressure on water resources management in California, California is facing an extra challenge of addressing potential climate change impacts on water supple and demand in California. The concerns on water facilities planning and flood control caused by climate change include modified precipitation patterns, changes in snow levels and runoff patterns due to increased air temperatures. Although long-term climate projections are largely uncertain, there appears to be a strong consistency in predicting the warming trend of future surface temperature, and the resulting shift in the seasonal patterns of runoff. However, projected changes in precipitation (wetting or drying), which control annual runoff, are far less certain. This paper attempts to separate the effects of warming trend from the effects of precipitation trend on water planning especially in California where reservoir operations are more sensitive to seasonal patterns of runoff than to the total annual runoff. The water resources systems planning model, CALSIM2, is used to evaluate climate change impact on water resource management in California. Rather than directly ingesting estimated streamflows from climate model projections into CALSIM2, a three step perturbation ratio method is proposed to introduce climate change impact into the planning model. Firstly, monthly perturbation ratio of projected monthly inflow to simulated historical monthly inflow is applied to observed historical monthly inflow to generate climate change inflows to major dams and reservoirs. To isolate the effects of warming trend on water resources, a further annual inflow adjustment is applied to the inflows generated in step one to preserve the volume of the observed annual inflow. To re-introduce the effects of precipitation trend on water resources, an additional inflow trend adjustment is applied to the adjusted climate change inflow. Therefore, three CALSIM2 experiments will be implemented: (1) base run with the observed historic inflow (1921 to 2003); (2) sensitivity run with the adjusted climate change inflow through annual inflow adjustment; (3) sensitivity run with the adjusted climate change inflow through annual inflow adjustment and inflow trend adjustment. To account for the variability of various climate models in projecting future climates, the uncertainty in future emission scenarios, and the difference in different projection periods, estimated inflows from 6 climate models for 2 emission scenarios (A2 and B1) and two projection periods (2030-2059 and 2070-2099) are included in the CALSIM model experiments.

Effects of human activities and climate change on the reduction of visibility in Beijing over the past 36 years.

PubMed

Chen, Xuwu; Li, Xiaodong; Yuan, Xingzhong; Zeng, Guangming; Liang, Jie; Li, Xin; Xu, Wanjun; Luo, Yuan; Chen, Gaojie

2018-07-01

Both climate change and intensive human activities are thought to have contributed to the impairment of atmospheric visibility in Beijing. But the detailed processes involved and relative roles of human activities and climate change have not been quantified. Optical extinction of aerosols, the inverse of meteorological visibility is especially sensitive to fine particles <1.0 μm. These submicron particles are considered more hazardous than larger ones in terms of cardiovascular and respiratory diseases. Here we used the aerosol optical extinction (inverse of visibility) as the indicator of submicron particles pollution to estimate its inter-annual variability from 1980 to 2015. Our results indicated that optical extinction experienced two different periods: a weakly increasing stage (1980-2005) and a rapidly increasing stage (2005-2015). We attributed the variations of optical extinction to the joint effects of human activities and climate change. Over the past 36 years, human activities played a leading role in the increase of optical extinction, with a positive contribution of 0.077 km -1 /10 y. While under the effects of climate change, optical extinction firstly decreased by 0.035 km -1 /10 y until 2005 and then increased by 0.087 km -1 /10 y. Detailed analysis revealed that the abrupt change (around 2005) of optical extinction resulted from the trend reversals of climate change. We found since 2005 the decreasing trend by 0.58 m·s -1 /10 y in wind speed, the growing trend at 8.69%/10 y in relative humidity and the declining trend by 2.72 hPa/10 y in atmospheric pressure have caused the rapid increase of optical extinction. In brief, the higher load of fine particles <1.0 μm in Beijing in recent decades could be associated with both human activities and climate change. Particularly after 2005, the adverse climate change aggravated the situation of submicron particles pollution. Copyright © 2018 Elsevier Ltd. All rights reserved.

Globally Increased Crop Growth and Cropping Intensity from the Long-Term Satellite-Based Observations

NASA Astrophysics Data System (ADS)

Chen, Bin

2018-04-01

Understanding the spatiotemporal change trend of global crop growth and multiple cropping system under climate change scenarios is a critical requirement for supporting the food security issue that maintains the function of human society. Many studies have predicted the effects of climate changes on crop production using a combination of filed studies and models, but there has been limited evidence relating decadal-scale climate change to global crop growth and the spatiotemporal distribution of multiple cropping system. Using long-term satellite-derived Normalized Difference Vegetation Index (NDVI) and observed climate data from 1982 to 2012, we investigated the crop growth trend, spatiotemporal pattern trend of agricultural cropping intensity, and their potential correlations with respect to the climate change drivers at a global scale. Results show that 82.97 % of global cropland maximum NDVI witnesses an increased trend while 17.03 % of that shows a decreased trend over the past three decades. The spatial distribution of multiple cropping system is observed to expand from lower latitude to higher latitude, and the increased cropping intensity is also witnessed globally. In terms of regional major crop zones, results show that all nine selected zones have an obvious upward trend of crop maximum NDVI (p < 0.001), and as for climatic drivers, the gradual temperature and precipitation changes have had a measurable impact on the crop growth trend.

Trends in Global Vegetation Activity and Climatic Drivers Indicate a Decoupled Response to Climate Change.

PubMed

Schut, Antonius G T; Ivits, Eva; Conijn, Jacob G; Ten Brink, Ben; Fensholt, Rasmus

2015-01-01

Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP) and TBW per biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBW trends and monotonic negative or segmented and negative NDVI trends, was observed for 17-36% of all productive areas depending on the NDVI metric used. For only 1-2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity.

Spatial trends in Pearson Type III statistical parameters

USGS Publications Warehouse

Lichty, R.W.; Karlinger, M.R.

1995-01-01

Spatial trends in the statistical parameters (mean, standard deviation, and skewness coefficient) of a Pearson Type III distribution of the logarithms of annual flood peaks for small rural basins (less than 90 km2) are delineated using a climate factor CT, (T=2-, 25-, and 100-yr recurrence intervals), which quantifies the effects of long-term climatic data (rainfall and pan evaporation) on observed T-yr floods. Maps showing trends in average parameter values demonstrate the geographically varying influence of climate on the magnitude of Pearson Type III statistical parameters. The spatial trends in variability of the parameter values characterize the sensitivity of statistical parameters to the interaction of basin-runoff characteristics (hydrology) and climate. -from Authors

Mechanistic Lake Modeling to Understand and Predict Heterogeneous Responses to Climate Warming

NASA Astrophysics Data System (ADS)

Read, J. S.; Winslow, L. A.; Rose, K. C.; Hansen, G. J.

2016-12-01

Substantial warming has been documented for of hundreds globally distributed lakes, with likely impacts on ecosystem processes. Despite a clear pattern of widespread warming, thermal responses of individual lakes to climate change are often heterogeneous, with the warming rates of neighboring lakes varying across depths and among seasons. We aggregated temperature observations and parameterized mechanistic models for 9,000 lakes in the U.S. states of Minnesota, Wisconsin, and Michigan to examine broad-scale lake warming trends and among-lake diversity. Daily lake temperature profiles and ice-cover dynamics were simulated using the General Lake Model for the contemporary period (1979-2015) using drivers from the North American Land Data Assimilation System (NLDAS-2) and for contemporary and future periods (1980-2100) using downscaled data from six global circulation models driven by the Representative Climate Pathway 8.5 scenario. For the contemporary period, modeled vs observed summer mean surface temperatures had a root mean squared error of 0.98°C with modeled warming trends similar to observed trends. Future simulations under the extreme 8.5 scenario predicted a median lake summer surface warming rate of 0.57°C/decade until mid-century, with slower rates in the later half of the 21st century (0.35°C/decade). Modeling scenarios and analysis of field data suggest that the lake-specific properties of size, water clarity, and depth are strong controls on the sensitivity of lakes to climate change. For example, a simulated 1% annual decline in water clarity was sufficient to override the effects of climate warming on whole lake water temperatures in some - but not all - study lakes. Understanding heterogeneous lake responses to climate variability can help identify lake-specific features that influence resilience to climate change.

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

PubMed

Prabnakorn, Saowanit; Maskey, Shreedhar; Suryadi, F X; de Fraiture, Charlotte

2018-04-15

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. Copyright © 2017 Elsevier B.V. All rights reserved.

Attribution of recent ozone changes in the Southern Hemisphere mid-latitudes using statistical analysis and chemistry-climate model simulations

NASA Astrophysics Data System (ADS)

Zeng, Guang; Morgenstern, Olaf; Shiona, Hisako; Thomas, Alan J.; Querel, Richard R.; Nichol, Sylvia E.

2017-09-01

Ozone (O3) trends and variability from a 28-year (1987-2014) ozonesonde record at Lauder, New Zealand, have been analysed and interpreted using a statistical model and a global chemistry-climate model (CCM). Lauder is a clean rural measurement site often representative of the Southern Hemisphere (SH) mid-latitude background atmosphere. O3 trends over this period at this location are characterised by a significant positive trend below 6 km, a significant negative trend in the tropopause region and the lower stratosphere between 9 and 15 km, and no significant trend in the free troposphere (6-9 km) and the stratosphere above 15 km. We find that significant positive trends in lower tropospheric ozone are correlated with increasing temperature and decreasing relative humidity at the surface over this period, whereas significant negative trends in the upper troposphere and the lower stratosphere appear to be strongly linked to an upward trend of the tropopause height. Relative humidity and the tropopause height also dominate O3 variability at Lauder in the lower troposphere and the tropopause region, respectively. We perform an attribution of these trends to anthropogenic forcings including O3 precursors, greenhouse gases (GHGs), and O3-depleting substances (ODSs), using CCM simulations. Results indicate that changes in anthropogenic O3 precursors contribute significantly to stratospheric O3 reduction, changes in ODSs contribute significantly to tropospheric O3 reduction, and increased GHGs contribute significantly to stratospheric O3 increases at Lauder. Methane (CH4) likely contributes positively to O3 trends in both the troposphere and the stratosphere, but the contribution is not significant at the 95 % confidence level over this period. An extended analysis of CCM results covering 1960-2010 (i.e. starting well before the observations) reveals significant contributions from all forcings to O3 trends at Lauder - i.e. increases in GHGs and the increase in CH4 alone all contribute significantly to O3 increases, net increases in ODSs lead to O3 reduction, and increases in non-methane O3 precursors cause O3 increases in the troposphere and reductions in the stratosphere. This study suggests that a long-term ozonesonde record obtained at a SH mid-latitude background site (corroborated by a surface O3 record at a nearby SH mid-latitude site, Baring Head, which also shows a significant positive trend) is a useful indicator for detecting atmospheric composition and climate change associated with human activities.

Regional Exploratory Analysis Between Atomospheric Aerosols and Precipitable Water in the Lower Troposhere via Inferential Statistics

NASA Astrophysics Data System (ADS)

Martinez, B. S.; Ye, H.; Levy, R. C.; Fetzer, E. J.; Remer, L.

2017-12-01

Atmospheric aerosols expose high levels of uncertainty in regard to Earth's changing atmospheric energy budget. Continued exploration and analysis is necessary to obtain more complete understanding in which, and to what degree, aerosols contribute within climate feedbacks and global climate change. With the advent of global satellite retrievals, along with specific aerosol optical depth (AOD) Dark Target and Deep Blue algorithms, aerosols can now be better measured and analyzed. Aerosol effect on climate depends primarily on altitude, the reflectance albedo of the underlying surface, along with the presence of clouds and the dynamics thereof. As currently known, the majority of aerosol distribution and mixing occur in the lower troposphere from the surface upwards to around 2km. Additionally, being a primary greenhouse gas contributor, water vapor is significant to climate feedbacks and Earth's radiation budget. Feedbacks are generally reported from the top of atmosphere (TOA). Therefore, little is known of the relationship between water vapor and aerosols; specifically, in regional areas of the globe known for aerosol loading such as anthropogenic biomass burning in South America and naturally occurring dust blowing off the deserts in the African and Arabian peninsulas. Statistical regression and timeseries analysis are used in determining significant probabilities suggesting trends of both regional precipitable water (PW) and AOD increase and decrease over a 13-year time period from 2003-2015. Regions with statistically significant positive or negative trends of AOD and PW are analyzed in determining correlations, or lack thereof. This initial examination helps to deduce and better understand how aerosols contribute to the radiation budget and assessing climate change.

Long-term growth trends and time series of elemental wood composition from two old-growth forests - natural versus anthropogenic influences

NASA Astrophysics Data System (ADS)

Scharnweber, Tobias; van der Maaten, Ernst; Heinrich, Ingo; Buras, Allan; van der Maaten Theunissen, Marieke; Wilmking, Martin

2014-05-01

In contrast to extreme environments with low human impact, where often one specific (climatic) factor is limiting tree growth, dendrochronological research in the temperate zone has to cope with a wide variety of climatic and non-climatic drivers. Sophisticated statistical tools, like various detrending and filtering techniques, allow for a rather precise analysis of high-frequency (annual) climate-growth relationships. However, as almost all forests in the temperate zone are to some degree influenced by human activities, it is difficult to separate anthropogenic from climatic influence on the lower time-frequencies of decades to centuries. Footprints of human activity in time series of tree-ring parameters might be caused directly through forest utilization (logging) or indirectly through environmental changes such as eutrophication or atmospheric pollution. The former can be elucidated by traditional dendrochronological techniques based on ring parameters; evaluation of the latter requires additional proxies such as dendrochemical data. For the interpretation of long-term trends and the calibration of tree-ring based reconstructions it is therefore necessary to study tree growth in as undisturbed forest environments as possible. Comparison with dendrochronological time series from managed forest might then allow separation of climatic- from anthropogenic signals. Here, we present long-term growth trends for the broadleaved tree species common beech, pedunculate oak and sycamore maple, from two protected old-growth forests in northern Germany (one with a documented last logging activity dating back to 1527), and compare those with well-replicated regional chronologies from other, mostly managed forests. Our results indicate that several low frequency trends that can be found in many regional chronologies are likely caused by synchronous periods of heavy loggings as for example during the years following World War II, and do not relate to climatic drivers. In addition, elemental wood composition of trees growing on an island relatively isolated from agricultural depositions or direct atmospheric pollution is compared to elemental concentrations in the wood of trees from a forest surrounded by intensive agriculture in the vicinity of Greifswald, a medium-sized town in Germany. The aim is to detect historical changes in soil chemistry attributable to either atmospheric depositions or groundwater input of nitrogen or sulphur. Therefore, high-resolution (50 µm) X-ray fluorescence (XRF) analysis is carried out and species-specific annual chronologies of relative concentrations of the most abundant elements as well as of different indicative element-ratios are built. We discuss our findings in the light of ongoing soil acidification that might be responsible for some of the detected trends (e.g. decrease in base cations like Ca or Mn), while considering possible radial translocation processes in the wood that might blur the obtained dendrochemical data.

Temporal variability of total cloud cover at a Mediterranean megacity in the 20th century: Evidence from visual observations and climate models

NASA Astrophysics Data System (ADS)

Founda, Dimitra; Giannakopoulos, Christos; Pierros, Fragiskos

2013-04-01

Cloud cover is one of the major factors that determine the radiation budget and the climate system of the Earth. Moreover, the response of clouds has always been an important source of uncertainty in global climate models. Visual surface observations of clouds have been conducted at the National Observatory of Athens (NOA) since the mid 19th century. The historical archive of cloud reports at NOA since 1860 has been digitized and updated, spanning now a period of one and a half century. Mean monthly values of total cloud cover were derived by averaging subdaily observations of cloud cover (3 observations/day). Changes in observational practice (e.g. from 1/10 to 1/8 units) were considered, however, subjective measures of cloud cover from trained observers introduces some kind of uncertainty in the time series. Data before 1884 were considered unreliable, so the analysis was restricted to the series from 1884 to 2012. The time series of total cloud cover at NOA is validated and correlated with historical time series of other (physically related) variables such as the total sunshine duration as well as DTR (Diurnal Temperature Range) which are independently measured. Trend analysis was performed on the mean annual and seasonal series of total cloud cover from 1884-2012. The mean annual values show a marked temporal variability with sub periods of decreasing and increasing tendencies, however, the overall linear trend is positive and statistically significant (p <0.001) amounting to +2% per decade and implying a total increase of almost 25% for the whole analysed period. These results are in agreement qualitatively with the trends reported in other studies worldwide, especially concerning the period before the mid 20th century. On a seasonal basis, spring and summer series present outstanding positive long term trends, while in winter and autumn total cloud cover reveals also positive but less pronounced long term trends Additionally, an evaluation of cloud cover and/or sunshine duration/diurnal temperature range as depicted by regional climate models over Athens will be performed. Regional climate models are valuable tools for projections of future climate change but their performance is typically assessed only in terms of temperature and precipitation. The representation of non-standard parameters such as cloud cover and/or sunshine duration/diurnal temperature range has so far seen little or no evaluation in the models and can therefore be prone to large uncertainties. Regional climate models developed in the framework of recent EU projects, such as the ENSEMBLES (www.ensembles-eu.org) and the CIRCE (www.circeproject.eu) projects, will be used and an initial validation of these parameters against the historical archive of NOA will be performed.

A Decadal Regional and Global Trend Analysis of the Aerosol Optical Depth using a Data-Assimilation Grade Over-Water MODIS and Level 2 MISR Aerosol Products

DTIC Science & Technology

2010-01-01

and seasonal sensitivities to clear sky fraction and emissions (e.g., see annual state of the climate summaries in the BAMS, http://www.ncdc.noaa...gov/bams- state - of - the - climate /). Long term changes are as- sumed to be attributable to more background changes of en- ergy use and economic development

Consistent response of bird populations to climate change on two continents

USGS Publications Warehouse

Stephens, Philip A.; Mason, Lucy R.; Green, Rhys E.; Gregory, Richard D.; Sauer, John R.; Alison, Jamie; Aunins, Ainars; Brotons, Lluís; Butchart, Stuart H.M.; Campedelli, Tommaso; Chodkiewicz, Tomasz; Chylarecki, Przemyslaw; Crowe, Olivia; Elts, Jaanus; Escandell, Virginia; Foppen, Ruud P.B.; Heldbjerg, Henning; Herrando, Sergi; Husby, Magne; Jiguet, Frédéric; Lehikoinen, Aleksi; Lindström, Åke; Noble, David G.; Paquet, Jean-Yves; Reif, Jiri; Sattler, Thomas; Szép, Tibor; Teufelbauer, Norbert; Trautmann, Sven; Van Strien, Arco; van Turnhout, Chris A.M.; Vorisek, Petr; Willis, Stephen G.

2016-01-01

Global climate change is a major threat to biodiversity. Large-scale analyses have generally focused on the impacts of climate change on the geographic ranges of species and on phenology, the timing of ecological phenomena. We used long-term monitoring of the abundance of breeding birds across Europe and the United States to produce, for both regions, composite population indices for two groups of species: those for which climate suitability has been either improving or declining since 1980. The ratio of these composite indices, the climate impact indicator (CII), reflects the divergent fates of species favored or disadvantaged by climate change. The trend in CII is positive and similar in the two regions. On both continents, interspecific and spatial variation in population abundance trends are well predicted by climate suitability trends.

Indices of climate change in the Atlantic coast derived from radiosondes

NASA Astrophysics Data System (ADS)

Añel, J. A.; Gimeno, L.; Nieto, R.; Tesouro, M.; de La Torre, L.; Ribera, P.; García, R.; Hernández, E.

2003-04-01

In this poster we present the use of National Climatic Data Center Upper Air Digital Files (CARDS) to look for indications of climatic change over the principal area affected by the North Atlantic Oscillation. To do that we use several parameters calculated using radiosonde data. In this analysis, we take into account radiosonde stations from 28 North to 64 North, with data for the period from 1973 to 1998. Trends, oscillations and the relationship with the Northern Annular Mode and ENSO (El Niño-Southern Oscillation) were also studied.

Spatio-Temporal Analysis of Trends and periodicities of regional drought projections in India

NASA Astrophysics Data System (ADS)

Gupta, Vivek; Jain, Manoj Kumar

2017-04-01

Climate change is believed to be altering the hydrologic cycle of different regions worldwide. This may alter the occurrence and distribution of extreme events such as droughts and floods. India is one of the most drought affected country, it is therefore important to understand spatiotemporal variation of droughts in future due to climate change. In this paper, we have analyzed the spatiotemporal projections of droughts over India for 21st century using Global Climate Model (GCM) precipitation projections of ESM2G model under two Representative Concentration Pathways (RCP) namely, RCP 4.5 and RCP 8.5. K-means Clustering algorithm has been exploited to obtain homogeneous precipitation region in India for regional drought analysis. Further, temporal analysis of projected annual minimum SPI for year 2006 to 2100 has been performed for different homogeneous regions obtained using cluster analysis. Trend analysis of annual minimum SPI series has also been performed using Mann-Kendall and Sen's slope method. Furthermore, periodicity in SPI series have been examined using wavelet periodogram analysis. Findings of this paper suggest that major drought events for Northeastern and Southern India are likely to occur in second half of the 21st century while for all other parts of India, most of the major drought events are expected in first half of the 21st century. Also, wavelet periodicity analysis indicates inter-annual periodicities of projected droughts between 3 to 9.5 years in different regions of India.

Variability of the recent climate of eastern Africa

NASA Astrophysics Data System (ADS)

Schreck, Carl J., III; Semazzi, Fredrick H. M.

2004-05-01

The primary objective of this study is to investigate the recent variability of the eastern African climate. The region of interest is also known as the Greater Horn of Africa (GHA), and comprises the countries of Burundi, Djibouti, Eritrea, Ethiopia, Kenya, Rwanda, Somalia, Sudan, Uganda, and Tanzania.The analysis was based primarily on the construction of empirical orthogonal functions (EOFs) of gauge rainfall data and on CPC Merged Analysis of Precipitation (CMAP) data, derived from a combination of rain-gauge observations and satellite estimates. The investigation is based on the period 1961-2001 for the short rains season of eastern Africa of October through to December. The EOF analysis was supplemented by projection of National Centers for Environmental Prediction wind data onto the rainfall eigenmodes to understand the rainfall-circulation relationships. Furthermore, correlation and composite analyses have been performed with the Climatic Research Unit globally averaged surface-temperature time series to explore the potential relationship between the climate of eastern Africa and global warming.The most dominant mode of variability (EOF1) based on CMAP data over eastern Africa corresponds to El Niño-southern oscillation (ENSO) climate variability. It is associated with above-normal rainfall amounts during the short rains throughout the entire region, except for Sudan. The corresponding anomalous low-level circulation is dominated by easterly inflow from the Indian Ocean, and to a lesser extent the Congo tropical rain forest, into the positive rainfall anomaly region that extends across most of eastern Africa. The easterly inflow into eastern Africa is part of diffluent outflow from the maritime continent during the warm ENSO events. The second eastern African EOF (trend mode) is associated with decadal variability. In distinct contrast from the ENSO mode pattern, the trend mode is characterized by positive rainfall anomalies over the northern sector of eastern Africa and opposite conditions over the southern sector. This rainfall trend mode eluded detection in previous studies that did not include recent decades of data, because the signal was still relatively weak. The wind projection onto this mode indicates that the primary flow that feeds the positive anomaly region over the northern part of eastern Africa emanates primarily from the rainfall-deficient southern region of eastern Africa and Sudan. Although we do not assign attribution of the trend mode to global warming (in part because of the relatively short period of analysis), the evidence, based on our results and previous studies, strongly suggests a potential connection.

Spatial-temporal analysis of climate variations in mid-17th through 19th centuries in East China and the possible relationships with Monsoon climate

NASA Astrophysics Data System (ADS)

Lin, K. H. E.; Wang, P. K.; Liao, Y. C.; Lee, S. Y.; Tan, P.

2016-12-01

IPCC AR5 has revealed more frequent extreme climate events and higher climate variability in the near future. Regardless of all the improvements, East Asia monsoon climate is still less understood and/or poorly projected due partly to insufficient records. Most areas of the Asian region lack sufficient observational records to draw conclusions about trends in annual precipitation over the past century (i.e. WGIAR5 Chapter 2). Precipitation trends, including extremes, are characterized by strong variability, with both increasing and decreasing observed in different parts and seasons of Asia. Understanding the variations of the monsoon climate in historical time may bring significant insights to reveal its spatial and temporal patterns embedded in the atmospheric dynamics at different decadal or centennial scales. This study presents some preliminary research results of high resolution climate reconstruction, in both time and space coverage, in east China, by using RCEC historical climate dataset that is developed under interdisciplinary collaboration led by Research Center for Environmental Changes at Academia Sinica, Taiwan. The present research results are derived from chronological meteorological records in the RCEC dataset in Qing dynasty labeling mid-17th to 19th centuries. In total, the dataset comprises more than 1,300 cities/counties in China that has had more than sixty thousands meteorological records in the period. The analysis comprises three parts. Firstly, the frequency of extreme temperature, precipitation, drought, and flood in every recorded cities/counties were computed to depicting climate variabilities in northeast, central-east and southeast China. Secondly, the multivariate regression model was conducted to estimate the coefficients among the climatic index (temperature, precipitation, and drought). It is found that the temperature and wet-dry characteristics have great seasonal and yearly variations; northeast China compared with central-east or southeast tends to have higher variability. Thirdly, those data was used to conduct empirical orthogonal function (EOF) analysis to decompose possible mechanisms that might have cause changes in East Asia monsoon regime during the time period. The reconstructed data were also compared against paleoclimate simulation.

Climate induced changes in biome distribution, NPP and hydrology for potential vegetation of the Upper Midwest U.S

NASA Astrophysics Data System (ADS)

Motew, M.; Kucharik, C. J.

2011-12-01

While much attention is focused on future impacts of climate change on ecosystems, much can be learned about the previous interactions of ecosystems with recent climate change. In this study, we investigated the impacts of climate change on potential vegetation distributions (i.e. grasses, trees, and shrubs) and carbon and water cycling across the Upper Midwest USA from 1948-2007 using the Agro-IBIS dynamic vegetation model. We drove the model using a historical, gridded daily climate data set (temperature, precipitation, humidity, solar radiation, and wind speed) at a spatial resolution of 5 min x 5 min. While trends in climate variables exhibited heterogeneous spatial patterns over the study period, the overall impact of climate change on vegetation productivity was positive. We observed total increases in net primary productivity (NPP) ranging from 20-150 g C m-2, based on linear regression analysis. We determined that increased summer relative humidity, increased annual precipitation and decreased mean maximum summer temperatures were key variables contributing to these positive trends, likely through a reduction in soil moisture stress (e.g., increased available water) and heat stress. Model simulations also illustrated an increase in annual drainage throughout the region of 20-140 mm yr-1, driven by substantial increases in annual precipitation. Evapotranspiration had a highly variable spatial trend over the 60-year period, with total change over the study period ranging between -100 and +100 mm yr-1. We also analyzed potential changes in plant functional type (PFT) distributions at the biome level, but hypothesize that the model may be unable to adequately capture competitive interactions among PFTs as well as the dynamics between upper and lower canopies consisting of trees, grasses and shrubs. An analysis of the bioclimatic envelopes for PFTs common to the region revealed no significant change to the boreal conifer tree climatic domain over the study period, yet did reveal a slightly expanded domain for temperate deciduous broadleaf trees. The location of the Tension Zone, a broad ecotone dividing mixed forests in the north and southern hardwood forests and prairies in the south, was not observed to shift using analyses of both meteorological variables and through the results of simulated vegetation distributions. In general, our results supported the idea that climate change is spatially variable in nature, having significant effects on ecosystem structure and function. Our analysis also revealed interesting relationships among the key climatic quantities driving plant productivity and hydrology in the region. Most notably, while the model suggested that potential biome and PFT distributions have not likely shifted significantly in the past 60 years, climate change has contributed to substantial changes in coupled carbon, water, and energy exchange in natural ecosystems of the Upper Midwest US. We conclude that incorporating recent, high-resolution climate records into ecological studies offers valuable insight into the heterogeneous nature of climate change and its impacts on ecosystems at the local level.

Global Trends in Chlorophyll Concentration Observed with the Satellite Ocean Colour Data Record

NASA Astrophysics Data System (ADS)

Melin, F.; Vantrepotte, V.; Chuprin, A.; Grant, M.; Jackson, T.; Sathyendranath, S.

2016-08-01

To detect climate change signals in the data records derived from remote sensing of ocean colour, combining data from multiple missions is required, which implies that the existence of inter-mission differences be adequately addressed prior to undertaking trend studies. Trend distributions associated with merged products are compared with those obtained from single-mission data sets in order to evaluate their suitability for climate studies. Merged products originally developed for operational applications such as near-real time distribution (GlobColour) do not appear to be proper climate data records, showing large parts of the ocean with trends significantly different from trends obtained with SeaWiFS, MODIS or MERIS. On the other hand, results obtained from the Climate Change Initiative (CCI) data are encouraging, showing a good consistency with single-mission products.

An assessment of historical Antarctic precipitation and temperature trend using CMIP5 models and reanalysis datasets

NASA Astrophysics Data System (ADS)

Tang, Malcolm S. Y.; Chenoli, Sheeba Nettukandy; Samah, Azizan Abu; Hai, Ooi See

2018-03-01

The study of Antarctic precipitation has attracted a lot of attention recently. The reliability of climate models in simulating Antarctic precipitation, however, is still debatable. This work assess the precipitation and surface air temperature (SAT) of Antarctica (90 oS to 60 oS) using 49 Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models and the European Centre for Medium-range Weather Forecasts "Interim" reanalysis (ERA-Interim); the National Centers for Environmental Prediction Climate Forecast System Reanalysis (CFSR); the Japan Meteorological Agency 55-year Reanalysis (JRA-55); and the Modern Era Retrospective-analysis for Research and Applications (MERRA) datasets for 1979-2005 (27 years). For precipitation, the time series show that the MERRA and JRA-55 have significantly increased from 1979 to 2005, while the ERA-Int and CFSR have insignificant changes. The reanalyses also have low correlation with one another (generally less than +0.69). 37 CMIP5 models show increasing trend, 18 of which are significant. The resulting CMIP5 MMM also has a significant increasing trend of 0.29 ± 0.06 mm year-1. For SAT, the reanalyses show insignificant changes and have high correlation with one another, while the CMIP5 MMM shows a significant increasing trend. Nonetheless, the variability of precipitation and SAT of MMM could affect the significance of its trend. One of the many reasons for the large differences of precipitation is the CMIP5 models' resolution.

Frequency Analysis of Modis Ndvi Time Series for Determining Hotspot of Land Degradation in Mongolia

NASA Astrophysics Data System (ADS)

Nasanbat, E.; Sharav, S.; Sanjaa, T.; Lkhamjav, O.; Magsar, E.; Tuvdendorj, B.

2018-04-01

This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September) for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.

Changes in Hydrological Extremes and its Relation to Climate Variability in Mountainous Watershed: A Case Study from Gandaki River Basin, Nepal

NASA Astrophysics Data System (ADS)

Shrestha, N. S.; Dahal, P.

2016-12-01

Changes in the hydrological extreme are expected due to climate variability and are needed to assess at local and regional scales since these changes are not uniform over the globe. This study analyses the changes in intensity, frequency and persistence hydrological extreme in Gandaki River Basin (GRB) Nepal over past and future and its relation to climate variability. Hydrological data of 12 different hydrological stations covering all the sub basins of Gandaki River Basin were analyzed. At least 1 hydrological station in each sub basin to the maximum of 3 was taken into consideration for this study. Results show that hydrological extreme have increased in intensity, frequency and persistence over recent year and are predicted to increase in future (2030-2060). The time-series analysis revealed an increase in the magnitude, frequency and duration of flood and drought. The instantaneous maximum flow, flood events and duration of flood events are found to have increasing trend. The minimum discharge was observed to be decreasing which entails that the water availability in the driest time is decreasing. Trend analysis of seasonal flow revealed an increase in monsoon flows and decreasing in post monsoon. Changes in climate variability over the same period shows higher anomalies in both temperature and precipitation in recent decades (1990s and 2000s) compared to the baseline period (1970-2000). Model suggests an increasing trend in annual flows with the increase more pronounced in 2060s. Significant increase in extreme flows and subsequent decrease in dependable flows suggest increase in frequency of isolated extreme flows followed by prolonged dry spells. Data also showed that the mean temperature will be increasing from 1.9 0C to 3.1 0C and precipitation will be changing by -8% to +12% in 2031-2060 compared to the baseline period. For long-term planning and management of water resources, current trend and future change in the pattern of water availability should be analysed well in advance. Climate change with intensifying extreme events will likely have serious consequences on the hydrological changes. Therefore, this study would be useful in understanding how the hydrological regime has been changing with climate change in mountainous watershed.

Trends in lake chemistry in response to atmospheric deposition and climate in selected Class I wilderness areas in Colorado, Idaho, Utah, and Wyoming, 1993-2009

USGS Publications Warehouse

Mast, M. Alisa; Ingersoll, George P.

2011-01-01

In 2010, the U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Forest Service, Air Resource Management, began a study to evaluate long-term trends in lake-water chemistry for 64 high-elevation lakes in selected Class I wilderness areas in Colorado, Idaho, Utah, and Wyoming during 1993 to 2009. The purpose of this report is to describe trends in the chemical composition of these high-elevation lakes. Trends in emissions, atmospheric deposition, and climate variables (air temperature and precipitation amount) are evaluated over a similar period of record to determine likely drivers of changing lake chemistry. Sulfate concentrations in precipitation decreased over the past two decades at high-elevation monitoring stations in the Rocky Mountain region. The trend in deposition chemistry is consistent with regional declines in sulfur dioxide emissions resulting from installation of emission controls at large stationary sources. Trends in nitrogen deposition were not as widespread as those for sulfate. About one-half of monitoring stations showed increases in ammonium concentrations, but few showed significant changes in nitrate concentrations. Trends in nitrogen deposition appear to be inconsistent with available emission inventories, which indicate modest declines in nitrogen emissions in the Rocky Mountain region since the mid-1990s. This discrepancy may reflect uncertainties in emission inventories or changes in atmospheric transformations of nitrogen species that may be affecting deposition processes. Analysis of long-term climate records indicates that average annual mean air temperature minimums have increased from 0.57 to 0.75 °C per decade in mountain areas of the region with warming trends being more pronounced in Colorado. Trends in annual precipitation were not evident over the period 1990 to 2006, although wetter than average years during 1995 to 1997 and drier years during 2001 to 2004 caused a notable decline in precipitation in the middle part of the record.

The role of internal climate variability for interpreting climate change scenarios

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-04-01

When communicating information on climate change, the use of multi-model ensembles has been advocated to sample uncertainties over a range as wide as possible. To meet the demand for easily accessible results, the ensemble is often summarised by its multi-model mean signal. In rare cases, additional uncertainty measures are given to avoid loosing all information on the ensemble spread, e.g., the highest and lowest projected values. Such approaches, however, disregard the fundamentally different nature of the different types of uncertainties and might cause wrong interpretations and subsequently wrong decisions for adaptation. Whereas scenario and climate model uncertainties are of epistemic nature, i.e., caused by an in principle reducible lack of knowledge, uncertainties due to internal climate variability are aleatory, i.e., inherently stochastic and irreducible. As wisely stated in the proverb "climate is what you expect, weather is what you get", a specific region will experience one stochastic realisation of the climate system, but never exactly the expected climate change signal as given by a multi model mean. Depending on the meteorological variable, region and lead time, the signal might be strong or weak compared to the stochastic component. In cases of a low signal-to-noise ratio, even if the climate change signal is a well defined trend, no trends or even opposite trends might be experienced. Here I propose to use the time of emergence (TOE) to quantify and communicate when climate change trends will exceed the internal variability. The TOE provides a useful measure for end users to assess the time horizon for implementing adaptation measures. Furthermore, internal variability is scale dependent - the more local the scale, the stronger the influence of internal climate variability. Thus investigating the TOE as a function of spatial scale could help to assess the required spatial scale for implementing adaptation measures. I exemplify this proposal with a recently published study on the TOE for mean and heavy precipitation trends in Europe. In some regions trends emerge only late in the 21st century or even later, suggesting that in these regions adaptation to internal variability rather than to climate change is required. Yet in other regions the climate change signal is strong, urging for timely adaptation. Douglas Maraun, When at what scale will trends in European mean and heavy precipitation emerge? Env. Res. Lett., in press, 2013.

Long-term trends of surface ozone and its influencing factors at the Mt Waliguan GAW station, China - Part 2: The roles of anthropogenic emissions and climate variability

NASA Astrophysics Data System (ADS)

Xu, Wanyun; Xu, Xiaobin; Lin, Meiyun; Lin, Weili; Tarasick, David; Tang, Jie; Ma, Jianzhong; Zheng, Xiangdong

2018-01-01

Inter-annual variability and long-term trends in tropospheric ozone are both environmental and climate concerns. Ozone measured at Mt Waliguan Observatory (WLG, 3816 m a.s.l.) on the Tibetan Plateau over the period of 1994-2013 has increased significantly by 0.2-0.3 ppbv yr-1 during spring and autumn but shows a much smaller trend in winter and no significant trend in summer. Here we explore the factors driving the observed ozone changes at WLG using backward trajectory analysis, chemistry-climate model hindcast simulations (GFDL AM3), a trajectory-mapped ozonesonde data set, and several climate indices. A stratospheric ozone tracer implemented in GFDL AM3 indicates that stratosphere-to-troposphere transport (STT) can explain ˜ 60 % of the simulated springtime ozone increase at WLG, consistent with an increase in the NW air-mass frequency inferred from the trajectory analysis. Enhanced STT associated with the strengthening of the mid-latitude jet stream contributes to the observed high ozone anomalies at WLG during the springs of 1999 and 2012. During autumn, observations at WLG are more heavily influenced by polluted air masses originating from South East Asia than in the other seasons. Rising Asian anthropogenic emissions of ozone precursors are the key driver of increasing autumnal ozone observed at WLG, as supported by the GFDL AM3 model with time-varying emissions, which captures the observed ozone increase (0.26 ± 0.11 ppbv yr-1). AM3 simulates a greater ozone increase of 0.38 ± 0.11 ppbv yr-1 at WLG in autumn under conditions with strong transport from South East Asia and shows no significant ozone trend in autumn when anthropogenic emissions are held constant in time. During summer, WLG is mostly influenced by easterly air masses, but these trajectories do not extend to the polluted regions of eastern China and have decreased significantly over the last 2 decades, which likely explains why summertime ozone measured at WLG shows no significant trend despite ozone increases in eastern China. Analysis of the Trajectory-mapped Ozonesonde data set for the Stratosphere and Troposphere (TOST) and trajectory residence time reveals increases in direct ozone transport from the eastern sector during autumn, which adds to the autumnal ozone increase. We further examine the links of ozone variability at WLG to the quasi-biennial oscillation (QBO), the East Asian summer monsoon (EASM), and the sunspot cycle. Our results suggest that the 2-3-, 3-7-, and 11-year periodicities are linked to the QBO, EASM index, and sunspot cycle, respectively. A multivariate regression analysis is performed to quantify the relative contributions of various factors to surface ozone concentrations at WLG. Through an observational and modelling analysis, this study demonstrates the complex relationships between surface ozone at remote locations and its dynamical and chemical influencing factors.

Secular trends and climate drift in coupled ocean-atmosphere general circulation models

NASA Astrophysics Data System (ADS)

Covey, Curt; Gleckler, Peter J.; Phillips, Thomas J.; Bader, David C.

2006-02-01

Coupled ocean-atmosphere general circulation models (coupled GCMs) with interactive sea ice are the primary tool for investigating possible future global warming and numerous other issues in climate science. A long-standing problem with such models is that when different components of the physical climate system are linked together, the simulated climate can drift away from observation unless constrained by ad hoc adjustments to interface fluxes. However, 11 modern coupled GCMs, including three that do not employ flux adjustments, behave much better in this respect than the older generation of models. Surface temperature trends in control run simulations (with external climate forcing such as solar brightness and atmospheric carbon dioxide held constant) are small compared with observed trends, which include 20th century climate change due to both anthropogenic and natural factors. Sea ice changes in the models are dominated by interannual variations. Deep ocean temperature and salinity trends are small enough for model control runs to extend over 1000 simulated years or more, but trends in some regions, most notably the Arctic, differ substantially among the models and may be problematic. Methods used to initialize coupled GCMs can mitigate climate drift but cannot eliminate it. Lengthy "spin-ups" of models, made possible by increasing computer power, are one reason for the improvements this paper documents.

Climate change, water rights, and water supply: The case of irrigated agriculture in Idaho

NASA Astrophysics Data System (ADS)

Xu, Wenchao; Lowe, Scott E.; Adams, Richard M.

2014-12-01

We conduct a hedonic analysis to estimate the response of agricultural land use to water supply information under the Prior Appropriation Doctrine by using Idaho as a case study. Our analysis includes long-term climate (weather) trends and water supply conditions as well as seasonal water supply forecasts. A farm-level panel data set, which accounts for the priority effects of water rights and controls for diversified crop mixes and rotation practices, is used. Our results indicate that farmers respond to the long-term surface and ground water conditions as well as to the seasonal water supply variations. Climate change-induced variations in climate and water supply conditions could lead to substantial damages to irrigated agriculture. We project substantial losses (up to 32%) of the average crop revenue for major agricultural areas under future climate scenarios in Idaho. Finally, farmers demonstrate significantly varied responses given their water rights priorities, which imply that the distributional impact of climate change is sensitive to institutions such as the Prior Appropriation Doctrine.

Climate change and observed climate trends in the fort cobb experimental watershed.

PubMed

Garbrecht, J D; Zhang, X C; Steiner, J L

2014-07-01

Recurring droughts in the Southern Great Plains of the United States are stressing the landscape, increasing uncertainty and risk in agricultural production, and impeding optimal agronomic management of crop, pasture, and grazing systems. The distinct possibility that the severity of recent droughts may be related to a greenhouse-gas induced climate change introduces new challenges for water resources managers because the intensification of droughts could represent a permanent feature of the future climate. Climate records of the Fort Cobb watershed in central Oklahoma were analyzed to determine if recent decade-long trends in precipitation and air temperature were consistent with climate change projections for central Oklahoma. The historical precipitation record did not reveal any compelling evidence that the recent 20-yr-long decline in precipitation was related to climate change. Also, precipitation projections by global circulation models (GCMs) displayed a flat pattern through the end of the 21st century. Neither observed nor projected precipitation displayed a multidecadal monotonic rising or declining trend consistent with an ongoing warming climate. The recent trend in observed annual precipitation was probably a decade-scale variation not directly related to the warming climate. On the other hand, the observed monotonic warming trend of 0.34°C decade that started around 1978 is consistent with GCM projections of increasing temperature for central Oklahoma. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Trends in record-breaking temperatures for the conterminous United States

NASA Astrophysics Data System (ADS)

Rowe, Clinton M.; Derry, Logan E.

2012-08-01

In an unchanging climate, record-breaking temperatures are expected to decrease in frequency over time, as established records become increasingly more difficult to surpass. This inherent trend in the number of record-breaking events confounds the interpretation of actual trends in the presence of any underlying climate change. Here, a simple technique to remove the inherent trend is introduced so that any remaining trend can be examined separately for evidence of a climate change. As this technique does not use the standard definition of a broken record, our records* are differentiated by an asterisk. Results for the period 1961-2010 indicate that the number of record* low daily minimum temperatures has been significantly and steadily decreasing nearly everywhere across the United States while the number of record* high daily minimum temperatures has been predominantly increasing. Trends in record* low and record* high daily maximum temperatures are generally weaker and more spatially mixed in sign. These results are consistent with other studies examining changes expected in a warming climate.

Untangling Trends and Drivers of Changing River Discharge Along Florida's Gulf Coast

NASA Astrophysics Data System (ADS)

Glodzik, K.; Kaplan, D. A.; Klarenberg, G.

2017-12-01

Along the relatively undeveloped Big Bend coastline of Florida, discharge in many rivers and springs is decreasing. The causes are unclear, though they likely include a combination of groundwater extraction for water supply, climate variability, and altered land use. Saltwater intrusion from altered freshwater influence and sea level rise is causing transformative ecosystem impacts along this flat coastline, including coastal forest die-off and oyster reef collapse. A key uncertainty for understanding river discharge change is predicting discharge from rainfall, since Florida's karstic bedrock stores large amounts of groundwater, which has a long residence time. This study uses Dynamic Factor Analysis (DFA), a multivariate data reduction technique for time series, to find common trends in flow and reveal hydrologic variables affecting flow in eight Big Bend rivers since 1965. The DFA uses annual river flows as response time series, and climate data (annual rainfall and evapotranspiration by watershed) and climatic indices (El Niño Southern Oscillation [ENSO] Index and North Atlantic Oscillation [NAO] Index) as candidate explanatory variables. Significant explanatory variables (one evapotranspiration and three rainfall time series) explained roughly 50% of discharge variation across rivers. Significant trends (representing unexplained variation) were shared among rivers, with geographical grouping of five northern rivers and three southern rivers, along with a strong downward trend affecting six out of eight systems. ENSO and NAO had no significant impact. Advancing knowledge of these dynamics is necessary for forecasting how altered rainfall and temperatures from climate change may impact flows. Improved forecasting is especially important given Florida's reliance on groundwater extraction to support its growing population.

Use and Limitations of a Climate-Quality Data Record to Study Temperature Trends on the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Comiso, Josefino C.; Shuman, Christopher A.; Koenig, Lora S.; DiGirolamo, Nicolo E.

2011-01-01

Enhanced melting of the Greenland Ice Sheet has been documented in recent literature along with surface-temperature increases measured using infrared satellite data since 1981. Using a recently-developed climate-quality data record, 11- and 12-year trends in the clear-sky ice-surface temperature (IST) of the Greenland Ice Sheet have been studied using the Moderate-Resolution Imaging Spectroradiometer (MODIS) IST product. Daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are now available at 6.25-km spatial resolution on a polar stereographic grid as described in Hall et al. (submitted). This record will be elevated in status to a climate-data record (CDR) when more years of data become available either from the MODIS on the Terra or Aqua satellites, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Maps showing the maximum extent of melt for the entire ice sheet and for the six major drainage basins have been developed from the MODIS IST dataset. Twelve-year trends of the duration of the melt season on the ice sheet vary in different drainage basins with some basins melting progressively earlier over the course of the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. IST 12-year trends are compared with in-situ data, and climate data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) Reanalysis.

Seasonal trend analysis and ARIMA modeling of relative humidity and wind speed time series around Yamula Dam

NASA Astrophysics Data System (ADS)

Eymen, Abdurrahman; Köylü, Ümran

2018-02-01

Local climate change is determined by analysis of long-term recorded meteorological data. In the statistical analysis of the meteorological data, the Mann-Kendall rank test, which is one of the non-parametrical tests, has been used; on the other hand, for determining the power of the trend, Theil-Sen method has been used on the data obtained from 16 meteorological stations. The stations cover the provinces of Kayseri, Sivas, Yozgat, and Nevşehir in the Central Anatolia region of Turkey. Changes in land-use affect local climate. Dams are structures that cause major changes on the land. Yamula Dam is located 25 km northwest of Kayseri. The dam has huge water body which is approximately 85 km2. The mentioned tests have been used for detecting the presence of any positive or negative trend in meteorological data. The meteorological data in relation to the seasonal average, maximum, and minimum values of the relative humidity and seasonal average wind speed have been organized as time series and the tests have been conducted accordingly. As a result of these tests, the following have been identified: increase was observed in minimum relative humidity values in the spring, summer, and autumn seasons. As for the seasonal average wind speed, decrease was detected for nine stations in all seasons, whereas increase was observed in four stations. After the trend analysis, pre-dam mean relative humidity time series were modeled with Autoregressive Integrated Moving Averages (ARIMA) model which is statistical modeling tool. Post-dam relative humidity values were predicted by ARIMA models.

Climate change or climate cycles? Snowpack trends in the Olympic and Cascade Mountains, Washington, USA.

