Variability and trends of wet season temperature in the Sudano-Sahelian zone and relationships with precipitation

NASA Astrophysics Data System (ADS)

Oueslati, Boutheina; Camberlin, Pierre; Zoungrana, Joël; Roucou, Pascal; Diallo, Saliou

2018-02-01

The relationships between precipitation and temperature in the central Sudano-Sahelian belt are investigated by analyzing 50 years (1959-2008) of observed temperature (Tx and Tn) and rainfall variations. At daily time-scale, both Tx and Tn show a marked decrease as a response to rainfall occurrence, with a strongest departure from normal 1 day after the rainfall event (-0.5 to -2.5 °C depending on the month). The cooling is slightly larger when heavy rainfall events (>5 mm) are considered. The temperature anomalies weaken after the rainfall event, but are still significant several days later. The physical mechanisms accounting for the temperature response to precipitation are analysed. The Tx drop is accounted for by reduced incoming solar radiation associated with increased cloud cover and increased surface evaporation following surface moistening. The effect of evaporation becomes dominant a few days after the rainfall event. The reduced daytime heat storage and the subsequent sensible heat flux result in a later negative Tn anomaly. The effect of rainfall variations on temperature is significant for long-term warming trends. The rainfall decrease experienced between 1959 and 2008 accounts for a rainy season Tx increase of 0.15 to 0.3 °C, out of a total Tx increase of 1.3 to 1.5 °C. These results have strong implications on the assessment of future temperature changes. The dampening or amplifying effects of precipitation are determined by the sign of future precipitation trends. Confidence on temperature changes under global warming partly depend on the robustness of precipitation projections.

Daily variations in weather and the relationship with physical activity and sedentary time in European 10- to 12-year-olds: The ENERGY-Project.

PubMed

Yildirim, Mine; Schoeni, Anna; Singh, Amika S; Altenburg, Teatske M; Brug, Johannes; De Bourdeaudhuij, Ilse; Kovacs, Eva; Bringolf-Isler, Bettina; Manios, Yannis; Chinapaw M, J M

2014-02-01

The aim of the study was to examine the association of daily variations in rainfall and temperature with sedentary time (ST) and physical activity (PA) in European children. Children were included from 5 countries (Belgium, Greece, Hungary, the Netherlands, Switzerland) as part of the ENERGY-project. We used cross-sectional data from 722 children aged 10-12 years (47% boys). ST and PA were measured by accelerometers for 6 consecutive days, including weekend days. Weather data were collected from online national weather reports. Multilevel regression models were used for data analyses. Maximum temperature was positively associated with light PA (β = 3.1 min/day; 95% CI = 2.4-3.8), moderate-to-vigorous PA (β = 0.6 min/day; 95% CI = 0.4-0.8), and average PA [β = 4.1 counts per minute (cpm); 95% CI = 1.6-6.5, quadratic relationship]. Rainfall was inversely and quadratically associated with light PA (β = -1.3 min/day; 95% CI = -1.9 to -0.6), moderate-to-vigorous PA (β = -0.6 min/day; 95% CI = -0.8 to -0.3), and average PA (β = -1.6 cpm; 95% CI = -2.2 to -0.9). Maximum temperature was not significantly associated with ST (β = -0.2 min/day; 95% CI = -1.0 to 0.6), while rainfall was positively associated with ST (β = 0.9 min/day; 95% CI = 0.6-1.3). The current study shows that temperature and rainfall are significantly associated with PA and ST in 10- to 12-year-old European children.

Identification of key climatic factors regulating the transport of pesticides in leaching and to tile drains.

PubMed

Nolan, Bernard T; Dubus, Igor G; Surdyk, Nicolas; Fowler, Hayley J; Burton, Aidan; Hollis, John M; Reichenberger, Stefan; Jarvis, Nicholas J

2008-09-01

Key climatic factors influencing the transport of pesticides to drains and to depth were identified. Climatic characteristics such as the timing of rainfall in relation to pesticide application may be more critical than average annual temperature and rainfall. The fate of three pesticides was simulated in nine contrasting soil types for two seasons, five application dates and six synthetic weather data series using the MACRO model, and predicted cumulative pesticide loads were analysed using statistical methods. Classification trees and Pearson correlations indicated that simulated losses in excess of 75th percentile values (0.046 mg m(-2) for leaching, 0.042 mg m(-2) for drainage) generally occurred with large rainfall events following autumn application on clay soils, for both leaching and drainage scenarios. The amount and timing of winter rainfall were important factors, whatever the application period, and these interacted strongly with soil texture and pesticide mobility and persistence. Winter rainfall primarily influenced losses of less mobile and more persistent compounds, while short-term rainfall and temperature controlled leaching of the more mobile pesticides. Numerous climatic characteristics influenced pesticide loss, including the amount of precipitation as well as the timing of rainfall and extreme events in relation to application date. Information regarding the relative influence of the climatic characteristics evaluated here can support the development of a climatic zonation for European-scale risk assessment for pesticide fate.

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.

Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System) for Sicily

NASA Astrophysics Data System (ADS)

Brigandì, Giuseppina; Tito Aronica, Giuseppe; Bonaccorso, Brunella; Gueli, Roberto; Basile, Giuseppe

2017-09-01

The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall-runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002-2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce warning on a daily basis for the entire region.

Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting

NASA Astrophysics Data System (ADS)

Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.

2008-07-01

SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

Rainfall model investigation and scenario analyses of the effect of government reforestation policy on seasonal rainfalls: A case study from Northern Thailand

NASA Astrophysics Data System (ADS)

Duangdai, Eakkapong; Likasiri, Chulin

2017-03-01

In this work, 4 models for predicting rainfall amounts are investigated and compared using Northern Thailand's seasonal rainfall data for 1973-2008. Two models, global temperature, forest area and seasonal rainfall (TFR) and modified TFR based on a system of differential equations, give the relationships between global temperature, Northern Thailand's forest cover and seasonal rainfalls in the region. The other two models studied are time series and Autoregressive Moving Average (ARMA) models. All models are validated using the k-fold cross validation method with the resulting errors being 0.971233, 0.740891, 2.376415 and 2.430891 for time series, ARMA, TFR and modified TFR models, respectively. Under Business as Usual (BaU) scenario, seasonal rainfalls in Northern Thailand are projected through the year 2020 using all 4 models. TFR and modified TFR models are also used to further analyze how global temperature rise and government reforestation policy affect seasonal rainfalls in the region. Rainfall projections obtained via the two models are also compared with those from the International Panel on Climate Change (IPCC) under IS92a scenario. Results obtained through a mathematical model for global temperature, forest area and seasonal rainfall show that the higher the forest cover, the less fluctuation there is between rainy-season and summer rainfalls. Moreover, growth in forest cover also correlates with an increase in summer rainfalls. An investigation into the relationship between main crop productions and rainfalls in dry and rainy seasons indicates that if the rainy-season rainfall is high, that year's main-crop rice production will decrease but the second-crop rice, maize, sugarcane and soybean productions will increase in the following year.

Impact of climate change on runoff in Lake Urmia basin, Iran

NASA Astrophysics Data System (ADS)

Sanikhani, Hadi; Kisi, Ozgur; Amirataee, Babak

2018-04-01

Investigation of the impact of climate change on water resources is very necessary in dry and arid regions. In the first part of this paper, the climate model Long Ashton Research Station Weather Generator (LARS-WG) was used for downscaling climate data including rainfall, solar radiation, and minimum and maximum temperatures. Two different case studies including Aji-Chay and Mahabad-Chay River basins as sub-basins of Lake Urmia in the northwest part of Iran were considered. The results indicated that the LARS-WG successfully downscaled the climatic variables. By application of different emission scenarios (i.e., A1B, A2, and B1), an increasing trend in rainfall and a decreasing trend in temperature were predicted for both the basins over future time periods. In the second part of this paper, gene expression programming (GEP) was applied for simulating runoff of the basins in the future time periods including 2020, 2055, and 2090. The input combination including rainfall, solar radiation, and minimum and maximum temperatures in current and prior time was selected as the best input combination with highest predictive power for runoff prediction. The results showed that the peak discharge will decrease by 50 and 55.9% in 2090 comparing with the baseline period for the Aji-Chay and Mahabad-Chay basins, respectively. The results indicated that the sustainable adaptation strategies are necessary for these basins for protection of water resources in future.

Improved interpolation of meteorological forcings for hydrologic applications in a Swiss Alpine region

NASA Astrophysics Data System (ADS)

Tobin, Cara; Nicotina, Ludovico; Parlange, Marc B.; Berne, Alexis; Rinaldo, Andrea

2011-04-01

SummaryThis paper presents a comparative study on the mapping of temperature and precipitation fields in complex Alpine terrain. Its relevance hinges on the major impact that inadequate interpolations of meteorological forcings bear on the accuracy of hydrologic predictions regardless of the specifics of the models, particularly during flood events. Three flood events measured in the Swiss Alps are analyzed in detail to determine the interpolation methods which best capture the distribution of intense, orographically-induced precipitation. The interpolation techniques comparatively examined include: Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and Kriging with External Drift (KED). Geostatistical methods rely on a robust anisotropic variogram for the definition of the spatial rainfall structure. Results indicate that IDW tends to significantly underestimate rainfall volumes whereas OK and KED methods capture spatial patterns and rainfall volumes induced by storm advection. Using numerical weather forecasts and elevation data as covariates for precipitation, we provide evidence for KED to outperform the other methods. Most significantly, the use of elevation as auxiliary information in KED of temperatures demonstrates minimal errors in estimated instantaneous rainfall volumes and provides instantaneous lapse rates which better capture snow/rainfall partitioning. Incorporation of the temperature and precipitation input fields into a hydrological model used for operational management was found to provide vastly improved outputs with respect to measured discharge volumes and flood peaks, with notable implications for flood modeling.

Estimating methane emissions from landfills based on rainfall, ambient temperature, and waste composition: The CLEEN model.

PubMed

Karanjekar, Richa V; Bhatt, Arpita; Altouqui, Said; Jangikhatoonabad, Neda; Durai, Vennila; Sattler, Melanie L; Hossain, M D Sahadat; Chen, Victoria

2015-12-01

Accurately estimating landfill methane emissions is important for quantifying a landfill's greenhouse gas emissions and power generation potential. Current models, including LandGEM and IPCC, often greatly simplify treatment of factors like rainfall and ambient temperature, which can substantially impact gas production. The newly developed Capturing Landfill Emissions for Energy Needs (CLEEN) model aims to improve landfill methane generation estimates, but still require inputs that are fairly easy to obtain: waste composition, annual rainfall, and ambient temperature. To develop the model, methane generation was measured from 27 laboratory scale landfill reactors, with varying waste compositions (ranging from 0% to 100%); average rainfall rates of 2, 6, and 12 mm/day; and temperatures of 20, 30, and 37°C, according to a statistical experimental design. Refuse components considered were the major biodegradable wastes, food, paper, yard/wood, and textile, as well as inert inorganic waste. Based on the data collected, a multiple linear regression equation (R(2)=0.75) was developed to predict first-order methane generation rate constant values k as functions of waste composition, annual rainfall, and temperature. Because, laboratory methane generation rates exceed field rates, a second scale-up regression equation for k was developed using actual gas-recovery data from 11 landfills in high-income countries with conventional operation. The Capturing Landfill Emissions for Energy Needs (CLEEN) model was developed by incorporating both regression equations into the first-order decay based model for estimating methane generation rates from landfills. CLEEN model values were compared to actual field data from 6 US landfills, and to estimates from LandGEM and IPCC. For 4 of the 6 cases, CLEEN model estimates were the closest to actual. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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.

Climate Effects on Corn Yield in Missouri(.

NASA Astrophysics Data System (ADS)

Hu, Qi; Buyanovsky, Gregory

2003-11-01

Understanding climate effects on crop yield has been a continuous endeavor aiming at improving farming technology and management strategy, minimizing negative climate effects, and maximizing positive climate effects on yield. Many studies have examined climate effects on corn yield in different regions of the United States. However, most of those studies used yield and climate records that were shorter than 10 years and were for different years and localities. Although results of those studies showed various influences of climate on corn yield, they could be time specific and have been difficult to use for deriving a comprehensive understanding of climate effects on corn yield. In this study, climate effects on corn yield in central Missouri are examined using unique long-term (1895 1998) datasets of both corn yield and climate. Major results show that the climate effects on corn yield can only be explained by within-season variations in rainfall and temperature and cannot be distinguished by average growing-season conditions. Moreover, the growing-season distributions of rainfall and temperature for high-yield years are characterized by less rainfall and warmer temperature in the planting period, a rapid increase in rainfall, and more rainfall and warmer temperatures during germination and emergence. More rainfall and cooler-than-average temperatures are key features in the anthesis and kernel-filling periods from June through August, followed by less rainfall and warmer temperatures during the September and early October ripening time. Opposite variations in rainfall and temperature in the growing season correspond to low yield. Potential applications of these results in understanding how climate change may affect corn yield in the region also are discussed.

Rainfall and temperature changes and variability in the Upper East Region of Ghana

NASA Astrophysics Data System (ADS)

Issahaku, Abdul-Rahaman; Campion, Benjamin Betey; Edziyie, Regina

2016-08-01

The aim of the research was to assess the current trend and variation in rainfall and temperature in the Upper East Region, Ghana, using time series moving average analysis and decomposition methods. Meteorological data obtained from the Ghana Meteorological Agency in Accra, Ghana, from 1954 to 2014 were used in the models. The additive decomposition model was used to analyze the rainfall because the seasonal variation was relatively constant over time, while the multiplicative model was used for both the daytime and nighttime temperatures because their seasonal variations increase over time. The monthly maximum and the minimum values for the entire period were as follows: rainfall 455.50 and 0.00 mm, nighttime temperature 29.10°C and 13.25°C and daytime temperature 41.10°C and 26.10°C, respectively. Also, while rainfall was decreasing, nighttime and daytime temperatures were increasing in decadal times. Since both the daytime and nighttime temperatures were increasing and rainfall was decreasing, climate extreme events such as droughts could result and affect agriculture in the region, which is predominantly rain fed. Also, rivers, dams, and dugouts are likely to dry up in the region. It was also observed that there was much variation in rainfall making prediction difficult. Day temperatures were generally high with the months of March and April have been the highest. The months of December recorded the lowest night temperature. Inhabitants are therefore advised to sleep in well-ventilated rooms during the warmest months and wear protective clothing during the cold months to avoid contracting climate-related diseases.

Simulating the impacts of chronic ozone exposure on plant conductance and photosynthesis, and on the regional hydroclimate using WRF/Chem

NASA Astrophysics Data System (ADS)

Li, Jialun; Mahalov, Alex; Hyde, Peter

2016-11-01

The Noah-Multiparameterization land surface model in the Weather Research and Forecasting (WRF) with Chemistry (WRF/Chem) is modified to include the effects of chronic ozone exposure (COE) on plant conductance and photosynthesis (PCP) found from field experiments. Based on the modified WRF/Chem, the effects of COE on regional hydroclimate have been investigated over the continental United States. Our results indicate that the model with/without modification in its current configuration can reproduce the rainfall and temperature patterns of the observations and reanalysis data, although it underestimates rainfall in the central Great Plains and overestimates it in the eastern coast states. The experimental tests on the effects of COE include setting different thresholds of ambient ozone concentrations ([O3]) and using different linear regressions to quantify PCP against the COE. Compared with the WRF/Chem control run (i.e., without considering the effects of COE), the modified model at different experiment setups improves the simulated estimates of rainfall and temperatures in Texas and regions to the immediate north. The simulations in June, July and August of 2007-2012 show that surface [O3] decrease latent heat fluxes (LH) by 10-27 W m-2, increase surface air temperatures (T 2) by 0.6 °C-2.0 °C, decrease rainfall by 0.9-1.4 mm d-1, and decrease runoff by 0.1-0.17 mm d-1 in Texas and surrounding areas, all of which highly depends on the precise experiment setup, especially the [O3] threshold. The mechanism producing these results is that COE decreases the LH and increases sensible heat fluxes, which in turn increases the Bowen ratios and air temperatures. This lowering of the LH also results in the decrease of convective potential and finally decreases convective rainfall. Employing this modified WRF/Chem model in any high [O3] region can improve the understanding of the interactions of vegetation, meteorology, chemistry/emissions, and crop productivity.

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.

Prediction model for peninsular Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

Vathsala, H.; Koolagudi, Shashidhar G.

2017-01-01

In this paper we discuss a data mining application for predicting peninsular Indian summer monsoon rainfall, and propose an algorithm that combine data mining and statistical techniques. We select likely predictors based on association rules that have the highest confidence levels. We then cluster the selected predictors to reduce their dimensions and use cluster membership values for classification. We derive the predictors from local conditions in southern India, including mean sea level pressure, wind speed, and maximum and minimum temperatures. The global condition variables include southern oscillation and Indian Ocean dipole conditions. The algorithm predicts rainfall in five categories: Flood, Excess, Normal, Deficit and Drought. We use closed itemset mining, cluster membership calculations and a multilayer perceptron function in the algorithm to predict monsoon rainfall in peninsular India. Using Indian Institute of Tropical Meteorology data, we found the prediction accuracy of our proposed approach to be exceptionally good.

The impact of meteorology on the occurrence of waterborne outbreaks of vero cytotoxin-producing Escherichia coli (VTEC): a logistic regression approach.

PubMed

O'Dwyer, Jean; Morris Downes, Margaret; Adley, Catherine C

2016-02-01

This study analyses the relationship between meteorological phenomena and outbreaks of waterborne-transmitted vero cytotoxin-producing Escherichia coli (VTEC) in the Republic of Ireland over an 8-year period (2005-2012). Data pertaining to the notification of waterborne VTEC outbreaks were extracted from the Computerised Infectious Disease Reporting system, which is administered through the national Health Protection Surveillance Centre as part of the Health Service Executive. Rainfall and temperature data were obtained from the national meteorological office and categorised as cumulative rainfall, heavy rainfall events in the previous 7 days, and mean temperature. Regression analysis was performed using logistic regression (LR) analysis. The LR model was significant (p < 0.001), with all independent variables: cumulative rainfall, heavy rainfall and mean temperature making a statistically significant contribution to the model. The study has found that rainfall, particularly heavy rainfall in the preceding 7 days of an outbreak, is a strong statistical indicator of a waterborne outbreak and that temperature also impacts waterborne VTEC outbreak occurrence.

Impacts of rainfall and air temperature variations due to climate change upon hydrological characteristics: A case study

Treesearch

Ying Ouyang; Jia-En Zhang; Yide Li; Prem Parajuli; Gary Feng

2015-01-01

Rainfall and air temperature variations resulting from climate change are important driving forces to change hydrologic processes in watershed ecosystems. This study investigated the impacts of past and future rainfall and air temperature variations upon water discharge, water outflow (from the watershed outlet), and evaporative loss in the Lower Yazoo River Watershed...

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.

Climate-change driven increase in high intensity rainfall events: Analysis of development in the last decades and towards an extrapolation of future progression

NASA Astrophysics Data System (ADS)

Müller, Eva; Pfister, Angela; Gerd, Büger; Maik, Heistermann; Bronstert, Axel

2015-04-01

Hydrological extreme events can be triggered by rainfall on different spatiotemporal scales: river floods are typically caused by event durations of between hours and days, while urban flash floods as well as soil erosion or contaminant transport rather result from storms events of very short duration (minutes). Still, the analysis of climate change impacts on rainfall-induced extreme events is usually carried out using daily precipitation data at best. Trend analyses of extreme rainfall at sub-daily or even sub-hourly time scales are rare. In this contribution two lines of research are combined: first, we analyse sub-hourly rainfall data for several decades in three European regions.Second, we investigate the scaling behaviour of heavy short-term precipitation with temperature, i.e. the dependence of high intensity rainfall on the atmospheric temperature at that particular time and location. The trend analysis of high-resolution rainfall data shows for the first time that the frequency of short and intensive storm events in the temperate lowland regions in Germany has increased by up to 0.5 events per year over the last decades. I.e. this trend suggests that the occurrence of these types of storms have multiplied over only a few decades. Parallel to the changes in the rainfall regime, increases in the annual and seasonal average temperature and changes in the occurrence of circulation patterns responsible for the generation of high-intensity storms have been found. The analysis of temporally highly resolved rainfall records from three European regions further indicates that extreme precipitation events are more intense with warmer temperatures during the rainfall event. These observations follow partly the Clausius-Clapeyron relation. Based on this relation one may derive a general rule of maximum rainfall intensity associated to the event temperature, roughly following the Clausius-Clapeyron (CC) relation. This rule might be used for scenarios of future maximum rainfall intensities under a warming climate.

Wavelet Scale Analysis of Mesoscale Convective Systems for Detecting Deep Convection From Infrared Imagery

NASA Astrophysics Data System (ADS)

Klein, Cornelia; Belušić, Danijel; Taylor, Christopher M.

2018-03-01

Mesoscale convective systems (MCSs) are frequently associated with rainfall extremes and are expected to further intensify under global warming. However, despite the significant impact of such extreme events, the dominant processes favoring their occurrence are still under debate. Meteosat geostationary satellites provide unique long-term subhourly records of cloud top temperatures, allowing to track changes in MCS structures that could be linked to rainfall intensification. Focusing on West Africa, we show that Meteosat cloud top temperatures are a useful proxy for rainfall intensities, as derived from snapshots from the Tropical Rainfall Measuring Mission 2A25 product: MCSs larger than 15,000 km2 at a temperature threshold of -40°C are found to produce 91% of all extreme rainfall occurrences in the study region, with 80% of the storms producing extreme rain when their minimum temperature drops below -80°C. Furthermore, we present a new method based on 2-D continuous wavelet transform to explore the relationship between cloud top temperature and rainfall intensity for subcloud features at different length scales. The method shows great potential for separating convective and stratiform cloud parts when combining information on temperature and scale, improving the common approach of using a temperature threshold only. We find that below -80°C, every fifth pixel is associated with deep convection. This frequency is doubled when looking at subcloud features smaller than 35 km. Scale analysis of subcloud features can thus help to better exploit cloud top temperature data sets, which provide much more spatiotemporal detail of MCS characteristics than available rainfall data sets alone.

Spatiotemporal trends in extreme rainfall and temperature indices over Upper Tapi Basin, India

NASA Astrophysics Data System (ADS)

Sharma, Priyank J.; Loliyana, V. D.; S. R., Resmi; Timbadiya, P. V.; Patel, P. L.

2017-12-01

The flood risk across the globe is intensified due to global warming and subsequent increase in extreme temperature and precipitation. The long-term trends in extreme rainfall (1944-2013) and temperature (1969-2012) indices have been investigated at annual, seasonal, and monthly time scales using nonparametric Mann-Kendall (MK), modified Mann-Kendall (MMK), and Sen's slope estimator tests. The extreme rainfall and temperature indices, recommended by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI), have been analyzed at finer spatial scales for trend detection. The results of trend analyses indicate decreasing trend in annual total rainfall, significant decreasing trend in rainy days, and increasing trend in rainfall intensity over the basin. The seasonal rainfall has been found to decrease for all the seasons except postmonsoon, which could affect the rain-fed agriculture in the basin. The 1- and 5-day annual maximum rainfalls exhibit mixed trends, wherein part of the basin experiences increasing trend, while other parts experience a decreasing trend. The increase in dry spells and concurrent decrease in wet spells are also observed over the basin. The extreme temperature indices revealed increasing trends in hottest and coldest days, while decreasing trends in coldest night are found over most parts of the basin. Further, the diurnal temperature range is also found to increase due to warming tendency in maximum temperature (T max) at a faster rate compared to the minimum temperature (T min). The increase in frequency and magnitude of extreme rainfall in the basin has been attributed to the increasing trend in maximum and minimum temperatures, reducing forest cover, rapid pace of urbanization, increase in human population, and thereby increase in the aerosol content in the atmosphere. The findings of the present study would significantly help in sustainable water resource planning, better decision-making for policy framework, and setting up infrastructure against flood disasters in Upper Tapi Basin, India.

Remote rainfall sensing for landslide hazard analysis

USGS Publications Warehouse

Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay

2001-01-01

Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.

A STORMWATER CONSTRUCTED WETLAND USING RENEWABLE AND RECYCLABLE MATERIALS AND NATIVE WETLAND PLANTS

EPA Science Inventory

To complete the first objective, we installed a weather station within the storm water drainage area that measured air temperature, relative humidity, solar radiation, wind speed, and rainfall. Measurements were taken every 30 minutes and included the average temperature, rela...

A role of high impact weather events in waterborne disease outbreaks in Canada, 1975 - 2001.

PubMed

Thomas, Kate M; Charron, Dominique F; Waltner-Toews, David; Schuster, Corinne; Maarouf, Abdel R; Holt, John D

2006-06-01

Recent outbreaks of Escherichia coli O157:H7, Campylobacter, and Cryptosporidium have heightened awareness of risks associated with contaminated water supply. The objectives of this research were to describe the incidence and distribution of waterborne disease outbreaks in Canada in relation to preceding weather conditions and to test the association between high impact weather events and waterborne disease outbreaks. We examined extreme rainfall and spring snowmelt in association with 92 Canadian waterborne disease outbreaks between 1975 and 2001, using case-crossover methodology. Explanatory variables including accumulated rainfall, air temperature, and peak stream flow were used to determine the relationship between high impact weather events and the occurrence of waterborne disease outbreaks. Total maximum degree-days above 0 degrees C and accumulated rainfall percentile were associated with outbreak risk. For each degree-day above 0 degrees C the relative odds of an outbreak increased by a factor of 1.007 (95% confidence interval [CI] = 1.002 - 1.012). Accumulated rainfall percentile was dichotomized at the 93rd percentile. For rainfall events greater than the 93rd percentile the relative odds of an outbreak increased by a factor of 2.283 (95% [CI] = 1.216 - 4.285). These results suggest that warmer temperatures and extreme rainfall are contributing factors to waterborne disease outbreaks in Canada. This could have implications for water management and public health initiatives.

Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models

NASA Astrophysics Data System (ADS)

Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby

2018-06-01

The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices.

Assessing operative natural and anthropogenic forcing factors from long-term climate time series of Uttarakhand (India) in the backdrop of recurring extreme rainfall events over northwest Himalaya

NASA Astrophysics Data System (ADS)

Agnihotri, Rajesh; Dimri, A. P.; Joshi, H. M.; Verma, N. K.; Sharma, C.; Singh, J.; Sundriyal, Y. P.

2017-05-01

The entire Indo-Himalayan region from northwest (Kashmir) to northeast (Assam) is facing prevalence of floods and landslides in recent years causing massive loss of property, human and animal lives, infrastructure, and eventually threatening tourist activities substantially. Extremely intense rainfall event of 2013 C.E. (between 15 and 17 June) kicked off mammoth flash floods in the Kedarnath area of Uttarakhand state, resulting in huge socioeconomic losses to the state and country. Uttarakhand is an important hilly region attracting thousands of tourists every year owing to numerous shrines and forested mountainous tourist spots. Though recent studies indicate a plausible weakening of Indian summer monsoon rainfall overall, recurrent anomalous high rainfall events over northwest Himalaya (e.g. -2010, 2013, and 2016) point out the need for a thorough reassessment of long-term time series data of regional rainfall and ambient temperatures in order to trace signatures of a shifting pattern in regional meteorology, if any. Accordingly, here we investigate 100-year-long monthly rainfall and air temperature time series data for a selected grid (28.5°N, 31.25°N; 78.75°E, 81.25°E) covering most parts of Uttarakhand state. We also examined temporal variance in interrelationships among regional meteorological data (temperature and precipitation) and key global climate variability indices using advance statistical methods. Major findings are (i) significant increase in pre-monsoon air temperature over Uttarakhand after 1997, (ii) increasing upward trend in June-July rainfall and its relationship with regional May temperatures (iii) monsoonal rainfall (June, July, August, and September; JJAS) showing covariance with interannual variability in Eurasian snow cover (ESC) extent during the month of March, and (iv) enhancing tendency of anomalous high rainfall events during negative phases of Arctic Oscillation. Obtained results indicate that under warming scenario, JJ rainfall (over AS) may further increase with occasional extreme rainfall spells when AO index (March) is negative.

Changes in intensity of precipitation extremes in Romania on very hight temporal scale and implications on the validity of the Clausius-Clapeyron relation

NASA Astrophysics Data System (ADS)

Busuioc, Aristita; Baciu, Madalina; Breza, Traian; Dumitrescu, Alexandru; Stoica, Cerasela; Baghina, Nina

2016-04-01

Many observational, theoretical and based on climate model simulation studies suggested that warmer climates lead to more intense precipitation events, even when the total annual precipitation is slightly reduced. In this way, it was suggested that extreme precipitation events may increase at Clausius-Clapeyron (CC) rate under global warming and constraint of constant relative humidity. However, recent studies show that the relationship between extreme rainfall intensity and atmospheric temperature is much more complex than would be suggested by the CC relationship and is mainly dependent on precipitation temporal resolution, region, storm type and whether the analysis is conducted on storm events rather than fixed data. The present study presents the dependence between the very hight temporal scale extreme rainfall intensity and daily temperatures, with respect to the verification of the CC relation. To solve this objective, the analysis is conducted on rainfall event rather than fixed interval using the rainfall data based on graphic records including intensities (mm/min.) calculated over each interval with permanent intensity per minute. The annual interval with available a such data (April to October) is considered at 5 stations over the interval 1950-2007. For Bucuresti-Filaret station the analysis is extended over the longer interval (1898-2007). For each rainfall event, the maximum intensity (mm/min.) is retained and these time series are considered for the further analysis (abbreviated in the following as IMAX). The IMAX data were divided based on the daily mean temperature into bins 2oC - wide. The bins with less than 100 values were excluded. The 90th, 99th and 99.9th percentiles were computed from the binned data using the empirical distribution and their variability has been compared to the CC scaling (e.g. exponential relation given by a 7% increase per temperature degree rise). The results show a dependence close to double the CC relation for temperatures less than ~ 220C and negative scaling rates for higher temperatures. This behaviour is similar for all the 5 analysed stations over the common interval 1950-2007. This scaling is more exactly for the 90th percentile, while for the higher percentiles the rainfall intensity in response to warming exceeds sometimes the CC rate. For Bucuresti-Filaret station, the results are similar over a longer interval (1898-2007) showing that these findings are robust. Similar techniques has been previously applied to the hourly rainfall intensities recorded at 9 stations (including the 5 ones) and the results are slightly different: the 90th percentile shows dependence close to the CC relation for all temperatures; the 99th and 99.9th percentiles exhibit rates close to double the CC rate for temperatures between ~ 100C and ~ 220C and negative scaling rates for higher temperatures. In conclusion, these results show that the dependence between the extreme precipitation intensity and atmospheric temperature in Romania is mainly dependent on the temporal precipitation resolution and the degree of the extreme precipitation event (moderate or stronger); these findings are mainly in agreenment with the conclusions presented by previous international studies (mentioned above), with some regional specific features, showing the importance of the regional studies. The results presented is this study were funded by the Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI) through the research project CLIMHYDEX, "Changes in climate extremes and associated impact in hydrological events in Romania", code PNII-ID-2011-2-0073 (http://climhydex.meteoromania.ro).

Precipitation Discrimination from Satellite Infrared Temperatures over the CCOPE Mesonet Region.

NASA Astrophysics Data System (ADS)

Weiss, Mitchell; Smith, Eric A.

1987-06-01

A quantitative investigation of the relationship between satellite-derived cloud-top temperature parameters and the detection of intense convective rainfall is described. The area of study is that of the Cooperative Convective Precipitation Experiment (CCOPE), which was held near Miles City, Montana during the summer of 1981. Cloud-top temperatures, derived from the GOES-West operational satellite, were used to calculate a variety of parameters for objectively quantifying the convective intensity of a storm. A dense network of rainfall provided verification of surface rainfall. The cloud-top temperature field and surface rainfall data were processed into equally sized grid domains in order to best depict the individual samples of instantaneous precipitation.The technique of statistical discriminant analysis was used to determine which combinations of cloud-top temperature parameters best classify rain versus no-rain occurrence using three different rain-rate cutoffs: 1, 4, and 10 mm h1. Time lags within the 30 min rainfall verification were tested to determine the optimum time delay associated with rainfall reaching the ground.A total of six storm cases were used to develop and test the statistical models. Discrimination of rain events was found to be most accurate when using a 10 mm h1 rain-rate cutoff. Use parameters designated as coldest cloud-top temperature, the spatial mean of coldest cloud-top temperature, and change over time of mean coldest cloud-top temperature were found to be the best classifiers of rainfall in this study. Combining both a 10-min time lag (in terms of surface verification) with a 10 mm h1 rain-rate threshold resulted in classifying over 60% of all rain and no-rain cases correctly.

Climate Change In Indonesia (Case Study : Medan, Palembang, Semarang)

NASA Astrophysics Data System (ADS)

Suryadi, Yadi; Sugianto, Denny Nugroho; Hadiyanto

2018-02-01

Indonesia's maritime continent is one of the most vulnerable regions regarding to climate change impacts. One of the vulnerable areas affected are the urban areas, because they are home to almost half of Indonesia's population where they live and earn a living, so that environmental management efforts need to be done. To support such efforts, climate change analysis is required. The analysis was carried out in several big cities in Indonesia. The method used in the research was trend analysis of temperature, rainfall, shifts in rainfall patterns, and extreme climatic trend. The data of rainfall and temperature were obtained from Meteorology and Geophysics Agency (BMKG). The result shows that the air temperature and rainfall have a positive trend, except in Semarang City which having a negative rainfall trend. The result also shows heavy rainfall trends. These indicate that climate is changing in these three cities.

Evaluation of common bean lines for adaptation to high temperatures in Honduras

USDA-ARS?s Scientific Manuscript database

As in other regions worldwide, common bean (Phaseolus vulgaris L.) production in Central America and the Caribbean (CA/C) region is threatened by effects of climate change including increasing temperatures and drought due to variable rainfall patterns. One of the main alternatives for increasing ada...

Infrared Data for Storm Analysis

NASA Technical Reports Server (NTRS)

Adler, R.

1982-01-01

The papers in this section include: 1) 'Thunderstorm Top Structure Observed by Aircraft Overflights with an Infrared Radiometer'; 2) 'Thunderstorm Intensity as Determined from Satellite Data'; 3) 'Relation of Satellite-Based Thunderstorm Intensity to Radar-Estimated Rainfall'; 4) 'A Simple Physical Basis for Relating Geosynchronous Satellite Infrared Observations to Thunderstorm Rainfall'; 5) 'Satellite-Observed Cloud-Top Height Changes in Tornadic Thunderstorms'; 6) 'Predicting Tropical Cyclone Intensity Using Satellite-Measured Equivalent Blackbody Temperatures of Cloud Tops'.

Role of Temperature, Humidity and Rainfall on Influenza Transmission in Guatemala, El Salvador and Panama

NASA Technical Reports Server (NTRS)

Soebiyanto, Radina P.; Bonilla, Luis; Jara, Jorge; McCracken, John; Azziz?-Baumgartner, Eduardo; Widdowson, Marc-Alain; Kiang, Richard

2012-01-01

Worldwide, seasonal influenza causes about 500,000 deaths and 5 million severe illnesses per year. The environmental drivers of influenza transmission are poorly understood especially in the tropics. We aimed to identify meteorological factors for influenza transmission in tropical Central America. We gathered laboratory-confirmed influenza case-counts by week from Guatemala City, San Salvador Department (El Salvador) and Panama Province from 2006 to 2010. The average total cases per year were: 390 (Guatemala), 99 (San Salvador) and 129 (Panama). Meteorological factors including daily air temperature, rainfall, relative and absolute humidity (RH, AH) were obtained from ground stations, NASA satellites and land models. For these factors, we computed weekly averages and their deviation from the 5-yr means. We assessed the relationship between the number of influenza case-counts and the meteorological factors, including effects lagged by 1 to 4 weeks, using Poisson regression for each site. Our results showed influenza in San Salvador would increase by 1 case within a week of every 1 day with RH>75% (Relative Risk (RR)= 1.32, p=.001) and every 1C increase in minimum temperature (RR=1.29, p=.007) but it would decrease by 1 case for every 1mm-above mean weekly rainfall (RR=0.93,p<.001) (model pseudo-R2=0.55). Within 2 weeks, influenza in Panama was increased by 1 case for every 1% increase in RH (RR=1.04, p=.003), and it was increased by 2 cases for every 1C increase of minimum temperature (RR=2.01, p<.001) (model pseudo-R2=0.4). Influenza counts in Guatemala had 1 case increase for every 1C increase in minimum temperature in the previous week (RR=1.21, p<.001), and for every 1mm/day-above normal increase of rainfall rate (RR=1.03, p=.03) (model pseudo-R2=0.54). Our findings that cases increase with temperature and humidity differ from some temperate-zone studies. But they indicate that climate parameters such as humidity and temperature could be predictive of influenza activity and should be incorporated into country-specific influenza transmission models

Changes to Sub-daily Rainfall Patterns in a Future Climate

NASA Astrophysics Data System (ADS)

Westra, S.; Evans, J. P.; Mehrotra, R.; Sharma, A.

2012-12-01

An algorithm is developed for disaggregating daily rainfall into sub-daily rainfall 'fragments' (continuous high temporal-resolution rainfall sequences whose total depth sums to the daily rainfall amount) under a future, warmer climate. The basis of the algorithm is to re-sample sub-daily fragments from the historical record conditional on the total daily rainfall amount and a range of temperature-based atmospheric predictors. The logic is that as the atmosphere warms, future rainfall patterns will be more reflective of historical rainfall patterns which occurred on warmer days at the same location, or at locations which have an atmospheric temperature profile more representative of expected future atmospheric conditions. It was found that the daily to sub-daily scaling relationship varied significantly by season and by location, with rainfall patterns on warmer seasons or at warmer locations typically exhibiting higher rainfall intensity occurring over shorter periods within a day, compared with cooler seasons and locations. Importantly, by regressing against temperature-based atmospheric covariates, this effect was substantially reduced, suggesting that the approach also may be valid when extrapolating to a future climate. An adjusted method of fragments algorithm was then applied to nine stations around Australia, with the results showing that when holding total daily rainfall constant, the maximum intensity of short duration rainfall increased by a median of about 5% per degree for the maximum 6 minute burst, and 3.5% for the maximum one hour burst, whereas the fraction of the day with no rainfall increased by a median of 1.5%. This highlights that a large proportion of the change to the distribution of rainfall is likely to occur at sub-daily timescales, with significant implications for many hydrological systems.

Tropical cyclone rainfall area controlled by relative sea surface temperature

PubMed Central

Lin, Yanluan; Zhao, Ming; Zhang, Minghua

2015-01-01

Tropical cyclone rainfall rates have been projected to increase in a warmer climate. The area coverage of tropical cyclones influences their impact on human lives, yet little is known about how tropical cyclone rainfall area will change in the future. Here, using satellite data and global atmospheric model simulations, we show that tropical cyclone rainfall area is controlled primarily by its environmental sea surface temperature (SST) relative to the tropical mean SST (that is, the relative SST), while rainfall rate increases with increasing absolute SST. Our result is consistent with previous numerical simulations that indicated tight relationships between tropical cyclone size and mid-tropospheric relative humidity. Global statistics of tropical cyclone rainfall area are not expected to change markedly under a warmer climate provided that SST change is relatively uniform, implying that increases in total rainfall will be confined to similar size domains with higher rainfall rates. PMID:25761457

Rainfall estimation with TFR model using Ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Asyiqotur Rohmah, Nabila; Apriliani, Erna

2018-03-01

Rainfall fluctuation can affect condition of other environment, correlated with economic activity and public health. The increasing of global average temperature is influenced by the increasing of CO2 in the atmosphere, which caused climate change. Meanwhile, the forests as carbon sinks that help keep the carbon cycle and climate change mitigation. Climate change caused by rainfall intensity deviations can affect the economy of a region, and even countries. It encourages research on rainfall associated with an area of forest. In this study, the mathematics model that used is a model which describes the global temperatures, forest cover, and seasonal rainfall called the TFR (temperature, forest cover, and rainfall) model. The model will be discretized first, and then it will be estimated by the method of Ensemble Kalman Filter (EnKF). The result shows that the more ensembles used in estimation, the better the result is. Also, the accurateness of simulation result is influenced by measurement variable. If a variable is measurement data, the result of simulation is better.

Vegetative and reproductive phenology of a floodplain tree species Barringtonia acutangula from North East India.

PubMed

Nath, Shikhasmita; Nath, Arun Jyoti; Das, Ashesh Kumar

2016-03-01

Vegetative and reproductive phenology of Barringtonia acutangula, a floodplain tree species was studied at Chatla floodplain, Assam North East India with the aim to investigate vegetative and reproductive phenology under stressful environment of seasonal submergence and to assess the impact of environmental variables (temperature and precipitation) on tree phenophases. Quantitative assessment was made at 15 day interval for all the phenophases (leaf initiation, leaf-fall, flowering and fruiting) by tagging 40 (forty) trees over aperiod of two years (2012-14).To test seasonal influence on the phenology of Barringtonia acutangula different phenophases were correlated with environmental variables and statistical spearman's rank correlation coefficient was employed. Aridity index was computed that delineate influence of rainfall and temperature together on any phenophases. Leaf initiation showed positively significant correlation with temperature (r(s) = 0.601, p = < .05) during the year 2012-2013 whereas it was significantly correlated with rainfall (r(s) = 0.583, p = < .05) and aridity index (r(s) = 0.583, p = < .05) during the year 2013-2014. Leaf-fall was significant negatively correlated with temperature (r(s) = -0.623, p = < .05), rainfall (r(s) = -0.730, p = < .01) and aridity index (r(s) = -0.730, p = < .01) for both the studied years. Flowering was significantly influenced by temperature (r(s) = 0.639, p = < .05), rainfall (r(s) = 0.890, p = < .01) and aridity index (r(s) = 0.890, p = < .01) while in one month lag flowering was significantly correlated with rainfall (r(s) = 0.678, p = < .01) in 2012-13. Fruiting was also positively significant with temperature (r(s) = 0.795, P < .05), rainfall (r(s) = 0.835, P < .01) and aridity index (r(s) = 0.835, P < .01) for both the years. During one month lag period fruiting was positively correlated with temperature, rainfall and aridity index in both the years. Temperature, rainfall and aridity index were major determinants of the various vegetative and reproductive phenology of B. acutangula and any changes in these variables in future due to climate change, might have profound effect on phenophases of this tree species.

Markov modulated Poisson process models incorporating covariates for rainfall intensity.

PubMed

Thayakaran, R; Ramesh, N I

2013-01-01

Time series of rainfall bucket tip times at the Beaufort Park station, Bracknell, in the UK are modelled by a class of Markov modulated Poisson processes (MMPP) which may be thought of as a generalization of the Poisson process. Our main focus in this paper is to investigate the effects of including covariate information into the MMPP model framework on statistical properties. In particular, we look at three types of time-varying covariates namely temperature, sea level pressure, and relative humidity that are thought to be affecting the rainfall arrival process. Maximum likelihood estimation is used to obtain the parameter estimates, and likelihood ratio tests are employed in model comparison. Simulated data from the fitted model are used to make statistical inferences about the accumulated rainfall in the discrete time interval. Variability of the daily Poisson arrival rates is studied.

Spatio-temporal heterogeneity of malaria morbidity in Ghana: Analysis of routine health facility data

PubMed Central

Malm, Keziah; Peprah, Nana Yaw; Silal, Sheetal P.

2018-01-01

Background Malaria incidence is largely influenced by vector abundance. Among the many interconnected factors relating to malaria transmission, weather conditions such as rainfall and temperature are known to create suitable environmental conditions that sustain reproduction and propagation of anopheles mosquitoes and malaria parasites. In Ghana, climatic conditions vary across the country. Understanding the heterogeneity of malaria morbidity using data sourced from a recently setup data repository for routine health facility data could support planning. Methods Monthly aggregated confirmed uncomplicated malaria cases from the District Health Information Management System and average monthly rainfall and temperature records obtained from the Ghana Meteorological Agency from 2008 to 2016 were analysed. Univariate time series models were fitted to the malaria, rainfall and temperature data series. After pre-whitening the morbidity data, cross correlation analyses were performed. Subsequently, transfer function models were developed for the relationship between malaria morbidity and rainfall and temperature. Results Malaria morbidity patterns vary across zones. In the Guinea savannah, morbidity peaks once in the year and twice in both the Transitional forest and Coastal savannah, following similar patterns of rainfall at the zonal level. While the effects of rainfall on malaria morbidity are delayed by a month in the Guinea savannah and Transitional Forest zones those of temperature are delayed by two months in the Transitional forest zone. In the Coastal savannah however, incidence of malaria is significantly associated with two months lead in rainfall and temperature. Conclusion Data captured on the District Health Information Management System has been used to demonstrate heterogeneity in the dynamics of malaria morbidity across the country. Timing of these variations could guide the deployment of interventions such as indoor residual spraying, Seasonal Malaria Chemoprevention or vaccines to optimise effectiveness on zonal basis. PMID:29377908

Spatio-temporal heterogeneity of malaria morbidity in Ghana: Analysis of routine health facility data.

PubMed

Awine, Timothy; Malm, Keziah; Peprah, Nana Yaw; Silal, Sheetal P

2018-01-01

Malaria incidence is largely influenced by vector abundance. Among the many interconnected factors relating to malaria transmission, weather conditions such as rainfall and temperature are known to create suitable environmental conditions that sustain reproduction and propagation of anopheles mosquitoes and malaria parasites. In Ghana, climatic conditions vary across the country. Understanding the heterogeneity of malaria morbidity using data sourced from a recently setup data repository for routine health facility data could support planning. Monthly aggregated confirmed uncomplicated malaria cases from the District Health Information Management System and average monthly rainfall and temperature records obtained from the Ghana Meteorological Agency from 2008 to 2016 were analysed. Univariate time series models were fitted to the malaria, rainfall and temperature data series. After pre-whitening the morbidity data, cross correlation analyses were performed. Subsequently, transfer function models were developed for the relationship between malaria morbidity and rainfall and temperature. Malaria morbidity patterns vary across zones. In the Guinea savannah, morbidity peaks once in the year and twice in both the Transitional forest and Coastal savannah, following similar patterns of rainfall at the zonal level. While the effects of rainfall on malaria morbidity are delayed by a month in the Guinea savannah and Transitional Forest zones those of temperature are delayed by two months in the Transitional forest zone. In the Coastal savannah however, incidence of malaria is significantly associated with two months lead in rainfall and temperature. Data captured on the District Health Information Management System has been used to demonstrate heterogeneity in the dynamics of malaria morbidity across the country. Timing of these variations could guide the deployment of interventions such as indoor residual spraying, Seasonal Malaria Chemoprevention or vaccines to optimise effectiveness on zonal basis.

Spatio-temporal modelling of dengue fever incidence in Malaysia

NASA Astrophysics Data System (ADS)

Che-Him, Norziha; Ghazali Kamardan, M.; Saifullah Rusiman, Mohd; Sufahani, Suliadi; Mohamad, Mahathir; @ Kamariah Kamaruddin, Nafisah

2018-04-01

Previous studies reported significant relationship between dengue incidence rate (DIR) and both climatic and non-climatic factors. Therefore, this study proposes a generalised additive model (GAM) framework for dengue risk in Malaysia by using both climatic and non-climatic factors. The data used is monthly DIR for 12 states of Malaysia from 2001 to 2009. In this study, we considered an annual trend, seasonal effects, population, population density and lagged DIR, rainfall, temperature, number of rainy days and El Niño-Southern Oscillation (ENSO). The population density is found to be positively related to monthly DIR. There are generally weak relationships between monthly DIR and climate variables. A negative binomial GAM shows that there are statistically significant relationships between DIR with climatic and non-climatic factors. These include mean rainfall and temperature, the number of rainy days, sea surface temperature and the interaction between mean temperature (lag 1 month) and sea surface temperature (lag 6 months). These also apply to DIR (lag 3 months) and population density.

Could Malaria Control Programmes be Timed to Coincide with Onset of Rainfall?

PubMed

Komen, Kibii

2017-06-01

Malaria cases in South Africa's Northern Province of Limpopo have surpassed known endemic KwaZulu Natal and Mpumalanga Provinces. This paper applies statistical methods: regression analysis and impulse response function to understand the timing of impact and the length that such impacts last. Climate data (rainfall and temperature) are obtained from South African Weather Services (SAWs); global data from the European Centre for Medium-Range Weather Forecasts (ECMWF), while clinical malaria data came from Malaria Control Centre in Tzaneen (Limpopo Province). Data collected span from January 1998 to July 2007. Signs of the coefficients are positive for rainfall and temperature and negative for their exponents. Three out of five independent variables consistently maintain a very high statistical level of significance. The coefficients for climate variables describe an inverted u-shape: parameters for the exponents of rainfall (-0.02, -0.01, -0.02, -0.00) and temperature (-46.61, -47.46, -48.14, -36.04) are both negative. A one standard deviation rise in rainfall (rainfall onset) increases malaria cases, and the effects become sustained for at least 3 months and conclude that onset of rainfall therefore triggers a 'malaria season'. Malaria control programme and early warning system should be intensified in the first 3 months following the onset of rainfall.

Long-run relative importance of temperature as the main driver to malaria transmission in Limpopo Province, South Africa: a simple econometric approach.

PubMed

Komen, Kibii; Olwoch, Jane; Rautenbach, Hannes; Botai, Joel; Adebayo, Adetunji

2015-03-01

Malaria in Limpopo Province of South Africa is shifting and now observed in originally non-malaria districts, and it is unclear whether climate change drives this shift. This study examines the distribution of malaria at district level in the province, determines direction and strength of the linear relationship and causality between malaria with the meteorological variables (rainfall and temperature) and ascertains their short- and long-run variations. Spatio-temporal method, Correlation analysis and econometric methods are applied. Time series monthly meteorological data (1998-2007) were obtained from South Africa Weather Services, while clinical malaria data came from Malaria Control Centre in Tzaneen (Limpopo Province) and South African Department of Health. We find that malaria changes and pressures vary in different districts with a strong positive correlation between temperature with malaria, r = 0.5212, and a weak positive relationship for rainfall, r = 0.2810. Strong unidirectional causality runs from rainfall and temperature to malaria cases (and not vice versa): F (1, 117) = 3.89, ρ = 0.0232 and F (1, 117) = 20.08, P < 0.001 and between rainfall and temperature, a bi-directional causality exists: F (1, 117) = 19.80; F (1,117) = 17.14, P < 0.001, respectively, meaning that rainfall affects temperature and vice versa. Results show evidence of strong existence of a long-run relationship between climate variables and malaria, with temperature maintaining very high level of significance than rainfall. Temperature, therefore, is more important in influencing malaria transmission in Limpopo Province.

Mapping as a tool for predicting the risk of anthrax outbreaks in Northern Region of Ghana.

PubMed

Nsoh, Ayamdooh Evans; Kenu, Ernest; Forson, Eric Kofi; Afari, Edwin; Sackey, Samuel; Nyarko, Kofi Mensah; Yebuah, Nathaniel

2016-01-01

Anthrax is a febrile soil-born infectious disease that can affect all warm-blooded animals including man. Outbreaks of anthrax have been reported in northern region of Ghana but no concerted effort has been made to implement risk-based surveillance systems to document outbreaks so as to implement policies to address the disease. We generated predictive maps using soil pH, temperature and rainfall as predictor variables to identify hotspot areas for the outbreaks. A 10-year secondary data records on soil pH, temperature and rainfall were used to create climate-based risk maps using ArcGIS 10.2. The monthly mean values of rainfall and temperature for ten years were calculated and anthrax related evidence based constant raster values were created as weights for the three factors. All maps were generated using the Kriging interpolation method. There were 43 confirmed outbreaks. The deaths involved were 131 cattle, 44 sheep, 15 goats, 562 pigs with 6 human deaths and 22 developed cutaneous anthrax. We found three strata of well delineated distribution pattern indicating levels of risk due to suitability of area for anthrax spore survival. The likelihood of outbreaks occurrence and reoccurrence was higher in Strata I, Strata II and strata III respectively in descending order, due to the suitability of soil pH, temperature and rainfall for the survival and dispersal of B. anthracis spore. The eastern corridor of Northern region is a Hots spot area. Policy makers can develop risk based surveillance system and focus on this area to mitigate anthrax outbreaks and reoccurrence.

Simulation of the Onset of the Southeast Asian Monsoon During 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2003-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data fiom the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo- China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the lowlevel temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation.

Application of geotechnical and geophysical field measurements in an active alpine environment

NASA Astrophysics Data System (ADS)

Lucas, D. R.; Fankhauser, K.; Springman, S. M.

2015-09-01

Rainfall can trigger landslides, rockfalls and debris flow events. When rainfall infiltrates into the soil, the suction (if there is any) is reduced, until positive water pressure can be developed, decreasing the effective stresses and leading to a potential failure. A challenging site for the study of mass movement is the Meretschibach catchment, a location in the Swiss Alps in the vicinity of Agarn, Canton of Valais. To study the effect of rainfall on slope stabilities, the soil characterization provides valuable insight on soil properties, necessary to establish a realistic ground model. This model, together with an effective long term-field monitoring, deliver the essential information and boundary conditions for predicting and validating rainfall- induced slope instabilities using numerical and physical modelling. Geotechnical monitoring, including soil temperature and volumetric water content measurements, has been performed on the study site together with geophysical measurements (ERT) to study the effect of rainfall on the (potential) triggering of landslides on a scree slope composed of a surficial layer of gravelly soil. These techniques were combined to provide information on the soil characteristics and depth to the bedrock. Seasonal changes of precipitation and temperature were reflected in corresponding trends in all measurements. A comparison of volumetric water content records was obtained from decagons, time domain reflectometry (TDR) and electrical resistivity tomography (ERT) conducted throughout the spring and summer months of 2014, yielding a reasonable agreement.

Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d'Ivoire.

PubMed

N'gattia, A K; Coulibaly, D; Nzussouo, N Talla; Kadjo, H A; Chérif, D; Traoré, Y; Kouakou, B K; Kouassi, P D; Ekra, K D; Dagnan, N S; Williams, T; Tiembré, I

2016-09-13

In temperate regions, influenza epidemics occur in the winter and correlate with certain climatological parameters. In African tropical regions, the effects of climatological parameters on influenza epidemics are not well defined. This study aims to identify and model the effects of climatological parameters on seasonal influenza activity in Abidjan, Cote d'Ivoire. We studied the effects of weekly rainfall, humidity, and temperature on laboratory-confirmed influenza cases in Abidjan from 2007 to 2010. We used the Box-Jenkins method with the autoregressive integrated moving average (ARIMA) process to create models using data from 2007-2010 and to assess the predictive value of best model on data from 2011 to 2012. The weekly number of influenza cases showed significant cross-correlation with certain prior weeks for both rainfall, and relative humidity. The best fitting multivariate model (ARIMAX (2,0,0) _RF) included the number of influenza cases during 1-week and 2-weeks prior, and the rainfall during the current week and 5-weeks prior. The performance of this model showed an increase of >3 % for Akaike Information Criterion (AIC) and 2.5 % for Bayesian Information Criterion (BIC) compared to the reference univariate ARIMA (2,0,0). The prediction of the weekly number of influenza cases during 2011-2012 with the best fitting multivariate model (ARIMAX (2,0,0) _RF), showed that the observed values were within the 95 % confidence interval of the predicted values during 97 of 104 weeks. Including rainfall increases the performances of fitted and predicted models. The timing of influenza in Abidjan can be partially explained by rainfall influence, in a setting with little change in temperature throughout the year. These findings can help clinicians to anticipate influenza cases during the rainy season by implementing preventive measures.

Local sea surface temperatures add to extreme precipitation in northeast Australia during La Niña

NASA Astrophysics Data System (ADS)

Evans, Jason P.; Boyer-Souchet, Irène

2012-05-01

This study examines the role played by high sea surface temperatures around northern Australia, in producing the extreme precipitation which occurred during the strong La Niña in December 2010. These extreme rains produced floods that impacted almost 1,300,000 km2, caused billions of dollars in damage, led to the evacuation of thousands of people and resulted in 35 deaths. Through the use of regional climate model simulations the contribution of the observed high sea surface temperatures to the rainfall is quantified. Results indicate that the large-scale atmospheric circulation changes associated with the La Niña event, while associated with above average rainfall in northeast Australia, were insufficient to produce the extreme rainfall and subsequent flooding observed. The presence of high sea surface temperatures around northern Australia added ˜25% of the rainfall total.

A 100 000-year record of annual and seasonal rainfall and temperature for northwestern Australia based on a pollen record obtained offshore

NASA Astrophysics Data System (ADS)

van der Kaars, Sander; de Deckker, Patrick; Gingele, Franz X.

2006-12-01

Pollen recovered from core tops of deep-sea cores from offshore northwestern Western Australia were used to build climatic transfer functions applied to sediment samples from major rivers bordering the ocean in the same region and a deep-sea core offshore Northwest Cape. Results show for the last 100 000 years, with a gap in the record spanning the 64 000 to 46 000 years interval, that from about 100 000 to 82 000 yr BP, climatic conditions represented by rainfall, temperature and number of humid months, were significantly higher than today's values. For the entire record, the coldest period occurred about 43 000 to 39 000 yr BP but it was wetter than today, whereas the Last Glacial Maximum saw a significant reduction in summer rainfall, interpreted as a result of the absence of monsoonal activity in the region. The Holocene can be divided into two distinct phases: one peaking around 6000 cal. yr BP with highest rainfall and summer temperatures; the second one commencing at 5000 cal. yr BP and showing a progressive decrease in summer rainfall in contrast to an increase in winter rainfall, paralleled by a progressive decrease in temperatures. Copyright

Biogeographical variation of plumage coloration in the sexually dichromatic Hawai‘i ‘Amakihi (Chlorodrepanis virens)

USGS Publications Warehouse

Gaudioso-Levita, Jacqueline M.; Hart, Patrick J.; Lapointe, Dennis; Veillet, Anne; Sebastian-Gonzalez, Esther

2017-01-01

Plumage coloration in birds can be of major importance to mate selection, social signaling, or predator avoidance. Variations in plumage coloration related to sex, age class, or seasons have been widely studied, but the effect of other factors such as climate is less known. In this study, we examine how carotenoid-based plumage coloration and sexual dichromatism of the Hawai‘i ‘Amakihi (Chlorodrepanis virens) varies with rainfall and temperature on Hawai‘i Island. We also examined whether Hawai‘i ‘Amakihi plumage coloration patterns follow Gloger’s rule, which states that animals in wetter climates have darker coloration. Hawai‘i ‘Amakihi were mist-netted and banded at 12 sites representing six major climatic zones on Hawai‘i Island. Feather samples were collected from two body regions: the breast and rump. Using spectrophotometry, we recorded coloration using measures of hue, saturation, and brightness. We conducted sex determination by polymerase chain reaction to confirm the sex of birds sampled. We found that the plumage coloration of Hawai‘i ‘Amakihi varied with both temperature and rainfall. ‘Amakihi plumage’s brightness showed a quadratic relationship with rainfall, contrary to Gloger’s rule, and decreased with temperature. Saturation depended on the interaction between temperature and rainfall. Increases in rainfall also increased saturation in warm areas, while they reduced saturation when the temperature was low. Finally, we found chromatic differences among sexes, but sexual dichromatism was not affected by the climatic conditions. This study provides evidence that rainfall and temperature play an important role in determining the plumage traits of Hawai‘i ‘Amakihi.

Unbiased estimation of oceanic mean rainfall from satellite borne radiometer measurements

NASA Technical Reports Server (NTRS)

Mittal, M. C.

1981-01-01

The statistical properties of the radar derived rainfall obtained during the GARP Atlantic Tropical Experiment (GATE) are used to derive quantitative estimates of the spatial and temporal sampling errors associated with estimating rainfall from brightness temperature measurements such as would be obtained from a satelliteborne microwave radiometer employing a practical size antenna aperture. A basis for a method of correcting the so called beam filling problem, i.e., for the effect of nonuniformity of rainfall over the radiometer beamwidth is provided. The method presented employs the statistical properties of the observations themselves without need for physical assumptions beyond those associated with the radiative transfer model. The simulation results presented offer a validation of the estimated accuracy that can be achieved and the graphs included permit evaluation of the effect of the antenna resolution on both the temporal and spatial sampling errors.

Climatic controls on the global distribution, abundance, and species richness of mangrove forests

USGS Publications Warehouse

Osland, Michael J.; Feher, Laura C.; Griffith, Kereen; Cavanaugh, Kyle C.; Enwright, Nicholas M.; Day, Richard H.; Stagg, Camille L.; Krauss, Ken W.; Howard, Rebecca J.; Grace, James B.; Rogers, Kerrylee

2017-01-01

Mangrove forests are highly productive tidal saline wetland ecosystems found along sheltered tropical and subtropical coasts. Ecologists have long assumed that climatic drivers (i.e., temperature and rainfall regimes) govern the global distribution, structure, and function of mangrove forests. However, data constraints have hindered the quantification of direct climate-mangrove linkages in many parts of the world. Recently, the quality and availability of global-scale climate and mangrove data have been improving. Here, we used these data to better understand the influence of air temperature and rainfall regimes upon the distribution, abundance, and species richness of mangrove forests. Although our analyses identify global-scale relationships and thresholds, we show that the influence of climatic drivers is best characterized via regional range limit-specific analyses. We quantified climatic controls across targeted gradients in temperature and/or rainfall within 14 mangrove distributional range limits. Climatic thresholds for mangrove presence, abundance, and species richness differed among the 14 studied range limits. We identified minimum temperature-based thresholds for range limits in eastern North America, eastern Australia, New Zealand, eastern Asia, eastern South America, and southeast Africa. We identified rainfall-based thresholds for range limits in western North America, western Gulf of Mexico, western South America, western Australia, Middle East, northwest Africa, east central Africa, and west central Africa. Our results show that in certain range limits (e.g., eastern North America, western Gulf of Mexico, eastern Asia), winter air temperature extremes play an especially important role. We conclude that rainfall and temperature regimes are both important in western North America, western Gulf of Mexico, and western Australia. With climate change, alterations in temperature and rainfall regimes will affect the global distribution, abundance, and diversity of mangrove forests. In general, warmer winter temperatures are expected to allow mangroves to expand poleward at the expense of salt marshes. However, dispersal and habitat availability constraints may hinder expansion near certain range limits. Along arid and semi-arid coasts, decreases or increases in rainfall are expected to lead to mangrove contraction or expansion, respectively. Collectively, our analyses quantify climate-mangrove linkages and improve our understanding of the expected global- and regional-scale effects of climate change upon mangrove forests.

The asymmetric response of Yangtze river basin summer rainfall to El Niño/La Niña

NASA Astrophysics Data System (ADS)

Hardiman, Steven C.; Dunstone, Nick J.; Scaife, Adam A.; Bett, Philip E.; Li, Chaofan; Lu, Bo; Ren, Hong-Li; Smith, Doug M.; Stephan, Claudia C.

2018-02-01

The Yangtze river basin, in South East China, experiences anomalously high precipitation in summers following El Niño. This can lead to extensive flooding and loss of life. However, the response following La Niña has not been well documented. In this study, the response of Yangtze summer rainfall to El Niño/La Niña is found to be asymmetric, with no significant response following La Niña. The nature of this asymmetric response is found to be in good agreement with that simulated by the Met Office seasonal forecast system. Yangtze summer rainfall correlates positively with spring sea surface temperatures in the Indian Ocean and northwest Pacific. Indian Ocean sea surface temperatures are found to respond linearly to El Niño/La Niña, and to have a linear impact on Yangtze summer rainfall. However, northwest Pacific sea surface temperatures respond much more strongly following El Niño and, further, correlate more strongly with positive rainfall years. It is concluded that, whilst delayed Indian Ocean signals may influence summer Yangtze rainfall, it is likely that they do not lead to the asymmetric nature of the rainfall response to El Niño/La Niña.

