A High-Resolution ENSO-Driven Rainfall Record Derived From an Exceptionally Fast Growing Stalagmite From Niue Island (South Pacific)

NASA Astrophysics Data System (ADS)

Troy, S.; Aharon, P.; Lambert, W. J.

2012-12-01

El Niño-Southern Oscillation's (ENSO) dominant control over the present global climate and its unpredictable response to a global warming makes the study of paleo-ENSO important. So far corals, spanning the Tropical Pacific Ocean, are the most commonly used geological archives of paleo-ENSO. This is because corals typically exhibit high growth rates (>1 cm/yr), and reproduce reliably surface water temperatures at sub-annual resolution. However there are limitations to coral archives because their time span is relatively brief (in the order of centuries), thus far making a long and continuous ENSO record difficult to achieve. On the other hand stalagmites from island settings can offer long and continuous records of ENSO-driven rainfall. Niue Island caves offer an unusual opportunity to investigate ENSO-driven paleo-rainfall because the island is isolated from other large land masses, making it untainted by continental climate artifacts, and its geographical location is within the Tropical Pacific "rain pool" (South Pacific Convergence Zone; SPCZ) that makes the rainfall variability particularly sensitive to the ENSO phase switches. We present here a δ18O and δ13C time series from a stalagmite sampled on Niue Island (19°00' S, 169°50' W) that exhibits exceptionally high growth rates (~1.2 mm/yr) thus affording a resolution comparable to corals but for much longer time spans. A precise chronology, dating back to several millennia, was achieved by U/Th dating of the stalagmite. The stalagmite was sampled using a Computer Automated Mill (CAM) at 300 μm increments in order to receive sub-annual resolution (every 3 months) and calcite powders of 50-100 μg weight were analyzed for δ18O and δ13C using a Continuous Flow Isotope Ratio Mass Spectrometer (CF-IRMS). The isotope time series contains variable shifts at seasonal, inter-annual, and inter-decadal periodicities. The δ13C and δ18O yield ranges of -3.0 to -13.0 (‰ VPDB) and -3.2 to -6.2 (‰ VPDB), respectively. The presentation will describe the factors impacting the seasonal, inter-annual and inter-decadal variability in a highly resolved ENSO record.

Adapting to climate variability and change: experiences from cereal-based farming in the central rift and Kobo Valleys, Ethiopia.

PubMed

Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

2013-11-01

Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions-the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers' perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new risks outside the range of current experiences. To enable farmers to adapt to these impacts critical technological, institutional, and market-access constraints need to be removed. Inconsistencies between farmers' perceptions and observed climate trends (e.g., decrease in annual rainfall) could lead to sub-optimal or counterproductive adaptations, and therefore must be removed by better communication and capacity building, for example through Climate Field Schools. Enabling strategies, which are among others targeted at agricultural inputs, credit supply, market access, and strengthening of local knowledge and information services need to become integral part of government policies to assist farmers to adapt to the impacts of current and future climate change.

Adapting to Climate Variability and Change: Experiences from Cereal-Based Farming in the Central Rift and Kobo Valleys, Ethiopia

NASA Astrophysics Data System (ADS)

Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

2013-11-01

Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions—the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers’ perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new risks outside the range of current experiences. To enable farmers to adapt to these impacts critical technological, institutional, and market-access constraints need to be removed. Inconsistencies between farmers’ perceptions and observed climate trends (e.g., decrease in annual rainfall) could lead to sub-optimal or counterproductive adaptations, and therefore must be removed by better communication and capacity building, for example through Climate Field Schools. Enabling strategies, which are among others targeted at agricultural inputs, credit supply, market access, and strengthening of local knowledge and information services need to become integral part of government policies to assist farmers to adapt to the impacts of current and future climate change.

Sensitivity of crop cover to climate variability: insights from two Indian agro-ecoregions.

PubMed

Mondal, Pinki; Jain, Meha; DeFries, Ruth S; Galford, Gillian L; Small, Christopher

2015-01-15

Crop productivity in India varies greatly with inter-annual climate variability and is highly dependent on monsoon rainfall and temperature. The sensitivity of yields to future climate variability varies with crop type, access to irrigation and other biophysical and socio-economic factors. To better understand sensitivities to future climate, this study focuses on agro-ecological subregions in Central and Western India that span a range of crops, irrigation, biophysical conditions and socioeconomic characteristics. Climate variability is derived from remotely-sensed data products, Tropical Rainfall Measuring Mission (TRMM - precipitation) and Moderate Resolution Imaging Spectroradiometer (MODIS - temperature). We examined green-leaf phenologies as proxy for crop productivity using the MODIS Enhanced Vegetation Index (EVI) from 2000 to 2012. Using both monsoon and winter growing seasons, we assessed phenological sensitivity to inter-annual variability in precipitation and temperature patterns. Inter-annual EVI phenology anomalies ranged from -25% to 25%, with some highly anomalous values up to 200%. Monsoon crop phenology in the Central India site is highly sensitive to climate, especially the timing of the start and end of the monsoon and intensity of precipitation. In the Western India site, monsoon crop phenology is less sensitive to precipitation variability, yet shows considerable fluctuations in monsoon crop productivity across the years. Temperature is critically important for winter productivity across a range of crop and management types, such that irrigation might not provide a sufficient buffer against projected temperature increases. Better access to weather information and usage of climate-resilient crop types would play pivotal role in maintaining future productivity. Effective strategies to adapt to projected climate changes in the coming decades would also need to be tailored to regional biophysical and socio-economic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Flexible Strategies for Coping with Rainfall Variability: Seasonal Adjustments in Cropped Area in the Ganges Basin

PubMed Central

Siderius, Christian; Biemans, Hester; van Walsum, Paul E. V.; van Ierland, Ekko C.; Kabat, Pavel; Hellegers, Petra J. G. J.

2016-01-01

One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999–2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions. PMID:26934389

Monthly Rainfall Erosivity Assessment for Switzerland

NASA Astrophysics Data System (ADS)

Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

2016-04-01

Water erosion is crucially controlled by rainfall erosivity, which is quantified out of the kinetic energy of raindrop impact and associated surface runoff. Rainfall erosivity is often expressed as the R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). Just like precipitation, the rainfall erosivity of Switzerland has a characteristic seasonal dynamic throughout the year. This inter-annual variability is to be assessed by a monthly and seasonal modelling approach. We used a network of 86 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term average monthly R-factors. Stepwise regression and Monte Carlo Cross Validation (MCCV) was used to select spatial covariates to explain the spatial pattern of R-factor for each month across Switzerland. The regionalized monthly R-factor is mapped by its individual regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow height, a combination of hourly gauging measurements and radar observations (CombiPrecip), mean monthly alpine precipitation (EURO4M-APGD) and monthly precipitation sums (Rhires). Topographic parameters were also significant explanatory variables for single months. The comparison of all 12 monthly rainfall erosivity maps showed seasonality with highest rainfall erosivity in summer (June, July, and August) and lowest rainfall erosivity in winter months. Besides the inter-annual temporal regime, a seasonal spatial variability was detectable. Spatial maps of monthly rainfall erosivity are presented for the first time for Switzerland. The assessment of the spatial and temporal dynamic behaviour of the R-factor is valuable for the identification of more susceptible seasons and regions as well as for the application of selective erosion control measures. A combination with monthly vegetation cover (C-factor) maps would enable the assessment of seasonal dynamics of erosion processes in Switzerland.

The effect of vaccination coverage and climate on Japanese encephalitis in Sarawak, Malaysia.

PubMed

Impoinvil, Daniel E; Ooi, Mong How; Diggle, Peter J; Caminade, Cyril; Cardosa, Mary Jane; Morse, Andrew P; Baylis, Matthew; Solomon, Tom

2013-01-01

Japanese encephalitis (JE) is the leading cause of viral encephalitis across Asia with approximately 70,000 cases a year and 10,000 to 15,000 deaths. Because JE incidence varies widely over time, partly due to inter-annual climate variability effects on mosquito vector abundance, it becomes more complex to assess the effects of a vaccination programme since more or less climatically favourable years could also contribute to a change in incidence post-vaccination. Therefore, the objective of this study was to quantify vaccination effect on confirmed Japanese encephalitis (JE) cases in Sarawak, Malaysia after controlling for climate variability to better understand temporal dynamics of JE virus transmission and control. Monthly data on serologically confirmed JE cases were acquired from Sibu Hospital in Sarawak from 1997 to 2006. JE vaccine coverage (non-vaccine years vs. vaccine years) and meteorological predictor variables, including temperature, rainfall and the Southern Oscillation index (SOI) were tested for their association with JE cases using Poisson time series analysis and controlling for seasonality and long-term trend. Over the 10-years surveillance period, 133 confirmed JE cases were identified. There was an estimated 61% reduction in JE risk after the introduction of vaccination, when no account is taken of the effects of climate. This reduction is only approximately 45% when the effects of inter-annual variability in climate are controlled for in the model. The Poisson model indicated that rainfall (lag 1-month), minimum temperature (lag 6-months) and SOI (lag 6-months) were positively associated with JE cases. This study provides the first improved estimate of JE reduction through vaccination by taking account of climate inter-annual variability. Our analysis confirms that vaccination has substantially reduced JE risk in Sarawak but this benefit may be overestimated if climate effects are ignored.

An assessment of temporal effect on extreme rainfall estimates

NASA Astrophysics Data System (ADS)

Das, Samiran; Zhu, Dehua; Chi-Han, Cheng

2018-06-01

This study assesses the temporal behaviour in terms of inter-decadal variability of extreme daily rainfall of stated return period relevant for hydrologic risk analysis using a novel regional parametric approach. The assessment is carried out based on annual maximum daily rainfall series of 180 meteorological stations of Yangtze River Basin over a 50-year period (1961-2010). The outcomes of the analysis reveal that while there were effects present indicating higher quantile values when estimated from data of the 1990s, it is found not to be noteworthy to exclude the data of any decade from the extreme rainfall estimation process for hydrologic risk analysis.

Analysis of trends and dominant periodicities in drought variables in India: A wavelet transform based approach

NASA Astrophysics Data System (ADS)

Joshi, Nitin; Gupta, Divya; Suryavanshi, Shakti; Adamowski, Jan; Madramootoo, Chandra A.

2016-12-01

In this study, seasonal trends as well as dominant and significant periods of variability of drought variables were analyzed for 30 rainfall subdivisions in India over 141 years (1871-2012). Standardized precipitation index (SPI) was used as a meteorological drought indicator, and various drought variables (monsoon SPI, non-monsoon SPI, yearly SPI, annual drought duration, annual drought severity and annual drought peak) were analyzed. Discrete wavelet transform was used in conjunction with the Mann-Kendall test to analyze trends and dominant periodicities associated with the drought variables. Furthermore, continuous wavelet transform (CWT) based global wavelet spectrum was used to analyze significant periods of variability associated with the drought variables. From the trend analysis, we observed that over the second half of the 20th century, drought occurrences increased significantly in subdivisions of Northeast and Central India. In both short-term (2-8 years) and decadal (16-32 years) periodicities, the drought variables were found to influence the trend. However, CWT analysis indicated that the dominant periodic components were not significant for most of the geographical subdivisions. Although inter-annual and inter-decadal periodic components play an important role, they may not completely explain the variability associated with the drought variables across the country.

ENSO Related Interannual Lightning Variability from the Full TRMM LIS Lightning Climatology

NASA Technical Reports Server (NTRS)

Clark, Austin; Cecil, Daniel J.

2018-01-01

It has been shown that the El Nino/Southern Oscillation (ENSO) contributes to inter-annual variability of lightning production in the tropics and subtropics more than any other atmospheric oscillation. This study further investigated how ENSO phase affects lightning production in the tropics and subtropics. Using the Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) and the Oceanic Nino Index (ONI) for ENSO phase, lightning data were averaged into corresponding mean annual warm, cold, and neutral 'years' for analysis of the different phases. An examination of the regional sensitivities and preliminary analysis of three locations was conducted using model reanalysis data to determine the leading convective mechanisms in these areas and how they might respond to the ENSO phases. These processes were then studied for inter-annual variance and subsequent correlation to ENSO during the study period to best describe the observed lightning deviations from year to year at each location.

Inter-Seasonal and Annual Co-Variation of Smallholder Production Portfolios, Volumes and Incomes with Rainfall and Flood Levels in the Amazon Estuary: Implications for Building Livelihood Resilience to Increasing Variability of Hydro-Climatic Regimes

NASA Astrophysics Data System (ADS)

Vogt, N. D.; Fernandes, K.; Pinedo-Vasquez, M.; Brondizio, E. S.; Almeida, O.; Rivero, S.; Rabelo, F. R.; Dou, Y.; Deadman, P.

2014-12-01

In this paper we investigate inter-seasonal and annual co-variations of rainfall and flood levels with Caboclo production portfolios, and proportions of it they sell and consume, in the Amazon Estuary from August 2012 to August 2014. Caboclos of the estuary maintain a diverse and flexible land-use portfolio, with a shift in dominant use from agriculture to agroforestry and forestry since WWII (Vogt et al., 2014). The current landscape is configured for acai, shrimp and fish production. In the last decade the frequency of wet seasons with anomalous flood levels and duration has increased primarily from changes in rainfall and discharge from upstream basins. Local rainfall, though with less influence on extreme estuarine flood levels, is reported to be more sporadic and intense in wet season and variable in both wet and dry seasons, for yet unknown reasons. The current production portfolio and its flexibility are felt to build resilience to these increases in hydro-climatic variability and extreme events. What is less understood, for time and costliness of daily measures at household levels, is how variations in flood and rainfall levels affect shifts in the current production portfolio of estuarine Caboclos, and the proportions of it they sell and consume. This is needed to identify what local hydro-climatic thresholds are extreme for current livelihoods, that is, that most adversely affect food security and income levels. It is also needed identify the large-scale forcings driving those extreme conditions to build forecasts for when they will occur. Here we present results of production, rainfall and flood data collected daily in households from both the North and South Channel of the Amazon estuary over last two years to identify how they co-vary, and robustness of current production portfolio under different hydro-climatic conditions.

Managment oriented analysis of sediment yield time compression

NASA Astrophysics Data System (ADS)

Smetanova, Anna; Le Bissonnais, Yves; Raclot, Damien; Nunes, João P.; Licciardello, Feliciana; Le Bouteiller, Caroline; Latron, Jérôme; Rodríguez Caballero, Emilio; Mathys, Nicolle; Klotz, Sébastien; Mekki, Insaf; Gallart, Francesc; Solé Benet, Albert; Pérez Gallego, Nuria; Andrieux, Patrick; Moussa, Roger; Planchon, Olivier; Marisa Santos, Juliana; Alshihabi, Omran; Chikhaoui, Mohamed

2016-04-01

The understanding of inter- and intra-annual variability of sediment yield is important for the land use planning and management decisions for sustainable landscapes. It is of particular importance in the regions where the annual sediment yield is often highly dependent on the occurrence of few large events which produce the majority of sediments, such as in the Mediterranean. This phenomenon is referred as time compression, and relevance of its consideration growths with the increase in magnitude and frequency of extreme events due to climate change in many other regions. So far, time compression has ben studied mainly on events datasets, providing high resolution, but (in terms of data amount, required data precision and methods), demanding analysis. In order to provide an alternative simplified approach, the monthly and yearly time compressions were evaluated in eight Mediterranean catchments (of the R-OSMed network), representing a wide range of Mediterranean landscapes. The annual sediment yield varied between 0 to ~27100 Mg•km-2•a-1, and the monthly sediment yield between 0 to ~11600 Mg•km-2•month-1. The catchment's sediment yield was un-equally distributed at inter- and intra-annual scale, and large differences were observed between the catchments. Two types of time compression were distinguished - (i) the inter-annual (based on annual values) and intra- annual (based on monthly values). Four different rainfall-runoff-sediment yield time compression patterns were observed: (i) no time-compression of rainfall, runoff, nor sediment yield, (ii) low time compression of rainfall and runoff, but high compression of sediment yield, (iii) low compression of rainfall and high of runoff and sediment yield, and (iv) low, medium and high compression of rainfall, runoff and sediment yield. All four patterns were present at inter-annual scale, while at intra-annual scale only the two latter were present. This implies that high sediment yields occurred in particular months, even in catchment with low or no inter-annual time compression. The analysis of seasonality of time compression showed that in most of the catchments large sediment yields were more likely to occur between October and January, while in two catchments it was in summer (June and July). The appropriate sediment yield management measure: enhancement of soil properties, (dis)connectivity measures or vegetation cover, should therefore be selected with regard to the type of inter-annual time compression, to the properties of the individual catchments, and to the magnitudes of sediment yield. To increase the effectivity and lower the costs of the applied measures, the management in the months or periods when large sediment yields are most likely to occur should be prioritized. The analysis of the monthly time compression might be used for their identification in areas where no event datasets are available. The R-OSMed network of Mediterranean erosion research catchments was funded by "SicMed-Mistrals" grants from 2011 to 2014. Anna Smetanová has received the support of the European Union, in the framework of the Marie-Curie FP7 COFUND People Programme, through the award of an AgreenSkills' fellowship (under grant agreement n° 267196). João Pedro Nunes has received support from the European Union (in the framework of the European Social Fund) and the Portuguese Government under a post-doctoral fellowship (SFRH/BPD/87571/2012).

Characterizing phenological vegetation dynamics amidst extreme climate variability in Australia with MODIS VI data

NASA Astrophysics Data System (ADS)

Broich, M.; Huete, A. R.; Xuanlon, M.; Davies, K.; Restrepo-Coupe, N.; Ratana, P.

2012-12-01

Australia's climate is extremely variable with inter-annual rainfall at any given site varying by 5- or 6-fold or more, across the continent. In addition to such inter-annual variability, there can be significant intra-annual variability, especially in monsoonal Australia (e.g. the wet tropical savannas) and Mediterranean climates in SW Australia where prolonged dry seasons occur each year. This presents unique challenges to the characterization of seasonal dynamics with satellite datasets. In contrast to annual reoccurring temperature-driven phenology of northern hemisphere mid-latitudes, vegetation dynamics of the vast and dry Australian interior are poorly quantified by existing remote sensing products. For example, in the current global-based MODIS phenology product, central Australia is covered by ~30% fill values for any given year. Two challenges are specific to Australian landscapes: first, the difficulty of characterizing seasonality of rainfall-driven ecosystems in interior Australia where duration and magnitude of green-up and brown down cycles show high inter annual variability; second, modeling two phenologic layers, the trees and the grass in savannas were the trees are evergreen but the herbaceous understory varies with rainfall. Savannas cover >50% of Australia. Australia's vegetation and climate are different from other continents. A MODIS phenology product capable of characterizing vegetation dynamics across the continent is being developed in this research as part of the AusCover national expert network aiming to provide Australian biophysical remote sensing data time-series and continental-scale map products. These products aim to support the Terrestrial Ecosystem Research Network (TERN) serving ecosystem research in Australia. The MODIS land surface product for Australia first searches the entire time series of each Climate Modeling Grid pixel for low-high-low extreme point sequences. A double logistic function is then fit to each of these sequences allowing identification of growth periods with different magnitudes and durations anywhere in the time series. Results show that the highest absolute variability in peak greenness occurred in cropped areas while the highest relative variability (coefficient of variation) occurred in interior Australia particularly around Lake Eyre, the center of a closed drainage basin in the dry interior of the continent. Across the desert interior, the timing of the green-up onset and the peak greenness was correlated with the landfall of cyclones and the inland penetration and strength of the north Australian summer monsoon (represented by TRMM data). The variability of Australian land surface phenology magnitude and timing was found to be strongly correlated with the swings between La Nina and El Nino events. The information on vegetation dynamics represented here is critical for land surface, fuel accumulation, agricultural production, and permanent ecosystem change modeling in relation to climate trends. A unique research opportunity is provided by recent climate variability: in 2010 a persistent El Nino has given way to a strong two-year La Nina breaking a decade long drought that was followed by record-breaking rainfall across most of the continent and extensive flooding followed by sustained greening.

Interpretation of the impact of different managements and the rainfall variability on the soil erosion in a Mediterranean olive orchard microcatchment

NASA Astrophysics Data System (ADS)

Taguas, E. V.; Burguet, M.; Pérez, R.; Ayuso, J. L.; Gómez, J. A.

2012-04-01

The microcatchment is a spatial scale which allows to evaluate and to quantify the erosive processes under conditions close to those perceived by farmers. In this work, soil erosion and runoff over six hydrological years (2005 and 2011) were monitored in an olive orchard microcatchment of 6.4 ha, where different management types were applied. The aim was to evaluate the impact of the management and the rainfall regime variability. Non-tillage was applied during the years 2005-2007, tillage operations were carried in April in the period 2007-2010 while in the year 2010-2011, the tillage was applied in January and mulches (olives leaves and branches) were established for reducing the soil losses, mainly generated from rills. At the annual scale, the variation ranges of the cumulative rainfall depth and of the erosivity were between 600 and 1000 mm and between 600 and 1500 MJ mm ha-1 h-1, respectively. Although there are some gaps in the data series, the annual runoff coefficients calculated were smaller than 5% and the total sediment load range was between less than 1 t ha-1 year-1and more than 20 t ha-1 year-1. During these years olive yield also showed a high degree of variability, between 5000 kg ha-1 year-1and 10000 kg ha-1 year-1, typical of the alternate bearing of this crop, without correlation with annual rainfall. The annual rainfall depth explained significantly the sediment load and the runoff in spite of the different managements applied. At the event scale, rainfall depth was correlated with runoff, however, sediment load was very sensible to management. The high variability of the hydrological regime (inter and intra-annual) and the importance of the precedent hydrological years determine complex interpretations of the impact of the management on the soil losses and the olive yield by the farmers, so the continuity of the data analysis is essential for supporting the suitable taking decisions about the overall farm management.

Intra-seasonal and Inter-annual variability of Bowen Ratio over rain-shadow region of North peninsular India

NASA Astrophysics Data System (ADS)

Morwal, S. B.; Narkhedkar, S. G.; Padmakumari, B.; Maheskumar, R. S.; Deshpande, C. G.; Kulkarni, J. R.

2017-05-01

Intra-seasonal and inter-annual variability of Bowen Ratio (BR) have been studied over the rain-shadow region of north peninsular India during summer monsoon season. Daily grid point data of latent heat flux (LHF), sensible heat flux (SHF) from NCEP/NCAR Reanalysis for the period 1970-2014 have been used to compute daily area-mean BR. Daily grid point rainfall data at a resolution of 0.25° × 0.25° from APHRODITE's Water Resources for the available period 1970-2007 have been used to study the association between rainfall and BR. The study revealed that BR rapidly decreases from 4.1 to 0.29 in the month of June and then remains nearly constant at the same value (≤0.1) in the rest of the season. High values of BR in the first half of June are indicative of intense thermals and convective clouds with higher bases. Low values of BR from July to September period are indicative of weak thermals and convective clouds with lower bases. Intra-seasonal and inter-annual variability of BR is found to be inversely related to precipitation over the region. BR analysis indicates that the land surface characteristics of the study region during July-September are similar to that over oceanic regions as far as intensity of thermals and associated cloud microphysical properties are concerned. Similar variation of BR is found in El Nino and La Nina years. During June, an increasing trend is observed in SHF and BR and decreasing trend in LHF from 1976 to 2014. Increasing trend in the SHF is statistically significant.

The Effect of Vaccination Coverage and Climate on Japanese Encephalitis in Sarawak, Malaysia

PubMed Central

Impoinvil, Daniel E.; Ooi, Mong How; Diggle, Peter J.; Caminade, Cyril; Cardosa, Mary Jane; Morse, Andrew P.

2013-01-01

Background Japanese encephalitis (JE) is the leading cause of viral encephalitis across Asia with approximately 70,000 cases a year and 10,000 to 15,000 deaths. Because JE incidence varies widely over time, partly due to inter-annual climate variability effects on mosquito vector abundance, it becomes more complex to assess the effects of a vaccination programme since more or less climatically favourable years could also contribute to a change in incidence post-vaccination. Therefore, the objective of this study was to quantify vaccination effect on confirmed Japanese encephalitis (JE) cases in Sarawak, Malaysia after controlling for climate variability to better understand temporal dynamics of JE virus transmission and control. Methodology/principal findings Monthly data on serologically confirmed JE cases were acquired from Sibu Hospital in Sarawak from 1997 to 2006. JE vaccine coverage (non-vaccine years vs. vaccine years) and meteorological predictor variables, including temperature, rainfall and the Southern Oscillation index (SOI) were tested for their association with JE cases using Poisson time series analysis and controlling for seasonality and long-term trend. Over the 10-years surveillance period, 133 confirmed JE cases were identified. There was an estimated 61% reduction in JE risk after the introduction of vaccination, when no account is taken of the effects of climate. This reduction is only approximately 45% when the effects of inter-annual variability in climate are controlled for in the model. The Poisson model indicated that rainfall (lag 1-month), minimum temperature (lag 6-months) and SOI (lag 6-months) were positively associated with JE cases. Conclusions/significance This study provides the first improved estimate of JE reduction through vaccination by taking account of climate inter-annual variability. Our analysis confirms that vaccination has substantially reduced JE risk in Sarawak but this benefit may be overestimated if climate effects are ignored. PMID:23951373

In the hot seat : Insolation and ENSO controls on vegetation productivity in tropical Africa inferred from NDVI

NASA Astrophysics Data System (ADS)

Ivory, S.; Russell, J. L.; Cohen, A. S.

2010-12-01

Threats to tropical biodiversity with serious and costly implications for both ecosystems and human well-being in Africa have led the IPCC to classify this region as vulnerable to negative impacts from climate change. Yet little is known about how vegetation communities respond to altered patterns of rainfall and evaporation. Paleoclimate records within the tropics can help answer questions about how vegetation response to climate forcing changes over time. However, sparse spatial extent of records and uncertainty surrounding the climate-vegetation relationship complicate these insights. Understanding the climatic mechanisms involved in landscape change at all temporal scales creates the need for quantitative constraints of the modern relationship between climatic controls, hydrology, and vegetation. Though modern observational data can help elucidate this relationship, low resolution and complicated rainfall/vegetation associations make them less than ideal. Satellite data of vegetation productivity (NDVI) with continuous high-resolution spatial coverage provides a robust and elegant tool for identifying the link between global and regional controls and vegetation. We use regression analyses of variables either previously proposed or potentially important in regulating Afro-tropical vegetation (insolation, out-going long-wave radiation, geopotential height, Southern Oscillation Index, Indian Ocean Dipole, Indian Monsoon precipitation, sea-level pressure, surface wind, sea-surface temperature) on continuous, time-varying spatial fields of 8km NDVI for sub-Saharan Africa. These analyses show the importance of global atmospheric controls in producing regional intra-annual and inter-annual vegetation variability. Dipole patterns emerge primarily correlated with both the seasonal and inter-annual extent of the Intertropical Convergence Zone (ITCZ). Inter-annual ITCZ variability drives patterns in African vegetation resulting from the effect of insolation anomalies and ENSO events on atmospheric circulation rather than sea surface temperatures or teleconnections to mid/high latitudes. Global controls on tropical atmospheric circulation regulate vegetation throughout sub-Saharan Africa on many time scales through alteration of dry season length and moisture convergence, rather than precipitation amount.

Explaining the inter-annual variability in the ecosystem fluxes of the Brasschaat Scots pine forest: 20 years of eddy flux and pollution monitoring

NASA Astrophysics Data System (ADS)

Horemans, Joanna; Roland, Marilyn; Janssens, Ivan; Ceulemans, Reinhart

2017-04-01

Because of their ecological and recreational value, the health of forest ecosystems and their response to global change and pollution are of high importance. At a number of EuroFlux and ICOS ecosystem sites in Europe - as the Brasschaat forest site - the measurements of ecosystem fluxes of carbon and other gases are combined with vertical profiles of air pollution within the framework of the ICP-Forest monitoring program. The Brasschaat forest is dominated by 80-year old Scots pines (Pinus sylvestris L.), and has a total area of about 150 ha. It is situated near an urban area in the Campine region of Flanders, Belgium and is characterized by a mean annual temperature of 9.8 °C and an annual rainfall of 830 mm. In this contribution we report on a long-term analysis (1996-2016) of the ecosystem carbon and water fluxes, the energy exchanges and the pollutant concentrations (ozone, NOx, NH3, SO2). Particular interest goes to the inter-annual variation of the carbon fluxes and the carbon allocation patterns. The impact of the long-term (aggregated) and the short-term variability in both the meteorological drivers and in the main tropospheric pollutants on the carbon fluxes is examined, as well as their mutual interactive effects and their potential memory effect. The effect of variability in the drivers during the phenological phases (seasonality) on the inter-annual variability of the fluxes is also examined. Basic statistical techniques as well as spectral analyses and data mining techniques are being used.

Assessing the Change in Rainfall Characteristics and Trends for the Southern African ITCZ Region

NASA Astrophysics Data System (ADS)

Baumberg, Verena; Weber, Torsten; Helmschrot, Jörg

2015-04-01

Southern Africa is strongly influenced by the movement and intensity of the Intertropical Convergence Zone (ITCZ) thus determining the climate in this region with distinct seasonal and inter-annual rainfall dynamics. The amount and variability of rainfall affect the various ecosystems by controlling the hydrological system, regulating water availability and determining agricultural practices. Changes in rainfall characteristics potentially caused by climate change are of uppermost relevance for both ecosystem functioning and human well-being in this region and, thus, need to be investigated. To analyse the rainfall variability governed by the ITCZ in southern Africa, observational daily rainfall datasets with a high spatial resolution of 0.25° x 0.25° (about 28 km x 28 km) from satellite-based Tropical Rainfall Measuring Mission (TRMM) and Global Land Data Assimilation System (GLDAS) are used. These datasets extend from 1998 to 2008 and 1948 to 2010, respectively, and allow for the assessment of rainfall characteristics over different spatial and temporal scales. Furthermore, a comparison of TRMM and GLDAS and, where available, with observed data will be made to determine the differences of both datasets. In order to quantify the intra- and inner-annual variability of rainfall, the amount of total rainfall, duration of rainy seasons and number of dry spells along with further indices are calculated from the observational datasets. Over the southern African ITCZ region, the rainfall characteristics change moving from wetter north to the drier south, but also from west to east, i.e. the coast to the interior. To address expected spatial and temporal variabilities, the assessment of changes in the rainfall parameters will be carried out for different transects in zonal and meridional directions over the region affected by the ITCZ. Revealing trends over more than 60 years, the results will help to identify and understand potential impacts of climate change on rainfall characteristics for the southern African ITCZ region. The findings of this study will feed into various ecosystem assessment and biodiversity change studies in Angola and Zambia.

Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model

NASA Astrophysics Data System (ADS)

Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

2017-10-01

In this study, the performance of the Generalized LInear Modelling of daily CLImate sequence (GLIMCLIM) statistical downscaling model was assessed to simulate extreme rainfall indices and annual maximum daily rainfall (AMDR) when downscaled daily rainfall from National Centers for Environmental Prediction (NCEP) reanalysis and Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCM) (four GCMs and two scenarios) output datasets and then their changes were estimated for the future period 2041-2060. The model was able to reproduce the monthly variations in the extreme rainfall indices reasonably well when forced by the NCEP reanalysis datasets. Frequency Adapted Quantile Mapping (FAQM) was used to remove bias in the simulated daily rainfall when forced by CMIP5 GCMs, which reduced the discrepancy between observed and simulated extreme rainfall indices. Although the observed AMDR were within the 2.5th and 97.5th percentiles of the simulated AMDR, the model consistently under-predicted the inter-annual variability of AMDR. A non-stationary model was developed using the generalized linear model for local, shape and scale to estimate the AMDR with an annual exceedance probability of 0.01. The study shows that in general, AMDR is likely to decrease in the future. The Onkaparinga catchment will also experience drier conditions due to an increase in consecutive dry days coinciding with decreases in heavy (>long term 90th percentile) rainfall days, empirical 90th quantile of rainfall and maximum 5-day consecutive total rainfall for the future period (2041-2060) compared to the base period (1961-2000).

China's water sustainability in the 21st century: a climate-informed water risk assessment covering multi-sector water demands

NASA Astrophysics Data System (ADS)

Chen, X.; Naresh, D.; Upmanu, L.; Hao, Z.; Dong, L.; Ju, Q.; Wang, J.; Wang, S.

2014-05-01

China is facing a water resources crisis with growing concerns as to the reliable supply of water for agricultural, industrial and domestic needs. High inter-annual rainfall variability and increasing consumptive use across the country exacerbates the situation further and is a constraint on future development. For water sustainability, it is necessary to examine the differences in water demand and supply and their spatio-temporal distribution in order to quantify the dimensions of the water risk. Here, a detailed quantitative assessment of water risk as measured by the spatial distribution of cumulated deficits for China is presented. Considering daily precipitation and temperature variability over fifty years and the current water demands, risk measures are developed to inform county level water deficits that account for both within-year and across-year variations in climate. We choose political rather than watershed boundaries since economic activity and water use are organized by county and the political process is best informed through that unit. As expected, the risk measures highlight North China Plain counties as highly water stressed. Regions with high water stress have high inter-annual variability in rainfall and now have depleted groundwater aquifers. The stress components due to agricultural, industrial and domestic water demands are illustrated separately to assess the vulnerability of particular sectors within the country to provide a basis for targeted policy analysis for reducing water stress.

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes

PubMed Central

Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.

2016-01-01

India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes.

PubMed

Ghosh, Subimal; Vittal, H; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K S; Dhanesh, Y; Sudheer, K P; Gunthe, S S

2016-01-01

India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.

Temporal and spatial characteristics of annual and seasonal rainfall in Malawi

NASA Astrophysics Data System (ADS)

Ngongondo, Cosmo; Xu, Chong-Yu; Gottschalk, Lars; Tallaksen, Lena M.; Alemaw, Berhanu

2010-05-01

An understanding of the temporal and spatial characteristics of rainfall is central to water resources planning and management. However, such information is often limited in many developing countries like Malawi. In an effort to bridge the information gap, this study examined the temporal and spatial charecteristics of rainfall in Malawi. Rainfall readings from 42 stations across Malawi from 1960 to 2006 were analysed at monthly, annual and seasonal scales. The Malawian rainfall season lasts from November to April. The data were firstly subjected to quality checks through the cumulative deviations test and the Standard Normal Homogeinity Test (SNHT). Monthly distribution in a typical year, called heterogeneity, was investigated using the Precipitation Concentration Index (PCI). Further, normalized precipitation anomaly series of annual rainfall series (AR) and the PCI (APCI) were used to test for interannual rainfall variability. Spatial variability was characterised by fitting the Spatial Correlation function (SCF). The nonparametric Mann-Kendall statistic was used to investigate the temporal trends of the various rainfall variables. The results showed that 40 of the stations passed both data quality tests. For the two stations that failed, the data were adjusted using nearby stations. Annual and seasonal rainfall were found to be characterised by high spatial variation. The country mean annual rainfall was 1095 mm with mean interannual variability of 26%. The highland areas to the north and southeast of the country exhibited the highest rainfall and lowest interannual variability. Lowest rainfall coupled with high interannual variability was found in the Lower Shire basin, in the southern part of Malawi. This simillarity is the pattern of annual and seasonal rainfall should be expected because all stations had over 90% of their observed annual rainfall in the six month period between November and April. Monthly rainfall was found to be highly variable both temporally and spatially. None of the stations have stable monthly rainfall regimes (mean PCI of less than 10). Stations with the highest mean rainfall were found to have a lower interannual variability. The rainfall stations showed low spatial correlations for annual, monthly as well as seasonal timescales indicating that the data may not be suitable for spatial interpolation. However, some structure (i.e. lower correlation with distance) could be observed when aggregating the data at 50 mile intervals. The annual and seasonal rainfall series were dominated by negative trends. The spatial distribution of the trends can be described as heterogeneous, although most of the stations in the southern region have negative trends. At the monthly timescale, 37 of the stations show a negative trend with four of the stations, all in the south, showing significant negative trends. On the other hand, only 5 stations show positive trends with only one significant trend in the south. Keywords: Malawi, rainfall trends, spatial variation

The impact of annual and seasonal rainfall patterns on growth and phenology of emergent tree species in Southeastern Amazonia, Brazil

Treesearch

James Grogan; Mark Schulze

2012-01-01

Understanding tree growth in response to rainfall distribution is critical to predicting forest and species population responses to climate change. We investigated inter-annual and seasonal variation in stem diameter by three emergent tree species in a seasonally dry tropical forest in southeast Pará, Brazil. Annual diameter growth rates by Swietenia macrophylla...

Atmospheric water budget over the South Asian summer monsoon region

NASA Astrophysics Data System (ADS)

Unnikrishnan, C. K.; Rajeevan, M.

2018-04-01

High resolution hybrid atmospheric water budget over the South Asian monsoon region is examined. The regional characteristics, variability, regional controlling factors and the interrelations of the atmospheric water budget components are investigated. The surface evapotranspiration was created using the High Resolution Land Data Assimilation System (HRLDAS) with the satellite-observed rainfall and vegetation fraction. HRLDAS evapotranspiration shows significant similarity with in situ observations and MODIS satellite-observed evapotranspiration. Result highlights the fundamental importance of evapotranspiration over northwest and southeast India on atmospheric water balance. The investigation shows that the surface net radiation controls the annual evapotranspiration over those regions, where the surface evapotranspiration is lower than 550 mm. The rainfall and evapotranspiration show a linear relation over the low-rainfall regions (<500 mm/year). Similar result is observed in in NASA GLDAS data (1980-2014). The atmospheric water budget shows annual, seasonal, and intra-seasonal variations. Evapotranspiration does not show a high intra-seasonal variability as compared to other water budget components. The coupling among the water budget anomalies is investigated. The results show that regional inter-annual evapotranspiration anomalies are not exactly in phase with rainfall anomalies; it is strongly influenced by the surface conditions and other atmospheric forcing (like surface net radiation). The lead and lag correlation of water budget components show that the water budget anomalies are interrelated in the monsoon season even up to 4 months lead. These results show the important regional interrelation of water budget anomalies on south Asian monsoon.

A comparison of extreme rainfall characteristics in the Brazilian Amazon derived from two gridded data sets and a national rain gauge network

NASA Astrophysics Data System (ADS)

Clarke, Robin T.; Bulhoes Mendes, Carlos Andre; Costa Buarque, Diogo

2010-07-01

Two issues of particular importance for the Amazon watershed are: whether annual maxima obtained from reanalysis and raingauge records agree well enough for the former to be useful in extending records of the latter; and whether reported trends in Amazon annual rainfall are reflected in the behavior of annual extremes in precipitation estimated from reanalyses and raingauge records. To explore these issues, three sets of daily precipitation data (1979-2001) from the Brazilian Amazon were analyzed (NCEP/NCAR and ERA-40 reanalyses, and records from the raingauge network of the Brazilian water resources agency - ANA), using the following variables: (1) mean annual maximum precipitation totals, accumulated over one, two, three and five days; (2) linear trends in these variables; (3) mean length of longest within-year "dry" spell; (4) linear trends in these variables. Comparisons between variables obtained from all three data sources showed that reanalyses underestimated time-trends and mean annual maximum precipitation (over durations of one to five days), and the correlations between reanalysis and spatially-interpolated raingauge estimates were small for these two variables. Both reanalyses over-estimated mean lengths of dry period relative to the mean length recorded by the raingauge network. Correlations between the trends calculated from all three data sources were small. Time-trends averaged over the reanalysis grid-squares, and spatially-interpolated time trends from raingauge data, were all clustered around zero. In conclusion, although the NCEP/NCAR and ERA-40 gridded data-sets may be valuable for studies of inter-annual variability in precipitation totals, they were found to be inappropriate for analysis of precipitation extremes.

Stochastic evaluation of annual micropollutant loads and their uncertainties in separate storm sewers.

PubMed

Hannouche, Ali; Chebbo, Ghassan; Joannis, Claude; Gasperi, Johnny; Gromaire, Marie-Christine; Moilleron, Régis; Barraud, Sylvie; Ruban, Véronique

2017-12-01

This article describes a stochastic method to calculate the annual pollutant loads and its application over several years at the outlet of three catchments drained by separate storm sewers. A stochastic methodology using Monte Carlo simulations is proposed for assessing annual pollutant load, as well as the associated uncertainties, from a few event sampling campaigns and/or continuous turbidity measurements (representative of the total suspended solids concentration (TSS)). Indeed, in the latter case, the proposed method takes into account the correlation between pollutants and TSS. The developed method was applied to data acquired within the French research project "INOGEV" (innovations for a sustainable management of urban water) at the outlet of three urban catchments drained by separate storm sewers. Ten or so event sampling campaigns for a large range of pollutants (46 pollutants and 2 conventional water quality parameters: TSS and total organic carbon (TOC)) are combined with hundreds of rainfall events for which, at least one among three continuously monitored parameters (rainfall intensity, flow rate, and turbidity) is available. Results obtained for the three catchments show that the annual pollutant loads can be estimated with uncertainties ranging from 10 to 60%, and the added value of turbidity monitoring for lowering the uncertainty is demonstrated. A low inter-annual and inter-site variability of pollutant loads, for many of studied pollutants, is observed with respect to the estimated uncertainties, and can be explained mainly by annual precipitation.

Hydroelectric production from Brazil's São Francisco River could cease due to climate change and inter-annual variability.

PubMed

de Jong, Pieter; Tanajura, Clemente Augusto Souza; Sánchez, Antonio Santos; Dargaville, Roger; Kiperstok, Asher; Torres, Ednildo Andrade

2018-09-01

By the end of this century higher temperatures and significantly reduced rainfall are projected for the Brazilian North and Northeast (NE) regions due to Global Warming. This study examines the impact of these long-term rainfall changes on the Brazilian Northeast's hydroelectric production. Various studies that use different IPCC models are examined in order to determine the average rainfall reduction by the year 2100 in comparison to baseline data from the end of the 20th century. It was found that average annual rainfall in the NE region could decrease by approximately 25-50% depending on the emissions scenario. Analysis of historical rainfall data in the São Francisco basin during the last 57years already shows a decline of more than 25% from the 1961-90 long-term average. Moreover, average annual rainfall in the basin has been below its long-term average every year bar one since 1992. If this declining trend continues, rainfall reduction in the basin could be even more severe than the most pessimistic model projections. That is, the marked drop in average rainfall projected for 2100, based on the IPCC high emissions scenario, could actually eventuate before 2050. Due to the elasticity factor between rainfall and streamflow and because of increased amounts of irrigation in the São Francisco basin, the reduction in the NE's average hydroelectric production in the coming decades could be double the predicted decline in rainfall. Conversely, it is estimated that wind power potential in the Brazilian NE will increase substantially by 2100. Therefore both wind and solar power will need to be significantly exploited in order for the NE region to sustainably replace lost hydroelectric production. Copyright © 2018 Elsevier B.V. All rights reserved.

China's water sustainability in the 21st century: a climate informed water risk assessment covering multi-sector water demands

NASA Astrophysics Data System (ADS)

Chen, X.; Devineni, N.; Lall, U.; Hao, Z.; Dong, L.; Ju, Q.; Wang, J.; Wang, S.

2013-08-01

China is facing a water resources crisis with growing concerns as to the reliable supply of water for agricultural, industrial and domestic needs. High inter-annual rainfall variability and increasing consumptive use across the country exacerbates the situation further and is a constraint on future development. For water sustainability, it is necessary to examine the differences in water demand and supply and their spatio-temporal distribution in order to quantify the dimensions of the water risk. Here, a detailed quantitative assessment of water risk as measured by the distribution of cumulated deficits for China is presented. Considering daily precipitation and temperature variability over fifty years and the current water demands, risk measures are developed to inform county level water deficits that account for both within year and across year variations in climate. We choose political rather than watershed boundaries since economic activity and water use are organized by county and the political process is best informed through that unit. The risk measures highlight North China Plain counties as highly water stressed. Regions with high water stress are typically the regions with high inter-annual variability in rainfall and now have depleted groundwater aquifers. The stress components due to agricultural, industrial and domestic water demands are illustrated separately to assess the vulnerability of particular sectors within the country to provide a basis for targeted policy analysis for reducing water stress.

Climatic effects on mosquito abundance in Mediterranean wetlands

PubMed Central

2014-01-01

Background The impact of climate change on vector-borne diseases is highly controversial. One of the principal points of debate is whether or not climate influences mosquito abundance, a key factor in disease transmission. Methods To test this hypothesis, we analysed ten years of data (2003–2012) from biweekly surveys to assess inter-annual and seasonal relationships between the abundance of seven mosquito species known to be pathogen vectors (West Nile virus, Usutu virus, dirofilariasis and Plasmodium sp.) and several climatic variables in two wetlands in SW Spain. Results Within-season abundance patterns were related to climatic variables (i.e. temperature, rainfall, tide heights, relative humidity and photoperiod) that varied according to the mosquito species in question. Rainfall during winter months was positively related to Culex pipiens and Ochlerotatus detritus annual abundances. Annual maximum temperatures were non-linearly related to annual Cx. pipiens abundance, while annual mean temperatures were positively related to annual Ochlerotatus caspius abundance. Finally, we modelled shifts in mosquito abundances using the A2 and B2 temperature and rainfall climate change scenarios for the period 2011–2100. While Oc. caspius, an important anthropophilic species, may increase in abundance, no changes are expected for Cx. pipiens or the salt-marsh mosquito Oc. detritus. Conclusions Our results highlight that the effects of climate are species-specific, place-specific and non-linear and that linear approaches will therefore overestimate the effect of climate change on mosquito abundances at high temperatures. Climate warming does not necessarily lead to an increase in mosquito abundance in natural Mediterranean wetlands and will affect, above all, species such as Oc. caspius whose numbers are not closely linked to rainfall and are influenced, rather, by local tidal patterns and temperatures. The final impact of changes in vector abundance on disease frequency will depend on the direct and indirect effects of climate and other parameters related to pathogen amplification and spillover on humans and other vertebrates. PMID:25030527

Exploring the new long-term (150 years) precipitation dataset in Azores archipelago

NASA Astrophysics Data System (ADS)

Hernández, Armand; Trigo, Ricardo M.; Kutiel, Haim; Valente, Maria A.; Sigró, Javier

2015-04-01

Within the scope of the two major international projects of long-term reanalysis for the 20th century coordinated by NOAA (Compo et al. 2011) and ECMWF (Hersbach et al. 2013) the IDL Institute from the University of Lisbon has digitized a large number of long-term stations records from Portugal and former Portuguese Colonies (Stickler et al. 2014). Recently we have finished the digitization of all precipitation values from Ponta Delgada (capital of the Azores archipelago) obtaining an uninterrupted precipitation monthly time series since 1864 and additionally an almost complete corresponding daily precipitation series, with the exception of some years (1864/1872; 1878/1879; 1888/1905; 1931; 1936 and 1938) for which only monthly values are available. Here, we present an annually, seasonally and daily resolution study of the rainfall regime in Ponta Delgada for the last 150 years and the North Atlantic Oscillation (NAO) influence over this precipitation regime. The distribution of precipitation presents an evident seasonal pattern, with a strong difference between the 'rainy season' (November/March) and the 'dry season' (June/August) with very little rainfall. April/May and September/October correspond to the transitional seasons. The mean annual rainfall in Ponta Delgada is approximately 910 mm and is accumulated (on average) in about 120 rainy days. The precipitation regime in Azores archipelago reveals large inter-annual and intra-annual variability and both have increased considerably in the last decades. The entire studied period (1865-2012) shows an increase in the rainfall conditions between a drier earlier period (1865-1938) and a wetter recent period (1939-2012). At daily resolution, we have used an approach based on different characteristics of rain spells (consecutive days with rainfall accumulation) that has been proved to be satisfactory for the analysis of the different parameters related to the rainfall regime (Kutiel and Trigo, 2014). This approach shows that the increase in precipitation is mainly due to more intense events which are reflected by higher rain spell yields (amount of precipitation) and rain spell intensity (amount of precipitation by day) values in the last decades. On the other hand, despite the fact that one of the most widely used NAO definitions includes sea level pressure from the Ponta Delgada station, its long-term impact on the Azores archipelago climate is not well established yet. Here, we assessed the NAO influence over the precipitation regime according to Spearman's rank correlation coefficients. Results show that the inter-annual variability of precipitation is largely modulated by the NAO mode. Correlation values of r=-0.90, r=-0.79 and r=-0.63 were obtained for years with positive (>1) or negative (

Numerical modelling assessment of climate-change impacts and mitigation measures on the Querença-Silves coastal aquifer (Algarve, Portugal)

NASA Astrophysics Data System (ADS)

Hugman, Rui; Stigter, Tibor; Costa, Luis; Monteiro, José Paulo

2017-11-01

Predicted changes in climate will lead to seawater intrusion in the Querença-Silves (QS) coastal aquifer (south Portugal) during the coming century if the current water-resource-management strategy is maintained. As for much of the Mediterranean, average rainfall is predicted to decrease along with increasing seasonal and inter-annual variability and there is a need to understand how these changes will affect the sustainable use of groundwater resources. A density-coupled flow and transport model of the QS was used to simulate an ensemble of climate, water-use and adaptation scenarios from 2010 to 2099 taking into account intra- and inter-annual variability in recharge and groundwater use. By considering several climate models, bias correction and recharge calculation methods, a degree of uncertainty was included. Changes in rainfall regimes will have an immediate effect on groundwater discharge; however, the effect on saltwater intrusion is attenuated by the freshwater-saltwater interfaces' comparatively slow rate of movement. Comparing the effects of adaptation measures demonstrates that the extent of intrusion in the QS is controlled by the long-term water budget, as the effectiveness of both demand and supply oriented measures is proportional to the change in water budget, and that to maintain the current position, average groundwater discharge should be in the order of 50 × 106 m3 yr-1.

Satellite derived estimates of forest leaf area index in South-west Western Australia are not tightly coupled to inter-annual variations in rainfall: implications for groundwater decline in a drying climate.

NASA Astrophysics Data System (ADS)

Smettem, Keith; Waring, Richard; Callow, Nik; Wilson, Melissa; Mu, Qiaozhen

2013-04-01

There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. Ecological optimality proposes that the long term average canopy size of undisturbed perennial vegetation is tightly coupled to climate. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study we analysed satellite-derived estimates of monthly LAI across forested coastal catchments of South-west Western Australia over a 12 year period (2000-2011) that included the driest year on record for the last 60 years. We observed that over the 12 year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, inter-annual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long term decline in areal average underground water storage storage and diminished summer flows, with a trend towards more ephemeral flow regimes.

Detecting the hydrological impacts of forest cover change in tropical mountain areas: need for detrending time series of rainfall and streamflow data.

NASA Astrophysics Data System (ADS)

Molina, A.; Vanacker, V.; Brisson, E.; Balthazar, V.

2012-04-01

Interactions between human activities and the physical environment have increasingly transformed the hydrological functioning of Andean ecosystems. In these human-modified landscapes, land use/-cover change may have a profound effect on riverine water and sediment fluxes. The hydrological impacts of land use/-cover change are diverse, as changes in vegetation affect the various components of the hydrological cycle including evapotranspiration, infiltration and surface runoff. Quantitative data for tropical mountain regions are scarce, as few long time series on rainfall, water discharge and land use are available. Furthermore, time series of rainfall and streamflow data in tropical mountains are often highly influenced by large inter- and intra-annual variability. In this paper, we analyse the hydrological response to complex forest cover change for a catchment of 280 km2 located in the Ecuadorian Andes. Forest cover change in the Pangor catchment was reconstructed based on airphotos (1963, 1977), LANDSAT TM (1991) and ETM+ data (2001, 2009). From 1963, natural vegetation was converted to agricultural land and pine plantations: forests decreased by a factor 2, and paramo decreased by 20 km2 between 1963 and 2009. For this catchment, there exists an exceptionally long record of rainfall and streamflow data that dates back from the '70s till now, but large variability in hydrometeorological data exists that is partly related to ENSO events. Given the nonstationary and nonlinear character of the ENSO-related changes in rainfall, we used the Hilbert-Huang transformation to detrend the time series of the river flow data from inter- and intra-annual fluctuations in rainfall. After applying adaptive data analysis based on empirical model decomposition techniques, it becomes apparent that the long-term trend in streamflow is different from the long-term trend in rainfall data. While the streamflow data show a long-term decrease in monthly flow, the rainfall data have a trend of increasing and then decreasing precipitation amounts. These results suggest that the land use changes had an important impact on the total water yield of the catchment. Interestingly, the effect of reforestation in the upper part of the catchment with its associated decrease in water yield seems to be dominant over the effect of deforestation in the lower part of the basin.

Optimization of rainfall networks using information entropy and temporal variability analysis

NASA Astrophysics Data System (ADS)

Wang, Wenqi; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-04-01

Rainfall networks are the most direct sources of precipitation data and their optimization and evaluation are essential and important. Information entropy can not only represent the uncertainty of rainfall distribution but can also reflect the correlation and information transmission between rainfall stations. Using entropy this study performs optimization of rainfall networks that are of similar size located in two big cities in China, Shanghai (in Yangtze River basin) and Xi'an (in Yellow River basin), with respect to temporal variability analysis. Through an easy-to-implement greedy ranking algorithm based on the criterion called, Maximum Information Minimum Redundancy (MIMR), stations of the networks in the two areas (each area is further divided into two subareas) are ranked during sliding inter-annual series and under different meteorological conditions. It is found that observation series with different starting days affect the ranking, alluding to the temporal variability during network evaluation. We propose a dynamic network evaluation framework for considering temporal variability, which ranks stations under different starting days with a fixed time window (1-year, 2-year, and 5-year). Therefore, we can identify rainfall stations which are temporarily of importance or redundancy and provide some useful suggestions for decision makers. The proposed framework can serve as a supplement for the primary MIMR optimization approach. In addition, during different periods (wet season or dry season) the optimal network from MIMR exhibits differences in entropy values and the optimal network from wet season tended to produce higher entropy values. Differences in spatial distribution of the optimal networks suggest that optimizing the rainfall network for changing meteorological conditions may be more recommended.

The periodicity of Plasmodium vivax and Plasmodium falciparum in Venezuela.

PubMed

Grillet, María-Eugenia; El Souki, Mayida; Laguna, Francisco; León, José Rafael

2014-01-01

We investigated the periodicity of Plasmodium vivax and P. falciparum incidence in time-series of malaria data (1990-2010) from three endemic regions in Venezuela. In particular, we determined whether disease epidemics were related to local climate variability and regional climate anomalies such as the El Niño Southern Oscillation (ENSO). Malaria periodicity was found to exhibit unique features in each studied region. Significant multi-annual cycles of 2- to about 6-year periods were identified. The inter-annual variability of malaria cases was coherent with that of SSTs (ENSO), mainly at temporal scales within the 3-6 year periods. Additionally, malaria cases were intensified approximately 1 year after an El Niño event, a pattern that highlights the role of climate inter-annual variability in the epidemic patterns. Rainfall mediated the effect of ENSO on malaria locally. Particularly, rains from the last phase of the season had a critical role in the temporal dynamics of Plasmodium. The malaria-climate relationship was complex and transient, varying in strength with the region and species. By identifying temporal cycles of malaria we have made a first step in predicting high-risk years in Venezuela. Our findings emphasize the importance of analyzing high-resolution spatial-temporal data to better understand malaria transmission dynamics. Copyright © 2013 Elsevier B.V. All rights reserved.

Sahelian rangeland response to changes in rainfall over two decades in the Gourma region, Mali

NASA Astrophysics Data System (ADS)

Hiernaux, Pierre; Mougin, Eric; Diarra, Lassine; Soumaguel, Nogmana; Lavenu, François; Tracol, Yann; Diawara, Mamadou

2009-08-01

SummaryTwenty-five rangeland sites were monitored over two decades (1984-2006) first to assess the impact of the 1983-1984 droughts on fodder resources, then to better understand ecosystem functioning and dynamics. Sites are sampled along the south-north bioclimatic gradient in Gourma (Mali), within three main edaphic situations: sandy, loamy-clay and shallow soils. In addition, three levels of grazing pressure where systematically sampled within sandy soils. Located at the northern edge of the area reached by the West African monsoon, the Gourma gradient has recorded extremes in inter-annual variations of rainfall and resulting variations in vegetation growth. Following rainfall variability, inter-annual variability of herbaceous yield increases as climate gets dryer with latitudes at least on the sandy soils sites. Local redistribution of rainfall explains the high patchiness of herbaceous vegetation, especially on shallow soils. Yet spatial heterogeneity of the vegetation does not buffer between year yield variability that increases with spatial heterogeneity. At short term, livestock grazing during the wet season affects plant growth and thus yield in direction and proportions that vary with the timing and intensity of grazing. In the longer term, grazing also impinges upon species composition in many ways. Hence, long histories of heavy grazing promote either long cycle annuals refused by livestock or else short cycle good quality feed species. Primary production is maintained or even increased in the case of refusal such as Sida cordifolia, and is lessened in the case of short cycle species such as Zornia glochidiata. These behaviours explain that the yield anomalies calculated for the rangelands on sandy soils relative to the yield of site less grazed under similar climate tend to be negative in northern Sahel where the scenario of short cycle species dominates, while yield anomalies are close to nil in centre Sahel and slightly positive in South Sahel where the refusal scenario is more frequent. Because grazing promotes short cycle species, grazed rangelands respond faster to droughts. Year to year changes in species composition are abrupt as expected from the transient soil seed stock. However, some decadal trends in species composition are identified, with a wave of pioneer species following the 1983-1984 droughts, and a more progressive diversification and return to typical Sahel flora from 1992 onwards.

Attributing Asymmetric Productivity Responses to Internal Ecosystem Dynamics and External Drivers Using Probabilistic Models

NASA Astrophysics Data System (ADS)

Parolari, A.; Goulden, M.

2017-12-01

A major challenge to interpreting asymmetric changes in ecosystem productivity is the attribution of these changes to external climate forcing or to internal ecophysiological processes that respond to these drivers (e.g., photosynthesis response to drying soil). For example, positive asymmetry in productivity can result from either positive skewness in the distribution of annual rainfall amount or from negative curvature in the productivity response to annual rainfall. To analyze the relative influences of climate and ecosystem dynamics on both positive and negative asymmetry in multi-year ANPP experiments, we use a multi-scale coupled ecosystem water-carbon model to interpret field experimental results that span gradients of rainfall skewness and ANPP response curvature. The model integrates rainfall variability, soil moisture dynamics, and net carbon assimilation from the daily to inter-annual scales. From the underlying physical basis of the model, we compute the joint probability distribution of the minimum and maximum ANPP for an annual ANPP experiment of N years. The distribution is used to estimate the likelihood that either positive or negative asymmetry will be observed in an experiment, given the annual rainfall distribution and the ANPP response curve. We estimate the total asymmetry as the mode of this joint distribution and the relative contribution attributable to rainfall skewness as the mode for a linear ANPP response curve. Applied to data from several long-term ANPP experiments, we find that there is a wide range of observed ANPP asymmetry (positive and negative) and a spectrum of contributions from internal and external factors. We identify the soil water holding capacity relative to the mean rain event depth as a critical ecosystem characteristic that controls the non-linearity of the ANPP response and positive curvature at high rainfall. Further, the seasonal distribution of rainfall is shown to control the presence or absence of negative curvature at low rainfall. Therefore, a combination of rooting depth, soil texture, and climate seasonality contribute to ANPP response curvature and its contribution to overall observed asymmetry.

A comparative modeling analysis of multiscale temporal variability of rainfall in Australia

NASA Astrophysics Data System (ADS)

Samuel, Jos M.; Sivapalan, Murugesu

2008-07-01

The effects of long-term natural climate variability and human-induced climate change on rainfall variability have become the focus of much concern and recent research efforts. In this paper, we present the results of a comparative analysis of observed multiscale temporal variability of rainfall in the Perth, Newcastle, and Darwin regions of Australia. This empirical and stochastic modeling analysis explores multiscale rainfall variability, i.e., ranging from short to long term, including within-storm patterns, and intra-annual, interannual, and interdecadal variabilities, using data taken from each of these regions. The analyses investigated how storm durations, interstorm periods, and average storm rainfall intensities differ for different climate states and demonstrated significant differences in this regard between the three selected regions. In Perth, the average storm intensity is stronger during La Niña years than during El Niño years, whereas in Newcastle and Darwin storm duration is longer during La Niña years. Increase of either storm duration or average storm intensity is the cause of higher average annual rainfall during La Niña years as compared to El Niño years. On the other hand, within-storm variability does not differ significantly between different ENSO states in all three locations. In the case of long-term rainfall variability, the statistical analyses indicated that in Newcastle the long-term rainfall pattern reflects the variability of the Interdecadal Pacific Oscillation (IPO) index, whereas in Perth and Darwin the long-term variability exhibits a step change in average annual rainfall (up in Darwin and down in Perth) which occurred around 1970. The step changes in Perth and Darwin and the switch in IPO states in Newcastle manifested differently in the three study regions in terms of changes in the annual number of rainy days or the average daily rainfall intensity or both. On the basis of these empirical data analyses, a stochastic rainfall time series model was developed that incorporates the entire range of multiscale variabilities observed in each region, including within-storm, intra-annual, interannual, and interdecadal variability. Such ability to characterize, model, and synthetically generate realistic time series of rainfall intensities is essential for addressing many hydrological problems, including estimation of flood and drought frequencies, pesticide risk assessment, and landslide frequencies.

Characteristics of aggregation of daily rainfall in a middle-latitudes region during a climate variability in annual rainfall amount

NASA Astrophysics Data System (ADS)

Lucero, Omar A.; Rozas, Daniel

Climate variability in annual rainfall occurs because the aggregation of daily rainfall changes. A topic open to debate is whether that change takes place because rainfall becomes more intense, or because it rains more often, or a combination of both. The answer to this question is of interest for water resources planning, hydrometeorological design, and agricultural management. Change in the number of rainy days can cause major disruptions in hydrological and ecological systems, with important economic and social effects. Furthermore, the characteristics of daily rainfall aggregation in ongoing climate variability provide a reference to evaluate the capability of GCM to simulate changes in the hydrologic cycle. In this research, we analyze changes in the aggregation of daily rainfall producing a climate positive trend in annual rainfall in central Argentina, in the southern middle-latitudes. This state-of-the-art agricultural region has a semiarid climate with dry and wet seasons. Weather effects in the region influence world-market prices of several crops. Results indicate that the strong positive trend in seasonal and annual rainfall amount is produced by an increase in number of rainy days. This increase takes place in the 3-month periods January-March (summer) and April-June (autumn). These are also the 3-month periods showing a positive trend in the mean of annual rainfall. The mean of the distribution of annual number of rainy day (ANRD) increased in 50% in a 36-year span (starting at 44 days/year). No statistically significant indications on time changes in the probability distribution of daily rainfall amount were found. Non-periodic fluctuations in the time series of annual rainfall were analyzed using an integral wavelet transform. Fluctuations with a time scale of about 10 and 20 years construct the trend in annual rainfall amount. These types of non-periodic fluctuations have been observed in other regions of the world. This suggests that results of this research could have further geographical validity.

Seasonal, inter-annual and decadal drivers of tree and grass productivity in an Australian tropical savanna.

NASA Astrophysics Data System (ADS)

Moore, C.; Beringer, J.; Hutley, L. B.; Evans, B. J.; Tapper, N. J.; Donohue, R. J.; Exbrayat, J. F.

2016-12-01

Tree-grass savannas are a widespread biome and are highly valued for their ecosystem services. Natural or anthropogenic shifts in the savanna tree-grass ratio have wide-reaching implications for food production, timber harvesting, biodiversity, the water cycle and carbon sequestration. It is important to understand the long-term dynamics and drivers of both tree and grass productivity separately, in order to successfully manage savannas in the future. This study investigates the inter-annual variability (IAV) of tree (overstory) and grass (understory) productivity at the Howard Springs OzFlux/Fluxnet site by combining a long-term (15 year) eddy covariance flux record and DIFFUSE model estimates of tree and grass productivity inferred from satellite remote sensing. On a seasonal basis, the primary drivers of overstory and understory productivity were solar radiation in the wet season and soil moisture in the dry season, with deeper soil layers becoming more important as the dry season progressed. On an inter-annual basis, variability in the amount of annual rainfall and length of the rainy season determined soil water availability, which had a positive effect on overstory productivity and a negative effect on understory productivity. No linear trend in the tree-grass ratio was observed over the 15-year study period, indicating that woody encroachment was not occurring to a significant degree at the study site. However, the tree-grass ratio was well correlated with modes of climate variability, namely the Southern Oscillation Index. This study has provided important insight into the long-term contributions of trees and grasses to savanna productivity, along with the respective drivers of IAV. The results will contribute towards model development and building better links with remote sensing techniques in order to more comprehensively monitor savanna structure and function across space and time.

Intra-Seasonal Rainfall Variations and Linkage with Kharif Crop Production: An Attempt to Evaluate Predictability of Sub-Seasonal Rainfall Events

NASA Astrophysics Data System (ADS)

Singh, Ankita; Ghosh, Kripan; Mohanty, U. C.

2018-03-01

The sub-seasonal variation of Indian summer monsoon rainfall highly impacts Kharif crop production in comparison with seasonal total rainfall. The rainfall frequency and intensity corresponding to various rainfall events are found to be highly related to crop production and therefore, the predictability of such events are considered to be diagnosed. Daily rainfall predictions are made available by one of the coupled dynamical model National Centers for Environmental Prediction Climate Forecast System (NCEPCFS). A large error in the simulation of daily rainfall sequence influences to take up a bias correction and for that reason, two approaches are used. The bias-corrected GCM is able to capture the inter-annual variability in rainfall events. Maximum prediction skill of frequency of less rainfall (LR) event is observed during the month of September and a similar result is also noticed for moderate rainfall event with maximum skill over the central parts of the country. On the other hand, the impact of rainfall weekly rainfall intensity is evaluated against the Kharif rice production. It is found that weekly rainfall intensity during July is having a significant impact on Kharif rice production, but the corresponding skill was found very low in GCM. The GCM are able to simulate the less and moderate rainfall frequency with significant skill.

Remote Sensing Approach to Drought Monitoring to Inform Range Management at the Hopi Tribe and Navajo Nation

NASA Astrophysics Data System (ADS)

El Vilaly, M. M.; Van Leeuwen, W. J.; Didan, K.; Marsh, S. E.; Crimmins, , M. A.

2012-12-01

The Hopi Tribe and Navajo Nation are situated in the Northeastern corner of Arizona in the Colorado River Plateau. For more than a decade, the area has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. Moreover, these persistent droughts threaten ecosystem services, agriculture, and livestock production activities, and make this region sensitive to inter-annual climate variability and change. The limited hydroclimatic observations, bolstered by numerous anecdotal drought impact reports, indicate that the region has been suffering through an almost 15-year long drought which is threatening its socio-economic development. The objective of this research is to employ remote sensing data to monitor the ongoing drought and inform management and decision-making. The overall goals of this study are to develop a common understanding of the current status of drought across the area in order to understand the existing seasonal and inter-annual relationships between climate variability and vegetation dynamics. To analyze and investigate vegetation responses to climate variability, land use practices, and environmental factors in Hopi and Navajo nation during the last 22 years, a drought assessment framework was developed that integrates climate and topographical data with land surface remote sensing time series data. Multi-sensor Normalized Difference Vegetation Index time series data were acquired from the vegetation index and phenology project (vip.arizona.edu) from 1989 to 2010 at 5.6 km, were analyzed to characterize the intra-annual changes of vegetation, seasonal phenology and inter-annual vegetation response to climate variability and environmental factors. Due to the low number of retrieval obtained from TIMESAT software, we developed a new framework that can maximize the number of retrieval. Four vegetation development stages, annual integrated NDVI (Net Primary Production (NPP)), minimum annual NDVI, maximum annual NDVI, and annual amplitude, were extracted using that new framework. A multi-linear regression has been applied to these vegetation phenology metrics as well as to the relationship between pheno-metrics and environmental variables, to detect potential vegetation changes and to examine the existing relationship between vegetation dynamics and rainfall and elevation gradients. The results suggest that vegetation behavior is foremost governed by rainfall gradients (R-square =0.74). Trend analyses confirmed that around 80 percent of pixels showed a general decline of greenness with confidence level of 95% (p< 0.05), while 4 percent showed a general greening up. Vegetation in the area showed a significant and strong relationship with elevation and precipitation gradients. This correlation was more prominent at mid-elevations, which could be explained by the snowmelt dynamics and hydrological redistribution of water at that elevation. These tools, methods and results can be used to aid in monitoring and understanding climate change and variability impacts on vegetation productivity, ecosystem services, and water resources of the region, and to inform decision-makers and range managers at Hopi Tribe and Navajo nation. Keywords: drought, remote sensing, time series, vegetation dynamics, Hopi Tribe and Navajo Nations

Influence of seasonal and inter-annual hydro-meteorological variability on surface water fecal coliform concentration under varying land-use composition.

PubMed

St Laurent, Jacques; Mazumder, Asit

2014-01-01

Quantifying the influence of hydro-meteorological variability on surface source water fecal contamination is critical to the maintenance of safe drinking water. Historically, this has not been possible due to the scarcity of data on fecal indicator bacteria (FIB). We examined the relationship between hydro-meteorological variability and the most commonly measured FIB, fecal coliform (FC), concentration for 43 surface water sites within the hydro-climatologically complex region of British Columbia. The strength of relationship was highly variable among sites, but tended to be stronger in catchments with nival (snowmelt-dominated) hydro-meteorological regimes and greater land-use impacts. We observed positive relationships between inter-annual FC concentration and hydro-meteorological variability for around 50% of the 19 sites examined. These sites are likely to experience increased fecal contamination due to the projected intensification of the hydrological cycle. Seasonal FC concentration variability appeared to be driven by snowmelt and rainfall-induced runoff for around 30% of the 43 sites examined. Earlier snowmelt in nival catchments may advance the timing of peak contamination, and the projected decrease in annual snow-to-precipitation ratio is likely to increase fecal contamination levels during summer, fall, and winter among these sites. Safeguarding drinking water quality in the face of such impacts will require increased monitoring of FIB and waterborne pathogens, especially during periods of high hydro-meteorological variability. This data can then be used to develop predictive models, inform source water protection measures, and improve drinking water treatment. Copyright © 2013 Elsevier Ltd. All rights reserved.

Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2017-01-01

Dynamical systems in nature exhibit self-similar fractal space-time fluctuations on all scales indicating long-range correlations and, therefore, the statistical normal distribution with implicit assumption of independence, fixed mean and standard deviation cannot be used for description and quantification of fractal data sets. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts the following. (1) The fractal fluctuations signify an underlying eddy continuum, the larger eddies being the integrated mean of enclosed smaller-scale fluctuations. (2) The probability distribution of eddy amplitudes and the variance (square of eddy amplitude) spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. (3) Fractal fluctuations are signatures of quantum-like chaos since the additive amplitudes of eddies when squared represent probability densities analogous to the sub-atomic dynamics of quantum systems such as the photon or electron. (4) The model predicted distribution is very close to statistical normal distribution for moderate events within two standard deviations from the mean but exhibits a fat long tail that are associated with hazardous extreme events. Continuous periodogram power spectral analyses of available GHCN annual total rainfall time series for the period 1900-2008 for Indian and USA stations show that the power spectra and the corresponding probability distributions follow model predicted universal inverse power law form signifying an eddy continuum structure underlying the observed inter-annual variability of rainfall. On a global scale, man-made greenhouse gas related atmospheric warming would result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference to possible prediction of climate change. Model concepts, if correct, rule out unambiguously, linear trends in climate. Climate change will only be manifested as increase or decrease in the natural variability. However, more stringent tests of model concepts and predictions are required before applications to such an important issue as climate change. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate (O'Gorman in Curr Clim Change Rep 1:49-59, 2015).

Projections of Rainfall and Temperature from CMIP5 Models over BIMSTEC Countries

NASA Astrophysics Data System (ADS)

Pattnayak, K. C.; Kar, S. C.; Ragi, A. R.

2014-12-01

Rainfall and surface temperature are the most important climatic variables in the context of climate change. Thus, these variables simulated from fifth phase of the Climate Model Inter-comparison Project (CMIP5) models have been compared against Climatic Research Unit (CRU) observed data and projected for the twenty first century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emission scenarios. Results for the seven countries under Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) such as Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand have been examined. Six CMIP5 models namely GFDL-CM3, GFDL-ESM2M, GFDL-ESM2G, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES have been chosen for this study. The study period has been considered is from 1861 to 2100. From this period, initial 145 years i.e. 1861 to 2005 is reference or historical period and the later 95 years i.e. 2005 to 2100 is projected period. The climate change in the projected period has been examined with respect to the reference period. In order to validate the models, the mean annual rainfall and temperature has been compared with CRU over the reference period 1901 to 2005. Comparison reveals that most of the models are able to capture the spatial distribution of rainfall and temperature over most of the regions of BIMSTEC countries. Therefore these model data can be used to study the future changes in the 21st Century. Four out six models shows that the rainfall over Central and North India, Thailand and eastern part of Myanmar shows decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka shows an increasing trend in both RCP 4.5 and 8.5 scenarios. In case of temperature, all of the models show an increasing trend over all the BIMSTEC countries in both scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. Annual cycles of rainfall and temperature over Bangladesh, Myanmar and Thailand reveals that the magnitudes are more in 2070 to 2100 of RCP8.5. Inter-model comparison show that there are large more uncertainties within the CMIP5 model projections.

Projections of Rainfall and Surface Temperature from CMIP5 Models under RCP4.5 and 8.5 over BIMSTEC Countries

NASA Astrophysics Data System (ADS)

Charan Pattnayak, Kanhu; Kar, Sarat Chandra; Kumari Pattnayak, Rashmita

2015-04-01

Rainfall and surface temperature are the most important climatic variables in the context of climate change. Thus, these variables simulated from fifth phase of the Climate Model Inter-comparison Project (CMIP5) models have been compared against Climatic Research Unit (CRU) observed data and projected for the twenty first century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emission scenarios. Results for the seven countries under Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) such as Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand have been examined. Six CMIP5 models namely GFDL-CM3, GFDL-ESM2M, GFDL-ESM2G, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES have been chosen for this study. The study period has been considered is from 1861 to 2100. From this period, initial 145 years i.e. 1861 to 2005 is reference or historical period and the later 95 years i.e. 2005 to 2100 is projected period. The climate change in the projected period has been examined with respect to the reference period. In order to validate the models, the mean annual rainfall and temperature has been compared with CRU over the reference period 1901 to 2005. Comparison reveals that most of the models are able to capture the spatial distribution of rainfall and temperature over most of the regions of BIMSTEC countries. Therefore these model data can be used to study the future changes in the 21st Century. Four out six models shows that the rainfall over Central and North India, Thailand and eastern part of Myanmar shows decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka shows an increasing trend in both RCP 4.5 and 8.5 scenarios. In case of temperature, all of the models show an increasing trend over all the BIMSTEC countries in both scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. Annual cycles of rainfall and temperature over Bangladesh, Myanmar and Thailand reveals that the magnitudes are more in 2070 to 2100 of RCP8.5. Inter-model comparison show that there are large more uncertainties within the CMIP5 model projections.

Impact of Satellite Remote Sensing Data on Simulations of ...

EPA Pesticide Factsheets

We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer (MODIS) were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability wasmissed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the

Calibrating multiple isotopic proxies in a modern aragonite speleothem from northeast India

NASA Astrophysics Data System (ADS)

Ronay, E.; Oster, J. L.; Sharp, W. D.; Marks, N.; Erhardt, A.; Breitenbach, S. F. M.

2017-12-01

Uranium, strontium, and calcium isotope ratios in calcite speleothems are used as proxies for water-soil-rock interactions and prior calcite precipitation, and thus provide information about effective rainfall amount variations, primarily in semi-arid or highly seasonal regions. However, less is known about how these proxies function in humid regions and in aragonite speleothems. In this study, we use meteorological data to calibrate (234U/238U)i and 87Sr/86Sr in a modern aragonite speleothem from northeast India, the rainiest place on Earth, to determine how these proxies reflect effective monsoon rainfall amount. MAW-0201 is an annually laminated aragonite stalagmite that grew from 1960-2013 in Mawmluh Cave, Meghalaya, India. Rainfall here is extremely seasonal due to the Indian Summer Monsoon (ISM), which brings several meters of rain to the region each summer, but with inter-annual variability in total rainfall. The δ18O in Mawmluh dripwater and speleothems reflects moisture source and transport, rather than rainfall amount. Variations in Mg, U, and Ba concentrations in MAW-0201 show seasonal and multi-annual variability. U and Mg are closely correlated, but multi-year periods show significant anti-correlation. The Mg and U distribution coefficients in calcite and aragonite indicate correlated periods are times of prior calcite precipitation (PCP) and anti-correlated periods are times of prior aragonite precipitation (PAP) in the epikarst. We use δ44/40Ca to test this hypothesis, as Ca isotopes fractionate differently during calcite and aragonite precipitation and speleothem δ44/40Ca will record unique PAP and PCP fingerprints. We propose such shifts from PCP to PAP reflect hydrologic variability and/or flow path changes, which provide a useful tool for understanding epikarst hydrology but may also be a complicating factor in speleothem-based paleoclimate interpretations. Preliminary (234U/238U)i (always <1) and 87Sr/86Sr spanning 1991-2009 each show significant variability outside of analytical error. (234U/238U)i displays a decadal trend, gradually increasing until 2000 and decreasing to the end of the record. Several years in the 87Sr/86Sr record have anomalously high values, which may reflect increased sea spray input and provide unique information on the wind component of the ISM.

Understanding litter decomposition in semiarid ecosystems: linking leaf traits, UV exposure and rainfall variability

PubMed Central

Gaxiola, Aurora; Armesto, Juan J.

2015-01-01

Differences in litter quality, microbial activity or abiotic conditions cannot fully account for the variability in decomposition rates observed in semiarid ecosystems. Here we tested the role of variation in litter quality, water supply, and UV radiation as drivers of litter decomposition in arid lands. And show that carry-over effects of litter photodegradation during dry periods can regulate decomposition during subsequent wet periods. We present data from a two-phase experiment, where we first exposed litter from a drought-deciduous and an evergreen shrub to natural UV levels during five, rainless summer months and, subsequently, in the laboratory, we assessed the carry-over effects of photodegradation on biomass loss under different irrigation treatments representing the observed range of local rainfall variation among years (15–240 mm). Photodegradation of litter in the field produced average carbon losses of 12%, but deciduous Proustia pungens lost >25%, while evergreen Porlieria chilensis less than 5%. Natural exposure to UV significantly reduced carbon-to-nitrogen and lignin:N ratios in Proustia litter but not in Porlieria. During the subsequent wet phase, remaining litter biomass was lower in Proustia than in Porlieria. Indeed UV exposure increased litter decomposition of Proustia under low and medium rainfall treatments, whereas no carry-over effects were detected under high rainfall treatment. Consequently, for deciduous Proustia carry-over effects of UV exposure were negligible under high irrigation. Litter decomposition of the evergreen Porlieria depended solely on levels of rainfall that promote microbial decomposers. Our two-phase experiment revealed that both the carry-over effects of photodegradation and litter quality, modulated by inter-annual variability in rainfall, can explain the marked differences in decomposition rates and the frequent decoupling between rainfall and litter decomposition observed in semiarid ecosystems. PMID:25852705

Understanding litter decomposition in semiarid ecosystems: linking leaf traits, UV exposure and rainfall variability.

PubMed

Gaxiola, Aurora; Armesto, Juan J

2015-01-01

Differences in litter quality, microbial activity or abiotic conditions cannot fully account for the variability in decomposition rates observed in semiarid ecosystems. Here we tested the role of variation in litter quality, water supply, and UV radiation as drivers of litter decomposition in arid lands. And show that carry-over effects of litter photodegradation during dry periods can regulate decomposition during subsequent wet periods. We present data from a two-phase experiment, where we first exposed litter from a drought-deciduous and an evergreen shrub to natural UV levels during five, rainless summer months and, subsequently, in the laboratory, we assessed the carry-over effects of photodegradation on biomass loss under different irrigation treatments representing the observed range of local rainfall variation among years (15-240 mm). Photodegradation of litter in the field produced average carbon losses of 12%, but deciduous Proustia pungens lost >25%, while evergreen Porlieria chilensis less than 5%. Natural exposure to UV significantly reduced carbon-to-nitrogen and lignin:N ratios in Proustia litter but not in Porlieria. During the subsequent wet phase, remaining litter biomass was lower in Proustia than in Porlieria. Indeed UV exposure increased litter decomposition of Proustia under low and medium rainfall treatments, whereas no carry-over effects were detected under high rainfall treatment. Consequently, for deciduous Proustia carry-over effects of UV exposure were negligible under high irrigation. Litter decomposition of the evergreen Porlieria depended solely on levels of rainfall that promote microbial decomposers. Our two-phase experiment revealed that both the carry-over effects of photodegradation and litter quality, modulated by inter-annual variability in rainfall, can explain the marked differences in decomposition rates and the frequent decoupling between rainfall and litter decomposition observed in semiarid ecosystems.

Hydroclimate temporal variability in a coastal Mediterranean watershed: the Tafna basin, North-West Algeria

NASA Astrophysics Data System (ADS)

Boulariah, Ouafik; Longobardi, Antonia; Meddi, Mohamed

2017-04-01

One of the major challenges scientists, practitioners and stakeholders are nowadays involved in, is to provide the worldwide population with reliable water supplies, protecting, at the same time, the freshwater ecosystems quality and quantity. Climate and land use changes undermine the balance between water demand and water availability, causing alteration of rivers flow regime. Knowledge of hydro-climate variables temporal and spatial variability is clearly helpful to plan drought and flood hazard mitigation strategies but also to adapt them to future environmental scenarios. The present study relates to the coastal semi-arid Tafna catchment, located in the North-West of Algeria, within the Mediterranean basin. The aim is the investigation of streamflow and rainfall indices temporal variability in six sub-basins of the large catchment Tafna, attempting to relate streamflow and rainfall changes. Rainfall and streamflow time series have been preliminary tested for data quality and homogeneity, through the coupled application of two-tailed t test, Pettitt test and Cumsum tests (significance level of 0.1, 0.05 and 0.01). Subsequently maximum annual daily rainfall and streamflow and average daily annual rainfall and streamflow time series have been derived and tested for temporal variability, through the application of the Mann Kendall and Sen's test. Overall maximum annual daily streamflow time series exhibit a negative trend which is however significant for only 30% of the station. Maximum annual daily rainfall also e exhibit a negative trend which is intend significant for the 80% of the stations. In the case of average daily annual streamflow and rainfall, the tendency for decrease in time is unclear and, in both cases, appear significant for 60% of stations.

The Influence of ENSO to the Rainfall Variability in North Sumatra Province

NASA Astrophysics Data System (ADS)

Irwandi, H.; Pusparini, N.; Ariantono, J. Y.; Kurniawan, R.; Tari, C. A.; Sudrajat, A.

2018-04-01

The El Niño Southern Oscillation (ENSO) is a global phenomenon that affects the variability of rainfall in North Sumatra. The influence of ENSO will be different for each region. This review will analyse the influence of ENSO activity on seasonal and annual rainfall variability. In this research, North Sumatra Province will be divided into 4 (four) regions based on topographical conditions, such as: East Coast (EC), East Slope (ES), Mountains (MT), and West Coast (WC). The method used was statistical and descriptive analysis. Data used in this research were rainfall data from 15 stations / climate observation posts which spread in North Sumatera region and also anomaly data of Nino 3.4 region from period 1981-2016. The results showed that the active El Niño had an effect on the decreasing the rainfall during the period of DJF, JJA and SON in East Coast, East Slope, and Mountains with the decreasing of average percentage of annual rainfall up to 7%. On the contrary, the active La Nina had an effect on the addition of rainfall during the period DJF and JJA in the East Coast and Mountains with the increasing of average percentage of annual rainfall up to 6%.

Inter-annual variability of urolithiasis epidemic from semi-arid part of Deccan Volcanic Province, India: climatic and hydrogeochemical perspectives.

PubMed

Kale, Sanjay S; Ghole, Vikram Shantaram; Pawar, N J; Jagtap, Deepak V

2014-01-01

Semi-arid Karha basin from Deccan Volcanic Province, India was investigated for inter-annual variability of urolithiasis epidemic. The number of reported urolith patient, weather station data and groundwater quality results was used to assess impact of geoenvironment on urolithiasis. Data of 7081 urolith patient were processed for epidemiological study. Gender class, age group, year-wise cases and urolith type were studied in epidemiology. Rainfall, temperature, pan evaporation and sunshine hours were used to correlate urolithiasis. Further, average values of groundwater parameters were correlated with the number of urolith episodes. A total of 52 urolith samples were collected from hospitals and analysed using FTIR technique to identify dominant urolith type in study area. Result shows that male population is more prone, age group of 20-40 is more susceptible and calcium oxalate uroliths are dominant in study area. Year-wise distribution revealed that there is steady increase in urolithiasis with inflation in drought years. In climatic parameters, hot days are significantly correlated with urolithiasis. In groundwater quality, EC, Na and F are convincingly correlated with urolith patients, which concludes the strong relation between geo-environment and urolithiasis.

Effects of climatic factors and ecosystem responses on the inter-annual variability of evapotranspiration in a coniferous plantation in subtropical China.