PubMed

Barry, Dwight; McDonald, Shea

2013-01-01

Climate change could significantly influence seasonal streamflow and water availability in the snowpack-fed watersheds of Washington, USA. Descriptions of snowpack decline often use linear ordinary least squares (OLS) models to quantify this change. However, the region's precipitation is known to be related to climate cycles. If snowpack decline is more closely related to these cycles, an OLS model cannot account for this effect, and thus both descriptions of trends and estimates of decline could be inaccurate. We used intervention analysis to determine whether snow water equivalent (SWE) in 25 long-term snow courses within the Olympic and Cascade Mountains are more accurately described by OLS (to represent gradual change), stationary (to represent no change), or step-stationary (to represent climate cycling) models. We used Bayesian information-theoretic methods to determine these models' relative likelihood, and we found 90 models that could plausibly describe the statistical structure of the 25 snow courses' time series. Posterior model probabilities of the 29 "most plausible" models ranged from 0.33 to 0.91 (mean = 0.58, s = 0.15). The majority of these time series (55%) were best represented as step-stationary models with a single breakpoint at 1976/77, coinciding with a major shift in the Pacific Decadal Oscillation. However, estimates of SWE decline differed by as much as 35% between statistically plausible models of a single time series. This ambiguity is a critical problem for water management policy. Approaches such as intervention analysis should become part of the basic analytical toolkit for snowpack or other climatic time series data.

Potential impacts of climate change on water quality in a shallow reservoir in China.

PubMed

Zhang, Chen; Lai, Shiyu; Gao, Xueping; Xu, Liping

2015-10-01

To study the potential effects of climate change on water quality in a shallow reservoir in China, the field data analysis method is applied to data collected over a given monitoring period. Nine water quality parameters (water temperature, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total nitrogen, total phosphorus, chemical oxygen demand, biochemical oxygen demand and dissolved oxygen) and three climate indicators for 20 years (1992-2011) are considered. The annual trends exhibit significant trends with respect to certain water quality and climate parameters. Five parameters exhibit significant seasonality differences in the monthly means between the two decades (1992-2001 and 2002-2011) of the monitoring period. Non-parametric regression of the statistical analyses is performed to explore potential key climate drivers of water quality in the reservoir. The results indicate that seasonal changes in temperature and rainfall may have positive impacts on water quality. However, an extremely cold spring and high wind speed are likely to affect the self-stabilising equilibrium states of the reservoir, which requires attention in the future. The results suggest that land use changes have important impact on nitrogen load. This study provides useful information regarding the potential effects of climate change on water quality in developing countries.

Climatic and technological ceilings for Chinese rice stagnation based on yield gaps and yield trend pattern analysis.

PubMed

Zhang, Tianyi; Yang, Xiaoguang; Wang, Hesong; Li, Yong; Ye, Qing

2014-04-01

Climatic or technological ceilings could cause yield stagnation. Thus, identifying the principal reasons for yield stagnation within the context of the local climate and socio-economic conditions are essential for informing regional agricultural policies. In this study, we identified the climatic and technological ceilings for seven rice-production regions in China based on yield gaps and on a yield trend pattern analysis for the period 1980-2010. The results indicate that 54.9% of the counties sampled experienced yield stagnation since the 1980. The potential yield ceilings in northern and eastern China decreased to a greater extent than in other regions due to the accompanying climate effects of increases in temperature and decreases in radiation. This may be associated with yield stagnation and halt occurring in approximately 49.8-57.0% of the sampled counties in these areas. South-western China exhibited a promising scope for yield improvement, showing the greatest yield gap (30.6%), whereas the yields were stagnant in 58.4% of the sampled counties. This finding suggests that efforts to overcome the technological ceiling must be given priority so that the available exploitable yield gap can be achieved. North-eastern China, however, represents a noteworthy exception. In the north-central area of this region, climate change has increased the yield potential ceiling, and this increase has been accompanied by the most rapid increase in actual yield: 1.02 ton ha(-1) per decade. Therefore, north-eastern China shows a great potential for rice production, which is favoured by the current climate conditions and available technology level. Additional environmentally friendly economic incentives might be considered in this region. © 2013 John Wiley & Sons Ltd.

Statistical assessment of changes in extreme maximum temperatures over Saudi Arabia, 1985-2014

NASA Astrophysics Data System (ADS)

Raggad, Bechir

2018-05-01

In this study, two statistical approaches were adopted in the analysis of observed maximum temperature data collected from fifteen stations over Saudi Arabia during the period 1985-2014. In the first step, the behavior of extreme temperatures was analyzed and their changes were quantified with respect to the Expert Team on Climate Change Detection Monitoring indices. The results showed a general warming trend over most stations, in maximum temperature-related indices, during the period of analysis. In the second step, stationary and non-stationary extreme-value analyses were conducted for the temperature data. The results revealed that the non-stationary model with increasing linear trend in its location parameter outperforms the other models for two-thirds of the stations. Additionally, the 10-, 50-, and 100-year return levels were found to change with time considerably and that the maximum temperature could start to reappear in the different T-year return period for most stations. This analysis shows the importance of taking account the change over time in the estimation of return levels and therefore justifies the use of the non-stationary generalized extreme value distribution model to describe most of the data. Furthermore, these last findings are in line with the result of significant warming trends found in climate indices analyses.

Global Warming and Northern Hemisphere Sea Ice Extent.

PubMed

Vinnikov; Robock; Stouffer; Walsh; Parkinson; Cavalieri; Mitchell; Garrett; Zakharov

1999-12-03

Surface and satellite-based observations show a decrease in Northern Hemisphere sea ice extent during the past 46 years. A comparison of these trends to control and transient integrations (forced by observed greenhouse gases and tropospheric sulfate aerosols) from the Geophysical Fluid Dynamics Laboratory and Hadley Centre climate models reveals that the observed decrease in Northern Hemisphere sea ice extent agrees with the transient simulations, and both trends are much larger than would be expected from natural climate variations. From long-term control runs of climate models, it was found that the probability of the observed trends resulting from natural climate variability, assuming that the models' natural variability is similar to that found in nature, is less than 2 percent for the 1978-98 sea ice trends and less than 0.1 percent for the 1953-98 sea ice trends. Both models used here project continued decreases in sea ice thickness and extent throughout the next century.

Precise monitoring of global temperature trends from satellites

NASA Technical Reports Server (NTRS)

Spencer, Roy W.; Christy, John R.

1990-01-01

Passive microwave radiometry from satellites provides more precise atmospheric temperature information than that obtained from the relatively sparse distribution of thermometers over the earth's surface. Accurate global atmospheric temperature estimates are needed for detection of possible greenhouse warming, evaluation of computer models of climate change, and for understanding important factors in the climate system. Analysis of the first 10 years (1979 to 1988) of satellite measurements of lower atmospheric temperature changes reveals a monthly precision of 0.01 C, large temperature variability on time scales from weeks to several years, but no obvious trend for the 10-year period. The warmest years, in descending order, were 1987, 1988, 1983, and 1980. The years 1984, 1985, and 1986 were the coolest.

Applying Metrological Techniques to Satellite Fundamental Climate Data Records

NASA Astrophysics Data System (ADS)

Woolliams, Emma R.; Mittaz, Jonathan PD; Merchant, Christopher J.; Hunt, Samuel E.; Harris, Peter M.

2018-02-01

Quantifying long-term environmental variability, including climatic trends, requires decadal-scale time series of observations. The reliability of such trend analysis depends on the long-term stability of the data record, and understanding the sources of uncertainty in historic, current and future sensors. We give a brief overview on how metrological techniques can be applied to historical satellite data sets. In particular we discuss the implications of error correlation at different spatial and temporal scales and the forms of such correlation and consider how uncertainty is propagated with partial correlation. We give a form of the Law of Propagation of Uncertainties that considers the propagation of uncertainties associated with common errors to give the covariance associated with Earth observations in different spectral channels.

On the definition and identifiability of the alleged “hiatus” in global warming

PubMed Central

Lewandowsky, Stephan; Risbey, James S.; Oreskes, Naomi

2015-01-01

Recent public debate and the scientific literature have frequently cited a “pause” or “hiatus” in global warming. Yet, multiple sources of evidence show that climate change continues unabated, raising questions about the status of the “hiatus”. To examine whether the notion of a “hiatus” is justified by the available data, we first document that there are multiple definitions of the “hiatus” in the literature, with its presumed onset spanning a decade. For each of these definitions we compare the associated temperature trend against trends of equivalent length in the entire record of modern global warming. The analysis shows that the “hiatus” trends are encompassed within the overall distribution of observed trends. We next assess the magnitude and significance of all possible trends up to 25 years duration looking backwards from each year over the past 30 years. At every year during the past 30 years, the immediately preceding warming trend was always significant when 17 years (or more) were included in the calculation, alleged “hiatus” periods notwithstanding. If current definitions of the “pause” used in the literature are applied to the historical record, then the climate system “paused” for more than 1/3 of the period during which temperatures rose 0.6 K. PMID:26597713

Statistical Analysis of Terrestrial Water Storage Change Over Southwestern United States

NASA Astrophysics Data System (ADS)

Eibedingil, I. G.; Mubako, S. T.; Hargrove, W. L.; Espino, A. C.

2017-12-01

A warming trend over recent decades has aggravated water resource challenges in the arid southwestern region of the United States (U.S.). An increase in temperature, coupled with decreasing snowpack and rainfall have impacted the region's cities, ecosystems, and agriculture. The region is the largest contributor of agricultural products to the U.S. market resulting from irrigation. Water use through irrigation is stressing already limited terrestrial water resources. Population growth in recent decades has also led to increased water demand. This study utilizes products of the Gravity Recovery and Climate Experiment (GRACE) twin satellites experiment in MATLAB and ArcGIS to examine terrestrial water storage changes in the southwestern region of the U.S., comprised of the eight states of Texas, California, Nevada, Utah, Arizona, Colorado, New Mexico, and Oklahoma. Linear trend analysis was applied to the equivalent water-height data of terrestrial water storage changes (TWSC), precipitation, and air temperature. Correlation analysis was performed on couplings of TWSC - precipitation and TWSC - air temperature to examine the impact of temperature and precipitation on the region's water resources. Our preliminary results show a decreasing trend of TWSC from April 2002 to July 2016 in almost all parts of the region. Precipitation shows a decreasing trend from March 2000 to March 2017 for most of the region, except for sparse areas of increased precipitation near the northwestern coast of California, and a belt running from Oklahoma through the middle of Texas to the El Paso/New Mexico border. From April 2002 to December 2014, air temperature exhibited a negative trend for most of the region, except a larger part of California and a small location in central Texas. Correlation between TWSC and precipitation was mostly positive, but a negative trend was observed when TWSC and air temperature were correlated. The study contributes to the understanding of terrestrial water storage trends and their relationship with climatic variables, crucial for implementing appropriate adaptation and mitigation policies and strategies, and managing water demand.

Historical trends and extremes in boreal Alaska river basins

DOE PAGES

Bennett, Katrina E.; Cannon, Alex J.; Hinzman, Larry

2015-05-12

Climate change will shift the frequency, intensity, duration and persistence of extreme hydroclimate events and have particularly disastrous consequences in vulnerable systems such as the warm permafrost-dominated Interior region of boreal Alaska. This work focuses on recent research results from nonparametric trends and nonstationary generalized extreme value (GEV) analyses at eight Interior Alaskan river basins for the past 50/60 years (1954/64–2013). Trends analysis of maximum and minimum streamflow indicates a strong (>+50%) and statistically significant increase in 11-day flow events during the late fall/winter and during the snowmelt period (late April/mid-May), followed by a significant decrease in the 11-day flowmore » events during the post-snowmelt period (late May and into the summer). The April–May–June seasonal trends show significant decreases in maximum streamflow for snowmelt dominated systems (<–50%) and glacially influenced basins (–24% to –33%). Annual maximum streamflow trends indicate that most systems are experiencing declines, while minimum flow trends are largely increasing. Nonstationary GEV analysis identifies time-dependent changes in the distribution of spring extremes for snowmelt dominated and glacially dominated systems. Temperature in spring influences the glacial and high elevation snowmelt systems and winter precipitation drives changes in the snowmelt dominated basins. The Pacific Decadal Oscillation was associated with changes occurring in snowmelt dominated systems, and the Arctic Oscillation was linked to one lake dominated basin, with half of the basins exhibiting no change in response to climate variability. The paper indicates that broad scale studies examining trend and direction of change should employ multiple methods across various scales and consider regime dependent shifts to identify and understand changes in extreme streamflow within boreal forested watersheds of Alaska.« less

Observed Changes at the Surface of the Arctic Ocean

NASA Astrophysics Data System (ADS)

Ortmeyer, M.; Rigor, I.

2004-12-01

The Arctic has long been considered a harbinger of global climate change since simulations with global climate models predict that if the concentration of CO2 in the atmosphere doubles, the Arctic would warm by more than 5°C, compared to a warming of 2°C for subpolar regions (Manabe et al., 1991). And indeed, studies of the observational records show polar amplification of the warming trends (e.g. Serreze and Francis, 2004). These temperature trends are accompanied by myriad concurrent changes in Arctic climate. One of the first indicators of Arctic climate change was found by Walsh et al. (1996) using sea level pressure (SLP) data from the International Arctic Buoy Programme (IABP, http://iabp.apl.washington.edu). In this study, they showed that SLP over the Arctic Ocean decreased by over 4 hPa from 1979 - 1994. The decreases in SLP (winds) over the Arctic Ocean, forced changes in the circulation of sea ice and the surface ocean currents such that the Beaufort Gyre is reduced in size and speed (e.g. Rigor et al., 2002). Data from the IABP has also been assimilated into the global surface air temperature (SAT) climatologies (e.g. Jones et al. 1999), and the IABP SAT analysis shows that the temperature trends noted over land extend out over the Arctic Ocean. Specifically, Rigor et al. (2000) found warming trends in SAT over the Arctic Ocean during win¬ter and spring, with values as high as 2°C/decade in the eastern Arctic during spring. It should be noted that many of the changes in Arctic climate were first observed or explained using data from the IABP. The observations from IABP have been one of the cornerstones for environmental forecasting and studies of climate and climate change. These changes have a profound impact on wildlife and people. Many species and cultures depend on the sea ice for habitat and subsistence. Thus, monitoring the Arctic Ocean is crucial not only for our ability to detect climate change, but also to improve our understanding of the Arctic and global climate system, and for forecasting weather and sea ice conditions. The IABP provides the longest continuing record of observations for the Arctic Ocean.

Emerging trends in global freshwater availability.

PubMed

Rodell, M; Famiglietti, J S; Wiese, D N; Reager, J T; Beaudoing, H K; Landerer, F W; Lo, M-H

2018-05-01

Freshwater availability is changing worldwide. Here we quantify 34 trends in terrestrial water storage observed by the Gravity Recovery and Climate Experiment (GRACE) satellites during 2002-2016 and categorize their drivers as natural interannual variability, unsustainable groundwater consumption, climate change or combinations thereof. Several of these trends had been lacking thorough investigation and attribution, including massive changes in northwestern China and the Okavango Delta. Others are consistent with climate model predictions. This observation-based assessment of how the world's water landscape is responding to human impacts and climate variations provides a blueprint for evaluating and predicting emerging threats to water and food security.

Annual minimum temperature variations in early 21st century in Punjab, Pakistan

NASA Astrophysics Data System (ADS)

Jahangir, Misbah; Maria Ali, Syeda; Khalid, Bushra

2016-01-01

Climate change is a key emerging threat to the global environment. It imposes long lasting impacts both at regional and national level. In the recent era, global warming and extreme temperatures have drawn great interest to the scientific community. As in a past century considerable increase in global surface temperatures have been observed and predictions revealed that it will continue in the future. In this regard, current study mainly focused on analysis of regional climatic change (annual minimum temperature trends and its correlation with land surface temperatures in the early 21st century in Punjab) for a period of 1979-2013. The projected model data European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) has been used for eight Tehsils of Punjab i.e., annual minimum temperatures and annual seasonal temperatures. Trend analysis of annual minimum and annual seasonal temperature in (Khushab, Noorpur, Sargodha, Bhalwal, Sahiwal, Shahpur, Sillanwali and Chinoit) tehsils of Punjab was carried out by Regression analysis and Mann-Kendall test. Landsat 5 Thematic Mapper (TM) data was used in comparison with Model data for the month of May from the years 2000, 2009 and 2010. Results showed that no significant trends were observed in annual minimum temperature. A significant change was observed in Noorpur, Bhalwal, Shahpur, Sillanwali, Sahiwal, Chinoit and Sargodha tehsils during spring season, which indicated that this particular season was a transient period of time.

Phenological Changes in the Southern Hemisphere

PubMed Central

Chambers, Lynda E.; Altwegg, Res; Barbraud, Christophe; Barnard, Phoebe; Beaumont, Linda J.; Crawford, Robert J. M.; Durant, Joel M.; Hughes, Lesley; Keatley, Marie R.; Low, Matt; Morellato, Patricia C.; Poloczanska, Elvira S.; Ruoppolo, Valeria; Vanstreels, Ralph E. T.; Woehler, Eric J.; Wolfaardt, Anton C.

2013-01-01

Current evidence of phenological responses to recent climate change is substantially biased towards northern hemisphere temperate regions. Given regional differences in climate change, shifts in phenology will not be uniform across the globe, and conclusions drawn from temperate systems in the northern hemisphere might not be applicable to other regions on the planet. We conduct the largest meta-analysis to date of phenological drivers and trends among southern hemisphere species, assessing 1208 long-term datasets from 89 studies on 347 species. Data were mostly from Australasia (Australia and New Zealand), South America and the Antarctic/subantarctic, and focused primarily on plants and birds. This meta-analysis shows an advance in the timing of spring events (with a strong Australian data bias), although substantial differences in trends were apparent among taxonomic groups and regions. When only statistically significant trends were considered, 82% of terrestrial datasets and 42% of marine datasets demonstrated an advance in phenology. Temperature was most frequently identified as the primary driver of phenological changes; however, in many studies it was the only climate variable considered. When precipitation was examined, it often played a key role but, in contrast with temperature, the direction of phenological shifts in response to precipitation variation was difficult to predict a priori. We discuss how phenological information can inform the adaptive capacity of species, their resilience, and constraints on autonomous adaptation. We also highlight serious weaknesses in past and current data collection and analyses at large regional scales (with very few studies in the tropics or from Africa) and dramatic taxonomic biases. If accurate predictions regarding the general effects of climate change on the biology of organisms are to be made, data collection policies focussing on targeting data-deficient regions and taxa need to be financially and logistically supported. PMID:24098389

Analysis of European ozone trends in the period 1995-2014

NASA Astrophysics Data System (ADS)

Yan, Yingying; Pozzer, Andrea; Ojha, Narendra; Lin, Jintai; Lelieveld, Jos

2018-04-01

Surface-based measurements from the EMEP and Airbase networks are used to estimate the changes in surface ozone levels during the 1995-2014 period over Europe. We find significant ozone enhancements (0.20-0.59 µg m-3 yr-1 for the annual means; P-value < 0.01 according to an F-test) over the European suburban and urban stations during 1995-2012 based on the Airbase sites. For European background ozone observed at EMEP sites, it is shown that a significantly decreasing trend in the 95th percentile ozone concentrations has occurred, especially at noon (0.9 µg m-3 yr-1; P-value < 0.01), while the 5th percentile ozone concentrations continued to increase with a trend of 0.3 µg m-3 yr-1 (P-value < 0.01) during the study period. With the help of numerical simulations performed with the global chemistry-climate model EMAC, the importance of anthropogenic emissions changes in determining these changes over background sites are investigated. The EMAC model is found to successfully capture the observed temporal variability in mean ozone concentrations, as well as the contrast in the trends of 95th and 5th percentile ozone over Europe. Sensitivity simulations and statistical analysis show that a decrease in European anthropogenic emissions had contrasting effects on surface ozone trends between the 95th and 5th percentile levels and that background ozone levels have been influenced by hemispheric transport, while climate variability generally regulated the inter-annual variations of surface ozone in Europe.

An assessment of precipitation and surface air temperature over China by regional climate models

NASA Astrophysics Data System (ADS)

Wang, Xueyuan; Tang, Jianping; Niu, Xiaorui; Wang, Shuyu

2016-12-01

An analysis of a 20-year summer time simulation of present-day climate (1989-2008) over China using four regional climate models coupled with different land surface models is carried out. The climatic means, interannual variability, linear trends, and extremes are examined, with focus on precipitation and near surface air temperature. The models are able to reproduce the basic features of the observed summer mean precipitation and temperature over China and the regional detail due to topographic forcing. Overall, the model performance is better for temperature than that of precipitation. The models reasonably grasp the major anomalies and standard deviations over China and the five subregions studied. The models generally reproduce the spatial pattern of high interannual variability over wet regions, and low variability over the dry regions. The models also capture well the variable temperature gradient increase to the north by latitude. Both the observed and simulated linear trend of precipitation shows a drying tendency over the Yangtze River Basin and wetting over South China. The models capture well the relatively small temperature trends in large areas of China. The models reasonably simulate the characteristics of extreme precipitation indices of heavy rain days and heavy precipitation fraction. Most of the models also performed well in capturing both the sign and magnitude of the daily maximum and minimum temperatures over China.

Long-term hydrometeorological trends in the Midwest region based on a century long gridded hydrometeorological dataset and simulations from a macro-scale hydrology model

NASA Astrophysics Data System (ADS)

Chiu, C. M.; Hamlet, A. F.

2014-12-01

Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.

Changes toward earlier streamflow timing across western North America

USGS Publications Warehouse

Stewart, I.T.; Cayan, D.R.; Dettinger, M.D.

2005-01-01

The highly variable timing of streamflow in snowmelt-dominated basins across western North America is an important consequence, and indicator, of climate fluctuations. Changes in the timing of snowmelt-derived streamflow from 1948 to 2002 were investigated in a network of 302 western North America gauges by examining the center of mass for flow, spring pulse onset dates, and seasonal fractional flows through trend and principal component analyses. Statistical analysis of the streamflow timing measures with Pacific climate indicators identified local and key large-scale processes that govern the regionally coherent parts of the changes and their relative importance. Widespread and regionally coherent trends toward earlier onsets of springtime snowmelt and streamflow have taken place across most of western North America, affecting an area that is much larger than previously recognized. These timing changes have resulted in increasing fractions of annual flow occurring earlier in the water year by 1-4 weeks. The immediate (or proximal) forcings for the spatially coherent parts of the year-to-year fluctuations and longer-term trends of streamflow timing have been higher winter and spring temperatures. Although these temperature changes are partly controlled by the decadal-scale Pacific climate mode [Pacific decadal oscillation (PDO)], a separate and significant part of the variance is associated with a springtime warming trend that spans the PDO phases. ?? 2005 American Meteorological Society.

Trends and Projections of Climatic Extremes in the Black Volta Basin, West Africa: Towards Climate Change Adaptation.

NASA Astrophysics Data System (ADS)

Aziz, F.

2015-12-01

The water resources of the Black Volta Basin in West Africa constitute a major resource for the four countries (Burkina Faso, Ghana, Côte d'Ivoire, Mali) that share it. For Burkina Faso and Ghana, the river is the main natural resource around which the development of the diverse sectors of the two economies is built. Whereas Ghana relies heavily on the river for energy, land-locked Burkina Faso continuously develops the water for agricultural purposes. Such important role of the river makes it an element around which there are potential conflicts: either among riparian countries or within the individual countries themselves. This study documents the changes in temperature and precipitation extremes in the Black Volta Basin region for the past (1981-2010) and makes projections for the mid-late 21st century (2051-2080) under two emission scenarios; RCP 2.6 and RCP 8.5. The Expert Team on Climate Change Detection and Indices (ETCCDI) temperature- and precipitation-based indices are computed with the RClimdex software. Observed daily records and downscaled CORDEX data of precipitation and maximum and minimum temperatures are used for historical and future trend analysis respectively. In general low emission scenarios show increases in the cold extremes. The region shows a consistent pattern of trends in hot extremes for the 1990's. An increasing trend in hot extremes is expected in the future under RCP 8.5 while RCP 2.5 shows reductions in hot extremes. Regardless of the emission scenario, projections show more frequent hot nights in the 21st century. Generally, the region shows variability in trends for future extreme precipitation indices with only a few of the trends being statistically significant (5% level). Results obtained provide a basic and first step to understanding how climatic extremes have been changing in the Volta Basin region and gives an idea of what to expect in the future. Such studies will also help in making informed decisions on water management in the basin. The various water users; agriculture, household, industries will be able to prepare adequately and adapt to changes when they have information of the trends of extreme events well ahead of time.

Antarctic Climate Variability: Covariance of Ozone and Sea Ice in Atmosphere - Ocean Coupled Model Simulations

NASA Astrophysics Data System (ADS)

Jrrar, Amna; Abraham, N. Luke; Pyle, John A.; Holland, David

2014-05-01

Changes in sea ice significantly modulate climate change because of its high reflective and insulating nature. While Arctic Sea Ice Extent (SIE) shows a negative trend. Antarctic SIE shows a weak but positive trend, estimated at 0.127 x 106 km2 per decade. The trend results from large regional cancellations, more ice in the Weddell and the Ross seas, and less ice in the Amundsen - Bellingshausen seas. A number of studies had demonstrated that stratospheric ozone depletion has had a major impact on the atmospheric circulation, causing a positive trend in the Southern Annular Mode (SAM), which has been linked to the observed positive trend in autumn sea ice in the Ross Sea. However, other modelling studies show that models forced with prescribed ozone hole simulate decreased sea ice in all regions comparative to a control run. A recent study has also shown that stratospheric ozone recovery will mitigate Antarctic sea ice loss. To verify this assumed relationship, it is important first to investigate the covariance between ozone's natural (dynamical) variability and Antarctic sea ice distribution in pre-industrial climate, to estimate the trend due to natural variability. We investigate the relationship between anomalous Antarctic ozone years and the subsequent changes in Antarctic sea ice distribution in a multidecadal control simulation using the AO-UMUKCA model. The model has a horizontal resolution of 3.75 X 2.5 degrees in longitude and latitude; and 60 hybrid height levels in the vertical, from the surface up to a height of 84 km. The ocean component is the NEMO ocean model on the ORCA2 tripolar grid, and the sea ice model is CICE. We evaluate the model's performance in terms of sea ice distribution, and we calculate sea ice extent trends for composites of anomalously low versus anomalously high SH polar ozone column. We apply EOF analysis to the seasonal anomalies of sea ice concentration, MSLP, and Z 500, and identify the leading climate modes controlling the variability of Antarctic sea ice in each case, and study their relationship with SH polar ozone column.

Future changes over the Himalayas: Maximum and minimum temperature

NASA Astrophysics Data System (ADS)

Dimri, A. P.; Kumar, D.; Choudhary, A.; Maharana, P.

2018-03-01

An assessment of the projection of minimum and maximum air temperature over the Indian Himalayan region (IHR) from the COordinated Regional Climate Downscaling EXperiment- South Asia (hereafter, CORDEX-SA) regional climate model (RCM) experiments have been carried out under two different Representative Concentration Pathway (RCP) scenarios. The major aim of this study is to assess the probable future changes in the minimum and maximum climatology and its long-term trend under different RCPs along with the elevation dependent warming over the IHR. A number of statistical analysis such as changes in mean climatology, long-term spatial trend and probability distribution function are carried out to detect the signals of changes in climate. The study also tries to quantify the uncertainties associated with different model experiments and their ensemble in space, time and for different seasons. The model experiments and their ensemble show prominent cold bias over Himalayas for present climate. However, statistically significant higher warming rate (0.23-0.52 °C/decade) for both minimum and maximum air temperature (Tmin and Tmax) is observed for all the seasons under both RCPs. The rate of warming intensifies with the increase in the radiative forcing under a range of greenhouse gas scenarios starting from RCP4.5 to RCP8.5. In addition to this, a wide range of spatial variability and disagreements in the magnitude of trend between different models describes the uncertainty associated with the model projections and scenarios. The projected rate of increase of Tmin may destabilize the snow formation at the higher altitudes in the northern and western parts of Himalayan region, while rising trend of Tmax over southern flank may effectively melt more snow cover. Such combined effect of rising trend of Tmin and Tmax may pose a potential threat to the glacial deposits. The overall trend of Diurnal temperature range (DTR) portrays increasing trend across entire area with highest magnitude under RCP8.5. This higher rate of increase is imparted from the predominant rise of Tmax as compared to Tmin.

Threat to future global food security from climate change and ozone air pollution

NASA Astrophysics Data System (ADS)

Tai, Amos P. K.; Martin, Maria Val; Heald, Colette L.

2014-09-01

Future food production is highly vulnerable to both climate change and air pollution with implications for global food security. Climate change adaptation and ozone regulation have been identified as important strategies to safeguard food production, but little is known about how climate and ozone pollution interact to affect agriculture, nor the relative effectiveness of these two strategies for different crops and regions. Here we present an integrated analysis of the individual and combined effects of 2000-2050 climate change and ozone trends on the production of four major crops (wheat, rice, maize and soybean) worldwide based on historical observations and model projections, specifically accounting for ozone-temperature co-variation. The projections exclude the effect of rising CO2, which has complex and potentially offsetting impacts on global food supply. We show that warming reduces global crop production by >10% by 2050 with a potential to substantially worsen global malnutrition in all scenarios considered. Ozone trends either exacerbate or offset a substantial fraction of climate impacts depending on the scenario, suggesting the importance of air quality management in agricultural planning. Furthermore, we find that depending on region some crops are primarily sensitive to either ozone (for example, wheat) or heat (for example, maize) alone, providing a measure of relative benefits of climate adaptation versus ozone regulation for food security in different regions.

Do climate model predictions agree with long-term precipitation trends in the arid southwestern United States?

USDA-ARS?s Scientific Manuscript database

Researchers evaluating climate projections across southwestern North America observed a decreasing precipitation trend. Aridification was most pronounced in the cold (non-monsoonal) season, whereas downward trends in precipitation were smaller in the warm (monsoonal) season. In this region, based up...

Consistent response of bird populations to climate change on two continents.

PubMed

Stephens, Philip A; Mason, Lucy R; Green, Rhys E; Gregory, Richard D; Sauer, John R; Alison, Jamie; Aunins, Ainars; Brotons, Lluís; Butchart, Stuart H M; Campedelli, Tommaso; Chodkiewicz, Tomasz; Chylarecki, Przemysław; Crowe, Olivia; Elts, Jaanus; Escandell, Virginia; Foppen, Ruud P B; Heldbjerg, Henning; Herrando, Sergi; Husby, Magne; Jiguet, Frédéric; Lehikoinen, Aleksi; Lindström, Åke; Noble, David G; Paquet, Jean-Yves; Reif, Jiri; Sattler, Thomas; Szép, Tibor; Teufelbauer, Norbert; Trautmann, Sven; van Strien, Arco J; van Turnhout, Chris A M; Vorisek, Petr; Willis, Stephen G

2016-04-01

Global climate change is a major threat to biodiversity. Large-scale analyses have generally focused on the impacts of climate change on the geographic ranges of species and on phenology, the timing of ecological phenomena. We used long-term monitoring of the abundance of breeding birds across Europe and the United States to produce, for both regions, composite population indices for two groups of species: those for which climate suitability has been either improving or declining since 1980. The ratio of these composite indices, the climate impact indicator (CII), reflects the divergent fates of species favored or disadvantaged by climate change. The trend in CII is positive and similar in the two regions. On both continents, interspecific and spatial variation in population abundance trends are well predicted by climate suitability trends. Copyright © 2016, American Association for the Advancement of Science.

Climate Trend Detection using Sea-Surface Temperature Data-sets from the (A)ATSR and AVHRR Space Sensors.

NASA Astrophysics Data System (ADS)

Llewellyn-Jones, D. T.; Corlett, G. K.; Remedios, J. J.; Noyes, E. J.; Good, S. A.

2007-05-01

Sea-Surface Temperature (SST) is an important indicator of global change, designated by GCOS as an essential Climate Variable (ECV). The detection of trends in Global SST requires rigorous measurements that are not only global, but also highly accurate and consistent. Space instruments can provide the means to achieve these required attributes in SST data. This paper presents an analysis of 15 years of SST data from two independent data sets, generated from the (A)ATSR and AVHRR series of sensors respectively. The analyses reveal trends of increasing global temperature between 0.13°C to 0.18 °C, per decade, closely matching that expected from some current predictions. A high level of consistency in the results from the two independent observing systems is seen, which gives increased confidence in data from both systems and also enables comparative analyses of the accuracy and stability of both data sets to be carried out. The conclusion is that these satellite SST data-sets provide important means to quantify and explore the processes of climate change. An analysis based upon singular value decomposition, allowing the removal of gross transitory disturbances, notably the El Niño, in order to examine regional areas of change other than the tropical Pacific, is also presented. Interestingly, although El Niño events clearly affect SST globally, they are found to have a non- significant (within error) effect on the calculated trends, which changed by only 0.01 K/decade when the pattern of El Niño and the associated variations was removed from the SST record. Although similar global trends were calculated for these two independent data sets, larger regional differences are noted. Evidence of decreased temperatures after the eruption of Mount Pinatubo in 1991 was also observed. The methodology demonstrated here can be applied to other data-sets, which cover long time-series observations of geophysical observations in order to characterise long-term change.

Changing stream temperatures in a changing world: evaluating spatio-temporal patterns and trends across the eastern US

NASA Astrophysics Data System (ADS)

Kelleher, C.; Archfield, S. A.

2016-12-01

Stream temperatures drive biogeochemical processes and influence ecosystem health and extent, with patterns of stream temperature arising from complex interactions between climate, land cover, and in-stream diversions and dams. While each of these individual drivers may have well-understood implications for changing stream temperatures, considering the concomitant impacts of these drivers along the stream network is much more difficult. This is true especially for the eastern United States, where downstream temperature integrates many different upstream impacts. To begin to decipher the influence of these different drivers on changing stream temperatures and how these impacts may manifest through time, we examined trends for 66 sites with continuous stream temperature measurements across the eastern United States. Stream temperature records were summarized as daily mean, maximum, and mimimum values, and sites consisting of 15 or more years of data were selected for analysis. While annual stream temperatures at 53 locations were warming, a few sites on larger rivers (n = 13) have been cooling. To explore the timing of these changes as well as their implications for aquatic species, we calculated trends for seasonal extremes (average of the five warmest and coolest daily stream temperatures) during spring, summer, and fall. Interestingly, while some streams displayed strong warming trends in peak summer temperatures (n = 43), many streams also displayed cooling trends (n = 23). We also found that peak stream temperatures were warming faster in fall than in summer for many locations (n = 36). Results of this analysis show that warming (and cooling) happens at different times in different places, as a function of climate and anthropogenic impacts. Finally, we explore potential drivers of these different patterns, to determine the relative impacts of climate, land cover, and in-stream water diversions on stream temperature change. Given that the number of regulated stream miles is only increasing, improving our understanding of linkages between landscape drivers and stream temperature variation may have important outcomes for river management in a changing world.

Sediment load trends in the Magdalena River basin (1980-2010): Anthropogenic and climate-induced causes

NASA Astrophysics Data System (ADS)

Restrepo, Juan D.; Escobar, Heber A.

2018-02-01

The Colombian Andes and its main river basin, the Magdalena, have witnessed dramatic changes in land cover and further forest loss during the last three decades. For the Magdalena River, human activities appear to have played a more prominent role compared to rainfall (climate change) to mobilize sediment. However, environmental authorities in Colombia argue that climate change is the main trigger of erosion and floods experienced during the last decade. Here we present the first regional exercise addressing the following: (1) what are the observed trends of sediment load in the northern Andes during the last three decades? and (2) are sediment load trends in agreement with tendencies in land use change and climate (e.g., precipitation)? We perform Mann-Kendall tests on sediment load series for 21 main tributary systems during the 1980-2010 period. These gauging stations represent 77% of the whole Magdalena basin area. The last decade has been a period of increased pulses in sediment transport as seen by the statistical significant trends in load. Overall, six subcatchments, representing 55% of the analyzed Magdalena basin area, have witnessed increasing trends in sediment load. Also, some major tributaries have experienced changes in their interannual mean sediment flux during the mid- 1990s and 2005. Further analysis of land cover change (e.g., deforestation) indicates that the basin has undergone considerable change. Forest cover decreased by 40% over the period of study, while the area under agriculture and pasture cover (agricultural lands 1 and 2) increased by 65%. The highest peak of forest loss on record in the Magdalena basin, 5106 km2 or 24% of the combined deforestation in Colombia, occurred during the 2005-2010 period. In contrast, Mann-Kendall tests on rainfall series for 61 stations reveal that precipitation shows no regional signs of increasing trends. Also, increasing trends in sediment load match quite well with the marked increase in forest clearance during the 1990-2000 and 2005-2010 periods. Such signs of increasing sediment fluxes should not be attributed to climate change and rainfall variability alone. As a whole, the Magdalena, one of the top 10 rivers in terms of sediment delivery to the ocean (184 Mt y- 1), and its tributaries have experienced increasing trends in sediment load during the 1980-2010 period; increases in close agreement with trends in land use change and deforestation. During the last decade, the Magdalena River drainage basin has witnessed an increase in erosion rates of 34%, from 550 t km- 2 y- 1 before 2000 to 710 t km- 2 y- 1 for the 2000-2010 period, and the average sediment load for the whole basin increased to 44 Mt y- 1 for the same period. Similar to the global picture of human contribution to sediment generation, the rate of anthropogenic soil erosion in the Magdalena basin probably exceeds the rate of climate-driven erosion by several orders of magnitude.

Land use/land cover change effects on temperature trends at U.S. Climate Normals stations

USGS Publications Warehouse

Hale, R.C.; Gallo, K.P.; Owen, T.W.; Loveland, Thomas R.

2006-01-01

Alterations in land use/land cover (LULC) in areas near meteorological observation stations can influence the measurement of climatological variables such as temperature. Urbanization near climate stations has been the focus of considerable research attention, however conversions between non-urban LULC classes may also have an impact. In this study, trends of minimum, maximum, and average temperature at 366 U.S. Climate Normals stations are analyzed based on changes in LULC defined by the U.S. Land Cover Trends Project. Results indicate relatively few significant temperature trends before periods of greatest LULC change, and these are generally evenly divided between warming and cooling trends. In contrast, after the period of greatest LULC change was observed, 95% of the stations that exhibited significant trends (minimum, maximum, or mean temperature) displayed warming trends. Copyriht 2006 by the American Geophysical Union.

Detection and attribution of climate change at regional scale: case study of Karkheh river basin in the west of Iran

NASA Astrophysics Data System (ADS)

Zohrabi, Narges; Goodarzi, Elahe; Massah Bavani, Alireza; Najafi, Husain

2017-11-01

This research aims at providing a statistical framework for detection and attribution of climate variability and change at regional scale when at least 30 years of observation data are available. While extensive research has been done on detecting significant observed trends in hydroclimate variables and attribution to anthropogenic greenhouse gas emissions in large continents, less attention has been paid for regional scale analysis. The latter is mainly important for adaptation to climate change in different sectors including but not limited to energy, agriculture, and water resources planning and management, and it is still an open discussion in many countries including the West Asian ones. In the absence of regional climate models, an informative framework is suggested providing useful insights for policymakers. It benefits from general flexibility, not being computationally expensive, and applying several trend tests to analyze temporal variations in temperature and precipitation (gradual and step changes). The framework is implemented for a very important river basin in the west of Iran. In general, some increasing and decreasing trends of the interannual precipitation and temperature have been detected. For precipitation annual time series, a reducing step was seen around 1996 compared with the gradual change in most of the stations, which have not experience a dramatical change. The range of natural forcing is found to be ±76 % for precipitation and ±1.4 °C for temperature considering a two-dimensional diagram of precipitation and temperature anomalies from 1000-year control run of global climate model (GCM). Findings out of applying the proposed framework may provide useful insights into how to approach structural and non-structural climate change adaptation strategies from central governments.

To what extent does climate explain variations in reported malaria cases in early 20th century Uganda?

PubMed

Tompkins, Adrian M; Larsen, Laragh; McCreesh, Nicky; Taylor, David

2016-03-31

Malaria case statistics were analysed for the period 1926 to 1960 to identify inter-annual variations in malaria cases for the Uganda Protectorate. The analysis shows the mid-to-late 1930s to be a period of increased reported cases. After World War II, malaria cases trend down to a relative minimum in the early 1950s, before increasing rapidly after 1953 to the end of the decade. Data for the Western Province confirm these national trends, which at the time were attributed to a wide range of causes, including land development and management schemes, population mobility, interventions and misdiagnosis. Climate was occasionally proposed as a contributor to enhanced case numbers, and unusual precipitation patterns were held responsible; temperature was rarely, if ever, considered. In this study, a dynamical malaria model was driven with available precipitation and temperature data from the period for five stations located across a range of environments in Uganda. In line with the historical data, the simulations produced relatively enhanced transmission in the 1930s, although there is considerable variability between locations. In all locations, malaria transmission was low in the late 1940s and early 1950s, steeply increasing after 1954. Results indicate that past climate variability explains some of the variations in numbers of reported malaria cases. The impact of multiannual variability in temperature, while only on the order of 0.5°C, was sufficient to drive some of the trends observed in the statistics and thus the role of climate was likely underestimated in the contemporary reports. As the elimination campaigns of the 1960s followed this partly climate-driven increase in malaria, this emphasises the need to account for climate when planning and evaluating intervention strategies.

Canadian boreal forest greening and browning trends: an analysis of biogeographic patterns and the relative roles of disturbance versus climate drivers

NASA Astrophysics Data System (ADS)

Sulla-Menashe, Damien; Woodcock, Curtis E.; Friedl, Mark A.

2018-01-01

Recent studies have used satellite-derived normalized difference vegetation index (NDVI) time series to explore geographic patterns in boreal forest greening and browning. A number of these studies indicate that boreal forests are experiencing widespread browning, and have suggested that these patterns reflect decreases in forest productivity induced by climate change. Here we use NDVI time series from Landsat, which has much higher quality and spatial resolution than imagery used in most previous studies, to characterize biogeographic patterns in greening and browning across Canada’s boreal forest and to explore the drivers behind observed trends. Our results show that the majority of NDVI changes in Canada’s boreal forest reflect disturbance-recovery dynamics not climate change impacts, that greening and browning trends outside of disturbed forests are consistent with expected ecological responses to regional changes in climate, and that observed NDVI changes are geographically limited and relatively small in magnitude. By examining covariance between changes in NDVI and temperature and precipitation in locations not affected by disturbance, our results isolate and characterize the nature and magnitude of greening and browning directly associated with climate change. Consistent with biogeographic theory, greening and browning unrelated to disturbance tended to be located in ecotones near boundaries of the boreal forest bioclimatic envelope. We observed greening to be most prevalent in Eastern Canada, which is more humid, and browning to be most prevalent in Western Canada, where forests are more prone to moisture stress. We conclude that continued long-term climate change has the potential to significantly alter the character and function of Canada’s boreal forest, but recent changes have been modest and near-term impacts are likely to be focused in or near ecotones.

Risk of spring frost to apple production under future climate scenarios: the role of phenological acclimation.

PubMed

Eccel, Emanuele; Rea, Roberto; Caffarra, Amelia; Crisci, Alfonso

2009-05-01

In the context of global warming, the general trend towards earlier flowering dates of many temperate tree species is likely to result in an increased risk of damage from exposure to frost. To test this hypothesis, a phenological model of apple flowering was applied to a temperature series from two locations in an important area for apple production in Europe (Trentino, Italy). Two simulated 50-year climatic projections (A2 and B2 of the Intergovernmental Panel on Climate Change--Special Report on Emission Scenarios) from the HadCM3 general circulation model were statistically downscaled to the two sites. Hourly temperature records over a 40-year period were used as the reference for past climate. In the phenological model, the heat requirement (degree hours) for flowering was parameterized using two approaches; static (constant over time) and dynamic (climate dependent). Parameterisation took into account the trees' adaptation to changing temperatures based on either past instrumental records or the downscaled outputs from the climatic simulations. Flowering dates for the past 40 years and simulated flowering dates for the next 50 years were used in the model. A significant trend towards earlier flowering was clearly detected in the past. This negative trend was also apparent in the simulated data. However, the significance was less apparent when the "dynamic" setting for the degree hours requirement was used in the model. The number of frost episodes and flowering dates, on an annual basis, were graphed to assess the risk of spring frost. Risk analysis confirmed a lower risk of exposure to frost at present than in the past, and probably either constant or a slightly lower risk in future, especially given that physiological processes are expected to acclimate to higher temperatures.

Large-Scale Changes in Community Composition: Determining Land Use and Climate Change Signals

PubMed Central

Kampichler, Christian; van Turnhout, Chris A. M.; Devictor, Vincent; van der Jeugd, Henk P.

2012-01-01

Human land use and climate change are regarded as the main driving forces of present-day and future species extinction. They may potentially lead to a profound reorganisation of the composition and structure of natural communities throughout the world. However, studies that explicitly investigate both forms of impact—land use and climate change—are uncommon. Here, we quantify community change of Dutch breeding bird communities over the past 25 years using time lag analysis. We evaluate the chronological sequence of the community temperature index (CTI) which reflects community response to temperature increase (increasing CTI indicates an increase in relative abundance of more southerly species), and the temporal trend of the community specialisation index (CSI) which reflects community response to land use change (declining CSI indicates an increase of generalist species). We show that the breeding bird fauna underwent distinct directional change accompanied by significant changes both in CTI and CSI which suggests a causal connection between climate and land use change and bird community change. The assemblages of particular breeding habitats neither changed at the same speed and nor were they equally affected by climate versus land use changes. In the rapidly changing farmland community, CTI and CSI both declined slightly. In contrast, CTI increased in the more slowly changing forest and heath communities, while CSI remained stable. Coastal assemblages experienced both an increase in CTI and a decline in CSI. Wetland birds experienced the fastest community change of all breeding habitat assemblages but neither CTI nor CSI showed a significant trend. Overall, our results suggest that the interaction between climate and land use changes differs between habitats, and that comparing trends in CSI and CTI may be useful in tracking the impact of each determinant. PMID:22523579

Large-scale changes in community composition: determining land use and climate change signals.

PubMed

Kampichler, Christian; van Turnhout, Chris A M; Devictor, Vincent; van der Jeugd, Henk P

2012-01-01

Human land use and climate change are regarded as the main driving forces of present-day and future species extinction. They may potentially lead to a profound reorganisation of the composition and structure of natural communities throughout the world. However, studies that explicitly investigate both forms of impact--land use and climate change--are uncommon. Here, we quantify community change of Dutch breeding bird communities over the past 25 years using time lag analysis. We evaluate the chronological sequence of the community temperature index (CTI) which reflects community response to temperature increase (increasing CTI indicates an increase in relative abundance of more southerly species), and the temporal trend of the community specialisation index (CSI) which reflects community response to land use change (declining CSI indicates an increase of generalist species). We show that the breeding bird fauna underwent distinct directional change accompanied by significant changes both in CTI and CSI which suggests a causal connection between climate and land use change and bird community change. The assemblages of particular breeding habitats neither changed at the same speed and nor were they equally affected by climate versus land use changes. In the rapidly changing farmland community, CTI and CSI both declined slightly. In contrast, CTI increased in the more slowly changing forest and heath communities, while CSI remained stable. Coastal assemblages experienced both an increase in CTI and a decline in CSI. Wetland birds experienced the fastest community change of all breeding habitat assemblages but neither CTI nor CSI showed a significant trend. Overall, our results suggest that the interaction between climate and land use changes differs between habitats, and that comparing trends in CSI and CTI may be useful in tracking the impact of each determinant.

Management and climate contributions to satellite-derived active fire trends in the contiguous United States

PubMed Central

Lin, Hsiao-Wen; McCarty, Jessica L; Wang, Dongdong; Rogers, Brendan M; Morton, Douglas C; Collatz, G James; Jin, Yufang; Randerson, James T

2014-01-01

Fires in croplands, plantations, and rangelands contribute significantly to fire emissions in the United States, yet are often overshadowed by wildland fires in efforts to develop inventories or estimate responses to climate change. Here we quantified decadal trends, interannual variability, and seasonality of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of active fires (thermal anomalies) as a function of management type in the contiguous U.S. during 2001–2010. We used the Monitoring Trends in Burn Severity database to identify active fires within the perimeter of large wildland fires and land cover maps to identify active fires in croplands. A third class of fires defined as prescribed/other included all residual satellite active fire detections. Large wildland fires were the most variable of all three fire types and had no significant annual trend in the contiguous U.S. during 2001–2010. Active fires in croplands, in contrast, increased at a rate of 3.4% per year. Cropland and prescribed/other fire types combined were responsible for 77% of the total active fire detections within the U.S and were most abundant in the south and southeast. In the west, cropland active fires decreased at a rate of 5.9% per year, likely in response to intensive air quality policies. Potential evaporation was a dominant regulator of the interannual variability of large wildland fires, but had a weaker influence on the other two fire types. Our analysis suggests it may be possible to modify landscape fire emissions within the U.S. by influencing the way fires are used in managed ecosystems. Key Points Wildland, cropland, and prescribed fires had different trends and patterns Sensitivity to climate varied with fire type Intensity of air quality regulation influenced cropland burning trends PMID:26213662

Management and climate contributions to satellite-derived active fire trends in the contiguous United States.