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.

Trends in rainfall and temperature extremes in Morocco

NASA Astrophysics Data System (ADS)

Khomsi, K.; Mahe, G.; Tramblay, Y.; Sinan, M.; Snoussi, M.

2015-02-01

In Morocco, socioeconomic fields are vulnerable to weather extreme events. This work aims to analyze the frequency and the trends of temperature and rainfall extreme events in two contrasted Moroccan regions (the Tensift in the semi-arid South, and the Bouregreg in the sub-humid North), during the second half of the 20th century. This study considers long time series of daily extreme temperatures and rainfall, recorded in the stations of Marrakech and Safi for the Tensift region, and Kasba-Tadla and Rabat-Sale for the Bouregreg region, data from four other stations (Tanger, Fes, Agadir and Ouarzazate) from outside the regions were added. Extremes are defined by using as thresholds the 1st, 5th, 90th, 95th, and 99th percentiles. Results show upward trends in maximum and minimum temperatures of both regions and no generalized trends in rainfall amounts. Changes in cold events are larger than those for warm events, and the number of very cold events decrease significantly in the whole studied area. The southern region is the most affected with the changes of the temperature regime. Most of the trends found in rainfall heavy events are positive with weak magnitudes even though no statistically significant generalized trends could be identified during both seasons.

Universal inverse power-law distribution for temperature and rainfall in the UK region

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2014-06-01

Meteorological parameters, such as temperature, rainfall, pressure, etc., exhibit selfsimilar space-time fractal fluctuations generic to dynamical systems in nature such as fluid flows, spread of forest fires, earthquakes, etc. The power spectra of fractal fluctuations display inverse power-law form signifying long-range correlations. A general systems theory model predicts universal inverse power-law form incorporating the golden mean for the fractal fluctuations. The model predicted distribution was compared with observed distribution of fractal fluctuations of all size scales (small, large and extreme values) in the historic month-wise temperature (maximum and minimum) and total rainfall for the four stations Oxford, Armagh, Durham and Stornoway in the UK region, for data periods ranging from 92 years to 160 years. For each parameter, the two cumulative probability distributions, namely cmax and cmin starting from respectively maximum and minimum data value were used. The results of the study show that (i) temperature distributions (maximum and minimum) follow model predicted distribution except for Stornowy, minimum temperature cmin. (ii) Rainfall distribution for cmin follow model predicted distribution for all the four stations. (iii) Rainfall distribution for cmax follows model predicted distribution for the two stations Armagh and Stornoway. The present study suggests that fractal fluctuations result from the superimposition of eddy continuum fluctuations.

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.

Assessment on spatiotemporal relationship between rainfall and cloud top temperature from new generation weather satellite imagery

NASA Astrophysics Data System (ADS)

Wei, Chiang; Yeh, Hui-Chung; Chen, Yen-Chang

2017-04-01

This study addressed the relationship between rainfall and cloud top temperature (CCT) from new generation satellite Himawari-8 imagery at different spatiotemporal scale. This satellite provides higher band, more bits for data format, spatial and temporal resolution compared with previous GMS series. The multi-infrared channels with 10-minute and 1-2 km resolution make it possible for rainfall estimating/forecasting in small/medium watershed. The preliminary result investigated at Chenyulan watershed (443.6 square kilometer) of Central Taiwan in 2016 Typhoon Megi shows the regression coefficient fitted by negative exponential equation of largest rainfall vs. CCT (B8 band) at pixel scale increases as time scales enlarges and reach 0.462 for 120-minute accumulative rainfall; the value (CTT of B15 band) decreases from 0.635 for 10-minute to 0.423 for 120-minute accumulative rainfall at basin-wide scale. More rainfall events for different regime are yet to evaluate to get solid results.

How is rainfall interception in urban area affected by meteorological parameters?

NASA Astrophysics Data System (ADS)

Zabret, Katarina; Rakovec, Jože; Mikoš, Matjaž; Šraj, Mojca

2017-04-01

Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The amount of rainfall reaching the ground depends on various meteorological and vegetation parameters. Rainfall, throughfall and stemflow have been measured in the city of Ljubljana, Slovenia since the beginning of 2014. Manual and automatic measurements are performed regularly under Betula pendula and Pinus nigra trees in urban area. In 2014, there were detected 178 rainfall events with total amount of 1672.1 mm. In average B. pendula intercepted 44% of rainfall and P. nigra intercepted 72% of rainfall. In 2015 we have detected 117 events with 1047.4 mm of rainfall, of which 37% was intercepted by B. pendula and 60% by P. nigra. The effect of various meteorological parameters on the rainfall interception was analysed in the study. The parameters included in the analysis were rainfall rate, rainfall duration, drop size distribution (average drop velocity and diameter), average wind speed, and average temperature. The results demonstrate decreasing rainfall interception with longer rainfall duration and higher rainfall intensity although the impact of the latter one is not statistically significant. In the case of very fast or very slow rainfall drops, the interception is higher than for the mean rain drop velocity values. In the case of P. nigra the impact of the rain drop diameter on interception is similar to the one of rain drop velocity while for B. pendula increasing of drop diameter also increases the interception. As expected, interception is higher for warmer events. This trend is more evident for P. nigra than for B. pendula. Furthermore, the amount of intercepted rainfall also increases with wind although it could be relatively high in case of very low wind speeds.

The short-term association of temperature and rainfall with mortality in Vadu Health and Demographic Surveillance System: a population level time series analysis

PubMed Central

Ingole, Vijendra; Juvekar, Sanjay; Muralidharan, Veena; Sambhudas, Somnath; Rocklöv, Joacim

2012-01-01

Background Research in mainly developed countries has shown that some changes in weather are associated with increased mortality. However, due to the lack of accessible data, few studies have examined such effects of weather on mortality, particularly in rural regions in developing countries. Objective In this study, we aimed to investigate the relationship between temperature and rainfall with daily mortality in rural India. Design Daily mortality data were obtained from the Health and Demographic Surveillance System (HDSS) in Vadu, India. Daily mean temperature and rainfall data were obtained from a regional meteorological center, India Meteorological Department (IMD), Pune. A Poisson regression model was established over the study period (January 2003–May 2010) to assess the short-term relationship between weather variables and total mortality, adjusting for time trends and stratifying by both age and sex. Result Mortality was found to be significantly associated with daily ambient temperatures and rainfall, after controlling for seasonality and long-term time trends. Children aged 5 years or below appear particularly susceptible to the effects of warm and cold temperatures and heavy rainfall. The population aged 20–59 years appeared to face increased mortality on hot days. Most age groups were found to have increased mortality rates 7–13 days after rainfall events. This association was particularly evident in women. Conclusion We found the level of mortality in Vadu HDSS in rural India to be highly affected by both high and low temperatures and rainfall events, with time lags of up to 2 weeks. These results suggest that weather-related mortality may be a public health problem in rural India today. Furthermore, as changes in local climate occur, adaptation measures should be considered to mitigate the potentially negative impacts on public health in these rural communities. PMID:23195513

In situ adaptive response to climate and habitat quality variation: spatial and temporal variation in European badger (Meles meles) body weight.

PubMed

Byrne, Andrew W; Fogarty, Ursula; O'Keeffe, James; Newman, Chris

2015-09-01

Variation in climatic and habitat conditions can affect populations through a variety of mechanisms, and these relationships can act at different temporal and spatial scales. Using post-mortem badger body weight records from 15 878 individuals captured across the Republic of Ireland (7224 setts across ca. 15 000 km(2) ; 2009-2012), we employed a hierarchical multilevel mixed model to evaluate the effects of climate (rainfall and temperature) and habitat quality (landscape suitability), while controlling for local abundance (unique badgers caught/sett/year). Body weight was affected strongly by temperature across a number of temporal scales (preceding month or season), with badgers being heavier if preceding temperatures (particularly during winter/spring) were warmer than the long-term seasonal mean. There was less support for rainfall across different temporal scales, although badgers did exhibit heavier weights when greater rainfall occurred one or 2 months prior to capture. Badgers were also heavier in areas with higher landscape habitat quality, modulated by the number of individuals captured per sett, consistent with density-dependent effects reducing weights. Overall, the mean badger body weight of culled individuals rose during the study period (2009-2012), more so for males than for females. With predicted increases in temperature, and rainfall, augmented by ongoing agricultural land conversion in this region, we project heavier individual badger body weights in the future. Increased body weight has been associated with higher fecundity, recruitment and survival rates in badgers, due to improved food availability and energetic budgets. We thus predict that climate change could increase the badger population across the Republic of Ireland. Nevertheless, we emphasize that, locally, populations could still be vulnerable to extreme weather variability coupled with detrimental agricultural practice, including population management. © 2015 John Wiley & Sons Ltd.

Mapping malaria incidence distribution that accounts for environmental factors in Maputo Province - Mozambique

PubMed Central

2010-01-01

Background The objective was to study if an association exists between the incidence of malaria and some weather parameters in tropical Maputo province, Mozambique. Methods A Bayesian hierarchical model to malaria count data aggregated at district level over a two years period is formulated. This model made it possible to account for spatial area variations. The model was extended to include environmental covariates temperature and rainfall. Study period was then divided into two climate conditions: rainy and dry seasons. The incidences of malaria between the two seasons were compared. Parameter estimation and inference were carried out using MCMC simulation techniques based on Poisson variation. Model comparisons are made using DIC. Results For winter season, in 2001 the temperature covariate with estimated value of -8.88 shows no association to malaria incidence. In year 2002, the parameter estimation of the same covariate resulted in 5.498 of positive level of association. In both years rainfall covariate determines no dependency to malaria incidence. Malaria transmission is higher in wet season with both covariates positively related to malaria with posterior means 1.99 and 2.83 in year 2001. For 2002 only temperature is associated to malaria incidence with estimated value 2.23. Conclusions The incidence of malaria in year 2001, presents an independent spatial pattern for temperature in summer and for rainfall in winter seasons respectively. In year 2002 temperature determines the spatial pattern of malaria incidence in the region. Temperature influences the model in cases where both covariates are introduced in winter and summer season. Its influence is extended to the summer model with temperature covariate only. It is reasonable to state that with the occurrence of high temperatures, malaria incidence had certainly escalated in this year. PMID:20302674

Global warming induced hybrid rainy seasons in the Sahel

NASA Astrophysics Data System (ADS)

Salack, Seyni; Klein, Cornelia; Giannini, Alessandra; Sarr, Benoit; Worou, Omonlola N.; Belko, Nouhoun; Bliefernicht, Jan; Kunstman, Harald

2016-10-01

The small rainfall recovery observed over the Sahel, concomitant with a regional climate warming, conceals some drought features that exacerbate food security. The new rainfall features include false start and early cessation of rainy seasons, increased frequency of intense daily rainfall, increasing number of hot nights and warm days and a decreasing trend in diurnal temperature range. Here, we explain these mixed dry/wet seasonal rainfall features which are called hybrid rainy seasons by delving into observed data consensus on the reduction in rainfall amount, its spatial coverage, timing and erratic distribution of events, and other atmospheric variables crucial in agro-climatic monitoring and seasonal forecasting. Further composite investigations of seasonal droughts, oceans warming and the regional atmospheric circulation nexus reveal that the low-to-mid-level atmospheric winds pattern, often stationary relative to either strong or neutral El-Niño-Southern-Oscillations drought patterns, associates to basin warmings in the North Atlantic and the Mediterranean Sea to trigger hybrid rainy seasons in the Sahel. More challenging to rain-fed farming systems, our results suggest that these new rainfall conditions will most likely be sustained by global warming, reshaping thereby our understanding of food insecurity in this region.

Linking the Response of Annual Grasslands to Warming and Altered Rainfall Across Scales of Gene Expression, Species, and Ecosystem

NASA Astrophysics Data System (ADS)

Torn, M. S.; Bernard, S. M.; Castanha, C.; Fischer, M. L.; Hopkins, F. M.; Placella, S. A.; St. Clair, S. B.; Salve, R.; Sudderth, E.; Herman, D.; Ackerly, D.; Firestone, M. K.

2007-12-01

Climate change can influence terrestrial ecosystems at multiple biological levels: gene expression, species, and ecosystem. We are studying California grassland mesocosms with seven annual species (five grasses, two forbs) that were started in 2005. In the 2006-2007 growing season, they were exposed to three rainfall treatments (297, 552, and 867 mm y-1) and soil and air temperature (ambient and elevated +4oC) in replicated greenhouses. This presentation will combine plant and ecosystem level results with transcript level analyses associated with key enzymes, such as rubisco and glutamine synthetase (GS). Because rainfall is the dominant climate variable for most processes in this Mediterranean ecosystem, the effect of warming was strongly mediated by rainfall. In fact, we saw significant interactions between temperature and rainfall treatments at all three biological levels. For example, at the ecosystem level, warming led to a decrease in aboveground and total NPP under low rainfall, and an increase under high rainfall. For the dominant species, Avena barbata, warming had no effect under high rainfall, but suppressed Avena NPP in low rainfall. At the same time, warmer, wetter conditions accelerated Avena flowering by almost 15 days. This shift in phenology was presaged by observations at the transcript level. Specifically, in the high temperature, high rainfall treatment, the levels of mRNAs for RbcS and GS2 (encoding the small subunit of rubisco and the chloroplastic isoform of GS, respectively) declined while GS1 (encoding the cytosolic isoform of GS) was upregulated several weeks before heading. The transcript level response (along with soil and plant nitrogen data) indicated the leaf had switched from a carbon and nitrogen sink to a source - consistent with more mature plant function and earlier flowering. Soil CO2 respiration also showed strong rain-by-temperature interactions that were due mainly to changes in root response (respiration and/or exudates) rather than in microbial respiration. Overall, the pervasive rain-by-temperature interactions mean that it may be very difficult to predict the effect of warming alone, without accounting for changes in precipitation (in our Mediterranean system). While predictions of warming of 3-6°C in the next 100 years are fairly certain, changes in precipitation are much more uncertain, with some forecasts drier and others wetter for a given location. We suggest that uncertainty about future precipitation and the interacting influences of temperature and moisture on ecosystems are currently key limitations in predicting ecosystem response to climate change, particularly in Mediterranean ecosystems such as the one studied here.

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.

Significant influences of global mean temperature and ENSO on extreme rainfall over Southeast Asia

NASA Astrophysics Data System (ADS)

Villafuerte, Marcelino, II; Matsumoto, Jun

2014-05-01

Along with the increasing concerns on the consequences of global warming, and the accumulating records of disaster related to heavy rainfall events in Southeast Asia, this study investigates whether a direct link can be detected between the rising global mean temperature, as well as the El Niño-Southern Oscillation (ENSO), and extreme rainfall over the region. The maximum likelihood modeling that allows incorporating covariates on the location parameter of the generalized extreme value (GEV) distribution is employed. The GEV model is fitted to annual and seasonal rainfall extremes, which were taken from a high-resolution gauge-based gridded daily precipitation data covering a span of 57 years (1951-2007). Nonstationarities in extreme rainfall are detected over the central parts of Indochina Peninsula, eastern coasts of central Vietnam, northwest of the Sumatra Island, inland portions of Borneo Island, and on the northeastern and southwestern coasts of the Philippines. These nonstationarities in extreme rainfall are directly linked to near-surface global mean temperature and ENSO. In particular, the study reveals that a kelvin increase in global mean temperature anomaly can lead to an increase of 30% to even greater than 45% in annual maximum 1-day rainfall, which were observed pronouncedly over central Vietnam, southern coast of Myanmar, northwestern sections of Thailand, northwestern tip of Sumatra, central portions of Malaysia, and the Visayas island in central Philippines. Furthermore, a pronounced ENSO influence manifested on the seasonal maximum 1-day rainfall; a northward progression of 10%-15% drier condition over Southeast Asia as the El Niño develops from summer to winter is revealed. It is important therefore, to consider the results obtained here for water resources management as well as for adaptation planning to minimize the potential adverse impact of global warming, particularly on extreme rainfall and its associated flood risk over the region. Acknowledgment: This study is supported by the Tokyo Metropolitan Government through its AHRF program.

A monitor for continuous measurement of temperature, pH, and conductance of wet precipitation: Preliminary results from the Adirondack Mountains, New York

USGS Publications Warehouse

Johnsson, P.A.; Reddy, M.M.

1990-01-01

This report describes a continuous wet-only precipitation monitor designed by the U.S. Geological Survey to record variations in rainfall temperature, pH, and specific conductance at 1-min intervals over the course of storms. Initial sampling in the Adirondack Mountains showed that rainfall acidity varied over the course of summer storms, with low initial pH values increasing as storm intensity increased.This report describes a continuous wet-only precipitation monitor designed by the U.S. Geological Survey to record variations in rainfall temperature, pH, and specific conductance at 1-min intervals over the course of storms. Initial sampling in the Adirondack Mountains showed that rainfall acidity varied over the course of summer storms, with low initial pH values increasing as storm intensity increased.

Sensitivity of Rainfall Extremes Under Warming Climate in Urban India

NASA Astrophysics Data System (ADS)

Ali, H.; Mishra, V.

2017-12-01

Extreme rainfall events in urban India halted transportation, damaged infrastructure, and affected human lives. Rainfall extremes are projected to increase under the future climate. We evaluated the relationship (scaling) between rainfall extremes at different temporal resolutions (daily, 3-hourly, and 30 minutes), daily dewpoint temperature (DPT) and daily air temperature at 850 hPa (T850) for 23 urban areas in India. Daily rainfall extremes obtained from Global Surface Summary of Day Data (GSOD) showed positive regression slopes for most of the cities with median of 14%/K for the period of 1979-2013 for DPT and T850, which is higher than Clausius-Clapeyron (C-C) rate ( 7%). Moreover, sub-daily rainfall extremes are more sensitive to both DPT and T850. For instance, 3-hourly rainfall extremes obtained from Tropical Rainfall Measurement Mission (TRMM 3B42 V7) showed regression slopes more than 16%/K aginst DPT and T850 for the period of 1998-2015. Half-hourly rainfall extremes from the Integrated Multi-satellitE Retrievals (IMERGE) of Global precipitation mission (GPM) also showed higher sensitivity against changes in DPT and T850. The super scaling of rainfall extremes against changes in DPT and T850 can be attributed to convective nature of precipitation in India. Our results show that urban India may witness non-stationary rainfall extremes, which, in turn will affect stromwater designs and frequency and magniture of urban flooding.

Towards combining GPM and MFG observations to monitor near real time heavy precipitation at fine scale over India and nearby oceanic regions

NASA Astrophysics Data System (ADS)

Mishra, Anoop; Rafiq, Mohammd

2017-12-01

This is the first attempt to merge highly accurate precipitation estimates from Global Precipitation Measurement (GPM) with gap free satellite observations from Meteosat to develop a regional rainfall monitoring algorithm to estimate heavy rainfall over India and nearby oceanic regions. Rainfall signature is derived from Meteosat observations and is co-located against rainfall from GPM to establish a relationship between rainfall and signature for various rainy seasons. This relationship can be used to monitor rainfall over India and nearby oceanic regions. Performance of this technique was tested by applying it to monitor heavy precipitation over India. It is reported that our algorithm is able to detect heavy rainfall. It is also reported that present algorithm overestimates rainfall areal spread as compared to rain gauge based rainfall product. This deficiency may arise from various factors including uncertainty caused by use of different sensors from different platforms (difference in viewing geometry from MFG and GPM), poor relationship between warm rain (light rain) and IR brightness temperature, and weak characterization of orographic rain from IR signature. We validated hourly rainfall estimated from the present approach with independent observations from GPM. We also validated daily rainfall from this approach with rain gauge based product from India Meteorological Department (IMD). Present technique shows a Correlation Coefficient (CC) of 0.76, a bias of -2.72 mm, a Root Mean Square Error (RMSE) of 10.82 mm, Probability of Detection (POD) of 0.74, False Alarm Ratio (FAR) of 0.34 and a Skill score of 0.36 with daily rainfall from rain gauge based product of IMD at 0.25° resolution. However, FAR reduces to 0.24 for heavy rainfall events. Validation results with rain gauge observations reveal that present technique outperforms available satellite based rainfall estimates for monitoring heavy rainfall over Indian region.

Interannual Rainfall Variability in North-East Brazil: Observation and Model Simulation

NASA Astrophysics Data System (ADS)

Harzallah, A.; Rocha de Aragão, J. O.; Sadourny, R.

1996-08-01

The relationship between interannual variability of rainfall in north-east Brazil and tropical sea-surface temperature is studied using observations and model simulations. The simulated precipitation is the average of seven independent realizations performed using the Laboratoire de Météorologie Dynamique atmospheric general model forced by the 1970-1988 observed sea-surface temperature. The model reproduces very well the rainfall anomalies (correlation of 091 between observed and modelled anomalies). The study confirms that precipitation in north-east Brazil is highly correlated to the sea-surface temperature in the tropical Atlantic and Pacific oceans. Using the singular value decomposition method, we find that Nordeste rainfall is modulated by two independent oscillations, both governed by the Atlantic dipole, but one involving only the Pacific, the other one having a period of about 10 years. Correlations between precipitation in north-east Brazil during February-May and the sea-surface temperature 6 months earlier indicate that both modes are essential to estimate the quality of the rainy season.

Projecting Changes in S. Florida Rainfall for the 21st century: Scenarios, Downscaling and Analysis

NASA Astrophysics Data System (ADS)

Cioffi, F.; Lall, U.; Monti, A.

2013-12-01

A Non-Homogeneous hidden Markov Models (NHMM) is developed using a 65-years record (1948-2012) of daily rainfall amount at nineteen stations in South Florida and re-analysis atmospheric fields of Temperature (T) at 1000 hPa, Geo Potential Height (GPH) at 1000 hPa, Meridional Winds (MW) and Zonal Winds (ZW) at 850 hPa, and Zonal Winds on the specific latitude of 27N (ZW27N) from 10 to 1000 hPa. The NHMM fitted is then used for predicting future rainfall patterns under global warming scenario (RCP8.5), using predictors from the CMCC-CMS simulations from 1950-2100. The model directly includes a consideration of seasonality through changes in the driving variables thus addressing the question of how future changes in seasonality of precipitation can also be modeled. The results of the simulations obtained by using the downscaling model NHMM, with predictors derived from the simulations of CMCC-CMS CGM, in the worst conditions of global warming as simulated by RCP8.5 scenario, seems to indicate that, as a consequence of increase of CO2 concentration and temperature, South Florida should be subjected to more frequent dry conditions for the most part of the year, due mainly to a reduction of number of wet days and, at the same time, the territory should be also affected by extreme rainfall events that are more intense than the present ones. What appears from results is an increases of rainfall variability. This scenario seems coherent with the trends of rainfall patterns observed in the XX century. An investigation on the causes of such hydrologic changes, and specifically on the role of North Atlantic Subtropical High is pursued.

Attribution of Extreme Rainfall Events in the South of France Using EURO-CORDEX Simulations

NASA Astrophysics Data System (ADS)

Luu, L. N.; Vautard, R.; Yiou, P.

2017-12-01

The Mediterranean region regularly undergoes episodes of intense precipitation in the fall season that exceed 300mm a day. This study focuses on the role of climate change on the dynamics of the events that occur in the South of France. We used an ensemble of 10 EURO-CORDEX model simulations with two horizontal resolutions (EUR-11: 0.11° and EUR-44: 0.44°) for the attribution of extreme rainfall in the fall in the Cevennes mountain range (South of France). The biases of the simulations were corrected with simple scaling adjustment and a quantile correction (CDFt). This produces five datasets including EUR-44 and EUR-11 with and without scaling adjustment and CDFt-EUR-11, on which we test the impact of resolution and bias correction on the extremes. Those datasets, after pooling all of models together, are fitted by a stationary Generalized Extreme Value distribution for several periods to estimate a climate change signal in the tail of distribution of extreme rainfall in the Cévenne region. Those changes are then interpreted by a scaling model that links extreme rainfall with mean and maximum daily temperature. The results show that higher-resolution simulations with bias adjustment provide a robust and confident increase of intensity and likelihood of occurrence of autumn extreme rainfall in the area in current climate in comparison with historical climate. The probability (exceedance probability) of 1-in-1000-year event in historical climate may increase by a factor of 1.8 under current climate with a confident interval of 0.4 to 5.3 following the CDFt bias-adjusted EUR-11. The change of magnitude appears to follow the Clausius-Clapeyron relation that indicates a 7% increase in rainfall per 1oC increase in temperature.

Biological soil crust succession impact on soil moisture and temperature in the sub-surface along a rainfall gradient

NASA Astrophysics Data System (ADS)

Zaady, E.; Yizhaq, H.; Ashkenazy, Y.

2012-04-01

Biological soil crusts produce mucilage sheets of polysaccharides that cover the soil surface. This hydrophobic coating can seal the soil micro-pores and thus cause reduction of water permeability and may influence soil temperature. This study evaluates the impact of crust composition on sub-surface water and temperature over time. We hypothesized that the successional stages of biological soil crusts, affect soil moisture and temperature differently along a rainfall gradient throughout the year. Four experimental sites were established along a rainfall gradient in the western Negev Desert. At each site three treatments; crust removal, pure sand (moving dune) and natural crusted were monitored. Crust successional stage was measured by biophysiological and physical measurements, soil water permeability by field mini-Infiltrometer, soil moisture by neutron scattering probe and temperature by sensors, at different depths. Our main interim conclusions from the ongoing study along the rainfall gradient are: 1. the biogenic crust controls water infiltration into the soil in sand dunes, 2. infiltration was dependent on the composition of the biogenic crust. It was low for higher successional stage crusts composed of lichens and mosses and high with cyanobacterial crust. Thus, infiltration rate controlled by the crust is inverse to the rainfall gradient. Continuous disturbances to the crust increase infiltration rates, 3. despite the different rainfall amounts at the sites, soil moisture content below 50 cm is almost the same. We therefore predict that climate change in areas that are becoming dryer (desertification) will have a positive effect on soil water content and vice versa.

Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature

NASA Astrophysics Data System (ADS)

Hassan, Zulkarnain; Shamsudin, Supiah; Harun, Sobri

2014-04-01

Climate change is believed to have significant impacts on the water basin and region, such as in a runoff and hydrological system. However, impact studies on the water basin and region are difficult, since general circulation models (GCMs), which are widely used to simulate future climate scenarios, do not provide reliable hours of daily series rainfall and temperature for hydrological modeling. There is a technique named as "downscaling techniques", which can derive reliable hour of daily series rainfall and temperature due to climate scenarios from the GCMs output. In this study, statistical downscaling models are used to generate the possible future values of local meteorological variables such as rainfall and temperature in the selected stations in Peninsular of Malaysia. The models are: (1) statistical downscaling model (SDSM) that utilized the regression models and stochastic weather generators and (2) Long Ashton research station weather generator (LARS-WG) that only utilized the stochastic weather generators. The LARS-WG and SDSM models obviously are feasible methods to be used as tools in quantifying effects of climate change condition in a local scale. SDSM yields a better performance compared to LARS-WG, except SDSM is slightly underestimated for the wet and dry spell lengths. Although both models do not provide identical results, the time series generated by both methods indicate a general increasing trend in the mean daily temperature values. Meanwhile, the trend of the daily rainfall is not similar to each other, with SDSM giving a relatively higher change of annual rainfall compared to LARS-WG.

Estimation of Rainfall Rates from Passive Microwave Remote Sensing.

NASA Astrophysics Data System (ADS)

Sharma, Awdhesh Kumar

Rainfall rates have been estimated using the passive microwave and visible/infrared remote sensing techniques. Data of September 14, 1978 from the Scanning Multichannel Microwave Radiometer (SMMR) on board SEA SAT-A and the Visible and Infrared Spin Scan Radiometer (VISSR) on board GOES-W (Geostationary Operational Environmental Satellite - West) was obtained and analyzed for rainfall rate retrieval. Microwave brightness temperatures (MBT) are simulated, using the microwave radiative transfer model (MRTM) and atmospheric scattering models. These MBT were computed as a function of rates of rainfall from precipitating clouds which are in a combined phase of ice and water. Microwave extinction due to ice and liquid water are calculated using Mie-theory and Gamma drop size distributions. Microwave absorption due to oxygen and water vapor are based on the schemes given by Rosenkranz, and Barret and Chung. The scattering phase matrix involved in the MRTM is found using Eddington's two stream approximation. The surface effects due to winds and foam are included through the ocean surface emissivity model. Rainfall rates are then inverted from MBT using the optimization technique "Leaps and Bounds" and multiple linear regression leading to a relationship between the rainfall rates and MBT. This relationship has been used to infer the oceanic rainfall rates from SMMR data. The VISSR data has been inverted for the rainfall rates using Griffith's scheme. This scheme provides an independent means of estimating rainfall rates for cross checking SMMR estimates. The inferred rainfall rates from both techniques have been plotted on a world map for comparison. A reasonably good correlation has been obtained between the two estimates.

Climatic trends over Ethiopia: regional signals and drivers

USGS Publications Warehouse

Jury, Mark R.; Funk, Christopher C.

2013-01-01

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

Temperature and rainfall are related to fertility rate after spring artificial insemination in small ruminants

NASA Astrophysics Data System (ADS)

Abecia, J. A.; Arrébola, F.; Macías, A.; Laviña, A.; González-Casquet, O.; Benítez, F.; Palacios, C.

2016-10-01

A total number of 1092 artificial inseminations (AIs) performed from March to May were documented over four consecutive years on 10 Payoya goat farms (36° N) and 19,392 AIs on 102 Rasa Aragonesa sheep farms (41° N) over 10 years. Mean, maximum, and minimum ambient temperatures, mean relative humidity, mean solar radiation, and total rainfall on each insemination day were recorded. Overall, fertility rates were 58 % in goats and 45 % in sheep. The fertility rates of the highest and lowest deciles of each of the meteorological variables indicated that temperature and rainfall had a significant effect on fertility in goats. Specifically, inseminations that were performed when mean (68 %), maximum (68 %), and minimum (66 %) temperatures were in the highest decile, and rainfall was in the lowest decile (59 %), had a significantly ( P < 0.0001) higher proportion of does that became pregnant than did the ewes in the lowest decile (56, 54, 58, and 49 %, respectively). In sheep, the fertility rates of the highest decile of mean (62 %), maximum (62 %), and minimum (52 %) temperature, RH (52 %), THI (53 %), and rainfall (45 %) were significantly higher ( P < 0.0001) than were the fertility rates among ewes in the lowest decile (46, 45, 45, 45, 46, and 43 %, respectively). In conclusion, weather was related to fertility in small ruminants after AI in spring. It remains to be determined whether scheduling the dates of insemination based on forecasted temperatures can improve the success of AI in goats and sheep.

Untangling the Impacts of Climate Change on Waterborne Diseases: a Systematic Review of Relationships between Diarrheal Diseases and Temperature, Rainfall, Flooding, and Drought.

PubMed

Levy, Karen; Woster, Andrew P; Goldstein, Rebecca S; Carlton, Elizabeth J

2016-05-17

Global climate change is expected to affect waterborne enteric diseases, yet to date there has been no comprehensive, systematic review of the epidemiological literature examining the relationship between meteorological conditions and diarrheal diseases. We searched PubMed, Embase, Web of Science, and the Cochrane Collection for studies describing the relationship between diarrheal diseases and four meteorological conditions that are expected to increase with climate change: ambient temperature, heavy rainfall, drought, and flooding. We synthesized key areas of agreement and evaluated the biological plausibility of these findings, drawing from a diverse, multidisciplinary evidence base. We identified 141 articles that met our inclusion criteria. Key areas of agreement include a positive association between ambient temperature and diarrheal diseases, with the exception of viral diarrhea and an increase in diarrheal disease following heavy rainfall and flooding events. Insufficient evidence was available to evaluate the effects of drought on diarrhea. There is evidence to support the biological plausibility of these associations, but publication bias is an ongoing concern. Future research evaluating whether interventions, such as improved water and sanitation access, modify risk would further our understanding of the potential impacts of climate change on diarrheal diseases and aid in the prioritization of adaptation measures.

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

A preliminary look at the impact of warming Mediterranean Sea temperatures on some aspects of extreme thunderstorm events in Italy

NASA Astrophysics Data System (ADS)

Gallus, William; Parodi, Antonio; Miglietta, Marcello; Maugeri, Maurizio

2017-04-01

As the global climate has warmed in recent decades, interest has grown in the impacts on extreme events associated with thunderstorms such as tornadoes and intense rainfall that can cause flash flooding. Because warmer temperatures allow the atmosphere to contain larger values of water vapor, it is generally accepted that short-term rainfall may become more intense in a future warmer climate. Regarding tornadoes, it is more difficult to say what might happen since although increased temperatures and humidity in the lowest part of the troposphere should increase thermodynamic instability, allowing for stronger thunderstorm updrafts, vertical wind shear necessary for storm-scale rotation may decrease as the pole to equator temperature gradient weakens. The Mediterranean Sea is an important source for moisture that fuels thunderstorms in Italy, and it has been warming faster than most water bodies in recent decades. The present study uses three methods to gain preliminary insight into the role that the warming Mediterranean may have on tornadoes and thunderstorms with intense rainfall in Italy. First, a historical archive of Italian tornadoes has been updated for the 1990s, and it will be used along with other data from the European Severe Weather Database to discuss possible trends in tornado occurrence. Second, convection-allowing Weather Research and Forecasting (WRF) model simulations have been performed for three extreme events to examine sensitivity to both the sea surface temperatures and other model parameters. These events include a flash flood-producing storm event near Milan, a non-tornadic severe hail event in far northeastern Italy, and the Mira EF-4 tornado of July 2015. Sensitivities in rainfall amount, radar reflectivity and storm structure, and storm rotation will be discussed. Finally, changes in the frequency of intense mesoscale convective system events in and near the Ligurian Sea, inferred from the presence of strong convergence lines in EXPRESS-Hydro regional climate model output, will be examined.

The Role of Temperature and Humidity on Seasonal Influenza in Tropical Areas: Guatemala, El Salvador and Panama, 2008-2013

NASA Technical Reports Server (NTRS)

Soebiyanto, Radina P.; Clara, Wilfrido; Jara, Jorge; Castillo, Leticia; Sorto, Oscar Rene; Marinero, Sidia; Antinori, Maria E. Barnett de; McCracken, John P.; Widdowson, Marc-Alain; Azziz-Baumgartner, Eduardo;

The role of temperature and humidity on seasonal influenza in tropical areas: Guatemala, El Salvador and Panama, 2008-2013.

PubMed

Soebiyanto, Radina P; Clara, Wilfrido; Jara, Jorge; Castillo, Leticia; Sorto, Oscar Rene; Marinero, Sidia; de Antinori, María E Barnett; McCracken, John P; Widdowson, Marc-Alain; Azziz-Baumgartner, Eduardo; Kiang, Richard K

2014-01-01

The role of meteorological factors on influenza transmission in the tropics is less defined than in the temperate regions. We assessed the association between influenza activity and temperature, specific humidity and rainfall in 6 study areas that included 11 departments or provinces within 3 tropical Central American countries: Guatemala, El Salvador and Panama. Logistic regression was used to model the weekly proportion of laboratory-confirmed influenza positive samples during 2008 to 2013 (excluding pandemic year 2009). Meteorological data was obtained from the Tropical Rainfall Measuring Mission satellite and the Global Land Data Assimilation System. We found that specific humidity was positively associated with influenza activity in El Salvador (Odds Ratio (OR) and 95% Confidence Interval of 1.18 (1.07-1.31) and 1.32 (1.08-1.63)) and Panama (OR = 1.44 (1.08-1.93) and 1.97 (1.34-2.93)), but negatively associated with influenza activity in Guatemala (OR = 0.72 (0.6-0.86) and 0.79 (0.69-0.91)). Temperature was negatively associated with influenza in El Salvador's west-central departments (OR = 0.80 (0.7-0.91)) whilst rainfall was positively associated with influenza in Guatemala's central departments (OR = 1.05 (1.01-1.09)) and Panama province (OR = 1.10 (1.05-1.14)). In 4 out of the 6 locations, specific humidity had the highest contribution to the model as compared to temperature and rainfall. The model performed best in estimating 2013 influenza activity in Panama and west-central El Salvador departments (correlation coefficients: 0.5-0.9). The findings highlighted the association between influenza activity and specific humidity in these 3 tropical countries. Positive association with humidity was found in El Salvador and Panama. Negative association was found in the more subtropical Guatemala, similar to temperate regions. Of all the study locations, Guatemala had annual mean temperature and specific humidity that were lower than the others.

Changing climate and endangered high mountain ecosystems in Colombia.

PubMed

Ruiz, Daniel; Moreno, Hernán Alonso; Gutiérrez, María Elena; Zapata, Paula Andrea

2008-07-15

High mountain ecosystems are among the most sensitive environments to changes in climatic conditions occurring on global, regional and local scales. The article describes the changing conditions observed over recent years in the high mountain basin of the Claro River, on the west flank of the Colombian Andean Central mountain range. Local ground truth data gathered at 4150 m, regional data available at nearby weather stations, and satellite info were used to analyze changes in the mean and the variance, and significant trends in climatic time series. Records included minimum, mean and maximum temperatures, relative humidity, rainfall, sunshine, and cloud characteristics. In high levels, minimum and maximum temperatures during the coldest days increased at a rate of about 0.6 degrees C/decade, whereas maximum temperatures during the warmest days increased at a rate of about 1.3 degrees C/decade. Rates of increase in maximum, mean and minimum diurnal temperature range reached 0.6, 0.7, and 0.5 degrees C/decade. Maximum, mean and minimum relative humidity records showed reductions of about 1.8, 3.9 and 6.6%/decade. The total number of sunny days per month increased in almost 2.1 days. The headwaters exhibited no changes in rainfall totals, but evidenced an increased occurrence of unusually heavy rainfall events. Reductions in the amount of all cloud types over the area reached 1.9%/decade. In low levels changes in mean monthly temperatures and monthly rainfall totals exceeded + 0.2 degrees C and - 4% per decade, respectively. These striking changes might have contributed to the retreat of glacier icecaps and to the disappearance of high altitude water bodies, as well as to the occurrence and rapid spread of natural and man-induced forest fires. Significant reductions in water supply, important disruptions of the integrity of high mountain ecosystems, and dramatic losses of biodiversity are now a steady menu of the severe climatic conditions experienced by these fragile tropical environments.

Analysis of the variation of the 0°C isothermal altitude during rainfall events

NASA Astrophysics Data System (ADS)

Zeimetz, Fränz; Garcìa, Javier; Schaefli, Bettina; Schleiss, Anton J.

2016-04-01

In numerous countries of the world (USA, Canada, Sweden, Switzerland,…), the dam safety verifications for extreme floods are realized by referring to the so called Probable Maximum Flood (PMF). According to the World Meteorological Organization (WMO), this PMF is determined based on the PMP (Probable Maximum Precipitation). The PMF estimation is performed with a hydrological simulation model by routing the PMP. The PMP-PMF simulation is normally event based; therefore, if no further information is known, the simulation needs assumptions concerning the initial soil conditions such as saturation or snow cover. In addition, temperature series are also of interest for the PMP-PMF simulations. Temperature values can not only be deduced from temperature measurement but also using the temperature gradient method, the 0°C isothermal altitude can lead to temperature estimations on the ground. For practitioners, the usage of the isothermal altitude for referring to temperature is convenient and simpler because one value can give information over a large region under the assumption of a certain temperature gradient. The analysis of the evolution of the 0°C isothermal altitude during rainfall events is aimed here and based on meteorological soundings from the two sounding stations Payerne (CH) and Milan (I). Furthermore, hourly rainfall and temperature data are available from 110 pluviometers spread over the Swiss territory. The analysis of the evolution of the 0°C isothermal altitude is undertaken for different precipitation durations based on the meteorological measurements mentioned above. The results show that on average, the isothermal altitude tends to decrease during the rainfall events and that a correlation between the duration of the altitude loss and the duration of the rainfall exists. A significant difference in altitude loss is appearing when the soundings from Payerne and Milan are compared.

Constraining the Sensitivity of Amazonian Rainfall with Observations of Surface Temperature

NASA Astrophysics Data System (ADS)

Dolman, A. J.; von Randow, C.; de Oliveira, G. S.; Martins, G.; Nobre, C. A.

2016-12-01

Earth System models generally do a poor job in predicting Amazonian rainfall, necessitating the need to look for observational constraints on their predictability. We use observed surface temperature and precipitation of the Amazon and a set of 21 CMIP5 models to derive an observational constraint of the sensitivity of rainfall to surface temperature (dP/dT). From first principles such a relation between the surface temperature of the earth and the amount of precipitation through the surface energy balance should exist, particularly in the tropics. When de-trended anomalies in surface temperature and precipitation from a set of datasets are plotted, a clear linear relation between surface temperature and precipitation appears. CMIP5 models show a similar relation with relatively cool models having a larger sensitivity, producing more rainfall. Using the ensemble of models and the observed surface temperature we were able to derive an emerging constraint, reducing the dPdt sensitivity of the CMIP5 model from -0.75 mm day-1 0C-1 (+/- 0.54 SD) to -0.77 mm day-1 0C-1 with a reduced uncertainty of about a factor 5. dPdT from the observation is -0.89 mm day-1 0C-1 . We applied the method to wet and dry season separately noticing that in the wet season we shifted the mean and reduced uncertainty, while in the dry season we very much reduced uncertainty only. The method can be applied to other model simulations such as specific deforestation scenarios to constrain the sensitivity of rainfall to surface temperature. We discuss the implications of the constrained sensitivity for future Amazonian predictions.

How much complexity is warranted in a rainfall-runoff model? Findings obtained from symbolic regression, using Eureqa

NASA Astrophysics Data System (ADS)

Abrahart, R. J.; Beriro, D. J.

2012-04-01

The information content in a rainfall-runoff record is sufficient to support models of only very limited complexity (Jakeman and Hornberger, 1993). This begs the question of what limits should observed data place on the allowable complexity of rainfall-runoff models? Eureqa1 (Schmidt and Lipson, 2009) - pronounced "eureka" - is a software tool for finding equations and detecting mathematical relationships in a dataset. The challenge, for both software and modeller, is to identify, by means of symbolic regression, the simplest mathematical formulas which describe the underlying mechanisms that produced the data. It actually delivers, however, a series of preferred modelling solutions comprising one champion for each specific level of complexity i.e. related to solution enlargement involving the progressive incorporation of additional permitted factors (internal operators/ external drivers). The potential benefit of increased complexity can as a result be assessed in a rational manner. Eureqa is free to download and use; and, in the current study, has been employed to construct a set of rainfall-runoff transfer function models for the Annapolis River at Wilmot, in north-western Nova Scotia, Canada. The climatic conditions in this catchment present an interesting set of modelling challenges; daily variations and seasonal changes in temperature, snowfall and retention result in great difficulty for runoff prediction by means of a data-driven approach. Data from 10 years of daily observations are used in the present study (01/01/2000-31/12/2009): comprising [i] discharge, [ii] total rainfall (excluding snowfall), [iii] total snowfall, [iv] thickness of snow cover, and [v] maximum and [vi] minimum temperature. Precipitation occurs throughout the whole year being slightly lower during summer. Snowfall is common from November until April and rare hurricane weather may occur in autumn. The average maximum temperature is below 0 0C in January and February, but significant variation may result, producing milder weather and snowmelt throughout the winter. The average minimum temperature is below 0 0C during half of the year, such that freezing and melting occur frequently. The principal rainfall-runoff drivers are found to be lagged discharge and lagged precipitation, as expected. The complexity-accuracy trade-off, is nevertheless found to exhibit threshold behaviour, in which snow cover is eventually included at higher levels of complexity to account for multifaceted cold season processes.

Evaluation and prediction of anomalous El Niño generated rainfalls in Peruvian and Ecuadorian coastal zone

NASA Astrophysics Data System (ADS)

Cadier, E.; Rossel, F.; Pouyaud, B.; Raymond, M.

2003-04-01

Coastal regions of Southern Ecuador and Northern Peru rainfalls are well known for their sensitivity to the El Niño/Southern Oscillation (ENSO) phenomenon. New monthly rainfall index series were set up from a network of 200 rainfall stations in the Ecuadorian and Peruvian coastal region. Throughout the study, rainfall was modelled keeping a distinction between a "dependent" data set used as a training period and an "independent" portion of the record reserved for validation. Multiple regression models were proposed to predict monthly rainfall in the Guayaquil and in northern coastal Peru, using as predictors, sea surface temperature, precipitation, meridional and zonal wind in the eastern equatorial Pacific. Then, the resulting equations were used to predict rainfall anomalies in the independent data set. In the Guayaquil zone, there is considerable predictable expertise for the rainy months of the year, the best predictability being assessed from March to May. The multiple linear correlations explain 60 to 82% of the monthly-precipitation variance. Northern coastal Ecuadorian region's preseason rainfall is the most powerful predictor for the rainy season peak in Guayaquil, while the eastern equatorial Pacific sea surface temperature is the most powerful predictor for the end of rainy season. KEY WORDS: El Niño, Rainfall Prediction, Ecuador.

Mineralogical evidence of reduced East Asian summer monsoon rainfall on the Chinese loess plateau during the early Pleistocene interglacials

NASA Astrophysics Data System (ADS)

Meng, Xianqiang; Liu, Lianwen; Wang, Xingchen T.; Balsam, William; Chen, Jun; Ji, Junfeng

2018-03-01

The East Asian summer monsoon (EASM) is an important component of the global climate system. A better understanding of EASM rainfall variability in the past can help constrain climate models and better predict the response of EASM to ongoing global warming. The warm early Pleistocene, a potential analog of future climate, is an important period to study EASM dynamics. However, existing monsoon proxies for reconstruction of EASM rainfall during the early Pleistocene fail to disentangle monsoon rainfall changes from temperature variations, complicating the comparison of these monsoon records with climate models. Here, we present three 2.6 million-year-long EASM rainfall records from the Chinese Loess Plateau (CLP) based on carbonate dissolution, a novel proxy for rainfall intensity. These records show that the interglacial rainfall on the CLP was lower during the early Pleistocene and then gradually increased with global cooling during the middle and late Pleistocene. These results are contrary to previous suggestions that a warmer climate leads to higher monsoon rainfall on tectonic timescales. We propose that the lower interglacial EASM rainfall during the early Pleistocene was caused by reduced sea surface temperature gradients across the equatorial Pacific, providing a testable hypothesis for climate models.

Amazon Basin climate under global warming: the role of the sea surface temperature.

PubMed

Harris, Phil P; Huntingford, Chris; Cox, Peter M

2008-05-27

The Hadley Centre coupled climate-carbon cycle model (HadCM3LC) predicts loss of the Amazon rainforest in response to future anthropogenic greenhouse gas emissions. In this study, the atmospheric component of HadCM3LC is used to assess the role of simulated changes in mid-twenty-first century sea surface temperature (SST) in Amazon Basin climate change. When the full HadCM3LC SST anomalies (SSTAs) are used, the atmosphere model reproduces the Amazon Basin climate change exhibited by HadCM3LC, including much of the reduction in Amazon Basin rainfall. This rainfall change is shown to be the combined effect of SSTAs in both the tropical Atlantic and the Pacific, with roughly equal contributions from each basin. The greatest rainfall reduction occurs from May to October, outside of the mature South American monsoon (SAM) season. This dry season response is the combined effect of a more rapid warming of the tropical North Atlantic relative to the south, and warm SSTAs in the tropical east Pacific. Conversely, a weak enhancement of mature SAM season rainfall in response to Atlantic SST change is suppressed by the atmospheric response to Pacific SST. This net wet season response is sufficient to prevent dry season soil moisture deficits from being recharged through the SAM season, leading to a perennial soil moisture reduction and an associated 30% reduction in annual Amazon Basin net primary productivity (NPP). A further 23% NPP reduction occurs in response to a 3.5 degrees C warmer air temperature associated with a global mean SST warming.

Nonlinear Meridional Moisture Advection and the ENSO-Southern China Rainfall Teleconnection

NASA Astrophysics Data System (ADS)

Wang, Qiang; Cai, Wenju; Zeng, Lili; Wang, Dongxiao

2018-05-01

In the boreal cooler months of 2015, southern China (SC) experienced the largest rainfall since 1950, exceeding 4 times the standard deviation of SC rainfall. Although an El Niño typically induces a positive SC rainfall anomaly during these months, the unprecedented rainfall increase cannot be explained by the strong El Niño of 2015/2016, and the dynamics is unclear. Here we show that a nonlinear meridional moisture advection contributes substantially to the unprecedented rainfall increase. During cooler months of 2015, the meridional flow anomaly over the South China Sea region, which acts on an El Niño-induced anomalous meridional moisture gradient, is particularly large and is supported by an anomalous zonal sea surface temperature gradient over the northwestern Pacific, which recorded its largest value in 2015 since 1950. Our study highlights, for the first time, the importance of the nonlinear process associated with the combined impact of a regional sea surface temperature gradient and large-scale El Niño anomalies in forcing El Niño rainfall teleconnection.

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.

Understanding the science of climate change: Talking points - Impacts to the Atlantic Coast

Treesearch

Rachel Loehman; Greer Anderson

2009-01-01

Observed 20th century climate changes in the Atlantic Coast bioregion include warmer air and sea surface temperatures, increased winter precipitation (especially rainfall), and an increased frequency of extreme precipitation events. Climate change impacts during the century include phenological shifts in plant and animals species, such as earlier occurrence of lilac...

Indian summer monsoon rainfall variability during 2014 and 2015 and associated Indo-Pacific upper ocean temperature patterns

NASA Astrophysics Data System (ADS)

Kakatkar, Rashmi; Gnanaseelan, C.; Chowdary, J. S.; Parekh, Anant; Deepa, J. S.

2018-02-01

In this study, factors responsible for the deficit Indian Summer Monsoon (ISM) rainfall in 2014 and 2015 and the ability of Indian Institute of Tropical Meteorology-Global Ocean Data Assimilation System (IITM-GODAS) in representing the oceanic features are examined. IITM-GODAS has been used to provide initial conditions for seasonal forecast in India during 2014 and 2015. The years 2014 and 2015 witnessed deficit ISM rainfall but were evolved from two entirely different preconditions over Pacific. This raises concern over the present understanding of the role of Pacific Ocean on ISM variability. Analysis reveals that the mechanisms associated with the rainfall deficit over the Indian Subcontinent are different in the two years. It is found that remote forcing in summer of 2015 due to El Niño is mostly responsible for the deficit monsoon rainfall through changes in Walker circulation and large-scale subsidence. In the case of the summer of 2014, both local circulation with anomalous anticyclone over central India and intrusion of mid-latitude dry winds from north have contributed for the deficit rainfall. In addition to the above, Tropical Indian Ocean (TIO) sea surface temperature (SST) and remote forcing from Pacific Ocean also modulated the ISM rainfall. It is observed that Pacific SST warming has extended westward in 2014, making it a basin scale warming unlike the strong El Niño year 2015. The eastern equatorial Indian Ocean is anomalously warmer than west in summer of 2014, and vice versa in 2015. These differences in SST in both tropical Pacific and TIO have considerable impact on ISM rainfall in 2014 and 2015. The study reveals that initializing coupled forecast models with proper upper ocean temperature over the Indo-Pacific is therefore essential for improved model forecast. It is important to note that the IITM-GODAS which assimilates only array for real-time geostrophic oceanography (ARGO) temperature and salinity profiles could capture most of the observed surface and subsurface temperature variations from early spring to summer during the years 2014 and 2015 over the Indo-Pacific region. This study highlights the importance of maintaining observing systems such as ARGO for accurate monsoon forecast.

Modulation of SSM/I microwave soil radiances by rainfall

NASA Technical Reports Server (NTRS)

Heymsfield, Gerald M.; Fulton, Richard

1992-01-01

The feasibility of using SSM/I satellite data for estimating the soil moisture content was investigated by correlating the rainfall and soil moisture data with values of the SSM/I microwave brightness temperature obtained for the lower Great Plains in the United States during 1987. It was found that the areas of lowest brightness temperatures coincided with regions of bare soil which had received significant rainfall. The time-history plots of the brightness temperature and the antecedent precipitation index during an extremely large rain event indicated a slow recovery period (about 15 days) back to the dry soil state. However, regions covered with vegetation showed smaller temperature drops and much weaker correlation with rain events, questioning the feasibility of using SSM/I measurements for estimations of soil moisture in regions containing vegetation-covered soil.

Relationships between southeastern Australian rainfall and sea surface temperatures examined using a climate model

NASA Astrophysics Data System (ADS)

Watterson, I. G.

2010-05-01

Rainfall in southeastern Australia has declined in recent years, particularly during austral autumn over the state of Victoria. A recent study suggests that sea surface temperature (SST) variations in both the Indonesian Throughflow (ITF) region and in a meridional dipole in the central Indian Ocean have influenced Victorian late autumn rainfall since 1950. However, it remains unclear to what extent SSTs in these and other regions force such a teleconnection. Analysis of a 1080 year simulation by the climate model CSIRO Mk3.5 shows that the model Victorian rainfall is correlated rather realistically with SSTs but that part of the above relationships is due to the model ENSO. Furthermore, the remote patterns of pressure, rainfall, and land temperature greatly diminish when the data are lagged by 1 month, suggesting that the true forcing by the persisting SSTs is weak. In a series of simulations of the atmospheric Mk3.5 with idealized SST anomalies, raised SSTs to the east of Indonesia lower the simulated Australian rainfall, while those to the west raise it. A positive ITF anomaly lowers pressure over Australia, but with little effect on Victorian rainfall. The meridional dipole and SSTs to the west and southeast of Australia have little direct effect on southeastern Australia in the model. The results suggest that tropical SSTs predominate as an influence on Victorian rainfall. However, the SST indices appear to explain only a fraction of the observed trend, which in the case of decadal means remains within the range of unforced variability simulated by Mk3.5.

Temperature and rainfall interact to control carbon cycling in tropical forests.

PubMed

Taylor, Philip G; Cleveland, Cory C; Wieder, William R; Sullivan, Benjamin W; Doughty, Christopher E; Dobrowski, Solomon Z; Townsend, Alan R

2017-06-01

Tropical forests dominate global terrestrial carbon (C) exchange, and recent droughts in the Amazon Basin have contributed to short-term declines in terrestrial carbon dioxide uptake and storage. However, the effects of longer-term climate variability on tropical forest carbon dynamics are still not well understood. We synthesised field data from more than 150 tropical forest sites to explore how climate regulates tropical forest aboveground net primary productivity (ANPP) and organic matter decomposition, and combined those data with two existing databases to explore climate - C relationships globally. While previous analyses have focused on the effects of either temperature or rainfall on ANPP, our results highlight the importance of interactions between temperature and rainfall on the C cycle. In cool forests (< 20 °C), high rainfall slowed rates of C cycling, but in warm tropical forests (> 20 °C) it consistently enhanced both ANPP and decomposition. At the global scale, our analysis showed an increase in ANPP with rainfall in relatively warm sites, inconsistent with declines in ANPP with rainfall reported previously. Overall, our results alter our understanding of climate - C cycle relationships, with high precipitation accelerating rates of C exchange with the atmosphere in the most productive biome on earth. © 2017 John Wiley & Sons Ltd/CNRS.

East Asian Summer Monsoon Rainfall: A Historical Perspective of the 1998 Flood over Yangtze River

NASA Technical Reports Server (NTRS)

Weng, H.-Y.; Lau, K.-M.

1999-01-01

One of the main factors that might have caused the disastrous flood in China during 1998 summer is long-term variations that include a trend indicating increasing monsoon rainfall over the Yangtze River Valley. China's 160-station monthly rainfall anomaly for the summers of 1955-98 is analyzed for exploring such long-term variations. Singular value decomposition (SVD) between the summer rainfall and the global sea surface temperature (SST) anomalies reveals that the rainfall over Yangtze River Valley is closely related to global and regional SST variabilities at both interannual and interdecadal timescales. SVD1 mode links the above normal rainfall condition in central China to an El Nino-like SSTA distribution, varying on interannual timescale modified by a trend during the period. SVD3 mode links positive rainfall anomaly in Yangtze River Valley to the warm SST anomaly in the subtropical western Pacific, varying on interannual timescales modified by interdecadal timescales. This link tends to be stronger when the Nino3 area becomes colder and the western subtropical Pacific becomes warmer. The 1998 summer is a transition season when the 1997/98 El Nino event was in its decaying phase, and the SST in the Nino3 area emerged below normal anomaly while the subtropical western Pacific SST above normal. Thus, the first and third SVD modes become dominant in 1998 summer, favoring more Asian summer monsoon rainfall over the Yangtze River Valley.

Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Lin, Xin; Zhang, Sara Q.; Hou, Arthur Y.

2006-01-01

Global microwave rainfall retrievals from a 5-satellite constellation, including TMI from TRMM, SSWI from DMSP F13, F14 and F15, and AMSR-E from EOS-AQUA, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) using a 1-D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses and forecasts is examined at various temporal and spatial scales. This study demonstrates that the 1-D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over the land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly-mean and 6-hour time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1-D VCA algorithm, by compensating for errors in the model s moist time-tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall-assimilation m especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicates that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity are more realistically captured across the front. Short-term forecasts using initial conditions assimilated with rainfall data also show slight improvements. 1

Increase in flood risk resulting from climate change in a developed urban watershed - the role of storm temporal patterns

NASA Astrophysics Data System (ADS)

Hettiarachchi, Suresh; Wasko, Conrad; Sharma, Ashish

2018-03-01

The effects of climate change are causing more frequent extreme rainfall events and an increased risk of flooding in developed areas. Quantifying this increased risk is of critical importance for the protection of life and property as well as for infrastructure planning and design. The updated National Oceanic and Atmospheric Administration (NOAA) Atlas 14 intensity-duration-frequency (IDF) relationships and temporal patterns are widely used in hydrologic and hydraulic modeling for design and planning in the United States. Current literature shows that rising temperatures as a result of climate change will result in an intensification of rainfall. These impacts are not explicitly included in the NOAA temporal patterns, which can have consequences on the design and planning of adaptation and flood mitigation measures. In addition there is a lack of detailed hydraulic modeling when assessing climate change impacts on flooding. The study presented in this paper uses a comprehensive hydrologic and hydraulic model of a fully developed urban/suburban catchment to explore two primary questions related to climate change impacts on flood risk. (1) How do climate change effects on storm temporal patterns and rainfall volumes impact flooding in a developed complex watershed? (2) Is the storm temporal pattern as critical as the total volume of rainfall when evaluating urban flood risk? We use the NOAA Atlas 14 temporal patterns, along with the expected increase in temperature for the RCP8.5 scenario for 2081-2100, to project temporal patterns and rainfall volumes to reflect future climatic change. The model results show that different rainfall patterns cause variability in flood depths during a storm event. The changes in the projected temporal patterns alone increase the risk of flood magnitude up to 35 %, with the cumulative impacts of temperature rise on temporal patterns and the storm volume increasing flood risk from 10 to 170 %. The results also show that regional storage facilities are sensitive to rainfall patterns that are loaded in the latter part of the storm duration, while extremely intense short-duration storms will cause flooding at all locations. This study shows that changes in temporal patterns will have a significant impact on urban/suburban flooding and need to be carefully considered and adjusted to account for climate change when used for the design and planning of future storm water systems.

Year-round breeding equatorial Larks from three climatically-distinct populations do not use rainfall, temperature or invertebrate biomass to time reproduction

PubMed Central

Ndithia, Henry K.; Matson, Kevin D.; Versteegh, Maaike A.; Muchai, Muchane; Tieleman, B. Irene

2017-01-01

Timing of reproduction in birds is important for reproductive success and is known to depend on environmental cues such as day length and food availability. However, in equatorial regions, where day length is nearly constant, other factors such as rainfall and temperature are thought to determine timing of reproduction. Rainfall can vary at small spatial and temporal scales, providing a highly fluctuating and unpredictable environmental cue. In this study we investigated the extent to which spatio-temporal variation in environmental conditions can explain the timing of breeding of Red-capped Lark, Calandrella cinerea, a species that is capable of reproducing during every month of the year in our equatorial east African study locations. For 39 months in three climatically-distinct locations, we monitored nesting activities, sampled ground and flying invertebrates, and quantified rainfall, maximum (Tmax) and minimum (Tmin) temperatures. Among locations we found that lower rainfall and higher temperatures did not coincide with lower invertebrate biomasses and decreased nesting activities, as predicted. Within locations, we found that rainfall, Tmax, and Tmin varied unpredictably among months and years. The only consistent annually recurring observations in all locations were that January and February had low rainfall, high Tmax, and low Tmin. Ground and flying invertebrate biomasses varied unpredictably among months and years, but invertebrates were captured in all months in all locations. Red-capped Larks bred in all calendar months overall but not in every month in every year in every location. Using model selection, we found no clear support for any relationship between the environmental variables and breeding in any of the three locations. Contrary to popular understanding, this study suggests that rainfall and invertebrate biomass as proxy for food do not influence breeding in equatorial Larks. Instead, we propose that factors such as nest predation, female protein reserves, and competition are more important in environments where weather and food meet minimum requirements for breeding during most of the year. PMID:28419105

A Broadband Microwave Radiometer Technique at X-band for Rain and Drop Size Distribution Estimation

NASA Technical Reports Server (NTRS)

Meneghini, R.

2005-01-01

Radiometric brightess temperatures below about 12 GHz provide accurate estimates of path attenuation through precipitation and cloud water. Multiple brightness temperature measurements at X-band frequencies can be used to estimate rainfall rate and parameters of the drop size distribution once correction for cloud water attenuation is made. Employing a stratiform storm model, calculations of the brightness temperatures at 9.5, 10 and 12 GHz are used to simulate estimates of path-averaged median mass diameter, number concentration and rainfall rate. The results indicate that reasonably accurate estimates of rainfall rate and information on the drop size distribution can be derived over ocean under low to moderate wind speed conditions.

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

Simulation of the Onset of the Southeast Asian Monsoon During 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lau, W.; Baker, R.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo-China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the low-level temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation. The model results will be compared to the simulation of the 6-7 May 2000 Missouri flash flood event. In addition, the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation will be examined.

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Wang, Y.; Lau, W.; Baker, R. D.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo-China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the low-level temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation. The model results will be compared to the simulation of the 6-7 May 2000 Missouri flash flood event. In addition, the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation will be examined.

A further assessment of vegetation feedback on decadal Sahel rainfall variability

NASA Astrophysics Data System (ADS)

Kucharski, Fred; Zeng, Ning; Kalnay, Eugenia

2013-03-01

The effect of vegetation feedback on decadal-scale Sahel rainfall variability is analyzed using an ensemble of climate model simulations in which the atmospheric general circulation model ICTPAGCM ("SPEEDY") is coupled to the dynamic vegetation model VEGAS to represent feedbacks from surface albedo change and evapotranspiration, forced externally by observed sea surface temperature (SST) changes. In the control experiment, where the full vegetation feedback is included, the ensemble is consistent with the observed decadal rainfall variability, with a forced component 60 % of the observed variability. In a sensitivity experiment where climatological vegetation cover and albedo are prescribed from the control experiment, the ensemble of simulations is not consistent with the observations because of strongly reduced amplitude of decadal rainfall variability, and the forced component drops to 35 % of the observed variability. The decadal rainfall variability is driven by SST forcing, but significantly enhanced by land-surface feedbacks. Both, local evaporation and moisture flux convergence changes are important for the total rainfall response. Also the internal decadal variability across the ensemble members (not SST-forced) is much stronger in the control experiment compared with the one where vegetation cover and albedo are prescribed. It is further shown that this positive vegetation feedback is physically related to the albedo feedback, supporting the Charney hypothesis.