PubMed

Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui

2014-01-01

Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003-2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003-2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May-June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation.

Effects of Climatic Factors and Ecosystem Responses on the Inter-Annual Variability of Evapotranspiration in a Coniferous Plantation in Subtropical China

PubMed Central

Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui

2014-01-01

Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003–2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003–2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May–June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation. PMID:24465610

A sensitivity study of the coupled simulation of the Northeast Brazil rainfall variability

NASA Astrophysics Data System (ADS)

Misra, Vasubandhu

2007-06-01

Two long-term coupled ocean-land-atmosphere simulations with slightly different parameterization of the diagnostic shallow inversion clouds in the atmospheric general circulation model (AGCM) of the Center for Ocean-Land-Atmosphere Studies (COLA) coupled climate model are compared for their annual cycle and interannual variability of the northeast Brazil (NEB) rainfall variability. It is seen that the solar insolation affected by the changes to the shallow inversion clouds results in large scale changes to the gradients of the SST and the surface pressure. The latter in turn modulates the surface convergence and the associated Atlantic ITCZ precipitation and the NEB annual rainfall variability. In contrast, the differences in the NEB interannual rainfall variability between the two coupled simulations is attributed to their different remote ENSO forcing.

Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

NASA Astrophysics Data System (ADS)

Garrigues, S.; Olioso, A.; Carrer, D.; Decharme, B.; Calvet, J.-C.; Martin, E.; Moulin, S.; Marloie, O.

2015-10-01

Generic land surface models are generally driven by large-scale data sets to describe the climate, the soil properties, the vegetation dynamic and the cropland management (irrigation). This paper investigates the uncertainties in these drivers and their impacts on the evapotranspiration (ET) simulated from the Interactions between Soil, Biosphere, and Atmosphere (ISBA-A-gs) land surface model over a 12-year Mediterranean crop succession. We evaluate the forcing data sets used in the standard implementation of ISBA over France where the model is driven by the SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) high spatial resolution atmospheric reanalysis, the leaf area index (LAI) time courses derived from the ECOCLIMAP-II land surface parameter database and the soil texture derived from the French soil database. For climate, we focus on the radiations and rainfall variables and we test additional data sets which include the ERA-Interim (ERA-I) low spatial resolution reanalysis, the Global Precipitation Climatology Centre data set (GPCC) and the MeteoSat Second Generation (MSG) satellite estimate of downwelling shortwave radiations. The evaluation of the drivers indicates very low bias in daily downwelling shortwave radiation for ERA-I (2.5 W m-2) compared to the negative biases found for SAFRAN (-10 W m-2) and the MSG satellite (-12 W m-2). Both SAFRAN and ERA-I underestimate downwelling longwave radiations by -12 and -16 W m-2, respectively. The SAFRAN and ERA-I/GPCC rainfall are slightly biased at daily and longer timescales (1 and 0.5 % of the mean rainfall measurement). The SAFRAN rainfall is more precise than the ERA-I/GPCC estimate which shows larger inter-annual variability in yearly rainfall error (up to 100 mm). The ECOCLIMAP-II LAI climatology does not properly resolve Mediterranean crop phenology and underestimates the bare soil period which leads to an overall overestimation of LAI over the crop succession. The simulation of irrigation by the model provides an accurate irrigation amount over the crop cycle but the timing of irrigation occurrences is frequently unrealistic. Errors in the soil hydrodynamic parameters and the lack of irrigation in the simulation have the largest influence on ET compared to uncertainties in the large-scale climate reanalysis and the LAI climatology. Among climate variables, the errors in yearly ET are mainly related to the errors in yearly rainfall. The underestimation of the available water capacity and the soil hydraulic diffusivity induce a large underestimation of ET over 12 years. The underestimation of radiations by the reanalyses and the absence of irrigation in the simulation lead to the underestimation of ET while the overall overestimation of LAI by the ECOCLIMAP-II climatology induces an overestimation of ET over 12 years. This work shows that the key challenges to monitor the water balance of cropland at regional scale concern the representation of the spatial distribution of the soil hydrodynamic parameters, the variability of the irrigation practices, the seasonal and inter-annual dynamics of vegetation and the spatiotemporal heterogeneity of rainfall.

On the Comparison of the Global Surface Soil Moisture product and Land Surface Modeling

NASA Astrophysics Data System (ADS)

Delorme, B., Jr.; Ottlé, C.; Peylin, P.; Polcher, J.

2016-12-01

Thanks to its large spatio-temporal coverage, the new ESA CCI multi-instruments dataset offers a good opportunity to assess and improve land surface models parametrization. In this study, the ESA CCI surface soil moisture (SSM) combined product (v2.2) has been compared to the simulated top first layers of the ORCHIDEE LSM (the continental part of the IPSL earth system model), in order to evaluate its potential of improvements with data assimilation techniques. The ambition of the work was to develop a comprehensive comparison methodology by analyzing simultaneously the temporal and spatial structures of both datasets. We analyzed the SSM synoptic, seasonal, and inter-annual variations by decomposing the signals into fast and slow components. ORCHIDEE was shown to adequately reproduce the observed SSM dynamics in terms of temporal correlation. However, these correlation scores are supposed to be strongly influenced by SSM seasonal variability and the quality of the model input forcing. Autocorrelation and spectral analyses brought out disagreements in the temporal inertia of the upper soil moisture reservoirs. By linking our results to land cover maps, we found that ORCHIDEE is more dependent on rainfall events compared to the observations in regions with sparse vegetation cover. These diflerences might be due to a wrong partition of rainfall between soil evaporation, transpiration, runofl and drainage in ORCHIDEE. To refine this analysis, a single value decomposition (SVD) of the co-variability between rainfall provided by WFDEI and soil moisture was pursued over Central Europe and South Africa. It showed that spatio-temporal co-varying patterns between ORCHIDEE and rainfall and the ESA-CCI product and rainfall are in relatively good agreement. However, the leading SVD pattern, which exhibits a strong annual cycle and explains the same portion of covariance for both datasets, explains a much larger fraction of variance for ORCHIDEE than for the ESA-CCI product. These results highlight that the role of other surface variables presenting a strong seasonal variability (like vegetation cover, possibly irrigation) is not accounted for similarly in both the model and the product, and that further work is needed to explore these discrepancies.

Inter-Annual and Shorter-Term Variability in Physical and Biological Characteristics Across Barrow Canyon in August - September 2005-2014

NASA Astrophysics Data System (ADS)

Ashjian, C. J.; Okkonen, S. R.; Campbell, R. G.; Alatalo, P.

2014-12-01

Late summer physical and biological conditions along a 37-km transect crossing Barrow Canyon have been described for the past ten years as part of an ongoing program, supported by multiple funding sources including the NSF AON, focusing on inter-annual variability and the formation of a bowhead whale feeding hotspot near Barrow. These repeated transects (at least two per year, separated in time by days-weeks) provide an opportunity to assess the inter-annual and shorter term (days-weeks) changes in hydrographic structure, ocean temperature, current velocity and transport, chlorophyll fluorescence, nutrients, and micro- and mesozooplankton community composition and abundance. Inter-annual variability in all properties was high and was associated with larger scale, meteorological forcing. Shorter-term variability could also be high but was strongly influenced by changes in local wind forcing. The sustained sampling at this location provided critical measures of inter-annual variability that should permit detection of longer-term trends that are associated with ongoing climate change.

Spatial and temporal variation of rainfall trends of Sri Lanka

NASA Astrophysics Data System (ADS)

Wickramagamage, P.

2016-08-01

This study was based on daily rainfall data of 48 stations distributed over the entire island covering a 30-year period from 1981 to 2010. Data analysis was done to identify the spatial pattern of rainfall trends. The methods employed in data analysis are linear regression and interpolation by Universal Kriging and Radial Basis function. The slope of linear regression curves of 48 stations was used in interpolation. The regression coefficients show spatially and seasonally variable positive and negative trends of annual and seasonal rainfall. About half of the mean annual pentad series show negative trends, while the rest shows positive trends. By contrast, the rainfall trends of the Southwest Monsoon (SWM) season are predominantly negative throughout the country. The first phase of the Northeast Monsoon (NEM1) displays downward trends everywhere, with the exception of the Southeastern coastal area. The strongest negative trends were found in the Northeast and in the Central Highlands. The second phase (NEM2) is mostly positive, except in the Northeast. The Inter-Monsoon (IM) periods have predominantly upward trends almost everywhere, but still the trends in some parts of the Highlands and Northeast are negative. The long-term data at Watawala Nuwara Eliya and Sandringham show a consistent decline in the rainfall over the last 100 years, particularly during the SWM. There seems to be a faster decline in the rainfall in the last 3 decades. These trends are consistent with the observations in India. It is generally accepted that there has been changes in the circulation pattern. Weakening of the SWM circulation parameters caused by global warming appears to be the main causes of recent changes. Effect of the Asian Brown Cloud may also play a role in these changes.

Climate change impacts on rainfall and temperature in sugarcane growing Upper Gangetic Plains of India

NASA Astrophysics Data System (ADS)

Verma, Ram Ratan; Srivastava, Tapendra Kumar; Singh, Pushpa

2018-01-01

Assessment of variability in climate extremes is crucial for managing their aftermath on crops. Sugarcane (Saccharum officinarum L.), a major C4 crop, dominates the Upper Gangetic Plain (UGP) in India and is vulnerable to both direct and indirect effects of changes in temperature and rainfall. The present study was taken up to assess the weekly, monthly, seasonal, and annual trends of rainfall and temperature variability during the period 1956-2015 (60 years) for envisaging the probabilities of different levels of rainfall suitable for sugarcane in UGP in the present climate scenario. The analysis revealed that 87% of total annual rainfall was received during southwest monsoon months (June-September) while post-monsoon (October to February) and pre-monsoon months (March-May) accounted for only 9.4 and 3.6%, respectively. There was a decline in both monthly and annual normal rainfall during the period 1986-2015 as compared to 1956-1985, and an annual rainfall deficiency of 205.3 mm was recorded. Maximum monthly normal rainfall deficiencies of 52.8, 84.2, and 54.0 mm were recorded during the months of July, August, and September, respectively, while a minimum rainfall deficiency of 2.2 mm was observed in November. There was a decline by 196.3 mm in seasonal normal rainfall during June-September (kharif). The initial probability of a week going dry was higher (> 70%) from the 1st to the 25th week; however, standard meteorological weeks (SMW) 26 to 37 had more than 50% probability of going wet. The normal annual maximum temperature (Tmax) decreased by 0.4 °C while normal annual minimum temperatures (Tmin) increased by 0.21 °C. Analysis showed that there was an increase in frequency of drought from 1986 onwards in the zone and a monsoon rainfall deficit by about 21.25% during June-September which coincided with tillering and grand growth stage of sugarcane. The imposed drought during the growth and elongation phase is emerging as a major constraint in realizing high cane productivity in the zone. Strategies for mitigating the negative impacts of rainfall and temperature variability on sugarcane productivity through improvement in existing adaptation strategies are proposed.

The effect of El-Niño on South Asian Monsoon and agricultural production

NASA Astrophysics Data System (ADS)

Mukherjee, A.

2015-12-01

Mukherjee A, Wang S.Y.Abstract:The South Asian Monsoon has a prominent and significant impact on South Asian countries like India, Bangladesh, Nepal, Pakistan, Sri Lanka and it is one of the most studied phenomena in the world. The monsoon is historically known to be influenced by El Niño-Southern Oscillation (ENSO). The inter-annual and inter-decadal variability of seasonal precipitation over India strongly depends upon the ENSO phasing. The average southwest monsoon rainfall received during the years with El Niño was found to be less compared to normal years and the average rainfall during the northeast monsoon is higher in coastal Andhra Pradesh. ENSO is anti-correlated with Indian summer monsoon (ISM). The last prominent effect of ENSO on India's monsoon occurred in 2009 with 23% reduction in annual rainfall, reducing summer sown crops such as rice, sugar cane etc. and pushing up food prices. Climatic resources endowment plays a major role in planning agricultural production in tropical and sub-tropical environment especially under rain-fed agriculture, and so contingent crop planning drawn on this relationship would help to mitigate the effects of ENSO episodes in the region. The unexplored area in this domain of research is the changes in the frequency and intensity of ENSO due to global warming and its impact on ENSO prediction and agricultural management practices. We analyze the last 30 years datasets of Pacific SST, and precipitation and air temperature over Southeast Asia to examine the evolution of ENSO teleconnections with ISM, as well as making estimates of drought indices such as Palmer Drought Severity Index. This research can lead toward better crop management strategies in the South Asian monsoon region.

Optimal traits of plant hydraulic capacitance as an adaptation to hydroclimatic variability

NASA Astrophysics Data System (ADS)

Hartzell, S. R.; Bartlett, M. S., Jr.; Porporato, A. M.

2016-12-01

Hydraulic capacitance allows plants to uptake and store water when it is abundant. This stored water is utilized during periods of water stress, decreasing tissue damage and increasing carbon assimilation. By providing a more consistent and readily accessible water supply, it buffers water stress variability across daily and seasonal timescales. The rate of plant water storage and withdrawal varies widely between plant species and is principally governed by several plant hydraulic parameters, principally the hydraulic capacitance, the total water storage capacity, and the conductance between xylem and water storage tissue. The timescale of the plant response to changes in environmental conditions may be related to the timescale of relevant environmental variability. For example, the Baobab tree (Adansonia), which grows in an environment with very strong seasonal rainfall variability, has a relatively long timescale of hydraulic response, while an evergreen tree such as Pinus taeda, which mainly contends with daily and inter-rainfall moisture variability, has a much shorter timescale of hydraulic response. Here a model of hydraulic capacitance is coupled to a resistance model of soil-plant-atmosphere continuum. We force this model with stochastic rainfall and examine plant responses to moisture variability at various timescales. Optimal plant hydraulic properties are examined as a function of mean soil moisture (daily variability), mean period between rainfall events (inter-rainfall variability), and seasonal rainfall variability, and the relative importance of each type of variability in shaping plant water use strategies is assessed. Results are compared to typical hydraulic parameters of plants growing under specific environmental conditions. Values of hydraulic traits which optimize carbon assimilation and water use efficiency are found; these values are dependent on mean environmental conditions as well as the timescale of environmental variability.

Extreme Events in China under Climate Change: Uncertainty and related impacts (CSSP-FOREX)

NASA Astrophysics Data System (ADS)

Leckebusch, Gregor C.; Befort, Daniel J.; Hodges, Kevin I.

2016-04-01

Suitable adaptation strategies or the timely initiation of related mitigation efforts in East Asia will strongly depend on robust and comprehensive information about future near-term as well as long-term potential changes in the climate system. Therefore, understanding the driving mechanisms associated with the East Asian climate is of major importance. The FOREX project (Fostering Regional Decision Making by the Assessment of Uncertainties of Future Regional Extremes and their Linkage to Global Climate System Variability for China and East Asia) focuses on the investigation of extreme wind and rainfall related events over Eastern Asia and their possible future changes. Here, analyses focus on the link between local extreme events and their driving weather systems. This includes the coupling between local rainfall extremes and tropical cyclones, the Meiyu frontal system, extra-tropical teleconnections and monsoonal activity. Furthermore, the relation between these driving weather systems and large-scale variability modes, e.g. NAO, PDO, ENSO is analysed. Thus, beside analysing future changes of local extreme events, the temporal variability of their driving weather systems and related large-scale variability modes will be assessed in current CMIP5 global model simulations to obtain more robust results. Beyond an overview of FOREX itself, first results regarding the link between local extremes and their steering weather systems based on observational and reanalysis data are shown. Special focus is laid on the contribution of monsoonal activity, tropical cyclones and the Meiyu frontal system on the inter-annual variability of the East Asian summer rainfall.

Descriptive Statistics and Cluster Analysis for Extreme Rainfall in Java Island

NASA Astrophysics Data System (ADS)

E Komalasari, K.; Pawitan, H.; Faqih, A.

2017-03-01

This study aims to describe regional pattern of extreme rainfall based on maximum daily rainfall for period 1983 to 2012 in Java Island. Descriptive statistics analysis was performed to obtain centralization, variation and distribution of maximum precipitation data. Mean and median are utilized to measure central tendency data while Inter Quartile Range (IQR) and standard deviation are utilized to measure variation of data. In addition, skewness and kurtosis used to obtain shape the distribution of rainfall data. Cluster analysis using squared euclidean distance and ward method is applied to perform regional grouping. Result of this study show that mean (average) of maximum daily rainfall in Java Region during period 1983-2012 is around 80-181mm with median between 75-160mm and standard deviation between 17 to 82. Cluster analysis produces four clusters and show that western area of Java tent to have a higher annual maxima of daily rainfall than northern area, and have more variety of annual maximum value.

Performance of ICTP's RegCM4 in Simulating the Rainfall Characteristics over the CORDEX-SEA Domain

NASA Astrophysics Data System (ADS)

Neng Liew, Ju; Tangang, Fredolin; Tieh Ngai, Sheau; Chung, Jing Xiang; Narisma, Gemma; Cruz, Faye Abigail; Phan Tan, Van; Thanh, Ngo-Duc; Santisirisomboon, Jerasron; Milindalekha, Jaruthat; Singhruck, Patama; Gunawan, Dodo; Satyaningsih, Ratna; Aldrian, Edvin

2015-04-01

The performance of the RegCM4 in simulating rainfall variations over the Southeast Asia regions was examined. Different combinations of six deep convective parameterization schemes, namely i) Grell scheme with Arakawa-Schubert closure assumption, ii) Grell scheme with Fritch-Chappel closure assumption, iii) Emanuel MIT scheme, iv) mixed scheme with Emanuel MIT scheme over the Ocean and the Grell scheme over the land, v) mixed scheme with Grell scheme over the land and Emanuel MIT scheme over the ocean and (vi) Kuo scheme, and three ocean flux treatments were tested. In order to account for uncertainties among the observation products, four different gridded rainfall products were used for comparison. The simulated climate is generally drier over the equatorial regions and slightly wetter over the mainland Indo-China compare to the observation. However, simulation with MIT cumulus scheme used over the land area consistently produces large amplitude of positive rainfall biases, although it simulates more realistic annual rainfall variations. The simulations are found less sensitive to treatment of ocean fluxes. Although the simulations produced the rainfall climatology well, all of them simulated much stronger interannual variability compare to that of the observed. Nevertheless, the time evolution of the inter-annual variations was well reproduced particularly over the eastern part of maritime continent. Over the mainland Southeast Asia (SEA), unrealistic rainfall anomalies processes were simulated. The lacking of summer season air-sea interaction results in strong oceanic forcings over the regions, leading to positive rainfall anomalies during years with warm ocean temperature anomalies. This incurs much stronger atmospheric forcings on the land surface processes compare to that of the observed. A score ranking system was designed to rank the simulations according to their performance in reproducing different aspects of rainfall characteristics. The result suggests that the simulation with Emanuel MIT convective scheme and BATs land surface scheme produces better collective performance compare to the rest of the simulations.

Effect of inter- and intra-annual thermohaline variability on acoustic propagation

NASA Astrophysics Data System (ADS)

Chu, Peter C.; McDonald, Colleen M.; Kucukosmanoglu, Murat; Judono, Albert; Margolina, Tetyana; Fan, Chenwu

2017-05-01

This paper is to answer the question "How can inter- and intra-annual variability in the ocean be leveraged by the submarine Force?" through quantifying inter- and intra-annual variability in (T, S) fields and in turn underwater acoustic characteristics such as transmission loss, signal excess, and range of detection. The Navy's Generalized Digital Environmental Model (GDEM) is the climatological monthly mean data and represents mean annual variability. An optimal spectral decomposition method is used to produce a synoptic monthly gridded (SMG) (T, S) dataset for the world oceans with 1° ×1° horizontal resolution, 28 vertical levels (surface to 3,000 m depth), monthly time increment from January 1945 to December 2014 now available at the NOAA/NCEI website: http://data.nodc.noaa.gov/cgibin/iso?id=gov.noaa.nodc:0140938. The sound velocity decreases from 1945 to 1975 and increases afterwards due to global climate change. Effect of the inter- and intra-annual (T, S) variability on acoustic propagation in the Yellow Sea is investigated using a well-developed acoustic model (Bellhop) in frequencies from 3.5 kHz to 5 kHz with sound velocity profile (SVP) calculated from GDEM and SMG datasets, various bottom types (silty clay, fine sand, gravelly mud, sandy mud, and cobble or gravel) from the NAVOCEANO`s High Frequency Environmental Algorithms (HFEVA), source and receiver depths. Acoustic propagation ranges are extended drastically due to the inter-annual variability in comparison with the climatological SVP (from GDEM). Submarines' vulnerability of detection as its depth varies and avoidance of short acoustic range due to inter-annual variability are also discussed.

Seasonal and inter-annual variability of the net ecosystem CO2 exchange of a temperate mountain grassland: effects of climate and management.

PubMed

Wohlfahrt, Georg; Hammerle, Albin; Haslwanter, Alois; Bahn, Michael; Tappeiner, Ulrike; Cernusca, Alexander

2008-04-27

The role and relative importance of climate and cutting for the seasonal and inter-annual variability of the net ecosystem CO 2 (NEE) of a temperate mountain grassland was investigated. Eddy covariance CO 2 flux data and associated measurements of the green area index and the major environmental driving forces acquired during 2001-2006 at the study site Neustift (Austria) were analyzed. Driven by three cutting events per year which kept the investigated grassland in a stage of vigorous growth, the seasonal variability of NEE was primarily modulated by gross primary productivity (GPP). The role of environmental parameters in modulating the seasonal variability of NEE was obscured by the strong response of GPP to changes in the amount of green area, as well as the cutting-mediated decoupling of phenological development and the seasonal course of climate drivers. None of the climate and management metrics examined was able to explain the inter-annual variability of annual NEE. This is thought to result from (1) a high covariance between GPP and ecosystem respiration (R eco ) at the annual time scale which results in a comparatively small inter-annual variation of NEE, (2) compensating effects between carbon exchange during and outside the management period, and (3) changes in the biotic response to rather than the climate variables per se. GPP was more important in modulating inter-annual variations in NEE in spring and before the first and second cut, while R eco explained a larger fraction of the inter-annual variability of NEE during the remaining, in particular the post-cut, periods.

Effects of Severe Floods and Droughts on Wildlife of the Pantanal Wetland (Brazil)—A Review

PubMed Central

Alho, Cleber J. R.; Silva, João S. V.

2012-01-01

Simple Summary The Pantanal is a wetland in the center of South America, (140,000 km² in Brazil), in the Upper Paraguay River Basin. Because of its diverse and abundant wildlife, it is recognized as one of the most important freshwater ecosystems in the world. Many endangered species occur there, including jaguar; waterfowl are exceptionally abundant. Relief varies between the low, and flat floodplain, and the surrounding non-flooded plateau areas. Rainfall shows inter-annual variability, influencing the flooding patterns. Historical climate instability of severe multi-annual flood and dry events has affected animals’ habitats as well as their community structure, population size and behavioral ecology. Abstract Flooding throughout the Pantanal is seasonal. The complex vegetative cover and high seasonal productivity support a diverse and abundant fauna. A gradient in flood level supports a range of major habitats in a complex mosaic with annual seasonality. The rivers and streams are lined with gallery forests, and other arboreal habitats exist in the more elevated areas. The remainder is either grasslands or seasonally flooded grasslands. The regional flora and fauna are adapted to annual water fluctuation. However, an inter-annual series of higher or lower rainfalls has caused either severe floods or drastic dry seasons. Large scale climate phenomena such as greenhouse gases, El Niño and La Niña influence the seasonality of floods and droughts in the Pantanal. Knowledge of severe floods and droughts, which characterize natural disasters, is fundamental for wildlife management and nature conservation of the Pantanal. Plants and wild animals, for example, are affected by tree mortality in riparian forest after extreme flooding, with consequent habitat modification for wild animals. In addition, human activities are also affected since cattle ranching and ecotourism are economically important in the region, and when seasons with unusual floods or droughts occur, areas with human settlements are impacted. PMID:26487165

The response of the southwest Western Australian wave climate to Indian Ocean climate variability

NASA Astrophysics Data System (ADS)

Wandres, Moritz; Pattiaratchi, Charitha; Hetzel, Yasha; Wijeratne, E. M. S.

2018-03-01

Knowledge of regional wave climates is critical for coastal planning, management, and protection. In order to develop a regional wave climate, it is important to understand the atmospheric systems responsible for wave generation. This study examines the variability of the southwest Western Australian (SWWA) shelf and nearshore wind wave climate and its relationship to southern hemisphere climate variability represented by various atmospheric indices: the southern oscillation index (SOI), the Southern Annular Mode (SAM), the Indian Ocean Dipole Mode Index (DMI), the Indian Ocean Subtropical Dipole (IOSD), the latitudinal position of the subtropical high-pressure ridge (STRP), and the corresponding intensity of the subtropical ridge (STRI). A 21-year wave hindcast (1994-2014) of the SWWA continental shelf was created using the third generation wave model Simulating WAves Nearshore (SWAN), to analyse the seasonal and inter-annual wave climate variability and its relationship to the atmospheric regime. Strong relationships between wave heights and the STRP and the STRI, a moderate correlation between the wave climate and the SAM, and no significant correlation between SOI, DMI, and IOSD and the wave climate were found. Strong spatial, seasonal, and inter-annual variability, as well as seasonal longer-term trends in the mean wave climate were studied and linked to the latitudinal changes in the subtropical high-pressure ridge and the Southern Ocean storm belt. As the Southern Ocean storm belt and the subtropical high-pressure ridge shifted southward (northward) wave heights on the SWWA shelf region decreased (increased). The wave height anomalies appear to be driven by the same atmospheric conditions that influence rainfall variability in SWWA.

A 305-year continuous monthly rainfall series for the island of Ireland (1711-2016)

NASA Astrophysics Data System (ADS)

Murphy, Conor; Broderick, Ciaran; Burt, Timothy P.; Curley, Mary; Duffy, Catriona; Hall, Julia; Harrigan, Shaun; Matthews, Tom K. R.; Macdonald, Neil; McCarthy, Gerard; McCarthy, Mark P.; Mullan, Donal; Noone, Simon; Osborn, Timothy J.; Ryan, Ciara; Sweeney, John; Thorne, Peter W.; Walsh, Seamus; Wilby, Robert L.

2018-03-01

A continuous 305-year (1711-2016) monthly rainfall series (IoI_1711) is created for the Island of Ireland. The post 1850 series draws on an existing quality assured rainfall network for Ireland, while pre-1850 values come from instrumental and documentary series compiled, but not published by the UK Met Office. The series is evaluated by comparison with independent long-term observations and reconstructions of precipitation, temperature and circulation indices from across the British-Irish Isles. Strong decadal consistency of IoI_1711 with other long-term observations is evident throughout the annual, boreal spring and autumn series. Annually, the most recent decade (2006-2015) is found to be the wettest in over 300 years. The winter series is probably too dry between the 1740s and 1780s, but strong consistency with other long-term observations strengthens confidence from 1790 onwards. The IoI_1711 series has remarkably wet winters during the 1730s, concurrent with a period of strong westerly airflow, glacial advance throughout Scandinavia and near unprecedented warmth in the Central England Temperature record - all consistent with a strongly positive phase of the North Atlantic Oscillation. Unusually wet summers occurred in the 1750s, consistent with proxy (tree-ring) reconstructions of summer precipitation in the region. Our analysis shows that inter-decadal variability of precipitation is much larger than previously thought, while relationships with key modes of climate variability are time-variant. The IoI_1711 series reveals statistically significant multi-centennial trends in winter (increasing) and summer (decreasing) seasonal precipitation. However, given uncertainties in the early winter record, the former finding should be regarded as tentative. The derived record, one of the longest continuous series in Europe, offers valuable insights for understanding multi-decadal and centennial rainfall variability in Ireland, and provides a firm basis for benchmarking other long-term records and reconstructions of past climate. Correlation of Irish rainfall with other parts of Europe increases the utility of the series for understanding historical climate in further regions.

Vertical structure of atmospheric boundary layer over Ranchi during the summer monsoon season

NASA Astrophysics Data System (ADS)

Chandra, Sagarika; Srivastava, Nishi; Kumar, Manoj

2018-04-01

Thermodynamic structure and variability in the atmospheric boundary layer have been investigated with the help of balloon-borne GPS radiosonde over a monsoon trough station Ranchi (Lat. 23°45'N, Long. 85°43'E, India) during the summer monsoon season (June-September) for a period of 2011-2013. Virtual potential temperature gradient method is used for the determination of mixed layer height (MLH). The MLH has been found to vary in the range of 1000-1300 m during the onset, 600-900 m during the active and 1400-1750 m during the break phase of monsoon over this region. Inter-annual variations noticed in MLH could be associated with inter-annual variability in convection and rainfall prevailing over the region. Along with the MLH, the cloud layer heights are also derived from the thermodynamic profiles for the onset, active and break phases of monsoon. Cloud layer height varied a lot during different phases of the monsoon. For the determination of boundary-layer convection, thermodynamic parameter difference (δθ = θ es- θ e) between saturated equivalent potential temperature (θ es ) and equivalent potential temperature (θ e) is used. It is a good indicator of convection and indicates the intense and suppressed convection during different phases of monsoon.

The need to consider temporal variability when modelling exchange at the sediment-water interface

USGS Publications Warehouse

Rosenberry, Donald O.

2011-01-01

Most conceptual or numerical models of flows and processes at the sediment-water interface assume steady-state conditions and do not consider temporal variability. The steady-state assumption is required because temporal variability, if quantified at all, is usually determined on a seasonal or inter-annual scale. In order to design models that can incorporate finer-scale temporal resolution we first need to measure variability at a finer scale. Automated seepage meters that can measure flow across the sediment-water interface with temporal resolution of seconds to minutes were used in a variety of settings to characterize seepage response to rainfall, wind, and evapotranspiration. Results indicate that instantaneous seepage fluxes can be much larger than values commonly reported in the literature, although seepage does not always respond to hydrological processes. Additional study is needed to understand the reasons for the wide range and types of responses to these hydrologic and atmospheric events.

Distributional changes in rainfall and river flow in Sarawak, Malaysia

NASA Astrophysics Data System (ADS)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

2017-11-01

Climate change may not change the rainfall mean, but the variability and extremes. Therefore, it is required to explore the possible distributional changes of rainfall characteristics over time. The objective of present study is to assess the distributional changes in annual and northeast monsoon rainfall (November-January) and river flow in Sarawak where small changes in rainfall or river flow variability/distribution may have severe implications on ecology and agriculture. A quantile regression-based approach was used to assess the changes of scale and location of empirical probability density function over the period 1980-2014 at 31 observational stations. The results indicate that diverse variation patterns exist at all stations for annual rainfall but mainly increasing quantile trend at the lowers, and higher quantiles for the month of January and December. The significant increase in annual rainfall is found mostly in the north and central-coastal region and monsoon month rainfalls in the interior and north of Sarawak. Trends in river flow data show that changes in rainfall distribution have affected higher quantiles of river flow in monsoon months at some of the basins and therefore more flooding. The study reveals that quantile trend can provide more information of rainfall change which may be useful for climate change mitigation and adaptation planning.

Implications for water use of a shift from annual to perennial crops - A stochastic modelling approach based on a trait meta-analysis

NASA Astrophysics Data System (ADS)

Vico, Giulia; Brunsell, Nathaniel

2017-04-01

The projected population growth and changes in climate and dietary habits will further increase the pressure on water resources globally. Within precision farming, a host of technical solutions has been developed to reduce water consumption for agricultural uses. The next frontier for a more sustainable agriculture is the combination of reduced water requirements with enhanced ecosystem services. Currently, staple grains are obtained from annuals crops. A shift from annual to perennial crops has been suggested as a way to enhance ecosystem services. In fact, perennial plants, with their continuous soil cover and the higher allocation of resources to the below ground, contribute to the reduction of soil erosion and nutrient losses, while enhancing carbon sequestration in the root zone. Nevertheless, the net effect of a shift to perennial crops on water use for agriculture is still unknown, despite its relevance for the sustainability of such a shift. We explore here the implications for water management at the field- to farm-scale of a shift from annual to perennial crops, under rainfed and irrigated agriculture. A probabilistic description of the soil water balance and crop development is employed to quantify water requirements and yields and their inter-annual variability, as a function of rainfall patterns, soil and crop features. Optimal irrigation strategies are thus defined in terms of maximization of yield and minimization of required irrigation volumes and their inter-annual variability. The probabilistic model is parameterized based on an extensive meta-analysis of traits of co-generic annual and perennial species to explore the consequences for water requirements of shifting from annual to perennial crops under current and future climates. We show that the larger and more developed roots of perennial crops may allow a better exploitation of soil water resources and a reduction of yield variability with respect to annual species. At the same time, perennial crops are larger and may require adequate water supply for longer periods, thus leading to higher water requirements. Furthermore, they lead to lower yields per unit area, thus requiring irrigation of larger areas.

Animal perception of seasonal thresholds: changes in elephant movement in relation to rainfall patterns.

PubMed

Birkett, Patricia J; Vanak, Abi T; Muggeo, Vito M R; Ferreira, Salamon M; Slotow, Rob

2012-01-01

The identification of temporal thresholds or shifts in animal movement informs ecologists of changes in an animal's behaviour, which contributes to an understanding of species' responses in different environments. In African savannas, rainfall, temperature and primary productivity influence the movements of large herbivores and drive changes at different scales. Here, we developed a novel approach to define seasonal shifts in movement behaviour by examining the movements of a highly mobile herbivore (elephant; Loxodonta africana), in relation to local and regional rainfall patterns. We used speed to determine movement changes of between 8 and 14 GPS-collared elephant cows, grouped into five spatial clusters, in Kruger National Park, South Africa. To detect broad-scale patterns of movement, we ran a three-year daily time-series model for each individual (2007-2009). Piecewise regression models provided the best fit for elephant movement, which exhibited a segmented, waveform pattern over time. Major breakpoints in speed occurred at the end of the dry and wet seasons of each year. During the dry season, female elephant are constrained by limited forage and thus the distances they cover are shorter and less variable. Despite the inter-annual variability of rainfall, speed breakpoints were strongly correlated with both local and regional rainfall breakpoints across all three years. Thus, at a multi-year scale, rainfall patterns significantly affect the movements of elephant. The variability of both speed and rainfall breakpoints across different years highlights the need for an objective definition of seasonal boundaries. By using objective criteria to determine behavioural shifts, we identified a biologically meaningful indicator of major changes in animal behaviour in different years. We recommend the use of such criteria, from an animal's perspective, for delineating seasons or other extrinsic shifts in ecological studies, rather than arbitrarily fixed definitions based on convention or common practice.

GPM and TRMM Radar Vertical Profiles and Impact on Large-scale Variations of Surface Rain

NASA Astrophysics Data System (ADS)

Wang, J. J.; Adler, R. F.

2017-12-01

Previous studies by the authors using Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) data have shown that TRMM Precipitation Radar (PR) and GPM Dual-Frequency Precipitation Radar (DPR) surface rain estimates do not have corresponding amplitudes of inter-annual variations over the tropical oceans as do passive microwave observations by TRMM Microwave Imager (TMI) and GPM Microwave Imager (GMI). This includes differences in surface temperature-rainfall variations. We re-investigate these relations with the new GPM Version 5 data with an emphasis on understanding these differences with respect to the DPR vertical profiles of reflectivity and rainfall and the associated convective and stratiform proportions. For the inter-annual variation of ocean rainfall from both passive microwave (TMI and GMI) and active microwave (PR and DPR) estimates, it is found that for stratiform rainfall both TMI-PR and GMI-DPR show very good correlation. However, the correlation of GMI-DPR is much higher than TMI-PR in convective rainfall. The analysis of vertical profile of PR and DPR rainfall during the TRMM and GPM overlap period (March-August, 2014) reveals that PR and DPR have about the same rainrate at 4km and above, but PR rainrate is more than 10% lower that of DPR at the surface. In other words, it seems that convective rainfall is better defined with DPR near surface. However, even though the DPR results agree better with the passive microwave results, there still is a significant difference, which may be a result of DPR retrieval error, or inherent passive/active retrieval differences. Monthly and instantaneous GMI and DPR data need to be analyzed in details to better understand the differences.

Extreme climatic events drive mammal irruptions: regression analysis of 100-year trends in desert rainfall and temperature

PubMed Central

Greenville, Aaron C; Wardle, Glenda M; Dickman, Chris R

2012-01-01

Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra-annual rainfall had become more variable over time. Using long-term live-trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires. PMID:23170202

Spatio-temporal variability and trends of precipitation and extreme rainfall events in Ethiopia in 1980-2010

NASA Astrophysics Data System (ADS)

Gummadi, Sridhar; Rao, K. P. C.; Seid, Jemal; Legesse, Gizachew; Kadiyala, M. D. M.; Takele, Robel; Amede, Tilahun; Whitbread, Anthony

2017-12-01

This article summarizes the results from an analysis conducted to investigate the spatio-temporal variability and trends in the rainfall over Ethiopia over a period of 31 years from 1980 to 2010. The data is mostly observed station data supplemented by bias-corrected AgMERRA climate data. Changes in annual and Belg (March-May) and Kiremt (June to September) season rainfalls and rainy days have been analysed over the entire Ethiopia. Rainfall is characterized by high temporal variability with coefficient of variation (CV, %) varying from 9 to 30% in the annual, 9 to 69% during the Kiremt season and 15-55% during the Belg season rainfall amounts. Rainfall variability increased disproportionately as the amount of rainfall declined from 700 to 100 mm or less. No significant trend was observed in the annual rainfall amounts over the country, but increasing and decreasing trends were observed in the seasonal rainfall amounts in some areas. A declining trend is also observed in the number of rainy days especially in Oromia, Benishangul-Gumuz and Gambella regions. Trends in seasonal rainfall indicated a general decline in the Belg season and an increase in the Kiremt season rainfall amounts. The increase in rainfall during the main Kiremt season along with the decrease in the number of rainy days leads to an increase in extreme rainfall events over Ethiopia. The trends in the 95th-percentile rainfall events illustrate that the annual extreme rainfall events are increasing over the eastern and south-western parts of Ethiopia covering Oromia and Benishangul-Gumuz regions. During the Belg season, extreme rainfall events are mostly observed over central Ethiopia extending towards the southern part of the country while during the Kiremt season, they are observed over parts of Oromia, (covering Borena, Guji, Bali, west Harerge and east Harerge), Somali, Gambella, southern Tigray and Afar regions. Changes in the intensity of extreme rainfall events are mostly observed over south-eastern parts of Ethiopia extending to the south-west covering Somali and Oromia regions. Similar trends are also observed in the greatest 3-, 5- and 10-day rainfall amounts. Changes in the consecutive dry and wet days showed that consecutive wet days during Belg and Kiremt seasons decreased significantly in many areas in Ethiopia while consecutive dry days increased. The consistency in the trends over large spatial areas confirms the robustness of the trends and serves as a basis for understanding the projected changes in the climate. These results were discussed in relation to their significance to agriculture.

Projections of on-farm salinity in coastal Bangladesh.

PubMed

Clarke, D; Williams, S; Jahiruddin, M; Parks, K; Salehin, M

2015-06-01

This paper quantifies the expected impacts of climate change, climate variability and salinity accumulation on food production in coastal Bangladesh during the dry season. This forms part of a concerted series of actions on agriculture and salinity in Bangladesh under the UK funded Ecosystems for Poverty Alleviation programme and the British Council INSPIRE scheme. The work was undertaken by developing simulation models for soil water balances, dry season irrigation requirements and the effectiveness of the monsoon season rainfall at leaching accumulated salts. Simulations were run from 1981 to 2098 using historical climate data and a daily climate data set based on the Met Office Hadley Centre HadRM3P regional climate model. Results show that inter-seasonal and inter-annual variability are key factors that affect the viability of dry season vegetable crop growing. By the end of the 21(st) century the dry season is expected to be 2-3 weeks longer than now (2014). Monsoon rainfall amounts will remain the same or possibly slightly increase but it will occur over a slightly shorter wet season. Expectations of sea level rise and additional saline intrusion into groundwater aquifers mean that dry season irrigation water is likely to become more saline by the end of the 21(st) century. A study carried out at Barisal indicates that irrigating with water at up to 4 ppt can be sustainable. Once the dry season irrigation water quality goes above 5 ppt, the monsoon rainfall is no longer able to leach the dry season salt deposits so salt accumulation becomes significant and farm productivity will reduce by as a much as 50%, threatening the livelihoods of farmers in this region.

Rainfall erosivity and sediment load over the Poyang Lake Basin under variable climate and human activities since the 1960s

NASA Astrophysics Data System (ADS)

Gu, Chaojun; Mu, Xingmin; Gao, Peng; Zhao, Guangju; Sun, Wenyi; Yu, Qiang

2018-03-01

Accelerated soil erosion exerts adverse effects on water and soil resources. Rainfall erosivity reflects soil erosion potential driven by rainfall, which is essential for soil erosive risk assessment. This study investigated the spatiotemporal variation of rainfall erosivity and its impacts on sediment load over the largest freshwater lake basin of China (the Poyang Lake Basin, abbreviate to PYLB). The spatiotemporal variations of rainfall erosivity from 1961 to 2014 based on 57 meteorological stations were detected using the Mann-Kendall test, linear regression, and kriging interpolation method. The sequential t test analysis of regime shift (STARS) was employed to identify the abrupt changes of sediment load, and the modified double mass curve was used to assess the impacts of rainfall erosivity variability on sediment load. It was found that there was significant increase (P < 0.05) in rainfall erosivity in winter due to the significant increase in January over the last 54 years, whereas no trend in year and other seasons. Annual sediment load into the Poyang Lake (PYL) decreased significantly (P < 0.01) between 1961 and 2014, and the change-points were identified in both 1985 and 2003. It was found that take annual rainfall erosivity as the explanatory variables of the double mass curves is more reasonable than annual rainfall and erosive rainfall. The estimation via the modified double mass curve demonstrated that compared with the period before change-point (1961-1984), the changes of rainfall erosivity increased 8.0 and 2.1% of sediment load during 1985-2002 and 2003-2014, respectively. Human activities decreased 50.2 and 69.7% of sediment load during the last two periods, which indicated effects of human activities on sediment load change was much larger than that of rainfall erosivity variability in the PYLB.

Multimodel ensemble projection of precipitation in eastern China under A1B emission scenario

NASA Astrophysics Data System (ADS)

Niu, Xiaorui; Wang, Shuyu; Tang, Jianping; Lee, Dong-Kyou; Gao, Xuejie; Wu, Jia; Hong, Songyou; Gutowski, William J.; McGregor, John

2015-10-01

As part of the Regional Climate Model Intercomparison Project for Asia, future precipitation projection in China is constructed using five regional climate models (RCMs) driven by the same global climate model (GCM) of European Centre/Hamburg version 5. The simulations cover both the control climate (1978-2000) and future projection (2041-2070) under the Intergovernmental Panel on Climate Change emission scenario A1B. For the control climate, the RCMs have an advantage over the driving GCM in reproducing the summer mean precipitation distribution and the annual cycle. The biases in simulating summer precipitation mainly are caused by the deficiencies in reproducing the low-level circulation, such as the western Pacific subtropical high. In addition, large inter-RCM differences exist in the summer precipitation simulations. For the future climate, consistent and inconsistent changes in precipitation between the driving GCM and the nested RCMs are observed. Similar changes in summer precipitation are projected by RCMs over western China, but model behaviors are quite different over eastern China, which is dominated by the Asian monsoon system. The inter-RCM difference of rainfall changes is more pronounced in spring over eastern China. North China and the southern part of South China are very likely to experience less summer rainfall in multi-RCM mean (MRM) projection, while limited credibility in increased summer rainfall MRM projection over the lower reaches of the Yangtze River Basin. The inter-RCM variability is the main contributor to the total uncertainty for the lower reaches of the Yangtze River Basin and South China during 2041-2060, while lowest for Northeast China, being less than 40%.

Historical analysis of interannual rainfall variability and trends in southeastern Brazil based on observational and remotely sensed data

NASA Astrophysics Data System (ADS)

Vásquez P., Isela L.; de Araujo, Lígia Maria Nascimento; Molion, Luiz Carlos Baldicero; de Araujo Abdalad, Mariana; Moreira, Daniel Medeiros; Sanchez, Arturo; Barbosa, Humberto Alves; Rotunno Filho, Otto Corrêa

2018-02-01

The Brazilian Southeast is considered a humid region. It is also prone to landslides and floods, a result of significant increases in rainfall during spring and summer caused by the South Atlantic Convergence Zone (SACZ). Recently, however, the region has faced a striking rainfall shortage, raising serious concerns regarding water availability. The present work endeavored to explain the meteorological drought that has led to hydrological imbalance and water scarcity in the region. Hodrick-Prescott smoothing and wavelet transform techniques were applied to long-term hydrologic and sea surface temperature (SST)—based climate indices monthly time series data in an attempt to detect cycles and trends that could help explain rainfall patterns and define a framework for improving the predictability of extreme events in the region. Historical observational hydrologic datasets available include monthly precipitation amounts gauged since 1888 and 1940 and stream flow measured since the 1930s. The spatial representativeness of rain gauges was tested against gridded rainfall satellite estimates from 2000 to 2015. The analyses revealed variability in four time scale domains—infra-annual, interannual, quasi-decadal and inter-decadal or multi-decadal. The strongest oscillations periods revealed were: for precipitation—8 months, 2, 8 and 32 years; for Pacific SST in the Niño-3.4 region—6 months, 2, 8 and 35.6 years, for North Atlantic SST variability—6 months, 2, 8 and 32 years and for Pacific Decadal Oscillation (PDO) index—6.19 months, 2.04, 8.35 and 27.31 years. Other periodicities less prominent but still statistically significant were also highlighted.

Stochastic soil water balance under seasonal climates

PubMed Central

Feng, Xue; Porporato, Amilcare; Rodriguez-Iturbe, Ignacio

2015-01-01

The analysis of soil water partitioning in seasonally dry climates necessarily requires careful consideration of the periodic climatic forcing at the intra-annual timescale in addition to daily scale variabilities. Here, we introduce three new extensions to a stochastic soil moisture model which yields seasonal evolution of soil moisture and relevant hydrological fluxes. These approximations allow seasonal climatic forcings (e.g. rainfall and potential evapotranspiration) to be fully resolved, extending the analysis of soil water partitioning to account explicitly for the seasonal amplitude and the phase difference between the climatic forcings. The results provide accurate descriptions of probabilistic soil moisture dynamics under seasonal climates without requiring extensive numerical simulations. We also find that the transfer of soil moisture between the wet to the dry season is responsible for hysteresis in the hydrological response, showing asymmetrical trajectories in the mean soil moisture and in the transient Budyko's curves during the ‘dry-down‘ versus the ‘rewetting‘ phases of the year. Furthermore, in some dry climates where rainfall and potential evapotranspiration are in-phase, annual evapotranspiration can be shown to increase because of inter-seasonal soil moisture transfer, highlighting the importance of soil water storage in the seasonal context. PMID:25663808

Intra- and Inter-Annual Variability in Surface Hydrology in Northern Arizona from δ18O of Tree-Ring Cellulose

NASA Astrophysics Data System (ADS)

Whittaker, T. E.; Galewsky, J.; Scuderi, L. A.; Sharp, Z. D.

2010-12-01

The primary goal of our research is to better understand how the surface hydrology of semi-arid sites in the Southwestern U.S. is affected by the annual cycles of precipitation and evaporation. Both are tied to relative strength of the North American Monsoon, El Niño-Southern Oscillation and, on shorter timescales, the occasional passage of tropical cyclone remnants. To achieve this we aim to develop high-resolution stable oxygen isotope ratio (δ18O) profiles of tree-ring cellulose for much of the last 20 years that can be ground-truthed to direct meteorological observations. It is well documented that δ18O of alpha-cellulose extracted from wood reflects hydrological conditions of a trees’ environment at the time the tree grew. Primary controls on isotopic variability are changes in source waters and relative humidity during the growing season. We sampled rings from ≥ 10 Pinus ponderosa (Douglas) at six stands along an east-west transect across northern Arizona. Annual precipitation at these sites has a bimodal distribution with almost all annual rainfall occurring during the summer monsoon (Jul, Aug) and winter storms. At Flagstaff, in the center of our study area, monthly mean precipitation δ18O values are enriched ~6‰ during the monsoon relative to winter storms. P. ponderosa (Dougl.) rings display distinct early- and latewood bands. Earlywood typically forms using winter storm precipitation that has resided within the soil until the tree began growing and ought to reflect the isotopic composition of this water. Latewood δ18O reportedly reflect summer rainfall isotopic values. We investigate the eleven year period 1994-2004. This range encompasses the transition into the present ‘drought’, the intense 1997/98 El Niño, and the passage of the remnants of Hurricanes Nora (1997) and Javier (2004). Individual rings are sliced into subsamples of mass ~1.5 mg (yielding 3-13 samples/ring). Early isotopic data from these samples display three significant trends. First, isotopic variability in a given annual ring is closely matched at intra- and inter-tree scales in a single stand (inter-site comparisons unavailable at time of writing). Second, isotopic values demonstrate that trees growing within meters of each other do not begin/cease growing simultaneously, which has implications for low-resolution isotope cross-dating studies. Third, and most significantly, earlywood samples are consistently enriched in 18O relative to latewood samples by on average ~6‰. This result is unexpected based on the isotopic composition of local precipitation and suggests that rates of evaporative enrichment of 18O in soil and leaf moisture during the growing season vary and with significant effect. Further investigation of this phenomenon will incorporate IsoGSM model output of growing season precipitation and water vapor δ18O for the period of study.

Simulating the hydrological impacts of inter-annual and seasonal variability in land use land cover change on streamflow

NASA Astrophysics Data System (ADS)

Taxak, A. K.; Ojha, C. S. P.

2017-12-01

Land use and land cover (LULC) changes within a watershed are recognised as an important factor affecting hydrological processes and water resources. LULC changes continuously not only in long term but also on the inter-annual and season level. Changes in LULC affects the interception, storage and moisture. A widely used approach in rainfall-runoff modelling through Land surface models (LSM)/ hydrological models is to keep LULC same throughout the model running period. In long term simulations where land use change take place during the run period, using a single LULC does not represent a true picture of ground conditions could result in stationarity of model responses. The present work presents a case study in which changes in LULC are incorporated by using multiple LULC layers. LULC for the study period were created using imageries from Landsat series, Sentinal, EO-1 ALI. Distributed, physically based Variable Infiltration Capacity (VIC) model was modified to allow inclusion of LULC as a time varying variable just like climate. The Narayani basin was simulated with LULC, leaf area index (LAI), albedo and climate data for 1992-2015. The results showed that the model simulation with varied parametrization approach has a large improvement over the conventional fixed parametrization approach in terms of long-term water balance. The proposed modelling approach could improve hydrological modelling for applications like land cover change studies, water budget studies etc.

Sustainable management for rangelands in a variable climate: evidence and insights from northern Australia.

PubMed

O'Reagain, P J; Scanlan, J C

2013-03-01

Inter-annual rainfall variability is a major challenge to sustainable and productive grazing management on rangelands. In Australia, rainfall variability is particularly pronounced and failure to manage appropriately leads to major economic loss and environmental degradation. Recommended strategies to manage sustainably include stocking at long-term carrying capacity (LTCC) or varying stock numbers with forage availability. These strategies are conceptually simple but difficult to implement, given the scale and spatial heterogeneity of grazing properties and the uncertainty of the climate. This paper presents learnings and insights from northern Australia gained from research and modelling on managing for rainfall variability. A method to objectively estimate LTCC in large, heterogeneous paddocks is discussed, and guidelines and tools to tactically adjust stocking rates are presented. The possible use of seasonal climate forecasts (SCF) in management is also considered. Results from a 13-year grazing trial in Queensland show that constant stocking at LTCC was far more profitable and largely maintained land condition compared with heavy stocking (HSR). Variable stocking (VAR) with or without the use of SCF was marginally more profitable, but income variability was greater and land condition poorer than constant stocking at LTCC. Two commercial scale trials in the Northern Territory with breeder cows highlighted the practical difficulties of variable stocking and provided evidence that heavier pasture utilisation rates depress reproductive performance. Simulation modelling across a range of regions in northern Australia also showed a decline in resource condition and profitability under heavy stocking rates. Modelling further suggested that the relative value of variable v. constant stocking depends on stocking rate and land condition. Importantly, variable stocking may possibly allow slightly higher stocking rates without pasture degradation. Enterprise-level simulations run for breeder herds nevertheless show that poor economic performance can occur under constant stocking and even under variable stocking in some circumstances. Modelling and research results both suggest that a form of constrained flexible stocking should be applied to manage for climate variability. Active adaptive management and research will be required as future climate changes make managing for rainfall variability increasingly challenging.

Orographic Barriers, Rainshadows, and Earth Surface Processes in the Central Andes

NASA Astrophysics Data System (ADS)

Bookhagen, B.; Strecker, M. R.

2016-12-01

The Central Andes of NW Argentina, northern Chile, and SW Bolivia are characterized by a steep E-W topographic, climatic and environmental gradient. The first windward topographic rise in the eastern Central Andes forces high orographic rainfall and dense vegetation. In contrast, the higher-elevation areas of the windward flanks become progressively drier, until arid conditions are attained in the orogen interior. On seasonal, annual, and inter-annual timescales, large rainstorms may propagate into the semi-arid to arid high-elevation sectors and cause erosion and mass-transport processes that impact infrastructure and the natural environment. Similar to these present-day effects of climate variability the Central Andes experienced pronounced paleoclimatic changes with deeper penetration of moisture into the orogen and thus an orogenward shift of the climate gradient during Pleistocene and Holocene times, lasting several millennia. In this presentation, we demonstrate the impact of climate change on Earth surface processes at different timescales ranging from the late Pleistocene to the past decade. For millennial timescales and beyond, we rely on field observations, dating of geomorphic markers, erosion rates from cosmogenic nuclide dating, and the analysis of sedimentary archives to reconstruct past environmental conditions. For the last decades we use, satellite-derived rainfall and landcover observations, climate models, hydrometeorologic data, and riverbed-elevation changes are used to characterize environmental and atmospheric conditions. Decadal-scale climate variability shows statistically significant hydrometeorologic trends and exhibits changes of fluvial-transport magnitudes. Hydrometeorologic data, their trends and change points suggest that highest rainfall magnitudes have increased most in the past decades, resulting in large, event-driven mass-transport processes with fundamental impacts on population and infrastructure.

Drivers of inter-annual variability in C4 abundance in mixed C3-C4 grasslands

NASA Astrophysics Data System (ADS)

Griffith, D.; Ratajczak, Z.; Anderson, M.; Lind, E. M.; Still, C. J.

2016-12-01

Grassland communities tend to be dominated by either C3 or C4 grass species, as opposed to being evenly mixed. Globally, this pattern is a consequence of the crossover temperature threshold above which C4 grasses are climatically favored. However, C3-C4 distributions can also be distinctly bimodal at the landscape scale, reflecting variation in fire regime, herbivory, soils, and other factors that favor either C3 or C4 vegetation. As such, our aims were to first investigate the global controls on C3 and C4 species pools, and second to determine the magnitude of inter-annual variation in C4 grass relative abundance in mixed C3-C4 grasslands with different fire regimes, soil nitrogen, and grazing pressures. Our analyses used data from 74 globally distributed Nutrient Network sites, 30 of which are mixed C3-C4 grasslands. Each site has factorial fertilizer (NPK) and herbivore exclosure treatments in replicated blocks. To address our first goal we conducted a random forest analysis of site-level C4 relative abundances in relation to mean annual temperature and rainfall, growing season temperature (GST) and rainfall, rainfall seasonality, aridity, fire frequency and management, frost, soil fertility, and grass lineage. In order to address our second goal, we narrowed our focus to sites having mixed C3-C4 grass composition and at least five years of species composition data (16 sites). A GST of 15 °C was a good descriptor of C4 versus C3 grass dominance, although there were marked differences among specific C4 grass lineages in their distributions. For example, whether or not a site has an actively managed burn regime was a greater predictor of Andropogoneae (C4) than GST. Furthermore, in mixed C3-C4 grasslands fertilization favored C3 grasses. Our research delineates the climatic limits of mixed C3-C4 grasslands and highlights the influence of disturbance, soil, and phylogeny on C4 and C3 grass dominance.

Rainfall extremes, weather and climatic characterization over complex terrain: A data-driven approach based on signal enhancement methods and extreme value modeling

NASA Astrophysics Data System (ADS)

Pineda, Luis E.; Willems, Patrick

2017-04-01

Weather and climatic characterization of rainfall extremes is both of scientific and societal value for hydrometeorogical risk management, yet discrimination of local and large-scale forcing remains challenging in data-scarce and complex terrain environments. Here, we present an analysis framework that separate weather (seasonal) regimes and climate (inter-annual) influences using data-driven process identification. The approach is based on signal-to-noise separation methods and extreme value (EV) modeling of multisite rainfall extremes. The EV models use a semi-automatic parameter learning [1] for model identification across temporal scales. At weather scale, the EV models are combined with a state-based hidden Markov model [2] to represent the spatio-temporal structure of rainfall as persistent weather states. At climatic scale, the EV models are used to decode the drivers leading to the shift of weather patterns. The decoding is performed into a climate-to-weather signal subspace, built via dimension reduction of climate model proxies (e.g. sea surface temperature and atmospheric circulation) We apply the framework to the Western Andean Ridge (WAR) in Ecuador and Peru (0-6°S) using ground data from the second half of the 20th century. We find that the meridional component of winds is what matters for the in-year and inter-annual variability of high rainfall intensities alongside the northern WAR (0-2.5°S). There, low-level southerly winds are found as advection drivers for oceanic moist of the normal-rainy season and weak/moderate the El Niño (EN) type; but, the strong EN type and its unique moisture surplus is locally advected at lowlands in the central WAR. Moreover, the coastal ridges, south of 3°S dampen meridional airflows, leaving local hygrothermal gradients to control the in-year distribution of rainfall extremes and their anomalies. Overall, we show that the framework, which does not make any prior assumption on the explanatory power of the weather and climate drivers, allows identification of well-known features of the regional climate in a purely data-driven fashion. Thus, this approach shows potential for characterization of precipitation extremes in data-scarce and orographically complex regions in which model reconstructions are the only climate proxies References [1] Mínguez, R., F.J. Méndez, C. Izaguirre, M. Menéndez, and I.J. Losada (2010), Pseudooptimal parameter selection of non-stationary generalized extreme value models for environmental variables, Environ. Modell. Softw. 25, 1592-1607. [2] Pineda, L., P. Willems (2016), Multisite Downscaling of Seasonal Predictions to Daily Rainfall Characteristics over Pacific-Andean River Basins in Ecuador and Peru using a non-homogenous hidden Markov model, J. Hydrometeor, 17(2), 481-498, doi:10.1175/JHM-D-15-0040.1, http://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0040.1

TRMM Fire Algorithm, Product and Applications

NASA Technical Reports Server (NTRS)

Ji, Yi-Min; Stocker, Erich

2003-01-01

Land fires are frequent menaces to human lives and property. They also change the state of the vegetation and contribute to the climate forcing by releasing large amount of aerosols and greenhouse gases into the atmosphere. This paper summarizes methodologies of detecting global land fires from the Tropical Rainfall Measuring Mission (TRMM) Visible Infrared Scanner FIRS) measurements. The TRMM Science Data and Information System (TSDIS) fire products include global images of daily hot spots and monthly fire counts at 0.5 deg. x 0.5 deg. resolution, as well as text fiies that details necessary information of all fire pixels. The information includes date, orbit number, pixel number, local time, solar zenith angle, latitude, longitude, reflectance of visible/near infrared channels, brightness temperatures of infrared channels, as well as background brightness temperatures of infrared channels. These products have been archived since January 1998. The TSDIS fire products are compared with the coincidental European Commission (EC) Joint Research Center (JRC) 1 km AVHRR fire products. Analyses of the TSDIS monthly fire products during the period from 1998 to 2003 manifested seasonal cycles of biomass fires over Southeast Asia, Africa, North America and South America. The data also showed interannual variations associated with the 98/99 ENS0 cycle in Central America and the Indonesian region. In order to understand the variability of global land fires and their effects on the distribution of atmospheric aerosols, statistical methods were applied to the TSDIS fire products as well as to the Total Ozone Mapping Spectrometer (TOMS) aerosol index products for a period of five years from January 1998 to December 2002. The variability of global atmospheric aerosol is consistent with the fire variations over these regions during this period. The correlation between fire count and TOMS aerosol index is about 0.55 for fire pixels in Southeast Asia, Indonesia, and Africa. Parallel statistical analyses such as Empirical Orthogonal Function (EOF) analysis and Singular Spectrum Analysis (SSA) methods were applied to pentad TRMM fire data and TOMS aerosol data. The EOF analyses showed contrast between North and South hemispheres and also inter- continental transitions in Africa and America. EOF and SSA analyses also identified 25-60 day intra-seasonal oscillations that were superimposed on the annual cycles of both fire and aerosol data. The intra-seasonal variability of fires showed similarity of tropical rainfall oscillation modes. The TRMM fire products were also compared to the coincident TRMh4 rainfall and other rainfall products to investigate the interaction between rainfall and fire. The results indicate that the annual, interannual and intraseasonal variability of fire are dominated by global rainfall variations. However, the feedback of fire to the rainfall occurrence at regional scale for certain regions is also evident.

Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe

NASA Astrophysics Data System (ADS)

Muchuru, Shepherd; Botai, Joel O.; Botai, Christina M.; Landman, Willem A.; Adeola, Abiodun M.

2016-04-01

In this study, average monthly and annual rainfall totals recorded for the period 1970 to 2010 from a network of 13 stations across the Lake Kariba catchment area of the Zambezi river basin were analyzed in order to characterize the spatial-temporal variability of rainfall across the catchment area. In the analysis, the data were subjected to intervention and homogeneity analysis using the Cumulative Summation (CUSUM) technique and step change analysis using rank-sum test. Furthermore, rainfall variability was characterized by trend analysis using the non-parametric Mann-Kendall statistic. Additionally, the rainfall series were decomposed and the spectral characteristics derived using Cross Wavelet Transform (CWT) and Wavelet Coherence (WC) analysis. The advantage of using the wavelet-based parameters is that they vary in time and can therefore be used to quantitatively detect time-scale-dependent correlations and phase shifts between rainfall time series at various localized time-frequency scales. The annual and seasonal rainfall series were homogeneous and demonstrated no apparent significant shifts. According to the inhomogeneity classification, the rainfall series recorded across the Lake Kariba catchment area belonged to category A (useful) and B (doubtful), i.e., there were zero to one and two absolute tests rejecting the null hypothesis (at 5 % significance level), respectively. Lastly, the long-term variability of the rainfall series across the Lake Kariba catchment area exhibited non-significant positive and negative trends with coherent oscillatory modes that are constantly locked in phase in the Morlet wavelet space.

The influence of multiyear drought on the annual rainfall-runoff relationship: An Australian perspective

NASA Astrophysics Data System (ADS)

Saft, Margarita; Western, Andrew W.; Zhang, Lu; Peel, Murray C.; Potter, Nick J.

2015-04-01

Most current long-term (decadal and longer) hydrological predictions implicitly assume that hydrological processes are stationary even under changing climate. However, in practice, we suspect that changing climatic conditions may affect runoff generation processes and cause changes in the rainfall-runoff relationship. In this article, we investigate whether temporary but prolonged (i.e., of the order of a decade) shifts in rainfall result in changes in rainfall-runoff relationships at the catchment scale. Annual rainfall and runoff records from south-eastern Australia are used to examine whether interdecadal climate variability induces changes in hydrological behavior. We test statistically whether annual rainfall-runoff relationships are significantly different during extended dry periods, compared with the historical norm. The results demonstrate that protracted drought led to a significant shift in the rainfall-runoff relationship in ˜44% of the catchment-dry periods studied. The shift led to less annual runoff for a given annual rainfall, compared with the historical relationship. We explore linkages between cases where statistically significant changes occurred and potential explanatory factors, including catchment properties and characteristics of the dry period (e.g., length, precipitation anomalies). We find that long-term drought is more likely to affect transformation of rainfall to runoff in drier, flatter, and less forested catchments. Understanding changes in the rainfall-runoff relationship is important for accurate streamflow projections and to help develop adaptation strategies to deal with multiyear droughts.

Effects of ambient air temperature, humidity and rainfall on annual survival of adult little penguins Eudyptula minor in southeastern Australia

NASA Astrophysics Data System (ADS)

Ganendran, L. B.; Sidhu, L. A.; Catchpole, E. A.; Chambers, L. E.; Dann, P.

2016-08-01

Seabirds are subject to the influences of local climate variables during periods of land-based activities such as breeding and, for some species, moult; particularly if they undergo a catastrophic moult (complete simultaneous moult) as do penguins. We investigated potential relationships between adult penguin survival and land-based climate variables (ambient air temperature, humidity and rainfall) using 46 years of mark-recapture data of little penguins Eudyptula minor gathered at a breeding colony on Phillip Island in southeastern Australia. Our results showed that adult penguin survival had a stronger association with land-based climate variables during the moult period, when birds were unable to go to sea for up to 3 weeks, than during the breeding period, when birds could sacrifice breeding success in favour of survival. Annual adult survival probability was positively associated with humidity during moult and negatively associated with rainfall during moult. Prolonged heat during breeding and moult had a negative association with annual adult survival. Local climate projections suggest increasing days of high temperatures, fewer days of rainfall which will result in more droughts (and by implication, lower humidity) and more extreme rainfall events. All of these predicted climate changes are expected to have a negative impact on adult penguin survival.

Effects of ambient air temperature, humidity and rainfall on annual survival of adult little penguins Eudyptula minor in southeastern Australia.

PubMed

Ganendran, L B; Sidhu, L A; Catchpole, E A; Chambers, L E; Dann, P

2016-08-01

Seabirds are subject to the influences of local climate variables during periods of land-based activities such as breeding and, for some species, moult; particularly if they undergo a catastrophic moult (complete simultaneous moult) as do penguins. We investigated potential relationships between adult penguin survival and land-based climate variables (ambient air temperature, humidity and rainfall) using 46 years of mark-recapture data of little penguins Eudyptula minor gathered at a breeding colony on Phillip Island in southeastern Australia. Our results showed that adult penguin survival had a stronger association with land-based climate variables during the moult period, when birds were unable to go to sea for up to 3 weeks, than during the breeding period, when birds could sacrifice breeding success in favour of survival. Annual adult survival probability was positively associated with humidity during moult and negatively associated with rainfall during moult. Prolonged heat during breeding and moult had a negative association with annual adult survival. Local climate projections suggest increasing days of high temperatures, fewer days of rainfall which will result in more droughts (and by implication, lower humidity) and more extreme rainfall events. All of these predicted climate changes are expected to have a negative impact on adult penguin survival.

Relationships between Tropical Rainfall Events and Regional Annual Rainfall Anomalies

NASA Astrophysics Data System (ADS)

Painter, C.; Varble, A.; Zipser, E. J.

2016-12-01

Regional annual precipitation anomalies strongly impact the health of regional ecosystems, water resources, agriculture, and the probability of flood and drought conditions. Individual event characteristics, including rain rate, areal coverage, and stratiform fraction are also crucial in considering large-scale impacts on these resources. Therefore, forecasting individual event characteristics is important and could potentially be improved through correlation with longer and better predicted timescale environmental variables such as annual rainfall. This study examines twelve years of retrieved rainfall characteristics from the Tropical Rainfall Measuring Mission (TRMM) satellite at a 5° x 5° resolution between 35°N and 35°S, as a function of annual rainfall anomaly derived from Global Precipitation Climatology Project data. Rainfall event characteristics are derived at a system scale from the University of Utah TRMM Precipitation Features database and at a 5-km pixel scale from TRMM 2A25 products. For each 5° x 5° grid box and year, relationships between these characteristics and annual rainfall anomaly are derived. Additionally, years are separated into wet and dry groups for each grid box and are compared versus one another. Convective and stratiform rain rates, along with system area and volumetric rainfall, generally increase during wetter years, and this increase is most prominent over oceans. This is in agreement with recent studies suggesting that convective systems become larger and rainier when regional annual rainfall increases or when the climate warms. Over some land regions, on the other hand, system rain rate, volumetric rainfall, and area actually decrease as annual rainfall increases. Therefore, land and ocean regions generally exhibit different relationships. In agreement with recent studies of extreme rainfall in a changing climate, the largest and rainiest systems increase in relative size and intensity compared to average systems, and do so as a function of annual rainfall in most tropical regions. However, select land regions such as the Congo fail to follow this tendency. Changes in seasonal and diurnal cycles of PF characteristics as a function of regional annual rainfall anomaly are also analyzed.

Flood risk reduction and flow buffering as ecosystem services - Part 1: Theory on flow persistence, flashiness and base flow

NASA Astrophysics Data System (ADS)

van Noordwijk, Meine; Tanika, Lisa; Lusiana, Betha

2017-05-01

Flood damage reflects insufficient adaptation of human presence and activity to location and variability of river flow in a given climate. Flood risk increases when landscapes degrade, counteracted or aggravated by engineering solutions. Efforts to maintain and restore buffering as an ecosystem function may help adaptation to climate change, but this require quantification of effectiveness in their specific social-ecological context. However, the specific role of forests, trees, soil and drainage pathways in flow buffering, given geology, land form and climate, remains controversial. When complementing the scarce heavily instrumented catchments with reliable long-term data, especially in the tropics, there is a need for metrics for data-sparse conditions. We present and discuss a flow persistence metric that relates transmission to river flow of peak rainfall events to the base-flow component of the water balance. The dimensionless flow persistence parameter Fp is defined in a recursive flow model and can be estimated from limited time series of observed daily flow, without requiring knowledge of spatially distributed rainfall upstream. The Fp metric (or its change over time from what appears to be the local norm) matches local knowledge concepts. Inter-annual variation in the Fp metric in sample watersheds correlates with variation in the flashiness index used in existing watershed health monitoring programmes, but the relationship between these metrics varies with context. Inter-annual variation in Fp also correlates with common base-flow indicators, but again in a way that varies between watersheds. Further exploration of the responsiveness of Fp in watersheds with different characteristics to the interaction of land cover and the specific realisation of space-time patterns of rainfall in a limited observation period is needed to evaluate interpretation of Fp as an indicator of anthropogenic changes in watershed conditions.

Stationarity and Inequality from the Mississippi to the Kissimmee: Climatic Control of Temporal Patterns in Catchment Discharge and Solute Export

NASA Astrophysics Data System (ADS)

Jawitz, J. W.

2011-12-01

What are the relative contributions of climatic variability, land management, and local geomorphology in determining the temporal dynamics of streamflow and the export of solutes from watersheds to receiving water bodies? A simple analytical framework is introduced for characterizing the temporal inequality of stream discharge and solute export from catchments using Lorenz diagrams and the associated Gini coefficient. These descriptors are used to illustrate a broad range of observed flow variability with a synthesis of multi-decadal flow data from 22 rivers in Florida. The analytical framework is extended to comprehensively link variability in flows and loads to climatically-driven inputs in terms of these inequality-based metrics. Further, based on a synthesis of data from the basins of the Baltic Sea, the Mississippi River, the Kissimmee River and other tributaries to Lake Okeechobee, FL, it is shown that inter-annual variations in exported loads for geogenic constituents, and for total N and total P, are dominantly controlled by discharge. Emergence of this consistent pattern across diverse managed catchments is attributed to the anthropogenic legacy of accumulated nutrient sources generating memory, similar to ubiquitously present sources for geogenic constituents. Multi-decadal phosphorus load data from 4 of the primary tributaries to Lake Okeechobee and sodium and nitrate load data from 9 of the Hubbard Brook, NH long-term study site catchments are used to examine the relation between inequality of climatic inputs, river flows and catchment loads. The intra-annual loads to Lake Okeechobee are shown to be highly unequal, such that 90% of annual load is delivered in as little as 15% of the time. Analytic expressions are developed for measures of inequality in terms of parameters of the lognormal distribution under general conditions that include intermittency. In cases where climatic variability is high compared to that of concentrations (chemostatic conditions), such as for P in the Lake Okeechobee basin and Na in Hubbard Brook, the temporal inequality of rainfall and flow are strong surrogates for load inequality. However, in cases where variability of concentrations is high compared to that of flows (chemodynamic conditions), such as for nitrate in the Hubbard Brook catchments, load inequality is greater than rainfall or flow inequality. The measured degree of correspondence between climatic, flow, and load inequality for these data sets are shown to be well described using the general inequality framework introduced here. Important implications are that (1) variations in hydro-climatic or anthropogenic forcing can be used to robustly predict inter-annual variations in flows and loads, (2) water quality problems in receiving inland and coastal waters may persist until the accumulated storages of nutrients have been substantially depleted, and (3) remedial measures designed to intercept or capture exported flows and loads must be designed with consideration of the intra-annual inequality.

Relationships between atmospheric circulation indices and rainfall in Northern Algeria and comparison of observed and RCM-generated rainfall

NASA Astrophysics Data System (ADS)

Taibi, S.; Meddi, M.; Mahé, G.; Assani, A.

2017-01-01

This work aims, as a first step, to analyze rainfall variability in Northern Algeria, in particular extreme events, during the period from 1940 to 2010. Analysis of annual rainfall shows that stations in the northwest record a significant decrease in rainfall since the 1970s. Frequencies of rainy days for each percentile (5th, 10th, 25th, 50th, 75th, 90th, 95th, and 99th) and each rainfall interval class (1-5, 5-10, 10-20, 20-50, and ≥50 mm) do not show a significant change in the evolution of daily rainfall. The Tenes station is the only one to show a significant decrease in the frequency of rainy days up to the 75th percentile and for the 10-20-mm interval class. There is no significant change in the temporal evolution of extreme events in the 90th, 95th, and 99th percentiles. The relationships between rainfall variability and general atmospheric circulation indices for interannual and extreme event variability are moderately influenced by the El Niño-Southern Oscillation and Mediterranean Oscillation. Significant correlations are observed between the Southern Oscillation Index and annual rainfall in the northwestern part of the study area, which is likely linked with the decrease in rainfall in this region. Seasonal rainfall in Northern Algeria is affected by the Mediterranean Oscillation and North Atlantic Oscillation in the west. The ENSEMBLES regional climate models (RCMs) are assessed using the bias method to test their ability to reproduce rainfall variability at different time scales. The Centre National de Recherches Météorologiques (CNRM), Czech Hydrometeorological Institute (CHMI), Eidgenössische Technische Hochschule Zürich (ETHZ), and Forschungszentrum Geesthacht (GKSS) models yield the least biased results.

Models are likely to underestimate increase in heavy rainfall in regions with high rainfall intensity

NASA Astrophysics Data System (ADS)

Borodina, Aleksandra; Fischer, Erich M.; Knutti, Reto

2017-04-01

Model projections of heavy rainfall are uncertain. On timescales of few decades, internal variability plays an important role and therefore poses a challenge to detect robust model responses. We show that spatial aggregation across regions with intense heavy rainfall events, - defined as grid cells with high annual precipitation maxima (Rx1day), - allows to reduce the role of internal variability and thus to detect a robust signal during the historical period. This enables us to evaluate models with observational datasets and to constrain long-term projections of the intensification of heavy rainfall, i.e., to recalibrate full model ensemble consistent with observations resulting in narrower range of projections. In the regions of intense heavy rainfall, we found two present-day metrics that are related to a model's projection. The first metric is the observed relationship between the area-weighted mean of the annual precipitation maxima (Rx1day) and the global land temperatures. The second is the fraction of land exhibiting statistically significant relationships between local annual precipitation maxima (Rx1day) and global land temperatures over the historical period. The models that simulate high values in both metrics are those that are in better agreement with observations and show strong future intensification of heavy rainfall. This implies that changes in heavy rainfall are likely to be more intense than anticipated from the multi-model mean.

Climate impact on malaria in northern Burkina Faso.

PubMed

Tourre, Yves M; Vignolles, Cécile; Viel, Christian; Mounier, Flore

2017-11-27

The Paluclim project managed by the French Centre National d'Etudes Spatiales (CNES) found that total rainfall for a 3-month period is a confounding factor for the density of malaria vectors in the region of Nouna in the Sahel administrative territory of northern Burkina Faso. Following the models introduced in 1999 by Craig et al. and in 2003 by Tanser et al., a climate impact model for malaria risk (using different climate indices) was created. Several predictions of this risk at different temporal scales (i.e. seasonal, inter-annual and low-frequency) were assessed using this climate model. The main result of this investigation was the discovery of a significant link between malaria risk and low-frequency rainfall variability related to the Atlantic Multi-decadal Oscillation (AMO). This result is critical for the health information systems in this region. Knowledge of the AMO phases would help local authorities to organise preparedness and prevention of malaria, which is of particular importance in the climate change context.

Patterns of tree growth in relation to environmental variability in the tropical dry deciduous forest at Mudumalai, southern India.

PubMed

Nath, Cheryl D; Dattaraja, H S; Suresh, H S; Joshi, N V; Sukumar, R

2006-12-01

Tree diameter growth is sensitive to environmental fluctuations and tropical dry forests experience high seasonal and inter-annual environmental variation. Tree growth rates in a large permanent plot at Mudumalai, southern India, were examined for the influences of rainfall and three intrinsic factors (size, species and growth form) during three 4-year intervals over the period 1988-2000. Most trees had lowest growth during the second interval when rainfall was lowest, and skewness and kurtosis of growth distributions were reduced during this interval. Tree diameter generally explained less than 10% of growth variation and had less influence on growth than species identity or time interval. Intraspecific variation was high, yet species identity accounted for up to 16% of growth variation in the community. There were no consistent differences between canopy and understory tree growth rates; however, a few subgroups of species may potentially represent canopy and understory growth guilds. Environmentally-induced temporal variations in growth generally did not reduce the odds of subsequent survival. Growth rates appear to be strongly influenced by species identity and environmental variability in the Mudumalai dry forest. Understanding and predicting vegetation dynamics in the dry tropics thus also requires information on temporal variability in local climate.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D. C.; Kiem, A. S.

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

NASA Astrophysics Data System (ADS)

Wu, Donghai; Ciais, Philippe; Viovy, Nicolas; Knapp, Alan K.; Wilcox, Kevin; Bahn, Michael; Smith, Melinda D.; Vicca, Sara; Fatichi, Simone; Zscheischler, Jakob; He, Yue; Li, Xiangyi; Ito, Akihiko; Arneth, Almut; Harper, Anna; Ukkola, Anna; Paschalis, Athanasios; Poulter, Benjamin; Peng, Changhui; Ricciuto, Daniel; Reinthaler, David; Chen, Guangsheng; Tian, Hanqin; Genet, Hélène; Mao, Jiafu; Ingrisch, Johannes; Nabel, Julia E. S. M.; Pongratz, Julia; Boysen, Lena R.; Kautz, Markus; Schmitt, Michael; Meir, Patrick; Zhu, Qiuan; Hasibeder, Roland; Sippel, Sebastian; Dangal, Shree R. S.; Sitch, Stephen; Shi, Xiaoying; Wang, Yingping; Luo, Yiqi; Liu, Yongwen; Piao, Shilong

2018-06-01

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon-water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

Regionalization of monthly rainfall erosivity patternsin Switzerland

NASA Astrophysics Data System (ADS)

Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

2016-10-01

One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of the total annual rainfall erosivity is identified within four months only (June-September). The highest erosion risk can be expected in July, where not only rainfall erosivity but also erosivity density is high. In addition to the intra-annual temporal regime, a spatial variability of this seasonality was detectable between different regions of Switzerland. The assessment of the dynamic behavior of the R-factor is valuable for the identification of susceptible seasons and regions.

Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

NASA Astrophysics Data System (ADS)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

2017-11-01

This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

Investigating the complexity of precipitation sets within California via the fractal-multifractal method

NASA Astrophysics Data System (ADS)

Puente, Carlos E.; Maskey, Mahesh L.; Sivakumar, Bellie

2017-04-01

A deterministic geometric approach, the fractal-multifractal (FM) method, is adapted in order to encode highly intermittent daily rainfall records observed over a year. Using such a notion, this research investigates the complexity of rainfall in various stations within the State of California. Specifically, records gathered at (from South to North) Cherry Valley, Merced, Sacramento and Shasta Dam, containing 59, 116, 115 and 72 years, all ending at water year 2015, were encoded and analyzed in detail. The analysis reveals that: (a) the FM approach yields faithful encodings of all records, by years, with mean square and maximum errors in accumulated rain that are less than a mere 2% and 10%, respectively; (b) the evolution of the corresponding "best" FM parameters, allowing visualization of the inter-annual rainfall dynamics from a reduced vantage point, exhibit implicit variability that precludes discriminating between sites and extrapolating to the future; (c) the evolution of the FM parameters, restricted to specific regions within space, allows finding sensible future simulations; and (d) the rain signals at all sites may be termed "equally complex," as usage of k-means clustering and conventional phase space analysis of FM parameters yields comparable results for all sites.

Constraining continuous rainfall simulations for derived design flood estimation

NASA Astrophysics Data System (ADS)

Woldemeskel, F. M.; Sharma, A.; Mehrotra, R.; Westra, S.

2016-11-01

Stochastic rainfall generation is important for a range of hydrologic and water resources applications. Stochastic rainfall can be generated using a number of models; however, preserving relevant attributes of the observed rainfall-including rainfall occurrence, variability and the magnitude of extremes-continues to be difficult. This paper develops an approach to constrain stochastically generated rainfall with an aim of preserving the intensity-durationfrequency (IFD) relationships of the observed data. Two main steps are involved. First, the generated annual maximum rainfall is corrected recursively by matching the generated intensity-frequency relationships to the target (observed) relationships. Second, the remaining (non-annual maximum) rainfall is rescaled such that the mass balance of the generated rain before and after scaling is maintained. The recursive correction is performed at selected storm durations to minimise the dependence between annual maximum values of higher and lower durations for the same year. This ensures that the resulting sequences remain true to the observed rainfall as well as represent the design extremes that may have been developed separately and are needed for compliance reasons. The method is tested on simulated 6 min rainfall series across five Australian stations with different climatic characteristics. The results suggest that the annual maximum and the IFD relationships are well reproduced after constraining the simulated rainfall. While our presentation focusses on the representation of design rainfall attributes (IFDs), the proposed approach can also be easily extended to constrain other attributes of the generated rainfall, providing an effective platform for post-processing of stochastic rainfall generators.

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

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

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

DOE PAGES

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark; ...

2016-06-21

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

Improving uncertainty estimates: Inter-annual variability in Ireland

NASA Astrophysics Data System (ADS)

Pullinger, D.; Zhang, M.; Hill, N.; Crutchley, T.

2017-11-01

This paper addresses the uncertainty associated with inter-annual variability used within wind resource assessments for Ireland in order to more accurately represent the uncertainties within wind resource and energy yield assessments. The study was undertaken using a total of 16 ground stations (Met Eireann) and corresponding reanalysis datasets to provide an update to previous work on this topic undertaken nearly 20 years ago. The results of the work demonstrate that the previously reported 5.4% of wind speed inter-annual variability is considered to be appropriate, guidance is given on how to provide a robust assessment of IAV using available sources of data including ground stations, MERRA-2 and ERA-Interim.

Inter-annual Variability of Snowfall in the Lower Peninsula of Michigan, USA

NASA Astrophysics Data System (ADS)

Meng, L.

2016-12-01

Winter snowfall, particularly lake-effect snowfall, impacts all aspects of Michigan life in the wintertime, from motorsports and tourism to impacting the day-to-day lives of residents. Understanding the inter-annual variability of winter snowfall will provide sound basis for local community safety management and improve weather forecasting. This study attempts to understand the trend in winter snowfall and the influencing factors of winter snowfall variability in the Lower Peninsula of Michigan (LPM) using station snowfall measurements and statistical analysis. Our study demonstrates that snowfall has significantly increased from 1932 to 2015. Correlation analysis suggests that regionally average air temperatures have a strong negative relationship with snowfall in LPM. On average, approximately 27% of inter-annual variability in snowfall can be explained by regionally average air temperatures. ENSO events are also negatively related to snowfall in LPM and can explain 8% of inter-annual variability. North Atlantic Oscillation (NAO) does not have strong influence on snowfall. Composite analysis demonstrates that on annual basis, more winter snowfall occurs during the years with higher maximum ice cover (MIC) than during the years with lower MIC in Lake Michigan. Higher MIC is often associated with lower air temperatures which are negatively related to winter snowfall. This study could provide insight on future snow related climate model improvement and weather forecasting.