PubMed

Lin, Hsiao-Wen; McCarty, Jessica L; Wang, Dongdong; Rogers, Brendan M; Morton, Douglas C; Collatz, G James; Jin, Yufang; Randerson, James T

2014-04-01

Fires in croplands, plantations, and rangelands contribute significantly to fire emissions in the United States, yet are often overshadowed by wildland fires in efforts to develop inventories or estimate responses to climate change. Here we quantified decadal trends, interannual variability, and seasonality of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of active fires (thermal anomalies) as a function of management type in the contiguous U.S. during 2001-2010. We used the Monitoring Trends in Burn Severity database to identify active fires within the perimeter of large wildland fires and land cover maps to identify active fires in croplands. A third class of fires defined as prescribed/other included all residual satellite active fire detections. Large wildland fires were the most variable of all three fire types and had no significant annual trend in the contiguous U.S. during 2001-2010. Active fires in croplands, in contrast, increased at a rate of 3.4% per year. Cropland and prescribed/other fire types combined were responsible for 77% of the total active fire detections within the U.S and were most abundant in the south and southeast. In the west, cropland active fires decreased at a rate of 5.9% per year, likely in response to intensive air quality policies. Potential evaporation was a dominant regulator of the interannual variability of large wildland fires, but had a weaker influence on the other two fire types. Our analysis suggests it may be possible to modify landscape fire emissions within the U.S. by influencing the way fires are used in managed ecosystems. Wildland, cropland, and prescribed fires had different trends and patternsSensitivity to climate varied with fire typeIntensity of air quality regulation influenced cropland burning trends.

21st Century Trends in the Potential for Ozone Depletion

NASA Astrophysics Data System (ADS)

Hurwitz, M. M.; Newman, P. A.

2009-05-01

We find robust trends in the area where Antarctic stratospheric temperatures are below the threshold for polar stratospheric cloud (PSC) formation in Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) simulations of the 21st century. In late winter (September-October-November), cold area trends are consistent with the respective trends in equivalent effective stratospheric chlorine (EESC), i.e. negative cold area trends in 'realistic future' simulations where EESC decreases and the ozone layer recovers. In the early winter (April through June), regardless of EESC scenario, we find an increasing cold area trend in all simulations; multiple linear regression analysis shows that this early winter cooling trend is associated with the predicted increase in greenhouse gas concentrations in the future. We compare the seasonality of the potential for Antarctic ozone depletion in two versions of the GEOS CCM and assess the impact of the above-mentioned cold area trends on polar stratospheric chemistry.

An effective drift correction for dynamical downscaling of decadal global climate predictions

NASA Astrophysics Data System (ADS)

Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

2018-04-01

Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

Trends in Global Vegetation Activity and Climatic Drivers Indicate a Decoupled Response to Climate Change

PubMed Central

Schut, Antonius G. T.; Ivits, Eva; Conijn, Jacob G.; ten Brink, Ben; Fensholt, Rasmus

2015-01-01

Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982–2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP) and TBW per biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBW trends and monotonic negative or segmented and negative NDVI trends, was observed for 17–36% of all productive areas depending on the NDVI metric used. For only 1–2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity. PMID:26466347

Extreme Flood Events Over the Past 300 Years Recorded in the Sediments of a Mountain Lake in the Altay Mountains, Northwestern China

NASA Astrophysics Data System (ADS)

Wu, J.; Zhou, J.; Shen, B.; Zeng, H.

2017-12-01

Global climate change has the potential to accelerate the hydrological cycle, which may further enhance the temporal frequency of regional extreme floods. Climatic models predict that intra-annual rainfall variability will intensify, which will shift current rainfall regimes towards more extreme systems with lower precipitation frequencies, longer dry periods, and larger individual precipitation events worldwide. Understanding the temporal variations of extreme floods that occur in response to climate change is essential to anticipate the trends in flood magnitude and frequency in the context of global warming. However, currently available instrumental data are not long enough for capturing the most extreme events, thus the acquisition of long duration datasets for historical floods that extend beyond available instrumental records is clearly an important step in discerning trends in flood frequency and magnitude with respect to climate change. In this study, a reconstruction of paleofloods over the past 300 years was conducted through an analysis of grain sizes from the sediments of Kanas Lake in the Altay Mountains of northwestern China. Grain parameters and frequency distributions both demonstrate that two abrupt environment changes exist within the lake sedimentary sequence. Based on canonical discriminant analysis (CDA) and C-M pattern analysis, two flood events corresponding to ca. 1760 AD and ca. 1890 AD were identified, both of which occurred during warmer and wetter climate conditions according to tree-ring records. These two flood events are also evidenced by lake sedimentary records in the Altay and Tianshan areas. Furthermore, through a comparison with other records, the flood event in ca. 1760 AD seems to have occurred in both the arid central Asia and the Alps in Europe, and thus may have been associated with changes in the North Atlantic Oscillation (NAO) index.

Land Use and Environmental Variability Impacts on the Phenology of Arid Agro-Ecosystems.

PubMed

Romo-Leon, Jose Raul; van Leeuwen, Willem J D; Castellanos-Villegas, Alejandro

2016-02-01

The overexploitation of water resources in arid environments often results in abandonment of large extensions of agricultural lands, which may (1) modify phenological trends, and (2) alter the sensitivity of specific phenophases to environmental triggers. In Mexico, current governmental policies subsidize restoration efforts, to address ecological degradation caused by abandonments; however, there is a need for new approaches to assess their effectiveness. Addressing this, we explore a method to monitor and assess (1) land surface phenology trends in arid agro-ecosystems, and (2) the effect of climatic factors and restoration treatments on the phenology of abandoned agricultural fields. We used 16-day normalized difference vegetation index composites from the moderate resolution imaging spectroradiometer from 2000 to 2009 to derive seasonal phenometrics. We then derived phenoclimatic variables and land cover thematic maps, to serve as a set of independent factors that influence vegetation phenology. We conducted a multivariate analysis of variance to analyze phenological trends among land cover types, and developed multiple linear regression models to assess influential climatic factors driving phenology per land cover analyzed. Our results suggest that the start and length of the growing season had different responses to environmental factors depending on land cover type. Our analysis also suggests possible establishment of arid adapted species (from surrounding ecosystems) in abandoned fields with longer times since abandonment. Using this approach, we were able increase our understanding on how climatic factors influence phenology on degraded arid agro-ecosystems, and how this systems evolve after disturbance.

The paradox of cooling streams in a warming world: Regional climate trends do not parallel variable local trends in stream temperature in the Pacific continental United States

USGS Publications Warehouse

Arismendi, Ivan; Johnson, Sherri; Dunham, Jason B.; Haggerty, Roy; Hockman-Wert, David

2012-01-01

Temperature is a fundamentally important driver of ecosystem processes in streams. Recent warming of terrestrial climates around the globe has motivated concern about consequent increases in stream temperature. More specifically, observed trends of increasing air temperature and declining stream flow are widely believed to result in corresponding increases in stream temperature. Here, we examined the evidence for this using long-term stream temperature data from minimally and highly human-impacted sites located across the Pacific continental United States. Based on hypothesized climate impacts, we predicted that we should find warming trends in the maximum, mean and minimum temperatures, as well as increasing variability over time. These predictions were not fully realized. Warming trends were most prevalent in a small subset of locations with longer time series beginning in the 1950s. More recent series of observations (1987-2009) exhibited fewer warming trends and more cooling trends in both minimally and highly human-influenced systems. Trends in variability were much less evident, regardless of the length of time series. Based on these findings, we conclude that our perspective of climate impacts on stream temperatures is clouded considerably by a lack of long-termdata on minimally impacted streams, and biased spatio-temporal representation of existing time series. Overall our results highlight the need to develop more mechanistic, process-based understanding of linkages between climate change, other human impacts and stream temperature, and to deploy sensor networks that will provide better information on trends in stream temperatures in the future.

Variations in northern hemisphere snowfall: An analysis of historical trends and the projected response to anthropogenic forcing in the twenty-first century

NASA Astrophysics Data System (ADS)

Krasting, John P.

Snowfall is an important feature of the Earth's climate system that has the ability to influence both the natural world and human activity. This dissertation examines past and future changes in snowfall related to increasing concentrations of anthropogenic greenhouse gases. Snowfall observations for North America, derived snowfall products for the Northern Hemisphere, and simulations performed with 13 coupled atmosphere-ocean global climate models are analyzed. The analysis of the spatial pattern of simulated annual trends on a grid point basis from 1951 to 1999 indicates that a transition zone exists above 60° N latitude across the Northern Hemisphere that separates negative trends in annual snowfall in the mid-latitudes and positive trends at higher latitudes. Regional analysis of observed annual snowfall indicates that statistically significant trends are found in western North America, Japan, and southern Russia. A majority of the observed historical trends in annual snowfall elsewhere in the Northern Hemisphere, however, are not statistically significant and this result is consistent with model simulations. Projections of future snowfall indicate the presence of a similar transition zone between negative and positive snowfall trends that corresponds with the area between the -10 to -15°C isotherms of the multi-model mean temperature of the late twentieth century in each of the fall, winter, and spring seasons. Redistributions of snowfall throughout the entire snow season are likely -- even in locations where there is little change in annual snowfall. Changes in the fraction of precipitation falling as snow contribute to decreases in snowfall across most Northern Hemisphere regions, while changes in precipitation typically contribute to increases in snowfall. Snowfall events less than or equal to 5 cm are found to decrease in the future across most of the Northern Hemisphere, while snowfall events greater than or equal to 20 cm increase in some locations, such as northern Quebec. A signal-to-noise analysis reveals that the projected changes in snowfall are likely to become apparent during the twenty-first century for most locations in the Northern Hemisphere.

Unidirectional trends in annual and seasonal climate and extremes in Egypt

NASA Astrophysics Data System (ADS)

Nashwan, Mohamed Salem; Shahid, Shamsuddin; Abd Rahim, Norhan

2018-05-01

The presence of short- and long-term autocorrelations can lead to considerable change in significance of trend in hydro-climatic time series. Therefore, past findings of climatic trend studies that did not consider autocorrelations became a questionable issue. The spatial patterns in the trends of annual and seasonal temperature, rainfall, and related extremes in Egypt have been assessed in this paper using modified Mann-Kendal (MMK) trend test which can detect unidirectional trends in time series in the presence of short- and long-term autocorrelations. The trends obtained using the MMK test was compared with that obtained using standard Mann-Kendall (MK) test to show how natural variability in climate affects the trends. The daily rainfall and temperature data of Princeton Global Meteorological Forcing for the period 1948-2010 having a spatial resolution of 0.25° × 0.25° was used for this purpose. The results showed a large difference between the trends obtained using MMK and MK tests. The MMK test showed increasing trends in temperature and a number of temperature extremes in Egypt, but almost no change in rainfall and rainfall extremes. The minimum temperature was found to increase (0.08-0.29 °C/decade) much faster compared to maximum temperature (0.07-0.24 °C/decade) and therefore, a decrease in diurnal temperature range (- 0.01 to - 0.16 °C/decade) in most part of Egypt. The number of winter hot days and nights are increasing, while the number of cold days is decreasing in most part of the country. The study provides a more realistic scenario of the changes in climate and weather extremes of Egypt.

Identify temporal trend of air temperature and its impact on forest stream flow in Lower Mississippi River Alluvial Valley using wavelet analysis

USDA-ARS?s Scientific Manuscript database

Characterization of stream flow is essential to water resource management, water supply planning, environmental protection, and ecological restoration; while climate change can exacerbate stream flow and add instability to the flow. In this study, the wavelet analysis technique was employed to asse...

Climate change trends, grape production, and potential alcohol concentration in wine from the "Romagna Sangiovese" appellation area (Italy)

NASA Astrophysics Data System (ADS)

Teslić, Nemanja; Zinzani, Giordano; Parpinello, Giuseppina P.; Versari, Andrea

2018-01-01

The trend of climate change and its effect on grape production and wine composition was evaluated using a real case study of seven wineries located in the "Romagna Sangiovese" appellation area (northern Italy), one of the most important wine producing region of Italy. This preliminary study focused on three key aspects: (i) Assessment of climate change trends by calculating bioclimatic indices over the last 61 years (from 1953 to 2013) in the Romagna Sangiovese area: significant increasing trends were found for the maximum, mean, and minimum daily temperatures, while a decreasing trend was found for precipitation during the growing season period (April-October). Mean growing season temperature was 18.49 °C, considered as warm days in the Romagna Sangiovese area and optimal for vegetative growth of Sangiovese, while nights during the ripening months were cold (13.66 °C). The rise of temperature shifted studied area from the temperate/warm temperate to the warm temperate-/warm grape-growing region (according to the Huglin classification). (ii) Relation between the potential alcohol content from seven wineries and the climate change from 2001 to 2012: dry spell index (DSI) and Huglin index (HI) suggested a large contribution to increasing level of potential alcohol in Sangiovese wines, whereas DSI showed higher correlation with potential alcohol respect to the HI. (iii) Relation between grape production and the climate change from 1982 to 2012: a significant increasing trend was found with little effect of the climate change trends estimated with used bioclimatic indices. Practical implication at viticultural and oenological levels is discussed.

Prevailing climatic trends and runoff response from Hindukush-Karakoram-Himalaya, upper Indus basin

NASA Astrophysics Data System (ADS)

Hasson, S.; Böhner, J.; Lucarini, V.

2015-03-01

Largely depending on meltwater from the Hindukush-Karakoram-Himalaya, withdrawals from the upper Indus basin (UIB) contribute to 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, we present a comprehensive hydro-climatic trend analysis over the UIB, including for the first time observations from high-altitude automated weather stations. We analyze trends in maximum, minimum and mean temperatures (Tx, Tn, and Tavg, respectively), diurnal temperature range (DTR) 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). We apply Mann-Kendall test on serially independent time series to assess existence of a trend while true slope is estimated using Sen's slope method. Further, we statistically assess the spatial scale (field) significance of local climatic trends within ten identified sub-regions of UIB and analyze whether the spatially significant (field significant) climatic trends qualitatively agree with a trend in discharge out of corresponding sub-region. Over the recent period (1995-2012), we find a well agreed and mostly field significant cooling (warming) during monsoon season i.e. July-October (March-May and November), which is higher in magnitude relative to long term trends (1961-2012). We also find general cooling in Tx and a mixed response in Tavg during the winter season and a year round decrease in DTR, which are in direct contrast to their long term trends. The observed decrease in DTR is stronger and more significant at high altitude stations (above 2200 m a.s.l.), and mostly due to higher cooling in Tx than in Tn. Moreover, we find a field significant decrease (increase) in late-monsoonal precipitation for lower (higher) latitudinal regions of Himalayas (Karakoram and Hindukush), whereas an increase in winter precipitation for Hindukush, western- and whole Karakoram, UIB-Central, UIB-West, UIB-West-upper and whole UIB regions. We find a spring warming (field significant in March) and drying (except for Karakoram and its sub-regions), and subsequent rise in early-melt season flows. Such early melt response together with effective cooling during monsoon period subsequently resulted in a substantial drop (weaker increase) in discharge out of higher (lower) latitudinal regions (Himalaya and UIB-West-lower) during late-melt season, particularly during July. These discharge tendencies qualitatively differ to their long term trends for all regions, except for UIB-West-upper, western-Karakorum and Astore. The observed hydroclimatic trends, being driven by certain changes in the monsoonal system and westerly disturbances, indicate dominance (suppression) of nival (glacial) runoff regime, altering substantially the overall hydrology of UIB in future. These findings largely contribute to address the hydroclimatic explanation of the "Karakoram Anomaly".

Climate Risk and Vulnerability in the Caribbean and Gulf of Mexico Region: Interactions with Spatial Population and Land Cover Change

NASA Astrophysics Data System (ADS)

Chen, R. S.; Levy, M.; Baptista, S.; Adamo, S.

2010-12-01

Vulnerability to climate variability and change will depend on dynamic interactions between different aspects of climate, land-use change, and socioeconomic trends. Measurements and projections of these changes are difficult at the local scale but necessary for effective planning. New data sources and methods make it possible to assess land-use and socioeconomic changes that may affect future patterns of climate vulnerability. In this paper we report on new time series data sets that reveal trends in the spatial patterns of climate vulnerability in the Caribbean/Gulf of Mexico Region. Specifically, we examine spatial time series data for human population over the period 1990-2000, time series data on land use and land cover over 2000-2009, and infant mortality rates as a proxy for poverty for 2000-2008. We compare the spatial trends for these measures to the distribution of climate-related natural disaster risk hotspots (cyclones, floods, landslides, and droughts) in terms of frequency, mortality, and economic losses. We use these data to identify areas where climate vulnerability appears to be increasing and where it may be decreasing. Regions where trends and patterns are especially worrisome include coastal areas of Guatemala and Honduras.

Analysis of Trends in Fish Assemblages in Narragansett Bay, RI/MA

EPA Science Inventory

Estuarine fish are highly valued resources that are affected by several factors, including climate, landscape, pollution, and fishing pressure. Here, we examine patterns of variability in estuarine fish assemblages in Narragansett Bay, an estuary located in Rhode Island and Mass...

Improving the community-temperature index as a climate change indicator.

PubMed

Bowler, Diana; Böhning-Gaese, Katrin

2017-01-01

Climate change indicators are tools to assess, visualize and communicate the impacts of climate change on species and communities. Indicators that can be applied to different taxa are particularly useful because they allow comparative analysis to identify which kinds of species are being more affected. A general prediction, supported by empirical data, is that the abundance of warm-adapted species should increase over time, relative to the cool-adapted ones within communities, under increasing ambient temperatures. The community temperature index (CTI) is a community weighted mean of species' temperature preferences and has been used as an indicator to summarize this temporal shift. The CTI has the advantages of being a simple and generalizable indicator; however, a core problem is that temporal trends in the CTI may not only reflect changes in temperature. This is because species' temperature preferences often covary with other species attributes, and these other attributes may affect species response to other environmental drivers. Here, we propose a novel model-based approach that separates the effects of temperature preference from the effects of other species attributes on species' abundances and subsequently on the CTI. Using long-term population data of breeding birds in Denmark and demersal marine fish in the southeastern North Sea, we find differences in CTI trends with the original approach and our model-based approach, which may affect interpretation of climate change impacts. We suggest that our method can be used to test the robustness of CTI trends to the possible effects of other drivers of change, apart from climate change.

75 FR 43944 - Defense Science Board; Task Force on Trends and Implications of Climate Change for National and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-27

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Science Board; Task Force on Trends and Implications of Climate Change for National and International Security AGENCY: Department of Defense (DoD... and Implications of Climate Change for National and International Security will meet in closed session...

75 FR 34438 - Defense Science Board Task Force on Trends and Implications of Climate Change for National and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-17

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Science Board Task Force on Trends and Implications of Climate Change for National and International Security AGENCY: Department of Defense (DoD... and Implications of Climate Change for National and International Security will meet in closed session...

Hydrologic responses to climate change: considering geographic context and alternative hypotheses

Treesearch

J.A. Jones

2011-01-01

One of the most significant consequences of climate warming is the likely change in streamflow as a result of warming air temperatures. Hydrologists have responded to the challenge of understanding these effects. Many recent studies quantify historical trends in streamflow and usually attribute these trends to climate warming, via altered evapotranspiration and...

Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China

PubMed Central

2011-01-01

Background Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China. Methods The annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables. Results A distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (F = 446.452, P < 0.001, adjusted R2 = 0.75) than in the general multiple regression model (F = 223.670, P < 0.000, adjusted R2 = 0.51). Conclusion The temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang. PMID:22133347

Southwestern Region climate change trends and forest planning: A guide for addressing climate change in forest plan revision on southwestern National Forests and Grasslands

Treesearch

Richard Periman; Christine Dawe; Bryce Rickel; Amy Unthank; Champe Green; Roy Jemison; Kurt Nelson; Brian Kent

2009-01-01

Climate scientists agree that the earth is undergoing a warming trend, and that human-caused elevations in atmospheric concentrations of carbon dioxide (CO2) and other greenhouse gases (GHGs) are among the causes of global temperature increases. The observed concentrations of these greenhouse gases are projected to increase. Climate change may intensify the risk of...

Using Time Series of Landsat Data to Improve Understanding of Short- and Long-Term Changes to Vegetation Phenology in Response to Climate Change

NASA Astrophysics Data System (ADS)

Friedl, M. A.; Melaas, E. K.; Sulla-menashe, D. J.; Gray, J. M.

2014-12-01

Phenology, the seasonal progression of organisms through stages of dormancy, active growth, and senescence is a key regulator of ecosystem processes and is widely used as an indicator of vegetation responses to climate change. This is especially true in temperate forests, where seasonal dynamics in canopy development and senescence are tightly coupled to the climate system. Despite this, understanding of climate-phenology interactions is incomplete. A key impediment to improving this understanding is that available datasets are geographically sparse, and in most cases include relatively short time series. Remote sensing has been widely promoted as a useful tool for studies of large-scale phenology, but long-term studies from remote sensing have been limited to AVHRR data, which suffers from limitations related to its coarse spatial resolution and uncertainties in atmospheric corrections and radiometric adjustments that are used to create AVHRR time series. In this study, we used 30 years of Landsat data to quantify the nature and magnitude of long-term trends and short-term variability in the timing of spring leaf emergence and fall senescence. Our analysis focuses on temperate forest locations in the Northeastern United States that are co-located with surface meteorological observations, where we have estimated the timing of leaf emergence and leaf senescence at annual time steps using atmospherically corrected surface reflectances from Landsat TM and ETM+ imagery. Comparison of results from Landsat against ground observations demonstrates that phenological events can be reliably estimated from Landsat time series. More importantly, results from this analysis suggest two main conclusions related to the nature of climate change impacts on temperate forest phenology. First, there is clear evidence of trends towards longer growing seasons in the Landsat record. Second, interannual variability is large, with average year-to-year variability exceeding the magnitude of total changes to the growing season that have occurred over the last three decades. Based on these results we suggest that year-to-year variability in phenology, rather than long-term trends, provides the best basis for predicting future changes in temperate forest phenology in response to climate change.

Trend assessment: applications for hydrology and climate research

NASA Astrophysics Data System (ADS)

Kallache, M.; Rust, H. W.; Kropp, J.

2005-02-01

The assessment of trends in climatology and hydrology still is a matter of debate. Capturing typical properties of time series, like trends, is highly relevant for the discussion of potential impacts of global warming or flood occurrences. It provides indicators for the separation of anthropogenic signals and natural forcing factors by distinguishing between deterministic trends and stochastic variability. In this contribution river run-off data from gauges in Southern Germany are analysed regarding their trend behaviour by combining a deterministic trend component and a stochastic model part in a semi-parametric approach. In this way the trade-off between trend and autocorrelation structure can be considered explicitly. A test for a significant trend is introduced via three steps: First, a stochastic fractional ARIMA model, which is able to reproduce short-term as well as long-term correlations, is fitted to the empirical data. In a second step, wavelet analysis is used to separate the variability of small and large time-scales assuming that the trend component is part of the latter. Finally, a comparison of the overall variability to that restricted to small scales results in a test for a trend. The extraction of the large-scale behaviour by wavelet analysis provides a clue concerning the shape of the trend.

Extent of Night Warming and Spatially Heterogeneous Cloudiness Differentiate Temporal Trend of Greenness in Mountainous Tropics in the New Century

NASA Astrophysics Data System (ADS)

Yu, Mei; Gao, Qiong; Gao, Chunxiao; Wang, Chao

2017-01-01

Tropical forests have essential functions in global C dynamics but vulnerable to changes in land cover land use (LCLUC) and climate. The tropics of Caribbean are experiencing warming and drying climate and diverse LCLUC. However, large-scale studies to detect long-term trends of C and mechanisms behind are still rare. Using MODIS Enhanced Vegetation Index (EVI), we investigated greenness trend in the Greater Antilles Caribbean during 2000-2015, and analyzed trend of vegetation patches without LCLUC to give prominence to climate impacts. We hypothesized that night warming and heavy cloudiness would reduce EVI in this mountainous tropical region. Over the 15 years, EVI decreased significantly in Jamaica, Haiti, Dominican Republic, and Puerto Rico, but increased in Cuba partly due to its strong reforestation. Haiti had the largest decreasing trend because of continuous deforestation for charcoals. After LCLUC was excluded, EVI trend still varied greatly, decreasing in the windward but increasing in the leeward of Puerto Rico. Nighttime warming reinforced by spatially heterogeneous cloudiness was found to significantly and negatively correlate with EVI trend, and explained the spatial pattern of the latter. Although cooled daytime and increased rainfall might enhance EVI, nighttime warming dominated the climate impacts and differentiated the EVI trend.

Extent of Night Warming and Spatially Heterogeneous Cloudiness Differentiate Temporal Trend of Greenness in Mountainous Tropics in the New Century

PubMed Central

Yu, Mei; Gao, Qiong; Gao, Chunxiao; Wang, Chao

2017-01-01

Tropical forests have essential functions in global C dynamics but vulnerable to changes in land cover land use (LCLUC) and climate. The tropics of Caribbean are experiencing warming and drying climate and diverse LCLUC. However, large-scale studies to detect long-term trends of C and mechanisms behind are still rare. Using MODIS Enhanced Vegetation Index (EVI), we investigated greenness trend in the Greater Antilles Caribbean during 2000–2015, and analyzed trend of vegetation patches without LCLUC to give prominence to climate impacts. We hypothesized that night warming and heavy cloudiness would reduce EVI in this mountainous tropical region. Over the 15 years, EVI decreased significantly in Jamaica, Haiti, Dominican Republic, and Puerto Rico, but increased in Cuba partly due to its strong reforestation. Haiti had the largest decreasing trend because of continuous deforestation for charcoals. After LCLUC was excluded, EVI trend still varied greatly, decreasing in the windward but increasing in the leeward of Puerto Rico. Nighttime warming reinforced by spatially heterogeneous cloudiness was found to significantly and negatively correlate with EVI trend, and explained the spatial pattern of the latter. Although cooled daytime and increased rainfall might enhance EVI, nighttime warming dominated the climate impacts and differentiated the EVI trend. PMID:28120949

Testing Hypotheses about Sun-Climate Complexity Linking

NASA Astrophysics Data System (ADS)

Rypdal, M.; Rypdal, K.

2010-03-01

We reexamine observational evidence presented in support of the hypothesis of a sun-climate complexity linking by N. Scafetta and B. J. West, Phys. Rev. Lett. 90, 248701 (2003)PRLTAO0031-900710.1103/PhysRevLett.90.248701, which contended that the integrated solar flare index (SFI) and the global temperature anomaly (GTA) both follow Lévy walk statistics with the same waiting-time exponent μ≈2.1. However, their analysis does not account for trends in the signal, cannot deal correctly with infinite variance processes (Lévy flights), and suffers from considering only the second moment. Our analysis shows that properly detrended, the integrated SFI is well described as a Lévy flight, and the integrated GTA as a persistent fractional Brownian motion. These very different stochastic properties of the solar and climate records do not support the hypothesis of a sun-climate complexity linking.

Seasonal and interannual variations of atmospheric CO2 and climate

NASA Astrophysics Data System (ADS)

Dettinger, Michael D.; Ghil, Michael

1998-02-01

Interannual variations of atmospheric CO2 concentrations at Mauna Loa are almost masked by the seasonal cycle and a strong trend; at the South Pole, the seasonal cycle is small and is almost lost in the trend and interannual variations. Singular-spectrum analysis (SSA) is used here to isolate and reconstruct interannual signals at both sites and to visualize recent decadal changes in the amplitude and phase of the seasonal cycle. Analysis of the Mauna Loa CO2 series illustrates a hastening of the CO2 seasonal cycle, a close temporal relation between Northern Hemisphere (NH) mean temperature trends and the amplitude of the seasonal CO2 cycle, and tentative ties between the latter and seasonality changes in temperature over the NH continents. Variations of the seasonal CO2 cycle at the South Pole differ from those at Mauna Loa: it is phase changes of the seasonal cycle at the South Pole, rather than amplitude changes, that parallel hemispheric and global temperature trends. The seasonal CO2 cycles exhibit earlier occurrences of the seasons by 7days at Mauna Loa and 18days at the South Pole. Interannual CO2 variations are shared at the two locations, appear to respond to tropical processes, and can be decomposed mostly into two periodicities, around (3years)1 and (4years)1, respectively. Joint SSA analyses of CO2 concentrations and tropical climate indices isolate a shared mode with a quasi-triennial (QT) period in which the CO2 and sea-surface temperature (SST) participation are in phase opposition. The other shared mode has a quasi-quadrennial (QQ) period and CO2 variations are in phase with the corresponding tropical SST variations throughout the tropics. Together these interannual modes exhibit a mean lag between tropical SSTs and CO2 variations of about 6 8months, with SST leading. Analysis of the QT and QQ signals in global gridded SSTs, joint SSA of CO2 and δ13C isotopic ratios, and SSA of CO2 and NH-land temperatures indicate that the QT variations in CO2 mostly reflect upwelling variations in the eastern tropical Pacific. QQ variations are dominated by the CO2 signature of terrestrial-ecosystem response to global QQ climate variations. Climate variations associated with these two interannual components of tropical variability have very different effects on global climate and, especially, on terrestrial ecosystems and the carbon cycle.

[Climate suitability for tea growing in Zhejiang Province].

PubMed

Jin, Zhi-Feng; Ye, Jian-Gang; Yang, Zai-Qiang; Sun, Rui; Hu, Bo; Li, Ren-Zhong

2014-04-01

It is important to quantitatively assess the climate suitability of tea and its response to climate change. Based on meteorological indices of tea growth and daily meteorological data from 1971 to 2010 in Zhejiang Province, three climate suitability models for single climate factors, including temperature, precipitation and sunshine, were established at a 10-day scale by using the fuzzy mathematics method, and a comprehensive climate suitability model was established with the geometric average method. The results indicated that the climate suitability was high in the tea growth season in Zhejiang Province, and the three kinds of climate suitability were all higher than 0.6. As for the single factor climate suitability, temperature suitability was the highest and sunshine suitability was the lowest. There were obvious inter-annual variations of tea climate suitability, with a decline trend in the 1970s, less variation in the 1980s, and an obvious incline trend after the 1990s. The change tendency of climate suitability for spring tea was similar with that of annual climate suitability, lower in the 1980s, higher in the 1970s and after the 1990s. However, the variation amplitude of the climate suitability for spring tea was larger. The climate suitability for summer tea and autumn tea showed a decline trend from 1971 to 2010.

Analysis of the evolution of precipitation in the Haihe river basin of China under changing environment

NASA Astrophysics Data System (ADS)

Ding, Xiangyi; Liu, Jiahong; Gong, Jiaguo

2018-02-01

Precipitation is one of the important factors of water cycle and main sources of regional water resources. It is of great significance to analyze the evolution of precipitation under changing environment for identifying the evolution law of water resources, thus can provide a scientific reference for the sustainable utilization of water resources and the formulation of related policies and measures. Generally, analysis of the evolution of precipitation consists of three levels: analysis the observed precipitation change based on measured data, explore the possible factors responsible for the precipitation change, and estimate the change trend of precipitation under changing environment. As the political and cultural centre of China, the climatic conditions in the Haihe river basin have greatly changed in recent decades. This study analyses the evolution of precipitation in the basin under changing environment based on observed meteorological data, GCMs and statistical methods. Firstly, based on the observed precipitation data during 1961-2000 at 26 meteorological stations in the basin, the actual precipitation change in the basin is analyzed. Secondly, the observed precipitation change in the basin is attributed using the fingerprint-based attribution method, and the causes of the observed precipitation change is identified. Finally, the change trend of precipitation in the basin under climate change in the future is predicted based on GCMs and a statistical downscaling model. The results indicate that: 1) during 1961-2000, the precipitation in the basin showed a decreasing trend, and the possible mutation time was 1965; 2) natural variability may be the factor responsible for the observed precipitation change in the basin; 3) under climate change in the future, precipitation in the basin will slightly increase by 4.8% comparing with the average, and the extremes will not vary significantly.

Global trends in vegetation phenology from 32-year GEOV1 leaf area index time series

NASA Astrophysics Data System (ADS)

Verger, Aleixandre; Baret, Frédéric; Weiss, Marie; Filella, Iolanda; Peñuelas, Josep

2013-04-01

Phenology is a critical component in understanding ecosystem response to climate variability. Long term data records from global mapping satellite platforms are valuable tools for monitoring vegetation responses to climate change at the global scale. Phenology satellite products and trend detection from satellite time series are expected to contribute to improve our understanding of climate forcing on vegetation dynamics. The capacity of monitoring ecosystem responses to global climate change was evaluated in this study from the 32-year time series of global Leaf Area Index (LAI) which have been recently produced within the geoland2 project. The long term GEOV1 LAI products were derived from NOAA/AVHRR (1981 to 2000) and SPOT/VGT (1999 to the present) with specific emphasis on consistency and continuity. Since mid-November, GEOV1 LAI products are freely available to the scientific community at geoland2 portal (www.geoland2.eu/core-mapping-services/biopar.html). These products are distributed at a dekadal time step for the period 1981-2000 and 2000-2012 at 0.05° and 1/112°, respectively. The use of GEOV1 data covering a long time period and providing information at dense time steps are expected to increase the reliability of trend detection. In this study, GEOV1 LAI time series aggregated at 0.5° spatial resolution are used. The CACAO (Consistent Adjustment of the Climatology to Actual Observations) method (Verger et al, 2013) was applied to characterize seasonal anomalies as well as identify trends. For a given pixel, CACAO computes, for each season, the time shift and the amplitude difference between the current temporal profile and the climatology computed over the 32 years. These CACAO parameters allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. Interannual variations in the timing of the Start of Season and End of Season, Season Length and LAI level in the peak of the growing season are analyzed. Trend analysis with robust statistical test of significance is conducted. Climate variables (precipitation, temperature, radiation) are then used to interpret the anomaly patterns detected in vegetation response.

Global Changes of the Water Cycle Intensity

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Schubert, Siegfried D.; Walker, Gregory K.

2003-01-01

In this study, we evaluate numerical simulations of the twentieth century climate, focusing on the changes in the intensity of the global water cycle. A new diagnostic of atmospheric water vapor cycling rate is developed and employed, that relies on constituent tracers predicted at the model time step. This diagnostic is compared to a simplified traditional calculation of cycling rate, based on monthly averages of precipitation and total water content. The mean sensitivity of both diagnostics to variations in climate forcing is comparable. However, the new diagnostic produces systematically larger values and more variability than the traditional average approach. Climate simulations were performed using SSTs of the early (1902-1921) and late (1979- 1998) twentieth century along with the appropriate C02 forcing. In general, the increase of global precipitation with the increases in SST that occurred between the early and late twentieth century is small. However, an increase of atmospheric temperature leads to a systematic increase in total precipitable water. As a result, the residence time of water in the atmosphere increased, indicating a reduction of the global cycling rate. This result was explored further using a number of 50-year climate simulations from different models forced with observed SST. The anomalies and trends in the cycling rate and hydrologic variables of different GCMs are remarkably similar. The global annual anomalies of precipitation show a significant upward trend related to the upward trend of surface temperature, during the latter half of the twentieth century. While this implies an increase in the hydrologic cycle intensity, a concomitant increase of total precipitable water again leads to a decrease in the calculated global cycling rate. An analysis of the land/sea differences shows that the simulated precipitation over land has a decreasing trend while the oceanic precipitation has an upward trend consistent with previous studies and the available observations. The decreasing continental trend in precipitation is located primarily over tropical land regions, with some other regions, such as North America experiencing an increasing trend. Precipitation trends are diagnosed further using the water tracers to delineate the precipitation that occurs because of continental evaporation, as opposed to oceanic evaporation. These diagnostics show that over global land areas, the recycling of continental moisture is decreasing in time. However, the recycling changes are not spatially uniform so that some regions, most notably over the United States, experience continental recycling of water that increases in time.

A climate trend analysis of Ethiopia

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Eilerts, Gary; Kebebe, Emebet; Biru, Nigist; White, Libby; Galu, Gideon

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), examines recent trends in March-June, June-September, and March-September rainfall and temperature, identifying significant reductions in rainfall and increases in temperature over time in many areas of Ethiopia. Conclusions: * Spring and summer rains in parts of Ethiopia have declined by 15-20 percent since the mid-1970s. * Substantial warming across the entire country has exacerbated the dryness.* An important pattern of observed existing rainfall declines coincides with heavily populated areas of the Rift Valley in south-central Ethiopia, and is likely already adversely affecting crop yields and pasture conditions. * Rapid population growth and the expansion of farming and pastoralism under a drier, warmer climate regime could dramatically increase the number of at-risk people in Ethiopia during the next 20 years.* Many areas of Ethiopia will maintain moist climate conditions, and agricultural development in these areas could help offset rainfall declines and reduced production in other areas.

Changes of cloudiness over tropical land during the past few decades and its link to global climate change

NASA Astrophysics Data System (ADS)

Arias, P.; Fu, R.; Li, W.

2007-12-01

Tropical forests play a key role in determining the global carbon-climate feedback in the 21st century. Changes in rainforest growth and mortality rates, especially in the deep and least perturbed forest areas, have been consistently observed across global tropics in recent years. Understanding the underlying causes of these changes, especially their links to the global climate change, is especially important in determining the future of the tropical rainforests in the 21st century. Previous studies have mostly focus on the potential influences from elevated atmospheric CO2 and increasing surface temperature. Because the rainforests in wet tropical region is often light limited, we explore whether cloudiness have changed, if so, whether it is consistent with that expected from changes in forest growth rate. We will report our observational analysis examining the trends in annual average shortwave (SW) downwelling radiation, total cloud cover, and cumulus cover over the tropical land regions and to link them with trends in convective available potencial energy (CAPE). ISCCP data and radiosonde records available from the Department of Atmospheric Sciences of the University of Wyoming (http://www.weather.uwyo.edu/upperair/sounding.html) are used to study the trends. The period for the trend analysis is 1984-2004 for the ISCCP data and 1980-2006 for the radiosondes. The results for the Amazon rainforest region suggest a decreasing trend in total cloud and convective cloud covers, which results in an increase in downwelling SW radiation at the surface. These changes of total and convective clouds are consistent with a trend of decreasing CAPE and an elevated Level of Free Convection (LFC) height, as obtained from the radiosondes. All the above mentioned trends are statistically significant based on the Mann-Kendall test with 95% of confidence. These results consistently suggest the downward surface solar radiation has been increasing since 1984, result from a decrease of convective and total cloudiness over the Southern Amazon basin, due to an increase of LFC and atmospheric thermodynamic stability. Such an increase of surface SW radiation probably has contributed to the increasing in growth rate for the forests in the Amazon forests. Currently, the same analysis is being applied using radiosonde data from the Comprehensive Aerological Reference Data Set (CARDS) over the Amazon and Congo basins and the Southeast Asia. Our objective is to identify changes in cloudiness over tropical land and identify its underlying causes, especially the link to changes in surface temperature and humidity.

Analyzing climate variations at multiple timescales can guide Zika virus response measures.

PubMed

Muñoz, Ángel G; Thomson, Madeleine C; Goddard, Lisa; Aldighieri, Sylvain

2016-10-06

The emergence of Zika virus (ZIKV) in Latin America and the Caribbean in 2014-2016 occurred during a period of severe drought and unusually high temperatures, conditions that have been associated with the 2015-2016 El Niño event, and/or climate change; however, no quantitative assessment has been made to date. Analysis of related flaviviruses transmitted by the same vectors suggests that ZIKV dynamics are sensitive to climate seasonality and longer-term variability and trends. A better understanding of the climate conditions conducive to the 2014-2016 epidemic may permit the development of climate-informed short and long-term strategies for ZIKV prevention and control. Using a novel timescale-decomposition methodology, we demonstrate that the extreme climate anomalies observed in most parts of South America during the current epidemic are not caused exclusively by El Niño or climate change, but by a combination of climate signals acting at multiple timescales. In Brazil, the dry conditions present in 2013-2015 are primarily explained by year-to-year variability superimposed on decadal variability, but with little contribution of long-term trends. In contrast, the warm temperatures of 2014-2015 resulted from the compound effect of climate change, decadal and year-to-year climate variability. ZIKV response strategies made in Brazil during the drought concurrent with the 2015-2016 El Niño event, may require revision in light of the likely return of rainfall associated with the borderline La Niña event expected in 2016-2017. Temperatures are likely to remain warm given the importance of long term and decadal scale climate signals. The Author(s)

Assess Climate Change's Impact on Coastal Rivers using a Coupled Climate-Hydrology Model

NASA Astrophysics Data System (ADS)

Xue, Z. G.; Gochis, D.; Yu, W.; Zang, Z.; Sampson, K. M.; Keim, B. D.

2016-12-01

In this study we present a coupled climate-hydrological model reproducing the water cycle of three coastal river basins along the northern Gulf of Mexico for the past three decades (1985-2014). Model simulated climate condition, surface physics, and streamflow were well validated against in situ data and satellite-derived products, giving us the confidence that the newly developed WRF-Hydro model can be a robust tool for evaluating climate change's impact on hydrological regime. Trend analysis of model simulated monthly and annual time series indicates that local climate is getting hotter and dryer, specifically during the growing season. Wavelet analysis reveals that local evapotranspiration is strongly correlated with temperature, while soil moisture, water surplus, and streamflow are coupled with precipitation. In addition, local climate is closely correlated with large-scale climate dynamics such as AMO and ENSO. A possible change-point is detected around year 2004, after which, the monthly precipitation decreased by 14.2%, evapotranspiration increased by 2.9%, and water surplus decreased by 36.5%. The implication of the difference between the water surplus (runoff) calculated using the classic Thornthwaite method and river discharge estimated using streamflow records to the coastal environment is also discussed.

How resilient are ecosystems in adapting to climate variability

NASA Astrophysics Data System (ADS)

Savenije, Hubert H. G.

2015-04-01

The conclusion often drawn in the media is that ecosystems may perish as a result of climate change. Although climatic trends may indeed lead to shifts in ecosystem composition, the challenge to adjust to climatic variability - even if there is no trend - is larger, particularly in semi-arid or topical climates where climatic variability is large compared to temperate climates. How do ecosystems buffer for climatic variability? The most powerful mechanism is to invest in root zone storage capacity, so as to guarantee access to water and nutrients during period of drought. This investment comes at a cost of having less energy available to invest in growth or formation of fruits. Ecosystems are expected to create sufficient buffer to overcome critical periods of drought, but not more than is necessary to survive or reproduce. Based on this concept, a methodology has been developed to estimate ecosystem root zone storage capacity at local, regional and global scale. These estimates correspond well with estimates made by combining soil and ecosystem information, but are more accurate and more detailed. The methodology shows that ecosystems have intrinsic capacity to adjust to climatic variability and hence have a high resilience to both climatic variability and climatic trends.

Quantitative Assessment of Antarctic Climate Variability and Change

NASA Astrophysics Data System (ADS)

Ordonez, A.; Schneider, D. P.

2013-12-01

The Antarctic climate is both extreme and highly variable, but there are indications it may be changing. As the climate in Antarctica can affect global sea level and ocean circulation, it is important to understand and monitor its behavior. Observational and model data have been used to study climate change in Antarctica and the Southern Ocean, though observational data is sparse and models have difficulty reproducing many observed climate features. For example, a leading hypothesis that ozone depletion has been responsible for sea ice trends is struggling with the inability of ozone-forced models to reproduce the observed sea ice increase. The extent to which this data-model disagreement represents inadequate observations versus model biases is unknown. This research assessed a variety of climate change indicators to present an overview of Antarctic climate that will allow scientists to easily access this data and compare indicators with other observational data and model output. Indicators were obtained from observational and reanalysis data for variables such as temperature, sea ice area, and zonal wind stress. Multiple datasets were used for key variables. Monthly and annual anomaly data from Antarctica and the Southern Ocean as well as tropical indices were plotted as time series on common axes for comparison. Trends and correlations were also computed. Zonal wind, surface temperature, and austral springtime sea ice had strong relationships and were further discussed in terms of how they may relate to climate variability and change in the Antarctic. This analysis will enable hypothesized mechanisms of Antarctic climate change to be critically evaluated.

Land surface temperature over global deserts: Means, variability, and trends

NASA Astrophysics Data System (ADS)

Zhou, Chunlüe; Wang, Kaicun

2016-12-01

Land surface air temperature (LSAT) has been a widely used metric to study climate change. Weather observations of LSAT are the fundamental data for climate change studies and provide key evidence of global warming. However, there are very few meteorological observations over deserts due to their uninhabitable environment. This study fills this gap and provides independent evidence using satellite-derived land surface temperatures (LSTs), benefiting from their global coverage. The frequency of clear sky from MODerate Resolution Imaging Spectroradiometer (MODIS) LST data over global deserts was found to be greater than 94% for the 2002-2015 period. Our results show that MODIS LST has a bias of 1.36°C compared to ground-based observations collected at 31 U.S. Climate Reference Network (USCRN) stations, with a standard deviation of 1.83°C. After bias correction, MODIS LST was used to evaluate existing reanalyses, including ERA-Interim, Japanese 55-year Reanalysis (JRA-55), Modern-Era Retrospective Analysis for Research and Applications (MERRA), MERRA-land, National Centers for Environmental Prediction (NCEP)-R1, and NCEP-R2. The reanalyses accurately reproduce the seasonal cycle and interannual variability of the LSTs, but their multiyear means and trends of LSTs exhibit large uncertainties. The multiyear averaged LST over global deserts is 23.5°C from MODIS and varies from 20.8°C to 24.5°C in different reanalyses. The MODIS LST over global deserts increased by 0.25°C/decade from 2002 to 2015, whereas the reanalyses estimated a trend varying from -0.14 to 0.10°C/decade. The underestimation of the LST trend by the reanalyses occurs for approximately 70% of the global deserts, likely due to the imperfect performance of the reanalyses in reproducing natural climate variability.

CLIMATE CHANGE. Possible artifacts of data biases in the recent global surface warming hiatus.

PubMed

Karl, Thomas R; Arguez, Anthony; Huang, Boyin; Lawrimore, Jay H; McMahon, James R; Menne, Matthew J; Peterson, Thomas C; Vose, Russell S; Zhang, Huai-Min

2015-06-26

Much study has been devoted to the possible causes of an apparent decrease in the upward trend of global surface temperatures since 1998, a phenomenon that has been dubbed the global warming "hiatus." Here, we present an updated global surface temperature analysis that reveals that global trends are higher than those reported by the Intergovernmental Panel on Climate Change, especially in recent decades, and that the central estimate for the rate of warming during the first 15 years of the 21st century is at least as great as the last half of the 20th century. These results do not support the notion of a "slowdown" in the increase of global surface temperature. Copyright © 2015, American Association for the Advancement of Science.

Knowledge discovery and nonlinear modeling can complement climate model simulations for predictive insights about climate extremes and their impacts

NASA Astrophysics Data System (ADS)

Ganguly, A. R.; Steinbach, M.; Kumar, V.