Global intensification in observed short-duration rainfall extremes

NASA Astrophysics Data System (ADS)

Fowler, H. J.; Lewis, E.; Guerreiro, S.; Blenkinsop, S.; Barbero, R.; Westra, S.; Lenderink, G.; Li, X.

2017-12-01

Extreme rainfall events are expected to intensify with a warming climate and this is currently driving extensive research. While daily rainfall extremes are widely thought to have increased globally in recent decades, changes in rainfall extremes on shorter timescales, often associated with flash flooding, have not been documented at global scale due to surface observational limitations and the lack of a global sub-daily rainfall database. The access to and use of such data remains a challenge. For the first time, we have synthesized across multiple data sources providing gauge-based sub-daily rainfall observations across the globe over the last 6 decades. This forms part of the INTENSE project (part of the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges (GEWEX) Hydroclimate Project cross-cut on sub-daily rainfall). A set of global hydroclimatic indices have been produced based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. This will provide a unique global data resource on sub-daily precipitation whose derived indices will be freely available to the wider scientific community. Because of the physical connection between global warming and the moisture budget, we also sought to infer long-term changes in sub-daily rainfall extremes contingent on global mean temperature. Whereas the potential influence of global warming is uncertain at regional scales, where natural variability dominates, aggregating surface stations across parts of the world may increase the global warming-induced signal. Changes in terms of annual maximum rainfall across various resolutions ranging from 1-h to 24-h are presented and discussed.

Temperature and rainfall are related to fertility rate after spring artificial insemination in small ruminants.

PubMed

Abecia, J A; Arrébola, F; Macías, A; Laviña, A; González-Casquet, O; Benítez, F; Palacios, C

2016-10-01

A total number of 1092 artificial inseminations (AIs) performed from March to May were documented over four consecutive years on 10 Payoya goat farms (36° N) and 19,392 AIs on 102 Rasa Aragonesa sheep farms (41° N) over 10 years. Mean, maximum, and minimum ambient temperatures, mean relative humidity, mean solar radiation, and total rainfall on each insemination day were recorded. Overall, fertility rates were 58 % in goats and 45 % in sheep. The fertility rates of the highest and lowest deciles of each of the meteorological variables indicated that temperature and rainfall had a significant effect on fertility in goats. Specifically, inseminations that were performed when mean (68 %), maximum (68 %), and minimum (66 %) temperatures were in the highest decile, and rainfall was in the lowest decile (59 %), had a significantly (P < 0.0001) higher proportion of does that became pregnant than did the ewes in the lowest decile (56, 54, 58, and 49 %, respectively). In sheep, the fertility rates of the highest decile of mean (62 %), maximum (62 %), and minimum (52 %) temperature, RH (52 %), THI (53 %), and rainfall (45 %) were significantly higher (P < 0.0001) than were the fertility rates among ewes in the lowest decile (46, 45, 45, 45, 46, and 43 %, respectively). In conclusion, weather was related to fertility in small ruminants after AI in spring. It remains to be determined whether scheduling the dates of insemination based on forecasted temperatures can improve the success of AI in goats and sheep.

Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model

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

Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.

Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over centralmore » India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important implications of LULCC over India during the monsoon season. Although, the regional climate model helps in better resolving land–atmosphere feedbacks over the Indian region, the inferences do depend on the fidelity of the model in capturing the features of Indian monsoon realistically. Lastly, it is proposed that similar studies using a suite of climate models will further enrich our understanding about the role of LULCC in the Indian monsoon climate.« less

Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model

DOE PAGES

Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.; ...

2016-05-10

Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over centralmore » India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important implications of LULCC over India during the monsoon season. Although, the regional climate model helps in better resolving land–atmosphere feedbacks over the Indian region, the inferences do depend on the fidelity of the model in capturing the features of Indian monsoon realistically. Lastly, it is proposed that similar studies using a suite of climate models will further enrich our understanding about the role of LULCC in the Indian monsoon climate.« less

The influence of intra- and inter-annual meteorological variability on dengue transmission: a multi-level modeling analysis

NASA Astrophysics Data System (ADS)

Wen, Tzai-Hung; Chen, Tzu-Hsin

2017-04-01

Dengue fever is one of potentially life-threatening mosquito-borne diseases and IPCC Fifth Assessment Report (AR5) has confirmed that dengue incidence is sensitive to the critical weather conditions, such as effects of temperature. However, previous literature focused on the effects of monthly or weekly average temperature or accumulative precipitation on dengue incidence. The influence of intra- and inter-annual meteorological variability on dengue outbreak is under investigated. The purpose of the study focuses on measuring the effect of the intra- and inter-annual variations of temperature and precipitation on dengue outbreaks. We developed the indices of intra-annual temperature variability are maximum continuity, intermittent, and accumulation of most suitable temperature (MST) for dengue vectors; and also the indices of intra-annual precipitation variability, including the measure of continuity of wetness or dryness during a pre-epidemic period; and rainfall intensity during an epidemic period. We used multi-level modeling to investigate the intra- and inter-annual meteorological variations on dengue outbreaks in southern Taiwan from 1998-2015. Our results indicate that accumulation and maximum continuity of MST are more significant than average temperature on dengue outbreaks. The effect of continuity of wetness during the pre-epidemic period is significantly more positive on promoting dengue outbreaks than the rainfall effect during the epidemic period. Meanwhile, extremely high or low rainfall density during an epidemic period do not promote the spread of dengue epidemics. Our study differentiates the effects of intra- and inter-annual meteorological variations on dengue outbreaks and also provides policy implications for further dengue control under the threats of climate change. Keywords: dengue fever, meteorological variations, multi-level model

Response of salt marsh and mangrove wetlands to changes in atmospheric CO2, climate, and sea-level

USGS Publications Warehouse

Mckee, Karen L.; Rogers, Kerrylee; Saintilan, Neil; Middleton, Beth A.

2012-01-01

Coastal salt marsh and mangrove ecosystems are particularly vulnerable to changes in atmospheric CO2 concentrations and associated climate and climate-induced changes. We provide a review of the literature detailing theoretical predictions and observed responses of coastal wetlands to a range of climate change stressors, including CO2, temperature, rainfall, and sea-level rise. This review incorporates a discussion of key processes controlling responses in different settings and thresholds of resilience derived from experimental and observational studies. We specifically consider the potential and observed effects on salt marsh and mangrove vegetation of changes in (1) elevated [CO2] on physiology, growth, and distribution; (2) temperature on distribution and diversity; (3) rainfall and salinity regimes on growth and competitive interactions; and (4) sea level on geomorphological, hydrological, and biological processes.

CTS/Comstar communications link characterization experiment

NASA Technical Reports Server (NTRS)

Hodge, D. B.; Taylor, R. C.

1980-01-01

Measurements of angle of arrival and amplitude fluctuations on millimeter wavelength Earth-space communication links are described. Measurement of rainfall attenuation and radiometric temperature statistics and the assessment of the performance of a self-phased array as a receive antenna on an Earth-space link are also included.

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.

Rainfall simulation experiments: Influence of water temperature, water quality and plot design on soil erosion and runoff

NASA Astrophysics Data System (ADS)

Iserloh, Thomas; Pegoraro, Dominique; Schlösser, Angelika; Thesing, Hannah; Seeger, Manuel; Ries, Johannes B.

2015-04-01

Field rainfall simulators are designed to study soil erosion processes and provide urgently needed data for various geomorphological, hydrological and pedological issues. Due to the different conditions and technologies applied, there are several methodological aspects under review of the scientific community, particularly concerning design, procedures and conditions of measurement for infiltration, runoff and soil erosion. This study aims at contributing fundamental data for understanding rainfall simulations in depth by studying the effect of the following parameters on the measurement results: 1. Plot design - round or rectangular plot: Can we identify differences in amount of runoff and erosion? 2. Water quality: What is the influence of the water's salt load on interrill erosion and infiltration as measured by rainfall experiments? 3. Water temperature: How much are the results conditioned by the temperature of water, which is subject to changes due to environmental conditions during the experiments? Preliminary results show a moderate increase of soil erosion with the water's salt load while runoff stays almost on the same level. With increasing water temperature, runoff increases continuously. At very high temperatures, soil erosion is clearly increased. A first comparison between round and rectangular plot indicates the rectangular plot to be the most suitable plot shape, but ambiguous results make further research necessary. The analysis of these three factors concerning their influence on runoff and erosion shows that clear methodological standards are necessary in order to make rainfall simulation experiments comparable.

Direct measurement of the combined effects of lichen, rainfall, and temperature onsilicate weathering

USGS Publications Warehouse

Brady, P.V.; Dorn, R.I.; Brazel, A.J.; Clark, J.; Moore, R.B.; Glidewell, T.

1999-01-01

A key uncertainty in models of the global carbonate-silicate cycle and long-term climate is the way that silicates weather under different climatologic conditions, and in the presence or absence of organic activity. Digital imaging of basalts in Hawaii resolves the coupling between temperature, rainfall, and weathering in the presence and absence of lichens. Activation energies for abiotic dissolution of plagioclase (23.1 ?? 2.5 kcal/mol) and olivine (21.3 ?? 2.7 kcal/mol) are similar to those measured in the laboratory, and are roughly double those measured from samples taken underneath lichen. Abiotic weathering rates appear to be proportional to rainfall. Dissolution of plagioclase and olivine underneath lichen is far more sensitive to rainfall.

An Investigation of the Influence of Urban Areas on Rainfall Using the TRMM Satellite and a Cloud-Mesoscale Model

NASA Astrophysics Data System (ADS)

Shepherd, J.

2002-05-01

A recent paper by Shepherd et al. (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study.

Best convective parameterization scheme within RegCM4 to downscale CMIP5 multi-model data for the CORDEX-MENA/Arab domain

NASA Astrophysics Data System (ADS)

Almazroui, Mansour; Islam, Md. Nazrul; Al-Khalaf, A. K.; Saeed, Fahad

2016-05-01

A suitable convective parameterization scheme within Regional Climate Model version 4.3.4 (RegCM4) developed by the Abdus Salam International Centre for Theoretical Physics, Trieste, Italy, is investigated through 12 sensitivity runs for the period 2000-2010. RegCM4 is driven with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim 6-hourly boundary condition fields for the CORDEX-MENA/Arab domain. Besides ERA-Interim lateral boundary conditions data, the Climatic Research Unit (CRU) data is also used to assess the performance of RegCM4. Different statistical measures are taken into consideration in assessing model performance for 11 sub-domains throughout the analysis domain, out of which 7 (4) sub-domains give drier (wetter) conditions for the area of interest. There is no common best option for the simulation of both rainfall and temperature (with lowest bias); however, one option each for temperature and rainfall has been found to be superior among the 12 options investigated in this study. These best options for the two variables vary from region to region as well. Overall, RegCM4 simulates large pressure and water vapor values along with lower wind speeds compared to the driving fields, which are the key sources of bias in simulating rainfall and temperature. Based on the climatic characteristics of most of the Arab countries located within the study domain, the drier sub-domains are given priority in the selection of a suitable convective scheme, albeit with a compromise for both rainfall and temperature simulations. The most suitable option Grell over Land and Emanuel over Ocean in wet (GLEO wet) delivers a rainfall wet bias of 2.96 % and a temperature cold bias of 0.26 °C, compared to CRU data. An ensemble derived from all 12 runs provides unsatisfactory results for rainfall (28.92 %) and temperature (-0.54 °C) bias in the drier region because some options highly overestimate rainfall (reaching up to 200 %) and underestimate temperature (reaching up to -1.16 °C). Overall, a suitable option (GLEO wet) is recommended for downscaling the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model database using RegCM4 for the CORDEX-MENA/Arab domain for its use in future climate change impact studies.

Analysis of climate change impact on rainfall pattern of Sambas district, West Kalimantan

NASA Astrophysics Data System (ADS)

Berliana Sipayung, Sinta; Nurlatifah, Amalia; Siswanto, Bambang; Slamet S, Lilik

2018-05-01

Climate change is one of the most important issues being discussed globally. It caused by global warming and indirectly affecting the world climate cycle. This research discussed the effect of climate change on rainfall pattern of Sambas District and predicted the future rainfall pattern due to climate change. CRU and TRMM were used and has been validated using in situ data. This research was used Climate Modelling and Prediction using CCAM (Conformal Cubic Atmospheric Model) which also validated by in situ data (correlation= 0.81). The results show that temperature trends in Sambas regency increased to 0.082°C/yr from 1991-2014 according to CRU data. High temperature trigger changes in rainfall patterns. Rainfall pattern in Sambas District has an equatorial type where the peak occurs when the sun is right on the equator. Rainfall in Sambas reaches the maximum in March and September when the equinox occurs. The CCAM model is used to project rainfall in Sambas District in the future. The model results show that rainfall in Sambas District is projected to increase to 0.018 mm/month until 2055 so the flow rate increase 0.006 m3/month and the water balance increase 0.009 mm/month.

The local and global climate forcings induced inhomogeneity of Indian rainfall.

PubMed

Nair, P J; Chakraborty, A; Varikoden, H; Francis, P A; Kuttippurath, J

2018-04-16

India is home for more than a billion people and its economy is largely based on agrarian society. Therefore, rainfall received not only decides its livelihood, but also influences its water security and economy. This situation warrants continuous surveillance and analysis of Indian rainfall. These kinds of studies would also help forecasters to better tune their models for accurate weather prediction. Here, we introduce a new method for estimating variability and trends in rainfall over different climate regions of India. The method based on multiple linear regression helps to assess contributions of different remote and local climate forcings to seasonal and regional inhomogeneity in rainfall. We show that the Indian Summer Monsoon Rainfall (ISMR) variability is governed by Eastern and Central Pacific El Niño Southern Oscillation, equatorial zonal winds, Atlantic zonal mode and surface temperatures of the Arabian Sea and Bay of Bengal, and the North East Monsoon Rainfall variability is controlled by the sea surface temperature of the North Atlantic and extratropial oceans. Also, our analyses reveal significant positive trends (0.43 mm/day/dec) in the North West for ISMR in the 1979-2017 period. This study cautions against the significant changes in Indian rainfall in a perspective of global climate change.

Recent climate variability and its impacts on soybean yields in Southern Brazil

NASA Astrophysics Data System (ADS)

Ferreira, Danielle Barros; Rao, V. Brahmananda

2011-08-01

Recent climate variability in rainfall, temperatures (maximum and minimum), and the diurnal temperature range is studied with emphasis on its influence over soybean yields in southern Brazil, during 1969 to 2002. The results showed that the soybean ( Glycine max L. Merril) yields are more affected by changes in temperature during summer, while changes in rainfall are more important during the beginning of plantation and at its peak of development. Furthermore, soybean yields in Paraná are more sensitive to rainfall variations, while soybean yields in the Rio Grande do Sul are more sensitive to variations in temperature. Effects of interannual climatic variability on soybean yields are evaluated through three agro-meteorological models: additive Stewart, multiplicative Rao, and multiplicative Jensen. The Jensen model is able to reproduce the interannual behavior of soybean yield reasonably well.

The effect of altitude and climate on the suicide rates in Turkey.

PubMed

Asirdizer, Mahmut; Kartal, Erhan; Etli, Yasin; Tatlisumak, Ertugrul; Gumus, Orhan; Hekimoglu, Yavuz; Keskin, Sıddık

2018-02-01

Suicide is one of the most important public health problems. There was an association between suicide and several factors such as psychiatric diseases and psychological characteristics, somatic illness, cultural, socioeconomic, familial, occupational and individual risk factors. Also, high altitude and climatic factors including high temperature, cloudiness, more sunshine and low rainfalls were defined as some of these risk factors in the literature. In this study, we aimed to investigate correlation between suicide rates and altitudes of all cities in Turkey and between suicide rates and climatic factors including Rainfall Activity Index, Winter Mean Temperatures, Summer Mean Temperatures and Temperature Difference between January and July previously defined by several authors in the broad series in Turkey. In Turkey, 29865 suicidal deaths occurred in 10 years period between 2006 and 2015. Of them, 21020 (70.4%) were males and 8845 (29.6%) were females. In this study, we found that high altitude above 1500 m, winter median temperature lower than -10 °C and hard temperature changes above 25 °C between winter and summer of settlements were important factors that affected on female suicide rates appropriate to knowledge which defined in previous studies. In conclusion, we suggested that the associations among suicide rates with altitudes and climate should be studied in wider series obtained from different countries for reaching more reliable results. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Climate variability and environmental stress in the Sudan-Sahel zone of West Africa.

PubMed

Mertz, Ole; D'haen, Sarah; Maiga, Abdou; Moussa, Ibrahim Bouzou; Barbier, Bruno; Diouf, Awa; Diallo, Drissa; Da, Evariste Dapola; Dabi, Daniel

2012-06-01

Environmental change in the Sudan-Sahel region of West Africa (SSWA) has been much debated since the droughts of the 1970s. In this article we assess climate variability and environmental stress in the region. Households in Senegal, Mali, Burkina Faso, Niger, and Nigeria were asked about climatic changes and their perceptions were compared across north-south and west-east rainfall gradients. More than 80% of all households found that rainfall had decreased, especially in the wettest areas. Increases in wind speeds and temperature were perceived by an overall 60-80% of households. Contrary to household perceptions, observed rainfall patterns showed an increasing trend over the past 20 years. However, August rainfall declined, and could therefore potentially explain the contrasting negative household perceptions of rainfall trends. Most households reported degradation of soils, water resources, vegetation, and fauna, but more so in the 500-900 mm zones. Adaptation measures to counter environmental degradation included use of manure, reforestation, soil and water conservation, and protection of fauna and vegetation. The results raise concerns for future environmental management in the region, especially in the 500-900 mm zones and the western part of SSWA.

The Costs of Climate Change: A Study of Cholera in Tanzania

PubMed Central

Trærup, Sara L. M.; Ortiz, Ramon A.; Markandya, Anil

2011-01-01

Increased temperatures and changes in rainfall patterns as a result of climate change are widely recognized to entail potentially serious consequences for human health, including an increased risk of diarrheal diseases. This study integrates historical data on temperature and rainfall with the burden of disease from cholera in Tanzania and uses socioeconomic data to control for the impacts of general development on the risk of cholera. The results show a significant relationship between temperature and the incidence of cholera. For a 1 degree Celsius temperature increase the initial relative risk of cholera increases by 15 to 29 percent. Based on the modeling results, we project the number and costs of additional cases of cholera that can be attributed to climate change by 2030 in Tanzania for a 1 and 2 degree increase in temperatures, respectively. The total costs of cholera attributable to climate change are shown to be in the range of 0.32 to 1.4 percent of GDP in Tanzania 2030. The results provide useful insights into national-level estimates of the implications of climate change on the health sector and offer information which can feed into both national and international debates on financing and planning adaptation. PMID:22408580

Understanding extreme rainfall events in Australia through historical data

NASA Astrophysics Data System (ADS)

Ashcroft, Linden; Karoly, David John

2016-04-01

Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this relationship has remained stable since the early to mid-19th century. Ashcroft, L., Gergis, J., Karoly, D.J., 2014a. A historical climate dataset for southeastern Australia, 1788-1859. Geosci. Data J. 1, 158-178. doi:10.1002/gdj3.19 Ashcroft, L., Karoly, D.J., Gergis, J., 2014b. Southeastern Australian climate variability 1860-2009: A multivariate analysis. Int. J. Climatol. 34, 1928-1944. doi:10.1002/joc.3812

Environmental factors influencing the development of black leaf streak (Mycosphaerella fijiensis Morelet) on bananas in Puerto Rico.

USDA-ARS?s Scientific Manuscript database

The effects of environmental factors on the development of black leaf streak (BLS) were studied in Puerto Rico under field conditions. Environmental factors evaluated included temperature, relative humidity, rainfall and solar radiation. Their effect on BLS was determined by recording the youngest...

Natural variability of the Keetch-Byram Drought Index in the Hawaiian Islands

Treesearch

Klaus Dolling; Pao-Shin Chu; Francis Fujioka

2009-01-01

The Hawaiian Islands experience damaging wildfires on a yearly basis. Soil moisture or lack thereof influences the amount and flammability of vegetation. Incorporating daily maximum temperatures and daily rainfall amounts, the Keetch–Byram Drought Index (KBDI) estimates the amount of soil moisture by tracking daily maximum temperatures and rainfall. A previous study...

Potential aboveground biomass in drought-prone forest used for rangeland pastoralism.

PubMed

Fensham, R J; Fairfax, R J; Dwyer, J M

2012-04-01

The restoration of cleared dry forest represents an important opportunity to sequester atmospheric carbon. In order to account for this potential, the influences of climate, soils, and disturbance need to be deciphered. A data set spanning a region defined the aboveground biomass of mulga (Acacia aneura) dry forest and was analyzed in relation to climate and soil variables using a Bayesian model averaging procedure. Mean annual rainfall had an overwhelmingly strong positive effect, with mean maximum temperature (negative) and soil depth (positive) also important. The data were collected after a recent drought, and the amount of recent tree mortality was weakly positively related to a measure of three-year rainfall deficit, and maximum temperature (positive), soil depth (negative), and coarse sand (negative). A grazing index represented by the distance of sites to watering points was not incorporated by the models. Stark management contrasts, including grazing exclosures, can represent a substantial part of the variance in the model predicting biomass, but the impact of management was unpredictable and was insignificant in the regional data set. There was no evidence of density-dependent effects on tree mortality. Climate change scenarios represented by the coincidence of historical extreme rainfall deficit with extreme temperature suggest mortality of 30.1% of aboveground biomass, compared to 21.6% after the recent (2003-2007) drought. Projections for recovery of forest using a mapping base of cleared areas revealed that the greatest opportunities for restoration of aboveground biomass are in the higher-rainfall areas, where biomass accumulation will be greatest and droughts are less intense. These areas are probably the most productive for rangeland pastoralism, and the trade-off between pastoral production and carbon sequestration will be determined by market forces and carbon-trading rules.

A statistical technique for determining rainfall over land employing Nimbus-6 ESMR measurements

NASA Technical Reports Server (NTRS)

Rodgers, E.; Siddalingaiah, H.; Chang, A. T. C.; Wilheit, T. T.

1978-01-01

At 37 GHz, the frequency at which the Nimbus 6 Electrically Scanning Microwave Radiometer (ESMR 6) measures upwelling radiance, it was shown theoretically that the atmospheric scattering and the relative independence on electromagnetic polarization of the radiances emerging from hydrometers make it possible to monitor remotely active rainfall over land. In order to verify experimentally these theoretical findings and to develop an algorithm to monitor rainfall over land, the digitized ESMR 6 measurements were examined statistically. Horizontally and vertically polarized brightness temperature pairs (TH, TV) from ESMR 6 were sampled for areas of rainfall over land as determined from the rain recording stations and the WSR 57 radar, and areas of wet and dry ground (whose thermodynamic temperatures were greater than 5 C) over the Southeastern United States. These three categories of brightness temperatures were found to be significantly different in the sense that the chances that the mean vectors of any two populations coincided were less than 1 in 100.

Climatic factors associated with amyotrophic lateral sclerosis: a spatial analysis from Taiwan.

PubMed

Tsai, Ching-Piao; Tzu-Chi Lee, Charles

2013-11-01

Few studies have assessed the spatial association of amyotrophic lateral sclerosis (ALS) incidence in the world. The aim of this study was to identify the association of climatic factors and ALS incidence in Taiwan. A total of 1,434 subjects with the primary diagnosis of ALS between years 1997 and 2008 were identified in the national health insurance research database. The diagnosis was also verified by the national health insurance programme, which had issued and providing them with "serious disabling disease (SDD) certificates". Local indicators of spatial association were employed to investigate spatial clustering of age-standardised incidence ratios in the townships of the study area. Spatial regression was utilised to reveal any association of annual average climatic factors and ALS incidence for the 12-year study period. The climatic factors included the annual average time of sunlight exposure, average temperature, maximum temperature, minimum temperature, atmospheric pressure, rainfall, relative humidity and wind speed with spatial autocorrelation controlled. Significant correlations were only found for exposure to sunlight and rainfall and it was similar in both genders. The annual average of the former was found to be negatively correlated with ALS, while the latter was positively correlated with ALS incidence. While accepting that ALS is most probably multifactorial, it was concluded that sunlight deprivation and/or rainfall are associated to some degree with ALS incidence in Taiwan.

Coupled modes of rainfall over China and the pacific sea surface temperature in boreal summertime

NASA Astrophysics Data System (ADS)

Li, Chun; Ma, Hao

2011-09-01

In addition, the possible atmospheric teleconnections of the coupled rainfall and SST modes were discussed. For the ENSO-NC mode, anomalous low-pressure and high-pressure over the Asian continent induces moisture divergence over North China and reduces summer rainfall there. For the WTP-YRV mode, East Asia-Pacific teleconnection induces moisture convergence over the Yangtze River valley and enhances the summer rainfall there. The TPMM SST and the summer rainfall anomalies over the YRVL are linked by a circumglobal, wave-train-like, atmospheric teleconnection.

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

Yoon, Jin -Ho

Amazon rainfall is subject to year-to-year fluctuation resulting in drought and flood in various intensities. A major climatic driver of the interannual variation of the Amazon rainfall is El Niño/Southern Oscillation. Also, the Sea Surface Temperature over the Atlantic Ocean is identified as an important climatic driver on the Amazon water cycle. Previously, observational datasets were used to support the Atlantic influence on Amazon rainfall. Furthermore, it is found that multiple global climate models do reproduce the Atlantic-Amazon link robustly. However, there exist differences in rainfall response, which primarily depends on the climatological rainfall amount.

Meteorological factors affecting scrub typhus occurrence: a retrospective study of Yamagata Prefecture, Japan, 1984-2014.

PubMed

Seto, J; Suzuki, Y; Nakao, R; Otani, K; Yahagi, K; Mizuta, K

2017-02-01

Climate change, by its influence on the ecology of vectors might affect the occurrence of vector-borne diseases. This study examines the effects of meteorological factors in Japan on the occurrence of scrub typhus, a mite-borne zoonosis caused by Orientia tsutsugamushi. Using negative binomial regression, we analysed the relationships between meteorological factors (including temperature, rainfall, snowfall) and spring-early summer cases of scrub typhus in Yamagata Prefecture, Japan, during 1984-2014. The average temperature in July and August of the previous year, cumulative rainfall in September of the previous year, snowfall throughout the winter, and maximum depth of snow cover in January and February were positively correlated with the number of scrub typhus cases. By contrast, cumulative rainfall in July of the previous year showed a negative relationship to the number of cases. These associations can be explained by the life-cycle of Leptotrombidium pallidum, a predominant vector of spring-early summer cases of scrub typhus in northern Japan. Our findings show that several meteorological factors are useful to estimate the number of scrub typhus cases before the endemic period. They are applicable to establish an early warning system for scrub typhus in northern Japan.

Seasonal precipitation forecasting for the Melbourne region using a Self-Organizing Maps approach

NASA Astrophysics Data System (ADS)

Pidoto, Ross; Wallner, Markus; Haberlandt, Uwe

2017-04-01

The Melbourne region experiences highly variable inter-annual rainfall. For close to a decade during the 2000s, below average rainfall seriously affected the environment, water supplies and agriculture. A seasonal rainfall forecasting model for the Melbourne region based on the novel approach of a Self-Organizing Map has been developed and tested for its prediction performance. Predictor variables at varying lead times were first assessed for inclusion within the model by calculating their importance via Random Forests. Predictor variables tested include the climate indices SOI, DMI and N3.4, in addition to gridded global sea surface temperature data. Five forecasting models were developed: an annual model and four seasonal models, each individually optimized for performance through Pearson's correlation r and the Nash-Sutcliffe Efficiency. The annual model showed a prediction performance of r = 0.54 and NSE = 0.14. The best seasonal model was for spring, with r = 0.61 and NSE = 0.31. Autumn was the worst performing seasonal model. The sea surface temperature data contributed fewer predictor variables compared to climate indices. Most predictor variables were supplied at a minimum lead, however some predictors were found at lead times of up to a year.

Impervious surfaces and sewer pipe effects on stormwater runoff temperature

NASA Astrophysics Data System (ADS)

Sabouri, F.; Gharabaghi, B.; Mahboubi, A. A.; McBean, E. A.

2013-10-01

The warming effect of the impervious surfaces in urban catchment areas and the cooling effect of underground storm sewer pipes on stormwater runoff temperature are assessed. Four urban residential catchment areas in the Cities of Guelph and Kitchener, Ontario, Canada were evaluated using a combination of runoff monitoring and modelling. The stormwater level and water temperature were monitored at 10 min interval at the inlet of the stormwater management ponds for three summers 2009, 2010 and 2011. The warming effect of the ponds is also studied, however discussed in detail in a separate paper. An artificial neural network (ANN) model for stormwater temperature was trained and validated using monitoring data. Stormwater runoff temperature was most sensitive to event mean temperature of the rainfall (EMTR) with a normalized sensitivity coefficient (Sn) of 1.257. Subsequent levels of sensitivity corresponded to the longest sewer pipe length (LPL), maximum rainfall intensity (MI), percent impervious cover (IMP), rainfall depth (R), initial asphalt temperature (AspT), pipe network density (PND), and rainfall duration (D), respectively. Percent impervious cover of the catchment area (IMP) was the key parameter that represented the warming effect of the paved surfaces; sensitivity analysis showed IMP increase from 20% to 50% resulted in runoff temperature increase by 3 °C. The longest storm sewer pipe length (LPL) and the storm sewer pipe network density (PND) are the two key parameters that control the cooling effect of the underground sewer system; sensitivity analysis showed LPL increase from 345 to 966 m, resulted in runoff temperature drop by 2.5 °C.

On the Relationship of Rainfall and Temperature across Amazonia

NASA Astrophysics Data System (ADS)

Ribeiro Lima, C. H.; AghaKouchak, A.

2017-12-01

Extreme droughts in Amazonia seem to become more frequent and have been associated with local and global impacts on society and the ecosystem. The understanding of the dynamics and causes of Amazonia droughts have attracted some attention in the last years and pose several challenges for the scientific community. For instance, in previous work we have identified, based on empirical data, a compounding effect during Amazonia droughts: periods of low rainfall are always associated with positive anomalies of near surface air temperature. This inverse relationship of temperature and rainfall appears at multiple time scales and its intensity varies across Amazonia. To our knowledge, these findings have not been properly addressed in the literature, being not clear whether there is a causal relationship between these two variables, and in this case, which one leads the other one, or they are just responding to the same causal factor. Here we investigate the hypothesis that high temperatures during drought periods are a major response to an increase in the shortwave radiation (due to the lack of clouds) not compensating by an expected increase in the evapotranspiration from the rainforest. Our empirical analysis is based on observed series of daily temperature and rainfall over the Brazilian Amazonia and reanalysis data of cloud cover, outgoing longwave radiation (OLR) and moisture fluxes. The ability of Global Circulation Models (GCMs) to reproduce such compounding effect is also investigated for the historical period and for future RCP scenarios of global climate change. Preliminary results show that this is a plausible hypothesis, despite the complexity of land-atmosphere processes of mass and energy fluxes in Amazonia. This work is a step forward in better understanding the compounding effects of rainfall and temperature on Amazonia droughts, and what changes one might expect in a future warming climate.

Multi-model analysis of the Atlantic influence on Southern Amazon rainfall

DOE PAGES

Yoon, Jin -Ho

2015-12-07

Amazon rainfall is subject to year-to-year fluctuation resulting in drought and flood in various intensities. A major climatic driver of the interannual variation of the Amazon rainfall is El Niño/Southern Oscillation. Also, the Sea Surface Temperature over the Atlantic Ocean is identified as an important climatic driver on the Amazon water cycle. Previously, observational datasets were used to support the Atlantic influence on Amazon rainfall. Furthermore, it is found that multiple global climate models do reproduce the Atlantic-Amazon link robustly. However, there exist differences in rainfall response, which primarily depends on the climatological rainfall amount.

Direct measurement of the combined effects of lichen, rainfall, and temperature on silicate weathering

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

Brady, P.V.; Dorn, R.I.; Brazel, A.J.

1999-10-01

A key uncertainty in models of the global carbonate-silicate cycle and long-term climate is the way that silicates weather under different climatologic conditions, and in the presence or absence of organic activity. Digital imaging of basalts in Hawaii resolves the coupling between temperature, rainfall, and weathering in the presence and absence of lichens. Activation energies for abiotic dissolution of plagioclase (23.1 {+-} 2.5 kcal/mol) and olivine (21.3 {+-} 2.7 kcal/mol) are similar to those measured in the laboratory, and are roughly double those measured from samples taken underneath lichen. Abiotic weathering rates appear to be proportional to rainfall. Dissolution ofmore » plagioclase and olivine underneath lichen is far more sensitive to rainfall.« 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.

Climate change in Lagos state, Nigeria: what really changed?

PubMed

Sojobi, Adebayo Olatunbosun; Balogun, Isaac Idowu; Salami, Adebayo Wahab

2015-10-01

Our study revealed periodicities of 2.3 and 2.25 years in wet and dry seasons and periodicities of 2 to 5 years on seasonal and annual timescales. Minimum temperature (Tmin), maximum temperature (Tmax) and evaporation recorded increases of 2.47, 1.37 and 28.37 %, respectively, but a reduction of 19.58 % in rainfall on decadal timescale. Periodicity of 8 to 12 years was also observed in annual Tmax. Cramer's test indicated a warming trend with significant Tmax increase in February, April, July, August, October and November during 2000-2009 on decadal monthly timescale, a significant decline in Summer rainfall but significant Tmax increase in Spring, Autumn and Winter on decadal seasonal timescale. The low correlation of rainfall with temperature parameters and evaporation indicates that advection of moisture into Lagos State seems to be the dominant mechanism controlling rainfall within the State alongside other tropical and extra-tropical factors. In addition, our study revealed that the persistent state of minimum temperature often precedes the arrival and reversal of the phase of maximum temperature. Furthermore, our study also revealed that extreme and high variable rainfalls, which are associated with the increased warming trend, had periodicities of 1 to 3 years with a probability of 86.45 % of occurring every 3 years between April and September. It is recommended that government and private sector should give financial and technical supports to climate researches in order to appropriately inform policy making to improve the adaptive capacity and resilience of Lagos State against climate change impacts and guard against maladaptation.

Spatial outline of malaria transmission in Iran.

PubMed

Barati, Mohammad; Keshavarz-valian, Hossein; Habibi-nokhandan, Majid; Raeisi, Ahmad; Faraji, Leyla; Salahi-moghaddam, Abdoreza

2012-10-01

To conduct for modeling spatial distribution of malaria transmission in Iran. Records of all malaria cases from the period 2008-2010 in Iran were retrieved for malaria control department, MOH&ME. Metrological data including annual rainfall, maximum and minimum temperature, relative humidity, altitude, demographic, districts border shapefiles, and NDVI images received from Iranian Climatologic Research Center. Data arranged in ArcGIS. 99.65% of malaria transmission cases were focused in southeast part of Iran. These transmissions had statistically correlation with altitude (650 m), maximum (30 °C), minimum (20 °C) and average temperature (25.3 °C). Statistical correlation and overall relationship between NDVI (118.81), relative humidity (⩾45%) and rainfall in southeast area was defined and explained in this study. According to ecological condition and mentioned cut-off points, predictive map was generated using cokriging method. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

Linking the North Atlantic Oscillation to Rainfall Over Northern Lake Malawi

NASA Astrophysics Data System (ADS)

Johnson, T. C.; Powers, L. A.; Werne, J. P.; Brown, E. T.; Castaneda, I.; Schouten, S.; Sinninghe-Damste, J.

2005-12-01

Piston and multi-cores recovered from the north basin of Lake Malawi in 1998 by the International Decade for the East African Lakes (IDEAL) have provided a rich history of climate variability spanning the past 25,000 years. As we now begin to analyze the cores recovered by the Malawi Drilling Project in early 2005, we are considering the relationships among sedimentary signals of temperature (TEX86), northerly winds associated with a southward excursion of the Inter-Tropical Convergence Zone (per cent biogenic silica), and rainfall (terrigenous mass accumulation rate) in the well dated 1998 cores. A high-resolution record of the past 800 years suggests that rainfall in this region (10 - 12° S, 30 - 35° E) was relatively low during the Little Ice Age, when northerly winds were more prevalent, attributed to a more southerly position of the ITCZ during austral summers. The TEX86 signal of lake (surface?) temperature ranged mostly between 24 and 26°C during this period, with the coldest temperature of about 22°C around AD1680 and the warmest temperature, exceeding 27°C, in the youngest sediment sample. The cooler water temperatures coincide with periods of highest diatom productivity, consistent with the latter being due to relatively intense upwelling associated with the northerly winds. Our observation of low rainfall during periods of more southerly migration of the ITCZ is consistent with the results of McHugh and Rogers (2001), who linked rainfall in southeastern Africa to the North Atlantic Oscillation (NAO). During years of weak NAO, equatorial westerly transport of Atlantic moisture across Africa during austral summer is relatively intense, causing high rainfall in the East African Rift between the equator and 16° S. Conversely, when the NAO is positive, rainfall is higher south of 15° S than north of this latitude, which is consistent with a southward migration of the ITCZ. McHugh, M. J. and J. C. Rogers (2001). "North Atlantic Oscillation influence on precipitation variability around the southeast African convergence zone." Journal of Climate 14: 3631-3642.

Realism of Indian Summer Monsoon Simulation in a Quarter Degree Global Climate Model

NASA Astrophysics Data System (ADS)

Salunke, P.; Mishra, S. K.; Sahany, S.; Gupta, K.

2017-12-01

This study assesses the fidelity of Indian Summer Monsoon (ISM) simulations using a global model at an ultra-high horizontal resolution (UHR) of 0.25°. The model used was the atmospheric component of the Community Earth System Model version 1.2.0 (CESM 1.2.0) developed at the National Center for Atmospheric Research (NCAR). Precipitation and temperature over the Indian region were analyzed for a wide range of space and time scales to evaluate the fidelity of the model under UHR, with special emphasis on the ISM simulations during the period of June-through-September (JJAS). Comparing the UHR simulations with observed data from the India Meteorological Department (IMD) over the Indian land, it was found that 0.25° resolution significantly improved spatial rainfall patterns over many regions, including the Western Ghats and the South-Eastern peninsula as compared to the standard model resolution. Convective and large-scale rainfall components were analyzed using the European Centre for Medium Range Weather Forecast (ECMWF) Re-Analysis (ERA)-Interim (ERA-I) data and it was found that at 0.25° resolution, there was an overall increase in the large-scale component and an associated decrease in the convective component of rainfall as compared to the standard model resolution. Analysis of the diurnal cycle of rainfall suggests a significant improvement in the phase characteristics simulated by the UHR model as compared to the standard model resolution. Analysis of the annual cycle of rainfall, however, failed to show any significant improvement in the UHR model as compared to the standard version. Surface temperature analysis showed small improvements in the UHR model simulations as compared to the standard version. Thus, one may conclude that there are some significant improvements in the ISM simulations using a 0.25° global model, although there is still plenty of scope for further improvement in certain aspects of the annual cycle of rainfall.

Global warming and South Indian monsoon rainfall-lessons from the Mid-Miocene.

PubMed

Reuter, Markus; Kern, Andrea K; Harzhauser, Mathias; Kroh, Andreas; Piller, Werner E

2013-04-01

Precipitation over India is driven by the Indian monsoon. Although changes in this atmospheric circulation are caused by the differential seasonal diabatic heating of Asia and the Indo-Pacific Ocean, it is so far unknown how global warming influences the monsoon rainfalls regionally. Herein, we present a Miocene pollen flora as the first direct proxy for monsoon over southern India during the Middle Miocene Climate Optimum. To identify climatic key parameters, such as mean annual temperature, warmest month temperature, coldest month temperature, mean annual precipitation, mean precipitation during the driest month, mean precipitation during the wettest month and mean precipitation during the warmest month the Coexistence Approach is applied. Irrespective of a ~ 3-4 °C higher global temperature during the Middle Miocene Climate Optimum, the results indicate a modern-like monsoonal precipitation pattern contrasting marine proxies which point to a strong decline of Indian monsoon in the Himalaya at this time. Therefore, the strength of monsoon rainfall in tropical India appears neither to be related to global warming nor to be linked with the atmospheric conditions over the Tibetan Plateau. For the future it implies that increased global warming does not necessarily entail changes in the South Indian monsoon rainfall.

Regional patterns of the change in annual-mean tropical rainfall under global warming

NASA Astrophysics Data System (ADS)

Huang, P.

2013-12-01

Projection of the change in tropical rainfall under global warming is a major challenge with great societal implications. The current study analyzes the 18 models from the Coupled Models Intercomparison Project, and investigates the regional pattern of annual-mean rainfall change under global warming. With surface warming, the climatological ascending pumps up increased surface moisture and leads rainfall increase over the tropical convergence zone (wet-get-wetter effect), while the pattern of sea surface temperature (SST) increase induces ascending flow and then increasing rainfall over the equatorial Pacific and the northern Indian Ocean where the local oceanic warming exceeds the tropical mean temperature increase (warmer-get-wetter effect). The background surface moisture and SST also can modify warmer-get-wetter effect: the former can influence the moisture change and contribute to the distribution of moist instability change, while the latter can suppress the role of instability change over the equatorial eastern Pacific due to the threshold effect of convection-SST relationship. The wet-get-wetter and modified warmer-get-wetter effects form a hook-like pattern of rainfall change over the tropical Pacific and an elliptic pattern over the northern Indian Ocean. The annual-mean rainfall pattern can be partly projected based on current rainfall climatology, while it also has great uncertainties due to the uncertain change in SST pattern.

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.

Observational evidence for the relationship between spring soil moisture and June rainfall over the Indian region

NASA Astrophysics Data System (ADS)

KanthaRao, B.; Rakesh, V.

2018-05-01

Understanding the relationship between gradually varying soil moisture (SM) conditions and monsoon rainfall anomalies is crucial for seasonal prediction. Though it is an important issue, very few studies in the past attempted to diagnose the linkages between the antecedent SM and Indian summer monsoon rainfall. This study examined the relationship between spring (April-May) SM and June rainfall using observed data during the period 1979-2010. The Empirical Orthogonal Function (EOF) analyses showed that the spring SM plays a significant role in June rainfall over the Central India (CI), South India (SI), and North East India (NEI) regions. The composite anomaly of the spring SM and June rainfall showed that excess (deficit) June rainfall over the CI was preceded by wet (dry) spring SM. The anomalies in surface-specific humidity, air temperature, and surface radiation fluxes also supported the existence of a positive SM-precipitation feedback over the CI. On the contrary, excess (deficit) June rainfall over the SI and NEI region were preceded by dry (wet) spring SM. The abnormal wet (dry) SM over the SI and NEI decreased (increased) the 2-m air temperature and increased (decreased) the surface pressure compared to the surrounding oceans which resulted in less (more) moisture transport from oceans to land (negative SM-precipitation feedback over the Indian monsoon region).

The Response of Environmental Capacity for Malaria Transmission in West Africa to Climate Change

NASA Astrophysics Data System (ADS)

Yamana, T. K.; Eltahir, E. A.

2011-12-01

The climate of West Africa is characterized by north-south gradients in temperature and rainfall. Environmental capacity for malaria transmission (e.g. as measured by vectorial capacity) is strongly tied to these two variables; temperature affects the development rate of the malaria parasite, as well as the lifespan of the mosquitoes that transmit the disease, and rainfall is tied to mosquito abundance, as the vector lays its eggs in rain-fed water pools. A change in climate is therefore expected to lead to changes in the distribution of malaria transmission. Current general circulation models agree that the temperature in West Africa is expected to increase by several degrees in the next century. However they predict a wide range of possible rainfall scenarios in the future, from intense drying to significant increases in rainfall (Christensen et al., 2007). The effects these changes will have on environmental capacity for malaria transmission depend on the magnitude and direction of the changes, and on current conditions. For example, malaria transmission will be more sensitive to positive changes in rainfall in dry areas where mosquito populations are currently limited by water availability than in relatively wet areas. Here, we analyze combinations of changes in rainfall and temperature within the ranges predicted by GCMs, and assess the impact these combinations will have on the environmental capacity for malaria transmission. In particular, we identify climate change scenarios that are likely to have the greatest impact on environmental capacity for malaria transmission, as well as geographic "hot spots" where the greatest changes are to be expected. Christensen, J. H., Busuioc, A., & et al. (2007). Regional climate projections. In S. Solomon (Ed.), Climate change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.

Role of meteorological conditions in reported chickenpox cases in Wuhan and Hong Kong, China.

PubMed

Chen, Banghua; Sumi, Ayako; Wang, Lei; Zhou, Wang; Kobayashi, Nobumichi

2017-08-03

Chickenpox is a common contagious disease that remains an important public health issue worldwide. Over 90% of unvaccinated individuals become infected, but infection occurs at different ages in different parts of the world. Many people have been infected by 20 to 30 years of age in China, and adults and pregnant women who become infected often develop severe infection. Furthermore, a mortality rate of 2-3 per 100,000 infected persons has been reported. In this study, we explore the temperature-dependent transition of patterns of reported chickenpox cases in two large subtropical climate cities, Wuhan and Hong Kong, China, to aid in the prediction of epidemics and preparation for the effects of climatic changes on epidemiology of chickenpox in China. We used a time series analysis comprising a spectral analysis based on the maximum entropy method in the frequency domain and the nonlinear least squares method in the time domain. Specifically, the following time series data were analyzed: data of reported chickenpox cases and meteorological data, including the mean temperature, relative humidity and total rainfall in Wuhan and Hong Kong from January 2008 to June 2015. The time series data of chickenpox for both Wuhan and Hong Kong have two peaks per year, one in winter and another in spring, indicating a bimodal cycle. To investigate the source of the bimodal cycle of the chickenpox data, we defined the contribution ratio of the 1-year cycle, Q 1 , and the 6-month cycle, Q 2 , as the contribution of the amplitude of a 1-year cycle and a 6-month cycle, respectively, to the entire amplitude of the time-series data. The Q 1 values of Wuhan and Hong Kong were positively correlated with the annual mean temperature and rainfall of each city. Conversely, the Q 2 values of Wuhan and Hong Kong were negatively correlated with the annual mean temperature and rainfall of Wuhan and Hong Kong. Our results showed that the mean temperature and rainfall have a significant influence on the incidence of chickenpox, and might be important predictors of chickenpox incidence in Wuhan and Hong Kong.

Disaggregating from daily to sub-daily rainfall under a future climate

NASA Astrophysics Data System (ADS)

Westra, S.; Evans, J.; Mehrotra, R.; Sharma, A.

2012-04-01

We describe an algorithm for disaggregating daily rainfall into sub-daily rainfall 'fragments' (continuous fine-resolution rainfall sequences whose total depth sums to the daily rainfall amount) under a future, warmer climate. The basis of the algorithm is re-sample sub-daily fragments from the historical record conditional on the total daily rainfall amount and a range of atmospheric predictors representative of the future climate. The logic is that as the atmosphere warms, future rainfall patterns will be more reflective of historical rainfall patterns which occurred on warmer days at the same location, or at locations which have an atmospheric profile more reflective of expected future conditions. When looking at the scaling from daily to sub-daily rainfall over the historical record, it was found that the relationship varied significantly by season and by location, with rainfall patterns on warmer seasons or at warmer locations typically showing more intense rain falling over shorter periods compared with cooler seasons and stations. Importantly, by regressing against atmospheric covariates such as temperature this effect was almost entirely eliminated, providing a basis for suggesting the approach may be valid when extrapolating sub-daily sequences to a future climate. The method of fragments algorithm was then applied to nine stations around Australia, and showed that when holding the total daily rainfall constant, the maximum intensity of a short duration (6 minute) rainfall increased by between 4.1% and 13.4% per degree change in temperature for the maximum six minute burst, between 3.1% and 6.8% for the maximum one hour burst, and between 1.5% and 3.5% for the fraction of the day with no rainfall. This highlights that a large proportion of the change to the distribution of precipitation in the future is likely to occur at sub-daily timescales, with significant implications for many hydrological systems.

Meteorological Trigger Conditions for Different Geomorphic Processes in Steep Mountain Channels in the Austrian Alps

NASA Astrophysics Data System (ADS)

Kaitna, R.; Braun, M.

2016-12-01

Steep mountain channels episodically can experience very different geomorphic processes, ranging from flash floods, intensive bedload transport, debris floods, and debris flows. Rainfall-related trigger conditions and geomorphic disposition for each of these processes to occur, as well as conditions leading to one process and not to the other, are not well understood. In this contribution, we analyze triggering rainfalls for all documented events in the Eastern (Austrian) Alps on a daily and sub-daily basis. The analysis with daily rainfall data covers more than 6640 events between 1901 and 2014 and the analysis based on sub-daily (10 min interval) rainfall data includes around 950 events between 1992 and 2014. Of the four investigated event types, we find that debris flows are typically associated with the least cumulative rainfall, while intensive bedload transport as well as torrential floods occur when there is a substantial amount of cumulative rainfall. Debris floods are occurring on average with cumulative rainfall in a range between the aforementioned processes. Comparison of historical data shows, that about 90% of events are triggered with a combination of extreme rainfall and temperature. Bayesian analysis reveals that a high degree of geomorphic events is associated with very short rainfall durations that cannot be resolved with daily rainfall data. A comparison of both datasets shows that subdaily data gives more accurate results. Additionally, we find a high degree of regional differences, e.g. between regions north and south of the Alpine chain or high or low Alpine regions. There is indication that especially debris flows need less total rainfall amount when occurring in regions with a high relief energy than in less steep environments. The limitation of our analysis is mainly due to the distance between the locations of event triggering and rainfall measurement and the definition of rainfall events for the Bayesian analysis. In a next step, we will connect our results with the analyses of the hydrological as well as geomorphological disposition in selected study regions and with projections of changing climate conditions.

Understanding the science of climate change: Talking points - Impacts to the Gulf Coast

Treesearch

Rachel Loehman; Greer Anderson

2010-01-01

Predicted climate changes in the Gulf Coast bioregion include increased air and sea surface temperatures, altered fire regimes and rainfall patterns, increased frequency of extreme weather events, rising sea levels, increased hurricane intensity, and potential destruction of coastal wetlands and the species that reside within them. Prolonged drought conditions, storm...

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.

Characterizing response of total suspended solids and total phosphorus loading to weather and watershed characteristics for rainfall and snowmelt events in agricultural watersheds

USGS Publications Warehouse

Danz, Mari E.; Corsi, Steven; Brooks, Wesley R.; Bannerman, Roger T.

2013-01-01

Understanding the response of total suspended solids (TSS) and total phosphorus (TP) to influential weather and watershed variables is critical in the development of sediment and nutrient reduction plans. In this study, rainfall and snowmelt event loadings of TSS and TP were analyzed for eight agricultural watersheds in Wisconsin, with areas ranging from 14 to 110 km2 and having four to twelve years of data available. The data showed that a small number of rainfall and snowmelt runoff events accounted for the majority of total event loading. The largest 10% of the loading events for each watershed accounted for 73–97% of the total TSS load and 64–88% of the total TP load. More than half of the total annual TSS load was transported during a single event for each watershed at least one of the monitored years. Rainfall and snowmelt events were both influential contributors of TSS and TP loading. TSS loading contributions were greater from rainfall events at five watersheds, from snowmelt events at two watersheds, and nearly equal at one watershed. The TP loading contributions were greater from rainfall events at three watersheds, from snowmelt events at two watersheds and nearly equal at three watersheds. Stepwise multivariate regression models for TSS and TP event loadings were developed separately for rainfall and snowmelt runoff events for each individual watershed and for all watersheds combined by using a suite of precipitation, melt, temperature, seasonality, and watershed characteristics as predictors. All individual models and the combined model for rainfall events resulted in two common predictors as most influential for TSS and TP. These included rainfall depth and the antecedent baseflow. Using these two predictors alone resulted in an R2 greater than 0.7 in all but three individual models and 0.61 or greater for all individual models. The combined model yielded an R2 of 0.66 for TSS and 0.59 for TP. Neither the individual nor the combined models were substantially improved by using additional predictors. Snowmelt event models were statistically significant for individual and combined watershed models, but the model fits were not all as good as those for rainfall events (R2 between 0.19 and 0.87). Predictor selection varied from watershed to watershed, and the common variables that were selected were not always selected in the same order. Influential variables were commonly direct measures of moisture in the watershed such as snowmelt, rainfall + snowmelt, and antecedent baseflow, or measures of potential snowmelt volume in the watershed such as air temperature.

Tendencies of extreme values on rainfall and temperature and its relationship with teleconnection patterns

NASA Astrophysics Data System (ADS)

Taboada, J. J.; Cabrejo, A.; Guarin, D.; Ramos, A. M.

2009-04-01

It is now very well established that yearly averaged temperatures are increasing due to anthropogenic climate change. In the area of Galicia (NW Spain) this trend has also been determined. Rainfall does not show a clear tendency in its yearly accumulated values. The aim of this work is to study different extreme indices of rainfall and temperatures analysing variability and possible trends associated to climate change. Station data for the study was provided by the CLIMA database of the regional government of Galicia (NW Spain). The definition of the extreme indices was taken from the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI) This group has defined a set of standard extreme values to simplify intercomparison of data from different regions of the world. For the temperatures in the period 1960-2006, results show a significant increase of the number of days with maximum temperatures above the 90th percentile. Furthermore, a significant decrease of the days with maximum temperatures below the 10th percentile has been found. The tendencies of minimum temperatures are reverse: fewer nights with minimum temperatures below 10th percentile, and more with minimum temperatures above 90th percentile. Those tendencies can be observed all over the year, but are more pronounced in summer. This trend is expected to continue in the next decades because of anthropogenic climate change. We have also calculated the relationship between the above mentioned extreme values and different teleconnection patterns appearing in the North Atlantic area. Results show that local tendencies are associated with trends of EA (Eastern Atlantic) and SCA (Scandinavian) patterns. NAO (North Atlantic Oscillation) has also some relationship with these tendencies, but only related with cold days and nights in winter. Rainfall index do not show any clear tendency on the annual scale. Nevertheless, the count of days when precipitation is greater than 20mm (R20mm) and the total precipitation when rainfall is greater than 95th percentile (R95pTOT) diminishes in winter and spring, but increases in autumn. This trend is related with NAO in winter and spring and with SCA in autumn.

Short-term effects of weather and air pollution on atopic dermatitis symptoms in children: A panel study in Korea.

PubMed

Kim, Young-Min; Kim, Jihyun; Han, Youngshin; Jeon, Byoung-Hak; Cheong, Hae-Kwan; Ahn, Kangmo

2017-01-01

The effects of weather and air pollution on the severity and persistence of atopic dermatitis (AD) are important issues that have not been investigated in detail. The objective of our study was to determine the short-term effects of meteorological variables and air pollution on AD symptoms in children. We enrolled 177 AD patients with 5 years or younger from the Seoul Metropolitan Area, Korea, and followed for 17 months between August 2013 and December 2014. Symptoms records of 35,158 person-days, including itching, sleep disturbance, erythema, dry skin, oozing, and edema, were obtained. We estimated the effect of meteorological variables including daily mean temperature, relative humidity (RH), diurnal temperature range (DTR), rainfall and air pollutants including particulate matter with an aerodynamic diameter ≤10 μm (PM10), nitrogen dioxide (NO2), and tropospheric ozone (O3) on AD symptoms using a generalized linear mixed model with adjustment for related confounding factors. A 5°C increase in outdoor temperature and a 5% increase in outdoor RH was associated with 12.8% (95% confidence intervals (CI): 10.5, 15.2) and 3.3% (95% CI: 1.7, 4.7) decrease in AD symptoms, respectively, on the same day. An increase of rainfall by 5 mm increased AD symptoms by 7.3% (95% CI: 3.6, 11.1) for the days with <40 mm rainfall. The risk of AD symptoms increased by 284.9% (95% CI: 67.6, 784.2) according to a 5°C increase in DTR when it was >14°C. An increase in PM10, NO2, and O3 by 10 units increased the risk of AD symptoms on the same day by 3.2% (95% CI: 1.5, 4.9), 5.0% (95% CI: 1.4, 8.8), and 6.1% (95% CI: 3.2, 9.0), respectively. Exposure to meteorological variables and air pollutants are associated with AD symptoms in young children.

Empirical rainfall thresholds for the triggering of landslides in Asturias (NW Spain)

NASA Astrophysics Data System (ADS)

Valenzuela, Pablo; Luís Zêzere, José; José Domínguez-Cuesta, María; Mora García, Manuel Antonio

2017-04-01

Rainfall-triggered landslides are common and widespread phenomena in Asturias, a mountainous region in the NW of Spain where the climate is characterized by average annual precipitation and temperature values of 960 mm and 13.3°C respectively. Different types of landslides (slides, flows and rockfalls) frequently occur during intense rainfall events, causing every year great economic losses and sometimes human injuries or fatalities. For this reason, its temporal forecast is of great interest. The main goal of the present research is the calculation of empirical rainfall thresholds for the triggering of landslides in the Asturian region, following the methodology described by Zêzere et al., 2015. For this purpose, data from 559 individual landslides collected from press archives during a period of eight hydrological years (October 2008-September 2016) and gathered within the BAPA landslide database (http://geol.uniovi.es/BAPA) were used. Precipitation data series of 37 years came from 6 weather stations representative of the main geographical and climatic conditions within the study area. Applied methodology includes: (i) the definition of landslide events, (ii) the reconstruction of the cumulative antecedent rainfall for each event from 1 to 90 consecutive days, (iii) the estimation of the return period for each cumulated rainfall-duration condition using Gumbel probability distribution, (iv) the definition of the critical cumulated rainfall-duration conditions taking into account the highest return period, (v) the calculation of the thresholds considering both the conditions for the occurrence and non-occurrence of landslides. References: Zêzere, J.L., Vaz, T., Pereira, S., Oliveira, S.C., Marqués, R., García, R.A.C. 2015. Rainfall thresholds for landslide activity in Portugal: a state of the art. Environmental Earth Sciences, 73, 2917-2936. doi: 10.1007/s12665-014-3672-0

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.

Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

Selection of meteorological parameters affecting rainfall estimation using neuro-fuzzy computing methodology

NASA Astrophysics Data System (ADS)

Hashim, Roslan; Roy, Chandrabhushan; Motamedi, Shervin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Lee, Siew Cheng

2016-05-01

Rainfall is a complex atmospheric process that varies over time and space. Researchers have used various empirical and numerical methods to enhance estimation of rainfall intensity. We developed a novel prediction model in this study, with the emphasis on accuracy to identify the most significant meteorological parameters having effect on rainfall. For this, we used five input parameters: wet day frequency (dwet), vapor pressure (e̅a), and maximum and minimum air temperatures (Tmax and Tmin) as well as cloud cover (cc). The data were obtained from the Indian Meteorological Department for the Patna city, Bihar, India. Further, a type of soft-computing method, known as the adaptive-neuro-fuzzy inference system (ANFIS), was applied to the available data. In this respect, the observation data from 1901 to 2000 were employed for testing, validating, and estimating monthly rainfall via the simulated model. In addition, the ANFIS process for variable selection was implemented to detect the predominant variables affecting the rainfall prediction. Finally, the performance of the model was compared to other soft-computing approaches, including the artificial neural network (ANN), support vector machine (SVM), extreme learning machine (ELM), and genetic programming (GP). The results revealed that ANN, ELM, ANFIS, SVM, and GP had R2 of 0.9531, 0.9572, 0.9764, 0.9525, and 0.9526, respectively. Therefore, we conclude that the ANFIS is the best method among all to predict monthly rainfall. Moreover, dwet was found to be the most influential parameter for rainfall prediction, and the best predictor of accuracy. This study also identified sets of two and three meteorological parameters that show the best predictions.

Fire season and intensity affect shrub recruitment in temperate sclerophyllous woodlands.

PubMed

Knox, K J E; Clarke, P J

2006-10-01

The season in which a fire occurs may regulate plant seedling recruitment because of: (1) the interaction of season and intensity of fire and the temperature requirements for seed release, germination and growth; (2) post-fire rainfall and temperature patterns affecting germination; (3) the interaction of post-fire germination conditions and competition from surrounding vegetation; and (4) the interaction of post-fire germination conditions and seed predators and/or seedling herbivores. This study examined the effects of different fire intensities and fire seasons on the emergence and survival of shrubs representing a range of fire response syndromes from a summer rainfall cool climate region. Replicated experimental burns were conducted in two seasons (spring and autumn) in 2 consecutive years and fuel loads were increased to examine the effects of fire intensity (low intensity and moderate intensity). Post-fire watering treatments partitioned the effects of seasonal temperature from soil moisture. Higher intensity fires resulted in enhanced seedling emergence for hard-seeded species but rarely influenced survival. Spring fires enhanced seedling emergence across all functional groups. Reduced autumn recruitment was related to seasonal temperature inhibiting germination rather than a lack of soil moisture or competition. In Mediterranean-type climate regions, seedling emergence has been related to post-fire rainfall and exposure of seeds to seed predators. We think a similar model may operate in temperate summer rainfall regions where cold-induced dormancy over winter exposes seeds to predators for a longer time and subsequently results in recruitment failure. Our results support the theory that the effect of fire season is more predictable where there are strong seasonal patterns in climate. In this study seasonal temperature rather than rainfall appears to be more influential.

Three-dimensional circulation structures leading to heavy summer rainfall over central North China

NASA Astrophysics Data System (ADS)

Sun, Wei; Yu, Rucong; Li, Jian; Yuan, Weihua

2016-04-01

Using daily and hourly rain gauge records and Japanese 25 year reanalysis data over 30 years, this work reveals two major circulation structures leading to heavy summer rainfall events in central North China (CNC), and further analyzes the effects of the circulations on these rainfall events. One circulation structure has an extensive upper tropospheric warm anomaly (UTWA) covering North China (NC). By strengthening the upper anticyclonic anomaly and lower southerly flows around NC, the UTWA plays a positive role in forming upper level divergence and lower level moisture convergence. As a result, the warm anomalous circulation has a solid relationship with large-scale, long-duration rainfall events with a diurnal peak around midnight to early morning. The other circulation structure has an upper tropospheric cold anomaly (UTCA) located in the upper stream of NC. Contributed to by the UTCA, a cold trough appears in the upper stream of NC and an unstable configuration with upper (lower) cold (warm) anomalies forms around CNC. Consequently, CNC is covered by strong instability and high convective energy, and the cold anomalous circulation is closely connected with local, short-duration rainfall events concentrated from late afternoon to early nighttime. The close connections between circulation structures and typical rainfall events are confirmed by two independent converse analysis processes: from circulations to rainfall characteristics, and from typical rainfall events to circulations. The results presented in this work indicate that the upper tropospheric temperature has significant influences on heavy rainfall, and thus more attention should be paid to the upper tropospheric temperature in future analyses.

Future Changes to ENSO Temperature and Precipitation Teleconnections Under Warming

NASA Astrophysics Data System (ADS)

Perry, S.; McGregor, S.; Sen Gupta, A.; England, M. H.

2016-12-01

As the dominant mode of interannual climate variability, the El Niño-Southern Oscillation (ENSO) modulates temperature and rainfall globally, additionally contributing to weather extremes. Anthropogenic climate change has the potential to alter the strength and frequency of ENSO and may also alter ENSO-driven atmospheric teleconnections, affecting ecosystems and human activity in regions far removed from the tropical Pacific. State-of-art climate models exhibit considerable disagreement in projections of future changes in ENSO sea surface temperature variability. Despite this uncertainty, recent model studies suggest that the precipitation response to ENSO will be enhanced in the tropical Pacific under future warming, and as such the societal impacts of ENSO will increase. Here we use temperature and precipitation data from an ensemble of 41 CMIP5 models to show where ENSO teleconnections are being enhanced and dampened in a high-emission future scenario (RCP8.5) focusing on the changes that are occurring over land areas globally. Although there is some spread between the model projections, robust changes with strong ensemble agreement are found in certain locations, including amplification of teleconnections in southeast Australia, South America and the Maritime Continent. Our results suggest that in these regions future ENSO events will lead to more extreme temperature and rainfall responses.