Reduced-complexity multi-site rainfall generation: one million years over night using the model TripleM

NASA Astrophysics Data System (ADS)

Breinl, Korbinian; Di Baldassarre, Giuliano; Girons Lopez, Marc

2017-04-01

We assess uncertainties of multi-site rainfall generation across spatial scales and different climatic conditions. Many research subjects in earth sciences such as floods, droughts or water balance simulations require the generation of long rainfall time series. In large study areas the simulation at multiple sites becomes indispensable to account for the spatial rainfall variability, but becomes more complex compared to a single site due to the intermittent nature of rainfall. Weather generators can be used for extrapolating rainfall time series, and various models have been presented in the literature. Even though the large majority of multi-site rainfall generators is based on similar methods, such as resampling techniques or Markovian processes, they often become too complex. We think that this complexity has been a limit for the application of such tools. Furthermore, the majority of multi-site rainfall generators found in the literature are either not publicly available or intended for being applied at small geographical scales, often only in temperate climates. Here we present a revised, and now publicly available, version of a multi-site rainfall generation code first applied in 2014 in Austria and France, which we call TripleM (Multisite Markov Model). We test this fast and robust code with daily rainfall observations from the United States, in a subtropical, tropical and temperate climate, using rain gauge networks with a maximum site distance above 1,000km, thereby generating one million years of synthetic time series. The modelling of these one million years takes one night on a recent desktop computer. In this research, we first start the simulations with a small station network of three sites and progressively increase the number of sites and the spatial extent, and analyze the changing uncertainties for multiple statistical metrics such as dry and wet spells, rainfall autocorrelation, lagged cross correlations and the inter-annual rainfall variability. Our study contributes to the scientific community of earth sciences and the ongoing debate on extreme precipitation in a changing climate by making a stable, and very easily applicable, multi-site rainfall generation code available to the research community and providing a better understanding of the performance of multi-site rainfall generation depending on spatial scales and climatic conditions.

Soil Water Balance and Vegetation Dynamics in two Water-limited Mediterranean Ecosystem on Sardinia under past and future climate change

NASA Astrophysics Data System (ADS)

Corona, R.; Montaldo, N.; Albertson, J. D.

2016-12-01

Water limited conditions strongly impacts soil and vegetation dynamics in Mediterranean regions, which are commonly heterogeneous ecosystems, characterized by inter-annual rainfall variability, topography variability and contrasting plant functional types (PFTs) competing for water use. Historical human influences (e.g., deforestation, urbanization) further altered these ecosystems. Sardinia island is a representative region of Mediterranean ecosystems. It is low urbanized except some plan areas close to the main cities where main agricultural activities are concentrated. Two contrasting case study sites are within the Flumendosa river basin (1700 km2). The first site is a typical grassland on an alluvial plan valley (soil depth > 2m) while the second is a patchy mixture of Mediterranean vegetation species (mainly wild olive trees and C3 herbaceous) that grow in a soil bounded from below by a rocky layer of basalt, partially fractured (soil depth 15 - 40 cm). In both sites land-surface fluxes and CO2 fluxes are estimated by the eddy correlation technique while soil moisture was continuously estimated with water content reflectometers, and periodically leaf area index (LAI) was estimated. The following objectives are addressed:1) pointing out the dynamics of land surface fluxes, soil moisture, CO2 and vegetation cover for two contrasting water-limited ecosystems; 2) assess the impact of the soil depth and type on the CO2 and water balance dynamics; 3) evaluate the impact of past and future climate change scenarios on the two contrasting ecosystems. For reaching the objectives an ecohydrologic model that couples a vegetation dynamic model (VDM), and a 3-component (bare soil, grass and woody vegetation) land surface model (LSM) has been used. Historical meteorological data are available from 1922 and hydro-meteorological scenarios are then generated using a weather generator. The VDM-LSM model predict soil water balance and vegetation dynamics for the generated hydrometeorological scenarios in the two contrasting ecosystems. Results demonstrate that vegetation dynamics are influenced by the inter-annual variability of atmospheric forcing, with vegetation density changing significantly according to seasonal rainfall amount. At the same time the vegetation dynamics affect the soil water balance.

Intra-seasonal rainfall variability during the maize growing season in the northern lowlands of Lesotho

NASA Astrophysics Data System (ADS)

Tongwane, Mphethe Isaac; Moeletsi, Mokhele Edmond

2015-05-01

Intra-seasonal rainfall distribution was identified as a priority gap that needs to be addressed for southern Africa to cope with agro-meteorological risks. The region in the northwest of Lesotho is appropriate for crop cultivation due to its relatively favourable climatic conditions and soils. High rainfall variability is often blamed for poor agricultural production in this region. This study aims to determine the onset of rains, cessation of rains and rainy season duration using historical climate data. Temporal variability of these rainy season characteristics was also investigated. The earliest and latest onset dates of the rainy season are during the last week of October at Butha-Buthe and the third week of November at Mapoteng, respectively. Cessation of the season is predominantly in the first week of April making the season approximately 137-163 days long depending on the location. Average seasonal rainfall ranged from 474 mm at Mapoteng to 668 mm at Butha-Buthe. Onset and cessation of the rainfall season vary by 4-7 weeks and 1 week, respectively. Mean coefficient of variation of seasonal rainfall is 39 %, but monthly variations are higher. These variations make annual crop management and planning difficult each year. Trends show a decrease in the rainfall amounts but improvements in both the temporal distribution of annual rainfall, onset and cessation dates.

Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

NASA Astrophysics Data System (ADS)

Mandal, S.; Choudhury, B. U.

2015-07-01

Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.

Alluvial groundwater recharge estimation in semi-arid environment using remotely sensed data

NASA Astrophysics Data System (ADS)

Coelho, Victor Hugo R.; Montenegro, Suzana; Almeida, Cristiano N.; Silva, Bernardo B.; Oliveira, Leidjane M.; Gusmão, Ana Cláudia V.; Freitas, Emerson S.; Montenegro, Abelardo A. A.

2017-05-01

Data limitations on groundwater (GW) recharge over large areas are still a challenge for efficient water resource management, especially in semi-arid regions. Thus, this study seeks to integrate hydrological cycle variables from satellite imagery to estimate the spatial distribution of GW recharge in the Ipanema river basin (IRB), which is located in the State of Pernambuco in Northeast Brazil. Remote sensing data, including monthly maps (2011-2012) of rainfall, runoff and evapotranspiration, are used as input for the water balance method within Geographic Information Systems (GIS). Rainfall data are derived from the TRMM Multi-satellite Precipitation Analysis (TMPA) Version 7 (3B43V7) product and present the same monthly average temporal distributions from 15 rain gauges that are distributed over the study area (r = 0.93 and MAE = 12.7 mm), with annual average estimates of 894.3 (2011) and 300.7 mm (2012). The runoff from the Natural Resources Conservation Service (NRCS) method, which is based on regional soil information and Thematic Mapper (TM) sensor image, represents 29% of the TMPA rainfall that was observed across two years of study. Actual evapotranspiration data, which were provided by the SEBAL application of MODIS images, present annual averages of 1213 (2011) and 1067 (2012) mm. The water balance results reveal a large inter-annual difference in the IRB GW recharge, which is characterized by different rainfall regimes, with averages of 30.4 (2011) and 4.7 (2012) mm year-1. These recharges were mainly observed between January and July in regions with alluvial sediments and highly permeable soils. The GW recharge approach with remote sensing is compared to the WTF (Water Table Fluctuation) method, which is used in an area of alluvium in the IRB. The estimates from these two methods exhibit reliable annual agreement, with average values of 154.6 (WTF) and 124.6 (water balance) mm in 2011. These values correspond to 14.89 and 13.53% of the rainfall that was recorded at the rain gauges and the TMPA, respectively. Only the WTF method indicates a very low recharge of 15.9 mm for the second year. The values in this paper provide reliable insight regarding the use of remotely sensed data to evaluate the rates of alluvial GW recharge in regions where the potential runoff cannot be disregarded from WB equation and must be calculated spatially.

Variability and predictability of decadal mean temperature and precipitation over China in the CCSM4 last millennium simulation

NASA Astrophysics Data System (ADS)

Ying, Kairan; Frederiksen, Carsten S.; Zheng, Xiaogu; Lou, Jiale; Zhao, Tianbao

2018-02-01

The modes of variability that arise from the slow-decadal (potentially predictable) and intra-decadal (unpredictable) components of decadal mean temperature and precipitation over China are examined, in a 1000 year (850-1850 AD) experiment using the CCSM4 model. Solar variations, volcanic aerosols, orbital forcing, land use, and greenhouse gas concentrations provide the main forcing and boundary conditions. The analysis is done using a decadal variance decomposition method that identifies sources of potential decadal predictability and uncertainty. The average potential decadal predictabilities (ratio of slow-to-total decadal variance) are 0.62 and 0.37 for the temperature and rainfall over China, respectively, indicating that the (multi-)decadal variations of temperature are dominated by slow-decadal variability, while precipitation is dominated by unpredictable decadal noise. Possible sources of decadal predictability for the two leading predictable modes of temperature are the external radiative forcing, and the combined effects of slow-decadal variability of the Arctic oscillation (AO) and the Pacific decadal oscillation (PDO), respectively. Combined AO and PDO slow-decadal variability is associated also with the leading predictable mode of precipitation. External radiative forcing as well as the slow-decadal variability of PDO are associated with the second predictable rainfall mode; the slow-decadal variability of Atlantic multi-decadal oscillation (AMO) is associated with the third predictable precipitation mode. The dominant unpredictable decadal modes are associated with intra-decadal/inter-annual phenomena. In particular, the El Niño-Southern Oscillation and the intra-decadal variability of the AMO, PDO and AO are the most important sources of prediction uncertainty.

The impact of inter-annual variability of annual cycle on long-term persistence of surface air temperature in long historical records

NASA Astrophysics Data System (ADS)

Deng, Qimin; Nian, Da; Fu, Zuntao

2018-02-01

Previous studies in the literature show that the annual cycle of surface air temperature (SAT) is changing in both amplitude and phase, and the SAT departures from the annual cycle are long-term correlated. However, the classical definition of temperature anomalies is based on the assumption that the annual cycle is constant, which contradicts the fact of changing annual cycle. How to quantify the impact of the changing annual cycle on the long-term correlation of temperature anomaly variability still remains open. In this paper, a recently developed data adaptive analysis tool, the nonlinear mode decomposition (NMD), is used to extract and remove time-varying annual cycle to reach the new defined temperature anomalies in which time-dependent amplitude of annual cycle has been considered. By means of detrended fluctuation analysis, the impact induced by inter-annual variability from the time-dependent amplitude of annual cycle has been quantified on the estimation of long-term correlation of long historical temperature anomalies in Europe. The results show that the classical climatology annual cycle is supposed to lack inter-annual fluctuation which will lead to a maximum artificial deviation centering around 600 days. This maximum artificial deviation is crucial to defining the scaling range and estimating the long-term persistence exponent accurately. Selecting different scaling range could lead to an overestimation or underestimation of the long-term persistence exponent. By using NMD method to extract the inter-annual fluctuations of annual cycle, this artificial crossover can be weakened to extend a wider scaling range with fewer uncertainties.

Volcanic forcing of the North Atlantic Oscillation over the last 2,000 years

NASA Astrophysics Data System (ADS)

Breitenbach, Sebastian F. M.; Ridley, Harriet E.; Lechleitner, Franziska A.; Asmerom, Yemane; Rehfeld, Kira; Prufer, Keith M.; Kennett, Douglas J.; Aquino, Valorie V.; Polyak, Victor; Goswami, Bedartha; Marwan, Norbert; Haug, Gerald H.; Baldini, James U. L.

2015-04-01

The North Atlantic Oscillation (NAO) is a principal mode of atmospheric circulation in the North Atlantic realm (Hurrell et al. 2003) and influences rainfall distribution over Europe, North Africa and North America. Although observational data inform us on multi-annual variability of the NAO, long and detailed paleoclimate datasets are required to understand the mechanisms and full range of its variability and the spatial extent of its influence. Chronologies of available proxy-based NAO reconstructions are often interdependent and cover only the last ~1,100 years, while longer records are characterized by low sampling resolution and chronological constraints. This complicates the reconstruction of regional responses to NAO changes. We present data from a 2,000 year long sub-annual carbon isotope record from speleothem YOK-I from Yok Balum Cave, Belize, Central America. YOK-I has been extensively dated using U-series (Kennett et al. 2012). Monitoring shows that stalagmite δ13C in Yok Balum cave is governed by infiltration changes associated with tropical wet season rainfall. Higher (lower) δ13C values reflect drier (wetter) conditions related to Intertropical Convergence Zone position and trade winds intensity. Comparison with NAO reconstructions (Proctor et al. 2000, Trouet et al. 2009, Wassenburg et al. 2013) reveals that YOK-I δ13C sensitively records NAO-related rainfall dynamics over Belize. The Median Absolute Deviation (MAD) of δ13C extends NAO reconstructions to the last 2,000 years and indicates that high latitude volcanic aerosols force negative NAO phases. We infer that volcanic aerosols modify inter-hemispheric temperature contrasts at multi-annual scale, resulting in meridional relocation of the ITCZ and the Bermuda-Azores High, altering NAO and tropical rainfall patterns. Decade-long dry periods in the 11th and the late 18th century relate to major high northern latitude eruptions and exemplify the climatic response to volcanic forcing by reorganization of atmospheric circulation over the North Atlantic. References Hurrell et al. (2003) An Overview of the North Atlantic Oscillation. Geophys. Monogr. 134 Kennett & Breitenbach et al. (2012) Development and Disintegration of Maya Political Systems in Response to Climate Change. Science 338, 788-791 Proctor et al. (2000) A thousand year speleothem proxy record of North Atlantic climate from Scotland. Clim. Dyn. 16, 815-820 Trouet et al. (2009) Persistent Positive North Atlantic Oscillation Mode Dominated the Medieval Climate Anomaly. Science 324, 78-80 Wassenburg et al. (2013) Moroccan speleothem and tree ring records suggest a variable positive state of the North Atlantic Oscillation during the Medieval Warm Period. Earth Planet. Sci. Lett. 375, 291-302

Hydroclimatic influences on non-stationary transit time distributions in a boreal headwater catchment

NASA Astrophysics Data System (ADS)

Peralta-Tapia, A.; Soulsby, C.; Tetzlaff, D.; Sponseller, R.; Bishop, K.; Laudon, H.

2016-12-01

Understanding how water moves through catchments - from the time it enters as precipitation to when it exits via streamflow - is of fundamental importance to understanding hydrological and biogeochemical processes. A basic descriptor of this routing is the Transit Time Distribution (TTD) which is derived from the input-output behavior of conservative tracers, the mean of which represents the average time elapsed between water molecules entering and exiting a flow system. In recent decades, many transit time studies have been conducted, but few of these have focused on snow-dominated catchments. We assembled a 10-year time series of isotopic data (δ18O and δ2H) for precipitation and stream water to estimate the characteristics of the transit time distribution in a boreal catchment in northern Sweden. We applied lumped parameter models using a gamma distribution to calculate the Mean Transit Time (MTT) of water over the entire period of record and to evaluate how inter-annual differences in transit times relate to hydroclimatic variability. The best fit MTT for the complete 10-year period was 650 days (Nash-Sutcliff Efficiency = 0.65), while the best fit inter-annual MTT ranged from 300 days up to 1200 days. Whilst there was a weak negative correlation between mean annual total precipitation and the annual MTT, this relationship was stronger (r2 = 0.53, p = 0.02) for the annual rain water input. This strong connection between the MTT and annual rainfall, rather than snowmelt, has strong implications for understanding future hydrological and biogeochemical processes in boreal regions, given that predicted warmer winters would translate into a greater proportion of precipitation falling as rain and thus shorter MTT in catchments. Such a change could have direct implications for the export of solutes and pollutants.

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.

Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

NASA Astrophysics Data System (ADS)

Santos, Monica; Fragoso, Marcelo

2010-05-01

Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude, latitude, distance from sea and distance to the highest orographic barrier) on the rainfall behaviours described by the studied variables. The techniques of spatial interpolation evaluated include univariate and multivariate methods: cokriging, kriging, IDW (inverse distance weighted) and multiple linear regression. Validation procedures were used, assessing the estimated errors in the analysis of descriptive statistics of the models. Multiple linear regression models produced satisfactory results in relation to 70% of the rainfall parameters, suggested by lower average percentage of error. However, the results also demonstrates that there is no an unique and ideal model, depending on the rainfall parameter in consideration. Probably, the unsatisfactory results obtained in relation to some rainfall parameters was motivated by constraints as the spatial complexity of the precipitation patterns, as well as to the deficient spatial coverage of the territory by the rain-gauges network. References Diodato, N. (2005). The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain. Internacional Journal of Climatology, 25(3), 351-363. Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228, 113 - 129.

Characterizing 40-years of inter-regional migration in Southern Mauritania as a result of environmental changes

NASA Astrophysics Data System (ADS)

Salam El Vilaly, Mohamed Abd; El Vilaly, Audra; Mahe, Gil

2017-04-01

Formerly a country of nomadism par excellence, Mauritania has experienced since its independence in 1960 a spectacular sedentarisation of its nomadic population. In fact, nomads have decreased from 75% of the total population in 1965 to 12 % in 1988, and just 6% in 2000. This rapid and unprecedented sedentarisation, particularly in Southern Mauritania, can be explained by several factors, including the devastating droughts in the 1970s and 1980s, as well as the turbulent transformation of Mauritania's political economy. Together, these factors have destabilized rural livelihoods and accelerated land degradation, livestock loss, urbanization, and conflict between farmers and herders over natural resources and water access across the area, resulting in unprecedented inter-regional migration. The aim of this 40- years study is not to review in detail all the factors driving inter-regional migration in Southern Mauritania, but instead to scrutinize at the relationship between vegetation productivity, land cover changes, rainfall trends, and dynamic spatial demographic shifts from 1971 to 2015. In this regard, we propose an advanced assessment approach that integrates demographic information, climatological data, and multi-sensor Normalized Difference Vegetation Index (NDVI) time series data from 1981 to 2015 at 5.6 km to characterize the inter-regional migration movements in Southern Mauritania. A multi-linear regression analysis was conducted to examine to which extent the inter-regional migration movements are controlled by both climate and environmental changes. The demographic data show that Southern Mauritania's population grew less rapidly at an annual rate between 1977 and 1988 than between 1988 and 2000. The annual growth rate recorded in 2000 was 2.9%, compared to 2.5% in 1988 and 2.29% in 1960. Moreover, the population sedentarized dramatically at a rate of 95.2% in 2000 compared to 84.4% in 1988. The results also show distinctive interactions between vegetation dynamics, rainfall variations, and inter-regional migration during the last four decades: between 1977 and 1988, changes in rainfall bore the greatest impact on migration. Keywords: migration, climat change, environnemental migrants,

How certain is desiccation in west African Sahel rainfall (1930-1990)?

NASA Astrophysics Data System (ADS)

Chappell, Adrian; Agnew, Clive T.

2008-04-01

Hypotheses for the late 1960s to 1990 period of desiccation (secular decrease in rainfall) in the west African Sahel (WAS) are typically tested by comparing empirical evidence or model predictions against "observations" of Sahelian rainfall. The outcomes of those comparisons can have considerable influence on the understanding of regional and global environmental systems. Inverse-distance squared area-weighted (IDW) estimates of WAS rainfall observations are commonly aggregated over space to provide temporal patterns without uncertainty. Spatial uncertainty of WAS rainfall was determined using the median approximation sequential indicator simulation. Every year (1930-1990) 300 equally probable realizations of annual summer rainfall were produced to honor station observations, match percentiles of the observed cumulative distributions and indicator variograms and perform adequately during cross validation. More than 49% of the IDW mean annual rainfall fell outside the 5th and 95th percentiles for annual rainfall realization means. The IDW means represented an extreme realization. Uncertainty in desiccation was determined by repeatedly (100,000) sampling the annual distribution of rainfall realization means and by applying Mann-Kendall nonparametric slope detection and significance testing. All of the negative gradients for the entire period were statistically significant. None of the negative gradients for the expected desiccation period were statistically significant. The results support the presence of a long-term decline in annual rainfall but demonstrate that short-term desiccation (1965-1990) cannot be detected. Estimates of uncertainty for precipitation and other climate variables in this or other regions, or across the globe, are essential for the rigorous detection of spatial patterns and time series trends.

Absolute water storages in the Congo River floodplains from integration of InSAR and satellite radar altimetry

NASA Astrophysics Data System (ADS)

Lee, H.; Yuan, T.; Jung, H. C.; Aierken, A.; Beighley, E.; Alsdorf, D. E.; Tshimanga, R.; Kim, D.

2017-12-01

Floodplains delay the transport of water, dissolved matter and sediments by storing water during flood peak seasons. Estimation of water storage over the floodplains is essential to understand the water balances in the fluvial systems and the role of floodplains in nutrient and sediment transport. However, spatio-temporal variations of water storages over floodplains are not well known due to their remoteness, vastness, and high temporal variability. In this study, we propose a new method to estimate absolute water storages over the floodplains by establishing relations between water depths (d) and water volumes (V) using 2-D water depth maps from the integration of Interferometric Synthetic Aperture Radar (InSAR) and altimetry measurements. We applied this method over the Congo River floodplains and modeled the d-V relation using a power function (note that d-V indicates relation between d and V, not d minus V), which revealed the cross-section geometry of the floodplains as a convex curve. Then, we combined this relation and Envisat altimetry measurements to construct time series of floodplain's absolute water storages from 2002 to 2011. Its mean annual amplitude over the floodplains ( 7,777 km2) is 3.860.59 km3 with peaks in December, which lags behind total water storage (TWS) changes from the Gravity Recovery and Climate Experiment (GRACE) and precipitation changes from Tropical Rainfall Measuring Mission (TRMM) by about one month. The results also exhibit inter-annual variability, with maximum water volume to be 5.9 +- 0.72 km3 in the wet year of 2002 and minimum volume to be 2.01 +- 0.63 km3 in the dry year of 2005. The inter-annual variation of water storages can be explained by the changes of precipitation from TRMM.

Flood risk reduction and flow buffering as ecosystem services - Part 2: Land use and rainfall intensity effects in Southeast Asia

NASA Astrophysics Data System (ADS)

van Noordwijk, Meine; Tanika, Lisa; Lusiana, Betha

2017-05-01

Watersheds buffer the temporal pattern of river flow relative to the temporal pattern of rainfall. This ecosystem service is inherent to geology and climate, but buffering also responds to human use and misuse of the landscape. Buffering can be part of management feedback loops if salient, credible and legitimate indicators are used. The flow persistence parameter Fp in a parsimonious recursive model of river flow (Part 1, van Noordwijk et al., 2017) couples the transmission of extreme rainfall events (1 - Fp), to the annual base-flow fraction of a watershed (Fp). Here we compare Fp estimates from four meso-scale watersheds in Indonesia (Cidanau, Way Besai and Bialo) and Thailand (Mae Chaem), with varying climate, geology and land cover history, at a decadal timescale. The likely response in each of these four to variation in rainfall properties (including the maximum hourly rainfall intensity) and land cover (comparing scenarios with either more or less forest and tree cover than the current situation) was explored through a basic daily water-balance model, GenRiver. This model was calibrated for each site on existing data, before being used for alternative land cover and rainfall parameter settings. In both data and model runs, the wet-season (3-monthly) Fp values were consistently lower than dry-season values for all four sites. Across the four catchments Fp values decreased with increasing annual rainfall, but specific aspects of watersheds, such as the riparian swamp (peat soils) in Cidanau reduced effects of land use change in the upper watershed. Increasing the mean rainfall intensity (at constant monthly totals for rainfall) around the values considered typical for each landscape was predicted to cause a decrease in Fp values by between 0.047 (Bialo) and 0.261 (Mae Chaem). Sensitivity of Fp to changes in land use change plus changes in rainfall intensity depends on other characteristics of the watersheds, and generalisations made on the basis of one or two case studies may not hold, even within the same climatic zone. A wet-season Fp value above 0.7 was achievable in forest-agroforestry mosaic case studies. Inter-annual variability in Fp is large relative to effects of land cover change. Multiple (5-10) years of paired-plot data would generally be needed to reject no-change null hypotheses on the effects of land use change (degradation and restoration). Fp trends over time serve as a holistic scale-dependent performance indicator of degrading/recovering watershed health and can be tested for acceptability and acceptance in a wider social-ecological context.

Measurement of inter- and intra-annual variability of landscape fire activity at a continental scale: The Australian case

Treesearch

Grant J. Williamson; Lynda D. Prior; Matt Jolly; Mark A. Cochrane; Brett P. Murphy; David M. J. S. Bowman

2016-01-01

Climate dynamics at diurnal, seasonal and inter-annual scales shape global fire activity, although difficulties of assembling reliable fire and meteorological data with sufficient spatio-temporal resolution have frustrated quantification of this variability. Using Australia as a case study, we combine data from 4760 meteorological stations with 12 years of satellite-...

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

NASA Astrophysics Data System (ADS)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

Evaluation of rainfall simulations over West Africa in dynamically downscaled CMIP5 global circulation models

NASA Astrophysics Data System (ADS)

Akinsanola, A. A.; Ajayi, V. O.; Adejare, A. T.; Adeyeri, O. E.; Gbode, I. E.; Ogunjobi, K. O.; Nikulin, G.; Abolude, A. T.

2018-04-01

This study presents evaluation of the ability of Rossby Centre Regional Climate Model (RCA4) driven by nine global circulation models (GCMs), to skilfully reproduce the key features of rainfall climatology over West Africa for the period of 1980-2005. The seasonal climatology and annual cycle of the RCA4 simulations were assessed over three homogenous subregions of West Africa (Guinea coast, Savannah, and Sahel) and evaluated using observed precipitation data from the Global Precipitation Climatology Project (GPCP). Furthermore, the model output was evaluated using a wide range of statistical measures. The interseasonal and interannual variability of the RCA4 were further assessed over the subregions and the whole of the West Africa domain. Results indicate that the RCA4 captures the spatial and interseasonal rainfall pattern adequately but exhibits a weak performance over the Guinea coast. Findings from the interannual rainfall variability indicate that the model performance is better over the larger West Africa domain than the subregions. The largest difference across the RCA4 simulated annual rainfall was found in the Sahel. Result from the Mann-Kendall test showed no significant trend for the 1980-2005 period in annual rainfall either in GPCP observation data or in the model simulations over West Africa. In many aspects, the RCA4 simulation driven by the HadGEM2-ES perform best over the region. The use of the multimodel ensemble mean has resulted to the improved representation of rainfall characteristics over the study domain.

Assessing acid rain and climate effects on the temporal variation of dissolved organic matter in the unsaturated zone of a karstic system from southern China

NASA Astrophysics Data System (ADS)

Liao, Jin; Hu, Chaoyong; Wang, Miao; Li, Xiuli; Ruan, Jiaoyang; Zhu, Ying; Fairchild, Ian J.; Hartland, Adam

2018-01-01

Acid rain has the potential to significantly impact the quantity and quality of dissolved organic matter (DOM) leached from soil to groundwater. Yet, to date, the effects of acid rain have not been investigated in karstic systems, which are expected to strongly buffer the pH of atmospheric rainfall. This study presents a nine-year DOM fluorescence dataset from a karst unsaturated zone collected from two drip sites (HS4, HS6) in Heshang Cave, southern China between 2005 and 2014. Cross-correlograms show that fluorescence intensity of both dripwaters lagged behind rainfall by ∼1 year (∼11 months lag for HS4, and ∼13 months for HS6), whereas drip rates responded quite quickly to rainfall (0 months lag for HS4, and ∼3 months for HS6), based on optimal correlation coefficients. The rapid response of drip rates to rainfall is related to the change of reservoir head pressure in summer, associated with higher rainfall. In winter, low rainfall has a limited effect on head pressure, and drip rates gradually slow to a constant value associated with base flow from the overlying reservoir- this effect being most evident on inter-annual timescales (R2 = 0.80 for HS4 and R2 = 0.86 for HS6, n = 9, p < 0.01). We ascribed the ∼1 year lag of fluorescence intensity to the effect of the soil moisture deficit and the karst process on delaying water and solute transport. After eliminating the one year lag, the congruent seasonal pacing and amplitude between fluorescence intensity and rainfall observed suggests that the seasonality of fluorescence intensity was mainly controlled by the monsoonal rains which can govern the output of DOM from the soil, as well as the residence time of water in the unsaturated zone. On inter-annual timescales, a robust linear relationship between fluorescence intensity and annual (effective) precipitation amount (R2 = 0.86 for HS4 and R2 = 0.77 for HS6, n = 9, p < 0.01) was identified, implying that annual (effective) precipitation is the main determinant of DOM concentration in the aquifer. Conversely, the insensitivity of fluorescence intensity and fluorescence wavelength maxima to variations in the pH of local rainfall suggests that acid rain over the study period (∼pH 5.6 to ∼ 4.5) had no discernable effect on the quantity and quality of DOM in karst soil and soil solution, likely being strongly buffered by soil carbonates. Therefore, despite large increases in anthropogenic acid rain in recent Chinese history, hydrologic forcing is the predominant factor driving variations in DOM in karst aquifers.

Demographic patterns of a widespread long-lived tree are associated with rainfall and disturbances along rainfall gradients in SE Australia

PubMed Central

Cohn, Janet S; Lunt, Ian D; Bradstock, Ross A; Hua, Quan; McDonald, Simon

2013-01-01

Predicting species distributions with changing climate has often relied on climatic variables, but increasingly there is recognition that disturbance regimes should also be included in distribution models. We examined how changes in rainfall and disturbances along climatic gradients determined demographic patterns in a widespread and long-lived tree species, Callitris glaucophylla in SE Australia. We examined recruitment since 1950 in relation to annual (200–600 mm) and seasonal (summer, uniform, winter) rainfall gradients, edaphic factors (topography), and disturbance regimes (vertebrate grazing [tenure and species], fire). A switch from recruitment success to failure occurred at 405 mm mean annual rainfall, coincident with a change in grazing regime. Recruitment was lowest on farms with rabbits below 405 mm rainfall (mean = 0–0.89 cohorts) and highest on less-disturbed tenures with no rabbits above 405 mm rainfall (mean = 3.25 cohorts). Moderate levels of recruitment occurred where farms had no rabbits or less disturbed tenures had rabbits above and below 405 mm rainfall (mean = 1.71–1.77 cohorts). These results show that low annual rainfall and high levels of introduced grazing has led to aging, contracting populations, while higher annual rainfall with low levels of grazing has led to younger, expanding populations. This study demonstrates how demographic patterns vary with rainfall and spatial variations in disturbances, which are linked in complex ways to climatic gradients. Predicting changes in tree distribution with climate change requires knowledge of how rainfall and key disturbances (tenure, vertebrate grazing) will shift along climatic gradients. PMID:23919160

Relative importance of precipitation frequency and intensity in inter-annual variation of precipitation in Singapore during 1980-2013

NASA Astrophysics Data System (ADS)

Li, Xin; Babovic, Vladan

2017-04-01

Observed studies on inter-annual variation of precipitation provide insight into the response of precipitation to anthropogenic climate change and natural climate variability. Inter-annual variation of precipitation results from the concurrent variations of precipitation frequency and intensity, understanding of the relative importance of frequency and intensity in the variability of precipitation can help fathom its changing properties. Investigation of the long-term changes of precipitation schemes has been extensively carried out in many regions across the world, however, detailed studies of the relative importance of precipitation frequency and intensity in inter-annual variation of precipitation are still limited, especially in the tropics. Therefore, this study presents a comprehensive framework to investigate the inter-annual variation of precipitation and the dominance of precipitation frequency and intensity in a tropical urban city-state, Singapore, based on long-term (1980-2013) daily precipitation series from 22 rain gauges. First, an iterative Mann-Kendall trend test method is applied to detect long-term trends in precipitation total, frequency and intensity at both annual and seasonal time scales. Then, the relative importance of precipitation frequency and intensity in inducing the inter-annual variation of wet-day precipitation total is analyzed using a dominance analysis method based on linear regression. The results show statistically significant upward trends in wet-day precipitation total, frequency and intensity at annual time scale, however, these trends are not evident during the monsoon seasons. The inter-annual variation of wet-day precipitation is mainly dominated by precipitation intensity for most of the stations at annual time scale and during the Northeast monsoon season. However, during the Southwest monsoon season, the inter-annual variation of wet-day precipitation is mainly dominated by precipitation frequency. These results have implications for water resources management practices in Singapore.

Effects of rainfall seasonality and soil moisture capacity on mean annual water balance for Australian catchments

USGS Publications Warehouse

Potter, N.J.; Zhang, L.; Milly, P.C.D.; McMahon, T.A.; Jakeman, A.J.

2005-01-01

An important factor controlling catchment‐scale water balance is the seasonal variation of climate. The aim of this study is to investigate the effect of the seasonal distributions of water and energy, and their interactions with the soil moisture store, on mean annual water balance in Australia at catchment scales using a stochastic model of soil moisture balance with seasonally varying forcing. The rainfall regime at 262 catchments around Australia was modeled as a Poisson process with the mean storm arrival rate and the mean storm depth varying throughout the year as cosine curves with annual periods. The soil moisture dynamics were represented by use of a single, finite water store having infinite infiltration capacity, and the potential evapotranspiration rate was modeled as an annual cosine curve. The mean annual water budget was calculated numerically using a Monte Carlo simulation. The model predicted that for a given level of climatic aridity the ratio of mean annual evapotranspiration to rainfall was larger where the potential evapotranspiration and rainfall were in phase, that is, in summer‐dominant rainfall catchments, than where they were out of phase. The observed mean annual evapotranspiration ratios have opposite results. As a result, estimates of mean annual evapotranspiration from the model compared poorly with observational data. Because the inclusion of seasonally varying forcing alone was not sufficient to explain variability in the mean annual water balance, other catchment properties may play a role. Further analysis showed that the water balance was highly sensitive to the catchment‐scale soil moisture capacity. Calibrations of this parameter indicated that infiltration‐excess runoff might be an important process, especially for the summer‐dominant rainfall catchments; most similar studies have shown that modeling of infiltration‐excess runoff is not required at the mean annual timescale.

Phenology and growth adjustments of oil palm (Elaeis guineensis) to photoperiod and climate variability

PubMed Central

Legros, S.; Mialet-Serra, I.; Caliman, J.-P.; Siregar, F. A.; Clément-Vidal, A.; Dingkuhn, M.

2009-01-01

Background and Aims Oil palm flowering and fruit production show seasonal maxima whose causes are unknown. Drought periods confound these rhythms, making it difficult to analyse or predict dynamics of production. The present work aims to analyse phenological and growth responses of adult oil palms to seasonal and inter-annual climatic variability. Methods Two oil palm genotypes planted in a replicated design at two sites in Indonesia underwent monthly observations during 22 months in 2006–2008. Measurements included growth of vegetative and reproductive organs, morphology and phenology. Drought was estimated from climatic water balance (rainfall – potential evapotranspiration) and simulated fraction of transpirable soil water. Production history of the same plants for 2001–2005 was used for inter-annual analyses. Key Results Drought was absent at the equatorial Kandista site (0°55′N) but the Batu Mulia site (3°12′S) had a dry season with variable severity. Vegetative growth and leaf appearance rate fluctuated with drought level. Yield of fruit, a function of the number of female inflorescences produced, was negatively correlated with photoperiod at Kandista. Dual annual maxima were observed supporting a recent theory of circadian control. The photoperiod-sensitive phases were estimated at 9 (or 9 + 12 × n) months before bunch maturity for a given phytomer. The main sensitive phase for drought effects was estimated at 29 months before bunch maturity, presumably associated with inflorescence sex determination. Conclusion It is assumed that seasonal peaks of flowering in oil palm are controlled even near the equator by photoperiod response within a phytomer. These patterns are confounded with drought effects that affect flowering (yield) with long time-lag. Resulting dynamics are complex, but if the present results are confirmed it will be possible to predict them with models. PMID:19748909

Describing rainfall in northern Australia using multiple climate indices

NASA Astrophysics Data System (ADS)

Wilks Rogers, Cassandra Denise; Beringer, Jason

2017-02-01

Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere-biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index-rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian-Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño-Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

Importance of the Annual Cycles of SST and Solar Irradiance for Circulation and Rainfall: A Climate Model Simulation Study

NASA Technical Reports Server (NTRS)

Sud, Yogesh C.; Lau, William K. M.; Walker, G. K.; Mehta, V. M.

2001-01-01

Annual cycle of climate and precipitation is related to annual cycle of sunshine and sea-surface temperatures. Understanding its behavior is important for the welfare of humans worldwide. For example, failure of Asian monsoons can cause widespread famine and grave economic disaster in the subtropical regions. For centuries meteorologists have struggled to understand the importance of the summer sunshine and associated heating and the annual cycle of sea-surface temperatures (SSTs) on rainfall in the subtropics. Because the solar income is pretty steady from year to year, while SSTs depict large interannual variability as consequence of the variability of ocean dynamics, the influence of SSTs on the monsoons are better understood through observational and modeling studies whereas the relationship of annual rainfall to sunshine remains elusive. However, using NASA's state of the art climate model(s) that can generate realistic climate in a computer simulation, one can answer such questions. We asked the question: if there was no annual cycle of the sunshine (and its associated land-heating) or the SST and its associated influence on global circulation, what will happen to the annual cycle of monsoon rains? By comparing the simulation of a 4-year integration of a baseline Control case with two parallel anomaly experiments: 1) with annual mean solar and 2) with annual mean sea-surface temperatures, we were able to draw the following conclusions: (1) Tropical convergence zone and rainfall which moves with the Sun into the northern and southern hemispheres, specifically over the Indian, African, South American and Australian regions, is strongly modulated by the annual cycles of SSTs as well as solar forcings. The influence of the annual cycle of solar heating over land, however, is much stronger than the corresponding SST influence for almost all regions, particularly the subtropics; (2) The seasonal circulation patterns over the vast land-masses of the Northern Hemisphere at mid and high latitudes also get strongly influenced by the annual cycles of solar heating. The SST influence is largely limited to the oceanic regions of these latitudes; (3) The annual mode of precipitation over Amazonia has an equatorial regime revealing a maxima in the month of March associated with SST, and another maxima in the month of January associated with the solar annual cycles, respectively. The baseline simulation, which has both annual cycles, depicts both annual modes and its rainfall is virtually equal to the sum of those two modes; (4) Rainfall over Sahelian-Africa is significantly reduced (increased) in simulations lacking (invoking) solar irradiation with (without) the annual cycle. In fact, the dominant influence of solar irradiation emerges in almost all monsoonal-land regions: India, Southeast Asia, as well as Australia. The only exception is the Continental United States, where solar annual cycle shows only a relatively minor influence on the annual mode of rainfall.

Global scale modeling of riverine sediment loads: tropical rivers in a global context

NASA Astrophysics Data System (ADS)

Cohen, Sagy; Syvitski, James; Kettner, Albert

2015-04-01

A global scale riverine sediment flux model (termed WBMsed) is introduced. The model predicts spatially and temporally explicit water, suspended sediment and nutrients flux in relatively high resolutions (6 arc-min and daily). Modeled riverine suspended sediment flux through global catchments is used in conjunction with observational data for 35 tropical basins to highlight key basin scaling relationships. A 50 year, daily model simulation illuminates how precipitation, relief, lithology and drainage basin area affect sediment load, yield and concentration. Tropical river systems, wherein much of a drainage basin experiences tropical climate are strongly influenced by the annual and inter-annual variations of the Inter-tropical Convergence Zone (ITCZ) and its derivative monsoonal winds, have comparatively low inter-annual variation in sediment yield. Rivers draining rainforests and those subjected to tropical monsoons typically demonstrate high runoff, but with notable exceptions. High rainfall intensities from burst weather events are common in the tropics. The release of rain-forming aerosols also appears to uniquely increase regional rainfall, but its geomorphic manifestation is hard to detect. Compared to other more temperate river systems, climate-driven tropical rivers do not appear to transport a disproportionate amount of particulate load to the world's oceans, and their warmer, less viscous waters are less competent. Multiple-year hydrographs reveal that seasonality is a dominant feature of most tropical rivers, but the rivers of Papua New Guinea are somewhat unique being less seasonally modulated. Local sediment yield within the Amazon is highest near the Andes, but decreases towards the ocean as the river's discharge is diluted by water influxes from sediment-deprived rainforest tributaries

Multi-tissue analyses reveal limited inter-annual and seasonal variation in mercury exposure in an Antarctic penguin community.

PubMed

Brasso, Rebecka L; Polito, Michael J; Emslie, Steven D

2014-10-01

Inter-annual variation in tissue mercury concentrations in birds can result from annual changes in the bioavailability of mercury or shifts in dietary composition and/or trophic level. We investigated potential annual variability in mercury dynamics in the Antarctic marine food web using Pygoscelis penguins as biomonitors. Eggshell membrane, chick down, and adult feathers were collected from three species of sympatrically breeding Pygoscelis penguins during the austral summers of 2006/2007-2010/2011. To evaluate the hypothesis that mercury concentrations in penguins exhibit significant inter-annual variation and to determine the potential source of such variation (dietary or environmental), we compared tissue mercury concentrations with trophic levels as indicated by δ(15)N values from all species and tissues. Overall, no inter-annual variation in mercury was observed in adult feathers suggesting that mercury exposure, on an annual scale, was consistent for Pygoscelis penguins. However, when examining tissues that reflected more discrete time periods (chick down and eggshell membrane) relative to adult feathers, we found some evidence of inter-annual variation in mercury exposure during penguins' pre-breeding and chick rearing periods. Evidence of inter-annual variation in penguin trophic level was also limited suggesting that foraging ecology and environmental factors related to the bioavailability of mercury may provide more explanatory power for mercury exposure compared to trophic level alone. Even so, the variable strength of relationships observed between trophic level and tissue mercury concentrations across and within Pygoscelis penguin species suggest that caution is required when selecting appropriate species and tissue combinations for environmental biomonitoring studies in Antarctica.

Climate Change Studies over Bangalore using Multi-source Remote Sensing Data and GIS

NASA Astrophysics Data System (ADS)

B, S.; Gouda, K. C.; Laxmikantha, B. P.; Bhat, N.

2014-12-01

Urbanization is a form of metropolitan growth that is a response to often bewildering sets of economic, social, and political forces and to the physical geography of an area. Some of the causes of the sprawl include - population growth, economy, patterns of infrastructure initiatives like the construction of roads and the provision of infrastructure using public money encouraging development. The direct implication of such urban sprawl is the change in land use and land cover of the region. In this study the long term climate data from multiple sources like NCEP reanalysis, IMD observations and various satellite derived products from MAIRS, IMD, ERSL and TRMM are considered and analyzed using the developed algorithms for the better understanding of the variability in the climate parameters over Bangalore. These products are further mathematically analyzed to arrive at desired results by extracting land surface temperature (LST), Potential evapo-transmission (PET), Rainfall, Humidity etc. Various satellites products are derived from NASA (National Aeronautics Space Agency), Indian meteorological satellites and global satellites are helpful in massive study of urban issues at global and regional scale. Climate change analysis is well studied by using either single source data such as Temperature or Rainfall from IMD (Indian Meteorological Department) or combined data products available as in case of MAIRS (Monsoon Asia Integrated Regional Scale) program to get rainfall at regional scale. Finally all the above said parameters are normalized and analyzed with the help of various open source available software's for pre and post processing our requirements to obtain desired results. A sample of analysis i.e. the Inter annual variability of annual averaged Temperature over Bangalore is presented in figure 1, which clearly shows the rising trend of the temperature (0.06oC/year). Also the Land use and land cover (LULC) analysis over Bangalore, Day light hours from satellite derived products are analyzed and the correlation of climate parameters with LULC are presented.

Estimating fire severity and carbon emissions over Australian tropical savannas based on passive microwave satellite observations

NASA Astrophysics Data System (ADS)

Chen, X.; Liu, Y.; Evans, J. P.; Parinussa, R.

2017-12-01

Carbon emissions from large-scale fire activity over the Australian tropical savannas have strong inter-annual variability, due mainly to variations in fuel accumulation in response to rainfall. We investigated the use of a recently developed satellite-based vegetation optical depth (VOD) dataset to estimate fire severity and carbon emission. VOD is sensitive to the dynamics of all aboveground vegetation and available nearly every two days. For areas burned during 2003 - 2010, we calculated the VOD change (ΔVOD) pre- and post-fire and the associated loss in above ground biomass carbon. Both results compare well with widely-accepted approaches: ΔVOD agreed well with the Normalized Burn Ratio change (ΔNBR) and carbon loss with modelled emissions from the Global Fire Emissions Database (GFED). We found that the ΔVOD and ΔNBR are generally linearly related. The Pearson correlation coefficients (R) between VOD- and GFED-based fire carbon emissions for monthly and annual total estimates are very high, 0.92 and 0.96 respectively. A key feature of fire carbon emissions is the strong inter-annual variation, ranging from 21.1 million tonnes in 2010 to 84.3 million tonnes in 2004. This study demonstrates that a reasonable estimate of fire carbon emissions can be achieved in a timely manner based on multiple satellite observations over the regions where the emissions are primarily from aboveground vegetation loss, which can be complementary to the currently used approaches.

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.

The contribution of CEOP data to the understanding and modeling of monsoon systems

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2005-01-01

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validating models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Similar validation projects in other monsoon regions are being started. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of key components of the convective,and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variability, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

The forcing of monthly precipitation variability over Southwest Asia during the Boreal cold season

USGS Publications Warehouse

Hoell, Andrew; Shukla, Shraddhanand; Barlow, Mathew; Cannon, Forest; Kelley, Colin; Funk, Christopher C.

2015-01-01

Southwest Asia, deemed as the region containing the countries of Afghanistan, Iran, Iraq and Pakistan, is water scarce and receives nearly 75% of its annual rainfall during8 the boreal cold season of November-April. The forcing of Southwest Asia precipitation has been previously examined for the entire boreal cold season from the perspective of climate variability originating over the Atlantic and tropical Indo-Pacific Oceans. Here, we examine the inter-monthly differences in precipitation variability over Southwest Asia and the atmospheric conditions directly responsible in forcing monthly November-April precipitation. Seasonally averaged November-April precipitation over Southwest Asia is significantly correlated with sea surface temperature (SST) patterns consistent with Pacific Decadal Variability (PDV), the El Nino-Southern Oscillation (ENSO) and the warming trend of SST (Trend). On the contrary, the precipitation variability during individual months of November-April are unrelated and are correlated with SST signatures that include PDV, ENSO and Trend in different combinations. Despite strong inter-monthly differences in precipitation variability during November- April over Southwest Asia, similar atmospheric circulations, highlighted by a stationary equivalent barotropic Rossby wave centered over Iraq, force the monthly spatial distributions of precipitation. Tropospheric waves on the eastern side of the equivalent barotropic Rossby wave modifies the flux of moisture and advects the mean temperature gradient, resulting in temperature advection that is balanced by vertical motions over Southwest Asia. The forcing of monthly Southwest Asia precipitation by equivalent barotropic Rossby waves is different than the forcing by baroclinic Rossby waves associated with tropically-forced-only modes of climate variability.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

USGS Publications Warehouse

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-01-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-12-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Regional precipitation trend analysis at the Langat River Basin, Selangor, Malaysia

NASA Astrophysics Data System (ADS)

Palizdan, Narges; Falamarzi, Yashar; Huang, Yuk Feng; Lee, Teang Shui; Ghazali, Abdul Halim

2014-08-01

Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982-2011 were examined at the 95 % level of significance using the regional average Mann-Kendall (RAMK) test and the regional average Mann-Kendall coupled with bootstrap (RAMK-bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km × 5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations.

From TRMM to GPM: How well can heavy rainfall be detected from space?

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mitra, Ashis K.; Pai, D. S.; AghaKouchak, Amir

2016-02-01

In this study, we investigate the capabilities of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and the recently released Integrated Multi-satellitE Retrievals for GPM (IMERG) in detecting and estimating heavy rainfall across India. First, the study analyzes TMPA data products over a 17-year period (1998-2014). While TMPA and reference gauge-based observations show similar mean monthly variations of conditional heavy rainfall events, the multi-satellite product systematically overestimates its inter-annual variations. Categorical as well as volumetric skill scores reveal that TMPA over-detects heavy rainfall events (above 75th percentile of reference data), but it shows reasonable performance in capturing the volume of heavy rain across the country. An initial assessment of the GPM-based multi-satellite IMERG precipitation estimates for the southwest monsoon season shows notable improvements over TMPA in capturing heavy rainfall over India. The recently released IMERG shows promising results to help improve modeling of hydrological extremes (e.g., floods and landslides) using satellite observations.

Guidelines for rainwater harvesting system design and assessment for the city of Johannesburg, South Africa

NASA Astrophysics Data System (ADS)

Ndiritu, John; Ilemobade, Adesola; Kagoda, Paulo

2018-06-01

As water demand increases rainwater harvesting (RWH) systems are increasingly being installed for water supply but comprehensive hydrologic design guidelines for RWH do not exist in many parts of the world. The objective of this study was to develop guidelines for the hydrologic design and assessment of rainwater harvesting (RWH) systems in the City of Johannesburg, South Africa. The data for developing the guidelines were mainly obtained from multiple daily simulations of potential RWH systems in the city. The simulations used daily rainfall from 8 stations and demands based on the probable non-potable uses of RWH systems - toilet flushing, air conditioning and irrigation. The guidelines were confined to systems that would typically fill up in the wet season and empty towards the end of the dry season of the same year. Therefore, supply-to-demand ratios ranging from 0.1 to 0.9 were applied. Two generalized design charts of dimensionless relationships were developed. One relates the yield ratio with supply-to-demand ratio and reliability while the other relates the yield ratio with the storage-to-demand ratio and reliability. Reliability was defined as the probability of exceedance of annual yield in order to incorporate the large inter-annual variability of rainfall experienced in the region. The analyses and design of an example RWH system is used to illustrate the application of the design charts.

Using Digital Repeat Photography to Link Vegetative Phenology and Carbon Fluxes to Biotic and Abiotic Drivers in Three Semi-arid Systems (New Mexico, USA)

NASA Astrophysics Data System (ADS)

Hallmark, A.; Litvak, M. E.; Collins, S. L.

2015-12-01

Arid and semi-arid ecosystems account for over 45% of global land cover. While mean annual carbon uptake in these ecosystems is relatively low, aridlands collectively store a significant amount of carbon. There is high inter- and intra-annual variability of plant growth in aridlands, depending largely on the timing and size of rainfall events. This variation is also of great significance, as the variation in annual semi-aridland carbon uptake accounts for ~39% of the inter-annual variability of the global terrestrial carbon sink, the largest percentage of any land cover type. Although arid and semi-arid ecosystems are of global importance, they are understudied. To better understand the drivers and variability of carbon uptake in these critical ecosystems, we utilize a six-year record of digital images (45,000+ images), carbon flux and meteorological data, soil water content, and associated ecological measurements from three eddy covariance tower sites in central New Mexico. These sites include a Chihuahuan Desert/short-grass Plains grassland site, and post-fire successional grassland site, and a creosote-encroached shrubland site, each of which have unique species compositions, carbon fluxes, and reactions to disturbance and resource addition. All images used are co-registered and corrected for radial lens distortions (when necessary) and greenness indices (2GRBi, gcc, and/or NDVI) are calculated for each scene's overall "canopy" and for individual species and plant functional types therein. At all three sites, camera-derived greenness is correlated to measured carbon uptake with fine resolution (R2 up to 0.8), capturing temporal and spatial variation usually not seen in satellite-based imagery. At sites with lower LAI, species-specific ROI's were more correlated to the site's measured carbon flux across shorter time scales. Understanding the biota comprising each image and its contribution to changing scene greenness at different times of year can lead to more accurate carbon flux predictions in semi-arid systems, with species-specific biotic constraints (maximum growth rate, lifespan, and seasonality), growth parameters (light availability, VPD, soil water content, and temperature) as well as community-wide abiotic drivers considered.

Inter-annual variability and spatial coherence of net primary productivity across a western Oregon Cascades landscape

Treesearch

Travis J. Woolley; Mark E. Harmon; Kari B. O’Connell

2015-01-01

Inter-annual variability (IAV) of forest Net Primary Productivity (NPP) is a function of both extrinsic (e.g., climate) and intrinsic (e.g., stand dynamics) drivers. As estimates of NPP in forests are scaled from trees to stands to the landscape, an understanding of the relative effects of these factors on spatial and temporal behavior of NPP is important. Although a...

Watershed-scale response of groundwater recharge to inter-annual and inter-decadal variability in precipitation (Alberta, Canada)

NASA Astrophysics Data System (ADS)

Hayashi, Masaki; Farrow, Christopher R.

2014-12-01

Groundwater recharge sets a constraint on aquifer water balance in the context of water management. Historical data on groundwater and other relevant hydrological processes can be used to understand the effects of climatic variability on recharge, but such data sets are rare. The climate of the Canadian prairies is characterized by large inter-annual and inter-decadal variability in precipitation, which provides opportunities to examine the response of groundwater recharge to changes in meteorological conditions. A decadal study was conducted in a small (250 km2) prairie watershed in Alberta, Canada. Relative magnitude of annual recharge, indicated by water-level rise, was significantly correlated with a combination of growing-season precipitation and snowmelt runoff, which drives depression-focussed infiltration of meltwater. Annual precipitation was greater than vapour flux at an experimental site in some years and smaller in other years. On average precipitation minus vapour flux was 10 mm y-1, which was comparable to the magnitude of watershed-scale groundwater recharge estimated from creek baseflow. Average baseflow showed a distinct shift from a low value (4 mm y-1) in 1982-1995 to a high value (15 mm y-1) in 2003-2013, indicating the sensitivity of groundwater recharge to a decadal-scale variability of meteorological conditions.

Spatial variability of extreme rainfall at radar subpixel scale

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2018-01-01

Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.

On the distributions of annual and seasonal daily rainfall extremes in central Arizona and their spatial variability

NASA Astrophysics Data System (ADS)

Mascaro, Giuseppe

2018-04-01

This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.

Examining spatial-temporal variability and prediction of rainfall in North-eastern Nigeria

NASA Astrophysics Data System (ADS)

Muhammed, B. U.; Kaduk, J.; Balzter, H.

2012-12-01

In the last 50 years rainfall in North-eastern Nigeria under the influence of the West African Monsoon (WAM) has been characterised by large annual variations with severe droughts recorded in 1967-1973, and 1983-1987. This variability in rainfall has a large impact on the regions agricultural output, economy and security where the majority of the people depend on subsistence agriculture. In the 1990s there was a sign of recovery with higher annual rainfall totals compared to the 1961-1990 period but annual totals were slightly above the long term mean for the century. In this study we examine how significant this recovery is by analysing medium-term (1980-2006) rainfall of the region using the Climate Research Unit (CRU) and National Centre for Environment Prediction (NCEP) precipitation ½ degree, 6 hourly reanalysis data set. Percentage coefficient of variation increases northwards for annual rainfall (10%-35%) and the number of rainy days (10%-50%). The standardized precipitation index (SPI) of the area shows 7 years during the period as very wet (1996, 1999, 2003 and 2004) with SPI≥1.5 and moderately wet (1993, 1998, and 2006) with values of 1.0≥SPI≤1.49. Annual rainfall indicates a recovery from the 1990s and onwards but significant increases (in the amount of rainfall and number of days recorded with rainfall) is only during the peak of the monsoon season in the months of August and September (p<0.05) with no significant increases in the months following the onset of rainfall. Forecasting of monthly rainfall was made using the Auto Regressive Integrated Moving Average (ARIMA) model. The model is further evaluated using 24 months rainfall data yielding r=0.79 (regression slope=0.8; p<0.0001) in the sub-humid part of the study area and r=0.65 (regression slope=0.59, and p<0.0001) in the northern semi-arid part. The results suggest that despite the positive changes in rainfall (without significant increases in the months following the onset of the monsoon), the area has not fully recovered from the drought years of the 1960s, 70s, and 80s. These findings also highlight the implications of the current recovery on rain fed agriculture and water resources in the study area. The strong correlation and a root mean square error of 64.8 mm between the ARIMA model and the rainfall data used for this study indicates that the model can be satisfactorily used in forecasting rainfall in the in the sub-humid part of North-eastern Nigeria over a 24 months period.

Performance of CMIP3 and CMIP5 GCMs to simulate observed rainfall characteristics over the Western Himalayan region

NASA Astrophysics Data System (ADS)

Meher, J. K.; Das, L.

2017-12-01

The Western Himalayan Region (WHR) was subject to a significant negative trend in the annual and monsoon rainfall during 1902-2005. Annual and seasonal rainfall change over WHR of India was estimated using 22 rain gauge station rainfall data from the India Meteorological Department. The performance of 13 global climate models (GCMs) from the coupled model intercomparison project phase 3 (CMIP3) and 42 GCMs from CMIP5 was evaluated through multiple analysis: the evaluation of the mean annual cycle, annual cycles of interannual variability, spatial patterns, trends and signal-to-noise ratio. In general, CMIP5 GCMs were more skillful in terms of simulating the annual cycle of interannual variability compared to CMIP3 GCMs. The CMIP3 GCMs failed to reproduce the observed trend whereas 50% of the CMIP5 GCMs reproduced the statistical distribution of short-term (30-years) trend-estimates than for the longer term (99-years). GCMs from both CMIP3 and CMIP5 were able to simulate the spatial distribution of observed rainfall in pre-monsoon and winter months. Based on performance, each model of CMIP3 and CMIP5 was given an overall rank, which puts the high resolution version of the MIROC3.2 model (MIROC3.2 hires) and MIROC5 at the top in CMIP3 and CMIP5 respectively. Robustness of the ranking was judged through a sensitivity analysis, which indicated that ranks were independent during the process of adding or removing any individual method. It also revealed that trend analysis was not a robust method of judging performances of the model as compared to other methods.

Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

2015-04-01

Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Gao, Chujie

2018-02-01

This study assesses the performance of 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of rainfall over East Africa (EA) against reanalyzed datasets during 1951-2005. The datasets were sourced from Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU). The metrics used to rank CMIP5 Global Circulation Models (GCMs) based on their performance in reproducing the observed rainfall include correlation coefficient, standard deviation, bias, percentage bias, root mean square error, and trend. Performances of individual models vary widely. The overall performance of the models over EA is generally low. The models reproduce the observed bimodal rainfall over EA. However, majority of them overestimate and underestimate the October-December (OND) and March-May (MAM) rainfall, respectively. The monthly (inter-annual) correlation between model and reanalyzed is high (low). More than a third of the models show a positive bias of the annual rainfall. High standard deviation in rainfall is recorded in the Lake Victoria Basin, central Kenya, and eastern Tanzania. A number of models reproduce the spatial standard deviation of rainfall during MAM season as compared to OND. The top eight models that produce rainfall over EA relatively well are as follows: CanESM2, CESM1-CAM5, CMCC-CESM, CNRM-CM5, CSIRO-Mk3-6-0, EC-EARTH, INMCM4, and MICROC5. Although these results form a fairly good basis for selection of GCMs for carrying out climate projections and downscaling over EA, it is evident that there is still need for critical improvement in rainfall-related processes in the models assessed. Therefore, climate users are advised to use the projections of rainfall from CMIP5 models over EA cautiously when making decisions on adaptation to or mitigation of climate change.

Rainfall and runoff variability in Ethiopia

NASA Astrophysics Data System (ADS)

Billi, Paolo; Fazzini, Massimiliano; Tadesse Alemu, Yonas; Ciampalini, Rossano

2014-05-01

Rainfall and river flow variability have been deeply investigated and and the impact of climate change on both is rather well known in Europe (EEA, 2012) or in other industrialized countries. Reports of international organizations (IPCC, 2012) and the scientific literature provide results and outlooks that were found contrasting and spatially incoherent (Manton et al., 2001; Peterson et al., 2002; Griffiths et al., 2003; Herath and Ratnayake, 2004) or weakened by limitation of data quality and quantity. According to IPCC (2012), in East Africa precipitation there are contrasting regional and seasonal variations and trends, though Easterling et al. (2000) and Seleshi and Camberlin (2006) report decreasing trends in heavy precipitation over parts of Ethiopia during the period 1965-2002. Literature on the impact of climate change on river flow is scarce in Africa and IPCC Technical Paper VI (IPCC, 2008) concluded that no evidence, based on instrumental records, has been found for a climate-driven globally widespread change in the magnitude/frequency of floods during the last decades (Rosenzweig et al., 2007), though increases in runoff and increased risk of flood events in East Africa are expected. Some papers have faced issues regarding rainfall and river flow variability in Ethiopia (e.g. Seleshi and Demaree, 1995; Osman and Sauerborn, 2002; Seleshi and Zanke, 2004; Meze-Hausken, 2004; Korecha and Barnston, 2006; Cheung et al., 2008) but their investigations are commonly geographically limited or used a small number of rain and flow gauges with the most recent data bound to the beginning of the last decade. In this study an attempt to depict rainfall and river flow variability, considering the longer as possible time series for the largest as possible number of meteo-stations and flow gauge evenly distributed across Ethiopia, is presented. 25 meteo-stations and 21 flow gauges with as much as possible continuous data records were selected. The length of the time series ranges between 35 to 50 and 9 to 49 years for rainfall and river flow, respectively. In order to improve the poor linear correlation model to describe rainfall gradient with altitude a simple topographic parameter is introduced capable to better depict the spatial variability of annual rainfall and its coefficient of variation. The small rains (Belg) were found to be much more unpredictable than the long, monsoon-type rains (Kiremt) and hence much more out of phase with the variation of annual precipitation amount that is significantly influenced by the Kiremt rains. In order to investigate the long term trends, rainfall anomalies were calculated as Z score for annual, Belg and Kiremt precipitation for all the stations and average values are calculated and plotted against time. The three Z trend lines obtained show no marked deviation from the mean as only an almost negligible decreasing trend is observed. Rainfall intensity in 24 hours is analyzed and the trend line of the maximum intensity averaged over the maximum value of each year recorded at each meteo-station is constructed. These data indicate a general decrease in daily rainfall intensity across Ethiopia with clear exceptions in a few selected areas. The same procedure, based on the Z scores, used to analyze rainfall variability is applied also to the river flow data and a similar result is obtained. If compared with rainfall, annual runoff shows a much wider range of variation among the study rivers. This issue is discussed and possible explanations are presented.

A Multi-sensor Approach to Identify Crop Sensitivity Related to Climate Variability in Central India

NASA Astrophysics Data System (ADS)

Mondal, P.; DeFries, R. S.; Jain, M.; Robertson, A. W.; Galford, G. L.; Small, C.

2012-12-01

Agriculture is a primary source of livelihood for over 70% of India's population, with staple crops (e.g. winter wheat) playing a pivotal role in satisfying an ever-increasing food-demand of a growing population. Agricultural yield in India has been reported to be highly correlated with the timing and total amount of monsoon rainfall and/or temperature depending on crop type. With expected change in future climate (temperature and precipitation), significant fluctuations in crop yields are projected for near future. To date, little work has identified the sensitivity of cropping intensity, or the number of crops planted in a given year, to climate variability. The objective of this study is to shed light on relative importance of different climate parameters through a statistical analysis of inter-annual variations in cropping intensity at a regional scale, which may help identify adaptive strategies in response to future climate anomalies. Our study focuses on a highly human-modified landscape in central India, and uses a multi-sensor approach to determine the sensitivity of agriculture to climate variability. First, we assembled the 16-day time-series of 250m Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), and applied a spline function-based smoothing algorithm to develop maps of monsoon and winter crops in Central India for a decadal time-span. A hierarchical model involving moderate resolution Landsat (30m) data was used to estimate the heterogeneity of the spectral signature within the MODIS dataset (250m). We then compared the season-specific cropping patterns with spatio-temporal variability in climate parameters derived from the Tropical Rainfall Measuring Mission (TRMM) data. Initial data indicates that the existence of a monsoon crop has moderate to strong correlation with wet season end date (ρ = .522), wet season length (ρ = .522), and the number of rainy days during wet season (ρ = .829). Existence of a winter crop, however, has a moderately strong correlation with wet season start date (ρ = .577). In addition, winter crop yield (ton/ha) has a moderate correlation with wet season end date (ρ = .624), number of rainy days during the wet season (ρ = .492), and during the dry season (ρ = .410). Future work will assess which other factors influence cropping intensity (e.g. access to irrigation among many other), since a complex interplay of bio-physical and socio-economic factors governs the decision-making at the farm-level, ultimately leading to inter-annual variability in cropping intensity and/or yield.

Trends in rainfall and rainfall-related extremes in the east coast of peninsular Malaysia

NASA Astrophysics Data System (ADS)

Mayowa, Olaniya Olusegun; Pour, Sahar Hadi; Shahid, Shamsuddin; Mohsenipour, Morteza; Harun, Sobri Bin; Heryansyah, Arien; Ismail, Tarmizi

2015-12-01

The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971-2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann-Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

Trends and spatial distribution of annual and seasonal rainfall in Ethiopia

USGS Publications Warehouse

Cheung, W.H.; Senay, G.B.; Singh, A.

2008-01-01

As a country whose economy is heavily dependent on low-productivity rainfed agriculture, rainfall trends are often cited as one of the more important factors in explaining various socio-economic problems such as food insecurity. Therefore, in order to help policymakers and developers make more informed decisions, this study investigated the temporal dynamics of rainfall and its spatial distribution within Ethiopia. Changes in rainfall were examined using data from 134 stations in 13 watersheds between 1960 and 2002. The variability and trends in seasonal and annual rainfall were analysed at the watershed scale with data (1) from all available years, and (2) excluding years that lacked observations from at least 25% of the gauges. Similar analyses were also performed at the gauge, regional, and national levels. By regressing annual watershed rainfall on time, results from the one-sample t-test show no significant changes in rainfall for any of the watersheds examined. However, in our regressions of seasonal rainfall averages against time, we found a significant decline in June to September rainfall (i.e. Kiremt) for the Baro-Akobo, Omo-Ghibe, Rift Valley, and Southern Blue Nile watersheds located in the southwestern and central parts of Ethiopia. While the gauge level analysis showed that certain gauge stations experienced recent changes in rainfall, these trends are not necessarily reflected at the watershed or regional levels.

Droughts, rainfall and rural water supply in northern Nigeria

NASA Astrophysics Data System (ADS)

Tarhule, Aondover Augustine

Knowledge concerning various aspects of drought and water scarcity is required to predict, and to articulate strategies to minimize the effects of future events. This thesis investigated different aspects of droughts and rainfall variability at several time scales and described the dynamics of water supply and use in a rural village in northeastern Nigeria. The parallel existence of measured climatic records and information on famine/folklore events is utilized to calibrate the historical information against the measured data. It is shown that famines or historical droughts occurred when the cumulative deficit of rainfall fell below 1.3 times the standard deviation of the long-term mean rainfall. The study demonstrated that famine chronologies are adequate proxy for drought events, providing a means for the reconstruction of the drought/climatic history of the region. Analysis of recent changes in annual rainfall characteristics show that the series of annual rainfall and number of rain days experienced a discontinuity during the 1960's, caused largely by the decrease in the frequency of moderate to high intensity rain events. The periods prior to and after the change point are homogenous and provide an objective basis for the estimation of changes in rainfall characteristics, drought parameters and for demarcating the region into sub-zones. Rainfall variability was unaffected by the abrupt change. Furthermore, the variability is independently distributed and adequately described by the normal distribution. This allows estimates of the probability of various magnitudes or thresholds of variability. The effects of droughts and rainfall variability are most strongly felt in rural areas. Analysis of the patterns of water supply and use in a typical rural village revealed that the hydrologic system is driven by the local rainfall. Perturbations in the rains propagate through the system with short lag time between the various components. Where fadama aquifers occur, they offer a major supplement of water for six to seven months during the dry season. Under traditional systems, the pattern of water withdrawal from the fadama aquifers is designed to accommodate the diverse interests of different groups and to minimize the potential for conflict. The results contribute to our understanding of drought and water scarcity and are useful in various practical applications.

Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

NASA Astrophysics Data System (ADS)

Singh, U. K.; Singh, G. P.; Singh, Vikas

2015-04-01

The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread among the ensemble members of individual model, strong teleconnection (correlation analysis) with SST, coefficient of variation, inter-annual variability, analysis of Taylor diagram, etc. suggest that there is a need to improve coupled model instead of uncoupled model for the development of a better dynamical seasonal forecast system.

AVHRR channel selection for land cover classification

USGS Publications Warehouse

Maxwell, S.K.; Hoffer, R.M.; Chapman, P.L.

2002-01-01

Mapping land cover of large regions often requires processing of satellite images collected from several time periods at many spectral wavelength channels. However, manipulating and processing large amounts of image data increases the complexity and time, and hence the cost, that it takes to produce a land cover map. Very few studies have evaluated the importance of individual Advanced Very High Resolution Radiometer (AVHRR) channels for discriminating cover types, especially the thermal channels (channels 3, 4 and 5). Studies rarely perform a multi-year analysis to determine the impact of inter-annual variability on the classification results. We evaluated 5 years of AVHRR data using combinations of the original AVHRR spectral channels (1-5) to determine which channels are most important for cover type discrimination, yet stabilize inter-annual variability. Particular attention was placed on the channels in the thermal portion of the spectrum. Fourteen cover types over the entire state of Colorado were evaluated using a supervised classification approach on all two-, three-, four- and five-channel combinations for seven AVHRR biweekly composite datasets covering the entire growing season for each of 5 years. Results show that all three of the major portions of the electromagnetic spectrum represented by the AVHRR sensor are required to discriminate cover types effectively and stabilize inter-annual variability. Of the two-channel combinations, channels 1 (red visible) and 2 (near-infrared) had, by far, the highest average overall accuracy (72.2%), yet the inter-annual classification accuracies were highly variable. Including a thermal channel (channel 4) significantly increased the average overall classification accuracy by 5.5% and stabilized interannual variability. Each of the thermal channels gave similar classification accuracies; however, because of the problems in consistently interpreting channel 3 data, either channel 4 or 5 was found to be a more appropriate choice. Substituting the thermal channel with a single elevation layer resulted in equivalent classification accuracies and inter-annual variability.

Inter-annual Variability in Global Suspended Particulate Inorganic Carbon Inventory Using Space-based Measurements

NASA Astrophysics Data System (ADS)

Hopkins, J.; Balch, W. M.; Henson, S.; Poulton, A. J.; Drapeau, D.; Bowler, B.; Lubelczyk, L.

2016-02-01

Coccolithophores, the single celled phytoplankton that produce an outer covering of calcium carbonate coccoliths, are considered to be the greatest contributors to the global oceanic particulate inorganic carbon (PIC) pool. The reflective coccoliths scatter light back out from the ocean surface, enabling PIC concentration to be quantitatively estimated from ocean color satellites. Here we use datasets of AQUA MODIS PIC concentration from 2003-2014 (using the recently-revised PIC algorithm), as well as statistics on coccolithophore vertical distribution derived from cruises throughout the world ocean, to estimate the average global (surface and integrated) PIC standing stock and its associated inter-annual variability. In addition, we divide the global ocean into Longhurst biogeochemical provinces, update the PIC biomass statistics and identify those regions that have the greatest inter-annual variability and thus may exert the greatest influence on global PIC standing stock and the alkalinity pump.

Inter-annual rainfall variations and suicide in New South Wales, Australia, 1964-2001

NASA Astrophysics Data System (ADS)

Nicholls, Neville; Butler, Colin D.; Hanigan, Ivan

2006-01-01

The suicide rate in New South Wales is shown to be related to annual precipitation, supporting a widespread and long-held assumption that drought in Australia increases the likelihood of suicide. The relationship, although statistically significant, is not especially strong and is confounded by strong, long-term variations in the suicide rate not related to precipitation variations. A decrease in precipitation of about 300 mm would lead to an increase in the suicide rate of approximately 8% of the long-term mean suicide rate.

Decent wage is more important than absolution of debts: A smallholder socio-hydrological modelling framework

NASA Astrophysics Data System (ADS)

Pande, Saket; Savenije, Hubert

2015-04-01

We present a framework to understand the socio-hydrological system dynamics of a small holder. Small holders are farmers who own less than 2 ha of farmland. It couples the dynamics of 6 main variables that are most relevant at the scale of a small holder: local storage (soil moisture and other water storage), capital, knowledge, livestock production, soil fertility and grass biomass production. The hydroclimatic variability is at sub-annual scale and influences the socio-hydrology at annual scale. The model incorporates rule-based adaptation mechanisms (for example: adjusting expenditures on food and fertilizers, selling livestocks etc.) of small holders when they face adverse socio-hydrological conditions, such as low annual rainfall, higher intra-annual variability in rainfall or variability in agricultural prices. We apply the framework to understand the socio-hydrology of a sugarcane small holder in Aurangabad, Maharashtra. This district has witnessed suicides of many sugarcane farmers who could not extricate themselves out of the debt trap. These farmers lack irrigation and are susceptible to fluctuating sugar prices and intra-annual hydro-climatic variability. We study the sensitivity of annual total capital averaged over 30 years, an indicator of small holder wellbeing, to initial capital that a small holder starts with and the prevalent wage rates. We find that a smallholder well being is low (below Rs 30000 per annum, a threshold above which a smallholder can afford a basic standard of living) and is rather insensitive to initial capital at low wage rates. Initial capital perhaps matters to small holder livelihoods at higher wage rates. Further, the small holder system appears to be resilient at around Rs 115/mandays in the sense that small perturbations in wage rates around this rate still sustains the smallholder above the basic standard of living. Our results thus indicate that government intervention to absolve the debt of farmers is not enough. It must invest in local storages that can buffer intra-annual variability in rainfall in tandem and good wages for alternative sources of income.

Future Simulated Intensification of Precipitation Extremes, CMIP5 Model Uncertainties and Dependencies

NASA Astrophysics Data System (ADS)

Bador, M.; Donat, M.; Geoffroy, O.; Alexander, L. V.

2017-12-01

Precipitation intensity during extreme events is expected to increase with climate change. Throughout the 21st century, CMIP5 climate models project a general increase in annual extreme precipitation in most regions. We investigate how robust this future increase is across different models, regions and seasons. We find that there is strong similarity in extreme precipitation changes between models that share atmospheric physics, reducing the ensemble of 27 models to 14 independent projections. We find that future simulated extreme precipitation increases in most models in the majority of land grid cells located in the dry, intermediate and wet regions according to each model's precipitation climatology. These increases significantly exceed the range of natural variability estimated from long equilibrium control runs. The intensification of extreme precipitation across the entire spectrum of dry to wet regions is particularly robust in the extra-tropics in both wet and dry season, whereas uncertainties are larger in the tropics. The CMIP5 ensemble therefore indicates robust future intensification of annual extreme rainfall in particular in extra-tropical regions. Generally, the CMIP5 robustness is higher during the dry season compared to the wet season and the annual scale, but inter-model uncertainties in the tropics remain important.

How important and different are tropical rivers? - An overview

NASA Astrophysics Data System (ADS)

Syvitski, James P. M.; Cohen, Sagy; Kettner, Albert J.; Brakenridge, G. Robert

2014-12-01

Tropical river systems, wherein much of the drainage basin experiences tropical climate are strongly influenced by the annual and inter-annual variations of the Inter-tropical Convergence Zone (ITCZ) and its derivative monsoonal winds. Rivers draining rainforests and those subjected to tropical monsoons typically demonstrate high runoff, but with notable exceptions. High rainfall intensities from burst weather events are common in the tropics. The release of rain-forming aerosols also appears to uniquely increase regional rainfall, but its geomorphic manifestation is hard to detect. Compared to other more temperate river systems, climate-driven tropical rivers do not appear to transport a disproportionate amount of particulate load to the world's oceans, and their warmer, less viscous waters are less competent. Tropical biogeochemical environments do appear to influence the sedimentary environment. Multiple-year hydrographs reveal that seasonality is a dominant feature of most tropical rivers, but the rivers of Papua New Guinea are somewhat unique being less seasonally modulated. Modeled riverine suspended sediment flux through global catchments is used in conjunction with observational data for 35 tropical basins to highlight key basin scaling relationships. A 50 year, daily model simulation illuminates how precipitation, relief, lithology and drainage basin area affect sediment load, yield and concentration. Local sediment yield within the Amazon is highest near the Andes, but decreases towards the ocean as the river's discharge is diluted by water influxes from sediment-deprived rainforest tributaries. Bedload is strongly affected by the hydraulic gradient and discharge, and the interplay of these two parameters predicts foci of net bedload deposition or erosion. Rivers of the tropics have comparatively low inter-annual variation in sediment yield.

The Contribution of CEOP Data to the Understanding and Modeling of Monsoon Systems

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2005-01-01

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validaintg models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of, key components of the convective and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variabillity, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

DCERP Annual Technical Report III: March 2009-February 2010. Executive Summary

DTIC Science & Technology

2010-04-01

groundwater passing though marshes to the estuary. Loading estimates may vary considerably depending on inter-annual hydrologic (storm versus drought ...climatic events (i.e., hurricanes and droughts ); and integrate results with the other DCERP modules. The benefits of the Aquatic/Estuarine Module...inter-annual hydrologic (storm versus drought years) variability. ▪ Several large phytoplankton blooms in mid-estuary to upper estuary locations

Nutrient loads exported from managed catchments reveal emergent biogeochemical stationarity

NASA Astrophysics Data System (ADS)

Basu, Nandita B.; Destouni, Georgia; Jawitz, James W.; Thompson, Sally E.; Loukinova, Natalia V.; Darracq, Amélie; Zanardo, Stefano; Yaeger, Mary; Sivapalan, Murugesu; Rinaldo, Andrea; Rao, P. Suresh C.

2010-12-01

Complexity of heterogeneous catchments poses challenges in predicting biogeochemical responses to human alterations and stochastic hydro-climatic drivers. Human interferences and climate change may have contributed to the demise of hydrologic stationarity, but our synthesis of a large body of observational data suggests that anthropogenic impacts have also resulted in the emergence of effective biogeochemical stationarity in managed catchments. Long-term monitoring data from the Mississippi-Atchafalaya River Basin (MARB) and the Baltic Sea Drainage Basin (BSDB) reveal that inter-annual variations in loads (LT) for total-N (TN) and total-P (TP), exported from a catchment are dominantly controlled by discharge (QT) leading inevitably to temporal invariance of the annual, flow-weighted concentration, $\\overline{Cf = (LT/QT). Emergence of this consistent pattern across diverse managed catchments is attributed to the anthropogenic legacy of accumulated nutrient sources generating memory, similar to ubiquitously present sources for geogenic constituents that also exhibit a linear LT-QT relationship. These responses are characteristic of transport-limited systems. In contrast, in the absence of legacy sources in less-managed catchments, $\\overline{Cf values were highly variable and supply limited. We offer a theoretical explanation for the observed patterns at the event scale, and extend it to consider the stochastic nature of rainfall/flow patterns at annual scales. Our analysis suggests that: (1) expected inter-annual variations in LT can be robustly predicted given discharge variations arising from hydro-climatic or anthropogenic forcing, and (2) water-quality problems in receiving inland and coastal waters would persist until the accumulated storages of nutrients have been substantially depleted. The finding has notable implications on catchment management to mitigate adverse water-quality impacts, and on acceleration of global biogeochemical cycles.

Designing low-carbon power systems for Great Britain in 2050 that are robust to the spatiotemporal and inter-annual variability of weather

NASA Astrophysics Data System (ADS)

Zeyringer, Marianne; Price, James; Fais, Birgit; Li, Pei-Hao; Sharp, Ed

2018-05-01

The design of cost-effective power systems with high shares of variable renewable energy (VRE) technologies requires a modelling approach that simultaneously represents the whole energy system combined with the spatiotemporal and inter-annual variability of VRE. Here, we soft-link a long-term energy system model, which explores new energy system configurations from years to decades, with a high spatial and temporal resolution power system model that captures VRE variability from hours to years. Applying this methodology to Great Britain for 2050, we find that VRE-focused power system design is highly sensitive to the inter-annual variability of weather and that planning based on a single year can lead to operational inadequacy and failure to meet long-term decarbonization objectives. However, some insights do emerge that are relatively stable to weather-year. Reinforcement of the transmission system consistently leads to a decrease in system costs while electricity storage and flexible generation, needed to integrate VRE into the system, are generally deployed close to demand centres.

Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

NASA Astrophysics Data System (ADS)

Tafoughalti, K.; El Faleh, E. M.; Moujahid, Y.; Ouargaga, F.

2018-05-01

Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

Factors Affecting the Inter-annual to Centennial Time Scale Variability of All Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan

2016-04-01

The All Indian Summer Monsoon Rainfall (AISMR) is highly important for the livelihood of more than 1 billion people living in the Indian sub-continent. The agriculture of this region is heavily dependent on seasonal (JJAS) monsoon rainfall. An early start or a slight delay of monsoon, or an early withdrawal or prolonged monsoon season may upset the farmer's agricultural plans, can cause significant reduction in crop yield, and hence economic loss. Understanding of AISMR is also vital because it is a part of global atmospheric circulation system. Several studies show that AISMR is influenced by internal climate forcings (ICFs) viz. ENSO, AMO, PDO etc. as well as external climate forcings (ECFs) viz. Greenhouse Gases, volcanic eruptions, and Total Solar Irradiance (TSI). We investigate the influence of ICFs and ECFs on AISMR using recently developed statistical technique called De-trended Partial-Cross-Correlation Analysis (DPCCA). DPCCA can analyse a complex system of several interlinked variables. Often, climatic variables, being cross correlated, are simultaneously tele-connected with several other variables and it is not easy to isolate their intrinsic relationship. In the presence of non-stationarities and background signals the calculated correlation coefficients can be overestimated and erroneous. DPCCA method removes the non-stationarities and partials out the influence of background signals from the variables being cross correlated and thus give a robust estimate of correlation. We have performed the analysis using NOAA Reconstructed SSTs and homogenised instrumental AISMR data set from 1854-1999. By employing the DPCCA method we find that there is a statistically insignificant negative intrinsic relation (by excluding the influence of ICFs, and ECFs except TSI) between AISMR and TSI on decadal to centennial time scale. The ICFs considerably modulate the relation between AISMR and solar activity between 50-80 year time scales and transform this relationship to statistically significant positive. We conclude that the positive relation between AISMR and solar activity, as found by other authors, is due to the combined effect of AMO, PDO and multi-decadal ENSO variability on AISMR. The solar activity influences the ICFs and this influence is then transmitted to AISMR. Further, we find that there is statistically positive intrinsic relation between AISMR and AMO from 26 to 100 year time scales which is modulated by ICFs (PDO, ENSO) and ECFs. PDO, ENSO, and solar activity weaken this intrinsic relationship whereas the combined effect of ECFc (solar activity, volcanic eruptions, CO2, & tropospheric aerosol optical depth) results in strengthening of this relationship from 70 to 100 year time scales. There is a negative intrinsic relation between AISMR and PDO which is not statistically significant at any time scale. However this relationship becomes statistically significant only in the presence of combined effect of North Atlantic SSTs and ENSO (4-39 year time scale) and individual effect of TSI (3-26 year time scale) on AISMR. We also find that there is statistical significant negative relationship between AISMR and ENSO on inter-annual to centennial time scale and the strength of this relationship is modulated by solar activity from 3 to 40 year time scale.

Projections of annual rainfall and surface temperature from CMIP5 models over the BIMSTEC countries

NASA Astrophysics Data System (ADS)

Pattnayak, K. C.; Kar, S. C.; Dalal, Mamta; Pattnayak, R. K.

2017-05-01

Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) comprising Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand brings together 21% of the world population. Thus the impact of climate change in this region is a major concern for all. To study the climate change, fifth phase of Climate Model Inter-comparison Project (CMIP5) models have been used to project the climate for the 21st century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 over the BIMSTEC countries for the period 1901 to 2100 (initial 105 years are historical period and the later 95 years are projected period). Climate change in the projected period has been examined with respect to the historical period. In order to validate the models, the mean annual rainfall has been compared with observations from multiple sources and temperature has been compared with the data from Climatic Research Unit (CRU) during the historical period. Comparison reveals that ensemble mean of the models is able to represent the observed spatial distribution of rainfall and temperature over the BIMSTEC countries. Therefore, data from these models may be used to study the future changes in the 21st century. Four out of six models show that the rainfall over India, Thailand and Myanmar has decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka show an increasing trend in both the RCP scenarios. In case of temperature, all the models show an increasing trend over all the BIMSTEC countries in both the scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. The rate of increase/decrease in rainfall and temperature are relatively more in RCP8.5 than RCP4.5 over all these countries. Inter-model comparison show that there are uncertainties within the CMIP5 model projections. More similar studies are required to be done for better understanding the model uncertainties in climate projections over this region.

The predicted CLARREO sampling error of the inter-annual SW variability

NASA Astrophysics Data System (ADS)

Doelling, D. R.; Keyes, D. F.; Nguyen, C.; Macdonnell, D.; Young, D. F.

2009-12-01

The NRC Decadal Survey has called for SI traceability of long-term hyper-spectral flux measurements in order to monitor climate variability. This mission is called the Climate Absolute Radiance and Refractivity Observatory (CLARREO) and is currently defining its mission requirements. The requirements are focused on the ability to measure decadal change of key climate variables at very high accuracy. The accuracy goals are set using anticipated climate change magnitudes, but the accuracy achieved for any given climate variable must take into account the temporal and spatial sampling errors based on satellite orbits and calibration accuracy. The time period to detect a significant trend in the CLARREO record depends on the magnitude of the sampling calibration errors relative to the current inter-annual variability. The largest uncertainty in climate feedbacks remains the effect of changing clouds on planetary energy balance. Some regions on earth have strong diurnal cycles, such as maritime stratus and afternoon land convection; other regions have strong seasonal cycles, such as the monsoon. However, when monitoring inter-annual variability these cycles are only important if the strength of these cycles vary on decadal time scales. This study will attempt to determine the best satellite constellations to reduce sampling error and to compare the error with the current inter-annual variability signal to ensure the viability of the mission. The study will incorporate Clouds and the Earth's Radiant Energy System (CERES) (Monthly TOA/Surface Averages) SRBAVG product TOA LW and SW climate quality fluxes. The fluxes are derived by combining Terra (10:30 local equator crossing time) CERES fluxes with 3-hourly 5-geostationary satellite estimated broadband fluxes, which are normalized using the CERES fluxes, to complete the diurnal cycle. These fluxes were saved hourly during processing and considered the truth dataset. 90°, 83° and 74° inclination precessionary orbits as well as sun-synchronous orbits will be evaluated. This study will focus on the SW radiance, since these low earth orbits are only in daylight for half the orbit. The precessionary orbits were designed to cycle through all solar zenith angles over the course of a year. The inter-annual variability sampling error will be stratified globally/zonally and annually/seasonally and compared with the corresponding truth anomalies.