2009-12-01

The IPCC AR4 not only provided conclusive evidence about anticipated global warming at century scales, but also indicated with a high level of certainty that the warming is caused by anthropogenic emissions. However, an outstanding knowledge-gap is to develop credible projections of climate extremes and their impacts. Climate extremes are defined in this context as extreme weather and hydrological events, as well as changes in regional hydro-meteorological patterns, especially at decadal scales. While temperature extremes from climate models have relatively better skills, hydrological variables and their extremes have significant shortcomings. Credible projections about tropical storms, sea level rise, coastal storm surge, land glacier melts, and landslides remain elusive. The next generation of climate models is expected to have higher precision. However, their ability to provide more accurate projections of climate extremes remains to be tested. Projections of observed trends into the future may not be reliable in non-stationary environments like climate change, even though functional relationships derived from physics may hold. On the other hand, assessments of climate change impacts which are useful for stakeholders and policy makers depend critically on regional and decadal scale projections of climate extremes. Thus, climate impacts scientists often need to develop qualitative inferences about the not so-well predicted climate extremes based on insights from observations (e.g., increased hurricane intensity) or conceptual understanding (e.g., relation of wildfires to regional warming or drying and hurricanes to SST). However, neither conceptual understanding nor observed trends may be reliable when extrapolating in a non-stationary environment. These urgent societal priorities offer fertile grounds for nonlinear modeling and knowledge discovery approaches. Thus, qualitative inferences on climate extremes and impacts may be transformed into quantitative predictive insights based on a combination of hypothesis-guided data analysis and relatively hypothesis-free but data-guided discovery processes. The analysis and discovery approaches need to be cognizant of climate data characteristics like nonlinear processes, low-frequency variability, long-range spatial dependence and long-memory temporal processes; the value of physically-motivated conceptual understanding and functional associations; as well as possible thresholds and tipping points in the impacted natural, engineered or human systems. Case studies focusing on new methodologies as well as novel climate insights are discussed with a focus on stakeholder requirements.

Use and Limitations of a Climate-Quality Data Record to Study Temperature Trends on the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Hall, D. K.; Comiso, J. C.; Shuman, C. A.; Koenig, L.; DiGirolamo, N. E.

2011-12-01

Enhanced melting of the Greenland Ice Sheet has been documented in recent literature along with surface-temperature increases measured using infrared satellite data since 1981. Using a recently-developed climate-quality data record, 11- and 12-year trends in the clear-sky ice-surface temperature (IST) of the Greenland Ice Sheet have been studied using the Moderate-Resolution Imaging Spectroradiometer (MODIS) IST product. Daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are now available at 6.25-km spatial resolution on a polar stereographic grid as described in Hall et al. (submitted). This record will be elevated in status to a climate-data record (CDR) when more years of data become available either from the MODIS on the Terra or Aqua satellites, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Maps showing the maximum extent of melt for the entire ice sheet and for the six major drainage basins have been developed from the MODIS IST dataset. Twelve-year trends in the extent of melt and duration of the melt season on the ice sheet vary in different drainage basins with some basins melting progressively earlier over the course of the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. Twelve-year trends in IST are compared with in-situ data, and climate data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) Reanalysis. Hall, D.K., J.C. Comiso, N.E. DiGirolamo, C.A. Shuman, J. Key and L.S. Koenig, submitted for journal publication: A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet.

Is Forest Restoration in the Southwest China Karst Promoted Mainly by Climate Change or Human-Induced Factors?

NASA Astrophysics Data System (ADS)

Cai, H.

2017-12-01

The Southwest China Karst, the largest continuous karst zone in the world, has suffered serious rock desertification due to the large population pressure in the area. Recent trend analyses have indicated general greening trends in this region. The region has experienced mild climate change, and yet significant land use changes, such as afforestation and reforestation. In addition, out-migration has occurred. Whether climate change or human-induced factors, i.e., ecological afforestation projects and out-migration have primarily promoted forest restoration in this region was investigated in this study, using Guizhou Province as the study area. Based on Moderate-Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data, we found general greening trends of the forest from 2000 to 2010. About 89% of the forests have experienced an increase in the annual NDVI, and among which, about 41% is statistically significant. For the summer season, more than 65% of the forests have increases in summer NDVI, and about 16% of the increases are significant. The strongest greening trends mainly occurred in the karst areas. Meanwhile, annual average and summer average temperature in this region have increased and the precipitation in most of the region has decreased, although most of these changes were not statistically significant (p > 0.1). A site-based regression analysis using 19 climate stations with minimum land use changes showed that a warming climate coupled with a decrease in precipitation explained some of the changes in the forest NDVI, but the results were not conclusive. The major changes were attributed to human-induced factors, especially in the karst areas. The implications of an ecological afforestation project and out-migration for forest restoration were also discussed, and the need for further investigations at the household level to better understand the out-migration-environment relationship was identified.

Elevation-dependent temperature trends in the Rocky Mountain Front Range: changes over a 56- and 20-year record.

PubMed

McGuire, Chris R; Nufio, César R; Bowers, M Deane; Guralnick, Robert P

2012-01-01

Determining the magnitude of climate change patterns across elevational gradients is essential for an improved understanding of broader climate change patterns and for predicting hydrologic and ecosystem changes. We present temperature trends from five long-term weather stations along a 2077-meter elevational transect in the Rocky Mountain Front Range of Colorado, USA. These trends were measured over two time periods: a full 56-year record (1953-2008) and a shorter 20-year (1989-2008) record representing a period of widely reported accelerating change. The rate of change of biological indicators, season length and accumulated growing-degree days, were also measured over the 56 and 20-year records. Finally, we compared how well interpolated Parameter-elevation Regression on Independent Slopes Model (PRISM) datasets match the quality controlled and weather data from each station. Our results show that warming signals were strongest at mid-elevations over both temporal scales. Over the 56-year record, most sites show warming occurring largely through increases in maximum temperatures, while the 20-year record documents warming associated with increases in maximum temperatures at lower elevations and increases in minimum temperatures at higher elevations. Recent decades have also shown a shift from warming during springtime to warming in July and November. Warming along the gradient has contributed to increases in growing-degree days, although to differing degrees, over both temporal scales. However, the length of the growing season has remained unchanged. Finally, the actual and the PRISM interpolated yearly rates rarely showed strong correlations and suggest different warming and cooling trends at most sites. Interpretation of climate trends and their seasonal biases in the Rocky Mountain Front Range are dependent on both elevation and the temporal scale of analysis. Given mismatches between interpolated data and the directly measured station data, we caution against an over-reliance on interpolation methods for documenting local patterns of climatic change.

Elevation-Dependent Temperature Trends in the Rocky Mountain Front Range: Changes over a 56- and 20-Year Record

PubMed Central

McGuire, Chris R.; Nufio, César R.; Bowers, M. Deane; Guralnick, Robert P.

2012-01-01

Determining the magnitude of climate change patterns across elevational gradients is essential for an improved understanding of broader climate change patterns and for predicting hydrologic and ecosystem changes. We present temperature trends from five long-term weather stations along a 2077-meter elevational transect in the Rocky Mountain Front Range of Colorado, USA. These trends were measured over two time periods: a full 56-year record (1953–2008) and a shorter 20-year (1989–2008) record representing a period of widely reported accelerating change. The rate of change of biological indicators, season length and accumulated growing-degree days, were also measured over the 56 and 20-year records. Finally, we compared how well interpolated Parameter-elevation Regression on Independent Slopes Model (PRISM) datasets match the quality controlled and weather data from each station. Our results show that warming signals were strongest at mid-elevations over both temporal scales. Over the 56-year record, most sites show warming occurring largely through increases in maximum temperatures, while the 20-year record documents warming associated with increases in maximum temperatures at lower elevations and increases in minimum temperatures at higher elevations. Recent decades have also shown a shift from warming during springtime to warming in July and November. Warming along the gradient has contributed to increases in growing-degree days, although to differing degrees, over both temporal scales. However, the length of the growing season has remained unchanged. Finally, the actual and the PRISM interpolated yearly rates rarely showed strong correlations and suggest different warming and cooling trends at most sites. Interpretation of climate trends and their seasonal biases in the Rocky Mountain Front Range are dependent on both elevation and the temporal scale of analysis. Given mismatches between interpolated data and the directly measured station data, we caution against an over-reliance on interpolation methods for documenting local patterns of climatic change. PMID:22970205

The CARIPANDA project: Climate change and water resources in the Adamello Natural Park of Italy

NASA Astrophysics Data System (ADS)

Bocchiola, D.

2009-04-01

The three years (2007-2009) CARIPANDA project funded by the Cariplo Foundation of Italy is aimed to evaluate scenarios for water resources in the Adamello natural Park of Italy in a window of 50 years or so (until 2050). The project is led by Ente Parco Adamello and involves Politecnico di Milano, Università Statale di Milano, Università di Brescia, and ARPA Lombardia as scientific partners, while ENEL hydropower Company of Italy joins the project as stake holder. The Adamello Natural Park is a noteworthy resource in the Italian Alps. The Adamello Group is made of several glacierized areas (c. 24 km2), of both debris covered and free ice types, including the widest Italian Glacier, named Adamello, spreading on an area of about c. 18 km2. Also the Adamello Natural Reserve, covering 217 km2 inside the Adamello Park and including the Adamello glaciers, hosts a number of high altitude safeguarded vegetal and animal species, the safety of which is a primary task of the Reserve. Project's activity involves analysis of local climate trend, field campaigns on glaciers, hydrological modelling and remote sensing of snow and ice covered areas, aimed to build a consistent model of the present hydrological conditions and of the areas. Then, properly tailored climate change projections for the area, obtained using local data driven downscaling of climate change projections from GCMs model, are used to infer the likely response to expected climate change conditions. With two years in the project now some preliminary findings can be highlighted and some preliminary trend analysis carried out. The proposed poster provides a resume of the main results of the project insofar, of interest as a benchmark for similar ongoing and foregoing projects about climate change impact on European mountainous natural areas.

Probabilistic attribution of individual unprecedented extreme events

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.

2016-12-01

The last decade has seen a rapid increase in efforts to understand the influence of global warming on individual extreme climate events. Although trends in the distributions of climate observations have been thoroughly analyzed, rigorously quantifying the contribution of global-scale warming to individual events that are unprecedented in the observed record presents a particular challenge. This paper describes a method for leveraging observations and climate model ensembles to quantify the influence of historical global warming on the severity and probability of unprecedented events. This approach uses formal inferential techniques to quantify four metrics: (1) the contribution of the observed trend to the event magnitude, (2) the contribution of the observed trend to the event probability, (3) the probability of the observed trend in the current climate and a climate without human influence, and (4) the probability of the event magnitude in the current climate and a climate without human influence. Illustrative examples are presented, spanning a range of climate variables, timescales, and regions. These examples illustrate that global warming can influence the severity and probability of unprecedented extremes. In some cases - particularly high temperatures - this change is indicated by changes in the mean. However, changes in probability do not always arise from changes in the mean, suggesting that global warming can alter the frequency with which complex physical conditions co-occur. Because our framework is transparent and highly generalized, it can be readily applied to a range of climate events, regions, and levels of climate forcing.

Identifying trends in climate: an application to the cenozoic

NASA Astrophysics Data System (ADS)

Richards, Gordon R.

1998-05-01

The recent literature on trending in climate has raised several issues, whether trends should be modeled as deterministic or stochastic, whether trends are nonlinear, and the relative merits of statistical models versus models based on physics. This article models trending since the late Cretaceous. This 68 million-year interval is selected because the reliability of tests for trending is critically dependent on the length of time spanned by the data. Two main hypotheses are tested, that the trend has been caused primarily by CO2 forcing, and that it reflects a variety of forcing factors which can be approximated by statistical methods. The CO2 data is obtained from model simulations. Several widely-used statistical models are found to be inadequate. ARIMA methods parameterize too much of the short-term variation, and do not identify low frequency movements. Further, the unit root in the ARIMA process does not predict the long-term path of temperature. Spectral methods also have little ability to predict temperature at long horizons. Instead, the statistical trend is estimated using a nonlinear smoothing filter. Both of these paradigms make it possible to model climate as a cointegrated process, in which temperature can wander quite far from the trend path in the intermediate term, but converges back over longer horizons. Comparing the forecasting properties of the two trend models demonstrates that the optimal forecasting model includes CO2 forcing and a parametric representation of the nonlinear variability in climate.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bennett, Katrina E.; Cannon, Alex J.; Hinzman, Larry

Climate change will shift the frequency, intensity, duration and persistence of extreme hydroclimate events and have particularly disastrous consequences in vulnerable systems such as the warm permafrost-dominated Interior region of boreal Alaska. This work focuses on recent research results from nonparametric trends and nonstationary generalized extreme value (GEV) analyses at eight Interior Alaskan river basins for the past 50/60 years (1954/64–2013). Trends analysis of maximum and minimum streamflow indicates a strong (>+50%) and statistically significant increase in 11-day flow events during the late fall/winter and during the snowmelt period (late April/mid-May), followed by a significant decrease in the 11-day flowmore » events during the post-snowmelt period (late May and into the summer). The April–May–June seasonal trends show significant decreases in maximum streamflow for snowmelt dominated systems (<–50%) and glacially influenced basins (–24% to –33%). Annual maximum streamflow trends indicate that most systems are experiencing declines, while minimum flow trends are largely increasing. Nonstationary GEV analysis identifies time-dependent changes in the distribution of spring extremes for snowmelt dominated and glacially dominated systems. Temperature in spring influences the glacial and high elevation snowmelt systems and winter precipitation drives changes in the snowmelt dominated basins. The Pacific Decadal Oscillation was associated with changes occurring in snowmelt dominated systems, and the Arctic Oscillation was linked to one lake dominated basin, with half of the basins exhibiting no change in response to climate variability. The paper indicates that broad scale studies examining trend and direction of change should employ multiple methods across various scales and consider regime dependent shifts to identify and understand changes in extreme streamflow within boreal forested watersheds of Alaska.« less

Searching for evidence of changes in extreme rainfall indices in the Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Muluneh, Alemayehu; Bewket, Woldeamlak; Keesstra, Saskia; Stroosnijder, Leo

2017-05-01

Extreme rainfall events have serious implications for economic sectors with a close link to climate such as agriculture and food security. This holds true in the Central Rift Valley (CRV) of Ethiopia where communities rely on highly climate-sensitive rainfed subsistence farming for livelihoods. This study investigates changes in ten extreme rainfall indices over a period of 40 years (1970-2009) using 14 meteorological stations located in the CRV. The CRV consists of three landscape units: the valley floor, the escarpments, and the highlands all of which are considered in our data analysis. The Belg (March-May) and Kiremt (June-September) seasons are also considered in the analysis. The Mann-Kendall test was used to detect trends of the rainfall indices. The results indicated that at the annual time scale, more than half (57 %) of the stations showed significant trends in total wet-day precipitation (PRCPTOT) and heavy precipitation days (R10mm). Only 7-35 % of stations showed significant trends, for the other rainfall indices. Spatially, the valley floor received increasing annual rainfall while the escarpments and the highlands received decreasing annual rainfall over the last 40 years. During Belg, 50 % of the stations showed significant increases in the maximum number of consecutive dry days (CDD) in all parts of the CRV. However, most other rainfall indices during Belg showed no significant changes. During Kiremt, considering both significant and non-significant trends, almost all rainfall indices showed an increasing trend in the valley floor and a decreasing trend in the escarpment and highlands. During Belg and Kiremt, the CDD generally showed increasing tendency in the CRV.

Population Trends of Central European Montane Birds Provide Evidence for Adverse Impacts of Climate Change on High-Altitude Species.

PubMed

Flousek, Jiří; Telenský, Tomáš; Hanzelka, Jan; Reif, Jiří

2015-01-01

Climate change is among the most important global threats to biodiversity and mountain areas are supposed to be under especially high pressure. Although recent modelling studies suggest considerable future range contractions of montane species accompanied with increased extinction risk, data allowing to test actual population consequences of the observed climate changes and identifying traits associated to their adverse impacts are very scarce. To fill this knowledge gap, we estimated long-term population trends of montane birds from 1984 to 2011 in a central European mountain range, the Giant Mountains (Krkonoše), where significant warming occurred over this period. We then related the population trends to several species' traits related to the climate change effects. We found that the species breeding in various habitats at higher altitudes had more negative trends than species breeding at lower altitudes. We also found that the species moved upwards as a response to warming climate, and these altitudinal range shifts were associated with more positive population trends at lower altitudes than at higher altitudes. Moreover, long-distance migrants declined more than residents or species migrating for shorter distances. Taken together, these results indicate that the climate change, besides other possible environmental changes, already influences populations of montane birds with particularly adverse impacts on high-altitude species such as water pipit (Anthus spinoletta). It is evident that the alpine species, predicted to undergo serious climatically induced range contractions due to warming climate in the future, already started moving along this trajectory.

Evaluating historical climate and hydrologic trends in the Central Appalachian region of the United States

NASA Astrophysics Data System (ADS)

Gaertner, B. A.; Zegre, N.

2015-12-01

Climate change is surfacing as one of the most important environmental and social issues of the 21st century. Over the last 100 years, observations show increasing trends in global temperatures and intensity and frequency of precipitation events such as flooding, drought, and extreme storms. Global circulation models (GCM) show similar trends for historic and future climate indicators, albeit with geographic and topographic variability at regional and local scale. In order to assess the utility of GCM projections for hydrologic modeling, it is important to quantify how robust GCM outputs are compared to robust historical observations at finer spatial scales. Previous research in the United States has primarily focused on the Western and Northeastern regions due to dominance of snow melt for runoff and aquifer recharge but the impact of climate warming in the mountainous central Appalachian Region is poorly understood. In this research, we assess the performance of GCM-generated historical climate compared to historical observations primarily in the context of forcing data for macro-scale hydrologic modeling. Our results show significant spatial heterogeneity of modeled climate indices when compared to observational trends at the watershed scale. Observational data is showing considerable variability within maximum temperature and precipitation trends, with consistent increases in minimum temperature. The geographic, temperature, and complex topographic gradient throughout the central Appalachian region is likely the contributing factor in temperature and precipitation variability. Variable climate changes are leading to more severe and frequent climate events such as temperature extremes and storm events, which can have significant impacts on our drinking water supply, infrastructure, and health of all downstream communities.

Long-term trends in climate and hydrology in an agricultural headwater watershed of central Pennsylvania, USA

USDA-ARS?s Scientific Manuscript database

Climate change has emerged as a key issue facing agriculture and water resources in the US. Long-term (1968-2012) temperature, precipitation and streamflow data from a small (7.3 km2) watershed in east-central Pennsylvania was used to examine climatic and hydrologic trends in the context of recent c...

Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions

USGS Publications Warehouse

Amy K. Snover,; Nathan J. Mantua,; Littell, Jeremy; Michael A. Alexander,; Michelle M. McClure,; Janet Nye,

2013-01-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment.

An observationally centred method to quantify local climate change as a distribution

NASA Astrophysics Data System (ADS)

Stainforth, David; Chapman, Sandra; Watkins, Nicholas

2013-04-01

For planning and adaptation, guidance on trends in local climate is needed at the specific thresholds relevant to particular impact or policy endeavours. This requires quantifying trends at specific quantiles in distributions of variables such as daily temperature or precipitation. These non-normal distributions vary both geographically and in time. The trends in the relevant quantiles may not simply follow the trend in the distribution mean. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs how the trend or sensitivity varies with temperature (or occurrence likelihood), and with geographical location. These sensitivities are found to be geographically varying across Europe; as one would expect given the different influences on local climate between, say, Western Scotland and central Italy. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, in press [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201

Temporal patterns of vegetation phenology and their responses to climate change in mid-latitude grasslands of the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Ren, S.; Chen, X.; Qin, Q.; Zhang, Y.; Wu, Z.

2017-12-01

Grassland ecosystem is greatly sensitive to regional and global climate changes. In this study, the start (SOS) and end (EOS) date of growing season were extracted from NDVI data (1981 2014) across the mid-latitude (30°N 55°N) grasslands of Northern Hemisphere. We first validated their accuracy by ground observed phenological data and phenological metrics derived from gross primary production (GPP) data. And then, main climatic factors influencing the temporal patterns of SOS/EOS were explored by means of gridded meteorological data and partial correlation analysis. Based on the results of above statistical analysis, the similarities and differences of spring and autumn phenological responses to climate change among North American grasslands, Mid-West Asian grasslands, and Mongolian grasslands were analyzed. The main results and conclusions are as follows. First, a significant positive correlation was found between SOS/EOS and observed green-up/brown-off date (P<0.05) and GPP-based SOS/EOS (P<0.05), which means remote sensed SOS/EOS can reflect temporal dynamics of terrestrial vegetation phenology. Second, SOS in Mid-West Asian grasslands showed a significant advancing trend (0.22 days/year, P<0.01), whereas the trend of SOS in North American grasslands and Mongolian grasslands was not significant. EOS in North American grasslands (0.31 dyas/year, P<0.01) and Mongolian grasslands (0.09 days/year, P<0.05) both presented a significant delaying trend, but the trend of EOS in Mid-West Asian grasslands was not significant. Furthermore, the correlation analysis of SOS/EOS inter-annual fluctuations and hydrothermal factors showed that a significant negative correlation was found between SOS and the pre-season temperature in 41.6% of pixels (P<0.05), while a significant negative/positive correlation was detected between SOS and pre-season rainfall/snowfall in 14.6%/19.0% of pixels (P<0.05). EOS was significantly positively correlated with pre-season rainfall in 34.5% of pixels (P<0.05), and significantly negatively/positively correlated with pre-season temperature in 12.1%/11.9% of pixels (P<0.05). This indicates that the fluctuations of SOS and EOS are mainly affected by pre-season temperature and pre-season rainfall.

Changes in precipitation-streamflow transformation around the world: interdecadal variability and trends.

NASA Astrophysics Data System (ADS)

Saft, M.; Peel, M. C.; Andreassian, V.; Parajka, J.; Coxon, G.; Freer, J. E.; Woods, R. A.

2017-12-01

Accurate prediction of hydrologic response to potentially changing climatic forcing is a key current challenge in hydrology. Recent studies exploring decadal to multidecadal climate drying in the African Sahel and south-eastern and south-western Australia demonstrated that long dry periods also had an indirect cumulative impact on streamflow via altered catchment biophysical properties. As a result, hydrologic response to persisting change in climatic conditions, i.e. precipitation, cannot be confidently inferred from the hydrologic response to short-term interannual climate fluctuations of similar magnitude. This study aims to characterise interdecadal changes in precipitation-runoff conversion processes globally. The analysis is based on long continuous records from near-natural baseline catchments in North America, Europe, and Australia. We used several complimentary metrics characterising precipitation-runoff relationship to assess how partitioning changed over recent decades. First, we explore the hypothesis that during particularly dry or wet decades the precipitation elasticity of streamflow increases over what can be expected from inter-annual variability. We found this hypothesis holds for both wet and dry periods in some regions, but not everywhere. Interestingly, trend-like behaviour in the precipitation-runoff partitioning, unrelated to precipitation changes, offset the impact of persisting precipitation change in some regions. Therefore, in the second part of this study we explored longer-term trends in precipitation-runoff partitioning, and related them to climate and streamflow changes. We found significant changes in precipitation-runoff relationship around the world, which implies that runoff response to a given precipitation can vary over decades even in near-natural catchments. When significant changes occur, typically less runoff is generated for a given precipitation over time - even when precipitation is increasing. We discuss the consistency of the results and how the likely drivers differ between regions, and between water-limited and energy limited environments. We argue that when considering the impact of climatic change on hydrological systems we need to consider potential cumulative impacts of climatic shifts.

Phenological behaviour of early spring flowering trees in Spain in response to recent climate changes

NASA Astrophysics Data System (ADS)

Hidalgo-Galvez, M. D.; García-Mozo, H.; Oteros, J.; Mestre, A.; Botey, R.; Galán, C.

2018-04-01

This research reports the phenological trends of four early spring and late winter flowering trees in Spain (south Europe) from a recent period (1986-2012). The studied species were deciduous trees growing in different climatic areas: hazel ( Corylus avellana L.), willow ( Salix alba L.), ash ( Fraxinus angustifolia Vahl.) and white mulberry ( Morus alba L.). We analysed the response to climate and the trends of the following phenophases observed at the field: budburst, leaf unfolding, flowering, fruit ripening, fruit harvesting, leaf colour change and leaf-fall. The study was carried out in 17 sampling sites in the country with the aim of detecting the recent phenological response to the climate of these species, and the possible effect of climate change. We have observed differences in the phenological response to climate depending on each species. Sixty-one percent of studied sites suffered an advance of early spring phenophases, especially budburst on average by -0.67 days and flowering on average by -0.15 days during the studied period, and also in the subsequent fruit ripening and harvesting phases on average by -1.06 days. By contrast, it has been detected that 63% of sampling sites showed a delay in autumn vegetative phases, especially leaf-fall events on average by +1.15 days. The statistic correlation analysis shows in the 55% of the studied localities that phenological advances are the consequence of the increasing trend detected for temperature—being minimum temperature the most influential factor—and in the 52% of them, phenological advances occurred by rainfall variations. In general, leaf unfolding and flowering from these species showed negative correlations in relation to temperature and rainfall, whereas that leaf colour change and leaf-fall presented positive correlations. The results obtained have a great relevance due to the fact that they can be considered as reliable bio-indicators of the impact of the recent climate changes in southern Europe.

Recent trends of groundwater temperatures in Austria

NASA Astrophysics Data System (ADS)

Benz, Susanne A.; Bayer, Peter; Winkler, Gerfried; Blum, Philipp

2018-06-01

Climate change is one of if not the most pressing challenge modern society faces. Increasing temperatures are observed all over the planet and the impact of climate change on the hydrogeological cycle has long been shown. However, so far we have insufficient knowledge on the influence of atmospheric warming on shallow groundwater temperatures. While some studies analyse the implication climate change has for selected wells, large-scale studies are so far lacking. Here we focus on the combined impact of climate change in the atmosphere and local hydrogeological conditions on groundwater temperatures in 227 wells in Austria, which have in part been observed since 1964. A linear analysis finds a temperature change of +0.7 ± 0.8 K in the years from 1994 to 2013. In the same timeframe surface air temperatures in Austria increased by 0.5 ± 0.3 K, displaying a much smaller variety. However, most of the extreme changes in groundwater temperatures can be linked to local hydrogeological conditions. Correlation between groundwater temperatures and nearby surface air temperatures was additionally analysed. They vary greatly, with correlation coefficients of -0.3 in central Linz to 0.8 outside of Graz. In contrast, the correlation of nationwide groundwater temperatures and surface air temperatures is high, with a correlation coefficient of 0.83. All of these findings indicate that while atmospheric climate change can be observed in nationwide groundwater temperatures, individual wells are often primarily dominated by local hydrogeological conditions. In addition to the linear temperature trend, a step-wise model was also applied that identifies climate regime shifts, which were observed globally in the late 70s, 80s, and 90s. Hinting again at the influence of local conditions, at most 22 % of all wells show these climate regime shifts. However, we were able to identify an additional shift in 2007, which was observed by 37 % of all wells. Overall, the step-wise representation provides a slightly more accurate picture of observed temperatures than the linear trend.

Identification of trend in long term precipitation and reference evapotranspiration over Narmada river basin (India)

NASA Astrophysics Data System (ADS)

Pandey, Brij Kishor; Khare, Deepak

2018-02-01

Precipitation and reference evapotranspiration are key parameters in hydro-meteorological studies and used for agricultural planning, irrigation system design and management. Precipitation and evaporative demand are expected to be alter under climate change and affect the sustainable development. In this article, spatial variability and temporal trend of precipitation and reference evapotranspiration (ETo) were investigated over Narmada river basin (India), a humid tropical climatic region. In the present study, 12 and 28 observatory stations were selected for precipitation and ETo, respectively of 102-years period (1901-2002). A rigorous analysis for trend detection was carried out using non parametric tests such as Mann-Kendall (MK) and Spearman Rho (SR). Sen's slope estimator was used to analyze the rate of change in long term series. Moreover, all the stations of basin exhibit positive trend for annual ETo, while 8% stations indicate significant negative trend for mean annual precipitation, respectively. Change points of annual precipitation were identified around the year 1962 applying Buishand's and Pettit's test. Annual mean precipitation reduced by 9% in upper part while increased maximum by 5% in lower part of the basin due temporal changes. Although annual mean ETo increase by 4-12% in most of the region. Moreover, results of the study are very helpful in planning and development of agricultural water resources.

Development of A Dust Climate Indicator for the US National Climate Assessment

NASA Astrophysics Data System (ADS)

Tong, D.; Wang, J. X. L.; Gill, T. E.; Van Pelt, S.; Kim, D.

2016-12-01

Dust activity is a relatively simple but practical indicator to document the response of dryland ecosystems to climate change, making it an integral part of the National Climate Assessment (NCA). We present here a multi-agency collaboration that aims at developing a suite of dust climate indicators to document and monitor the long-term variability and trend of dust storm activity in the western United States. Recent dust observations have revealed rapid intensification of dust storm activity in the western United States. This trend is also closely correlated with a rapid increase in dust deposition in rainwater and "valley fever" hospitalization in southwestern states. It remains unclear, however, if such a trend, when enhanced by predicted warming and rainfall oscillation in the Southwest, will result in irreversible environmental development such as desertification or even another "Dust Bowl". Based on continuous ground aerosol monitoring, we have reconstructed a long-term dust storm climatology in the western United States. We report here direct evidence of rapid intensification of dust storm activity over US deserts in the past decades (1990 to 2013), in contrast to the decreasing trends in Asia and Africa. The US trend is spatially and temporally correlated with incidences of valley fever, an infectious disease caused by soil-dwelling fungus that has increased eight-fold in the past decade. We further investigate the linkage between dust variations and possible climate drivers and find that the regional dust trends are likely driven by large-scale variations of sea surface temperature in the Pacific Ocean, with the strongest correlation with the Pacific Decadal Oscillation (PDO). Future study will explore the link between the temporal and spatial trends of increase in dustiness and vegetation change in southwestern semi-arid and arid ecosystems.

AGU Journals Among Most Cited Publications in Climate Change Research

NASA Astrophysics Data System (ADS)

Sears, Jon

2010-03-01

Geophysical Research Letters (GRL) and Journal of Geophysical Research-Atmospheres (JGR-D) both ranked among the top 10 of the most highly cited research publications on climate change over the past decade in a recent analysis by sciencewatch.com, an Internet tool published by the Thomson Reuters Web of Science® that tracks trends and performances in basic research. Although Nature and Science—the multidisciplinary heavyweights—led the field, GRL ranked fifth and JGR-D ranked sixth. The study was conducted by searching the Web of Science® database for terms such as “global warming,” “climate change,” “human impact,” and other key phrases in journal articles published and cited between 1999 and the spring of 2009. The analysis produced over 28,000 papers, from which sciencewatch.com identified the most cited institutions, authors, and journals. To see the analysis in full, visit http://sciencewatch.com/ana/fea/09novdecFea/.

Trend Detection and Bivariate Frequency Analysis for Nonstrationary Rainfall Data

NASA Astrophysics Data System (ADS)

Joo, K.; Kim, H.; Shin, J. Y.; Heo, J. H.

2017-12-01

Multivariate frequency analysis has been developing for hydro-meteorological data such as rainfall, flood, and drought. Particularly, the copula has been used as a useful tool for multivariate probability model which has no limitation on deciding marginal distributions. The time-series rainfall data can be characterized to rainfall event by inter-event time definition (IETD) and each rainfall event has a rainfall depth and rainfall duration. In addition, nonstationarity in rainfall event has been studied recently due to climate change and trend detection of rainfall event is important to determine the data has nonstationarity or not. With the rainfall depth and duration of a rainfall event, trend detection and nonstationary bivariate frequency analysis has performed in this study. 62 stations from Korea Meteorological Association (KMA) over 30 years of hourly recorded data used in this study and the suitability of nonstationary copula for rainfall event has examined by the goodness-of-fit test.

Inference of Global Mean Temperature Trend and Climate Change from MSU and AMSU

NASA Technical Reports Server (NTRS)

Prabhakara, Cuddapah; Iacovazzi, R. A., Jr.; Yoo, J.-M.; Lau, William K. M. (Technical Monitor)

2001-01-01

Microwave Sounding Unit (MSU) and Advanced MSU (AMSU) radiometers flown on the NOAA operational satellite series are potentially valuable as global temperature monitoring devices. Spencer and Christy pioneered the analysis of mid-tropospheric temperature, given by MSU Channel 2 (Ch 2) at 53.74 GHz, to derive the global temperature trend. Also, in addition to monitoring global temperature, these microwave radiometers have the potential to reveal interannual climate signals in tropics. We have analyzed the data of MSU Ch 2 and AMSU Ch 5 (53.6 GHz) from the NOAA operational satellites for the period 1980 to 2000, utilizing the NOAA calibration procedure. The data are corrected for the satellite orbital drift based on the temporal changes of the on-board warm blackbody temperature. From our analysis, we find that the global temperature increased at a rate of 0.13 +/- 0.05 Kdecade(sup -1) during 1980 to 2000. From an Empirical Orthogonal Function (EOF) analysis of the MSU global data, we find that the mid-tropospheric temperature in middle and high latitudes responds to the ENSO forcing during the Northern Hemisphere Winter in a distinct manner. This mid-latitude response is opposite in phase to that in the tropics. This result is in accord with simulations performed with an ECMWF global spectral model. This study shows a potential use of the satellite observations for climatic change.

Drinking-water treatment, climate change, and childhood gastrointestinal illness projections for northern Wisconsin (USA) communities drinking untreated groundwater

NASA Astrophysics Data System (ADS)

Uejio, Christopher K.; Christenson, Megan; Moran, Colleen; Gorelick, Mark

2017-06-01

This study examined the relative importance of climate change and drinking-water treatment for gastrointestinal illness incidence in children (age <5 years) from period 2046-2065 compared to 1991-2010. The northern Wisconsin (USA) study focused on municipalities distributing untreated groundwater. A time-series analysis first quantified the observed (1991-2010) precipitation and gastrointestinal illness associations after controlling for seasonality and temporal trends. Precipitation likely transported pathogens into drinking-water sources or into leaking water-distribution networks. Building on observed relationships, the second analysis projected how climate change and drinking-water treatment installation may alter gastrointestinal illness incidence. Future precipitation values were modeled by 13 global climate models and three greenhouse-gas emissions levels. The second analysis was rerun using three pathways: (1) only climate change, (2) climate change and the same slow pace of treatment installation observed over 1991-2010, and (3) climate change and the rapid rate of installation observed over 2011-2016. The results illustrate the risks that climate change presents to small rural groundwater municipalities without drinking water treatment. Climate-change-related seasonal precipitation changes will marginally increase the gastrointestinal illness incidence rate (mean: ˜1.5%, range: -3.6-4.3%). A slow pace of treatment installation somewhat decreased precipitation-associated gastrointestinal illness incidence (mean: ˜3.0%, range: 0.2-7.8%) in spite of climate change. The rapid treatment installation rate largely decreases the gastrointestinal illness incidence (mean: ˜82.0%, range: 82.0-83.0%).

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

PubMed Central

Mantilla, Gilma; Oliveros, Hugo; Barnston, Anthony G

2009-01-01

Background Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Methods Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. Results The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Conclusion Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models. PMID:19133152

Effects of climate change on Salmonella infections.

PubMed

Akil, Luma; Ahmad, H Anwar; Reddy, Remata S

2014-12-01

Climate change and global warming have been reported to increase spread of foodborne pathogens. To understand these effects on Salmonella infections, modeling approaches such as regression analysis and neural network (NN) were used. Monthly data for Salmonella outbreaks in Mississippi (MS), Tennessee (TN), and Alabama (AL) were analyzed from 2002 to 2011 using analysis of variance and time series analysis. Meteorological data were collected and the correlation with salmonellosis was examined using regression analysis and NN. A seasonal trend in Salmonella infections was observed (p<0.001). Strong positive correlation was found between high temperature and Salmonella infections in MS and for the combined states (MS, TN, AL) models (R(2)=0.554; R(2)=0.415, respectively). NN models showed a strong effect of rise in temperature on the Salmonella outbreaks. In this study, an increase of 1°F was shown to result in four cases increase of Salmonella in MS. However, no correlation between monthly average precipitation rate and Salmonella infections was observed. There is consistent evidence that gastrointestinal infection with bacterial pathogens is positively correlated with ambient temperature, as warmer temperatures enable more rapid replication. Warming trends in the United States and specifically in the southern states may increase rates of Salmonella infections.

Annual and seasonal analysis of temperature and precipitation in Andorra (Pyrenees) from 1934 to 2008: quality check, homogenization and trends

NASA Astrophysics Data System (ADS)

Esteban, Pere; Prohom, Marc; Aguilar, Enric; Mestre, Olivier

2010-05-01

The analysis of temperature and precipitation change and variability in high elevations is a difficult issue due to the lack of long term climatic series in those environments. Nonetheless, it is important to evaluate how much high elevations follow the same climate evolution than low lying sites. In this work, using daily data from three Andorran weather stations (maintained by the power company Forces Elèctriques d'Andorra, FEDA), climate trends of annual and seasonal temperature and precipitation were obtained for the period 1934-2008. The series are complete (99.9%) and are located in a mountainous area ranging from 1110 m to 1600 m asl. As a previous step to the analysis, data rescue, quality control and homogeneity tests were applied to the daily data. For quality control, several procedures were applied to identify and flag suspicious or erroneous data: duplicated days, outliers, excessive differences between consecutive days, flat line checking, days with maximum temperature lower that minimum temperature, and rounding analysis. All the station sites were visited to gather the available metadata. Concerning homogeneity, a homogeneous climate time series is defined as one where variations are caused only by variations in climate and not to non-climatic factors (i.e., changes in site location, instruments, station environment…). As a result, homogeneity of the series was inspected from several methodologies that have been used in a complementary and independent way in order to attain solid results: C3-SNHT (with software developed under the Spanish Government Grant CGL2007-65546-C03-02), and Caussinus-Mestre (C-M) approaches. In both cases, tests were applied to mean annual temperature and precipitation series, using Catalan and French series as references (provided respectively by the Meteorological Service of Catalonia and Météo-France, in the framework of the Action COST-ES0601: Advances in homogenisation methods of climate series: an integrated approach, HOME). For precipitation, an additional test - RhTestV3 - was applied over the station data to ensure the homogeneity of the series. The analysis of the quality-controlled and homogenized maximum and minimum temperature series, shows an increase and statistically significant trend for the period 1934-2008. More precisely, the results are significant for both approaches (C3-SNHT and C-M) and for annual maximum temperature (0.12 and 0.10°C/decade, respectively), maximum summer temperature (0.25 and 0.17°C/decade, respectively), and minimum winter temperature (0.18 and 0.11°C/decade, respectively). The results were also obtained for the period 1971-2008. It is observed that the upward trend of the temperature has been reinforced in Andorra for this most recent period. Regarding precipitation, with the application of different tests, non-significant results for all the seasons and for the whole period (1934-2008) were obtained, so it cannot be concluded any increasing or decreasing trend. Nevertheless, preliminary results for the 1950-2008 period aim clearly towards a significant decrease of the annual total accumulation (-4.26mm/decade [being -7.80/-1.03, the confidence intervals at 95% level]), being especially relevant and also significant for the summer totals (-2.44 mm/decade [being -3.74/-1.13, the confidence intervals at 95% level]). The obtained trends for temperature agree with those obtained in Spain (Brunet et al., 2007), France (Spagnoli et al., 2002 and Maris et al., 2009) and Catalonia (Meteorological Service of Catalonia, 2008). Bibliography: - Brunet M, Jones PD, Sigró J, Saladié O, Aguilar E, Moberg A, Della-Marta PM, Lister D, Whalter A, López D. 2007. Temporal and spatial temperature variability and change over Spain during 1850-2005. Journal of Geophysical Research,, 112, D12117, doi:10.1029/2006JD008249 - Butlletí Anual d'Indicadors Climàtics, 2008 (BAIC,2008). Àrea de Climatologia, Servei Meteorològic de Catalunya. (http://www.meteo.cat) - Spagnoli B, Planton S, Mestre O, Déqué M, Moisselin, JM (2002). Detecting climate change at a regional scale: the case of France. Geophys. Res. Lett., 29, n.10, pp. 91-94. - Maris M, Giraud G, Durand Y, Navarre JP, Mérindol L. 2009. Results of 50 years of climate reanalysis in the French Pyrenees (1958-2008) using SAFRAN and CROCUS models. International Snow Science Workshop, Davos 2009, Proceedings.

Influence of climate variability and urban areas on the flood events in Bari (Apulia, southern Italy)

NASA Astrophysics Data System (ADS)

Lonigro, Teresa; Polemio, Maurizio

2014-05-01

The Damaging Hydrogeological Events (DHEs) can be defined as the occurrence of one or more simultaneous phenomena, such as droughts, windstorms, heat waves, landslides, floods and secondary floods (i.e. rapid accumulation or pounding of surface water with very low flow velocity), causing damages. They represent a serious problem, especially in DHE-prone areas with growing urbanization, where the infiltration capability is limited by buildings and where the vulnerability is higher than other areas. The paper proposes a methodology, based on both historical and time series approaches, used for describing the influence of climatic variability and urban development on the number of phenomena observed. The historical approach is finalised to collect phenomenon historical data, very important for the comprehension of the evolution of a study area. Phenomenon historical data is useful for expanding the historical period of investigation in order to assess the occurrence trend of DHEs. The historical analysis of DHEs can support decision making and land-use planning, ultimately reducing natural risks. The time series approach includes the collection and the statistical analysis of climatic data (monthly rainfall, wet days, rainfall intensity, and temperature), useful to characterise the climate variations and trends and to roughly assess the effects of these trends on river discharge and on the triggering of landslides. The time series approach is completed by tools to analyse simultaneously all data types. The study of land use variations, with a special emphasis on the urban areas, is important to understand how the modifications occurred in the territory, especially in terms of vulnerability, could influence the occurrence of DHEs. The methodology can be applied simultaneously to floods and landslides and was tested considering the municipality of Bari (southern Italy), particularly affected by flood events. Since the climate trend (decreasing trend of rainfall and rainfall intensity and an increasing trend of wet days and temperatures) does not show favourable conditions for the increase of the annual number of damaging floods, its trend is increasing. The role of anthropogenic modifications and the mismanagement of risk-prone areas should be considered to justify the increasing occurrences of floods. A validation of this hypothesis comes from the study of land use modifications, carried out comparing different temporal levels of land use (from 1959 to 2006). The analysis shows, starting from 1959 to 2006, a significant increase in urban areas (of about 50%) on the entire regional territory. The municipality of Bari, the regional main town, has undergone a remarkable development of its urban areas, from 12.45 Km2 in 1959 to 58.82 Km2 in 2006. The consequent increased vulnerability of this area has been highlighted during the recent flood event occurred in 2005, which caused six casualties, numerous injuries and damages to roads, buildings, industries, agriculture, livestock and services. More details on previous results of this research activity were recently published (Polemio, 2010; Polemio and Lonigro, 2012). References Polemio M. (2010): Historical floods and a recent extreme rainfall event in the Murgia karstic environment (Southern Italy). Zeitschrift für Geomorphologie, 54(2): 195-219. Polemio M., Lonigro T. (2012): Variabilità climatica e ricorrenza delle calamità idrogeologiche in Puglia. Geologia dell'Ambiente, 2/2012: 262-266.

Contribution of environmental forcings to US runoff changes for the period 1950–2010

DOE PAGES

Forbes, Whitney L.; Mao, Jiafu; Jin, Mingzhou; ...

2018-05-04

Runoff in the United States is changing, and this study finds that the measured change is dependent on the geographic region and varies seasonally. Specifically, observed annual total runoff had an insignificant increasing trend in the US between 1950 and 2010, but this insignificance was due to regional heterogeneity with both significant and insignificant increases in the eastern, northern, and southern US, and a greater significant decrease in the western US. Trends for seasonal mean runoff also differed across regions. By region, the season with the largest observed trend was autumn for the east (positive), spring for the north (positive),more » winter for the south (positive), winter for the west (negative), and autumn for the US as a whole (positive). Based on the detection and attribution analysis using gridded WaterWatch runoff observations along with semi-factorial land surface model simulations from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we found that while the roles of CO 2 concentration, nitrogen deposition, and land use and land cover were inconsistent regionally and seasonally, the effect of climatic variations was detected for all regions and seasons, and the change in runoff could be attributed to climate change in summer and autumn in the south and in autumn in the west. It was also found that the climate-only and historical transient simulations consistently underestimated the runoff trends, possibly due to precipitation bias in the MsTMIP driver or within the models themselves.« less

Contribution of environmental forcings to US runoff changes for the period 1950–2010

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forbes, Whitney L.; Mao, Jiafu; Jin, Mingzhou

Runoff in the United States is changing, and this study finds that the measured change is dependent on the geographic region and varies seasonally. Specifically, observed annual total runoff had an insignificant increasing trend in the US between 1950 and 2010, but this insignificance was due to regional heterogeneity with both significant and insignificant increases in the eastern, northern, and southern US, and a greater significant decrease in the western US. Trends for seasonal mean runoff also differed across regions. By region, the season with the largest observed trend was autumn for the east (positive), spring for the north (positive),more » winter for the south (positive), winter for the west (negative), and autumn for the US as a whole (positive). Based on the detection and attribution analysis using gridded WaterWatch runoff observations along with semi-factorial land surface model simulations from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we found that while the roles of CO 2 concentration, nitrogen deposition, and land use and land cover were inconsistent regionally and seasonally, the effect of climatic variations was detected for all regions and seasons, and the change in runoff could be attributed to climate change in summer and autumn in the south and in autumn in the west. It was also found that the climate-only and historical transient simulations consistently underestimated the runoff trends, possibly due to precipitation bias in the MsTMIP driver or within the models themselves.« less

Identification of relationships between climate indices and long-term precipitation in South Korea using ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Kim, Taereem; Shin, Ju-Young; Kim, Sunghun; Heo, Jun-Haeng

2018-02-01

Climate indices characterize climate systems and may identify important indicators for long-term precipitation, which are driven by climate interactions in atmosphere-ocean circulation. In this study, we investigated the climate indices that are effective indicators of long-term precipitation in South Korea, and examined their relationships based on statistical methods. Monthly total precipitation was collected from a total of 60 meteorological stations, and they were decomposed by ensemble empirical mode decomposition (EEMD) to identify the inherent oscillating patterns or cycles. Cross-correlation analysis and stepwise variable selection were employed to select the significant climate indices at each station. The climate indices that affect the monthly precipitation in South Korea were identified based on the selection frequencies of the selected indices at all stations. The NINO12 indices with four- and ten-month lags and AMO index with no lag were identified as indicators of monthly precipitation in South Korea. Moreover, they indicate meaningful physical information (e.g. periodic oscillations and long-term trend) inherent in the monthly precipitation. The NINO12 indices with four- and ten- month lags was a strong indicator representing periodic oscillations in monthly precipitation. In addition, the long-term trend of the monthly precipitation could be explained by the AMO index. A multiple linear regression model was constructed to investigate the influences of the identified climate indices on the prediction of monthly precipitation. Three identified climate indices successfully explained the monthly precipitation in the winter dry season. Compared to the monthly precipitation in coastal areas, the monthly precipitation in inland areas showed stronger correlation to the identified climate indices.

Role of volcanic and anthropogenic aerosols in the recent global surface warming slowdown

NASA Astrophysics Data System (ADS)

Smith, Doug M.; Booth, Ben B. B.; Dunstone, Nick J.; Eade, Rosie; Hermanson, Leon; Jones, Gareth S.; Scaife, Adam A.; Sheen, Katy L.; Thompson, Vikki

2016-10-01

The rate of global mean surface temperature (GMST) warming has slowed this century despite the increasing concentrations of greenhouse gases. Climate model experiments show that this slowdown was largely driven by a negative phase of the Pacific Decadal Oscillation (PDO), with a smaller external contribution from solar variability, and volcanic and anthropogenic aerosols. The prevailing view is that this negative PDO occurred through internal variability. However, here we show that coupled models from the Fifth Coupled Model Intercomparison Project robustly simulate a negative PDO in response to anthropogenic aerosols implying a potentially important role for external human influences. The recovery from the eruption of Mount Pinatubo in 1991 also contributed to the slowdown in GMST trends. Our results suggest that a slowdown in GMST trends could have been predicted in advance, and that future reduction of anthropogenic aerosol emissions, particularly from China, would promote a positive PDO and increased GMST trends over the coming years. Furthermore, the overestimation of the magnitude of recent warming by models is substantially reduced by using detection and attribution analysis to rescale their response to external factors, especially cooling following volcanic eruptions. Improved understanding of external influences on climate is therefore crucial to constrain near-term climate predictions.