Land use change exacerbates tropical South American drought by sea surface temperature variability

NASA Astrophysics Data System (ADS)

Lee, Jung-Eun; Lintner, Benjamin R.; Boyce, C. Kevin; Lawrence, Peter J.

2011-10-01

Observations of tropical South American precipitation over the last three decades indicate an increasing rainfall trend to the north and a decreasing trend to the south. Given that tropical South America has experienced significant land use change over the same period, it is of interest to assess the extent to which changing land use may have contributed to the precipitation trends. Simulations of the National Center for Atmospheric Research Community Atmosphere Model (NCAR CAM3) analyzed here suggest a non-negligible impact of land use on this precipitation behavior. While forcing the model by imposed historical sea surface temperatures (SSTs) alone produces a plausible north-south precipitation dipole over South America, NCAR CAM substantially underestimates the magnitude of the observed southern decrease in rainfall unless forcing associated with human-induced land use change is included. The impact of land use change on simulated precipitation occurs primarily during the local dry season and in regions of relatively low annual-mean rainfall, as the incidence of very low monthly-mean accumulations (<10 mm/month) increases significantly when land use change is imposed. Land use change also contributes to the simulated temperature increase by shifting the surface turbulent flux partitioning to favor sensible over latent heating. Moving forward, continuing pressure from deforestation in tropical South America will likely increase the occurrence of significant drought beyond what would be expected by anthropogenic warming alone and in turn compound biodiversity decline from habitat loss and fragmentation.

Assessment of the APCC Coupled MME Suite in Predicting the Distinctive Climate Impacts of Two Flavors of ENSO during Boreal Winter

NASA Technical Reports Server (NTRS)

Jeong, Hye-In; Lee, Doo Young; Karumuri, Ashok; Ahn, Joong-Bae; Lee, June-Yi; Luo, Jing-Jia; Schemm, Jae-Kyung E.; Hendon, Harry H.; Braganza, Karl; Ham, Yoo-Geun

2012-01-01

Forecast skill of the APEC Climate Center (APCC) Multi-Model Ensemble (MME) seasonal forecast system in predicting two main types of El Nino-Southern Oscillation (ENSO), namely canonical (or cold tongue) and Modoki ENSO, and their regional climate impacts is assessed for boreal winter. The APCC MME is constructed by simple composite of ensemble forecasts from five independent coupled ocean-atmosphere climate models. Based on a hindcast set targeting boreal winter prediction for the period 19822004, we show that the MME can predict and discern the important differences in the patterns of tropical Pacific sea surface temperature anomaly between the canonical and Modoki ENSO one and four month ahead. Importantly, the four month lead MME beats the persistent forecast. The MME reasonably predicts the distinct impacts of the canonical ENSO, including the strong winter monsoon rainfall over East Asia, the below normal rainfall and above normal temperature over Australia, the anomalously wet conditions across the south and cold conditions over the whole area of USA, and the anomalously dry conditions over South America. However, there are some limitations in capturing its regional impacts, especially, over Australasia and tropical South America at a lead time of one and four months. Nonetheless, forecast skills for rainfall and temperature over East Asia and North America during ENSO Modoki are comparable to or slightly higher than those during canonical ENSO events.

Meteorological factors affecting the sudden decline in Lake Urmia's water level

NASA Astrophysics Data System (ADS)

Arkian, Foroozan; Nicholson, Sharon E.; Ziaie, Bahareh

2018-01-01

Lake Urmia, in northwest Iran, is the second most saline lake in the world. During the past two decades, the level of water has markedly decreased. In this paper, climate of the lake region is investigated by using data from four meteorological stations near the lake. The data include climatic parameters such as temperature, precipitation, humidity, wind speed, sunshine hours, number of rain days, and evaporation. Climate around the lake is examined by way of climate classification in the periods before and after the reduction in water level. Rainfall in the lake catchment is also evaluated using both gauge and satellite data. The results show a significant decreasing trend in mean annual precipitation and wind speed and an increasing trend in annual average temperature and sunshine hours at the four stations. Precipitation and wind speed have decreased by 37 mm and 2.7 m/s, respectively, and the mean annual temperature and sunshine hours have increased by 1.4 °C and 41.6 days, respectively, over these six decades. Only the climate of the Tabriz region is seen to have significantly changed, going from semiarid to arid. Gauge records and satellite data show a large-scale decreasing trend in rainfall since 1995. The correlation between rainfall and year-to-year changes in lake level is 0.69 over the period 1965 to 2010. The relationship is particularly strong from the early 1990s to 2005. This suggests that precipitation has played an important role in the documented decline of the lake.

Climate Assessment for 2000.

NASA Astrophysics Data System (ADS)

Lawrimore, Jay H.; Halpert, Michael S.; Bell, Gerald D.; Menne, Matthew J.; Lyon, Bradfield; Schnell, Russell C.; Gleason, Karin L.; Easterling, David R.; Thiaw, Wasila; Wright, William J.; Heim, Richard R., Jr.; Robinson, David A.; Alexander, Lisa

2001-06-01

The global climate in 2000 was again influenced by the long-running Pacific cold episode (La Niña) that began in mid-1998. Consistent with past cold episodes, enhanced convection occurred across the climatologically convective regions of Indonesia and the western equatorial Pacific, while convection was suppressed in the central Pacific. The La Niña was also associated with a well-defined African easterly jet located north of its climatological mean position and low vertical wind shear in the tropical Atlantic and Caribbean, both of which contributed to an active North Atlantic hurricane season. Precipitation patterns influenced by typical La Niña conditions included 1) above-average rainfall in southeastern Africa, 2) unusually heavy rainfall in northern and central regions of Australia, 3) enhanced precipitation in the tropical Indian Ocean and western tropical Pacific, 4) little rainfall in the central tropical Pacific, 5) below-normal precipitation over equatorial east Africa, and 6) drier-than-normal conditions along the Gulf coast of the United States.Although no hurricanes made landfall in the United States in 2000, another active North Atlantic hurricane season featured 14 named storms, 8 of which became hurricanes, with 3 growing to major hurricane strength. All of the named storms over the North Atlantic formed during the August-October period with the first hurricane of the season, Hurricane Alberto, notable as the third-longest-lived tropical system since reliable records began in 1945. The primary human loss during the 2000 season occurred in Central America, where Hurricane Gordon killed 19 in Guatemala, and Hurricane Keith killed 19 in Belize and caused $200 million dollars of damage.Other regional events included 1) record warm January-October temperatures followed by record cold November-December temperatures in the United States, 2) extreme drought and widespread wildfires in the southern and western Unites States, 3) continued long-term drought in the Hawaiian Islands throughout the year with record 24-h rainfall totals in November, 4) deadly storms and flooding in western Europe in October, 5) a summer heat wave and drought in southern Europe, 6) monsoon flooding in parts of Southeast Asia and India, 7) extreme winter conditions in Mongolia, 8) extreme long-term drought in the Middle East and Southwest Asia, and 9) severe flooding in southern Africa.Global mean temperatures remained much above average in 2000. The average land and ocean temperature was 0.39°C above the 1880-1999 long-term mean, continuing a trend to warmer-than-average temperatures that made the 1990s the warmest decade on record. While the persistence of La Niña conditions in 2000 was associated with somewhat cooler temperatures in the Tropics, temperatures in the extratropics remained near record levels. Land surface temperatures in the high latitudes of the Northern Hemisphere were notably warmer than normal, with annually averaged anomalies greater than 2°C in parts of Alaska, Canada, Asia, and northern Europe.

Monitoring and Prediction of Precipitable Water Vapor using GPS data in Turkey

NASA Astrophysics Data System (ADS)

Ansari, Kutubuddin; Althuwaynee, Omar F.; Corumluoglu, Ozsen

2016-12-01

Although Global Positioning System (GPS) primarily provide accurate estimates of position, velocity and time of the receiver, as the signals pass through the atmoshphere carrying its signatures, thus offers opportunities for atmoshpheric applications. Precipitable water vapor (PWV) is a vital component of the atmosphere and significantly influences atmospheric processes like rainfall and atmospheric temperature. The developing networks of continuously operating GPS can be used to efficiently estimate PWV. The Turkish Permanent GPS Network (TPGN) is employed to monitor PWV information in Turkey. This work primarily aims to derive long-term data of PWV by using atmospheric path delays observed through continuously operating TPGN from November 2014 to October 2015. A least square mathematical approach was then applied to establish the relation of the observed PWV to rainfall and temperature. The modeled PWV was correlated with PWV estimated from GPS data, with an average correlation of 67.10 %-88.60 %. The estimated root mean square error (RMSE) varied from 2.840 to 6.380, with an average of 4.697. Finally, data of TPGN, rainfall, and temperature were obtained for less than 2 months (November 2015 to December 2015) and assessed to validate the mathematical model. This study provides a basis for determining PWV by using rainfall and temperature data.

Influence of preonset land atmospheric conditions on the Indian summer monsoon rainfall variability

NASA Astrophysics Data System (ADS)

Rai, Archana; Saha, Subodh K.; Pokhrel, Samir; Sujith, K.; Halder, Subhadeep

2015-05-01

A possible link between preonset land atmospheric conditions and the Indian summer monsoon rainfall (ISMR) is explored. It is shown that, the preonset positive (negative) rainfall anomaly over northwest India, Pakistan, Afghanistan, and Iran is associated with decrease (increase) in ISMR, primarily in the months of June and July, which in turn affects the seasonal mean. ISMR in the months of June and July is also strongly linked with the preonset 2 m air temperature over the same regions. The preonset rainfall/2 m air temperature variability is linked with stationary Rossby wave response, which is clearly evident in the wave activity flux diagnostics. As the predictability of Indian summer monsoon relies mainly on the El Niño-Southern Oscillation (ENSO), the found link may further enhance our ability to predict the monsoon, particularly during a non-ENSO year.

Gamma-radiation monitoring in post-tectonic biotitic granites at Celorico da Beira

NASA Astrophysics Data System (ADS)

Domingos, Filipa; Barbosa, Susana; Pereira, Alcides; Neves, Luís

2017-04-01

Despite its obvious relevance, the effect of meteorological variables such as temperature, pressure, wind, rainfall and particularly humidity on the temporal variability of natural radiation is complex and still not fully understood. Moreover, the nature of their influence with increasing depth is also poorly understood. Thereby, two boreholes were set 3 m apart in the region of Celorico da Beira within post-tectonic biotitic granites of the Beiras Batolith. Continuous measurements were obtained with identical gamma-ray scintillometers deployed at depths of 1 and 6 m during a 6 month period in the years of 2014 and 2015. Temperature, relative humidity, pressure, rainfall, wind speed and direction were measured at the site, as well as temperature and relative humidity inside the boreholes, with the aim of assessing the influence of meteorological parameters on the temporal variability of gamma radiation at two distinct depths. Both time series display a complex temporal structure including multiyear, seasonal and daily variability. At 1 m depth, a daily periodicity on the gamma ray counts time series was noticed with daily maxima occurring most frequently from 8 to 12 p.m. and daily minima between 8 and 12 a.m.. At 6 m depth, maximum and minimum daily means occurred with approximately a 10 h lag from the above. Gamma radiation data exhibited fairly strong correlations with temperature and relative humidity, however, varying with depth. Gamma radiation counts increased with increasing temperature and decreasing relative humidity at 1 m depth, while at a 6 m depth the opposite was recorded, with counts increasing with relative humidity and decreasing with temperature. Wind speed was shown to be inversely related with counts at 6 m depth, while positively correlated at 1 m depth. Pressure and rainfall had minor effects on both short-term and long-term gamma radiation counts.

The cross wavelet analysis of dengue fever variability influenced by meteorological conditions

NASA Astrophysics Data System (ADS)

Lin, Yuan-Chien; Yu, Hwa-Lung; Lee, Chieh-Han

2015-04-01

The multiyear variation of meteorological conditions induced by climate change causes the changing diffusion pattern of infectious disease and serious epidemic situation. Among them, dengue fever is one of the most serious vector-borne diseases distributed in tropical and sub-tropical regions. Dengue virus is transmitted by several species of mosquito and causing lots amount of human deaths every year around the world. The objective of this study is to investigate the impact of meteorological variables to the temporal variation of dengue fever epidemic in southern Taiwan. Several extreme and average indices of meteorological variables, i.e. temperature and humidity, were used for this analysis, including averaged, maximum and minimum temperature, and average rainfall, maximum 1-hr rainfall, and maximum 24-hr rainfall. This study plans to identify and quantify the nonlinear relationship of meteorological variables and dengue fever epidemic, finding the non-stationary time-frequency relationship and phase lag effects of those time series from 1998-2011 by using cross wavelet method. Results show that meteorological variables all have a significant time-frequency correlation region to dengue fever epidemic in frequency about one year (52 weeks). The associated phases can range from 0 to 90 degrees (0-13 weeks lag from meteorological factors to dengue incidences). Keywords: dengue fever, cross wavelet analysis, meteorological factor

Exploratory Long-Range Models to Estimate Summer Climate Variability over Southern Africa.

NASA Astrophysics Data System (ADS)

Jury, Mark R.; Mulenga, Henry M.; Mason, Simon J.

1999-07-01

Teleconnection predictors are explored using multivariate regression models in an effort to estimate southern African summer rainfall and climate impacts one season in advance. The preliminary statistical formulations include many variables influenced by the El Niño-Southern Oscillation (ENSO) such as tropical sea surface temperatures (SST) in the Indian and Atlantic Oceans. Atmospheric circulation responses to ENSO include the alternation of tropical zonal winds over Africa and changes in convective activity within oceanic monsoon troughs. Numerous hemispheric-scale datasets are employed to extract predictors and include global indexes (Southern Oscillation index and quasi-biennial oscillation), SST principal component scores for the global oceans, indexes of tropical convection (outgoing longwave radiation), air pressure, and surface and upper winds over the Indian and Atlantic Oceans. Climatic targets include subseasonal, area-averaged rainfall over South Africa and the Zambezi river basin, and South Africa's annual maize yield. Predictors and targets overlap in the years 1971-93, the defined training period. Each target time series is fitted by an optimum group of predictors from the preceding spring, in a linear multivariate formulation. To limit artificial skill, predictors are restricted to three, providing 17 degrees of freedom. Models with colinear predictors are screened out, and persistence of the target time series is considered. The late summer rainfall models achieve a mean r2 fit of 72%, contributed largely through ENSO modulation. Early summer rainfall cross validation correlations are lower (61%). A conceptual understanding of the climate dynamics and ocean-atmosphere coupling processes inherent in the exploratory models is outlined.Seasonal outlooks based on the exploratory models could help mitigate the impacts of southern Africa's fluctuating climate. It is believed that an advance warning of drought risk and seasonal rainfall prospects will improve the economic growth potential of southern Africa and provide additional security for food and water supplies.

Projected rainfall and temperature changes over Malaysia at the end of the 21st century based on PRECIS modelling system

NASA Astrophysics Data System (ADS)

Loh, Jui Le; Tangang, Fredolin; Juneng, Liew; Hein, David; Lee, Dong-In

2016-05-01

This study investigates projected changes in rainfall and temperature over Malaysia by the end of the 21st century based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2, A1B and B2 emission scenarios using the Providing Regional Climates for Impacts Studies (PRECIS). The PRECIS regional climate model (HadRM3P) is configured in 0.22° × 0.22° horizontal grid resolution and is forced at the lateral boundaries by the UKMO-HadAM3P and UKMOHadCM3Q0 global models. The model performance in simulating the present-day climate was assessed by comparing the modelsimulated results to the Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) dataset. Generally, the HadAM3P/PRECIS and HadCM3Q0/PRECIS simulated the spatio-temporal variability structure of both temperature and rainfall reasonably well, albeit with the presence of cold biases. The cold biases appear to be associated with the systematic error in the HadRM3P. The future projection of temperature indicates widespread warming over the entire country by the end of the 21st century. The projected temperature increment ranges from 2.5 to 3.9°C, 2.7 to 4.2°C and 1.7 to 3.1°C for A2, A1B and B2 scenarios, respectively. However, the projection of rainfall at the end of the 21st century indicates substantial spatio-temporal variation with a tendency for drier condition in boreal winter and spring seasons while wetter condition in summer and fall seasons. During the months of December to May, ~20-40% decrease of rainfall is projected over Peninsular Malaysia and Borneo, particularly for the A2 and B2 emission scenarios. During the summer months, rainfall is projected to increase by ~20-40% across most regions in Malaysia, especially for A2 and A1B scenarios. The spatio-temporal variations in the projected rainfall can be related to the changes in the weakening monsoon circulations, which in turn alter the patterns of regional moisture convergences in the region.

The creation of future daily gridded datasets of precipitation and temperature with a spatial weather generator, Cyprus 2020-2050

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Pashiardis, Stelios; Lange, Manfred

2014-05-01

High-resolution gridded daily datasets are essential for natural resource management and the analysis of climate changes and their effects. This study aimed to create gridded datasets of daily precipitation and daily minimum and maximum temperature, for the future (2020-2050). The horizontal resolution of the developed datasets is 1 x 1 km2, covering the area under control of the Republic of Cyprus (5.760 km2). The study is divided into two parts. The first consists of the evaluation of the performance of different interpolation techniques for daily rainfall and temperature data (1980-2010) for the creation of the gridded datasets. Rainfall data recorded at 145 stations and temperature data from 34 stations were used. For precipitation, inverse distance weighting (IDW) performs best for local events, while a combination of step-wise geographically weighted regression and IDW proves to be the best method for large scale events. For minimum and maximum temperature, a combination of step-wise linear multiple regression and thin plate splines is recognized as the best method. Six Regional Climate Models (RCMs) for the A1B SRES emission scenario from the EU ENSEMBLE project database were selected as sources for future climate projections. The RCMs were evaluated for their capacity to simulate Cyprus climatology for the period 1980-2010. Data for the period 2020-2050 from the three best performing RCMs were downscaled, using the change factors approach, at the location of observational stations. Daily time series were created with a stochastic rainfall and temperature generator. The RainSim V3 software (Burton et al., 2008) was used to generate spatial-temporal coherent rainfall fields. The temperature generator was developed in R and modeled temperature as a weakly stationary process with the daily mean and standard deviation conditioned on the wet and dry state of the day (Richardson, 1981). Finally gridded datasets depicting projected future climate conditions were created with the identified best interpolation methods. The difference between the input and simulated mean daily rainfall, averaged over all the stations, was 0.03 mm (2.2%), while the error related to the number of dry days was 2 (0.6%). For mean daily minimum temperature the error was 0.005 ºC (0.04%), while for maximum temperature it was 0.01 ºC (0.04%). Overall, the weather generators were found to be reliable instruments for the downscaling of precipitation and temperature. The resulting datasets indicate a decrease of the mean annual rainfall over the study area between 5 and 70 mm (1-15%) for 2020-2050, relative to 1980-2010. Average annual minimum and maximum temperature over the Republic of Cyprus are projected to increase between 1.2 and 1.5 ºC. The dataset is currently used to compute agricultural production and water use indicators, as part of the AGWATER project (AEIFORIA/GEORGO/0311(BIE)/06), co-financed by the European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation. Burton, A., Kilsby, C.G., Fowler, H.J., Cowpertwait, P.S.P., and O'Connell, P.E.: RainSim: A spatial-temporal stochastic rainfall modelling system. Environ. Model. Software 23, 1356-1369, 2008 Richardson, C.W.: Stochastic simulation of daily precipitation, temperature, and solar radiation. Water Resour. Res. 17, 182-190, 1981.

Six-year longitudinal study of Fasciola hepatica bulk milk antibody ELISA in the dairy dense region of the Republic Ireland.

PubMed

Munita, M P; Rea, R; Bloemhoff, Y; Byrne, N; Martinez-Ibeas, A M; Sayers, R G

2016-11-01

Completion of the F. hepatica lifecycle is dependent on suitable climatic conditions for development of immature stages of the parasite, and its snail intermediate host. Few investigations have been conducted regarding temporal variations in F. hepatica status in Irish dairy herds. The current study aimed to conduct a longitudinal study examining annual and seasonal trends in bulk milk seropositivity over six years, while also investigating associations with soil temperature, rainfall and flukicide treatment. Monthly bulk milk samples (BTM) were submitted by 28 herds between March 2009 and December 2014. In all, 1337 samples were analysed using a Cathepsin L1 ELISA. Soil temperature, rainfall and management data were obtained for general estimating equation and regression analyses. A general decrease in milk seropositivity was observed over the six year study period and was associated with an increased likelihood of treating for liver fluke (OR range=2.73-6.96). Annual and seasonal analyses of rainfall and F. hepatica BTM status yielded conflicting results. Higher annual rainfall (>1150mm) yielded a lower likelihood of being BTM positive than annual rainfall of <1000mm (OR=0.47; P=0.036). This was most likely due to farmers being more proactive in treating for F. hepatica in wetter years, although a 'wash effect' by high rainfall of the free living stages and snails cannot be ruled out. Higher seasonal rainfall (>120mm), however, was associated with increased ELISA S/P% values (Coefficient=9.63S/P%; P=0.001). Soil temperature was not found to influence F. hepatica to the same extent as rainfall and may reflect the lack of severe temperature fluctuations in Ireland. Flukicides active against both immature and mature F. hepatica were approximately half as likely to record a positive F. hepatica herd BTM status than a flukicide active against only the mature stage of the parasite (OR≅0.45; P<0.01). This study highlights the importance of examining both annual and seasonal F. hepatica data, which can vary significantly. Additionally, it highlights the progress that can be achieved in fluke control by application of a continuous BTM monitoring program. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Climate Assessment for 1997.

NASA Astrophysics Data System (ADS)

Bell, Gerald D.; Halpert, Michael S.

1998-05-01

The global climate during 1997 was affected by both extremes of the El Niño-Southern Oscillation (ENSO), with weak Pacific cold episode conditions prevailing during January and February, and one of the strongest Pacific warm episodes (El Niño) in the historical record prevailing during the remainder of the year. This warm episode contributed to major regional rainfall and temperature anomalies over large portions of the Tropics and extratropics, which were generally consistent with those observed during past warm episodes. In many regions, these anomalies were opposite to those observed during 1996 and early 1997 in association with Pacific cold episode conditions.Some of the most dramatic El Niño impacts during 1997 were observed in the Tropics, where anomalous convection was evident across the entire Pacific and throughout most major monsoon regions of the world. Tropical regions most affected by excessive El Niño-related rainfall during the year included 1) the eastern half of the tropical Pacific, where extremely heavy rainfall and strong convective activity covered the region from April through December; 2) equatorial eastern Africa, where excessive rainfall during OctoberDecember led to widespread flooding and massive property damage; 3) Chile, where a highly amplified and extended South Pacific jet stream brought increased storminess and above-normal rainfall during the winter and spring; 4) southeastern South America, where these same storms produced above-normal rainfall during JuneDecember; and 5) Ecuador and northern Peru, which began receiving excessive rainfall totals in November and December as deep tropical convection spread eastward across the extreme eastern Pacific.In contrast, El Niño-related rainfall deficits during 1997 included 1) Indonesia, where significantly below-normal rainfall from June through December resulted in extreme drought and contributed to uncontrolled wildfires; 2) New Guinea, where drought contributed to large-scale food shortages leading to an outbreak of malnutrition; 3) the Amazon Basin, which received below-normal rainfall during June-December in association with substantially reduced tropical convection throughout the region; 4) the tropical Atlantic, which experienced drier than normal conditions during July-December; and 5) central America and the Caribbean Sea, which experienced below-normal rainfall during March-December.The El Niño also contributed to a decrease in tropical storm and hurricane activity over the North Atlantic during August-November, and to an expanded area of conditions favorable for tropical cyclone and hurricane formation over the eastern North Pacific. These conditions are in marked contrast to both the 1995 and 1996 hurricane seasons, in which significantly above-normal tropical cyclone activity was observed over the North Atlantic and suppressed activity prevailed across the eastern North Pacific.Other regional aspects of the short-term climate during 1997 included 1) wetter than average 1996/97 rainy seasons in both northeastern Australia and southern Africa in association with a continuation of weak cold episode conditions into early 1997; 2) below-normal rainfall and drought in southeastern Australia from October 1996 to December 1997 following very wet conditions in this region during most of 1996; 3) widespread flooding in the Red River Valley of the north-central United States during April following an abnormally cold and snowy winter; 4) floods in central Europe during July following several consecutive months of above-normal rainfall; 5) near-record to record rainfall in southeastern Asia during June-August in association with an abnormally weak upper-level monsoon ridge; and 6) near-normal rainfall across India during the Indian monsoon season (June-September) despite the weakened monsoon ridge.

The Tropical Convective Spectrum. Part 1; Archetypal Vertical Structures

NASA Technical Reports Server (NTRS)

Boccippio, Dennis J.; Petersen, Walter A.; Cecil, Daniel J.

2005-01-01

A taxonomy of tropical convective and stratiform vertical structures is constructed through cluster analysis of 3 yr of Tropical Rainfall Measuring Mission (TRMM) "warm-season" (surface temperature greater than 10 C) precipitation radar (PR) vertical profiles, their surface rainfall, and associated radar-based classifiers (convective/ stratiform and brightband existence). Twenty-five archetypal profile types are identified, including nine convective types, eight stratiform types, two mixed types, and six anvil/fragment types (nonprecipitating anvils and sheared deep convective profiles). These profile types are then hierarchically clustered into 10 similar families, which can be further combined, providing an objective and physical reduction of the highly multivariate PR data space that retains vertical structure information. The taxonomy allows for description of any storm or local convective spectrum by the profile types or families. The analysis provides a quasi-independent corroboration of the TRMM 2A23 convective/ stratiform classification. The global frequency of occurrence and contribution to rainfall for the profile types are presented, demonstrating primary rainfall contribution by midlevel glaciated convection (27%) and similar depth decaying/stratiform stages (28%-31%). Profiles of these types exhibit similar 37- and 85-GHz passive microwave brightness temperatures but differ greatly in their frequency of occurrence and mean rain rates, underscoring the importance to passive microwave rain retrieval of convective/stratiform discrimination by other means, such as polarization or texture techniques, or incorporation of lightning observations. Close correspondence is found between deep convective profile frequency and annualized lightning production, and pixel-level lightning occurrence likelihood directly tracks the estimated mean ice water path within profile types.

A predictive model for spotted wilt epidemics in peanut based on local weather conditions and the tomato spotted wilt virus risk index.

PubMed

Olatinwo, R O; Paz, J O; Brown, S L; Kemerait, R C; Culbreath, A K; Beasley, J P; Hoogenboom, G

2008-10-01

Tomato spotted wilt virus (TSWV), a member of the genus Tospovirus (family Bunyaviridae), is an important plant virus that causes severe damage to peanut (Arachis hypogaea) in the southeastern United States. Disease severity has been extremely variable in individual fields in Georgia, due to several factors including variability in weather patterns. A TSWV risk index has been developed by the University of Georgia to aid peanut growers with the assessment and avoidance of high risk situations. This study was conducted to examine the relationship between weather parameters and spotted wilt severity in peanut, and to develop a predictive model that integrates localized weather information into the risk index. On-farm survey data collected during 1999, 2002, 2004, and 2005 growing seasons, and derived weather variables during the same years were analyzed using nonlinear and multiple regression analyses. Meteorological data were obtained from the Georgia Automated Environmental Monitoring Network. The best model explained 61% of the variation in spotted wilt severity (square root transformed) as a function of the interactions between the TSWV risk index, the average daily temperature in April (TavA), the average daily minimum temperature between March and April (TminMA), the accumulated rainfall in March (RainfallM), the accumulated rainfall in April (RainfallA), the number of rain days in April (RainDayA), evapotranspiration in April (EVTA), and the number of days from 1 January to the planting date (JulianDay). Integrating this weather-based model with the TSWV risk index may help peanut growers more effectively manage tomato spotted wilt disease.

Rainfall erosivity in Europe.

PubMed

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Klik, Andreas; Rousseva, Svetla; Tadić, Melita Perčec; Michaelides, Silas; Hrabalíková, Michaela; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Beguería, Santiago; Alewell, Christine

2015-04-01

Rainfall is one the main drivers of soil erosion. 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 USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha(-1) h(-1) yr(-1), with the highest values (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Contrasting rainfall declines in northern and southern Tanzania: Potential differential impacts of west Pacific warming and east Pacific cooling

NASA Astrophysics Data System (ADS)

Harrison, L.; Funk, C. C.; Verdin, J. P.; Pedreros, D. H.; Shukla, S.; Husak, G. J.

2015-12-01

Here, we present analysis of a new 1900-2014 rainfall record for the Greater Horn of Africa with high station density (CenTrends), and evaluate potential climate change "hot spots" in Tanzania. We identify recent (1981-2014) downward trends in Tanzanian rainfall, use CenTrends to place these in a longer historical context, and relate rainfall in these regions to decadal changes in global sea surface temperatures (SSTs). To identify areas of concern, we consider the potential food security impacts of the recent rainfall declines and also rapid population growth. Looking forward, we consider what the links to SSTs might mean for rainfall in the next several decades based on SST projections. In addition to CenTrends, we use a variety of geographic data sets, including 1981-2014 rainfall from the Climate Hazards group InfraRed Precipitation with Stations (CHIRPSv2.0), simulated crop stress from the USGS Geospatial Water Requirement Satisfaction Index (GeoWRSI) model, NOAA Extended Reconstructed SSTs (ERSST v4), SST projections from the Coupled Model Intercomparison Project (CMIP5), and land cover and population maps from SERVIR, WorldPOP, and CIESIN's Gridded Population of the World. The long-term CenTrends record allows us to suggest an interesting dichotomy in decadal rainfall forcing. During the March to June season, SSTs in the west Pacific appear to be driving post-1980 rainfall reductions in northern Tanzania. In the 2000s, northern Tanzania's densely populated Pangani River, Internal Drainage, and Lake Victoria basins experienced the driest period in more than a century. During summer, negative trends in southern Tanzania appear linked to a negative SST trend in the Nino3.4 region. Since the SST trend in the west (east) Pacific appears strongly influenced by global warming (natural decadal variability), we suggest that water resources in northern Tanzania may face increasing challenges, but that this will be less the case in southern Tanzania.

The influence of temperature, relative humidity and rainfall on the occurrence of the Pine Wood Nematode in Góis Council, Portugal

NASA Astrophysics Data System (ADS)

Costa, M. E. G.; Rodrigues, M. A.

2012-04-01

In this work, we propose to investigate the influence of the pine wood nematode in the species pinus pinaster in Góis council and the way it affects the economic activity in this region. In order to do that we are going to analyse the influence of temperature, relative humidity and rainfall in the development of the vector insect of the pine wood nematode. In a first stage we are going to do a homogenisation of the series of temperature and rainfall, since they present a significant lack of data. For that we have chosen a reference station that allows us to determine the correlation coefficient to eliminate the lacks that are present in the other series. After that we are going to do the correlation with the number of nematode episodes that occurred and evaluate the area affected for a single year.

Variation of Temperature and Precipitation in Urban Agglomeration and Prevention Suggestion of Waterlogging in Middle and Lower Reaches of Yangtze River

NASA Astrophysics Data System (ADS)

Na, Liu; Youjie, Jin; Jiaqi, Dai

2018-03-01

The variation trend of temperature and precipitation during flood season in the middle and lower reaches of the Yangtze River basin in recent 50 years and change characteristics of rainfall in five typical flood prone cities are analysed. Aiming at waterlogging problems in the urban agglomeration of middle and lower reaches of the Yangtze River, the comprehensive prevention and control suggestions are put forward. The results showed that: the temperature trend in the basin decreased and then increased, and the precipitation showed a downward-rising-downward trend, no mutation occurred; The incidence of heavy rainfall events in the five typical cities with daily rainfall more than 50mm showed an upward trend, and increased significantly after 2002. The intensity of precipitation increased gradually. Climate change makes urban agglomeration waterlogging disasters become increasingly prominent in the middle and lower reaches of the Yangtze River.

A comparison of weather variables linked to infectious disease patterns using laboratory addresses and patient residence addresses.

PubMed

Djennad, Abdelmajid; Lo Iacono, Giovanni; Sarran, Christophe; Fleming, Lora E; Kessel, Anthony; Haines, Andy; Nichols, Gordon L

2018-04-27

To understand the impact of weather on infectious diseases, information on weather parameters at patient locations is needed, but this is not always accessible due to confidentiality or data availability. Weather parameters at nearby locations are often used as a proxy, but the accuracy of this practice is not known. Daily Campylobacter and Cryptosporidium cases across England and Wales were linked to local temperature and rainfall at the residence postcodes of the patients and at the corresponding postcodes of the laboratory where the patient's specimen was tested. The paired values of daily rainfall and temperature for the laboratory versus residence postcodes were interpolated from weather station data, and the results were analysed for agreement using linear regression. We also assessed potential dependency of the findings on the relative geographic distance between the patient's residence and the laboratory. There was significant and strong agreement between the daily values of rainfall and temperature at diagnostic laboratories with the values at the patient residence postcodes for samples containing the pathogens Campylobacter or Cryptosporidium. For rainfall, the R-squared was 0.96 for the former and 0.97 for the latter, and for maximum daily temperature, the R-squared was 0.99 for both. The overall mean distance between the patient residence and the laboratory was 11.9 km; however, the distribution of these distances exhibited a heavy tail, with some rare situations where the distance between the patient residence and the laboratory was larger than 500 km. These large distances impact the distributions of the weather variable discrepancies (i.e. the differences between weather parameters estimated at patient residence postcodes and those at laboratory postcodes), with discrepancies up to ±10 °C for the minimum and maximum temperature and 20 mm for rainfall. Nevertheless, the distributions of discrepancies (estimated separately for minimum and maximum temperature and rainfall), based on the cases where the distance between the patient residence and the laboratory was within 20 km, still exhibited tails somewhat longer than the corresponding exponential fits suggesting modest small scale variations in temperature and rainfall. The findings confirm that, for the purposes of studying the relationships between meteorological variables and infectious diseases using data based on laboratory postcodes, the weather results are sufficiently similar to justify the use of laboratory postcode as a surrogate for domestic postcode. Exclusion of the small percentage of cases where there is a large distance between the residence and the laboratory could increase the precision of estimates, but there are generally strong associations between daily weather parameters at residence and laboratory.

Unidirectional trends in annual and seasonal climate and extremes in Egypt

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Sunspots, El Niño, and the levels of Lake Victoria, East Africa

NASA Astrophysics Data System (ADS)

Stager, J. Curt; Ruzmaikin, Alexander; Conway, Declan; Verburg, Piet; Mason, Peter J.

2007-08-01

An association of high sunspot numbers with rises in the level of Lake Victoria, East Africa, has been the focus of many investigations and vigorous debate during the last century. In this paper, we show that peaks in the ~11-year sunspot cycle were accompanied by Victoria level maxima throughout the 20th century, due to the occurrence of positive rainfall anomalies ~1 year before solar maxima. Similar patterns also occurred in at least five other East African lakes, which indicates that these sunspot-rainfall relationships were broadly regional in scale. Although irradiance fluctuations associated with the sunspot cycle are weak, their effects on tropical rainfall could be amplified through interactions with sea surface temperatures and atmospheric circulation systems, including ENSO. If this Sun-rainfall relationship persists in the future, then sunspot cycles can be used for long-term prediction of precipitation anomalies and associated outbreaks of insect-borne disease in much of East Africa. In that case, unusually wet rainy seasons and Rift Valley Fever epidemics should occur a year or so before the next solar maximum, which is expected to occur in 2011-2012 AD.

Identification of the Key Weather Factors Affecting Overwintering Success of Apolygus lucorum Eggs in Dead Host Tree Branches

PubMed Central

Pan, Hongsheng; Liu, Bing; Lu, Yanhui; Desneux, Nicolas

2014-01-01

Understanding the effects of weather on insect population dynamics is crucial to simulate and forecast pest outbreaks, which is becoming increasingly important with the effects of climate change. The mirid bug Apolygus lucorum is an important pest on cotton, fruit trees and other crops in China, and primarily lays its eggs on dead parts of tree branches in the fall for subsequent overwintering. As such, the eggs that hatch the following spring are most strongly affected by ambient weather factors, rather than by host plant biology. In this study, we investigated the effects of three major weather factors: temperature, relative humidity and rainfall, on the hatching rate of A. lucorum eggs overwintering on dead branches of Chinese date tree (Ziziphus jujuba). Under laboratory conditions, rainfall (simulated via soaking) was necessary for the hatching of overwintering A. lucorum eggs. In the absence of rainfall (unsoaked branches), very few nymphs successfully emerged under any of the tested combinations of temperature and relative humidity. In contrast, following simulated rainfall, the hatching rate of the overwintering eggs increased dramatically. Hatching rate and developmental rate were positively correlated with relative humidity and temperature, respectively. Under field conditions, the abundance of nymphs derived from overwintering eggs was positively correlated with rainfall amount during the spring seasons of 2009–2013, while the same was not true for temperature and relative humidity. Overall, our findings indicate that rainfall is the most important factor affecting the hatching rate of overwintering A. lucorum eggs on dead plant parts and nymph population levels during the spring season. It provides the basic information for precisely forecasting the emergence of A. lucorum and subsequently timely managing its population in spring, which will make it possible to regional control of this insect pest widely occurring in multiple crops in summer. PMID:24705353

Identification of the key weather factors affecting overwintering success of Apolygus lucorum eggs in dead host tree branches.

PubMed

Pan, Hongsheng; Liu, Bing; Lu, Yanhui; Desneux, Nicolas

2014-01-01

Understanding the effects of weather on insect population dynamics is crucial to simulate and forecast pest outbreaks, which is becoming increasingly important with the effects of climate change. The mirid bug Apolygus lucorum is an important pest on cotton, fruit trees and other crops in China, and primarily lays its eggs on dead parts of tree branches in the fall for subsequent overwintering. As such, the eggs that hatch the following spring are most strongly affected by ambient weather factors, rather than by host plant biology. In this study, we investigated the effects of three major weather factors: temperature, relative humidity and rainfall, on the hatching rate of A. lucorum eggs overwintering on dead branches of Chinese date tree (Ziziphus jujuba). Under laboratory conditions, rainfall (simulated via soaking) was necessary for the hatching of overwintering A. lucorum eggs. In the absence of rainfall (unsoaked branches), very few nymphs successfully emerged under any of the tested combinations of temperature and relative humidity. In contrast, following simulated rainfall, the hatching rate of the overwintering eggs increased dramatically. Hatching rate and developmental rate were positively correlated with relative humidity and temperature, respectively. Under field conditions, the abundance of nymphs derived from overwintering eggs was positively correlated with rainfall amount during the spring seasons of 2009-2013, while the same was not true for temperature and relative humidity. Overall, our findings indicate that rainfall is the most important factor affecting the hatching rate of overwintering A. lucorum eggs on dead plant parts and nymph population levels during the spring season. It provides the basic information for precisely forecasting the emergence of A. lucorum and subsequently timely managing its population in spring, which will make it possible to regional control of this insect pest widely occurring in multiple crops in summer.

Effects of seasonal climatic variability on several toxic contaminants in urban lakes: Implications for the impacts of climate change.

PubMed

Wu, Qiong; Xia, Xinghui; Mou, Xinli; Zhu, Baotong; Zhao, Pujun; Dong, Haiyang

2014-12-01

Climate change is supposed to have influences on water quality and ecosystem. However, only few studies have assessed the effect of climate change on environmental toxic contaminants in urban lakes. In this research, response of several toxic contaminants in twelve urban lakes in Beijing, China, to the seasonal variations in climatic factors was studied. Fluorides, volatile phenols, arsenic, selenium, and other water quality parameters were analyzed monthly from 2009 to 2012. Multivariate statistical methods including principle component analysis, cluster analysis, and multiple regression analysis were performed to study the relationship between contaminants and climatic factors including temperature, precipitation, wind speed, and sunshine duration. Fluoride and arsenic concentrations in most urban lakes exhibited a significant positive correlation with temperature/precipitation, which is mainly caused by rainfall induced diffuse pollution. A negative correlation was observed between volatile phenols and temperature/precipitation, and this could be explained by their enhanced volatilization and biodegradation rates caused by higher temperature. Selenium did not show a significant response to climatic factor variations, which was attributed to low selenium contents in the lakes and soils. Moreover, the response degrees of contaminants to climatic variations differ among lakes with different contamination levels. On average, temperature/precipitation contributed to 8%, 15%, and 12% of the variations in volatile phenols, arsenic, and fluorides, respectively. Beijing is undergoing increased temperature and heavy rainfall frequency during the past five decades. This study suggests that water quality related to fluoride and arsenic concentrations of most urban lakes in Beijing is becoming worse under this climate change trend. Copyright © 2014. Published by Elsevier B.V.

NASA Tropical Rainfall Measurement Mission (TRMM): Effects of tropical rainfall on upper ocean dynamics, air-sea coupling and hydrologic cycle

NASA Technical Reports Server (NTRS)

Lagerloef, Gary; Busalacchi, Antonio J.; Liu, W. Timothy; Lukas, Roger B.; Niiler, Pern P.; Swift, Calvin T.

1995-01-01

This was a Tropical Rainfall Measurement Mission (TRMM) modeling, analysis and applications research project. Our broad scientific goals addressed three of the seven TRMM Priority Science Questions, specifically: What is the monthly average rainfall over the tropical ocean areas of about 10(exp 5) sq km, and how does this rain and its variability affect the structure and circulation of the tropical oceans? What is the relationship between precipitation and changes in the boundary conditions at the Earth's surface (e.g., sea surface temperature, soil properties, vegetation)? How can improved documentation of rainfall improve understanding of the hydrological cycle in the tropics?

Interannual rainfall variability in the Amazon basin and sea-surface temperatures in the equatorial Pacific and the tropical Atlantic Oceans

NASA Astrophysics Data System (ADS)

Ronchail, Josyane; Cochonneau, Gérard; Molinier, Michel; Guyot, Jean-Loup; Chaves, Adriana Goretti De Miranda; Guimarães, Valdemar; de Oliveira, Eurides

2002-11-01

Rainfall variability in the Amazon basin is studied in relation to sea-surface temperatures (SSTs) in the equatorial Pacific and the northern and southern tropical Atlantic during the 1977-99 period, using the HiBAm original rainfall data set and complementary cluster and composite analyses.The northeastern part of the basin, north of 5 °S and east of 60 °W, is significantly related with tropical SSTs: a rainier wet season is observed when the equatorial Pacific and the northern (southern) tropical Atlantic are anomalously cold (warm). A shorter and drier wet season is observed during El Niño events and negative rainfall anomalies are also significantly associated with a warm northern Atlantic in the austral autumn and a cold southern Atlantic in the spring. The northeastern Amazon rainfall anomalies are closely related with El Niño-southern oscillation during the whole year, whereas the relationships with the tropical Atlantic SST anomalies are mainly observed during the autumn. A time-space continuity is observed between El Niño-related rainfall anomalies in the northeastern Amazon, those in the northern Amazon and south-eastern Amazon, and those in northern South America and in the Nordeste of Brazil.A reinforcement of certain rainfall anomalies is observed when specific oceanic events combine. For instance, when El Niño and cold SSTs in the southern Atlantic are associated, very strong negative anomalies are observed in the whole northern Amazon basin. Nonetheless, the comparison of the cluster and the composite analyses results shows that the rainfall anomalies in the northeastern Amazon are not always associated with tropical SST anomalies.In the southern and western Amazon, significant tropical SST-related rainfall anomalies are very few and spatially variable. The precipitation origins differ from those of the northeastern Amazon: land temperature variability, extratropical perturbations and moisture advection are important rainfall factors, as well as SSTs. This could partially explain why: (a) the above-mentioned signals weaken or disappear, with the exception of the relative dryness that is observed at the peak of an El Niño event and during the dry season when northern Atlantic SSTs are warmer than usual; (b) rainfall anomalies tend to resemble those of southeastern South America, noticeably at the beginning and the end of El Niño and La Niña events; (c) some strong excesses of rain are not associated with any SST anomalies and merit further investigation.

Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses.

PubMed

Chadsuthi, Sudarat; Modchang, Charin; Lenbury, Yongwimon; Iamsirithaworn, Sopon; Triampo, Wannapong

2012-07-01

To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

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.

WetNet: Using SSM/I data interactively for global distribution of tropical rainfall and precipitable water

NASA Technical Reports Server (NTRS)

Zipser, Edward J.; Mcguirk, James P.

1993-01-01

The research objectives were the following: (1) to use SSM/I to categorize, measure, and parameterize effects of rainfall systems around the globe, especially mesoscale convective systems; (2) to use SSM/I to monitor key components of the global hydrologic cycle, including tropical rainfall and precipitable water, and links to increasing sea surface temperatures; and (3) to assist in the development of efficient methods of exchange of massive satellite data bases and of analysis techniques, especially their use at a university. Numerous tasks have been initiated. First and foremost has been the integration and startup of the WetNet computer system into the TAMU computer network. Scientific activity was infeasible before completion of this activity. Final hardware delivery was not completed until October 1991, after which followed a period of identification and solution of several hardware and software and software problems. Accomplishments representing approximately four months work with the WetNEt system are presented.

A self-consistency approach to improve microwave rainfall rate estimation from space

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Mack, Robert A.; Hakkarinen, Ida M.

1989-01-01

A multichannel statistical approach is used to retrieve rainfall rates from the brightness temperature T(B) observed by passive microwave radiometers flown on a high-altitude NASA aircraft. T(B) statistics are based upon data generated by a cloud radiative model. This model simulates variabilities in the underlying geophysical parameters of interest, and computes their associated T(B) in each of the available channels. By further imposing the requirement that the observed T(B) agree with the T(B) values corresponding to the retrieved parameters through the cloud radiative transfer model, the results can be made to agree quite well with coincident radar-derived rainfall rates. Some information regarding the cloud vertical structure is also obtained by such an added requirement. The applicability of this technique to satellite retrievals is also investigated. Data which might be observed by satellite-borne radiometers, including the effects of nonuniformly filled footprints, are simulated by the cloud radiative model for this purpose.

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania

PubMed Central

Tumbo, S. D.; Kihupi, N. I.; Rwehumbiza, Filbert B.

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly. PMID:28536708

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

PubMed

Msongaleli, Barnabas M; Tumbo, S D; Kihupi, N I; Rwehumbiza, Filbert B

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly.

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.

Vulnerability of riparian obligate species to the interactive effect of fire, climate and hydrological change

Treesearch

Megan M. Friggens; Rachel Loehman; Lisa Holsinger; Deborah Finch

2014-01-01

Climate change is expected to have multiple direct and indirect impacts on ecosystems in the interior western U.S. (Christensen et al., 2007; IPCC 2013). Global climate predictions for the Southwest include higher temperatures, more variable rainfall, and more drought periods, which will likely exacerbate the ongoing issues relating to wildfire and water allocation in...

Analysis of dengue fever risk using geostatistics model in bone regency

NASA Astrophysics Data System (ADS)

Amran, Stang, Mallongi, Anwar

2017-03-01

This research aim is to analysis of dengue fever risk based on Geostatistics model in Bone Regency. Risk levels of dengue fever are denoted by parameter of Binomial distribution. Effect of temperature, rainfalls, elevation, and larvae abundance are investigated through Geostatistics model. Bayesian hierarchical method is used in estimation process. Using dengue fever data in eleven locations this research shows that temperature and rainfall have significant effect of dengue fever risk in Bone regency.

Biocrusts modulate warming and rainfall exclusion effects on soil respiration in a semi-arid grassland

PubMed Central

Escolar, Cristina; Maestre, Fernando T.; Rey, Ana

2015-01-01

Soil surface communities composed of cyanobacteria, algae, mosses, liverworts, fungi, bacteria and lichens (biocrusts) largely affect soil respiration in dryland ecosystems. Climate change is expected to have large effects on biocrusts and associated ecosystem processes. However, few studies so far have experimentally assessed how expected changes in temperature and rainfall will affect soil respiration in biocrust-dominated ecosystems. We evaluated the impacts of biocrust development, increased air temperature and decreased precipitation on soil respiration dynamics during dry (2009) and wet (2010) years, and investigated the relative importance of soil temperature and moisture as environmental drivers of soil respiration, in a semiarid grassland from central Spain. Soil respiration rates were significantly lower in the dry than during the wet year, regardless of biocrust cover. Warming increased soil respiration rates, but this response was only significant in biocrust-dominated areas (> 50% biocrust cover). Warming also increased the temperature sensitivity (Q10 values) of soil respiration in biocrust-dominated areas, particularly during the wet year. The combination of warming and rainfall exclusion had similar effects in low biocrust cover areas. Our results highlight the importance of biocrusts as a modulator of soil respiration responses to both warming and rainfall exclusion, and indicate that they must be explicitly considered when evaluating soil respiration responses to climate change in drylands. PMID:25914428

Review of Malaria Epidemics in Ethiopia using Enhanced Climate Services (ENACTS)

NASA Astrophysics Data System (ADS)

Muhammad, A.

2015-12-01

Malaria is a disease directly linked to temperature and rainfall. In Ethiopia, the influence of climate variables on malaria transmission and the subsequent role of ENSO in the rise of malaria incidence are becoming more recognized. Numerous publications attest to the extreme sensitivity of malaria to climate in Ethiopia. The majority of large-scale epidemics in the past were associated with climatic factors such as temperature and rainfall. However, there is limited information on climate variability and ENSO at the district level to aid in public health decision-making. Since 2008, the National Meteorogy Agency (NMA) and the International Research Institute for Climate and Society (IRI) have been collaborating on improving climate services in Ethiopia. This collaboration spurred the implementation of the Enhancing National Climate Services (ENACTS) initiative and the creation of the IRI Data Library (DL) NMA Ethiopia Maproom. ENACTS provides reliable and readily accessible climate data at high resolutions and the Maproom uses ENACTS to build a collection of maps and other figures that monitor climate and societal conditions at present and in the recent past (1981-2010). A recent analysis exploring the relationship of rainfall and temperature ENACTS products to malaria epidemics in proceeding rainy seasons within 12 woredas found above normal temperature anomalies to be more readily associated with epidemics when compared to above normal rainfall anomalies, regardless of the ENSO phase (Figure 1-2).

Projected changes in rainfall and temperature over homogeneous regions of India

NASA Astrophysics Data System (ADS)

Patwardhan, Savita; Kulkarni, Ashwini; Rao, K. Koteswara

2018-01-01

The impact of climate change on the characteristics of seasonal maximum and minimum temperature and seasonal summer monsoon rainfall is assessed over five homogeneous regions of India using a high-resolution regional climate model. Providing REgional Climate for Climate Studies (PRECIS) is developed at Hadley Centre for Climate Prediction and Research, UK. The model simulations are carried out over South Asian domain for the continuous period of 1961-2098 at 50-km horizontal resolution. Here, three simulations from a 17-member perturbed physics ensemble (PPE) produced using HadCM3 under the Quantifying Model Uncertainties in Model Predictions (QUMP) project of Hadley Centre, Met. Office, UK, have been used as lateral boundary conditions (LBCs) for the 138-year simulations of the regional climate model under Intergovernmental Panel on Climate Change (IPCC) A1B scenario. The projections indicate the increase in the summer monsoon (June through September) rainfall over all the homogeneous regions (15 to 19%) except peninsular India (around 5%). There may be marginal change in the frequency of medium and heavy rainfall events (>20 mm) towards the end of the present century. The analysis over five homogeneous regions indicates that the mean maximum surface air temperatures for the pre-monsoon season (March-April-May) as well as the mean minimum surface air temperature for winter season (January-February) may be warmer by around 4 °C towards the end of the twenty-first century.

Breeding period in the mangrove crab Goniopsis cruentata (Decapoda: Grapsidae) in Northeast Brazil.

PubMed

de Lira, José Jonathas Pereira Rodrigues; Calado, Tereza Cristina dos Santos; de Araújo, Marina de Sá Leitão Câmara

2013-03-01

The brachyuran crabs are iteroparous species which present a high diversification of reproduction patterns, which may have evolved as a species-specific response to environmental conditions. Tropical species commonly present a year-round reproduction due to stable environment conditions. Goniopsis cruentata is a crab species widely distributed along the Western Atlantic, inhabiting practically every microhabitat in the mangrove ecosystem. The aim of the present study is to determine the breeding period of the crab Goniopsis cruentata in Northeastern Brazil and also to evaluate the influence of water salinity, rainfall and air and water temperature on it. A total of 71 ovigerous females, captured from August-2007 to July-2008, were used to assess the breeding period of this species. It was analyzed by the monthly proportion of ovigerous females. A correlation was applied to verify the influence of the abiotic factors on the breeding period. The present population bred seasonal-continuously with peaks in the dry period, which was not associated with monthly variations of salinity, rainfall and air and water temperatures. Therefore, according to statistical analyses, our hypothesis was refuted. However, breeding was intensified in the dry period, when salinity and temperatures were higher and rainfall was lower. We conclude that, even though breeding is not related to monthly variation of environmental factors, it occurs in periods of higher salinity and temperatures and lower rainfall.

Analysis of the causes of spawning of large-scale, severe malarial epidemics and their rapid total extinction in western Provence, historically a highly endemic region of France (1745–1850)

PubMed Central

2014-01-01

Background The two main puzzles of this study are the onset and then sudden stopping of severe epidemics in western Provence (a highly malaria-endemic region of Mediterranean France) without any deliberate counter-measures and in the absence of significant population flux. Methods Malaria epidemics during the period from 1745 to 1850 were analysed against temperature and rainfall records and several other potentially relevant factors. Results Statistical analyses indicated that relatively high temperatures in early spring and in September/October, rainfall during the previous winter (principally December) and even from November to September and epidemics during the previous year could have played a decisive role in the emergence of these epidemics. Moreover, the epidemics were most likely not driven by other parameters (e.g., social, cultural, agricultural and geographical). Until 1776, very severe malarial epidemics affected large areas, whereas after this date, they were rarer and generally milder for local people and were due to canal digging activities. In the latter period, decreased rainfall in December, and more extreme and variable temperatures were observed. It is known that rainfall anomalies and temperature fluctuations may be detrimental to vector and parasite development. Conclusion This study showed the particular characteristics of malaria in historical Provence. Contrary to the situation in most other Mediterranean areas, Plasmodium falciparum was most likely not involved (during the years with epidemics, the mean temperature during the months of July and August, among other factors, did not play a role) and the population had no protective mutation. The main parasite species was Plasmodium vivax, which was responsible for very severe diseases, but contrary to in northern Europe, it is likely that transmission occurred only during the period where outdoor sporogony was possible, and P. vivax sporogony was always feasible, even during colder summers. Possible key elements in the understanding of the course of malaria epidemics include changes in the virulence of P. vivax strains, the refractoriness of anophelines and/or the degree or efficiency of acquired immunity. This study could open new lines of investigation into the comprehension of the conditions of disappearance/emergence of severe malaria epidemics in highly endemic areas. PMID:24581282

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.

Using CHIRPS Rainfall Dataset to detect rainfall trends in West Africa

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Climate changes effects on vegetation in Mediterranean areas

NASA Astrophysics Data System (ADS)

Viola, F.; Pumo, D.; Noto, L. V.

2009-04-01

The Mediterranean ecosystems evolved under climatic conditions characterized by precipitations markedly out of phase with the growing period for the vegetation there established. In such environments, deep and shallow rooted species cohabit and compete each other. The formers, being characterized by deeper root, are able to utilize the water stored during the dormant season, while the conditions of shallow rooted plant are closely related to the intermittence of the precipitations. A numerical model has been here used in order to carry out an analysis of the potential climate changes influence on the vegetation state in a typical Mediterranean environment, such as Sicilian one. The most important consequences arising from climate changes in the Mediterranean area, due to the CO2 increase, are the temperatures raise and the contemporaneous rainfall reduction. Probably, this reduction could be accompanied by an increase in events intensity and, at the same time, by a decrease in the number of annual events. There are very few information about possible changes in the distribution of the rainfall events over the year. However, according to the analysis of the recorded trend, it is possible to predict that the rainfall reduction will be mainly concentrated during the autumnal and wintry months. The goal of this work is a quantitative evaluation of the effects due to the climatic forcing changes, on vegetation water stress. In particular, great attention is paid to the effects that rainfall decrease may have on vegetation, by itself or coupled with the temperature increase. A detailed investigation on the influence of the variations in rainfall seasonality, frequency and intensity is carried out. In this work two vegetation covers, with shallow and deep rooting depth (grass and tree) laying on three different soil types (loamy sand, sandy loam and clay) are considered. Simulations on Mediterranean ecosystems have lead to recognize the role of the rainfall amount, frequency and temporal distribution. Rainfall decrease increases the vegetation water stress much more than temperature increase do. Intense and rare rainfall events, as they are expected to be, could attenuate the effects of rainfall reduction because of the less interception correlated to them. The future rainfall distribution over the year is also crucial for vegetation water stress. If the current ratio between the growing season and the dormant season rainfall will be kept, trees and grasses will suffer a common increase of water stress, which seems more severe for trees than for grasses. Otherwise, if the rainfall reduction will be concentrated during the wintry periods, as emerges from literature, grasses will have some advantages over the trees species. In this conditions grasses will keep the water stress similar to the nowadays value, while trees will suffer for the lack of the winter recharge increasing their water stress.

Observed climate variability over Chad using multiple observational and reanalysis datasets

NASA Astrophysics Data System (ADS)

Maharana, Pyarimohan; Abdel-Lathif, Ahmat Younous; Pattnayak, Kanhu Charan

2018-03-01

Chad is the largest of Africa's landlocked countries and one of the least studied region of the African continent. The major portion of Chad lies in the Sahel region, which is known for its rapid climate change. In this study, multiple observational datasets are analyzed from 1950 to 2014, in order to examine the trend of precipitation and temperature along with their variability over Chad to understand possible impacts of climate change over this region. Trend analysis of the climatic fields has been carried out using Mann-Kendall test. The precipitation over Chad is mostly contributed during summer by West African Monsoon, with maximum northward limit of 18° N. The Atlantic Ocean as well as the Mediterranean Sea are the major source of moisture for the summer rainfall over Chad. Based on the rainfall time series, the entire study period has been divided in to wet (1950 to 1965), dry (1966 to 1990) and recovery period (1991 to 2014). The rainfall has decreased drastically for almost 3 decades during the dry period resulted into various drought years. The temperature increases at a rate of 0.15 °C/decade during the entire period of analysis. The seasonal rainfall as well as temperature plays a major role in the change of land use/cover. The decrease of monsoon rainfall during the dry period reduces the C4 cover drastically; this reduction of C4 grass cover leads to increase of C3 grass cover. The slow revival of rainfall is still not good enough for the increase of shrub cover but it favors the gradual reduction of bare land over Chad.

Widespread climate change in the Himalayas and associated changes in local ecosystems.

PubMed

Shrestha, Uttam Babu; Gautam, Shiva; Bawa, Kamaljit S

2012-01-01

Climate change in the Himalayas, a biodiversity hotspot, home of many sacred landscapes, and the source of eight largest rivers of Asia, is likely to impact the well-being of ~20% of humanity. However, despite the extraordinary environmental, cultural, and socio-economic importance of the Himalayas, and despite their rapidly increasing ecological degradation, not much is known about actual changes in the two most critical climatic variables: temperature and rainfall. Nor do we know how changes in these parameters might impact the ecosystems including vegetation phenology. By analyzing temperature and rainfall data, and NDVI (Normalized Difference Vegetation Index) values from remotely sensed imagery, we report significant changes in temperature, rainfall, and vegetation phenology across the Himalayas between 1982 and 2006. The average annual mean temperature during the 25 year period has increased by 1.5 °C with an average increase of 0.06 °C yr(-1). The average annual precipitation has increased by 163 mm or 6.52 mmyr(-1). Since changes in temperature and precipitation are immediately manifested as changes in phenology of local ecosystems, we examined phenological changes in all major ecoregions. The average start of the growing season (SOS) seems to have advanced by 4.7 days or 0.19 days yr(-1) and the length of growing season (LOS) appears to have advanced by 4.7 days or 0.19 days yr(-1), but there has been no change in the end of the growing season (EOS). There is considerable spatial and seasonal variation in changes in climate and phenological parameters. This is the first time that large scale climatic and phenological changes at the landscape level have been documented for the Himalayas. The rate of warming in the Himalayas is greater than the global average, confirming that the Himalayas are among the regions most vulnerable to climate change.

Variations in household microclimate affect outdoor-biting behaviour of malaria vectors

PubMed Central

Ngowo, Halfan S.; Kaindoa, Emmanuel Wilson; Matthiopoulos, Jason; Ferguson, Heather M.; Okumu, Fredros O.

2017-01-01

Background: Mosquito behaviours including the degree to which they bite inside houses or outside is a crucial determinant of human exposure to malaria. Whilst seasonality in mosquito vector abundance is well documented, much less is known about the impact of climate on mosquito behaviour. We investigated how variations in household microclimate affect outdoor-biting by malaria vectors, Anopheles arabiensis and Anopheles funestus. Methods: Mosquitoes were sampled indoors and outdoors weekly using human landing catches at eight households in four villages in south-eastern Tanzania, resulting in 616 trap-nights over 12 months. Daily temperature, relative humidity and rainfall were recorded. Generalized additive mixed models (GAMMs) were used to test associations between mosquito abundance and the microclimatic conditions. Generalized linear mixed models (GLMMs) were used to investigate the influence of microclimatic conditions on the tendency of vectors to bite outdoors (proportion of outdoor biting). Results:  An. arabiensis abundance peaked during high rainfall months (February-May), whilst An. funestus density remained stable into the dry season (May-August) . Across the range of observed household temperatures, a rise of 1 ºC marginally increased nightly An. arabiensis abundance (~11%), but more prominently increased An. funestus abundance (~66%). The abundance of An. arabiensis and An. funestus showed strong positive associations with time-lagged rainfall (2-3 and 3-4 weeks before sampling). The degree of outdoor biting in An. arabiensis was significantly associated with the relative temperature difference between indoor and outdoor environments, with exophily increasing as temperature inside houses became relatively warmer. The exophily of An. funestus did not vary with temperature differences.   Conclusions: This study demonstrates that malaria vector An. arabiensis shifts the location of its biting from indoors to outdoors in association with relative differences in microclimatic conditions. These environmental impacts could give rise to seasonal variation in mosquito biting behaviour and degree of protection provided by indoor-based vector control strategies. PMID:29552642

Widespread Climate Change in the Himalayas and Associated Changes in Local Ecosystems

PubMed Central

Shrestha, Uttam Babu; Gautam, Shiva; Bawa, Kamaljit S.

2012-01-01

Background Climate change in the Himalayas, a biodiversity hotspot, home of many sacred landscapes, and the source of eight largest rivers of Asia, is likely to impact the well-being of ∼20% of humanity. However, despite the extraordinary environmental, cultural, and socio-economic importance of the Himalayas, and despite their rapidly increasing ecological degradation, not much is known about actual changes in the two most critical climatic variables: temperature and rainfall. Nor do we know how changes in these parameters might impact the ecosystems including vegetation phenology. Methodology/Principal Findings By analyzing temperature and rainfall data, and NDVI (Normalized Difference Vegetation Index) values from remotely sensed imagery, we report significant changes in temperature, rainfall, and vegetation phenology across the Himalayas between 1982 and 2006. The average annual mean temperature during the 25 year period has increased by 1.5°C with an average increase of 0.06°C yr−1. The average annual precipitation has increased by 163 mm or 6.52 mmyr−1. Since changes in temperature and precipitation are immediately manifested as changes in phenology of local ecosystems, we examined phenological changes in all major ecoregions. The average start of the growing season (SOS) seems to have advanced by 4.7 days or 0.19 days yr−1 and the length of growing season (LOS) appears to have advanced by 4.7 days or 0.19 days yr−1, but there has been no change in the end of the growing season (EOS). There is considerable spatial and seasonal variation in changes in climate and phenological parameters. Conclusions/Significance This is the first time that large scale climatic and phenological changes at the landscape level have been documented for the Himalayas. The rate of warming in the Himalayas is greater than the global average, confirming that the Himalayas are among the regions most vulnerable to climate change. PMID:22615804

Intrinsic Coupled Ocean-Atmosphere Modes of the Asian Summer Monsoon: A Re-assessment of Monsoon-ENSO Relationships

NASA Technical Reports Server (NTRS)

Lau, K.-M.; Wu, H. T.