Regional meteorological drivers and long term trends of winter-spring nitrate dynamics across watersheds in northeastern North America

USGS Publications Warehouse

Crossman, Jill; Eimers, M Catherine; Casson, Nora J.; Burns, Douglas A.; Campbell, John L.; Likens, Gene E; Mitchell, Myron J; Nelson, Sarah J.; Shanley, James B.; Watmough, Shaun A.; Webster, Kara L

2016-01-01

This study evaluated the contribution of winter rain-on-snow (ROS) events to annual and seasonal nitrate (N-NO3) export and identified the regional meteorological drivers of inter-annual variability in ROS N-NO3 export (ROS-N) at 9 headwater streams located across Ontario, Canada and the northeastern United States. Although on average only 3.3 % of annual precipitation fell as ROS during winter over the study period, these events contributed a significant proportion of annual and winter N-NO3 export at the majority of sites (average of 12 and 42 %, respectively); with the exception of the most northern catchment, where total winter precipitation was exceptionally low (average 77 mm). In years with a greater magnitude of ROS events, the timing of the peak N-NO3 export period (during spring melt) was redistributed to earlier in the year. Variability in ROS frequency and magnitude amongst sites was high and a generalised linear model demonstrated that this spatial variability could be explained by interactive effects between regional and site-specific drivers. Snowpack coverage was particularly important for explaining the site-specific ROS response. Specifically, ROS events were less common when higher temperatures eliminated snow cover despite increasing the proportion of winter rainfall, whereas ROS event frequency was greater at sites where sufficient snow cover remained. This research suggests that catchment response to changes in N deposition is sensitive to climate change; a vulnerability which appears to vary in intensity throughout the seasonally snow-covered temperate region. Furthermore, the sensitivity of stream N-NO3 export to ROS events and potential shifts (earlier) in the timing of N-NO3 export relative to other nutrients affect downstream nutrient stoichiometry and the community composition of phytoplankton and other algae.

Cross-timescale Interference and Rainfall Extreme Events in South Eastern South America

NASA Astrophysics Data System (ADS)

Munoz, Angel G.

The physical mechanisms and predictability associated with extreme daily rainfall in South East South America (SESA) are investigated for the December-February season. Through a k-mean analysis, a robust set of daily circulation regimes is identified and then it is used to link the frequency of rainfall extreme events with large-scale potential predictors at subseasonal-to-seasonal scales. This basic set of daily circulation regimes is related to the continental and oceanic phases of the South Atlantic Convergence Zone (SACZ) and wave train patterns superimposed on the Southern Hemisphere Polar Jet. Some of these recurrent synoptic circulation types are conducive to extreme rainfall events in the region through synoptic control of different meso-scale physical features and, at the same time, are influenced by climate phenomena that could be used as sources of potential predictability. Extremely high rainfall (as measured by the 95th- and 99th-percentiles) is preferentially associated with two of these weather types, which are characterized by moisture advection intrusions from lower latitudes and the Pacific; another three weather types, characterized by above-normal moisture advection toward lower latitudes or the Andes, are preferentially associated with dry days (days with no rain). The analysis permits the identification of several subseasonal-to-seasonal scale potential predictors that modulate the occurrence of circulation regimes conducive to extreme rainfall events in SESA. It is conjectured that a cross-timescale interference between the different climate drivers improves the predictive skill of extreme precipitation in the region. The potential and real predictive skill of the frequency of extreme rainfall is then evaluated, finding evidence indicating that mechanisms of climate variability at one timescale contribute to the predictability at another scale, i.e., taking into account the interference of different potential sources of predictability at different timescales increases the predictive skill. This fact is in agreement with the Cross-timescale Interference Conjecture proposed in the first part of the thesis. At seasonal scale, a combination of those weather types tends to outperform all the other potential predictors explored, i.e., sea surface temperature patterns, phases of the Madden-Julian Oscillation, and combinations of both. Spatially averaged Kendall’s τ improvements of 43% for the potential predictability and 23% for realtime predictions are attained with respect to standard models considering sea-surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed, based on probability forecasts of seasonal sequences of these weather types. The cross-validated realtime skill of the new probabilistic approach, as measured by the Hit Score and the Heidke Skill Score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season, but also in how, when and where those events will probably occur. In order to gain further understanding about how the cross-timescale interference occurs, an externally-forced Lorenz model is used to explore the impact of different kind of forcings, at inter-annual and decadal scales, in the establishment of constructive interactions associated with the simulated “extreme events”. Using a wavelet analysis, it is shown that this simple model is capable of reproducing the same kind of cross-timescale structures observed in the wavelet power spectrum of the Nino3.4 index only when it is externally forced by both inter-annual and decadal signals: the annual cycle and a decadal forcing associated with the natural solar variability. The nature of this interaction is non-linear, and it impacts both mean and extreme values in the time series. No predictive power was found when using metrics like standard deviation and auto-correlation. Nonetheless, it was proposed that an early warning signal for occurrence of extreme rainfall in SESA may be possible via a continuous monitoring of relative phases between the cross-timescale leading components.

Multi-model trends in East African rainfall associated with increased CO2

NASA Astrophysics Data System (ADS)

McHugh, Maurice J.

2005-01-01

Nineteen coupled ocean-atmosphere general circulation models participating in the Coupled Model Intercomparison Program (CMIP) were used to analyze future rainfall conditions over East Africa under enhanced CO2 conditions. 80 year control runs of these models indicated that four models produced mean annual rainfall distributions closely resembling climatological means and all four models had normalized root mean square errors well within the bounds of observed variability. East African (10°N-20°S, 25°-50°E) rainfall data from transient 80 year experiments which featured CO2 increases of 1% per year were compared with 80 year control simulations. Results indicate enhanced annual and seasonal rainfall rates, and increased extreme wet period frequency. These results indicate that East Africa may face a future in which mosquito-borne diseases such as malaria and Rift Valley fever proliferate resulting from increased CO2.

Mechanisms for Diurnal Variability of Global Tropical Rainfall Observed from TRMM

NASA Technical Reports Server (NTRS)

Yang, Song; Smith, Eric A.

2004-01-01

The behavior and various controls of diurnal variability in tropical-subtropical rainfall are investigated using Tropical Rainfall Measuring Mission (TRMM) precipitation measurements retrieved from: (1) TRMM Microwave Imager (TMI), (2) Precipitation Radar (PR), and (3) TMI/PR Combined, standard level 2 algorithms for the 1998 annual cycle. Results show that the diurnal variability characteristics of precipitation are consistent for all three algorithms, providing assurance that TRMM retrievals are providing consistent estimates of rainfall variability. As anticipated, most ocean areas exhibit more rainfall at night, while over most land areas rainfall peaks during daytime ,however, various important exceptions are found. The dominant feature of the oceanic diurnal cycle is a rainfall maximum in late-evening/early-morning (LE-EM) hours, while over land the dominant maximum occurs in the mid- to late-afternoon (MLA). In conjunction with these maxima are pronounced seasonal variations of the diurnal amplitudes. Amplitude analysis shows that the diurnal pattern and its seasonal evolution are closely related to the rainfall accumulation pattern and its seasonal evolution. In addition, the horizontal distribution of diurnal variability indicates that for oceanic rainfall there is a secondary MLA maximum, co-existing with the LE-EM maximum, at latitudes dominated by large scale convergence and deep convection. Analogously, there is a preponderance for an LE-EM maximum over land, co-existing with the stronger MLA maximum, although it is not evident that this secondary continental feature is closely associated with the large scale circulation. The ocean results clearly indicate that rainfall diurnal variability associated with large scale convection is an integral part of the atmospheric general circulation.

The role of climate and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria

NASA Astrophysics Data System (ADS)

Abdussalam, Auwal; Thornes, John; Leckebusch, Gregor

2015-04-01

Nigeria has a number of climate-sensitive infectious diseases; one of the most important of these diseases that remains a threat to public health is cholera. This study investigates the influences of both meteorological and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria. A stepwise multiple regression models are used to estimate the influence of the year-to-year variations of cholera cases and deaths for individual states in the country and as well for three groups of states that are classified based on annual rainfall amount. Specifically, seasonal mean maximum and minimum temperatures and annual rainfall totals were analysed with annual aggregate count of cholera cases and deaths, taking into account of the socioeconomic factors that are potentially enhancing vulnerability such as: absolute poverty, adult literacy, access to pipe borne water and population density. Result reveals that the most important explanatory meteorological and socioeconomic variables in explaining the spatiotemporal variability of the disease are rainfall totals, seasonal mean maximum temperature, absolute poverty, and accessibility to pipe borne water. The influences of socioeconomic factors appeared to be more pronounced in the northern part of the country, and vice-versa in the case of meteorological factors. Also, cross validated models output suggests a strong possibility of disease prediction, which will help authorities to put effective control measures in place which depend on prevention, and or efficient response.

Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

PubMed

van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

2015-05-01

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Smallholder Socio-hydrological Modelling Framework

NASA Astrophysics Data System (ADS)

Pande, S.; Savenije, H.; Rathore, P.

2014-12-01

Small holders are farmers who own less than 2 ha of farmland. They often have low productivity and thus remain at subsistence level. A fact that nearly 80% of Indian farmers are smallholders, who merely own a third of total farmlands and belong to the poorest quartile, but produce nearly 40% of countries foodgrains underlines the importance of understanding the socio-hydrology of a small holder. We present a framework to understand the socio-hydrological system dynamics of a small holder. It couples the dynamics of 6 main variables that are most relevant at the scale of a small holder: local storage (soil moisture and other water storage), capital, knowledge, livestock production, soil fertility and grass biomass production. The model incorporates rule-based adaptation mechanisms (for example: adjusting expenditures on food and fertilizers, selling livestocks etc.) of small holders when they face adverse socio-hydrological conditions, such as low annual rainfall, higher intra-annual variability in rainfall or variability in agricultural prices. It allows us to study sustainability of small holder farming systems under various settings. We apply the framework to understand the socio-hydrology of small holders in Aurangabad, Maharashtra, India. This district has witnessed suicides of many sugarcane farmers who could not extricate themselves out of the debt trap. These farmers lack irrigation and are susceptible to fluctuating sugar prices and intra-annual hydroclimatic variability. This presentation discusses two aspects in particular: whether government interventions to absolve the debt of farmers is enough and what is the value of investing in local storages that can buffer intra-annual variability in rainfall and strengthening the safety-nets either by creating opportunities for alternative sources of income or by crop diversification.

Adaptability and performance of short-season maize hybrids in the southern high plains

USDA-ARS?s Scientific Manuscript database

Drought incidences change with year and location, and are prevalent in the Southern High Plains where annual rainfall is low and highly variable and most maize and other crops are irrigated. The low rainfall and groundwater overuse are leading to shortages of water for crop irrigation in this regio...

Analysis of water-level fluctuations of Lakes Winona and Winnemissett-- two landlocked lakes in a karst terrane in Volusia County, Florida

USGS Publications Warehouse

Hughes, G.H.

1979-01-01

The water levels of Lakes Winona and Winnemissett in Volusia County, Fla., correlate reasonably well during dry spells but only poorly during wet spells. Disparities develop mostly at times when the lake levels rise abruptly owing to rainstorms passing over the lake basins. The lack of correlation is attributed to the uneven distribution of the storm rainfall, even though the average annual rainfall at National Weather Service gages in the general area of the lakes is about the same. Analyses of the monthly rainfall data show that the rainfall variability between gages is sufficient to account for most of the disparity between monthly changes in the levels of the two lakes. The total annual rainfall at times may differ between rainfall gages by as much as 15 to 20 inches. Such differences tend to balance over the long term but may persist in the same direction for two or more years, causing apparent anomalies in lake-level fluctuations. (Woodard-USGS)

Spatial structure of monthly rainfall measurements average over 25 years and trends of the hourly variability of a current rainy day in Rwanda.

NASA Astrophysics Data System (ADS)

Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

2013-04-01

Climate plays a vital role in a wide range of socio-economic activities of most nations particularly of developing countries. Climate (rainfall) plays a central role in agriculture which is the main stay of the Rwandan economy and community livelihood and activities. The majority of the Rwandan population (81,1% in 2010) relies on rain fed agriculture for their livelihoods, and the impacts of variability in climate patterns are already being felt. Climate-related events like heavy rainfall or too little rainfall are becoming more frequent and are impacting on human wellbeing.The torrential rainfall that occurs every year in Rwanda could disturb the circulation for many days, damages houses, infrastructures and causes heavy economic losses and deaths. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). Globally, the spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front» mechanism. What is the hourly variability in this mountainous area? Is there any correlation with the identified zones of the monthly average series (from 1965 to 1990 established by the Rwandan meteorological services)? Where could we have hazards with several consecutive rainy days (using forecasted datas from the Norwegian Meteorological Institute)? Spatio-temporal analysis allows for identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting these hydrological events. The objective of our current research (Rainfall variability) is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical predictions and simulations, machine learning algorithm (different types of neural networks) and GIS. Hybrid models - mixing geostatistics and machine learning, will be applied to study spatial non-stationarity of rainfall fields. The research will include rainfalls variability mapping and probabilistic analyses of extreme events. Key words: rainfall variability, Rwanda, extreme event, model, mapping, geostatistics.

Climatic driving forces in inter-annual variation of global FPAR

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Liu, Liangyun; Yang, Xiaohua; Zhou, Bin

2012-09-01

Fraction of Absorbed Photosynthetically Active Radiation (FPAR) characterizes vegetation canopy functioning and its energy absorption capacity. In this paper, we focus on climatic driving forces in inter-annual variation of global FPAR from 1982 to 2006 by Global Historical Climatology Network (GHCN-Monthly) data. Using FPAR-Simple Ratio Vegetation Index (SR) relationship, Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) was used to estimate FPAR at the global scale. The correlation between inter-annual variation of FPAR and temperature, precipitation derived from GHCN-Monthly was examined, during the periods of March-May (MAM), June-August (JJA), September-November (SON), and December-February (DJF) over from 1982 to 2006. The analysis of climatic influence on global FPAR revealed the significant correlation with temperature and precipitation in some meteorological stations area, and a more significant correlation with precipitation was found than which with temperature. Some stations in the regions between 30° N and 60° N and around 30° S in South America, where the annual FPAR variation showed a significant positive correlation with temperature (P < 0.01 or P < 0.05) during MAM, SON, and DJF, as well as in Europe during MAM and SON period. A negative correlation for more stations was observed during JJA. For precipitation, there were many stations showed a significant positive correlation with inter-annual variation of global FPAR (P < 0.01 or P < 0.05), especially for the tropical rainfall forest of Africa and Amazon during the dry season of JJA and SON.

Assessment of Surface Water Storage trends for increasing groundwater areas in India

NASA Astrophysics Data System (ADS)

Banerjee, Chandan; Kumar, D. Nagesh

2018-07-01

Recent studies based on Gravity Recovery and Climate Experiment (GRACE) satellite mission suggested that groundwater has increased in central and southern parts of India. However, surface water, which is an equally important source of water in these semi-arid areas has not been studied yet. In the present study, the study areas were outlined based on trends in GRACE data followed by trend identification in surface water storages and checking the hypothesis of causality. Surface Water Extent (SWE) and Surface Soil Moisture (SSM) derived from Moderate-resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) respectively, are selected as proxies of surface water storage (SWS). Besides SWE and SSM, trend test was performed for GRACE derived terrestrial water storage (TWS) for the study areas named as R1, R2, GOR1 and KOR1. Granger-causality test is used to test the hypothesis that rainfall is a causal factor of the inter-annual variability of SWE, SSM and TWS. Positive trends were observed in TWS for R1, R2 and GOR1 whereas SWE and SSM show increasing trends for all the study regions. Results suggest that rainfall is the granger-causal of all the storage variables for R1 and R2, the regions exhibiting the most significant positive trends in TWS.

Inter-annual variability of carbon fluxes in temperate forest ecosystems: effects of biotic and abiotic factors

NASA Astrophysics Data System (ADS)

Chen, M.; Keenan, T. F.; Hufkens, K.; Munger, J. W.; Bohrer, G.; Brzostek, E. R.; Richardson, A. D.

2014-12-01

Carbon dynamics in terrestrial ecosystems are influenced by both abiotic and biotic factors. Abiotic factors, such as variation in meteorological conditions, directly drive biophysical and biogeochemical processes; biotic factors, referring to the inherent properties of the ecosystem components, reflect the internal regulating effects including temporal dynamics and memory. The magnitude of the effect of abiotic and biotic factors on forest ecosystem carbon exchange has been suggested to vary at different time scales. In this study, we design and conduct a model-data fusion experiment to investigate the role and relative importance of the biotic and abiotic factors for inter-annual variability of the net ecosystem CO2 exchange (NEE) of temperate deciduous forest ecosystems in the Northeastern US. A process-based model (FöBAAR) is parameterized at four eddy-covariance sites using all available flux and biometric measurements. We conducted a "transplant" modeling experiment, that is, cross- site and parameter simulations with different combinations of site meteorology and parameters. Using wavelet analysis and variance partitioning techniques, analysis of model predictions identifies both spatial variant and spatially invariant parameters. Variability of NEE was primarily modulated by gross primary productivity (GPP), with relative contributions varying from hourly to yearly time scales. The inter-annual variability of GPP and NEE is more regulated by meteorological forcing, but spatial variability in certain model parameters (biotic response) has more substantial effects on the inter-annual variability of ecosystem respiration (Reco) through the effects on carbon pools. Both the biotic and abiotic factors play significant roles in modulating the spatial and temporal variability in terrestrial carbon cycling in the region. Together, our study quantifies the relative importance of both, and calls for better understanding of them to better predict regional CO2 exchanges.

A stochastical event-based continuous time step rainfall generator based on Poisson rectangular pulse and microcanonical random cascade models

NASA Astrophysics Data System (ADS)

Pohle, Ina; Niebisch, Michael; Zha, Tingting; Schümberg, Sabine; Müller, Hannes; Maurer, Thomas; Hinz, Christoph

2017-04-01

Rainfall variability within a storm is of major importance for fast hydrological processes, e.g. surface runoff, erosion and solute dissipation from surface soils. To investigate and simulate the impacts of within-storm variabilities on these processes, long time series of rainfall with high resolution are required. Yet, observed precipitation records of hourly or higher resolution are in most cases available only for a small number of stations and only for a few years. To obtain long time series of alternating rainfall events and interstorm periods while conserving the statistics of observed rainfall events, the Poisson model can be used. Multiplicative microcanonical random cascades have been widely applied to disaggregate rainfall time series from coarse to fine temporal resolution. We present a new coupling approach of the Poisson rectangular pulse model and the multiplicative microcanonical random cascade model that preserves the characteristics of rainfall events as well as inter-storm periods. In the first step, a Poisson rectangular pulse model is applied to generate discrete rainfall events (duration and mean intensity) and inter-storm periods (duration). The rainfall events are subsequently disaggregated to high-resolution time series (user-specified, e.g. 10 min resolution) by a multiplicative microcanonical random cascade model. One of the challenges of coupling these models is to parameterize the cascade model for the event durations generated by the Poisson model. In fact, the cascade model is best suited to downscale rainfall data with constant time step such as daily precipitation data. Without starting from a fixed time step duration (e.g. daily), the disaggregation of events requires some modifications of the multiplicative microcanonical random cascade model proposed by Olsson (1998): Firstly, the parameterization of the cascade model for events of different durations requires continuous functions for the probabilities of the multiplicative weights, which we implemented through sigmoid functions. Secondly, the branching of the first and last box is constrained to preserve the rainfall event durations generated by the Poisson rectangular pulse model. The event-based continuous time step rainfall generator has been developed and tested using 10 min and hourly rainfall data of four stations in North-Eastern Germany. The model performs well in comparison to observed rainfall in terms of event durations and mean event intensities as well as wet spell and dry spell durations. It is currently being tested using data from other stations across Germany and in different climate zones. Furthermore, the rainfall event generator is being applied in modelling approaches aimed at understanding the impact of rainfall variability on hydrological processes. Reference Olsson, J.: Evaluation of a scaling cascade model for temporal rainfall disaggregation, Hydrology and Earth System Sciences, 2, 19.30

Inter Annual Variability of the Acoustic Propagation in the Yellow Sea Identified from a Synoptic Monthly Gridded Database as Compared with GDEM

DTIC Science & Technology

2016-09-01

the world climate is in fact warming due to anthropogenic causes (Anderegg et al. 2010; Solomon et al. 2009). To put this in terms for this research ...2006). The present research uses a 0.5’ resolution. B. SEDIMENTS DATABASE There are four openly available sediment databases: Enhanced, Standard...DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) This research investigates the inter-annual acoustic variability in the Yellow Sea identified from

Effect of inter-annual variability in pasture growth and irrigation response on farm productivity and profitability based on biophysical and farm systems modelling.

PubMed

Vogeler, Iris; Mackay, Alec; Vibart, Ronaldo; Rendel, John; Beautrais, Josef; Dennis, Samuel

2016-09-15

Farm system and nutrient budget models are increasingly being used in analysis to inform on farm decision making and evaluate land use policy options at regional scales. These analyses are generally based on the use of average annual pasture yields. In New Zealand (NZ), like in many countries, there is considerable inter-annual variation in pasture growth rates, due to climate. In this study a modelling approach was used to (i) include inter-annual variability as an integral part of the analysis and (ii) test the approach in an economic analysis of irrigation in a case study within the Hawkes Bay Region of New Zealand. The Agricultural Production Systems Simulator (APSIM) was used to generate pasture dry matter yields (DMY) for 20 different years and under both dryland and irrigation. The generated DMY were linked to outputs from farm-scale modelling for both Sheep and Beef Systems (Farmaxx Pro) and Dairy Systems (Farmax® Dairy Pro) to calculate farm production over 20 different years. Variation in DMY and associated livestock production due to inter-annual variation in climate was large, with a coefficient of variations up to 20%. Irrigation decreased this inter-annual variation. On average irrigation, with unlimited available water, increased income by $831 to 1195/ha, but when irrigation was limited to 250mm/ha/year income only increased by $525 to 883/ha. Using pasture responses in individual years to capturing the inter-annual variation, rather than the pasture response averaged over 20years resulted in lower financial benefits. In the case study income from irrigation based on an average year were 10 to >20% higher compared with those obtained from individual years. Copyright © 2016 Elsevier B.V. All rights reserved.

The Variation of Tropical Cyclone Rainfall within the North Atlantic and Pacific as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward; Pierce, Harold; Adler, Robert

1999-01-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations in the North Atlantic and in three equal geographical regions of the North Pacific (i.e., Western, Central, and Eastern North Pacific). These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the 1987-1989, 1991-1998 North Atlantic and Pacific rainfall during June-November when tropical cyclones are most abundant. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from the Defence Meteorological Satellite Program (DMSP) Special Sensor Microwave/ Radiometer (SSM/I) observations within 444 km radius of the center of those North Atlantic and Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are then multiplied by the number of hours in a given month. Mean monthly rainfall amounts are also constructed for all the other North Atlantic and Pacific raining systems during this eleven year period for the purpose of estimating the geographical distribution and intensity of rainfall contributed by non-tropical cyclone systems. Further, the combination of the non-tropical cyclone and tropical cyclone (i.e., total) rainfall is constructed to delineate the fractional amount that tropical cyclones contributed to the total North Pacific rainfall.

A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models

PubMed Central

Stratton, Margaret D.; Ehrlich, Hanna Y.; Mor, Siobhan M.; Naumova, Elena N.

2017-01-01

Ross River virus (RRV), Barmah Forest virus (BFV), and dengue are three common mosquito-borne diseases in Australia that display notable seasonal patterns. Although all three diseases have been modeled on localized scales, no previous study has used harmonic models to compare seasonality of mosquito-borne diseases on a continent-wide scale. We fit Poisson harmonic regression models to surveillance data on RRV, BFV, and dengue (from 1993, 1995 and 1991, respectively, through 2015) incorporating seasonal, trend, and climate (temperature and rainfall) parameters. The models captured an average of 50–65% variability of the data. Disease incidence for all three diseases generally peaked in January or February, but peak timing was most variable for dengue. The most significant predictor parameters were trend and inter-annual periodicity for BFV, intra-annual periodicity for RRV, and trend for dengue. We found that a Temperature Suitability Index (TSI), designed to reclassify climate data relative to optimal conditions for vector establishment, could be applied to this context. Finally, we extrapolated our models to estimate the impact of a false-positive BFV epidemic in 2013. Creating these models and comparing variations in periodicities may provide insight into historical outbreaks as well as future patterns of mosquito-borne diseases. PMID:28071683

A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models.

PubMed

Stratton, Margaret D; Ehrlich, Hanna Y; Mor, Siobhan M; Naumova, Elena N

2017-01-10

Ross River virus (RRV), Barmah Forest virus (BFV), and dengue are three common mosquito-borne diseases in Australia that display notable seasonal patterns. Although all three diseases have been modeled on localized scales, no previous study has used harmonic models to compare seasonality of mosquito-borne diseases on a continent-wide scale. We fit Poisson harmonic regression models to surveillance data on RRV, BFV, and dengue (from 1993, 1995 and 1991, respectively, through 2015) incorporating seasonal, trend, and climate (temperature and rainfall) parameters. The models captured an average of 50-65% variability of the data. Disease incidence for all three diseases generally peaked in January or February, but peak timing was most variable for dengue. The most significant predictor parameters were trend and inter-annual periodicity for BFV, intra-annual periodicity for RRV, and trend for dengue. We found that a Temperature Suitability Index (TSI), designed to reclassify climate data relative to optimal conditions for vector establishment, could be applied to this context. Finally, we extrapolated our models to estimate the impact of a false-positive BFV epidemic in 2013. Creating these models and comparing variations in periodicities may provide insight into historical outbreaks as well as future patterns of mosquito-borne diseases.

A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models

NASA Astrophysics Data System (ADS)

Stratton, Margaret D.; Ehrlich, Hanna Y.; Mor, Siobhan M.; Naumova, Elena N.

2017-01-01

Ross River virus (RRV), Barmah Forest virus (BFV), and dengue are three common mosquito-borne diseases in Australia that display notable seasonal patterns. Although all three diseases have been modeled on localized scales, no previous study has used harmonic models to compare seasonality of mosquito-borne diseases on a continent-wide scale. We fit Poisson harmonic regression models to surveillance data on RRV, BFV, and dengue (from 1993, 1995 and 1991, respectively, through 2015) incorporating seasonal, trend, and climate (temperature and rainfall) parameters. The models captured an average of 50-65% variability of the data. Disease incidence for all three diseases generally peaked in January or February, but peak timing was most variable for dengue. The most significant predictor parameters were trend and inter-annual periodicity for BFV, intra-annual periodicity for RRV, and trend for dengue. We found that a Temperature Suitability Index (TSI), designed to reclassify climate data relative to optimal conditions for vector establishment, could be applied to this context. Finally, we extrapolated our models to estimate the impact of a false-positive BFV epidemic in 2013. Creating these models and comparing variations in periodicities may provide insight into historical outbreaks as well as future patterns of mosquito-borne diseases.

Annual rings in a native Hawaiian tree, Sophora chrysophylla, on Maunakea, Hawai‘i

Treesearch

Kainana S. Francisco; Patrick J. Hart; Jinbao Li; Edward R. Cook; Patrick J. Baker

2015-01-01

Annual rings are not commonly produced in tropical trees because they grow in a relatively aseasonal environment. However, in the subalpine zones of Hawai‘i's highest volcanoes, there is often strong seasonal variability in temperature and rainfall. Using classical dendrochronological methods, annual growth rings were shown to occur in Sophora...

The Influences of Drought and Land-Cover Conversion on Inter-Annual Variation of NPP in the Three-North Shelterbelt Program Zone of China Based on MODIS Data

PubMed Central

Wu, Chaoyang; Zhang, Bing; Huete, Alfredo; Zhang, Xiaoyang; Sun, Rui; Lei, Liping; Huang, Wenjing; Liu, Liangyun; Liu, Xinjie; Li, Jun; Luo, Shezhou; Fang, Bin

2016-01-01

Terrestrial ecosystems greatly contribute to carbon (C) emission reduction targets through photosynthetic C uptake.Net primary production (NPP) represents the amount of atmospheric C fixed by plants and accumulated as biomass. The Three-North Shelterbelt Program (TNSP) zone accounts for more than 40% of China’s landmass. This zone has been the scene of several large-scale ecological restoration efforts since the late 1990s, and has witnessed significant changes in climate and human activities.Assessing the relative roles of different causal factors on NPP variability in TNSP zone is very important for establishing reasonable local policies to realize the emission reduction targets for central government. In this study, we examined the relative roles of drought and land cover conversion(LCC) on inter-annual changes of TNSP zone for 2001–2010. We applied integrated correlation and decomposition analyses to a Standardized Evapotranspiration Index (SPEI) and MODIS land cover dataset. Our results show that the 10-year average NPP within this region was about 420 Tg C. We found that about 60% of total annual NPP over the study area was significantly correlated with SPEI (p<0.05). The LCC-NPP relationship, which is especially evident for forests in the south-central area, indicates that ecological programs have a positive impact on C sequestration in the TNSP zone. Decomposition analysis generally indicated that the contributions of LCC, drought, and other Natural or Anthropogenic activities (ONA) to changes in NPP generally had a consistent distribution pattern for consecutive years. Drought and ONA contributed about 74% and 23% to the total changes in NPP, respectively, and the remaining 3% was attributed to LCC. Our results highlight the importance of rainfall supply on NPP variability in the TNSP zone. PMID:27348303

How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data

NASA Astrophysics Data System (ADS)

Rödenbeck, Christian; Zaehle, Sönke; Keeling, Ralph; Heimann, Martin

2018-04-01

The response of the terrestrial net ecosystem exchange (NEE) of CO2 to climate variations and trends may crucially determine the future climate trajectory. Here we directly quantify this response on inter-annual timescales by building a linear regression of inter-annual NEE anomalies against observed air temperature anomalies into an atmospheric inverse calculation based on long-term atmospheric CO2 observations. This allows us to estimate the sensitivity of NEE to inter-annual variations in temperature (seen as a climate proxy) resolved in space and with season. As this sensitivity comprises both direct temperature effects and the effects of other climate variables co-varying with temperature, we interpret it as inter-annual climate sensitivity. We find distinct seasonal patterns of this sensitivity in the northern extratropics that are consistent with the expected seasonal responses of photosynthesis, respiration, and fire. Within uncertainties, these sensitivity patterns are consistent with independent inferences from eddy covariance data. On large spatial scales, northern extratropical and tropical inter-annual NEE variations inferred from the NEE-T regression are very similar to the estimates of an atmospheric inversion with explicit inter-annual degrees of freedom. The results of this study offer a way to benchmark ecosystem process models in more detail than existing effective global climate sensitivities. The results can also be used to gap-fill or extrapolate observational records or to separate inter-annual variations from longer-term trends.

Statistical Analysis of 30 Years Rainfall Data: A Case Study

NASA Astrophysics Data System (ADS)

Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.

2017-07-01

Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.

Soil Texture Mediates the Response of Tree Cover to Rainfall Intensity in African Savannas

NASA Astrophysics Data System (ADS)

Case, M. F.; Staver, A. C.

2017-12-01

Global circulation models predict widespread shifts in the frequency and intensity of rainfall, even where mean annual rainfall does not change. Resulting changes in soil moisture dynamics could have major consequences for plant communities and ecosystems, but the direction of potential vegetation responses can be challenging to predict. In tropical savannas, where tree and grasses coexist, contradictory lines of evidence have suggested that tree cover could respond either positively or negatively to less frequent, more intense rainfall. Here, we analyzed remote sensing data and continental-scale soils maps to examine whether soil texture or fire could explain heterogeneous responses of savanna tree cover to intra-annual rainfall variability across sub-Saharan Africa. We find that tree cover generally increases with mean wet-season rainfall, decreases with mean wet-season rainfall intensity, and decreases with fire frequency. However, soil sand content mediates these relationships: the response to rainfall intensity switches qualitatively depending on soil texture, such that tree cover decreases dramatically with less frequent, more intense rainfall on clay soils but increases with rainfall intensity on sandy soils in semi-arid savannas. We propose potential ecohydrological mechanisms for this heterogeneous response, and emphasize that predictions of savanna vegetation responses to global change should account for interactions between soil texture and changing rainfall patterns.

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.

Effect of biotic and abiotic factors on inter- and intra-event variability in stemflow rates in oak and pine stands in a Mediterranean mountain area

NASA Astrophysics Data System (ADS)

Cayuela, C.; Llorens, P.; Sánchez-Costa, E.; Levia, D. F.; Latron, J.

2018-05-01

Stemflow, despite being a small proportion of gross rainfall, is an important and understudied flux of water in forested areas. Recent studies have highlighted its complexity and relative importance for understanding soil and groundwater recharge. Stemflow dynamics offer an insight into how rain water is stored and released from the stems of trees to the soil. Past attempts have been made to understand the variability of stemflow under different types of vegetation, but rather few studies have focused on the combined influence of biotic and abiotic factors on inter and intra-storm stemflow variability, and none in Mediterranean climates. This study presents stemflow data collected at high temporal resolution for two species with contrasting canopies and bark characteristics: Quercus pubescens Willd. (downy oak) and Pinus sylvestris L. (Scots pine) in the Vallcebre research catchments (NE of Spain, 42° 12‧N, 1° 49‧E). The main objective was to understand how the interaction of biotic and abiotic factors affected stemflow dynamics. Mean stemflow production was low for both species (∼1% of incident rainfall) and increased with rainfall amount. However, the magnitude of the response depended on the combination of multiple biotic and abiotic factors. Both species produced similar stemflow volumes and the largest differences were found among trees of the same species. The combined analysis of biotic and abiotic factors showed that funneling ratios and stemflow dynamics were highly influenced by the interaction of rainfall intensity and tree size.

Yearly fluctuations of flower landscape in a Mediterranean scrubland: Consequences for floral resource availability.

PubMed

Flo, Víctor; Bosch, Jordi; Arnan, Xavier; Primante, Clara; Martín González, Ana M; Barril-Graells, Helena; Rodrigo, Anselm

2018-01-01

Species flower production and flowering phenology vary from year to year due to extrinsic factors. Inter-annual variability in flowering patterns may have important consequences for attractiveness to pollinators, and ultimately, plant reproductive output. To understand the consequences of flowering pattern variability, a community approach is necessary because pollinator flower choice is highly dependent on flower context. Our objectives were: 1) To quantify yearly variability in flower density and phenology; 2) To evaluate whether changes in flowering patterns result in significant changes in pollen/nectar composition. We monitored weekly flowering patterns in a Mediterranean scrubland community (23 species) over 8 years. Floral resource availability was estimated based on field measures of pollen and nectar production per flower. We analysed inter-annual variation in flowering phenology (duration and date of peak bloom) and flower production, and inter-annual and monthly variability in flower, pollen and nectar species composition. We also investigated potential phylogenetic effects on inter-annual variability of flowering patterns. We found dramatic variation in yearly flower production both at the species and community levels. There was also substantial variation in flowering phenology. Importantly, yearly fluctuations were far from synchronous across species, and resulted in significant changes in floral resources availability and composition at the community level. Changes were especially pronounced late in the season, at a time when flowers are scarce and pollinator visitation rates are particularly high. We discuss the consequences of our findings for pollinator visitation and plant reproductive success in the current scenario of climate change.

Yearly fluctuations of flower landscape in a Mediterranean scrubland: Consequences for floral resource availability

PubMed Central

Primante, Clara; Martín González, Ana M.; Barril-Graells, Helena

2018-01-01

Species flower production and flowering phenology vary from year to year due to extrinsic factors. Inter-annual variability in flowering patterns may have important consequences for attractiveness to pollinators, and ultimately, plant reproductive output. To understand the consequences of flowering pattern variability, a community approach is necessary because pollinator flower choice is highly dependent on flower context. Our objectives were: 1) To quantify yearly variability in flower density and phenology; 2) To evaluate whether changes in flowering patterns result in significant changes in pollen/nectar composition. We monitored weekly flowering patterns in a Mediterranean scrubland community (23 species) over 8 years. Floral resource availability was estimated based on field measures of pollen and nectar production per flower. We analysed inter-annual variation in flowering phenology (duration and date of peak bloom) and flower production, and inter-annual and monthly variability in flower, pollen and nectar species composition. We also investigated potential phylogenetic effects on inter-annual variability of flowering patterns. We found dramatic variation in yearly flower production both at the species and community levels. There was also substantial variation in flowering phenology. Importantly, yearly fluctuations were far from synchronous across species, and resulted in significant changes in floral resources availability and composition at the community level. Changes were especially pronounced late in the season, at a time when flowers are scarce and pollinator visitation rates are particularly high. We discuss the consequences of our findings for pollinator visitation and plant reproductive success in the current scenario of climate change. PMID:29346453

Inter-annual and spatial variability in hillslope runoff and mercury flux during spring snowmelt.

PubMed

Haynes, Kristine M; Mitchell, Carl P J

2012-08-01

Spring snowmelt is an important period of mercury (Hg) export from watersheds. Limited research has investigated the potential effects of climate variability on hydrologic and Hg fluxes during spring snowmelt. The purpose of this research was to assess the potential impacts of inter-annual climate variability on Hg mobility in forested uplands, as well as spatial variability in hillslope hydrology and Hg fluxes. We compared hydrological flows, Hg and solute mobility from three adjacent hillslopes in the S7 watershed of the Marcell Experimental Forest, Minnesota during two very different spring snowmelt periods: one following a winter (2009-2010) with severely diminished snow accumulation (snow water equivalent (SWE) = 48 mm) with an early melt, and a second (2010-2011) with significantly greater winter snow accumulation (SWE = 98 mm) with average to late melt timing. Observed inter-annual differences in total Hg (THg) and dissolved organic carbon (DOC) yields were predominantly flow-driven, as the proportion by which solute yields increased was the same as the increase in runoff. Accounting for inter-annual differences in flow, there was no significant difference in THg and DOC export between the two snowmelt periods. The spring 2010 snowmelt highlighted the important contribution of melting soil frost in the timing of a considerable portion of THg exported from the hillslope, accounting for nearly 30% of the THg mobilized. Differences in slope morphology and soil depths to the confining till layer were important in controlling the large observed spatial variability in hydrological flowpaths, transmissivity feedback responses, and Hg flux trends across the adjacent hillslopes.

Estimation of streamflow, base flow, and nitrate-nitrogen loads in Iowa using multiple linear regression models

USGS Publications Warehouse

Schilling, K.E.; Wolter, C.F.

2005-01-01

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest. (JAWRA) (Copyright ?? 2005).

Assessing future changes in the occurrence of rainfall-induced landslides at a regional scale.

PubMed

Gariano, S L; Rianna, G; Petrucci, O; Guzzetti, F

2017-10-15

According to the fifth report of the Intergovernmental Panel on Climate Change, an increase in the frequency and the intensity of extreme rainfall is expected in the Mediterranean area. Among different impacts, this increase might result in a variation in the frequency and the spatial distribution of rainfall-induced landslides, and in an increase in the size of the population exposed to landslide risk. We propose a method for the regional-scale evaluation of future variations in the occurrence of rainfall-induced landslides, in response to changes in rainfall regimes. We exploit information on the occurrence of 603 rainfall-induced landslides in Calabria, southern Italy, in the period 1981-2010, and daily rainfall data recorded in the same period in the region. Furthermore, we use high-resolution climate projections based on RCP4.5 and RCP8.5 scenarios. In particular, we consider the mean variations between a 30-year future period (2036-2065) and the reference period 1981-2010 in three variables assumed as proxy for landslide activity: annual rainfall, seasonal cumulated rainfall, and annual maxima of daily rainfall. Based on reliable correlations between landslide occurrence and weather variables estimated in the reference period, we assess future variations in rainfall-induced landslide occurrence for all the municipalities of Calabria. A +45.7% and +21.2% average regional variation in rainfall-induced landslide occurrence is expected in the region for the period 2036-2065, under the RCP4.5 and RCP8.5 scenario, respectively. We also investigate the future variations in the impact of rainfall-induced landslides on the population of Calabria. We find a +80.2% and +54.5% increase in the impact on the population for the period 2036-2065, under the RCP4.5 and RCP8.5 scenario, respectively. The proposed method is quantitative and reproducible, thus it can be applied in similar regions, where adequate landslide and rainfall information is available. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying the increasing sensitivity of power systems to climate variability

NASA Astrophysics Data System (ADS)

Bloomfield, H. C.; Brayshaw, D. J.; Shaffrey, L. C.; Coker, P. J.; Thornton, H. E.

2016-12-01

Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insufficient for providing robust power system planning guidance. This suggests renewable integration studies—widely used in policy, investment and system design—should adopt a more robust approach to climate characterisation.

Breeding decisions and output are correlated with both temperature and rainfall in an arid-region passerine, the sociable weaver

PubMed Central

Paquet, Matthieu; Spottiswoode, Claire N.; Covas, Rita

2017-01-01

Animal reproductive cycles are commonly triggered by environmental cues of favourable breeding conditions. In arid environments, rainfall may be the most conspicuous cue, but the effects on reproduction of the high inter- and intra-annual variation in temperature remain poorly understood, despite being relevant to the current context of global warming. Here, we conducted a multiyear examination of the relationships between a suite of measures of temperature and rainfall, and the onset and length of the breeding season, the probability of breeding and reproductive output in an arid-region passerine, the sociable weaver (Philetairus socius). As expected, reproductive output increased with rainfall, yet specific relationships were conditional on the timing of rainfall: clutch production was correlated with rainfall throughout the season, whereas fledgling production was correlated with early summer rainfall. Moreover, we reveal novel correlations between aspects of breeding and temperature, indicative of earlier laying dates after warmer springs, and longer breeding seasons during cooler summers. These results have implications for understanding population trends under current climate change scenarios and call for more studies on the role of temperature in reproduction beyond those conducted on temperate-region species. PMID:28989782

Contingency in the Direction and Mechanics of Soil Organic Matter Responses to Increased Rainfall

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

Berhe, Asmeret A.; Suttle, K. Blake; Burton, Sarah D.

2012-09-03

Shifts in regional precipitation patterns will be a major component of global climate change. Rainfall will show greater and more variable changes in response to rising earth surface temperatures than most other climatic variables, and will be a major driver of ecosystem change. We studied the consequences of predicted changes in California’s rainy season for storage and stabilization mechanisms of soil organic matter (SOM). In a controlled and replicated experiment, we amended rainfall over large plots of natural grassland in accordance with alternative scenarios of future climate change. Results show that increases in annual rainfall have important consequences for soilmore » C storage, but that the strength and even direction of these effects depend entirely on seasonal timing. Rainfall increases during the winter rainy season led to pronounced C loss from soil while rainfall increases after the typical rainy season increased soil C stocks. Analysis of mineral-OM associations reveals a powerful mechanism underlying this difference: increased winter rainfall vastly diminished the role of Fe and Al oxides in SOM stabilization. Dithionite extractable crystalline Fe oxides explained more than 35 percent of the variability in C storage in ambient control and spring-addition treatments, compared to less than 0.01 percent in the winter-addition treatment. Likewise, poorly crystalline Fe and Al oxides explained more than 25 and 40 percent of the variability in C storage, respectively, in the control and spring-addition treatments compared to less than 5 percent in the -winter-addition treatment. Increases in annual precipitation identical in amount but at three-month offsets produced opposite effects on soil C storage. These results highlight the complexity inherent in biospheric feedbacks to the climate system, and the way that careful experimentation can penetrate that complexity to improve predictions of ecosystem and climatic change.« less

Net ecosystem carbon exchange of a dry temperate eucalypt forest

NASA Astrophysics Data System (ADS)

Hinko-Najera, Nina; Isaac, Peter; Beringer, Jason; van Gorsel, Eva; Ewenz, Cacilia; McHugh, Ian; Exbrayat, Jean-François; Livesley, Stephen J.; Arndt, Stefan K.

2017-08-01

Forest ecosystems play a crucial role in the global carbon cycle by sequestering a considerable fraction of anthropogenic CO2, thereby contributing to climate change mitigation. However, there is a gap in our understanding about the carbon dynamics of eucalypt (broadleaf evergreen) forests in temperate climates, which might differ from temperate evergreen coniferous or deciduous broadleaved forests given their fundamental differences in physiology, phenology and growth dynamics. To address this gap we undertook a 3-year study (2010-2012) of eddy covariance measurements in a dry temperate eucalypt forest in southeastern Australia. We determined the annual net carbon balance and investigated the temporal (seasonal and inter-annual) variability in and environmental controls of net ecosystem carbon exchange (NEE), gross primary productivity (GPP) and ecosystem respiration (ER). The forest was a large and constant carbon sink throughout the study period, even in winter, with an overall mean NEE of -1234 ± 109 (SE) g C m-2 yr-1. Estimated annual ER was similar for 2010 and 2011 but decreased in 2012 ranging from 1603 to 1346 g C m-2 yr-1, whereas GPP showed no significant inter-annual variability, with a mean annual estimate of 2728 ± 39 g C m-2 yr-1. All ecosystem carbon fluxes had a pronounced seasonality, with GPP being greatest during spring and summer and ER being highest during summer, whereas peaks in NEE occurred in early spring and again in summer. High NEE in spring was likely caused by a delayed increase in ER due to low temperatures. A strong seasonal pattern in environmental controls of daytime and night-time NEE was revealed. Daytime NEE was equally explained by incoming solar radiation and air temperature, whereas air temperature was the main environmental driver of night-time NEE. The forest experienced unusual above-average annual rainfall during the first 2 years of this 3-year period so that soil water content remained relatively high and the forest was not water limited. Our results show the potential of temperate eucalypt forests to sequester large amounts of carbon when not water limited. However, further studies using bottom-up approaches are needed to validate measurements from the eddy covariance flux tower and to account for a possible underestimation in ER due to advection fluxes.

Adapting to the unpredictable: reproductive biology of vertebrates in the Australian wet-dry tropics.

PubMed

Shine, Richard; Brown, Gregory P

2008-01-27

In the wet-dry tropics of northern Australia, temperatures are high and stable year-round but monsoonal rainfall is highly seasonal and variable both annually and spatially. Many features of reproduction in vertebrates of this region may be adaptations to dealing with this unpredictable variation in precipitation, notably by (i) using direct proximate (rainfall-affected) cues to synchronize the timing and extent of breeding with rainfall events, (ii) placing the eggs or offspring in conditions where they will be buffered from rainfall extremes, and (iii) evolving developmental plasticity, such that the timing and trajectory of embryonic differentiation flexibly respond to local conditions. For example, organisms as diverse as snakes (Liasis fuscus, Acrochordus arafurae), crocodiles (Crocodylus porosus), birds (Anseranas semipalmata) and wallabies (Macropus agilis) show extreme annual variation in reproductive rates, linked to stochastic variation in wet season rainfall. The seasonal timing of initiation and cessation of breeding in snakes (Tropidonophis mairii) and rats (Rattus colletti) also varies among years, depending upon precipitation. An alternative adaptive route is to buffer the effects of rainfall variability on offspring by parental care (including viviparity) or by judicious selection of nest sites in oviparous taxa without parental care. A third type of adaptive response involves flexible embryonic responses (including embryonic diapause, facultative hatching and temperature-dependent sex determination) to incubation conditions, as seen in squamates, crocodilians and turtles. Such flexibility fine-tunes developmental rates and trajectories to conditions--especially, rainfall patterns--that are not predictable at the time of oviposition.

Long-Term Simulation of Dust Distribution with the GOCART Model: Correlation with the North Atlantic Oscillation

NASA Technical Reports Server (NTRS)

Ginoux, P.; Prospero, J.; Torres, O.; Chin, M.

2002-01-01

Global distribution of aeolian dust is simulated from 1981 to 1996 with the Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. The results are assessed with in-situ measurements and the Total Ozone Mapping Spectrometer (TOMS) aerosol products. The annual budget over the different continents and oceans are analyzed. It is found that there is a maximum of 25% difference of global annual emission from the minimum in 1996 to the maximum in 1988. There is a downward trend of dust emission over Africa and East Asia, of 6 and 2 Tg/yr, respectively. The inter-annual variability of dust distribution is analyzed over the North Atlantic and Africa. It is found that in winter most of the North Atlantic and Africa dust loading is correlated with the North Atlantic Oscillation. The GOCART model indicates that a controlling factor of such correlation can be attributed to dust emission from the Sahel. The Bodele depression is the major dust source in winter and its inter-annual variability is highly correlated with the NAO. However, it is not possible to conclude without further analysis that the North Atlantic Oscillation is forcing the inter-annual variability of dust emission and in-turn dust concentration over the North Atlantic.

Sensitivity of Catchment Transit Times to Rainfall Variability Under Present and Future Climates

NASA Astrophysics Data System (ADS)

Wilusz, Daniel C.; Harman, Ciaran J.; Ball, William P.

2017-12-01

Hydrologists have a relatively good understanding of how rainfall variability shapes the catchment hydrograph, a reflection of the celerity of hydraulic head propagation. Much less is known about the influence of rainfall variability on catchment transit times, a reflection of water velocities that control solute transport. This work uses catchment-scale lumped parameter models to decompose the relationship between rainfall variability and an important metric of transit times, the time-varying fraction of young water (<90 days old) in streams (FYW). A coupled rainfall-runoff model and rank StorAge Selection (rSAS) transit time model were calibrated to extensive hydrometric and environmental tracer data from neighboring headwater catchments in Plynlimon, Wales from 1999 to 2008. At both sites, the mean annual FYW increased more than 13 percentage points from the driest to the wettest year. Yearly mean rainfall explained most between-year variation, but certain signatures of rainfall pattern were also associated with higher FYW including: more clustered storms, more negatively skewed storms, and higher covariance between daily rainfall and discharge. We show that these signatures are symptomatic of an "inverse storage effect" that may be common among watersheds. Looking to the future, changes in rainfall due to projected climate change caused an up to 19 percentage point increase in simulated mean winter FYW and similarly large decreases in the mean summer FYW. Thus, climate change could seasonally alter the ages of water in streams at these sites, with concomitant impacts on water quality.

Climate variability, vulnerability, and coping mechanism in Alaknanda catchment, Central Himalaya, India.

PubMed

Kumar, Kireet; Joshi, Sneh; Joshi, Varun

2008-06-01

A study was carried out to discover trends in the rainfall and temperature pattern of the Alaknanda catchment in the Central Himalaya. Data on the annual rainfall, monsoon rainfall for the last decade, and average annual temperatures over the last few decades were analyzed. Nonparametric methods (Mann-Kendall and Sen's method) were employed to identify trends. The Mann-Kendall test shows a decline in rainfall and rise in temperature, and these trends were found to be statistically significant at the 95% confidence level for both transects. Sen's method also confirms this trend. This aspect has to be considered seriously for the simple reason that if the same trend continues in the future, more chances of drought are expected. The impact of climate change has been well perceived by the people of the catchment, and a coping mechanism has been developed at the local level.

A dependence modelling study of extreme rainfall in Madeira Island

NASA Astrophysics Data System (ADS)

Gouveia-Reis, Délia; Guerreiro Lopes, Luiz; Mendonça, Sandra

2016-08-01

The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.

Analysis of water-level fluctuations of the US Highway 90 retention pond, Madison, Florida

USGS Publications Warehouse

Bridges, W.C.

1985-01-01

A closed basin stormwater retention pond, located 1 mile west of Madison, Florida, has a maximum storage capacity of 134.1 acre-feet at the overtopping altitude of 100.2 feet. The maximum observed altitude (July 1982 to March 1984) was 99.52 feet (126.7 acre-feet) on March 28, 1984. This report provides a technique for simulating net monthly change-in-altitude in response to rainfall and evaporation. A regression equation was developed which relates net monthly change in altitude (dependent variable) to rainfall and evaporation (independent variables). Rainfall frequency curves were developed using a log-Pearson Type III distribution of the annual, January through April, June through August, and July monthly rainfall totals for the years 1908-72, 1974, 1976-82. The altitude of the retention pond increased almost 7 feet during the 4-month period January through April 1983. The rainfall total was 35.1 inches, and the recurrence interval exceeded the 100-year January-April rainfall. (USGS)

Temporal and spatial evaluation of satellite rainfall estimates over different regions in Latin-America.

NASA Astrophysics Data System (ADS)

Villanueva, O. M. B.; Zambrano-Bigiarini, M.; Ribbe, L.; Nauditt, A.; Rebolledo Coy, M. A.; Xuan Thinh, N.; Bartz-Beielstein, T.

2017-12-01

In developing countries an accurate representation of the spatio-temporal variability of catchment rainfall inputs is currently severely limited. This issue can be overcame with the use of satellite rainfall estimates (SREs), which provide rainfall data in such environments for a wide range of hydrological applications, such as extreme events analysis and water accounting. Three different basins in Latin-America (Imperial Basin in Chile, Paraiba do Sul in Brazil and Magdalena in Colombia) were evaluated with a point-to-pixel analysis to determine the best SRE for further hydrological modelling. For this purpose, daily values of six state-of-the-art SRE products (TMPA 3B42v7, TMPA 3B42RT, CHIRPSv2, CMORPH, PERSIANN-CDR and MSWEPv1.2) were evaluated at annual and seasonal scales. The modified Kling-Gupta Efficiency (KGE') was used to evaluate the linear correlation, variability and bias relationship between satellite data and observations. Also, two categorical indices (POD and fBias) were used to assess product performance for different rainfall intensities. The results showed that for the southern Imperial River Basin PERSIANN-CDR presented the best performance at the annual scale, while TRMM 3B42v7 and PERSIANN-CDR had the best performance in a seasonal basis. In the Brazilian Paraiba do Sul, MSWEP performed the best in annual and seasonal basis. For the Magdalena Basin, CHIRPS and TRMM 3B42RT presented the highest performance in the seasonal analysis, while CHIRPS showed the best annual performance. When the bias term of the modified KGE' was removed from KGE', it was observed that the best evaluated SRE was not necessarily the one that have the highest linear correlation and variability relation with the observed data. In the categorical indices, all SREs showed a good detection in no-rain events, but low skill classifying days with precipitation. Nevertheless, all SREs performed relatively well identifying moderate rain events in all regions. We finally conclude that there is not a best performing SRE over all, a specific assessment is required to determine which SRE is the most suitable for each region. However, SREs show promising potential to be used for hydrological studies, and they must be taken in to account in order to derive better rainfall estimates.

Implications of altered rainfall and exotic plants on soil microbial communities and carbon biomass

NASA Astrophysics Data System (ADS)

Castro, S.; Lipson, D.; Cleland, E. E.

2016-12-01

Climate and exotic plant disturbances are among the most significant threats to Mediterranean-type ecosystems, compromising their renowned biodiversity and role in the global carbon cycle. Predicted shifts in rainfall patterns have become a particular concern, especially when interactions with other stressors and effects on biogeochemical processes remain poorly understood. To understand the impacts of altered rainfall on belowground dynamics as well as the role of inter- and intra-annual variation and plant community composition, we monitored soil microbial communities under native and exotic plant dominated plots with rainfall manipulation treatments in a semi-arid Mediterranean-type ecosystem. We measured microbial biomass, respiration rates, and community structure across treatments and vegetation types. Soil moisture and dissolved organic carbon were also measured to characterize abiotic soil properties. The soil moisture gradient established by the rainfall treatments had a positive correlation with microbial biomass carbon under native- and exotic-dominated plots but had no effect on respiration rates. A significant reduction in microbial biomass under exotic plants was found in 2013 but not in 2014 and 2015. Substrate-induced respiration values were higher in the exotic-dominated plots during the spring seasons, resulting in a significant interaction between plant community type and season. Bacterial communities showed little variation except in the Proteobacteria phyla, which was lower in exotic plants-dominated plots. Dissolved organic carbon was significantly reduced in exotic-dominated plots by approximately 26% based on average values of all plots throughout. Our results illustrate that rainfall quantity and exotic plants can cause changes in microbial biomass, community composition and respiration rates jeopardizing soil carbon storage. They also reinforce the importance of temporal variability and the need for repeated sampling to correctly interpret environmental changes in semi-arid ecosystems. We conclude that to improve predictions of the implications of global stressors on biogeochemical cycles in semi-arid ecosystems, there is a need to incorporate microbial data with the understanding that it is highly dependent on temporal dynamics and plant community.

An Investigation of the Hydroclimate Variability of Eastern Africa

NASA Astrophysics Data System (ADS)

Smith, K. A.; Semazzi, F. H. M.

2015-12-01

The flow of the Victoria Nile, and the productivity of the dams along it, is determined by the level of Lake Victoria, which is primarily dictated by the rainfall and temperature variability over the Lake Victoria Basin. Notwithstanding the indisputable decline of water resources over the lake basin during the Long Rains of March - May, there is a strong indication based on IPCC climate projections that this trend, which has persisted for several decades, will reverse in the next few decades. This phenomenon has come to be known as the Eastern-Central African climate change paradox and could have profound implications on sustainable development for the next few decades in Lake Victoria Basin. The purpose of this study is to investigate the climate variability associated with the East African Climate Change Paradox for the recent decades. This research analyzes observations to understand the sources of variability and potential physical mechanisms related to the decline in precipitation over Eastern Africa. We then investigate the hydrological factors involved in the decline of Lake Victoria levels in the context of the decline in rainfall. While East Africa has been experiencing persistent decline of the Long Rains for multiple decades, this same decline is not seen in annual rainfall. The remaining seasons show an increase in rainfall which is compensating for the decline of the Long Rains. It is possible that the Long Rains season is shifting in such a way that the season starts earlier, in February, and ending sooner. The corresponding annual Lake Victoria levels modeled using observed rainfall do not decline in the recent decades, except when the Long Rains seasonal variability is considered without variability from other seasons. This shift could impact hydroelectric power planning on a monthly or seasonal time scale, and could potentially have a large impact on agriculture, since it would shift the growing season in the region.

Large-scale assessment of present day and future groundwater recharge and its sensitivity to climate variability in Europe's karst regions

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Gleeson, T. P.; Wagener, T.; Wada, Y.

2016-12-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

Enhanced recharge rates and altered recharge sensitivity to climate variability through subsurface heterogeneity

NASA Astrophysics Data System (ADS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2017-04-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

Linking nutrient inputs, phytoplankton composition, zooplankton dynamics and the recruitment of pink snapper, Chrysophrys auratus, in a temperate bay

NASA Astrophysics Data System (ADS)

Black, Kerry P.; Longmore, Andrew R.; Hamer, Paul A.; Lee, Randall; Swearer, Stephen E.; Jenkins, Gregory P.

2016-12-01

Survival of larval fish is often linked to production of preferred prey such as copepods, both inter- and intra-annually. In turn, copepod production depends not only the quantity of food, but also on the nutritional quality, edibility and/or toxicity of their micro-algal food. Hence, larval fish survival can become de-coupled from levels of nutrient input depending on the resulting composition of the plankton. Here we use a plankton dynamics model to study nutrient input, phytoplankton composition and copepod, Paracalanus, production in relation to interannual variation in recruitment of snapper, Chrysophrys auratus, in Port Phillip Bay, Australia. The model was able to simulate the ratio of diatoms to flagellates in the plume of the main river entering Port Phillip Bay. Interannual variability in the copepod, Paracalanus, abundance during the C. auratus spawning period over 5 years was accurately predicted. The seasonal peak in Paracalanus production depended on the timing and magnitude (match-mismatch) of nutrient inputs and how these were reflected in temporal change in the diatom:flagellate ratio. In turn, the model-predicted Paracalanus abundance was strongly related to inter-annaul variability in abundance of snapper, C. auratus, larvae over 7 years. Years of highest larval C. auratus abundance coincided with a matching of the spawning period with the peak in Paracalanus abundance. High freshwater flows and nutrient inputs led to an early seasonal dominance of diatoms, and consequently reduced abundances of copepods over the C. auratus spawning period with correspondingly low abundances of larvae. Conversely years of very low rainfall and nutrient input also led to low phytoplankton and copepod concentrations and larval C. auratus abundances. Highest abundances of larval C. auratus occurred in years of low to intermediate rainfall and nutrient inputs, particularly when pulses of nutrients occurred in the spring period, the latter supporting the match-mismatch hypothesis.

Spatiotemporal variability of rainfall extremes in monsoonal climates - examples from the South American Monsoon and the Indian Monsoon Systems (Invited)

NASA Astrophysics Data System (ADS)

Bookhagen, B.; Boers, N.; Marwan, N.; Malik, N.; Kurths, J.

2013-12-01

Monsoonal rainfall is the crucial component for more than half of the world's population. Runoff associated with monsoon systems provide water resources for agriculture, hydropower, drinking-water generation, recreation, and social well-being and are thus a fundamental part of human society. However, monsoon systems are highly stochastic and show large variability on various timescales. Here, we use various rainfall datasets to characterize spatiotemporal rainfall patterns using traditional as well as new approaches emphasizing nonlinear spatial correlations from a complex networks perspective. Our analyses focus on the South American (SAMS) and Indian (ISM) Monsoon Systems on the basis of Tropical Rainfall Measurement Mission (TRMM) using precipitation radar and passive-microwave products with horizontal spatial resolutions of ~5x5 km^2 (products 2A25, 2B31) and 25x25 km^2 (3B42) and interpolated rainfall-gauge data for the ISM (APHRODITE, 25x25 km^2). The eastern slopes of the Andes of South America and the southern front of the Himalaya are characterized by significant orographic barriers that intersect with the moisture-bearing, monsoonal wind systems. We demonstrate that topography exerts a first-order control on peak rainfall amounts on annual timescales in both mountain belts. Flooding in the downstream regions is dominantly caused by heavy rainfall storms that propagate deep into the mountain range and reach regions that are arid and without vegetation cover promoting rapid runoff. These storms exert a significantly different spatial distribution than average-rainfall conditions and assessing their recurrence intervals and prediction is key in understanding flooding for these regions. An analysis of extreme-value distributions of our high-spatial resolution data reveal that semi-arid areas are characterized by low-frequency/high-magnitude events (i.e., are characterized by a ';heavy tail' distribution), whereas regions with high mean annual rainfall have a less skewed distribution. In a second step, an analysis of the spatial characteristics of extreme rainfall synchronicity by means of complex networks reveals patterns of the propagation of extreme rainfall events. These patterns differ substantially from those obtained from the mean annual rainfall distribution. In addition, we have developed a scheme to predict rainfall extreme events in the eastern Central Andes based on event synchronization and spatial patterns of complex networks. The presented methods and result will allow to critically evaluate data and models in space and time.

Using Low-Cost GNSS Receivers to Investigate the Small-Scale Precipitable Water Vapor Variability in the Atmosphere for Improving High Resolution Rainfall Forecasts

NASA Astrophysics Data System (ADS)

Krietemeyer, Andreas; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-04-01

Recent research has shown that assimilation of Precipitable Water Vapor (PWV) measurements into numerical weather predictions models improve the quality of rainfall now- and forecasting. Local PWV fluctuations may be related with water vapor increases in the lower troposphere which lead to deep convection. Prior studies show that about 20 minutes before rain occurs, the amount of water vapor in the atmosphere at 1 km height increases. Monitoring the small-scale temporal and spatial variability of PWV is therefore crucial to improve the weather now- and forecasting for convective storms, that are typically critical for urban stormwater systems. One established technique to obtain PWV measurements in the atmosphere is to exploit signal delays from GNSS satellites to dual-frequency receivers on the ground. Existing dual-frequency receiver networks typically have inter-station distances in the order of tens of kilometers, which is not sufficiently dense to capture the small-scale PWV variations. In this study, we will add low-cost, single-frequency GNSS receivers to an existing dual-frequency receiver network to obtain an inter-station distance of about 1 km in the Rotterdam area (Netherlands). The aim is to investigate the spatial variability of PWV in the atmosphere at this scale. We use the surrounding dual-frequency network (distributed over a radius of approximately 25 km) to apply an ionospheric delay model that accounts for the delay in the ionosphere (50-1000 km altitude) that cannot be eliminated by single-frequency receivers. The results are validated by co-aligning a single-frequency receiver to a dual-frequency receiver. In the next steps, we will investigate how the high temporal and increased spatial resolution network can help to improve high-resolution rainfall forecasts. Their supposed improved forecasting results will be evaluated based on high-resolution rainfall estimates from a polarimetric X-band rainfall radar installed in the city of Rotterdam.

Groundwater recharge estimation under semi arid climate: Case of Northern Gafsa watershed, Tunisia

NASA Astrophysics Data System (ADS)

Melki, Achraf; Abdollahi, Khodayar; Fatahi, Rouhallah; Abida, Habib

2017-08-01

Natural groundwater recharge under semi arid climate, like rainfall, is subjected to large variations in both time and space and is therefore very difficult to predict. Nevertheless, in order to set up any strategy for water resources management in such regions, understanding the groundwater recharge variability is essential. This work is interested in examining the impact of rainfall on the aquifer system recharge in the Northern Gafsa Plain in Tunisia. The study is composed of two main parts. The first is interested in the analysis of rainfall spatial and temporal variability in the study basin while the second is devoted to the simulation of groundwater recharge. Rainfall analysis was performed based on annual precipitation data recorded in 6 rainfall stations over a period of 56 years (1960-2015). Potential evapotranspiration data were also collected from 1960 to 2011 (52 years). The hydrologic distributed model WetSpass was used for the estimation of groundwater recharge. Model calibration was performed based on an assessment of the agreement between the sum of recharge and runoff values estimated by the WetSpass hydrological model and those obtained by the climatic method. This latter is based on the difference calculated between rainfall and potential evapotranspiration recorded at each rainy day. Groundwater recharge estimation, on monthly scale, showed that average annual precipitation (183.3 mm/year) was partitioned to 5, 15.3, 36.8, and 42.8% for interception, runoff, actual evapotranspiration and recharge respectively.

Malaria early warning tool: linking inter-annual climate and malaria variability in northern Guadalcanal, Solomon Islands.

PubMed

Smith, Jason; Tahani, Lloyd; Bobogare, Albino; Bugoro, Hugo; Otto, Francis; Fafale, George; Hiriasa, David; Kazazic, Adna; Beard, Grant; Amjadali, Amanda; Jeanne, Isabelle

2017-11-21

Malaria control remains a significant challenge in the Solomon Islands. Despite progress made by local malaria control agencies over the past decade, case rates remain high in some areas of the country. Studies from around the world have confirmed important links between climate and malaria transmission. This study focuses on understanding the links between malaria and climate in Guadalcanal, Solomon Islands, with a view towards developing a climate-based monitoring and early warning for periods of enhanced malaria transmission. Climate records were sourced from the Solomon Islands meteorological service (SIMS) and historical malaria case records were sourced from the National Vector-Borne Disease Control Programme (NVBDCP). A declining trend in malaria cases over the last decade associated with improved malaria control was adjusted for. A stepwise regression was performed between climate variables and climate-associated malaria transmission (CMT) at different lag intervals to determine where significant relationships existed. The suitability of these results for use in a three-tiered categorical warning system was then assessed using a Mann-Whitney U test. Of the climate variables considered, only rainfall had a consistently significant relationship with malaria in North Guadalcanal. Optimal lag intervals were determined for prediction using R 2 skill scores. A highly significant negative correlation (R = - 0.86, R 2  = 0.74, p < 0.05, n = 14) was found between October and December rainfall at Honiara and CMT in northern Guadalcanal for the subsequent January-June. This indicates that drier October-December periods are followed by higher malaria transmission periods in January-June. Cross-validation emphasized the suitability of this relationship for forecasting purposes [Formula: see text]  as did Mann-Whitney U test results showing that rainfall below or above specific thresholds was significantly associated with above or below normal malaria transmission, respectively. This study demonstrated that rainfall provides the best predictor of malaria transmission in North Guadalcanal. This relationship is thought to be underpinned by the unique hydrological conditions in northern Guadalcanal which allow sandbars to form across the mouths of estuaries which act to develop or increase stagnant brackish marshes in low rainfall periods. These are ideal habitats for the main mosquito vector, Anopheles farauti. High rainfall accumulations result in the flushing of these habitats, reducing their viability. The results of this study are now being used as the basis of a malaria early warning system which has been jointly implemented by the SIMS, NVBDCP and the Australian Bureau of Meteorology.

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

Ghosh, Subimal; Das, Debasish; Kao, Shih-Chieh

Recent studies disagree on how rainfall extremes over India have changed in space and time over the past half century, as well as on whether the changes observed are due to global warming or regional urbanization. Although a uniform and consistent decrease in moderate rainfall has been reported, a lack of agreement about trends in heavy rainfall may be due in part to differences in the characterization and spatial averaging of extremes. Here we use extreme value theory to examine trends in Indian rainfall over the past half century in the context of long-term, low-frequency variability.We show that when generalizedmore » extreme value theory is applied to annual maximum rainfall over India, no statistically significant spatially uniform trends are observed, in agreement with previous studies using different approaches. Furthermore, our space time regression analysis of the return levels points to increasing spatial variability of rainfall extremes over India. Our findings highlight the need for systematic examination of global versus regional drivers of trends in Indian rainfall extremes, and may help to inform flood hazard preparedness and water resource management in the region.« less

Multiple recharge processes to heterogeneous Mediterranean coastal aquifers and implications on recharge rates evolution in time

NASA Astrophysics Data System (ADS)

Santoni, S.; Huneau, F.; Garel, E.; Celle-Jeanton, H.

2018-04-01

Climate change is nowadays widely considered to have major effects on groundwater resources. Climatic projections suggest a global increase in evaporation and higher frequency of strong rainfall events especially in Mediterranean context. Since evaporation is synonym of low recharge conditions whereas strong rainfall events are more favourable to recharge in heterogeneous subsurface contexts, a lack of knowledge remains then on the real ongoing and future drinking groundwater supply availability at aquifers scale. Due to low recharge potential and high inter-annual climate variability, this issue is strategic for the Mediterranean hydrosystems. This is especially the case for coastal aquifers because they are exposed to seawater intrusion, sea-level rise and overpumping risks. In this context, recharge processes and rates were investigated in a Mediterranean coastal aquifer with subsurface heterogeneity located in Southern Corsica (France). Aquifer recharge rates from combining ten physical and chemical methods were computed. In addition, hydrochemical and isotopic investigations were carried out through a monthly two years monitoring combining major ions and stable isotopes of water in rain, runoff and groundwater. Diffuse, focused, lateral mountain system and irrigation recharge processes were identified and characterized. A predominant focused recharge conditioned by subsurface heterogeneity is evidenced in agreement with variable but highly favourable recharge rates. The fast water transfer from the surface to the aquifer implied by this recharge process suggests less evaporation, which means higher groundwater renewal and availability in such Mediterranean coastal aquifers.

Contributions of Tropical Cyclones to the North Atlantic Climatological Rainfall as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.; Einaudi, Franco (Technical Monitor)

2000-01-01

The tropical cyclone rainfall climatology study that was performed for the North Pacific was extended to the North Atlantic. Similar to the North Pacific tropical cyclone study, mean monthly rainfall within 444 km of the center of the North Atlantic tropical cyclones (i.e., that reached storm stage and greater) was estimated from passive microwave satellite observations during, an eleven year period. These satellite-observed rainfall estimates were used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Atlantic total rainfall during, June-November when tropical cyclones were most abundant. The main results from this study indicate: 1) that tropical cyclones contribute, respectively, 4%, 3%, and 4% to the western, eastern, and entire North Atlantic; 2) similar to that observed in the North Pacific, the maximum in North Atlantic tropical cyclone rainfall is approximately 5 - 10 deg poleward (depending on longitude) of the maximum non-tropical cyclone rainfall; 3) tropical cyclones contribute regionally a maximum of 30% of the total rainfall 'northeast of Puerto Rico, within a region near 15 deg N 55 deg W, and off the west coast of Africa; 4) there is no lag between the months with maximum tropical cyclone rainfall and non-tropical cyclone rainfall in the western North Atlantic, while in the eastern North Atlantic, maximum tropical cyclone rainfall precedes maximum non-tropical cyclone rainfall; 5) like the North Pacific, North Atlantic tropical cyclones Of hurricane intensity generate the greatest amount of rainfall in the higher latitudes; and 6) warm ENSO events inhibit tropical cyclone rainfall.

Rain-fed fig yield as affected by rainfall distribution

NASA Astrophysics Data System (ADS)

Bagheri, Ensieh; Sepaskhah, Ali Reza

2014-08-01

Variable annual rainfall and its uneven distribution are the major uncontrolled inputs in rain-fed fig production and possibly the main cause of yield fluctuation in Istahban region of Fars Province, I.R. of Iran. This introduces a considerable risk in rain-fed fig production. The objective of this study was to find relationships between seasonal rainfall distribution and rain-fed fig production in Istahban region to determine the critical rainfall periods for rain-fed fig production and supplementary irrigation water application. Further, economic analysis for rain-fed fig production was considered in this region to control the risk of production. It is concluded that the monthly, seasonal and annual rainfall indices are able to show the effects of rainfall and its distribution on the rain-fed fig yield. Fig yield with frequent occurrence of 80 % is 374 kg ha-1. The internal rates of return for interest rate of 4, 8 and 12 % are 21, 58 and 146 %, respectively, that are economically feasible. It is concluded that the rainfall in spring especially in April and in December has negatively affected fig yield due to its interference with the life cycle of Blastophaga bees for pollination. Further, it is concluded that when the rainfall is limited, supplementary irrigation can be scheduled in March.

Influence of net freshwater supply on salinity in Florida Bay

USGS Publications Warehouse

Nuttle, William K.; Fourqurean, James W.; Cosby, Bernard J.; Zieman, Joseph C.; Robblee, Michael B.

2000-01-01

An annual water budget for Florida Bay, the large, seasonally hypersaline estuary in the Everglades National Park, was constructed using physically based models and long‐term (31 years) data on salinity, hydrology, and climate. Effects of seasonal and interannual variations of the net freshwater supply (runoff plus rainfall minus evaporation) on salinity variation within the bay were also examined. Particular attention was paid to the effects of runoff, which are the focus of ambitious plans to restore and conserve the Florida Bay ecosystem. From 1965 to 1995 the annual runoff from the Everglades into the bay was less than one tenth of the annual direct rainfall onto the bay, while estimated annual evaporation slightly exceeded annual rainfall. The average net freshwater supply to the bay over a year was thus approximately zero, and interannual variations in salinity appeared to be affected primarily by interannual fluctuations in rainfall. At the annual scale, runoff apparently had little effect on the bay as a whole during this period. On a seasonal basis, variations in rainfall, evaporation, and runoff were not in phase, and the net freshwater supply to the bay varied between positive and negative values, contributing to a strong seasonal pattern in salinity, especially in regions of the bay relatively isolated from exchanges with the Gulf of Mexico and Atlantic Ocean. Changes in runoff could have a greater effect on salinity in the bay if the seasonal patterns of rainfall and evaporation and the timing of the runoff are considered. One model was also used to simulate spatial and temporal patterns of salinity responses expected to result from changes in net freshwater supply. Simulations in which runoff was increased by a factor of 2 (but with no change in spatial pattern) indicated that increased runoff will lower salinity values in eastern Florida Bay, increase the variability of salinity in the South Region, but have little effect on salinity in the Central and West Regions.

Influence of declining mean annual rainfall on the behavior and yield of sediment and particulate organic carbon from tropical watersheds

NASA Astrophysics Data System (ADS)

Strauch, Ayron M.; MacKenzie, Richard A.; Giardina, Christian P.; Bruland, Gregory L.

2018-04-01

The capacity to forecast climate and land-use driven changes to runoff, soil erosion and sediment transport in the tropics is hindered by a lack of long-term data sets and model study systems. To address these issues we utilized three watersheds characterized by similar shape, geology, soils, vegetation cover, and land use arranged across a 900 mm gradient in mean annual rainfall (MAR). Using this space-for-time design, we quantified suspended sediment (SS) and particulate organic carbon (POC) export over 18 months to examine how large-scale climate trends (MAR) affect sediment supply and delivery patterns (hysteresis) in tropical watersheds. Average daily SS yield ranged from 0.128 to 0.618 t km- 2 while average daily POC ranged from 0.002 to 0.018 t km- 2. For the largest storm events, we found that sediment delivery exhibited similar clockwise hysteresis patterns among the watersheds, with no significant differences in the similarity function between watershed pairs, indicating that: (1) in-stream and near-stream sediment sources drive sediment flux; and (2) the shape and timing of hysteresis is not affected by MAR. With declining MAR, the ratio of runoff to baseflow and inter-storm length between pulse events both increased. Despite increases in daily rainfall and the number of days with large rainfall events increasing with MAR, there was a decline in daily SS yield possibly due to the exhaustion of sediment supply by frequent runoff events in high MAR watersheds. By contrast, mean daily POC yield increased with increasing MAR, possibly as a result of increased soil organic matter decomposition, greater biomass, or increased carbon availability in higher MAR watersheds. We compared results to modeled values using the Load Estimator (LOADEST) FORTRAN model, confirming the negative relationship between MAR and sediment yield. However, because of its dependency on mean daily flow, LOADEST tended to under predict sediment yield, a result of its poor ability to capture the high variability in tropical streamflow. Taken together, results indicate that declines in MAR can have contrasting effects on hydrological processes in tropical watersheds, with consequences for instream ecology, downstream water users, and nearshore habitat.

Modeling the impacts of phenological and inter-annual changes in landscape metrics on local biodiversity of agricultural lands of Eastern Ontario using multi-spatial and multi-temporal remote sensing data

NASA Astrophysics Data System (ADS)

Alavi-Shoushtari, N.; King, D.

2017-12-01

Agricultural landscapes are highly variable ecosystems and are home to many local farmland species. Seasonal, phenological and inter-annual agricultural landscape dynamics have potential to affect the richness and abundance of farmland species. Remote sensing provides data and techniques which enable monitoring landscape changes in multiple temporal and spatial scales. MODIS high temporal resolution remote sensing images enable detection of seasonal and phenological trends, while Landsat higher spatial resolution images, with its long term archive enables inter-annual trend analysis over several decades. The objective of this study to use multi-spatial and multi-temporal remote sensing data to model the response of farmland species to landscape metrics. The study area is the predominantly agricultural region of eastern Ontario. 92 sample landscapes were selected within this region using a protocol designed to maximize variance in composition and configuration heterogeneity while controlling for amount of forest and spatial autocorrelation. Two sample landscape extents (1×1km and 3×3km) were selected to analyze the impacts of spatial scale on biodiversity response. Gamma diversity index data for four taxa groups (birds, butterflies, plants, and beetles) were collected during the summers of 2011 and 2012 within the cropped area of each landscape. To extract the seasonal and phenological metrics a 2000-2012 MODIS NDVI time-series was used, while a 1985-2012 Landsat time-series was used to model the inter-annual trends of change in the sample landscapes. The results of statistical modeling showed significant relationships between farmland biodiversity for several taxa and the phenological and inter-annual variables. The following general results were obtained: 1) Among the taxa groups, plant and beetles diversity was most significantly correlated with the phenological variables; 2) Those phenological variables which are associated with the variability in the start of season date across the sample landscapes and the variability in the corresponding NDVI values at that date showed the strongest correlation with the biodiversity indices; 3) The significance of the models improved when using 3×3km site extent both for MODIS and Landsat based models due most likely to the larger sample size over 3x3km.

Recent trends in rainfall and temperature over North West India during 1871-2016

NASA Astrophysics Data System (ADS)

Saxena, Rani; Mathur, Prasoon

2018-03-01

Rainfall and temperature are the most important environmental factors influencing crop growth, development, and yield. The northwestern (NW) part of India is one of the main regions of food grain production of the country. It comprises of six meteorological subdivisions (Haryana, Punjab, West Rajasthan, East Rajasthan, Gujarat and Saurashtra, Kutch and Diu). In this study, attempts were made to study variability and trends in rainfall and temperature during 30-year climate normal periods (CN) and 10-year decadal excess or deficit rainfall frequency during the historical period from 1871 to 2016. The Mann-Kendall and Spearman's rank correlation (Spearman's rho) tests were used to determine significance of trends. Least square linear fitting method was adopted to find out the slopes of the trend lines. The long-term mean annual rainfall over North West India is 587.7 mm (standard deviation of 153.0 mm and coefficient of variation 26.0). There was increasing trend in minimum and maximum temperatures during post monsoon season in entire study period and current climate normal period (1991-2016) due to which the sowing of rabi season crops may be delayed and there may be germination problem too. There was a non-significant decreasing trend in rainfall during monsoon season and an increasing trend in rainfall during post monsoon over North West India during entire study period. During current CN5 (1991-2016), all the subdivision (except the Saurashtra region) showed a decreasing trend in rainfall during monsoon season which is a matter of concern for kharif crops and those rabi crops which are grown as rainfed on conserved soil moisture. The decadal annual and seasonal frequencies of excess and deficit years results revealed that the annual total deficit rainfall years (24) exceeded total excess rainfall years (22) in North West India during the entire study period. While during the current decadal period (2011 to 2016), single year was the excess year and 2 years were deficit rainfall years in all subdivisions (except East Rajasthan) on annual basis.

Interannual and intra-annual variability of rainfall in Haiti (1905-2005)

NASA Astrophysics Data System (ADS)

Moron, Vincent; Frelat, Romain; Jean-Jeune, Pierre Karly; Gaucherel, Cédric

2015-08-01

The interannual variability of annual and monthly rainfall in Haiti is examined from a database of 78 rain gauges in 1905-2005. The spatial coherence of annual rainfall is rather low, which is partly due to Haiti's rugged landscape, complex shoreline, and surrounding warm waters (mean sea surface temperatures >27 °C from May to December). The interannual variation of monthly rainfall is mostly shaped by the intensity of the low-level winds across the Caribbean Sea, leading to a drier- (or wetter-) than-average rainy season associated with easterly (or westerly) anomalies, increasing (or decreasing) winds. The varying speed of low-level easterlies across the Caribbean basin may reflect at least four different processes during the year: (1) an anomalous trough/ridge over the western edge of the Azores high from December to February, peaking in January; (2) a zonal pressure gradient between Eastern Pacific and the tropical Northern Atlantic from May/June to September, with a peak in August (i.e. lower-than-average rainfall in Haiti is associated with positive sea level pressure anomalies over the tropical North Atlantic and negative sea level pressure anomalies over the Eastern Pacific); (3) a local ocean-atmosphere coupling between the speed of the Caribbean Low Level Jet and the meridional sea surface temperature (SST) gradient across the Caribbean basin (i.e. colder-than-average SST in the southern Caribbean sea is associated with increased easterlies and below-average rainfall in Haiti). This coupling is triggered when the warmest Caribbean waters move northward toward the Gulf of Mexico; (4) in October/November, a drier- (or wetter-) than-usual rainy season is related to an almost closed anticyclonic (or cyclonic) anomaly located ENE of Haiti on the SW edge of the Azores high. This suggests a main control of the interannual variations of rainfall by intensity, track and/or recurrence of tropical depressions traveling northeast of Haiti. During this period, the teleconnection of Haitian rainfall with synchronous Atlantic and Eastern Pacific SST is at a minimum.

Analytical estimation of annual runoff distribution in ungauged seasonally dry basins based on a first order Taylor expansion of the Fu's equation

NASA Astrophysics Data System (ADS)

Caracciolo, D.; Deidda, R.; Viola, F.

2017-11-01

The assessment of the mean annual runoff and its interannual variability in a basin is the first and fundamental task for several activities related to water resources management and water quality analysis. The scarcity of observed runoff data is a common problem worldwide so that the runoff estimation in ungauged basins is still an open question. In this context, the main aim of this work is to propose and test a simple tool able to estimate the probability distribution of the annual surface runoff in ungauged river basins in arid and semi-arid areas using a simplified Fu's parameterization of the Budyko's curve at regional scale. Starting from a method recently developed to derive the distribution of annual runoff, under the assumption of negligible inter-annual change in basin water storage, we here generalize the application to any catchment where the parameter of the Fu's curve is known. Specifically, we provide a closed-form expression of the annual runoff distribution as a function of the mean and standard deviation of annual rainfall and potential evapotranspiration, and the Fu's parameter. The proposed method is based on a first order Taylor expansion of the Fu's equation and allows calculating the probability density function of annual runoff in seasonally dry arid and semi-arid geographic context around the world by taking advantage of simple easy-to-find climatic data and the many studies with estimates of the Fu's parameter worldwide. The computational simplicity of the proposed tool makes it a valuable supporting tool in the field of water resources assessment for practitioners, regional agencies and authorities.

Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē-Atbara river basin, Ethiopia

NASA Astrophysics Data System (ADS)

Gebremicael, Tesfay G.; Mohamed, Yasir A.; Zaag, Pieter v.; Hagos, Eyasu Y.