Landsat-based Analysis of Mountain Forest-tundra Ecotone Response to Climate Trends in Sayan Mountains

NASA Technical Reports Server (NTRS)

Kharuk, Viatcheslav I.; Im, Sergey T.; Ranson, K. Jon

2007-01-01

observations of temperatures Siberia has shown a several degree warming over the past 30 years. It is expected that forest will respond to warming at high latitudes through increased tree growth and northward or upward slope migration. migration. Tree response to climate trends is most likely observable in the forest-tundra ecotone, where temperature mainly limits tree growth. Making repeated satellite observations over several decades provides an opportunity to track vegetation response to climate change. Based on Landsat data of the Sayan Mountains, Siberia, there was an increase in forest stand crown closure and an upward tree-line shift in the of the forest-tundra ecotone during the last quarter of the 2oth century,. On-ground observations, supporting these results, also showed regeneration of Siberian pine in the alpine tundra, and the transformation of prostrate Siberian pine and fir into arboreal (upright) forms. During this time period sparse stands transformed into closed stands, with existing closed stands increasing in area at a rate of approx. 1 %/yr, and advancing their upper border at a vertical rate of approx. 1.0 m/yr. In addition, the vertical rate of regeneration propagation is approx. 5 m/yr. It was also found that these changes correlated positively with temperature trends

Small lakes show muted climate change signal in deepwater temperatures

USGS Publications Warehouse

Winslow, Luke A.; Read, Jordan S.; Hansen, Gretchen J. A.; Hanson, Paul C.

2015-01-01

Water temperature observations were collected from 142 lakes across Wisconsin, USA, to examine variation in temperature of lakes exposed to similar regional climate. Whole lake water temperatures increased across the state from 1990 to 2012, with an average trend of 0.042°C yr−1 ± 0.01°C yr−1. In large (>0.5 km2) lakes, the positive temperature trend was similar across all depths. In small lakes (<0.5 km2), the warming trend was restricted to shallow waters, with no significant temperature trend observed in water >0.5 times the maximum lake depth. The differing response of small versus large lakes is potentially a result of wind-sheltering reducing turbulent mixing magnitude in small lakes. These results demonstrate that small lakes respond differently to climate change than large lakes, suggesting that current predictions of impacts to lakes from climate change may require modification.

Implications of multi-scale sea level and climate variability for coastal resources

USGS Publications Warehouse

Karamperidou, Christina; Engel, Victor; Lall, Upmanu; Stabenau, Erik; Smith, Thomas J.

2013-01-01

While secular changes in regional sea levels and their implications for coastal zone management have been studied extensively, less attention is being paid to natural fluctuations in sea levels, whose interaction with a higher mean level could have significant impacts on low-lying areas, such as wetlands. Here, the long record of sea level at Key West, FL is studied in terms of both the secular trend and the multi-scale sea level variations. This analysis is then used to explore implications for the Everglades National Park (ENP), which is recognized internationally for its ecological significance, and is the site of the largest wetland restoration project in the world. Very shallow topographic gradients (3–6 cm per km) make the region susceptible to small changes in sea level. Observations of surface water levels from a monitoring network within ENP exhibit both the long-term trends and the interannual-to-(multi)decadal variability that are observed in the Key West record. Water levels recorded at four long-term monitoring stations within ENP exhibit increasing trends approximately equal to or larger than the long-term trend at Key West. Time- and frequency-domain analyses highlight the potential influence of climate mechanisms, such as the El Niño/Southern Oscillation and the North Atlantic Oscillation (NAO), on Key West sea levels and marsh water levels, and the potential modulation of their influence by the background state of the North Atlantic Sea Surface Temperatures. In particular, the Key West sea levels are found to be positively correlated with the NAO index, while the two series exhibit high spectral power during the transition to a cold Atlantic Multidecadal Oscillation (AMO). The correlation between the Key West sea levels and the NINO3 Index reverses its sign in coincidence with a reversal of the AMO phase. Water levels in ENP are also influenced by precipitation and freshwater releases from the northern boundary of the Park. The analysis of both climate variability and climate change in such wetlands is needed to inform management practices in coastal wetland zones around the world.

Evaluating collective significance of climatic trends: A comparison of methods on synthetic data

NASA Astrophysics Data System (ADS)

Huth, Radan; Dubrovský, Martin

2017-04-01

The common approach to determine whether climatic trends are significantly different from zero is to conduct individual (local) tests at each single site (station or gridpoint). Whether the number of sites where the trends are significantly non-zero can or cannot occur by random, is almost never evaluated in trend studies. That is, collective (global) significance of trends is ignored. We compare three approaches to evaluating collective statistical significance of trends at a network of sites, using the following statistics: (i) the number of successful local tests (a successful test means here a test in which the null hypothesis of no trend is rejected); this is a standard way of assessing collective significance in various applications in atmospheric sciences; (ii) the smallest p-value among the local tests (Walker test); and (iii) the counts of positive and negative trends regardless of their magnitudes and local significance. The third approach is a new procedure that we propose; the rationale behind it is that it is reasonable to assume that the prevalence of one sign of trends at individual sites is indicative of a high confidence in the trend not being zero, regardless of the (in)significance of individual local trends. A potentially large amount of information contained in trends that are not locally significant, which are typically deemed irrelevant and neglected, is thus not lost and is retained in the analysis. In this contribution we examine the feasibility of the proposed way of significance testing on synthetic data, produced by a multi-site stochastic generator, and compare it with the two other ways of assessing collective significance, which are well established now. The synthetic dataset, mimicking annual mean temperature on an array of stations (or gridpoints), is constructed assuming a given statistical structure characterized by (i) spatial separation (density of the station network), (ii) local variance, (iii) temporal and spatial autocorrelations, and (iv) the trend magnitude. The probabilistic distributions of the three test statistics (null distributions) and critical values of the tests are determined from multiple realizations of the synthetic dataset, in which no trend is imposed at each site (that is, any trend is a result of random fluctuations only). The procedure is then evaluated by determining the type II error (the probability of a false detection of a trend) in the presence of a trend with a known magnitude, for which the synthetic dataset with an imposed spatially uniform non-zero trend is used. A sensitivity analysis is conducted for various combinations of the trend magnitude and spatial autocorrelation.

Temperature and heat wave trends in northwest Mexico

NASA Astrophysics Data System (ADS)

Martínez-Austria, Polioptro F.; Bandala, Erick R.; Patiño-Gómez, Carlos

2016-02-01

Increase in temperature extremes is one of the main expected impacts of climate change, as well as one of the first signs of its occurrence. Nevertheless, results emerging from General Circulation Models, while sufficient for large scales, are not enough for forecasting local trends and, hence, the IPCC has called for local studies based on on-site data. Indeed, it is expected that climate extremes will be detected much earlier than changes in climate averages. Heat waves are among the most important and least studied climate extremes, however its occurrence has been only barely studied and even its very definition remains controversial. This paper discusses the observed changes in temperature trends and heat waves in Northwestern Mexico, one of the most vulnerable regions of the country. The climate records in two locations of the region are analyzed, including one of the cities with extreme climate in Mexico, Mexicali City in the state of Baja California and the Yaqui River basin at Sonora State using three different methodologies. Results showed clear trends on temperature increase and occurrence of heat waves in both of the study zones using the three methodologies proposed. As result, some policy making suggestion are included in order to increase the adaptability of the studied regions to climate change, particularly related with heat wave occurrence.

Agriculturally Relevant Climate Extremes and Their Trends in the World's Major Growing Regions

NASA Astrophysics Data System (ADS)

Zhu, Xiao; Troy, Tara J.

2018-04-01

Climate extremes can negatively impact crop production, and climate change is expected to affect the frequency and severity of extremes. Using a combination of in situ station measurements (Global Historical Climatology Network's Daily data set) and multiple other gridded data products, a derived 1° data set of growing season climate indices and extremes is compiled over the major growing regions for maize, wheat, soybean, and rice for 1951-2006. This data set contains growing season climate indices that are agriculturally relevant, such as the number of hot days, duration of dry spells, and rainfall intensity. Before 1980, temperature-related indices had few trends; after 1980, statistically significant warming trends exist for each crop in the majority of growing regions. In particular, crops have increasingly been exposed to extreme hot temperatures, above which yields have been shown to decline. Rainfall trends are less consistent compared to temperature, with some regions receiving more rainfall and others less. Anomalous temperature and precipitation conditions are shown to often occur concurrently, with dry growing seasons more likely to be hotter, have larger drought indices, and have larger vapor pressure deficits. This leads to the confluence of a variety of climate conditions that negatively impact crop yields. These results show a consistent increase in global agricultural exposure to negative climate conditions since 1980.

Long-term trends in climate and hydrology in an agricultural headwater watershed of central Pennsylvania, USA

Treesearch

Ray B. Bryant; Haiming Lu; Kyle R. Elkin; Anthony R. Buda; Amy S. Collick; Gordon J. Folmar; Peter J. Kleinman

2016-01-01

Climate change has emerged as a key issue facing agriculture and water resources in the US. Long-term (1968-2012) temperature, precipitation and streamflow data from a small (7.3 km2) watershed in east-central Pennsylvania was used to examine climatic and hydrologic trends in the context of recent climate change. Annual mean temperatures increased 0.38°C per decade,...

Striking Seasonality in the Secular Warming of the Northern Continents: Structure and Mechanisms

NASA Astrophysics Data System (ADS)

Nigam, S.; Thomas, N. P.

2017-12-01

The linear trend in twentieth-century surface air temperature (SAT)—a key secular warming signal— exhibits striking seasonal variations over Northern Hemisphere continents; SAT trends are pronounced in winter and spring but notably weaker in summer and fall. The SAT trends in historical twentieth-century climate simulations informing the Intergovernmental Panel for Climate Change's Fifth Assessment show varied (and often unrealistic) strength and structure, and markedly weaker seasonal variation. The large intra-ensemble spread of winter SAT trends in some historical simulations was surprising, especially in the context of century-long linear trends, with implications for the detection of the secular warming signal. The striking seasonality of observed secular warming over northern continents warrants an explanation and the representation of related processes in climate models. Here, the seasonality of SAT trends over North America is shown to result from land surface-hydroclimate interactions and, to an extent, also from the secular change in low-level atmospheric circulation and related thermal advection. It is argued that the winter dormancy and summer vigor of the hydrologic cycle over middle- to high-latitude continents permit different responses to the additional incident radiative energy from increasing greenhouse gas concentrations. The seasonal cycle of climate, despite its monotony, provides an expanded phase space for the exposition of the dynamical and thermodynamical processes generating secular warming, and an exceptional cost-effective opportunity for benchmarking climate projection models.

Trend Patterns of Vegetative Coverage and Their Underlying Causes in the Deserts of Northwest China over 1982 – 2008

PubMed Central

Zhang, Tianyi; Wang, Hesong

2015-01-01

We identified the spatiotemporal patterns of the Normalized Difference Vegetation Index (NDVI) for the years 1982–2008 in the desert areas of Northwest China and quantified the impacts of climate and non-climate factors on NDVI changes. The results indicate that although the mean NDVI has improved in 24.7% of the study region; 16.3% among the region has been stagnating in recent years and only 8.4% had a significantly increasing trend. Additionally, 45.3% of the region has maintained a stable trend over the study period and 30.0% has declined. A multiple regression model suggests that a wetter climate (quantified by the Palmer Drought Severity Index, PDSI) is associated with higher NDVI in most areas (18.1% of significance) but these historical changes in PDSI only caused an average improvement of approximately 0.4% over the study region. Contrasting the regression results under different trend patterns, no significant differences in PDSI impacts were detected among the four trend patterns. Therefore, we conclude that climate is not the primary driver for vegetative coverage in Northwest China. Future studies will be required to identify the impacts of specific non-climatic factors on vegetative coverage based on high-resolution data, which will be beneficial in creating an effective strategy to combat the recent desertification trend in China. PMID:25961563

Extent of Night Warming Differentiates the Temporal Trend of Tropical Greenness over 2001-2015

NASA Astrophysics Data System (ADS)

Yu, M.; Gao, Q.; Gao, C.; Wang, C.

2016-12-01

Tropical forests have essential functions in global C dynamic but vulnerable to changes in land cover land use (LCLUC) and climate. The tropics of Caribbean are experiencing warming and drying climate and diverse LCLUC. However, large-scale studies to detect long-term trends of C and associated mechanisms are still rare. Using MODIS Enhanced Vegetation Index (EVI), we investigated trend of greenness in the Greater Antilles Caribbean during 2000 - 2015 and further analyzed the trend of vegetation patches without LCLUC to separate the climate impacts. We hypothesized that rainfall decrease or/and warming would reduce EVI in this tropical region. All five countries showed significantly decreasing EVI except Cuba of which EVI was increasing partly due to strong reforestation. Haiti has the steepest decreasing EVI due to its deforestation for charcoals. EVI trend varied greatly even for patches without LCLUC, tending to decrease in the windward but increase in the leeward of the island Puerto Rico. Contrary to our intuition, the rainfall was mostly increasing. However the rising night temperature significantly and negatively correlates with the spatial pattern of EVI trends. Although the cooled daytime and increased rainfall might enhance EVI, night warming dominated the climate impacts and differentiated the EVI trend.

National Variation in Crop Yield Production Functions

NASA Astrophysics Data System (ADS)

Devineni, N.; Rising, J. A.

2017-12-01

A new multilevel model for yield prediction at the county scale using regional climate covariates is presented in this paper. A new crop specific water deficit index, growing degree days, extreme degree days, and time-trend as an approximation of technology improvements are used as predictors to estimate annual crop yields for each county from 1949 to 2009. Every county in the United States is allowed to have unique parameters describing how these weather predictors are related to yield outcomes. County-specific parameters are further modeled as varying according to climatic characteristics, allowing the prediction of parameters in regions where crops are not currently grown and into the future. The structural relationships between crop yield and regional climate as well as trends are estimated simultaneously. All counties are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. The model captures up to 60% of the variability in crop yields after removing the effect of technology, does well in out of sample predictions and is useful in relating the climate responses to local bioclimatic factors. We apply the predicted growing models in a cost-benefit analysis to identify the most economically productive crop in each county.

Analysis of near-shore sea surface temperatures in the Northern Pacific

EPA Science Inventory

Recent studies report a warming trend in Pacific Ocean temperatures over the last 50 years. However, much less is known about temperature change in the near-coastal environment, which is particularly sensitive to climatic change. In near-shore regions in situ sea surface temper...

Drought risk assessment under climate change is sensitive to methodological choices for the estimation of evaporative demand.

PubMed

Dewes, Candida F; Rangwala, Imtiaz; Barsugli, Joseph J; Hobbins, Michael T; Kumar, Sanjiv

2017-01-01

Several studies have projected increases in drought severity, extent and duration in many parts of the world under climate change. We examine sources of uncertainty arising from the methodological choices for the assessment of future drought risk in the continental US (CONUS). One such uncertainty is in the climate models' expression of evaporative demand (E0), which is not a direct climate model output but has been traditionally estimated using several different formulations. Here we analyze daily output from two CMIP5 GCMs to evaluate how differences in E0 formulation, treatment of meteorological driving data, choice of GCM, and standardization of time series influence the estimation of E0. These methodological choices yield different assessments of spatio-temporal variability in E0 and different trends in 21st century drought risk. First, we estimate E0 using three widely used E0 formulations: Penman-Monteith; Hargreaves-Samani; and Priestley-Taylor. Our analysis, which primarily focuses on the May-September warm-season period, shows that E0 climatology and its spatial pattern differ substantially between these three formulations. Overall, we find higher magnitudes of E0 and its interannual variability using Penman-Monteith, in particular for regions like the Great Plains and southwestern US where E0 is strongly influenced by variations in wind and relative humidity. When examining projected changes in E0 during the 21st century, there are also large differences among the three formulations, particularly the Penman-Monteith relative to the other two formulations. The 21st century E0 trends, particularly in percent change and standardized anomalies of E0, are found to be sensitive to the long-term mean value and the amplitude of interannual variability, i.e. if the magnitude of E0 and its interannual variability are relatively low for a particular E0 formulation, then the normalized or standardized 21st century trend based on that formulation is amplified relative to other formulations. This is the case for the use of Hargreaves-Samani and Priestley-Taylor, where future E0 trends are comparatively much larger than for Penman-Monteith. When comparing Penman-Monteith E0 responses between different choices of input variables related to wind speed, surface roughness, and net radiation, we found differences in E0 trends, although these choices had a much smaller influence on E0 trends than did the E0 formulation choices. These methodological choices and specific climate model selection, also have a large influence on the estimation of trends in standardized drought indices used for drought assessment operationally. We find that standardization tends to amplify divergences between the E0 trends calculated using different E0 formulations, because standardization is sensitive to both the climatology and amplitude of interannual variability of E0. For different methodological choices and GCM output considered in estimating E0, we examine potential sources of uncertainty in 21st century trends in the Standardized Precipitation Evapotranspiration Index (SPEI) and Evaporative Demand Drought Index (EDDI) over selected regions of the CONUS to demonstrate the practical implications of these methodological choices for the quantification of drought risk under climate change.

A climate trend analysis of Sudan

USGS Publications Warehouse

Funk, Christopher C.; Eilerts, Gary; Verdin, Jim; Rowland, Jim; Marshall, Michael

2011-01-01

Summer rains in western and southern Sudan have declined by 10-20 percent since the mid-1970s. Observed warming of more than 1 degree Celsius is equivalent to another 10-20 percent reduction in rainfall for crops. The warming and drying have impacted southern Darfur and areas around Juba. Rainfall declines west of Juba threaten southern Sudan's future food production prospects. In many cases, areas with changing climate are coincident with zones of substantial conflict, suggesting some degree of association; however, the contribution of climate change to these conflicts is not currently understood. Rapid population growth and the expansion of farming and pastoralism under a more variable climate regime could dramatically increase the number of at-risk people in Sudan over the next 20 years.

A natural resource condition assessment for Sequoia and Kings Canyon National Parks: Appendix 22: climatic change

USGS Publications Warehouse

Das, Adrian J.; Stephenson, Nathan L.

2013-01-01

30-year time periods -- the Independence station, with a relatively continuous temperature record starting in 1925 -- shows a modest warming, not a cooling, between 1925-1940 and 1971-2000, further casting doubt on the Kings Canyon cooling shown in Figs. 6 and 11 of Appendix 1. If funds become available, it will be useful to more formally analyze potential PRISM biases in long-term SEKI climatic trends. Until then, the analyses of individual weather station records presented here (effectively an analysis of source data that PRISM uses) are meant to provide a robust summary of climatic changes in SEKI.

Trends in seasonal warm anomalies across the contiguous United States: Contributions from natural climate variability

Treesearch

Lejiang Yu; Shiyuan Zhong; Warren E. Heilman; Xindi Bian

2018-01-01

Many studies have shown the importance of anthropogenic greenhouse gas emissions in contributing to observed upward trends in the occurrences of temperature extremes over the U.S. However, few studies have investigated the contributions of internal variability in the climate system to these observed trends. Here we use daily maximum temperature time series from the...

Understanding the Seasonal Greenness Trends and Controls in South Asia Using Satellite Based Observations

NASA Astrophysics Data System (ADS)

Sarmah, S.; Jia, G.; Zhang, A.; Singha, M.

2017-12-01

South Asia (SA) is one of the most remarkable regions in changing vegetation greenness along with its major expansion of agricultural activity, especially irrigated farming. However, SA is predicted to be a vulnerable agricultural regions to future climate changes. The influence of monsoon climate on the seasonal trends and anomalies of vegetation greenness are not well understood in the region which can provide valuable information about climate-ecosystem interaction. This study analyzed the spatio-temporal patterns of seasonal vegetation trends and variability using satellite vegetation indices (VI) including AVHRR Normalized Difference Vegetation Index (NDVI) (1982-2013) and MODIS Enhanced Vegetation Index (EVI) (2000-2013) in summer monsoon (SM) (June-Sept) and winter monsoon (WM) (Dec-Apr) seasons among irrigated cropland (IC), rainfed cropland (RC) and natural vegetation (NV). Seasonal VI variations with climatic factors (precipitation and temperature) and LULC changes have been investigated to identify the forcings behind the vegetation trends and variability. We found that major greening occurred in the last three decades due to the increase in IC productivity noticeably in WM, however, recent (2000-2013) greening trends were lower than the previous decades (1982-1999) in both the IC and RC indicating the stresses on them. The browning trends, mainly concentrated in NV areas were prominent during WM and rigorous since 2000, confirmed from the moderate resolution EVI and LULC datasets. Winter time maximal temperature had been increasing tremendously whereas precipitation trend was not significant over SA. Both the climate variability and LULC changes had integrated effects on the vegetation changes in NV areas specifically in hilly regions. However, LULC impact was intensified since 2000, mostly in north east India. This study also revealed a distinct seasonal variation in spatial distribution of correlation between VI's and climate anomalies over SA. Concluding, so far SA has managed to get a decent productivity over croplands due to the advanced cultivation techniques which likely to be at risk under future warming climate. Also NV areas of SA are in constant threat from the anthropogenic activities and climate changes.

Pollen record of the mid- to late-Holocene centennial climate change on the East coast of South Korea and its influential factors

NASA Astrophysics Data System (ADS)

Song, Bing; Yi, Sangheon; Jia, Hongjuan; Nahm, Wook-Hyun; Kim, Jin-Cheul; Lim, Jaesoo; Lee, Jin-Young; Sha, Longbin; Mao, Limi; Yang, Zhongyong; Nakanishi, Toshimichi; Hong, Wan; Li, Zhen

2018-01-01

To understand historical climate change in western Pacific coastal areas, a sediment core (SOJ-2) from the stable sedimentary environment of the Songjiho Lagoon on the east coast of South Korea was obtained for centennial-resolution palynological analysis. The ages of the SOJ-2 core is well controlled by carbon 14 dating with high-resolution accelerator mass spectrometry (AMS), and the results indicated a general warm to cold climate trend from the mid-Holocene to the present, which can be divided into two different stages: a warmer stage between 6842 and 1297 cal yr BP and a colder stage from 1297 cal yr BP to the present, with fluctuations during these stages. The climate was wetter from 6842 to 6227 cal yr BP and 4520 to 1297 cal yr BP and was drier from 6227 to 4520 cal yr BP. The climate changed to cold and dry during the period from 1297-425 cal yr BP. The impact of human activity on the climate began at approximately 1297 cal yr BP and became pronounced starting in 425 cal yr BP. The general cooling trend may represent a response to decreasing solar insolation; however, the relative dryness or wetness of the climate may have been co-determined by westerlies and the East Asian summer monsoon (EASM). The climate had a teleconnection with the North Atlantic region, resulting from changes in solar activity. Nevertheless, EI Niño-Southern Oscillation (ENSO) activity played an important role in impacting the EASM changes in western Pacific coastal areas.

Historical Change of Equilibrium Water Temperature in Japan

NASA Astrophysics Data System (ADS)

Miyamoto, H.

2015-12-01

Changes in freshwater ecosystems due to a climate change have been great concern for sustainable river basin management both for water resources utilization and ecological conservation. However, their impact seems to be difficult to evaluate because of wide variety of basin characteristics along a river network both in nature and social environment. This presentation uses equilibrium water temperature as a simple criterion index for evaluating the long-term changes of stream thermal environment due to the historical climate change in Japan. It examines, at first, the relationship between the equilibrium water temperature and the stream temperature observed for 7 years at a lower reach in the Ibo River, Japan. It analyzes, then, the seasonal and regional trends of the equilibrium water temperature change for the last 50 years at 133 meteorological station sites throughout Japan, discussing their rising or falling characteristics. The correlation analysis at the local reach of the Ibo River shows that the equilibrium water temperature has similar trend of change as the stream temperature. However, its value tends to be higher than the stream temperature in summer, while lower in winter. The onset of the higher equilibrium water temperature fluctuates annually from mid February to early April. This onset fluctuation at each spring could be influenced by the different amount of snow at the antecedent winter. The rising or falling trends of the equilibrium water temperature are analyzed both annually and seasonally through the regression analysis of the 133 sites in Japan. Consequently, the trends of the temperature change could be categorized by 12 patterns. As for the seasonal analysis, the results shows that there are many sites indicating the falling trend in spring and summer, and rising trends in autumn and winter. In particular, winter has the strong rising tendency throughout Japan. As for the regional analysis, the result illustrates the precise rationality; e.g., northern parts of Japan show the temperature fall in spring and the temperature rise in autumn, while the urbanized regions along the Pacific coastline indicate the temperature rise in all the four seasons.

Trend in land degradation has been the most contended issue in the Sahel. Trends documented have not been consistent across authors and science disciplines, hence little agreement has been gained on the magnitude and direction of land degradation in the Sahel. Differentiated science outputs are related to methods and data used at various scales.

NASA Astrophysics Data System (ADS)

Mbow, C.; Brandt, M.; Fensholt, R.; Ouedraogo, I.; Tagesson, T.

2015-12-01

Thematic gaps in land degradation trends in the SahelTrend in land degradation has been the most contended issue for arid and semi-arid regions. In the Sahel, depending to scale of analysis and methods and data used, the trend documented have not been consistent across authors and science disciplines. The assessment of land degradation and the quantification of its effects on land productivity have been assessed for many decades, but little agreement has been gained on the magnitude and direction in the Sahel. This lack of consistency amid science outputs can be related to many methodological underpinnings and data used for various scales of analysis. Assessing biophysical trends on the ground requires long-term ground-based data collection to evaluate and better understand the mechanisms behind land dynamics. The Sahel is seen as greening by many authors? Is that greening geographically consistent? These questions enquire the importance of scale analysis and related drivers. The questions addressed are not only factors explaining loss of tree cover but also regeneration of degraded land. The picture used is the heuristic cycle model to assess loss and damages vs gain and improvements of various land use practices. The presentation will address the following aspects - How much we know from satellite data after 40 years of remote sensing analysis over the Sahel? That section discuss agreement and divergences of evidences and differentiated interpretation of land degradation in the Sahel. - The biophysical factors that are relevant for tracking land degradation in the Sahel. Aspects such detangling human to climate factors and biophysical factors behind land dynamics will be presented - Introduce some specific cases of driver of land architecture transition under the combined influence of climate and human factor. - Based on the above we will conclude with some key recommendations on how to improve land degradation assessment in the Arid region of the Sahel.

Risk assessments of regional climate change over Europe: generation of probabilistic ensemble and uncertainty assessment for EURO-CODEX

NASA Astrophysics Data System (ADS)

Yuan, J.; Kopp, R. E.

2017-12-01

Quantitative risk analysis of regional climate change is crucial for risk management and impact assessment of climate change. Two major challenges to assessing the risks of climate change are: CMIP5 model runs, which drive EURO-CODEX downscaling runs, do not cover the full range of uncertainty of future projections; Climate models may underestimate the probability of tail risks (i.e. extreme events). To overcome the difficulties, this study offers a viable avenue, where a set of probabilistic climate ensemble is generated using the Surrogate/Model Mixed Ensemble (SMME) method. The probabilistic ensembles for temperature and precipitation are used to assess the range of uncertainty covered by five bias-corrected simulations from the high-resolution (0.11º) EURO-CODEX database, which are selected by the PESETA (The Projection of Economic impacts of climate change in Sectors of the European Union based on bottom-up Analysis) III project. Results show that the distribution of SMME ensemble is notably wider than both distribution of raw ensemble of GCMs and the spread of the five EURO-CORDEX in RCP8.5. Tail risks are well presented by the SMME ensemble. Both SMME ensemble and EURO-CORDEX projections are aggregated to administrative level, and are integrated into impact functions of PESETA III to assess climate risks in Europe. To further evaluate the uncertainties introduced by the downscaling process, we compare the 5 runs from EURO-CORDEX with runs from the corresponding GCMs. Time series of regional mean, spatial patterns, and climate indices are examined for the future climate (2080-2099) deviating from the present climate (1981-2010). The downscaling processes do not appear to be trend-preserving, e.g. the increase in regional mean temperature from EURO-CORDEX is slower than that from the corresponding GCM. The spatial pattern comparison reveals that the differences between each pair of GCM and EURO-CORDEX are small in winter. In summer, the temperatures of EURO-CORDEX are generally lower than those of GCMs, while the drying trends in precipitation of EURO-CORDEX are smaller than those of GCMs. Climate indices are significantly affected by bias-correction and downscaling process. Our study provides valuable information for selecting climate indices in different regions over Europe.

Climate-change driven increase in high intensity rainfall events: Analysis of development in the last decades and towards an extrapolation of future progression

NASA Astrophysics Data System (ADS)

Müller, Eva; Pfister, Angela; Gerd, Büger; Maik, Heistermann; Bronstert, Axel

2015-04-01

Hydrological extreme events can be triggered by rainfall on different spatiotemporal scales: river floods are typically caused by event durations of between hours and days, while urban flash floods as well as soil erosion or contaminant transport rather result from storms events of very short duration (minutes). Still, the analysis of climate change impacts on rainfall-induced extreme events is usually carried out using daily precipitation data at best. Trend analyses of extreme rainfall at sub-daily or even sub-hourly time scales are rare. In this contribution two lines of research are combined: first, we analyse sub-hourly rainfall data for several decades in three European regions.Second, we investigate the scaling behaviour of heavy short-term precipitation with temperature, i.e. the dependence of high intensity rainfall on the atmospheric temperature at that particular time and location. The trend analysis of high-resolution rainfall data shows for the first time that the frequency of short and intensive storm events in the temperate lowland regions in Germany has increased by up to 0.5 events per year over the last decades. I.e. this trend suggests that the occurrence of these types of storms have multiplied over only a few decades. Parallel to the changes in the rainfall regime, increases in the annual and seasonal average temperature and changes in the occurrence of circulation patterns responsible for the generation of high-intensity storms have been found. The analysis of temporally highly resolved rainfall records from three European regions further indicates that extreme precipitation events are more intense with warmer temperatures during the rainfall event. These observations follow partly the Clausius-Clapeyron relation. Based on this relation one may derive a general rule of maximum rainfall intensity associated to the event temperature, roughly following the Clausius-Clapeyron (CC) relation. This rule might be used for scenarios of future maximum rainfall intensities under a warming climate.

Recent surface cooling in the Yellow and East China Seas and the associated North Pacific climate regime shift

NASA Astrophysics Data System (ADS)

Kim, Yong Sun; Jang, Chan Joo; Yeh, Sang-Wook

2018-03-01

The Yellow and East China Seas (YECS) are widely believed to have experienced robust, basin-scale warming over the last few decades. However, the warming reached a peak in the late 1990s, followed by a significant cooling trend. In this study, we investigated the characteristics of this low-frequency sea surface temperature (SST) variance and its dynamic relationship with large-scale climate variability through cyclostationary orthogonal function analysis for the 1982-2014 period. Both regressed surface winds on the primary mode of the YECS SST and trends in air-sea heat fluxes demonstrate that the intensification of the northerly winds in winter contribute largely to the recent cooling trend by increasing heat loss to the atmosphere. As a localized oceanic response to these winds, the upwind flow seems to bring warm waters and partially counteracts the basin-scale cooling, thus contributing to a weakening of the cooling trend along the central trough of the Yellow Sea. In the context of the large-scale climate variabilities, a strong relationship between the YECS SST variability and Pacific Decadal Oscillation (PDO) became weak considerably during the recent cooling period after the late 1990s as the PDO signals appeared to be confined within the eastern basin of the North Pacific in association with the regime shift. In addition to this decoupling of the YECS SST from the PDO, the intensifying Siberian High pressure system likely caused the enhanced northerly winds, leading to the recent cooling trend. These findings highlight relative roles of the PDO and the Siberian High in shaping the YECS SST variance through the changes in the large-scale atmospheric circulation and attendant oceanic advection.

Placing the Common Era in a Holocene context: millennial to centennial patterns and trends in the hydroclimate of North America over the past 2000 years

NASA Astrophysics Data System (ADS)

Shuman, Bryan N.; Routson, Cody; McKay, Nicholas; Fritz, Sherilyn; Kaufman, Darrell; Kirby, Matthew E.; Nolan, Connor; Pederson, Gregory T.; St-Jacques, Jeannine-Marie

2018-05-01

A synthesis of 93 hydrologic records from across North and Central America, and adjacent tropical and Arctic islands, reveals centennial to millennial trends in the regional hydroclimates of the Common Era (CE; past 2000 years). The hydrological records derive from materials stored in lakes, bogs, caves, and ice from extant glaciers, which have the continuity through time to preserve low-frequency ( > 100 year) climate signals that may extend deeper into the Holocene. The most common pattern, represented in 46 (49 %) of the records, indicates that the centuries before 1000 CE were drier than the centuries since that time. Principal component analysis indicates that millennial-scale trends represent the dominant pattern of variance in the southwestern US, northeastern US, mid-continent, Pacific Northwest, Arctic, and tropics, although not all records within a region show the same direction of change. The Pacific Northwest and the southernmost tier of the tropical sites tended to dry toward present, as many other areas became wetter than before. In 22 records (24 %), the Medieval Climate Anomaly period (800-1300 CE) was drier than the Little Ice Age (1400-1900 CE), but in many cases the difference was part of the longer millennial-scale trend, and, in 25 records (27 %), the Medieval Climate Anomaly period represented a pluvial (wet) phase. Where quantitative records permitted a comparison, we found that centennial-scale fluctuations over the Common Era represented changes of 3-7 % in the modern interannual range of variability in precipitation, but the accumulation of these long-term trends over the entirety of the Holocene caused recent centuries to be significantly wetter, on average, than most of the past 11 000 years.

Is the Pearl River basin, China, drying or wetting? Seasonal variations, causes and implications

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Li, Jianfeng; Gu, Xihui; Shi, Peijun

2018-07-01

Soil moisture plays crucial roles in the hydrological cycle and is also a critical link between land surface and atmosphere. The Pearl River basin (PRb) is climatically subtropical and tropical and is highly sensitive to climate changes. In this study, seasonal soil moisture changes across the PRb were analyzed using the Variable Infiltration Capacity (VIC) model forced by the gridded 0.5° × 0.5° climatic observations. Seasonal changes of soil moisture in both space and time were investigated using the Mann-Kendall trend test method. Potential influencing factors behind seasonal soil moisture changes such as precipitation and temperature were identified using the Maximum Covariance Analysis (MCA) technique. The results indicated that: (1) VIC model performs well in describing changing properties of soil moisture across the PRb; (2) Distinctly different seasonal features of soil moisture can be observed. Soil moisture in spring decreased from east to west parts of the PRb. In summer however, soil moisture was higher in east and west parts but was lower in central parts of the PRb; (3) A significant drying trend was identified over the PRb in autumn, while no significant drying trends can be detected in other seasons; (4) The increase/decrease in precipitation can generally explain the wetting/drying tendency of soil moisture. However, warming temperature contributed significantly to the drying trends and these drying trends were particularly evident during autumn and winter; (5) Significant decreasing precipitation and increasing temperature combined to trigger substantially decreasing soil moisture in autumn. In winter, warming temperature is the major reason behind decreased soil moisture although precipitation is in slightly decreasing tendency. Season variations of soil moisture and related implications for hydro-meteorological processes in the subtropical and tropical river basins over the globe should arouse considerable human concerns.

An Intensified Arctic Water Cycle? Trend Analysis of the Arctic System Freshwater Cycle: Observations and Expectations

NASA Astrophysics Data System (ADS)

Rawlins, M. A.; Adam, J. C.; Vorosmarty, C. J.; Serreze, M. C.; Hinzman, L. D.; Holland, M.; Shiklomanov, A.

2007-12-01

It is expected that a warming climate will be attended by an intensification of the global hydrological cycle. While there are signs of positive trends in several hydrological quantities emerging at the global scale, the scope, character, and quantitative significance of these changes are not well established. In particular, long-term increases in river discharge across Arctic Eurasia are assumed to represent such an intensification and have received considerable attention. Yet, no change in long-term annual precipitation across the region can be related with the discharge trend. Given linkages and feedbacks between the arctic and global climate systems, a more complete understanding of observed changes across northern high latitudes is needed. We present a working definition of an accelerated or intensified hydrological cycle and a synthesis of long-term (nominally 50 years) trends in observed freshwater stocks and fluxes across the arctic land-atmosphere-ocean system. Trend and significance measures from observed data are described alongside expectations of intensification based on GCM simulations of contemporary and future climate. Our domain of interest includes the terrestrial arctic drainage (including all of Alaska and drainage to Hudson Bay), the Arctic Ocean, and the atmosphere over the land and ocean domains. For the terrestrial Arctic, time series of spatial averages which are derived from station data and atmospheric reanalysis are available. Reconstructed data sets are used for quantities such as Arctic Ocean ice and liquid freshwater transports. Study goals include a comprehensive survey of past changes in freshwater across the pan-arctic and a set of benchmarks for expected changes based on an ensemble of GCM simulations, and identification of potential mechanistic linkages which may be examined with contemporary remote sensing data sets.

Spatiotemporal changes in precipitation extremes over Yangtze River basin, China, considering the rainfall shift in the late 1970s

NASA Astrophysics Data System (ADS)

Gao, Tao; Xie, Lian

2016-12-01

Precipitation extremes are the dominated causes for the formation of severe flood disasters at regional and local scales under the background of global climate change. In the present study, five annual extreme precipitation events, including 1, 7 and 30 day annual maximum rainfall and 95th and 97.5th percentile threshold levels, are analyzed relating to the reference period 1960-2011 from 140 meteorological stations over Yangtze River basin (YRB). A generalized extreme value (GEV) distribution is applied to fit annual and percentile extreme precipitation events at each station with return periods up to 200 years. The entire time period is divided into preclimatic (preceding climatic) period 1960-1980 and aftclimatic (after climatic) period 1981-2011 by considering distinctly abrupt shift of precipitation regime in the late 1970s across YRB. And the Mann-Kendall trend test is adopted to conduct trend analysis during pre- and aftclimatic periods, respectively, for the purpose of exploring possible increasing/decreasing patterns in precipitation extremes. The results indicate that the increasing trends for return values during aftclimatic period change significantly in time and space in terms of different magnitudes of extreme precipitation, while the stations with significantly positive trends are mainly distributed in the vicinity of the mainstream and major tributaries as well as large lakes, this would result in more tremendous flood disasters in the mid-lower reaches of YRB, especially in southeast coastal regions. The increasing/decreasing linear trends based on annual maximum precipitation are also investigated in pre- and aftclimatic periods, respectively, whereas those changes are not significantly similar to the variations of return values during both subperiods. Moreover, spatiotemporal patterns of precipitation extremes become more uneven and unstable in the second half period over YRB.

Short-term climate change impacts on Mara basin hydrology

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Roy, T.; Valdés, J. B.; Lyon, B.; Valdés-Pineda, R.; Serrat-Capdevila, A.; Durcik, M.; Gupta, H.

2017-12-01

The predictability of climate diminishes significantly at shorter time scales (e.g. decadal). Both natural variability as well as sampling variability of climate can obscure or enhance climate change signals in these shorter scales. Therefore, in order to assess the impacts of climate change on basin hydrology, it is important to design climate projections with exhaustive climate scenarios. In this study, we first create seasonal climate scenarios by combining (1) synthetic precipitation projections generated from a Vector Auto-Regressive (VAR) model using the University of East Anglia Climate Research Unit (UEA-CRU) data with (2) seasonal trends calculated from 31 models in the Coupled Model Intercomparison Project Phase 5 (CMIP). The seasonal climate projections are then disaggregated to daily level using the Agricultural Modern-Era Retrospective Analysis for Research and Applications (AgMERRA) data. The daily climate data are then bias-corrected and used as forcings to the land-surface model, Variable Infiltration Capacity (VIC), to generate different hydrological projections for the Mara River basin in East Africa, which are then evaluated to study the hydrologic changes in the basin in the next three decades (2020-2050).

On the use of Empirical Data to Downscale Non-scientific Scepticism About Results From Complex Physical Based Models

NASA Astrophysics Data System (ADS)

Germer, S.; Bens, O.; Hüttl, R. F.

2008-12-01

The scepticism of non-scientific local stakeholders about results from complex physical based models is a major problem concerning the development and implementation of local climate change adaptation measures. This scepticism originates from the high complexity of such models. Local stakeholders perceive complex models as black-box models, as it is impossible to gasp all underlying assumptions and mathematically formulated processes at a glance. The use of physical based models is, however, indispensible to study complex underlying processes and to predict future environmental changes. The increase of climate change adaptation efforts following the release of the latest IPCC report indicates that the communication of facts about what has already changed is an appropriate tool to trigger climate change adaptation. Therefore we suggest increasing the practice of empirical data analysis in addition to modelling efforts. The analysis of time series can generate results that are easier to comprehend for non-scientific stakeholders. Temporal trends and seasonal patterns of selected hydrological parameters (precipitation, evapotranspiration, groundwater levels and river discharge) can be identified and the dependence of trends and seasonal patters to land use, topography and soil type can be highlighted. A discussion about lag times between the hydrological parameters can increase the awareness of local stakeholders for delayed environment responses.

Separating Vegetation Greening and Climate Change Controls on Evapotranspiration trend over the Loess Plateau.

PubMed

Jin, Zhao; Liang, Wei; Yang, Yuting; Zhang, Weibin; Yan, Jianwu; Chen, Xuejuan; Li, Sha; Mo, Xingguo

2017-08-15

Evapotranspiration (ET) is a key ecological process connecting the soil-vegetation-atmosphere system, and its changes seriously affects the regional distribution of available water resources, especially in the arid and semiarid regions. With the Grain-for-Green project implemented in the Loess Plateau (LP) since 1999, water and heat distribution across the region have experienced great changes. Here, we investigate the changes and associated driving forces of ET in the LP from 2000 to 2012 using a remote sensing-based evapotranspiration model. Results show that annual ET significantly increased by 3.4 mm per year (p = 0.05) with large interannual fluctuations during the study period. This trend is higher than coincident increases in precipitation (2.0 mm yr -2 ), implying a possible pressure of water availability. The correlation analysis showed that vegetation change is the major controlling factor on interannual variability of annual ET with ~52.8% of pixels scattered in the strip region from the northeastern to southwestern parts of the LP. Further factorial analysis suggested that vegetation greening is the primary driver of the rises of ET over the study period relative to climate change. Our study can provide an improved understanding of the effects of vegetation and climate change on terrestrial ecosystem ET in the LP.

[Spatiotemporal changes of potential evapotranspiration in Songnen Plain of Northeast China].

PubMed

Zhang, Yong-fang; Deng, Jun-li; Guan, De-xin; Jin, Chang-jie; Wang, An-zhi; Wu, Jia-bing; Yuan, Feng-hui

2011-07-01

Based on the daily meteorological data from 72 weather stations from 1961-2003, a quantitative analysis was conducted on the spatiotemporal changes of the potential evapotranspiration in the Plain. The Penman-Monteith model was applied to calculate the potential evapotranspiration; the Mann-Kendall test, accumulative departure curve, and climatic change rate were adopted to analyze the change trend of the evapotranspiration; and the spatial analysis function of ArcGIS was used to detect the spatial distribution of the evapotranspiration. In 1961-2003, the mean annual potential evapotranspiration in the Plain was 330 - 860 mm, and presented an overall decreasing trend, with the high value appeared in southwest region, low value in surrounding areas of southwest region, and a ring-belt increasing southwestward. The climatic change rate of the annual potential evapotranspiration was -0.21 mm x a(-1). The annual potential evapotranspiration was the highest in 1982, the lowest in 1995, and increased thereafter. Seasonally, the climatic change rate of the potential evapotranspiration in spring, summer, autumn, and winter was -0.19, 0.01, -0.05, and 0.03 mm x a(-1), respectively, suggesting that the potential evapotranspiration had a weak increase in winter and summer and a slight decrease in spring and autumn.

NCA-LDAS: A Terrestrial Water Analysis System Enabling Sustained Assessment and Dissemination of National Climate Indicators

NASA Astrophysics Data System (ADS)

Jasinski, M. F.; Kumar, S.; Peters-Lidard, C. D.; Arsenault, K. R.; Beaudoing, H. K.; Bolten, J. D.; Borak, J.; Kempler, S.; Li, B.; Mocko, D. M.; Rodell, M.; Rui, H.; Silberstein, D. S.; Teng, W. L.; Vollmer, B.

2016-12-01

The National Climate Assessment - Land Data Assimilation System, or NCA-LDAS, is an integrated terrestrial water analysis system created as an end-to-end enabling tool for sustained assessment and dissemination of terrestrial hydrologic indicators in support of the NCA. The primary features are i) gridded, daily time series of over forty hydrologic variables including terrestrial water and energy balance stores, states and fluxes over the continental U.S. derived from land surface modeling with multivariate satellite data record assimilation (1979-2015), ii) estimated trends of the principal water balance components over a wide range of scales and locations, and iii) public dissemination of all NCA-LDAS model forcings, and input and output data products through dedicated NCA-LDAS and NASA GES-DISC websites. NCA-LDAS supports sustained assessment of our national terrestrial hydrologic climate for improved scientific understanding, and the adaptation and management of water resources and related energy sectors. This presentation provides an overview of the NCA-LDAS system together with an evaluation of the initial release of NCA-LDAS data products and trends using two land surface models; Noah Ver. 3.3 and Catchment Ver. Fortuna 2.5, and a listing of several available pathways for public access and visualization of NCA-LDAS background information and data products.

A Review of Recent Changes in Southern Ocean Sea Ice, Their Drivers and Forcings

NASA Technical Reports Server (NTRS)

Hobbs, William R.; Massom, Rob; Stammerjohn, Sharon; Reid, Phillip; Williams, Guy; Meier, Walter

2016-01-01

Over the past 37years, satellite records show an increase in Antarctic sea ice cover that is most pronounced in the period of sea ice growth. This trend is dominated by increased sea ice coverage in the western Ross Sea, and is mitigated by a strong decrease in the Bellingshausen and Amundsen seas. The trends in sea ice areal coverage are accompanied by related trends in yearly duration. These changes have implications for ecosystems, as well as global and regional climate. In this review, we summarize the researchto date on observing these trends, identifying their drivers, and assessing the role of anthropogenic climate change. Whilst the atmosphere is thought to be the primary driver, the ocean is also essential in explaining the seasonality of the trend patterns. Detecting an anthropogenic signal in Antarctic sea ice is particularly challenging for a number of reasons: the expected response is small compared to the very high natural variability of the system; the observational record is relatively short; and the ability of global coupled climate models to faithfully represent the complex Antarctic climate system is in doubt.

Climate Change Education in Earth System Science

NASA Astrophysics Data System (ADS)

Hänsel, Stephanie; Matschullat, Jörg

2013-04-01

The course "Atmospheric Research - Climate Change" is offered to master Earth System Science students within the specialisation "Climate and Environment" at the Technical University Bergakademie Freiberg. This module takes a comprehensive approach to climate sciences, reaching from the natural sciences background of climate change via the social components of the issue to the statistical analysis of changes in climate parameters. The course aims at qualifying the students to structure the physical and chemical basics of the climate system including relevant feedbacks. The students can evaluate relevant drivers of climate variability and change on various temporal and spatial scales and can transform knowledge from climate history to the present and the future. Special focus is given to the assessment of uncertainties related to climate observations and projections as well as the specific challenges of extreme weather and climate events. At the end of the course the students are able to critically reflect and evaluate climate change related results of scientific studies and related issues in media. The course is divided into two parts - "Climate Change" and "Climate Data Analysis" and encompasses two lectures, one seminar and one exercise. The weekly "Climate change" lecture transmits the physical and chemical background for climate variation and change. (Pre)historical, observed and projected climate changes and their effects on various sectors are being introduced and discussed regarding their implications for society, economics, ecology and politics. The related seminar presents and discusses the multiple reasons for controversy in climate change issues, based on various texts. Students train the presentation of scientific content and the discussion of climate change aspects. The biweekly lecture on "Climate data analysis" introduces the most relevant statistical tools and methods in climate science. Starting with checking data quality via tools of exploratory data analysis the approaches on climate time series, trend analysis and extreme events analysis are explained. Tools to describe relations within the data sets and significance tests further corroborate this. Within the weekly exercises that have to be prepared at home, the students work with self-selected climate data sets and apply the learned methods. The presentation and discussion of intermediate results by the students is as much part of the exercises as the illustration of possible methodological procedures by the teacher using exemplary data sets. The total time expenditure of the course is 270 hours with 90 attendance hours. The remainder consists of individual studies, e.g., preparation of discussions and presentations, statistical data analysis, and scientific writing. Different forms of examination are applied including written or oral examination, scientific report, presentation and portfolio work.

Problems in evaluating regional and local trends in temperature: An example from eastern Colorado, USA

USGS Publications Warehouse

Pielke, R.A.; Stohlgren, T.; Schell, L.; Parton, W.; Doesken, N.; Redmond, K.; Moeny, J.; McKee, T.; Kittel, T.G.F.