2000-01-01

Using global rainfall and sea surface temperature (SST) data for the past two decades (1979-1998), we have investigated the intrinsic modes of Asian summer monsoon (ASM) and ENSO co-variability. Three recurring ASM rainfall-SST coupled modes were identified. The first is a basin scale mode that features SST and rainfall variability over the entire tropics (including the ASM region), identifiable with those occurring during El Nino or La Nina. This mode is further characterized by a pronounced biennial variation in ASM rainfall and SST associated with fluctuations of the anomalous Walker circulation that occur during El Nino/La Nina transitions. The second mode comprises mixed regional and basin-scale rainfall and SST signals, with pronounced intraseasonal and interannual variabilities. This mode features a SST pattern associated with a developing La Nina, with a pronounced low level anticyclone in the subtropics of the western Pacific off the coast of East Asia. The third mode depicts an east-west rainfall and SST dipole across the southern equatorial Indian Ocean, most likely stemming from coupled ocean-atmosphere processes within the ASM region. This mode also possesses a decadal time scale and a linear trend, which are not associated with El Nino/La Nina variability. Possible causes of year-to-year rainfall variability over the ASM and sub-regions have been evaluated from a reconstruction of the observed rainfall from singular eigenvectors of the coupled modes. It is found that while basin-scale SST can account for portions of ASM rainfall variability during ENSO events (up to 60% in 1998), regional processes can accounts up to 20-25% of the rainfall variability in typical non-ENSO years. Stronger monsoon-ENSO relationship tends to occur in the boreal summer immediately preceding a pronounced La Nina, i.e., 1998, 1988 and 1983. Based on these results, we discuss the possible impacts of the ASM on ENSO variability via the west Pacific anticyclone and articulate a hypothesis that anomalous wind forcings derived from the anticyclone may be instrumental in inducing a strong biennial modulation to natural ENSO cycles.

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.

Drought stress suppresses phytoalexin production against Fusarium verticilliodes

USDA-ARS?s Scientific Manuscript database

Global climate change involves rising temperatures and potentially decreased rainfall or changes in rainfall patterns, which could dramatically decrease the yield of food crops. Drought alone can impair plant growth and development, but in nature plants are continuously exposed to both abiotic and b...

An Environmental Data Set for Vector-Borne Disease Modeling and Epidemiology

PubMed Central

Chabot-Couture, Guillaume; Nigmatulina, Karima; Eckhoff, Philip

2014-01-01

Understanding the environmental conditions of disease transmission is important in the study of vector-borne diseases. Low- and middle-income countries bear a significant portion of the disease burden; but data about weather conditions in those countries can be sparse and difficult to reconstruct. Here, we describe methods to assemble high-resolution gridded time series data sets of air temperature, relative humidity, land temperature, and rainfall for such areas; and we test these methods on the island of Madagascar. Air temperature and relative humidity were constructed using statistical interpolation of weather station measurements; the resulting median 95th percentile absolute errors were 2.75°C and 16.6%. Missing pixels from the MODIS11 remote sensing land temperature product were estimated using Fourier decomposition and time-series analysis; thus providing an alternative to the 8-day and 30-day aggregated products. The RFE 2.0 remote sensing rainfall estimator was characterized by comparing it with multiple interpolated rainfall products, and we observed significant differences in temporal and spatial heterogeneity relevant to vector-borne disease modeling. PMID:24755954

A climate trend analysis of Ethiopia

USGS Publications Warehouse

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

2012-01-01

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

How East Asian westerly jet's meridional position affects the summer rainfall in Yangtze-Huaihe River Valley?

NASA Astrophysics Data System (ADS)

Wang, Shixin; Zuo, Hongchao; Zhao, Shuman; Zhang, Jiankai; Lu, Sha

2017-03-01

Existing studies show that the change in the meridional position of East Asian westerly jet (EAWJ) is associated with rainfall anomalies in Yangtze-Huaihe River Valley (YHRV) in summer. However, the dynamic mechanism has not been resolved yet. The present study reveals underlying mechanisms for this impact for early summer and midsummer, separately. Mechanism1: associated with EAWJ's anomalously southward displacement, the 500-hPa westerly wind over YHRV is strengthened through midtropospheric horizontal circulation anomalies; the westerly anomalies are related to the formation of warm advection anomalies over YHRV, which cause increased rainfall through adiabatic ascent motion and convective activities; the major difference in these processes between early summer and midsummer is the midtropospheric circulation anomaly pattern. Mechanism 2: associated with EAWJ's anomalously southward displacement, the large day-to-day variability of midtropospheric temperature advection in midlatitudes is displaced southward by the jet's trapping transient eddies; this change enhances the day-to-day variability of temperature advection over YHRV, which in turn causes the increased rainfall in most part of YHRV through "lower-bound effect" (rainfall amount can not become negative); there is not much difference in these processes between early summer and midsummer.

Impact of Climatic Variability on Hydropower Reservoirs in the Paraiba Basin, Southeast of Brazil

NASA Astrophysics Data System (ADS)

Barros, A.; simoes, s

2002-05-01

During 2000/2001, a severe drought greatly reduced the volume of water available to Brazilian hydropower plants and lead to a national water rationing plan. To undestand the potential for climatic change in hydrological regimes and its impact on hydropower we chose the Paraiba Basin located in Southeast Brazil. Three important regional multi-purpose reservoirs are operating in this basin. Moreover, the Paraiba River is of great economic and environmental importance and also constitutes a major corridor connecting the two cities of Sao Paulo and Rio de Janeiro. We analyzed monthly and daily records for rainfall, streamflow and temperature using regression and variance analysis. Rainfall records do not show any significant trend since the 1930s/1940s. By contrast, analysis of seasonal patterns show that in the last twenty years rainfall has increased during autumn and winter (dry season) and decreased during spring and summer (rainy season). Comparison between rainfall and streaflow, from small catchment without man-made influences, shows a more pronounced deficit in streamflow when compared with rainfall. The shifts in seasonal rainfall could indicate a tendency towards a more uniform rainfall pattern and could serve to reduce the streamflow. However, the largest upward trends in temperature were found in the driest months (JJA). The increase in rainfall would not be sufficient to overcome increased of evaporation expect to the same period. Instead, such increase in evaporation could create an over more pronounced streamflow deficit. Climatic variability could be reducing water availability in these reservoirs especially in the driest months. To reduce the uncertainties in hydrological predictions, planners need to incorporate climatic variability, at the catchment scale, in order to accomodate the new conditions resulting from these changes.

Tropical Indian Ocean Variability Driving Southeast Australian Droughts

NASA Astrophysics Data System (ADS)

Ummenhofer, C. C.; England, M. H.; McIntosh, P. C.; Meyers, G. A.; Pook, M. J.; Risbey, J. S.; Sen Gupta, A.; Taschetto, A. S.

2009-04-01

Variability in the tropical Indian Ocean has widespread effects on rainfall in surrounding countries, including East Africa, India and Indonesia. The leading mode of tropical Indian Ocean variability, the Indian Ocean Dipole (IOD), is a coupled ocean-atmosphere mode characterized by sea surface temperature (SST) anomalies of opposite sign in the east and west of the basin with an associated large-scale atmospheric re-organisation. Earlier work has often focused on the positive phase of the IOD. However, we show here that the negative IOD phase is an important driver of regional rainfall variability and multi-year droughts. For southeastern Australia, we show that it is actually a lack of the negative IOD phase, rather than the positive IOD phase or Pacific variability, that provides the most robust explanation for recent drought conditions. Since 1995, a large region of Australia has been gripped by the most severe drought in living memory, the so-called "Big Dry". The ramifications for affected regions are dire, with acute water shortages for rural and metropolitan areas, record agricultural losses, the drying-out of two of Australia's major river systems and far-reaching ecosystem damage. Yet the drought's origins have remained elusive. For Southeast Australia, we show that the "Big Dry" and other iconic 20th Century droughts, including the Federation Drought (1895-1902) and World War II drought (1937-1945), are driven by tropical Indian Ocean variability, not Pacific Ocean conditions as traditionally assumed. Specifically, a conspicuous absence of characteristic Indian Ocean temperature conditions that are conducive to enhanced tropical moisture transport has deprived southeastern Australia of its normal rainfall quota. In the case of the "Big Dry", its unprecedented intensity is also related to recent above-average temperatures. Implications of recent non-uniform warming trends in the Indian Ocean and how that might affect ocean characteristics and climate in Indian Ocean rim countries are also discussed.

Nonlinear responses of southern African rainfall to forcing from Atlantic SST in a high-resolution regional climate model

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, high resolution satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA) are used as a basis for undertaking model experiments using a state-of-the-art regional climate model. The MIRA dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the regional climate model's domain size are briefly presented, before a comparison of simulated daily rainfall from the model with the satellite-derived dataset. Secondly, simulations of current climate and rainfall extremes from the model are compared to the MIRA dataset at daily timescales. Finally, the results from the idealised SST experiments are presented, suggesting highly nonlinear associations between rainfall extremes remote SST anomalies.

Improving PERSIANN-CCS rain estimation using probabilistic approach and multi-sensors information

NASA Astrophysics Data System (ADS)

Karbalaee, N.; Hsu, K. L.; Sorooshian, S.; Kirstetter, P.; Hong, Y.

2016-12-01

This presentation discusses the recent implemented approaches to improve the rainfall estimation from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Cloud Classification System (PERSIANN-CCS). PERSIANN-CCS is an infrared (IR) based algorithm being integrated in the IMERG (Integrated Multi-Satellite Retrievals for the Global Precipitation Mission GPM) to create a precipitation product in 0.1x0.1degree resolution over the chosen domain 50N to 50S every 30 minutes. Although PERSIANN-CCS has a high spatial and temporal resolution, it overestimates or underestimates due to some limitations.PERSIANN-CCS can estimate rainfall based on the extracted information from IR channels at three different temperature threshold levels (220, 235, and 253k). This algorithm relies only on infrared data to estimate rainfall indirectly from this channel which cause missing the rainfall from warm clouds and false estimation for no precipitating cold clouds. In this research the effectiveness of using other channels of GOES satellites such as visible and water vapors has been investigated. By using multi-sensors the precipitation can be estimated based on the extracted information from multiple channels. Also, instead of using the exponential function for estimating rainfall from cloud top temperature, the probabilistic method has been used. Using probability distributions of precipitation rates instead of deterministic values has improved the rainfall estimation for different type of clouds.

A study of the dynamics of droughts in Northern Brazil: Observations, theory, and numerical experiments with a global atmospheric circulation model

NASA Technical Reports Server (NTRS)

Shukla, J.; Moura, A. D.

1980-01-01

The monthly mean sea surface temperature anomalies over tropical Altantic and rainfall anomalies over two selected stations for 25 years (1948-1972) were examined. It is found that the most severe drought events are associated with the simultaneous occurrence of warm sea surface temperature anomalies over north and cold sea surface temperature anomalies over south tropical Atlantic. Simultaneous occurrences of warm sea surface temperature anomaly at 15 deg N, 45 deg W and cold sea surface temperature anomaly at 15 deg S, 5 deg W were always associated with negative anomalies of rainfall, and vice versa. A simple primitive equation model is used to calculate the frictionally controlled and thermally driven circulation due to a prescribed heating function in a resting atmosphere.

An Investigation of the Influence of Urban Areas on Rainfall Using the TRMM Satellite and a Cloud-Mesoscale Model

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; OCStarr, David (Technical Monitor)

2002-01-01

A recent paper by Shepherd and Pierce (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of approx. 28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Simulation of the Indian Summer Monsoon Using Comprehensive Atmosphere-land Interactions, in the Absence of Two-way Air-sea Interactions

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Shin, D. W.; Cocke, Steven; Kang, Sung-Dae; Kim, Hae-Dong

2011-01-01

Community Land Model version 2 (CLM2) as a comprehensive land surface model and a simple land surface model (SLM) were coupled to an atmospheric climate model to investigate the role of land surface processes in the development and the persistence of the South Asian summer monsoon. Two-way air-sea interactions were not considered in order to identify the reproducibility of the monsoon evolution by the comprehensive land model, which includes more realistic vertical soil moisture structures, vegetation and 2-way atmosphere-land interactions at hourly intervals. In the monsoon development phase (May and June). comprehensive land-surface treatment improves the representation of atmospheric circulations and the resulting convergence/divergence through the improvements in differential heating patterns and surface energy fluxes. Coupling with CLM2 also improves the timing and spatial distribution of rainfall maxima, reducing the seasonal rainfall overestimation by approx.60 % (1.8 mm/d for SLM, 0.7 mm/dI for CLM2). As for the interannual variation of the simulated rainfall, correlation coefficients of the Indian seasonal rainfall with observation increased from 0.21 (SLM) to 0.45 (CLM2). However, in the mature monsoon phase (July to September), coupling with the CLM2 does not exhibit a clear improvement. In contrast to the development phase, latent heat flux is underestimated and sensible heat flux and surface temperature over India are markedly overestimated. In addition, the moisture fluxes do not correlate well with lower-level atmospheric convergence, yielding correlation coefficients and root mean square errors worse than those produced by coupling with the SLM. A more realistic representation of the surface temperature and energy fluxes is needed to achieve an improved simulation for the mature monsoon period.

Identification of climate-resilient integrated nutrient management practices for rice-rice cropping system--an empirical approach to uphold food security.

PubMed

Subash, N; Gangwar, B; Singh, Rajbir; Sikka, A K

2015-01-01

Yield datasets of long-term experiments on integrated nutrient management in rice-rice cropping systems were used to investigate the relationship of variability in rainfall, temperature, and integrated nutrient management (INM) practices in rice-rice cropping system in three different agroecological regions of India. Twelve treatments with different combinations of inorganic (chemical fertilizer) and organic (farmyard manure, green manure, and paddy straw) were compared with farmer's conventional practice. The intraseasonal variations in rice yields are largely driven by rainfall during kharif rice and by temperature during rabi rice. Half of the standard deviation from the average monthly as well as seasonal rainfall during kharif rice and 1 °C increase or decrease from the average maximum and minimum temperature during rabi rice has been taken as the classification of yield groups. The trends in the date of effective onset of monsoon indicate a 36-day delay during the 30-year period at Rajendranagar, which is statistically significant at 95 % confidence level. The mean annual maximum temperature shows an increasing trend in all the study sites. The length of monsoon also showed a shrinking trend in the rate of 40 days during the 30-year study period at Rajendranagar representing a semiarid region. At Bhubaneshwar, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through green manure resulted in an overall average higher increase of 5.1 % in system productivity under both excess and deficit rainfall years and also during the years having seasonal mean maximum temperature ≥35 °C. However, at Jorhat, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through straw resulted in an overall average higher increase of 7.4 % in system productivity, while at Rajendranagar, the application of 75 % NPK through chemical fertilizers and 25 % N through green manusre resulted in an overall average higher increase of 8.8 % in system productivity. This study highlights the adaptive capacity of different integrated nutrient management practices to rainfall and temperature variability under a rice-rice cropping system in humid, subhumid, and semiarid ecosystems.

Analysis of Rainfall Infiltration Law in Unsaturated Soil Slope

PubMed Central

Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

2014-01-01

In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering the characteristics of slope and rainfall, the key factors affecting rainfall infiltration of slope, including hydraulic properties, water storage capacity (θ s - θ r), soil types, rainfall intensities, and antecedent and subsequent infiltration rates on unsaturated soil slope, are discussed by using theory analysis and numerical simulation technology. Based on critical factors changing, this paper presents three calculation models of rainfall infiltrability for unsaturated slope, including (1) infiltration model considering rainfall intensity; (2) effective rainfall model considering antecedent rainfall; (3) infiltration model considering comprehensive factors. Based on the technology of system response, the relationship of rainfall and infiltration is described, and the prototype of regression model of rainfall infiltration is given, in order to determine the amount of rain penetration during a rain process. PMID:24672332

Analysis of rainfall infiltration law in unsaturated soil slope.

PubMed

Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

2014-01-01

In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering the characteristics of slope and rainfall, the key factors affecting rainfall infiltration of slope, including hydraulic properties, water storage capacity (θs - θr), soil types, rainfall intensities, and antecedent and subsequent infiltration rates on unsaturated soil slope, are discussed by using theory analysis and numerical simulation technology. Based on critical factors changing, this paper presents three calculation models of rainfall infiltrability for unsaturated slope, including (1) infiltration model considering rainfall intensity; (2) effective rainfall model considering antecedent rainfall; (3) infiltration model considering comprehensive factors. Based on the technology of system response, the relationship of rainfall and infiltration is described, and the prototype of regression model of rainfall infiltration is given, in order to determine the amount of rain penetration during a rain process.

Ecophysiological function of leaf 'windows' in Lithops species - 'Living Stones' that grow underground.

PubMed

Martin, C E; Brandmeyer, E A; Ross, R D

2013-01-01

Leaf temperatures were lower when light entry at the leaf tip window was prevented through covering the window with reflective tape, relative to leaf temperatures of plants with leaf tip windows covered with transparent tape. This was true when leaf temperatures were measured with an infrared thermometer, but not with a fine-wire thermocouple. Leaf tip windows of Lithops growing in high-rainfall regions of southern Africa were larger than the windows of plants (numerous individuals of 17 species) growing in areas with less rainfall and, thus, more annual insolation. The results of this study indicate that leaf tip windows of desert plants with an underground growth habit can allow entry of supra-optimal levels of radiant energy, thus most likely inhibiting photosynthetic activity. Consequently, the size of the leaf tip windows correlates inversely with habitat solar irradiance, minimising the probability of photoinhibition, while maximising the absorption of irradiance in cloudy, high-rainfall regions. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.

Non-linear intensification of Sahel rainfall as a possible dynamic response to future warming

NASA Astrophysics Data System (ADS)

Schewe, Jacob; Levermann, Anders

2017-07-01

Projections of the response of Sahel rainfall to future global warming diverge significantly. Meanwhile, paleoclimatic records suggest that Sahel rainfall is capable of abrupt transitions in response to gradual forcing. Here we present climate modeling evidence for the possibility of an abrupt intensification of Sahel rainfall under future climate change. Analyzing 30 coupled global climate model simulations, we identify seven models where central Sahel rainfall increases by 40 to 300 % over the 21st century, owing to a northward expansion of the West African monsoon domain. Rainfall in these models is non-linearly related to sea surface temperature (SST) in the tropical Atlantic and Mediterranean moisture source regions, intensifying abruptly beyond a certain SST warming level. We argue that this behavior is consistent with a self-amplifying dynamic-thermodynamical feedback, implying that the gradual increase in oceanic moisture availability under warming could trigger a sudden intensification of monsoon rainfall far inland of today's core monsoon region.

Determination of mean rainfall from the Special Sensor Microwave/Imager (SSM/I) using a mixed lognormal distribution

NASA Technical Reports Server (NTRS)

Berg, Wesley; Chase, Robert

1992-01-01

Global estimates of monthly, seasonal, and annual oceanic rainfall are computed for a period of one year using data from the Special Sensor Microwave/Imager (SSM/I). Instantaneous rainfall estimates are derived from brightness temperature values obtained from the satellite data using the Hughes D-matrix algorithm. The instantaneous rainfall estimates are stored in 1 deg square bins over the global oceans for each month. A mixed probability distribution combining a lognormal distribution describing the positive rainfall values and a spike at zero describing the observations indicating no rainfall is used to compute mean values. The resulting data for the period of interest are fitted to a lognormal distribution by using a maximum-likelihood. Mean values are computed for the mixed distribution and qualitative comparisons with published historical results as well as quantitative comparisons with corresponding in situ raingage data are performed.

Relative contribution of biotic and abiotic factors to the population density of the cassava green mite, Mononychellus tanajoa (Acari: Tetranychidae).

PubMed

Rêgo, Adriano S; Teodoro, Adenir V; Maciel, Anilde G S; Sarmento, Renato A

2013-08-01

The cassava green mite, Mononychellus tanajoa, is a key pest of cassava, Manihot esculenta Crantz (Euphorbiaceae), and it may be kept in check by naturally occurring predatory mites of the family Phytoseiidae. In addition to predatory mites, abiotic factors may also contribute to regulate pest mite populations in the field. Here, we evaluated the population densities of both M. tanajoa and the generalist predatory mite Euseius ho DeLeon (Acari: Phytoseiidae) over the cultivation cycle (11 months) of cassava in four study sites located around the city of Miranda do Norte, Maranhão, Brazil. The abiotic variables rainfall, temperature and relative humidity were also recorded throughout the cultivation cycle of cassava. We determined the relative importance of biotic (density of E. ho) and abiotic (rainfall, temperature and relative humidity) factors to the density of M. tanajoa. The density of M. tanajoa increased whereas the density of E. ho remained constant throughout time. A hierarchical partitioning analysis revealed that most of the variance for the density of M. tanajoa was explained by rainfall and relative humidity followed by E. ho density and temperature. We conclude that abiotic factors, especially rainfall, were the main mechanisms driving M. tanajoa densities.

Applications of high resolution rainfall radar data to quantify water temperature dynamics in urban catchments

NASA Astrophysics Data System (ADS)

Croghan, Danny; Van Loon, Anne; Bradley, Chris; Sadler, Jon; Hannnah, David

2017-04-01

Studies relating rainfall events to river water quality are frequently hindered by the lack of high resolution rainfall data. Local studies are particularly vulnerable due to the spatial variability of precipitation, whilst studies in urban environments require precipitation data at high spatial and temporal resolutions. The use of point-source data makes identifying causal effects of storms on water quality problematic and can lead to erroneous interpretations. High spatial and temporal resolution rainfall radar data offers great potential to address these issues. Here we use rainfall radar data with a 1km spatial resolution and 5 minute temporal resolution sourced from the UK Met Office Nimrod system to study the effects of storm events on water temperature (WTemp) in Birmingham, UK. 28 WTemp loggers were placed over 3 catchments on a rural-urban land use gradient to identify trends in WTemp during extreme events within urban environments. Using GIS, the catchment associated with each logger was estimated, and 5 min. rainfall totals and intensities were produced for each sub-catchment. Comparisons of rainfall radar data to meteorological stations in the same grid cell revealed the high accuracy of rainfall radar data in our catchments (<5% difference for studied months). The rainfall radar data revealed substantial differences in rainfall quantity between the three adjacent catchments. The most urban catchment generally received more rainfall, with this effect greatest in the highest intensity storms, suggesting the possibility of urban heat island effects on precipitation dynamics within the catchment. Rainfall radar data provided more accurate sub-catchment rainfall totals allowing better modelled estimates of storm flow, whilst spatial fluctuations in both discharge and WTemp can be simply related to precipitation intensity. Storm flow inputs for each sub-catchment were estimated and linked to changes in WTemp. WTemp showed substantial fluctuations (>1 °C) over short durations (<30 minutes) during storm events in urbanised sub-catchments, however WTemp recovery times were more prolonged. Use of the rainfall radar data allowed increased accuracy in estimates of storm flow timings and rainfall quantities at each sub-catchment, from which the impact of storm flow on WTemp could be quantified. We are currently using the radar data to derive thresholds for rainfall amount and intensity at which these storm deviations occur for each logger, from which the relative effects of land use and other catchment characteristics in each sub-catchment can be assessed. Our use of the rainfall radar data calls into question the validity of using station based data for small scale studies, particularly in urban areas, with high variation apparent in rainfall intensity both spatially and temporally. Variation was particularly high within the heavily urbanised catchment. For water quality studies, high resolution rainfall radar can be implemented to increase the reliability of interpretations of the response of water quality variables to storm water inputs in urban catchments.

Development of microwave rainfall retrieval algorithm for climate applications

NASA Astrophysics Data System (ADS)

KIM, J. H.; Shin, D. B.

2014-12-01

With the accumulated satellite datasets for decades, it is possible that satellite-based data could contribute to sustained climate applications. Level-3 products from microwave sensors for climate applications can be obtained from several algorithms. For examples, the Microwave Emission brightness Temperature Histogram (METH) algorithm produces level-3 rainfalls directly, whereas the Goddard profiling (GPROF) algorithm first generates instantaneous rainfalls and then temporal and spatial averaging process leads to level-3 products. The rainfall algorithm developed in this study follows a similar approach to averaging instantaneous rainfalls. However, the algorithm is designed to produce instantaneous rainfalls at an optimal resolution showing reduced non-linearity in brightness temperature (TB)-rain rate(R) relations. It is found that the resolution tends to effectively utilize emission channels whose footprints are relatively larger than those of scattering channels. This algorithm is mainly composed of a-priori databases (DBs) and a Bayesian inversion module. The DB contains massive pairs of simulated microwave TBs and rain rates, obtained by WRF (version 3.4) and RTTOV (version 11.1) simulations. To improve the accuracy and efficiency of retrieval process, data mining technique is additionally considered. The entire DB is classified into eight types based on Köppen climate classification criteria using reanalysis data. Among these sub-DBs, only one sub-DB which presents the most similar physical characteristics is selected by considering the thermodynamics of input data. When the Bayesian inversion is applied to the selected DB, instantaneous rain rate with 6 hours interval is retrieved. The retrieved monthly mean rainfalls are statistically compared with CMAP and GPCP, respectively.

Rainfall Data Simulation

Treesearch

T.L. Rogerson

1980-01-01

A simple simulation model to predict rainfall for individual storms in central Arkansas is described. Output includes frequency distribution tables for days between storms and for storm size classes; a storm summary by day number (January 1 = 1 and December 31 = 365) and rainfall amount; and an annual storm summary that includes monthly values for rainfall and number...

Warm season heavy rainfall events over the Huaihe River Valley and their linkage with wintertime thermal condition of the tropical oceans

NASA Astrophysics Data System (ADS)

Li, Laifang; Li, Wenhong; Tang, Qiuhong; Zhang, Pengfei; Liu, Yimin

2016-01-01

Warm season heavy rainfall events over the Huaihe River Valley (HRV) of China are amongst the top causes of agriculture and economic loss in this region. Thus, there is a pressing need for accurate seasonal prediction of HRV heavy rainfall events. This study improves the seasonal prediction of HRV heavy rainfall by implementing a novel rainfall framework, which overcomes the limitation of traditional probability models and advances the statistical inference on HRV heavy rainfall events. The framework is built on a three-cluster Normal mixture model, whose distribution parameters are sampled using Bayesian inference and Markov Chain Monte Carlo algorithm. The three rainfall clusters reflect probability behaviors of light, moderate, and heavy rainfall, respectively. Our analysis indicates that heavy rainfall events make the largest contribution to the total amount of seasonal precipitation. Furthermore, the interannual variation of summer precipitation is attributable to the variation of heavy rainfall frequency over the HRV. The heavy rainfall frequency, in turn, is influenced by sea surface temperature anomalies (SSTAs) over the north Indian Ocean, equatorial western Pacific, and the tropical Atlantic. The tropical SSTAs modulate the HRV heavy rainfall events by influencing atmospheric circulation favorable for the onset and maintenance of heavy rainfall events. Occurring 5 months prior to the summer season, these tropical SSTAs provide potential sources of prediction skill for heavy rainfall events over the HRV. Using these preceding SSTA signals, we show that the support vector machine algorithm can predict HRV heavy rainfall satisfactorily. The improved prediction skill has important implication for the nation's disaster early warning system.

How is the River Water Quality Response to Climate Change Impacts?

NASA Astrophysics Data System (ADS)

Nguyen, T. T.; Willems, P.

2015-12-01

Water quality and its response to climate change have been become one of the most important issues of our society, which catches the attention of many scientists, environmental activists and policy makers. Climate change influences the river water quality directly and indirectly via rainfall and air temperature. For example, low flow decreases the volume of water for dilution and increases the residence time of the pollutants. By contrast, high flow leads to increases in the amount of pollutants and sediment loads from catchments to rivers. The changes in hydraulic characteristics, i.e. water depth and velocity, affect the transportation and biochemical transformation of pollutants in the river water body. The high air temperature leads to increasing water temperature, shorter growing periods of different crops and water demands from domestic households and industries, which eventually effects the level of river pollution. This study demonstrates the quantification of the variation of the water temperature and pollutant concentrations along the Molse Neet river in the North East of Belgium as a result of the changes in the catchment rainfall-runoff, air temperature and nutrient loads. Firstly, four climate change scenarios were generated based on a large ensemble of available global and regional climate models and statistical downscaling based on a quantile perturbation method. Secondly, the climatic changes to rainfall and temperature were transformed to changes in the evapotranspiration and runoff flow through the conceptual hydrological model PDM. Thirdly, the adjustment in nutrient loads from agriculture due to rainfall and growing periods of crops were calculated by means of the semi-empirical SENTWA model. Water temperature was estimated from air temperature by a stochastic model separating the temperature into long-term annual and short-term residual components. Next, hydrodynamic and water quality models of the river, implemented in InfoWorks RS, were simulated for both historical (2000-2010) and projected future periods (2050-2060). The advection movement and physico-biochemical processes were considered for simulation of the following water quality variables: water temperature, dissolved oxygen, biological oxygen demand, ammonium, nitrate, nitrite and organic nitrogen.

Midweek Intensification of Rain in the U.S.: Does Air Pollution Invigorate Storms?

NASA Technical Reports Server (NTRS)

Bell, T. L.; Rosenfeld, D.; Hahnenberger, M.

2005-01-01

The effect of pollution on rainfall has been observed to depend both on the type of pollution and the precipitating environment. The climatological consequences of pollution for rainfall are uncertain. In some urban areas, pollution varies with the day of the week because of weekly variations in human activity, in effect providing a repeated experiment on the effects of pollution. Weekly variations in temperature, pressure, cloud characteristics, hails and lightning are observed in many areas. Observing a weekly cycle in rainfall statistics has proven to be more difficult, although there is some evidence for it. Here we examine rainfall statistics from the Tropical Rainfall Measuring Mission (TRMM) satellite over the southern U.S. and adjacent waters, and find that there is a distinct, statistically significant weekly cycle in summertime rainfall over the southeast U.S., as well as weekly variations in rainfall over the nearby Atlantic and the Gulf of Mexico. Rainfall over land peaks in the middle of the week, suggesting that summer rainfall on large scales may increase as pollution levels rise. Both rain statistics over land and what appear to be compensating effects over adjacent seas support the suggestion that air pollution invigorates convection and outflow aloft.

Estimation and analysis of interannual variations in tropical oceanic rainfall using data from SSM/I

NASA Technical Reports Server (NTRS)

Berg, Wesley

1992-01-01

Rainfall over tropical ocean regions, particularly in the tropical Pacific, is estimated using Special Sensor Microwave/Imager (SSM/I) data. Instantaneous rainfall estimates are derived from brightness temperature values obtained from the satellite data using the Hughes D-Matrix algorithm. Comparisons with other satellite techniques are made to validate the SSM/I results for the tropical Pacific. The correlation coefficients are relatively high for the three data sets investigated, especially for the annual case.

Modeling the Effect of Summertime Heating on Urban Runoff Temperature

NASA Astrophysics Data System (ADS)

Thompson, A. M.; Gemechu, A. L.; Norman, J. M.; Roa-Espinosa, A.

2007-12-01

Urban impervious surfaces absorb and store thermal energy, particularly during warm summer months. During a rainfall/runoff event, thermal energy is transferred from the impervious surface to the runoff, causing it to become warmer. As this higher temperature runoff enters receiving waters, it can be harmful to coldwater habitat. A simple model has been developed for the net energy flux at the impervious surfaces of urban areas to account for the heat transferred to runoff. Runoff temperature is determined as a function of the physical characteristics of the impervious areas, the weather, and the heat transfer between the moving film of runoff and the heated impervious surfaces that commonly exist in urban areas. Runoff from pervious surfaces was predicted using the Green- Ampt Mein-Larson infiltration excess method. Theoretical results were compared to experimental results obtained from a plot-scale field study conducted at the University of Wisconsin's West Madison Agricultural Research Station. Surface temperatures and runoff temperatures from asphalt and sod plots were measured throughout 15 rainfall simulations under various climatic conditions during the summers of 2004 and 2005. Average asphalt runoff temperatures ranged from 23.2°C to 37.1°C. Predicted asphalt runoff temperatures were in close agreement with measured values for most of the simulations (average RMSE = 4.0°C). Average pervious runoff temperatures ranged from 19.7° to 29.9°C and were closely approximated by the rainfall temperature (RMSE = 2.8°C). Predicted combined asphalt and sod runoff temperatures using a flow-weighted average were in close agreement with observed values (average RMSE = 3.5°C).

A comparison of methods to estimate future sub-daily design rainfall

NASA Astrophysics Data System (ADS)

Li, J.; Johnson, F.; Evans, J.; Sharma, A.

2017-12-01

Warmer temperatures are expected to increase extreme short-duration rainfall due to the increased moisture-holding capacity of the atmosphere. While attention has been paid to the impacts of climate change on future design rainfalls at daily or longer time scales, the potential changes in short duration design rainfalls have been often overlooked due to the limited availability of sub-daily projections and observations. This study uses a high-resolution regional climate model (RCM) to predict the changes in sub-daily design rainfalls for the Greater Sydney region in Australia. Sixteen methods for predicting changes to sub-daily future extremes are assessed based on different options for bias correction, disaggregation and frequency analysis. A Monte Carlo cross-validation procedure is employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It is found that bias correction significantly improves the accuracy of the design rainfall estimated for the current climate. For 1 h events, bias correcting the hourly annual maximum rainfall simulated by the RCM produces design rainfall closest to observations, whereas for multi-hour events, disaggregating the daily rainfall total is recommended. This suggests that the RCM fails to simulate the observed multi-duration rainfall persistence, which is a common issue for most climate models. Despite the significant differences in the estimated design rainfalls between different methods, all methods lead to an increase in design rainfalls across the majority of the study region.

Global meteorological influences on the record UK rainfall of winter 2013-14

NASA Astrophysics Data System (ADS)

Knight, Jeff R.; Maidens, Anna; Watson, Peter A. G.; Andrews, Martin; Belcher, Stephen; Brunet, Gilbert; Fereday, David; Folland, Chris K.; Scaife, Adam A.; Slingo, Julia

2017-07-01

The UK experienced record average rainfall in winter 2013-14, leading to widespread and prolonged flooding. The immediate cause of this exceptional rainfall was a very strong and persistent cyclonic atmospheric circulation over the North East Atlantic Ocean. This was related to a very strong North Atlantic jet stream which resulted in numerous damaging wind storms. These exceptional meteorological conditions have led to renewed questions about whether anthropogenic climate change is noticeably influencing extreme weather. The regional weather pattern responsible for the extreme UK winter coincided with highly anomalous conditions across the globe. We assess the contributions from various possible remote forcing regions using sets of ocean-atmosphere model relaxation experiments, where winds and temperatures are constrained to be similar to those observed in winter 2013-14 within specified atmospheric domains. We find that influences from the tropics were likely to have played a significant role in the development of the unusual extra-tropical circulation, including a role for the tropical Atlantic sector. Additionally, a stronger and more stable stratospheric polar vortex, likely associated with a strong westerly phase of the stratospheric Quasi-Biennial Oscillation (QBO), appears to have contributed to the extreme conditions. While intrinsic climatic variability clearly has the largest effect on the generation of extremes, results from an analysis which segregates circulation-related and residual rainfall variability suggest that emerging climate change signals made a secondary contribution to extreme rainfall in winter 2013-14.

[Impact of seasons, years El Nino/La Nina and rainfalls on stroke-related morbidity and mortality in Kinshasa].

PubMed

Kintoki Mbala, F; Longo-Mbenza, B; Mbungu Fuele, S; Zola, N; Motebang, D; Nakin, V; Lueme Lokotola, C; Simbarashe, N; Nge Okwe, A

2016-02-01

The significant impact of seasonality and climate change on stroke-related morbidity and mortality is well established, however, some findings on this issue are conflicting. The objective was to determine the impact of gender, age, season, year of admission, temperature, rainfall and El Nino phenomenon on ischemic and hemorrhagic strokes and fatal cases of stroke. The study was carried out at the teaching hospital of Kinshasa, DRC, between January 1998 and December 2004. Rainy and dry seasons, elevated temperatures, indices of rainfalls El Nino years 1998, 2002 and 2004, but La Nina years 1999-2000 and neutral/normal years 2001 and 2003 were defined. Among 470 incident strokes, 34.5% of victims (n=162) died. Traditional seasons (small dry season, small rainy season, great dry season, great rainy season) and temperatures did not significantly (P>0.005) impact on stroke incidence. However, there was a positive association between the decrease in rainfall, El Nino, and incident ischemic strokes, but a significant positive association between the increase in rainfall, La Nina, and incident hemorrhagic strokes. Using logistic regression analysis, age ≥ 60 years (OR: 1.7, 95% CI: 1.2-2.5; P=0.018) and El Nino years (OR: 2, 95% CI: 1.2-3.3; P=0.009) were identified as the independent predictors of fatal strokes. Early warning systems should be developed to predict the impact of seasons and climate variability on stroke morbidity and mortality. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Climate Variability and Yields of Major Staple Food Crops in Northern Ghana

NASA Astrophysics Data System (ADS)

Amikuzuno, J.

2012-12-01

Climate variability, the short-term fluctuations in average weather conditions, and agriculture affect each other. Climate variability affects the agroecological and growing conditions of crops and livestock, and is recently believed to be the greatest impediment to the realisation of the first Millennium Development Goal of reducing poverty and food insecurity in arid and semi-arid regions of developing countries. Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we provide some insight into the long run relationship between inter-annual variations in temperature and rainfall, and annual yields of the most important staple food crops in Northern Ghana. Applying pooled panel data of rainfall, temperature and yields of the selected crops from 1976 to 2010 to cointegration and Granger causality models, there is cogent evidence of cointegration between seasonal, total rainfall and crop yields; and causality from rainfall to crop yields in the Sudano-Guinea Savannah and Guinea Savannah zones of Northern Ghana. This suggests that inter-annual yields of the crops have been influenced by the total mounts of rainfall in the planting season. Temperature variability over the study period is however stationary, and is suspected to have minimal effect if any on crop yields. Overall, the results confirm the appropriateness of our attempt in modelling long-term relationships between the climate and crop yield variables.

Climate change impact assessment on food security in Indonesia

NASA Astrophysics Data System (ADS)

Ettema, Janneke; Aldrian, Edvin; de Bie, Kees; Jetten, Victor; Mannaerts, Chris

2013-04-01

As Indonesia is the world's fourth most populous country, food security is a persistent challenge. The potential impact of future climate change on the agricultural sector needs to be addressed in order to allow early implementation of mitigation strategies. The complex island topography and local sea-land-air interactions cannot adequately be represented in large scale General Climate Models (GCMs) nor visualized by TRMM. Downscaling is needed. Using meteorological observations and a simple statistical downscaling tool, local future projections are derived from state-of-the-art, large-scale GCM scenarios, provided by the CMIP5 project. To support the agriculture sector, providing information on especially rainfall and temperature variability is essential. Agricultural production forecast is influenced by several rain and temperature factors, such as rainy and dry season onset, offset and length, but also by daily and monthly minimum and maximum temperatures and its rainfall amount. A simple and advanced crop model will be used to address the sensitivity of different crops to temperature and rainfall variability, present-day and future. As case study area, Java Island is chosen as it is fourth largest island in Indonesia but contains more than half of the nation's population and dominates it politically and economically. The objective is to identify regions at agricultural risk due to changing patterns in precipitation and temperature.

Influences of the MJO on the space-time organization of tropical convection

NASA Astrophysics Data System (ADS)

Dias, Juliana; Sakaeda, Naoko; Kiladis, George N.; Kikuchi, Kazuyoshi

2017-08-01

The fact that the Madden-Julian Oscillation (MJO) is characterized by large-scale patterns of enhanced tropical rainfall has been widely recognized for decades. However, the precise nature of any two-way feedback between the MJO and the properties of smaller-scale organization that makes up its convective envelope is not well understood. Satellite estimates of brightness temperature are used here as a proxy for tropical rainfall, and a variety of diagnostics are applied to determine the degree to which tropical convection is affected either locally or globally by the MJO. To address the multiscale nature of tropical convective organization, the approach ranges from space-time spectral analysis to an object-tracking algorithm. In addition to the intensity and distribution of global tropical rainfall, the relationship between the MJO and other tropical processes such as convectively coupled equatorial waves, mesoscale convective systems, and the diurnal cycle of tropical convection is also analyzed. The main findings of this paper are that, aside from the well-known increase in rainfall activity across scales within the MJO convective envelope, the MJO does not favor any particular scale or type of organization, and there is no clear signature of the MJO in terms of the globally integrated distribution of brightness temperature or rainfall.

Correcting speleothem oxygen isotopic variations for growth-rate controlled kinetic fractionation effects

NASA Astrophysics Data System (ADS)

Stoll, Heather; Moreno, Ana; Cacho, Isabel; Mendez Vicence, Ana; Gonzalez Lemos, Saul; Pirla Casasayas, Gemma; Cheng, Hai; Wang, Xianfeng; Edwards, R. Lawrence

2015-04-01

The oxygen isotopic signature may be the most widely used climate indicator in stalagmites, but recent experimental and theoretical studies indicate the potential for kinetic fractionation effects which may be significant, especially in situations where the primary signal from rainfall isotopic composition and cave temperature is limited to a few permil. Here we use a natural set of stalagmites to illustrate the magnitude of such effects and the potential for deconvolving kinetic signals from the primary temperature and rainfall signals. We compare isotopic records from 6 coeval stalagmites covering the interval 140 to 70 ka, from two proximal caves in NW Spain which experienced the same primary variations in temperature and rainfall d18O, but exhibit a large range in growth rates and temporal trends in growth rate. Stalagmites growing at faster rates near 50 microns/year have oxygen isotopic ratios more than 1 permil more negative than coeval stalagmites with very slow (5 micron/year) growth rates. Because growth rate variations also occur over time within any given stalagmite, the measured oxygen isotopic time series for a given stalagmite includes both climatic and kinetic components. Removal of the kinetic component of variation in each stalagmite, based on the dependence of the kinetic component on growth rate, is effective at distilling a common temporal evolution among the oxygen isotopic records of the multiple stalagmites. However, this approach is limited by the quality of the age model. For time periods characterized by very slow growth and long durations between dates, the presence of crypto-hiatus may result in average growth rates which underestimate the instantaneous speleothem deposition rates and which therefore underestimate the magnitude of kinetic effects. We compare the composite corrected oxygen isotopic record with other records of the timing of glacial inception in the North Atlantic realm.

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.

A multisensor analysis of Nimbus-5 data recorded on 22 January 1973. [measurement of rainfall rates for east coast of the United States

NASA Technical Reports Server (NTRS)

Allison, L. J.; Rodgers, E. B.; Wilheit, T. T.; Wexler, R.

1975-01-01

The Nimbus 5 meteorological satellite has a full complement of radiation sensors. Data from these sensors were analyzed and intercompared for orbits 569 and 570. The electrically-scanning microwave radiometer (19.35-GHz region) delineated rain areas over the ocean off the U.S. east coast, in good agreement with radar imagery, and permitted the estimation of rainfall rates in this region. Residual ground water, from abnormal rainfall in the lower Mississippi Valley, was indicated under clear sky conditions by soil brightness temperature values in the Nimbus 5 electrically scanning microwave radiometer and U.S. Air Force Data Acquisition and Processing Program infrared data. The temperature-humidity infrared radiometer (6.7 micron and 11 micron) showed the height and spatial configuration of frontal clouds along the east coast and outlined the confluence of a polar jet stream with a broad subtropical jet stream along the U.S. Gulf Coast. Temperature profiles from three vertical temperature sounders are found to be in good agreement with related radiosonde ascents along orbit 569 from the subtropics to the Arctic Circle.

An exploratory study on occurrence and impact of climate change on agriculture in Tamil Nadu, India

NASA Astrophysics Data System (ADS)

Varadan, R. Jayakumara; Kumar, Pramod; Jha, Girish Kumar; Pal, Suresh; Singh, Rashmi

2017-02-01

This study has been undertaken to examine the occurrence of climate change in Tamil Nadu, the southernmost state of India and its impact on rainfall pattern which is a primary constraint for agricultural production. Among the five sample stations examined across the state, the minimum temperature has increased significantly in Coimbatore while the same has decreased significantly in Vellore whereas both minimum and maximum temperatures have increased significantly in Madurai since 1969 with climate change occurring between late 1980s and early 1990s. As a result, the south-west monsoon has been disturbed with August rainfall increasing with more dispersion while September rainfall decreasing with less dispersion. Thus, September, the peak rainfall month of south-west monsoon before climate change, has become the monsoon receding month after climate change. Though there has been no change in the trend of the north-east monsoon, the quantity of October and November rainfall has considerably increased with increased dispersion after climate change. On the whole, south-west monsoon has decreased with decreased dispersion while north-east monsoon has increased with increased dispersion. Consequently, the season window for south-west monsoon crops has shortened while the north-east monsoon crops are left to fend against flood risk during their initial stages. Further, the incoherence in warming, climate change and rainfall impact seen across the state necessitates devising different indigenous and institutional adaptation strategies for different regions to overcome the adverse impacts of climate change on agriculture.

Climate-disease connections: Rift Valley Fever in Kenya

NASA Technical Reports Server (NTRS)

Anyamba, A.; Linthicum, K. J.; Tucker, C. J.

2001-01-01

All known Rift Valley fever(RVF) outbreaks in Kenya from 1950 to 1998 followed periods of abnormally high rainfall. On an interannual scale, periods of above normal rainfall in East Africa are associated with the warm phase of the El Nino/Southern Oscillation (ENSO) phenomenon. Anomalous rainfall floods mosquito-breeding habitats called dambos, which contain transovarially infected mosquito eggs. The eggs hatch Aedes mosquitoes that transmit the RVF virus preferentially to livestock and to humans as well. Analysis of historical data on RVF outbreaks and indicators of ENSO (including Pacific and Indian Ocean sea surface temperatures and the Southern Oscillation Index) indicates that more than three quarters of the RVF outbreaks have occurred during warm ENSO event periods. Mapping of ecological conditions using satellite normalized difference vegetation index (NDVI) data show that areas where outbreaks have occurred during the satellite recording period (1981-1998) show anomalous positive departures in vegetation greenness, an indicator of above-normal precipitation. This is particularly observed in arid areas of East Africa, which are predominantly impacted by this disease. These results indicate a close association between interannual climate variability and RVF outbreaks in Kenya.

Climate-disease connections: Rift Valley Fever in Kenya.

PubMed

Anyamba, A; Linthicum, K J; Tucker, C J

2001-01-01

All known Rift Valley fever(RVF) outbreaks in Kenya from 1950 to 1998 followed periods of abnormally high rainfall. On an interannual scale, periods of above normal rainfall in East Africa are associated with the warm phase of the El Niño/Southern Oscillation (ENSO) phenomenon. Anomalous rainfall floods mosquito-breeding habitats called dambos, which contain transovarially infected mosquito eggs. The eggs hatch Aedes mosquitoes that transmit the RVF virus preferentially to livestock and to humans as well. Analysis of historical data on RVF outbreaks and indicators of ENSO (including Pacific and Indian Ocean sea surface temperatures and the Southern Oscillation Index) indicates that more than three quarters of the RVF outbreaks have occurred during warm ENSO event periods. Mapping of ecological conditions using satellite normalized difference vegetation index (NDVI) data show that areas where outbreaks have occurred during the satellite recording period (1981-1998) show anomalous positive departures in vegetation greenness, an indicator of above-normal precipitation. This is particularly observed in arid areas of East Africa, which are predominantly impacted by this disease. These results indicate a close association between interannual climate variability and RVF outbreaks in Kenya.

Effect of Dam operation on monthly and annual trends of flow discharge in the Qom Rood Watershed, Iran

NASA Astrophysics Data System (ADS)

Yaghmaei, Hiva; Sadeghi, Seyed Hamidreza; Moradi, Hamidreza; Gholamalifard, Mehdi

2018-02-01

Trends in flow discharge, temperature and rainfall from the Qom Rood Watershed, Iran, for a period of 1979-2016 were analyzed at monthly and annual time scales. Trend analyses were conducted using the Mann-Kendall test, the double-mass curve of mean annual discharge versus rainfall, and rainfall-runoff relationship before and after the 15 Khordad Dam operation. Multiple regression of flow discharge against rainfall and temperature was used to determine the residual trend at four meteorological and hydrological stations located upstream and downstream of the Qom Rood Watershed. Results showed that the temperature at the upstream and downstream stations did not have any significant trend, but a significant decreasing trend (P < .05) in rainfall was detected only in May (z = -1.66) at the downstream stations. There was a significant positive trend (P < .05) in rainfall in February (z = 2.22) and July (z = 2.15) at the upstream stations, and in October (z = 2.3) and November (z = 1.8) at the downstream stations. However, there was a noticeable decrease in monthly and annual flow discharge, and residual trend at 99% significance level at the downstream stations. At the upstream stations, the flow discharges had significant (P < .05) declining trend in all months, but annual flow discharge did not change significantly. Analysis of double mass curve between runoff and rainfall at the downstream stations showed an inconsistency in the line slope concordant with the time of 15 Khordad Dam operation. Annual mean discharge at the upstream stations did not show a significant change before and after 15 Khordad Dam operation. However, annual flow magnitude decreased significantly by 87.5 and 81.7% in Shad Abad and KoohSefid, respectively. These results confirmed that natural driving forces did not affect flow discharge changes and the observed decreasing tendency in flow discharge at the downstream stations was due to 15 Khordad Dam, and at the upstream stations due to diversion/storage dams. These findings highlighted the role of human interference in changing the hydrologic regime in the study area based on which appropriate adaptive decisions can be made.

Skill of ENSEMBLES seasonal re-forecasts for malaria prediction in West Africa

NASA Astrophysics Data System (ADS)

Jones, A. E.; Morse, A. P.

2012-12-01

This study examines the performance of malaria-relevant climate variables from the ENSEMBLES seasonal ensemble re-forecasts for sub-Saharan West Africa, using a dynamic malaria model to transform temperature and rainfall forecasts into simulated malaria incidence and verifying these forecasts against simulations obtained by driving the malaria model with General Circulation Model-derived reanalysis. Two subregions of forecast skill are identified: the highlands of Cameroon, where low temperatures limit simulated malaria during the forecast period and interannual variability in simulated malaria is closely linked to variability in temperature, and northern Nigeria/southern Niger, where simulated malaria variability is strongly associated with rainfall variability during the peak rain months.

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.

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.

Precipitation Regime Shift Enhanced the Rain Pulse Effect on Soil Respiration in a Semi-Arid Steppe

PubMed Central

Yan, Liming; Chen, Shiping; Xia, Jianyang; Luo, Yiqi

2014-01-01

The effect of resource pulses, such as rainfall events, on soil respiration plays an important role in controlling grassland carbon balance, but how shifts in long-term precipitation regime regulate rain pulse effect on soil respiration is still unclear. We first quantified the influence of rainfall event on soil respiration based on a two-year (2006 and 2009) continuously measured soil respiration data set in a temperate steppe in northern China. In 2006 and 2009, soil carbon release induced by rainfall events contributed about 44.5% (83.3 g C m−2) and 39.6% (61.7 g C m−2) to the growing-season total soil respiration, respectively. The pulse effect of rainfall event on soil respiration can be accurately predicted by a water status index (WSI), which is the product of rainfall event size and the ratio between antecedent soil temperature to moisture at the depth of 10 cm (r 2 = 0.92, P<0.001) through the growing season. It indicates the pulse effect can be enhanced by not only larger individual rainfall event, but also higher soil temperature/moisture ratio which is usually associated with longer dry spells. We then analyzed a long-term (1953–2009) precipitation record in the experimental area. We found both the extreme heavy rainfall events (>40 mm per event) and the long dry-spells (>5 days) during the growing seasons increased from 1953–2009. It suggests the shift in precipitation regime has increased the contribution of rain pulse effect to growing-season total soil respiration in this region. These findings highlight the importance of incorporating precipitation regime shift and its impacts on the rain pulse effect into the future predictions of grassland carbon cycle under climate change. PMID:25093573

Precipitation regime shift enhanced the rain pulse effect on soil respiration in a semi-arid steppe.

PubMed

Yan, Liming; Chen, Shiping; Xia, Jianyang; Luo, Yiqi

2014-01-01

The effect of resource pulses, such as rainfall events, on soil respiration plays an important role in controlling grassland carbon balance, but how shifts in long-term precipitation regime regulate rain pulse effect on soil respiration is still unclear. We first quantified the influence of rainfall event on soil respiration based on a two-year (2006 and 2009) continuously measured soil respiration data set in a temperate steppe in northern China. In 2006 and 2009, soil carbon release induced by rainfall events contributed about 44.5% (83.3 g C m(-2)) and 39.6% (61.7 g C m(-2)) to the growing-season total soil respiration, respectively. The pulse effect of rainfall event on soil respiration can be accurately predicted by a water status index (WSI), which is the product of rainfall event size and the ratio between antecedent soil temperature to moisture at the depth of 10 cm (r2 = 0.92, P<0.001) through the growing season. It indicates the pulse effect can be enhanced by not only larger individual rainfall event, but also higher soil temperature/moisture ratio which is usually associated with longer dry spells. We then analyzed a long-term (1953-2009) precipitation record in the experimental area. We found both the extreme heavy rainfall events (>40 mm per event) and the long dry-spells (>5 days) during the growing seasons increased from 1953-2009. It suggests the shift in precipitation regime has increased the contribution of rain pulse effect to growing-season total soil respiration in this region. These findings highlight the importance of incorporating precipitation regime shift and its impacts on the rain pulse effect into the future predictions of grassland carbon cycle under climate change.

Climate change projections for Tamil Nadu, India: deriving high-resolution climate data by a downscaling approach using PRECIS

NASA Astrophysics Data System (ADS)

Bal, Prasanta Kumar; Ramachandran, A.; Geetha, R.; Bhaskaran, B.; Thirumurugan, P.; Indumathi, J.; Jayanthi, N.

2016-02-01

In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments.

Observations of cloud and rainfall enhancement over irrigated agriculture in an arid environment

NASA Astrophysics Data System (ADS)

Garcia-Carreras, Luis; Marsham, John H.; Spracklen, Dominick V.

2017-04-01

The impact of irrigated agriculture on clouds and rainfall remains uncertain, particularly in less studied arid regions. Irrigated crops account for 20% of global cropland area, and non-renewable groundwater accounts for 20% of global irrigation water demand. Quantifying the feedbacks between agriculture and the atmosphere are therefore not only necessary to better understand the climate impacts of land-use change, but are also crucial for predicting long-term water use in water-scarce regions. Here we use high spatial-resolution satellite data to show the impact of irrigated crops in the arid environment of northern Saudi Arabia on cloud cover and rainfall patterns. Land surface temperatures over the crops are 5-10 K lower than their surroundings, linked to evapotranspiration rates of up to 20 mm/ month. Daytime cloud cover is up to 30% higher over the cropland compared to its immediate surroundings, and this enhancement is highly correlated with the seasonal variability in leaf area index. The cloud enhancement is associated with a much more rapid cloud cloud development during the morning. Afternoon rainfall is 85% higher over, and just downwind, of the cropland during the growing season, although rainfall remains very low in absolute terms. The feedback sign we find is the opposite to what has been observed in tropical and semiarid regions, where temperature gradients promote convergence and clouds on the warmer side of land-surface type discontinuities. This suggests that different processes are responsible for the land-atmosphere feedback in very dry environments, where lack of moisture may be a stronger constraint. Increased cloud and rainfall, and associated increases in diffuse radiation and reductions in temperature, can affect vegetation growth thus producing an internal feedback. These effects will therefore need to be taken into account to properly assess the impact of climate change on crop productivity and water use, as well as how global land-use change affects climate.

The stable isotope amount effect: New insights from NEXRAD echo tops, Luquillo Mountains, Puerto Rico

USGS Publications Warehouse

Scholl, Martha A.; Shanley, James B.; Zegarra, Jan Paul; Coplen, Tyler B.

2009-01-01

The stable isotope amount effect has often been invoked to explain patterns of isotopic composition of rainfall in the tropics. This paper describes a new approach, correlating the isotopic composition of precipitation with cloud height and atmospheric temperature using NEXRAD radar echo tops, which are a measure of the maximum altitude of rainfall within the clouds. The seasonal differences in echo top altitudes and their corresponding temperatures are correlated with the isotopic composition of rainfall. These results offer another factor to consider in interpretation of the seasonal variation in isotopic composition of tropical rainfall, which has previously been linked to amount or rainout effects and not to temperature effects. Rain and cloud water isotope collectors in the Luquillo Mountains in northeastern Puerto Rico were sampled monthly for three years and precipitation was analyzed for δ18O and δ2H. Precipitation enriched in 18O and 2H occurred during the winter dry season (approximately December–May) and was associated with a weather pattern of trade wind showers and frontal systems. During the summer rainy season (approximately June–November), precipitation was depleted in 18O and 2H and originated in low pressure systems and convection associated with waves embedded in the prevailing easterly airflow. Rain substantially depleted in 18O and 2H compared to the aforementioned weather patterns occurred during large low pressure systems. Weather analysis showed that 29% of rain input to the Luquillo Mountains was trade wind orographic rainfall, and 30% of rainfall could be attributed to easterly waves and low pressure systems. Isotopic signatures associated with these major climate patterns can be used to determine their influence on streamflow and groundwater recharge and to monitor possible effects of climate change on regional water resources.

Throughfall under a teak plantation in Thailand: a multifactorial analysis on the effects of canopy phenology and meteorological conditions

NASA Astrophysics Data System (ADS)

Tanaka, N.; Levia, D. F., Jr.; Igarashi, Y.; Nanko, K.; Yoshifuji, N.; Tanaka, K.; Chatchai, T.; Suzuki, M.; Kumagai, T.

2014-12-01

Teak (Tectona grandis Linn. f.) plantations cover vast areas throughout Southeast Asia and are of great economic importance. This study has sought to increase our understanding of throughfall inputs under teak by analyzing the abiotic and biotic factors governing throughfall amounts and throughfall ratios in relation to three canopy phenophases (leafless, leafing, and leafed). There is no rain during the brief leaf senescence phenophase. Daily data was available for both throughfall volumes and depths as well as leaf area index. Detailed meteorological data were available in situ every ten minutes. Leveraging this high-resolution field data, we employed boosted regression trees (BRT) analysis to identify the primary controls on throughfall amount and ratio during each of the three canopy phenophases. Whereas throughfall amounts were always dominated by the magnitude of rainfall (as expected), throughfall ratios were governed by a suite of predictor variables during each phenophase. The BRT analysis demonstrated that throughfall ratio in the leafless phase was most influenced (in descending order of importance) by air temperature, rainfall amount, maximum wind speed, and rainfall intensity. Throughfall ratio in the leafed phenophase was dominated by rainfall amount which exerted 54.0% of the relative influence. The leafing phenophase was an intermediate case where rainfall amount, air temperature, and vapor pressure deficit were most important. Our results highlight the fact that throughfall ratios are differentially influenced by a suite of meteorological variables during leafless, leafing, and leafed phenophases. Abiotic variables (rainfall amount, air temperature, vapor pressure deficit, and maximum wind speed) trumped leaf area index and stand density in their effect on throughfall ratio. The leafing phenophase, while transitional in nature and short in duration, has a detectable and unique impact on water inputs to teak plantations. Further work is clearly needed to better gauge the importance of the leaf emergence period to the stemflow hydrology and forest biogeochemistry of teak plantations.

The association between temperature, rainfall and humidity with common climate-sensitive infectious diseases in Bangladesh.

PubMed

Chowdhury, Fazle Rabbi; Ibrahim, Quazi Shihab Uddin; Bari, Md Shafiqul; Alam, M M Jahangir; Dunachie, Susanna J; Rodriguez-Morales, Alfonso J; Patwary, Md Ismail

2018-01-01

Bangladesh is one of the world's most vulnerable countries for climate change. This observational study examined the association of temperature, humidity and rainfall with six common climate-sensitive infectious diseases in adults (malaria, diarrheal disease, enteric fever, encephalitis, pneumonia and bacterial meningitis) in northeastern Bangladesh. Subjects admitted to the adult medicine ward of a tertiary referral hospital in Sylhet, Bangladesh from 2008 to 2012 with a diagnosis of one of the six chosen climate-sensitive infectious diseases were enrolled in the study. Climate-related data were collected from the Bangladesh Meteorological Institute. Disease incidence was then analyzed against mean temperature, humidity and average rainfall for the Sylhet region. Statistical significance was determined using Mann-Whitney test, Chi-square test and ANOVA testing. 5033 patients were enrolled (58% male, 42% female, ratio 1.3:1). All six diseases showed highly significant (p = 0.01) rises in incidence between the study years 2008 (540 cases) and 2012 (1330 cases), compared with no significant rise in overall all-cause hospital admissions in the same period (p = 0.19). The highest number of malaria (135), diarrhea (266) and pneumonia (371) cases occurred during the rainy season. On the other hand, the maximum number of enteric fever (408), encephalitis (183) and meningitis (151) cases occurred during autumn, which follows the rainy season. A positive (P = 0.01) correlation was observed between increased temperature and the incidence of malaria, enteric fever and diarrhea, and a negative correlation with encephalitis, meningitis and pneumonia. Higher humidity correlated (P = 0.01) with a higher number of cases of malaria and diarrhea, but inversely correlated with meningitis and encephalitis. Higher incidences of encephalitis and meningitis occurred while there was low rainfall. Incidences of diarrhea, malaria and enteric fever, increased with rainfall, and then gradually decreased. The findings support a relationship between weather patterns and disease incidence, and provide essential baseline data for future large prospective studies.

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets

NASA Astrophysics Data System (ADS)

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Spinoni, Jonathan; Alewell, Christine; Borrelli, Pasquale

2017-05-01

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha-1 h-1 yr-1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets.

PubMed

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Spinoni, Jonathan; Alewell, Christine; Borrelli, Pasquale

2017-05-01

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha -1  h -1  yr -1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Western Pacific emergent constraint lowers projected increase in Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Li, Gen; Xie, Shang-Ping; He, Chao; Chen, Zesheng

2017-10-01

The agrarian-based socioeconomic livelihood of densely populated South Asian countries is vulnerable to modest changes in Indian summer monsoon (ISM) rainfall. How the ISM rainfall will evolve is a question of broad scientific and socioeconomic importance. In response to increased greenhouse gas (GHG) forcing, climate models commonly project an increase in ISM rainfall. This wetter ISM projection, however, does not consider large model errors in both the mean state and ocean warming pattern. Here we identify a relationship between biases in simulated present climate and future ISM projections in a multi-model ensemble: models with excessive present-day precipitation over the tropical western Pacific tend to project a larger increase in ISM rainfall under GHG forcing because of too strong a negative cloud-radiation feedback on sea surface temperature. The excessive negative feedback suppresses the local ocean surface warming, strengthening ISM rainfall projections via atmospheric circulation. We calibrate the ISM rainfall projections using this `present-future relationship’ and observed western Pacific precipitation. The correction reduces by about 50% of the projected rainfall increase over the broad ISM region. Our study identifies an improved simulation of western Pacific convection as a priority for reliable ISM projections.

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).

Longer growing seasons shift grassland vegetation towards more-productive species

NASA Astrophysics Data System (ADS)

Fridley, Jason D.; Lynn, Josh S.; Grime, J. P.; Askew, A. P.