2017-04-01

The Upper Tekezē-Atbara river sub-basin, part of the Nile Basin, is characterized by high temporal and spatial variability of rainfall and streamflow. In spite of its importance for sustainable water use and food security, the changing patterns of streamflow and its association with climate change is not well understood. This study aims to improve the understanding of the linkages between rainfall and streamflow trends and identify possible drivers of streamflow variabilities in the basin. Trend analyses and change-point detections of rainfall and streamflow were analysed using Mann-Kendall and Pettitt tests, respectively, using data records for 21 rainfall and 9 streamflow stations. The nature of changes and linkages between rainfall and streamflow were carefully examined for monthly, seasonal and annual flows, as well as indicators of hydrologic alteration (IHA). The trend and change-point analyses found that 19 of the tested 21 rainfall stations did not show statistically significant changes. In contrast, trend analyses on the streamflow showed both significant increasing and decreasing patterns. A decreasing trend in the dry season (October to February), short season (March to May), main rainy season (June to September) and annual totals is dominant in six out of the nine stations. Only one out of nine gauging stations experienced significant increasing flow in the dry and short rainy seasons, attributed to the construction of Tekezē hydropower dam upstream this station in 2009. Overall, streamflow trends and change-point timings were found to be inconsistent among the stations. Changes in streamflow without significant change in rainfall suggests factors other than rainfall drive the change. Most likely the observed changes in streamflow regimes could be due to changes in catchment characteristics of the basin. Further studies are needed to verify and quantify the hydrological changes shown in statistical tests by identifying the physical mechanisms behind those changes. The findings from this study are useful as a prerequisite for studying the effects of catchment management dynamics on the hydrological variabilities in the basin.

Rainfall effects on rare annual plants

USGS Publications Warehouse

Levine, J.M.; McEachern, A.K.; Cowan, C.

2008-01-01

Variation in climate is predicted to increase over much of the planet this century. Forecasting species persistence with climate change thus requires understanding of how populations respond to climate variability, and the mechanisms underlying this response. Variable rainfall is well known to drive fluctuations in annual plant populations, yet the degree to which population response is driven by between-year variation in germination cueing, water limitation or competitive suppression is poorly understood.We used demographic monitoring and population models to examine how three seed banking, rare annual plants of the California Channel Islands respond to natural variation in precipitation and their competitive environments. Island plants are particularly threatened by climate change because their current ranges are unlikely to overlap regions that are climatically favourable in the future.Species showed 9 to 100-fold between-year variation in plant density over the 5–12 years of censusing, including a severe drought and a wet El Niño year. During the drought, population sizes were low for all species. However, even in non-drought years, population sizes and per capita growth rates showed considerable temporal variation, variation that was uncorrelated with total rainfall. These population fluctuations were instead correlated with the temperature after the first major storm event of the season, a germination cue for annual plants.Temporal variation in the density of the focal species was uncorrelated with the total vegetative cover in the surrounding community, suggesting that variation in competitive environments does not strongly determine population fluctuations. At the same time, the uncorrelated responses of the focal species and their competitors to environmental variation may favour persistence via the storage effect.Population growth rate analyses suggested differential endangerment of the focal annuals. Elasticity analyses and life table response experiments indicated that variation in germination has the same potential as the seeds produced per germinant to drive variation in population growth rates, but only the former was clearly related to rainfall.Synthesis. Our work suggests that future changes in the timing and temperatures associated with the first major rains, acting through germination, may more strongly affect population persistence than changes in season-long rainfall.

An Analysis of Inter-annual Variability and Uncertainty of Continental Surface Heat Fluxes

NASA Astrophysics Data System (ADS)

Huang, S. Y.; Deng, Y.; Wang, J.

2016-12-01

The inter-annual variability and the corresponding uncertainty of land surface heat fluxes during the first decade of the 21st century are re-evaluated at continental scale based on the heat fluxes estimated by the maximum entropy production (MEP) model. The MEP model predicted heat fluxes are constrained by surface radiation fluxes, automatically satisfy surface energy balance, and are independent of temperature/moisture gradient, wind speed, and roughness lengths. The surface radiation fluxes and temperature data from Clouds and the Earth's Radiant Energy System and the surface specific humidity data from Modern-Era Retrospective analysis for Research and Applications were used to reproduce the global surface heat fluxes with land-cover data from the NASA Energy and Water cycle Study (NEWS). Our analysis shows that the annual means of continental latent heat fluxes have increasing trends associated with increasing trends in surface net radiative fluxes. The sensible heat fluxes also have increasing trends over most continents except for South America. Ground heat fluxes have little trends. The continental-scale analysis of the MEP fluxes are compared with other existing global surface fluxes data products and the implications of the results for inter-annual to decadal variability of regional surface energy budget are discussed.

Rainfall erosivity in the Fukushima Prefecture: implications for radiocesium mobilization and migration

NASA Astrophysics Data System (ADS)

Laceby, J. Patrick; Chartin, Caroline; Degan, Francesca; Onda, Yuichi; Evrard, Olivier; Cerdan, Olivier; Ayrault, Sophie

2015-04-01

The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 led to the fallout of predominantly radiocesium (137Cs and 134Cs) on soils of the Fukushima Prefecture. This radiocesium was primarily fixated to fine soil particles. Subsequently, rainfall and snow melt run-off events result in significant quantities of radiocesium being eroded and transported throughout the coastal catchments and ultimately exported to the Pacific Ocean. Erosion models, such as the Universal Soil Loss Equation (USLE), relate rainfall directly to soil erosion in that an increase in rainfall one month will directly result in a proportional increase in sediment generation. Understanding the rainfall regime of the region is therefore fundamental to modelling and predicting long-term radiocesium export. Here, we analyze rainfall data for ~40 stations within a 100 km radius of the FDNPP. First we present general information on the rainfall regime in the region based on monthly and annual rainfall totals. Second we present general information on rainfall erosivity, the R-factor of the USLE equation and its relationship to the general rainfall data. Third we examine rainfall trends over the last 100 years at several of the rainfall stations to understand temporal trends and whether ~20 years of data is sufficient to calculate the R-factor for USLE models. Fourth we present monthly R-factor maps for the Fukushima coastal catchments impacted by the FDNPP accident. The variability of the rainfall in the region, particularly during the typhoon season, is likely resulting in a similar variability in the transfer and migration of radiocesium throughout the coastal catchments of the Fukushima Prefecture. Characterizing the region's rainfall variability is fundamental to modelling sediment and the concomitant radiocesium migration and transfer throughout these catchments and ultimately to the Pacific Ocean.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-04-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall the day-to-day variability is crucial for the risk of flooding, national water supply and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the IPCC's AR-5, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. While all models show an increase in day-to-day variability, some models are more realistic in capturing the observed seasonal mean rainfall over India than others. While no model's monsoon rainfall exceeds the observed value by more than two standard deviations, half of the models simulate a significantly weaker monsoon than observed. The relative increase in day-to-day variability by the year 2100 ranges from 15% to 48% under the strongest scenario (RCP-8.5), in the ten models which capture seasonal mean rainfall closest to observations. The variability increase per degree of global warming is independent of the scenario in most models, and is 8% +/- 4% per K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

On the relative role of fire and rainfall in determining vegetation patterns in tropical savannas: a simulation study

NASA Astrophysics Data System (ADS)

Spessa, Allan; Fisher, Rosie

2010-05-01

Tropical savannas cover 18% of the world's land surface and are amongst the most productive terrestrial systems in the world. They comprise 15% of the total terrestrial carbon stock, with an estimated mean net primary productivity (NPP) of 7.2 tCha-1yr-1 or two thirds of NPP in tropical forests. Tropical savannas are the most frequently burnt biome, with fire return intervals in highly productive areas being typically 1-2 years. Fires shape vegetation species composition, tree to grass ratios and nutrient redistribution, as well as the biosphere-atmosphere exchange of trace gases, momentum and radiative energy. Tropical savannas are a major source of emissions, contributing 38 % of total annual CO2 from biomass burning, 30% CO, 19 % CH4 and 59 % NOx. Climatically, they occur in regions subject to a strongly seasonal ‘wet-dry' regime, usually under monsoonal control from the movement of the inter-tropical convergence zone. In general, rainfall during the prior wet season(s) determines the amount of grass fuel available for burning while the length of the dry season influences fuel moisture content. Rainfall in tropical savannas exhibits high inter-annual variability, and under future climate change, is projected to change significantly in much of Africa, South America and northern Australia. Process-based simulation models of fire-vegetation dynamics and feedbacks are critical for determining the impacts of wildfires under projected future climate change on i) ecosystem structure and function, and ii) emissions of trace gases and aerosols from biomass burning. A new mechanistic global fire model SPITFIRE (SPread and InTensity of FIRE) has been designed to overcome many of the limitations in existing fire models set within Dynamic Global Vegetation Models (DGVMs). SPITFIRE has been applied in coupled mode globally and southern Africa, both as part of the LPJ DGVM. It has also been driven with MODIS burnt area data applied to sub-Saharan Africa, while coupled to the LPJ-GUESS vegetation model. Recently, SPIFTIRE has been coupled to the Ecosystem Demography (ED) model, which simulates global vegetation dynamics as part of the new land surface scheme JULES (Joint UK Environment Simulator) within the QUEST Earth System Model (http://www.quest-esm.ac.uk/). This study forms part of on-going work to further improve and test the ability of JULES to accurately simulate the terrestrial carbon cycle and land-atmosphere exchanges under different climates. Using the JULES (ED-SPITFIRE) model driven by observed climate (1901-2002), and focusing on large-scale rainfall gradients in the tropical savannas of west Africa, the Northern Territory (Australia) and central-southern Brazil, this study assesses: i) simulated versus observed vegetation dynamics and distributions, and ii) the relative importance of fire versus rainfall in determining vegetation patterns. A sensitivity analysis approach was used.

Climate and soil attributes determine plant species turnover in global drylands.

PubMed

Ulrich, Werner; Soliveres, Santiago; Maestre, Fernando T; Gotelli, Nicholas J; Quero, José L; Delgado-Baquerizo, Manuel; Bowker, Matthew A; Eldridge, David J; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R; Hernández, Rosa M; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A; Raveh, Eran; Romão, Roberto L; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2014-12-01

Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R 2 )), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R 2 )) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.

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.

Linkages Between Multiscale Global Sea Surface Temperature Change and Precipitation Variabilities in the US

NASA Technical Reports Server (NTRS)

Lau, K. M.; Weng, Heng-Yi

1999-01-01

A growing number of evidence indicates that there are coherent patterns of variability in sea surface temperature (SST) anomaly not only at interannual timescales, but also at decadal-to-inter-decadal timescale and beyond. The multi-scale variabilities of SST anomaly have shown great impacts on climate. In this work, we analyze multiple timescales contained in the globally averaged SST anomaly with and their possible relationship with the summer and winter rainfall in the United States over the past four decades.

Monitoring the Change in Urban Vegetation in 13 Chilean Cities Located in a Rainfall Gradient. What is the Contribution of the Widespread Creation of New Urban Parks?

NASA Astrophysics Data System (ADS)

de la Barrera, Francisco; Henríquez, Cristian

2017-10-01

The well-being of people living in cities is strongly dependent on the existence of urban vegetation because of the ecosystem services or benefits it provides. This is why governments develop plans to create green spaces, plant trees, promote the maintenance of vegetation in private spaces and also monitor their status over time. In Latin America, and particularly in Chile, the increase of urban vegetation has been stimulated through different initiatives and regulations. However, development of monitoring programs at the national level is scarce, so it is yet unknown if these initiatives and regulations have had positive effects. In this article, we monitor the change in urban vegetation in 13 Chilean cities located in a latitudinal gradient of practically zero to almost 1800 mm of annual rainfall. We calculated the trends in NDVI (2000-2016) as an indicator of change in urban greenery using data from the MODIS Subsets platform. Likewise, to assess whether the initiatives have had an effect we quantified the number of urban parks existing at the beginning of the period and how many were created during the study period. For this, we analysed official databases and high spatial resolution satellite images. Armed with said data, we assessed whether these new parks had impacted the tendency toward change in urban greenery. The results indicate that, in general, Chilean cities vary greatly inter-annually in urban greenery and have lost urban vegetation in the last 16 years, with significant losses in four of those cities. Two cities located in desert ecosystems represent an exception and showed positive trends in their urban vegetation. The rainfall in cities has an impact on the amount of vegetation, but not on their tendency to change, i.e. there are cities with loss of vegetation at all levels of precipitation. The creation of parks has not been able to reverse negative trends, which indicates the prevalence of other drivers of change that are not sufficiently compensated by initiatives and regulations that seek to increase urban vegetation. Today, planning and management of urban vegetation is a challenge for urban sustainability and must be addressed systematically, integrally and implemented via urban regulations. It is imperative to focus on cities in extenso, taking into consideration residential areas, private spaces, peri-urban areas, etc. Likewise, climate in each city, inter-annual variability and future changes must also be considered when designing green areas to make them resilient, prevent increases in maintenance costs and provide benefits for the inhabitants in perpetuity.

Factors influencing inter-annual variability of growing season optimum gross primary production and ecosystem respiration in a semi-arid savanna ecosystem: A case study of Skukuza, South Africa

NASA Astrophysics Data System (ADS)

Brummer, C.; Mukwashi, K.; Falge, E. M.; Mudau, A.; Odipo, V.; Schmullius, C.; Lenfers, U.; Thiel-Clemen, T.; Thomas, C. K.; Kutsch, W. L.; Scholes, R. J.; Berger, C.

2016-12-01

The goal of this study was to improve understanding of factors affecting temporal carbon metabolism at a natural savanna site near Skukuza, South Africa. We investigated inter-annual variability of optimum gross primary production (GPPopt) and ecosystem respiration (Reco) from 2000-2014. GPPopt refers to maximum total amount of carbon fixed by plants per unit area and time. Carbon dioxide (CO2) fluxes have been measured continuously at a 16 m tower at Skukuza using eddy covariance technique since 2000. The GPPopt and Reco parameters were derived from modelled light response curve fits of net ecosystem exchange (NEE) for summer `vegetative' periods. Hydro-ecological years (HEY) were stratified into functional seasons and data were classified into three soil moisture (SM) classes, i.e. wet (SM ≥ 9%), drying (6%< SM ≤9%) and dry periods (SM ≤ 6%), in order to separate biologically functional periods from periods of water constraints. For each SM class data were sub-classified into four air temperature (Tair) classes to separate Tair effects on NEE response to light. Wet periods recorded higher GPPopt and Reco estimates compared to drying periods. The curve fits for dry periods were not significant. We found high variability of GPPopt and Reco from `summer' to `summer' of each HEY. Wet period GPPopt of 2008/2009 and 2010/2011 were highest with 29.2±1.8 and 32.7±1.6 µmol CO2 m-2s-1, respectively, whilst 2006/2007 recorded the lowest GPPopt of 6.5±1.3 µmol CO2 m-2s-1 for Tair class `20°Cair≤25°C'. A similar pattern for Reco trend was observed. We also investigated the influence of rainfall distribution and amount, vapour pressure deficit, Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the GPPopt and Reco trends and found a high correlation between GPPopt and variables NDVI and EVI. Our findings have implications in understanding causality and temporal dynamics of GPPopt and Reco in precipitation pulse-driven semi-arid ecosystems.

Inter- and intra-annual variation of water footprint of crops and blue water scarcity in the Yellow River basin (1961-2009)

NASA Astrophysics Data System (ADS)

Zhuo, La; Mekonnen, Mesfin M.; Hoekstra, Arjen Y.; Wada, Yoshihide

2016-01-01

The Yellow River Basin (YRB), the second largest river basin of China, has experienced a booming agriculture over the past decades. But data on variability of and trends in water consumption, pollution and scarcity in the YRB are lacking. We estimate, for the first time, the inter- and intra-annual water footprint (WF) of crop production in the YRB for the period 1961-2009 and the variation of monthly scarcity of blue water (ground and surface water) for 1978-2009, by comparing the blue WF of agriculture, industry and households in the basin to the maximum sustainable level. Results show that the average overall green (from rainfall) and blue (from irrigation) WFs of crops in the period 2001-2009 were 14% and 37% larger, respectively, than in the period 1961-1970. The annual nitrogen- and phosphorus-related grey WFs (water required to assimilate pollutants) of crop production grew by factors of 24 and 36, respectively. The green-blue WF per ton of crop reduced significantly due to improved crop yields, while the grey WF increased because of the growing application of fertilizers. The ratio of blue to green WF increased during the study period resulting from the expansion of irrigated agriculture. In the period 1978-2009, the annual total blue WFs related to agriculture, industry and households varied between 19% and 52% of the basin's natural runoff. The blue WF in the YRB generally peaks around May-July, two months earlier than natural peak runoff. On average, the YRB faced moderate to severe blue water scarcity during seven months (January-July) per year. Even in the wettest month in a wet year, about half of the area of the YRB still suffered severe blue water scarcity, especially in the basin's northern part.

Simulation of streamflow, evapotranspiration, and groundwater recharge in the lower San Antonio River Watershed, South-Central Texas, 2000-2007

USGS Publications Warehouse

Lizarraga, Joy S.; Ockerman, Darwin J.

2010-01-01

The U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, the Evergreen Underground Water Conservation District, and the Goliad County Groundwater Conservation District, configured, calibrated, and tested a watershed model for a study area consisting of about 2,150 square miles of the lower San Antonio River watershed in Bexar, Guadalupe, Wilson, Karnes, DeWitt, Goliad, Victoria, and Refugio Counties in south-central Texas. The model simulates streamflow, evapotranspiration (ET), and groundwater recharge using rainfall, potential ET, and upstream discharge data obtained from National Weather Service meteorological stations and USGS streamflow-gaging stations. Additional time-series inputs to the model include wastewater treatment-plant discharges, withdrawals for cropland irrigation, and estimated inflows from springs. Model simulations of streamflow, ET, and groundwater recharge were done for 2000-2007. Because of the complexity of the study area, the lower San Antonio River watershed was divided into four subwatersheds; separate HSPF models were developed for each subwatershed. Simulation of the overall study area involved running simulations of the three upstream models, then running the downstream model. The surficial geology was simplified as nine contiguous water-budget zones to meet model computational limitations and also to define zones for which ET, recharge, and other water-budget information would be output by the model. The model was calibrated and tested using streamflow data from 10 streamflow-gaging stations; additionally, simulated ET was compared with measured ET from a meteorological station west of the study area. The model calibration is considered very good; streamflow volumes were calibrated to within 10 percent of measured streamflow volumes. During 2000-2007, the estimated annual mean rainfall for the water-budget zones ranged from 33.7 to 38.5 inches per year; the estimated annual mean rainfall for the entire watershed was 34.3 inches. Using the HSPF model it was estimated that for 2000-2007, less than 10 percent of the annual mean rainfall on the study watershed exited the watershed as streamflow, whereas about 82 percent, or an average of 28.2 inches per year, exited the watershed as ET. Estimated annual mean groundwater recharge for the entire study area was 3.0 inches, or about 9 percent of annual mean rainfall. Estimated annual mean recharge was largest in water-budget zone 3, the zone where the Carrizo Sand outcrops. In water-budget zone 3, the estimated annual mean recharge was 5.1 inches or about 15 percent of annual mean rainfall. Estimated annual mean recharge was smallest in water-budget zone 6, about 1.1 inches or about 3 percent of annual mean rainfall. The Cibolo Creek subwatershed and the subwatershed of the San Antonio River upstream from Cibolo Creek had the largest and smallest basin yields, about 4.8 inches and 1.2 inches, respectively. Estimated annual ET and annual recharge generally increased with increasing annual rainfall. Also, ET was larger in zones 8 and 9, the most downstream zones in the watershed. Model limitations include possible errors related to model conceptualization and parameter variability, lack of data to quantify certain model inputs, and measurement errors. Uncertainty regarding the degree to which available rainfall data represent actual rainfall is potentially the most serious source of measurement error.

Evaluating spatial and temporal variations of rainfall erosivity, case of Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Meshesha, Derege Tsegaye; Tsunekawa, Atsushi; Tsubo, Mitsuru; Haregeweyn, Nigussie; Adgo, Enyew

2015-02-01

Land degradation in many Ethiopian highlands occurs mainly due to high rainfall erosivity and poor soil conservation practices. Rainfall erosivity is an indicator of the precipitation energy and ability to cause soil erosion. In Central Rift Valley (CRV) of Ethiopia, where the climate is characterized as arid and semiarid, rainfall is the main driver of soil erosion that in turn causes a serious expansion in land degradation. In order to evaluate the spatial and temporal variability of rainfall erosivity and its impact on soil erosion, long-term rainfall data (1980-2010) was used, and the monthly Fournier index (FI) and the annual modified Fournier index (MFI) were applied. Student's t test analysis was performed particularly to examine statistical significances of differences in average monthly and annual erosivity values. The result indicated that, in a similar spatial pattern with elevation and rainfall amount, average annual erosivity is also found being higher in western highlands of the valley and gradually decreased towards the east. The long-term average annual erosivity (MFI) showed a general decreasing trend in recent 10 years (2000-2010) as compared to previous 20 years (1980-1999). In most of the stations, average erosivity of main rainy months (May, June, July, and August) showed a decreasing trend, whereby some of them (about 33.3 %) are statically significant at 90 and 95 % confidence intervals but with high variation in spatial pattern of changes. The overall result of the study showed that rainfall aggression (erosivity) in the region has a general decreasing trend in the recent decade as compared to previous decades, especially in the western highlands of the valley. Hence, it implies that anthropogenic factors such as land use change being coupled with topography (steep slope) have largely contributed to increased soil erosion rate in the region.

Hydrological Responses to Changes in the Rainfall Regime are Less Pronounced in Forested Basins: an Analysis of Southern Brazil, 1975-2010

NASA Astrophysics Data System (ADS)

Chagas, V. B. P.; Chaffe, P. L. B.

2017-12-01

It is unknown to what extent the hydrological responses to changes in the rainfall regime vary across forested and non-forested landscapes. Southern Brazil is approximately 570000 km² and was naturally covered mostly by tropical and subtropical forests. In the last century, a large proportion of forests were replaced by agricultural activities. The rainfall regime has also changed substantially in the last decades. The annual rainfall, number and magnitude of extreme events, and number of non-rainy days have increased in most of the area. In this study, we investigated the changes in the regime of 142 streamflow gauges and 674 rainfall gauges in Southern Brazil, from 1975 to 2010. The changes in the regime were analyzed for forested basins (i.e., with more than 50% forest coverage) and non-forested basins (i.e., with less than 20% forest coverage). The area of the river basins ranged from 100 to 60000 km². We analyzed a total of six signatures that represent the regime, including annual averages, seasonality, floods, and droughts. The statistical trends of the signatures were calculated using the Mann-Kendall test and the Sen's slope. The results showed that the majority of basins with opposing signal trends for mean annual streamflow and rainfall are non-forested basins (i.e., basins with higher anthropogenic impacts). Forested basins had a lower correlation between trends in the streamflow and rainfall trends for the seasonality and the average duration of drought events. There was a lower variability in the annual maximum 1-day streamflow trends in the forested basins. Additionally, despite a decrease in the 31-day rainfall minima and an increase in the seasonality, in forested basins the 7-day streamflow minima increases were substantially larger than in non-forested basins. In summary, the forested basins were less responsive to the changes in the precipitation 1-day maxima, seasonality, number of dry days, and 31-day minima.

Rainfall Climatology over Asir Region, Saudi Arabia

NASA Astrophysics Data System (ADS)

Sharif, H.; Furl, C.; Al-Zahrani, M.

2012-04-01

Arid and semi-arid lands occupy about one-third of the land surface of the earth and support about one-fifth of the world population. The Asir area in Saudi Arabia is an example of these areas faced with the problem of maintaining sustainable water resources. This problem is exacerbated by the high levels of population growth, land use changes, increasing water demand, and climate variability. In this study, the characteristics of decade-scale variations in precipitation are examined in more detail for Asir region. The spatio-temporal distributions of rainfall over the region are analyzed. The objectives are to identify the sensitivity, magnitude, and range of changes in annual and seasonal evapotranspiration resulting from observed decade-scale precipitation variations. An additional objective is to characterize orographic controls on the space-time variability of rainfall. The rainfall data is obtained from more than 30 rain gauges spread over the region.

Dominance and environmental correlates of alien annual plants in the Mojave Desert, USA

USGS Publications Warehouse

Brooks, M.L.; Berry, K.H.

2006-01-01

Land managers are concerned about the negative effects of alien annual plants on native plants, threatened and endangered species such as the desert tortoise (Gopherus agassizii), and ecosystem integrity in the Mojave Desert. Management of alien plants is hampered by a lack of information regarding the dominance and environmental correlates of these species. The results of this study indicate that alien plant species comprised a small fraction of the total annual plant flora, but most of the annual plant community biomass. When rainfall was high in 1995, aliens comprised 6% of the flora and 66% of the biomass. When rainfall was low in 1999, aliens comprised 27% of the flora and 91% of the biomass. Bromus rubens, Schismus spp. (S. arabicus and S. barbatus), and Erodium cicutarium were the predominant alien species during both years, comprising 99% of the alien biomass. B. rubens was more abundant in relatively mesic microhabitats beneath shrub canopies and at higher elevations above 800-1000 m, whereas Schismus spp. and E. cicutarium were more abundant in the relatively arid interspaces between shrubs, and, for Schismus spp., at lower elevations as well. Disturbance variables were more reliable indicators of alien dominance than were productivity or native plant diversity variables, although relationships often varied between years of contrasting rainfall. The strongest environmental correlates occurred between dirt road density and alien species richness and biomass of E. cicutarium, and between frequency and size of fires and biomass of B. rubens.

Understanding Flood Seasonality and Its Temporal Shifts within the Contiguous United States

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

Ye, Sheng; Li, Hong-Yi; Leung, L. Ruby

2017-07-01

Understanding the causes of flood seasonality is critical for better flood management. This study examines the seasonality of annual maximum floods (AMF) and its changes before and after 1980 at over 250 natural catchments across the contiguous United States. Using circular statistics to define a seasonality index, our analysis focuses on the variability of the flood occurrence date. Generally, catchments with more synchronized seasonal water and energy cycles largely inherit their seasonality of AMF from that of annual maximum rainfall (AMR). In contrast, the seasonality of AMF in catchments with loosely synchronized water and energy cycles are more influenced bymore » high antecedent storage, which is responsible for the amplification of the seasonality of AMF over that of AMR. This understanding then effectively explains a statistically significant shift of flood seasonality detected in some catchments in the recent decades. Catchments where the antecedent soil water storage has increased since 1980 exhibit increasing flood seasonality while catchments that have experienced increases in storm rainfall before the floods have shifted towards floods occurring more variably across the seasons. In the eastern catchments, a concurrent widespread increase in event rainfall magnitude and reduced soil water storage have led to a more variable timing of floods. Our findings of the role of antecedent storage and event rainfall on the flood seasonality provide useful insights for understanding future changes in flood seasonality as climate models projected changes in extreme precipitation and aridity over land.« less

Analysis of trends in streamflow and its linkages with rainfall and anthropogenic factors in Gomti River basin of North India

NASA Astrophysics Data System (ADS)

Abeysingha, N. S.; Singh, Man; Sehgal, V. K.; Khanna, Manoj; Pathak, Himanshu

2016-02-01

Trend analysis of hydro-climatic variables such as streamflow, rainfall, and temperature provides useful information for effective water resources planning, designing, and management. Trends in observed streamflow at four gauging stations in the Gomti River basin of North India were assessed using the Mann-Kendall and Sen's slope for the 1982 to 2012 period. The relationships between trends in streamflow and rainfall were studied by correlation analyses. There was a gradual decreasing trend of annual, monsoonal, and winter seasonal streamflow ( p < 0.05) from the midstream to the downstream of the river and also a decreasing trend of annual streamflow for the 5-year moving averaged standardized anomalies of streamflow for the entire basin. The declining trend in the streamflow was attributed partly to the increased water withdrawal, to increased air temperature, to higher population, and partly to significant reducing trend of post monsoon rainfall especially at downstream. Upstream gauging station showed a significant increasing trend of streamflow (1.6 m3/s/year) at annual scale, and this trend was attributed to the significant increasing trend of catchment rainfall (9.54 mm/year). It was further evident in the significant coefficient of positive correlation ( ρ = 0.8) between streamflow and catchment rainfall. The decreasing trend in streamflow and post-monsoon rainfall especially towards downstream area with concurrent increasing trend of temperature indicates a drying tendency of the Gomti River basin over the study period. The results of this study may help stakeholders to design streamflow restoration strategies for sustainable water management planning of the Gomti River basin.

Emerging role of Indian ocean on Indian northeast monsoon

NASA Astrophysics Data System (ADS)

Yadav, Ramesh Kumar

2013-07-01

This study examines the emerging role of Indian Ocean sea surface temperature (SST) on the inter-annual variability (IAV) of Indian north-east monsoon rainfall (NEMR). The IAV of NEMR is associated with the warm SST anomaly over east Bay-of-Bengal (BoB) (88.5oE-98.5oE; 8.5oN-15.5oN) and cool SST anomaly over east equatorial Indian Ocean (80.5oE-103.5oE; 6.5oS-3.5oN). The gradient of SST between these boxes (i.e. northern box minus southern box) shows strong and robust association with the Indian NEMR variability in the recent decades. For establishing the teleconnections, SST, mean sea level pressure, North Indian Ocean tropical storm track, and circulation data have been used. The study reveals that during the positive SST gradient years, the inter-tropical convergence zone (ITCZ) shifts northwards over the East Indian Ocean. The tropical depressions, storms and cyclones formed in the North Indian Ocean moves more zonally and strike the southern peninsular India and hence excess NEMR. While, during the negative SST gradient years, the ITCZ shifts southwards over the Indian Ocean. The tropical depressions, storms and cyclones formed in the North Indian Ocean moves more northwestward direction and after crossing 15oN latitude re-curve to north-east direction towards head BoB and misses southern peninsular India and hence, deficient NEMR.

The magnitude of variability produced by methods used to estimate annual stormwater contaminant loads for highly urbanised catchments.

PubMed

Beck, H J; Birch, G F

2013-06-01

Stormwater contaminant loading estimates using event mean concentration (EMC), rainfall/runoff relationship calculations and computer modelling (Model of Urban Stormwater Infrastructure Conceptualisation--MUSIC) demonstrated high variability in common methods of water quality assessment. Predictions of metal, nutrient and total suspended solid loadings for three highly urbanised catchments in Sydney estuary, Australia, varied greatly within and amongst methods tested. EMC and rainfall/runoff relationship calculations produced similar estimates (within 1 SD) in a statistically significant number of trials; however, considerable variability within estimates (∼50 and ∼25 % relative standard deviation, respectively) questions the reliability of these methods. Likewise, upper and lower default inputs in a commonly used loading model (MUSIC) produced an extensive range of loading estimates (3.8-8.3 times above and 2.6-4.1 times below typical default inputs, respectively). Default and calibrated MUSIC simulations produced loading estimates that agreed with EMC and rainfall/runoff calculations in some trials (4-10 from 18); however, they were not frequent enough to statistically infer that these methods produced the same results. Great variance within and amongst mean annual loads estimated by common methods of water quality assessment has important ramifications for water quality managers requiring accurate estimates of the quantities and nature of contaminants requiring treatment.

Climate influence on dengue epidemics in Puerto Rico.

PubMed

Jury, Mark R

2008-10-01

The variability of the insect-borne disease dengue in Puerto Rico was studied in relation to climatic variables in the period 1979-2005. Annual and monthly reported dengue cases were compared with precipitation and temperature data. Results show that the incidence of dengue in Puerto Rico was relatively constant over time despite global warming, possibly due to the offsetting effects of declining rainfall, improving health care and little change in population. Seasonal fluctuations of dengue were driven by rainfall increases from May to November. Year-to-year variability in dengue cases was positively related to temperature, but only weakly associated with local rainfall and an index of El Nino Southern Oscillation (ENSO). Climatic conditions were mapped with respect to dengue cases and patterns in high and low years were compared. During epidemics, a low pressure system east of Florida draws warm humid air over the northwestern Caribbean. Long-term trends in past observed and future projected rainfall and temperatures were studied. Rainfall has declined slowly, but temperatures in the Caribbean are rising with the influence of global warming. Thus, dengue may increase in the future, and it will be necessary to anticipate dengue epidemics using climate forecasts, to reduce adverse health impacts.

Effects of climate change on phenology in two French LTER (Alps and Brittany) for the period 1998-2009

NASA Astrophysics Data System (ADS)

Perrimond, B.; Bigot, S.; Quénol, H.; Spielgelberger, T.; Baudry, J.

2012-04-01

Climate and vegetation are linked all over the world. In this study, we work on a seasonal weather classification based on air temperature and precipitation to deduce a link with different phenological stage (greening up, senescence, ...) over a 12 year period (1998-2009) for two different domains in France (Alps and Brittany). In temperate land, the main climatic variable with a potential effect on vegetation is the mean temperature followed by the rainfall deficit. A better understanding in season and their climatic characteristic is need to establish link between climate and phenology; so a weather classification is proposed based on empirical orthogonal functions and ascending hierarchical classification on atmospheric variables. This classification allows us to exhibit the inter-annual and intra-seasonal climatic spatiotemporal variability for both experimental site. Relationships between climate and phenology consist in a comparison between advance and delay in phenological stage and weather type issue from the classification. Experiment field are two french Long Term Ecological Research (LTER). The first one (LTER 'Alps' ) have mountain characteristics about 1000 to 4780 m ASL, ~65% of forest occupation ; the second one (LTER Armorique) is an Atlantic coastal landscape, 0-360 m ASL, ~70% of agricultural field. Climatic data are SAFRAN-France reanalysis which are developed to run SVAT model and come from the French meteorological service 'Météo-France'. All atmospheric variable needed to run a hydrological model are available (air temperature, rainfall/snowfall, wind speed, relative humidity, incoming/outcoming radiation) at a 8-8 km2 space resolution and with a daily time resolution. The phenological data are extracted from SPOT-VGT product 1-1 km2 space resolution and 10 days time resolution) by time series analysis process. Such of study is particularly important to understand relationships between environmental and ecological variables and it will allow to better predict ecological reaction under climate change constraint.

Quantifying the Spatial Distribution of Hill Slope Erosion Using a 3-D Laser Scanner

NASA Astrophysics Data System (ADS)

Scholl, B. N.; Bogonko, M.; He, Y.; Beighley, R. E.; Milberg, C. T.

2007-12-01

Soil erosion is a complicated process involving many interdependent variables including rainfall intensity and duration, drop size, soil characteristics, ground cover, and surface slope. The interplay of these variables produces differing spatial patterns of rill versus inter-rill erosion by changing the effective energy from rain drop impacts and the quantities and timing of sheet and shallow, concentrated flow. The objective of this research is to characterize the spatial patterns of rill and inter-rill erosion produced from simulated rainfall on different soil densities and surface slopes using a 3-D laser scanner. The soil used in this study is a sandy loam with bulk density due to compaction ranging from 1.25-1.65 g/cm3. The surface slopes selected for this study are 25, 33, and 50 percent and represent common slopes used for grading on construction sites. The spatial patterns of soil erosion are measured using a Trimble GX DR 200+ 3D Laser Scanner which employs a time of flight calculation averaged over 4 points using a class 2, pulsed, 532 nm, green laser at a distance of 2 to 11 m from the surface. The scanner measures point locations on an approximately 5 mm grid. The pre- and post-erosion scan surfaces are compared to calculate the change in volume and the dimensions of rills and inter-rill areas. The erosion experiments were performed in the Soil Erosion Research Laboratory (SERL), part of the Civil and Environmental Engineering department at San Diego State University. SERL experiments utilize a 3-m by 10-m tilting soil bed with a soil depth of 0.5 meters. Rainfall is applied to the soil surface using two overhead Norton ladder rainfall simulators, which produce realistic rain drop diameters (median = 2.25 mm) and impact velocities. Simulated storm events used in this study consist of rainfall intensities ranging from 5, 10 to 15 cm/hr for durations of 20 to 30 minutes. Preliminary results are presented that illustrate a change in runoff processes and erosion patterns as soil density increases and reduces infiltration characteristics. Total soil loss measured from the bottom of the erosion bed is compared to the volume of soil loss determined using the laser scanner. Due to soil consolidation during the experiment, the accuracy of measured soil loss from the laser scanner increases with increasing soil density. Ratios of rill and inter-rill erosions for each experiment are also presented. URL: http://spatialhydro.sdsu.edu

High-resolution dynamical downscaling of re-analysis data over the Kerguelen Islands using the WRF model

NASA Astrophysics Data System (ADS)

Fonseca, Ricardo; Martín-Torres, Javier

2018-03-01

We have used the Weather Research and Forecasting (WRF) model to simulate the climate of the Kerguelen Islands (49° S, 69° E) and investigate its inter-annual variability. Here, we have dynamically downscaled 30 years of the Climate Forecast System Reanalysis (CFSR) over these islands at 3-km horizontal resolution. The model output is found to agree well with the station and radiosonde data at the Port-aux-Français station, the only location in the islands for which observational data is available. An analysis of the seasonal mean WRF data showed a general increase in precipitation and decrease in temperature with elevation. The largest seasonal rainfall amounts occur at the highest elevations of the Cook Ice Cap in winter where the summer mean temperature is around 0 °C. Five modes of variability are considered: conventional and Modoki El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Subtropical IOD (SIOD) and Southern Annular Mode (SAM). It is concluded that a key mechanism by which these modes impact the local climate is through interaction with the diurnal cycle in particular in the summer season when it has a larger magnitude. One of the most affected regions is the area just to the east of the Cook Ice Cap extending into the lower elevations between the Gallieni and Courbet Peninsulas. The WRF simulation shows that despite the small annual variability, the atmospheric flow in the Kerguelen Islands is rather complex which may also be the case for the other islands located in the Southern Hemisphere at similar latitudes.

Effect of initial conditions and of intra-event rainfall intensity variability on shallow landslide triggering return period

NASA Astrophysics Data System (ADS)

Peres, David Johnny; Cancelliere, Antonino

2016-04-01

Assessment of shallow landslide hazard is important for appropriate planning of mitigation measures. Generally, return period of slope instability is assumed as a quantitative metric to map landslide triggering hazard on a catchment. The most commonly applied approach to estimate such return period consists in coupling a physically-based landslide triggering model (hydrological and slope stability) with rainfall intensity-duration-frequency (IDF) curves. Among the drawbacks of such an approach, the following assumptions may be mentioned: (1) prefixed initial conditions, with no regard to their probability of occurrence, and (2) constant intensity-hyetographs. In our work we propose the use of a Monte Carlo simulation approach in order to investigate the effects of the two above mentioned assumptions. The approach is based on coupling a physically based hydrological and slope stability model with a stochastic rainfall time series generator. By this methodology a long series of synthetic rainfall data can be generated and given as input to a landslide triggering physically based model, in order to compute the return period of landslide triggering as the mean inter-arrival time of a factor of safety less than one. In particular, we couple the Neyman-Scott rectangular pulses model for hourly rainfall generation and the TRIGRS v.2 unsaturated model for the computation of transient response to individual rainfall events. Initial conditions are computed by a water table recession model that links initial conditions at a given event to the final response at the preceding event, thus taking into account variable inter-arrival time between storms. One-thousand years of synthetic hourly rainfall are generated to estimate return periods up to 100 years. Applications are first carried out to map landslide triggering hazard in the Loco catchment, located in highly landslide-prone area of the Peloritani Mountains, Sicily, Italy. Then a set of additional simulations are performed in order to compare the results obtained by the traditional IDF-based method with the Monte Carlo ones. Results indicate that both variability of initial conditions and of intra-event rainfall intensity significantly affect return period estimation. In particular, the common assumption of an initial water table depth at the base of the pervious strata may lead in practice to an overestimation of return period up to one order of magnitude, while the assumption of constant-intensity hyetographs may yield an overestimation by a factor of two or three. Hence, it may be concluded that the analysed simplifications involved in the traditional IDF-based approach generally imply a non-conservative assessment of landslide triggering hazard.

Rainfall spatiotemporal variability relation to wetlands hydroperiods

NASA Astrophysics Data System (ADS)

Serrano-Hidalgo, Carmen; Guardiola-Albert, Carolina; Fernandez-Naranjo, Nuria

2017-04-01

Doñana natural space (Southwestern Spain) is one of the largest protected wetlands in Europe. The wide marshes present in this natural space have such ecological value that this wetland has been declared a Ramsar reserve in 1982. Apart from the extensive marsh, there are also small lagoons and seasonally flooded areas which are likewise essential to maintain a wide variety of valuable habitats. Hydroperiod, the length of time each point remains flooded along an annual cycle, is a critical ecological parameter that shapes aquatic plants and animals distribution and determines available habitat for many of the living organisms in the marshes. Recently, there have been published two different works estimating the hydroperiod of Doñana lagoons with Landsat Time Series images (Cifuentes et al., 2015; Díaz-Delgado et al., 2016). In both works the flooding cycle hydroperiod in Doñana marshes reveals a flooding regime mainly driven by rainfall, evapotranspiration, topography and local hydrological management actions. The correlation found between rainfall and hydroperiod is studied differently in both works. While in one the rainfall is taken from one raingauge (Cifuentes et al., 2015), the one performed by Díaz-Delgado (2016) uses annual rainfall maps interpolated with the inverse of the distance method. The rainfall spatiotemporal variability in this area can be highly significant; however the amount of this importance has not been quantified at the moment. In the present work the geostatistical tool known as spatiotemporal variogram is used to study the rainfall spatiotemporal variability. The spacetime package implemented in R (Pebesma, 2012) facilities its computation from a high rainfall data base of more than 100 raingauges from 1950 to 2016. With the aid of these variograms the rainfall spatiotemporal variability is quantified. The principal aim of the present work is the study of the relation between the rainfall spatiotemporal variability and the hydroperiods of wetlands present in Doñana natural space. Key issues: spatiotemporal variability, geostatistics, hydroperiod, wetlands. References: Cifuentes, V., García, M.A., Checa, M.J. & Escudero, R. (2015). Estimación por teledetección de la superficie de la lámina de agua y los niveles de profundidad de las lagunas en los humedales de la Campiña Andaluza Central incluidos en la demarcación hidrográfica del Guadalquivir. Teledetección: Humedales y Espacios Protegidos. Presented in XVI Congreso de la Asociación Española de Teledetección. pp. 322-325. Sevilla 21-23 octubre 2015. http://ocs.ebd.csic.es/index.php/AET/2015/schedConf/presentations Díaz-Delgado, R., Carro, F., Herruzo, F. Q., Osuna, A., & Baena, M. (2016). Contribución del seguimiento ecológico a largo plazo a la investigación y la gestión en la plataforma LTSER-Doñana. Revista Ecosistemas, 25(1), 9-18. Pebesma, E. (2012). spacetime: Spatio-temporal data in r. Journal of Statistical Software, 51(7), 1-30.

Use of microwave satellite data to study variations in rainfall over the Indian Ocean

NASA Technical Reports Server (NTRS)

Hinton, Barry B.; Martin, David W.; Auvine, Brian; Olson, William S.

1990-01-01

The University of Wisconsin Space Science and Engineering Center mapped rainfall over the Indian Ocean using a newly developed Scanning Multichannel Microwave Radiometer (SMMR) rain-retrieval algorithm. The short-range objective was to characterize the distribution and variability of Indian Ocean rainfall on seasonal and annual scales. In the long-range, the objective is to clarify differences between land and marine regimes of monsoon rain. Researchers developed a semi-empirical algorithm for retrieving Indian Ocean rainfall. Tools for this development have come from radiative transfer and cloud liquid water models. Where possible, ground truth information from available radars was used in development and testing. SMMR rainfalls were also compared with Indian Ocean gauge rainfalls. Final Indian Ocean maps were produced for months, seasons, and years and interpreted in terms of historical analysis over the sub-continent.

Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

2016-12-01

One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

Seasonal variation in pans in relation to limno-chemistry, size, hydroperiod, and river connectivity in a semi-arid subtropical region

NASA Astrophysics Data System (ADS)

Nhiwatiwa, Tamuka; Dalu, Tatenda

2017-02-01

Seasonal pans are hydrologically dynamic, with significant changes in water volume and depth in response to high evaporation, infiltration rates and inundation events. Intra-seasonal and inter-seasonal changes in endorheic and floodplain pans in relation to limnology, size, hydroperiod, and river connectivity were studied over two rainfall seasons across 36 pans at the Save Valley Conservancy. In the study region, floodplain pans were identified as pans that had connectivity with the Save River, while the endorheic pans (large and small) were hydrologically isolated basins. Seasonal trends for physico-chemical variables were initial low and gradual increased for both rainfall seasons. Significant inter-seasonal differences for several physico-chemical variables were observed. No significant differences in physico-chemical variables were observed between large and small endorheic pans, with the except for vegetation cover, which was higher in large pans. Floodplain pans differed from the endorheic systems in pH, conductivity, nutrients and suspended solids. Connectivity was found to be insignificant, as connections between these systems were probably too infrequent. Seasonal pans were uniquely distinguished by their morphometric, physico-chemical and hydrological characteristics. Inevitably, they are vulnerable to climate change with the extent of their resilience currently unknown.

Estimating annual bole biomass production using uncertainty analysis

Treesearch

Travis J. Woolley; Mark E. Harmon; Kari B. O' Connell

2007-01-01

Two common sampling methodologies coupled with a simple statistical model were evaluated to determine the accuracy and precision of annual bole biomass production (BBP) and inter-annual variability estimates using this type of approach. We performed an uncertainty analysis using Monte Carlo methods in conjunction with radial growth core data from trees in three Douglas...

Coral Luminescence Identifies the Pacific Decadal Oscillation as a Primary Driver of River Runoff Variability Impacting the Southern Great Barrier Reef

PubMed Central

Rodriguez-Ramirez, Alberto; Grove, Craig A.; Zinke, Jens; Pandolfi, John M.; Zhao, Jian-xin

2014-01-01

The Pacific Decadal Oscillation (PDO) is a large-scale climatic phenomenon modulating ocean-atmosphere variability on decadal time scales. While precipitation and river flow variability in the Great Barrier Reef (GBR) catchments are sensitive to PDO phases, the extent to which the PDO influences coral reefs is poorly understood. Here, six Porites coral cores were used to produce a composite record of coral luminescence variability (runoff proxy) and identify drivers of terrestrial influence on the Keppel reefs, southern GBR. We found that coral skeletal luminescence effectively captured seasonal, inter-annual and decadal variability of river discharge and rainfall from the Fitzroy River catchment. Most importantly, although the influence of El Niño-Southern Oscillation (ENSO) events was evident in the luminescence records, the variability in the coral luminescence composite record was significantly explained by the PDO. Negative luminescence anomalies (reduced runoff) were associated with El Niño years during positive PDO phases while positive luminescence anomalies (increased runoff) coincided with strong/moderate La Niña years during negative PDO phases. This study provides clear evidence that not only ENSO but also the PDO have significantly affected runoff regimes at the Keppel reefs for at least a century, and suggests that upcoming hydrological disturbances and ecological responses in the southern GBR region will be mediated by the future evolution of these sources of climate variability. PMID:24416214

Coral luminescence identifies the Pacific Decadal Oscillation as a primary driver of river runoff variability impacting the southern Great Barrier Reef.

PubMed

Rodriguez-Ramirez, Alberto; Grove, Craig A; Zinke, Jens; Pandolfi, John M; Zhao, Jian-xin

2014-01-01

The Pacific Decadal Oscillation (PDO) is a large-scale climatic phenomenon modulating ocean-atmosphere variability on decadal time scales. While precipitation and river flow variability in the Great Barrier Reef (GBR) catchments are sensitive to PDO phases, the extent to which the PDO influences coral reefs is poorly understood. Here, six Porites coral cores were used to produce a composite record of coral luminescence variability (runoff proxy) and identify drivers of terrestrial influence on the Keppel reefs, southern GBR. We found that coral skeletal luminescence effectively captured seasonal, inter-annual and decadal variability of river discharge and rainfall from the Fitzroy River catchment. Most importantly, although the influence of El Niño-Southern Oscillation (ENSO) events was evident in the luminescence records, the variability in the coral luminescence composite record was significantly explained by the PDO. Negative luminescence anomalies (reduced runoff) were associated with El Niño years during positive PDO phases while positive luminescence anomalies (increased runoff) coincided with strong/moderate La Niña years during negative PDO phases. This study provides clear evidence that not only ENSO but also the PDO have significantly affected runoff regimes at the Keppel reefs for at least a century, and suggests that upcoming hydrological disturbances and ecological responses in the southern GBR region will be mediated by the future evolution of these sources of climate variability.

Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

1997-01-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an eleven year period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444 km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are converted to monthly rainfall amounts and then compared to those for non-tropical cyclone systems. The main results of this study indicate that: 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maxima in tropical cyclone rainfall are poleward (5 deg to 10 deg latitude depending on longitude) of the maxima in non-tropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% of the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the ITCZ; and 5) in general, tropical cyclone rainfall is enhanced during the El Nino years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

Prediction of future climate change for the Blue Nile, using RCM nested in GCM

NASA Astrophysics Data System (ADS)

Sayed, E.; Jeuland, M.; Aty, M.

2009-04-01

Although the Nile River Basin is rich in natural resources, it faces many challenges. Rainfall is highly variable across the region, on both seasonal and inter-annual scales. This variability makes the region vulnerable to droughts and floods. Many development projects involving Nile waters are currently underway, or being studied. These projects will lead to land-use patterns changes and water distribution and availability. It is thus important to assess the effects of a) these projects and b) evolving water resource management and policies, on regional hydrological processes. This paper seeks to establish a basis for evaluation of such impacts within the Blue Nile River sub-basin, using the RegCM3 Regional Climate Model to simulate interactions between the land surface and climatic processes. We first present results from application of this RCM model nested with downscaled outputs obtained from the ECHAM5/MPI-OM1 transient simulations for the 20th Century. We then investigate changes associated with mid-21st century emissions forcing of the SRES A1B scenario. The results obtained from the climate model are then fed as inputs to the Nile Forecast System (NFS), a hydrologic distributed rainfall runoff model of the Nile Basin, The interaction between climatic and hydrological processes on the land surface has been fully coupled. Rainfall patterns and evaporation rates have been generated using RegCM3, and the resulting runoff and Blue Nile streamflow patterns have been simulated using the NFS. This paper compares the results obtained from the RegCM3 climate model with observational datasets for precipitation and temperature from the Climate Research Unit (UK) and the NASA Goddard Space Flight Center GPCP (USA) for 1985-2000. The validity of the streamflow predictions from the NFS is assessed using historical gauge records. Finally, we present results from modeling of the A1B emissions scenario of the IPCC for the years 2034-2055. Our results indicate that future changes in rainfall may vary over different areas of the Upper Blue Nile catchment in Ethiopia. Our results suggest that there may be good reasons for developing climate models with finer spatial resolution than the more commonly used GCMs.

Accounting for interannual variability: A comparison of options for water resources climate change impact assessments

NASA Astrophysics Data System (ADS)

Johnson, Fiona; Sharma, Ashish

2011-04-01

Empirical scaling approaches for constructing rainfall scenarios from general circulation model (GCM) simulations are commonly used in water resources climate change impact assessments. However, these approaches have a number of limitations, not the least of which is that they cannot account for changes in variability or persistence at annual and longer time scales. Bias correction of GCM rainfall projections offers an attractive alternative to scaling methods as it has similar advantages to scaling in that it is computationally simple, can consider multiple GCM outputs, and can be easily applied to different regions or climatic regimes. In addition, it also allows for interannual variability to evolve according to the GCM simulations, which provides additional scenarios for risk assessments. This paper compares two scaling and four bias correction approaches for estimating changes in future rainfall over Australia and for a case study for water supply from the Warragamba catchment, located near Sydney, Australia. A validation of the various rainfall estimation procedures is conducted on the basis of the latter half of the observational rainfall record. It was found that the method leading to the lowest prediction errors varies depending on the rainfall statistic of interest. The flexibility of bias correction approaches in matching rainfall parameters at different frequencies is demonstrated. The results also indicate that for Australia, the scaling approaches lead to smaller estimates of uncertainty associated with changes to interannual variability for the period 2070-2099 compared to the bias correction approaches. These changes are also highlighted using the case study for the Warragamba Dam catchment.

Energy Systems Integration News | Energy Systems Integration Facility |

Science.gov Websites

answer that question by examining the technical, infrastructure, economic, and policy barriers to greater intra-hour, inter-hour, seasonal, and inter-annual variability of solar resources-essential information powerful tool that provides essential information to policymakers, financiers, project developers, and

Climate change in Bangladesh: a spatio-temporal analysis and simulation of recent temperature and rainfall data using GIS and time series analysis model

NASA Astrophysics Data System (ADS)

Rahman, Md. Rejaur; Lateh, Habibah

2017-04-01

In this paper, temperature and rainfall data series were analysed from 34 meteorological stations distributed throughout Bangladesh over a 40-year period (1971 to 2010) in order to evaluate the magnitude of these changes statistically and spatially. Linear regression, coefficient of variation, inverse distance weighted interpolation techniques and geographical information systems were performed to analyse the trends, variability and spatial patterns of temperature and rainfall. Autoregressive integrated moving average time series model was used to simulate the temperature and rainfall data. The results confirm a particularly strong and recent climate change in Bangladesh with a 0.20 °C per decade upward trend of mean temperature. The highest upward trend in minimum temperature (range of 0.80-2.4 °C) was observed in the northern, northwestern, northeastern, central and central southern parts while greatest warming in the maximum temperature (range of 1.20-2.48 °C) was found in the southern, southeastern and northeastern parts during 1971-2010. An upward trend of annual rainfall (+7.13 mm per year) and downward pre-monsoon (-0.75 mm per year) and post-monsoon rainfall (-0.55 mm per year) trends were observed during this period. Rainfall was erratic in pre-monsoon season and even more so during the post-monsoon season (variability of 44.84 and 85.25 % per year, respectively). The mean forecasted temperature exhibited an increase of 0.018 °C per year in 2011-2020, and if this trend continues, this would lead to approximately 1.0 °C warmer temperatures in Bangladesh by 2020, compared to that of 1971. A greater rise is projected for the mean minimum (0.20 °C) than the mean maximum (0.16 °C) temperature. Annual rainfall is projected to decline 153 mm from 2011 to 2020, and a drying condition will persist in the northwestern, western and southwestern parts of the country during the pre- and post-monsoonal seasons.

Modelled rainfall skill assessment against a 1000-year time/space isotope dendro-climatology for southern Africa

NASA Astrophysics Data System (ADS)

Woodborne, Stephan; Hall, Grant; Zhang, Qiong

2016-04-01

Palaeoclimate reconstruction using isotopic analysis of tree growth increments has yielded a 1000-year record of rainfall variability in southern Africa. Isotope dendro-climatology reconstructions from baobab trees (Adansonia digitata) provide evidence for rainfall variability from the arid Namib Desert and the Limpopo River Valley. Isotopic analysis of a museum specimen of a yellowwood tree (Podocarps falcatus) yields another record from the southwestern part of the subcontinent. Combined with the limited classic denro-climatologies available in the region these records yield palaeo-rainfall variability in the summer and winter rainfall zones as well as the hyper-arid zone over the last 1000 years. Coherent shifts in all of the records indicate synoptic changes in the westerlies, the inter-tropical convergence zone, and the Congo air boundary. The most substantial rainfall shift takes place at about 1600 CE at the onset of the Little Ice Age. Another distinctive feature of the record is a widespread phenomenon that occurs shortly after 1810 CE that in southern Africa corresponds with a widespread social upheaval known as the Difequane or Mfekane. Large scale forcing of the system includes sea-surface temperatures in the Agulhas Current, the El Nino Southern Oscillation and the Southern Annular Mode. The Little Ice Age and Mfekane climate shifts result from different forcing mechanisms, and the rainfall response in the different regions at these times do not have a fixed phase relationship. This complexity provides a good scenario to test climate models. A first order (wetter versus drier) comparison between each of the tree records and a 1000-year palaeoclimate model simulation for the Little Ice Age and Mfekane transitions demonstrates a generally good correspondence.

Implications of global warming for regional climate and water resources of tropical islands: Case studies over Sri Lanka and Puerto Rico

NASA Astrophysics Data System (ADS)

Mawalagedara, R.; Kumar, D.; Oglesby, R. J.; Ganguly, A. R.

2013-12-01

The IPCC AR4 identifies small islands as particularly vulnerable to climate change. Here we consider the cases of two tropical islands: Sri Lanka in the Indian Ocean and Puerto Rico in the Caribbean. The islands share a predominantly tropical climate with diverse topography and hence significant spatial variability of regional climate. Seasonal variability in temperatures is relatively small, but spatial variations can be large owing to topography. Precipitation mechanisms and patterns over the two islands are different however. Sri Lanka receives a majority of the annual rainfall from the summer and winter monsoons, with convective rainfall dominating in the inter-monsoon period. Rainfall generating mechanisms over Puerto Rico can range from orographic lifting, disturbances embedded in Easterly waves and synoptic frontal systems. Here we compare the projected changes in the regional and seasonal means and extremes of temperature and precipitation over the two islands during the middle of this century with the present conditions. Two 5-year regional climate model runs for each region, representing the present (2006-2010) and future (2056-2060) conditions, are performed using the Weather Research and Forecasting model with the lateral boundary conditions provided using the output from CCSM4 RCP8.5 greenhouse gas emissions pathway simulation from the CMIP5 ensemble. The consequences of global warming for water resources and the overall economy are examined. While both economies have substantial contributions from tourism, there are major differences: The agricultural sector is much more important over Sri Lanka compared to Puerto Rico, while the latter exhibits no recent growth in population or in urbanization trends unlike the former. Policy implications for water sustainability and security are discussed, which highlight how despite the differences, certain lessons learned may generalize across the two relatively small tropical islands, which in turn have diverse economic, infrastructural, and societal constraints.

Demography and population dynamics of the mouse opossum (Thylamys elegans) in semi-arid Chile: seasonality, feedback structure and climate.

PubMed Central

Lima, M.; Stenseth, N. C.; Yoccoz, N. G.; Jaksic, F. M.

2001-01-01

Here we present, to the authors' knowledge for the very first time for a small marsupial, a thorough analysis of the demography and population dynamics of the mouse opossum (Thylamys elegans) in western South America. We test the relative importance of feedback structure and climatic factors (rainfall and the Southern Oscillation Index) in explaining the temporal variation in the demography of the mouse opossum. The demographic information was incorporated into a stage-structured population dynamics model and the model's predictions were compared with observed patterns. The mouse opossum's capture rates showed seasonal (within-year) and between-year variability, with individuals having higher capture rates during late summer and autumn and lower capture rates during winter and spring. There was also a strong between-year effect on capture probabilities. The reproductive (the fraction of reproductively active individuals) and recruitment rates showed a clear seasonal and a between-year pattern of variation with the peak of reproductive activity occuring during winter and early spring. In addition, the fraction of reproductive individuals was positively related to annual rainfall, while population density and annual rainfall positively influenced the recruitment rate. The survival rates were negatively related to annual rainfall. The average finite population growth rate during the study period was estimated to be 1.011 +/- 0.0019 from capture-recapture estimates. While the annual growth rate estimated from the seasonal linear matrix models was 1.026, the subadult and adult survival and maturation rates represent between 54% (winter) and 81% (summer) of the impact on the annual growth rate. PMID:11571053

Climate Change Impact on Water Balance at the Chipola River Watershed in Florida

NASA Astrophysics Data System (ADS)

Griffen, J. M.; Chen, X.; Wang, D.; Hagen, S. C.

2013-12-01

As the largest tributary to the Apalachicola River, the Chipola River originates in southern Alabama, flows through the Florida Panhandle and drains into the Gulf of Mexico. The Chipola watershed is located in an intermediate climate environment with an aridity index of approximately 1.0. However, climate change affects the hydrologic cycle of Chipola River watershed at various temporal and spatial scales. Studying the effects of climate variations is of great importance for water and environmental management purposes in this watershed. This research is mainly focused on assessing climate change impact on the partitioning of rainfall and the following runoff generation in Chipola watershed, from long-term mean annual to inter-annual and to seasonal and monthly scales. A comprehensive water balance model at inter-annual scale is built in this study based on Budyko's framework, two-stage runoff theory and proportionality hypothesis. The inter-annual scale model considers the impact of storage change, seasonality and landscape controls, which are normally assumed to be negligible on a long-term scale. The model is applied to the Chipola River Watershed in Florida to project future water balance pattern with the input from a Regional Climate Model projection. Based on the projection results: evaporation will increase in the future in all 12 months; runoff will increase only in dry months of July to October, while significantly decrease in wet months of December to April; storage change will increase in wet months of January to April, while decrease in the dry months of August to November.

Validation of satellite-based rainfall in Kalahari

NASA Astrophysics Data System (ADS)

Lekula, Moiteela; Lubczynski, Maciek W.; Shemang, Elisha M.; Verhoef, Wouter

2018-06-01

Water resources management in arid and semi-arid areas is hampered by insufficient rainfall data, typically obtained from sparsely distributed rain gauges. Satellite-based rainfall estimates (SREs) are alternative sources of such data in these areas. In this study, daily rainfall estimates from FEWS-RFE∼11 km, TRMM-3B42∼27 km, CMOPRH∼27 km and CMORPH∼8 km were evaluated against nine, daily rain gauge records in Central Kalahari Basin (CKB), over a five-year period, 01/01/2001-31/12/2005. The aims were to evaluate the daily rainfall detection capabilities of the four SRE algorithms, analyze the spatio-temporal variability of rainfall in the CKB and perform bias-correction of the four SREs. Evaluation methods included scatter plot analysis, descriptive statistics, categorical statistics and bias decomposition. The spatio-temporal variability of rainfall, was assessed using the SREs' mean annual rainfall, standard deviation, coefficient of variation and spatial correlation functions. Bias correction of the four SREs was conducted using a Time-Varying Space-Fixed bias-correction scheme. The results underlined the importance of validating daily SREs, as they had different rainfall detection capabilities in the CKB. The FEWS-RFE∼11 km performed best, providing better results of descriptive and categorical statistics than the other three SREs, although bias decomposition showed that all SREs underestimated rainfall. The analysis showed that the most reliable SREs performance analysis indicator were the frequency of "miss" rainfall events and the "miss-bias", as they directly indicated SREs' sensitivity and bias of rainfall detection, respectively. The Time Varying and Space Fixed (TVSF) bias-correction scheme, improved some error measures but resulted in the reduction of the spatial correlation distance, thus increased, already high, spatial rainfall variability of all the four SREs. This study highlighted SREs as valuable source of daily rainfall data providing good spatio-temporal data coverage especially suitable for areas with limited rain gauges, such as the CKB, but also emphasized SREs' drawbacks, creating avenue for follow up research.

Ecosystem and Community Responses to Rainfall Manipulations in Shrublands Depends on Dominant Vegetation Cover

NASA Astrophysics Data System (ADS)

Esch, E. H.; Lipson, D.; Kim, J. B.; Cleland, E. E.

2014-12-01

Southern California is predicted to face decreasing precipitation with increased interannual variability in the coming century. Native shrublands in this area are increasingly invaded by exotic annual grasses, though invasion dynamics can vary by rainfall scenario, with wet years generally associated with high invasion pressure. Interplay between rainfall and invasion scenarios can influence carbon stocks and community composition. Here we asked how invasion alters ecosystem and community responses in drought versus high rainfall scenarios, as quantified by community identity, biomass production, and the normalized difference vegetation index (NDVI). To do this, we performed a rainfall manipulation experiment with paired plots dominated either by native shrubs or exotic herbaceous species, subjected to treatments of 50%, 100%, or 150% of ambient rainfall. The study site was located in a coastal sage scrub ecosystem, with patches dominated by native shrubs and exotic grasses located in San Diego County, USA. During two growing seasons, we found that native, herbaceous biomass production was significantly affected by rainfall treatment (p<0.05 for both years), though was not affected by dominant community composition. Photosynthetic biomass production of shrub species also varied by treatment (p=0.035). Exotic biomass production showed a significant interaction between dominant community composition and rainfall treatment, and both individual effects (p<0.001 for all). NDVI showed similar results, but also indicated the importance of rainfall timing on overall biomass production between years. Community composition data showed certain species, of both native and exotic identities, segregating by treatment. These results indicate that exotic species are more sensitive to rainfall, and that increased rainfall may promote greater carbon storage in annual dominated communities when compared to shrub dominated communities in high rainfall years, but with drought, this trend is reversed.

Leaf and wood carbon isotope ratios, specific leaf areas and wood growth of Eucalyptus species across a rainfall gradient in Australia.

PubMed

Schulze, Ernst-Detlef; Turner, Neil C; Nicolle, Dean; Schumacher, Jens

2006-04-01

Leaves and samples of recent wood of Eucalyptus species were collected along a rainfall gradient parallel to the coast of Western Australia between Perth in the north and Walpole in the south and along a southwest to northeast transect from Walpole in southwestern Australia, to near Mount Olga in central Australia. The collection included 65 species of Eucalyptus sampled at 73 sites and many of the species were collected at several sites along the rainfall gradient. Specific leaf area (SLA) and isotopic ratio of 13C to 12C (delta 13C) of leaves that grew in 2002, and tree ring growth and delta 13C of individual cell layers of the wood were measured. Rainfall data were obtained from the Australian Bureau of Meteorology for 29 locations that represented one or a few closely located collection sites. Site-averaged data and species-specific values of delta 13C decreased with decreasing annual rainfall between 1200 and 300 mm at a rate of 1.63 per thousand per 1000 mm decrease in rainfall. Responses became variable in the low rainfall region (< 300 mm), with some species showing decreasing delta 13C with rainfall, whereas delta 13C increased or remained constant in other species. The range of delta 13C values in the low rainfall region was as large as the range observed at sites receiving > 300 mm of annual rainfall. Specific leaf area varied between 2 and 6 m2 kg(-1) and tended to increase with decreasing annual rainfall in some species, but not all, whereas delta 13C decreased with SLA. The relationship between delta 13C and SLA was highly species and soil-type specific. Leaf-area-based nitrogen (N) content varied between 2 and almost 6 g m(-2) and decreased with rainfall. Thus, thicker leaves were associated with higher N content and this compensated for the effect of drought on delta 13C. Nitrogen content was also related to soil type and species identity. Based on a linear mixed model, statistical analysis of the whole data set showed that 27% of the variation in delta 13C was associated with changes in SLA, 16% with soil type and only 1% with rainfall. Additionally, 21% was associated with species identity. For a subset of sites with > 300 mm rainfall, 43% of the variation was explained by SLA, 13% by soil type and only 3% by rainfall. The species effect decreased to 9% because there were fewer species in the subset of sites. The small effect of rainfall on delta 13C was further supported by a path analysis that yielded a standardized path coefficient of 0.38 for the effect of rainfall on SLA and -0.50 for the effect of SLA on delta 13C, but an insignificantly low standardized path coefficient of -0.05 for the direct effect of rainfall on delta 13C. Thus, in contrast to our hypothesis that delta 13C decreases with rainfall independent of soil type and species, we detected no statistically significant relationship between rainfall and delta 13C in leaves of trees growing at sites receiving < 300 mm of rainfall annually. Rainfall affected delta 13C indirectly through soil type (a surrogate for water-holding capacity) across the rainfall gradient. Annual tree rings are not clearly visible in evergreen Eucalyptus species, even in the seasonally cool climate of SW Australia. Generally, visible density transitions in the wood are related not to a strict annual cycle but to periods of growth associated mainly with rainfall. The relationship between delta 13C of leaves and the width of these stem increments was not statistically significant. Analysis of stem growth periods showed that delta 13C in wood responded to rainfall events, but carbohydrate storage and reallocation also affected the isotopic signature. Although delta 13C in wood of any one species varied over a range of 2 to 4 per thousand, there was a general relationship between delta 13C of the leaves and the annual range of delta 13C in wood. We conclude that species-specific traits are important in understanding the response of Eucalyptus to rainfall and that the diversity of the genus may reflect its response to the large climatic gradient in Australia and to the large annual and interannual variations in rainfall at any one location.

Interannual variability of mean sea level and its sensitivity to wind climate in an inter-tidal basin

NASA Astrophysics Data System (ADS)

Gerkema, Theo; Duran-Matute, Matias

2017-12-01

The relationship between the annual wind records from a weather station and annual mean sea level in an inter-tidal basin, the Dutch Wadden Sea, is examined. Recent, homogeneous wind records are used, covering the past 2 decades. It is demonstrated that even such a relatively short record is sufficient for finding a convincing relationship. The interannual variability of mean sea level is largely explained by the west-east component of the net wind energy, with some further improvement if one also includes the south-north component and the annual mean atmospheric pressure. Using measured data from a weather station is found to give a slight improvement over reanalysis data, but for both the correlation between annual mean sea level and wind energy in the west-east direction is high. For different tide gauge stations in the Dutch Wadden Sea and along the coast, we find the same qualitative characteristics, but even within this small region, different locations show a different sensitivity of annual mean sea level to wind direction. Correcting observed values of annual mean level for meteorological factors reduces the margin of error (expressed as 95 % confidence interval) by more than a factor of 4 in the trends of the 20-year sea level record. Supplementary data from a numerical hydrodynamical model are used to illustrate the regional variability in annual mean sea level and its interannual variability at a high spatial resolution. This study implies that climatic changes in the strength of winds from a specific direction may affect local annual mean sea level quite significantly.

Inter-Annual Variability of the Acoustic Propagation in the Mediterranean Sea Identified from a Synoptic Monthly Gridded Database as Compared with GDEM

DTIC Science & Technology

2016-12-01

VARIABILITY OF THE ACOUSTIC PROPAGATION IN THE MEDITERRANEAN SEA IDENTIFIED FROM A SYNOPTIC MONTHLY GRIDDED DATABASE AS COMPARED WITH GDEM by...ANNUAL VARIABILITY OF THE ACOUSTIC PROPAGATION IN THE MEDITERRANEAN SEA IDENTIFIED FROM A SYNOPTIC MONTHLY GRIDDED DATABASE AS COMPARED WITH GDEM 5...profiles obtained from the synoptic monthly gridded World Ocean Database (SMD-WOD) and Generalized Digital Environmental Model (GDEM) temperature (T

Comparison of simulated and reconstructed variations in East African hydroclimate over the last millennium

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

Klein, Francois; Goosse, Hugues; Graham, Nicholas E.

The multi-decadal to centennial hydroclimate changes in East Africa over the last millennium are studied by comparing the results of forced transient simulations by six general circulation models (GCMs) with published hydroclimate reconstructions from four lakes: Challa and Naivasha in equatorial East Africa, and Masoko and Malawi in southeastern inter-tropical Africa. All GCMs simulate fairly well the unimodal seasonal cycle of precipitation in the Masoko–Malawi region, while the bimodal seasonal cycle characterizing the Challa–Naivasha region is generally less well captured by most models. Model results and lake-based hydroclimate reconstructions display very different temporal patterns over the last millennium. Additionally, theremore » is no common signal among the model time series, at least until 1850. This suggests that simulated hydroclimate fluctuations are mostly driven by internal variability rather than by common external forcing. After 1850, half of the models simulate a relatively clear response to forcing, but this response is different between the models. Overall, the link between precipitation and tropical sea surface temperatures (SSTs) over the pre-industrial portion of the last millennium is stronger and more robust for the Challa–Naivasha region than for the Masoko–Malawi region. At the inter-annual timescale, last-millennium Challa–Naivasha precipitation is positively (negatively) correlated with western (eastern) Indian Ocean SST, while the influence of the Pacific Ocean appears weak and unclear. Although most often not significant, the same pattern of correlations between East African rainfall and the Indian Ocean SST is still visible when using the last-millennium time series smoothed to highlight centennial variability, but only in fixed-forcing simulations. Furthermore, this means that, at the centennial timescale, the effect of (natural) climate forcing can mask the imprint of internal climate variability in large-scale teleconnections.« less

Comparison of simulated and reconstructed variations in East African hydroclimate over the last millennium

DOE PAGES

Klein, Francois; Goosse, Hugues; Graham, Nicholas E.; ...

2016-07-13

The multi-decadal to centennial hydroclimate changes in East Africa over the last millennium are studied by comparing the results of forced transient simulations by six general circulation models (GCMs) with published hydroclimate reconstructions from four lakes: Challa and Naivasha in equatorial East Africa, and Masoko and Malawi in southeastern inter-tropical Africa. All GCMs simulate fairly well the unimodal seasonal cycle of precipitation in the Masoko–Malawi region, while the bimodal seasonal cycle characterizing the Challa–Naivasha region is generally less well captured by most models. Model results and lake-based hydroclimate reconstructions display very different temporal patterns over the last millennium. Additionally, theremore » is no common signal among the model time series, at least until 1850. This suggests that simulated hydroclimate fluctuations are mostly driven by internal variability rather than by common external forcing. After 1850, half of the models simulate a relatively clear response to forcing, but this response is different between the models. Overall, the link between precipitation and tropical sea surface temperatures (SSTs) over the pre-industrial portion of the last millennium is stronger and more robust for the Challa–Naivasha region than for the Masoko–Malawi region. At the inter-annual timescale, last-millennium Challa–Naivasha precipitation is positively (negatively) correlated with western (eastern) Indian Ocean SST, while the influence of the Pacific Ocean appears weak and unclear. Although most often not significant, the same pattern of correlations between East African rainfall and the Indian Ocean SST is still visible when using the last-millennium time series smoothed to highlight centennial variability, but only in fixed-forcing simulations. Furthermore, this means that, at the centennial timescale, the effect of (natural) climate forcing can mask the imprint of internal climate variability in large-scale teleconnections.« less

A view of annual water quality cycle and inter-annual variations in agricultural headwater catchment (Kervidy-Naizin, France)

NASA Astrophysics Data System (ADS)

Aubert, A.; Gascuel-odoux, C.; Merot, P.; Grimaldi, C.; Gruau, G.; Ruiz, L.

2011-12-01

Climatic conditions impact biotransformation and transfer of solutes. Therefore, they modify solute emissions in streams. Studying these modifications requires long term and detailed monitoring of both internal processes and river loads, which are rarely combined. The Kervidy-Naizin catchment, implemented in 1993, is part of the French network of catchment for environmental research (SOERE RBV, focused on the Critical Zone). It is an intensive agricultural catchment located in a temperate climate in Western France (Brittany) (Molenat et al., 2008; Morel et al., 2009). It presents shallow aquifers due to impervious bedrock. Both hydrology and water chemistry are monitored with a daily time step since 2000-01, as well as possible explanatory data (land use, meteorology, etc.). Concentrations in major anions in this catchment are extremely high, which make people call it a "saturated" catchment. We identified annual patterns for chloride, sulphate, dissolved organic and inorganic carbon and nitrate concentration variations. First, we considered the complete set of concentration data as function of the time. From that, we foresaw 3 cyclic temporal patterns. Then, from representing the concentrations as function of meteorological parameters, intra-annual hysteretic variations and their inter-annual variations were clearly identified. Our driving question is to know if and how climatic conditions are responsible for variations of the patterns in and between years. In winter, i.e. rainy and cold period, rainfall is closely linked to discharge because of a direct recharge to the shallow groundwater. Reversely, in transition periods (spring and fall) and hot periods, both rainfall and temperature influences discharge in relation to their range of variations. Moreover, biological processes, driven by temperature and wetness, also act during these periods. On the whole, we can emphasize the specificity of water chemistry patterns for each element. Noticeable differences between hot and cold years and between wet and dry years can mainly be observed during spring and autumn period, i.e. when combining variations of rainfall and temperature. Further jointed statistical analyses between water chemistry and meteorology have to be carried on. References Molenat, J., Gascuel-Odoux, C., Ruiz, L., and Gruau, G. (2008). Role of water table dynamics on stream nitrate export and concentration. in agricultural headwater catchment (France). Journal of Hydrology 348, 363-378. Morel, B., Durand, P., Jaffrezic, A., Gruau, G., and Molenat, J. (2009). Sources of dissolved organic carbon during stormflow in a headwater agricultural catchment. Hydrological Processes 23, 2888-2901.

The influence of climate, topography and land-use on the hydrology of ephemeral upland catchments

NASA Astrophysics Data System (ADS)

Daly, E.; Webb, J.; Dresel, E.

2016-12-01

We report on an on-going project aimed at determining the effects of climate variability and land use change on water resources in ephemeral productive catchments. Meteorological data (including rainfall, solar radiation, air temperature, humidity and wind speed), streamflow and groundwater levels were collected continuously for over five years in seven ephemeral catchments in southeastern Australia. The catchments, dominated by either pasture for grazing (four) or Eucalyptus globulus (blue gum) plantations of different ages (three), were located in three different geological settings. Rainfall varied from higher than the long-term average of this area for the initial years of the study period to much drier than the long-term average for the last two years. Groundwater levels in the farm sites remained stable or slightly increased through the study period, while levels declined in all the plantation catchments, where evapotranspiration rates were greater than rainfall. The trees intercept groundwater recharge and in some areas of the catchments directly access groundwater. Streamflow occurred mainly during winter, with short-term flows in summer caused by sporadic large rainfall events. Despite the large annual rainfall variability, flow rates in each year were similar in most catchments, with the duration of flow being important in determining the annual flow. The frequency rather than the amount of rainfall events determines the generation of streamflow in the two catchments with steeper slopes. The effect of the tree plantations on streamflow varied from a substantial reduction in one catchment to no effect in another, where the tree rows are oriented predominantly downslope, allowing greater runoff. In the third plantation catchment, geology is the main driver of runoff due to capture into underlying karst conduits.

ENSO variability over the last 2000 years from a sub-decadal lacustrine lipid biomarker record from Isabel Island, Mexico

NASA Astrophysics Data System (ADS)

Sachse, D.; Romero, L.; Kienel, U.; Haug, G. H.

2016-12-01

ENSO is one of the major drivers of inter-annual climate variability and its effects extend far beyond the Tropical Pacific. However, our knowledge about the stability and linearity of ENSO teleconnections is limited due to the short temporal coverage of observational data, in particular of well dated paleo-ENSO records. Here we present a high-resolution record of rainfall variability on the Pacific coast of Mexico, which today is significantly correlated to ENSO variability (NINO 3.4 index), with dryer conditions during an El Niño phase and wetter conditions during a La Niña phase. The lake, situated in a volcanic crater on Isabel Island, is strongly influenced by rainfall intensity, i.e. freshwater and saline sea water input. A halophile bacterial community dominates during dry phases and an algal community dominates in a freshwater lens which develops during the wet season. Specific lipid biomarkers in the sediments indicate the dominant bacterial community (tetrahymanol and long-chain diols, respectively) in an annually laminated sediment core and record the timing and direction of ENSO mean state changes. We find the region was dry before 825 AD, indicating dominant El Niño. Between 825 and 950 AD, wetter conditions provide evidence for a dominating La Niña like pattern. During the early Medieval Climate Anomaly (MCA, 925-1100 AD) we reconstruct a dryer (El Niño like) environment, changing into a La Niña dominated pattern, prevailing until 1700 AD. The late Little Ice Age (LIA, 1700-1850AD) was initially dry and changed into a wetter climate at 1750 AD. Afterwards El Niño dominated in the region. The overall pattern of these changes agrees with other paleoclimate records from the Pacific region. However, our well dated (±20 years) high-resolution record identifies a number of short-lived episodes of deviations from this pattern, in particular during the MCA and the LIA. We also find strong similarities in the timing of these episodes with North Pacific and North Atlantic records, indicating that ENSO-Northern Hemisphere teleconnections existed throughout the last 2000 years. We find that changes in ENSO pattern during the MCA and the LIA predate changes in the Northern Hemisphere, indicating that ENSO changes affected atmospheric circulation patterns and so directly influenced Northern hemispheric climate.

Inter-annual variability of North Sea plaice spawning habitat

NASA Astrophysics Data System (ADS)

Loots, C.; Vaz, S.; Koubbi, P.; Planque, B.; Coppin, F.; Verin, Y.

2010-11-01

Potential spawning habitat is defined as the area where environmental conditions are suitable for spawning to occur. Spawning adult data from the first quarter (January-March) of the International Bottom Trawl Survey have been used to study the inter-annual variability of the potential spawning habitat of North Sea plaice from 1980 to 2007. Generalised additive models (GAM) were used to create a model that related five environmental variables (depth, bottom temperature and salinity, seabed stress and sediment type) to presence-absence and abundance of spawning adults. Then, the habitat model was applied each year from 1970 to 2007 to predict inter-annual variability of the potential spawning habitat. Predicted responses obtained by GAM for each year were mapped using kriging. A hierarchical classification associated with a correspondence analysis was performed to cluster spawning suitable areas and to determine how they evolved across years. The potential spawning habitat was consistent with historical spawning ground locations described in the literature from eggs surveys. It was also found that the potential spawning habitat varied across years. Suitable areas were located in the southern part of the North Sea and along the eastern coast of England and Scotland in the eighties; they expanded further north from the nineties. Annual survey distributions did not show such northward expansion and remained located in the southern North Sea. This suggests that this species' actual spatial distribution remains stable against changing environmental conditions, and that the potential spawning habitat is not fully occupied. Changes in environmental conditions appear to remain within plaice environmental ranges, meaning that other factors may control the spatial distribution of plaice spawning habitat.

The AMMA-CATCH Gourma observatory site in Mali: Relating climatic variations to changes in vegetation, surface hydrology, fluxes and natural resources

NASA Astrophysics Data System (ADS)

Mougin, E.; Hiernaux, P.; Kergoat, L.; Grippa, M.; de Rosnay, P.; Timouk, F.; Le Dantec, V.; Demarez, V.; Lavenu, F.; Arjounin, M.; Lebel, T.; Soumaguel, N.; Ceschia, E.; Mougenot, B.; Baup, F.; Frappart, F.; Frison, P. L.; Gardelle, J.; Gruhier, C.; Jarlan, L.; Mangiarotti, S.; Sanou, B.; Tracol, Y.; Guichard, F.; Trichon, V.; Diarra, L.; Soumaré, A.; Koité, M.; Dembélé, F.; Lloyd, C.; Hanan, N. P.; Damesin, C.; Delon, C.; Serça, D.; Galy-Lacaux, C.; Seghieri, J.; Becerra, S.; Dia, H.; Gangneron, F.; Mazzega, P.

2009-08-01

SummaryThe Gourma site in Mali is one of the three instrumented meso-scale sites deployed in West-Africa as part of the African Monsoon Multi-disciplinary Analysis (AMMA) project. Located both in the Sahelian zone sensu stricto, and in the Saharo-Sahelian transition zone, the Gourma meso-scale window is the northernmost site of the AMMA-CATCH observatory reached by the West African Monsoon. The experimental strategy includes deployment of a variety of instruments, from local to meso-scale, dedicated to monitoring and documentation of the major variables characterizing the climate forcing, and the spatio-temporal variability of surface processes and state variables such as vegetation mass, leaf area index (LAI), soil moisture and surface fluxes. This paper describes the Gourma site, its associated instrumental network and the research activities that have been carried out since 1984. In the AMMA project, emphasis is put on the relations between climate, vegetation and surface fluxes. However, the Gourma site is also important for development and validation of satellite products, mainly due to the existence of large and relatively homogeneous surfaces. The social dimension of the water resource uses and governance is also briefly analyzed, relying on field enquiry and interviews. The climate of the Gourma region is semi-arid, daytime air temperatures are always high and annual rainfall amounts exhibit strong inter-annual and seasonal variations. Measurements sites organized along a north-south transect reveal sharp gradients in surface albedo, net radiation, vegetation production, and distribution of plant functional types. However, at any point along the gradient, surface energy budget, soil moisture and vegetation growth contrast between two main types of soil surfaces and hydrologic systems. On the one hand, sandy soils with high water infiltration rates and limited run-off support almost continuous herbaceous vegetation with scattered woody plants. On the other hand, water infiltration is poor on shallow soils, and vegetation is sparse and discontinuous, with more concentrated run-off that ends in pools or low lands within structured endorheic watersheds. Land surface in the Gourma is characterized by rapid response to climate variability, strong intra-seasonal, seasonal and inter-annual variations in vegetation growth, soil moisture and energy balance. Despite the multi-decadal drought, which still persists, ponds and lakes have increased, the grass cover has largely recovered, and there are signs of increased tree cover at least in the low lands.

The FOODBANCS project: Introduction and sinking fluxes of organic carbon, chlorophyll- a and phytodetritus on the western Antarctic Peninsula continental shelf

NASA Astrophysics Data System (ADS)

Smith, Craig R.; Mincks, Sarah; DeMaster, David J.