2002-01-01

We evaluated long-term trends in average maximum and minimum temperatures, threshold temperatures, and growing season in eastern Colorado, USA, to explore the potential shortcomings of many climate-change studies that either: (1) generalize regional patterns from single stations, single seasons, or a few parameters over short duration from averaging dissimilar stations: or (2) generalize an average regional pattern from coarse-scale general circulation models. Based on 11 weather stations, some trends were weakly regionally consistent with previous studies of night-time temperature warming. Long-term (80 + years) mean minimum temperatures increased significantly (P < 0.2) in about half the stations in winter, spring, and autumn and six stations had significant decreases in the number of days per year with temperatures ??? - 17.8 ??C (???0??F). However, spatial and temporal variation in the direction of change was enormous for all the other weather parameters tested, and, in the majority of tests, few stations showed significant trends (even at P < 0.2). In summer, four stations had significant increases and three stations had significant decreases in minimum temperatures, producing a strongly mixed regional signal. Trends in maximum temperature varied seasonally and geographically, as did trends in threshold temperature days ???32.2??C (???90??F) or days ???37.8??C (???100??F). There was evidence of a subregional cooling in autumn's maximum temperatures, with five stations showing significant decreasing trends. There were many geographic anomalies where neighbouring weather stations differed greatly in the magnitude of change or where they had significant and opposite trends. We conclude that sub-regional spatial and seasonal variation cannot be ignored when evaluating the direction and magnitude of climate change. It is unlikely that one or a few weather stations are representative of regional climate trends, and equally unlikely that regionally projected climate change from coarse-scale general circulation models will accurately portray trends at sub-regional scales. However, the assessment of a group of stations for consistent more qualitative trends (such as the number of days less than - 17.8??C, such as we found) provides a reasonably robust procedure to evaluate climate trends and variability. Copyright ?? 2002 Royal Meteorological Society.

Extreme floods in central Europe over the past 500 years: Role of cyclone pathway ``Zugstrasse Vb''

NASA Astrophysics Data System (ADS)

Mudelsee, M.; BöRngen, M.; Tetzlaff, G.; Grünewald, U.

2004-12-01

Anthropogenically induced climate change has been hypothesized to add to the risk of extreme river floods because a warmer atmosphere can carry more water. In the case of the central European rivers Elbe and Oder, another possibility that has been considered is a more frequent occurrence of a weather situation of the type "Zugstrasse Vb," where a low-pressure system travels from the Adriatic region northeastward, carrying moist air and bringing orographic rainfall in the mountainous catchment areas (Erzgebirge, Sudeten, and Beskids). Analysis of long, homogeneous records of past floods allows us to test such ideas. M. Mudelsee and co-workers recently presented flood records for the middle parts of the Elbe and Oder, which go continuously back to A.D. 1021 and A.D. 1269, respectively. Here we review the reconstruction and assess the data quality of the records, which are based on combining documentary data from the interval up to 1850 and measurements thereafter, finding both the Elbe and Oder records to provide reliable information on heavy floods at least since A.D. 1500. We explain that the statistical method of kernel occurrence rate estimation can overcome deficiencies of techniques previously used to investigate trends in the occurrence of climatic extremes, because it (1) allows nonmonotonic trends, (2) imposes no parametric restrictions, and (3) provides confidence bands, which are essential for evaluating whether observed trends are real or came by chance into the data. We further give a hypothesis test that can be used to evaluate monotonic trends. On the basis of these data and methods, we find for both the Elbe and Oder rivers (1) significant downward trends in winter flood risk during the twentieth century, (2) no significant trends in summer flood risk in the twentieth century, and (3) significant variations in flood risk during past centuries, with notable differences between the Elbe and Oder. The observed trends are shown to be both robust against data uncertainties and only slightly sensitive to land use changes or river engineering, lending support for climatic influences on flood occurrence rate. In the case of winter floods, regional warming during the twentieth century has likely reduced winter flood risk via a reduced rate of strong river freezing (breaking ice at the end of winter may function as a water barrier and enhance a high water stage severely). In the case of summer floods, correlation analysis shows a significant, but weak, relation between flood occurrence and meridional airflow, compatible with a "Zugstrasse Vb" weather situation. The weakness of this relation, together with the uncertainty about whether this weather situation became more frequent, explains the absence of trends in summer flood risk for the Elbe and Oder in the twentieth century. We finally draw conclusions about flood disaster management and modeling of flood occurrence under a changed climate.

Impact of Emissions and Long-Range Transport on Multi-Decadal Aerosol Trends: Implications for Air Quality and Climate

NASA Technical Reports Server (NTRS)

Chin, Mian

2012-01-01

We present a global model analysis of the impact of long-range transport and anthropogenic emissions on the aerosol trends in the major pollution regions in the northern hemisphere and in the Arctic in the past three decades. We will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model to analyze the multi-spatial and temporal scale data, including observations from Terra, Aqua, and CALIPSO satellites and from the long-term surface monitoring stations. We will analyze the source attribution (SA) and source-receptor (SR) relationships in North America, Europe, East Asia, South Asia, and the Arctic at the surface and free troposphere and establish the quantitative linkages between emissions from different source regions. We will discuss the implications for regional air quality and climate change.

Continuation of the NVAP Global Water Vapor Data Sets for Pathfinder Science Analysis

NASA Technical Reports Server (NTRS)

VonderHaar, Thomas H.; Engelen, Richard J.; Forsythe, John M.; Randel, David L.; Ruston, Benjamin C.; Woo, Shannon; Dodge, James (Technical Monitor)

2001-01-01

This annual report covers August 2000 - August 2001 under NASA contract NASW-0032, entitled "Continuation of the NVAP (NASA's Water Vapor Project) Global Water Vapor Data Sets for Pathfinder Science Analysis". NASA has created a list of Earth Science Research Questions which are outlined by Asrar, et al. Particularly relevant to NVAP are the following questions: (a) How are global precipitation, evaporation, and the cycling of water changing? (b) What trends in atmospheric constituents and solar radiation are driving global climate? (c) How well can long-term climatic trends be assessed or predicted? Water vapor is a key greenhouse gas, and an understanding of its behavior is essential in global climate studies. Therefore, NVAP plays a key role in addressing the above climate questions by creating a long-term global water vapor dataset and by updating the dataset with recent advances in satellite instrumentation. The NVAP dataset produced from 1988-1998 has found wide use in the scientific community. Studies of interannual variability are particularly important. A recent paper by Simpson, et al. that examined the NVAP dataset in detail has shown that its relative accuracy is sufficient for the variability studies that contribute toward meeting NASA's goals. In the past year, we have made steady progress towards continuing production of this high-quality dataset as well as performing our own investigations of the data. This report summarizes the past year's work on production of the NVAP dataset and presents results of analyses we have performed in the past year.

Evaluation of methodology for detecting/predicting migration of forest species

Treesearch

Dale S. Solomon; William B. Leak

1996-01-01

Available methods for analyzing migration of forest species are evaluated, including simulation models, remeasured plots, resurveys, pollen/vegetation analysis, and age/distance trends. Simulation models have provided some of the most drastic estimates of species changes due to predicted changes in global climate. However, these models require additional testing...

Morphometric traits capture the climatically driven species turnover of 10 spruce taxa across China.

PubMed

Li, He; Wang, GuoHong; Zhang, Yun; Zhang, WeiKang

2016-02-01

This study explored the relative roles of climate and phylogenetic background in driving morphometric trait variation in 10 spruce taxa in China. The study further addressed the hypothesis that these variations are consistent with species turnover on climatic gradients. Nine morphometric traits of leaves, seed cones, and seeds for the 10 studied spruce taxa were measured at 504 sites. These data were analyzed in combination with species DNA sequences from NCBI GenBank. We detected the effects of phylogeny and climate through trait-variation-based K statistics and phylogenetic eigenvector regression (PVR) analyses. Multivariate analyses were performed to detect trait variation along climatic gradients with species replacement. The estimated K-values for the nine studied morphometric traits ranged from 0.19 to 0.68, and the studied environmental variables explained 39-83% of the total trait variation. Trait variation tended to be determined largely by a temperature gradient varying from wet-cool climates to dry-warm summers and, additionally, by a moisture gradient. As the climate became wetter and cooler, spruce species tended to be replaced by other spruces with smaller needle leaves and seeds but larger cones and seed scales. A regression analysis showed that spruce species tended to be successively replaced by other species, along the gradient, although the trends observed within species were not necessarily consistent with the overall trend. The climatically driven replacement of the spruces in question could be well indicated by the between-species variation in morphometric traits that carry lower phylogenetic signal. Between-species variation in these traits is driven primarily by climatic factors. These species demonstrate a narrower ecological amplitude in temperature but wider ranges on the moisture gradient.

Holocene vegetation and climate dynamics of NE China based on the pollen record from Sihailongwan Maar Lake

NASA Astrophysics Data System (ADS)

Stebich, Martina; Rehfeld, Kira; Schlütz, Frank; Tarasov, Pavel E.; Liu, Jiaqi; Mingram, Jens

2015-09-01

High-resolution palynological analysis on annually laminated sediments of Sihailongwan Maar Lake (SHL) provides new insights into the Holocene vegetation and climate dynamics of NE China. The robust chronology of the presented record is based on varve counting and AMS radiocarbon dates from terrestrial plant macro-remains. In addition to the qualitative interpretation of the pollen data, we provide quantitative reconstructions of vegetation and climate based on the method of biomization and weighted averaging partial least squares regression (WA-PLS) technique, respectively. Power spectra were computed to investigate the frequency domain distribution of proxy signals and potential natural periodicities. Pollen assemblages, pollen-derived biome scores and climate variables as well as the cyclicity pattern indicate that NE China experienced significant changes in temperature and moisture conditions during the Holocene. Within the earliest phase of the Holocene, a large-scale reorganization of vegetation occurred, reflecting the reconstructed shift towards higher temperatures and precipitation values and the initial Holocene strengthening and northward expansion of the East Asian summer monsoon (EASM). Afterwards, summer temperatures remain at a high level, whereas the reconstructed precipitation shows an increasing trend until approximately 4000 cal. yr BP. Since 3500 cal. yr BP, temperature and precipitation values decline, indicating moderate cooling and weakening of the EASM. A distinct periodicity of 550-600 years and evidence of a Mid-Holocene transition from a temperature-triggered to a predominantly moisture-triggered climate regime are derived from the power spectra analysis. The results obtained from SHL are largely consistent with other palaeoenvironmental records from NE China, substantiating the regional nature of the reconstructed vegetation and climate patterns. However, the reconstructed climate changes contrast with the moisture evolution recorded in S China and the mid-latitude (semi-)arid regions of N China. Whereas a clear insolation-related trend of monsoon intensity over the Holocene is lacking from the SHL record, variations in the coupled atmosphere-Pacific Ocean system can largely explain the reconstructed changes in NE China.

Response of surface water chemistry to reduced levels of acid precipitation: Comparison of trends in two regions of New York, USA

USGS Publications Warehouse

Burns, Douglas A.; McHale, M.R.; Driscoll, C.T.; Roy, K.M.

2006-01-01

In light of recent reductions in sulphur (S) and nitrogen (N) emissions mandated by Title IV of the Clean Air Act Amendments of 1990, temporal trends and trend coherence in precipitation (1984-2001 and 1992-2001) and surface water chemistry (1992-2001) were determined in two of the most acid-sensitive regions of North America, i.e. the Catskill and Adirondack Mountains of New York. Precipitation chemistry data from six sites located near these regions showed decreasing sulphate (SO42-), nitrate (NO3-), and base cation (CB) concentrations and increasing pH during 1984-2001, but few significant trends during 1992-2001. Data from five Catskill streams and 12 Adirondack lakes showed decreasing trends in SO42- concentrations at all sites, and decreasing trends in NO3-, CB, and H+ concentrations and increasing trends in dissolved organic carbon at most sites. In contrast, acid-neutralizing capacity (ANC increased significantly at only about half the Adirondack lakes and in one of the Catskill streams. Flow correction prior to trend analysis did not change any trend directions and had little effect on SO42- trends, but it caused several significant non-flow-corrected trends in NO3- and ANC to become non-significant, suggesting that trend results for flow-sensitive constituents are affected by flow-related climate variation. SO42- concentrations showed high temporal coherence in precipitation, surface waters, and in precipitation-surface water comparisons, reflecting a strong link between S emissions, precipitation SO42- concentrations, and the processes that affect S cycling within these regions. NO3- and H+ concentrations and ANC generally showed weak coherence, especially in surface waters and in precipitation-surface water comparisons, indicating that variation in local-scale processes driven by factors such as climate are affecting trends in acid-base chemistry in these two regions. Copyright ?? 2005 John Wiley & Sons, Ltd.

Modelling the Effects of Land-Use Changes on Climate: a Case Study on Yamula DAM

NASA Astrophysics Data System (ADS)

Köylü, Ü.; Geymen, A.

2016-10-01

Dams block flow of rivers and cause artificial water reservoirs which affect the climate and the land use characteristics of the river basin. In this research, the effect of the huge water body obtained by Yamula Dam in Kızılırmak Basin is analysed over surrounding spatial's land use and climate change. Mann Kendal non-parametrical statistical test, Theil&Sen Slope method, Inverse Distance Weighting (IDW), Soil Conservation Service-Curve Number (SCS-CN) methods are integrated for spatial and temporal analysis of the research area. For this research humidity, temperature, wind speed, precipitation observations which are collected in 16 weather stations nearby Kızılırmak Basin are analyzed. After that these statistical information is combined by GIS data over years. An application is developed for GIS analysis in Python Programming Language and integrated with ArcGIS software. Statistical analysis calculated in the R Project for Statistical Computing and integrated with developed application. According to the statistical analysis of extracted time series of meteorological parameters, statistical significant spatiotemporal trends are observed for climate change and land use characteristics. In this study, we indicated the effect of big dams in local climate on semi-arid Yamula Dam.

Recent trends in paralytic shellfish toxins in Puget Sound, relationships to climate, and capacity for prediction of toxic events

Treesearch

Stephanie K. Moore; Nathan J. Mantua; Barbara M. Hickey; Vera L. Trainer

2009-01-01

Temporal and spatial trends in paralytic shellfish toxins (PSTs) in Puget Sound shellfish and their relationships with climate are investigated using long-term monitoring data since 1957. Data are selected for trend analyses based on the sensitivity of shellfish species to PSTs and their depuration rates, and the frequency of sample collection at individual sites....

Modeling seasonal variation of hip fracture in Montreal, Canada.

PubMed

Modarres, Reza; Ouarda, Taha B M J; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2012-04-01

The investigation of the association of the climate variables with hip fracture incidences is important in social health issues. This study examined and modeled the seasonal variation of monthly population based hip fracture rate (HFr) time series. The seasonal ARIMA time series modeling approach is used to model monthly HFr incidences time series of female and male patients of the ages 40-74 and 75+ of Montreal, Québec province, Canada, in the period of 1993-2004. The correlation coefficients between meteorological variables such as temperature, snow depth, rainfall depth and day length and HFr are significant. The nonparametric Mann-Kendall test for trend assessment and the nonparametric Levene's test and Wilcoxon's test for checking the difference of HFr before and after change point are also used. The seasonality in HFr indicated sharp difference between winter and summer time. The trend assessment showed decreasing trends in HFr of female and male groups. The nonparametric test also indicated a significant change of the mean HFr. A seasonal ARIMA model was applied for HFr time series without trend and a time trend ARIMA model (TT-ARIMA) was developed and fitted to HFr time series with a significant trend. The multi criteria evaluation showed the adequacy of SARIMA and TT-ARIMA models for modeling seasonal hip fracture time series with and without significant trend. In the time series analysis of HFr of the Montreal region, the effects of the seasonal variation of climate variables on hip fracture are clear. The Seasonal ARIMA model is useful for modeling HFr time series without trend. However, for time series with significant trend, the TT-ARIMA model should be applied for modeling HFr time series. Copyright © 2011 Elsevier Inc. All rights reserved.

Response of waves and coastline evolution to climate variability off the Niger Delta coast during the past 110 years

NASA Astrophysics Data System (ADS)

Dada, Olusegun A.; Li, Guangxue; Qiao, Lulu; Ma, Yanyan; Ding, Dong; Xu, Jishang; Li, Pin; Yang, Jichao

2016-08-01

River deltas, low-lying landforms that host critical economic infrastructures and diverse ecosystems as well as high concentrations of human population, are highly vulnerable to the effects of global climate change. In order to understand the wave climate, their potential changes and implication on coastline evolution for environment monitoring and sustainable management of the Niger Delta in the Gulf of Guinea, an investigation was carried out based on offshore wave statistics of an 110-year time series (1900-2010) dataset obtained from the ECMWF ERA-20C atmospheric reanalysis. Results of multivariate regression analyses indicate that interannual mean values of Hs and Tm trends tended to increase over time, especially in the western part of the delta coast, so that they are presently (1980 and 2010) up to 264 mm (300%) and 0.32 s (22%), respectively, higher than 80 years (1900-1930) ago. The maximum directions of the wave have become more westerly (southward) than southerly (westward) by up to 2° (33%) and the mean longshore sediment transport rate has increased by more than 8% over the last 80 years. The linear regression analysis for shoreline changes from 1987 to 2013 shows an erosional trend at the western part of the delta and accretional trends towards eastern part. The relationship between wave climate of the study area and atmospheric circulation using Pearson's correlation shows that the Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), East Atlantic pattern (EA) and El-Nino/Southern Oscillation (ENSO) Index explain significant proportion of the seasonal and annual wave variabilities compared to other indices. But it is most likely that the combination of these climatic indices acting together or separately constitutes a powerful and effective mechanism responsible for much of the variability of the offshore Niger Delta wave climate. The study concludes that changing wave climate off the Niger Delta has strong implications on the delta coastline changes. However, other processes (such as fluvial discharge variability due climatic variability and anthropogenic effect) may be acting concomitantly with changes in wave regime and associated littoral transport to influence shoreline evolution along the Niger Delta coast.

Winter Precipitation Forecast in the European and Mediterranean Regions Using Cluster Analysis

NASA Astrophysics Data System (ADS)

Totz, Sonja; Tziperman, Eli; Coumou, Dim; Pfeiffer, Karl; Cohen, Judah

2017-12-01

The European climate is changing under global warming, and especially the Mediterranean region has been identified as a hot spot for climate change with climate models projecting a reduction in winter rainfall and a very pronounced increase in summertime heat waves. These trends are already detectable over the historic period. Hence, it is beneficial to forecast seasonal droughts well in advance so that water managers and stakeholders can prepare to mitigate deleterious impacts. We developed a new cluster-based empirical forecast method to predict precipitation anomalies in winter. This algorithm considers not only the strength but also the pattern of the precursors. We compare our algorithm with dynamic forecast models and a canonical correlation analysis-based prediction method demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

Forecasting conditional climate-change using a hybrid approach

USGS Publications Warehouse

Esfahani, Akbar Akbari; Friedel, Michael J.

2014-01-01

A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.

Fe-oxide mineralogy of the Jiujiang red earth sediments and implications for Quaternary climate change, southern China.

PubMed

Yin, Ke; Hong, Hanlie; Algeo, Thomas J; Churchman, Gordon Jock; Li, Zhaohui; Zhu, Zongmin; Fang, Qian; Zhao, Lulu; Wang, Chaowen; Ji, Kaipeng; Lei, Weidong; Duan, Zhenggang

2018-02-26

Diffuse reflectance spectrophotometry (DRS) is a new, fast, and reliable method to characterize Fe-oxides in soils. The Fe-oxide mineralogy of the Jiujiang red earth sediments was investigated using DRS to investigate the climate evolution of southern China since the mid-Pleistocene. The DRS results show that hematite/(hematite + goethite) ratios [Hm/(Hm + Gt)] exhibit an upward decreasing trend within the Jiujiang section, suggesting a gradual climate change from warm and humid in the middle Pleistocene to cooler and drier in the late Pleistocene. Upsection trends toward higher (orthoclase + plagioclase)/quartz ratios [(Or + Pl)/Q] and magnetic susceptibility values (χ lf ) support this inference, which accords with global climate trends at that time. However, higher-frequency climatic subcycles observed in loess sections of northern China are not evident in the Jiujiang records, indicating a relatively lower climate sensitivity of the red earth sediments in southern China.

Estimating uncertainty and its temporal variation related to global climate models in quantifying climate change impacts on hydrology

NASA Astrophysics Data System (ADS)

Shen, Mingxi; Chen, Jie; Zhuan, Meijia; Chen, Hua; Xu, Chong-Yu; Xiong, Lihua

2018-01-01

Uncertainty estimation of climate change impacts on hydrology has received much attention in the research community. The choice of a global climate model (GCM) is usually considered as the largest contributor to the uncertainty of climate change impacts. The temporal variation of GCM uncertainty needs to be investigated for making long-term decisions to deal with climate change. Accordingly, this study investigated the temporal variation (mainly long-term) of uncertainty related to the choice of a GCM in predicting climate change impacts on hydrology by using multi-GCMs over multiple continuous future periods. Specifically, twenty CMIP5 GCMs under RCP4.5 and RCP8.5 emission scenarios were adapted to adequately represent this uncertainty envelope, fifty-one 30-year future periods moving from 2021 to 2100 with 1-year interval were produced to express the temporal variation. Future climatic and hydrological regimes over all future periods were compared to those in the reference period (1971-2000) using a set of metrics, including mean and extremes. The periodicity of climatic and hydrological changes and their uncertainty were analyzed using wavelet analysis, while the trend was analyzed using Mann-Kendall trend test and regression analysis. The results showed that both future climate change (precipitation and temperature) and hydrological response predicted by the twenty GCMs were highly uncertain, and the uncertainty increased significantly over time. For example, the change of mean annual precipitation increased from 1.4% in 2021-2050 to 6.5% in 2071-2100 for RCP4.5 in terms of the median value of multi-models, but the projected uncertainty reached 21.7% in 2021-2050 and 25.1% in 2071-2100 for RCP4.5. The uncertainty under a high emission scenario (RCP8.5) was much larger than that under a relatively low emission scenario (RCP4.5). Almost all climatic and hydrological regimes and their uncertainty did not show significant periodicity at the P = .05 significance level, but their temporal variation could be well modeled by using the fourth-order polynomial. Overall, this study further emphasized the importance of using multiple GCMs for studying climate change impacts on hydrology. Furthermore, the temporal variation of uncertainty sourced from GCMs should be given more attention.

Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.

ClimateWizard: A Framework and Easy-to-Use Web-Mapping Tool for Global, Regional, and Local Climate-Change Analysis

NASA Astrophysics Data System (ADS)

Girvetz, E. H.; Zganjar, C.; Raber, G. T.; Hoekstra, J.; Lawler, J. J.; Kareiva, P.

2008-12-01

Now that there is overwhelming evidence of global climate change, scientists, managers and planners (i.e. practitioners) need to assess the potential impacts of climate change on particular ecological systems, within specific geographic areas, and at spatial scales they care about, in order to make better land management, planning, and policy decisions. Unfortunately, this application of climate science to real world decisions and planning has proceeded too slowly because we lack tools for translating cutting-edge climate science and climate-model outputs into something managers and planners can work with at local or regional scales (CCSP 2008). To help increase the accessibility of climate information, we have developed a freely-available, easy-to-use, web-based climate-change analysis toolbox, called ClimateWizard, for assessing how climate has and is projected to change at specific geographic locations throughout the world. The ClimateWizard uses geographic information systems (GIS), web-services (SOAP/XML), statistical analysis platforms (e.g. R- project), and web-based mapping services (e.g. Google Earth/Maps, KML/GML) to provide a variety of different analyses (e.g. trends and departures) and outputs (e.g. maps, graphs, tables, GIS layers). Because ClimateWizard analyzes large climate datasets stored remotely on powerful computers, users of the tool do not need to have fast computers or expensive software, but simply need access to the internet. The analysis results are then provided to users in a Google Maps webpage tailored to the specific climate-change question being asked. The ClimateWizard is not a static product, but rather a framework to be built upon and modified to suit the purposes of specific scientific, management, and policy questions. For example, it can be expanded to include bioclimatic variables (e.g. evapotranspiration) and marine data (e.g. sea surface temperature), as well as improved future climate projections, and climate-change impact analyses involving hydrology, vegetation, wildfire, disease, and food security. By harnessing the power of computer and web- based technologies, the ClimateWizard puts local, regional, and global climate-change analyses in the hands of a wider array of managers, planners, and scientists.

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

Combining satellite derived phenology with climate data for climate change impact assessment

NASA Astrophysics Data System (ADS)

Ivits, E.; Cherlet, M.; Tóth, G.; Sommer, S.; Mehl, W.; Vogt, J.; Micale, F.

2012-05-01

The projected influence of climate change on the timing and volume of phytomass production is expected to affect a number of ecosystem services. In order to develop coherent and locally effective adaptation and mitigation strategies, spatially explicit information on the observed changes is needed. Long-term variations of the vegetative growing season in different environmental zones of Europe for 1982-2006 have been derived by analysing time series of GIMMS NDVI data. The associations of phenologically homogenous spatial clusters to time series of temperature and precipitation data were evaluated. North-east Europe showed a trend to an earlier and longer growing season, particularly in the northern Baltic areas. Despite the earlier greening up large areas of Europe exhibited rather stable season length indicating the shift of the entire growing season to an earlier period. The northern Mediterranean displayed a growing season shift towards later dates while some agglomerations of earlier and shorter growing season were also seen. The correlation of phenological time series with climate data shows a cause-and-effect relationship over the semi natural areas consistent with results in literature. Managed ecosystems however appear to have heterogeneous change pattern with less or no correlation to climatic trends. Over these areas climatic trends seemed to overlap in a complex manner with more pronounced effects of local biophysical conditions and/or land management practices. Our results underline the importance of satellite derived phenological observations to explain local nonconformities to climatic trends for climate change impact assessment.

Estimation of regional mass anomalies from Gravity Recovery and Climate Experiment (GRACE) over Himalayan region

NASA Astrophysics Data System (ADS)

Agrawal, R.; Singh, S. K.; Rajawat, A. S.; Ajai

2014-11-01

Time-variable gravity changes are caused by a combination of postglacial rebound, redistribution of water and snow/ice on land and as well as in the ocean. The Gravity Recovery and Climate Experiment (GRACE) satellite mission, launched in 2002, provides monthly average of the spherical harmonic co-efficient. These spherical harmonic co-efficient describe earth's gravity field with a resolution of few hundred kilometers. Time-variability of gravity field represents the change in mass over regional level with accuracies in cm in terms of Water Equivalent Height (WEH). The WEH reflects the changes in the integrated vertically store water including snow cover, surface water, ground water and soil moisture at regional scale. GRACE data are also sensitive towards interior strain variation, surface uplift and surface subsidence cover over a large area. GRACE data was extracted over the three major Indian River basins, Indus, Ganga and Brahmaputra, in the Himalayas which are perennial source of fresh water throughout the year in Northern Indian Plain. Time series analysis of the GRACE data was carried out from 2003-2012 over the study area. Trends and amplitudes of the regional mass anomalies in the region were estimated using level 3 GRACE data product with a spatial resolution at 10 by 10 grid provided by Center for Space Research (CSR), University of Texas at Austin. Indus basin has shown a subtle decreasing trend from 2003-2012 however it was observed to be statistically insignificant at 95 % confidence level. Ganga and Brahmaputra basins have shown a clear decreasing trend in WEH which was also observed to be statistically significant. The trend analysis over Ganga and Brahamputra basins have shown an average annual change of -1.28 cm and -1.06 cm in terms of WEH whereas Indus basin has shown a slight annual change of -0.07 cm. This analysis will be helpful to understand the loss of mass in terms of WEH over Indian Himalayas and will be crucial for hydrological and climate applications at regional scale.

Statistical analysis of trends in monthly precipitation at the Limbang River Basin, Sarawak (NW Borneo), Malaysia

NASA Astrophysics Data System (ADS)

Krishnan, M. V. Ninu; Prasanna, M. V.; Vijith, H.

2018-05-01

Effect of climate change in a region can be characterised by the analysis of rainfall trends. In the present research, monthly rainfall trends at Limbang River Basin (LRB) in Sarawak, Malaysia for a period of 45 years (1970-2015) were characterised through the non-parametric Mann-Kendall and Spearman's Rho tests and relative seasonality index. Statistically processed monthly rainfall of 12 well distributed rain gauging stations in LRB shows almost equal amount of rainfall in all months. Mann-Kendall and Spearman's Rho tests revealed a specific pattern of rainfall trend with a definite boundary marked in the months of January and August with positive trends in all stations. Among the stations, Limbang DID, Long Napir and Ukong showed positive (increasing) trends in all months with a maximum increase of 4.06 mm/year (p = 0.01) in November. All other stations showed varying trends (both increasing and decreasing). Significant (p = 0.05) decreasing trend was noticed in Ulu Medalam and Setuan during September (- 1.67 and - 1.79 mm/year) and October (- 1.59 and - 1.68 mm/year) in Mann-Kendall and Spearman's Rho tests. Spatial pattern of monthly rainfall trends showed two clusters of increasing rainfalls (maximas) in upper and lower part of the river basin separated with a dominant decreasing rainfall corridor. The results indicate a generally increasing trend of rainfall in Sarawak, Borneo.

Usefulness of AIRS-Derived OLR, Temperature, Water Vapor and Cloudiness Anomaly Trends for GCM Validation

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel; Iredell, Lena F.

2010-01-01

Mainly due to their global nature, satellite observations can provide a very useful basis for GCM validations. In particular, satellite sounders such as AIRS provide 3-D spatial information (most useful for GCMs), so the question arises: can we use AIRS datasets for climate variability assessments? We show that the recent (September 2002 February 2010) CERES-observed negative trend in OLR of approx.-0.1 W/sq m/yr averaged over the globe is found in the AIRS OLR data as well. Most importantly, even minute details (down to 1 x 1 degree GCM-scale resolution) of spatial and temporal anomalies and trends of OLR as observed by CERES and computed based on AIRS-retrieved surface and atmospheric geophysical parameters over this time period are essentially the same. The correspondence can be seen even in the very large spatial variations of these trends with local values ranging from -2.6 W/sq m/yr to +3.0 W/sq m/yr in the tropics, for example. This essentially perfect agreement of OLR anomalies and trends derived from observations by two different instruments, in totally independent and different manners, implies that both sets of results must be highly accurate, and indirectly validates the anomalies and trends of other AIRS derived products as well. These products show that global and regional anomalies and trends of OLR, water vapor and cloud cover over the last 7+ years are strongly influenced by EI-Nino-La Nina cycles . We have created climate parameter anomaly datasets using AIRS retrievals which can be compared directly with coupled GCM climate variability assessments. Moreover, interrelationships of these anomalies and trends should also be similar between the observed and GCM-generated datasets, and, in cases of discrepancies, GCM parameterizations could be improved based on the relationships observed in the data. First, we assess spatial "trends" of variability of climatic parameter anomalies [since anomalies relative to the seasonal cycle are good proxies of climate variability] at the common 1x1 degree GCM grid-scale by creating spatial anomaly "trends" based on the first 7+ years of AIRS Version 5 Leve13 data. We suggest that modelers should compare these with their (coupled) GCM's performance covering the same period. We evaluate temporal variability and interrelations of climatic anomalies on global to regional e.g., deep Tropical Hovmoller diagrams, El-Nino-related variability scales, and show the effects of El-Nino-La Nina activity on tropical anomalies and trends of water vapor cloud cover and OLR. For GCMs to be trusted highly for long-term climate change predictions, they should be able to reproduce findings similar to these. In summary, the AIRS-based climate variability analyses provide high quality, informative and physically plausible interrelationships among OLR, temperature, humidity and cloud cover both on the spatial and temporal scales. GCM validations can use these results even directly, e. g., by creating 1x1 degree trendmaps for the same period in coupled climate simulations.

Did Climate Change Cause the 2012-2014 California Drought?

NASA Astrophysics Data System (ADS)

Mao, Y.; Clark, E.; Xiao, M.; Nijssen, B.; Lettenmaier, D. P.

2014-12-01

California has experienced severe drought over the last three years, with especially deficient winter precipitation and mountain snowpack in 2013-2014. While the severity of California's water crisis this year is not in question, the causes of the drought are less clear, and there has been debate as to whether human-induced climate change is at least in part a cause of anomalously low winter precipitation (P) and snow water equivalent (SWE) this year, or whether the conditions are simply the result of natural variability that has been manifested in previous severe droughts in California. To provide more scientific insight to this question, we reconstructed, using the Variable Infiltration Capacity (VIC) hydrologic model, SWE and runoff from 1920 to 2014 at a spatial resolution of 1/16 degree over the Sierra Nevada range of California. We forced the VIC model with a temporally consistent set of index precipitation and temperature stations that are also used in the University of Washington's Drought Monitoring System for the West Coast Region (http://www.hydro.washington.edu/forecast/monitor_cali/index.shtml). We carried out trend analysis and examined cumulative probability for accumulated winter precipitation, SWE on Apr 1, annual, spring and winter runoff, average winter temperature (T) and SWE/P fraction. We also did correlation analysis between SWE and P as well as SWE and T. In addition, we used detrended temperature data to force the VIC model in order to analyze the role of climate change in SWE and runoff. Our results show that while the decreasing trend in SWE and earlier runoff peak in the year are related to long-term warming climate, there is no significant trend in winter P and there are lots of variability in the record of all variables. While this year's anomalously warm weather might have exacerbated the ongoing 3-year drought (and winter 2013-14 in particular), we conclude that natural variability is the main cause.

Streamflow characteristics and trends in New Jersey, water years 1897-2003

USGS Publications Warehouse

Watson, Kara M.; Reiser, Robert G.; Nieswand, Steven P.; Schopp, Robert D.

2005-01-01

Streamflow statistics were computed for 111 continuous-record streamflow-gaging stations with 20 or more years of continuous record and for 500 low-flow partial-record stations, including 66 gaging stations with less than 20 years of continuous record. Daily mean streamflow data from water year 1897 through water year 2001 were used for the computations at the gaging stations. (The water year is the 12-month period, October 1 through September 30, designated by the calendar year in which it ends). The characteristics presented for the long-term continuous-record stations are daily streamflow, harmonic mean flow, flow frequency, daily flow durations, trend analysis, and streamflow variability. Low-flow statistics for gaging stations with less than 20 years of record and for partial-record stations were estimated by correlating base-flow measurements with daily mean flows at long-term (more than 20 years) continuous-record stations. Instantaneous streamflow measurements through water year 2003 were used to estimate low-flow statistics at the partial-record stations. The characteristics presented for partial-record stations are mean annual flow; harmonic mean flow; and annual and winter low-flow frequency. The annual 1-, 7-, and 30-day low- and high-flow data sets were tested for trends. The results of trend tests for high flows indicate relations between upward trends for high flows and stream regulation, and high flows and development in the basin. The relation between development and low-flow trends does not appear to be as strong as for development and high-flow trends. Monthly, seasonal, and annual precipitation data for selected long-term meteorological stations also were tested for trends to analyze the effects of climate. A significant upward trend in precipitation in northern New Jersey, Climate Division 1 was identified. For Climate Division 2, no general increase in average precipitation was observed. Trend test results indicate that high flows at undeveloped, unregulated sites have not been affected by the increase in average precipitation. The ratio of instantaneous peak flow to 3-day mean flow, ratios of flow duration, ratios of high-flow/low-flow frequency, and coefficient of variation were used to define streamflow variability. Streamflow variability was significantly greater among the group of gaging stations located outside the Coastal Plain than among the group of gaging stations located in the Coastal Plain.

Detecting spatiotemporal changes of peak foliage coloration in deciduous and mixedforests across the Central and Eastern United States

NASA Astrophysics Data System (ADS)

Liu, Lingling; Zhang, Xiaoyang; Yu, Yunyue; Donnelly, Alison

2017-02-01

The timing of fall foliage coloration, especially peak coloration, is of great importance to the climate change research community as it has implications for carbon storage in forests. However, its long-term variation and response to climate change are poorly understood. To address this issue, we examined the long-term trends and breakpoints in satellite derived peak coloration onset from 1982 to 2014 using an innovative approach that combines Singular Spectrum Analysis (SSA) with Breaks for Additive Seasonal and Trend (BFAST). The peak coloration trend was then evaluated using both field foliage coloration observations and flux tower measurements. Finally, interannual changes in peak coloration onset were correlated with temperature and precipitation variation. Results showed that temporal trends in satellite-derived peak coloration onset were comparable with both field observations and flux tower measurements of gross primary productivity. Specifically, a breakpoint in long-term peak coloration onset was detected in 25% of pixels which were mainly distributed at latitudes north of 37°N. The breakpoint tended to occur between 1998 and 2004. Peak coloration onset was delayed before the breakpoint while it was transformed to an early trend after the breakpoint in nearly all pixels. The remaining 75% of pixels exhibited monotonic trends, 35% of which revealed a late trend and 40% an early trend. The results indicate that the onset of peak coloration experienced a late trend during the 1980s and 1990s in most deciduous and mixed forests. However, the trend was reversed during the most recent decade when the timing of peak coloration became earlier. The onset of peak coloration was significantly correlated with late summer and autumn temperature in 55.5% of pixels from 1982 to 2014. This pattern of temperature impacts was also verified using field observations and flux tower measurements. In the remaining 44.5% of pixels, 12.2% of pixels showed significantly positive correlation between the onset of peak coloration and cumulative precipitation during late summer and autumn period from 1982 to 2014. Our findings can improve understanding of the impact of changes in autumn phenology on carbon uptake in forests, which in turn facilitate more reliable measures of carbon dynamics in vegetation-climate interactions models.

Climate-driven variability in the occurrence of major floods across North America and Europe

NASA Astrophysics Data System (ADS)

Hodgkins, Glenn A.; Whitfield, Paul H.; Burn, Donald H.; Hannaford, Jamie; Renard, Benjamin; Stahl, Kerstin; Fleig, Anne K.; Madsen, Henrik; Mediero, Luis; Korhonen, Johanna; Murphy, Conor; Wilson, Donna

2017-09-01

Concern over the potential impact of anthropogenic climate change on flooding has led to a proliferation of studies examining past flood trends. Many studies have analysed annual-maximum flow trends but few have quantified changes in major (25-100 year return period) floods, i.e. those that have the greatest societal impacts. Existing major-flood studies used a limited number of very large catchments affected to varying degrees by alterations such as reservoirs and urbanisation. In the current study, trends in major-flood occurrence from 1961 to 2010 and from 1931 to 2010 were assessed using a very large dataset (>1200 gauges) of diverse catchments from North America and Europe; only minimally altered catchments were used, to focus on climate-driven changes rather than changes due to catchment alterations. Trend testing of major floods was based on counting the number of exceedances of a given flood threshold within a group of gauges. Evidence for significant trends varied between groups of gauges that were defined by catchment size, location, climate, flood threshold and period of record, indicating that generalizations about flood trends across large domains or a diversity of catchment types are ungrounded. Overall, the number of significant trends in major-flood occurrence across North America and Europe was approximately the number expected due to chance alone. Changes over time in the occurrence of major floods were dominated by multidecadal variability rather than by long-term trends. There were more than three times as many significant relationships between major-flood occurrence and the Atlantic Multidecadal Oscillation than significant long-term trends.

Climate-driven variability in the occurrence of major floods across North America and Europe

USGS Publications Warehouse

Hodgkins, Glenn A.; Whitfield, Paul H.; Burn, Donald H.; Hannaford, Jamie; Renard, Benjamin; Stahl, Kerstin; Fleig, Anne K.; Madsen, Henrik; Mediero, Luis; Korhonen, Johanna; Murphy, Conor; Wilson, Donna

2017-01-01

Concern over the potential impact of anthropogenic climate change on flooding has led to a proliferation of studies examining past flood trends. Many studies have analysed annual-maximum flow trends but few have quantified changes in major (25–100 year return period) floods, i.e. those that have the greatest societal impacts. Existing major-flood studies used a limited number of very large catchments affected to varying degrees by alterations such as reservoirs and urbanisation. In the current study, trends in major-flood occurrence from 1961 to 2010 and from 1931 to 2010 were assessed using a very large dataset (>1200 gauges) of diverse catchments from North America and Europe; only minimally altered catchments were used, to focus on climate-driven changes rather than changes due to catchment alterations. Trend testing of major floods was based on counting the number of exceedances of a given flood threshold within a group of gauges. Evidence for significant trends varied between groups of gauges that were defined by catchment size, location, climate, flood threshold and period of record, indicating that generalizations about flood trends across large domains or a diversity of catchment types are ungrounded. Overall, the number of significant trends in major-flood occurrence across North America and Europe was approximately the number expected due to chance alone. Changes over time in the occurrence of major floods were dominated by multidecadal variability rather than by long-term trends. There were more than three times as many significant relationships between major-flood occurrence and the Atlantic Multidecadal Oscillation than significant long-term trends.

Interannual Variations in Global Vegetation Phenology Derived from a Long Term AVHRR and MODIS Data Record

NASA Astrophysics Data System (ADS)

Zhang, X.; Friedl, M. A.; Yu, Y.

2013-12-01

Land surface phenology metrics are widely retrieved from satellite observations at regional and global scales, and have been shown to be valuable for monitoring terrestrial ecosystem dynamics in response to extreme climate events and predicting biological responses to future climate scenarios. While the response of spring vegetation greenup to climate warming at mid-to-high latitudes is well-documented, understanding of diverse phenological responses to climate change over entire growing cycles and at broad geographic scales is incomplete. Many studies assume that the timing of individual phenological indicators in responses to climate forcing is independent of phenological events that occur at other times during the growing season. In this paper we use a different strategy. Specifically, we hypothesize that integrating sequences of key phenological indicators across growing seasons provides a more effective way to capture long-term variation in phenology in response to climate change. To explore this hypothesis we use global land surface phenology metrics derived from the Version 3 Long Term Vegetation Index Products from Multiple Satellite Data Records data set to examine interannual variations and trends in global land surface phenology from 1982-2010. Using daily enhanced vegetation index (EVI) data at a spatial resolution of 0.05 degrees, we model the phenological trajectory for each individual pixel using piecewise logistic models. The modeled trajectories were then used to detect phenological indicators including the onset of greenness increase, the onset of greenness maximum, the onset of greenness decrease, the onset of greenness minimum, and the growing season length, among others at global scale. The quality of land surface phenology detection for individual pixels was calculated based on metrics that characterize the EVI quality and model fits in annual time series at each pixel. Phenological indicators characterized as having good quality were then used to detect interannual variation and long-term trends using linear and nonlinear trend analysis techniques.

Alexander Polonsky Global warming hiatus, ocean variability and regional climate change

NASA Astrophysics Data System (ADS)

Polonsky, A.

2016-02-01

This presentation generalizes the results concerning ocean variability, large-scale interdecadal ocean-atmosphere interaction in the Atlantic and Pacific Oceans and their impact on global and regional climate change carried out by the author and his colleagues for about 20 years. It is demonstrated once more that Atlantic Multidecadal Oscillation (AMO, which was early referred by the author as "interdecadal mode of North Atlantic Oscillation") is the crucial natural interdecadal climatic signal for the Atlantic-European and Mediterranean regions. It is characterized by amplitude which is the same order as human-induced centennial climate change and exceeds trend-like anthropogenic change at the decadal scale. Fast increasing of the global and Northern Hemisphere air temperature in the last 30 yrs of XX century (especially pronounced in the North Atlantic region and surrounded areas) is due to coincidence of human-induced positive trend and transition from the negative to the positive phase of AMO. AMO accounts for about 50% (60%) of the global (Northern Hemisphere) temperature trend in that period. Recent global warming hiatus is mostly the result of switch off the AMO phase. Typical AMO temporal scale is dictated by meridional overturning variability in the Atlantic Ocean and associated magnitude of meridional heat transport. Pacific Decadal Oscillation (PDO) is the other natural interdecadal signal which significantly impacts the global and regional climate variability. The rate of the ocean warming for different periods assessed separately for the upper mixed layer and deeper layers using data of oceanic re-analysis since 1959 confirms the principal role of the natural interdecadal oceanic modes (AMO and PDO) in observing climate change. At the same time a lack of deep-ocean long-term observing system restricts the accuracy of assessment of the heat redistribution in the World Ocean. I thanks to Pavel Sukhonos for help in the presentation preparing.

Quantitative analysis of the effect of climate change and human activities on runoff in the Liujiang River Basin

NASA Astrophysics Data System (ADS)

LI, X.

2017-12-01

Abstract: As human basic and strategic natural resources, Water resources have received an unprecedented challenge under the impacts of global climate change. Analyzing the variation characteristics of runoff and the effect of climate change and human activities on runoff could provide the basis for the reasonable utilization and management of water resources. Taking the Liujiang River Basin as the research object, the discharge data of hydrological station and meteorological data at 24 meteorological stations in the Guangxi Province as the basis, the variation characteristics of runoff and precipitation in the Liujiang River Basin was analyzed, and the quantitatively effect of climate change and human activities on runoff was proposed. The results showed that runoff and precipitation in the Liujiang River Basin had an increasing trend from 1964 to 2006. Using the method of accumulative anomaly and the orderly cluster method, the runoff series was divided into base period and change period. BP - ANN model and sensitivity coefficient method were used for quantifying the influences of climate change and human activities on runoff. We found that the most important factor which caused an increase trend of discharges in the Liujiang River Basin was precipitation. Human activities were also important factors which influenced the intra-annual distribution of runoff. Precipitation had a more sensitive influence to runoff variation than potential evaporation in the Liujiang River Basin. Key words: Liujiang River Basin, climate change, human activities, BP-ANN, sensitivity coefficient method

Quantifying the effects of climate variability and human activities on runoff for Kaidu River Basin in arid region of northwest China

NASA Astrophysics Data System (ADS)

Chen, Zhongsheng; Chen, Yaning; Li, Baofu

2013-02-01

Much attention has recently been focused on the effects that climate variability and human activities have had on runoff. In this study, data from the Kaidu River Basin in the arid region of northwest China were analyzed to investigate changes in annual runoff during the period of 1960-2009. The nonparametric Mann-Kendall test and the Mann-Kendall-Sneyers test were used to identify trend and step change point in the annual runoff. It was found that the basin had a significant increasing trend in annual runoff. Step change point in annual runoff was identified in the basin, which occurred in the year around 1993 dividing the long-term runoff series into a natural period (1960-1993) and a human-induced period (1994-2009). Then, the hydrologic sensitivity analysis method was employed to evaluate the effects of climate variability and human activities on mean annual runoff for the human-induced period based on precipitation and potential evapotranspiration. In 1994-2009, climate variability was the main factor that increased runoff with contribution of 90.5 %, while the increasing percentage due to human activities only accounted for 9.5 %, showing that runoff in the Kaidu River Basin is more sensitive to climate variability than human activities. This study quantitatively distinguishes the effects between climate variability and human activities on runoff, which can do duty for a reference for regional water resources assessment and management.

Dual impacts of climate change: forest migration and turnover through life history.

PubMed

Zhu, Kai; Woodall, Christopher W; Ghosh, Souparno; Gelfand, Alan E; Clark, James S

2014-01-01

Tree species are predicted to track future climate by shifting their geographic distributions, but climate-mediated migrations are not apparent in a recent continental-scale analysis. To better understand the mechanisms of a possible migration lag, we analyzed relative recruitment patterns by comparing juvenile and adult tree abundances in climate space. One would expect relative recruitment to be higher in cold and dry climates as a result of tree migration with juveniles located further poleward than adults. Alternatively, relative recruitment could be higher in warm and wet climates as a result of higher tree population turnover with increased temperature and precipitation. Using the USDA Forest Service's Forest Inventory and Analysis data at regional scales, we jointly modeled juvenile and adult abundance distributions for 65 tree species in climate space of the eastern United States. We directly compared the optimal climate conditions for juveniles and adults, identified the climates where each species has high relative recruitment, and synthesized relative recruitment patterns across species. Results suggest that for 77% and 83% of the tree species, juveniles have higher optimal temperature and optimal precipitation, respectively, than adults. Across species, the relative recruitment pattern is dominated by relatively more abundant juveniles than adults in warm and wet climates. These different abundance-climate responses through life history are consistent with faster population turnover and inconsistent with the geographic trend of large-scale tree migration. Taken together, this juvenile-adult analysis suggests that tree species might respond to climate change by having faster turnover as dynamics accelerate with longer growing seasons and higher temperatures, before there is evidence of poleward migration at biogeographic scales.