2016-09-01

Despite advances in plant functional ecology that provide a framework for predicting the responses of vegetation to environmental change, links between plant functional strategies and elevated temperatures are poorly understood. Here, we analyse the response of a species-rich grassland in northern England to two decades of temperature and rainfall manipulations in the context of the functional attributes of 21 coexisting species that represent a large array of resource-use strategies. Three principal traits, including body size (canopy height), tissue investment (leaf construction cost), and seed size, varied independently across species and reflect tradeoffs associated with competitiveness, stress tolerance, and colonization ability. Unlike past studies, our results reveal a strong association between functional traits and temperature regime; species favoured by extended growing seasons have taller canopies and faster assimilation rates, which has come at the expense of those species of high tissue investment. This trait-warming association was three times higher in deep soils, suggesting species shifts have been strongly mediated by competition. In contrast, vegetation shifts from rainfall manipulations have been associated only with tissue investment. Functional shifts towards faster growing species in response to warming may be responsible for a marginal increase in productivity in a system that was assumed to be nutrient-limited.

Development and testing of transfer functions for generating quantitative climatic estimates from Australian pollen data

NASA Astrophysics Data System (ADS)

Cook, Ellyn J.; van der Kaars, Sander

2006-10-01

We review attempts to derive quantitative climatic estimates from Australian pollen data, including the climatic envelope, climatic indicator and modern analogue approaches, and outline the need to pursue alternatives for use as input to, or validation of, simulations by models of past, present and future climate patterns. To this end, we have constructed and tested modern pollen-climate transfer functions for mainland southeastern Australia and Tasmania using the existing southeastern Australian pollen database and for northern Australia using a new pollen database we are developing. After testing for statistical significance, 11 parameters were selected for mainland southeastern Australia, seven for Tasmania and six for northern Australia. The functions are based on weighted-averaging partial least squares regression and their predictive ability evaluated against modern observational climate data using leave-one-out cross-validation. Functions for summer, annual and winter rainfall and temperatures are most robust for southeastern Australia, while in Tasmania functions for minimum temperature of the coldest period, mean winter and mean annual temperature are the most reliable. In northern Australia, annual and summer rainfall and annual and summer moisture indexes are the strongest. The validation of all functions means all can be applied to Quaternary pollen records from these three areas with confidence. Copyright

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were sigmficantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-china peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and gradient, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation apd associated moisture transport and convection.

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were significantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-China peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and merit, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation and associated moisture transport and convection.

The Eastern Pacific ITCZ during the Boreal Spring

NASA Technical Reports Server (NTRS)

Gu, Guojun; Adler, Robert F.; Sobel, Adam H.

2004-01-01

The 6-year (1998-2003) rainfall products from the Tropical Rainfall Measuring Mission (TRMM) are used to quantify the Intertropical Convergence Zone (ITCZ) in the eastern Pacific (defined by longitudinal averages over 90 degrees W-130 degrees W) during boreal spring (March-April). The double ITCZ phenomenon, represented by the occurrence of two maxima with respect to latitude in monthly mean rainfall, is observed in most but not all of the years studied. The relative spatial locations of maxima in sea surface temperature (SST), rainfall, and surface pressure are examined. Interannual and weekly variability are characterized in SST, rainfall, surface convergence, total column water vapor, and cloud water. There appears to be a competition for rainfall between the two hemispheres during this season. When one of the two rainfall maxima is particularly strong, the other tends to be weak, with the total rainfall integrated over the two varying less than does the difference between the rainfall integrated over each separately. There is some evidence for a similar competition between the SST maxima in the two hemispheres, but this is more ambiguous, and there is evidence that some variations in the relative strengths of the two rainfall maxima may be independent of SST. Using a 25-year (1979-2003) monthly rainfall dataset from the Global Precipitation Climatology Project (GPCP), four distinct ITCZ types during March-April are defined, based on the relative strengths of rainfall peaks north and south of, and right over the equator. Composite meridional profiles and spatial distributions of rainfall and SST are documented for each type. Consistent with previous studies, an equatorial cold tongue is essential to the existence of the double ITCZs. However, too strong a cold tongue may dampen either the southern or northern rainfall maximum, depending on the magnitude of SST north of the equator.

Sensitivity of extreme precipitation to temperature: the variability of scaling factors from a regional to local perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Kirchengast, G.

2018-06-01

Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.

The Use of Radar to Improve Rainfall Estimation over the Tennessee and San Joaquin River Valleys

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Gatlin, Patrick N.; Felix, Mariana; Carey, Lawrence D.

2010-01-01

This slide presentation provides an overview of the collaborative radar rainfall project between the Tennessee Valley Authority (TVA), the Von Braun Center for Science & Innovation (VCSI), NASA MSFC and UAHuntsville. Two systems were used in this project, Advanced Radar for Meteorological & Operational Research (ARMOR) Rainfall Estimation Processing System (AREPS), a demonstration project of real-time radar rainfall using a research radar and NEXRAD Rainfall Estimation Processing System (NREPS). The objectives, methodology, some results and validation, operational experience and lessons learned are reviewed. The presentation. Another project that is using radar to improve rainfall estimations is in California, specifically the San Joaquin River Valley. This is part of a overall project to develop a integrated tool to assist water management within the San Joaquin River Valley. This involves integrating several components: (1) Radar precipitation estimates, (2) Distributed hydro model, (3) Snowfall measurements and Surface temperature / moisture measurements. NREPS was selected to provide precipitation component.

Improvement of downscaled rainfall and temperature across generations over the Western Himalayan region of India

NASA Astrophysics Data System (ADS)

Das, L.; Dutta, M.; Akhter, J.; Meher, J. K.

2016-12-01

It is a challenging task to create station level (local scale) climate change information over the mountainous locations of Western Himalayan Region (WHR) in India because of limited data availability and poor data quality. In the present study, missing values of station data were handled through Multiple Imputation Chained Equation (MICE) technique. Finally 22 numbers of rain gauge and 16 number of temperature station data having continuous record during 1901­2005 and 1969­2009 period respectively were considered as reference stations for developing downscaled rainfall and temperature time series from five commonly available GCMs in the IPCC's different generation assessment reports namely 2nd, 3rd, 4th and 5th hereafter known as SAR, TAR, AR4 and AR5 respectively. Downscaled models were developed using the combined data from the ERA-interim reanalysis and GCMs historical runs (in spite of forcing were not identical in different generation) as predictor and station level rainfall and temperature as predictands. Station level downscaled rainfall and temperature time series were constructed for five GCMs available in each generation. Regional averaged downscaled time series comprising of all stations was prepared for each model and generation and the downscaled results were compared with observed time series. Finally an Overall Model Improvement Index (OMII) was developed using the downscaling results, which was used to investigate the model improvement across generations as well as the improvement of downscaling results obtained from the Empirical Statistical Downscaling (ESD) methods. In case of temperature, models have improved from SAR to AR5 over the study area. In all most all the GCMs TAR is showing worst performance over the WHR by considering the different statistical indices used in this study. In case of precipitation, no model has shown gradual improvement from SAR to AR5 both for interpolated and downscaled values.

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

Temporal variation of Mexiconema cichlasomae (Nematoda: Daniconematidae) in the Mayan cichlid fish Cichlasoma urophthalmus and its intermediate host Argulus yucatanus from a tropical coastal lagoon.

PubMed

May-Tec, A L; Pech, D; Aguirre-Macedo, M L; Lewis, J W; Vidal-Martínez, V M

2013-03-01

The aim of the present investigation was to determine whether temporal variation in environmental factors such as rainfall or temperature influence long-term fluctuations in the prevalence and mean abundance of the nematode Mexiconema cichlasomae in the cichlid fish Cichlasoma uropthalmus and its crustacean intermediate host, Argulus yucatanus. The study was undertaken in a tropical coastal lagoon in the Yucatan Peninsula (south-eastern Mexico) over an 8-year period. Variations in temperature, rainfall and monthly infection levels for both hosts were analysed using time series and cross-correlations to detect possible recurrent patterns. Infections of M. cichlasomae in A. yucatanus showed annual peaks, while in C. urophthalmus peaks were bi-annual. The latter appear to be related to the accumulation of several generations of this nematode in C. urophthalmus. Rainfall and temperature appear to be key environmental factors in influencing temporal variation in the infection of M. cichlasomae over periods longer than a year together with the accumulation of larval stages throughout time.

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.

A dipole pattern of summertime rainfall across the Indian subcontinent and the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Jiang, X.; Ting, M.

2017-12-01

The Tibetan Plateau (TP) has long been regarded as a key driver for the formation and variations of the Indian summer monsoon (ISM). Recent studies, however, indicated that the ISM also exerts a considerable impact on rainfall variations in the TP, suggesting that the ISM and the TP should be considered as an interactive system. From this perspective, we investigate the co-variability of the July-August mean rainfall across the Indian subcontinent (IS) and the TP. We found that the interannual variation of IS and TP rainfall exhibits a dipole pattern in which rainfall in the central and northern IS tends to be out of phase with that in the southeastern TP. This dipole pattern is associated with significant anomalies in rainfall, atmospheric circulation, and water vapor transport over the Asian continent and nearby oceans. Rainfall anomalies and the associated latent heating in the central and northern IS tend to induce changes in regional circulation -that suppress rainfall in the southeastern TP and vice versa. Furthermore, the sea surface temperature anomalies in the tropical southeastern Indian Ocean can trigger the dipole rainfall pattern by suppressing convection over the central IS and the northern Bay of Bengal, which further induces anomalous anticyclonic circulation to the south of TP that favors more rainfall in the southeastern TP by transporting more water vapor to the region. The dipole pattern is also linked to the Silk-Road wave train due to its link to rainfall over the northwestern IS.

Disentangling the contribution of precipitation and temperature to Chilean megadrought (2010-2015)

NASA Astrophysics Data System (ADS)

Zambrano-Bigiarini, M.; Garreaud, R. D.

2016-12-01

Central Chile (30-40°S) has experienced a rainfall decline since the early 80s. Such long-term drying has been accentuated by an intense rainfall deficit from 2010 to date. Moreover, the maximum air temperatures have risen since the late 70s, with warm anomalies between 0.5° and 1°C relative to the past 30 years, resulting in the use of the term megadrougth for the 2010-2015 period.In this work, we used two drought indices to analyze the contribution of precipitation and temperature on recent droughts, and to improve our understanding about the onset, duration and magnitude thereof. First, the traditional Standardized Precipitation Index (SPI) is used to describe the effect of lack of precipitation on drought conditions. Second, the Standardized Precipitation-Evapotranspiration Index (SPEI), based on a simple climatic water balance (precipitation minus reference evapotranspiration), is used to assess the effect of temperature -throughout changes in evaporation- on drought severity at different time scales. Data from 781 raingauges and 281 temperature stations were analyzed for the period 1981-2015, but only 21 stations with 98% of days with information (or more) were used to compute SPI and SPEI at 12-month scale (SPI-12 and SPEI-12, respectively), as representative of the long-term effects of meteorological droughts on hydrology. Results reveal that in almost all the analyzed stations both SPI and SPEI are close or below zero since August 2010 onwards, with stations located northern to 32°S recovering in July 2015 due to extreme rainfall events. We note that the SPEI-12 was able to identify drought events even after some above-normal rainfall periods, which was in agreement with reported socioeconomic impacts on agriculture and water supply. Comparison of moving averages of SPI-12 and SPEI-12 during the megadrought against their historical values (1966-2010), for selected stations, reveals two different conditions. In the arid north, the SPI-12 was low but not extraordinary, whilst the SPEI-12 was well beyond the historical distribution, indicating that the increase in temperature have worsened the rainfall deficit by increasing evaporation. In the humid south, we found little difference between SPI-12 and SPEI-12 during the megadrought, but both values were extraordinary in their historical context.

Response of Tropical Forests to Intense Climate Variability and Rainfall Anomaly over the Last Decade

NASA Astrophysics Data System (ADS)

Saatchi, S.; Asefi, S.

2012-04-01

During the last decade, strong precipitation anomalies resulted from increased sea surface temperature in the tropical Atlantic, have caused extensive drying trends in rainforests of western Amazonia, exerting water stress, tree mortality, biomass loss, and large-scale fire disturbance. In contrast, there have been no reports on large-scale disturbance in rainforests of west and central Africa, though being exposed to similar intensity of climate variability. Using data from Tropical Rainfall Mapping Mission (TRMM) (1999-2010), and time series of rainfall observations from meteorological stations (1971-2000), we show that both Amazonian and African rainforest experienced strong precipitation anomalies from 2005-2010. We monitored the response of forest to the climate variability by analyzing the canopy water content observed by SeaWinds Ku-band Scatterometer (QSCAT) (1999-2009) and found that more than 70 million ha of forests in western Amazonia experienced a strong water deficit during the dry season of 2005 and a closely corresponding decline in canopy backscatter that persisted until the next major drought in 2010. This decline in backscatter has been attributed to loss of canopy water content and large-scale tree mortality corroborated by ground and airborne observations. However, no strong impacts was observed on tropical forests of Africa, suggesting that the African rainforest may have more resilience to droughts. We tested this hypothesis by examining the seasonal rainfall patterns, maximum water deficit, and the surface temperature variations. Results show that there is a complex pattern of low annual rainfall, moderate seasonality, and lower surface temperature in Central Africa compared to Amazonia, indicating potentially a lower evapotranspiration circumventing strong water deficits

Response of Tropical Forests to Intense Climate Variability and Rainfall Anomaly of Last Decade

NASA Astrophysics Data System (ADS)

Saatchi, S. S.; Asefi Najafabady, S.

2011-12-01

During the last decade, strong precipitation anomalies resulted from increased sea surface temperature in the tropical Atlantic, have caused extensive drying trends in rainforests of western Amazonia, exerting water stress, tree mortality, biomass loss, and large-scale fire disturbance. In contrast, there have been no reports on large-scale disturbance in rainforests of west and central Africa, though being exposed to similar intensity of climate variability. Using data from Tropical Rainfall Mapping Mission (TRMM) (1999-2010), and time series of rainfall observations from meteorological stations (1971-2000), we show that both Amazonian and African rainforest experienced strong precipitation anomalies from 2005-2010. We monitored the response of forest to the climate variability by analyzing the canopy water content observed by SeaWinds Ku-band Scatterometer (QSCAT) (1999-2009) and found that more than 70 million ha of forests in western Amazonia experienced a strong water deficit during the dry season of 2005 and a closely corresponding decline in canopy backscatter that persisted until the next major drought in 2010. This decline in backscatter has been attributed to loss of canopy water content and large-scale tree mortality corroborated by ground and airborne observations. However, no strong impacts was observed on tropical forests of Africa, suggesting that the African rainforest may have more resilience to droughts. We tested this hypothesis by examining the seasonal rainfall patterns, maximum water deficit, and the surface temperature variations. Results show that there is a complex pattern of low annual rainfall, moderate seasonality, and lower surface temperature in Central Africa compared to Amazonia, indicating potentially a lower evapotranspiration circumventing strong water deficits.

The analysis of the possibility of using 10-minute rainfall series to determine the maximum rainfall amount with 5 minutes duration

NASA Astrophysics Data System (ADS)

Kaźmierczak, Bartosz; Wartalska, Katarzyna; Wdowikowski, Marcin; Kotowski, Andrzej

2017-11-01

Modern scientific research in the area of heavy rainfall analysis regarding to the sewerage design indicates the need to develop and use probabilistic rain models. One of the issues that remains to be resolved is the length of the shortest amount of rain to be analyzed. It is commonly believed that the best time is 5 minutes, while the least rain duration measured by the national services is often 10 or even 15 minutes. Main aim of this paper is to present the difference between probabilistic rainfall models results given from rainfall time series including and excluding 5 minutes rainfall duration. Analysis were made for long-time period from 1961-2010 on polish meteorological station Legnica. To develop best fitted to measurement rainfall data probabilistic model 4 probabilistic distributions were used. Results clearly indicates that models including 5 minutes rainfall duration remains more appropriate to use.

Atmospheric Signature of the Agulhas Current

NASA Astrophysics Data System (ADS)

Nkwinkwa Njouodo, Arielle Stela; Koseki, Shunya; Keenlyside, Noel; Rouault, Mathieu

2018-05-01

Western boundary currents play an important role in the climate system by transporting heat poleward and releasing it to the atmosphere. While their influence on extratropical storms and oceanic rainfall is becoming appreciated, their coastal influence is less known. Using satellite and climate reanalysis data sets and a regional atmospheric model, we show that the Agulhas Current is a driver of the observed band of rainfall along the southeastern African coast and above the Agulhas Current. The Agulhas current's warm core is associated with sharp gradients in sea surface temperature and sea level pressure, a convergence of low-level winds, and a co-located band of precipitation. Correlations among wind convergence, sea level pressure, and sea surface temperature indicate that these features show high degree of similarity to those in the Gulf Stream region. Model experiments further indicate that the Agulhas Current mostly impacts convective rainfall.

Climate variability, rice production and groundwater depletion in India

NASA Astrophysics Data System (ADS)

Bhargava, Alok

2018-03-01

This paper modeled the proximate determinants of rice outputs and groundwater depths in 27 Indian states during 1980-2010. Dynamic random effects models were estimated by maximum likelihood at state and well levels. The main findings from models for rice outputs were that temperatures and rainfall levels were significant predictors, and the relationships were quadratic with respect to rainfall. Moreover, nonlinearities with respect to population changes indicated greater rice production with population increases. Second, groundwater depths were positively associated with temperatures and negatively with rainfall levels and there were nonlinear effects of population changes. Third, dynamic models for in situ groundwater depths in 11 795 wells in mainly unconfined aquifers, accounting for latitudes, longitudes and altitudes, showed steady depletion. Overall, the results indicated that population pressures on food production and environment need to be tackled via long-term healthcare, agricultural, and groundwater recharge policies in India.

Climate Web sites

NASA Astrophysics Data System (ADS)

Showstack, Randy

With the growing interest in extreme climate and weather events, the National Oceanic and Atmospheric Administration (NOAA) has set up a one-stop Web site. It includes data on tornadoes, hurricanes, and heavy rainfall, temperature extremes, global climate change, satellite images, and El Niño and La Niña. The Web address is http://www.ncdc.noaa.gov.Another good climate Web site is the La Niña Home Page. Set up by the Environmental and Societal Impacts Group of the National Center for Atmospheric Research, the site includes forecasts, data sources, impacts, and Internet links.

Use of Regional Climate Model Output for Hydrologic Simulations

NASA Astrophysics Data System (ADS)

Hay, L. E.; Clark, M. P.; Wilby, R. L.; Gutowski, W. J.; Leavesley, G. H.; Pan, Z.; Arritt, R. W.; Takle, E. S.

2001-12-01

Daily precipitation and maximum and minimum temperature time series from a Regional Climate Model (RegCM2) were used as input to a distributed hydrologic model for a rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango, Colorado; East Fork of the Carson River near Gardnerville, Nevada; and Cle Elum River near Roslyn, Washington). For comparison purposes, spatially averaged daily data sets of precipitation and maximum and minimum temperature were developed from measured data. These datasets included precipitation and temperature data for all stations that are located within the area of the RegCM2 model output used for each basin, but excluded station data used to calibrate the hydrologic model. Both the RegCM2 output and station data capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all four basins, the RegCM2- and station-based simulations of runoff show little skill on a daily basis (Nash-Sutcliffe (NS) values ranging from 0.05-0.37 for RegCM2 and -0.08-0.65 for station). When the precipitation and temperature biases are corrected in the RegCM2 output and station data sets (Bias-RegCM2 and Bias-station, respectively) the accuracy of the daily runoff simulations improve dramatically for the snowmelt-dominated basins. In the rainfall-dominated basin, runoff simulations based on the Bias-RegCM2 output show no skill (NS value of 0.09) whereas Bias-All simulated runoff improves (NS value improved from -0.08 to 0.72). These results indicate that the resolution of the RegCM2 output is appropriate for basin-scale modeling, but RegCM2 model output does not contain the day-to-day variability needed for basin-scale modeling in rainfall-dominated basins. Future work is warranted to identify the causes for systematic biases in RegCM2 simulations, develop methods to remove the biases, and improve RegCM2 simulations of daily variability in local climate.

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.

2010 weather and aeolian sand-transport data from the Colorado River corridor, Grand Canyon, Arizona

USGS Publications Warehouse

Dealy, Timothy P.; East, Amy E.; Fairley, Helen C.

2014-01-01

Measurements of weather parameters and aeolian sand transport were made in 2010 near selected archeological sites in the Colorado River corridor through Grand Canyon, Arizona. Data collected in 2010 indicate event- and seasonal-scale variations in rainfall, wind, temperature, humidity, and barometric pressure. Differences in weather patterns between 2009 and 2010 included a slightly later spring windy season, greater spring precipitation and annual rainfall totals, and a later onset and length of the reduced diurnal barometric-pressure fluctuations commonly associated with summer monsoon conditions. The increase in spring precipitation was consistent with the 2010 spring El Niño conditions compared to the 2009 spring La Niña conditions, whereas the subsequent transition to an El Niño-Southern Oscillation neutral phase appeared to delay the reduction in diurnal barometric fluctuations.

Quantification of Holocene Asian monsoon rainfall from spatially separated cave records

NASA Astrophysics Data System (ADS)

Hu, Chaoyong; Henderson, Gideon M.; Huang, Junhua; Xie, Shucheng; Sun, Ying; Johnson, Kathleen R.

2008-02-01

A reconstruction of Holocene rainfall is presented for southwest China — an area prone to drought and flooding due to variability in the East Asian monsoon. The reconstruction is derived by comparing a new high-resolution stalagmite δ18O record with an existing record from the same moisture transport pathway. The new record is from Heshang Cave (30°27'N, 110°25'E; 294 m) and shows no sign of kinetic or evaporative effects so can be reliably interpreted as a record of local rainfall composition and temperature. Heshang lies 600 km downwind from Dongge Cave which has a published high-resolution δ18O record (Wang, Y.J., Cheng, H., Edwards, R.L., He, Y.Q., Kong, X.G., An, Z.S., Wu, J.Y., Kelly, M.J., Dykoski, C.A., Li, X.D., 2005. The Holocene Asian monsoon: links to solar changes and North Atlantic climate. Science 308, 854-857). By differencing co-eval δ18O values for the two caves, secondary controls on δ18O (e.g. moisture source, moisture transport, non-local rainfall, temperature) are circumvented and the resulting Δ δ18O signal is controlled directly by the amount of rain falling between the two sites. This is confirmed by comparison with rainfall data from the instrumental record, which also allows a calibration of the Δ δ18O proxy. The calibrated Δ δ18O record provides a quantitative history of rainfall in southwest China which demonstrates that rainfall was 8% higher than today during the Holocene climatic optimum (≈ 6 ka), but only 3% higher during the early Holocene. Significant multi-centennial variability also occurred, with notable dry periods at 8.2 ka, 4.8-4.1 ka, 3.7-3.1 ka, 1.4-1.0 ka and during the Little Ice Age. This Holocene rainfall record provides a good target with which to test climate models. The approach used here, of combining stalagmite records from more than one location, will also allow quantification of rainfall patterns for past times in other regions.

Based on the rainfall system platform raindrops research and analysis of pressure loss

NASA Astrophysics Data System (ADS)

Cao, Gang; Sun, Jian

2018-01-01

With the rapid development of China’s military career, land, sea and air force all services and equipment of modern equipment need to be in the rain test, and verify its might suffer during transportation, storage or use a different environment temperature lower water or use underwater, the water is derived from the heavy rain, the wind and rain, sprinkler system, splash water, water wheel, a violent shock waves or use underwater, etcTest the product performance and quality, under the condition of rainfall system platform in the process of development, how to control the raindrops pressure loss becomes the key to whether the system can simulate the real rainfall [1], this paper is according to the rainfall intensity, nozzle flow resistance, meet water flow of rain pressure loss calculation and analysis, and system arrangement of the optimal solution of rainfall is obtained [2].

AgMIP Regional Activities in a Global Framework: The Brazil Experience

NASA Technical Reports Server (NTRS)

Assad, Eduardo D.; Marin, Fabio R.; Valdivia, Roberto O.; Rosenzweig, Cynthia E.

2012-01-01

Climate variability and change are projected to increate the frequency of extreme high-temperature events, floods, and droughts, which can lead to subsequent changes in soil moister in many locations (Alexandrov and Hoogenboom, 2000). In Brazil, observations reveal a tendency for increasing frequency of extreme rainfall events particularly in south Brazil (Alexander et al., 2006; Carvalho et al., 2014; Groissman et al., 2005), as well as projections for increasing extremes in both maximum and minimum temperatures and high spatial variability for rainfall under the IPCC SRES A2 and B2 scenarios (Marengo et al., 2009).

Variability and Predictability of West African Droughts. A Review in the Role of Sea Surface Temperature Anomalies

NASA Technical Reports Server (NTRS)

Rodriguez-Fonseca, Belen; Mohino, Elsa; Mechoso, Carlos R.; Caminade, Cyril; Biasutti, Michela; Gaetani, Marco; Garcia-Serrano, J.; Vizy, Edward K.; Cook, Kerry; Xue, Yongkang;

Local and remote impacts of aerosol species on Indian summer monsoon rainfall in a GCM

NASA Astrophysics Data System (ADS)

Turner, A. G.; Guo, L.; Highwood, E.

2016-12-01

The HadGEM2 AGCM is used to determine the most important anthropogenic aerosols in the Indian monsoon using experiments in which observed trends in individual aerosol species are imposed. Sulphur dioxide (SD) emissions are shown to impact rainfall more strongly than black carbon (BC) aerosols, causing reduced rainfall especially over northern India. Significant perturbations due to BC are not noted until its emissions are scaled up in a sensitivity test, resulting in rainfall increases over northern India due to the Elevated Heat Pump mechanism, enhancing convection during the premonsoon and bringing forward the monsoon onset. Secondly, the impact of anthropogenic aerosols is compared to that of increasing greenhouse-gas concentrations and observed sea-surface temperature (SST) warming. The tropospheric temperature gradient driving the monsoon shows weakening when forced by either SD or imposed SST trends. However the observed SST trend is dominated by warming in the deep tropics; when the component of SST trend related to aerosol emissions is removed, further warming is found in the extratropical northern hemisphere that tends to offset monsoon weakening. This suggests caution is needed when using SST forcing as a proxy for greenhouse warming. Finally, aerosol emissions are decomposed into those from the Indian region and those elsewhere, in pairs of experiments with SD and BC. Both local and remote aerosol emissions are found to lead to rainfall changes over India; for SD, remote aerosols contribute around 75% of the rainfall decrease over India, while for BC the remote forcing is even more dominant.

Local and remote impacts of aerosol species on Indian summer monsoon rainfall in a GCM

NASA Astrophysics Data System (ADS)

Guo, Liang; Turner, Andrew; Highwood, Eleanor

2016-04-01

The HadGEM2 AGCM is used to determine the most important anthropogenic aerosols in the Indian monsoon using experiments in which observed trends in individual aerosol species are imposed. Sulphur dioxide (SD) emissions are shown to impact rainfall more strongly than black carbon (BC) aerosols, causing reduced rainfall especially over northern India. Significant perturbations due to BC are not noted until its emissions are scaled up in a sensitivity test, in which rainfall increases over northern India as a result of the Elevated Heat Pump mechanism, enhancing convection during the pre-monsoon and bringing forward the monsoon onset. Secondly, the impact of anthropogenic aerosols is compared to that of increasing greenhouse-gas concentrations and observed sea-surface temperature (SST) warming. The tropospheric temperature gradient driving the monsoon shows weakening when forced by either SD or imposed SST trends. However the observed SST trend is dominated by warming in the deep tropics; when the component of SST trend related to aerosol emissions is removed, further warming is found in the extratropical northern hemisphere that tends to offset monsoon weakening. This suggests caution is needed when using SST forcing as a proxy for greenhouse warming. Finally, aerosol emissions are decomposed into those from the Indian region and those elsewhere, in pairs of experiments with SD and BC. Both local and remote aerosol emissions are found to lead to rainfall changes over India; for SD, remote aerosols contribute around 75% of the rainfall decrease over India, while for BC the remote forcing is even more dominant.

The effect of climate manipulations on the herbivory of the pest slug Deroceras reticulatum (Müller, 1774) (Pulmonata: Agriolimacidae)

NASA Astrophysics Data System (ADS)

El-Danasoury, H.; Iglesias-Piñeiro, J.; Córdoba, M.

2016-10-01

The pestiferous status of the terrestrial slug Deroceras reticulatum and the strong dependence of its biology and ecology on climatic factors have driven research on the potential responses of the slug to predicted scenarios of climate change. Here, we report two short-term experiments performed outdoors, under seminatural conditions, to assess the behavioural response of D. reticulatum to different climate manipulations in terms of herbivory, by measuring over 7 days the damage inflicted by slug populations to lettuce seedlings. The climate manipulations tested emulate predicted climatic conditions for northwest Spain, specifically winter warming and increased summer rainfall, in contrast respectively with normal winter conditions and summer without rain conditions. In a winter experiment, we compared a normal winter treatment with a winter warming treatment; with respect to the normal winter treatment, the winter warming treatment was characterised by higher temperature, lower relative humidity and the absence of rainfall. In a summer experiment, we compared a summer drought treatment with an increased summer rainfall treatment; with respect to the summer drought treatment, the increased summer rainfall treatment was characterised by the presence of rainfall, while the conditions of temperature and relative humidity were similar in both treatments. Neither winter warming nor increased summer rainfall did lead to a significant increase on the number of seedlings damaged by the slugs. However, with both treatments, we found a moderate increase on the amount of damage suffered by the seedlings. The results are discussed in the context of the potential responses of D. reticulatum to future climatic conditions.

The effect of climate manipulations on the herbivory of the pest slug Deroceras reticulatum (Müller, 1774) (Pulmonata: Agriolimacidae).

PubMed

El-Danasoury, H; Iglesias-Piñeiro, J; Córdoba, M

2016-10-01

The pestiferous status of the terrestrial slug Deroceras reticulatum and the strong dependence of its biology and ecology on climatic factors have driven research on the potential responses of the slug to predicted scenarios of climate change. Here, we report two short-term experiments performed outdoors, under seminatural conditions, to assess the behavioural response of D. reticulatum to different climate manipulations in terms of herbivory, by measuring over 7 days the damage inflicted by slug populations to lettuce seedlings. The climate manipulations tested emulate predicted climatic conditions for northwest Spain, specifically winter warming and increased summer rainfall, in contrast respectively with normal winter conditions and summer without rain conditions. In a winter experiment, we compared a normal winter treatment with a winter warming treatment; with respect to the normal winter treatment, the winter warming treatment was characterised by higher temperature, lower relative humidity and the absence of rainfall. In a summer experiment, we compared a summer drought treatment with an increased summer rainfall treatment; with respect to the summer drought treatment, the increased summer rainfall treatment was characterised by the presence of rainfall, while the conditions of temperature and relative humidity were similar in both treatments. Neither winter warming nor increased summer rainfall did lead to a significant increase on the number of seedlings damaged by the slugs. However, with both treatments, we found a moderate increase on the amount of damage suffered by the seedlings. The results are discussed in the context of the potential responses of D. reticulatum to future climatic conditions.

A 31-day battery-operated recording weather station.

Treesearch

Richard J. Barney

1972-01-01

The battery-powered recording weather station measures and records wet bulb temperature, dry bulb temperature, wind travel, and rainfall for 31 days. Assembly procedures and cost of supplies and components are discussed.

Characteristics of Precipitation Features and Annual Rainfall during the TRMM Era in the Central Andes

NASA Technical Reports Server (NTRS)

Mohr, Karen I.; Slayback, Daniel; Yager, Karina

2014-01-01

The central Andes extends from 7 deg to 21 deg S, with its eastern boundary defined by elevation (1000m and greater) and its western boundary by the coastline. The authors used a combination of surface observations, reanalysis, and the University of Utah Tropical Rainfall Measuring Mission (TRMM) precipitation features (PF) database to understand the characteristics of convective systems and associated rainfall in the central Andes during the TRMM era, 1998-2012. Compared to other dry (West Africa), mountainous (Himalayas), and dynamically linked (Amazon) regions in the tropics, the central Andes PF population was distinct from these other regions, with small and weak PFs dominating its cumulative distribution functions and annual rainfall totals. No more than 10% of PFs in the central Andes met any of the thresholds used to identify and define deep convection (minimum IR cloud-top temperatures, minimum 85-GHz brightness temperature, maximum height of the 40-dBZ echo). For most of the PFs, available moisture was limited (less than 35mm) and instability low (less than 500 J kg(exp -1)). The central Andes represents a largely stable, dry to arid environment, limiting system development and organization. Hence, primarily short-duration events (less than 60 min) characterized by shallow convection and light to light-moderate rainfall rates (0.5-4.0 mm h(exp -1)) were found.

Large-scale precipitation estimation using Kalpana-1 IR measurements and its validation using GPCP and GPCC data

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mahesh, C.; Gairola, Rakesh M.

2011-12-01

Large-scale precipitation estimation is very important for climate science because precipitation is a major component of the earth's water and energy cycles. In the present study, the GOES precipitation index technique has been applied to the Kalpana-1 satellite infrared (IR) images of every three-hourly, i.e., of 0000, 0300, 0600,…., 2100 hours UTC, for rainfall estimation as a preparatory to the INSAT-3D. After the temperatures of all the pixels in a grid are known, they are distributed to generate a three-hourly 24-class histogram of brightness temperatures of IR (10.5-12.5 μm) images for a 1.0° × 1.0° latitude/longitude box. The daily, monthly, and seasonal rainfall have been estimated using these three-hourly rain estimates for the entire south-west monsoon period of 2009 in the present study. To investigate the potential of these rainfall estimates, the validation of monthly and seasonal rainfall estimates has been carried out using the Global Precipitation Climatology Project and Global Precipitation Climatology Centre data. The validation results show that the present technique works very well for the large-scale precipitation estimation qualitatively as well as quantitatively. The results also suggest that the simple IR-based estimation technique can be used to estimate rainfall for tropical areas at a larger temporal scale for climatological applications.

Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

USGS Publications Warehouse

Funk, Christopher C.; Hoell, Andrew; Shukla, Shraddhanand; Blade, Ileana; Liebmann, Brant; Roberts, Jason B.; Robertson, Franklin R.

2014-01-01

In southern Ethiopia, Eastern Kenya, and southern Somalia poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009 and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers support disaster risk reduction while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we explore the dominant modes of East African rainfall variability, links between these modes and sea surface temperatures, and a simple index-based monitoring-prediction system suitable for drought early warning.

Effects of rainfall patterns on toxic cyanobacterial blooms in a changing climate: between simplistic scenarios and complex dynamics.

PubMed

Reichwaldt, Elke S; Ghadouani, Anas

2012-04-01

Toxic cyanobacterial blooms represent a serious hazard to environmental and human health, and the management and restoration of affected waterbodies can be challenging. While cyanobacterial blooms are already a frequent occurrence, in the future their incidence and severity are predicted to increase due to climate change. Climate change is predicted to lead to increased temperature and changes in rainfall patterns, which will both have a significant impact on inland water resources. While many studies indicate that a higher temperature will favour cyanobacterial bloom occurrences, the impact of changed rainfall patterns is widely under-researched and therefore less understood. This review synthesizes the predicted changes in rainfall patterns and their potential impact on inland waterbodies, and identifies mechanisms that influence the occurrence and severity of toxic cyanobacterial blooms. It is predicted that there will be a higher frequency and intensity of rainfall events with longer drought periods in between. Such changes in the rainfall patterns will lead to favourable conditions for cyanobacterial growth due to a greater nutrient input into waterbodies during heavy rainfall events, combined with potentially longer periods of high evaporation and stratification. These conditions are likely to lead to an acceleration of the eutrophication process and prolonged warm periods without mixing of the water column. However, the frequent occurrence of heavy rain events can also lead to a temporary disruption of cyanobacterial blooms due to flushing and de-stratification, and large storm events have been shown to have a long-term negative effect on cyanobacterial blooms. In contrast, a higher number of small rainfall events or wet days can lead to proliferation of cyanobacteria, as they can rapidly use nutrients that are added during rainfall events, especially if stratification remains unchanged. With rainfall patterns changing, cyanobacterial toxin concentration in waterbodies is expected to increase. Firstly, this is due to accelerated eutrophication which supports higher cyanobacterial biomass. Secondly, predicted changes in rainfall patterns produce more favourable growth conditions for cyanobacteria, which is likely to increase the toxin production rate. However, the toxin concentration in inland waterbodies will also depend on the effect of rainfall events on cyanobacterial strain succession, a process that is still little understood. Low light conditions after heavy rainfall events might favour non-toxic strains, whilst inorganic nutrient input might promote the dominance of toxic strains in blooms. This review emphasizes that the impact of changes in rainfall patterns is very complex and will strongly depend on the site-specific dynamics, cyanobacterial species composition and cyanobacterial strain succession. More effort is needed to understand the relationship between rainfall patterns and cyanobacterial bloom dynamics, and in particular toxin production, to be able to assess and mediate the significant threat cyanobacterial blooms pose to our water resources. Copyright © 2011 Elsevier Ltd. All rights reserved.

Analysis of global oceanic rainfall from microwave data

NASA Technical Reports Server (NTRS)

Rao, M.

1978-01-01

A Global Rainfall Atlas was prepared from Nimbus 5 ESMR data. The Atlas includes global oceanic rainfall maps based on weekly, monthly and seasonal averages, complete through the end of 1975. Similar maps for 1973 and 1974 were studied. They reveal several previously unknown areas of enhanced rainfall and preliminary data on interannual variability of oceanic rainfall.

Agriculturally Relevant Climate Extremes and Their Trends in the World's Major Growing Regions

NASA Astrophysics Data System (ADS)

Zhu, Xiao; Troy, Tara J.

2018-04-01

Climate extremes can negatively impact crop production, and climate change is expected to affect the frequency and severity of extremes. Using a combination of in situ station measurements (Global Historical Climatology Network's Daily data set) and multiple other gridded data products, a derived 1° data set of growing season climate indices and extremes is compiled over the major growing regions for maize, wheat, soybean, and rice for 1951-2006. This data set contains growing season climate indices that are agriculturally relevant, such as the number of hot days, duration of dry spells, and rainfall intensity. Before 1980, temperature-related indices had few trends; after 1980, statistically significant warming trends exist for each crop in the majority of growing regions. In particular, crops have increasingly been exposed to extreme hot temperatures, above which yields have been shown to decline. Rainfall trends are less consistent compared to temperature, with some regions receiving more rainfall and others less. Anomalous temperature and precipitation conditions are shown to often occur concurrently, with dry growing seasons more likely to be hotter, have larger drought indices, and have larger vapor pressure deficits. This leads to the confluence of a variety of climate conditions that negatively impact crop yields. These results show a consistent increase in global agricultural exposure to negative climate conditions since 1980.

Hydrology Model Formulation within the Training Range Environmental Evaluation and Characterization System (TREECS)

DTIC Science & Technology

2014-02-01

Potential evapotranspiration is computed using the Thornthwaite Method. Infiltration is computed from a water balance. DISCLAIMER: The contents of...precipitation, rainfall, runoff, evapotranspiration , infiltration, and number of days with rainfall. A hydrology model was developed to estimate...temperatures. Potential evapotranspiration (PET) is computed using the Thornthwaite Method. Actual evapotranspiration (ET) and infiltration are computed from a

The Chennai extreme rainfall event in 2015: The Bay of Bengal connection

NASA Astrophysics Data System (ADS)

Boyaj, Alugula; Ashok, Karumuri; Ghosh, Subimal; Devanand, Anjana; Dandu, Govardhan

2018-04-01

Southeast India experienced a heavy rainfall during 30 Nov-2 Dec 2015. Particularly, the Chennai city, the fourth major metropolitan city in India with a population of 5 million, experienced extreme flooding and causalities. Using various observed/reanalysed datasets, we find that the concurrent southern Bay of Bengal (BoB) sea surface temperatures (SST) were anomalously warm. Our analysis shows that BoB sea surface temperature anomalies (SSTA) are indeed positively, and significantly, correlated with the northeastern Indian monsoonal rainfall during this season. Our sensitivity experiments carried out with the Weather Research and Forecasting (WRF) model at 25 km resolution suggest that, while the strong concurrent El Niño conditions contributed to about 21.5% of the intensity of the extreme Chennai rainfall through its signals in the local SST mentioned above, the warming trend in BoB SST also contributed equally to the extremity of the event. Further, the El Niño southern oscillation (ENSO) impacts on the intensity of the synoptic events in the BoB during the northeast monsoon are manifested largely through the local SST in the BoB as compared through its signature in the atmospheric circulations over the BoB.

Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

NASA Astrophysics Data System (ADS)

Funk, C.; Hoell, A.; Shukla, S.; Bladé, I.; Liebmann, B.; Roberts, J. B.; Robertson, F. R.; Husak, G.

2014-03-01

In southern Ethiopia, Eastern Kenya, and southern Somalia, poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009, and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers implement disaster risk reduction measures while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts in that region to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we show that the two dominant modes of East African boreal spring rainfall variability are tied, respectively, to western-central Pacific and central Indian Ocean SST. Variations in these rainfall modes can be predicted using two previously defined SST indices - the West Pacific Gradient (WPG) and Central Indian Ocean index (CIO), with the WPG and CIO being used, respectively, to predict the first and second rainfall modes. These simple indices can be used in concert with more sophisticated coupled modeling systems and land surface data assimilations to help inform early warning and guide climate outlooks.

Recent Improvements in Estimating Convective and Stratiform Rainfall in Amazonia

NASA Technical Reports Server (NTRS)

Negri, Andrew J.

1999-01-01

In this paper we present results from the application of a satellite infrared (IR) technique for estimating rainfall over northern South America. Our main objectives are to examine the diurnal variability of rainfall and to investigate the relative contributions from the convective and stratiform components. We apply the technique of Anagnostou et al (1999). In simple functional form, the estimated rain area A(sub rain) may be expressed as: A(sub rain) = f(A(sub mode),T(sub mode)), where T(sub mode) is the mode temperature of a cloud defined by 253 K, and A(sub mode) is the area encompassed by T(sub mode). The technique was trained by a regression between coincident microwave estimates from the Goddard Profiling (GPROF) algorithm (Kummerow et al, 1996) applied to SSM/I data and GOES IR (11 microns) observations. The apportionment of the rainfall into convective and stratiform components is based on the microwave technique described by Anagnostou and Kummerow (1997). The convective area from this technique was regressed against an IR structure parameter (the Convective Index) defined by Anagnostou et al (1999). Finally, rainrates are assigned to the Am.de proportional to (253-temperature), with different rates for the convective and stratiform

Comparisons of Monthly Oceanic Rainfall Derived from TMI and SSM/I

NASA Technical Reports Server (NTRS)

Chang, A. T. C.; Chiu, L. S.; Meng, J.; Wilheit, T. T.; Kummerow, C. D.

1999-01-01

A technique for estimating monthly oceanic rainfall rate using multi-channel microwave measurements has been developed. There are three prominent features of this algorithm. First, the knowledge of the form of the rainfall intensity probability density function used to augment the measurements. Second, utilizing a linear combination of the 19.35 and 22.235 GHz channels to de-emphasize the effect of water vapor. Third, an objective technique has been developed to estimate the rain layer thickness from the 19.35 and 22.235 GHz brightness temperature histograms. This technique is applied to the SSM/I data since 1987 to infer monthly rainfall for the Global Precipitation Climatology Project (GPCP). A modified version of this algorithm is now being applied to the TRMM Microwave Imager (TMI) data. TMI data with better spatial resolution and 24 hour sampling (vs. sun-synchronized sampling, which is limited to two narrow intervals of local solar time for DMSP satellites) prompt us to study the similarity and difference between these two rainfall estimates. Six months of rainfall data (January to June 1998) are used in this study. Means and standard deviations are calculated. Paired student t-tests are administrated to evaluate the differences between rainfall estimates from SSM/I and TMI data. Their differences are discussed in the context of global satellite rainfall estimation.

Empirical studies of the microwave radiometric response to rainfall in the tropics and midlatitudes

NASA Technical Reports Server (NTRS)

Petty, Grant W.; Katsaros, Kristina B.

1989-01-01

Results are presented from quantitative comparisons between satellite microwave radiometer observations and digital radar observations of equatorial convective cloud clusters and midlatitude frontal precipitation. Simultaneous data from the Winter Monsoon Experiment digital radar and the SMMR for December 1978 are analyzed. It is found that the most important differences between the microwave response to rainfall in the equatorial tropics and to stratiform rain in oceanic midlatitude fronts is caused by the different spatial characteristics of stratiform and convective rainfall and by the different background brightness temperature fields associated with tropical and midlatitude levels of atmospheric water vapor.

The functional correlation between rainfall rate and extinction coefficient for frequencies from 3 to 10 GHz

NASA Technical Reports Server (NTRS)

Jameson, A. R.

1990-01-01

The relationship between the rainfall rate (R) obtained from radiometric brightness temperatures and the extinction coefficient (k sub e) is investigated by computing the values of k sub e over a wide range of rainfall rates, for frequencies from 3 to 25 GHz. The results show that the strength of the relation between the R and the k sub e values exhibits considerable variation for frequencies at this range. Practical suggestions are made concerning the selection of particular frequencies for rain measurements to minimize the error in R determinations.

A comparison between the effects of artificial land cover and anthropogenic heat on a localized heavy rain event in 2008 in Zoshigaya, Tokyo, Japan

NASA Astrophysics Data System (ADS)

Souma, Kazuyoshi; Tanaka, Kenji; Suetsugi, Tadashi; Sunada, Kengo; Tsuboki, Kazuhisa; Shinoda, Taro; Wang, Yuqing; Sakakibara, Atsushi; Hasegawa, Koichi; Moteki, Qoosaku; Nakakita, Eiichi

2013-10-01

5 August 2008, a localized heavy rainfall event caused a rapid increase in drainpipe discharge, which killed five people working in a drainpipe near Zoshigaya, Tokyo. This study compared the effects of artificial land cover and anthropogenic heat on this localized heavy rainfall event based on three ensemble experiments using a cloud-resolving model that includes realistic urban features. The first experiment CTRL (control) considered realistic land cover and urban features, including artificial land cover, anthropogenic heat, and urban geometry. In the second experiment NOAH (no anthropogenic heat), anthropogenic heat was ignored. In the third experiment NOLC (no land cover), urban heating from artificial land cover was reduced by keeping the urban geometry but with roofs, walls, and roads of artificial land cover replaced by shallow water. The results indicated that both anthropogenic heat and artificial land cover increased the amount of precipitation and that the effect of artificial land cover was larger than that of anthropogenic heat. However, in the middle stage of the precipitation event, the difference between the two effects became small. Weak surface heating in NOAH and NOLC reduced the near-surface air temperature and weakened the convergence of horizontal wind and updraft over the urban areas, resulting in a reduced rainfall amount compared with that in CTRL.

Proxy system modeling of tree-ring isotope chronologies over the Common Era

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; LeGrande, A. N.

2017-12-01

The Asian monsoon can be characterized in terms of both precipitation variability and atmospheric circulation across a range of spatial and temporal scales. While multicentury time series of tree-ring widths at hundreds of sites across Asia provide estimates of past rainfall, the oxygen isotope ratios of annual rings may reveal broader regional hydroclimate and atmosphere-ocean dynamics. Tree-ring oxygen isotope chronologies from Monsoon Asia have been interpreted to reflect a local 'amount effect', relative humidity, source water and seasonality, and winter snowfall. Here, we use an isotope-enabled general circulation model simulation from the NASA Goddard Institute for Space Science (GISS) Model E and a proxy system model of the oxygen isotope composition of tree-ring cellulose to interpret the large-scale and local climate controls on δ 18O chronologies. Broad-scale dominant signals are associated with a suite of covarying hydroclimate variables including growing season rainfall amounts, relative humidity, and vapor pressure deficit. Temperature and source water influences are region-dependent, as are the simulated tree-ring isotope signals associated with the El Nino Southern Oscillation (ENSO) and large-scale indices of the Asian monsoon circulation. At some locations, including southern coastal Viet Nam, local precipitation isotope ratios and the resulting simulated δ 18O tree-ring chronologies reflect upstream rainfall amounts and atmospheric circulation associated with monsoon strength and wind anomalies.

Identification of the key ecological factors influencing vegetation degradation in semi-arid agro-pastoral ecotone considering spatial scales

NASA Astrophysics Data System (ADS)

Peng, Yu; Wang, Qinghui; Fan, Min

2017-11-01

When assessing re-vegetation project performance and optimizing land management, identification of the key ecological factors inducing vegetation degradation has crucial implications. Rainfall, temperature, elevation, slope, aspect, land use type, and human disturbance are ecological factors affecting the status of vegetation index. However, at different spatial scales, the key factors may vary. Using Helin County, Inner-Mongolia, China as the study site and combining remote sensing image interpretation, field surveying, and mathematical methods, this study assesses key ecological factors affecting vegetation degradation under different spatial scales in a semi-arid agro-pastoral ecotone. It indicates that the key factors are different at various spatial scales. Elevation, rainfall, and temperature are identified as crucial for all spatial extents. Elevation, rainfall and human disturbance are key factors for small-scale quadrats of 300 m × 300 m and 600 m × 600 m, temperature and land use type are key factors for a medium-scale quadrat of 1 km × 1 km, and rainfall, temperature, and land use are key factors for large-scale quadrats of 2 km × 2 km and 5 km × 5 km. For this region, human disturbance is not the key factor for vegetation degradation across spatial scales. It is necessary to consider spatial scale for the identification of key factors determining vegetation characteristics. The eco-restoration programs at various spatial scales should identify key influencing factors according their scales so as to take effective measurements. The new understanding obtained in this study may help to explore the forces which driving vegetation degradation in the degraded regions in the world.

The Potential Financial Costs of Climate Change on Health of Urban and Rural Citizens: A Case Study of Vibrio cholerae Infections at Bukavu Town, South Kivu Province, Eastern of Democratic Republic of Congo.

PubMed

Munyuli, Mb Théodore; Kavuvu, J-M Mbaka; Mulinganya, Guy; Bwinja, G Mulinganya

2013-01-01

Cholera epidemics have a recorded history in eastern Congo dating to 1971. A study was conducted to find out the linkage between climate variability/change and cholera outbreak and to assess the related economic cost in the management of cholera in Congo. This study integrates historical data (20 years) on temperature and rainfall with the burden of disease from cholera in South-Kivu province, eastern Congo. Analyses of precipitation and temperatures characteristics in South-Kivu provinces showed that cholera epidemics are closely associated with climatic factors variability. Peaks in Cholera new cases were in synchrony with peaks in rainfalls. Cholera infection cases declined significantly (P<0.05) with the rise in the average temperature. The monthly number of new Cholera cases oscillated between 5 and 450. For every rise of the average temperature by 0.35 °C to 0.75 °C degree Celsius, and for every change in the rainfall variability by 10-19%, it is likely cholera infection risks will increase by 17 to 25%. The medical cost of treatment of Cholera case infection was found to be of US$50 to 250 per capita. The total costs of Cholera attributable to climate change were found to fall in the range of 4 to 8% of the per capita in annual income in Bukavu town. It is likely that high rainfall favor multiplication of the bacteria and contamination of water sources by the bacteria (Vibrio cholerae). The consumption of polluted water, promiscuity, population density and lack of hygiene are determinants favoring spread and infection of the bacteria among human beings living in over-crowded environments.

Effect of climate change on agriculture sustainability in Jordan

NASA Astrophysics Data System (ADS)

Khresat, S.

2009-04-01

Jordan is a vulnerable country in terms of climate change impact. In the latest assessment report published by the Intergovernmental Panel on Climate Change. Jordan will suffer from reduced agricultural productivity due to more erratic rainfall patterns, reduced freshwater resources and increased temperatures. The Initial National Communication (INC) to the United Nations Framework Convention to Climate Change (UNFCCC) foresees that over the next three decades, Jordan will witness a rise in temperature, drop in rainfall, reduced ground cover, reduced water availability, heat-waves, and more frequent dust storms. Coupled with the effect of continuing drought incidents, plant cover removal was greatly accelerated. Climate change can impact agricultural sustainability in Jordan in two interrelated ways: first, by diminishing the long-term ability of agroecosystems to provide food and fiber locally; and second, by inducing shifts in agricultural regions that may encroach upon natural habitats, at the expense of floral and faunal diversity. Global warming may encourage the expansion of agricultural activities into regions now occupied by natural ecosystems such as rangelands in the Badia region and forests. Such encroachment will have adverse effects on the fragile ecosystem in those areas (Badia and steppe areas). Primary model test results showed that the reduction of rainfall by 10 to 20% had a negative impact while the increase in rainfall by 10 to 20% had a positive impact on grain yield for both barley and wheat at the different temperature regimes. This is due to the fact that water is the main limiting growth factor for wheat and barley under rainfed agriculture on Jordan. The warming (increase in temperature by 1 to 4˚ C) had negative impact on barley grain yield while it had a positive impact on grain yield of wheat.

Developing Multi-model Ensemble for Precipitation and Temperature Seasonal Forecasts: Implications for Karkheh River Basin in Iran

NASA Astrophysics Data System (ADS)

Najafi, Husain; Massah Bavani, Ali Reza; Wanders, Niko; Wood, Eric; Irannejad, Parviz; Robertson, Andrew

2017-04-01

Water resource managers can utilize reliable seasonal forecasts for allocating water between different users within a water year. In the west of Iran where a decline of renewable water resources has been observed, basin-wide water management has been the subject of many inter-provincial conflicts in recent years. The problem is exacerbated when the environmental water requirements is not provided leaving the Hoor-al-Azim marshland in the downstream dry. It has been argued that information on total seasonal rainfall can support the Iranian Ministry of Energy within the water year. This study explores the skill of the North America Multi Model Ensemble for Karkheh River Basin in the of west Iran. NMME seasonal precipitation and temperature forecasts from eight models are evaluated against PERSIANN-CDR and Climate Research Unit (CRU) datasets. Analysis suggests that anomaly correlation for both precipitation and temperature is greater than 0.4 for all individual models. Lead time-dependent seasonal forecasts are improved when a multi-model ensemble is developed for the river basin using stepwise linear regression model. MME R-squared exceeds 0.6 for temperature for almost all initializations suggesting high skill of NMME in Karkheh river basin. The skill of MME for rainfall forecasts is high for 1-month lead time for October, February, March and October initializations. However, for months when the amount of rainfall accounts for a significant proportion of total annual rainfall, the skill of NMME is limited a month in advance. It is proposed that operational regional water companies incorporate NMME seasonal forecasts into water resource planning and management, especially during growing seasons that are essential for agricultural risk management.

Interdecadal Change in SST Anomalies Associated with Winter Rainfall over South China

NASA Astrophysics Data System (ADS)

Liantong, Z.

2012-04-01

The present study investigates the interdecadal change in winter (January-February-March, or "JFM") rainfall over South China and in South China JFM rainfall-sea surface temperature (SST) relationship by using station observations for the period of 1958-2002, the Met Office Hadley Center's SST data for the period of 1900-2008, and the ERA-40 re-analysis for the period of 1958-2002. It is found that the relationship between South China JFM rainfall and SST experienced an obvious interdecadal change around the year 1978. The analyses show that the JFM rainfall anomalies during 1960-1977 and 1978-2002 were closely associated with the South China Sea (SCS) SST and El Niño-Southern Oscillation (ENSO), respectively. Moreover, southwesterly anomalies at 700 hPa dominate over the South China Sea for positive SCS SST anomaly years during 1960-1977, and for El Niño years during 1978-2002, respectively. These wind anomalies, which are associated with the enhancement of the western Pacific subtropical high, transport more moisture into South China, favoring increases in rainfall. KEY WORDS: ENSO; SCS SST; South China winter rainfall, western Pacific subtropical high.

Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model

NASA Technical Reports Server (NTRS)

Morin, Cory; Monaghan, Andrew; Crosson, William; Quattrochi, Dale; Luvall, Jeffrey

2014-01-01

Dengue fever is a mosquito-borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Because of variations in topography, ocean influences and atmospheric processes, temperature and rainfall patterns vary across Puerto Rico and so do dengue virus transmission rates. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input, ground-based observations for temperature input, and laboratory confirmed dengue cases reported by the Centers for Disease Control and Prevention for parameter calibration, we modeled dengue transmission at the county level across Puerto Rico from 2010-2013 using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations for each county in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. The top 1% of model simulations that best reproduced the reported dengue case data were then analyzed to determine the most important parameters for dengue virus transmission in each county, as well as the relative influence of climate variability on transmission. These results can be used by public health workers to implement dengue control methods that are targeted for specific locations and climate conditions.

Climate Change and its Impacts on Tourism and Livelihood in Manaslu Conservation Area, Nepal

NASA Astrophysics Data System (ADS)

K C, A.

2017-12-01

The Hindukush Himalayan region including Nepal, a country reliant on tourism, is particularly sensitive to climate change. It had impact on different sectors of the environment including tourism and livelihood. There are very few researches focused on tourism, livelihood and climate change in Nepal. The present research assesses the impact of climate change on tourism and livelihood in the Manaslu Conservation Area (MCA) of Nepal. In this study, the empirical data collected at the field was complemented by secondary data on climate and tourism. For primary data collection, seventy-six households were interviewed followed by three focus group discussions and five key informant interviews. Correlation, regression and graphical analysis was carried out for the presentation of data. Local people perceived that temperature and rainfall have been increasing in the study site as a result of climate change. Change in usual pattern of temperature and rainfall had affected tourism sector. Socioeconomic variables such as marital status, size of household, education and landholding status had positive effect on tourism participation while livestock-holding status and occupation of the household had negative effect on tourism participation. Number of visitors is increasing in MCA in recent years, and tourism participation is helping local people to earn more money and improve their living standard. In response to gradually warming temperature and decreasing snowfall, there seems an urgent need for tourism promotional activities in the study area. Also awareness and education related to tourism, gender empowerment of women, advertisement and publicity on tourism promotion, adequate subsidy and training on ecotourism and skill development trainings on handicraft are recommended.

Rainfall and temperature distinguish between Karnal bunt positive and negative years in wheat fields in Texas.

PubMed

Workneh, F; Allen, T W; Nash, G H; Narasimhan, B; Srinivasan, R; Rush, C M

2008-01-01

Karnal bunt of wheat, caused by the fungus Tilletia indica, is an internationally regulated disease. Since its first detection in central Texas in 1997, regions in which the disease was detected have been under strict federal quarantine regulations resulting in significant economic losses. A study was conducted to determine the effect of weather factors on incidence of the disease since its first detection in Texas. Weather variables (temperature and rainfall amount and frequency) were collected and used as predictors in discriminant analysis for classifying bunt-positive and -negative fields using incidence data for 1997 and 2000 to 2003 in San Saba County. Rainfall amount and frequency were obtained from radar (Doppler radar) measurements. The three weather variables correctly classified 100% of the cases into bunt-positive or -negative fields during the specific period overlapping the stage of wheat susceptibility (boot to soft dough) in the region. A linear discriminant-function model then was developed for use in classification of new weather variables into the bunt occurrence groups (+ or -). The model was evaluated using weather data for 2004 to 2006 for San Saba area (central Texas), and data for 2001 and 2002 for Olney area (north-central Texas). The model correctly predicted bunt occurrence in all cases except for the year 2004. The model was also evaluated for site-specific prediction of the disease using radar rainfall data and in most cases provided similar results as the regional level evaluation. The humid thermal index (HTI) model (widely used for assessing risk of Karnal bunt) agreed with our model in all cases in the regional level evaluation, including the year 2004 for the San Saba area, except for the Olney area where it incorrectly predicted weather conditions in 2001 as unfavorable. The current model has a potential to be used in a spray advisory program in regulated wheat fields.

Environmental behaviour of airborne Amaranthaceae pollen in the southern part of the Iberian Peninsula, and its role in future climate scenarios.

PubMed

Cariñanos, Paloma; Alcázar, Purificación; Galán, Carmen; Domínguez, Eugenio

2014-02-01

The Amaranthaceae family includes a number of species which, through a series of specific adaptations, thrive in salty soils, arid environments and altered human settlements. Their ability to tolerate high temperatures favours summer flowering, giving rise to the widespread involvement of Amaranthaceae pollen grains in summer allergies, both in Mediterranean Europe and in areas with arid climates. This study analysed a 21-year set of historical airborne Amaranthaceae pollen records for an area located in the southern part of the Iberian Peninsula, in order to chart species' environmental reaction to changing climate conditions which occurred in the last decades. Airborne pollen data were collected from January 1991 to December 2011 using a Hirst-type volumetric impact sampler. Results showed that Amaranthaceae pollen remained in the atmosphere for over 6 months along the year, from early spring until early autumn. The annual Pollen Index ranged from barely 200 grains to almost 2000 grains, and was strongly influenced by rainfall during the flowering period, which prompted the development of new individuals and thus an increase in pollen production. A trend was noted towards increasingly early pollen peak dates; peaks were recorded in August-September in years with summer rainfall, but as early as May-June in years when over 50% of annual rainfall was recorded in the months prior to flowering. The gradual decline in the annual Pollen Index over later years is attributable not only to growing urbanisation of the area but also to a change in rainfall distribution pattern. High maximum temperatures in spring were also directly related to the peak date and the Pollen Index. This ability to adapt to changeable and occasionally stressful and restrictive, environmental conditions places Amaranthaceae at a competitive advantage with respect to other species sharing the same ecological niche. An increased presence of Amaranthaceae is likely to have a greater impact on future scenarios for pollen allergy diseases associated with climate change. © 2013.

Modeling the impact of climate variability on diarrhea-associated diseases in Taiwan (1996-2007).

PubMed

Chou, Wei-Chun; Wu, Jiunn-Lin; Wang, Yu-Chun; Huang, Hsin; Sung, Fung-Chang; Chuang, Chun-Yu

2010-12-01

Diarrhea is an important public health problem in Taiwan. Climatic changes and an increase in extreme weather events (extreme heat, drought or rainfalls) have been strongly linked to the incidence of diarrhea-associated disease. This study investigated and quantified the relationship between climate variations and diarrhea-associated morbidity in subtropical Taiwan. Specifically, this study analyzed the local climatic variables and the number of diarrhea-associated infection cases from 1996 to 2007. This study applied a climate variation-guided Poisson regression model to predict the dynamics of diarrhea-associated morbidity. The proposed model allows for climate factors (relative humidity, maximum temperature and the numbers of extreme rainfall), autoregression, long-term trends and seasonality, and a lag-time effect. Results indicated that the maximum temperature and extreme rainfall days were strongly related to diarrhea-associated morbidity. The impact of maximum temperature on diarrhea-associated morbidity appeared primarily among children (0-14years) and older adults (40-64years), and had less of an effect on adults (15-39years). Otherwise, relative humidity and extreme rainfall days significantly contributed to the diarrhea-associated morbidity in adult. This suggested that children and older adults were the most susceptible to diarrhea-associated morbidity caused by climatic variation. Because climatic variation contributed to diarrhea morbidity in Taiwan, it is necessary to develop an early warning system based on the climatic variation information for disease control management. Copyright © 2010 Elsevier B.V. All rights reserved.

Regional rainfall thresholds for landslide occurrence using a centenary database

NASA Astrophysics Data System (ADS)

Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Garcia, Ricardo A. C.; Quaresma, Ivânia

2018-04-01

This work proposes a comprehensive method to assess rainfall thresholds for landslide initiation using a centenary landslide database associated with a single centenary daily rainfall data set. The method is applied to the Lisbon region and includes the rainfall return period analysis that was used to identify the critical rainfall combination (cumulated rainfall duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds are assessed and calibrated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, these thresholds may be used with acceptable confidence up to 50 km from the rain gauge. The rainfall thresholds obtained using linear and potential regression perform well in ROC metrics. However, the intermediate thresholds based on the probability of landslide events established in the zone between the lower-limit threshold and the upper-limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.