2008-11-01

The impact of the highly seasonal Antarctic primary production cycle on shelf benthic ecosystems remains poorly evaluated. Here we describe a times-series research project on the West Antarctic Peninsula (WAP) shelf designed to evaluate the seafloor deposition, and subsequent ecological and biogeochemical impacts, of the summer phytoplankton bloom along a transect crossing the Antarctic shelf near Anvers Island. During this project, entitled Food for Benthos on the Antarctic Continental Shelf (FOODBANCS), we deployed replicate sediment traps 150-170 m above the seafloor (total water-column depth of 590 m) on the central shelf from December 1999 to March 2001, recovering trap samples every 3-4 months. In addition, we used a seafloor time-lapse camera system, as well as video surveys conducted at 3-4 months intervals, to monitor the presence and accumulation of phytodetritus at the sediment-water interface. The fluxes of particulate organic carbon and chlorophyll- a into sediment traps (binned over 3-4 month intervals) showed patterns consistent with seasonal variability, with average summer fluxes during the first year exceeding winter fluxes by a factor of ˜2-3. However, inter-annual variability in summer fluxes was even greater than seasonal variability, with 4-10-fold differences in the flux of organic carbon and chlorophyll- a between the summer seasons of 1999-2000 and 2000-2001. Phytodetrital accumulation at the shelf floor also exhibited intense inter-annual variability, with no visible phytodetritus from essentially December 1999 to November 2000, followed by pulsed accumulation of 1-2 cm of phytodetritus over a ˜30,000 km 2 shelf area by March 2001. Comparisons with other studies suggest that the levels of inter-annual variability we observed are typical of the Antarctic shelf over decadal time scales. We conclude that fluxes of particulate organic carbon, chlorophyll- a and phytodetritus to WAP-shelf sediments vary intensely on seasonal to inter-annual time scales, yielding dramatic temporal variability in the flux of food for detritivores to the Antarctic shelf floor.

Annual variability of PAH concentrations in the Potomac River watershed

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

Maher, I.L.; Foster, G.D.

1995-12-31

Dynamics of organic contaminant transport in a large river system is influenced by annual variability in organic contaminant concentrations. Surface runoff and groundwater input control the flow of river waters. They are also the two major inputs of contaminants to river waters. The annual variability of contaminant concentrations in rivers may or may not represent similar trends to the flow changes of river waters. The purpose of the research is to define the annual variability in concentrations of polycyclic aromatic hydrocarbons (PAH) in riverine environment. To accomplish this, from March 1992 to March 1995 samples of Potomac River water weremore » collected monthly or bimonthly downstream of the Chesapeake Bay fall line (Chain Bridge) during base flow and main storm flow hydrologic conditions. Concentrations of selected PAHs were measured in the dissolved phase and the particulate phase via GC/MS. The study of the annual variability of PAH concentrations will be performed through comparisons of PAH concentrations seasonally, annually, and through study of PAH concentration river discharge dependency and rainfall dependency. For selected PAHs monthly and annual loadings will be estimated based on their measured concentrations and average daily river discharge. The monthly loadings of selected PAHs will be compared by seasons and annually.« less

Twenty Years of High-Resolution Sea Surface Temperature Imagery around Australia: Inter-Annual and Annual Variability

PubMed Central

Foster, Scott D.; Griffin, David A.; Dunstan, Piers K.

2014-01-01

The physical climate defines a significant portion of the habitats in which biological communities and species reside. It is important to quantify these environmental conditions, and how they have changed, as this will inform future efforts to study many natural systems. In this article, we present the results of a statistical summary of the variability in sea surface temperature (SST) time-series data for the waters surrounding Australia, from 1993 to 2013. We partition variation in the SST series into annual trends, inter-annual trends, and a number of components of random variation. We utilise satellite data and validate the statistical summary from these data to summaries of data from long-term monitoring stations and from the global drifter program. The spatially dense results, available as maps from the Australian Oceanographic Data Network's data portal (http://www.cmar.csiro.au/geonetwork/srv/en/metadata.show?id=51805), show clear trends that associate with oceanographic features. Noteworthy oceanographic features include: average warming was greatest off southern West Australia and off eastern Tasmania, where the warming was around 0.6°C per decade for a twenty year study period, and insubstantial warming in areas dominated by the East Australian Current, but this area did exhibit high levels of inter-annual variability (long-term trend increases and decreases but does not increase on average). The results of the analyses can be directly incorporated into (biogeographic) models that explain variation in biological data where both biological and environmental data are on a fine scale. PMID:24988444

The impact of antecedent fire area on burned area in southern California coastal ecosystems

USGS Publications Warehouse

Price, Owen F.; Bradstock, Ross A.; Keeley, Jon E.; Syphard, Alexandra D.

2012-01-01

Frequent wildfire disasters in southern California highlight the need for risk reduction strategies for the region, of which fuel reduction via prescribed burning is one option. However, there is no consensus about the effectiveness of prescribed fire in reducing the area of wildfire. Here, we use 29 years of historical fire mapping to quantify the relationship between annual wildfire area and antecedent fire area in predominantly shrub and grassland fuels in seven southern California counties, controlling for annual variation in weather patterns. This method has been used elsewhere to measure leverage: the reduction in wildfire area resulting from one unit of prescribed fire treatment. We found little evidence for a leverage effect (leverage = zero). Specifically our results showed no evidence that wildfire area was negatively influenced by previous fires, and only weak relationships with weather variables rainfall and Santa Ana wind occurrences, which were variables included to control for inter-annual variation. We conclude that this is because only 2% of the vegetation burns each year and so wildfires rarely encounter burned patches and chaparral shrublands can carry a fire within 1 or 2 years after previous fire. Prescribed burning is unlikely to have much influence on fire regimes in this area, though targeted treatment at the urban interface may be effective at providing defensible space for protecting assets. These results fit an emerging global model of fire leverage which position California at the bottom end of a continuum, with tropical savannas at the top (leverage = 1: direct replacement of wildfire by prescribed fire) and Australian eucalypt forests in the middle (leverage ∼ 0.25).

The impact of antecedent fire area on burned area in southern California coastal ecosystems.

PubMed

Price, Owen F; Bradstock, Ross A; Keeley, Jon E; Syphard, Alexandra D

2012-12-30

Frequent wildfire disasters in southern California highlight the need for risk reduction strategies for the region, of which fuel reduction via prescribed burning is one option. However, there is no consensus about the effectiveness of prescribed fire in reducing the area of wildfire. Here, we use 29 years of historical fire mapping to quantify the relationship between annual wildfire area and antecedent fire area in predominantly shrub and grassland fuels in seven southern California counties, controlling for annual variation in weather patterns. This method has been used elsewhere to measure leverage: the reduction in wildfire area resulting from one unit of prescribed fire treatment. We found little evidence for a leverage effect (leverage = zero). Specifically our results showed no evidence that wildfire area was negatively influenced by previous fires, and only weak relationships with weather variables rainfall and Santa Ana wind occurrences, which were variables included to control for inter-annual variation. We conclude that this is because only 2% of the vegetation burns each year and so wildfires rarely encounter burned patches and chaparral shrublands can carry a fire within 1 or 2 years after previous fire. Prescribed burning is unlikely to have much influence on fire regimes in this area, though targeted treatment at the urban interface may be effective at providing defensible space for protecting assets. These results fit an emerging global model of fire leverage which position California at the bottom end of a continuum, with tropical savannas at the top (leverage = 1: direct replacement of wildfire by prescribed fire) and Australian eucalypt forests in the middle (leverage ~ 0.25). Copyright © 2012 Elsevier Ltd. All rights reserved.

Nonstationarity of daily rainfall annual maxima in Puglia (Southern Italy)

NASA Astrophysics Data System (ADS)

Totaro, Vincenzo; Gioia, Andrea; Iacobellis, Vito

2017-04-01

Extreme flood events occurring in the last decades, due to climatic conditions in rapid evolution and/or changes in land cover, has lead the scientific community to develop and improve probabilistic techniques in order to take into account these effects, as also requested by the EU Floods Directive 2007/60. In the recent literature are becoming more popular studies that investigate the nonstationarity of the variables usually treated in hydrology through the analysis of their trend behavior. In this context it is also useful to assess the impact that the climate and /or land cover modifications have on the performances of the probabilistic stationary models used to predict hydrological variables such as rainfall and flood peaks. Among several proposed approaches, we use the redefined concept of return period and risk by considering the variability over time of the position parameter of the GEV distribution, with the subsequent discussion about the implications of analytical and technical characters. The analysis was carried out on the time series of annual maximum of daily precipitation available for a broad number of rainfall gauged stations in Puglia (Southern Italy). The investigation, conducted at the regional scale, leads to the identification of areas with different significativity of the statistical tests usually performed in order to assess nonstationarity. The evaluated change of return period leads to considerations useful to redesign methods for regional analysis of flood frequency.

[Temporal change in annual air temperature and heat island effect in a coastal city and an inland city at mid-latitude in China during 1956-1998].

PubMed

Chao, Lu-men; Sun, Jian-xin

2009-12-01

Temporal changes in air temperature and urban heat island (UHI) effects during 1956-1998 were compared between a coastal city, Ji' nan, and an inland city, Xi' an, which were similar in latitude, size and development. During 1956-1978, except that the annual mean minimum temperature in Ji' nan increased by 0.37 degrees C x 10 a(-1), the temperature variables in the two cities did not display any apparent trend. During 1979-1998, all temperature variables of the two cities showed an increasing trend. Comparing with that in Ji' nan, the increasing rate of annual mean maximum temperature and annual mean temperature in Xi' an was greater, but that of annual mean minimum temperature was smaller. In the two cities, heat island effect occurred during 1956-1978 but without any apparent trend, whereas during 1979-1998, this effect increased with time, especially in Xi' an where the annual mean minimum temperature and annual mean temperature increased by 0.22 degrees C x 10 a(-1) and 0.32 degrees C x 10 a(-1), respectively. Both the level and the inter-annual variation of the heat island effect were much greater in Ji' nan than in Xi' an, but the increasing rate of this effect was greater in Xi' an than in Ji' nan. Obvious differences were observed in the increasing rate of annual mean maximum air temperature, annual mean air temperature, and annual mean minimum temperature as well as the heat island effect in Ji' nan, whereas negligible differences were found in Xi' an. Among the three temperature variables, annual mean minimum temperature displayed the most obvious increasing trend and was most affected by heat island effect, while annual mean maximum temperature was most variable inter-annually. Geographical location not only affected the magnitude of urban warming, but also affected the mode of urban warming and the strength of heat island effect.

Improve projections of changes in southern African summer rainfall through comprehensive multi-timescale empirical statistical downscaling

NASA Astrophysics Data System (ADS)

Dieppois, B.; Pohl, B.; Eden, J.; Crétat, J.; Rouault, M.; Keenlyside, N.; New, M. G.

2017-12-01

The water management community has hitherto neglected or underestimated many of the uncertainties in climate impact scenarios, in particular, uncertainties associated with decadal climate variability. Uncertainty in the state-of-the-art global climate models (GCMs) is time-scale-dependant, e.g. stronger at decadal than at interannual timescales, in response to the different parameterizations and to internal climate variability. In addition, non-stationarity in statistical downscaling is widely recognized as a key problem, in which time-scale dependency of predictors plays an important role. As with global climate modelling, therefore, the selection of downscaling methods must proceed with caution to avoid unintended consequences of over-correcting the noise in GCMs (e.g. interpreting internal climate variability as a model bias). GCM outputs from the Coupled Model Intercomparison Project 5 (CMIP5) have therefore first been selected based on their ability to reproduce southern African summer rainfall variability and their teleconnections with Pacific sea-surface temperature across the dominant timescales. In observations, southern African summer rainfall has recently been shown to exhibit significant periodicities at the interannual timescale (2-8 years), quasi-decadal (8-13 years) and inter-decadal (15-28 years) timescales, which can be interpret as the signature of ENSO, the IPO, and the PDO over the region. Most of CMIP5 GCMs underestimate southern African summer rainfall variability and their teleconnections with Pacific SSTs at these three timescales. In addition, according to a more in-depth analysis of historical and pi-control runs, this bias is might result from internal climate variability in some of the CMIP5 GCMs, suggesting potential for bias-corrected prediction based empirical statistical downscaling. A multi-timescale regression based downscaling procedure, which determines the predictors across the different timescales, has thus been used to simulate southern African summer rainfall. This multi-timescale procedure shows much better skills in simulating decadal timescales of variability compared to commonly used statistical downscaling approaches.

Final Technical Report for "High-resolution temporal variations in groundwater chemistry: Tracing the links between climate, hydrology, and element mobility in the vadose zone"

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

Jay L. Banner

2002-04-23

In spite of a developing emphasis on geochemical methods in studies of modern hydrologic systems, there have been few attempts to examine temporal fluctuations in groundwater chemistry and element mobility in the near-surface environment. Relatively little is known regarding how groundwaters evolve over 10 to 10,000 year scales, yet this knowledge provides a critical framework for understanding the links between climate and hydrology, the evolution of soils, and element migration in the vadose environment. Recent analytical advances allow U-series measurements to be applied to developing high-resolution chronologies of Pleistocene and Holocene carbonates. The potential of these new tools is examinedmore » through an analysis of two well-defined, active karst systems in (1) Barbados and (2) Texas. (1) The research effort on Barbados has developed methods of estimating recharge and inferring the spatial and seasonal distribution of recharge to the Pleistocene limestone aquifer on Barbados. A new method has been developed to estimate recharge based on oxygen isotope variations in rainwater and groundwater. Inter-annual recharge variations indicate that recharge is dependent on the distribution of rainfall throughout the year rather than total annual rainfall. Consequently, a year when rainfall occurs primarily during the peak wet season months (August through November) may have more recharge than a year when rainfall is more evenly distributed through the year. These results lay important groundwork for analysis of rainfall/recharge variations over different time scales based on isotopic records presently being constructed using Barbados speleothems from the same aquifer. (2) The chronology of speleothems (cave calcite deposits) from three caves across 130 kilometers in central Texas provides a 71,000-year record of temporal changes in hydrology and climate. Fifty-three ages were determined by mass spectrometric 238U - 230Th and 235U - 231Pa analyses. The accuracy of the ages and the closed-system behavior of the speleothems are indicated by inter-laboratory comparisons, concordancy of 230Th and 231Pa ages, and the result that all ages are in correct stratigraphic order. Over the last 71,000 years, the stalagmites have similar growth histories with alternating periods of relatively rapid and slow growth. The growth rates vary over more than two orders-of-magnitude, with three periods of rapid growth from 71-60 ka, 39-33 ka, and 24-12 ka. These growth rate shifts correspond in part with global glacial-interglacial climatic shifts. The potential effects of temporal variations in precession of Earth?s orbit on regional effective moisture may provide a mechanism for increased effective moisture coincident with the observed intervals of increased speleothem growth. The stalagmites all exhibit a large drop in growth rate between 15 and 12 ka, and very slow growth up to the present, consistent with drier climate during the Holocene. These results illustrate that speleothem growth rates can reflect the regional response of a hydrologic system to regional and global climate variability.« less

Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia.

PubMed

Aragão, Luiz Eduardo O C; Malhi, Yadvinder; Barbier, Nicolas; Lima, Andre; Shimabukuro, Yosio; Anderson, Liana; Saatchi, Sassan

2008-05-27

Understanding the interplay between climate and land-use dynamics is a fundamental concern for assessing the vulnerability of Amazonia to climate change. In this study, we analyse satellite-derived monthly and annual time series of rainfall, fires and deforestation to explicitly quantify the seasonal patterns and relationships between these three variables, with a particular focus on the Amazonian drought of 2005. Our results demonstrate a marked seasonality with one peak per year for all variables analysed, except deforestation. For the annual cycle, we found correlations above 90% with a time lag between variables. Deforestation and fires reach the highest values three and six months, respectively, after the peak of the rainy season. The cumulative number of hot pixels was linearly related to the size of the area deforested annually from 1998 to 2004 (r2=0.84, p=0.004). During the 2005 drought, the number of hot pixels increased 43% in relation to the expected value for a similar deforested area (approx. 19000km2). We demonstrated that anthropogenic forcing, such as land-use change, is decisive in determining the seasonality and annual patterns of fire occurrence. Moreover, droughts can significantly increase the number of fires in the region even with decreased deforestation rates. We may expect that the ongoing deforestation, currently based on slash and burn procedures, and the use of fires for land management in Amazonia will intensify the impact of droughts associated with natural climate variability or human-induced climate change and, therefore, a large area of forest edge will be under increased risk of fires.

Measurement of inter- and intra-annual variability of landscape fire activity at a continental scale: the Australian case

NASA Astrophysics Data System (ADS)

Williamson, Grant J.; Prior, Lynda D.; Jolly, W. Matt; Cochrane, Mark A.; Murphy, Brett P.; Bowman, David M. J. S.

2016-03-01

Climate dynamics at diurnal, seasonal and inter-annual scales shape global fire activity, although difficulties of assembling reliable fire and meteorological data with sufficient spatio-temporal resolution have frustrated quantification of this variability. Using Australia as a case study, we combine data from 4760 meteorological stations with 12 years of satellite-derived active fire detections to determine day and night time fire activity, fire season start and end dates, and inter-annual variability, across 61 objectively defined climate regions in three climate zones (monsoon tropics, arid and temperate). We show that geographic patterns of landscape burning (onset and duration) are related to fire weather, resulting in a latitudinal gradient from the monsoon tropics in winter, through the arid zone in all seasons except winter, and then to the temperate zone in summer and autumn. Peak fire activity precedes maximum lightning activity by several months in all regions, signalling the importance of human ignitions in shaping fire seasons. We determined median daily McArthur forest fire danger index (FFDI50) for days and nights when fires were detected: FFDI50 varied substantially between climate zones, reflecting effects of fire management in the temperate zone, fuel limitation in the arid zone and abundance of flammable grasses in the monsoon tropical zone. We found correlations between the proportion of days when FFDI exceeds FFDI50 and the Southern Oscillation index across the arid zone during spring and summer, and Indian Ocean dipole mode index across south-eastern Australia during summer. Our study demonstrates that Australia has a long fire weather season with high inter-annual variability relative to all other continents, making it difficult to detect long term trends. It also provides a way of establishing robust baselines to track changes to fire seasons, and supports a previous conceptual model highlighting multi-temporal scale effects of climate in shaping continental-scale pyrogeography.

Climate and soil attributes determine plant species turnover in global drylands

PubMed Central

Maestre, Fernando T.; Gotelli, Nicholas J.; Quero, José L.; Delgado-Baquerizo, Manuel; Bowker, Matthew A.; Eldridge, David J.; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I.; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R.; Hernández, Rosa M.; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L.; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A.; Raveh, Eran; Romão, Roberto L.; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2015-01-01

Aim Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. Location 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Methods Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake’s beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R2)), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Results Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R2)) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Main conclusions Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation. PMID:25914437

A methodology for probabilistic assessment of solar thermal power plants yield

NASA Astrophysics Data System (ADS)

Fernández-Peruchena, Carlos M.; Lara-Faneho, Vicente; Ramírez, Lourdes; Zarzalejo, Luis F.; Silva, Manuel; Bermejo, Diego; Gastón, Martín; Moreno, Sara; Pulgar, Jesús; Pavon, Manuel; Macías, Sergio; Valenzuela, Rita X.

2017-06-01

A detailed knowledge of the solar resource is a critical point to perform an economic feasibility analysis of Concentrating Solar Power (CSP) plants. This knowledge must include its magnitude (how much solar energy is available at an area of interest over a long time period), and its variability over time. In particular, DNI inter-annual variations may be large, increasing the return of investment risk in CSP plant projects. This risk is typically evaluated by means of the simulation of the energy delivered by the CSP plant during years with low solar irradiation, which are typically characterized by annual solar radiation datasets with high probability of exceedance of their annual DNI values. In this context, this paper proposes the use meteorological years representative of a given probability of exceedance of annual DNI in order to realistically assess the inter-annual variability of energy yields. The performance of this approach is evaluated in the location of Burns station (University of Oregon Solar Radiation Monitoring Laboratory), where a 34-year (from 1980 to 2013) measured data set of solar irradiance and temperature is available.

Rainfall characterisation by application of standardised precipitation index (SPI) in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Yusof, Fadhilah; Hui-Mean, Foo; Suhaila, Jamaludin; Yusop, Zulkifli; Ching-Yee, Kong

2014-02-01

The interpretations of trend behaviour for dry and wet events are analysed in order to verify the dryness and wetness episodes. The fitting distribution of rainfall is computed to classify the dry and wet events by applying the standardised precipitation index (SPI). The rainfall amount for each station is categorised into seven categories, namely extremely wet, severely wet, moderately wet, near normal, moderately dry, severely dry and extremely dry. The computation of the SPI is based on the monsoon periods, which include the northeast monsoon, southwest monsoon and inter-monsoon. The trends of the dry and wet periods were then detected using the Mann-Kendall trend test and the results indicate that the major parts of Peninsular Malaysia are characterised by increasing droughts rather than wet events. The annual trends of drought and wet events of the randomly selected stations from each region also yield similar results. Hence, the northwest and southwest regions are predicted to have a higher probability of drought occurrence during a dry event and not much rain during the wet event. The east and west regions, on the other hand, are going through a significant upward trend that implies lower rainfall during the drought episodes and heavy rainfall during the wet events.

Maritime continent coastlines controlling Earth's climate

NASA Astrophysics Data System (ADS)

Yamanaka, Manabu D.; Ogino, Shin-Ya; Wu, Pei-Ming; Jun-Ichi, Hamada; Mori, Shuichi; Matsumoto, Jun; Syamsudin, Fadli

2018-12-01

During the Monsoon Asian Hydro-Atmosphere Scientific Research and Prediction Initiative (MAHASRI; 2006-16), we carried out two projects over the Indonesian maritime continent (IMC), constructing the Hydrometeorological Array for Intraseasonal Variation-Monsoon Automonitoring (HARIMAU; 2005-10) radar network and setting up a prototype institute for climate studies, the Maritime Continent Center of Excellence (MCCOE; 2009-14). Here, we review the climatological features of the world's largest "regional" rainfall over the IMC studied in these projects. The fundamental mode of atmospheric variability over the IMC is the diurnal cycle generated along coastlines by land-sea temperature contrast: afternoon land becomes hotter than sea by clear-sky insolation before noon, with the opposite contrast before sunrise caused by evening rainfall-induced "sprinkler"-like land cooling (different from the extratropical infrared cooling on clear nights). Thus, unlike the extratropics, the diurnal cycle over the IMC is more important in the rainy season. The intraseasonal, seasonal to annual, and interannual climate variabilities appear as amplitude modulations of the diurnal cycle. For example, in Jawa and Bali the rainy season is the southern hemispheric summer, because land heating in the clear morning and water vapor transport by afternoon sea breeze is strongest in the season of maximum insolation. During El Niño, cooler sea water surrounding the IMC makes morning maritime convection and rainfall weaker than normal. Because the diurnal cycle is almost the only mechanism generating convective clouds systematically near the equator with little cyclone activity, the local annual rainfall amount in the tropics is a steeply decreasing function of coastal distance ( e-folding scale 100-300 km), and regional annual rainfall is an increasing function of "coastline density" (coastal length/land area) measured at a horizontal resolution of 100 km. The coastline density effect explains why rainfall and latent heating over the IMC are twice the global mean for an area that makes up only 4% of the Earth's surface. The diurnal cycles appearing almost synchronously over the whole IMC generate teleconnections between the IMC convection and the global climate. Thus, high-resolution (<< 100 km; << 1 day) observations and models over the IMC are essential to improve both local disaster prevention and global climate prediction.

Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology

NASA Technical Reports Server (NTRS)

Forkel, Matthias; Carvalhais, Nuno; Verbesselt, Jan; Mahecha, Miguel D.; Neigh, Christopher S.R.; Reichstein, Markus

2013-01-01

Changing trends in ecosystem productivity can be quantified using satellite observations of Normalized Difference Vegetation Index (NDVI). However, the estimation of trends from NDVI time series differs substantially depending on analyzed satellite dataset, the corresponding spatiotemporal resolution, and the applied statistical method. Here we compare the performance of a wide range of trend estimation methods and demonstrate that performance decreases with increasing inter-annual variability in the NDVI time series. Trend slope estimates based on annual aggregated time series or based on a seasonal-trend model show better performances than methods that remove the seasonal cycle of the time series. A breakpoint detection analysis reveals that an overestimation of breakpoints in NDVI trends can result in wrong or even opposite trend estimates. Based on our results, we give practical recommendations for the application of trend methods on long-term NDVI time series. Particularly, we apply and compare different methods on NDVI time series in Alaska, where both greening and browning trends have been previously observed. Here, the multi-method uncertainty of NDVI trends is quantified through the application of the different trend estimation methods. Our results indicate that greening NDVI trends in Alaska are more spatially and temporally prevalent than browning trends. We also show that detected breakpoints in NDVI trends tend to coincide with large fires. Overall, our analyses demonstrate that seasonal trend methods need to be improved against inter-annual variability to quantify changing trends in ecosystem productivity with higher accuracy.

Tropical Mosquito Assemblages Demonstrate ‘Textbook’ Annual Cycles

PubMed Central

Franklin, Donald C.; Whelan, Peter I.

2009-01-01

Background Annual biological rhythms are often depicted as predictably cyclic, but quantitative evaluations are few and rarely both cyclic and constant among years. In the monsoon tropics, the intense seasonality of rainfall frequently drives fluctuations in the populations of short-lived aquatic organisms. However, it is unclear how predictably assemblage composition will fluctuate because the intensity, onset and cessation of the wet season varies greatly among years. Methodology/Principal Findings Adult mosquitoes were sampled using EVS suction traps baited with carbon dioxide around swamplands adjacent to the city of Darwin in northern Australia. Eleven sites were sampled weekly for five years, and one site weekly for 24 years, the sample of c. 1.4 million mosquitoes yielding 63 species. Mosquito abundance, species richness and diversity fluctuated seasonally, species richness being highly predictable. Ordination of assemblage composition demonstrated striking annual cycles that varied little from year to year. The mosquito assemblage was temporally structured by a succession of species peaks in abundance. Conclusion/Significance Ordination provided strong visual representation of annual rhythms in assemblage composition and the means to evaluate variability among years. Because most mosquitoes breed in shallow freshwater which fluctuates with rainfall, we did not anticipate such repeatability; we conclude that mosquito assemblage composition appears adapted to predictable elements of the rainfall. PMID:20011531

Regional contribution to variability and trends of global gross primary productivity

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

Chen, Min; Rafique, Rashid; Asrar, Ghassem R.

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117±13 Pg C yr-1 (mean ± 1 standard deviation), whichmore » was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.« less

Regional contribution to variability and trends of global gross primary productivity

NASA Astrophysics Data System (ADS)

Chen, Min; Rafique, Rashid; Asrar, Ghassem R.; Bond-Lamberty, Ben; Ciais, Philippe; Zhao, Fang; Reyer, Christopher P. O.; Ostberg, Sebastian; Chang, Jinfeng; Ito, Akihiko; Yang, Jia; Zeng, Ning; Kalnay, Eugenia; West, Tristram; Leng, Guoyong; Francois, Louis; Munhoven, Guy; Henrot, Alexandra; Tian, Hanqin; Pan, Shufen; Nishina, Kazuya; Viovy, Nicolas; Morfopoulos, Catherine; Betts, Richard; Schaphoff, Sibyll; Steinkamp, Jörg; Hickler, Thomas

2017-10-01

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117 ± 13 Pg C yr-1 (mean ± 1 standard deviation), which was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.

Inter-Annual Variability in Stream Water Temperature, Microclimate and Heat Exchanges: a Comparison of Forest and Moorland Environments

NASA Astrophysics Data System (ADS)

Garner, G.; Hannah, D. M.; Malcolm, I.; Sadler, J. P.

2012-12-01

Riparian forest is recognised as important for moderating stream temperature variability and has the potential to mitigate thermal extremes in a changing climate. Previous research on the heat exchanges controlling water column temperature has often been short-term or seasonally-constrained, with the few multi-year studies limited to a maximum of two years. This study advances previous work by providing a longer-term perspective which allows assessment of inter-annual variability in stream temperature, microclimate and heat exchange dynamics between a semi-natural woodland and a moorland (no trees) reach of the Girnock Burn, a tributary of the Scottish Dee. Automatic weather stations collected 15-minute data over seven consecutive years, which to our knowledge is a unique data set in providing the longest term perspective to date on stream temperature, microclimate and heat exchange processes. Results for spring-summer indicate that the presence of a riparian canopy has a consistent effect between years in reducing the magnitude and variability of mean daily water column temperature and daily net energy totals. Differences in the magnitude and variability in net energy fluxes between the study reaches were driven primarily by fluctuations in net radiation and latent heat fluxes in response to between- and within-year variability in growth of the riparian forest canopy at the forest and prevailing weather conditions at both the forest and moorland. This research provides new insights on the inter-annual variability of stream energy exchanges for moorland and forested reaches under a wide range of climatological and hydrological conditions. The findings therefore provide a more robust process basis for modelling the impact of changes in forest practice and climate change on river thermal dynamics.

El Niño Southern Oscillation as an early warning tool for malaria outbreaks in India.

PubMed

Dhiman, Ramesh C; Sarkar, Soma

2017-03-20

Risks of malaria epidemics in relation to El Niño and Southern Oscillation (ENSO) events have been mapped and studied at global level. In India, where malaria is a major public health problem, no such effort has been undertaken that inter-relates El Niño, Indian Summer Monsoon Rainfall (ISMR) and malaria. The present study has been undertaken to find out the relationship between ENSO events, ISMR and intra-annual variability in malaria cases in India, which in turn could help mitigate the malaria outbreaks. Correlation coefficients among 'rainfall index' (ISMR), '+ winter ONI' (NDJF) and 'malaria case index' were calculated using annual state-level data for the last 22 years. The 'malaria case index' representing 'relative change from mean' was correlated to the 4 month (November-February) average positive Oceanic Niño Index (ONI). The resultant correlations between '+ winter ONI' and 'malaria case index' were further analysed on geographical information system platform to generate spatial correlation map. The correlation between '+ winter ONI' and 'rainfall index' shows that there is great disparity in effect of ENSO over ISMR distribution across the country. Correlation between 'rainfall index' and 'malaria case index' shows that malaria transmission in all geographical regions of India are not equally affected by the ISMR deficit or excess. Correlation between '+ winter ONI' and 'malaria case index' was found ranging from -0.5 to + 0.7 (p < 0.05). A positive correlation indicates that increase in El Niño intensity (+ winter ONI) will lead to rise in total malaria cases in the concurrent year in the states of Orissa, Chhattisgarh, Jharkhand, Bihar, Goa, eastern parts of Madhya Pradesh, part of Andhra Pradesh, Uttarakhand and Meghalaya. Whereas, negative correlations were found in the states of Rajasthan, Haryana, Gujarat, part of Tamil Nadu, Manipur, Mizoram and Sikkim indicating the likelihood of outbreaks in La Nina condition. The generated map, representing spatial correlation between ' + winter ONI' and 'malaria case index', indicates positive correlations in eastern part, while negative correlations in western part of India. This study provides plausible guidelines to national programme for planning intervention measures in view of ENSO events. For better resolution, district level study with inclusion of IOD and 'epochal variation of monsoon rainfall' factors at micro-level is desired for better forecast of malaria outbreaks in the regions with 'no correlation'.

A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

NASA Astrophysics Data System (ADS)

Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

2002-12-01

The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

Mapping the world's tropical cyclone rainfall contribution over land using TRMM satellite data: precipitation budget and extreme rainfall

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2012-12-01

A study was performed to characterize over-land precipitation associated with tropical cyclones (TCs) for basins around the world gathered in the International Best Track Archive for Climate Stewardship (IBTrACS). From 1998 to 2010, rainfall data from TRMM 3B42, showed that TCs accounted for 8-, 11-, 7-, 10-, and 12-% of the annual over-land precipitation for North America, East Asia, Northern Indian Ocean, Australia, and South-West Indian Ocean respectively, and that TC-contribution decreased importantly within the first 150-km from the coast. At the local scale, TCs contributed on average to more than 40% and up to 77% of the annual precipitation budget over very different climatic areas with arid or tropical characteristics. The East Asia domain presented the higher and most constant TC-rain (170±23%-mm/yr) normalized over the area impacted, while the Southwest Indian domain presented the highest variability (130±48%-mm/yr), and the North American domain displayed the lowest average TC-rain (77±27%-mm/yr) despite a higher TC-activity. The maximum monthly TC-contribution (11-15%) was found later in the TC-season and was a conjunction between the peak of TC-activity, TC-rainfall, and the domain annual antagonism between dry and wet regimes if any. Furthermore, TC-days that accounted globally for 2±0.5% of all precipitation events for all basins, represented between 11-30% of rainfall extremes (>101.6mm/day). Locally, TC-rainfall was linked with the majority (>70%) or the quasi-totality (≈100%) of extreme rainfall. Finally, because of their importance in terms of rainfall amount, the contribution of tropical cyclones is provided for a selection of fifty urban areas experiencing cyclonic activity. Cases studies conducted at the regional scale will focus on the link between TC-activity, water resources, and hydrohazards such as floods and droughts.

Combined effects of short-term rainfall patterns and soil texture on nitrogen cycling -- A Modeling Analysis

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

Gu, C.; Riley, W.J.

2009-11-01

Precipitation variability and magnitude are expected to change in many parts of the world over the 21st century. We examined the potential effects of intra-annual rainfall patterns on soil nitrogen (N) transport and transformation in the unsaturated soil zone using a deterministic dynamic modeling approach. The model (TOUGHREACT-N), which has been tested and applied in several experimental and observational systems, mechanistically accounts for microbial activity, soil-moisture dynamics that respond to precipitation variability, and gaseous and aqueous tracer transport in the soil. Here, we further tested and calibrated the model against data from a precipitation variability experiment in a tropical systemmore » in Costa Rica. The model was then used to simulate responses of soil moisture, microbial dynamics, nitrogen (N) aqueous and gaseous species, N leaching, and N trace-gas emissions to changes in rainfall patterns; the effect of soil texture was also examined. The temporal variability of nitrate leaching and NO, N{sub 2}, and N{sub 2}O effluxes were significantly influenced by rainfall dynamics. Soil texture combined with rainfall dynamics altered soil moisture dynamics, and consequently regulated soil N responses to precipitation changes. The clay loam soil more effectively buffered water stress during relatively long intervals between precipitation events, particularly after a large rainfall event. Subsequent soil N aqueous and gaseous losses showed either increases or decreases in response to increasing precipitation variability due to complex soil moisture dynamics. For a high rainfall scenario, high precipitation variability resulted in as high as 2.4-, 2.4-, 1.2-, and 13-fold increases in NH{sub 3}, NO, N{sub 2}O and NO{sub 3}{sup -} fluxes, respectively, in clay loam soil. In sandy loam soil, however, NO and N{sub 2}O fluxes decreased by 15% and 28%, respectively, in response to high precipitation variability. Our results demonstrate that soil N cycling responses to increasing precipitation variability depends on precipitation amount and soil texture, and that accurate prediction of future N cycling and gas effluxes requires models with relatively sophisticated representation of the relevant processes.« less

Multisite rainfall downscaling and disaggregation in a tropical urban area

NASA Astrophysics Data System (ADS)

Lu, Y.; Qin, X. S.

2014-02-01

A systematic downscaling-disaggregation study was conducted over Singapore Island, with an aim to generate high spatial and temporal resolution rainfall data under future climate-change conditions. The study consisted of two major components. The first part was to perform an inter-comparison of various alternatives of downscaling and disaggregation methods based on observed data. This included (i) single-site generalized linear model (GLM) plus K-nearest neighbor (KNN) (S-G-K) vs. multisite GLM (M-G) for spatial downscaling, (ii) HYETOS vs. KNN for single-site disaggregation, and (iii) KNN vs. MuDRain (Multivariate Rainfall Disaggregation tool) for multisite disaggregation. The results revealed that, for multisite downscaling, M-G performs better than S-G-K in covering the observed data with a lower RMSE value; for single-site disaggregation, KNN could better keep the basic statistics (i.e. standard deviation, lag-1 autocorrelation and probability of wet hour) than HYETOS; for multisite disaggregation, MuDRain outperformed KNN in fitting interstation correlations. In the second part of the study, an integrated downscaling-disaggregation framework based on M-G, KNN, and MuDRain was used to generate hourly rainfall at multiple sites. The results indicated that the downscaled and disaggregated rainfall data based on multiple ensembles from HadCM3 for the period from 1980 to 2010 could well cover the observed mean rainfall amount and extreme data, and also reasonably keep the spatial correlations both at daily and hourly timescales. The framework was also used to project future rainfall conditions under HadCM3 SRES A2 and B2 scenarios. It was indicated that the annual rainfall amount could reduce up to 5% at the end of this century, but the rainfall of wet season and extreme hourly rainfall could notably increase.

Decadal features of heavy rainfall events in eastern China

NASA Astrophysics Data System (ADS)

Chen, Huopo; Sun, Jianqi; Fan, Ke

2012-06-01

Based on daily precipitation data, the spatial-temporal features of heavy rainfall events (HREs) during 1960-2009 are investigated. The results indicate that the HREs experienced strong decadal variability in the past 50 years, and the decadal features varied across regions. More HRE days are observed in the 1960s, 1980s, and 1990s over Northeast China (NEC); in the 1960s, 1970s, and 1990s over North China (NC); in the early 1960s, 1980s, and 2000s over the Huaihe River basin (HR); in the 1970s-1990s over the mid-lower reaches of the Yangtze River valley (YR); and in the 1970s and 1990s over South China (SC). These decadal changes of HRE days in eastern China are closely associated with the decadal variations of water content and stratification stability of the local atmosphere. The intensity of HREs in each sub-region is also characterized by strong decadal variability. The HRE intensity and frequency co-vary on the long-term trend, and show consistent variability over NEC, NC, and YR, but inconsistent variability over SC and HR. Further analysis of the relationships between the annual rainfall and HRE frequency as well as intensity indicates that the HRE frequency is the major contributor to the total rainfall variability in eastern China, while the HRE intensity shows only relative weak contribution.

Monitoring snow cover variability (2000-2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method

NASA Astrophysics Data System (ADS)

Li, Xinghua; Fu, Wenxuan; Shen, Huanfeng; Huang, Chunlin; Zhang, Liangpei

2017-08-01

Monitoring the variability of snow cover is necessary and meaningful because snow cover is closely connected with climate and ecological change. In this work, 500 m resolution MODIS daily snow cover products from 2000 to 2014 were adopted to analyze the status in Hengduan Mountains. In order to solve the spatial discontinuity caused by clouds in the products, we propose an adaptive spatio-temporal weighted method (ASTWM), which is based on the initial result of a Terra and Aqua combination. This novel method simultaneously considers the temporal and spatial correlations of the snow cover. The simulated experiments indicate that ASTWM removes clouds completely, with a robust overall accuracy (OA) of above 93% under different cloud fractions. The spatio-temporal variability of snow cover in the Hengduan Mountains was investigated with two indices: snow cover days (SCD) and snow fraction. The results reveal that the annual SCD gradually increases and the coefficient of variation (CV) decreases with elevation. The pixel-wise trends of SCD first rise and then drop in most areas. Moreover, intense intra-annual variability of the snow fraction occurs from October to March, during which time there is abundant snow cover. The inter-annual variability, which mainly occurs in high elevation areas, shows an increasing trend before 2004/2005 and a decreasing trend after 2004/2005. In addition, the snow fraction responds to the two climate factors of air temperature and precipitation. For the intra-annual variability, when the air temperature and precipitation decrease, the snow cover increases. Besides, precipitation plays a more important role in the inter-annual variability of snow cover than temperature.

A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas

NASA Astrophysics Data System (ADS)

Whitley, Rhys; Beringer, Jason; Hutley, Lindsay B.; Abramowitz, Gab; De Kauwe, Martin G.; Duursma, Remko; Evans, Bradley; Haverd, Vanessa; Li, Longhui; Ryu, Youngryel; Smith, Benjamin; Wang, Ying-Ping; Williams, Mathew; Yu, Qiang

2016-06-01

The savanna ecosystem is one of the most dominant and complex terrestrial biomes, deriving from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs) has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root-water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of six TBMs and assessed their performance at simulating latent energy (LE) and gross primary productivity (GPP) for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI). This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root-water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribed tree-rooting depths must be deep enough, enabling the extraction of deep soil-water stores to maintain photosynthesis and transpiration during the dry season. Second, models must treat grasses as a co-dominant interface for water and carbon exchange rather than a secondary one to trees. Third, models need a dynamic representation of LAI that encompasses the dynamic phenology of savanna vegetation and its response to rainfall interannual variability. We believe that this study is the first to assess how well TBMs simulate savanna ecosystems and that these results will be used to improve the representation of savannas ecosystems in future global climate model studies.

Secular Change and Inter-annual Variability of the Gulf Stream Position, 1993-2013, 70°-55°W

NASA Astrophysics Data System (ADS)

Bisagni, J. J.; Gangopadhyay, A.

2016-12-01

The Gulf Stream (GS) is the northeastward-flowing surface limb of the Atlantic Ocean meridional overturning circulation (AMOC) "conveyer belt" that flows towards Europe and the Nordic Seas. Changes in the GS position after its separation from the coast at Cape Hatteras, i.e., from 75°W to 50°W, may be key to understanding the AMOC, sea level variability and ecosystem behavior along the east coast of North America. In this study we compare secular change and inter-annual variability (IAV) of annual mean Gulf Stream North Wall (GSNW) position with equator-ward Labrador Current (LC) transport along the southwestern Grand Banks near 52° W using 21 years (1993-2013) of satellite altimeter data. Results at 70°, 65°, 60° and 55° W show a southward secular trend for the GSNW, decreasing to the west. IAV of de-trended GSNW position residuals also decreases to the west. The long-term secular trend of annual mean upper layer LC transport increases near 52° W. Furthermore, IAV of LC transport residuals near 52° W is significantly correlated with GSNW position residuals at 55° W at a lag of +1-year. Spectral analysis reveals inter-annual peaks at 5-7 years and 2-3 years for the North Atlantic Oscillation (NAO), GSNW (65°-55°W) and LC transport for 1993-2013. A volume calculation using the LC rms residual of +1.04 Sv near 52° W results in an estimated GSNW residual of 79 km, or 63% of the observed 125.6 km (1.13°) rms value at 55° W. A similar volume calculation using the positive long-term, upper-layer LC transport trend accounts for 68% of the observed southward shift of the GSNW over the 1993-2013 period. Our work provides observational evidence of direct interaction between the upper layers of the sub-polar and sub-tropical gyres within the North Atlantic over secular and inter-annual time scales as suggested by previous workers.

Hydrology of a zero-order Southern Piedmont watershed through 45 years of changing agricultural land use. Part 1. Monthly and seasonal rainfall-runoff relationships

NASA Astrophysics Data System (ADS)

Endale, Dinku M.; Fisher, Dwight S.; Steiner, Jean L.

2006-01-01

Few studies have reported runoff from small agricultural watersheds over sufficiently long period so that the effect of different cover types on runoff can be examined. We analyzed 45-yrs of monthly and annual rainfall-runoff characteristics of a small (7.8 ha) zero-order typical Southern Piedmont watershed in southeastern United States. Agricultural land use varied as follows: 1. Row cropping (5-yrs); 2. Kudzu ( Pueraria lobata; 5-yrs); 3. Grazed kudzu and rescuegrass ( Bromus catharticus; 7-yrs); and 4. Grazed bermudagrass and winter annuals ( Cynodon dactylon; 28-yrs). Land use and rainfall variability influenced runoff characteristics. Row cropping produced the largest runoff amount, percentage of the rainfall partitioned into runoff, and peak flow rates. Kudzu reduced spring runoff and almost eliminated summer runoff, as did a mixture of kudzu and rescuegrass (KR) compared to row cropping. Peak flow rates were also reduced during the kudzu and KR. Peak flow rates increased under bermudagrass but were lower than during row cropping. A simple process-based 'tanh' model modified to take the previous month's rainfall into account produced monthly rainfall and runoff correlations with coefficient of determination ( R2) of 0.74. The model was tested on independent data collected during drought. Mean monthly runoff was 1.65 times the observed runoff. Sustained hydrologic monitoring is essential to understanding long-term rainfall-runoff relationships in agricultural watersheds.

Inter-annual precipitation variabiity inferred from late Holocene speleothem records from Fiji: implications for SPCZ localisation and ENSO behaviour

NASA Astrophysics Data System (ADS)

Mattey, D.; Stephens, M.; Hoffmann, D.; Brett, M.

2015-12-01

The modern tropical Fiji climate is characterised by seasonal rainfall controlled by the position of the South Pacific Convergence Zone (SPCZ). Interannual rainfall is strongly modulated on decadal timescales by ENSO with higher rainfall associated with La Nina events. Voli Voli cave near Sigatoga (Viti Levu) is a stream passage that has been monitored since 2009. A U-Th dated laminated speleothem spans a 1500 year interval across the transition from the Medieval Warm Period into the Little Ice Age marked by a fabric change from finely laminated calcite with thin clay layers, to white well-laminated calcite. The older record is characterised by rising δ13C values followed by a rapid decrease in δ13C around 1200 AD. Evidence from cave monitoring shows that cave air CO2 levels are strongly seasonal as a result of greater ventilation by winter trade winds and high resolution δ13C record shows regularly spaced peaks correlated with paired laminae and cycles in P and S which provide annual markers driven by rainfall and seasonal ventilation. δ18O values remain relatively unchanged throughout the record but micromilling at sub-annual resolution reveals systematic cycles in δ18O that span groups of paired laminae with an inferred periodicity of 3-7 years i.e. a similar frequency to modern ENSO. The presence of these sub-decadal cycles in δ18O may be a result of a combination of factors. The amplitude of 2-3‰ would be equivalent to an amount-effect related change in annual precipitation of around 50% but an additional smoothing process, perhaps a result of aquifer storage, is required to attenuate interannual variance in precipitation. The Voli Voli record provides evidence of an underlying climatic change to more frequent La Niña conditions from 1200 AD and may be associated with increased conflict, shifts in settlements and changes in subsistence strategies on the island. Coeval speleothem isotope records from tropical Pacific Islands provide a provide a powerful means of locating the mean position and intensity of the SPCZ and changes in regional coupling of ocean-atmospheric circulation patterns.

Analysis of Rainfall and PM2.5 Data Using Clustered Trajectory Analysis for National Park Sites in the Western U.S.

NASA Astrophysics Data System (ADS)

Solorzano, N. N.; Hafner, W.; Jaffe, D.

2005-12-01

We calculated daily kinematic back-trajectories using the NOAA-HYSPLIT model to analyze 7 years of PM2.5 data from National Park sites in the Western U.S. (Glacier N.P., Mount Rainier N.P., Sequoia N.P., Rocky Mountain N.P. and Denali N.P.) The back-trajectories were clustered using a k-means clustering algorithm to segregate the trajectories into 6 main transport patterns. We calculated trajectory clusters for 1, 5 and 10 days to represent short, medium and long-range flow patterns. Some trajectory types and clusters show marked seasonality. Generally faster flow patterns are more prevalent in winter and slower/stagnant patterns are more prevalent in summer. In addition, we found significant inter-annual variability that may be important for explaining variations in rainfall and/or pollutant concentrations. The 5 and 10-day analyses revealed that, for the 4 non-Alaskan sites, trajectories from Asia tend to be less frequent in the summer, compared to the rest of the year. The clusters of different duration show very different predictive power for rainfall and PM2.5. We found that the 1-day clusters are a better predictor for precipitation and PM2.5 concentrations, as compared to the 5 and 10-day clusters. At each of the sites, there is at least one cluster with an average PM2.5 concentration that is different than the average for the site, indicating distinctive transport patterns. The same is true for 5 and 10-day clusters. Interestingly, only one site, Mount Rainier N.P., shows seasonal differences in PM2.5 concentrations between the clusters that differ from the average.

[Ecological suitability regionalization for Gastrodia elata in Zhaotong based on Maxent and ArcGIS].

PubMed

Shi, Zi-Wei; Ma, Cong-Ji; Kang, Chuan-Zhi; Wang, Li; Zhang, Zhi-Hui; Chen, Jun-Fei; Zhang, Xiao-Bo; Liu, Da-Hui

2016-09-01

In this paper, the potential distribution information and ecological suitability regionalization for Gastrodia elata in Zhaotong were studied based on the climate, terrain, soil and vegetation factors analysis by Maxent and ArcGIS. The results showed that the highly potential distribution (suitability index>0.6) mainly located in Zhaotong, Yunnan province（Zhenxiong,Yiliang and Daguan county, with an area of 2 872 km²）, and Bijie, Guizhou province （Hezhang,Bijie,Weining county, 1 251 km²）. The AUC of ROC curve was above 0.99, indicating that the predictive results with the Maxent model were highly precise. The main ecological factors determining the potential distribution were the altitude, average rainfall in November, average rainfall in October, vegetation types, average rainfall in March, average rainfall in April,soil types,isothermal characteristic and average rainfall in June. The environmental variables in the highly potential areas were determined as altitude around 1 450-2 200 m,annual average temperature around 18.0-20.4 ℃,annual average precipitation around 900 mm,yellow soil or yellow brown soil,and acid sandy loam or slightly acidic sandy loam.The results will provide valuable references for plantation regionalization and the siting for imitation wild planting of G. elata in Zhaotong. Copyright© by the Chinese Pharmaceutical Association.

Tradeoffs between vegetation management goals and livestock production under Adapative Grazing Management

USDA-ARS?s Scientific Manuscript database

Rangeland ecosystems are characterized by substantial temporal variability in weather overlaid on spatial variability associated with topography and soils (Fuhlendorf et al. 2012). Semiarid rangelands in particular are characterized by more extreme intra- and inter-annual variation in precipitation ...

Land-Climate Feedbacks in Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Asharaf, Shakeel; Ahrens, Bodo

2016-04-01

In an attempt to identify how land surface states such as soil moisture influence the monsoonal precipitation climate over India, a series of numerical simulations including soil moisture sensitivity experiments was performed. The simulations were conducted with a nonhydrostatic regional climate model (RCM), the Consortium for Small-Scale Modeling (COSMO) in climate mode (CCLM) model, which was driven by the European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Results showed that pre-monsoonal soil moisture has a significant impact on monsoonal precipitation formation and large-scale atmospheric circulations. The analysis revealed that even a small change in the processes that influence precipitation via changes in local evapotranspiration was able to trigger significant variations in regional soil moisture-precipitation feedback. It was observed that these processes varied spatially from humid to arid regions in India, which further motivated an examination of soil-moisture memory variation over these regions and determination of the ISM seasonal forecasting potential. A quantitative analysis indicated that the simulated soil-moisture memory lengths increased with soil depth and were longer in the western region than those in the eastern region of India. Additionally, the subsequent precipitation variance explained by soil moisture increased from east to west. The ISM rainfall was further analyzed in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenario (SRES: B1) and the new Representative Concentration Pathways (RCPs: RCP4.5). To that end, the CCLM and its driving global-coupled atmospheric-oceanic model (GCM), ECHAM/MPIOM were used in order to understand the driving processes of the projected inter-annual precipitation variability and associated trends. Results inferred that the projected rainfall changes were the result of two largely compensating processes: increase of remotely induced precipitation and decrease of precipitation efficiency. However, the complementing precipitation components and their simulation uncertainties rendered climate projections of the Indian summer monsoon rainfall as an ongoing, highly ambiguous challenge for both the GCM and the RCM.

Southern Hemisphere Carbon Monoxide Inferannual Variability Observed by Terra/Measurement of Pollution in the Troposphere (MOPITT)

NASA Technical Reports Server (NTRS)

Edwards, D. P.; Petron, G.; Novelli, P. C.; Emmons, L. K.; Gille, J. C.; Drummond, J. R.

2010-01-01

Biomass burning is an annual occurrence in the tropical southern hemisphere (SH) and represents a major source of regional pollution. Vegetation fires emit carbon monoxide (CO), which due to its medium lifetime is an excellent tracer of tropospheric transport. CO is also one of the few tropospheric trace gases currently observed from satellite and this provides long-term global measurements. In this paper, we use the 5 year CO data record from the Measurement Of Pollution In The Troposphere (MOPITT) instrument to examine the inter-annual variability of the SH CO loading and show how this relates to climate conditions which determine the intensity of fire sources. The MOPITT observations show an annual austral springtime peak in the SH zonal CO loading each year with dry-season biomass burning emissions in S. America, southern Africa, the Maritime Continent, and northwestern Australia. Although fires in southern Africa and S. America typically produce the greatest amount of CO, the most significant inter-annual variation is due to varying fire activity and emissions from the Maritime Continent and northern Australia. We find that this variation in turn correlates well with the El Nino Southern Oscillation precipitation index. Between 2000 and 2005, emissions were greatest in late 2002 and an inverse modeling of the MOPITT data using the MOZART chemical transport model estimates the southeast Asia regional fire source for the year August 2002 to September 2003 to be 52 Tg CO. Comparison of the MOPITT retrievals and NOAA surface network measurements indicate that the latter do not fully capture the inter-annual variability or the seasonal range of the CO zonal average concentration due to biases associated with atmospheric and geographic sampling.

Winter streamflow analysis in frozen, alpine catchments to quantify groundwater contribution and properties

NASA Astrophysics Data System (ADS)

Stoelzle, Michael; Weiler, Markus

2016-04-01

Alpine catchments are often considered as quickly responding systems where streamflow contributions from subsurface storages (groundwater) are mostly negligible due to the steep topography, low permeable bedrock and the absence of well-developed soils. Many studies in high altitude catchments have hence focused on water stored in snowpack and glaciers or on rainfall-runoff processes as the dominant streamflow contributions. Interestingly less effort has been devoted to winter streamflow analysis when melt- or rainfall-driven contributions are switched off due to the frozen state of the catchment. Considering projected changes in the alpine cryosphere (e.g. snow, glacier, permafrost) quantification of groundwater storage and contribution to streamflow is crucial to assess the social and ecological implications for downstream areas (e.g. water temperature, drought propagation). In this study we hypothesize that groundwater is the main streamflow contribution during winter and thus being responsible for the perennial regime of many alpine catchments. The hypothesis is investigated with well-known methods based on recession and breakpoint analysis of the streamflow regimes and temperature data to determine frozen periods. Analyzing nine catchments in Switzerland with mean elevation between 1000 and 2400 m asl, we found that above a mean elevation of 1800 m asl winter recessions are sufficient long and persistent enough to quantify groundwater contribution to streamflow and to characterize the properties of subsurface storage. The results show that groundwater in alpine catchment is the dominant streamflow contribution for nearly half a year and accountable for several hundred millimeter of annual streamflow. In sub-alpine catchments, driven by a mix of snowmelt and rainfall, a clear quantification of groundwater contributions is rather challenging due to discontinuous frozen periods in winter. We found that the inter-annual variability of different streamflow contributions is helpful to assess the water sustainability of alpine catchments functioning as water towers for downstream water basins. We outline how well-known hydrograph and recession analyses in alpine catchments can help to explore the role of catchment storage and to advance our understanding of (ground-)water management in alpine environments.

Phenotypic plasticity and local adaptation in leaf ecophysiological traits of 13 contrasting cork oak populations under different water availabilities.

PubMed

Ramírez-Valiente, Jose Alberto; Sánchez-Gómez, David; Aranda, Ismael; Valladares, Fernando

2010-05-01

Plants distributed across a wide range of environmental conditions are submitted to differential selective pressures. Long-term selection can lead to the development of adaptations to the local environment, generating ecotypic differentiation. Additionally, plant species can cope with this environmental variability by phenotypic plasticity. In this study, we examine the importance of both processes in coping with environmental heterogeneity in the Mediterranean sclerophyllous cork oak Quercus suber. For this purpose, we measured growth and key functional traits at the leaf level in 9-year-old plants across 2 years of contrasting precipitation (2005 and 2006) in a common garden. Plants were grown from acorns originated from 13 populations spanning a wide range of climates along the distribution range of the species. The traits measured were: leaf size (LS), specific leaf area (SLA), carbon isotope discrimination (Delta(13)C) and leaf nitrogen content per unit mass (N(mass)). Inter-population differences in LS, SLA and Delta(13)C were found. These differences were associated with rainfall and temperature at the sites of origin, suggesting local adaptation in response to diverging climates. Additionally, SLA and LS exhibited positive responses to the increase in annual rainfall. Year effect explained 28% of the total phenotypic variance in LS and 2.7% in SLA. There was a significant genotype x environment interaction for shoot growth and a phenotypic correlation between the difference in shoot growth among years and the annual mean temperature at origin. This suggests that populations originating from warm sites can benefit more from wet conditions than populations from cool sites. Finally, we investigated the relationships between functional traits and aboveground growth by several regression models. Our results showed that plants with lower SLA presented larger aboveground growth in a dry year and plants with larger leaf sizes displayed larger growth rates in both years. Overall, the study supports the adaptive value of SLA and LS for cork oak under a Mediterranean climate and their potentially important role for dealing with varying temperature and rainfall regimes through both local adaptation and phenotypic plasticity.

Coherent variability between seasonal temperatures and rainfalls in the Iberian Peninsula, 1951-2016

NASA Astrophysics Data System (ADS)

Rodrigo, F. S.

2018-02-01

In this work trends of seasonal mean of daily minimum (TN), maximum (TX), mean (TM) temperatures, daily range of temperature (DTR), and total seasonal rainfall (R) in 35 Iberian stations since mid-twentieth century are studied. The interest is focused on the relationships between temperature variables and rainfall, taking into account the correlation coefficients between R and the temperature variables. The negative link between rainfall and temperatures is detected in the four seasons of the year, except in western stations in winter for TN and TM, and in autumn for TN (for this variable a certain annual cycle is detected, with predominance of positive correlation in winter, negative in spring and summer, and the autumn as transition season). The role of cloud cover is confirmed in those stations with total cloud cover data. Using an average peninsular series, the relationship between nighttime temperature and rainfall related to long wave radiation is confirmed for the four seasons of the year, although in spring and summer has minor importance than in the cold half year. The relationships between R, TN, and TX are in general terms stable after a moving correlation analysis, although the negative correlation between TX and R seems be weakened in spring and autumn and reinforced in summer. The role of convective precipitation in autumn is discussed. The analysis of combined extreme indices in four representative stations shows an increase of warm and dry days, and a decrease of cold and wet days.

Mapping monthly rainfall erosivity in Europe.

PubMed

Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

2017-02-01

Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha -1 h -1 ) compared to winter (87MJmmha -1 h -1 ). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R 2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

[Spatio-temporal analysis of the biophysical and ecological conditions of Triatoma dimidiata (Hemiptera: Reduviidae: Triatominae) in the northeast region of Colombia].

PubMed

Badel-Mogollón, Jaime; Rodríguez-Figueroa, Laura; Parra-Henao, Gabriel

2017-03-29

Due to the lack of information regarding biophysical and spatio-temporal conditions (hydrometheorologic and vegetal coverage density) in areas with Triatoma dimidiata in the Colombian departments of Santander and Boyacá, there is a need to elucidate the association patterns of these variables to determine the distribution and control of this species. To make a spatio-temporal analysis of biophysical variables related to the distribution of T. dimidiate observed in the northeast region of Colombia. We used the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) data bases registering vector presence and hydrometheorologic data. We studied the variables of environmental temperature, relative humidity, rainfall and vegetal coverage density at regional and local levels, and we conducted spatial geostatistic, descriptive statistical and Fourier temporal series analyses. Temperatures two meters above the ground and on covered surface ranged from 14,5°C to 18,8°C in the areas with the higher density of T. dimidiata. The environmental temperature fluctuated between 30 and 32°C. Vegetal coverage density and rainfall showed patterns of annual and biannual peaks. Relative humidity values fluctuated from 66,8 to 85,1%. Surface temperature and soil coverage were the variables that better explained the life cycle of T. dimidiata in the area. High relative humidity promoted the seek of shelters and an increase of the geographic distribution in the annual and biannual peaks of regional rainfall. The ecologic and anthropic conditions suggest that T. dimidiata is a highly resilient species.

[Application of regression tree in analyzing the effects of climate factors on NDVI in loess hilly area of Shaanxi Province].

PubMed

Liu, Yang; Lü, Yi-he; Zheng, Hai-feng; Chen, Li-ding

2010-05-01

Based on the 10-day SPOT VEGETATION NDVI data and the daily meteorological data from 1998 to 2007 in Yan' an City, the main meteorological variables affecting the annual and interannual variations of NDVI were determined by using regression tree. It was found that the effects of test meteorological variables on the variability of NDVI differed with seasons and time lags. Temperature and precipitation were the most important meteorological variables affecting the annual variation of NDVI, and the average highest temperature was the most important meteorological variable affecting the inter-annual variation of NDVI. Regression tree was very powerful in determining the key meteorological variables affecting NDVI variation, but could not build quantitative relations between NDVI and meteorological variables, which limited its further and wider application.

Post-Fire Recovery of Eco-Hydrologic Behavior Given Historic and Projected Climate Variability in California Mediterranean Type Environments

NASA Astrophysics Data System (ADS)

Seaby, L. P.; Tague, C. L.; Hope, A. S.

2006-12-01

The Mediterranean type environments (MTEs) of California are characterized by a distinct wet and dry season and high variability in inter-annual climate. Water limitation in MTEs makes eco-hydrological processes highly sensitive to both climate variability and frequent fire disturbance. This research modeled post-fire eco- hydrologic behavior under historical and moderate and extreme scenarios of future climate in a semi-arid chaparral dominated southern California MTE. We used a physically-based, spatially-distributed, eco- hydrological model (RHESSys - Regional Hydro-Ecologic Simulation System), to capture linkages between water and vegetation response to the combined effects of fire and historic and future climate variability. We found post-fire eco-hydrologic behavior to be strongly influenced by the episodic nature of MTE climate, which intensifies under projected climate change. Higher rates of post-fire net primary productivity were found under moderate climate change, while more extreme climate change produced water stressed conditions which were less favorable for vegetation productivity. Precipitation variability in the historic record follows the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), and these inter-annual climate characteristics intensify under climate change. Inter-annual variation in streamflow follows these precipitation patterns. Post-fire streamflow and carbon cycling trajectories are strongly dependent on climate characteristics during the first 5 years following fire, and historic intra-climate variability during this period tends to overwhelm longer term trends and variation that might be attributable to climate change. Results have implications for water resource availability, vegetation type conversion from shrubs to grassland, and changes in ecosystem structure and function.

Asynchrony in the inter-annual recruitment of lake whitefish Coregonus clupeaformis in the Great Lakes region

USGS Publications Warehouse

Zischke, Mitchell T.; Bunnell, David B.; Troy, Cary D.; Berglund, Eric K.; Caroffino, David C.; Ebener, Mark P.; He, Ji X.; Sitar, Shawn P.; Hook, Tomas O.

2017-01-01

Spatially separated fish populations may display synchrony in annual recruitment if the factors that drive recruitment success, particularly abiotic factors such as temperature, are synchronised across broad spatial scales. We examined inter-annual variation in recruitment among lake whitefish (Coregonus clupeaformis) populations in lakes Huron, Michigan and Superior using fishery-dependent and -independent data from 1971 to 2014. Relative year-class strength (RYCS) was calculated from catch-curve residuals for each year class across multiple sampling years. Pairwise comparison of RYCS among datasets revealed no significant associations either within or between lakes, suggesting that recruitment of lake whitefish is spatially asynchronous. There was no consistent correlation between pairwise agreement and the distance between datasets, and models to estimate the spatial scale of recruitment synchrony did not fit well to these data. This suggests that inter-annual recruitment variation of lake whitefish is asynchronous across broad spatial scales in the Great Lakes. While our method primarily evaluated year-to-year recruitment variation, it is plausible that recruitment of lake whitefish varies at coarser temporal scales (e.g. decadal). Nonetheless, our findings differ from research on some other Coregonus species and suggest that local biotic or density-dependent factors may contribute strongly to lake whitefish recruitment rather than inter-annual variability in broad-scale abiotic factors.

How much of the interannual variability of East Asian summer rainfall is forced by SST?

NASA Astrophysics Data System (ADS)

He, Chao; Wu, Bo; Li, Chunhui; Lin, Ailan; Gu, Dejun; Zheng, Bin; Zhou, Tianjun

2016-07-01

It is widely accepted that the interannual variability of East Asian summer rainfall is forced by sea surface temperature (SST), and SST anomalies are widely used as predictors of East Asian summer rainfall. But it is still not very clear what percentage of the interannual rainfall variability is contributed by SST anomalies. In this study, Atmospheric general circulation model simulations forced by observed interannual varying SST are compared with those forced by the fixed annual cycle of SST climatology, and their ratios of interannual variance (IAV) are analyzed. The output of 12 models from the 5th Phase of Coupled Model Intercomparison Project (CMIP5) are adopted, and idealized experiments are done by Community Atmosphere Model version 4 (CAM4). Both the multi-model median of CMIP5 models and CAM4 experiments show that only about 18 % of the IAV of rainfall over East Asian land (EAL) is explained by SST, which is significantly lower than the tropical western Pacific, but comparable to the mid-latitude western Pacific. There is no significant difference between the southern part and the northern part of EAL in the percentages of SST contribution. The remote SST anomalies regulates rainfall over EAL probably by modulating the horizontal water vapor transport rather than the vertical motion, since the horizontal water vapor transport into EAL is strongly modulated by SST but the vertical motion over EAL is not. Previous studies argued about the relative importance of tropical Indian Ocean and tropical Pacific Ocean to East Asian summer rainfall anomalies. Our idealized experiments performed by CAM4 suggest that the contributions from these two ocean basins are comparable to each other, both of which account for approximately 6 % of the total IAV of rainfall over EAL.

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.

Studying Basin Water Balance Variations at Inter- and Intra-annual Time Scales Based On the Budyko Hypothesis and GRACE Gravimetry Satellite Observations

NASA Astrophysics Data System (ADS)

Shen, H.

2017-12-01

Increasing intensity in global warming and anthropogenic activities has triggered significant changes over regional climates and landscapes, which, in turn, drive the basin water cycle and hydrological balance into a complex and unstable state. Budyko hypothesis is a powerful tool to characterize basin water balance and hydrological variations at long-term average scale. However, due to the absence of basin water storage change, applications of Budyko theory to the inter-annual and intra-annual time scales has been prohibited. The launch of GRACE gavimetry satellites provides a great opportunity to quantify terrestrial water storage change, which can be further introduced into the Budyko hypothesis to reveal the inter- and intra-annual response of basin water components under impacts of climate variability and/or human activities. This research targeted Hai River Basin (in China) and Murray-Darling Basin (in Australia), which have been identified with a continuous groundwater depletion trend as well as impacts by extreme climates in the past decade. This can help us to explore how annual or seasonal precipitation were redistributed to evapotranspiration and runoff via changing basin water storage. Moreover, the impacts of vegetation on annual basin water balance will be re-examined. Our results are expected to provide deep insights about the water cycle and hydrological behaviors for the targeted basins, as well as a proof for a consideration of basin water storage change into the Budyko model at inter- or intra-annual time steps.

Study on the association of green house gas (CO2) with monsoon rainfall using AIRS and TRMM satellite observations

NASA Astrophysics Data System (ADS)

Singh, R. B.; Janmaijaya, M.; Dhaka, S. K.; Kumar, V.

Monsoon water cycle is the lifeline to over 60 per cent of the world's population. Throughout history, the monsoon-related calamities of droughts and floods have determined the life pattern of people. The association of Green House Gases (GHGs) particularly Carbon dioxide (CO2) with monsoon has been greatly debated amongst the scientific community in the past. The effect of CO2 on the monsoon rainfall over the Indian-Indonesian region (8-30°N, 65°-100°E) is being investigated using satellite data. The correlation coefficient (Rxy) between CO2 and monsoon is analysed. The Rxy is not significantly positive over a greater part of the study region, except a few regions. The inter-annual anomalies of CO2 is identified for playing a secondary role to influencing monsoon while other phenomenon like ENSO might be exerting a much greater influence.

Seasonal Freshwater and Salinity Budgets in the Tropical Atlantic Ocean

NASA Astrophysics Data System (ADS)

Yoo, Jung Moon

Seasonal freshwater and salt budgets in the tropical Atlantic are examined by incorporating precipitation, estimated from 11 years of outgoing longwave radiation (OLR) data. A spatially dependent formula is developed to estimate rainfall from the OLR data and the height of the base of the trade -wind inversion. This formula has been constructed by comparing rainfall records from twelve islands with the OLR data. Zonal asymmetries due to the differing cloud types in the eastern and western Atlantic and the presence of Saharan sand in the east are included. Significant inconsistencies between results of the present study the seasonal rainfall estimates of Dorman and Bourke (1981) are found. Annual and interannual variations of the moisture and freshwater budgets are examined in the same region. The seasonal moisture budget (E-P) is calculated from the above rainfall and evaporation estimated from surface data. Consistent with previous estimates, we find annual mean deficit of freshwater. The interannual variability of freshwater flux during the period 1974 to 1979 is examined. Seasonal or interannua1 variations of rainfall account for two-thirds of the variations of the freshwater flux. We examine the seasonal freshwater and salt budgets, and obtain their meridional transports by southward integration of their divergence fields. The annual freshwater transport in the tropical Atlantic is northward, ranging from 0 Sv near the equator to 0.3 Sv at 12^circ N and 20^circS. The seasonal meridional transport amounts of freshwater from surface to 500 m depth in the tropical Atlantic Ocean range from 1.35 Sv to -0.45 Sv. The strong northward freshwater transports prevail for the period summer to fall. This seasonal cycle is caused by the shifts of the ITCZ as well as the changes in the local freshwater storage. Annual and seasonal salt budgets are calculated from objectively analyzed historical (1900-1986) salinity observations. The annual salt flux in the tropical Atlantic is zero, showing that the salt flux by horizontal advection balances the flux by horizontal diffusion. The salt flux due to the diffusion is northward, and has a maximum of 5 times 10^6kg/s at 15^circN. Seasonal transport amounts of salt range from 30 times 10^6 kg/s to -35 times 10^6kg/s. The direction of the seasonal salt transports in the tropical Atlantic is northward except for the period summer to fall. We find an interannual variability of salinity along the coast of South America in the western Atlantic.

Rethinking "normal": The role of stochasticity in the phenology of a synchronously breeding seabird.

PubMed

Youngflesh, Casey; Jenouvrier, Stephanie; Hinke, Jefferson T; DuBois, Lauren; St Leger, Judy; Trivelpiece, Wayne Z; Trivelpiece, Susan G; Lynch, Heather J

2018-05-01

Phenological changes have been observed in a variety of systems over the past century. There is concern that, as a consequence, ecological interactions are becoming increasingly mismatched in time, with negative consequences for ecological function. Significant spatial heterogeneity (inter-site) and temporal variability (inter-annual) can make it difficult to separate intrinsic, extrinsic and stochastic drivers of phenological variability. The goal of this study was to understand the timing and variability in breeding phenology of Adélie penguins under fixed environmental conditions and to use those data to identify a "null model" appropriate for disentangling the sources of variation in wild populations. Data on clutch initiation were collected from both wild and captive populations of Adélie penguins. Clutch initiation in the captive population was modelled as a function of year, individual and age to better understand phenological patterns observed in the wild population. Captive populations displayed as much inter-annual variability in breeding phenology as wild populations, suggesting that variability in breeding phenology is the norm and thus may be an unreliable indicator of environmental forcing. The distribution of clutch initiation dates was found to be moderately asymmetric (right skewed) both in the wild and in captivity, consistent with the pattern expected under social facilitation. The role of stochasticity in phenological processes has heretofore been largely ignored. However, these results suggest that inter-annual variability in breeding phenology can arise independent of any environmental or demographic drivers and that synchronous breeding can enhance inherent stochasticity. This complicates efforts to relate phenological variation to environmental variability in the wild. Accordingly, we must be careful to consider random forcing in phenological processes, lest we fit models to data dominated by random noise. This is particularly true for colonial species where breeding synchrony may outweigh each individual's effort to time breeding with optimal environmental conditions. Our study highlights the importance of identifying appropriate null models for studying phenology. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Accounting for Rainfall Spatial Variability in Prediction of Flash Floods

NASA Astrophysics Data System (ADS)

Saharia, M.; Kirstetter, P. E.; Gourley, J. J.; Hong, Y.; Vergara, H. J.

2016-12-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 20,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. Next the model is used to predict flash flooding characteristics all over the continental U.S., specifically over regions poorly covered by hydrological observations. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Accounting for rainfall spatial variability in the prediction of flash floods

NASA Astrophysics Data System (ADS)

Saharia, Manabendra; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Hong, Yang; Vergara, Humberto; Flamig, Zachary L.

2017-04-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 15,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. The database has been subjected to rigorous quality control by accounting for radar beam height and percentage snow in basins. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Variability of East Asian summer monsoon precipitation during the Holocene and possible forcing mechanisms

NASA Astrophysics Data System (ADS)

Lu, Fuzhi; Ma, Chunmei; Zhu, Cheng; Lu, Huayu; Zhang, Xiaojian; Huang, Kangyou; Guo, Tianhong; Li, Kaifeng; Li, Lan; Li, Bing; Zhang, Wenqing

2018-03-01

Projecting how the East Asian summer monsoon (EASM) rainfall will change with global warming is essential for human sustainability. Reconstructing Holocene climate can provide critical insight into its forcing and future variability. However, quantitative reconstructions of Holocene summer precipitation are lacking for tropical and subtropical China, which is the core region of the EASM influence. Here we present high-resolution annual and summer rainfall reconstructions covering the whole Holocene based on the pollen record at Xinjie site from the lower Yangtze region. Summer rainfall was less seasonal and 30% higher than modern values at 10-6 cal kyr BP and gradually declined thereafter, which broadly followed the Northern Hemisphere summer insolation. Over the last two millennia, however, the summer rainfall has deviated from the downward trend of summer insolation. We argue that greenhouse gas forcing might have offset summer insolation forcing and contributed to the late Holocene rainfall anomaly, which is supported by the TraCE-21 ka transient simulation. Besides, tropical sea-surface temperatures could modulate summer rainfall by affecting evaporation of seawater. The rainfall pattern concurs with stalagmite and other proxy records from southern China but differs from mid-Holocene rainfall maximum recorded in arid/semiarid northern China. Summer rainfall in northern China was strongly suppressed by high-northern-latitude ice volume forcing during the early Holocene in spite of high summer insolation. In addition, the El Niño/Southern Oscillation might be responsible for droughts of northern China and floods of southern China during the late Holocene. Furthermore, quantitative rainfall reconstructions indicate that the Paleoclimate Modeling Intercomparison Project (PMIP) simulations underestimate the magnitude of Holocene precipitation changes. Our results highlight the spatial and temporal variability of the Holocene EASM precipitation and potential forcing mechanisms, which are very helpful for calibration of paleoclimate models and prediction of future precipitation changes in East Asia in the scenario of global warming.

Prediction of early summer rainfall over South China by a physical-empirical model

NASA Astrophysics Data System (ADS)

Yim, So-Young; Wang, Bin; Xing, Wen

2014-10-01

In early summer (May-June, MJ) the strongest rainfall belt of the northern hemisphere occurs over the East Asian (EA) subtropical front. During this period the South China (SC) rainfall reaches its annual peak and represents the maximum rainfall variability over EA. Hence we establish an SC rainfall index, which is the MJ mean precipitation averaged over 72 stations over SC (south of 28°N and east of 110°E) and represents superbly the leading empirical orthogonal function mode of MJ precipitation variability over EA. In order to predict SC rainfall, we established a physical-empirical model. Analysis of 34-year observations (1979-2012) reveals three physically consequential predictors. A plentiful SC rainfall is preceded in the previous winter by (a) a dipole sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (b) a tripolar SST tendency in North Atlantic Ocean, and (c) a warming tendency in northern Asia. These precursors foreshadow enhanced Philippine Sea subtropical High and Okhotsk High in early summer, which are controlling factors for enhanced subtropical frontal rainfall. The physical empirical model built on these predictors achieves a cross-validated forecast correlation skill of 0.75 for 1979-2012. Surprisingly, this skill is substantially higher than four-dynamical models' ensemble prediction for 1979-2010 period (0.15). The results here suggest that the low prediction skill of current dynamical models is largely due to models' deficiency and the dynamical prediction has large room to improve.

Preliminary response of primary production and community composition to precipitation variation in a temperate grassland

USDA-ARS?s Scientific Manuscript database

a) Background/Questions/Methods Grassland ecosystems are water-limited and show the highest interannual ANPP variability across biomes. Changes in annual amounts or seasonality of rainfall may interact with soil texture to impact grassland ecosystem functions including net primary productivity (NPP...

Dowry Deaths: Response to Weather Variability in India.

PubMed

Sekhri, Sheetal; Storeygard, Adam

2014-11-01

We examine the effect of rainfall shocks on dowry deaths using data from 583 Indian districts for 2002-2007. We find that a one standard deviation decline in annual rainfall from the local mean increases reported dowry deaths by 7.8 percent. Wet shocks have no apparent effect. We examine patterns of other crimes to investigate whether an increase in general unrest during economic downturns explains the results but do not find supportive evidence. Women's political representation in the national parliament has no apparent mitigating effect on dowry deaths.

Dowry Deaths: Response to Weather Variability in India☆

PubMed Central

Sekhri, Sheetal; Storeygard, Adam

2014-01-01

We examine the effect of rainfall shocks on dowry deaths using data from 583 Indian districts for 2002–2007. We find that a one standard deviation decline in annual rainfall from the local mean increases reported dowry deaths by 7.8 percent. Wet shocks have no apparent effect. We examine patterns of other crimes to investigate whether an increase in general unrest during economic downturns explains the results but do not find supportive evidence. Women’s political representation in the national parliament has no apparent mitigating effect on dowry deaths. PMID:25386044

Rainfall variability and drought characteristics in two agro-climatic zones: An assessment of climate change challenges in Africa.

PubMed

Ayanlade, Ayansina; Radeny, Maren; Morton, John F; Muchaba, Tabitha

2018-07-15

This paper examines drought characteristics as an evidence of climate change in two agro-climatic zones of Nigeria and farmers' climate change perceptions of impacts and adaptation strategies. The results show high spatial and temporal rainfall variability for the stations. Consequently, there are several anomalies in rainfall in recent years but much more in the locations around the Guinea savanna. The inter-station and seasonality statistics reveal less variable and wetter early growing seasons and late growing seasons in the Rainforest zone, and more variable and drier growing seasons in other stations. The probability (p) of dry spells exceeding 3, 5 and 10 consecutive days is very high with 0.62≤p≥0.8 in all the stations, though, the p-values for 10day spells drop below 0.6 in Ibadan and Osogbo. The results further show that rainfall is much more reliable from the month of May until July with the coefficient of variance for rainy days <0.30, but less reliable in the months of March, August and October (CV-RD>0.30), though CV-RD appears higher in the month of August for all the stations. It is apparent that farmers' perceptions of drought fundamentally mirror climatic patterns from historical weather data. The study concludes that the adaptation facilities and equipment, hybrids of crops and animals are to be provided to farmers, at a subsidized price by the government, for them to cope with the current condition of climate change. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Environmental variability drives shifts in the foraging behaviour and reproductive success of an inshore seabird.

PubMed

Kowalczyk, Nicole D; Reina, Richard D; Preston, Tiana J; Chiaradia, André

2015-08-01

Marine animals forage in areas that aggregate prey to maximize their energy intake. However, these foraging 'hot spots' experience environmental variability, which can substantially alter prey availability. To survive and reproduce animals need to modify their foraging in response to these prey shifts. By monitoring their inter-annual foraging behaviours, we can understand which environmental variables affect their foraging efficiency, and can assess how they respond to environmental variability. Here, we monitored the foraging behaviour and isotopic niche of little penguins (Eudyptula minor), over 3 years (2008, 2011, and 2012) of climatic and prey variability within Port Phillip Bay, Australia. During drought (2008), penguins foraged in close proximity to the Yarra River outlet on a predominantly anchovy-based diet. In periods of heavy rainfall, when water depth in the largest tributary into the bay (Yarra River) was high, the total distance travelled, maximum distance travelled, distance to core-range, and size of core- and home-ranges of penguins increased significantly. This larger foraging range was associated with broad dietary diversity and high reproductive success. These results suggest the increased foraging range and dietary diversity of penguins were a means to maximize resource acquisition rather than a strategy to overcome local depletions in prey. Our results demonstrate the significance of the Yarra River in structuring predator-prey interactions in this enclosed bay, as well as the flexible foraging strategies of penguins in response to environmental variability. This plasticity is central to the survival of this small-ranging, resident seabird species.

High-resolution multi-model projections of onshore wind resources over Portugal under a changing climate

NASA Astrophysics Data System (ADS)

Nogueira, Miguel; Soares, Pedro M. M.; Tomé, Ricardo; Cardoso, Rita M.

2018-05-01

We present a detailed evaluation of wind energy density (WED) over Portugal, based on the EURO-CORDEX database of high-resolution regional climate model (RCM) simulations. Most RCMs showed reasonable accuracy in reproducing the observed near-surface wind speed. The climatological patterns of WED displayed large sub-regional heterogeneity, with higher values over coastal regions and steep orography. Subsequently, we investigated the future changes of WED throughout the twenty-first century, considering mid- and end-century periods, and two emission scenarios (RCP4.5 and RCP8.5). On the yearly average, the multi-model ensemble WED changes were below 10% (15%) under RCP4.5 (RCP8.5). However, the projected WED anomalies displayed strong seasonality, dominated by low positive values in summer (< 10% for both scenarios), negative values in winter and spring (up to - 10% (- 20%) under RCP4.5 (RCP8.5)), and stronger negative anomalies in autumn (up to - 25% (- 35%) under RCP4.5 (RCP8.5)). These projected WED anomalies displayed large sub-regional variability. The largest reductions (and lowest increases) are linked to the northern and central-eastern elevated terrain, and the southwestern coast. In contrast, the largest increases (and lowest reductions) are linked to the central-western orographic features of moderate elevation. The projections also showed changes in inter-annual variability of WED, with small increases for annual averages, but with distinct behavior when considering year-to-year variability over a specific season: small increases in winter, larger increases in summer, slight decrease in autumn, and no relevant change in spring. The changes in inter-annual variability also displayed strong dependence on the underlying terrain. Finally, we found significant model spread in the magnitude of projected WED anomalies and inter-annual variability, affecting even the signal of the changes.

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

DOE PAGES

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.; ...

2017-02-03

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are alreadymore » limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.« less

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

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

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are alreadymore » limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.« less

Response of African Elephants (Loxodonta africana) to Seasonal Changes in Rainfall

PubMed Central

Garstang, Michael; Davis, Robert E.; Leggett, Keith; Frauenfeld, Oliver W.; Greco, Steven; Zipser, Edward; Peterson, Michael

2014-01-01

The factors that trigger sudden, seasonal movements of elephants are uncertain. We hypothesized that savannah elephant movements at the end of the dry season may be a response to their detection of distant thunderstorms. Nine elephants carrying Global Positioning System (GPS) receivers were tracked over seven years in the extremely dry and rugged region of northwestern Namibia. The transition date from dry to wet season conditions was determined annually from surface- and satellite-derived rainfall. The distance, location, and timing of rain events relative to the elephants were determined using the Tropical Rainfall Measurement Mission (TRMM) satellite precipitation observations. Behavioral Change Point Analysis (BCPA) was applied to four of these seven years demonstrating a response in movement of these elephants to intra- and inter-seasonal occurrences of rainfall. Statistically significant changes in movement were found prior to or near the time of onset of the wet season and before the occurrence of wet episodes within the dry season, although the characteristics of the movement changes are not consistent between elephants and years. Elephants in overlapping ranges, but following separate tracks, exhibited statistically valid non-random near-simultaneous changes in movements when rainfall was occurring more than 100 km from their location. While the environmental trigger that causes these excursions remains uncertain, rain-system generated infrasound, which can travel such distances and be detected by elephants, is a possible trigger for such changes in movement. PMID:25299514

Response of African elephants (Loxodonta africana) to seasonal changes in rainfall.

PubMed

Garstang, Michael; Davis, Robert E; Leggett, Keith; Frauenfeld, Oliver W; Greco, Steven; Zipser, Edward; Peterson, Michael

2014-01-01

The factors that trigger sudden, seasonal movements of elephants are uncertain. We hypothesized that savannah elephant movements at the end of the dry season may be a response to their detection of distant thunderstorms. Nine elephants carrying Global Positioning System (GPS) receivers were tracked over seven years in the extremely dry and rugged region of northwestern Namibia. The transition date from dry to wet season conditions was determined annually from surface- and satellite-derived rainfall. The distance, location, and timing of rain events relative to the elephants were determined using the Tropical Rainfall Measurement Mission (TRMM) satellite precipitation observations. Behavioral Change Point Analysis (BCPA) was applied to four of these seven years demonstrating a response in movement of these elephants to intra- and inter-seasonal occurrences of rainfall. Statistically significant changes in movement were found prior to or near the time of onset of the wet season and before the occurrence of wet episodes within the dry season, although the characteristics of the movement changes are not consistent between elephants and years. Elephants in overlapping ranges, but following separate tracks, exhibited statistically valid non-random near-simultaneous changes in movements when rainfall was occurring more than 100 km from their location. While the environmental trigger that causes these excursions remains uncertain, rain-system generated infrasound, which can travel such distances and be detected by elephants, is a possible trigger for such changes in movement.

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

NASA Astrophysics Data System (ADS)

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.; Hulshof, Catherine; Medvigy, David; Pizano, Camila; Salgado-Negret, Beatriz; Smith, Christina M.; Trierweiler, Annette; Van Bloem, Skip J.; Waring, Bonnie G.; Xu, Xiangtao; Powers, Jennifer S.

2017-02-01

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are already limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.

Rainfall Morphology in Semi-Tropical Convergence Zones

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Ferrier, Brad S.; Ray, Peter S.