Greening and browning of the Himalaya: Spatial patterns and the role of climatic change and human drivers.

PubMed

Mishra, Niti B; Mainali, Kumar P

2017-06-01

The reliable detection and attribution of changes in vegetation greenness is a prerequisite for the development of strategies for the sustainable management of ecosystems. We conducted a robust trend analysis on remote sensing derived vegetation index time-series matrices to detect significant changes in inter-annual vegetation productivity (greening versus browning) for the entire Himalaya, a biodiverse and ecologically sensitive yet understudied region. The spatial variability in trend was assessed considering elevation, 12 dominant land cover/use types and 10 ecoregions. To assess trend causation, at local scale, we compared multi-temporal imagery, and at regional scale, referenced ecological theories of mountain vegetation dynamics and ancillary literature. Overall, 17.56% of Himalayan vegetation (71,162km 2 ) exhibited significant trend (p<0.01) and majority (94%) showed positive trend (greening). Trend distribution showed strong elevational and ecoregion dependence as greening was most dominant at lower and middle elevations whereas majority of the browning occurred at higher elevation (>3800m), with eastern high Himalaya browning more dominantly than western high Himalaya. Land cover/use based categorization confirmed dominant greening of rainfed and irrigated agricultural areas, though cropped areas in western Himalaya contained higher proportion of greening areas. While rising atmospheric CO 2 concentration and nitrogen deposition are the most likely climatic causes of detected greening, success of sustainable forestry practices (community forestry in Nepal) along with increasing agricultural fertilization and irrigation facilities could be possible human drivers. Comparison of multi-temporal imagery enabled direct attribution of some browning areas to anthropogenic land change (dam, airport and tunnel construction). Our satellite detected browning of high altitude vegetation in eastern Himalaya confirm the findings of recent dendrochronology based studies which possibly resulted from reduced pre-monsoon moisture availability in recent decades. These results have significant implications for environmental management in the context of climate change and ecosystem dynamics in the Himalaya. Copyright © 2017 Elsevier B.V. All rights reserved.

The water footprint of California's energy system, 1990-2012.

PubMed

Fulton, Julian; Cooley, Heather

2015-03-17

California's energy and water systems are interconnected and have evolved in recent decades in response to changing conditions and policy goals. For this analysis, we use a water footprint methodology to examine water requirements of energy products consumed in California between 1990 and 2012. We combine energy production, trade, and consumption data with estimates of the blue and green water footprints of energy products. We find that while California's total annual energy consumption increased by just 2.6% during the analysis period, the amount of water required to produce that energy grew by 260%. Nearly all of the increase in California's energy-related water footprint was associated with water use in locations outside of California, where energy products that the state consumes were, and continue to be, produced. We discuss these trends and the implications for California's future energy system as it relates to climate change and expected water management challenges inside and outside the state. Our analysis shows that while California's energy policies have supported climate mitigation efforts, they have increased vulnerability to climate impacts, especially greater hydrologic uncertainty. More integrated analysis and planning are needed to ensure that climate adaptation and mitigation strategies do not work at cross purposes.

Impacts of Climate Trends and Variability on Livestock Production in Brazil

NASA Astrophysics Data System (ADS)

Cohn, A.; Munger, J.; Gibbs, H.

2015-12-01

Cattle systems of Brazil are of major economic and environmental importance. They occupy ¼ of the land surface of the country, account for over 15 billion USD of annual revenue through the sale of beef, leather, and milk, are closely associated with deforestation, and have been projected to substantially grow in the coming decades. Sustainable intensification of production in the sector could help to limit environmental harm from increased production, but productivity growth could be inhibited by climate change. Gauging the potential future impacts of climate change on the Brazilian livestock sector can be aided by examining past evidence of the link between climate and cattle production and productivity. We use statistical techniques to investigate the contribution of climate variability and climate change to variability in cattle system output in Brazil's municipalities over the period 1974 to 2013. We find significant impacts of both temperature and precipitation variability and temperature trends on municipality-level exports and the production of both milk and beef. Pasture productivity, represented by a vegetation index, also varies significantly with climate shocks. In some regions, losses from exposure to climate trends were of comparable magnitude to technology and/or market-driven productivity gains over the study period.

Variability, trends, and teleconnections of stream flows with large-scale climate signals in the Omo-Ghibe River Basin, Ethiopia.

PubMed

Degefu, Mekonnen Adnew; Bewket, Woldeamlak

2017-04-01

This study assesses variability, trends, and teleconnections of stream flow with large-scale climate signals (global sea surface temperatures (SSTs)) for the Omo-Ghibe River Basin of Ethiopia. Fourteen hydrological indices of variability and extremes were defined from daily stream flow data series and analyzed for two common periods, which are 1972-2006 for 5 stations and 1982-2006 for 15 stations. The Mann-Kendall's test was used to detect trends at 0.05 significance level, and simple correlation analysis was applied to evaluate associations between the selected stream flow indices and SSTs. We found weak and mixed (upward and downward) trend signals for annual and wet (Kiremt) season flows. Indices generated for high-flow (flood) magnitudes showed the same weak trend signals. However, trend tests for flood frequencies and low-flow magnitudes showed little evidences of increasing change. It was also found that El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) are the major anomalies affecting stream flow variability in the Omo-Ghibe Basin. The strongest associations are observed between ENSO/Niño3.4 and the stream flow in August and September, mean Kiremt flow (July-September), and flood frequency (peak over threshold on average three peaks per year (POT3_Fre)). The findings of this study provide a general overview on the long-term stream flow variability and predictability of stream flows for the Omo-Ghibe River Basin.

Analysis of long-term trends (1950–2009) in precipitation, runoff and runoff coefficient in major urban watersheds in the United States

USGS Publications Warehouse

Velpuri, N.M.; Senay, G.B.

2013-01-01

This study investigates the long-term trends in precipitation, runoff and runoff coefficient in major urban watersheds in the United States. The seasonal Mann–Kendall trend test was performed on monthly precipitation, runoff and runoff coefficient data from 1950 to 2009 obtained from 62 urban watersheds covering 21 major urban centers in the United States. The results indicate that only five out of 21 urban centers in the United States showed an uptrend in precipitation. Twelve urban centers showed an uptrend in runoff coefficient. However, six urban centers did not show any trend in runoff coefficient, and three urban centers showed a significant downtrend. The highest rate of change in precipitation, runoff and runoff coefficient was observed in the Houston urban watershed. Based on the results obtained, we also attributed plausible causes for the trends. Our analysis indicated that while a human only influence is observed in most of the urban watersheds, a combined climate and human influence is observed in the central United States.

A hybrid-domain approach for modeling climate data time series

NASA Astrophysics Data System (ADS)

Wen, Qiuzi H.; Wang, Xiaolan L.; Wong, Augustine

2011-09-01

In order to model climate data time series that often contain periodic variations, trends, and sudden changes in mean (mean shifts, mostly artificial), this study proposes a hybrid-domain (HD) algorithm, which incorporates a time domain test and a newly developed frequency domain test through an iterative procedure that is analogue to the well known backfitting algorithm. A two-phase competition procedure is developed to address the confounding issue between modeling periodic variations and mean shifts. A variety of distinctive features of climate data time series, including trends, periodic variations, mean shifts, and a dependent noise structure, can be modeled in tandem using the HD algorithm. This is particularly important for homogenization of climate data from a low density observing network in which reference series are not available to help preserve climatic trends and long-term periodic variations, preventing them from being mistaken as artificial shifts. The HD algorithm is also powerful in estimating trend and periodicity in a homogeneous data time series (i.e., in the absence of any mean shift). The performance of the HD algorithm (in terms of false alarm rate and hit rate in detecting shifts/cycles, and estimation accuracy) is assessed via a simulation study. Its power is further illustrated through its application to a few climate data time series.

The paradox of cooling streams in a warming world: regional climate trends do not parallel variable local trends in stream temperature in the Pacific continental United States

Treesearch

Ivan Arismendi; Sherri L. Johnson; Jason B. Dunham; Roy Haggerty

2012-01-01

Temperature is a fundamentally important driver of ecosystem processes in streams. Recent warming of terrestrial climates around the globe has motivated concern about consequent increases in stream temperature. More specifically, observed trends of increasing air temperature and declining stream flow are widely believed to result in corresponding increases in stream...

Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Worku, Gebrekidan; Teferi, Ermias; Bantider, Amare; Dile, Yihun T.

2018-02-01

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen's slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies.

Vegetation greenness trend (2000 to 2009) and the climate controls in the Qinghai-Tibetan Plateau

USGS Publications Warehouse

Zhang, Li; Guo, Huadong; Ji, Lei; Lei, Liping; Wang, Cuizhen; Yan, Dongmei; Li, Bin; Li, Jing

2013-01-01

The Qinghai-Tibetan Plateau has been experiencing a distinct warming trend, and climate warming has a direct and quick impact on the alpine grassland ecosystem. We detected the greenness trend of the grasslands in the plateau using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2009. Weather station data were used to explore the climatic drivers for vegetation greenness variations. The results demonstrated that the region-wide averaged normalized difference vegetation index (NDVI) increased at a rate of 0.036  yr−1. Approximately 20% of the vegetation areas, which were primarily located in the northeastern plateau, exhibited significant NDVI increase trend (p-value <0.05). Only 4% of the vegetated area showed significant decrease trends, which were mostly in the central and southwestern plateau. A strong positive relationship between NDVI and precipitation, especially in the northeastern plateau, suggested that precipitation was a favorable factor for the grassland NDVI. Negative correlations between NDVI and temperature, especially in the southern plateau, indicated that higher temperature adversely affected the grassland growth. Although a warming climate was expected to be beneficial to the vegetation growth in cold regions, the grasslands in the central and southwestern plateau showed a decrease in trends influenced by increased temperature coupled with decreased precipitation.

Climate variations in the late Miocene - early Pliocene in the Black Sea region (Taman peninsula) inferred from palynological analyses.

NASA Astrophysics Data System (ADS)

Grundan, Ekaterina; Kürschner, Wolfram; Krijgsman, Wout

2017-04-01

A palynological study of Neogene sediments from the cape "Zhelezny Rog" (Taman peninsula, the Black Sea area) was carried out as part of integrated micropaleontological, lithological and paleomagnetic research. The Neogene section of the cape "Zhelezny Rog" (the Zhelezny Rog section) is one of the most representative Upper Miocene to Lower Pliocene succession of Eastern Paratethys. The section covers the Sarmatian, Maeotian, Pontian (upper Miocene) and Kimmerian (lower Pliocene) local stages. One hundred and eighteen samples were selected from the Zhelezny rog section for quantitative palynological analysis. Using PCA analysis and additional proxy such as "steppe index", art/chen and poa/ast ratios the regional climate history was reconstructed. The Early Maeotian is characterized by a warm, warm-temperate climate on the background of relatively high humidity. During the Late Maeotian it became colder and dryer. The coldest and driest conditions during the Maeotian correspond to the middle part of the Late Maeotian. There were a high number of steppe elements (as Artemisia) and low amount of thermophilous ones. Climate of the end of the Maeotian was characterized by warmer and wetter conditions. In the beginning of the Pontian there was a cooling trend, as evidenced by the decreasing thermophilous elements and the increasing high-latitude trees. Most significant changes were found within the Pontian-Kimmerian boundary beds. This level is characterized by decreasing of thermophilous elements, increasing of cool-temperate pollen and Sphagnum spores that are considered as an evidence of a temperature decrease in the background of high humidity conditions. The results will be discussed and correlated to Neogene global climate trends.

High-Elevation Sierra Nevada Conifers Reveal Increasing Reliance on Snow Water with Changing Climate

NASA Astrophysics Data System (ADS)

Lepley, K. S.; Meko, D. M.; Touchan, R.; Shamir, E.; Graham, R.

2017-12-01

Snowpack in the Sierra Nevada Mountains accounts for around one third of California's water supply. Melting snow can provide water into dry summer months characteristic of the region's Mediterranean climate. As climate changes, understanding patterns of snowpack, snowmelt, and biological response are critical in this region of agricultural, recreational, and ecological value. Tree rings can act as proxy records to inform scientists and resource managers of past climate variability where instrumental data is unavailable. Here we investigate relationships between tree rings of high-elevation, snow-adapted conifer trees (Tsuga mertensiana, Abies magnifica) and April 1st snow-water equivalent (SWE) in the northern Sierra Nevada Mountains. The 1st principal component of 29 highly correlated regional SWE time series was modeled using multiple linear regression of four tree-ring chronologies including two lagged chronologies. Split-period verification analysis of this model revealed poor predictive skill in the early half (1929 - 1966) of the calibration period (1929 - 2003). Further analysis revealed a significant (p < 0.01) change in correlation between the Tsuga mertensiana chronology and SWE during early (1929 - 1970) and late (1971 - 2013) periods. Running 31-year correlations between this chronology and SWE rose from r = 0.10 in 1950 to r = 0.77 in 1996. This strengthening relationship is coincident with a positive trend in temperature, a negative trend in SWE, and increased variability in precipitation through time. Snow water is becoming a more limiting resource to tree growth as average temperatures rise and the hydrologic regime shifts. These results highlight the need for resource managers and policy makers to consider that biological response to climate is not static.

Assessing the robustness and uncertainties of projected changes in temperature and precipitation in AR4 Global Climate Models over the Arabian Peninsula

NASA Astrophysics Data System (ADS)

Almazroui, Mansour; Saeed, Fahad; Islam, Md. Nazrul; Alkhalaf, A. K.

2016-12-01

An ensemble from different climate projections is essential for attaining robust climate change information in a particular region. To achieve this purpose, the results of an ensemble combining the Global Climate Models data from Couple Model Intercomparison Project 3 (CMIP3), have been employed for the Arabian Peninsula region. Different analysis methods comprising spatial plots with robustness analysis, bar plots with likelihood ranges, as well as line plots with likelihood spread along with decadal trend analysis have been carried out at annual as well as seasonal time scales for temperature and precipitation. Results of CMIP3 data for the B1, A1B and A2 scenarios indicate robust changes in temperature and precipitation in the future climate. Spatial plots show a robust summer temperature increase over the whole Peninsula which is higher in the summer season as compared to the winter. The Northern Arabian Peninsula (NAP) region also shows a higher temperature increase in comparison with the Southern Arabian Peninsula (SAP) during the summer season. Moreover the NAP region, which generally comes under the influence of disturbances originating from the Mediterranean Sea region during the winter season, has shown a robust decrease in precipitation during the winter season. Contrarily the SAP region, which remains dry during the winter season and comes under the influence of South Asian Summer Monsoon in the summer season, indicates a robust increase in precipitation during the summer season. This behavior is also obvious from bar plots, which show a gradual decrease (increase) in median precipitation values towards the end of the 21st century for all the three scenarios over the NAP (SAP) region during the winter (summer) season. Moreover, smaller lengths of full as well as likely ranges in the bar plot for NAP (SAP) shows that these precipitation projections are less uncertain as compared to SAP (NAP) for the winter (summer) season. Furthermore from the line plots, a consistent decreasing trend in precipitation (1.35% per decade, significant at 99%) can be observed, while SAP shows an increasing trend in precipitation (1.21% per decade, significant at 99%). Similarly for the case of temperature, a significant (99% level) increase is projected over NAP and SAP regions with values of 0.37 and 0.35 °C per decade respectively. Considering the vulnerability of the region to climate change impacts, these results call for immediate actions in developing the long-term strategies to deal with the adverse impacts of climate change up-to the end of the 21st century at a regional level.

Information and communication technology and climate change adaptation: Evidence from selected mining companies in South Africa

PubMed Central

Nhamo, Godwell

2016-01-01

The mining sector is a significant contributor to the gross domestic product of many global economies. Given the increasing trends in climate-induced disasters and the growing desire to find lasting solutions, information and communication technology (ICT) has been introduced into the climate change adaptation mix. Climate change-induced extreme weather events such as flooding, drought, excessive fog, and cyclones have compounded the environmental challenges faced by the mining sector. This article presents the adoption of ICT innovation as part of the adaptation strategies towards reducing the mining sector’s vulnerability and exposure to climate change disaster risks. Document analysis and systematic literature review were adopted as the methodology. Findings from the study reflect how ICT intervention orchestrated changes in communication patterns which are tailored towards the reduction in climate change vulnerability and exposure. The research concludes with a proposition that ICT intervention must be part of the bigger and ongoing climate change adaptation agenda in the mining sector.

Climate variability, animal reservoir and transmission of scrub typhus in Southern China

PubMed Central

Li, Xiaoning; Ma, Yu; Tao, Xia; Wu, Xinwei

2017-01-01

Objectives We aimed to evaluate the relationships between climate variability, animal reservoirs and scrub typhus incidence in Southern China. Methods We obtained data on scrub typhus cases in Guangzhou every month from 2006 to 2014 from the Chinese communicable disease network. Time-series Poisson regression models and distributed lag nonlinear models (DLNM) were used to evaluate the relationship between risk factors and scrub typhus. Results Wavelet analysis found the incidence of scrub typhus cycled with a period of approximately 8–12 months and long-term trends with a period of approximately 24–36 months. The DLNM model shows that relative humidity, rainfall, DTR, MEI and rodent density were associated with the incidence of scrub typhus. Conclusions Our findings suggest that the incidence scrub typhus has two main temporal cycles. Determining the reason for this trend and how it can be used for disease control and prevention requires additional research. The transmission of scrub typhus is highly dependent on climate factors and rodent density, both of which should be considered in prevention and control strategies for scrub typhus. PMID:28273079

Climate variability, animal reservoir and transmission of scrub typhus in Southern China.

PubMed

Wei, Yuehong; Huang, Yong; Li, Xiaoning; Ma, Yu; Tao, Xia; Wu, Xinwei; Yang, Zhicong

2017-03-01

We aimed to evaluate the relationships between climate variability, animal reservoirs and scrub typhus incidence in Southern China. We obtained data on scrub typhus cases in Guangzhou every month from 2006 to 2014 from the Chinese communicable disease network. Time-series Poisson regression models and distributed lag nonlinear models (DLNM) were used to evaluate the relationship between risk factors and scrub typhus. Wavelet analysis found the incidence of scrub typhus cycled with a period of approximately 8-12 months and long-term trends with a period of approximately 24-36 months. The DLNM model shows that relative humidity, rainfall, DTR, MEI and rodent density were associated with the incidence of scrub typhus. Our findings suggest that the incidence scrub typhus has two main temporal cycles. Determining the reason for this trend and how it can be used for disease control and prevention requires additional research. The transmission of scrub typhus is highly dependent on climate factors and rodent density, both of which should be considered in prevention and control strategies for scrub typhus.

Creating Near-Term Climate Scenarios for AgMIP

NASA Astrophysics Data System (ADS)

Goddard, L.; Greene, A. M.; Baethgen, W.

2012-12-01

For the next assessment report of the IPCC (AR5), attention is being given to development of climate information that is appropriate for adaptation, such as decadal-scale and near-term predictions intended to capture the combined effects of natural climate variability and the emerging climate change signal. While the science and practice evolve for the production and use of dynamic decadal prediction, information relevant to agricultural decision-makers can be gained from analysis of past decadal-scale trends and variability. Statistical approaches that mimic the characteristics of observed year-to-year variability can indicate the range of possibilities and their likelihood. In this talk we present work towards development of near-term climate scenarios, which are needed to engage decision-makers and stakeholders in the regions in current decision-making. The work includes analyses of decadal-scale variability and trends in the AgMIP regions, and statistical approaches that capture year-to-year variability and the associated persistence of wet and dry years. We will outline the general methodology and some of the specific considerations in the regional application of the methodology for different AgMIP regions, such those for Western Africa versus southern Africa. We will also show some examples of quality checks and informational summaries of the generated data, including (1) metrics of information quality such as probabilistic reliability for a suite of relevant climate variables and indices important for agriculture; (2) quality checks relative to the use of this climate data in crop models; and, (3) summary statistics (e.g., for 5-10-year periods or across given spatial scales).

Development of a robust analytical framework for assessing landbird trends, dynamics and relationships with environmental covariates in the North Coast and Cascades Network

USGS Publications Warehouse

Ray, Chris; Saracco, James; Jenkins, Kurt J.; Huff, Mark; Happe, Patricia J.; Ransom, Jason I.

2017-01-01

During 2015-2016, we completed development of a new analytical framework for landbird population monitoring data from the National Park Service (NPS) North Coast and Cascades Inventory and Monitoring Network (NCCN). This new tool for analysis combines several recent advances in modeling population status and trends using point-count data and is designed to supersede the approach previously slated for analysis of trends in the NCCN and other networks, including the Sierra Nevada Network (SIEN). Advances supported by the new model-based approach include 1) the use of combined data on distance and time of detection to estimate detection probability without assuming perfect detection at zero distance, 2) seamless accommodation of variation in sampling effort and missing data, and 3) straightforward estimation of the effects of downscaled climate and other local habitat characteristics on spatial and temporal trends in landbird populations. No changes in the current field protocol are necessary to facilitate the new analyses. We applied several versions of the new model to data from each of 39 species recorded in the three mountain parks of the NCCN, estimating trends and climate relationships for each species during 2005-2014. Our methods and results are also reported in a manuscript in revision for the journal Ecosphere (hereafter, Ray et al.). Here, we summarize the methods and results outlined in depth by Ray et al., discuss benefits of the new analytical framework, and provide recommendations for its application to synthetic analyses of long-term data from the NCCN and SIEN. All code necessary for implementing the new analyses is provided within the Appendices to this report, in the form of fully annotated scripts written in the open-access programming languages R and JAGS.

Developing quantitative criteria to evaluate AOGCMs for application to regional climate assessments

NASA Astrophysics Data System (ADS)

Hayhoe, K.; Wake, C.; Bradbury, J.; Degaetano, A.; Hertel, A.

2006-12-01

Climate projections are the foundation for regional assessments of potential climate impacts. However, the soundness of regional assessments depends on the ability of global climate models to reproduce key processes responsible for regional climate trends. Here, we develop a systematic method to compare observed climate with historical atmosphere-ocean general circulation model (AOGCM) simulations, to assess the degree to which AOGCMs are able to reproduce regional circulation patterns. Applying this methodology to the U.S. Northeast (NE), we find that nearly all AOGCMs simulate a reasonable winter NAO pattern and seasonal positions of the Jet Stream and the East Coast Trough. However, not all models capture observed correlations between these circulation patterns and seasonal climate anomalies in the NE. Using only those AOGCMs that meet the criteria in each of these areas, we then develop projections of future climate change in the NE. The primary changes projected to occur over the next century - slightly greater temperature increases in summer than winter, and increases in winter precipitation - are consistent with projected trends in regional climate processes and are relatively independent of model or scale. These suggest confidence in the direction and potential range of the most notable regional climate trends, with the absolute magnitude of change depending on both the sensitivity of the climate system to human forcing as well as on human emissions over coming decades.

The changes in the frequency of daily precipitation in Urmia Lake basin, Iran

NASA Astrophysics Data System (ADS)

Salehi Bavil, Sepideh; Zeinalzadeh, Kamran; Hessari, Behzad

2017-06-01

Urmia Lake, as one of the most valuable saline ecosystems in the world, has faced a sharp drop in the water level in recent years. The trend studies of climatic parameters can be effective in identifying the responsible factors and managing this crisis. This research investigated the frequency trend of daily precipitation in the ranges of less than 5 mm, 5-10 mm, 10-15 mm, 15-20 mm, and more than 20 mm in the Urmia Lake basin. The trend was assessed using Mann-Kendall, Spearman Rho and linear regression tests on 60 stations during a period of 30 years (1981 to 2011). The results showed that in all the three tests, the frequency of daily precipitation of less than 5 mm had a significant increase at 1% level. The 5-10 mm range displayed no significant trend, while the 10-15 mm range showed a significantly decreasing trend. The frequency in the 15-20 mm and above 20 mm ranges showed an insignificant falling trend. The analysis also indicated jumps in 1996 and 1999 (almost coinciding with the sharp drop in the lake's water level). In other words, the frequency trends of daily precipitation with small amounts (as a result, high evapotranspiration loss) were increasing and with large amounts were decreasing. This can be a contributor to reduced run-off and, hence, decreased water entering the lake. The results emphasize the need for changes in the management and consumption of water resources in the basin, in order to adapt to the climatic change.

Consistent response of vegetation dynamics to recent climate change in tropical mountain regions.

PubMed

Krishnaswamy, Jagdish; John, Robert; Joseph, Shijo

2014-01-01

Global climate change has emerged as a major driver of ecosystem change. Here, we present evidence for globally consistent responses in vegetation dynamics to recent climate change in the world's mountain ecosystems located in the pan-tropical belt (30°N-30°S). We analyzed decadal-scale trends and seasonal cycles of vegetation greenness using monthly time series of satellite greenness (Normalized Difference Vegetation Index) and climate data for the period 1982-2006 for 47 mountain protected areas in five biodiversity hotspots. The time series of annual maximum NDVI for each of five continental regions shows mild greening trends followed by reversal to stronger browning trends around the mid-1990s. During the same period we found increasing trends in temperature but only marginal change in precipitation. The amplitude of the annual greenness cycle increased with time, and was strongly associated with the observed increase in temperature amplitude. We applied dynamic models with time-dependent regression parameters to study the time evolution of NDVI-climate relationships. We found that the relationship between vegetation greenness and temperature weakened over time or was negative. Such loss of positive temperature sensitivity has been documented in other regions as a response to temperature-induced moisture stress. We also used dynamic models to extract the trends in vegetation greenness that remain after accounting for the effects of temperature and precipitation. We found residual browning and greening trends in all regions, which indicate that factors other than temperature and precipitation also influence vegetation dynamics. Browning rates became progressively weaker with increase in elevation as indicated by quantile regression models. Tropical mountain vegetation is considered sensitive to climatic changes, so these consistent vegetation responses across widespread regions indicate persistent global-scale effects of climate warming and associated moisture stresses. © 2013 John Wiley & Sons Ltd.

Revisiting Southern Hemisphere polar stratospheric temperature trends in WACCM: The role of dynamical forcing

NASA Astrophysics Data System (ADS)

Calvo, N.; Garcia, R. R.; Kinnison, D. E.

2017-04-01

The latest version of the Whole Atmosphere Community Climate Model (WACCM), which includes a new chemistry scheme and an updated parameterization of orographic gravity waves, produces temperature trends in the Antarctic lower stratosphere in excellent agreement with radiosonde observations for 1969-1998 as regards magnitude, location, timing, and persistence. The maximum trend, reached in November at 100 hPa, is -4.4 ± 2.8 K decade-1, which is a third smaller than the largest trend in the previous version of WACCM. Comparison with a simulation without the updated orographic gravity wave parameterization, together with analysis of the model's thermodynamic budget, reveals that the reduced trend is due to the effects of a stronger Brewer-Dobson circulation in the new simulations, which warms the polar cap. The effects are both direct (a trend in adiabatic warming in late spring) and indirect (a smaller trend in ozone, hence a smaller reduction in shortwave heating, due to the warmer environment).

Holocene Faunal Trends in West Siberia and Their Causes

NASA Astrophysics Data System (ADS)

Gashev, S. N.; Aleshina, A. O.; Zuban, I. A.; Lupinos, M. Y.; Mardonova, L. B.; Mitropolskiy, M. G.; Selyukov, A. G.; Sorokina, N. V.; Stolbov, V. A.; Shapovalov, S. I.

2017-12-01

Based on an analysis of the transformation of vertebrate and invertebrate fauna of West Siberia in the Holocene, the classification and periodization of the main faunal trends are presented. Against the background of changing environmental conditions, the key regularities of the faunal dynamics, and the ways some species penetrate into the territory of the region and others disappear from the beginning of the Holocene to the present time have been indicated. Three global and four fluctuating trends are identified. The anthropogenic trend is ascertained separately. A conclusion is made about the prevailing causes of these changes, associated primarily with periodic climatic processes of different levels, determined by planetary geological and cosmic cycles. It is emphasized that, in the historical period, anthropogenic factors play a significant role in the regional faunal dynamics.

Climate and Hydrological Data Analysis for hydrological and solute transport modelling purposes in the Muriaé River basin, Atlantic Forest Biome, SE Brazil

NASA Astrophysics Data System (ADS)

Santos, Juliana; Künne, Annika; Kralisch, Sven; Fink, Manfred; Brenning, Alexander

2016-04-01

The Muriaé River basin in SE Brazil has been experiencing an increasing pressure on water resources, due to the population growth of the Rio de Janeiro urban area connected with the growth of the industrial and agricultural sector. This leads to water scarcity, riverine forest degradation, soil erosion and water quality problems among other impacts. Additionally the region has been suffering with seasonal precipitation variations leading to extreme events such as droughts, floods and landslides. Climate projections for the near future indicate a high inter-annual variability of rainfall with an increase in the frequency and intensity of heavy rainfall events combined with a statistically significant increase in the duration of dry periods and a reduced duration of wet periods. This may lead to increased soil erosion during the wet season, while the longer dry periods may reduce the vegetation cover, leaving the soil even more exposed and vulnerable to soil erosion. In consequence, it is crucial to understand how climate affects the interaction between the timing of extreme rainfall events, hydrological processes, vegetation growth, soil cover and soil erosion. In this context, physically-based hydrological modelling can contribute to a better understanding of spatial-temporal process dynamics in the Earth's system and support Integrated Water Resourses Management (IWRM) and adaptation strategies. The study area is the Muriaé river basin which has an area of approx. 8000 km² in Minas Gerais and Rio de Janeiro States. The basin is representative of a region of domain of hillslopes areas with the predominancy of pasture for livestock production. This study will present some of the relevant analyses which have been carried out on data (climate and streamflow) prior to using them for hydrological modelling, including consistency checks, homogeneity, pattern and statistical analyses, or annual and seasonal trends detection. Several inconsistencies on the raw data were detected and excluded from the dataset. Statistically significant annual and seasonal trends have been detected such as an increasing trend for annual mean temperature, a decreasing trend for annual relative humidity and an increasing trend for precipitation during the wet season. Moreover, the physically-based and fully distributed hydrological model JAMS/J2K-S has been applied and the spatial-temporal visualization of the climate data as well as an evaluation of spatial uncertainty will be presented.

Temperature trends in desert cities: how vegetation and urbanization affect the urban heat island dynamics in hyper-arid climates

NASA Astrophysics Data System (ADS)

Marpu, P. R.; Lazzarini, M.; Molini, A.; Ghedira, H.

2013-12-01

Urban areas represent a unique micro-climatic system, mainly characterized by scarcity of vegetation and ground moisture, an albedo strictly dependent on building materials and urban forms, high heat capacity, elevated pollutants emissions, anthropogenic heat production, and a characteristic boundary layer dynamics. For obvious historical reasons, the first to be addressed in the literature were the effects of urbanization on the local microclimate of temperate regions, where most of the urban development took place in the last centuries. Here micro-climatic characteristics all contribute to the warming of urban areas, also known as 'urban heat island' effect, and are expected to crucially impact future energy and water consumption, air quality, and human health. However, rapidly increasing urbanization rates in arid and hyper-arid developing countries could soon require more attention towards studying the effects of urban development on arid climates, which remained mainly unexplored till now. In this talk we investigate the climatology of urban heat islands in seven highly urbanized desert cities based on day and night temporal trends of land surface temperature (LST) and normalized difference vegetation index (NDVI) acquired using MODIS satellite during 2000-2012. Urban and rural areas are distinguished by analyzing the high-resolution temporal variability and averaged monthly values of LST, NDVI and Surface Urban Heat Island (SUHI) for all the seven cities and adjacent sub-urban areas. Different thermal behaviors were observed at the selected sites, also including temperature mitigation and inverse urban heat island, and are here discussed together with detailed analysis of the corresponding trends.

Assessing uncertainty in high-resolution spatial climate data across the US Northeast.

PubMed

Bishop, Daniel A; Beier, Colin M

2013-01-01

Local and regional-scale knowledge of climate change is needed to model ecosystem responses, assess vulnerabilities and devise effective adaptation strategies. High-resolution gridded historical climate (GHC) products address this need, but come with multiple sources of uncertainty that are typically not well understood by data users. To better understand this uncertainty in a region with a complex climatology, we conducted a ground-truthing analysis of two 4 km GHC temperature products (PRISM and NRCC) for the US Northeast using 51 Cooperative Network (COOP) weather stations utilized by both GHC products. We estimated GHC prediction error for monthly temperature means and trends (1980-2009) across the US Northeast and evaluated any landscape effects (e.g., elevation, distance from coast) on those prediction errors. Results indicated that station-based prediction errors for the two GHC products were similar in magnitude, but on average, the NRCC product predicted cooler than observed temperature means and trends, while PRISM was cooler for means and warmer for trends. We found no evidence for systematic sources of uncertainty across the US Northeast, although errors were largest at high elevations. Errors in the coarse-scale (4 km) digital elevation models used by each product were correlated with temperature prediction errors, more so for NRCC than PRISM. In summary, uncertainty in spatial climate data has many sources and we recommend that data users develop an understanding of uncertainty at the appropriate scales for their purposes. To this end, we demonstrate a simple method for utilizing weather stations to assess local GHC uncertainty and inform decisions among alternative GHC products.

Natural and Anthropogenic Aerosol Trends from Satellite and Surface Observations and Model Simulations over the North Atlantic Ocean from 2002 to 2012

NASA Technical Reports Server (NTRS)

Jongeward, Andrew R.; Li, Zhanqing; He, Hao; Xiong, Xiaoxiong

2016-01-01

Aerosols contribute to Earths radiative budget both directly and indirectly, and large uncertainties remain in quantifying aerosol effects on climate. Variability in aerosol distribution and properties, as might result from changing emissions and transport processes, must be characterized. In this study, variations in aerosol loading across the eastern seaboard of theUnited States and theNorthAtlanticOcean during 2002 to 2012 are analyzed to examine the impacts of anthropogenic emission control measures using monthly mean data from MODIS, AERONET, and IMPROVE observations and Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulation.MODIS observes a statistically significant negative trend in aerosol optical depth (AOD) over the midlatitudes (-0.030 decade(sup-1)). Correlation analyses with surface AOD from AERONET sites in the upwind region combined with trend analysis from GOCART component AOD confirm that the observed decrease in the midlatitudes is chiefly associated with anthropogenic aerosols that exhibit significant negative trends from the eastern U.S. coast extending over the western North Atlantic. Additional analysis of IMPROVE surface PM(sub 2.5) observations demonstrates statistically significant negative trends in the anthropogenic components with decreasing mass concentrations over the eastern United States. Finally, a seasonal analysis of observational datasets is performed. The negative trend seen by MODIS is strongest during spring (MAM) and summer (JJA) months. This is supported by AERONET seasonal trends and is identified from IMPROVE seasonal trends as resulting from ammonium sulfate decreases during these seasons.

Evaluating water quality ecosystem services of wetlands under historic and future climate

NASA Astrophysics Data System (ADS)

Records, R.; Arabi, M.; Fassnacht, S. R.; Duffy, W.; Ahmadi, M.; Hegewisch, K.

2013-12-01

Potential hydrologic effects of climate change have been assessed extensively; however, possible impacts of changing climate on in-stream water quality at the watershed scale have received little study. We assessed potential impacts of climate change on water quantity and quality in the mountainous Sprague River watershed, Oregon, USA, where high total phosphorus (TP) and sediment loads are associated with lake eutrophication and mortality of endangered fish species. Additionally, we analyzed water quality impacts of wetland and riparian zone loss and gain under present-day climate and future climate scenarios. We utilized the hydrologic model Soil and Water Assessment Tool (SWAT) forced with six distinct climate scenarios derived from Coupled Model Intercomparison Project 5 (CMIP5) General Circulation Models to assess magnitude and direction of trends in streamflow, sediment and TP fluxes in the mid-21st century (2030-2059). Model results showed little significant trend in average annual streamflow under most climate scenarios, but trends in annual and monthly streamflow, sediment, and TP fluxes were more pronounced and were generally increasing. Results also suggest that future loss of present-day wetlands and riparian zones under land use or climatic change could result in substantial increases in sediment and TP loads at the Sprague River outlet.

Coarse climate change projections for species living in a fine-scaled world.

PubMed

Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R

2017-01-01

Accurately predicting biological impacts of climate change is necessary to guide policy. However, the resolution of climate data could be affecting the accuracy of climate change impact assessments. Here, we review the spatial and temporal resolution of climate data used in impact assessments and demonstrate that these resolutions are often too coarse relative to biologically relevant scales. We then develop a framework that partitions climate into three important components: trend, variance, and autocorrelation. We apply this framework to map different global climate regimes and identify where coarse climate data is most and least likely to reduce the accuracy of impact assessments. We show that impact assessments for many large mammals and birds use climate data with a spatial resolution similar to the biologically relevant area encompassing population dynamics. Conversely, impact assessments for many small mammals, herpetofauna, and plants use climate data with a spatial resolution that is orders of magnitude larger than the area encompassing population dynamics. Most impact assessments also use climate data with a coarse temporal resolution. We suggest that climate data with a coarse spatial resolution is likely to reduce the accuracy of impact assessments the most in climates with high spatial trend and variance (e.g., much of western North and South America) and the least in climates with low spatial trend and variance (e.g., the Great Plains of the USA). Climate data with a coarse temporal resolution is likely to reduce the accuracy of impact assessments the most in the northern half of the northern hemisphere where temporal climatic variance is high. Our framework provides one way to identify where improving the resolution of climate data will have the largest impact on the accuracy of biological predictions under climate change. © 2016 John Wiley & Sons Ltd.

Communicating climate information to end-users: an experience driven by the understanding and anticipation of user needs.

NASA Astrophysics Data System (ADS)

Chaumont, Diane; Huard, David; Logan, Travis; Sottile, Marie-France; Brown, Ross; Gauvin St-Denis, Blaise; Grenier, Patrick; Braun, Marco

2013-04-01

Planning and adapting to a changing climate requires credible information about the magnitude and rate of projected changes. Ouranos, a consortium on regional climatology and adaptation to climate change was launched in the Province of Québec, Canada, ten years ago, with the objective of developing and providing climate information and expertise in support to adaption. Ouranos differs from most other climate service centers by integrating climate modeling activities, impacts and adaptation expertise and climate analysis services under one roof. The Climate Scenarios Group operates at the interface between climate modellers and users and is responsible for developing, producing and communicating climate scenarios to end-users in a consistent manner. This process requires close collaboration with users to define, understand and eventually anticipate their needs. The varied scientific expertise of climate scenarios specialists --who also act as communicators-- has proven to be a key element for successful communication. A large amount of effort is spent on the characterization and communication of the uncertainties involved in scenario construction. Two main activities have been put in place by the experts in climate modeling to address this: (1) a training course on climate models and (2) a fact-sheet summarizing the uncertainty and robustness of the climate change scenario provided for each I&A application. The latter tool ensures the transparency, traceability, and accountability of our products, and at the same time, encourages a sense of shared responsibility for the final choice of climate scenarios. In addition to uncertainty, two other main issues have been identified as essential in communication with users: 1) observed natural variability at relevant scales and 2) reconciliation of the projected trend with the recent observed trend. Our group has devoted substantial resources for the advancement of communication with end-users in these particular areas. This presentation will provide an overview of progress in communicating climate information at the Ouranos Consortium. We will discuss success and failures and future plans, in particular the extent to which Ouranos needs to work with users in decision-making activities.

Drought risk assessment under climate change is sensitive to methodological choices for the estimation of evaporative demand

PubMed Central

Barsugli, Joseph J.; Hobbins, Michael T.; Kumar, Sanjiv

2017-01-01

Several studies have projected increases in drought severity, extent and duration in many parts of the world under climate change. We examine sources of uncertainty arising from the methodological choices for the assessment of future drought risk in the continental US (CONUS). One such uncertainty is in the climate models’ expression of evaporative demand (E0), which is not a direct climate model output but has been traditionally estimated using several different formulations. Here we analyze daily output from two CMIP5 GCMs to evaluate how differences in E0 formulation, treatment of meteorological driving data, choice of GCM, and standardization of time series influence the estimation of E0. These methodological choices yield different assessments of spatio-temporal variability in E0 and different trends in 21st century drought risk. First, we estimate E0 using three widely used E0 formulations: Penman-Monteith; Hargreaves-Samani; and Priestley-Taylor. Our analysis, which primarily focuses on the May-September warm-season period, shows that E0 climatology and its spatial pattern differ substantially between these three formulations. Overall, we find higher magnitudes of E0 and its interannual variability using Penman-Monteith, in particular for regions like the Great Plains and southwestern US where E0 is strongly influenced by variations in wind and relative humidity. When examining projected changes in E0 during the 21st century, there are also large differences among the three formulations, particularly the Penman-Monteith relative to the other two formulations. The 21st century E0 trends, particularly in percent change and standardized anomalies of E0, are found to be sensitive to the long-term mean value and the amplitude of interannual variability, i.e. if the magnitude of E0 and its interannual variability are relatively low for a particular E0 formulation, then the normalized or standardized 21st century trend based on that formulation is amplified relative to other formulations. This is the case for the use of Hargreaves-Samani and Priestley-Taylor, where future E0 trends are comparatively much larger than for Penman-Monteith. When comparing Penman-Monteith E0 responses between different choices of input variables related to wind speed, surface roughness, and net radiation, we found differences in E0 trends, although these choices had a much smaller influence on E0 trends than did the E0 formulation choices. These methodological choices and specific climate model selection, also have a large influence on the estimation of trends in standardized drought indices used for drought assessment operationally. We find that standardization tends to amplify divergences between the E0 trends calculated using different E0 formulations, because standardization is sensitive to both the climatology and amplitude of interannual variability of E0. For different methodological choices and GCM output considered in estimating E0, we examine potential sources of uncertainty in 21st century trends in the Standardized Precipitation Evapotranspiration Index (SPEI) and Evaporative Demand Drought Index (EDDI) over selected regions of the CONUS to demonstrate the practical implications of these methodological choices for the quantification of drought risk under climate change. PMID:28301603

Long-term trends in climate and hydrology in an agricultural, headwater watershed of central Pennsylvania, USA

USDA-ARS?s Scientific Manuscript database

Strategies to mitigate agricultural runoff must consider long-term changes in climate. We investigated temperature, precipitation and runoff trends over roughly four decades of monitoring an agricultural watershed in east central Pennsylvania (1968-2012). Temperature data confirmed significant expan...

Relative Sea Level Trends Along the Coast of the Bay of Bengal

NASA Astrophysics Data System (ADS)

Becker, M.; Calmant, S.; Papa, F.; Delebecque, C.; Islam, A. S.; Shum, C. K.

2016-12-01

In the coastal belt of the Bay of Bengal, the sea level rise is one of a major threat, linked to climate change, which drastically affects the livelihoods of millions of people. A comprehensive understanding of sea level trends and its variability in this region is therefore crucial and should help to anticipate the impacts of climate change and implement adaptation strategies. This region is bordered mostly by Bangladesh, India, Malaysia, Myanmar, and Thailand. Here, we revisit the sea level changes in the Bay of Bengal region from tide gauges and satellite altimetry over the period 1993-2014. The 23 monthly mean tide gauge records, used in this study, are retrieved from PSMSL (15 records) and supplemented with Bangladeshi observations (8 records). We show that, over the satellite altimetry era, the sea level interannual/decadal variability is mainly due to ocean thermal expansion variability driven by IOD/ENSO events and their low frequency modulation. We focus on relative sea level rise at major coastal cities and try to separate the climatic signal (long term trend plus interannual/decadal variability) from local effects, in particular vertical land movements. Results from GPS are analysed where available. When no such data exist, vertical land movements are deduced from the combined use of tide gauge and altimetry data. While the analysis is performed over the whole region, a particular attention is given to the low-lyingBangladesh's coastal area.

Response of ice cover on shallow lakes of the North Slope of Alaska to contemporary climate conditions (1950-2011): radar remote-sensing and numerical modeling data analysis

NASA Astrophysics Data System (ADS)

Surdu, C. M.; Duguay, C. R.; Brown, L. C.; Fernández Prieto, D.

2014-01-01

Air temperature and winter precipitation changes over the last five decades have impacted the timing, duration, and thickness of the ice cover on Arctic lakes as shown by recent studies. In the case of shallow tundra lakes, many of which are less than 3 m deep, warmer climate conditions could result in thinner ice covers and consequently, in a smaller fraction of lakes freezing to their bed in winter. However, these changes have not yet been comprehensively documented. The analysis of a 20 yr time series of European remote sensing satellite ERS-1/2 synthetic aperture radar (SAR) data and a numerical lake ice model were employed to determine the response of ice cover (thickness, freezing to the bed, and phenology) on shallow lakes of the North Slope of Alaska (NSA) to climate conditions over the last six decades. Given the large area covered by these lakes, changes in the regional climate and weather are related to regime shifts in the ice cover of the lakes. Analysis of available SAR data from 1991 to 2011, from a sub-region of the NSA near Barrow, shows a reduction in the fraction of lakes that freeze to the bed in late winter. This finding is in good agreement with the decrease in ice thickness simulated with the Canadian Lake Ice Model (CLIMo), a lower fraction of lakes frozen to the bed corresponding to a thinner ice cover. Observed changes of the ice cover show a trend toward increasing floating ice fractions from 1991 to 2011, with the greatest change occurring in April, when the grounded ice fraction declined by 22% (α = 0.01). Model results indicate a trend toward thinner ice covers by 18-22 cm (no-snow and 53% snow depth scenarios, α = 0.01) during the 1991-2011 period and by 21-38 cm (α = 0.001) from 1950 to 2011. The longer trend analysis (1950-2011) also shows a decrease in the ice cover duration by ~24 days consequent to later freeze-up dates by 5.9 days (α = 0.1) and earlier break-up dates by 17.7-18.6 days (α = 0.001).

A remote-sensing/GIS application for analysis of sea surface temperature off the western coast of North America

EPA Science Inventory

Recent work reports a warming trend in Pacific Ocean temperatures over the last 50 years. Coastal regions along western North America are particularly sensitive to climatic change, an important indicator of which is sea surface temperature (SST). In situ SST measurements (typica...

Effects of Climate Change on Salmonella Infections

PubMed Central

Akil, Luma; Reddy, Remata S.

2014-01-01

Abstract Background: Climate change and global warming have been reported to increase spread of foodborne pathogens. To understand these effects on Salmonella infections, modeling approaches such as regression analysis and neural network (NN) were used. Methods: Monthly data for Salmonella outbreaks in Mississippi (MS), Tennessee (TN), and Alabama (AL) were analyzed from 2002 to 2011 using analysis of variance and time series analysis. Meteorological data were collected and the correlation with salmonellosis was examined using regression analysis and NN. Results: A seasonal trend in Salmonella infections was observed (p<0.001). Strong positive correlation was found between high temperature and Salmonella infections in MS and for the combined states (MS, TN, AL) models (R2=0.554; R2=0.415, respectively). NN models showed a strong effect of rise in temperature on the Salmonella outbreaks. In this study, an increase of 1°F was shown to result in four cases increase of Salmonella in MS. However, no correlation between monthly average precipitation rate and Salmonella infections was observed. Conclusion: There is consistent evidence that gastrointestinal infection with bacterial pathogens is positively correlated with ambient temperature, as warmer temperatures enable more rapid replication. Warming trends in the United States and specifically in the southern states may increase rates of Salmonella infections. PMID:25496072

Attribution of the Regional Patterns of North American Climate Trends

NASA Astrophysics Data System (ADS)

Hoerling, M.; Kumar, A.; Karoly, D.; Rind, D.; Hegerl, G.; Eischeid, J.

2007-12-01

North American trends in surface temperature and precipitation during 1951-2006 exhibit large spatial and seasonal variations. We seek to explain these by synthesizing new information based on existing model simulations of climate and its forcing, and based on modern reanalyses that describe past and current conditions within the free atmosphere. The presentation focuses on current capabilities to explain the spatial variations and seasonal differences in North American climate trends. It will address whether various heterogeneities in space and time can be accounted for by the climate system's sensitivity to time evolving anthropogenic forcing, and examines the influences of non-anthropogenic processes. New findings are presented that indicate anthropogenic forcing alone was unlikely the cause for key regional and seasonal patterns of change, including the absence of summertime warming over the Great Plains of the United States, and the absence of warming during both winter and summer over the southern United States. Key regional features are instead attributed to trends in the principal patterns of atmospheric flow that affect North American climate. It is demonstrated that observed variations in global sea surface temperatures have significantly influenced these patterns of atmospheric flow.