Quantitative assessment of current and future risks related rainfall in processing tomato in the Guadiana river basin (SW Spain)

NASA Astrophysics Data System (ADS)

Castañeda-Vera, Alba; Garrido, Alberto; Ruiz-Ramos, Margarita; Sánchez-Sánchez, Enrique; Inés Mínguez, M.

2013-04-01

An extension of risk coverages in the insurance policies for processing tomato, mainly related to rainfall events, has resulted in an important increase in claims. This suggests that damages related to extreme or ill-timed showers have been underestimated in previous years. An estimation of damages related to rainfall in the last thirty years and the impact of climate change in the risk related to rainfall in processing tomato crops in the Guadiana river basin (SW Spain) were studied through a risk index. First, the risk index was defined with temperature and relative humidity thresholds related to different damage magnitudes. Then, this index was applied to current climate and to future climate scenarios in nine weather stations representative of the studied area to determine the trends in losses related to extreme or inopportune rainfall events. Thresholds of temperature and relative humidity were obtained from cross-checking agricultural insurance records and meteorological data from local weather stations (REDAREX, http://sw-aperos.juntaex.es/redarex). To consider longer time series, the reanalysis database ERA-INTERIM (Dee et al., 2011) was used. Simulated climate was obtained from the European Project ENSEMBLES (http://www.ensembles-eu.org/). Trends in climatic risk were analysed by applying the risk index to three sets of data defining current climate (1980-2010), mid-future climate (2010-2040) and long-term future climate (2040-2070). An algorithm to choose the surrounding cell that minimizes the temperature and precipitation climatic biases and maximizes seasonal correlation when comparing ENSEMBLES regional climate model simulations and observed climate was applied before index calculation. The results show the trends in frequency and magnitude of the risk of suffering damages related to rainfall events. The methodology decreased the uncertainty on risk levels. Results contribute to detect the periods during the growing season with larger risk of damage in order to provide information to assist research on risk management practices and to support insurance policy makers to extend guaranties and to adapt the insurance conditions and costs to real crop risks. This research is being financed by MULCLIVAR project (CGL2012-38923-C02-02), MINECO, Spain Keywords: climate change, risk, rainfall, processing tomato. References Dee, D. P., with 35 co-authors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. R. Meteorol. Soc., 137, 553-597.

Base flow-driven shifts in tropical stream temperature regimes across a mean annual rainfall gradient

Treesearch

Ayron M. Strauch; Richard A. MacKenzie; Ralph W. Tingley

2017-01-01

Climate change is expected to affect air temperature and watershed hydrology, but the degree to which these concurrent changes affect stream temperature is not well documented in the tropics. How stream temperature varies over time under changing hydrologic conditions is difficult to isolate from seasonal changes in air temperature. Groundwater and bank storage...

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

NASA Astrophysics Data System (ADS)

Polemio, Maurizio; Lonigro, Teresa

2013-04-01

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

Interpretation of orbital scale variability in mid-latitude speleothem δ18O: Significance of growth rate controlled kinetic fractionation effects

NASA Astrophysics Data System (ADS)

Stoll, Heather; Mendez-Vicente, Ana; Gonzalez-Lemos, Saul; Moreno, Ana; Cacho, Isabel; Cheng, Hai; Edwards, R. Lawrence

2015-11-01

Oxygen isotopes have been the most widely used climate indicator in stalagmites, applied to reconstruct past changes in rainfall δ18O and cave temperature. However, the δ18O signal in speleothems may also be influenced by variable kinetic fractionation effects, here conceived broadly as fractionation effects not arising from temperature variation. The regional reproducibility of speleothem δ18O signals has been proposed as a way to distinguish the δ18O variations arising directly from changes rainfall δ18O and cave temperature, from variations due to kinetic effects which may nonetheless be influenced by climate. Here, we compare isotopic records from 5 coeval stalagmites from two proximal caves in NW Spain covering the interval 140 to 70 ka, which experienced the same primary variations in temperature and rainfall δ18O, but exhibit a large range in growth rates and temporal trends in growth rate. Stalagmites growing at faster rates near 50 μm/yr have oxygen isotopic ratios over 1‰ more negative than coeval stalagmites with very slow (5 μm/yr) growth rates. Because growth rate variations also occur over time within any given stalagmite, the measured oxygen isotopic time series for a given stalagmite includes both climatic and kinetic components. Removal of the kinetic component of variation in each stalagmite, based on the dependence of the kinetic component on growth rate, is effective at distilling a common temporal evolution of among the oxygen isotopic records of the multiple stalagmites. However, this approach is limited by the quality of the age model. For time periods characterized by very slow growth and long durations between dates, the presence of crypto-hiatus may result in average growth rates which underestimate the instantaneous speleothem deposition rates and which therefore underestimate the magnitude of kinetic effects. The stacked growth rate-corrected speleothem δ18O is influenced by orbital scale variation in the cave temperature and the δ18O of the ocean moisture source, but also by temporally variable fractionation in the hydrological cycle. The most salient trend is increased hydrological fractionation during the GI-22 period, when warmer sea surface temperatures in the subtropical Atlantic moisture source region may have favored greater precipitation amounts.

Rainfall Across the Globe: Precipitation. The Role of Landmass in Monsoon Development. The Relationship Between Precipitation and Sea Surface Temperature on Decadal Time Scales

NASA Technical Reports Server (NTRS)

Chao, Winston; Schubert, Siegfried; Suarez, Max; Pegion, Philip

2000-01-01

The numerical simulation of precipitation helps scientists understand the complex mechanisms that determine how and why rainfall is distributed across the globe. Simulation aids in the development of forecastin,g efforts that inform policies regarding the management of water resources. Precipitation modeling also provides short-term warnings, for emergencies such as flash floods and mudslides. Just as precipitation modeling can warn of an impending abundance of rainfall, it can help anticipate the absence of rainfall in drought. What constitutes a drought? A meteorological drought simply means that an area is getting a significantly lower amount of rain than usual over a prolonged period of time and an agricultural drought is based on the level of soil moisture.

A satellite rainfall retrieval technique over northern Algeria based on the probability of rainfall intensities classification from MSG-SEVIRI

NASA Astrophysics Data System (ADS)

Lazri, Mourad; Ameur, Soltane

2016-09-01

In this paper, an algorithm based on the probability of rainfall intensities classification for rainfall estimation from Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) has been developed. The classification scheme uses various spectral parameters of SEVIRI that provide information about cloud top temperature and optical and microphysical cloud properties. The presented method is developed and trained for the north of Algeria. The calibration of the method is carried out using as a reference rain classification fields derived from radar for rainy season from November 2006 to March 2007. Rainfall rates are assigned to rain areas previously identified and classified according to the precipitation formation processes. The comparisons between satellite-derived precipitation estimates and validation data show that the developed scheme performs reasonably well. Indeed, the correlation coefficient presents a significant level (r:0.87). The values of POD, POFD and FAR are 80%, 13% and 25%, respectively. Also, for a rainfall estimation of about 614 mm, the RMSD, Bias, MAD and PD indicate 102.06(mm), 2.18(mm), 68.07(mm) and 12.58, respectively.

Forecasting of Seasonal Rainfall using ENSO and IOD teleconnection with Classification Models

NASA Astrophysics Data System (ADS)

De Silva, T.; Hornberger, G. M.

2017-12-01

Seasonal to annual forecasts of precipitation patterns are very important for water infrastructure management. In particular, such forecasts can be used to inform decisions about the operation of multipurpose reservoir systems in the face of changing climate conditions. Success in making useful forecasts often is achieved by considering climate teleconnections such as the El-Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) as related to sea surface temperature variations. We present an analysis to explore the utility of using rainfall relationships in Sri Lanka with ENSO and IOD to predict rainfall to the Mahaweli, river basin. Forecasting of rainfall as classes - above normal, normal, and below normal - can be useful for water resource management decision making. Quadratic discrimination analysis (QDA) and random forest models are used to identify the patterns of rainfall classes with respect to ENSO and IOD indices. These models can be used to forecast the likelihood of areal rainfall anomalies using predicted climate indices. Results can be used for decisions regarding allocation of water for agriculture and electricity generation within the Mahaweli project of Sri Lanka.

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

NASA Astrophysics Data System (ADS)

Kashid, S. S.; Ghosh, Subimal; Maity, Rajib

2010-12-01

SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.

Climate Change and Its Impact on the Yield of Major Food Crops: Evidence from Pakistan

PubMed Central

Ali, Sajjad; Liu, Ying; Ishaq, Muhammad; Shah, Tariq; Abdullah; Ilyas, Aasir; Din, Izhar Ud

2017-01-01

Pakistan is vulnerable to climate change, and extreme climatic conditions are threatening food security. This study examines the effects of climate change (e.g., maximum temperature, minimum temperature, rainfall, relative humidity, and the sunshine) on the major crops of Pakistan (e.g., wheat, rice, maize, and sugarcane). The methods of feasible generalized least square (FGLS) and heteroscedasticity and autocorrelation (HAC) consistent standard error were employed using time series data for the period 1989 to 2015. The results of the study reveal that maximum temperature adversely affects wheat production, while the effect of minimum temperature is positive and significant for all crops. Rainfall effect towards the yield of a selected crop is negative, except for wheat. To cope with and mitigate the adverse effects of climate change, there is a need for the development of heat- and drought-resistant high-yielding varieties to ensure food security in the country. PMID:28538704

Climate Change and Its Impact on the Yield of Major Food Crops: Evidence from Pakistan.

PubMed

Ali, Sajjad; Liu, Ying; Ishaq, Muhammad; Shah, Tariq; Abdullah; Ilyas, Aasir; Din, Izhar Ud

2017-05-24

Pakistan is vulnerable to climate change, and extreme climatic conditions are threatening food security. This study examines the effects of climate change (e.g., maximum temperature, minimum temperature, rainfall, relative humidity, and the sunshine) on the major crops of Pakistan (e.g., wheat, rice, maize, and sugarcane). The methods of feasible generalized least square (FGLS) and heteroscedasticity and autocorrelation (HAC) consistent standard error were employed using time series data for the period 1989 to 2015. The results of the study reveal that maximum temperature adversely affects wheat production, while the effect of minimum temperature is positive and significant for all crops. Rainfall effect towards the yield of a selected crop is negative, except for wheat. To cope with and mitigate the adverse effects of climate change, there is a need for the development of heat- and drought-resistant high-yielding varieties to ensure food security in the country.

Factors Influencing the Sahelian Paradox at the Local Watershed Scale: Causal Inference Insights

NASA Astrophysics Data System (ADS)

Van Gordon, M.; Groenke, A.; Larsen, L.

2017-12-01

While the existence of paradoxical rainfall-runoff and rainfall-groundwater correlations are well established in the West African Sahel, the hydrologic mechanisms involved are poorly understood. In pursuit of mechanistic explanations, we perform a causal inference analysis on hydrologic variables in three watersheds in Benin and Niger. Using an ensemble of techniques, we compute the strength of relationships between observational soil moisture, runoff, precipitation, and temperature data at seasonal and event timescales. Performing analysis over a range of time lags allows dominant time scales to emerge from the relationships between variables. By determining the time scales of hydrologic connectivity over vertical and lateral space, we show differences in the importance of overland and subsurface flow over the course of the rainy season and between watersheds. While previous work on the paradoxical hydrologic behavior in the Sahel focuses on surface processes and infiltration, our results point toward the importance of subsurface flow to rainfall-runoff relationships in these watersheds. The hypotheses generated from our ensemble approach suggest that subsequent explorations of mechanistic hydrologic processes in the region include subsurface flow. Further, this work highlights how an ensemble approach to causal analysis can reveal nuanced relationships between variables even in poorly understood hydrologic systems.

[Advance to the research of the climate factor effect on the distribution of plague].

PubMed

Zhang, A P; Wei, R J; Xiong, H M; Wang, Z Y

2016-05-01

Plague is an anthropozoonotic disease caused by the Yersinia pestis ,which developed by many factors including local climate factors. In recent years, more and more studies on the effects of climate on plague were conducted. According to the researches, climate factors (mainly the rainfall and temperature) affected the development and distribution of plague by influencing the abundance of plague host animals and fleas index. The climate also affected the epidemic dynamics and the scope of plague. There were significant differences existing in the influence of climate on the palgue developed in the north and south China. In the two different plague epidemic systems, the solitary Daurian ground squirrel-flea-plague and the social Mongolian gerbil-flea-plague, the obvious population differences existed among the responses of the host animal to the climate changes. Although the internal relationship between the rainfall, the flea index, the density of rodents and the plague supported the nutritional cascade hypothesis, it can not prove that there is a clear causality between the occurrence of plague and rainfall. So the influence of climate factors on plague distribution can only be used for early forecasting and warning of the plague.

The impact of summer rainfall on the temperature gradient along the United States-Mexico border

NASA Technical Reports Server (NTRS)

Balling, Robert C., Jr.

1989-01-01

The international border running through the Sonoran Desert in southern Arizona and northern Sonora is marked by a sharp discontinuity in albedo and grass cover. The observed differences in surface properties are a result of long-term, severe overgrazing of the Mexican lands. Recently, investigators have shown the Mexican side of the border to have higher surface and air temperatures when compared to adjacent areas in the United State. The differences in temperatures appear to be more associated with differential evapotranspiration rates than with albedo changes along the border. In this study, the impact of summer rainfall on the observed seasonal and daily gradient in maximum temperature is examined. On a seasonal time scale, the temperature gradient increases with higher moisture levels, probably due to a vegetative response on the United States' side of the border; at the daily level, the gradient in maximum temperature decreases after a rain event as evaporation rates equalize between the countries. The results suggest that temperature differences between vegetated and overgrazed landscapes in arid areas are highly dependent upon the amount of moisture available for evapotranspiration.

Climate Change, Growth, and Poverty in Ethiopia

DTIC Science & Technology

2013-06-01

agricultural effects of global warming, reflecting their disadvantaged geographic location Higher evaporation and reduced soil moisture can damage crops...Ringler (2007) 5 Temperature, radiation, rainfall, soil moisture , and carbon dioxide (CO2) concentration are important variables that can proxy...iii) rainfall can affect other proxies of climate change in the literature such as soil moisture 6 This is based on FAOstat database 7 According to

Feeding and reproductive patterns of Astyanax intermedius in a headwater stream of Atlantic Rainforest.

PubMed

Souza, Ursulla P; Ferreira, Fabio C; Carmo, Michele A F; Braga, Francisco M S

2015-01-01

In this paper, we determined diet composition, reproductive periodicity and fecundity of Astyanax intermedius in a headwater stream of a State Park of an Atlantic rainforest. We also evaluated the influence of rainfall, water temperature and fish size on niche width and niche overlap. Sampling was conducted monthly throughout one year in the Ribeirão Grande stream, southeastern Brazil. Diet consisted of 31 food items with equal contribution of allochthonous and autochthonous items. Females were larger than males, and the mean sizes at first maturation were 4.44 cm and 3.92 cm, respectively. Based on 212 pairs of mature ovaries, the number of oocytes per female ranged from 538 to 6,727 (mean = 2,688.7). Niche width and niche overlap were not related to rainfall nor water temperature and only niche width increased with fish size, suggesting that as fish grow, more items are included in diet. Our results suggested that A. intermedius fit as a typical opportunistic strategist which may explain the prevalence of this species in several isolated headwater basins of vegetated Atlantic forested streams where food resources are abundant and distributed throughout the year.

Sensitivity of a Cumulus Parameterization Scheme to Precipitation Production Representation and Its Impact on a Heavy Rain Event over Korea

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

Han, Ji-Young; Hong, Song-You; Sunny Lim, Kyo-Sun

The sensitivity of a cumulus parameterization scheme (CPS) to a representation of precipitation production is examined. To do this, the parameter that determines the fraction of cloud condensate converted to precipitation in the simplified Arakawa–Schubert (SAS) convection scheme is modified following the results from a cloud-resolving simulation. While the original conversion parameter is assumed to be constant, the revised parameter includes a temperature dependency above the freezing level, whichleadstolessproductionoffrozenprecipitating condensate with height. The revised CPS has been evaluated for a heavy rainfall event over Korea as well as medium-range forecasts using the Global/Regional Integrated Model system (GRIMs). The inefficient conversionmore » of cloud condensate to convective precipitation at colder temperatures generally leads to a decrease in pre-cipitation, especially in the category of heavy rainfall. The resultant increase of detrained moisture induces moistening and cooling at the top of clouds. A statistical evaluation of the medium-range forecasts with the revised precipitation conversion parameter shows an overall improvement of the forecast skill in precipitation and large-scale fields, indicating importance of more realistic representation of microphysical processes in CPSs.« less

Validation of crowdsourced automatic rain gauge measurements in Amsterdam

NASA Astrophysics Data System (ADS)

de Vos, Lotte; Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

2016-04-01

The increasing number of privately owned weather stations and the facilitating role the internet to make this data publicly available, has led to several online platforms that collect and visualize crowdsourced weather data. This has resulted in ever increasing freely available datasets of weather measurements generated by amateur weather enthusiasts. Because of the lack of quality control and the frequent absence of metadata, these measurements are often considered as unreliable. Given the often large variability of weather variables in space and time, and the generally low number of official weather stations, this growing quantity of crowdsourced data may become an important additional source of information. Amateur weather observations have become more frequent over the past decade due to weather stations becoming more user-friendly and affordable. The variables measured by these weather stations are temperature, pressure and dew point, and in some cases wind and rainfall. Meteorological data from crowdsourced automatic weather stations in cities have primarily been used to examine the urban heat island effect. Thus far, these studies have focused on the comparison of the crowdsourced station temperature measurements with a nearby WMO-standard weather station, which is often located in a rural area or the outskirts of a city, generally not being representative of the city center. Instead of temperature, the rainfall measurements by the stations are examined. This research focuses on the combined ability of a large number of privately owned weather stations in an urban setting to correctly monitor rainfall. A set of 64 automatic weather stations distributed over Amsterdam (The Netherlands) that have at least 3 months of precipitation measurement during one year are evaluated. Precipitation measurements from stations are compared to a merged radar-gauge precipitation product. Disregarding sudden jumps in station measured precipitation, the accumulative rainfall over time in most stations showed an underestimation of rainfall compared to the accumulative values found in the corresponding radar pixel of the reference. Special consideration is given to the identification of faulty measurements without the need to obtain additional meta-data, such as setup and surroundings. This validation will show the potential of crowdsourced automatic weather stations for future urban rainfall monitoring.

Input Uncertainty and its Implications on Parameter Assessment in Hydrologic and Hydroclimatic Modelling Studies

NASA Astrophysics Data System (ADS)

Chowdhury, S.; Sharma, A.

2005-12-01

Hydrological model inputs are often derived from measurements at point locations taken at discrete time steps. The nature of uncertainty associated with such inputs is thus a function of the quality and number of measurements available in time. A change in these characteristics (such as a change in the number of rain-gauge inputs used to derive spatially averaged rainfall) results in inhomogeneity in the associated distributional profile. Ignoring such uncertainty can lead to models that aim to simulate based on the observed input variable instead of the true measurement, resulting in a biased representation of the underlying system dynamics as well as an increase in both bias and the predictive uncertainty in simulations. This is especially true of cases where the nature of uncertainty likely in the future is significantly different to that in the past. Possible examples include situations where the accuracy of the catchment averaged rainfall has increased substantially due to an increase in the rain-gauge density, or accuracy of climatic observations (such as sea surface temperatures) increased due to the use of more accurate remote sensing technologies. We introduce here a method to ascertain the true value of parameters in the presence of additive uncertainty in model inputs. This method, known as SIMulation EXtrapolation (SIMEX, [Cook, 1994]) operates on the basis of an empirical relationship between parameters and the level of additive input noise (or uncertainty). The method starts with generating a series of alternate realisations of model inputs by artificially adding white noise in increasing multiples of the known error variance. The alternate realisations lead to alternate sets of parameters that are increasingly biased with respect to the truth due to the increased variability in the inputs. Once several such realisations have been drawn, one is able to formulate an empirical relationship between the parameter values and the level of additive noise present. SIMEX is based on theory that the trend in alternate parameters can be extrapolated back to the notional error free zone. We illustrate the utility of SIMEX in a synthetic rainfall-runoff modelling scenario and an application to study the dependence of uncertain distributed sea surface temperature anomalies with an indicator of the El Nino Southern Oscillation, the Southern Oscillation Index (SOI). The errors in rainfall data and its affect is explored using Sacramento rainfall runoff model. The rainfall uncertainty is assumed to be multiplicative and temporally invariant. The model used to relate the sea surface temperature anomalies (SSTA) to the SOI is assumed to be of a linear form. The nature of uncertainty in the SSTA is additive and varies with time. The SIMEX framework allows assessment of the relationship between the error free inputs and response. Cook, J.R., Stefanski, L. A., Simulation-Extrapolation Estimation in Parametric Measurement Error Models, Journal of the American Statistical Association, 89 (428), 1314-1328, 1994.

Elements of a predictive model for determining beach closures on a real time basis: the case of 63rd Street Beach Chicago

USGS Publications Warehouse

Olyphant, Greg A.; Whitman, Richard L.

2004-01-01

Data on hydrometeorological conditions and E. coli concentration were simultaneously collected on 57 occasions during the summer of 2000 at 63rd Street Beach, Chicago, Illinois. The data were used to identify and calibrate a statistical regression model aimed at predicting when the bacterial concentration of the beach water was above or below the level considered safe for full body contact. A wide range of hydrological, meteorological, and water quality variables were evaluated as possible predictive variables. These included wind speed and direction, incoming solar radiation (insolation), various time frames of rainfall, air temperature, lake stage and wave height, and water temperature, specific conductance, dissolved oxygen, pH, and turbidity. The best-fit model combined real-time measurements of wind direction and speed (onshore component of resultant wind vector), rainfall, insolation, lake stage, water temperature and turbidity to predict the geometric mean E.coliconcentration in the swimming zone of the beach. The model, which contained both additive and multiplicative (interaction) terms, accounted for 71% of the observed variability in the log E. coliconcentrations. A comparison between model predictions of when the beach should be closed and when the actualbacterial concentrations were above or below the 235 cfu 100 ml-1 threshold value, indicated that the model accurately predicted openingsversus closures 88% of the time.

Rainfall and temperatures changes have confounding impacts on Phytophthora cinnamomi occurrence risk in the southwestern USA under climate change scenarios.

PubMed

Thompson, Sally E; Levin, Simon; Rodriguez-Iturbe, Ignacio

2014-04-01

Global change will simultaneously impact many aspects of climate, with the potential to exacerbate the risks posed by plant pathogens to agriculture and the natural environment; yet, most studies that explore climate impacts on plant pathogen ranges consider individual climatic factors separately. In this study, we adopt a stochastic modeling approach to address multiple pathways by which climate can constrain the range of the generalist plant pathogen Phytophthora cinnamomi (Pc): through changing winter soil temperatures affecting pathogen survival; spring soil temperatures and thus pathogen metabolic rates; and changing spring soil moisture conditions and thus pathogen growth rates through host root systems. We apply this model to the southwestern USA for contemporary and plausible future climate scenarios and evaluate the changes in the potential range of Pc. The results indicate that the plausible range of this pathogen in the southwestern USA extends over approximately 200,000 km(2) under contemporary conditions. While warming temperatures as projected by the IPCC A2 and B1 emissions scenarios greatly expand the range over which the pathogen can survive winter, projected reductions in spring rainfall reduce its feasible habitat, leading to spatially complex patterns of changing risk. The study demonstrates that temperature and rainfall changes associated with possible climate futures in the southwestern USA have confounding impacts on the range of Pc, suggesting that projections of future pathogen dynamics and ranges should account for multiple pathways of climate-pathogen interaction. © 2014 John Wiley & Sons Ltd.

Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China.

PubMed

Lin, Xiao-Sheng; Tang, Jie; Li, Zhao-Yang; Li, Hai-Yi

2016-01-01

Liao River basin in Jilin Province is the place of origin of the Dongliao River. This study gives a comprehensive analysis of the vegetation coverage in the region and provides a potential theoretical basis for ecological restoration. The seasonal variation of vegetation greenness and dynamics based on the Normalized Difference Vegetation Index (NDVI) in major land cover types in the region was studied. Analyzing the relationship NDVI, temperature and rainfall, we derived a set of predictor variables from 2001 to 2012 using the MODIS Terra level 1 Product (MOD02QKM). The results showed a general increasing trend in NDVI value in the region, while 34.63 % of the region showed degradation. NDVI values begin to rise from April when plants are regreening and they drop in September when temperature are decreasing and the leaves are falling in the study area and temperature was found decreasing during the period of 2001-2012 while rainfall showed an increasing trend. This model could be used to observe the change in vegetation greenness and the dynamic effects of temperature and rainfall. This study provided important data for the environmental protection of the basin area. And we hope to provide scientific analysis for controlling water and soil erosion, maintaining the sustainable productivity of land resources, enhancing the treatment of water pollution and stimulating the virtuous cycle of the ecological system.

Impact of climate change on hydrological extremes in Dobrogea region, Romania

NASA Astrophysics Data System (ADS)

Buta, Constantin; Maftei, Carmen

2015-04-01

Over time, Dobrogea territory has faced with fluctuations more or less severe in terms of basic parameters such as temperature, precipitations and annual discharges of rivers. It is highlighted the trend of aridity in the area, because of the fact that Dobrogea receives small amounts of water, ranging between 200-450 mm/year, with annual average temperatures lying around and above the average of 11°C. This fact is also proceeding from the many studies realized by other researchers. For this area there are also characteristic torrents (form of rainfall during the summer), the storms and floods accompanying these torrents of water on the narrow valleys, often intermittent, sometimes causing significant damage and even fatalities. Torrential rainfalls and flash floods are sometimes very strong and produce catastrophic damages, as happened at Constanta (in 2001), at Tulcea (in 13.07.2004 and in 29.08.2004), at Tuzla, Pantelimon, Agigea and others. At the opposite pole of the sporadic excess rainfall is drought, which is the largest meteorological phenomenon (both in time and in space) and the most obvious in Dobrogea climate. Drought represents the main argument of semi aridity of this region and the most visible image component which is observed by the inhabitants of this environment. Correlation and study of hydro-meteorological extremes is performed using indices that take into account meteorological and hydrological parameters such as precipitations, temperature, discharges of rivers etc. Hydro-meteorological indices used for this study are: Angot rainfall index; Peguy Climograms; de Martonne drought index; Thornthwaite index Moduli coefficients and Deciles. According to the studied indices, for the accomplishment of this present paper, we can say that Dobrogea is among the driest regions in the country. History of drought in Romania includes many dry years, of which are mentioned: 1894, 1888, 1904, 1918, 1934, 1945, but the droughts years with greater durations, more extensive in territory and severe, were those of 1946 and 2000, which affected Dobrogea region. According to this study and analysis carried out for the period 1965-2005 (regarding of temperatures and precipitations) at eight stations in the Dobrogea region, and for the period 1965 to 2011 (regarding the discharges of rivers) there can be mentioned several dry years, but between them some of them have proved extremely dry, such as the range of years 1973 - 1976, 1980 - 1983, 1986 - 1987 and 2000, and the years with risk by excess of water were: 1966, 1969, 1988, 1997, 2004 and 2005.

Regional rainfall thresholds for landslide occurrence using a centenary database

NASA Astrophysics Data System (ADS)

Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Quaresma, Ivânia

2017-04-01

Rainfall is one of the most important triggering factors for landslides occurrence worldwide. The relation between rainfall and landslide occurrence is complex and some approaches have been focus on the rainfall thresholds identification, i.e., rainfall critical values that when exceeded can initiate landslide activity. In line with these approaches, this work proposes and validates rainfall thresholds for the Lisbon region (Portugal), using a centenary landslide database associated with a centenary daily rainfall database. The main objectives of the work are the following: i) to compute antecedent rainfall thresholds using linear and potential regression; ii) to define lower limit and upper limit rainfall thresholds; iii) to estimate the probability of critical rainfall conditions associated with landslide events; and iv) to assess the thresholds performance using receiver operating characteristic (ROC) metrics. In this study we consider the DISASTER database, which lists landslides that caused fatalities, injuries, missing people, evacuated and homeless people occurred in Portugal from 1865 to 2010. The DISASTER database was carried out exploring several Portuguese daily and weekly newspapers. Using the same newspaper sources, the DISASTER database was recently updated to include also the landslides that did not caused any human damage, which were also considered for this study. The daily rainfall data were collected at the Lisboa-Geofísico meteorological station. This station was selected considering the quality and completeness of the rainfall data, with records that started in 1864. The methodology adopted included the computation, for each landslide event, of the cumulative antecedent rainfall for different durations (1 to 90 consecutive days). In a second step, for each combination of rainfall quantity-duration, the return period was estimated using the Gumbel probability distribution. The pair (quantity-duration) with the highest return period was considered as the critical rainfall combination responsible for triggering the landslide event. Only events whose critical rainfall combinations have a return period above 3 years were included. This criterion reduces the likelihood of been included events whose triggering factor was other than rainfall. The rainfall quantity-duration threshold for the Lisbon region was firstly defined using the linear and potential regression. Considering that this threshold allow the existence of false negatives (i.e. events below the threshold) it was also identified the lower limit and upper limit rainfall thresholds. These limits were defined empirically by establishing the quantity-durations combinations bellow which no landslides were recorded (lower limit) and the quantity-durations combinations above which only landslides were recorded without any false positive occurrence (upper limit). The zone between the lower limit and upper limit rainfall thresholds was analysed using a probabilistic approach, defining the uncertainties of each rainfall critical conditions in the triggering of landslides. Finally, the performances of the thresholds obtained in this study were assessed using ROC metrics. This work was supported by the project FORLAND - Hydrogeomorphologic risk in Portugal: driving forces and application for land use planning [grant number PTDC/ATPGEO/1660/2014] funded by the Portuguese Foundation for Science and Technology (FCT), Portugal. Sérgio Cruz Oliveira is a post-doc fellow of the FCT [grant number SFRH/BPD/85827/2012].

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

NASA Astrophysics Data System (ADS)

Murphy, Conor; Burt, Tim P.; Broderick, Ciaran; Duffy, Catriona; Macdonald, Neil; Matthews, Tom; McCarthy, Mark P.; Mullan, Donal; Noone, Simon; Ryan, Ciara; Thorne, Peter; Walsh, Seamus; Wilby, Robert L.

2017-04-01

This paper derives a continuous 305-year monthly rainfall series for the Island of Ireland (IoI) for the period 1711-2016. Two key data sources are employed: i) a previously unpublished UK Met Office Note which compiled annual rainfall anomalies and corresponding monthly per mille amounts from weather diaries and early observational records for the period 1711-1977; and ii) a long-term, homogenised monthly IoI rainfall series for the period 1850-2016. Using estimates of long-term average precipitation sampled from the quality assured series, the full record is reconstituted and insights drawn regarding notable periods and the range of climate variability and change experienced. Consistency with other long records for the region is examined, including: the England and Wales Precipitation series (EWP; 1766-2016); the early EWP Glasspoole series (1716-1765) and the Central England Temperature series (CET; 1711-2016). Strong correspondence between all records is noted from 1780 onwards. While disparities are evident between the early EWP and Ireland series, the latter shows strong decadal consistency with CET throughout the record. In addition, independent, early observations from Cork and Dublin, along with available documentary sources, corroborate the derived series and add confidence to our reconstruction. The new IoI rainfall record reveals that the wettest decades occurred in the early 18th Century, despite the fact that IoI has experienced a long-term winter wetting trend consistent with climate model projections. These exceptionally wet winters of the 1720s and 1730s were concurrent with almost unprecedented warmth in the CET, glacial advance throughout Scandinavia, and glacial retreat in West Greenland, consistent with a wintertime NAO-type forcing. Our study therefore demonstrates the value of long-term observational records for providing insight to the natural climate variability of the North Atlantic region.

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.

Precipitation-Runoff Modeling System (PRMS) and Streamflow Response to Spatially Distributed Precipitation in Two Large Watersheds in Northern California

NASA Astrophysics Data System (ADS)

Dhakal, A. S.; Adera, S.; Niswonger, R. G.; Gardner, M.

2016-12-01

The ability of the Precipitation-Runoff Modeling System (PRMS) to predict peak intensity, peak timing, base flow, and volume of streamflow was examined in Arroyo Hondo (180 km2) and Upper Alameda Creek (85 km2), two sub-watersheds of the Alameda Creek watershed in Northern California. Rainfall-runoff volume ratios vary widely, and can exceed 0.85 during mid-winter flashy rainstorm events. Due to dry antecedent soil moisture conditions, the first storms of the hydrologic year often produce smaller rainfall-runoff volume ratios. Runoff response in this watershed is highly hysteretic; large precipitation events are required to generate runoff following a 4-week period without precipitation. After about 150 mm of cumulative rainfall, streamflow responds quickly to subsequent storms, with variations depending on rainstorm intensity. Inputs to PRMS included precipitation, temperature, topography, vegetation, soils, and land cover data. The data was prepared for input into PRMS using a suite of data processing Python scripts written by the Desert Research Institute and U.S. Geological Survey. PRMS was calibrated by comparing simulated streamflow to measured streamflow at a daily time step during the period 1995 - 2014. The PRMS model is being used to better understand the different patterns of streamflow observed in the Alameda Creek watershed. Although Arroyo Hondo receives more rainfall than Upper Alameda Creek, it is not clear whether the differences in streamflow patterns are a result of differences in rainfall or other variables, such as geology, slope and aspect. We investigate the ability of PRMS to simulate daily streamflow in the two sub-watersheds for a variety of antecedent soil moisture conditions and rainfall intensities. After successful simulation of watershed runoff processes, the model will be expanded using GSFLOW to simulate integrated surface water and groundwater to support water resources planning and management in the Alameda Creek watershed.

Interannual rainfall variability and SOM-based circulation classification

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

2018-01-01

Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained variance, is consistent with the general understanding of the dominant processes and atmospheric variables that affect rainfall variability at a particular location.

Prognostic Aspects of Sub-seasonal Rainfall Characteristics using the Outputs of General Circulation Model: An Application of Statistical Downscaling and Temporal Disaggregation

NASA Astrophysics Data System (ADS)

Singh, A.; Mohanty, U. C.; Ghosh, K.

2015-12-01

Most regions of India experience varied rainfall duration during the southwest monsoon, changes in which exhibit major impact not only agriculture, but also other sectors like hydrology, agriculture, food and fodder storage etc. In addition, changes in sub-seasonal rainfall characteristics highly impact the rice production. As part of the endeavor seasonal climate outlook, as well as information for weather within climate may be helpful for advance planning and risk management in agriculture. The General Circulation Model (GCM) provide an alternative to gather information for weather within climate but variability is very low in comparison to observation. On the other hand, the spatial resolution of GCM predicted rainfall is not found at the observed station/grid point. To tackle the problem, initially a statistical downscaling over 19 station of Odisha state is undertaken using the atmospheric parameters predicted by a GCM (NCEP-CFSv2). For the purpose, an extended domain is taken for analyzing the significant zone for the atmospheric parameters like zonal wind at 850hPa, Sea Surface Temperature (SST), geopotential height. A statistical model using the pattern projection method is further developed based on empirical orthogonal function. The downscaled rainfall is found better in association with station observation in comparison to raw GCM prediction in view of deterministic and probabilistic skill measure. Further, the sub-seasonal and seasonal forecast from the GCMs can be used at different time steps for risk management. Therefore, downscaled seasonal/monthly rainfall is further converted to sub-seasonal/daily time scale using a non-homogeneous markov model. The simulated weather sequences are further compared with the observed sequence in view of categorical rainfall events. The outcomes suggest that the rainfall amount are overestimated for excess rainfall and henceforth larger excess rainfall events can be realized. The skill for prediction of rainfall events corresponding to lower thresholds is found higher. A detail discussion regarding skill of spatial downscale rainfall at observed stations and its further representation of sub-seasonal characteristics (spells, less rainfall, heavy rainfall, and moderate rainfall events) of rainfall for disaggregated outputs will be presented.

Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

2016-03-01

Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

Study on Rainfall Forecasting by Using Weather Satellite Imagery in a Small Watershed Located at Mountainous Area of Central Taiwan

NASA Astrophysics Data System (ADS)

Wei, C.; Cheng, K. S.

Using meteorological radar and satellite imagery had become an efficient tool for rainfall forecasting However few studies were aimed to predict quantitative rainfall in small watersheds for flood forecasting by using remote sensing data Due to the terrain shelter and ground clutter effect of Central Mountain Ridges the application of meteorological radar data was limited in mountainous areas of central Taiwan This study devises a new scheme to predict rainfall of a small upstream watershed by combing GOES-9 geostationary weather satellite imagery and ground rainfall records which can be applied for local quantitative rainfall forecasting during periods of typhoon and heavy rainfall Imagery of two typhoon events in 2004 and five correspondent ground raingauges records of Chitou Forest Recreational Area which is located in upstream region of Bei-Shi river were analyzed in this study The watershed accounts for 12 7 square kilometers and altitudes ranging from 1000 m to 1800 m Basin-wide Average Rainfall BAR in study area were estimated by block kriging Cloud Top Temperature CTT from satellite imagery and ground hourly rainfall records were medium correlated The regression coefficient ranges from 0 5 to 0 7 and the value decreases as the altitude of the gauge site increases The regression coefficient of CCT and next 2 to 6 hour accumulated BAR decrease as the time scale increases The rainfall forecasting for BAR were analyzed by Kalman Filtering Technique The correlation coefficient and average hourly deviates between estimated and observed value of BAR for

Rainfall prediction with backpropagation method

NASA Astrophysics Data System (ADS)

Wahyuni, E. G.; Fauzan, L. M. F.; Abriyani, F.; Muchlis, N. F.; Ulfa, M.

2018-03-01

Rainfall is an important factor in many fields, such as aviation and agriculture. Although it has been assisted by technology but the accuracy can not reach 100% and there is still the possibility of error. Though current rainfall prediction information is needed in various fields, such as agriculture and aviation fields. In the field of agriculture, to obtain abundant and quality yields, farmers are very dependent on weather conditions, especially rainfall. Rainfall is one of the factors that affect the safety of aircraft. To overcome the problems above, then it’s required a system that can accurately predict rainfall. In predicting rainfall, artificial neural network modeling is applied in this research. The method used in modeling this artificial neural network is backpropagation method. Backpropagation methods can result in better performance in repetitive exercises. This means that the weight of the ANN interconnection can approach the weight it should be. Another advantage of this method is the ability in the learning process adaptively and multilayer owned on this method there is a process of weight changes so as to minimize error (fault tolerance). Therefore, this method can guarantee good system resilience and consistently work well. The network is designed using 4 input variables, namely air temperature, air humidity, wind speed, and sunshine duration and 3 output variables ie low rainfall, medium rainfall, and high rainfall. Based on the research that has been done, the network can be used properly, as evidenced by the results of the prediction of the system precipitation is the same as the results of manual calculations.

Environmental correlates of breeding in the Crested Caracara (Caracara cheriway)

USGS Publications Warehouse

Morrison, J.L.; Pias, Kyle E.; Cohen, J.B.; Catlin, D.H.

2009-01-01

We evaluated the influence of weather on reproduction of the Crested Caracara (Caracara cheriway) in an agricultural landscape in south-central Florida. We used a mixed logistic-regression modeling approach within an information-theoretic framework to examine the influence of total rainfall, rainfall frequency, and temperature on the number of breeding pairs, timing of breeding, nest success, and productivity of Crested Caracaras during 1994–2000. The best models indicated an influence of rainfall frequency and laying period on reproduction. More individuals nested and more pairs nested earlier during years with more frequent rainfall in late summer and early fall. Pairs that nested later in each breeding season had smaller clutches, lower nest success and productivity, and higher probability of nest failure. More frequent rainfall during early spring months that are usually characterized by water deficit (March–May), more frequent rainfall during the fall drawdown period (September–November), and a shorter winter dry period showed some association with higher probability of brood reduction and lower nest success. The proportion of nests that failed was higher in “wet” years, when total rainfall during the breeding season (September–April) was >10% above the 20-year average. Rainfall may influence reproduction in Crested Caracaras indirectly through food resources. As total rainfall increased during February–April, when most pairs are feeding nestlings or dependent fledglings, the proportion of drawdown-dependent species (those that become available as rainfall decreases and wetlands become isolated and shallow) in the diet of Crested Caracaras declined, which may indicate reduced availability of foraging habitat for this primarily terrestrial raptor.

High ambient temperature and risk of intestinal obstruction in cystic fibrosis.

PubMed

Ooi, Chee Y; Jeyaruban, Christina; Lau, Jasmine; Katz, Tamarah; Matson, Angela; Bell, Scott C; Adams, Susan E; Krishnan, Usha

2016-04-01

Distal intestinal obstruction syndrome (DIOS) and constipation in cystic fibrosis (CF) are conditions associated with impaction and/or obstruction by abnormally viscid mucofaecal material within the intestinal lumen. Dehydration has been proposed as a risk factor for DIOS and constipation in CF. The study primarily aimed to determine whether warmer ambient temperature and lower rainfall are risk factors for DIOS and constipation in CF. Hospitalisations for DIOS (incomplete or complete) and/or constipation were retrospectively identified (2000-2012). Genotype, phenotype, temperatures and rainfall data (for the week preceding and season of hospitalisation) were collected. Twenty-seven DIOS (59.3% incomplete; 40.7% complete) and 44 constipation admissions were identified. All admitted patients were pancreatic insufficient. Meconium ileus was significantly more likely in DIOS than constipation (64.7% vs. 33.3%; P = 0.038) and in complete than incomplete DIOS (100% vs. 57.1%; P = 0.04). The maximum temperature of the week before DIOS admission (mean (standard deviation) = 28.0 (5.8) °C) was significantly higher than the maximum temperature of the season of admission (25.2 (3.4) °C; P = 0.002). Similarly, the maximum temperature of the week before hospitalisation for constipation (mean (standard deviation) = 27.9 (6.3) °C) was significantly warmer compared with the season of admission (24.0 (4.1) °C; P < 0.0001). There were no significant differences between levels of rainfall during the week before hospitalisation and the season of admission for both DIOS and constipation. Relatively high ambient temperature may play a role in the pathogenesis of DIOS and constipation in CF. © 2016 The Authors Journal of Paediatrics and Child Health © 2016 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Rainfall Intensity and Frequency Explain Production Basis Risk in Cumulative Rain Index Insurance

NASA Astrophysics Data System (ADS)

Muneepeerakul, Chitsomanus P.; Muneepeerakul, Rachata; Huffaker, Ray G.

2017-12-01

With minimal moral hazard and adverse selection, weather index insurance promises financial resilience to farmers struck by harsh weather conditions through swift compensation at affordable premium. Despite these advantages, the very nature of indexing gives rise to production basis risk as the selected weather indexes do not sufficiently correspond to actual damages. To address this problem, we develop a stochastic yield model, built upon a stochastic soil moisture model driven by marked Poisson rainfall. Our analysis shows that even under similar temperature and rainfall amount yields can differ significantly; this was empirically supported by a 2-year field experiment in which rain-fed maize was grown under very similar total rainfall. Here, the year with more intense, less-frequent rainfall produces a better yield—a rare counter evidence to most climate change projections. Through a stochastic yield model, we demonstrate the crucial roles of rainfall intensity and frequency in determining the yield. Importantly, the model allows us to compute rainfall pattern-related basis risk inherent in cumulative rain index insurance. The model results and a case study herein clearly show that total rainfall is a poor indicator of yield, imposing unnecessary production basis risk on farmers and false-positive payouts on insurers. Incorporating rainfall intensity and frequency in the design of rain index insurance can offer farmers better protection, while maintaining the attractive features of the weather index insurance and thus fulfilling its promise of financial resilience.

The effects of more extreme rainfall patterns on nitrogen leaching from a field crop system in the upper Midwest, USA

NASA Astrophysics Data System (ADS)

Hess, L.; Hinckley, E. L. S.; Robertson, G. P.; Matson, P. A.

2016-12-01

As global surface temperatures rise, the proportion of total rainfall that falls in heavy storm events is increasing in many areas, in particular the US Midwest, a major agricultural region. These changes in rainfall patterns may have consequences for ecosystem nutrient losses, especially from agricultural ecosystems. We conducted a multi-year rainfall manipulation experiment to examine how more extreme rainfall patterns affect nitrogen (N) leaching from row-crop ecosystems in the upper Midwest, and to what extent tillage may moderate these effects. 5x5m rainout shelters were installed in April 2015 to impose control and extreme rainfall patterns in replicated plots under conventional tillage and no-till management at the Kellogg Biological Station LTER site. Plots exposed to the control rainfall treatment received ambient rainfall, and those exposed to the extreme rainfall treatment received the same total amount of water but applied once every 2 weeks, to simulate larger, less frequent storms. N leaching was calculated as the product of measured soil water N concentrations and modeled soil water drainage at 1.2m depth using HYDRUS-1D. Based on data to date, more N has been leached from both tilled and no-till soils exposed to the extreme rainfall treatment compared to the control rainfall treatment. Results thus far suggest that greater soil water drainage is a primary driver of this increase, and changes in within-system nitrogen cycling - such as net N mineralization and crop N uptake - may also play a role. The experiment is ongoing, and our results so far suggest that intensifying precipitation patterns may exacerbate N leaching from agricultural soils, with potentially negative consequences for receiving ground- and surface waters, as well as for farmers.

Indian summer monsoon variability forecasts in the North American multimodel ensemble

NASA Astrophysics Data System (ADS)

Singh, Bohar; Cash, Ben; Kinter, James L., III

2018-04-01

The representation of the seasonal mean and interannual variability of the Indian summer monsoon rainfall (ISMR) in nine global ocean-atmosphere coupled models that participated in the North American Multimodal Ensemble (NMME) phase 1 (NMME:1), and in nine global ocean-atmosphere coupled models participating in the NMME phase 2 (NMME:2) from 1982-2009, is evaluated over the Indo-Pacific domain with May initial conditions. The multi-model ensemble (MME) represents the Indian monsoon rainfall with modest skill and systematic biases. There is no significant improvement in the seasonal forecast skill or interannual variability of ISMR in NMME:2 as compared to NMME:1. The NMME skillfully predicts seasonal mean sea surface temperature (SST) and some of the teleconnections with seasonal mean rainfall. However, the SST-rainfall teleconnections are stronger in the NMME than observed. The NMME is not able to capture the extremes of seasonal mean rainfall and the simulated Indian Ocean-monsoon teleconnections are opposite to what are observed.

Ajustement statistique des simulations climatiques : l'exemple des précipitations saisonnières de l'Amérique tropicaleStatistical adjustment of simulated climate: example of seasonal rainfall of tropical America.

NASA Astrophysics Data System (ADS)

Moron, Vincent; Navarra, Antonio

2000-05-01

This study presents the skill of the seasonal rainfall of tropical America from an ensemble of three 34-year general circulation model (ECHAM 4) simulations forced with observed sea surface temperature between 1961 and 1994. The skill gives a first idea of the amount of potential predictability if the sea surface temperatures are perfectly known some time in advance. We use statistical post-processing based on the leading modes (extracted from Singular Value Decomposition of the covariance matrix between observed and simulated rainfall fields) to improve the raw skill obtained by simple comparison between observations and simulations. It is shown that 36-55 % of the observed seasonal variability is explained by the simulations on a regional basis. Skill is greatest for Brazilian Nordeste (March-May), but also for northern South America or the Caribbean basin in June-September or northern Amazonia in September-November for example.

Effects of Hydrological Parameters on Palm Oil Fresh Fruit Bunch Yield)

NASA Astrophysics Data System (ADS)

Nda, M.; Adnan, M. S.; Suhadak, M. A.; Zakaria, M. S.; Lopa, R. T.

2018-04-01

Climate change effects and variability have been studied by many researchers in diverse geophysical fields. Malaysia produces large volume of palm oil, the effects of climate change on hydrological parameters (rainfall and precipitation) could have adverse effects on palm oil fresh fruit bunch (FFB) production with implications at both local and international market. It is important to understand the effects of climate change on crop yield to adopt new cultivation techniques and guaranteeing food security globally. Based on this background, the paper’s objective is to investigate the effects of rainfall and temperature pattern on crop yield (FFB) within five years period (2013 - 2017) at Batu Pahat District. The Man - Kendall rank technique (trend test) and statistical analyses (correlation and regression) were applied to the dataset used for the study. The results reveal that there are variabilities in rainfall and temperature from one month to the other and the statistical analysis reveals that the hydrological parameters have an insignificant effect on crop yield.

On the Relative Influences of Different Ocean Basin Sea Surface Temperature Anomalies on Southern African Rainfall in 20th and 21st Century GCM Simulations

NASA Astrophysics Data System (ADS)

Lickley, M.; Solomon, S.

2017-12-01

Southern Africa rainfall (SAR) is generally projected to decrease during the 21st century as a result of climate change, though there is some disagreement regarding the location and magnitude of this reduction in General Circulation Models (GCMs). Here we examine the robustness of the rainfall response to sea surface temperature (SST) anomalies. Previous work argues that warmer SSTs in the Indian Ocean suppress SAR. Other studies argue that El Niños lead to suppressed SAR. We examine the SAR response to SST anomalies in the Indian Ocean, Atlantic Ocean and ENSO 3.4 region both in observations and in two large ensembles of GCMs run over the 20th and 21st century. We find that ENSO SSTs are most correlated with SAR, while correlations between SAR and the Indian Ocean are dominated by their respective responses to ENSO. This relationship appears to persist under a warming background state.

The Tropical Rainfall Measuring (TRMM) - What Have We Learned and What Does the Future Hold?

NASA Technical Reports Server (NTRS)

Kummerow, C.; Hong, Y.; Olsen, W. S.

2000-01-01

Rainfall is important in the hydrological cycle and to the lives and welfare of humans. In addition to being a life-giving resource, rainfall processes also plays a crucial role in the dynamics of the global atmospheric circulation. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. It varies greatly in space and time. The rain-producing cloud systems may last several hours or days. Their dimensions range from 10 km to several hundred km. This makes it difficult to incorporate rainfall directly large-scale weather and climate models. Until the end of 1997, precipitation in the global tropics was not known to within a factor of two. Regarding "global warming", the various large-scale models differed among themselves in the predicted magnitude of the warming and in the expected regional effects of these temperature and moisture changes. The Tropical Rainfall Measuring Mission (TRMM) satellite has yielded important interim results related to rainfall observations, data assimilation and model forecast skills when rainfall data is assimilated. This talk will summarize where the TRMM science team is with regards to answering some of these important scientific challenges, as well as discuss the future Global Precipitation Mission which will provide 3 hourly rainfall coverage and offers some unique collaborative potential for NOAA and NASA.

Daily Rainfall Simulation Using Climate Variables and Nonhomogeneous Hidden Markov Model

NASA Astrophysics Data System (ADS)

Jung, J.; Kim, H. S.; Joo, H. J.; Han, D.

2017-12-01

Markov chain is an easy method to handle when we compare it with other ones for the rainfall simulation. However, it also has limitations in reflecting seasonal variability of rainfall or change on rainfall patterns caused by climate change. This study applied a Nonhomogeneous Hidden Markov Model(NHMM) to consider these problems. The NHMM compared with a Hidden Markov Model(HMM) for the evaluation of a goodness of the model. First, we chose Gum river basin in Korea to apply the models and collected daily rainfall data from the stations. Also, the climate variables of geopotential height, temperature, zonal wind, and meridional wind date were collected from NCEP/NCAR reanalysis data to consider external factors affecting the rainfall event. We conducted a correlation analysis between rainfall and climate variables then developed a linear regression equation using the climate variables which have high correlation with rainfall. The monthly rainfall was obtained by the regression equation and it became input data of NHMM. Finally, the daily rainfall by NHMM was simulated and we evaluated the goodness of fit and prediction capability of NHMM by comparing with those of HMM. As a result of simulation by HMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.2076 and 10.8243/131.1304mm each. In case of NHMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.6652 and 10.5112/100.9865mm each. We could verify that the error of daily and monthly rainfall simulated by NHMM was improved by 2.89% and 22.99% compared with HMM. Therefore, it is expected that the results of the study could provide more accurate data for hydrologic analysis. Acknowledgements This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(2017R1A2B3005695)

Factors governing the total rainfall yield from continental convective clouds

NASA Technical Reports Server (NTRS)

Rosenfeld, Daniel; Gagin, Abraham

1989-01-01

Several important factors that govern the total rainfall from continental convective clouds were investigated by tracking thousands of convective cells in Israel and South Africa. The rainfall volume yield (Rvol) of the individual cells that build convective rain systems has been shown to depend mainly on the cloud-top height. There is, however, considerable variability in this relationship. The following factors that influence the Rvol were parameterized and quantitatively analyzed: (1) cloud base temperature, (2)atmospheric instability, and (3) the extent of isolation of the cell. It is also shown that a strong low level forcing increases the duration of Rvol of clouds reaching the same vertical extent.

Testing the Role of Impacts in Warming Early Mars: Comparisons Between 1-D and GCM Results

NASA Astrophysics Data System (ADS)

Steakley, K.; Kahre, M. A.; Murphy, J. R.; Haberle, R. M.; Kling, A.

2017-12-01

Comet and asteroid impacts have been explored as a potential mechanism for producing warmer and wetter conditions for early Mars and possibly contributing to valley network formation. However, criticisms have been made regarding the timing of large impacts compared to valley network activity and the ability of such impacts to induce long lasting climate changes and the appropriate amount of precipitation. We test the impact heating hypothesis for the late Noachian Mars atmosphere by revisiting the scenarios described in Segura et al. (2008, JGR Planets 113, E11007) with a 3D global climate model (GCM). Segura et al. (2008) showed with a 1-D model that impacts ranging 30-100 km in diameter could in certain cases induce months to years of above-freezing temperatures and tens of cm to meters of rainfall in atmospheres with 150-mbar, 1-bar, or 2-bar surface pressures. We impose the same initial conditions into the Ames Research Center Mars GCM with updated water cycle physics that includes bulk cloud formation, sedimentation, precipitation (liquid or snow), a Manabe moist convection scheme, and the radiative effects of both liquid and ice clouds. Initial conditions in the GCM match those described in Segura et al. (2008) as closely as possible and include a hot post-impact debris layer, a warm atmosphere, and water vapor profiles consistent with the water abundances mobilized by the impact. Scenarios with 30-, 50- and 100- km impactors in 150-mbar, 1-bar, and 2-bar surface pressure cases are explored both with and without radiatively active water clouds. Our goals are to determine how global rainfall totals and global surface temperatures from the GCM compare with the simpler 1-D Segura et al. (2008) model, to examine what rainfall patterns emerge in the GCM and how they compare to the observed valley network distribution, and to more carefully assess the role of cloud microphysics and radiative effects on the duration and intensity of post-impact climates.

Reconstructing Seasonal Range Expansion of the Tropical Butterfly, Heliconius charithonia, into Texas Using Historical Records

PubMed Central

Cardoso, Márcio Zikán

2010-01-01

While butterfly responses to climate change are well studied, detailed analyses of the seasonal dynamics of range expansion are few. Therefore, the seasonal range expansion of the butterfly Heliconius charithonia L. (Lepidoptera: Nymphalidae) was analyzed using a database of sightings and collection records dating from 1884 to 1992 from Texas. First and last sightings for each year were noted, and residency time calculated, for each collection locality. To test whether sighting dates were a consequence of distance from source (defined as the southernmost location of permanent residence), the distance between source and other locations was calculated. Additionally, consistent directional change over time of arrival dates was tested in a well-sampled area (San Antonio). Also, correlations between temperature, rainfall, and butterfly distribution were tested to determine whether butterfly sightings were influenced by climate. Both arrival date and residency interval were influenced by distance from source: butterflies arrived later and residency time was shorter at more distant locations. Butterfly occurrence was correlated with temperature but not rainfall. Residency time was also correlated with temperature but not rainfall. Since temperature follows a north-south gradient this may explain the inverse relationship between residency and distance from entry point. No long-term directional change in arrival dates was found in San Antonio. The biological meaning of these findings is discussed suggesting that naturalist notes can be a useful tool in reconstructing spatial dynamics. PMID:20672989

Atmospheric Teleconnection and Climate Variability: Affecting Rice Productivity of Bihar, India

NASA Astrophysics Data System (ADS)

Saini, A.

2017-12-01

Climate variability brought various negative results to the environment around us and area under rice crop in Bihar has also faced a lot of negative impacts due to variability in temperature and rainfall. Location of Bihar in Northern Plain of India automatically makes it prime location for agriculture and therefore variability in climatic variables brings highly sensitive results to the agricultural production (especially rice). In this study, rainfall and temperature variables are taken into consideration to investigate the impact on rice cultivated area. Change in climate variable with the passage of time is prevailing since the start of geological time scale, how the variability in climate variables has affected the major crops. Climate index of Pacific Ocean and Indian Ocean influences the seasonal weather in Bihar and therefore role of ENSO and IOD is an interesting point of inquiry. Does there exists direct relation between climate variability and area under agricultural crops? How many important variables directly signals towards the change in area under agriculture production? These entire questions are answered with respect to change in area under rice cultivation of Bihar State of India. Temperature, rainfall and ENSO are a good indicator with respect to rice cultivation in Indian subcontinent. Impact on the area under rice has been signaled through ONI, Niño3 and DMI. Increasing range of temperature in the rice productivity declining years is observed since 1990.

Potential effects of climate change on Florida's Everglades.

PubMed

Nungesser, M; Saunders, C; Coronado-Molina, C; Obeysekera, J; Johnson, J; McVoy, C; Benscoter, B

2015-04-01

Restoration efforts in Florida's Everglades focus on preserving and restoring this unique wetland's natural landscape. Because most of the Everglades is a freshwater peatland, it requires surplus rainfall to remain a peatland. Restoration plans generally assume a stable climate, yet projections of altered climate over a 50-year time horizon suggest that this assumption may be inappropriate. Using a legacy regional hydrological model, we simulated combinations of a temperature rise of 1.5 °C, a ± 10% change in rainfall, and a 0.46 m sea level rise relative to base conditions. The scenario of increased evapotranspiration and increased rainfall produced a slight increase in available water. In contrast, the more likely scenario of increased evapotranspiration and decreased rainfall lowered median water depths by 5-114 cm and shortened inundation duration periods by 5-45%. Sea level rise increased stages and inundation duration in southern Everglades National Park. These ecologically significant decreases in water depths and inundation duration periods would greatly alter current ecosystems through severe droughts, peat loss and carbon emissions, wildfires, loss of the unique ridge and slough patterns, large shifts in plant and animal communities, and increased exotic species invasions. These results suggest using adaptive restoration planning, a method that explicitly incorporates large climatic and environmental uncertainties into long-term ecosystem restoration plans, structural design, and management. Anticipated water constraints necessitate alternative approaches to restoration, including maintaining critical landscapes and facilitating transitions in others. Accommodating these uncertainties may improve the likelihood of restoration success.

Meteorological factors and risk of scrub typhus in Guangzhou, southern China, 2006–2012

PubMed Central

2014-01-01

Background Scrub typhus is becoming the most common vector born disease in Guangzhou, southern China. In this study, we aimed to examine the effect of weather patterns on the incidence of Scrub typhus in the subtropical city of Guangzhou for the period 2006–2012, and assist public health prevention and control measures. Methods Scrub typhus reported cases during the period of 2006–2012 in Guangzhou were obtained from National Notifiable Disease Report System (NNDRS). Simultaneous meteorological data including temperature, relative humidity, atmospheric pressure, sunshine, and rainfall were obtained from the documentation of the Guangzhou Meteorological Bureau. A negative binomial regression was used to identify the relationship between meteorological variables and scrub typhus. Results Annual incidence rates of scrub typhus from 2006 to 2012 were 3.25, 2.67, 3.81, 4.22, 4.41, 5.12, and 9.75 (per 100 000) respectively. Each 1°C rise in temperature corresponded to an increase of 14.98% (95% CI 13.65% to 16.33%) in the monthly number of scrub typhus cases, while a 1 hPa rise in atmospheric pressure corresponded to a decrease in the number of cases by 8.03% (95% CI −8.75% to −7.31%). Similarly, a 1 hour rise in sunshine corresponded to an increase of 0.17% or 0.54%, and a 1 millimeter rise in rainfall corresponded to an increase of 0.05% or 0.10%, in the monthly number of scrub typhus cases, depending on the variables considered in the model. Conclusion Our study provided evidence that climatic factors were associated with occurrence of scrub typhus in Guangzhou city, China. Temperature, duration of sunshine, and rainfall were positively associated with scrub typhus incidence, while atmospheric pressure was inversely associated with scrub typhus incidence. These findings should be considered in the prediction of future patterns of scrub typhus transmission. PMID:24620733

Seasonality of Human Leptospirosis in Reunion Island (Indian Ocean) and Its Association with Meteorological Data

PubMed Central

Desvars, Amélie; Jégo, Sylvaine; Chiroleu, Frédéric; Bourhy, Pascale; Cardinale, Eric; Michault, Alain

2011-01-01

Background Leptospirosis is a disease which occurs worldwide but particularly affects tropical areas. Transmission of the disease is dependent on its excretion by reservoir animals and the presence of moist environment which allows the survival of the bacteria. Methods and Findings A retrospective study was undertaken to describe seasonal patterns of human leptospirosis cases reported by the Centre National de Références des Leptospiroses (CNRL, Pasteur Institute, Paris) between 1998 and 2008, to determine if there was an association between the occurrence of diagnosed cases and rainfall, temperature and global solar radiation (GSR). Meteorological data were recorded in the town of Saint-Benoît (Météo France “Beaufonds-Miria” station), located on the windward (East) coast. Time-series analysis was used to identify the variables that best described and predicted the occurrence of cases of leptospirosis on the island. Six hundred and thirteen cases were reported during the 11-year study period, and 359 cases (58.56%) were diagnosed between February and May. A significant correlation was identified between the number of cases in a given month and the associated cumulated rainfall as well as the mean monthly temperature recorded 2 months prior to diagnosis (r = 0.28 and r = 0.23 respectively). The predictive model includes the number of cases of leptospirosis recorded 1 month prior to diagnosis (b = 0.193), the cumulated monthly rainfall recorded 2 months prior to diagnosis (b = 0.145), the average monthly temperature recorded 0 month prior to diagnosis (b = 3.836), and the average monthly GSR recorded 0 month prior to diagnosis (b = −1.293). Conclusions Leptospirosis has a seasonal distribution in Reunion Island. Meteorological data can be used to predict the occurrence of the disease and our statistical model can help to implement seasonal prevention measures. PMID:21655257

Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

NASA Astrophysics Data System (ADS)

Dakhlaoui, H.; Ruelland, D.; Tramblay, Y.; Bargaoui, Z.

2017-07-01

To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that must be fairly reliable under changing climate conditions. The aim of this study was thus to assess the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in northern Tunisia under long-term climate variability, in the light of available future climate scenarios for this region. The robustness of the models was evaluated using a differential split sample test based on a climate classification of the observation period that simultaneously accounted for precipitation and temperature conditions. The study catchments include the main hydrographical basins in northern Tunisia, which produce most of the surface water resources in the country. A 30-year period (1970-2000) was used to capture a wide range of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while model transferability was evaluated based on the Nash-Sutcliffe efficiency criterion and volume error. The three hydrological models were shown to behave similarly under climate variability. The models simulated the runoff pattern better when transferred to wetter and colder conditions than to drier and warmer ones. It was shown that their robustness became unacceptable when climate conditions involved a decrease of more than 25% in annual precipitation and an increase of more than +1.75 °C in annual mean temperatures. The reduction in model robustness may be partly due to the climate dependence of some parameters. When compared to precipitation and temperature projections in the region, the limits of transferability obtained in this study are generally respected for short and middle term. For long term projections under the most pessimistic emission gas scenarios, the limits of transferability are generally not respected, which may hamper the use of conceptual models for hydrological projections in northern Tunisia.