2000-01-01

Central Florida is the ideal test laboratory for studying convergence zone-induced convection. The region regularly experiences sea breeze fronts and rainfall-induced outflow boundaries. The focus of this study is the common yet poorly-studied convergence zone established by the interaction of the sea breeze front and an outflow boundary. Previous studies have investigated mechanisms primarily affecting storm initiation by such convergence zones. Few have focused on rainfall morphology yet these storms contribute a significant amount precipitation to the annual rainfall budget. Low-level convergence and mid-tropospheric moisture have both been shown to correlate with rainfall amounts in Florida. Using 2D and 3D numerical simulations, the roles of low-level convergence and mid-tropospheric moisture in rainfall evolution are examined. The results indicate that time-averaged, vertical moisture flux (VMF) at the sea breeze front/outflow convergence zone is directly and linearly proportional to initial condensation rates. This proportionality establishes a similar relationship between VMF and initial rainfall. Vertical moisture flux, which encompasses depth and magnitude of convergence, is better correlated to initial rainfall production than surface moisture convergence. This extends early observational studies which linked rainfall in Florida to surface moisture convergence. The amount and distribution of mid-tropospheric moisture determines how rainfall associated with secondary cells develop. Rainfall amount and efficiency varied significantly over an observable range of relative humidities in the 850- 500 mb layer even though rainfall evolution was similar during the initial or "first-cell" period. Rainfall variability was attributed to drier mid-tropospheric environments inhibiting secondary cell development through entrainment effects. Observationally, 850-500 mb moisture structure exhibits wider variability than lower level moisture, which is virtually always present in Florida. A likely consequence of the variability in 850-500 moisture is a stronger statistical correlation to rainfall, which observational studies have noted. The study indicates that vertical moisture flux forcing at convergence zones is critical in determining rainfall in the initial stage of development but plays a decreasing role in rainfall evolution as the system matures. The mid-tropospheric moisture (e.g. environment) plays an increasing role in rainfall evolution as the system matures. This suggests the need to improve measurements of magnitude/depth of convergence and mid-tropospheric moisture distribution. It also highlights the need for better parameterization of entrainment and vertical moisture distribution in larger-scale models.

Observed Oceanic and Terrestrial Drivers of North African Climate

NASA Astrophysics Data System (ADS)

Yu, Y.; Notaro, M.; Wang, F.; Mao, J.; Shi, X.; Wei, Y.

2015-12-01

Hydrologic variability can pose a serious threat to the poverty-stricken regions of North Africa. Yet, the current understanding of oceanic versus terrestrial drivers of North African droughts/pluvials is largely model-based, with vast disagreement among models. In order to identify the observed drivers of North African climate and develop a benchmark for model evaluations, the multivariate Generalized Equilibrium Feedback Assessment (GEFA) is applied to observations, remotely sensed data, and reanalysis products. The identified primary oceanic drivers of North African rainfall variability are the Atlantic, tropical Indian, and tropical Pacific Oceans and Mediterranean Sea. During the summer monsoon, positive tropical eastern Atlantic sea-surface temperature (SST) anomalies are associated with a southward shift of the Inter-Tropical Convergence Zone, enhanced ocean evaporation, and greater precipitable water across coastal West Africa, leading to increased West African monsoon (WAM) rainfall and decreased Sahel rainfall. During the short rains, positive SST anomalies in the western tropical Indian Ocean and negative anomalies in the eastern tropical Indian Ocean support greater easterly oceanic flow, evaporation over the western ocean, and moisture advection to East Africa, thereby enhancing rainfall. The sign, magnitude, and timing of observed vegetation forcing on rainfall vary across North Africa. The positive feedback of leaf area index (LAI) on rainfall is greatest during DJF for the Horn of Africa, while it peaks in autumn and is weakest during the summer monsoon for the Sahel. Across the WAM region, a positive LAI anomaly supports an earlier monsoon onset, increased rainfall during the pre-monsoon, and decreased rainfall during the wet season. Through unique mechanisms, positive LAI anomalies favor enhanced transpiration, precipitable water, and rainfall across the Sahel and Horn of Africa, and increased roughness, ascent, and rainfall across the WAM region. The current study represents the first attempt to separate the observed roles of oceanic and vegetation feedbacks across North Africa, and provides observational benchmark for model evaluation.

Spatio-Temporal Variability of Summer Precipitation in Mexico under the Influence of the MJO, with Emphasis on the Bimodal Pattern

NASA Astrophysics Data System (ADS)

Perdigón, J.; Romero-Centeno, R.; Barrett, B.; Ordoñez-Perez, P.

2017-12-01

In many regions of Mexico, precipitation occurs in a very well defined annual cycle with peaks in May-June and September-October and a relative minimum in the middle of the rainy season known as the midsummer drought (MSD). The MJO is the most important mode of intraseasonal variability in the tropics, and, although some studies have shown its evident influence on summer precipitation in Mexico, its role in modulating the bimodal pattern of the summer precipitation cycle is still an open question. The spatio-temporal variability of summer precipitation in Mexico is analyzed through composite analysis according to the phases of the MJO, using the very high resolution CHIRPS precipitation data base and gridded data from the CFSR reanalysis to analyzing the MJO influence on the atmospheric circulation over Mexico and its adjacent basins. In general, during MJO phases 8-2 (4-6) rainfall is above-normal (below-normal), although, in some cases, the summer rainfall patterns during the same phase present considerable differences. The atmospheric circulation shows low (high) troposphere southwesterly (northeasterly) wind anomalies in southern Mexico under wetter conditions compared with climatological patterns, while the inverse pattern is observed under drier conditions. Composite anomalies of several variables also agreed well with those rainfall anomalies. Finally, a MJO complete cycle that reinforces (weakens) the bimodal pattern of summer rainfall in Mexico was found.

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

NASA Astrophysics Data System (ADS)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to constrain model uncertainty for an - assumed to be - ungauged basin. This shows that our method is promising for reconstructing long-term flow data for ungauged catchments on the Pacific side of Central America, and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

ENSO-driven climate variability promotes periodic major outbreaks of dengue in Venezuela.

PubMed

Vincenti-Gonzalez, M F; Tami, A; Lizarazo, E F; Grillet, M E

2018-04-10

Dengue is a mosquito-borne viral disease of global impact. In Venezuela, dengue has emerged as one of the most important public health problems of urban areas with frequent epidemics since 2001. The long-term pattern of this disease has involved not only a general upward trend in cases but also a dramatic increase in the size and frequency of epidemic outbreaks. By assuming that climate variability has a relevant influence on these changes in time, we quantified the periodicity of dengue incidence in time-series of data from two northern regions of Venezuela. Disease cycles of 1 and 3-4 years (p < 0.05) were detected. We determined that dengue cycles corresponded with local climate and the El Niño Southern Oscillation (ENSO) variation at both seasonal and inter-annual scales (every 2-3 years). Dengue incidence peaks were more prevalent during the warmer and dryer years of El Niño confirming that ENSO is a regional climatic driver of such long-term periodicity through local changes in temperature and rainfall. Our findings support the evidence of the effect of climate on dengue dynamics and advocate the incorporation of climate information in the surveillance and prediction of this arboviral disease in Venezuela.

Disparity in rainfall trend and patterns among different regions: analysis of 158 years' time series of rainfall dataset across India

NASA Astrophysics Data System (ADS)

Saha, Saurav; Chakraborty, Debasish; Paul, Ranjit Kumar; Samanta, Sandipan; Singh, S. B.

2017-10-01

Rainfall anomaly during crop-growing season can have large impact on the agricultural output of a country, especially like India, where two-thirds of the crop land is rain-fed. In such situation, decreased agricultural production not only challenges food security of the country but directly and immediately hits the livelihood of its farming community. In a vast country like India, rainfall or its anomalies hardly follow a specific pattern, rather it is having high variability in spatial domain. This study focused on the trends of national and regional rainfall anomalies (wetness/dryness) along with their interrelationship using time series data of past 158 years. The significant reducing wetness trend (p < 0.05) over north mountainous India was prominent with an increasing trend over southern peninsular India (p < 0.10). However, long-term annual wetness was increasing over entire peninsular India. The results of change point tests indicate that major abrupt changes occurred between early to mid-twentieth century having regional variations. The regional interrelationship was studied using principal component, hierarchical clustering, and pair-wise difference test, which clearly indicated a significantly different pattern in rainfall anomalies for north east India (p = 0.022), north central India (p = 0.022), and north mountainous India (p = 0.011) from that of the all India. Result of this study affirmed high spatial variability in rainfall anomaly and most importantly established the unalike pattern in trends of regional rainfall vis-à-vis national level, ushering towards paradigm shift in rainfall forecast from country scale to regional scale for pragmatic planning.

Sea level anomaly in the North Atlantic and seas around Europe: Long-term variability and response to North Atlantic teleconnection patterns.

PubMed

Iglesias, Isabel; Lorenzo, M Nieves; Lázaro, Clara; Fernandes, M Joana; Bastos, Luísa

2017-12-31

Sea level anomaly (SLA), provided globally by satellite altimetry, is considered a valuable proxy for detecting long-term changes of the global ocean, as well as short-term and annual variations. In this manuscript, monthly sea level anomaly grids for the period 1993-2013 are used to characterise the North Atlantic Ocean variability at inter-annual timescales and its response to the North Atlantic main patterns of atmospheric circulation variability (North Atlantic Oscillation, Eastern Atlantic, Eastern Atlantic/Western Russia, Scandinavian and Polar/Eurasia) and main driven factors as sea level pressure, sea surface temperature and wind fields. SLA variability and long-term trends are analysed for the North Atlantic Ocean and several sub-regions (North, Baltic and Mediterranean and Black seas, Bay of Biscay extended to the west coast of the Iberian Peninsula, and the northern North Atlantic Ocean), depicting the SLA fluctuations at basin and sub-basin scales, aiming at representing the regions of maximum sea level variability. A significant correlation between SLA and the different phases of the teleconnection patterns due to the generated winds, sea level pressure and sea surface temperature anomalies, with a strong variability on temporal and spatial scales, has been identified. Long-term analysis reveals the existence of non-stationary inter-annual SLA fluctuations in terms of the temporal scale. Spectral density analysis has shown the existence of long-period signals in the SLA inter-annual component, with periods of ~10, 5, 4 and 2years, depending on the analysed sub-region. Also, a non-uniform increase in sea level since 1993 is identified for all sub-regions, with trend values between 2.05mm/year, for the Bay of Biscay region, and 3.98mm/year for the Baltic Sea (no GIA correction considered). The obtained results demonstrated a strong link between the atmospheric patterns and SLA, as well as strong long-period fluctuations of this variable in spatial and temporal scales. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison between weather station data in south-eastern Italy and CRU precipitation datasets

NASA Astrophysics Data System (ADS)

Miglietta, D.

2009-04-01

Monthly precipitation data in south-eastern Italy from 1920 to 2005 have been extensively analyzed. Data were collected in almost 200 weather stations located 10-20km apart from each other and almost uniformly distributed in Puglia and Basilicata regions. Apart from few years around world war II, time series are mostly complete and allow a reliable reconstruction of climate variability in the considered region. Statistically significant trends have been studied by applying the Mann-Kendall test to annual, seasonal and monthly values. A comparison has been made between observations and precipitation data given by the Climate Research Unit (CRU), University of East Anglia, with both low (30') and high (10') space resolution grid. In particular, rainfall records, time series behaviors and annual cycles at each station have been compared to the corresponding CRU data. CRU time series show a large negative trend for winter since 1970. Trend is not significant if the whole 20th century is considered (both for the whole year and for winter only). This might be considered as an evidence of recent acceleration towards increasingly dry conditions. However correlation between CRU data and observations is not very high and large percent errors are present mainly in the mountains regions, where observations show a large annual cycle, with intense precipitation in winter, which is not present in CRU data. To identify trends, therefore observed data are needed, even at monthly scale. In particular observations confirm the overall trend, but also indicate large spatial variability, with locations where precipitation has even increased since 1970. Daily precipitation data coming from a subset of weather stations have also been studied for the same time period. The distributions of maximum annual rainfalls, wet spells and dry spells were analyzed for each station, together with their time series. The tools of statistical analysis of extremes have been used in order to evaluate return values and their space distribution over the considered region. A procedure for data quality control and homogeneity test on monthly rainfall records is also being applied, while kriging techniques are being developed in order to fully understand rainfall climatology in south-eastern Italy.

Prediction of future climate change for the Blue Nile, using a nested Regional Climate Model

NASA Astrophysics Data System (ADS)

Soliman, E.; Jeuland, M.

2009-04-01

Although the Nile River Basin is rich in natural resources, it faces many challenges. Rainfall is highly variable across the region, on both seasonal and inter-annual scales. This variability makes the region vulnerable to droughts and floods. Many development projects involving Nile waters are currently underway, or being studied. These projects will lead to land-use patterns changes and water distribution and availability. It is thus important to assess the effects of a) these projects and b) evolving water resource management and policies, on regional hydrological processes. This paper seeks to establish a basis for evaluation of such impacts within the Blue Nile River sub-basin, using the RegCM3 Regional Climate Model to simulate interactions between the land surface and climatic processes. We first present results from application of this RCM model nested with downscaled outputs obtained from the ECHAM5/MPI-OM1 transient simulations for the 20th Century. We then investigate changes associated with mid-21st century emissions forcing of the SRES A1B scenario. The results obtained from the climate model are then fed as inputs to the Nile Forecast System (NFS), a hydrologic distributed rainfall runoff model of the Nile Basin, The interaction between climatic and hydrological processes on the land surface has been fully coupled. Rainfall patterns and evaporation rates have been generated using RegCM3, and the resulting runoff and Blue Nile streamflow patterns have been simulated using the NFS. This paper compares the results obtained from the RegCM3 climate model with observational datasets for precipitation and temperature from the Climate Research Unit (UK) and the NASA Goddard Space Flight Center GPCP (USA) for 1985-2000. The validity of the streamflow predictions from the NFS is assessed using historical gauge records. Finally, we present results from modeling of the A1B emissions scenario of the IPCC for the years 2034-2055. Our results indicate that future changes in rainfall may vary over different areas of the Upper Blue Nile catchment in Ethiopia. Our results suggest that there may be good reasons for developing climate models with finer spatial resolution than the more commonly used GCMs.

Classification and Space-Time Analysis of Precipitation Events in Manizales, Caldas, Colombia.

NASA Astrophysics Data System (ADS)

Suarez Hincapie, J. N.; Vélez, J.; Romo Melo, L.; Chang, P.

2015-12-01

Manizales is a mid-mountain Andean city located near the Nevado del Ruiz volcano in west-central Colombia, this location exposes it to earthquakes, floods, landslides and volcanic eruptions. It is located in the intertropical convergence zone (ITCZ) and presents a climate with a bimodal rainfall regime (Cortés, 2010). Its mean annual rainfall is 2000 mm, one may observe precipitation 70% of the days over a year. This rain which favors the formation of large masses of clouds and the presence of macroclimatic phenomenon as "El Niño South Oscillation", has historically caused great impacts in the region (Vélez et al, 2012). For example the geographical location coupled with rain events results in a high risk of landslides in the city. Manizales has a hydrometeorological network of 40 stations that measure and transmit data of up to eight climate variables. Some of these stations keep 10 years of historical data. However, until now this information has not been used for space-time classification of precipitation events, nor has the meteorological variables that influence them been thoroughly researched. The purpose of this study was to classify historical events of rain in an urban area of Manizales and investigate patterns of atmospheric behavior that influence or trigger such events. Classification of events was performed by calculating the "n" index of the heavy rainfall, describing the behavior of precipitation as a function of time throughout the event (Monjo, 2009). The analysis of meteorological variables was performed using statistical quantification over variable time periods before each event. The proposed classification allowed for an analysis of the evolution of rainfall events. Specially, it helped to look for the influence of different meteorological variables triggering rainfall events in hazardous areas as the city of Manizales.

Soil erodibility variability in laboratory and field rainfall simulations

NASA Astrophysics Data System (ADS)

Szabó, Boglárka; Szabó, Judit; Jakab, Gergely; Centeri, Csaba; Szalai, Zoltán

2017-04-01

Rainfall simulation experiments are the most common way to observe and to model the soil erosion processes in in situ and ex situ circumstances. During modelling soil erosion, one of the most important factors are the annual soil loss and the soil erodibility which represent the effect of soil properties on soil loss and the soil resistance against water erosion. The amount of runoff and soil loss can differ in case of the same soil type, while it's characteristics determine the soil erodibility factor. This leads to uncertainties regarding soil erodibility. Soil loss and soil erodibility were examined with the investigation of the same soil under laboratory and field conditions with rainfall simulators. The comparative measurement was carried out in a laboratory on 0,5 m2, and in the field (Shower Power-02) on 6 m2 plot size where the applied slope angles were 5% and 12% with 30 and 90 mm/h rainfall intensity. The main idea was to examine and compare the soil erodibility and its variability coming from the same soil, but different rainfall simulator type. The applied model was the USLE, nomograph and other equations which concern single rainfall events. The given results show differences between the field and laboratory experiments and between the different calculations. Concerning for the whole rainfall events runoff and soil loss, were significantly higher at the laboratory experiments, which affected the soil erodibility values too. The given differences can originate from the plot size. The main research questions are that: How should we handle the soil erodibility factors and its significant variability? What is the best solution for soil erodibility determination?

Seasonal weather-related decision making for cattle production in the Northern Great Plains

USDA-ARS?s Scientific Manuscript database

High inter-annual variability of seasonal weather patterns can greatly affect forage and therefore livestock production in the Northern Great Plains. This variability can make it difficult for ranchers to set yearly stocking rates, particularly in advance of the grazing season. To better understand ...

Decadal prediction of Sahel rainfall: where does the skill (or lack thereof) come from?

NASA Astrophysics Data System (ADS)

Mohino, Elsa; Keenlyside, Noel; Pohlmann, Holger

2016-12-01

Previous works suggest decadal predictions of Sahel rainfall could be skillful. However, the sources of such skill are still under debate. In addition, previous results are based on short validation periods (i.e. less than 50 years). In this work we propose a framework based on multi-linear regression analysis to study the potential sources of skill for predicting Sahel trends several years ahead. We apply it to an extended decadal hindcast performed with the MPI-ESM-LR model that span from 1901 to 2010 with 1 year sampling interval. Our results show that the skill mainly depends on how well we can predict the timing of the global warming (GW), the Atlantic multidecadal variability (AMV) and, to a lesser extent, the inter-decadal Pacific oscillation signals, and on how well the system simulates the associated SST and West African rainfall response patterns. In the case of the MPI-ESM-LR decadal extended hindcast, the observed timing is well reproduced only for the GW and AMV signals. However, only the West African rainfall response to the AMV is correctly reproduced. Thus, for most of the lead times the main source of skill in the decadal hindcast of West African rainfall is from the AMV. The GW signal degrades skill because the response of West African rainfall to GW is incorrectly captured. Our results also suggest that initialized decadal predictions of West African rainfall can be further improved by better simulating the response of global SST to GW and AMV. Furthermore, our approach may be applied to understand and attribute prediction skill for other variables and regions.

Stochastic characteristics of different duration annual maximum rainfall and its spatial difference in China based on information entropy

NASA Astrophysics Data System (ADS)

Li, X.; Sang, Y. F.

2017-12-01

Mountain torrents, urban floods and other disasters caused by extreme precipitation bring great losses to the ecological environment, social and economic development, people's lives and property security. So there is of great significance to floods prevention and control by the study of its spatial distribution. Based on the annual maximum rainfall data of 60min, 6h and 24h, the paper generate long sequences following Pearson-III distribution, and then use the information entropy index to study the spatial distribution and difference of different duration. The results show that the information entropy value of annual maximum rainfall in the south region is greater than that in the north region, indicating more obvious stochastic characteristics of annual maximum rainfall in the latter. However, the spatial distribution of stochastic characteristics is different in different duration. For example, stochastic characteristics of 60min annual maximum rainfall in the Eastern Tibet is smaller than surrounding, but 6h and 24h annual maximum rainfall is larger than surrounding area. In the Haihe River Basin and the Huaihe River Basin, the stochastic characteristics of the 60min annual maximum rainfall was not significantly different from that in the surrounding area, and stochastic characteristics of 6h and 24h was smaller than that in the surrounding area. We conclude that the spatial distribution of information entropy values of annual maximum rainfall in different duration can reflect the spatial distribution of its stochastic characteristics, thus the results can be an importantly scientific basis for the flood prevention and control, agriculture, economic-social developments and urban flood control and waterlogging.

Fugitive dust mitigation for PM{sub 10} attainment in the western Mojave Desert: Recommendations on revegetation

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

Grantz, D.A.; Vaughn, D.L.; Roberts, E.

1997-12-31

Methods to suppress fugitive dust and associated violations of federal PM{sub 10} standards in the western Mojave Desert, following removal of native vegetation by tillage or overgrazing, have been under investigation by a multi-agency task force for several years. Interim recommendations are now possible for this area of high winds, low rainfall, and mostly arable soil with patchy blowing sand. There can be no guarantee of success in any revegetation program in the desert, but the greatest probability of success in this area can be attained by using the native shrub Atriplex canescens, whether direct seeded or transplanted. No additionalmore » nitrogen should be added, and excess nitrogen should be removed if possible, perhaps by a preliminary cropping of barley. This will itself stabilize the soil surface in the short term. Young plants should be protected from herbivory and the harsh elements by using plastic cones. Irrigation is helpful if available. In areas located near native populations of rabbitbrush annual plant cover should be burned but no tillage or other soil disturbance should be imposed, as this facilitates invasion of annual species, including russian thistle, and prevents establishment of rabbitbrush. In sandy areas, seeding with Indian ricegrass may be more effective than with A. canescens. For immediate, short-term, mitigation of blowing dust, furrowing alone and installation of windfences may be effective. Rainfall exhibits high annual variability in arid regions. Absence of fugitive dust emissions in rainy periods, associated with ground cover by annual vegetation, is unlikely to survive several years of low, but normal, rainfall. It is precisely during those periods when rainfall is adequate that long-term revegetation with shrubs has the best chance of success.« less

Estimation of design floods in ungauged catchments using a regional index flood method. A case study of Lake Victoria Basin in Kenya

NASA Astrophysics Data System (ADS)

Nobert, Joel; Mugo, Margaret; Gadain, Hussein

Reliable estimation of flood magnitudes corresponding to required return periods, vital for structural design purposes, is impacted by lack of hydrological data in the study area of Lake Victoria Basin in Kenya. Use of regional information, derived from data at gauged sites and regionalized for use at any location within a homogenous region, would improve the reliability of the design flood estimation. Therefore, the regional index flood method has been applied. Based on data from 14 gauged sites, a delineation of the basin into two homogenous regions was achieved using elevation variation (90-m DEM), spatial annual rainfall pattern and Principal Component Analysis of seasonal rainfall patterns (from 94 rainfall stations). At site annual maximum series were modelled using the Log normal (LN) (3P), Log Logistic Distribution (LLG), Generalized Extreme Value (GEV) and Log Pearson Type 3 (LP3) distributions. The parameters of the distributions were estimated using the method of probability weighted moments. Goodness of fit tests were applied and the GEV was identified as the most appropriate model for each site. Based on the GEV model, flood quantiles were estimated and regional frequency curves derived from the averaged at site growth curves. Using the least squares regression method, relationships were developed between the index flood, which is defined as the Mean Annual Flood (MAF) and catchment characteristics. The relationships indicated area, mean annual rainfall and altitude were the three significant variables that greatly influence the index flood. Thereafter, estimates of flood magnitudes in ungauged catchments within a homogenous region were estimated from the derived equations for index flood and quantiles from the regional curves. These estimates will improve flood risk estimation and to support water management and engineering decisions and actions.

Encounter risk analysis of rainfall and reference crop evapotranspiration in the irrigation district

NASA Astrophysics Data System (ADS)

Zhang, Jinping; Lin, Xiaomin; Zhao, Yong; Hong, Yang

2017-09-01

Rainfall and reference crop evapotranspiration are random but mutually affected variables in the irrigation district, and their encounter situation can determine water shortage risks under the contexts of natural water supply and demand. However, in reality, the rainfall and reference crop evapotranspiration may have different marginal distributions and their relations are nonlinear. In this study, based on the annual rainfall and reference crop evapotranspiration data series from 1970 to 2013 in the Luhun irrigation district of China, the joint probability distribution of rainfall and reference crop evapotranspiration are developed with the Frank copula function. Using the joint probability distribution, the synchronous-asynchronous encounter risk, conditional joint probability, and conditional return period of different combinations of rainfall and reference crop evapotranspiration are analyzed. The results show that the copula-based joint probability distributions of rainfall and reference crop evapotranspiration are reasonable. The asynchronous encounter probability of rainfall and reference crop evapotranspiration is greater than their synchronous encounter probability, and the water shortage risk associated with meteorological drought (i.e. rainfall variability) is more prone to appear. Compared with other states, there are higher conditional joint probability and lower conditional return period in either low rainfall or high reference crop evapotranspiration. For a specifically high reference crop evapotranspiration with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is increased with the decrease in frequency. For a specifically low rainfall with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is decreased with the decrease in frequency. When either the high reference crop evapotranspiration exceeds a certain frequency or low rainfall does not exceed a certain frequency, the higher conditional joint probability and lower conditional return period of various combinations likely cause a water shortage, but the water shortage is not severe.

Estimating annual suspended-sediment loads in the northern and central Appalachian Coal region

USGS Publications Warehouse

Koltun, G.F.

1985-01-01

Multiple-regression equations were developed for estimating the annual suspended-sediment load, for a given year, from small to medium-sized basins in the northern and central parts of the Appalachian coal region. The regression analysis was performed with data for land use, basin characteristics, streamflow, rainfall, and suspended-sediment load for 15 sites in the region. Two variables, the maximum mean-daily discharge occurring within the year and the annual peak discharge, explained much of the variation in the annual suspended-sediment load. Separate equations were developed employing each of these discharge variables. Standard errors for both equations are relatively large, which suggests that future predictions will probably have a low level of precision. This level of precision, however, may be acceptable for certain purposes. It is therefore left to the user to asses whether the level of precision provided by these equations is acceptable for the intended application.

Rainfall, runoff and sediment transport in a Mediterranean mountainous catchment.

PubMed

Tuset, J; Vericat, D; Batalla, R J

2016-01-01

The relation between rainfall, runoff, erosion and sediment transport is highly variable in Mediterranean catchments. Their relation can be modified by land use changes and climate oscillations that, ultimately, will control water and sediment yields. This paper analyses rainfall, runoff and sediment transport relations in a meso-scale Mediterranean mountain catchment, the Ribera Salada (NE Iberian Peninsula). A total of 73 floods recorded between November 2005 and November 2008 at the Inglabaga Sediment Transport Station (114.5 km(2)) have been analysed. Suspended sediment transport and flow discharge were measured continuously. Rainfall data was obtained by means of direct rain gauges and daily rainfall reconstructions from radar information. Results indicate that the annual sediment yield (2.3 t km(-1) y(-1) on average) and the flood-based runoff coefficients (4.1% on average) are low. The Ribera Salada presents a low geomorphological and hydrological activity compared with other Mediterranean mountain catchments. Pearson correlations between rainfall, runoff and sediment transport variables were obtained. The hydrological response of the catchment is controlled by the base flows. The magnitude of suspended sediment concentrations is largely correlated with flood magnitude, while sediment load is correlated with the amount of direct runoff. Multivariate analysis shows that total suspended load can be predicted by integrating rainfall and runoff variables. The total direct runoff is the variable with more weight in the equation. Finally, three main hydro-sedimentary phases within the hydrological year are defined in this catchment: (a) Winter, where the catchment produces only water and very little sediment; (b) Spring, where the majority of water and sediment is produced; and (c) Summer-Autumn, when little runoff is produced but significant amount of sediments is exported out of the catchment. Results show as land use and climate change may have an important role in modifying the cycles of water and sediment yields in Mediterranean mountain catchments. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

NASA Astrophysics Data System (ADS)

Osunmadewa, Babatunde Adeniyi; Gebrehiwot, Worku Zewdie; Csaplovics, Elmar; Adeofun, Olabinjo Clement

2018-03-01

Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

Evaluation of Rainfall-Runoff Models for Mediterranean Subcatchments

NASA Astrophysics Data System (ADS)

Cilek, A.; Berberoglu, S.; Donmez, C.

2016-06-01

The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA), a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

Estimating inter-annual variability in winter wheat sowing dates from satellite time series in Camargue, France

NASA Astrophysics Data System (ADS)

Manfron, Giacinto; Delmotte, Sylvestre; Busetto, Lorenzo; Hossard, Laure; Ranghetti, Luigi; Brivio, Pietro Alessandro; Boschetti, Mirco

2017-05-01

Crop simulation models are commonly used to forecast the performance of cropping systems under different hypotheses of change. Their use on a regional scale is generally constrained, however, by a lack of information on the spatial and temporal variability of environment-related input variables (e.g., soil) and agricultural practices (e.g., sowing dates) that influence crop yields. Satellite remote sensing data can shed light on such variability by providing timely information on crop dynamics and conditions over large areas. This paper proposes a method for analyzing time series of MODIS satellite data in order to estimate the inter-annual variability of winter wheat sowing dates. A rule-based method was developed to automatically identify a reliable sample of winter wheat field time series, and to infer the corresponding sowing dates. The method was designed for a case study in the Camargue region (France), where winter wheat is characterized by vernalization, as in other temperate regions. The detection criteria were chosen on the grounds of agronomic expertise and by analyzing high-confidence time-series vegetation index profiles for winter wheat. This automatic method identified the target crop on more than 56% (four-year average) of the cultivated areas, with low commission errors (11%). It also captured the seasonal variability in sowing dates with errors of ±8 and ±16 days in 46% and 66% of cases, respectively. Extending the analysis to the years 2002-2012 showed that sowing in the Camargue was usually done on or around November 1st (±4 days). Comparing inter-annual sowing date variability with the main local agro-climatic drivers showed that the type of preceding crop and the weather conditions during the summer season before the wheat sowing had a prominent role in influencing winter wheat sowing dates.

Effects of simulated daily precipitation patterns on annual plant populations depend on life stage and climatic region.

PubMed

Köchy, Martin

2008-03-27

To improve the understanding of consequences of climate change for annual plant communities, I used a detailed, grid-based model that simulates the effect of daily rainfall variability on individual plants in five climatic regions on a gradient from 100 to 800 mm mean annual precipitation (MAP). The model explicitly considers moisture storage in the soil. I manipulated daily rainfall variability by changing the daily mean rain (DMR, rain volume on rainy days averaged across years for each day of the year) by +/- 20%. At the same time I adjusted intervals appropriately between rainy days for keeping the mean annual volume constant. In factorial combination with changing DMR I also changed MAP by +/- 20%. Increasing MAP generally increased water availability, establishment, and peak shoot biomass. Increasing DMR increased the time that water was continuously available to plants in the upper 15 to 30 cm of the soil (longest wet period, LWP). The effect of DMR diminished with increasing humidity of the climate. An interaction between water availability and density-dependent germination increased the establishment of seedlings in the arid region, but in the more humid regions the establishment of seedlings decreased with increasing DMR. As plants matured, competition among individuals and their productivity increased, but the size of these effects decreased with the humidity of the regions. Therefore, peak shoot biomass generally increased with increasing DMR but the effect size diminished from the semiarid to the mesic Mediterranean region. Increasing DMR reduced via LWP the annual variability of biomass in the semiarid and dry Mediterranean regions. More rainstorms (greater DMR) increased the recharge of soil water reservoirs in more arid sites with consequences for germination, establishment, productivity, and population persistence. The order of magnitudes of DMR and MAP overlapped partially so that their combined effect is important for projections of climate change effects on annual vegetation.

Masting in ponderosa pine: comparisons of pollen and seed over space and time.

PubMed

Mooney, Kailen A; Linhart, Yan B; Snyder, Marc A

2011-03-01

Many plant species exhibit variable and synchronized reproduction, or masting, but less is known of the spatial scale of synchrony, effects of climate, or differences between patterns of pollen and seed production. We monitored pollen and seed cone production for seven Pinus ponderosa populations (607 trees) separated by up to 28 km and 1,350 m in elevation in Boulder County, Colorado, USA for periods of 4-31 years for a mean per site of 8.7 years for pollen and 12.1 for seed cone production. We also analyzed climate data and a published dataset on 21 years of seed production for an eighth population (Manitou) 100 km away. Individual trees showed high inter-annual variation in reproduction. Synchrony was high within populations, but quickly became asynchronous among populations with a combination of increasing distance and elevational difference. Inter-annual variation in temperature and precipitation had differing influences on seed production for Boulder County and Manitou. We speculate that geographically variable effects of climate on reproduction arise from environmental heterogeneity and population genetic differentiation, which in turn result in localized synchrony. Although individual pines produce pollen and seed, only one-third of the covariation within trees was shared. As compared to seed cones, pollen had lower inter-annual variation at the level of the individual tree and was more synchronous. However, pollen and seed production were similar with respect to inter-annual variation at the population level, spatial scales of synchrony and associations with climate. Our results show that strong masting can occur at a localized scale, and that reproductive patterns can differ between pollen and seed cone production in a hermaphroditic plant.

The Hydrometeorological DREAM: A Daily REcharge Assessment Model, for the Israeli Western Mountain Aquifer

NASA Astrophysics Data System (ADS)

Sheffer, N. A.; Dafny, E.; Gvirtzman, H.; Frumkin, A.; Navon, S.; Morin, E.

2008-05-01

The western part of the Israeli Mountain Aquifer (WMA) supplies 360-400 MCM/y of fresh water to the Israeli water budget, which is approximately 20% of the total consumption. The annually recharge to the WMA is considered to be 25-35% of annual rainfall. The high variability in recharge to the WMA is due to spatial and temporal differences in the rain contributing to the aquifer. Different winters producing the same amount of rain may contribute differently to the aquifer due to the locations of the storms, intensity, duration, dry spells between successive rain events, etc. Moreover, besides the climatic-meteorological factors, the recharge is dependent also on geographical factors, such as lithology, pedology, land-use, slope gradient, slope direction etc. The need for a robust reliable Hydrometeorological Daily basis REcharge Assessment Model (Hydrometeorological DREAM) brought us to develop a model with a relatively high spatial and temporal resolution. The concept is based on a relatively simple water budget that states that rainfall over land is added to the soil, and removed later on by means of evapotranspiration, recharge and runoff. The method in use to date at the Hydrological Service for estimating recharge to the WMA is based on an annual regression curve that can be implemented only after the total annual rainfall is known. The DREAM is a near real time estimator of recharge to the WMA using daily rainfall and pan evaporation data. Comparison of the DREAM results with the annual regression curve show a high agreement on an annual basis. The improvements introduced by the DREAM are: 1) Near real time daily values of infiltration, as opposed to calculated annual values established after the rain season is over. 2) High spatial resolution. The DREAM produces daily recharge values in more than 3000 mesh points throughout the 2200 km2 of recharge area. By linking the DREAM output as input to a hydrogeological model (such as FEFLOW, MODFLOW etc.) a completion of the water cycle can by achieved.

Vegetation Response to Changing Climate - A Case Study from Gandaki River Basin in Nepal Himalaya

NASA Astrophysics Data System (ADS)

Panthi, J., Sr.; Kirat, N. H.; Dahal, P.

2015-12-01

The climate of the Himalayan region is changing rapidly - temperature is increasingly high and rainfall has become unpredictable. IPCC predicts that average annual mean temperature over the Asian land mass, including the Himalayas, will increase by about 3°C by the 2050s and about 5°C by the 2080s and the average annual precipitation in this region will increase by 10-30% by 2080s. Climate and the human activities can influence the land cover status and the eco-environmental quality. There are enough evidences that there is strong interaction between climate variability and ecosystems. A project was carried out in Gandaki river basin in central Nepal to analyze the relationship of NDVI vegetation index with the temperature, rainfall and snowcover information. The relationships were analyzed for different landuses classes-grassland, forest and agriculture. Results show that the snowcover area is decreasing at the rate of 0.15% per year in the basin. The NDVI shows seasonal fluctuations and lightly correlated with the rainfall and temperature.

Increased resiliency and activity of microbial mediated carbon cycling enzymes in diversified bioenergy cropping systems

NASA Astrophysics Data System (ADS)

Upton, R.; Bach, E.; Hofmockel, K. S.

2017-12-01

Microbes are mediators of soil carbon (C) and are influenced in membership and activity by nitrogen (N) fertilization and inter-annual abiotic factors. Microbial communities and their extracellular enzyme activities (EEA) are important parameters that influence ecosystem C cycling properties and are often included in microbial explicit C cycling models. In an effort to generate model relevant, empirical findings, we investigated how both microbial community structure and C degrading enzyme activity are influenced by inter-annual variability and N inputs in bioenergy crops. Our study was performed at the Comparison of Biofuel Systems field-site from 2011 to 2014, in three bioenergy cropping systems, continuous corn (CC) and two restored prairies, both fertilized (FP) and unfertilized (P). We hypothesized microbial community structure would diverge during the prairie restoration, leading to changes in C cycling enzymes over time. Using a sequencing approach (16S and ITS) we determined the bacterial and fungal community structure response to the cropping system, fertilization, and inter-annual variability. Additionally, we used EEA of β-glucosidase, cellobiohydrolase, and β-xylosidase to determine inter-annual and ecosystem impacts on microbial activity. Our results show cropping system was a main effect for microbial community structure, with corn diverging from both prairies to be less diverse. Inter-annual changes showed that a drought occurring in 2012 significantly impacted microbial community structure in both the P and CC, decreasing microbial richness. However, FP increased in microbial richness, suggesting the application of N increased resiliency to drought. Similarly, the only year in which C cycling enzymes were impacted by ecosystem was 2012, with FP supporting higher potential enzymatic activity then CC and P. The highest EEA across all ecosystems occurred in 2014, suggesting the continued root biomass and litter build-up in this no till system provides increased C cycling activity. Our results showed that diverse cropping systems still benefit from N fertilization to confer resiliency to abiotic stress factors. Long-term studies for microbial mediation of soil C are necessary for modeling the impacts of restoration on SOC to assure inclusion of sustainability and resiliency.

Applying genetic algorithms to set the optimal combination of forest fire related variables and model forest fire susceptibility based on data mining models. The case of Dayu County, China.

PubMed

Hong, Haoyuan; Tsangaratos, Paraskevas; Ilia, Ioanna; Liu, Junzhi; Zhu, A-Xing; Xu, Chong

2018-07-15

The main objective of the present study was to utilize Genetic Algorithms (GA) in order to obtain the optimal combination of forest fire related variables and apply data mining methods for constructing a forest fire susceptibility map. In the proposed approach, a Random Forest (RF) and a Support Vector Machine (SVM) was used to produce a forest fire susceptibility map for the Dayu County which is located in southwest of Jiangxi Province, China. For this purpose, historic forest fires and thirteen forest fire related variables were analyzed, namely: elevation, slope angle, aspect, curvature, land use, soil cover, heat load index, normalized difference vegetation index, mean annual temperature, mean annual wind speed, mean annual rainfall, distance to river network and distance to road network. The Natural Break and the Certainty Factor method were used to classify and weight the thirteen variables, while a multicollinearity analysis was performed to determine the correlation among the variables and decide about their usability. The optimal set of variables, determined by the GA limited the number of variables into eight excluding from the analysis, aspect, land use, heat load index, distance to river network and mean annual rainfall. The performance of the forest fire models was evaluated by using the area under the Receiver Operating Characteristic curve (ROC-AUC) based on the validation dataset. Overall, the RF models gave higher AUC values. Also the results showed that the proposed optimized models outperform the original models. Specifically, the optimized RF model gave the best results (0.8495), followed by the original RF (0.8169), while the optimized SVM gave lower values (0.7456) than the RF, however higher than the original SVM (0.7148) model. The study highlights the significance of feature selection techniques in forest fire susceptibility, whereas data mining methods could be considered as a valid approach for forest fire susceptibility modeling. Copyright © 2018 Elsevier B.V. All rights reserved.

Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

NASA Astrophysics Data System (ADS)

Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

2018-05-01

Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed hydrology. However, a thorough validation and a comparison with other methods are recommended before using the JBC method, since it may perform worse than the IBC method for some cases due to bias nonstationarity of climate model outputs.

On the dust load and rainfall relationship in South Asia: an analysis from CMIP5

NASA Astrophysics Data System (ADS)

Singh, Charu; Ganguly, Dilip; Dash, S. K.

2018-01-01

This study is aimed at examining the consistency of the relationship between load of dust and rainfall simulated by different climate models and its implication for the Indian summer monsoon system. Monthly mean outputs of 12 climate models, obtained from the archive of the Coupled Model Intercomparison Project phase 5 (CMIP5) for the period 1951-2004, are analyzed to investigate the relationship between dust and rainfall. Comparative analysis of the model simulated precipitation with the India Meteorological Department (IMD) gridded rainfall, CRU TS3.21 and GPCP version 2.2 data sets show significant differences between the spatial patterns of JJAS rainfall as well as annual cycle of rainfall simulated by various models and observations. Similarly, significant inter-model differences are also noted in the simulation of load of dust, nevertheless it is further noted that most of the CMIP5 models are able to capture the major dust sources across the study region. Although the scatter plot analysis and the lead-lag pattern correlation between the dust load and the rainfall show strong relationship between the dust load over distant sources and the rainfall in the South Asian region in individual models, the temporal scale of this association indicates large differences amongst the models. Our results caution that it would be pre-mature to draw any robust conclusions on the time scale of the relationship between dust and the rainfall in the South Asian region based on either CMIP5 results or limited number of previous studies. Hence, we would like to emphasize upon the fact that any conclusions drawn on the relationship between the dust load and the South Asian rainfall using model simulation is highly dependent on the degree of complexity incorporated in those models such as the representation of aerosol life cycle, their interaction with clouds, precipitation and other components of the climate system.

A 507-year rainfall and runoff reconstruction for the Monsoonal North West, Australia derived from remote paleoclimate archives

NASA Astrophysics Data System (ADS)

Verdon-Kidd, Danielle C.; Hancock, Gregory R.; Lowry, John B.

2017-11-01

The Monsoonal North West (MNW) region of Australia faces a number of challenges adapting to anthropogenic climate change. These have the potential to impact on a range of industries, including agricultural, pastoral, mining and tourism. However future changes to rainfall regimes remain uncertain due to the inability of Global Climate Models to adequately capture the tropical weather/climate processes that are known to be important for this region. Compounding this is the brevity of the instrumental rainfall record for the MNW, which is unlikely to represent the full range of climatic variability. One avenue for addressing this issue (the focus of this paper) is to identify sources of paleoclimate information that can be used to reconstruct a plausible pre-instrumental rainfall history for the MNW. Adopting this approach we find that, even in the absence of local sources of paleoclimate data at a suitable temporal resolution, remote paleoclimate records can resolve 25% of the annual variability observed in the instrumental rainfall record. Importantly, the 507-year rainfall reconstruction developed using the remote proxies displays longer and more intense wet and dry periods than observed during the most recent 100 years. For example, the maximum number of consecutive years of below (above) average rainfall is 90% (40%) higher in the rainfall reconstruction than during the instrumental period. Further, implications for flood and drought risk are studied via a simple GR1A rainfall runoff model, which again highlights the likelihood of extremes greater than that observed in the limited instrumental record, consistent with previous paleoclimate studies elsewhere in Australia. Importantly, this research can assist in informing climate related risks to infrastructure, agriculture and mining, and the method can readily be applied to other regions in the MNW and beyond.

Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleoclimate data

NASA Astrophysics Data System (ADS)

Henley, B. J.; Thyer, M. A.; Kuczera, G. A.

2012-12-01

A hierarchical framework for incorporating modes of climate variability into stochastic simulations of hydrological data is developed, termed the climate-informed multi-time scale stochastic (CIMSS) framework. To characterize long-term variability for the first level of the hierarchy, paleoclimate and instrumental data describing the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO) are analyzed. A new paleo IPO-PDO time series dating back 440 yrs is produced, combining seven IPO-PDO paleo sources using an objective smoothing procedure to fit low-pass filters to individual records. The paleo data analysis indicates that wet/dry IPO-PDO states have a broad range of run-lengths, with 90% between 3 and 33 yr and a mean of 15 yr. Model selection techniques were used to determine a suitable stochastic model to simulate these run-lengths. The Markov chain model, previously used to simulate oscillating wet/dry climate states, was found to underestimate the probability of wet/dry periods >5 yr, and was rejected in favor of a gamma distribution. For the second level of the hierarchy, a seasonal rainfall model is conditioned on the simulated IPO-PDO state. Application to two high-quality rainfall sites close to water supply reservoirs found that mean seasonal rainfall in the IPO-PDO dry state was 15%-28% lower than the wet state. The model was able to replicate observed statistics such as seasonal and multi-year accumulated rainfall distributions and interannual autocorrelations for the case study sites. In comparison, an annual lag-one autoregressive AR(1) model was unable to adequately capture the observed rainfall distribution within separate IPO-PDO states. Furthermore, analysis of the impact of the CIMSS framework on drought risk analysis found that short-term drought risks conditional on IPO/PDO state were considerably higher than the traditional AR(1) model.hort-term conditional water supply drought risks for the CIMSS and AR(1) models for the dry IPO-PDO scenario with a range of initial storage levels expressed as a proportion of the annual demand (yield).

Regional meteorological drivers and long term trends of winter-spring nitrate dynamics across watersheds in northeastern North America

Treesearch

Jill Crossman; M. Catherine Eimers; Nora J. Casson; Douglas A. Burns; John L. Campbell; Gene E. Likens; Myron J. Mitchell; Sarah J. Nelson; James B. Shanley; Shaun A. Watmough; Kara L. Webster

2016-01-01

This study evaluated the contribution of winter rain-on-snow (ROS) events to annual and seasonal nitrate (N-NO3) export and identified the regional meteorological drivers of inter-annual variability in ROS N-NO3 export (ROS-N) at 9 headwater streams located across Ontario, Canada and the northeastern United States. Although...

Patterns and predictability in the intra-annual organic carbon variability across the boreal and hemiboreal landscape

USGS Publications Warehouse

Hytteborn, Julia K.; Temnerud, Johan; Alexander, Richard B.; Boyer, Elizabeth W.; Futter, Martyn N.; Fröberg, Mats; Dahné, Joel; Bishop, Kevin H.

2015-01-01

Factors affecting total organic carbon (TOC) concentrations in 215 watercourses across Sweden were investigated using parameter parsimonious regression approaches to explain spatial and temporal variabilities of the TOC water quality responses. We systematically quantified the effects of discharge, seasonality, and long-term trend as factors controlling intra-annual (among year) and inter-annual (within year) variabilities of TOC by evaluating the spatial variability in model coefficients and catchment characteristics (e.g. land cover, retention time, soil type).Catchment area (0.18–47,000 km2) and land cover types (forests, agriculture and alpine terrain) are typical for the boreal and hemiboreal zones across Fennoscandia. Watercourses had at least 6 years of monthly water quality observations between 1990 and 2010. Statistically significant models (p < 0.05) describing variation of TOC in streamflow were identified in 209 of 215 watercourses with a mean Nash-Sutcliffe efficiency index of 0.44. Increasing long-term trends were observed in 149 (70%) of the watercourses, and intra-annual variation in TOC far exceeded inter-annual variation. The average influences of the discharge and seasonality terms on intra-annual variations in daily TOC concentration were 1.4 and 1.3 mg l− 1 (13 and 12% of the mean annual TOC), respectively. The average increase in TOC was 0.17 mg l− 1 year− 1 (1.6% year− 1).Multivariate regression with over 90 different catchment characteristics explained 21% of the spatial variation in the linear trend coefficient, less than 20% of the variation in the discharge coefficient and 73% of the spatial variation in mean TOC. Specific discharge, water residence time, the variance of daily precipitation, and lake area, explained 45% of the spatial variation in the amplitude of the TOC seasonality.Because the main drivers of temporal variability in TOC are seasonality and discharge, first-order estimates of the influences of climatic variability and change on TOC concentration should be predictable if the studied catchments continue to respond similarly.

Temporal and taxonomic contrasts in coral growth at Davies Reef, central Great Barrier Reef, Australia

NASA Astrophysics Data System (ADS)

Anderson, Kristen D.; Cantin, Neal E.; Heron, Scott F.; Lough, Janice M.; Pratchett, Morgan S.

2018-06-01

Demographic processes, such as growth, can have an important influence on the population and community structure of reef-building corals. Importantly, ongoing changes in environmental conditions (e.g. ocean warming) are expected to affect coral growth, contributing to changes in the structure of coral populations and communities. This study quantified contemporary growth rates (linear extension and calcification) for the staghorn coral, Acropora muricata, at Davies Reef, central Great Barrier Reef, Australia. Growth rates were measured at three different depths (5, 10, and 15 m) over 2 yr (2012-2014) assessing both seasonal and inter-annual variability. Results of this study were compared to equivalent measurements made in 1980-1982 at the same location. To assist in understanding inter-annual variability in coral growth, we also examined annual growth bands from massive Porites providing continuous growth and records of flooding history for Davies Reef over the period 1979-2012. Linear extension rates of A. muricata were substantially (11-62%) lower in 2012-2014 compared to 1980-1982, especially at 10 and 15 m depths. These declines in growth coincide with a + 0.14 °C change in annual mean temperature. For massive Porites, however, calcification rates were highly variable among years and there was no discernible long-term change in growth despite sustained increases in temperature of 0.064 °C per decade. Apparent differences in the growth rates of Acropora between 1980-1982 and 2012-2014 may reflect inter-annual variation in coral growth (as seen for massive Porites), though it is known branching Acropora is much more sensitive to changing environmental conditions than massive corals. There are persistent issues in assessing the sensitivities of branching corals to environmental change due to limited capacity for retrospective analyses of growth, but given their disproportionate contribution to habitat complexity and reef structure, it is critical to ascertain whether there are increasing impacts on their demography.

Predicting long-term streamflow variability in moist eucalypt forests using forest growth models and a sapwood area index

NASA Astrophysics Data System (ADS)

Jaskierniak, D.; Kuczera, G.; Benyon, R.

2016-04-01

A major challenge in surface hydrology involves predicting streamflow in ungauged catchments with heterogeneous vegetation and spatiotemporally varying evapotranspiration (ET) rates. We present a top-down approach for quantifying the influence of broad-scale changes in forest structure on ET and hence streamflow. Across three catchments between 18 and 100 km2 in size and with regenerating Eucalyptus regnans and E. delegatensis forest, we demonstrate how variation in ET can be mapped in space and over time using LiDAR data and commonly available forest inventory data. The model scales plot-level sapwood area (SA) to the catchment-level using basal area (BA) and tree stocking density (N) estimates in forest growth models. The SA estimates over a 69 year regeneration period are used in a relationship between SA and vegetation induced streamflow loss (L) to predict annual streamflow (Q) with annual rainfall (P) estimates. Without calibrating P, BA, N, SA, and L to Q data, we predict annual Q with R2 between 0.68 and 0.75 and Nash Sutcliffe efficiency (NSE) between 0.44 and 0.48. To remove bias, the model was extended to allow for runoff carry-over into the following year as well as minor correction to rainfall bias, which produced R2 values between 0.72 and 0.79, and NSE between 0.70 and 0.79. The model under-predicts streamflow during drought periods as it lacks representation of ecohydrological processes that reduce L with either reduced growth rates or rainfall interception during drought. Refining the relationship between sapwood thickness and forest inventory variables is likely to further improve results.

Reconstructing pre-instrumental streamflow in Eastern Australia using a water balance approach

NASA Astrophysics Data System (ADS)

Tozer, C. R.; Kiem, A. S.; Vance, T. R.; Roberts, J. L.; Curran, M. A. J.; Moy, A. D.

2018-03-01

Streamflow reconstructions based on paleoclimate proxies provide much longer records than the short instrumental period records on which water resource management plans are currently based. In Australia there is a lack of in-situ high resolution paleoclimate proxy records, but remote proxies with teleconnections to Australian climate have utility in producing streamflow reconstructions. Here we investigate, via a case study for a catchment in eastern Australia, the novel use of an Antarctic ice-core based rainfall reconstruction within a Budyko-framework to reconstruct ∼1000 years of annual streamflow. The resulting streamflow reconstruction captures interannual to decadal variability in the instrumental streamflow, validating both the use of the ice core rainfall proxy record and the Budyko-framework method. In the preinstrumental era the streamflow reconstruction shows longer wet and dry epochs and periods of streamflow variability that are higher than observed in the instrumental era. Importantly, for both the instrumental record and preinstrumental reconstructions, the wet (dry) epochs in the rainfall record are shorter (longer) in the streamflow record and this non-linearity must be considered when inferring hydroclimatic risk or historical water availability directly from rainfall proxy records alone. These insights provide a better understanding of present infrastructure vulnerability in the context of past climate variability for eastern Australia. The streamflow reconstruction presented here also provides a better understanding of the range of hydroclimatic variability possible, and therefore represents a more realistic baseline on which to quantify the potential impacts of anthropogenic climate change on water security.

Farmers' perception and adaptation practice to climate variability and change: a case study of the Vea catchment in Ghana.

PubMed

Limantol, Andrew Manoba; Keith, Bruce Edward; Azabre, Bismark Atiayure; Lennartz, Bernd

2016-01-01

Rain-fed agriculture remains the source of employment for a majority of Ghana's population, particularly in northern Ghana where annual rainfall is low. The purpose of this study is to examine farmers' perceptions and adaptation practices to climate change and variability in accordance with actual recorded weather data of the Vea catchment in Upper East Region of northern Ghana during the time interval from 1972 to 2012. Climatic data over 41-years (1972-2012) from four stations in vicinity of the catchment was evaluated to identify actual weather outcomes. A survey questionnaire targeting farmers with at least 30-years of farming experience in the area was administered in six of the eleven agricultural enumeration areas in the catchment covering 305 km(2). Of the 466 farmers interviewed, 79 % utilized rain-fed practices while 21 % utilized some form of irrigation. Results indicate that nearly 90 % of the farmers interviewed believe that temperature increased over the past 30-years, while over 94 % of the farmers believe that amount of rainfall, duration, intensity and rainy days has decreased. Nearly 96 % of the farmers believe that their farms are extremely vulnerable to decreased rainfall, droughts and changed timing of rainfall events. Climatic data of the catchment indicates a rising trend in temperature but no long-term changes in annual and monthly rainfall, thereby possibly increasing levels of evapotranspiration. While no statistical differences were found between rain-fed and irrigation agricultural types regarding receipt of external support, their approaches to climatic change adaptation do differ. Patently, 94 and 90 % of farmers relying on rain-fed and irrigation strategies respectively receive some form of support, primarily via extension services. Farmers using rain-fed practices adjust to climate variability by varying crop types via rotation without fertilizer while farmers employing irrigation practices are more likely to offset climate variability with a greater use of fertilizer application. The Vea catchment faces rising temperature and evapotranspiration trends. Farmers are aware of these climatic changes and are adapting strategies to cope with the effects but require support. Adequate extension services and irrigation facilities are needed to assist farmers in order to sustain their livelihoods on the long run.

Climate Factors as Important Determinants of Dengue Incidence in Curaçao.

PubMed

Limper, M; Thai, K T D; Gerstenbluth, I; Osterhaus, A D M E; Duits, A J; van Gorp, E C M

2016-03-01

Macro- and microclimates may have variable impact on dengue incidence in different settings. We estimated the short-term impact and delayed effects of climate variables on dengue morbidity in Curaçao. Monthly dengue incidence data from 1999 to 2009 were included to estimate the short-term influences of climate variables by employing wavelet analysis, generalized additive models (GAM) and distributed lag nonlinear models (DLNM) on rainfall, temperature and relative humidity in relation to dengue incidence. Dengue incidence showed a significant irregular 4-year multi-annual cycle associated with climate variables. Based on GAM, temperature showed a U-shape, while humidity and rainfall exhibited a dome-shaped association, suggesting that deviation from mean temperature increases and deviation from mean humidity and rainfall decreases dengue incidence, respectively. Rainfall was associated with an immediate increase in dengue incidence of 4.1% (95% CI: 2.2-8.1%) after a 10-mm increase, with a maximum increase of 6.5% (95% CI: 3.2-10.0%) after 1.5 month lag. A 1 °C decrease of mean temperature was associated with a RR of 17.4% (95% CI: 11.2-27.0%); the effect was inversed for a 1°C increase of mean temperature (RR= 0.457, 95% CI: 0.278-0.752). Climate variables are important determinants of dengue incidence and provide insight into its short-term effects. An increase in mean temperature was associated with lower dengue incidence, whereas lower temperatures were associated with higher dengue incidence. © 2015 Blackwell Verlag GmbH.

On the fog variability over south Asia

NASA Astrophysics Data System (ADS)

Syed, F. S.; Körnich, H.; Tjernström, M.

2012-12-01

An increasing trend in fog frequencies over south Asia during winter in the last few decades has resulted in large economical losses and has caused substantial difficulties in the daily lives of people. In order to better understand the fog phenomenon, we investigated the climatology, inter-annual variability and trends in the fog occurrence from 1976 to 2010 using observational data from 82 stations, well distributed over India and Pakistan. Fog blankets large area from Pakistan to Bangladesh across north India from west to east running almost parallel to south of the Himalayas. An EOF analysis revealed that the fog variability over the whole region is coupled and therefore must be governed by some large scale phenomenon on the inter-annual time scale. Significant positive trends were found in the fog frequency but this increase is not gradual, as with the humidity, but comprises of two distinct regimes shifts, in 1990 and 1998, with respect to both mean and variance. The fog is also detected in ERA-Interim 3 hourly, surface and model level forecast data when using the concept of "cross-over temperature" combined with boundary layer stability. This fog index is able to reproduce the regime shift around 1998 and shows that the method can be applied to analyze fog over south Asia. The inter-annual variability seems to be associated with the wave train originating from the North Atlantic in the upper troposphere that when causing higher pressure over the region results in an increased boundary layer stability and surface-near relative humidity. The trend and shifts in the fog occurrence seems to be associated with the gradual increasing trend in relative humidity from 1990 onwards.

Numerical representation of rainfall field in the Yarmouk River Basin

NASA Astrophysics Data System (ADS)

Shentsis, Isabella; Inbar, Nimrod; Magri, Fabien; Rosenthal, Eliyahu

2017-04-01

Rainfall is the decisive factors in evaluating the water balance of river basins and aquifers. Accepted methods rely on interpolation and extrapolation of gauged rain to regular grid with high dependence on the density and regularity of network, considering the relief complexity. We propose an alternative method that makes up to those restrictions by taking into account additional physical features of the rain field. The method applies to areas with (i) complex plain- and mountainous topography, which means inhomogeneity of the rainfall field and (ii) non-uniform distribution of a rain gauge network with partial lack of observations. The rain model is implemented in two steps: 1. Study of the rainfall field, based on the climatic data (mean annual precipitation), its description by the function of elevation and other factors, and estimation of model parameters (normalized coefficients of the Taylor series); 2. Estimation of rainfall in each historical year using the available data (less complete and irregular versus climatic data) as well as the a-priori known parameters (by the basic hypothesis on inter-annual stability of the model parameters). The proposed method was developed by Shentsis (1990) for hydrological forecasting in Central Asia and was later adapted to the Lake Kinneret Basin. Here this model (the first step) is applied to the Yarmouk River Basin. The Yarmouk River is the largest tributary of the Jordan River. Its transboundary basin (6,833 sq. km) extends over Syria (5,257 sq.km), Jordan (1,379 sq. km) and Israel (197 sq. km). Altitude varies from 1800 m (and more) to -235 m asl. The total number of rain stations in use is 36 (17 in Syria, 19 in Jordan). There is evidently lack and non-uniform distribution of a rain gauge network in Syria. The Yarmouk Basin was divided into five regions considering typical relationship between mean annual rain and elevation for each region. Generally, the borders of regions correspond to the common topographic, geomorphologic and climatic division of the basin. Difference between regional curves is comparable with amplitude of rainfall variance within the regions. In general, rainfall increases with altitude and decreases from west to east (south-east). It should be emphasized that (i) Lake Kinneret Basin (2,490 sq. km) was earlier divided into seven "orographic regions" and (ii) the Lake Kinneret Basin and the Yarmouk River Basin are presented by the system of regional curves X = f (Z) as one whole rainfall field in the Upper Jordan River Basin, where the mean annual rain (X) increases with altitude (Z) and decreases from west to east and from north to south. In the Yarmouk Basin there is much less rainfall (344 mm) than in the Lake Kinneret Basin (749 mm), wherein mean annual rain (2,352 MCM versus 1,865 MCM) is shared between Syria, Jordan and Israel as 80%, 15% and 5%, respectively. The provided rainfall data allow more precise estimations of surface water balances and of recharge to the regional aquifers in the Upper Jordan River Basin. The derived rates serve as fundamental input data for numerical modeling of groundwater flow. This method can be applied to other areas at different temporal and spatial scales. The general applicability makes it a very useful tool in several hydrological problems connected with assessment, management and policy-making of water resources, as well as their changes due to climate and anthropogenic factors. Reference: I. Shentsis (1990). Mathematical models for long-term prediction of mountainous river runoff: methods, information and results, Hydrological Sciences Journal, 35:5, 487-500, DOI: 10.1080/02626669009492453

Geographical distribution of the association between El Niño South Oscillation and dengue fever in the Americas: a continental analysis using geographical information system-based techniques.

PubMed

Ferreira, Marcos C

2014-11-01

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

Trend Analysis of Annual and Seasonal Rainfall in Kansas

NASA Astrophysics Data System (ADS)

Rahmani, V.; Hutchinson, S. L.; Hutchinson, J.; Anandhi, A.

2012-12-01

Precipitation has direct impacts on agricultural production, water resources management, and recreational activities, all of which have significant economic impacts. Thus developing a solid understanding of rainfall patterns and trends is important, and is particularly vital for regions with high climate variability like Kansas. In this study, the annual and seasonal rainfall trends were analyzed using daily precipitation data for four consecutive periods (1891-1920, 1921-1950, 1951-1980, and 1981-2010) and an overall data range of 1890 through 2011 from 23 stations in Kansas. The overall analysis showed that on average Kansas receives 714 mm of rain annually with a strong gradient from west (425 mm, Tribune) to east (1069 mm, Columbus). Due to this gradient, western and central Kansas require more irrigation water than eastern Kansas during the summer growing season to reach the plant water requirements and optimize yield. In addition, a gradual increase in total annual rainfall was found for 21 of 23 stations with a greater increase for recent years (1956 through 2011) and eastern part. The average trend slope for the state is 0.7 mm/yr with a minimum value of -0.8 mm/yr for Saint Francis in Northwest and a maximum value of 2 mm/yr for Independence in Southeast. Seasonal analysis showed that all stations received the most rain during the summer season (June, July, Aug) followed by Spring, Fall and Winter respectively. Investigating the number of dry days (days with rain less than or equal to 2.5 mm) showed that 17 of 23 had a decreasing trend from west to east and across time with the greatest decrease of -0.07 days/yr for Winfield in South and the greatest increase of 0.05 days/yr for Elkhart in Southwest. When assessing the number of dry days between rainfall events, it was found that the majority of the stations had a decreasing trend for most of the months from west to east and across time. These results indicate that Kansas is experiencing fewer dry days and more rainy days with an increasing trend of total rainfall, so the irrigation amount should be updated for each region, and crop and plant types can be modified. The increasing rainfall will also affect hydraulic structures like dams, culverts and channels that may result in more property loss and threat to human life. New rainfall patterns should be considered when designing stormwater management system to avoid poor (over or under sized) design.

Temporal changes in climatic variables and their impact on crop yields in southwestern China

NASA Astrophysics Data System (ADS)

Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

2014-08-01

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing—a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series ( P < 0.05). Increased sunshine hours were observed during the oilseed rape growth period ( P < 0.05). Rainy days decreased slightly in annual and oilseed rape growth time series ( P < 0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall ( P < 0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity ( P < 0.01). Tobacco yield increased with mean temperature ( P < 0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

Temporal changes in climatic variables and their impact on crop yields in southwestern China.

PubMed

Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

2014-08-01

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing-a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series (P<0.05). Increased sunshine hours were observed during the oilseed rape growth period (P<0.05). Rainy days decreased slightly in annual and oilseed rape growth time series (P<0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall (P<0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity (P<0.01). Tobacco yield increased with mean temperature (P<0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

Relationship between turbidity and total suspended solids concentration within a combined sewer system.

PubMed

Hannouche, A; Chebbo, G; Ruban, G; Tassin, B; Lemaire, B J; Joannis, C

2011-01-01

This article confirms the existence of a strong linear relationship between turbidity and total suspended solids (TSS) concentration. However, the slope of this relation varies between dry and wet weather conditions, as well as between sites. The effect of this variability on estimating the instantaneous wet weather TSS concentration is assessed on the basis of the size of the calibration dataset used to establish the turbidity - TSS relationship. Results obtained indicate limited variability both between sites and during dry weather, along with a significant inter-event variability. Moreover, turbidity allows an evaluation of TSS concentrations with an acceptable level of accuracy for a reasonable rainfall event sampling campaign effort.

Effects of model spatial resolution on ecohydrologic predictions and their sensitivity to inter-annual climate variability

Treesearch

Kyongho Son; Christina Tague; Carolyn Hunsaker

2016-01-01

The effect of fine-scale topographic variability on model estimates of ecohydrologic responses to climate variability in California’s Sierra Nevada watersheds has not been adequately quantified and may be important for supporting reliable climate-impact assessments. This study tested the effect of digital elevation model (DEM) resolution on model accuracy and estimates...

Variability of extreme weather events over the equatorial East Africa, a case study of rainfall in Kenya and Uganda

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Omony, George William

2018-01-01

This study investigates the variability of extreme rainfall events over East Africa (EA), using indices from the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). The analysis was based on observed daily rainfall from 23 weather stations, with length varying within 1961 and 2010. The indices considered are: wet days ( R ≥1 mm), annual total precipitation in wet days (PRCPTOT), simple daily intensity index (SDII), heavy precipitation days ( R ≥ 10 mm), very heavy precipitation days ( R ≥ 20 mm), and severe precipitation ( R ≥ 50 mm). The non-parametric Mann-Kendall statistical analysis was carried out to identify trends in the data. Temporal precipitation distribution was different from station to station. Almost all indices considered are decreasing with time. The analysis shows that the PRCPTOT, very heavy precipitation, and severe precipitation are generally declining insignificantly at 5 % significant level. The PRCPTOT is evidently decreasing over Arid and Semi-Arid Land (ASAL) as compared to other parts of EA. The number of days that recorded heavy rainfall is generally decreasing but starts to rise in the last decade although the changes are insignificant. Both PRCPTOT and heavy precipitation show a recovery in trend starting in the 1990s. The SDII shows a reduction in most areas, especially the in ASAL. The changes give a possible indication of the ongoing climate variability and change which modify the rainfall regime of EA. The results form a basis for further research, utilizing longer datasets over the entire region to reduce the generalizations made herein. Continuous monitoring of extreme events in EA is critical, given that rainfall is projected to increase in the twenty-first century.

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.

Future Temperatures and Precipitations in the Arid Northern-Central Chile: A Multi-Model Downscaling Approach

NASA Astrophysics Data System (ADS)

Souvignet, M.; Heinrich, J.

2010-03-01

Downscaling of global climate outputs is necessary to transfer projections of potential climate change scenarios to local levels. This is of special interest to dry mountainous areas, which are particularly vulnerable to climate change due to risks of reduced freshwater availability. These areas play a key role for hydrology since they usually receive the highest local precipitation rates stored in form of snow and glaciers. In the central-northern Chile (Norte Chico, 26-33ºS), where agriculture still serves as a backbone of the economy as well as ensures the well being of people, the knowledge of water resources availability is essential. The region is characterised by a semiarid climate with a mean annual precipitation inferior to 100mm. Moreover, the local climate is also highly influenced by the ENSO phenomenon, which accounts for the strong inter-annual variability in precipitation patterns. Although historical and spatially extensive precipitation data in the headwaters of the basins in this region are not readily available, records at coastal stations show worrisome trends. For instance, the average precipitation in La Serena, the most important city located in the Coquimbo Region, has decreased dramatically in the past 100 years. The 30-year monthly average has decreased from 170 mm in the early 20th century to values less than 80 mm nowadays. Climate Change is expected to strengthen this pattern in the region, and therefore strongly influence local hydrological patterns. The objectives of this study are i) to develop climate change scenarios (2046-2099) for the Norte Chico using multi-model predictions in terms of temperatures and precipitations, and ii) to compare the efficiency of two downscaling techniques in arid mountainous regions. In addition, this study aims at iii) providing decision makers with sound analysis of potential impact of Climate Change on streamflow in the region. For the present study, future local climate scenarios were developed for maximum, minimum temperature and precipitation in the research area based on four different General Circulation Models (GCMs). On the first hand, the Statistical Downscaling Model (SDSM) was used. This model is based on a multiple linear regression method and is best described as a hybrid of the stochastic weather generator and transfer function methods. One common advantage of statistical downscaling is that it ensures the maintenance of local spatial and temporal variability in generating realistic data time series. On the other hand and for comparison purposes, the Change Factor method was used. This methodology is relatively straightforward and ideal for rapid climate change assessment. The outputs of the HadCM3, CGCM3.1, GDFL-CM2 and MRI-CGCM2.3.2 A1 and B2 scenarios were downscaled with both methodologies and thereafter compared by means of several hydro-meteorological indices for a 55-years period (2045-2099). Preliminary results indicate that local temperatures are expected to rise in the region, whereas precipitations may decrease. However, minimum and maximum temperatures might increase at a faster rate at higher altitude areas. In addition, the Cordillera mountain range may encounter and longer winters with a dramatic decrease of icing days (Tmax<0°C). As for precipitation, both SRES scenarios for all models return a diminishing tendency, though the A2 scenario results show a faster decrease rate. Results indicate potential strong inter-seasonal and inter-annual perturbations in Rainfall in the region. Consequently, the Norte Chico will possibly see its streamflow strongly impacted with a resulting high variability at the seasonal and inter-annual level. A probabilistic analysis of the projections of the four GCMs provided a better representation of uncertainties linked with downscaled scenarios. Whereas maximum and minimum temperatures were accurately simulated by both downscaling methods, precipitation simulations returned weaker results. SDSM proved to have a poor ability to simulate extreme rainfall events and few conclusions could be drawn with respect to future occurrences of ENSO phenomena. On the other hand, the change factor method reproduced comparatively better historical precipitations. Despite all sources of error and uncertainties, which must be taken into account when handling the projections, this study addresses an issue that goes beyond local concerns and aims at developing a better understanding of impacts of climate change in fragile environments such as the arid and semiarid transition zone of north-central Chile. Its additional applied component goes therefore beyond the classical comparative study and aims at supporting stakeholders in their processes of decision making.

Adaptation with climate uncertainty: An examination of agricultural land use in the United States

USGS Publications Warehouse

Mu, Jianhong E.; McCarl, Bruce A.; Sleeter, Benjamin M.; Abatzoglou, John T.; Zhang, Hongliang

2018-01-01

This paper examines adaptation responses to climate change through adjustment of agricultural land use. The climate drivers we examine are changes in long-term climate normals (e.g., 10-year moving averages) and changes in inter-annual climate variability. Using US county level data over 1982 to 2012 from Census of Agriculture, we find that impacts of long-term climate normals are as important as that of inter-annual climate variability. Projecting into the future, we find projected climate change will lead to an expansion in crop land share across the northern and interior western United States with decreases in the south. We also find that grazing land share increases in southern regions and Inland Pacific Northwest and declines in the northern areas. However, the extent to which the adaptation potential would be is dependent on the climate model, emission scenario and time horizon under consideration.

Seasonality of Fire Weather Strongly Influences Fire Regimes in South Florida Savanna-Grassland Landscapes

PubMed Central

Platt, William J.; Orzell, Steve L.; Slocum, Matthew G.

2015-01-01

Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature). We used nonparametric cluster analyses of a 17-year (1993–2009) data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture) to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires) over a 13-year period with fire records (1997–2009). Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with timing of natural lightning ignitions should be useful as a basis for ecological fire management of humid savanna-grassland landscapes worldwide. PMID:25574667

Seasonality of fire weather strongly influences fire regimes in South Florida savanna-grassland landscapes.

PubMed

Platt, William J; Orzell, Steve L; Slocum, Matthew G

2015-01-01

Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature). We used nonparametric cluster analyses of a 17-year (1993-2009) data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture) to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires) over a 13-year period with fire records (1997-2009). Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with timing of natural lightning ignitions should be useful as a basis for ecological fire management of humid savanna-grassland landscapes worldwide.

Multi-temporal clustering of continental floods and associated atmospheric circulations

NASA Astrophysics Data System (ADS)

Liu, Jianyu; Zhang, Yongqiang

2017-12-01

Investigating clustering of floods has important social, economic and ecological implications. This study examines the clustering of Australian floods at different temporal scales and its possible physical mechanisms. Flood series with different severities are obtained by peaks-over-threshold (POT) sampling in four flood thresholds. At intra-annual scale, Cox regression and monthly frequency methods are used to examine whether and when the flood clustering exists, respectively. At inter-annual scale, dispersion indices with four-time variation windows are applied to investigate the inter-annual flood clustering and its variation. Furthermore, the Kernel occurrence rate estimate and bootstrap resampling methods are used to identify flood-rich/flood-poor periods. Finally, seasonal variation of horizontal wind at 850 hPa and vertical wind velocity at 500 hPa are used to investigate the possible mechanisms causing the temporal flood clustering. Our results show that: (1) flood occurrences exhibit clustering at intra-annual scale, which are regulated by climate indices representing the impacts of the Pacific and Indian Oceans; (2) the flood-rich months occur from January to March over northern Australia, and from July to September over southwestern and southeastern Australia; (3) stronger inter-annual clustering takes place across southern Australia than northern Australia; and (4) Australian floods are characterised by regional flood-rich and flood-poor periods, with 1987-1992 identified as the flood-rich period across southern Australia, but the flood-poor period across northern Australia, and 2001-2006 being the flood-poor period across most regions of Australia. The intra-annual and inter-annual clustering and temporal variation of flood occurrences are in accordance with the variation of atmospheric circulation. These results provide relevant information for flood management under the influence of climate variability, and, therefore, are helpful for developing flood hazard mitigation schemes.

Interannual Variability of the Bimodal Distribution of Summertime Rainfall Over Central America and Tropical Storm Activity in the Far-Eastern Pacific

NASA Technical Reports Server (NTRS)

Curtis, Scott; Starr, David OC. (Technical Monitor)

2002-01-01

The summer climate of southern Mexico and Central America is characterized by a mid summer drought (MSD), where rainfall is reduced by 40% in July as compared to June and September. A mid-summer reduction in the climatological number of eastern Pacific tropical cyclones has also been noted. Little is understood about the climatology and interannual variability of these minima. The present study uses a novel approach to quantify the bimodal distribution of summertime rainfall for the globe and finds that this feature of the annual cycle is most extreme over Pan America and adjacent oceans. One dominant interannual signal in this region occurs the summer before a strong winter El Nino/Southern Oscillation ENSO. Before El Nino events the region is dry, the MSD is strong and centered over the ocean, and the mid-summer minimum in tropical cyclone frequency is most pronounced. This is significantly different from Neutral cases (non-El Nino and non-La Nina) when the MSD is weak and positioned over the land bridge. The MSD is highly variable for La Nina years, and there is not an obvious mid-summer minimum in the number of tropical cyclones.

An analytic solution of the stochastic storage problem applicable to soil water

USGS Publications Warehouse

Milly, P.C.D.

1993-01-01

The accumulation of soil water during rainfall events and the subsequent depletion of soil water by evaporation between storms can be described, to first order, by simple accounting models. When the alternating supplies (precipitation) and demands (potential evaporation) are viewed as random variables, it follows that soil-water storage, evaporation, and runoff are also random variables. If the forcing (supply and demand) processes are stationary for a sufficiently long period of time, an asymptotic regime should eventually be reached where the probability distribution functions of storage, evaporation, and runoff are stationary and uniquely determined by the distribution functions of the forcing. Under the assumptions that the potential evaporation rate is constant, storm arrivals are Poisson-distributed, rainfall is instantaneous, and storm depth follows an exponential distribution, it is possible to derive the asymptotic distributions of storage, evaporation, and runoff analytically for a simple balance model. A particular result is that the fraction of rainfall converted to runoff is given by (1 - R−1)/(eα(1−R−1) − R−1), in which R is the ratio of mean potential evaporation to mean rainfall and a is the ratio of soil water-holding capacity to mean storm depth. The problem considered here is analogous to the well-known problem of storage in a reservoir behind a dam, for which the present work offers a new solution for reservoirs of finite capacity. A simple application of the results of this analysis suggests that random, intraseasonal fluctuations of precipitation cannot by themselves explain the observed dependence of the annual water balance on annual totals of precipitation and potential evaporation.

Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

NASA Astrophysics Data System (ADS)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

2016-04-01

The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the Mediterranean area. This spatio-temporal analysis of rainfall erosivity at European scale is very important for policy makers and farmers for soil conservation, optimization of agricultural land use and natural hazards prediction. REDES is also used in combination with future rainfall data from WorldClim to run climate change scenarios. The projection of REDES combined with climate change scenarios (HADGEM2, RCP4.5) and using a robust geo-statistical model resulted in a 10-20% increase of the R-factor in Europe till 2050.

El Niño, Rainfall, and the Shifting Geography of Cholera in Africa

NASA Astrophysics Data System (ADS)

Moore, S.; Azman, A. S.; Zaitchik, B. F.; McKay, H.; Lessler, J.

2017-12-01

The El Niño Southern Oscillation (ENSO) and other climate patterns can have profound impacts on the occurrence of infectious diseases. Because of the key role of water supplies in cholera transmission, a relationship between El Niño events and cholera incidence is highly plausible, and previous research has shown a link between El Niño patterns and cholera in Bangladesh. However, there is little systematic evidence for this link in Africa where many cholera cases and deaths are reported. To understand how ENSO affects the geographic distribution of cholera incidence in Africa, we used a hierarchical Bayesian approach to integrate over 17,000 annual observations of cholera incidence from 2000-2014 in over 3,000 unique locations of varying spatial extent, ranging from entire countries to neighborhoods. The resulting maps reflect modeled cholera incidence at a fine spatial resolution using reported counts of cholera cases, key explanatory variables, and a spatially-dependent covariance term. We then examined the potential mechanistic association between ENSO-related changes in cholera incidence and several environmental variables including rainfall. El Niño profoundly changed the annual geographic distribution of cholera in Africa from 2000-2014, shifting the burden to continental East Africa, where almost 50,000 additional cases occur during El Niño years. Cholera incidence during El Niño years was higher in regions of East Africa with increased rainfall, but incidence was also higher in some areas with decreased rainfall suggesting a complex relationship between rainfall and cholera incidence. Here we show clear evidence for a shift in the distribution of cholera incidence throughout Africa in El Niño and non-El Niño years, likely mediated by El Niño's impact on local climatic factors. Knowledge of this relationship between cholera and climate patterns coupled with El Niño forecasting could be used to notify countries in Africa when they are likely to see a major shift in their cholera risk.

A decade of continuous NEE measurements at a Scottish peatland

NASA Astrophysics Data System (ADS)

Helfter, Carole; Campbell, Claire; Coyle, Mhairi; Anderson, Margaret; Drewer, Julia; Levy, Peter; Famulari, Daniela; Twigg, Marsailidh; Skiba, Ute; Billett, Michael; Dinsmore, Kerry; Nemitz, Eiko; Sutton, Mark

2013-04-01

Eddy-covariance measurements of carbon dioxide (CO2) fluxes have been running continuously at the Auchencorth Moss peatland site in Scotland (55o47'32N, 3o14'35W, 267 m a.s.l.) since the spring of 2002 which makes this study one of the longest ones to date on a peatland system. Auchencorth Moss is a low-lying, ombrotrophic peatland situated ca. 20 km south-west of Edinburgh. Peat depth ranges from <0.5 m to >0.5 m and the site has a mean annual precipitation of 1155 mm. The open moorland site has an extensive uniform fetch of blanket bog to the south, west and north. The vegetation present within the flux measurement footprint comprises mixed grass species, heather and substantial areas of moss species (Sphagnum spp. and Polytrichum spp.). The eddy-covariance system consists of a Licor 7000 closed-path infrared gas analyser operating at 10 Hz for the simultaneous measurement of carbon dioxide and water vapour and of a Gill Windmaster Pro ultrasonic anemometer, operating at 20 Hz, and mounted atop a 3 m mast. The effective measurement height is 3.5 m with a vertical separation of 20 cm between the anemometer and the inlet of the sampling line. Air is sampled at 20 litres per minute through a 40 m long Dekabon line (internal diameter 4 mm). In addition to eddy-covariance measurements, the site is equipped with a weather station, soil temperature measurements, total solar radiation and photosynthetically active radiation (PAR) sensors, a tipping bucket for rainfall and, since April 2007, water table depth has been recorded at half-hourly interval. On an annual basis, the peatland at Auchencorth Moss has consistently been a net sink of CO2 in the study period 2002-2012 with a mean net ecosystem exchange (NEE) of - 69.1 ± 33.6 g C-CO2 m-2 yr-1. This value is at the high end of other recent studies as is the inter-annual range of NEE (-31.4 to -135.9 g C-CO2 m-2 yr-1). Inter-annual variations in NEE are significant and strongly correlated to the length of the growing seasons whilst seasonal variations in both NEE and ecosystem respiration are largely driven by air temperature. Monthly and seasonal mean air temperatures during the 2002-2012 study period were very similar to 50-year means, whilst rainfall for that decade was on average higher. Potential effects of rainfall or water table height on NEE and respiration could not be separated from air temperature which appeared to be the strongest control. We conclude by discussing the 10 year NEE dataset in the context of future changes to our climate and the likely scenarios for peatland NEE fluxes.

Study of Inter Annual and Intra Seasonal cycle of Rainfall using NOAA/INSAT OLR and validation of daily 3B42RT precipitation data sets across India and neighboring seas.

NASA Astrophysics Data System (ADS)

U. Bhanu Kumar, O. S. R.; Ramalingeswara Rao, S.

In view of the thermally driving nature of tropical general circulation deep convection is a key parameter for highlighting the energy source that drives tropical atmospheric motion Regardless of their flaws in estimating deep convection the OLR can nevertheless offer reasonably good estimates for deep convection and rainfall in most tropical regions In the present study INSAT OLR datasets for 7-years 1993-1999 are used to examine the migration of heat sources and sinks over India and neighboring seas The locus of heating is associated with Indian monsoon system Since the motions are driven by gradients of heating and not the absolute magnitude of the sources and sinks themselves the heat sinks are integral parts of Indian monsoon systems Thus study of mean quantitative annual cycle of rainfall in terms of OLR is useful for farmer community and power generation industries over India Secondly anomaly pentad OLR data sets 1 r x1 r are used to examine onset withdrawal and break monsoon situations of summer monsoon season over India Next having identified active and inactive phases of intra seasonal oscillations during boreal summer and boreal winter using NOAA OLR for 25 years 1974-1999 their impact on monsoon systems and tropical cyclones over the Bay of Bengal are also investigated Finally available 3B42RT data sets which are real time multi satellite precipitation product 0 01 mm hr are validated with rain gauge data across India and island stations

Upper-soil moisture inter-comparison from SMOS's products and land surface models over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Aires, Filipe; Balsamo, Gianpaolo; Gelati, Emiliano; Rodríguez-Fernández, Nemesio

2015-04-01

Soil moisture is a key state variable of the hydrological cycle. It conditions runoff, infiltration and evaporation over continental surfaces, and is key for forecasting droughts and floods. It plays thus an important role in surface-atmosphere interactions. Surface Soil Moisture (SSM) can be measured by in situ measurements, by satellite observations or modelled using land surface models. As a complementary tool, data assimilation can be used to combine both modelling and satellite observations. The work presented here is an inter-comparison of retrieved and modelled SSM data, for the 2010 - 2012 period, over the Iberian Peninsula. The region has been chosen because its vegetation cover is not very dense and includes strong contrasts in the rainfall regimes and thus a diversity of behaviours for SSM. Furthermore this semi-arid region is strongly dependent on a good management of its water resources. Satellite observations correspond to the Soil Moisture and Ocean Salinity (SMOS) retrievals: the L2 product from an optimal interpolation retrieval, and 3 other products using Neural Network retrievals with different input information: SMOS time indexes, purely SMOS data, or addition of the European Advanced Scaterometer (ASCAT) backscattering, and the Moderate-Resolution Imaging Spectrometer (MODIS) surface temperature information. The modelled soil moistures have been taken from the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) and the HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchanges over Land) land surface models. Both models are forced with the same atmospheric conditions (as part of the Earth2Observe FP7 project) over the period but they represent the surface soil moisture with very different degrees of complexity. ORCHIDEE has 5 levels in the top 5 centimetres of soil while in HTESSEL this variable is part of the top soil moisture level. The two types of SMOS retrievals are compared to the model outputs in their spatial and temporal characteristics. The comparison with the model helps to identify which retrieval configuration is most consistent with our understanding of surface soil moisture in this region. In particular we have determined how each of the soil moisture products is related to the spatio-temporal variations of rainfall. In large parts of the Iberian Peninsula the co-variance of remote sensed SSM and rainfall is consistent with that of the models. But for some regions questions are raised. The variability of SSM observed by SMOS in the North West of the Iberian Peninsula is similar to that of rainfall, at least this relation of SSM and rainfall is closer than suggested by the two models.