Analyses of historical and projected climates to support climate adaptation in the northern Rocky Mountains: Chapter 4

USGS Publications Warehouse

Gross, John E.; Tercek, Michael; Guay, Kevin; Chang, Tony; Talbert, Marian; Rodman, Ann; Thoma, David; Jantz, Patrick; Morisette, Jeffrey T.

2016-01-01

Most of the western United States is experiencing the effects of rapid and directional climate change (Garfin et al. 2013). These effects, along with forecasts of profound changes in the future, provide strong motivation for resource managers to learn about and prepare for future changes. Climate adaptation plans are based on an understanding of historic climate variation and their effects on ecosystems and on forecasts of future climate trends. Frameworks for climate adaptation thus universally identify the importance of a summary of historical, current, and projected climates (Glick, Stein, and Edelson 2011; Cross et al. 2013; Stein et al. 2014). Trends in physical climate variables are usually the basis for evaluating the exposure component in vulnerability assessments. Thus, this chapter focuses on step 2 of the Climate-Smart Conservation framework (chap. 2): vulnerability assessment. We present analyses of historical and current observations of temperature, precipitation, and other key climate measurements to provide context and a baseline for interpreting the ecological impacts of projected climate changes.

Zoning vulnerability of climate change in variation of amount and trend of precipitation - Case Study: Great Khorasan province

NASA Astrophysics Data System (ADS)

Modiri, Ehsan; Modiri, Sadegh

2015-04-01

Climatic hazards have complex nature that many of them are beyond human control. Earth's climate is constantly fluctuating and trying to balance itself. More than 75% of Iran has arid and semi-arid climate thus assessment of climate change induced threats and vulnerabilities is essential. In order to investigate the reason for the changes in amount and trend of precipitation parameter, 17 synoptic stations have been selected in the interval of the establishment time of the station until 2013. These stations are located in three regions: Northern, Razavi and Southern Khorasan. For quality control of data in Monthly, quarterly and annual total precipitation of data were tested and checked by run test. Then probable trends in each of the areas was assessed by Kendall-tau test. Total annual precipitation of each station is the important factor that increase the sensitivity of vulnerability in the area with low rainfall. Annual amount of precipitation moving from north to south has been declining, though in different fields that they have different geomorphologic characteristics controversies occur. But clearly can be observed average of precipitation decline with decreasing latitude. There were positive trends in the annual precipitation in 6 stations, negative trends in 10 stations, as well as one station, has no trend. The remarkable notice is that all stations have a positive trend were in the northern region in the case study. These stations had been in ranging from none to Moderate classification of threats and vulnerability. After the initialization parameters to classify levels of risks and vulnerability, the two measures of mean annual precipitation and the trends of this fluctuation were combined together. This classification was created in five level for stations. Accordingly Golmakan, Ghochan, Torbate heydarieh, Bojnord and Mashhad were in none threat level. Khoor of Birjand and Boshruyeh have had complete stage of the threat level and had the greatest meteorological perspective risk. Finally, after determining the degree of threats, meteorological vulnerability zoning map was produced by kriging interpolation method and utilizing geographic information systems (GIS). It showed most studied areas were in complete level of investigation. Keywords: Vulnerability, Climate threats, GIS, Zoning, Precipitation, Crisis management.

Use of a Weather Generator for analysis of projections of future daily temperature and its validation with climate change indices

NASA Astrophysics Data System (ADS)

Di Piazza, A.; Cordano, E.; Eccel, E.

2012-04-01

The issue of climate change detection is considered a major challenge. In particular, high temporal resolution climate change scenarios are required in the evaluation of the effects of climate change on agricultural management (crop suitability, yields, risk assessment, etc.) energy production and water management. In this work, a "Weather Generator" technique was used for downscaling climate change scenarios for temperature. An R package (RMAWGEN, Cordano and Eccel, 2011 - available on http://cran.r-project.org) was developed aiming to generate synthetic daily weather conditions by using the theory of vectorial auto-regressive models (VAR). The VAR model was chosen for its ability in maintaining the temporal and spatial correlations among variables. In particular, observed time series of daily maximum and minimum temperature are transformed into "new" normally-distributed variable time series which are used to calibrate the parameters of a VAR model by using ordinary least square methods. Therefore the implemented algorithm, applied to monthly mean climatic values downscaled by Global Climate Model predictions, can generate several stochastic daily scenarios where the statistical consistency among series is saved. Further details are present in RMAWGEN documentation. An application is presented here by using a dataset with daily temperature time series recorded in 41 different sites of Trentino region for the period 1958-2010. Temperature time series were pre-processed to fill missing values (by a site-specific calibrated Inverse Distance Weighting algorithm, corrected with elevation) and to remove inhomogeneities. Several climatic indices were taken into account, useful for several impact assessment applications, and their time trends within the time series were analyzed. The indices go from the more classical ones, as annual mean temperatures, seasonal mean temperatures and their anomalies (from the reference period 1961-1990) to the climate change indices selected from the list recommended by the World Meteorological Organization Commission for Climatology (WMO-CCL) and the Research Programme on Climate Variability and Predictability (CLIVAR) project's Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). Each index was applied to both observed (and processed) data and to synthetic time series produced by the Weather Generator, over the thirty year reference period 1981-2010, in order to validate the procedure. Climate projections were statistically downscaled for a selection of sites for the two 30-year periods 2021-2050 and 2071-2099 of the European project "Ensembles" multi-model output (scenario A1B). The use of several climatic indices strengthens the trend analysis of both the generated synthetic series and future climate projections.

Climate-driven trends in stem wood density of tree species in the eastern United States: Ecological impact and implications for national forest carbon assessments

Treesearch

Brian J. Clough; Miranda T. Curzon; Grant M. Domke; Matthew B. Russell; Christopher W. Woodall

2017-01-01

Aim: For trees, wood density is linked to competing energetic demands and therefore reflects responses to the environment. Climatic trends in wood density are recognized, yet their contribution to regional biogeographical patterns or impact on forest biomass stocks is not understood. This study has the following two objectives: (O1) to characterize wood density–climate...

Multidecadal Changes and Interannual Variation in Springtime Phenology of North American Temperate and Boreal Deciduous Forests

NASA Astrophysics Data System (ADS)

Melaas, Eli K.; Sulla-Menashe, Damien; Friedl, Mark A.

2018-03-01

The timing of leaf emergence is an important diagnostic of climate change impacts on ecosystems. Here we present the first continental-scale analysis of multidecadal changes in the timing of spring onset across North American temperate and boreal forests based on Landsat imagery. Our results show that leaf emergence in Eastern Temperate Forests has consistently trended earlier, with a median change of about 1 week over the 30 year study period. Changes in leaf emergence dates in boreal forests were more heterogeneous, with some sites showing trends toward later dates. Interannual variability in leaf emergence dates was strongly sensitive to springtime accumulated growing degree days across all sites, and geographic patterns of changes in onset dates were highly correlated with changes in regional springtime temperatures. These results provide a refined characterization of recent changes in springtime forest phenology and improve understanding regarding the sensitivity of North American forests to climate change.

Understanding the relationship between the variability in agrometeorological indices and adaptation practices across the Canadian Prairies

NASA Astrophysics Data System (ADS)

Chipanshi, A.; Qi, D.; Zhang, Y.; Cherneski, P.

2017-12-01

In an attempt to understand how agriculture will adapt to the changing and variable climate, crop based agrometeorological indices including the Effective Growing Degree Days (EGDDs), Growing Season Length (GSL), Heat waves, Water Demand (Precipitation - Evapotranspiration) and the Standardized Precipitation Evapotranspiration Index (SPEI) were analyzed in terms of frequency, duration and trend over a 63-year timeframe (1950 to 2012) from the Canadian Prairies and related to crop production. The heat based indices (EGDD, GSL and Heat waves) increased over the analysis period due to an upward increase in the observed mean temperature. The change was most noticeable in the northern portion of the study area where agriculture is limited by insufficient heat units under the present climate. Heat waves became more frequent in the southern parts of the study area (there were more days above the 30oC threshold). Water availability as assessed from water demand (P-PE) and SPEI trended downward especially in Alberta and Saskatchewan. In spite of the increased severity and frequency in water deficits, there was a noticeable reduction in the variability of crop yield over time. This was attributed to the increased adaptive capacity that has been gained through the use of improved seed hybrids, fertilizer, the use of fungicides and adoption of best management practices such as zero till and direct seeding. After crop yields were de-trended to remove effects of technology, the cumulative precipitation during the growing season explained the majority of the variance in crop yield. This initial analysis has set the stage for analyzing the characteristics of agrometeorological indices under climate change scenarios and how accumulated precipitation during the growing season will affect crop yield and production.

Come rain or shine: Multi-model Projections of Climate Hazards affecting Transportation in the South Central United States

NASA Astrophysics Data System (ADS)

Mullens, E.; Mcpherson, R. A.

2016-12-01

This work develops detailed trends in climate hazards affecting the Department of Transportation's Region 6, in the South Central U.S. Firstly, a survey was developed to gather information regarding weather and climate hazards in the region from the transportation community, identifying key phenomena and thresholds to evaluate. Statistically downscaled datasets were obtained from the Multivariate Adaptive Constructed Analogues (MACA) project, and the Asynchronous Regional Regression Model (ARRM), for a total of 21 model projections, two coupled model intercomparisons (CMIP3, and CMIP5), and four emissions pathways (A1Fi, B1, RCP8.5, RCP4.5). Specific hazards investigated include winter weather, freeze-thaw cycles, hot and cold extremes, and heavy precipitation. Projections for each of these variables were calculated for the region, utilizing spatial mapping, and time series analysis at the climate division level. The results indicate that cold-season phenomena such as winter weather, freeze-thaw, and cold extremes, decrease in intensity and frequency, particularly with the higher emissions pathways. Nonetheless, specific model and downscaling method yields variability in magnitudes, with the most notable decreasing trends late in the 21st century. Hot days show a pronounced increase, particularly with greater emissions, producing annual mean 100oF day frequencies by late 21st century analogous to the 2011 heatwave over the central Southern Plains. Heavy precipitation, evidenced by return period estimates and counts-over-thresholds, also show notable increasing trends, particularly between the recent past through mid-21st Century. Conversely, mean precipitation does not show significant trends and is regionally variable. Precipitation hazards (e.g., winter weather, extremes) diverge between downscaling methods and their associated model samples much more substantially than temperature, suggesting that the choice of global model and downscaled data is particularly important when considering region-specific impacts for precipitation. These results are intended to inform region transportation professionals of the susceptibility of the area to climate extremes, and to be a resource for assessing and incorporating changing risk probabilities into their planning processes.

Quantifying alluvial fan sensitivity to climate in Death Valley, California, from field observations and numerical models

NASA Astrophysics Data System (ADS)

Brooke, Sam; Whittaker, Alexander; Armitage, John; D'Arcy, Mitch; Watkins, Stephen

2017-04-01

A quantitative understanding of landscape sensitivity to climate change remains a key challenge in the Earth Sciences. The stream-flow deposits of coupled catchment-fan systems offer one way to decode past changes in external boundary conditions as they comprise simple, closed systems that can be represented effectively by numerical models. Here we combine the collection and analysis of grain size data on well-dated alluvial fan surfaces in Death Valley, USA, with numerical modelling to address the extent to which sediment routing systems record high-frequency, high-magnitude climate change. We compile a new database of Holocene and Late-Pleistocene grain size trends from 11 alluvial fans in Death Valley, capturing high-resolution grain size data ranging from the Recent to 100 kyr in age. We hypothesise the observed changes in average surface grain size and fining rate over time are a record of landscape response to glacial-interglacial climatic forcing. With this data we are in a unique position to test the predictions of landscape evolution models and evaluate the extent to which climate change has influenced the volume and calibre of sediment deposited on alluvial fans. To gain insight into our field data and study area, we employ an appropriately-scaled catchment-fan model that calculates an eroded volumetric sediment budget to be deposited in a subsiding basin according to mass balance where grain size trends are predicted by a self-similarity fining model. We use the model to compare predicted trends in alluvial fan stratigraphy as a function of boundary condition change for a range of model parameters and input grain size distributions. Subsequently, we perturb our model with a plausible glacial-interglacial magnitude precipitation change to estimate the requisite sediment flux needed to generate observed field grain size trends in Death Valley. Modelled fluxes are then compared with independent measurements of sediment supply over time. Our results constitute one of the first attempts to combine the detailed collection of alluvial fan grain size data in time and space with coupled catchment-fan models, affording us the means to evaluate how well field and model data can be reconciled for simple sediment routing systems.

Climatic irregular staircases: generalized acceleration of global warming

PubMed Central

De Saedeleer, Bernard

2016-01-01

Global warming rates mentioned in the literature are often restricted to a couple of arbitrary periods of time, or of isolated values of the starting year, lacking a global view. In this study, we perform on the contrary an exhaustive parametric analysis of the NASA GISS LOTI data, and also of the HadCRUT4 data. The starting year systematically varies between 1880 and 2002, and the averaging period from 5 to 30 yr — not only decades; the ending year also varies . In this way, we uncover a whole unexplored space of values for the global warming rate, and access the full picture. Additionally, stairstep averaging and linear least squares fitting to determine climatic trends have been sofar exclusive. We propose here an original hybrid method which combines both approaches in order to derive a new type of climatic trend. We find that there is an overall acceleration of the global warming whatever the value of the averaging period, and that 99.9% of the 3029 Earth’s climatic irregular staircases are rising. Graphical evidence is also given that choosing an El Niño year as starting year gives lower global warming rates — except if there is a volcanic cooling in parallel. Our rates agree and generalize several results mentioned in the literature. PMID:26813867

The impact of climate change on river discharges in Eastern Romania

NASA Astrophysics Data System (ADS)

Croitoru, Adina-Eliza; Minea, Ionut

2014-05-01

Climate changes imply many changes in different socioeconomic and environmental fields. Among the most important impacts are changes in water resources. Long- and mid-term river discharge flow analysis is essential for the effective management of water resources. In this work, the changes in two climatic parameters (temperature and precipitation) and river discharges and the connections between precipitation and river discharges were investigated. Seasonal and annual climatic and hydrological data collected at six weather stations and 17 hydrological stations were employed. The data sets cover 57 years (1950-2006). The modified Mann-Kendall test was used to calculate trends, and the Bravais-Pearson correlation index was chosen to detect the connections between precipitation and river discharge data series. The main findings are as follows: A general increase was identified in all the three parameters. The air temperature data series showed the highest frequency of statistically significant slopes, mainly in annual and spring series. All data series, except the series for winter, showed an increase in precipitation; in winter, a significant decrease in precipitation was observed at most of the stations. The increase in precipitation is reflected in the upward trends of the river discharge flows, as verified by the good Bravais-Pearson correlations, mainly for annual, summer, and autumn series

Climatic irregular staircases: generalized acceleration of global warming.

PubMed

De Saedeleer, Bernard

2016-01-27

Global warming rates mentioned in the literature are often restricted to a couple of arbitrary periods of time, or of isolated values of the starting year, lacking a global view. In this study, we perform on the contrary an exhaustive parametric analysis of the NASA GISS LOTI data, and also of the HadCRUT4 data. The starting year systematically varies between 1880 and 2002, and the averaging period from 5 to 30 yr - not only decades; the ending year also varies . In this way, we uncover a whole unexplored space of values for the global warming rate, and access the full picture. Additionally, stairstep averaging and linear least squares fitting to determine climatic trends have been sofar exclusive. We propose here an original hybrid method which combines both approaches in order to derive a new type of climatic trend. We find that there is an overall acceleration of the global warming whatever the value of the averaging period, and that 99.9% of the 3029 Earth's climatic irregular staircases are rising. Graphical evidence is also given that choosing an El Niño year as starting year gives lower global warming rates - except if there is a volcanic cooling in parallel. Our rates agree and generalize several results mentioned in the literature.

The local and global climate forcings induced inhomogeneity of Indian rainfall.

PubMed

Nair, P J; Chakraborty, A; Varikoden, H; Francis, P A; Kuttippurath, J

2018-04-16

India is home for more than a billion people and its economy is largely based on agrarian society. Therefore, rainfall received not only decides its livelihood, but also influences its water security and economy. This situation warrants continuous surveillance and analysis of Indian rainfall. These kinds of studies would also help forecasters to better tune their models for accurate weather prediction. Here, we introduce a new method for estimating variability and trends in rainfall over different climate regions of India. The method based on multiple linear regression helps to assess contributions of different remote and local climate forcings to seasonal and regional inhomogeneity in rainfall. We show that the Indian Summer Monsoon Rainfall (ISMR) variability is governed by Eastern and Central Pacific El Niño Southern Oscillation, equatorial zonal winds, Atlantic zonal mode and surface temperatures of the Arabian Sea and Bay of Bengal, and the North East Monsoon Rainfall variability is controlled by the sea surface temperature of the North Atlantic and extratropial oceans. Also, our analyses reveal significant positive trends (0.43 mm/day/dec) in the North West for ISMR in the 1979-2017 period. This study cautions against the significant changes in Indian rainfall in a perspective of global climate change.

How well are the climate indices related to the GRACE-observed total water storage changes in China?

NASA Astrophysics Data System (ADS)

Devaraju, B.; Vishwakarma, B.; Sneeuw, N. J.

2017-12-01

The fresh water availability over land masses is changing rapidly under the influence of climate change and human intervention. In order to manage our water resources and plan for a better future, we need to demarcate the role of climate change. The total water storage change in a region can be obtained from the GRACE satellite mission. On the other hand, many climate change indicators, for example ENSO, are derived from sea surface temperature. In this contribution we investigate the relationship between the total water storage change over China with the climate indices using statistical time-series decomposition techniques, such as Seasonal and Trend decomposition using Loess (STL), Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA). The anomalies in climate variables, such as sea surface temperature, are responsible for anomalous precipitation and thus an anomalous total water storage change over land. Therefore, it is imperative that we use a GRACE product that can capture anomalous water storage changes with unprecedented accuracy. Since filtering decreases the sensitivity of GRACE products substantially, we use the data-driven method of deviation for recovering the signal lost due to filtering. To this end, we are able to obtain the spatial fingerprint of individual climate index on total water storage change observed over China.

The influence of internal climate variability on heatwave frequency trends

NASA Astrophysics Data System (ADS)

E Perkins-Kirkpatrick, S.; Fischer, E. M.; Angélil, O.; Gibson, P. B.

2017-04-01

Understanding what drives changes in heatwaves is imperative for all systems impacted by extreme heat. We examine short- (13 yr) and long-term (56 yr) heatwave frequency trends in a 21-member ensemble of a global climate model (Community Earth System Model; CESM), where each member is driven by identical anthropogenic forcings. To estimate changes dominantly due to internal climate variability, trends were calculated in the corresponding pre-industrial control run. We find that short-term trends in heatwave frequency are not robust indicators of long-term change. Additionally, we find that a lack of a long-term trend is possible, although improbable, under historical anthropogenic forcing over many regions. All long-term trends become unprecedented against internal variability when commencing in 2015 or later, and corresponding short-term trends by 2030, while the length of trend required to represent regional long-term changes is dependent on a given realization. Lastly, within ten years of a short-term decline, 95% of regional heatwave frequency trends have reverted to increases. This suggests that observed short-term changes of decreasing heatwave frequency could recover to increasing trends within the next decade. The results of this study are specific to CESM and the ‘business as usual’ scenario, and may differ under other representations of internal variability, or be less striking when a scenario with lower anthropogenic forcing is employed.

Climate-induced warming of lakes can be either amplified or suppressed by trends in water clarity

USGS Publications Warehouse

Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Hansen, Gretchen J. A.

2016-01-01

Climate change is rapidly warming aquatic ecosystems including lakes and reservoirs. However, variability in lake characteristics can modulate how lakes respond to climate. Water clarity is especially important both because it influences the depth range over which heat is absorbed, and because it is changing in many lakes. Here, we show that simulated long-term water clarity trends influence how both surface and bottom water temperatures of lakes and reservoirs respond to climate change. Clarity changes can either amplify or suppress climate-induced warming, depending on lake depth and the direction of clarity change. Using a process-based model to simulate 1894 north temperate lakes from 1979 to 2012, we show that a scenario of decreasing clarity at a conservative yet widely observed rate of 0.92% yr−1 warmed surface waters and cooled bottom waters at rates comparable in magnitude to climate-induced warming. For lakes deeper than 6.5 m, decreasing clarity was sufficient to fully offset the effects of climate-induced warming on median whole-lake mean temperatures. Conversely, a scenario increasing clarity at the same rate cooled surface waters and warmed bottom waters relative to baseline warming rates. Furthermore, in 43% of lakes, increasing clarity more than doubled baseline bottom temperature warming rates. Long-term empirical observations of water temperature in lakes with and without clarity trends support these simulation results. Together, these results demonstrate that water clarity trends may be as important as rising air temperatures in determining how waterbodies respond to climate change.

A comparison of metrics for assessing state-of-the-art climate models and implications for probabilistic projections of climate change

NASA Astrophysics Data System (ADS)

Ring, Christoph; Pollinger, Felix; Kaspar-Ott, Irena; Hertig, Elke; Jacobeit, Jucundus; Paeth, Heiko

2018-03-01

A major task of climate science are reliable projections of climate change for the future. To enable more solid statements and to decrease the range of uncertainty, global general circulation models and regional climate models are evaluated based on a 2 × 2 contingency table approach to generate model weights. These weights are compared among different methodologies and their impact on probabilistic projections of temperature and precipitation changes is investigated. Simulated seasonal precipitation and temperature for both 50-year trends and climatological means are assessed at two spatial scales: in seven study regions around the globe and in eight sub-regions of the Mediterranean area. Overall, 24 models of phase 3 and 38 models of phase 5 of the Coupled Model Intercomparison Project altogether 159 transient simulations of precipitation and 119 of temperature from four emissions scenarios are evaluated against the ERA-20C reanalysis over the 20th century. The results show high conformity with previous model evaluation studies. The metrics reveal that mean of precipitation and both temperature mean and trend agree well with the reference dataset and indicate improvement for the more recent ensemble mean, especially for temperature. The method is highly transferrable to a variety of further applications in climate science. Overall, there are regional differences of simulation quality, however, these are less pronounced than those between the results for 50-year mean and trend. The trend results are suitable for assigning weighting factors to climate models. Yet, the implications for probabilistic climate projections is strictly dependent on the region and season.

Comparison of future and base precipitation anomalies by SimCLIM statistical projection through ensemble approach in Pakistan

NASA Astrophysics Data System (ADS)

Amin, Asad; Nasim, Wajid; Mubeen, Muhammad; Kazmi, Dildar Hussain; Lin, Zhaohui; Wahid, Abdul; Sultana, Syeda Refat; Gibbs, Jim; Fahad, Shah

2017-09-01

Unpredictable precipitation trends have largely influenced by climate change which prolonged droughts or floods in South Asia. Statistical analysis of monthly, seasonal, and annual precipitation trend carried out for different temporal (1996-2015 and 2041-2060) and spatial scale (39 meteorological stations) in Pakistan. Statistical downscaling model (SimCLIM) was used for future precipitation projection (2041-2060) and analyzed by statistical approach. Ensemble approach combined with representative concentration pathways (RCPs) at medium level used for future projections. The magnitude and slop of trends were derived by applying Mann-Kendal and Sen's slop statistical approaches. Geo-statistical application used to generate precipitation trend maps. Comparison of base and projected precipitation by statistical analysis represented by maps and graphical visualization which facilitate to detect trends. Results of this study projects that precipitation trend was increasing more than 70% of weather stations for February, March, April, August, and September represented as base years. Precipitation trend was decreased in February to April but increase in July to October in projected years. Highest decreasing trend was reported in January for base years which was also decreased in projected years. Greater variation in precipitation trends for projected and base years was reported in February to April. Variations in projected precipitation trend for Punjab and Baluchistan highly accredited in March and April. Seasonal analysis shows large variation in winter, which shows increasing trend for more than 30% of weather stations and this increased trend approaches 40% for projected precipitation. High risk was reported in base year pre-monsoon season where 90% of weather station shows increasing trend but in projected years this trend decreased up to 33%. Finally, the annual precipitation trend has increased for more than 90% of meteorological stations in base (1996-2015) which has decreased for projected year (2041-2060) up to 76%. These result revealed that overall precipitation trend is decreasing in future year which may prolonged the drought in 14% of weather stations under study.

Climate-driven longitudinal trends in pasture-borne helminth infections of dairy cattle.

PubMed

Charlier, Johannes; Ghebretinsae, Aklilu H; Levecke, Bruno; Ducheyne, Els; Claerebout, Edwin; Vercruysse, Jozef

2016-12-01

Helminth parasites of grazing ruminants are highly prevalent globally and impact negatively on animal productivity and food security. There is a growing concern that climate change increases helminth disease frequency and intensity. In Europe, these concerns stem from case reports and theoretical life cycle models assessing the effects of climate change scenarios on helminth epidemiology. We believe this study is the first to investigate climate-driven trends in helminth infections of cattle on a cohort of randomly selected farms. One thousand, six hundred and eighty dairy farms were monitored over an 8year period for the two major helminth infections in temperate climate regions and climate-driven trends were investigated by multivariable linear mixed models. The general levels of exposure to Fasciola hepatica decreased over the study period while those to Ostertagia ostertagi increased, and this could at least be partially explained by meteorological factors (i.e. the number of rainy (precipitation >1mm) and warm days (average daily temperature >10°C) in a year). The longitudinal trends varied according to the altitude and the agricultural region of the farm. This study shows that longitudinal epidemiological data from sentinel farms combined with meteorological datasets can significantly contribute to understanding the effects of climate on infectious disease dynamics. When local environmental conditions are taken into account, the effects of climate change on disease dynamics can also be understood at more local scales. We recommend setting up a longitudinal sampling strategy across Europe in order to monitor climate-driven changes in helminth disease risk to inform adaptation strategies to promote animal health and productivity. Copyright © 2016 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Seasonality of change: Summer warming rates do not fully represent effects of climate change on lake temperatures

USGS Publications Warehouse

Winslow, Luke; Read, Jordan S.; Hansen, Gretchen J. A.; Rose, Kevin C.; Robertson, Dale M.

2017-01-01

Responses in lake temperatures to climate warming have primarily been characterized using seasonal metrics of surface-water temperatures such as summertime or stratified period average temperatures. However, climate warming may not affect water temperatures equally across seasons or depths. We analyzed a long-term dataset (1981–2015) of biweekly water temperature data in six temperate lakes in Wisconsin, U.S.A. to understand (1) variability in monthly rates of surface- and deep-water warming, (2) how those rates compared to summertime average trends, and (3) if monthly heterogeneity in water temperature trends can be predicted by heterogeneity in air temperature trends. Monthly surface-water temperature warming rates varied across the open-water season, ranging from 0.013 in August to 0.073°C yr−1 in September (standard deviation [SD]: 0.025°C yr−1). Deep-water trends during summer varied less among months (SD: 0.006°C yr−1), but varied broadly among lakes (–0.056°C yr−1 to 0.035°C yr−1, SD: 0.034°C yr−1). Trends in monthly surface-water temperatures were well correlated with air temperature trends, suggesting monthly air temperature trends, for which data exist at broad scales, may be a proxy for seasonal patterns in surface-water temperature trends during the open water season in lakes similar to those studied here. Seasonally variable warming has broad implications for how ecological processes respond to climate change, because phenological events such as fish spawning and phytoplankton succession respond to specific, seasonal temperature cues.

Observing climate change trends in ocean biogeochemistry: when and where.

PubMed

Henson, Stephanie A; Beaulieu, Claudie; Lampitt, Richard

2016-04-01

Understanding the influence of anthropogenic forcing on the marine biosphere is a high priority. Climate change-driven trends need to be accurately assessed and detected in a timely manner. As part of the effort towards detection of long-term trends, a network of ocean observatories and time series stations provide high quality data for a number of key parameters, such as pH, oxygen concentration or primary production (PP). Here, we use an ensemble of global coupled climate models to assess the temporal and spatial scales over which observations of eight biogeochemically relevant variables must be made to robustly detect a long-term trend. We find that, as a global average, continuous time series are required for between 14 (pH) and 32 (PP) years to distinguish a climate change trend from natural variability. Regional differences are extensive, with low latitudes and the Arctic generally needing shorter time series (<~30 years) to detect trends than other areas. In addition, we quantify the 'footprint' of existing and planned time series stations, that is the area over which a station is representative of a broader region. Footprints are generally largest for pH and sea surface temperature, but nevertheless the existing network of observatories only represents 9-15% of the global ocean surface. Our results present a quantitative framework for assessing the adequacy of current and future ocean observing networks for detection and monitoring of climate change-driven responses in the marine ecosystem. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Rainfall Patterns Analysis over Ampangan Muda, Kedah from 2007 - 2016

NASA Astrophysics Data System (ADS)

Chooi Tan, Kok

2018-04-01

The scientific knowledge about climate change and climate variability over Malaysia pertaining to the extreme water-related disaster such as drought and flood. A deficit or increment in precipitation occurred over the past century becomes a useful tool to understand the climate change in Malaysia. The purpose of this work is to examine the rainfall patterns over Ampangan Muda, Kedah. Daily rainfall data is acquired from Malaysian Meteorological Department to analyse the temporal and trends of the monthly and annual rainfall over the study area from 2007 to 2016. The obtained results show that the temporal and patterns of the rainfall over Ampangan Muda, Kedah is largely affected by the regional phenomena such as monsoon, El Niño Southern Oscillation (ENSO), and the Madden-Julian Oscillation. In addition, backward trajectories analysis is also used to identify the patterns for long-range of synoptic circulation over the region.

Variability and trends of local/regional scale surface climate in northern Africa during the twentieth century

NASA Astrophysics Data System (ADS)

Djomou, Zéphirin Yepdo; Monkam, David; Woafo, Paul

2014-08-01

Four regions are detected in northern Africa (20° W-40° E, 0-30° N) by applying the cluster analysis method on the annual rainfall anomalies of the period 1901-2000. The first region (R1), an arid land, covers essentially the north of 17.75° N from west to east of the study zone. The second region (R2), a semiarid land with a Sahelian climate, less warm than the dry climate of R1, is centred on Chad, with almost regular extension to the west towards Mauritania, and to the east, including the north of the Central African Republic and the Sudan. The region 3 (R3), a wet land, is centred on the Ivory Coast and covers totally Liberia, the south part of Ghana, Togo, Benin and the southwest of Nigeria. The fourth region (R4), corresponding to the wet equatorial forest, covers a part of Senegal, the Central Africa, the south of Sudan and a part of Ethiopia. An analysis of observed temperature and precipitation variability and trends throughout the twentieth century over these regions is presented. Summer, winter and annual data are examined using a range of variability measures. Statistically, significant warming trends are found over the majority of regions. The trends have a magnitude of up to 1.5 K per century. Only a few precipitation trends are statistically significant. Regional temperature and precipitation show pronounced variability at scales from interannual to multi-decadal. The interannual variability shows significant variations and trends throughout the century, the latter being mostly negative for precipitation and both positive and negative for temperature. Temperature and precipitation anomalies show a chaotic-type behaviour in which the regional conditions oscillate around the long-term mean trend and occasionally fall into long-lasting (up to 10 years or more) anomaly regimes. A generally modest temporal correlation is found between anomalies of different regions and between temperature and precipitation anomalies for the same region. This correlation is mostly positive for temperature in cases of adjacent regions. Several cases of negative interregional precipitation anomaly correlation are found. The El Niño Southern Oscillation significantly affects the anomaly variability patterns over a number of regions, mainly regions 3 (R3) and 4 (R4), while the North Atlantic Oscillation significantly affects the variability over arid and semiarid regions, R1 and R2.

Choosing and using climate-change scenarios for ecological-impact assessments and conservation decisions.

PubMed

Snover, Amy K; Mantua, Nathan J; Littell, Jeremy S; Alexander, Michael A; McClure, Michelle M; Nye, Janet

2013-12-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment. Selección y Uso de Escenarios de Cambio Climático para Estudios de Impacto Ecológico y Decisiones de Conservación. © 2013 Society for Conservation Biology.

Development of a Water Clarity Index for the Southeastern U.S. As a Climate Indicator

NASA Astrophysics Data System (ADS)

Sheridan, S. C.; Hu, C.; Lee, C. C.; Barnes, B.; Pirhalla, D.; Ransi, V.; Shein, K. A.

2014-12-01

A common index of water quality is water clarity, which can be estimated by measuring the diffuse attenuation coefficient for downwelling irradiance (Kd). Kd estimates the availability of light to marine organisms at various depths. Marine habitats, including such species as coral and seagrass, can be negatively affected by extreme episodes of sediment suspension, where water clarity is reduced and little light penetrates. Evidence of increased stress on coastal ecosystems exists, partially due to climate change, yet a systematic analysis of extreme events and trends is difficult due to limited data. To address this concern, we have developed as a potential climate indicator a Kd-Index for nine regions along the US coast of the Gulf of Mexico, in which Kd values have been standardized over time and space to allow for a more holistic assessment of climate drivers and their trends. Variability in the Kd-Index is then assessed with regard to occurrences of surface weather types (using the Spatial Synoptic Classification), a synoptic climatology of mean sea-level-pressure patterns across the region, along with heavy precipitation events. Kd can be estimated from MODIS and SeaWiFS observations from 1997 to date; an earlier period of satellite observations from 1978-86 is also available. A non-linear autoregressive neural network model with external input (NARX) is used to develop the historical relationship between Kd-Index and atmospheric conditions, and then this model is used to simulate a full time series from 1948 to 2013. The modeled data set is strongly correlated with observations, with correlations above 0.8 for many regions. Hit rates of extreme Kd-Index values - those which would most likely be associated with a negative environmental impact - exceed 70% in some regions. Across the full data set, long term trends vary slightly across regions but are generally small. Trends in extreme events appear to be more consistently increasing across the domain.

European temperature records of the past five centuries based on documentary information compared to climate simulations

NASA Astrophysics Data System (ADS)

Zorita, E.

2009-09-01

Two European temperature records for the past half-millennium, January-to-April air temperature for Stockholm (Sweden) and seasonal temperature for a Central European region, both derived from the analysis of documentary sources combined with long instrumental records, are compared with the output of forced (solar, volcanic, greenhouse gases) climate simulations with the model ECHO-G. The analysis is complemented with the long (early)-instrumental record of Central England Temperature (CET). Both approaches to study past climates (simulations and reconstructions) are burdened with uncertainties. The main objective of this comparative analysis is to identify robust features and weaknesses that may help to improve models and reconstruction methods. The results indicate a general agreement between simulations and the reconstructed Stockholm and CET records regarding the long-term temperature trend over the recent centuries, suggesting a reasonable choice of the amplitude of the solar forcing in the simulations and sensitivity of the model to the external forcing. However, the Stockholm reconstruction and the CET record also show a long and clear multi-decadal warm episode peaking around 1730, which is absent in the simulations. The uncertainties associated with the reconstruction method or with the simulated internal climate variability cannot easily explain this difference. Regarding the interannual variability, the Stockholm series displays in some periods higher amplitudes than the simulations but these differences are within the statistical uncertainty and further decrease if output from a regional model driven by the global model is used. The long-term trends in the simulations and reconstructions of the Central European temperature agree less well. The reconstructed temperature displays, for all seasons, a smaller difference between the present climate and past centuries than the simulations. Possible reasons for these differences may be related to a limitation of the traditional technique for converting documentary evidence to temperature values to capture long-term climate changes, because the documents often reflect temperatures relative to the contemporary authors' own perception of what constituted 'normal' conditions. By contrast, the simulated and reconstructed inter-annual variability is in rather good agreement.

Non-climatic factors and long-term, continental-scale changes in seasonally frozen ground

NASA Astrophysics Data System (ADS)

Shiklomanov, Nikolay I.

2012-03-01

Numerous studies indicate that the northern high latitudes are experiencing an unprecedented rate of environmental change, including an increase in air temperatures (e.g. Serreze and Francis 2006), reduction of snow cover (e.g. Brown and Robinson 2011), ecosystem transformations and land cover changes (e.g. Callaghan et al 2011). Many of the potential environmental impacts of global warming in the high latitudes are associated with frozen ground, which occupies about 55% of the unglaciated land area in the northern hemisphere and consists of both permafrost and seasonally frozen ground. Frozen soils have a tremendous impact on hydrologic, climatic and biologic systems. Periodic freezing and thawing promote changes in soil structure, affect the surface and subsurface water cycle, and regulate the availability of nutrients in the soil for plants and biota that depend upon them. Freezing and thawing cycles can affect the decomposition of organic substances in the soil and greenhouse gas exchange between the atmosphere and land surface. Significant efforts have been devoted to permafrost-related studies, including the establishment of standardized observations (e.g. Romanovsky et al 2010, Shiklomanov et al 2008), modeling (e.g. Riseborough et al 2008), and climate-related feedback processes (e.g. Schuur et al 2008). Despite its vast extent and importance, seasonally frozen ground has received much less attention. One of the major obstacles in assessing changes in seasonally frozen ground is the lack of long-term data. In general, observations on soil temperature and freeze propagation are available for a limited area and involve a relatively short time period, precluding assessment of long-term, climate-driven change. A few known exceptions include shallow soil temperature and freeze/thaw depth observations conducted as part of the standard hydrometeorological monitoring system in China (e.g. Zhao et al 2004) and the Soviet Union/Russia (e.g. Gilichinsky et al 2000). In their recent paper entitled 'An observational 71-year history of seasonally frozen ground changes in Eurasian high latitudes', Frauenfeld and Zhang (2011) provided detailed analysis of soil temperature data to assess 1930-2000 trends in seasonal freezing depth. The data were obtained from 387 Soviet non-permafrost meteorological stations. The authors performed systematic, quality-controlled, integrative analysis over the entire former Soviet Union domain. The long-term changes in depth of seasonal freezing were discussed in relation to such forcing variables as air temperature, degree days of freezing/thawing, snow depth and summer precipitation as well as modes of the North Atlantic Oscillation. The spatially average approach adopted for the study provides a generalized continental-scale trend. The study greatly improves, expands and extends previous 1956-90 analysis of the ground thermal regime over the Eurasian high latitudes (Frauenfeld et al 2004). Although the work of Frauenfeld and Zhang (2011) is the most comprehensive assessment of the continental-scale long-term trends in seasonal freezing available to date, more detailed analysis is needed to determine the effect of climate change on seasonally frozen ground. It should be noted that, in addition to the variables considered for analysis, other non-climatic factors affect the depth of freezing propagation. Unlike the surface, which is influenced by the climate directly, the ground even at shallow depth receives a climatic signal that is substantially modified by edaphic processes, contributing to highly localized thermal sensitivities of the ground to climatic forcing. Subsurface properties, soil moisture, and snow and vegetation covers influence the depth of freezing. Topography also plays an important role in establishing the ground thermal regime. It is an important determinant of the amount of heat received by the ground surface, affects the distribution of snow and vegetation, and influences the surface and subsurface moisture regimes. As a result, the ground temperature and the related depth of freezing propagation are characterized by very high variability over short lateral distances. The data used for analysis by Frauenfeld and Zhang are single-point measurements obtained from a network of stations sparsely distributed over a very large spatial domain. Since no variability in edaphic conditions was considered, the presented results should be interpreted with some degree of caution. In addition, long-term soil observations at a single point using unautomated techniques unavoidably cause site disturbance, which may significantly modify the ground thermal regime over time. I would like to emphasize that the generalized continental trend in the depth of seasonal freezing presented by Frauenfeld and Zhang is very likely associated with changes in atmospheric forcing. However, any long-term continental trends of such a spatially heterogeneous and sensitive parameter as shallow soil temperature potentially include a significant non-climatic component. Although the single-point temperature data used by Frauenfeld and Zhang might not be sufficient to fully evaluate the localized effects on the overall trend, they are a terrific asset for further studies on climate and ground thermal regime. Detailed spatial assessment of the available ground temperature records over relatively homogeneous regions is a necessary next step in the assessment of climate-induced changes in seasonally frozen ground. Such an analysis is likely to show significant regional differences in long-term freeze propagation trends over Northern Eurasia and reveal region-specific sensitivities of the ground thermal regime to climatic forcing. References Brown R D and Robinson D A 2011 Northern hemisphere spring snow cover variability and change over 1922-2010 including an assessment of uncertainty Cryosphere 5 219-29 Callaghan T V, Tweedie C E and Webber P J 2011 Multi-decadal changes in tundra environments and ecosystems: the International Polar Year-Back to the Future Project (IPYBTF) AMBIO 40 555-7 Frauenfeld O W and Zhang T 2011 An observational 71-year history of seasonally frozen ground changes in the Eurasian high latitudes Environ. Res. Lett. 6 044024 Frauenfeld O W, Zhang T, Barry R G and Gilichinsky D 2004 Interdecadal changes in seasonal freeze and thaw depths in Russia J. Geophys. Res. 109 D5101 Gilichinsky D A et al 2000 Use of the data of hydrometeorological survey for century history of soil temperature trends in the seasonally frozen and permafrost areas of Russia Earth Cryosp. 4 59-66 (in Russian) Riseborough D, Shiklomanov N I, Etselmuller B and Gruber S 2008 Recent advances in permafrost modeling Permafr. Pereglac. Process. 19 137-56 Romanovsky V E et al 2010 Thermal state of permafrost in Russia Permafr. Periglac. Process. 21 136-55 Schuur E A G et al 2008 Vulnerability of permafrost carbon to climate change: implications for the global carbon cycle Bioscience 58 701-14 Serreze M C and Francis J A 2006 The Arctic amplification debate Clim. Change 76 241-64 Shiklomanov N I, Nelson F E, Streletskiy D A, Hinkel K M and Brown J 2008 The circumpolar active layer monitoring (CALM) program: data collection, management, and dissemination strategies Proc. of the 9th International Conf. on Permafrost (Fairbanks, AK, 29 June-3 July 2008) vol 1, pp 1647-52 Zhao L, Ping C L, Yang D, Cheng G, Ding Y and Liu S 2004 Changes of climate and seasonally frozen ground over the past 30 years in Qinghai-Xizang (Tibetan) Plateau, China Glob. Planet. Change 43 19-31

Global Warming and Geographically Scalar Climatic Objects Exist: An Ontologically Realist and Object-Oriented Analysis of the Daymet TMAX Climate Summaries for North America

NASA Astrophysics Data System (ADS)

Jackson, C. P.

2017-12-01

The scientific materialist worldview, what Peter Unger refers to as the Scientiphical worldview, or Scientiphicalism, has been utterly catastrophic for mesoscale objects in general, but, with its closely associated twentieth-century formal logic, this has been especially true for notoriously vague things like climate change, coastlines, mountains and dust storms. That is, any so-called representations or references ultimately suffer the same ontological demise as their referents, no matter how well-defined their boundaries may in fact be. Against this reductionist metaphysics, climatic objects are discretized within three separate ontologically realist systems, Graham Harman's object-oriented philosophy, or ontology (OOO), Markus Gabriel's ontology of fields of sense (OFS) and Tristan Garcia's two systems and new order of time, so as to make an ontological case for any geographically scalar object, beginning with pixels, as well as any notoriously vague thing they are said to represent. Four-month overlapping TMAX seasonals were first developed from the Oak Ridge National Laboratory (ORNL) Daymet climate temperature maximum (TMAX) monthly summaries (1980-2016) for North America and segmented within Trimble's eCognition Developer using the simple and widely familiar quadtree algorithm with a scale parameter of four, in this example. The regression coefficient was then calculated for the resulting 37-year climatic objects and an equally simple classification was applied. The same segmentation and classification was applied to the Daymet annual summaries, as well, for comparison. As was expected, the mean warming and cooling trends are lowest for the annual summary TMAX climatic objects. However, the Fall (SOND) season has the largest and smallest areas of warming and cooling, respectively, and the highest mean trend for warming objects. Conversely, Spring (MAMJ) has the largest and smallest areas undergoing cooling and warming, respectively. Finally, Summer (JJAS) has the highest mean trend for cooling objects. Not only do these highly heterogeneous and variable patterns become readily apparent with each set of objects, but so do any possible anomalies that might warrant further investigation.

Simulated discharge trends indicate robustness of hydrological models in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Nikolova, Silviya; Seibert, Jan

2016-04-01

Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant parameter values over the whole reference period. Further, preliminary results suggest that some trends in parameter values do not reflect changes in hydrological processes, as reported by others previously, but instead might stem from a modeling artifact related to the parameterization of evapotranspiration, which is overly sensitive to temperature increase. We adopt a trading-space-for-time approach to better understand whether robust relationships between parameter values and forcing can be established, and to critically explore the rationale behind time-dependent parameter values in conceptual hydrological models.

Assessment of CORDEX-South Asia experiments for monsoonal precipitation over Himalayan region for future climate

NASA Astrophysics Data System (ADS)

Choudhary, A.; Dimri, A. P.

2018-04-01

Precipitation is one of the important climatic indicators in the global climate system. Probable changes in monsoonal (June, July, August and September; hereafter JJAS) mean precipitation in the Himalayan region for three different greenhouse gas emission scenarios (i.e. representative concentration pathways or RCPs) and two future time slices (near and far) are estimated from a set of regional climate simulations performed under Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) project. For each of the CORDEX-SA simulations and their ensemble, projections of near future (2020-2049) and far future (2070-2099) precipitation climatology with respect to corresponding present climate (1970-2005) over Himalayan region are presented. The variability existing over each of the future time slices is compared with the present climate variability to determine the future changes in inter annual fluctuations of monsoonal mean precipitation. The long-term (1970-2099) trend (mm/day/year) of monsoonal mean precipitation spatially distributed as well as averaged over Himalayan region is analyzed to detect any change across twenty-first century as well as to assess model uncertainty in simulating the precipitation changes over this period. The altitudinal distribution of difference in trend of future precipitation from present climate existing over each of the time slices is also studied to understand any elevation dependency of change in precipitation pattern. Except for a part of the Hindu-Kush area in western Himalayan region which shows drier condition, the CORDEX-SA experiments project in general wetter/drier conditions in near future for western/eastern Himalayan region, a scenario which gets further intensified in far future. Although, a gradually increasing precipitation trend is seen throughout the twenty-first century in carbon intensive scenarios, the distribution of trend with elevation presents a very complex picture with lower elevations showing a greater trend in far-future under RCP8.5 when compared with higher elevations.

Trends of Measured Climate Forcing Agents

NASA Technical Reports Server (NTRS)

Hansen, James E.; Sato, Makiko; Einaudi, Franco (Technical Monitor)

2002-01-01

The growth rate of climate forcing by measured greenhouse gases peaked near 1980 at almost 5 W/sq m per century. This growth rate has since declined to approximately equal to 3 W/sq m per century, largely because of cooperative international actions. We argue that trends can be reduced to the level needed for the moderate "alternative" climate scenario (approximately equal to 2 W/M2 per century for the next 50 years) by means of concerted actions that have other benefits, but the forcing reductions are not automatic "co-benefits" of actions that slow CO2 emissions. Current trends of climate forcings by aerosols remain very uncertain. Nevertheless, practical constraints on changes in emission levels suggest that global warming at a rate + 0.15 +/- 0.05 C per decade will occur over the next several decades.

Role of internal variability in recent decadal to multidecadal tropical Pacific climate changes

NASA Astrophysics Data System (ADS)

Bordbar, Mohammad Hadi; Martin, Thomas; Latif, Mojib; Park, Wonsun

2017-05-01

While the Earth's surface has considerably warmed over the past two decades, the tropical Pacific has featured a cooling of sea surface temperatures in its eastern and central parts, which went along with an unprecedented strengthening of the equatorial trade winds, the surface component of the Pacific Walker Circulation (PWC). Previous studies show that this decadal trend in the trade winds is generally beyond the range of decadal trends simulated by climate models when forced by historical radiative forcing. There is still a debate on the origin of and the potential role that internal variability may have played in the recent decadal surface wind trend. Using a number of long control (unforced) integrations of global climate models and several observational data sets, we address the question as to whether the recent decadal to multidecadal trends are robustly classified as an unusual event or the persistent response to external forcing. The observed trends in the tropical Pacific surface climate are still within the range of the long-term internal variability spanned by the models but represent an extreme realization of this variability. Thus, the recent observed decadal trends in the tropical Pacific, though highly unusual, could be of natural origin. We note that the long-term trends in the selected PWC indices exhibit a large observational uncertainty, even hindering definitive statements about the sign of the trends.