Variability of spawning time (lunar day) in Acropora versus merulinid corals: a 7-yr record of in situ coral spawning in Taiwan

NASA Astrophysics Data System (ADS)

Lin, Che-Hung; Nozawa, Yoko

2017-12-01

Despite the global accumulation of coral spawning records over the past three decades, information on inter-annual variation in spawning time is still insufficient, resulting in difficulty in predicting coral spawning time. Here, we present new information on in situ spawning times of scleractinian corals at Lyudao, Taiwan, covering their inter-annual variations over a 7-yr period (2010-2016). Spawning of 42 species from 16 genera in eight families was recorded. The majority were hermaphroditic spawners (38 of 42 species), and their spawning occurred 2-4 h after sunset on 1-11 d after the full moon (AFM), mostly in April and May. There were two distinct patterns in the two dominant taxa, the genus Acropora (14 species) and the family Merulinidae (18 species in eight genera). The annual spawning of Acropora corals mostly occurred on a single night in May with high inter-annual variation of spawning (lunar) days between 1 and 11 d AFM. In contrast, the annual spawning of merulinid corals commonly occurred over 2-3 consecutive nights in two consecutive months, April and May, with the specific range of spawning days around the last quarter moon (between 5 and 8 d AFM). The distinct spawning patterns of these taxa were also documented at Okinawa and Kochi, Japan, where similar long-term monitoring of in situ coral spawning has been conducted. This variability in spawning days implies different regulatory mechanisms of synchronous spawning where Acropora corals might be more sensitive to exogenous environmental factors (hourglass mechanism), compared to merulinid corals, which may rely more on endogenous biological rhythms (oscillator mechanism).

Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

NASA Astrophysics Data System (ADS)

Suepa, Tanita

The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability and internal climatic fluctuation. The EVI and phenological patterns varied spatially according to climate variations and human management. The overall regional mean EVI value in SEA from 2001 to 2010 has gradually decreased and phenological trends appeared to shift towards a later and slightly longer growing season. Regional vegetation dynamics over SEA exhibited patterns associated with major climate events such as El Nino in 2005. The rainy season tended to start early and end late and the length of rainy season was slightly longer. However, the amount of rainfall has decreased from 2001 to 2010. The relationship between phenology and rainfall varied among different ecosystems. Additionally, the local scale results indicated that rainfall is a dominant force of phenological changes in naturally vegetated areas and rainfed croplands, whereas human management is a key factor in heavily agricultural areas with irrigated systems. The results of estimating GHG emissions from rice fields in Thailand demonstrated that human management, climate variation, and physical geography had a significant influence on the change in GHG emissions. In addition, the complexity of spatio-temporal patterns in phenology and related variables were displayed on the visualization system with effective functions and an interactive interface. The information and knowledge in this research are useful for local and regional environmental management and for identifying mitigation strategies in the context of climate change and ecosystem dynamics in this region.

Water balance dynamics in the Nile Basin

USGS Publications Warehouse

Senay, Gabriel B.; Asante, Kwabena; Artan, Guleid A.

2009-01-01

Understanding the temporal and spatial dynamics of key water balance components of the Nile River will provide important information for the management of its water resources. This study used satellite-derived rainfall and other key weather variables derived from the Global Data Assimilation System to estimate and map the distribution of rainfall, actual evapotranspiration (ETa), and runoff. Daily water balance components were modelled in a grid-cell environment at 0·1 degree (∼10 km) spatial resolution for 7 years from 2001 through 2007. Annual maps of the key water balance components and derived variables such as runoff and ETa as a percent of rainfall were produced. Generally, the spatial patterns of rainfall and ETa indicate high values in the upstream watersheds (Uganda, southern Sudan, and southwestern Ethiopia) and low values in the downstream watersheds. However, runoff as a percent of rainfall is much higher in the Ethiopian highlands around the Blue Nile subwatershed. The analysis also showed the possible impact of land degradation in the Ethiopian highlands in reducing ETa magnitudes despite the availability of sufficient rainfall. Although the model estimates require field validation for the different subwatersheds, the runoff volume estimate for the Blue Nile subwatershed is within 7·0% of a figure reported from an earlier study. Further research is required for a thorough validation of the results and their integration with ecohydrologic models for better management of water and land resources in the various Nile Basin ecosystems.

Use of a scenario-neutral approach to identify the key hydro-meteorological attributes that impact runoff from a natural catchment

NASA Astrophysics Data System (ADS)

Guo, Danlu; Westra, Seth; Maier, Holger R.

2017-11-01

Scenario-neutral approaches are being used increasingly for assessing the potential impact of climate change on water resource systems, as these approaches allow the performance of these systems to be evaluated independently of climate change projections. However, practical implementations of these approaches are still scarce, with a key limitation being the difficulty of generating a range of plausible future time series of hydro-meteorological data. In this study we apply a recently developed inverse stochastic generation approach to support the scenario-neutral analysis, and thus identify the key hydro-meteorological variables to which the system is most sensitive. The stochastic generator simulates synthetic hydro-meteorological time series that represent plausible future changes in (1) the average, extremes and seasonal patterns of rainfall; and (2) the average values of temperature (Ta), relative humidity (RH) and wind speed (uz) as variables that drive PET. These hydro-meteorological time series are then fed through a conceptual rainfall-runoff model to simulate the potential changes in runoff as a function of changes in the hydro-meteorological variables, and runoff sensitivity is assessed with both correlation and Sobol' sensitivity analyses. The method was applied to a case study catchment in South Australia, and the results showed that the most important hydro-meteorological attributes for runoff were winter rainfall followed by the annual average rainfall, while the PET-related meteorological variables had comparatively little impact. The high importance of winter rainfall can be related to the winter-dominated nature of both the rainfall and runoff regimes in this catchment. The approach illustrated in this study can greatly enhance our understanding of the key hydro-meteorological attributes and processes that are likely to drive catchment runoff under a changing climate, thus enabling the design of tailored climate impact assessments to specific water resource systems.

Overland flow connectivity in olive orchard plots with cover crops and conventional tillage, and under different rainfall scenarios

NASA Astrophysics Data System (ADS)

López-Vicente, Manuel; García-Ruiz, Roberto; Guzmán, Gema; Vicente-Vicente, José Luis; Gómez, José Alfonso

2016-04-01

The study of overland flow connectivity (QC) allows understanding the redistribution dynamics of runoff and soil components as an emergent property of the spatio-temporal interactions of hydrological and geomorphic processes. However, very few studies have dealt with runoff connectivity in olive orchards. In this study we simulated QC in four olive orchard plots, located on the Santa Marta farm (37° 20' 33.6" N, 6° 13' 44" W), in Seville province (Andalusia) in SW Spain. The olive plantation was established in 1985 with trees planted at 8 m x 6 m. Each bounded plot is 8 m wide (between 2 tree lines) and 60 m long (total area of 480 m2), laid out with the longest dimension parallel to the maximum slope and to the tree lines. The slope is uniform, with an average steepness of 11%. Two plots (P2 and P4) were devoted to conventional tillage (CT) consisting of regular chisel plow passes depending on weed growth. Another set of two plots had two types of cover crops (CC) in the inter tree rows (the area outside the vertical olive canopy projection): uniform CC of Lolium multiflorum (P3) and a mixture of L. rigidum and L. multiflorum together with other species (P5). The tree rows were treated with herbicide to keep bare soil. We selected the Index of runoff and sediment Connectivity (IC) of Borselli et al. (2008) to simulate three rainfall scenarios: i) low rainfall intensity (Sc-LowInt) and using the MD flow accumulation algorithm; ii) moderate rainfall intensity (Sc-ModInt) and using MD8; and iii) high rainfall intensity (Sc-HighInt) and using D8. After analysing the values of rainfall intensity during two hydrological years (Oct'09-Sep'10 and Oct'10-Sep'11) we associated the three scenarios with the followings months: Sc-LowInt during the period Jan-Mar, that summarizes 42% of all annual rainfall events; Sc-ModInt during Oct-Nov and Apr-May (32% of all events); and Sc-HighInt during the period Jun-Sep and in December (26% of all events). Instead of using the C-RUSLE factor as it is indicated in the original version of the IC model, we chosen the product between the C (cover-management) and P (support-practices) factors. Previous studies in olive orchards (Gómez et al., 2003) demonstrated that this product is advisable in soil erosion studies. We distinguished four areas within the plots: inter-row-CC, inter-row-CT, olive trees and bare soil under the tree line. Values of the C-RUSLE factor were obtained from previous studies (e.g. Moreira-Madueño, 1991 in Andalusia; Panagos et al., 2015 in Europe). The minimum, mean and maximum values of connectivity in the two plots with CC were lower (-8% on average) than the corresponding values in the two plots under CT. This trend remained by using any of the three algorithms. CC efficiently reduced overland flow connectivity. Areas with low connectivity (deposition-prone areas) appeared more frequently in inter-row-CC in comparison with CT. The assessment of the C-RUSLE factor for each month according to the phenology of the CC and the sowing practices will be explored in further research.

Integrating Stomach Content and Stable Isotope Analyses to Quantify the Diets of Pygoscelid Penguins

PubMed Central

Polito, Michael J.; Trivelpiece, Wayne Z.; Karnovsky, Nina J.; Ng, Elizabeth; Patterson, William P.; Emslie, Steven D.

2011-01-01

Stomach content analysis (SCA) and more recently stable isotope analysis (SIA) integrated with isotopic mixing models have become common methods for dietary studies and provide insight into the foraging ecology of seabirds. However, both methods have drawbacks and biases that may result in difficulties in quantifying inter-annual and species-specific differences in diets. We used these two methods to simultaneously quantify the chick-rearing diet of Chinstrap (Pygoscelis antarctica) and Gentoo (P. papua) penguins and highlight methods of integrating SCA data to increase accuracy of diet composition estimates using SIA. SCA biomass estimates were highly variable and underestimated the importance of soft-bodied prey such as fish. Two-source, isotopic mixing model predictions were less variable and identified inter-annual and species-specific differences in the relative amounts of fish and krill in penguin diets not readily apparent using SCA. In contrast, multi-source isotopic mixing models had difficulty estimating the dietary contribution of fish species occupying similar trophic levels without refinement using SCA-derived otolith data. Overall, our ability to track inter-annual and species-specific differences in penguin diets using SIA was enhanced by integrating SCA data to isotopic mixing modes in three ways: 1) selecting appropriate prey sources, 2) weighting combinations of isotopically similar prey in two-source mixing models and 3) refining predicted contributions of isotopically similar prey in multi-source models. PMID:22053199

Root-associated fungi of Vaccinium carlesii in subtropical forests of China: intra- and inter-annual variability and impacts of human disturbances

PubMed Central

Zhang, Yanhua; Ni, Jian; Tang, Fangping; Pei, Kequan; Luo, Yiqi; Jiang, Lifen; Sun, Lifu; Liang, Yu

2016-01-01

Ericoid mycorrhiza (ERM) are expected to facilitate establishment of ericaceous plants in harsh habitats. However, diversity and driving factors of the root-associated fungi of ericaceous plants are poorly understood. In this study, hair-root samples of Vaccinium carlesii were taken from four forest types: old growth forests (OGF), secondary forests with once or twice cutting (SEC I and SEC II), and Cunninghamia lanceolata plantation (PLF). Fungal communities were determined using high-throughput sequencing, and impacts of human disturbances and the intra- and inter-annual variability of root-associated fungal community were evaluated. Diverse fungal taxa were observed and our results showed that (1) Intra- and inter-annual changes in root-associated fungal community were found, and the Basidiomycota to Ascomycota ratio was related to mean temperature of the sampling month; (2) Human disturbances significantly affected structure of root-associated fungal community of V. carlesii, and two secondary forest types were similar in root-associated fungal community and were closer to that of the old growth forest; (3) Plant community composition, edaphic parameters, and geographic factors significantly affected root-associated fungal communities of V. carlesii. These results may be helpful in better understanding the maintenance mechanisms of fungal diversity associated with hair roots of ERM plants under human disturbances. PMID:26928608

[Effect of climate change on the fisheries conununity pattern in the overwintering ground of open waters of northern East China Sea].

PubMed

Liu, Zun-lei; Yuan, Xing-wei; Yang, Lin-lin; Yan, Li-ping; Tian, Yong-jun; Chen, Jia-hua

2015-03-01

Data sets of 26 fisheries target species from the fishery-depen-dent and fishery-independent surveys in the overwintering ground of open waters of northern East China Sea (OW-NECS), combined sea surface temperature (SST), were used to examine the links between diversity index, pattern of common variability and climate changes based on the principal component analysis (PCA) and generalized additive model (GAM). The results showed that the shift from a cold regime to a warm regime was detected in SST during the 1970s-2011 with step changes around 1982/ 1983. SST increased during the cold regime and the warm regime before 1998 (warming trend period, 1972-1998), and decreased during the warm regime after 1998 (cooling trend period, 1999-2011). Shannon diversity index was largely dependent on the filefish, which contributed up to 50% of the total production as a single species, with low diversity in the waters of the OW-NECS, during the late 1980s and early 1990s. Excluding the filefish, the diversity index linearly increased and decreased during 1972-1998 and 1999-2011, respectively. The variation pattern generally corresponds with the trend in water temperature, strongly suggesting the effect of the SST on the diversity. The first two components (PC1 and PC2) of PCA for target species, which accounted for 32.43% of the total variance, showed evident decadal variation patterns with a step change during 1992-1999 and inter-annual variability with short-period fluctuation, respectively. It seems that PC1 was associated with large scale climatic change, while PC2 was related to inter-annual oceanographic variability such as ENSO events. Linear fitting results showed winEOF1 had significant effect on PC1, and GAM analysis for PC1 showed that winter EOF1 (winEOF1) and summer EOF2 (sumEOF2) can explain 88.9% of the total variance. Nonlinear effect was also found between PC2 and win EOF1, indicating that the fish community structure, which had predominantly decadal/inter-annual variation patterns, was influenced by inter-annual variations in oceanographic conditions.

Xylem and Leaf Functional Adjustments to Drought in Pinus sylvestris and Quercus pyrenaica at Their Elevational Boundary

PubMed Central

Fernández-de-Uña, Laura; Rossi, Sergio; Aranda, Ismael; Fonti, Patrick; González-González, Borja D.; Cañellas, Isabel; Gea-Izquierdo, Guillermo

2017-01-01

Climatic scenarios for the Mediterranean region forecast increasing frequency and intensity of drought events. Consequently, a reduction in Pinus sylvestris L. distribution range is projected within the region, with this species being outcompeted at lower elevations by more drought-tolerant taxa such as Quercus pyrenaica Willd. The functional response of these species to the projected shifts in water availability will partially determine their performance and, thus, their competitive success under these changing climatic conditions. We studied how the cambial and leaf phenology and xylem anatomy of these two species responded to a 3-year rainfall exclusion experiment set at their elevational boundary in Central Spain. Additionally, P. sylvestris leaf gas exchange, water potential and carbon isotope content response to the treatment were measured. Likewise, we assessed inter-annual variability in the studied functional traits under control and rainfall exclusion conditions. Prolonged exposure to drier conditions did not affect the onset of xylogenesis in either of the studied species, whereas xylem formation ceased 1–3 weeks earlier in P. sylvestris. The rainfall exclusion had, however, no effect on leaf phenology on either species, which suggests that cambial phenology is more sensitive to drought than leaf phenology. P. sylvestris formed fewer, but larger tracheids under dry conditions and reduced the proportion of latewood in the tree ring. On the other hand, Q. pyrenaica did not suffer earlywood hydraulic diameter changes under rainfall exclusion, but experienced a cumulative reduction in latewood width, which could ultimately challenge its hydraulic performance. The phenological and anatomical response of the studied species to drought is consistent with a shift in resource allocation under drought stress from xylem to other sinks. Additionally, the tighter stomatal control and higher intrinsic water use efficiency observed in drought-stressed P. sylvestris may eventually limit carbon uptake in this species. Our results suggest that both species are potentially vulnerable to the forecasted increase in drought stress, although P. sylvestris might experience a higher risk of drought-induced decline at its low elevational limit. PMID:28744292

Xylem and Leaf Functional Adjustments to Drought in Pinus sylvestris and Quercus pyrenaica at Their Elevational Boundary.

PubMed

Fernández-de-Uña, Laura; Rossi, Sergio; Aranda, Ismael; Fonti, Patrick; González-González, Borja D; Cañellas, Isabel; Gea-Izquierdo, Guillermo

2017-01-01

Climatic scenarios for the Mediterranean region forecast increasing frequency and intensity of drought events. Consequently, a reduction in Pinus sylvestris L. distribution range is projected within the region, with this species being outcompeted at lower elevations by more drought-tolerant taxa such as Quercus pyrenaica Willd. The functional response of these species to the projected shifts in water availability will partially determine their performance and, thus, their competitive success under these changing climatic conditions. We studied how the cambial and leaf phenology and xylem anatomy of these two species responded to a 3-year rainfall exclusion experiment set at their elevational boundary in Central Spain. Additionally, P. sylvestris leaf gas exchange, water potential and carbon isotope content response to the treatment were measured. Likewise, we assessed inter-annual variability in the studied functional traits under control and rainfall exclusion conditions. Prolonged exposure to drier conditions did not affect the onset of xylogenesis in either of the studied species, whereas xylem formation ceased 1-3 weeks earlier in P. sylvestris . The rainfall exclusion had, however, no effect on leaf phenology on either species, which suggests that cambial phenology is more sensitive to drought than leaf phenology. P. sylvestris formed fewer, but larger tracheids under dry conditions and reduced the proportion of latewood in the tree ring. On the other hand, Q. pyrenaica did not suffer earlywood hydraulic diameter changes under rainfall exclusion, but experienced a cumulative reduction in latewood width, which could ultimately challenge its hydraulic performance. The phenological and anatomical response of the studied species to drought is consistent with a shift in resource allocation under drought stress from xylem to other sinks. Additionally, the tighter stomatal control and higher intrinsic water use efficiency observed in drought-stressed P. sylvestris may eventually limit carbon uptake in this species. Our results suggest that both species are potentially vulnerable to the forecasted increase in drought stress, although P. sylvestris might experience a higher risk of drought-induced decline at its low elevational limit.

Quantifying the impact of the major driving mechanisms of inter-annual variability of salinity in the North Sea

NASA Astrophysics Data System (ADS)

Núñez-Riboni, Ismael; Akimova, Anna

2017-05-01

New 67-year long (1948-2014) gridded time series of salinity in the North Sea at all depths allowed to quantify, spatially resolved, the amount of inter-annual salinity variability explained by each of its driving mechanisms: sea level pressure (SLP), precipitation, river run-off, zonal and meridional winds and currents over the eastern North Atlantic. For the current data, not only annual averages but also their deviations, as measure of turbulence, were considered. Our results summarize and expand the knowledge gathered in the last 50 years about the mechanisms driving inter-annual variability of salinity in the North Sea. Three mechanisms, uncorrelated with each other and acting over separate regions of the North Sea, arise as most important: (1) River run-off from continental Europe explains 50-80% of inter-annual salinity variations at lag 0 in the Southern and German Bights and the Norwegian Trench up to the connection with the North Atlantic, down to the seabed near the coasts and to the deep Norwegian Trench (100 m); (2) Remote variations of salinity in the Rockall Trough explain 70% of salinity variations of the tongue of high salinity in the northwestern North Sea with a lag of one year and down the water column; (3) The Neva discharge explains 60% of salinity changes in Skagerrak and southern Norwegian trench at lag 0. An explanation for this correlation might be the Baltic freshwater outflow being modulated by the Neva discharge through intensification of the estuarine gravitational circulation. We confirmed known relations between river run-off, precipitation over continental Europe, SLP over northern Europe and zonal wind over western Europe. Linked to these changes, we found also changes of meridional wind north of Scotland favoring eastward Ekman transport of salty North Atlantic waters into the North Sea off the Norwegian coast. Excluding this only case, we found no significant correlation between wind-driven currents and North Sea salinity changes. This result supports the notion that the Atlantic inflow into the North Sea is mainly density-driven. Salinity in the region east of Scotland and northern England was alienated from all driving mechanisms tested. An explanation was found in concomitant canceling changes of the intensity of the North Sea circulation and the discharge of the river Tay.

Hydrologic response in karstic-ridge wetlands to rainfall and evapotranspiration, central Florida, 2001-2003

USGS Publications Warehouse

Knowles, Leel; Phelps, G.G.; Kinnaman, Sandra L.; German, Edward R.

2005-01-01

Two internally drained karstic wetlands in central Florida-Boggy Marsh at the Hilochee Wildlife Management Area and a large unnamed wetland at the Lyonia Preserve-were studied during 2001-03 to gain a better understanding of the net-recharge function that these wetlands provide, the significance of exchanges with ground water with regard to wetland water budgets, and the variability in wetland hydrologic response to a range of climate conditions. These natural, relatively remote and unaltered wetlands were selected to provide a baseline of natural wetland hydrologic variability to which anthropogenic influences on wetland hydrology could be compared. Large departures from normal rainfall during the study were fortuitous, and allowed monitoring of hydrologic processes over a wide range of climate conditions. Wetland responses varied greatly as a result of climate conditions that ranged from moderate drought to extremely moist. Anthropogenic activities influenced water levels at both study sites; however, because these activities were brief relative to the duration of the study, sufficient data were collected during unimpacted periods to allow for the following conclusions to be made. Water budgets developed for Boggy Marsh and the Lyonia large wetland showed strong similarity between the flux terms of rainfall, evaporation, net change in storage, and the net ground-water exchange residual. Runoff was assumed to be negligible. Of the total annual flux at Boggy Marsh, rainfall accounted for 45 percent; evaporation accounted for 25 percent; net change in storage accounted for 25 percent; and the net residual accounted for 5 percent. At the Lyonia large wetland, rainfall accounted for 44 percent; evaporation accounted for 29 percent; net change in storage accounted for 21 percent; and the net residual accounted for 6 percent of the total annual flux. Wetland storage and ground-water exchange were important when compared to the total water budget at both wetlands. Even though rainfall was far above average during the study, wetland evaporation volumetrically exceeded rainfall. Ground-water inflow was effective in partially offsetting the negative residual between rainfall and evaporation, thus adding to wetland storage. Ground-water inflow was most common at both wetlands when rainfall continued for days or weeks, or during a week with more than about 2.5 inches of rainfall. Large decreases in wetland storage were associated with large negative fluxes of evaporation and ground-water exchange. The response of wetland water levels to rainfall showed a strong and similar relation at both study sites; however, the greater variability in the relation of wetland water-level change to rainfall at higher rainfall rates indicated that hydrologic processes other than rainfall became more important in the response of the wetland. Changes in wetland water levels seemed to be related more to vertical gradients than to lateral gradients. The largest wetland water-level rises were associated mostly with lower vertical gradients, when vertical head differences were below the 18-month average; however, at the Lyonia large wetland, extremely large lateral gradients toward the wetland during late June 2002 may have contributed to substantial gains in wetland water. During the remainder of the study, wetland water-level rises were associated mostly with decreasing vertical gradients and highly variable lateral gradients. Conversely, wetland water-level decreases were associated mostly with increasing vertical gradients and lateral gradients away from the wetland, particularly during the dry season. The potential for lateral ground-water exchange with the wetlands varied substantially more than that for vertical exchange. Potential for vertical losses of wetland water to ground water was highest during a dry period from December 2001 to June 2002, during the wet season of 2002, and for several months into the following dry season. Lateral he

Rain rate intensity model for communication link design across the Indian region

NASA Astrophysics Data System (ADS)

Kilaru, Aravind; Kotamraju, Sarat K.; Avlonitis, Nicholas; Sri Kavya, K. Ch.

2016-07-01

A study on rain statistical parameters such as one minute rain intensity, possible number of minute occurrences with respective percentage of time in a year has been evaluated for the purpose of communication link design at Ka, Q, V bands as well as at Free-Space Optical communication links (FSO). To understand possible outage period of a communication links due to rainfall and to investigate rainfall pattern, Automatic Weather Station (AWS) rainfall data is analysed due its ample presence across India. The climates of the examined AWS regions vary from desert to cold climate, heavy rainfall to variable rainfall regions, cyclone effective regions, mountain and coastal regions. In this way a complete and unbiased picture of the rainfall statistics for Indian region is evaluated. The analysed AWS data gives insight into yearly accumulated rainfall, maximum hourly accumulated rainfall, mean hourly accumulated rainfall, number of rainy days and number of rainy hours from 668 AWS locations. Using probability density function the one minute rainfall measurements at KL University is integrated with AWS measurements for estimating number of rain occurrences in terms of one minute rain intensity for annual rainfall accumulated between 100 mm and 5000 mm to give an insight into possible one minute accumulation pattern in an hour for comprehensive analysis of rainfall influence on a communication link for design engineers. So that low availability communications links at higher frequencies can be transformed into a reliable and economically feasible communication links for implementing High Throughput Services (HTS).

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.

Exploring the impact of climate variability during the Last Glacial Maximum on the pattern of human occupation of Iberia.

PubMed

Burke, Ariane; Levavasseur, Guillaume; James, Patrick M A; Guiducci, Dario; Izquierdo, Manuel Arturo; Bourgeon, Lauriane; Kageyama, Masa; Ramstein, Gilles; Vrac, Mathieu

2014-08-01

The Last Glacial Maximum (LGM) was a global climate event, which had significant repercussions for the spatial distribution and demographic history of prehistoric populations. In Eurasia, the LGM coincides with a potential bottleneck for modern humans and may mark the divergence date for Asian and European populations (Keinan et al., 2007). In this research, the impact of climate variability on human populations in the Iberian Peninsula during the Last Glacial Maximum (LGM) is examined with the aid of downscaled high-resolution (16 × 16 km) numerical climate experiments. Human sensitivity to short time-scale (inter-annual) climate variability during this key time period, which follows the initial modern human colonisation of Eurasia and the extinction of the Neanderthals, is tested using the spatial distribution of archaeological sites. Results indicate that anatomically modern human populations responded to small-scale spatial patterning in climate variability, specifically inter-annual variability in precipitation levels as measured by the standard precipitation index. Climate variability at less than millennial scale, therefore, is shown to be an important component of ecological risk, one that played a role in regulating the spatial behaviour of prehistoric human populations and consequently affected their social networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Floods in Central Texas, September 7-14, 2010

USGS Publications Warehouse

Winters, Karl E.

2012-01-01

Severe flooding occurred near the Austin metropolitan area in central Texas September 7–14, 2010, because of heavy rainfall associated with Tropical Storm Hermine. The U.S. Geological Survey, in cooperation with the Upper Brushy Creek Water Control and Improvement District, determined rainfall amounts and annual exceedance probabilities for rainfall resulting in flooding in Bell, Williamson, and Travis counties in central Texas during September 2010. We documented peak streamflows and the annual exceedance probabilities for peak streamflows recorded at several streamflow-gaging stations in the study area. The 24-hour rainfall total exceeded 12 inches at some locations, with one report of 14.57 inches at Lake Georgetown. Rainfall probabilities were estimated using previously published depth-duration frequency maps for Texas. At 4 sites in Williamson County, the 24-hour rainfall had an annual exceedance probability of 0.002. Streamflow measurement data and flood-peak data from U.S. Geological Survey surface-water monitoring stations (streamflow and reservoir gaging stations) are presented, along with a comparison of September 2010 flood peaks to previous known maximums in the periods of record. Annual exceedance probabilities for peak streamflow were computed for 20 streamflow-gaging stations based on an analysis of streamflow-gaging station records. The annual exceedance probability was 0.03 for the September 2010 peak streamflow at the Geological Survey's streamflow-gaging stations 08104700 North Fork San Gabriel River near Georgetown, Texas, and 08154700 Bull Creek at Loop 360 near Austin, Texas. The annual exceedance probability was 0.02 for the peak streamflow for Geological Survey's streamflow-gaging station 08104500 Little River near Little River, Texas. The lack of similarity in the annual exceedance probabilities computed for precipitation and streamflow might be attributed to the small areal extent of the heaviest rainfall over these and the other gaged watersheds.

Possible connection between large volcanic eruptions and level rise episodes in the Dead Sea Basin

NASA Astrophysics Data System (ADS)

Bookman, R.; Filin, S.; Avni, Y.; Rosenfeld, D.; Marco, S.

2014-12-01

The June 1991 Pinatubo volcanic eruption perturbed the atmosphere, triggering short-term worldwide changes in climate. The following winter was anomalously wet in the Levant, with a ~2-meter increase in the Dead Sea level that created a morphological terrace along the lake's shore. Given the global effects of volcanogenic aerosols, we tested the hypothesis that the 1991-92 shore terrace is a modern analogue to the linkage between past volcanic eruptions and a sequence of shore terraces in the Dead Sea Basin. Analysis of precipitation series from Jerusalem showed a significant positive correlation between the Dust Veil Index (DVI) of the modern eruptions and annual rainfall. The DVI was found to explain nearly 50% of the variability in the annual rainfall, such that greater DVI means more rainfall. Other factors that may affect the annual rainfall in the region as the Southern Oscillation Index (SOI) and the North Atlantic oscillations (NAO) were incorporated along with the DVI in a linear multiple regression model. It was found that the NAO did not contribute anything except for increased noise, but the added SOI increased the explained variability of rainfall to more than 60%. Volcanic eruptions with a VEI of 6, as in the Pinatubo, occurred about once a century during the Holocene and the last glacial-interglacial cycle. This occurrence is similar to the frequency of shore terrace build-up during the Lake Lisan desiccation. Sixteen shore terraces, detected using airborne laser scanning data, were interpreted as indicating short-term level rises due to episodes of enhanced precipitation and runoff during the dramatic drop in Lake Lisan's (palaeo-Dead Sea) level at the end of the LGM. The terraces were compared with a time series of volcanogenic sulfate from the GISP2 record, and similar numbers of sulfate concentration peaks and terraces were found. Furthermore, a significant correlation was found between SO4 concentration peaks and the terraces heights. This correlation may indicate a link between the explosivity, magnitude of stratospheric injection, and the impact on the northern hemisphere water balance. The record of such short-term climato-hydrological effects is made possible by the dramatic desiccation of Lake Lisan. Detailed records of such events provide a demonstration of global climatic teleconnections.

Faithful or not: direct and indirect effects of climate on extra-pair paternities in a population of Alpine marmots

PubMed Central

Allainé, Dominique; Sauzet, Sandrine; Cohas, Aurélie

2016-01-01

Despite being identified an area that is poorly understood regarding the effects of climate change, behavioural responses to climatic variability are seldom explored. Climatic variability is likely to cause large inter-annual variation in the frequency of extra-pair litters produced, a widespread alternative mating tactic to help prevent, correct or minimize the negative consequences of sub-optimal mate choice. In this study, we investigated how climatic variability affects the inter-annual variation in the proportion of extra-pair litters in a wild population of Alpine marmots. During 22 years of monitoring, the annual proportion of extra-pair litters directly increased with the onset of earlier springs and indirectly with increased snow in winters. Snowier winters resulted in a higher proportion of families with sexually mature male subordinates and thus, created a social context within which extra-pair paternity was favoured. Earlier spring snowmelt could create this pattern by relaxing energetic, movement and time constraints. Further, deeper snow in winter could also contribute by increasing litter size and juvenile survival. Optimal mate choice is particularly relevant to generate adaptive genetic diversity. Understanding the influence of environmental conditions and the capacity of the individuals to cope with them is crucial within the context of rapid climate change. PMID:28003452

Faithful or not: direct and indirect effects of climate on extra-pair paternities in a population of Alpine marmots.

PubMed

Bichet, Coraline; Allainé, Dominique; Sauzet, Sandrine; Cohas, Aurélie

2016-12-28

Despite being identified an area that is poorly understood regarding the effects of climate change, behavioural responses to climatic variability are seldom explored. Climatic variability is likely to cause large inter-annual variation in the frequency of extra-pair litters produced, a widespread alternative mating tactic to help prevent, correct or minimize the negative consequences of sub-optimal mate choice. In this study, we investigated how climatic variability affects the inter-annual variation in the proportion of extra-pair litters in a wild population of Alpine marmots. During 22 years of monitoring, the annual proportion of extra-pair litters directly increased with the onset of earlier springs and indirectly with increased snow in winters. Snowier winters resulted in a higher proportion of families with sexually mature male subordinates and thus, created a social context within which extra-pair paternity was favoured. Earlier spring snowmelt could create this pattern by relaxing energetic, movement and time constraints. Further, deeper snow in winter could also contribute by increasing litter size and juvenile survival. Optimal mate choice is particularly relevant to generate adaptive genetic diversity. Understanding the influence of environmental conditions and the capacity of the individuals to cope with them is crucial within the context of rapid climate change. © 2016 The Author(s).

Toward an Improved Understanding of the Tropical Energy Budget Using TRMM-based Atmospheric Radiative Heating Products

NASA Astrophysics Data System (ADS)

L'Ecuyer, T.; McGarragh, G.; Ellis, T.; Stephens, G.; Olson, W.; Grecu, M.; Shie, C.; Jiang, X.; Waliser, D.; Li, J.; Tian, B.

2008-05-01

It is widely recognized that clouds and precipitation exert a profound influence on the propagation of radiation through the Earth's atmosphere. In fact, feedbacks between clouds, radiation, and precipitation represent one of the most important unresolved factors inhibiting our ability to predict the consequences of global climate change. Since its launch in late 1997, the Tropical Rainfall Measuring Mission (TRMM) has collected more than a decade of rainfall measurements that now form the gold standard of satellite-based precipitation estimates. Although not as widely advertised, the instruments aboard TRMM are also well-suited to the problem of characterizing the distribution of atmospheric heating in the tropics and a series of algorithms have recently been developed for estimating profiles of radiative and latent heating from these measurements. This presentation will describe a new multi-sensor tropical radiative heating product derived primarily from TRMM observations. Extensive evaluation of the products using a combination of ground and satellite-based observations is used to place the dataset in the context of existing techniques for quantifying atmospheric radiative heating. Highlights of several recent applications of the dataset will be presented that illustrate its utility for observation-based analysis of energy and water cycle variability on seasonal to inter-annual timescales and evaluating the representation of these processes in numerical models. Emphasis will be placed on the problem of understanding the impacts of clouds and precipitation on atmospheric heating on large spatial scales, one of the primary benefits of satellite observations like those provided by TRMM.

Farmers' perceptions of climate change and agricultural adaptation strategies in rural Sahel.

PubMed

Mertz, Ole; Mbow, Cheikh; Reenberg, Anette; Diouf, Awa

2009-05-01

Farmers in the Sahel have always been facing climatic variability at intra- and inter-annual and decadal time scales. While coping and adaptation strategies have traditionally included crop diversification, mobility, livelihood diversification, and migration, singling out climate as a direct driver of changes is not so simple. Using focus group interviews and a household survey, this study analyzes the perceptions of climate change and the strategies for coping and adaptation by sedentary farmers in the savanna zone of central Senegal. Households are aware of climate variability and identify wind and occasional excess rainfall as the most destructive climate factors. Households attribute poor livestock health, reduced crop yields and a range of other problems to climate factors, especially wind. However, when questions on land use and livelihood change are not asked directly in a climate context, households and groups assign economic, political, and social rather than climate factors as the main reasons for change. It is concluded that the communities studied have a high awareness of climate issues, but climatic narratives are likely to influence responses when questions mention climate. Change in land use and livelihood strategies is driven by adaptation to a range of factors of which climate appears not to be the most important. Implications for policy-making on agricultural and economic development will be to focus on providing flexible options rather than specific solutions to uncertain climate.

Climate change effects on water allocations with season dependent water rights.

PubMed

Null, Sarah E; Prudencio, Liana

2016-11-15

Appropriative water rights allocate surface water to competing users based on seniority. Often water rights vary seasonally with spring runoff, irrigation schedules, or other non-uniform supply and demand. Downscaled monthly Coupled Model Intercomparison Project multi-model, multi-emissions scenario hydroclimate data evaluate water allocation reliability and variability with anticipated hydroclimate change. California's Tuolumne watershed is a study basin, chosen because water rights are well-defined, simple, and include competing environmental, agricultural, and urban water uses representative of most basins. We assume that dedicated environmental flows receive first priority when mandated by federal law like the Endangered Species Act or hydropower relicensing, followed by senior agricultural water rights, and finally junior urban water rights. Environmental flows vary by water year and include April pulse flows, and senior agricultural water rights are 68% larger during historical spring runoff from April through June. Results show that senior water right holders receive the largest climate-driven reductions in allocated water when peak streamflow shifts from snowmelt-dominated spring runoff to mixed snowmelt- and rainfall-dominated winter runoff. Junior water right holders have higher uncertainty from inter-annual variability. These findings challenge conventional wisdom that water shortages are absorbed by junior water users and suggest that aquatic ecosystems may be disproportionally impaired by hydroclimate change, even when environmental flows receive priority. Copyright © 2016 Elsevier B.V. All rights reserved.

Inter-Annual Variability of Soil Moisture Stress Function in the Wheat Field

NASA Astrophysics Data System (ADS)

Akuraju, V. R.; Ryu, D.; George, B.; Ryu, Y.; Dassanayake, K. B.

2014-12-01

Root-zone soil moisture content is a key variable that controls the exchange of water and energy fluxes between land and atmosphere. In the soil-vegetation-atmosphere transfer (SVAT) schemes, the influence of root-zone soil moisture on evapotranspiration (ET) is parameterized by the soil moisture stress function (SSF). Dependence of actual ET: potential ET (fPET) or evaporative fraction to the root-zone soil moisture via SSF can also be used inversely to estimate root-zone soil moisture when fPET is estimated by remotely sensed land surface states. In this work we present fPET versus available soil water (ASW) in the root zone observed in the experimental farm sites in Victoria, Australia in 2012-2013. In the wheat field site, fPET vs ASW exhibited distinct features for different soil depth, net radiation, and crop growth stages. Interestingly, SSF in the wheat field presented contrasting shapes for two cropping years of 2012 and 2013. We argue that different temporal patterns of rainfall (and resulting soil moisture) during the growing seasons in 2012 and 2013 are responsible for the distinctive SSFs. SSF of the wheat field was simulated by the Agricultural Production Systems sIMulator (APSIM). The APSIM was able to reproduce the observed fPET vs. ASW. We discuss implications of our findings for existing modeling and (inverse) remote sensing approaches relying on SSF and alternative growth-stage-dependent SSFs.

Climate-driven diversity change in annual grasslands: Drought plus deluge does not equal normal.

PubMed

Harrison, Susan P; LaForgia, Marina L; Latimer, Andrew M

2018-04-01

Climate forecasts agree that increased variability and extremes will tend to reduce the availability of water in many terrestrial ecosystems. Increasingly severe droughts may be exacerbated both by warmer temperatures and by the relative unavailability of water that arrives in more sporadic and intense rainfall events. Using long-term data and an experimental water manipulation, we examined the resilience of a heterogeneous annual grassland community to a prolonged series of dry winters that led to a decline in plant species richness (2000-2014), followed by a near-record wet winter (2016-2017), a climatic sequence that broadly resembles the predicted future in its high variability. In our 80, 5-m 2 observational plots, species richness did not recover in response to the wet winter, and the positive relationship of richness to annual winter rainfall thus showed a significant weakening trend over the 18-year time period. In experiments on 100, 1-m 2 plots, wintertime water supplementation increased and drought shelters decreased the seedling survival and final individual biomass of native annual forbs, the main functional group contributing to the observed long-term decline in richness. Water supplementation also increased the total cover of native annual forbs, but only increased richness within nested subplots to which seeds were also added. We conclude that prolonged dry winters, by increasing seedling mortality and reducing growth of native forbs, may have diminished the seedbank and thus the recovery potential of diversity in this community. However, the wet winter and the watering treatment did cause recovery of the community mean values of a key functional trait (specific leaf area, an indicator of drought intolerance), suggesting that some aggregate community properties may be stabilized by functional redundancy among species. © 2017 John Wiley & Sons Ltd.

Exploring How Changing Monsoonal Dynamics and Human Pressures Challenge Multi-Reservoir Management of Food-Energy-Water Tradeoffs

NASA Astrophysics Data System (ADS)

Quinn, J.; Reed, P. M.; Giuliani, M.; Castelletti, A.; Oyler, J.; Nicholas, R.

2017-12-01

Multi-reservoir systems require robust and adaptive control policies capable of managing evolving hydroclimatic variability and human demands across a wide range of time scales. This is especially true for systems with high intra-annual and inter-annual variability, such as monsoonal river systems that need to buffer against seasonal droughts while also managing extreme floods. Moreover, the timing, intensity, duration, and frequency of these hydrologic extremes may be affected by deeply uncertain changes in socioeconomic and climatic pressures. This study contributes an innovative method for exploring how possible changes in the timing and magnitude of monsoonal seasonal extremes impact the robustness of reservoir operating policies optimized to historical conditions assuming stationarity. We illustrate this analysis on the Red River basin in Vietnam, where reservoirs and dams serve as important sources of hydropower production, irrigable water supply, and flood protection for the capital city of Hanoi. Applying our scenario discovery approach, we find food-energy-water tradeoffs are exacerbated by potential hydrologic shifts, with wetter worlds threatening the ability of operating strategies to manage flood risk and drier worlds threatening their ability to provide sufficient water supply and hydropower production, especially if demands increase. Most notably, though, amplification of the within-year monsoonal cycle and increased inter-annual variability threaten all of the above. These findings highlight the importance of considering changes in both lower order moments of annual streamflow and intra-annual monsoonal behavior when evaluating the robustness of alternative water systems control strategies for managing deeply uncertain futures.

Asymmetric Responses of Primary Productivity to Altered Precipitation Simulated by Land Surface Models across Three Long-term Grassland Sites

NASA Astrophysics Data System (ADS)

Wu, D.; Ciais, P.; Viovy, N.; Knapp, A.; Wilcox, K.; Bahn, M.; Smith, M. D.; Ito, A.; Arneth, A.; Harper, A. B.; Ukkola, A.; Paschalis, A.; Poulter, B.; Peng, C.; Reick, C. H.; Hayes, D. J.; Ricciuto, D. M.; Reinthaler, D.; Chen, G.; Tian, H.; Helene, G.; Zscheischler, J.; Mao, J.; Ingrisch, J.; Nabel, J.; Pongratz, J.; Boysen, L.; Kautz, M.; Schmitt, M.; Krohn, M.; Zeng, N.; Meir, P.; Zhang, Q.; Zhu, Q.; Hasibeder, R.; Vicca, S.; Sippel, S.; Dangal, S. R. S.; Fatichi, S.; Sitch, S.; Shi, X.; Wang, Y.; Luo, Y.; Liu, Y.; Piao, S.

2017-12-01

Changes in precipitation variability including the occurrence of extreme events strongly influence plant growth in grasslands. Field measurements of aboveground net primary production (ANPP) in temperate grasslands suggest a positive asymmetric response with wet years resulting in ANPP gains larger than ANPP declines in dry years. Whether land surface models used for historical simulations and future projections of the coupled carbon-water system in grasslands are capable to simulate such non-symmetrical ANPP responses remains an important open research question. In this study, we evaluate the simulated responses of grassland primary productivity to altered precipitation with fourteen land surface models at the three sites of Colorado Shortgrass Steppe (SGS), Konza prairie (KNZ) and Stubai Valley meadow (STU) along a rainfall gradient from dry to wet. Our results suggest that: (i) Gross primary production (GPP), NPP, ANPP and belowground NPP (BNPP) show nonlinear response curves (concave-down) in all the models, but with different curvatures and mean values. In contrast across the sites, primary production increases and then saturates along increasing precipitation with a flattening at the wetter site. (ii) Slopes of spatial relationships between modeled primary production and precipitation are steeper than the temporal slopes (obtained from inter-annual variations). (iii) Asymmetric responses under nominal precipitation range with modeled inter-annual primary production show large uncertainties, and model-ensemble median generally suggests negative asymmetry (greater declines in dry years than increases in wet years) across the three sites. (iv) Primary production at the drier site is predicted to more sensitive to precipitation compared to wetter site, and median sensitivity consistently indicates greater negative impacts of reduced precipitation than positive effects of increased precipitation under extreme conditions. This study implies that most models overemphasize the drought effects or underestimate the watering impacts on primary production in the normal-state, with the direct consequence that carbon-water interactions need to be improved in future model generations with improved mechanistic representations.

Rainfall mediations in the spreading of epidemic cholera

NASA Astrophysics Data System (ADS)

Righetto, L.; Bertuzzo, E.; Mari, L.; Schild, E.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

2013-10-01

Following the empirical evidence of a clear correlation between rainfall events and cholera resurgence that was observed in particular during the recent outbreak in Haiti, a spatially explicit model of epidemic cholera is re-examined. Specifically, we test a multivariate Poisson rainfall generator, with parameters varying in space and time, as a driver of enhanced disease transmission. The relevance of the issue relates to the key insight that predictive mathematical models may provide into the course of an ongoing cholera epidemic aiding emergency management (say, in allocating life-saving supplies or health care staff) or in evaluating alternative management strategies. Our model consists of a set of dynamical equations (SIRB-like i.e. subdivided into the compartments of Susceptible, Infected and Recovered individuals, and including a balance of Bacterial concentrations in the water reservoir) describing a connected network of human communities where the infection results from the exposure to excess concentrations of pathogens in the water. These, in turn, are driven by rainfall washout of open-air defecation sites or cesspool overflows, hydrologic transport through waterways and by mobility of susceptible and infected individuals. We perform an a posteriori analysis (from the beginning of the epidemic in October 2010 until December 2011) to test the model reliability in predicting cholera cases and in testing control measures, involving vaccination and sanitation campaigns, for the ongoing epidemic. Even though predicting reliably the timing of the epidemic resurgence proves difficult due to rainfall inter-annual variability, we find that the model can reasonably quantify the total number of reported infection cases in the selected time-span. We then run a multi-seasonal prediction of the course of the epidemic until December 2015, to investigate conditions for further resurgences and endemicity of cholera in the region with a view to policies which may bring to the eradication of the disease in Haiti. The projections, although strongly depending on still uncertain epidemiological processes, show an endemic, seasonal pattern establishing in the region, which can be better forestalled by an improvement of the sanitation system only, rather than by vaccination alone. We thus conclude that hydrologic drivers and water resources management prove central to prediction, emergency management and long-term control of epidemic cholera.

Rainfall simulations to study the types of groundcover on surface runoff and soil erosion in Champagne vineyards in France

NASA Astrophysics Data System (ADS)

Xavier, Morvan; Christophe, Naisse; Issa Oumarou, Malam; Jean-François, Desprats; Anne, Combaud; Olivier, Cerdan

2015-04-01

In the literature, grass cover is often considered to be one of the best methods of limiting runoff in the vineyards; But results can vary, especially when the plot area is <2 m². However, in any study to our knowledge, the way grass cover is structured in the inter-row is taken into account to explain the variability of runoff and soil loss. The objective of this study, conducted in Champagne vineyards in France, was to quantify the influence of the cultivation practices in the inter-rows of vines and determine the influence of the density of the grass cover in the wheel tracks on the surface runoff and soil erosion in experimental plots of 0.25 m2 under simulated rainfall. Three types of ground cover were studied. In the bark-and-vine-prunings plots, the runoff coefficient ranged from 1.3 to 4.0% and soil losses were <1 g/m²/h. In the bare soil plot, the highest runoff coefficient of the study was found (80.0%) and soil losses reached 7.4 g/m²/h. In the grass cover plots, the runoff coefficient and amount of eroded soil were highly variable: the runoff coefficients ranged from 0.4 to 77.0%, and soil losses were between less than 1 and 13.4 g/m²/h. Soil type, soil moisture, slope and agricultural practices did not account for the variability. In fact, the density of grass cover in the wheel tracks explained a portion of this variability. The lack of grass in the centre of the inter-row allowed for a preferential flow and created an erosion line in the wheel tracks where the soil was compacted. This study showed that grass cover in a vineyard was not necessarily sufficient to reduce surface runoff and prevent soil erosion. To be effective, the grass cover must be dense enough in the wheel tracks of agricultural machinery to avoid runoff coefficients close to those achieved with bare soil.

Potential Predictability and Prediction Skill for Southern Peru Summertime Rainfall

NASA Astrophysics Data System (ADS)

WU, S.; Notaro, M.; Vavrus, S. J.; Mortensen, E.; Block, P. J.; Montgomery, R. J.; De Pierola, J. N.; Sanchez, C.

2016-12-01

The central Andes receive over 50% of annual climatological rainfall during the short period of January-March. This summertime rainfall exhibits strong interannual and decadal variability, including severe drought events that incur devastating societal impacts and cause agricultural communities and mining facilities to compete for limited water resources. An improved seasonal prediction skill of summertime rainfall would aid in water resource planning and allocation across the water-limited southern Peru. While various underlying mechanisms have been proposed by past studies for the drivers of interannual variability in summertime rainfall across southern Peru, such as the El Niño-Southern Oscillation (ENSO), Madden Julian Oscillation (MJO), and extratropical forcings, operational forecasts continue to be largely based on rudimentary ENSO-based indices, such as NINO3.4, justifying further exploration of predictive skill. In order to bridge this gap between the understanding of driving mechanisms and the operational forecast, we performed systematic studies on the predictability and prediction skill of southern Peru summertime rainfall by constructing statistical forecast models using best available weather station and reanalysis datasets. At first, by assuming the first two empirical orthogonal functions (EOFs) of summertime rainfall are predictable, the potential predictability skill was evaluated for southern Peru. Then, we constructed a simple regression model, based on the time series of tropical Pacific sea-surface temperatures (SSTs), and a more advanced Linear Inverse Model (LIM), based on the EOFs of tropical ocean SSTs and large-scale atmosphere variables from reanalysis. Our results show that the LIM model consistently outperforms the more rudimentary regression models on the forecast skill of domain averaged precipitation index and individual station indices. The improvement of forecast correlation skill ranges from 10% to over 200% for different stations. Further analysis shows that this advantage of LIM is likely to arise from its representation of local zonal winds and the position of Intertropical Convergence Zone (ITCZ).

Evidence of Physiological Decoupling from Grassland Ecosystem Drivers by an Encroaching Woody Shrub

PubMed Central

Nippert, Jesse B.; Ocheltree, Troy W.; Orozco, Graciela L.; Ratajczak, Zak; Ling, Bohua; Skibbe, Adam M.

2013-01-01

Shrub encroachment of grasslands is a transformative ecological process by which native woody species increase in cover and frequency and replace the herbaceous community. Mechanisms of encroachment are typically assessed using temporal data or experimental manipulations, with few large spatial assessments of shrub physiology. In a mesic grassland in North America, we measured inter- and intra-annual variability in leaf δ13C in Cornus drummondii across a grassland landscape with varying fire frequency, presence of large grazers and topographic variability. This assessment of changes in individual shrub physiology is the largest spatial and temporal assessment recorded to date. Despite a doubling of annual rainfall (in 2008 versus 2011), leaf δ13C was statistically similar among and within years from 2008-11 (range of −28 to −27‰). A topography*grazing interaction was present, with higher leaf δ13C in locations that typically have more bare soil and higher sensible heat in the growing season (upland topographic positions and grazed grasslands). Leaf δ13C from slopes varied among grazing contrasts, with upland and slope leaf δ13C more similar in ungrazed locations, while slopes and lowlands were more similar in grazed locations. In 2011, canopy greenness (normalized difference vegetation index – NDVI) was assessed at the centroid of individual shrubs using high-resolution hyperspectral imagery. Canopy greenness was highest mid-summer, likely reflecting temporal periods when C assimilation rates were highest. Similar to patterns seen in leaf δ13C, NDVI was highest in locations that typically experience lowest sensible heat (lowlands and ungrazed). The ability of Cornus drummondii to decouple leaf physiological responses from climate variability and fire frequency is a likely contributor to the increase in cover and frequency of this shrub species in mesic grassland and may be generalizable to other grasslands undergoing woody encroachment. PMID:24339950

Rainfall statistics changes in Sicily

NASA Astrophysics Data System (ADS)

Arnone, E.; Pumo, D.; Viola, F.; Noto, L. V.; La Loggia, G.

2013-07-01

Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles that can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood-prone areas. In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends, while for longer durations the trends are mainly negative. Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the nonparametric Mann-Kendall test. In particular, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration, while daily rainfall properties have been analyzed in terms of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations, especially for 1 h rainfall duration. Conversely, precipitation events of long durations have exhibited a decreased trend. Increase in short-duration precipitation has been observed especially in stations located along the coastline; however, no clear and well-defined spatial pattern has been outlined by the results. Outcomes of analysis for daily rainfall properties have showed that heavy-torrential precipitation events tend to be more frequent at regional scale, while light rainfall events exhibited a negative trend at some sites. Values of total annual precipitation events confirmed a significant negative trend, mainly due to the reduction during the winter season.

Monitoring of Structural Components and Water Balance as AN Aid to Wetland Management Using Geospatial Techniques - a Case Study for Nalsarovar Lake, Gujarat

NASA Astrophysics Data System (ADS)

Murthy, T. V. R.; Panigrahy, S.

2011-09-01

The hydrologic variability greatly influences the structural components of wetlands that have a great bearing on habitats for avifauna, aquatic fauna including fish etc. This paper highlights the results of a study carried out to derive changes in open-water and vegetation, and also water balance for Nalsarovar Lake, Gujarat. MODIS 8-day composite data for three consecutive years viz 2002/03, 2003/04 and 2004/05 were used to study the seasonal and inter annual dynamics of water regime in the lake. Digital elevation model derived using Shuttle Radar Topographic Mission data with interpolated bottom topography was used to generate elevation contours and compute water volume from water spread data. The reference data of 2002 (drought year) shows the maximum extent of wetland to be 8.06 km2 with emergent vegetation of recorded as 2.36 km2 and open-water as 5.70 km2. The rainfall has an impact on the preferred habitat availability for various species of avifauna and it is noted that emergent vegetation present in the lake completely dried up by summer 2002, a rainfall deficit year but revived again in the preceding year i.e. 2003 which was a good rainfall year with 46.68 km2 under emergent vegetation and 61.96 km2 under open-water. The 2002 being a drought year has shown very low reference storage (0.256 MCM), which has shown a gradual decrease in the storage to 0.00019 MCM in March 2003. The reference storage also registered a steep increase to 18.165 MCM in October 2003 and decreased 1.264 MCM in March 2004. From this study it is evident that water level of about 9 m elevation at the end of the rainy season is found to be optimal for maintaining various habitats that in turn support the avifauna for the rest of the lean period.

Understanding spatio-temporal variation of vegetation phenology and rainfall seasonality in the monsoon Southeast Asia.

PubMed

Suepa, Tanita; Qi, Jiaguo; Lawawirojwong, Siam; Messina, Joseph P

2016-05-01

The spatio-temporal characteristics of remote sensing are considered to be the primary advantage in environmental studies. With long-term and frequent satellite observations, it is possible to monitor changes in key biophysical attributes such as phenological characteristics, and relate them to climate change by examining their correlations. Although a number of remote sensing methods have been developed to quantify vegetation seasonal cycles using time-series of vegetation indices, there is limited effort to explore and monitor changes and trends of vegetation phenology in the Monsoon Southeast Asia, which is adversely affected by changes in the Asian monsoon climate. In this study, MODIS EVI and TRMM time series data, along with field survey data, were analyzed to quantify phenological patterns and trends in the Monsoon Southeast Asia during 2001-2010 period and assess their relationship with climate change in the region. The results revealed a great regional variability and inter-annual fluctuation in vegetation phenology. The phenological patterns varied spatially across the region and they were strongly correlated with climate variations and land use patterns. The overall phenological trends appeared to shift towards a later and slightly longer growing season up to 14 days from 2001 to 2010. Interestingly, the corresponding rainy season seemed to have started earlier and ended later, resulting in a slightly longer wet season extending up to 7 days, while the total amount of rainfall in the region decreased during the same time period. The phenological shifts and changes in vegetation growth appeared to be associated with climate events such as EL Niño in 2005. Furthermore, rainfall seemed to be the dominant force driving the phenological changes in naturally vegetated areas and rainfed croplands, whereas land use management was the key factor in irrigated agricultural areas. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Large-scale climatic phenomena drive fluctuations in macroinvertebrate assemblages in lowland tropical streams, Costa Rica: The importance of ENSO events in determining long-term (15y) patterns

PubMed Central

Ramírez, Alonso; Pringle, Catherine M.

2018-01-01

Understanding how environmental variables influence the distribution and density of organisms over relatively long temporal scales is a central question in ecology given increased climatic variability (e.g., precipitation, ENSO events). The primary goal of our study was to evaluate long-term (15y time span) patterns of climate, as well as environmental parameters in two Neotropical streams in lowland Costa Rica, to assess potential effects on aquatic macroinvertebrates. We also examined the relative effects of an 8y whole-stream P-enrichment experiment on macroinvertebrate assemblages against the backdrop of this long-term study. Climate, environmental variables and macroinvertebrate samples were measured monthly for 7y and then quarterly for an additional 8y in each stream. Temporal patterns in climatic and environmental variables showed high variability over time, without clear inter-annual or intra-annual patterns. Macroinvertebrate richness and abundance decreased with increasing discharge and was positively related to the number of days since the last high discharge event. Findings show that fluctuations in stream physicochemistry and macroinvertebrate assemblage structure are ultimately the result of large-scale climatic phenomena, such as ENSO events, while the 8y P-enrichment did not appear to affect macroinvertebrates. Our study demonstrates that Neotropical lowland streams are highly dynamic and not as stable as is commonly presumed, with high intra- and inter-annual variability in environmental parameters that change the structure and composition of freshwater macroinvertebrate assemblages. PMID:29420548

Connecting Digital Repeat Photography to Ecosystem Fluxes in Inland Pacific Northwest, US Cropping Systems

NASA Astrophysics Data System (ADS)

Russell, E.; Chi, J.; Waldo, S.; Pressley, S. N.; Lamb, B. K.; Pan, W.

2017-12-01

Diurnal and seasonal gas fluxes vary by crop growth stage. Digital cameras are increasingly being used to monitor inter-annual changes in vegetation phenology in a variety of ecosystems. These cameras are not designed as scientific instruments but the information they gather can add value to established measurement techniques (i.e. eddy covariance). This work combined deconstructed digital images with eddy covariance data from five agricultural sites (1 fallow, 4 cropped) in the inland Pacific Northwest, USA. The data were broken down with respect to crop stage and management activities. The fallow field highlighted the camera response to changing net radiation, illumination, and rainfall. At the cropped sites, the net ecosystem exchange, gross primary production, and evapotranspiration were correlated with the greenness and redness values derived from the images over the growing season. However, the color values do not change quickly enough to respond to day-to-day variability in the flux exchange as the two measurement types are based on different processes. The management practices and changes in phenology through the growing season were not visible within the camera data though the camera did capture the general evolution of the ecosystem fluxes.

Stochastic Generation of Monthly Rainfall Data

NASA Astrophysics Data System (ADS)

Srikanthan, R.

2009-03-01

Monthly rainfall data is generally needed in the simulation of water resources systems, and in the estimation of water yield from large catchments. Monthly streamflow data generation models are usually applied to generate monthly rainfall data, but this presents problems for most regions, which have significant months of no rainfall. In an earlier study, Srikanthan et al. (J. Hydrol. Eng., ASCE 11(3) (2006) 222-229) recommended the modified method of fragments to disaggregate the annual rainfall data generated by a first-order autoregressive model. The main drawback of this approach is the occurrence of similar patterns when only a short length of historic data is available. Porter and Pink (Hydrol. Water Res. Symp. (1991) 187-191) used synthetic fragments from a Thomas-Fiering monthly model to overcome this drawback. As an alternative, a new two-part monthly model is nested in an annual model to generate monthly rainfall data which preserves both the monthly and annual characteristics. This nested model was applied to generate rainfall data from seven rainfall stations located in eastern and southern parts of Australia, and the results showed that the model performed satisfactorily.

A method to assess the inter-annual weather-dependent variability in air pollution concentration and deposition based on weather typing

NASA Astrophysics Data System (ADS)

Pleijel, Håkan; Grundström, Maria; Karlsson, Gunilla Pihl; Karlsson, Per Erik; Chen, Deliang

2016-02-01

Annual anomalies in air pollutant concentrations, and deposition (bulk and throughfall) of sulphate, nitrate and ammonium, in the Gothenburg region, south-west Sweden, were correlated with optimized linear combinations of the yearly frequency of Lamb Weather Types (LWTs) to determine the extent to which the year-to-year variation in pollution exposure can be partly explained by weather related variability. Air concentrations of urban NO2, CO, PM10, as well as O3 at both an urban and a rural monitoring site, and the deposition of sulphate, nitrate and ammonium for the period 1997-2010 were included in the analysis. Linear detrending of the time series was performed to estimate trend-independent anomalies. These estimated anomalies were subtracted from observed annual values. Then the statistical significance of temporal trends with and without LWT adjustment was tested. For the pollutants studied, the annual anomaly was well correlated with the annual LWT combination (R2 in the range 0.52-0.90). Some negative (annual average [NO2], ammonia bulk deposition) or positive (average urban [O3]) temporal trends became statistically significant (p < 0.05) when the LWT adjustment was applied. In all the cases but one (NH4 throughfall, for which no temporal trend existed) the significance of temporal trends became stronger with LWT adjustment. For nitrate and ammonium, the LWT based adjustment explained a larger fraction of the inter-annual variation for bulk deposition than for throughfall. This is probably linked to the longer time scale of canopy related dry deposition processes influencing throughfall being explained to a lesser extent by LWTs than the meteorological factors controlling bulk deposition. The proposed novel methodology can be used by authorities responsible for air pollution management, and by researchers studying temporal trends in pollution, to evaluate e.g. the relative importance of changes in emissions and weather variability in annual air pollution exposure.

Review and meta-analysis of trends in precipitation regime in Italy

NASA Astrophysics Data System (ADS)

Caporali, Enrica; Chiarello, Valentina; Defina, Ilaria; Fatichi, Simone

2017-04-01

Research to detect changes in climatic variables has become a topic of particular interest to observe signals of climate change as well as to understand drivers of modifications in water resources availability and suggest management adaptations. We specifically focus on Italy, outlining the "state of the art" of the Italian precipitation regime through a review of 46 published studies on rainfall trend analyses. The aim is to combine a large body of knowledge in a single review and to explain the main patterns of rainfall changes occurred in the last decades. The review results are analyzed for the entire Italian peninsula and separately for three macro areas: North, Central and South&Islands. The attention is focused on three indexes at the annual and seasonal scale: mean Total Precipitation (TP), number of Wet Days (WDs) and Precipitation Intensity (PI). Two other aspects are briefly investigated: drought and extreme rainfall events. Different geographic areas, time series length and number of stations, are taken into account using a "weight factor Fi". Subsequently, for each index, findings in terms of increasing or decreasing trends are collected into five principal categories: Negative (N), Negative Significant (NS), Positive (P), Positive Significant (PS), and No Trend (NT). Overall, there is an agreement about the tendency of the WDs that are decreasing on the whole Italy, with some discrepancies regarding the spring and the summer seasons. This is substantially in agreement with the tendency of the TP, especially at annual scale where the presence of a decreasing trend is detected. An opposite behavior is detected for PI, which increases both on an annual and on a seasonal basis. It is worth to point out that PI is analyzed just in few studies and it is strongly influenced on the classification in precipitation intensity intervals. A general finding is that signal to noise ratio on precipitation metrics is quite low, which hampers a clear definition of changes in rainfall occurred in Italy, especially for extreme events the large variability in space and time precludes robust conclusions despite the long-term records available.

Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon

NASA Astrophysics Data System (ADS)

Varikoden, Hamza; Revadekar, J. V.

2018-03-01

Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979-2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude-longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.

Sensitivity of soil respiration to variability in soil moisture and temperature in a humid tropical forest

Treesearch

Tana Wood; M. Detto; W.L. Silver

2013-01-01

Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal...

Modeling the influence of precipitation and nitrogen deposition on forest understory fuel connectivity in Sierra Nevada mixed-conifer forest

Treesearch

M. Hurteau; M. North; T. Foines

2009-01-01

Climate change models for California’s Sierra Nevada predict greater inter-annual variability in precipitation over the next 50 years. These increases in precipitation variability coupled with increases in nitrogen deposition fromfossil fuel consumption are likely to result in increased productivity levels and significant increases in...

A Moored System for Understanding the Temporal Variability of Prey Fields of Deep Diving Predators off Cape Hatteras and Response to Gulf Stream Fronts

DTIC Science & Technology

2015-09-30

Number: N000141310686 http://superpod.ml.duke.edu/ LONG-TERM GOALS Fisheries acoustics are routinely used for biomass and abundance surveys and...will be required every 10-12 months), allowing us to address the seasonality and the inter-annual variability in prey biomass and density in

Time variable eddy mixing in the global Sea Surface Salinity maxima

NASA Astrophysics Data System (ADS)

Busecke, J. J. M.; Abernathey, R.; Gordon, A. L.

2016-12-01

Lateral mixing by mesoscale eddies is widely recognized as a crucial mechanism for the global ocean circulation and the associated heat/salt/tracer transports. The Salinity in the Upper Ocean Processes Study (SPURS) confirmed the importance of eddy mixing for the surface salinity fields even in the center of the subtropical gyre of the North Atlantic. We focus on the global salinity maxima due to their role as indicators for global changes in the hydrological cycle as well as providing the source water masses for the shallow overturning circulation. We introduce a novel approach to estimate the contribution of eddy mixing to the global sea surface salinity maxima. Using a global 2D tracer experiments in a 1/10 degree MITgcm setup driven by observed surface velocities, we analyze the effect of eddy mixing using a water mass framework, thus focussing on the diffusive flux across surface isohalines. This enables us to diagnose temporal variability on seasonal to inter annual time scales, revealing regional differences in the mechanism causing temporal variability.Sensitivity experiments with various salinity backgrounds reveal robust inter annual variability caused by changes in the surface velocity fields potentially forced by large scale climate.

Early-Holocene intensified Indian summer monsoon and its impact on vegetation: study based on hydrogen and carbon isotope values in long chain alkane from relict lake sediments in the Central Himalaya

NASA Astrophysics Data System (ADS)

Sanyal, P.; Ghosh, S.; Bhushan, R.; Juyal, N.

2017-12-01

The early Holocene was characterized by intensified monsoon, however none of the paleoclimatic records showed the magnitude required to shape the observed landform in the Ganges plain and sediment discharge in the Bay of Bengal. The Tropical Rainfall Measurement Mission data suggests that the Central Himalaya ( 2 km altitude) is characterized by high rainfall and hence paleoclimate proxies from this region would provide excellent opportunity to reconstruct the Holocene monsoon. An attempt has been made, for the first time, to reconstruct the Holocene monsoon using n-alkane δDC29 values of lake sediments from Benital area in the Central Himalaya which receives ca. 80% of the mean annual rainfall during summer monsoon. The n-alkane δDC29 values indicated that early Holocene (ca. 9 ka) was characterised by a wet phase with 70% increase in the rainfall followed by the dry middle-late Holocene which is in agreement with existing continental records. However, the change in intensity as inferred in the present study is maximum compared to the existing records. The comparison of δDC29values and the solar insolation data at 30 °N latitude suggested that migration of the Inter Tropical Convergence Zone controlled the variation in monsoonal rainfall. Comparison with the modern plants, the δ13CC29 values indicated that during ca. pre and post 7 ka the lake catchment was dominated by woody and non-woody plants, respectively. The cross plot between δDC29 and δ13CC29 indicated that at higher rainfall, the δ13CC29 values of catchment vegetation were less-responsive.

Characterizing rainfall of hot arid region by using time-series modeling and sustainability approaches: a case study from Gujarat, India

NASA Astrophysics Data System (ADS)

Machiwal, Deepesh; Kumar, Sanjay; Dayal, Devi

2016-05-01

This study aimed at characterization of rainfall dynamics in a hot arid region of Gujarat, India by employing time-series modeling techniques and sustainability approach. Five characteristics, i.e., normality, stationarity, homogeneity, presence/absence of trend, and persistence of 34-year (1980-2013) period annual rainfall time series of ten stations were identified/detected by applying multiple parametric and non-parametric statistical tests. Furthermore, the study involves novelty of proposing sustainability concept for evaluating rainfall time series and demonstrated the concept, for the first time, by identifying the most sustainable rainfall series following reliability ( R y), resilience ( R e), and vulnerability ( V y) approach. Box-whisker plots, normal probability plots, and histograms indicated that the annual rainfall of Mandvi and Dayapar stations is relatively more positively skewed and non-normal compared with that of other stations, which is due to the presence of severe outlier and extreme. Results of Shapiro-Wilk test and Lilliefors test revealed that annual rainfall series of all stations significantly deviated from normal distribution. Two parametric t tests and the non-parametric Mann-Whitney test indicated significant non-stationarity in annual rainfall of Rapar station, where the rainfall was also found to be non-homogeneous based on the results of four parametric homogeneity tests. Four trend tests indicated significantly increasing rainfall trends at Rapar and Gandhidham stations. The autocorrelation analysis suggested the presence of persistence of statistically significant nature in rainfall series of Bhachau (3-year time lag), Mundra (1- and 9-year time lag), Nakhatrana (9-year time lag), and Rapar (3- and 4-year time lag). Results of sustainability approach indicated that annual rainfall of Mundra and Naliya stations ( R y = 0.50 and 0.44; R e = 0.47 and 0.47; V y = 0.49 and 0.46, respectively) are the most sustainable and dependable compared with that of other stations. The highest values of sustainability index at Mundra (0.120) and Naliya (0.112) stations confirmed the earlier findings of R y- R e- V y approach. In general, annual rainfall of the study area is less reliable, less resilient, and moderately vulnerable, which emphasizes the need of developing suitable strategies for managing water resources of the area on sustainable basis. Finally, it is recommended that multiple statistical tests (at least two) should be used in time-series modeling for making reliable decisions. Moreover, methodology and findings of the sustainability concept in rainfall time series can easily be adopted in other arid regions of the world.

Inter-annual variability of the Mediterranean thermohaline circulation in Med-CORDEX simulations

NASA Astrophysics Data System (ADS)

Vittoria Struglia, Maria; Adani, Mario; Carillo, Adriana; Pisacane, Giovanna; Sannino, Gianmaria; Beuvier, Jonathan; Lovato, Tomas; Sevault, Florence; Vervatis, Vassilios

2016-04-01

Recent atmospheric reanalysis products, such as ERA40 and ERA-interim, and their regional dynamical downscaling prompted the HyMeX/Med-CORDEX community to perform hind-cast simulations of the Mediterranean Sea, giving the opportunity to evaluate the response of different ocean models to a realistic inter-annual atmospheric forcing. Ocean numerical modeling studies have been steadily improving over the last decade through hind-cast processing, and are complementary to observations in studying the relative importance of the mechanisms playing a role in ocean variability, either external forcing or internal ocean variability. This work presents a review and an inter-comparison of the most recent hind-cast simulations of the Mediterranean Sea Circulation, produced in the framework of the Med-CORDEX initiative, at resolutions spanning from 1/8° to 1/16°. The richness of the simulations available for this study is exploited to address the effects of increasing resolution, both of models and forcing, the initialization procedure, and the prescription of the atmospheric boundary conditions, which are particularly relevant in order to model a realistic THC, in the perspective of fully coupled regional ocean-atmosphere models. The mean circulation is well reproduced by all the simulations. However, it can be observed that the horizontal resolution of both atmospheric forcing and ocean model plays a fundamental role in the reproduction of some specific features of both sub-basins and important differences can be observed among low and high resolution atmosphere forcing. We analyze the mean circulation on both the long-term and decadal time scale, and the represented inter-annual variability of intermediate and deep water mass formation processes in both the Eastern and Western sub-basins, finding that models agree with observations in correspondence of specific events, such as the 1992-1993 Eastern Mediterranean Transient, and the 2005-2006 event in the Gulf of Lion. Long-term trends of the hydrological properties have been investigated at sub-basin scale and have been interpreted in terms of response to forcing and boundary conditions, detectable differences resulting mainly due either to the different initialization and spin up procedure or to the different prescription of Atlantic boundary conditions.

High-frequency DOC and nitrate measurements provide new insights into their export and their relationships to rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Schwab, Michael; Klaus, Julian; Pfister, Laurent; Weiler, Markus

2015-04-01

Over the past decades, stream sampling protocols for environmental tracers were often limited by logistical and technological constraints. Long-term sampling programs would typically rely on weekly sampling campaigns, while high-frequency sampling would remain restricted to a few days or hours at best. We stipulate that the currently predominant sampling protocols are too coarse to capture and understand the full amplitude of rainfall-runoff processes and its relation to water quality fluctuations. Weekly sampling protocols are not suited to get insights into the hydrological system during high flow conditions. Likewise, high frequency measurements of a few isolated events do not allow grasping inter-event variability in contributions and processes. Our working hypothesis is based on the potential of a new generation of field-deployable instruments for measuring environmental tracers at high temporal frequencies over an extended period. With this new generation of instruments we expect to gain new insights into rainfall-runoff dynamics, both at intra- and inter-event scales. Here, we present the results of one year of DOC and nitrate measurements with the field deployable UV-Vis spectrometer spectro::lyser (scan Messtechnik GmbH). The instrument measures the absorption spectrum from 220 to 720 nm in situ and at high frequencies and derives DOC and nitrate concentrations. The measurements were carried out at 15 minutes intervals in the Weierbach catchment (0.47 km2) in Luxemburg. This fully forested catchment is characterized by cambisol soils and fractured schist as underlying bedrock. The time series of DOC and nitrate give insights into the high frequency dynamics of stream water. Peaks in DOC concentrations are closely linked to discharge peaks that occur during or right after a rainfall event. Those first discharge peaks can be linked to fast near surface runoff processes and are responsible for a remarkable amount of DOC export. A special characterisation of the Weierbach catchment are the delayed second peaks a few days after the rainfall event. Nitrate concentrations are following this second peak. We assume that this delayed response is going back to subsurface or upper groundwater flows, with nitrate enriched water. On an inter-event scale during low flow / base flow conditions, we observe interesting diurnal patterns of both DOC and nitrate concentrations. Overall, the long-term high-frequency measurements of DOC and nitrate provide us the opportunity to separate different rainfall-runoff processes and link the amount of DOC and nitrate export to them to quantify the overall relevance of the different processes.

Analysis of causal factors of fire regimes in Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Palumbo, I.; Lehsten, V.; Balzter, H.

2009-04-01

Wildfires are a wide spread global phenomenon. Their activity peaks in the tropical savannas, especially in the African continent, where fires are a key component of ecosystem dynamics. Fires affect the ecological balance between trees and grasses in savannas with concomitant effects on biodiversity, soil fertility and biogeochemical cycles. Large amounts of trace greenhouse gases and aerosols from wildfires are emitted each year in Africa, but the underlying dynamics of such wildfires and what drives them remain poorly understood. In general terms, the magnitude and the inter-annual variability of fire activity depend on fire frequency and its spatial distribution, also referred to as fire regimes. These are, in turn, determined by the environmental conditions at the time of burning, ignition sources, fuel type, fuel availability, and its moisture content. This study analysed the driving factors of fire regimes at continental level for a period of 5 years (2002-2007). We considered the following variables: climate (rainfall, temperature, humidity), population density, land cover and the burned areas derived from the MODIS MCD45A1 product at 500m resolution. GIS and multi-variate regression techniques were used to analyse the data. Understanding fire driving factors is fundamentally important for developing process-based simulation models of fire occurrence under future climate and environmental change scenarios. This is particularly relevant if we consider that the IPCC 4th Assessment report indicates that a change in the rainfall patterns has been observed in the last 40 years over most of Africa with a decrease of precipitation around 20-40% in West Africa and more intense and widespread droughts in Southern Africa. The simultaneous increase of temperatures can potentially lead to higher fire occurrence and modify the current fire regimes. This work contributes to climate change research with new insights and understanding about how fires are controlled by bioclimatic and demographic factors in African ecosystems.

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.

Landscape structure and climate influences on hydrologic response

NASA Astrophysics Data System (ADS)

Nippgen, Fabian; McGlynn, Brian L.; Marshall, Lucy A.; Emanuel, Ryan E.

2011-12-01

Climate variability and catchment structure (topography, geology, vegetation) have a significant influence on the timing and quantity of water discharged from mountainous catchments. How these factors combine to influence runoff dynamics is poorly understood. In this study we linked differences in hydrologic response across catchments and across years to metrics of landscape structure and climate using a simple transfer function rainfall-runoff modeling approach. A transfer function represents the internal catchment properties that convert a measured input (rainfall/snowmelt) into an output (streamflow). We examined modeled mean response time, defined as the average time that it takes for a water input to leave the catchment outlet from the moment it reaches the ground surface. We combined 12 years of precipitation and streamflow data from seven catchments in the Tenderfoot Creek Experimental Forest (Little Belt Mountains, southwestern Montana) with landscape analyses to quantify the first-order controls on mean response times. Differences between responses across the seven catchments were related to the spatial variability in catchment structure (e.g., slope, flowpath lengths, tree height). Annual variability was largely a function of maximum snow water equivalent. Catchment averaged runoff ratios exhibited strong correlations with mean response time while annually averaged runoff ratios were not related to climatic metrics. These results suggest that runoff ratios in snowmelt dominated systems are mainly controlled by topography and not by climatic variability. This approach provides a simple tool for assessing differences in hydrologic response across diverse watersheds and climate conditions.

Micro-phytoplankton community structure in the coastal upwelling zone off Concepción (central Chile): Annual and inter-annual fluctuations in a highly dynamic environment

NASA Astrophysics Data System (ADS)

Anabalón, V.; Morales, C. E.; González, H. E.; Menschel, E.; Schneider, W.; Hormazabal, S.; Valencia, L.; Escribano, R.

2016-12-01

An intensification of upwelling-favorable winds in recent decades has been detected in some of the main eastern boundary current systems, especially at higher latitudes, but the response of coastal phytoplankton communities in the Humboldt Current System (HCS) remains unknown. At higher latitudes in the HCS (35-40°S), strong seasonality in wind-driven upwelling during spring-summer coincides with an annual increase in coastal chlorophyll-a and primary production, and a dominance of micro-phytoplankton. In order to understand the effects of potential upwelling intensification on the micro-phytoplankton community in this region, annual and inter-annual variability in its structure (total and taxa-specific abundance and biomass) and its association with oceanographic fluctuations were analyzed using in situ time series data (2002-2009) from a shelf station off Concepcion (36.5°S). At the annual scale, total mean abundance and biomass, attributed to a few dominant diatom taxa, were at least one order of magnitude greater during spring-summer than autumn-winter, in association with changes in upwelling and surface salinity and temperature, whereas macro-nutrient concentrations remained relatively high all the year. At the inter-annual scale, total abundance and biomass decreased during the upwelling season of the 2006-2009 period compared with the 2002-2006 period, notably due to lower abundances of Skeletonema and Leptocylindrus, but the relative dominance of a few taxa was maintained. The 2006-2009 period was characterized by higher upwelling intensity, colder and higher salinity waters, and changes in nutrient concentrations and ratios compared with the first period. The inter-annual changes in the micro-phytoplankton community were mostly associated with changes in surface salinity and temperature (changes in upwelling intensity) but also with changes in Si/N and N/P, which relate to other land-derived processes.

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

PubMed

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

An analysis of the breakdown of paper products (toilet paper, tissues and tampons) in natural environments, Tasmania, Australia.

PubMed

Bridle, Kerry L; Kirkpatrick, J B

2005-01-01

An examination of the relative breakdown rates of unused toilet paper, facial tissues and tampons was undertaken in nine different environments typical of Tasmanian natural areas. Bags of the paper products (toilet paper, facial tissues, tampons) were buried for periods of 6, 12 and 24 months at depths of 5 and 15 cm. A nutrient solution simulating human body wastes was added to half of the samples, to test the hypothesis that the addition of nutrients would enhance the breakdown of paper products buried in the soil. Mean annual rainfall was the most important measured variable determining mean breakdown in the nutrient addition treatment between sites, with high rainfall sites (mean annual rainfall of greater than 650 mm) recording less decayed products than the drier sites (mean annual rainfall of 500-650 mm). Temperature and soil organic content were important influences on the breakdown of the unfertilised products. Toilet paper and tissues decayed more readily than tampons. Nutrient addition enhanced decay for all products across all sites. Depth of burial was not important in determining the degree to which products decayed. In alpine environments, burial under rocks at the surface did not increase the speed of decay of any product. The Western Alpine site, typical of alpine sites in the Tasmanian Wilderness World Heritage Area, showed very little decay over the two-year period, even for nutrient enhanced products. Management prescriptions should be amended to dissuade people from depositing human toilet waste in the extreme (montane to alpine) environments in western Tasmania. Tampons should continue to be carried out as currently prescribed.

How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

NASA Astrophysics Data System (ADS)

Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

2013-02-01

SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.

On interception modelling of a lowland coastal rainforest in northern Queensland, Australia

NASA Astrophysics Data System (ADS)

Wallace, Jim; McJannet, Dave

2006-10-01

SummaryRecent studies of the water balance of tropical rainforests in northern Queensland have revealed that large fractions of rainfall, up to 30%, are intercepted by the canopy and lost as evaporation. These loss rates are much higher than those reported for continental rainforests, for example, in the Amazon basin, where interception is around 9% of rainfall. Higher interception losses have been found in coastal and mountain rainforests and substantial advection of energy during rainfall is proposed to account for these results. This paper uses a process based model of interception to analyse the interception losses at Oliver Creek, a lowland coastal rainforest site in northern Queensland with a mean annual rainfall of 3952 mm. The observed interception loss of 25% of rainfall for the period August 2001 to January 2004 can be reproduced by the model with a suitable choice of the three key controlling variables, the canopy storage capacity, mean rainfall rate and mean wet canopy evaporation rate. Our analyses suggest that the canopy storage capacity of the Oliver Creek rainforest is between 3.0 and 3.5 mm, higher than reported for most other rainforests. Despite the high canopy capacity at our site, the interception losses can only be accounted for with energy advection during rainfall in the range 40-70% of the incident energy.

Rainfall variability over South-east Asia - connections with Indian monsoon and ENSO extremes: new perspectives

NASA Astrophysics Data System (ADS)

Kripalani, R. H.; Kulkarni, Ashwini

1997-09-01

Seasonal and annual rainfall data for 135 stations for periods varying from 25 to 125 years are utilized to investigate and understand the interannual and short-term (decadal) climate variability over the South-east Asian domain. Contemporaneous relations during the summer monsoon period (June to September) reveal that the rainfall variations over central India, north China, northern parts of Thailand, central parts of Brunei and Borneo and the Indonesian region east of 120°E vary in phase. However, the rainfall variations over the regions surrounding the South China Sea, in particular the north-west Philippines, vary in the opposite phase. Possible dynamic causes for the spatial correlation structure obtained are discussed.Based on the instrumental data available and on an objective criteria, regional rainfall anomaly time series for contiguous regions over Thailand, Malaysia, Singapore, Brunei, Indonesia and Philippines are prepared. Results reveal that although there are year-to-year random fluctuations, there are certain epochs of the above- and below-normal rainfall over each region. These epochs are not forced by the El Niño/La Nina frequencies. Near the equatorial regions the epochs tend to last for about a decade, whereas over the tropical regions, away from the Equator, epochs last for about three decades. There is no systematic climate change or trend in any of the series. Further, the impact of El Niño (La Nina) on the rainfall regimes is more severe during the below (above) normal epochs than during the above (below) normal epochs. Extreme drought/flood situations tend to occur when the epochal behaviour and the El Niño/La Nina events are phase-locked.

Tropical rainforests dominate multi-decadal variability of the global carbon cycle

NASA Astrophysics Data System (ADS)

Zhang, X.; Wang, Y. P.; Peng, S.; Rayner, P. J.; Silver, J.; Ciais, P.; Piao, S.; Zhu, Z.; Lu, X.; Zheng, X.

2017-12-01

Recent studies find that inter-annual variability of global atmosphere-to-land CO2 uptake (NBP) is dominated by semi-arid ecosystems. However, the NBP variations at decadal to multi-decadal timescales are still not known. By developing a basic theory for the role of net primary production (NPP) and heterotrophic respiration (Rh) on NBP and applying it to 100-year simulations of terrestrial ecosystem models forced by observational climate, we find that tropical rainforests dominate the multi-decadal variability of global NBP (48%) rather than the semi-arid lands (35%). The NBP variation at inter-annual timescales is almost 90% contributed by NPP, but across longer timescales is progressively controlled by Rh that constitutes the response from the NPP-derived soil carbon input (40%) and the response of soil carbon turnover rates to climate variability (60%). The NBP variations of tropical rainforests is modulated by the ENSO and the PDO through their significant influences on temperature and precipitation at timescales of 2.5-7 and 25-50 years, respectively. This study highlights the importance of tropical rainforests on the multi-decadal variability of global carbon cycle, suggesting that we need to carefully differentiate the effect of NBP long-term fluctuations associated with ocean-related climate modes on the long-term trend in land sink.