Space based observations: A state of the art solution for spatial monitoring tropical forested watershed productivity at regional scale in developing countries

NASA Astrophysics Data System (ADS)

Mahmud, M. R.

2014-02-01

This paper presents the simplified and operational approach of mapping the water yield in tropical watershed using space-based multi sensor remote sensing data. Two main critical hydrological rainfall variables namely rainfall and evapotranspiration are being estimated by satellite measurement and reinforce the famous Thornthwaite & Mather water balance model. The satellite rainfall and ET estimates were able to represent the actual value on the ground with accuracy under considerable conditions. The satellite derived water yield had good agreement and relation with actual streamflow. A high bias measurement may result due to; i) influence of satellite rainfall estimates during heavy storm, and ii) large uncertainties and standard deviation of MODIS temperature data product. The output of this study managed to improve the regional scale of hydrology assessment in Peninsular Malaysia.

Impact of climate variability on the transmission risk of malaria in northern Côte d'Ivoire.

PubMed

M'Bra, Richard K; Kone, Brama; Soro, Dramane P; N'krumah, Raymond T A S; Soro, Nagnin; Ndione, Jacques A; Sy, Ibrahima; Ceccato, Pietro; Ebi, Kristie L; Utzinger, Jürg; Schindler, Christian; Cissé, Guéladio

2018-01-01

Since the 1970s, the northern part of Côte d'Ivoire has experienced considerable fluctuation in its meteorology including a general decrease of rainfall and increase of temperature from 1970 to 2000, a slight increase of rainfall since 2000, a severe drought in 2004-2005 and flooding in 2006-2007. Such changing climate patterns might affect the transmission of malaria. The purpose of this study was to analyze climate and environmental parameters associated with malaria transmission in Korhogo, a city in northern Côte d'Ivoire. All data were collected over a 10-year period (2004-2013). Rainfall, temperature and Normalized Difference Vegetation Index (NDVI) were the climate and environmental variables considered. Association between these variables and clinical malaria data was determined, using negative binomial regression models. From 2004 to 2013, there was an increase in the annual average precipitation (1100.3-1376.5 mm) and the average temperature (27.2°C-27.5°C). The NDVI decreased from 0.42 to 0.40. We observed a strong seasonality in these climatic variables, which resembled the seasonality in clinical malaria. An incremental increase of 10 mm of monthly precipitation was, on average, associated with a 1% (95% Confidence interval (CI): 0.7 to 1.2%) and a 1.2% (95% CI: 0.9 to 1.5%) increase in the number of clinical malaria episodes one and two months later respectively. A 1°C increase in average monthly temperature was, on average, associated with a decline of a 3.5% (95% CI: 0.1 to 6.7%) in clinical malaria episodes. A 0.1 unit increase in monthly NDVI was associated with a 7.3% (95% CI: 0.8 to 14.1%) increase in the monthly malaria count. There was a similar increase for the preceding-month lag (6.7% (95% CI: 2.3% to 11.2%)). The study results can be used to establish a malaria early warning system in Korhogo to prepare for outbreaks of malaria, which would increase community resilience no matter the magnitude and pattern of climate change.

Tree Diameter Growth in the Dry Limestone Hills

Treesearch

C. B. Briscoe

1962-01-01

The dry limestone hill region of southwestern Puerto Rico, because of heavy, shallow soils and scant rainfall is not farmed, and is recognized as an area best suited for the growth of trees. With a mean temperature near 80°F and with rainfall averaging no more than 30 inches anually and much less during dry years, the site is adverse even for tree growth. Studies on...

Simulating land use changes in the Upper Narew catchment using the RegCM model

NASA Astrophysics Data System (ADS)

Liszewska, Malgorzata; Osuch, Marzena; Romanowicz, Renata

2010-05-01

Catchment hydrology is influenced by climate forcing in the form of precipitation, temperature, evapotranspiration and human interactions such as land use and water management practices. The difficulty in separating different causes of change in a hydrological regime results from the complexity of interactions between those three factors and catchment responses and the uncertainty and scarcity of available observations. This paper describes an application of a regional climate model to simulate the variability in precipitation, temperature, evaporation and discharge under different land use parameterizations, using the Upper Narew catchment (north-east Poland) as a case study. We use RegCM3 model, developed at the International Centre for Theoretical Physics, Trieste, Italy. The model's dynamic core is based on the hydrostatic version of the NCAR/PSU Mesoscale Model version 5 (primitive equations, hydrostatic, compressible, sigma-vertical coordinate). The physical input includes radiation transfer, large-scale and convective precipitation, Planetary Boundary Layer, biosphere. The RegCM3 model has options to interface with a variety of re-analyses and GCM boundary conditions, and can thus be used for scenario assessments. The variability of hydrological conditions in response to regional climate model projections is modeled using an integrated Data Based Mechanistic (DBM) rainfall-flow/flow-routing model of the Upper River Narew catchment. The modelling tool developed is formulated in the MATLAB-SIMULINK language. The basic system structure includes rainfall-flow and flow routing modules, based on a Stochastic Transfer Function (STF) approach combined with a nonlinear transformation of rainfall into effective rainfall. We analyse the signal resulting from modified land use in a given region. 10 month-long runs have been performed from February to November for the period of 1991-2000 based on the NCEP re-analyses. The land use data have been taken from the GLCC dataset and the Corine Land Cover programme (http://dataservice.eea.europa.eu/, GIOS, Poland). Simulations taking into account land use modifications in the catchment are compared with the reference simulations under no change in land use in the region. In the second part of the paper we discuss the application of the RegCM3 model in two climate change scenarios (SRES A2 and B1). The study is a contribution to the LUWR programme (http://luwr.igf.edu.pl).

Unexpected consequences of a drier world: evidence that delay in late summer rains biases the population sex ratio of an insect.

PubMed

Bonal, Raul; Hernández, Marisa; Espelta, Josep M; Muñoz, Alberto; Aparicio, José M

2015-09-01

The complexity of animal life histories makes it difficult to predict the consequences of climate change on their populations. In this paper, we show, for the first time, that longer summer drought episodes, such as those predicted for the dry Mediterranean region under climate change, may bias insect population sex ratio. Many Mediterranean organisms, like the weevil Curculio elephas, become active again after summer drought. This insect depends on late summer rainfall to soften the soil and allow adult emergence from their underground refuges. We found that, as in many protandric species, more C. elephas females emerged later in the season. Male emergence timing was on average earlier and also more dependent on the beginning of late summer rainfall. When these rains were delayed, the observed weevil sex ratio was biased towards females. So far, the effects of global warming on animal sex ratios has been reported for temperature-dependent sex determination in reptiles. Our results show that rainfall timing can also bias the sex ratio in an insect, and highlight the need for keeping a phenological perspective to predict the consequences of climate change. We must consider not just the magnitude of the predicted changes in temperature and rainfall but also the effects of their timing.

Unexpected consequences of a drier world: evidence that delay in late summer rains biases the population sex ratio of an insect

PubMed Central

Bonal, Raul; Hernández, Marisa; Espelta, Josep M.; Muñoz, Alberto; Aparicio, José M.

2015-01-01

The complexity of animal life histories makes it difficult to predict the consequences of climate change on their populations. In this paper, we show, for the first time, that longer summer drought episodes, such as those predicted for the dry Mediterranean region under climate change, may bias insect population sex ratio. Many Mediterranean organisms, like the weevil Curculio elephas, become active again after summer drought. This insect depends on late summer rainfall to soften the soil and allow adult emergence from their underground refuges. We found that, as in many protandric species, more C. elephas females emerged later in the season. Male emergence timing was on average earlier and also more dependent on the beginning of late summer rainfall. When these rains were delayed, the observed weevil sex ratio was biased towards females. So far, the effects of global warming on animal sex ratios has been reported for temperature-dependent sex determination in reptiles. Our results show that rainfall timing can also bias the sex ratio in an insect, and highlight the need for keeping a phenological perspective to predict the consequences of climate change. We must consider not just the magnitude of the predicted changes in temperature and rainfall but also the effects of their timing. PMID:26473046

Recent advances in research on climate and human conflict

NASA Astrophysics Data System (ADS)

Hsiang, S. M.

2014-12-01

A rapidly growing body of empirical, quantitative research examines whether rates of human conflict can be systematically altered by climatic changes. We discuss recent advances in this field, including Bayesian meta-analyses of the effect of temperature and rainfall on current and future large-scale conflicts, the impact of climate variables on gang violence and suicides in Mexico, and probabilistic projections of personal violence and property crime in the United States under RCP scenarios. Criticisms of this research field will also be explained and addressed.

Combining Hydrological Modeling and Remote Sensing Observations to Enable Data-Driven Decision Making for Devils Lake Flood Mitigation in a Changing Climate

NASA Technical Reports Server (NTRS)

Zhang, Xiaodong; Kirilenko, Andrei; Lim, Howe; Teng, Williams

2010-01-01

This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.

MARG - A Low Cost Solid State Microwave Areal Precipitation Measurement System

NASA Astrophysics Data System (ADS)

Paulitsch, Helmut; Dombai, Ferenc; Cremonini, Roberto; Bechini, Renzo

2014-05-01

Water is an essential resource for us so the measurements of its movement throughout the whole cycle is very important. The rainfall is discontinuous in space and in time having large natural variability unlike many other meteorological parameters. The widely used method for getting relatively accurate precipitation data over land is the combination of radar rainfall estimations and rain gauge data. The typically used radar data is coming from long-range weather radars operating in C or S band, or from mini radars operating in X band which is attenuating heavily in strong precipitation. Using such radar data we are facing several constraints: operating costs and limitations of long range radars, X band radars can be blocked totally in heavy thunderstorms even in short range, dual polarization solutions are expensive, etc. Recognizing that an important gap exists in instrumental precipitation measurements over land a consortium has been organized and a project has been established to develop a new measurement device, the so called Microwave Areal Rain Gauge (MARG). MARG is based on FMCW radar principle using solid state transmitter and digital signal processing and operating in C band. The MARG project aims to provide an innovative, real-time, low-cost, user friendly and accurate sensor technology to monitor and to measure continuously the rainfall intensity distribution over an area around some thousand square km. The MARG project proposal has been granted by the EU in FP7-SME-2012 funding scheme. The developed instrument is able to monitor in real-time intensity and spatial distribution of rainfall in rural and urban environments and can be operated by commercial weather data and value-added forecast product suppliers. To achieve sufficient isolation between the transmitter and receiver modules, and to avoid using complex and expensive microwave components, two parabolic antennae are used to transmit and receive the FMCW signal. The radar frontend operates in the C-band at 5.6 GHz with a maximal output power of 20 W continuous and a rainfall detection range of up to 30 km. Doppler processing is included in the signal processing for the purpose of clutter elimination. The reflectivity - rainfall conversion is performed with adjustable parameters as a function of rainfall type derived from morphological parameters of reflectivity fields and disdrometer measurements. Several algorithms, including mean bias correction, range correction and kriging interpolation with existing rain gauge networks to calibrate radar rainfall estimations are also foreseen. The MARG sensor will provide reflectivity, Doppler and precipitation data, but all measurements are organized and stored on the user centre's web server. The database contains precipitation data, measurement identification, and all available auxiliary meteorological data (e.g. temperature and air pressure). Precipitation data are further processed and combined with geographic background information through a GIS system. Finally the processed products, e.g. rainfall accumulation maps, are provided to the users by the GIS-based web service in the MARG user-centre module.

The Sahel Region of West Africa: Examples of Climate Analyses Motivated By Drought Management Needs

NASA Astrophysics Data System (ADS)

Ndiaye, O.; Ward, M. N.; Siebert, A. B.

2011-12-01

The Sahel is one of the most drought-prone regions in the world. This paper focuses on climate sources of drought, and some new analyses mostly driven by users needing climate information to help in drought management strategies. The Sahel region of West Africa is a transition zone between equatorial climate and vegetation to the south, and desert to the north. The climatology of the region is dominated by dry conditions for most of the year, with a single peak in rainfall during boreal summer. The seasonal rainfall total contains both interannual variability and substantial decadal to multidecadal variability (MDV). This brings climate analysis and drought management challenges across this range of timescales. The decline in rainfall from the wet decades of the 1950s and 60s to the dry decades of the 1970s and 80s has been well documented. In recent years, a moderate recovery has emerged, with seasonal totals in the period 1994-2010 significantly higher than the average rainfall 1970-1993. These MDV rainfall fluctuations have expression in large-scale sea-surface temperature fluctuations in all ocean basins, placing the changes in drought frequency within broader ocean-atmosphere climate fluctuation. We have evaluated the changing character of low seasonal rainfall total event frequencies in the Sahel region 1950-2010, highlighting the role of changes in the mean, variance and distribution shape of seasonal rainfall totals as the climate has shifted through the three observed phases. We also consider the extent to which updating climate normals in real-time can damp the bias in expected event frequency, an important issue for the feasibility of index insurance as a drought management tool in the presence of a changing climate. On the interannual timescale, a key factor long discussed for agriculture is the character of rainfall onset. An extended dry spell often occurs early in the rainy season before the crop is fully established, and this often leads to crop failure. This can be viewed as a special case of agricultural drought. Therefore, improving climate information around the time of planting can play a key role in agricultural risk management. Rainfall onset indices have been calculated for stations across Senegal. The problem is climatically challenging because the physical processes that impact rainfall onset appear to span aspects normally studied separately: weather system character, propagating intraseasonal features, and large-scale sea-surface temperature influence. We present aspects of all these, and ideas on how to combine them into seamless information to support agriculture.

Role of Ocean Initial Conditions to Diminish Dry Bias in the Seasonal Prediction of Indian Summer Monsoon Rainfall: A Case Study Using Climate Forecast System

NASA Astrophysics Data System (ADS)

Koul, Vimal; Parekh, Anant; Srinivas, G.; Kakatkar, Rashmi; Chowdary, Jasti S.; Gnanaseelan, C.

2018-03-01

Coupled models tend to underestimate Indian summer monsoon (ISM) rainfall over most of the Indian subcontinent. Present study demonstrates that a part of dry bias is arising from the discrepancies in Oceanic Initial Conditions (OICs). Two hindcast experiments are carried out using Climate Forecast System (CFSv2) for summer monsoons of 2012-2014 in which two different OICs are utilized. With respect to first experiment (CTRL), second experiment (AcSAL) differs by two aspects: usage of high-resolution atmospheric forcing and assimilation of only ARGO observed temperature and salinity profiles for OICs. Assessment of OICs indicates that the quality of OICs is enhanced due to assimilation of actual salinity profiles. Analysis reveals that AcSAL experiment showed 10% reduction in the dry bias over the Indian land region during the ISM compared to CTRL. This improvement is consistently apparent in each month and is highest for June. The better representation of upper ocean thermal structure of tropical oceans at initial stage supports realistic upper ocean stability and mixing. Which in fact reduced the dominant cold bias over the ocean, feedback to air-sea interactions and land sea thermal contrast resulting better representation of monsoon circulation and moisture transport. This reduced bias of tropospheric moisture and temperature over the Indian land mass and also produced better tropospheric temperature gradient over land as well as ocean. These feedback processes reduced the dry bias in the ISM rainfall. Study concludes that initializing the coupled models with realistic OICs can reduce the underestimation of ISM rainfall prediction.

Associations between seasonal influenza and meteorological parameters in Costa Rica, Honduras and Nicaragua.

PubMed

Soebiyanto, Radina P; Clara, Wilfrido A; Jara, Jorge; Balmaseda, Angel; Lara, Jenny; Lopez Moya, Mariel; Palekar, Rakhee; Widdowson, Marc-Alain; Azziz-Baumgartner, Eduardo; Kiang, Richard K

2015-11-04

Seasonal influenza affects a considerable proportion of the global population each year. We assessed the association between subnational influenza activity and temperature, specific humidity and rainfall in three Central America countries, i.e. Costa Rica, Honduras and Nicaragua. Using virologic data from each country's national influenza centre, rainfall from the Tropical Rainfall Measuring Mission and air temperature and specific humidity data from the Global Land Data Assimilation System, we applied logistic regression methods for each of the five sub-national locations studied. Influenza activity was represented by the weekly proportion of respiratory specimens that tested positive for influenza. The models were adjusted for the potentially confounding co-circulating respiratory viruses, seasonality and previous weeks' influenza activity. We found that influenza activity was proportionally associated (P<0.05) with specific humidity in all locations [odds ratio (OR) 1.21-1.56 per g/kg], while associations with temperature (OR 0.69-0.81 per °C) and rainfall (OR 1.01-1.06 per mm/day) were location-dependent. Among the meteorological parameters, specific humidity had the highest contribution (~3-15%) to the model in all but one location. As model validation, we estimated influenza activity for periods, in which the data was not used in training the models. The correlation coefficients between the estimates and the observed were ≤0.1 in 2 locations and between 0.6-0.86 in three others. In conclusion, our study revealed a proportional association between influenza activity and specific humidity in selected areas from the three Central America countries.

Projecting changes in Everglades soil biogeochemistry for carbon and other key elements, to possible 2060 climate and hydrologic scenarios.

PubMed

Orem, William; Newman, Susan; Osborne, Todd Z; Reddy, K Ramesh

2015-04-01

Based on previously published studies of elemental cycling in Everglades soils, we projected how soil biogeochemistry, specifically carbon, nitrogen, phosphorus, sulfur, and mercury might respond to climate change scenarios projected for 2060 by the South Florida Water Management Model. Water budgets and stage hydrographs from this model with future scenarios of a 10% increased or decreased rainfall, a 1.5 °C rise in temperature and associated increase in evapotranspiration (ET) and a 0.5 m rise in sea level were used to predict resulting effects on soil biogeochemistry. Precipitation is a much stronger driver of soil biogeochemical processes than temperature, because of links among water cover, redox conditions, and organic carbon accumulation in soils. Under the 10% reduced rainfall scenario, large portions of the Everglades will experience dry down, organic soil oxidation, and shifts in soil redox that may dramatically alter biogeochemical processes. Lowering organic soil surface elevation may make portions of the Everglades more vulnerable to sea level rise. The 10% increased rainfall scenario, while potentially increasing phosphorus, sulfur, and mercury loading to the ecosystem, would maintain organic soil integrity and redox conditions conducive to normal wetland biogeochemical element cycling. Effects of increased ET will be similar to those of decreased precipitation. Temperature increases would have the effect of increasing microbial processes driving biogeochemical element cycling, but the effect would be much less than that of precipitation. The combined effects of decreased rainfall and increased ET suggest catastrophic losses in carbon- and organic-associated elements throughout the peat-based Everglades.

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

PubMed

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

2017-05-25

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

The physics of rainclouds, what is behind rainfall trends?

NASA Astrophysics Data System (ADS)

Junkermann, Wolfgang; Hacker, Jorg

2017-04-01

In several locations in the world rainfall was significantly declining during the last four decades since about 1970, despite during the same timespan the water vapor availability in the planetary boundary layer (PBL) was increasing by about five percent. Increasing water vapor levels in the PBL are a result of climate change and well in agreement with the observed one degree increase of air temperature over the oceans. Increasing water vapor availability due to an increase in evaporation should lead to a higher turnover rate within the hydrological cycle, which should result either in more frequent or in more intense rainfall. Several regional observations especially along the Australian coastline show a contrary picture. Often rainfall is less frequent and the annual rainfall is declining. Also the number of rainy days goes down. This behavior could be caused by a number of different processes affecting both, the amount of liquid water in the atmosphere and the microphysical properties of clouds. Within the discussions are: -A change in the large scale advection patterns due to global warming, shifting the trajectories of low pressure systems, a slow process that takes several decades. -A change in land use by deforestation leading to lower roughness, higher albedo and lower convective energy. Such a land use change might happen within about one decade (e.g. Western Australia). -A change in aerosol abundance. Addition of anthropogenic cloud condensation nuclei lead instantly to smaller cloud droplets and subsequently to a regional to continental scale redistribution of rainfall within the time scales of cloud lifetime (hours to days). Airborne experiments show that indeed the number of aerosols in several of the respective areas investigated up to now was increasing roughly in time with the observed rainfall changes. However, only in few of the areas the availability of historical aerosol data is sufficient for a more detailed investigation. We show results from experiments in search for physical reasons for a regional scale rainfall decline observed along the Australian coastline. Here the historical database including an airborne survey in the early 70's allows to reconstruct a 'laboratory' notebook an aerosol trends. This makes the area a perfect 'natural laboratory' for such studies on the physical background for climate change trends and to disentangle different climate / hydrological cycle relevant physical processes.

WegenerNet 1km-scale sub-daily rainfall data and their application: a hydrological modeling study on the sensitivity of small-catchment runoff to spatial rainfall variability

NASA Astrophysics Data System (ADS)

Oh, Sungmin; Hohmann, Clara; Foelsche, Ulrich; Fuchsberger, Jürgen; Rieger, Wolfgang; Kirchengast, Gottfried

2017-04-01

WegenerNet Feldbach region (WEGN), a pioneering experiment for weather and climate observations, has recently completed its first 10-year precipitation measurement cycle. The WEGN has measured precipitation, temperature, humidity, and other parameters since the beginning of 2007, supporting local-level monitoring and modeling studies, over an area of about 20 km x 15 km centered near the City of Feldbach (46.93 ˚ N, 15.90 ˚ E) in the Alpine forelands of southeast Austria. All the 151 stations in the network are now equipped with high-quality Meteoservis sensors as of August 2016, following an equipment with Friedrichs sensors at most stations before, and continue to provide high-resolution (2 km2/5-min) gauge based precipitation measurements for interested users in hydro-meteorological communities. Here we will present overall characteristics of the WEGN, with a focus on sub-daily precipitation measurements, from the data processing (data quality control, gridded data products generation, etc.) to data applications (e.g., ground validation of satellite estimates). The latter includes our recent study on the propagation of uncertainty from rainfall to runoff. The study assesses responses of small-catchment runoff to spatial rainfall variability in the WEGN region over the Raab valley, using a physics-based distributed hydrological model; Water Flow and Balance Simulation Model (WaSiM), developed at ETH Zurich (Schulla, ETH Zurich, 1997). Given that uncertainty due to resolution of rainfall measurements is believed to be a significant source of error in hydrologic modeling especially for convective rainfall that dominates in the region during summer, the high-resolution of WEGN data furnishes a great opportunity to analyze effects of rainfall events on the runoff at different spatial resolutions. Furthermore, the assessment can be conducted not only for the lower Raab catchment (area of about 500 km2) but also for its sub-catchments (areas of about 30-70 km2). Beside the question how many stations are necessary for reliable hydrological modeling, different interpolation methods like Inverse Distance Interpolation, Elevation Dependent Regression, and combinations will be tested. This presentation will show the first results from a scale-depending analysis of spatial and temporal structures of heavy rainfall events and responses of simulated runoff at the event scale in the WEGN region.

Interpretation of Nimbus-7 37 GHz microwave brightness temperature data in semi-arid southern Africa

NASA Technical Reports Server (NTRS)

Prince, S. D.; Choudhury, B. J.

1989-01-01

Monthly 37 GHz microwave polarization difference temperatures (MPDT) derived from the Nimbus-7 scanning multichannel microwave radiometer (SMMR) for southern Africa from 1979 to 1985 are compared with rainfall and Advanced Very High Resolution Radiometer (AVHRR) normalized difference vegetation index (NDVI) data. MPDT rose sharply during a drought episode which occurred within the period included in the data. The rise was seen not only in the growing season, but also in the dry season MPDT when no actively photosynthetic, water-containing leaves are present. The results suggest that scattering of the emitted microwave radiation by dead and living vegetation is a more important factor than has previously been recognized.

Tropical Montane Cloud Forests: Hydrometeorological variability in three neighbouring catchments with different forest cover

NASA Astrophysics Data System (ADS)

Ramírez, Beatriz H.; Teuling, Adriaan J.; Ganzeveld, Laurens; Hegger, Zita; Leemans, Rik

2017-09-01

Mountain areas are characterized by a large heterogeneity in hydrological and meteorological conditions. This heterogeneity is currently poorly represented by gauging networks and by the coarse scale of global and regional climate and hydrological models. Tropical Montane Cloud Forests (TMCFs) are found in a narrow elevation range and are characterized by persistent fog. Their water balance depends on local and upwind temperatures and moisture, therefore, changes in these parameters will alter TMCF hydrology. Until recently the hydrological functioning of TMCFs was mainly studied in coastal regions, while continental TMCFs were largely ignored. This study contributes to fill this gap by focusing on a TMCF which is located on the northern eastern Andes at an elevation of 1550-2300 m asl, in the Orinoco river basin highlands. In this study, we describe the spatial and seasonal meteorological variability, analyse the corresponding catchment hydrological response to different land cover, and perform a sensitivity analysis on uncertainties related to rainfall interpolation, catchment area estimation and streamflow measurements. Hydro-meteorological measurements, including hourly solar radiation, temperature, relative humidity, wind speed, precipitation, soil moisture and streamflow, were collected from June 2013 to May 2014 at three gauged neighbouring catchments with contrasting TMCF/grassland cover and less than 250 m elevation difference. We found wetter and less seasonally contrasting conditions at higher elevations, indicating a positive relation between elevation and fog or rainfall persistence. This pattern is similar to that of other eastern Andean TMCFs, however, the study site had higher wet season rainfall and lower dry season rainfall suggesting that upwind contrasts in land cover and moisture can influence the meteorological conditions at eastern Andean TMCFs. Contrasting streamflow dynamics between the studied catchments reflect the overall system response as a function of the catchments' elevation and land cover. The forested catchment, located at the higher elevations, had the highest seasonal streamflows. During the wet season, different land covers at the lower elevations were important in defining the streamflow responses between the deforested catchment and the catchment with intermediate forest cover. Streamflows were higher and the rainfall-runoff responses were faster in the deforested catchment than in the intermediate forest cover catchment. During the dry season, the catchments' elevation defined streamflows due to higher water inputs and lower evaporative demand at the higher elevations.

Canopy storage capacity and wettability of leaves and needles: The effect of water temperature changes

NASA Astrophysics Data System (ADS)

Klamerus-Iwan, Anna; Błońska, Ewa

2018-04-01

The canopy storage capacity (S) is a major component of the surface water balance. We analysed the relationship between the tree canopy water storage capacity and leaf wettability under changing simulated rainfall temperature. We estimated the effect of the rain temperature change on the canopy storage capacity and contact angle of leave and needle surfaces based on two scenarios. Six dominant forest trees were analysed: English oak (Quercus roburL.), common beech (Fagus sylvatica L.), small-leaved lime (Tilia cordata Mill), silver fir (Abies alba), Scots pine (Pinus sylvestris L.),and Norway spruce (Picea abies L.). Twigs of these species were collected from Krynica Zdrój, that is, the Experimental Forestry unit of the University of Agriculture in Cracow (southern Poland). Experimental analyses (simulations of precipitation) were performed in a laboratory under controlled conditions. The canopy storage capacity and leaf wettability classification were determined at 12 water temperatures and a practical calculator to compute changes of S and contact angles of droplets was developed. Among all species, an increase of the rainfall temperature by 0.7 °C decreases the contact angle between leave and needle surfaces by 2.41° and increases the canopy storage capacity by 0.74 g g-1; an increase of the rain temperature by 2.7 °C decreases the contact angle by 9.29° and increases the canopy storage capacity by 2.85 g g-1. A decreased contact angle between a water droplet and leaf surface indicates increased wettability. Thus, our results show that an increased temperature increases the leaf wettability in all examined species. The comparison of different species implies that the water temperature has the strongest effect on spruce and the weakest effect on oak. These data indicate that the rainfall temperature influences the canopy storage capacity.

Seasonality of diarrheagenic Escherichia coli pathotypes in the US students acquiring diarrhea in Mexico.

PubMed

Paredes-Paredes, Mercedes; Okhuysen, Pablo C; Flores, Jose; Mohamed, Jamal A; Padda, Ranjit S; Gonzalez-Estrada, Alexei; Haley, Clinton A; Carlin, Lily G; Nair, Parvathy; DuPont, Herbert L

2011-01-01

Up to 60% of the US visitors to Mexico develop travelers' diarrhea (TD). In Mexico, rates of diarrhea have been associated with the rainy season and increase in ambient temperature. However, the seasonality of the various diarrheagenic Escherichia coli pathotypes in travelers has not been well described. A study was undertaken to determine if ambient temperature and rainfall have an impact on the acquisition of TD due to different diarrheagenic E coli pathotypes in Mexico. We conducted a cohort study of the US adult students traveling to Cuernavaca, Mexico, who were followed during their stay and provided a stool sample with the onset of TD. The presence of E coli was analyzed by a direct fecal multiplex polymerase chain reaction for common E coli pathotypes including enterotoxigenic, enteropathogenic, enteroinvasive, shiga toxin-producing, and enteroaggregative E coli (ETEC, EPEC, EIEC, STEC, and EAEC respectively). The presence of pathotypes was correlated with daily rainfall, average, maximum, and minimum temperatures. A total of 515 adults were enrolled from January 2006 to February 2007. The weekly attack rate of TD for newly arrived travelers was lower in the winter months (range 6.8%-16.3%) than in summer months (range 11.5%-25%; p = 0.05). The rate of ETEC infection increased by 7% for each degree centigrade increase in weekly ambient temperature (p = 0.003). In contrast, EPEC and EAEC were identified in similar proportions during the winter and summer seasons. Temperature variations in central Mexico influenced the rate of ETEC but not EAEC-associated diarrhea in the US visitors. This epidemiological finding could influence seasonal recommendations for the use of ETEC vaccines in Mexico. © 2011 International Society of Travel Medicine.

Rainfall effects on inflow and infiltration in wastewater treatment systems in a coastal plain region.

PubMed

Cahoon, Lawrence B; Hanke, Marc H

2017-04-01

Aging wastewater collection and treatment systems have not received as much attention as other forms of infrastructure, even though they are vital to public health, economic growth, and environmental quality. Inflow and infiltration (I&I) are among potentially widespread problems facing central sewage collection and treatment systems, posing risks of sanitary system overflows (SSOs), system degradation, and water quality impairment, but remain poorly quantified. Whole-system analyses of I&I were conducted by regression analyses of system flow responses to rainfall and temperature for 93 wastewater treatment plants in 23 counties in eastern North Carolina, USA, a coastal plain region with high water tables and generally higher rainfalls than the continental interior. Statistically significant flow responses to rainfall were found in 92% of these systems, with 2-year average I&I values exceeding 10% of rainless system flow in over 40% of them. The effects of rainfall, which can be intense in this coastal region, have region-wide implications for sewer system performance and environmental management. The positive association between rainfall and excessive I&I parallels the effects of storm water runoff on water quality, in that excessive I&I can also drive SSOs, thus confounding water quality protection efforts.

Modulation of Heavy Rainfall in the Middle East and North Africa by Madden-Julian Oscillation Using High Resolution Atmospheric General Circulation Model

NASA Astrophysics Data System (ADS)

Deng, L.; Stenchikov, G. L.; McCabe, M. F.; Bangalath, H. K.

2014-12-01

Recently, the modulation of subtropical rainfall by the dominant tropical intraseasonal signal of the Madden-Julian Oscillation (MJO), has been explored through the discussion of the MJO-convection-induced Kelvin and Rossby wave related teleconnection patterns. Our study focuses on characterizing the modulation of heavy rainfall in the Middle East and North Africa (MENA) region by the MJO, using the Geophysical Fluid Dynamics Laboratory (GFDL) global High Resolution Atmospheric Model (HIRAM) simulations (25-km; 1979-2012) and a combination of available atmospheric products from satellite, in-situ and reanalysis data. The observed Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) and the simulated SST from GFDL's global coupled carbon-climate Earth System Models (ESM2M) are employed in HIRAM to investigate the sensitivity of the simulated heavy rainfall and MJO to SST. The future trend of the extreme rainfalls and their links to the MJO response to climate change are examined using HIRAM simulations of 2012-2050 with the RCP4.5 and RCP 8.5 scenarios to advance the possibility of characterization and forecasting of future extreme rainfall events in the MENA region.

Large rainfall changes consistently projected over substantial areas of tropical land

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Good, Peter; Martin, Gill; Rowell, David P.

2016-02-01

Many tropical countries are exceptionally vulnerable to changes in rainfall patterns, with floods or droughts often severely affecting human life and health, food and water supplies, ecosystems and infrastructure. There is widespread disagreement among climate model projections of how and where rainfall will change over tropical land at the regional scales relevant to impacts, with different models predicting the position of current tropical wet and dry regions to shift in different ways. Here we show that despite uncertainty in the location of future rainfall shifts, climate models consistently project that large rainfall changes will occur for a considerable proportion of tropical land over the twenty-first century. The area of semi-arid land affected by large changes under a higher emissions scenario is likely to be greater than during even the most extreme regional wet or dry periods of the twentieth century, such as the Sahel drought of the late 1960s to 1990s. Substantial changes are projected to occur by mid-century--earlier than previously expected--and to intensify in line with global temperature rise. Therefore, current climate projections contain quantitative, decision-relevant information on future regional rainfall changes, particularly with regard to climate change mitigation policy.

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

NASA Technical Reports Server (NTRS)

Grecu, Mircea; Anagnostou, Emmanouil N.; Olson, William S.; Starr, David OC. (Technical Monitor)

2002-01-01

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated using both simulated and airborne data. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) satellite multi-frequency active and passive observations. These observations are characterized by various spatial and sampling resolutions. This makes the retrieval problem mathematically more difficult and ill-determined because the quality of information decreases with decreasing resolution. A model that, given reflectivity profiles and a small set of parameters (including the cloud water content, the intercept drop size distribution, and a variable describing the frozen hydrometeor properties), simulates high-resolution brightness temperatures is used. The high-resolution simulated brightness temperatures are convolved at the real sensor resolution. An optimal estimation procedure is used to minimize the differences between simulated and observed brightness temperatures. The retrieval technique is investigated using cloud model synthetic and airborne data from the Fourth Convection And Moisture Experiment. Simulated high-resolution brightness temperatures and reflectivities and airborne observation strong are convolved at the resolution of the TRMM instruments and retrievals are performed and analyzed relative to the reference data used in observations synthesis. An illustration of the possible use of the technique in satellite rainfall estimation is presented through an application to TRMM data. The study suggests improvements in combined active and passive retrievals even when the instruments resolutions are significantly different. Future work needs to better quantify the retrievals performance, especially in connection with satellite applications, and the uncertainty of the models used in retrieval.

Phenology of sexual reproduction in the common coral reef sponge, Carteriospongia foliascens

NASA Astrophysics Data System (ADS)

Abdul Wahab, M. A.; de Nys, R.; Webster, N.; Whalan, S.

2014-06-01

Understanding processes that contribute to population maintenance is critical to the management and conservation of species. Despite this, very little is currently known about the reproductive biology of Great Barrier Reef (GBR) sponge species. Here, we established reproductive parameters including mode of sexuality and development, seasonality, sex ratios, gametogenesis, reproductive output, and size at sexual maturity for the common phototrophic intertidal sponge, Carteriospongia foliascens, in the central GBR over two reproductive cycles. A population sexual productivity index (PoSPi) integrating key reproductive parameters was formulated to compare population larval supply over time. This study shows that C. foliascens is reproductive all year round, gonochoric and viviparous, with larvae developing asynchronously throughout the mesohyl. The influence of environmental parameters relevant to C. foliascens reproduction [i.e., sea surface temperature (SST), photoperiod, and rainfall] was also examined, and SST was found to have the most significant effect on phenology. C. foliascens reproduction exhibited annual mono-cyclic patterns closely resembling SST fluctuations. Reproductive output was depressed at low SST (<23 °C) and increased at temperatures above 23 °C. Peak sperm release occurred at temperatures above 25 °C, while peak larval release occurred during the annual temperature maxima (>28 °C). A twofold increase in maximum larval production (PoSPi) in C. foliascens was observed in the second reproductive cycle, following a depressed PoSPi in the first cycle. This reduction in PoSPi in the first reproductive cycle was associated with elevated SST and rainfall, coinciding with one of the strongest La Niña events on record.

Aerosol- and greenhouse gas-induced changes in summer rainfall and circulation in the Australasian region: a study using single-forcing climate simulations

NASA Astrophysics Data System (ADS)

Rotstayn, L. D.; Jeffrey, S. J.; Collier, M. A.; Dravitzki, S. M.; Hirst, A. C.; Syktus, J. I.; Wong, K. K.

2012-07-01

We use a coupled atmosphere-ocean global climate model (CSIRO-Mk3.6) to investigate the drivers of trends in summer rainfall and circulation in the vicinity of northern Australia. As part of the Coupled Model Intercomparison Project Phase 5 (CMIP5), we perform a 10-member 21st century ensemble driven by Representative Concentration Pathway 4.5 (RCP4.5). To investigate the roles of different forcing agents, we also perform multiple 10-member ensembles of historical climate change, which are analysed for the period 1951-2010. The historical runs include ensembles driven by "all forcings" (HIST), all forcings except anthropogenic aerosols (NO_AA) and forcing only from long-lived greenhouse gases (GHGAS). Anthropogenic aerosol-induced effects in a warming climate are calculated from the difference of HIST minus NO_AA. CSIRO-Mk3.6 simulates a strong summer rainfall decrease over north-western Australia (NWA) in RCP4.5, whereas simulated trends in HIST are weakly positive (but insignificant) during 1951-2010. The weak rainfall trends in HIST are due to compensating effects of different forcing agents: there is a significant decrease in GHGAS, offset by an aerosol-induced increase. Observations show a significant increase of summer rainfall over NWA during the last few decades. The large magnitude of the observed NWA rainfall trend is not captured by 440 unforced 60-yr trends calculated from a 500-yr pre-industrial control run, even though the model's decadal variability appears to be realistic. This suggests that the observed trend includes a forced component, despite the fact that the model does not simulate the magnitude of the observed rainfall increase in response to "all forcings" (HIST). We investigate the mechanism of simulated and observed NWA rainfall changes by exploring changes in circulation over the Indo-Pacific region. The key circulation feature associated with the rainfall increase in reanalyses is a lower-tropospheric cyclonic circulation trend off the coast of NWA, which enhances the monsoonal flow. The model shows an aerosol-induced cyclonic circulation trend off the coast of NWA in HIST minus NO_AA, whereas GHGAS shows an anticyclonic circulation trend. This explains why the aerosol-induced effect is an increase of rainfall over NWA, and the greenhouse gas-induced effect is of opposite sign. Possible explanations for the cyclonic (anticyclonic) circulation trend in HIST minus NO_AA (GHGAS) involve changes in the Walker circulation or the local Hadley circulation. In either case, a plausible atmospheric mechanism is that the circulation anomaly is a Rossby wave response to convective heating anomalies south of the Equator. We also discuss the possible role of air-sea interactions, e.g. an increase (decrease) of sea-surface temperatures off the coast of NWA in HIST minus NO_AA (GHGAS). Further research is needed to better understand the mechanisms and the extent to which these are model-dependent. In summary, our results suggest that anthropogenic aerosols may have "masked" greenhouse gas-induced changes in rainfall over NWA and in circulation over the wider Indo-Pacific region. Due to the opposing effects of greenhouse gases and anthropogenic aerosols, future trends may be very different from trends observed over the last few decades.

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.

Rainfall and its seasonality over the Amazon in the 21st century as assessed by the coupled models for the IPCC AR4

NASA Astrophysics Data System (ADS)

Li, Wenhong; Fu, Rong; Dickinson, Robert E.

2006-01-01

The global climate models for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) predict very different changes of rainfall over the Amazon under the SRES A1B scenario for global climate change. Five of the eleven models predict an increase of annual rainfall, three models predict a decrease of rainfall, and the other three models predict no significant changes in the Amazon rainfall. We have further examined two models. The UKMO-HadCM3 model predicts an El Niño-like sea surface temperature (SST) change and warming in the northern tropical Atlantic which appear to enhance atmospheric subsidence and consequently reduce clouds over the Amazon. The resultant increase of surface solar absorption causes a stronger surface sensible heat flux and thus reduces relative humidity of the surface air. These changes decrease the rate and length of wet season rainfall and surface latent heat flux. This decreased wet season rainfall leads to drier soil during the subsequent dry season, which in turn can delay the transition from the dry to wet season. GISS-ER predicts a weaker SST warming in the western Pacific and the southern tropical Atlantic which increases moisture transport and hence rainfall in the Amazon. In the southern Amazon and Nordeste where the strongest rainfall increase occurs, the resultant higher soil moisture supports a higher surface latent heat flux during the dry and transition season and leads to an earlier wet season onset.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

NASA Astrophysics Data System (ADS)

Konda, Gopinadh; Chowdary, J. S.; Srinivas, G.; Gnanaseelan, C.; Parekh, Anant; Attada, Raju; Rama Krishna, S. S. V. S.

2018-06-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

NASA Astrophysics Data System (ADS)

Tariku, Tebikachew Betru; Gan, Thian Yew

2018-06-01

Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional climate of NRB over 1980-2001 which include a combination of wet and dry years of the NRB.

Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

NASA Astrophysics Data System (ADS)

Tariku, Tebikachew Betru; Gan, Thian Yew

2017-08-01

Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional climate of NRB over 1980-2001 which include a combination of wet and dry years of the NRB.

Comparisons of Rain Estimates from Ground Radar and Satellite Over Mountainous Regions

NASA Technical Reports Server (NTRS)

Lin, Xin; Kidd, Chris; Tao, Jing; Barros, Ana

2016-01-01

A high-resolution rainfall product merging surface radar and an enhanced gauge network is used as a reference to examine two operational surface radar rainfall products over mountain areas. The two operational rainfall products include radar-only and conventional-gauge-corrected radar rainfall products. Statistics of rain occurrence and rain amount including their geographical, seasonal, and diurnal variations are examined using 3-year data. It is found that the three surface radar rainfall products in general agree well with one another over mountainous regions in terms of horizontal mean distributions of rain occurrence and rain amount. Frequency of rain occurrence and fraction of rain amount also indicate similar distribution patterns as a function of rain intensity. The diurnal signals of precipitation over mountain ridges are well captured and joint distributions of coincident raining samples indicate reasonable correlations during both summer and winter. Factors including undetected low-level precipitation, limited availability of gauges for correcting the Z-R relationship over the mountains, and radar beam blocking by mountains are clearly noticed in the two conventional radar rainfall products. Both radar-only and conventional-gauge-corrected radar rainfall products underestimate the rain occurrence and fraction of rain amount at intermediate and heavy rain intensities. Comparison of PR and TMI against a surface radar-only rainfall product indicates that the PR performs equally well with the high-resolution radar-only rainfall product over complex terrains at intermediate and heavy rain intensities during the summer and winter. TMI, on the other hand, requires improvement to retrieve wintertime precipitation over mountain areas.

Influence of climatic variables, forest type, and condition on activity patterns of Geoffroyi's spider monkeys throughout Mesoamerica.

PubMed

González-Zamora, Arturo; Arroyo-Rodríguez, Víctor; Chaves, Oscar M; Sánchez-López, Sónia; Aureli, Filippo; Stoner, Kathryn E

2011-12-01

Understanding how species cope with variations in climatic conditions, forest types and habitat amount is a fundamental challenge for ecologists and conservation biologists. We used data from 18 communities of Mesoamerican spider monkeys (Ateles geoffroyi) throughout their range to determine whether their activity patterns are affected by climatic variables (temperature and rainfall), forest types (seasonal and nonseasonal forests), and forest condition (continuous and fragmented). Data were derived from 15 published and unpublished studies carried out in four countries (Mexico, El Salvador, Costa Rica, and Panama), cumulatively representing more than 18 years (221 months, >3,645 hr) of behavioral observations. Overall, A. geoffroyi spent most of their time feeding (38.4 ± 14.0%, mean ± SD) and resting (36.6 ± 12.8%) and less time traveling (19.8 ± 11.3%). Resting and feeding were mainly affected by rainfall: resting time increased with decreasing rainfall, whereas feeding time increased with rainfall. Traveling time was negatively related to both rainfall and maximum temperature. In addition, both resting and traveling time were higher in seasonal forests (tropical dry forest and tropical moist forest) than in nonseasonal forests (tropical wet forest), but feeding time followed the opposite pattern. Furthermore, spider monkeys spent more time feeding and less time resting (i.e., higher feeding effort) in forest fragments than in continuous forest. These findings suggest that global climate changes and habitat deforestation and fragmentation in Mesoamerica will threaten the survival of spider monkeys and reduce the distributional range of the species in the coming decades. © 2011 Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

Abbasnia, Mohsen; Toros, Hüseyin

2018-05-01

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

Stress modulation of cellular metabolic sensors: interaction of stress from temperature and rainfall on the intertidal limpet Cellana toreuma.

PubMed

Dong, Yun-Wei; Han, Guo-Dong; Huang, Xiong-Wei

2014-09-01

In the natural environment, organisms are exposed to large variations in physical conditions. Quantifying such physiological responses is, however, often performed in laboratory acclimation studies, in which usually only a single factor is varied. In contrast, field acclimatization may expose organisms to concurrent changes in several environmental variables. The interactions of these factors may have strong effects on organismal function. In particular, rare events that occur stochastically and have relatively short duration may have strong effects. The present experiments studied levels of expression of several genes associated with cellular stress and metabolic regulation in a field population of limpet Cellana toreuma that encountered a wide range of temperatures plus periodic rain events. Physiological responses to these variable conditions were quantified by measuring levels of mRNA of genes encoding heat-shock proteins (Hsps) and metabolic sensors (AMPKs and Sirtuin 1). Our results reveal high ratios of individuals in upregulation group of stress-related gene expression at high temperature and rainy days, indicating the occurrence of stress from both prevailing high summer temperatures and occasional rainfall during periods of emersion. At high temperature, stress due to exposure to rainfall may be more challenging than heat stress alone. The highly variable physiological performances of limpets in their natural habitats indicate the possible differences in capability for physiological regulation among individuals. Our results emphasize the importance of studies of field acclimatization in unravelling the effects of environmental change on organisms, notably in the context of multiple changes in abiotic factors that are accompanying global change. © 2014 John Wiley & Sons Ltd.

How do temperature and rainfall affect nitrous oxide emissions from open-lot beef cattle feedyard pens?

USDA-ARS?s Scientific Manuscript database

Temperature is a primary factor affecting greenhouse gas (GHG) emissions from agricultural soils, but little is known about how temperature affects nitrous oxide (N2O) emissions from manure. The majority of grain-fed cattle in the Texas Panhandle are finished in large, earthen-surfaced, open-lot fee...

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.

Results of hydrologic monitoring on landslide-prone coastal bluffs near Mukilteo, Washington

USGS Publications Warehouse

Smith, Joel B.; Baum, Rex L.; Mirus, Benjamin B.; Michel, Abigail R.; Stark, Ben

2017-08-31

A hydrologic monitoring network was installed to investigate landslide hazards affecting the railway corridor along the eastern shore of Puget Sound between Seattle and Everett, near Mukilteo, Washington. During the summer of 2015, the U.S. Geological Survey installed monitoring equipment at four sites equipped with instrumentation to measure rainfall and air temperature every 15 minutes. Two of the four sites are installed on contrasting coastal bluffs, one landslide scarred and one vegetated. At these two sites, in addition to rainfall and air temperature, volumetric water content, pore pressure, soil suction, soil temperature, and barometric pressure were measured every 15 minutes. The instrumentation was designed to supplement landslide-rainfall thresholds developed by the U.S. Geological Survey with a long-term goal of advancing the understanding of the relationship between landslide potential and hydrologic forcing along the coastal bluffs. Additionally, the system was designed to function as a prototype monitoring system to evaluate criteria for site selection, instrument selection, and placement of instruments. The purpose of this report is to describe the monitoring system, present the data collected since installation, and describe significant events represented within the dataset, which is published as a separate data release. The findings provide insight for building and configuring larger, modular monitoring networks.

Migration Related to Climate Change: Impact, Challenges and Proposed Policy Initiatives

NASA Astrophysics Data System (ADS)

Sarkar, A.

2015-12-01

Migration of human population possesses a great threat to human development and nation building. A significant cause for migration is due to change in climatic conditions and vulnerabilities associated with it. Our case study focuses on the consequent reason and impact of such migration in the coastal areas of West Bengal, India. The changes in rainfall pattern and the variation of temperature have been considered as parameters which have resulted in migration. It is worthy to note that the agricultural pattern has subsequently changed over the last two decades due to change in rainfall and temperature. India being an agriculture oriented economy, the changes in the meteorological variables have not only altered the rate of agricultural pattern but also the rate of migration. A proposed framework depicting relationship between changes in meteorological variables and the migration pattern, and an estimate of how the migration pattern is expected to change over the next century by utilizing the downscaled values of future rainfall and temperature has been analyzed. Moreover, various public policy frameworks has also been proposed through the study for addressing the challenges of migration related to climate change. The proposed public policy framework has been streamlined along the lines of various international treaties and conventions in order to integrate the policy initiatives through universalization of law and policy research.

Contrasting diel hysteresis between soil autotrophic and heterotrophic respiration in a desert ecosystem under different rainfall scenarios

PubMed Central

Song, Weimin; Chen, Shiping; Zhou, Yadan; Wu, Bo; Zhu, Yajuan; Lu, Qi; Lin, Guanghui

2015-01-01

Diel hysteresis occurs often between soil CO2 efflux (RS) and temperature, yet, little is known if diel hysteresis occurs in the two components of RS, i.e., autotrophic respiration (RA) and heterotrophic respiration (RH), and how diel hysteresis will respond to future rainfall change. We conducted a field experiment in a desert ecosystem in northern China simulating five different scenarios of future rain regimes. Diel variations of soil CO2 efflux and soil temperature were measured on Day 6 and Day 16 following the rain addition treatments each month during the growing season. We found contrasting responses in the diel hysteresis of RA and RH to soil temperature, with a clockwise hysteresis loop for RH but a counter-clockwise hysteresis loop for RA. Rain addition significantly increased the magnitude of diel hysteresis for both RH and RA on Day 6, but had no influence on either on Day 16 when soil moisture was much lower. These findings underline the different roles of biological (i.e. plant and microbial activities) and physical-chemical (e.g. heat transport and inorganic CO2 exchange) processes in regulating the diel hysteresis of RA and RH, which should be considered when estimating soil CO2 efflux in desert regions under future rainfall regime. PMID:26615895

Isotopic evidence for cooler and drier conditions in the tropical Andes during the last glacial stage

NASA Astrophysics Data System (ADS)

Mora, Germán; Pratt, Lisa M.

2001-06-01

Documentation of paleoclimatic conditions during the last glacial stage in the tropical Andes is sparse despite the importance of understanding past climate changes in the tropics. To reconstruct paleoenvironmental conditions in the alpine neotropics, we measured the oxygen (δ18O) and hydrogen (δD) isotopic composition of authigenic kaolinite within weathering profiles of the Bogota basin (Colombia) because of the strong dependence of isotopic values on both surface temperature and rainfall. While kaolinite isotope data from Holocene soils in the basin reflect modern mean annual temperature and mean weighted rainwater isotopic composition of the basin, kaolinite isotope data from paleosols developed during the last glacial stage suggest 6 ± 2 °C cooler temperatures. Moreover, the isotope data indicate higher isotopic values of paleorainwater, interpreted to reflect drier conditions. The combination of reduced rainfall, temperature, and pCO2 significantly affected the distribution of tropical montane flora during the last glacial stage.

Transient modelling of lacustrine regressions: two case studies from the Andean Altiplano

NASA Astrophysics Data System (ADS)

Condom, Thomas; Coudrain, Anne; Dezetter, Alain; Brunstein, Daniel; Delclaux, François; Jean-Emmanuel, Sicart

2004-09-01

A model was developed for estimating the delay between a change in climatic conditions and the corresponding fall of water level in large lakes. The input data include: rainfall, temperature, extraterrestrial radiation and astronomical mid-month daylight hours. The model uses two empirical coefficients for computing the potential evaporation and one parameter for the soil capacity. The case studies are two subcatchments of the Altiplano (196 000 km2), in which the central low points are Lake Titicaca and a salar corresponding to the desiccation of the Tauca palaeolake. During the Holocene, the two catchments experienced a 100 m fall in water level corresponding to a decrease in water surface area of 3586 km2 and 55 000 km2, respectively. Under modern climatic conditions with a marked rainy season, the model allows simulation of water levels in good agreement with the observations: 3810 m a.s.l. for Lake Titicaca and lack of permanent wide ponds in the southern subcatchment. Simulations were carried out under different climatic conditions that might explain the Holocene fall in water level. Computed results show quite different behaviour for the two subcatchments. For the northern subcatchment, the time required for the 100 m fall in lake-level ranges between 200 and 2000 years when, compared with the present conditions, (i) the rainfall is decreased by 15% (640 mm/year), or (ii) the temperature is increased by 5.5 °C, or (iii) rainfall is distributed equally over the year. For the southern subcatchment (Tauca palaeolake), the time required for a 100 m decrease in water level ranges between 50 and 100 years. This decrease requires precipitation values lower than 330 mm/year.

Climate projections and extremes in dynamically downscaled CMIP5 model outputs over the Bengal delta: a quartile based bias-correction approach with new gridded data

NASA Astrophysics Data System (ADS)

Hasan, M. Alfi; Islam, A. K. M. Saiful; Akanda, Ali Shafqat

2017-11-01

In the era of global warning, the insight of future climate and their changing extremes is critical for climate-vulnerable regions of the world. In this study, we have conducted a robust assessment of Regional Climate Model (RCM) results in a monsoon-dominated region within the new Coupled Model Intercomparison Project Phase 5 (CMIP5) and the latest Representative Concentration Pathways (RCP) scenarios. We have applied an advanced bias correction approach to five RCM simulations in order to project future climate and associated extremes over Bangladesh, a critically climate-vulnerable country with a complex monsoon system. We have also generated a new gridded product that performed better in capturing observed climatic extremes than existing products. The bias-correction approach provided a notable improvement in capturing the precipitation extremes as well as mean climate. The majority of projected multi-model RCMs indicate an increase of rainfall, where one model shows contrary results during the 2080s (2071-2100) era. The multi-model mean shows that nighttime temperatures will increase much faster than daytime temperatures and the average annual temperatures are projected to be as hot as present-day summer temperatures. The expected increase of precipitation and temperature over the hilly areas are higher compared to other parts of the country. Overall, the projected extremities of future rainfall are more variable than temperature. According to the majority of the models, the number of the heavy rainy days will increase in future years. The severity of summer-day temperatures will be alarming, especially over hilly regions, where winters are relatively warm. The projected rise of both precipitation and temperature extremes over the intense rainfall-prone northeastern region of the country creates a possibility of devastating flash floods with harmful impacts on agriculture. Moreover, the effect of bias-correction, as presented in probable changes of both bias-corrected and uncorrected extremes, can be considered in future policy making.

MECO Warming Changes Continental Rainfall Patterns in Eocene Western North America

NASA Astrophysics Data System (ADS)

Methner, K.; Mulch, A.; Fiebig, J.; Wacker, U.; Gerdes, A.; Graham, S. A.; Chamberlain, C. P.

2016-12-01

Eocene hyperthermals represent temperature extremes superimposed on an existing warm climate. They dramatically affected the marine and terrestrial biosphere, but still remain among the most enigmatic phenomena of Cenozoic climate dynamics. To evaluate the impacts of global warm periods on terrestrial temperature and rainfall records in continental interiors, we sampled a suite of middle Eocene ( 40 Ma) paleosols from a high-elevation mammal fossil locality in the hinterland of the North American Cordillera (Sage Creek Basin, Montana, USA) and integrated laser ablation U-Pb dating of pedogenic carbonate, stable isotope (δ18O) and clumped isotope temperature (Δ47) records. Δ47 temperature data of soil carbonates progressively increase from 23 °C ±3 °C to peak temperatures of 32 °C ±3 °C and subsequently drop to 21 °C ±2 °C and delineate a rapid +9/-11 °C temperature excursion in the paleosol record. This hyperthermal event is accompanied by large and rapid shifts towards low δ18O values and reduced pedogenic CaCO3 contents. U-Pb geochronology of the paleosol carbonate confirms a middle Eocene age for soil carbonate formation (39.5 ±1.4 Ma and 40.1 ±0.8 Ma). Based on U-Pb geochronology, magneto- and biostratigraphy we suggest that the recorded Δ47 temperature excursion reflects peak warming during the Middle Eocene Climatic Optimum (MECO). The MECO in continental western North America appears to be characterized by warmer and wetter (sub-humid) conditions in this high-elevation site. Shifts in δ18O values of precipitation and pedogenic CaCO3 contents parallel temperature changes and require modification of mid-latitude rainfall patterns, indicating a profound impact of the MECO on the hydrological cycle and consequently on atmospheric circulation patterns in the hinterland of the North American Cordillera.

Natural and anthropogenic phenomena affecting the historical landslide trend in the Subappennino Dauno (southern Italy)

NASA Astrophysics Data System (ADS)

Lonigro, Teresa; Santaloia, Francesca; Polemio, Maurizio

2014-05-01

The aim of this work is to present a methodology, based both on the use methods of time series analyses and of geospatial analyses of monthly climatic data (rainfall, wet days, rainfall intensity, and temperature), annual maximum of short-duration rainfall (from 1 hour to 5 days), historical modification of land use, and population variations in order to characterise the effects of these variables on the occurrence of landsliding in Daunia area, located on the eastern margin of the Southern Apennines thrust belt (southern Italy). Rock strata (mainly) interbedded with clayey marls, clays and silty-clays outcrop in this area. Due to the intense strain history, these successions are found to be from stratified to deeply fractured, up to be disrupted and floating as blocks in a clayey matrix. In turn, the clay units are laminated to intensely fissured and characterised by very poor mechanical properties (Santaloia et al., 2012). The statistical analyses deal with data coming from published databases, integrated by public and private documents, referring to a wide time span. Climate data records from 1877 to 2008 were elaborated, in particular the data coming from sixteen rainfall gauges, ten of which were also thermometric. Moreover, some monthly indices of rainfall, wet days, rainfall intensity, temperature, and landslide occurrence were introduced to simplify the analysis of parameters, characterised by spatial and temporal variability. The population records are from the 19th century up to now while the time period of reference for the land use data is from 1930 up to now. As concerns the landslide events, they were collected from 1918 to 2006. The main source of these records is the AVI database, an existing Italian database that collects data about damaging floods and landslides from 1918 to 1996. This dataset was integrated up to 2006 by consulting newspapers, scientific publications, technical reports, written by the researchers of the CNR-IRPI for the Civil Protection, and also documents belonging to a research project (PS_119; Cotecchia et al. 2010). According to the landslide data collected, the landslide events resulted to be 175 in the study area. The trend analyses show that the landslide occurrence was increased with the time, despite of the rainfall and temperature data are not prone to landsliding. As a matter of fact, the trend of both the monthly rainfall and the rainfall intensity decreases, and the temperature and the wet days show a positive trend during the period of reference. The trend of the short-duration rainfall results generally to decrease. Not existing an evident relationship between climate variability and the increase of landslide occurrence, some other factors should be considered, as, for instance, the poor mechanical soil properties, the role of anthropogenic modifications and the mismanagement of risk-prone areas. In this regards, the preliminary results obtained from the data analyses of the land use and the populations could partly justify the increasing trend of landslide occurrence. More details on previous results of this research activity were recently published (Cotecchia et al., 2010; Polemio and Lonigro, 2011 and 2013; Santaloia et al., 2012). References Cotecchia F., Santaloia F., Lollino P., C. Vitone, G. Mitaritonna (2010) "Deterministic landslide hazard assessment at regional scale". Geoflorida 2010, : 3130-3139. Santaloia F, Cotecchia F, Vitone C (2012) "Applicazione dei metodi avanzati al fronte appenninico apulo-lucano: analisi di I livello. In: Cascini L. (Ed) "Criteri di zonazione della suscettibilità e della pericolosità da frane innescate da eventi estremi (piogge e sisma)"; 130-140, Padova:Composervice srl. Polemio M., Lonigro T. (2011) "Variabilità climatica e ricorrenza delle calamità idrogeologiche in Puglia". In: "Le modificazioni climatiche e i rischi naturali", Polemio M. (Ed.), CNR IRPI, Bari, pp. 13-16. Polemio M., Lonigro T. (2013) "Climate variability and landslide occurrence in Apulia (southern Italy)". In: C. Margottini et al. (eds.), Landslide Science and Practice, Springer-Verlag Berlin Heidelberg, 4: 37-41.

Estimating malaria burden in Nigeria: a geostatistical modelling approach.

PubMed

Onyiri, Nnadozie

2015-11-04

This study has produced a map of malaria prevalence in Nigeria based on available data from the Mapping Malaria Risk in Africa (MARA) database, including all malaria prevalence surveys in Nigeria that could be geolocated, as well as data collected during fieldwork in Nigeria between March and June 2007. Logistic regression was fitted to malaria prevalence to identify significant demographic (age) and environmental covariates in STATA. The following environmental covariates were included in the spatial model: the normalized difference vegetation index, the enhanced vegetation index, the leaf area index, the land surface temperature for day and night, land use/landcover (LULC), distance to water bodies, and rainfall. The spatial model created suggests that the two main environmental covariates correlating with malaria presence were land surface temperature for day and rainfall. It was also found that malaria prevalence increased with distance to water bodies up to 4 km. The malaria risk map estimated from the spatial model shows that malaria prevalence in Nigeria varies from 20% in certain areas to 70% in others. The highest prevalence rates were found in the Niger Delta states of Rivers and Bayelsa, the areas surrounding the confluence of the rivers Niger and Benue, and also isolated parts of the north-eastern and north-western parts of the country. Isolated patches of low malaria prevalence were found to be scattered around the country with northern Nigeria having more such areas than the rest of the country. Nigeria's belt of middle regions generally has malaria prevalence of 40% and above.

Cutaneous Leishmaniasis and Sand Fly Fluctuations Are Associated with El Niño in Panamá

PubMed Central

Chaves, Luis Fernando; Calzada, José E.; Valderrama, Anayansí; Saldaña, Azael

2014-01-01

Background Cutaneous Leishmaniasis (CL) is a neglected tropical vector-borne disease. Sand fly vectors (SF) and Leishmania spp parasites are sensitive to changes in weather conditions, rendering disease transmission susceptible to changes in local and global scale climatic patterns. Nevertheless, it is unclear how SF abundance is impacted by El Niño Southern Oscillation (ENSO) and how these changes might relate to changes in CL transmission. Methodology and Findings We studied association patterns between monthly time series, from January 2000 to December 2010, of: CL cases, rainfall and temperature from Panamá, and an ENSO index. We employed autoregressive models and cross wavelet coherence, to quantify the seasonal and interannual impact of local climate and ENSO on CL dynamics. We employed Poisson Rate Generalized Linear Mixed Models to study SF abundance patterns across ENSO phases, seasons and eco-epidemiological settings, employing records from 640 night-trap sampling collections spanning 2000–2011. We found that ENSO, rainfall and temperature were associated with CL cycles at interannual scales, while seasonal patterns were mainly associated with rainfall and temperature. Sand fly (SF) vector abundance, on average, decreased during the hot and cold ENSO phases, when compared with the normal ENSO phase, yet variability in vector abundance was largest during the cold ENSO phase. Our results showed a three month lagged association between SF vector abundance and CL cases. Conclusion Association patterns of CL with ENSO and local climatic factors in Panamá indicate that interannual CL cycles might be driven by ENSO, while the CL seasonality was mainly associated with temperature and rainfall variability. CL cases and SF abundance were associated in a fashion suggesting that sudden extraordinary changes in vector abundance might increase the potential for CL epidemic outbreaks, given that CL epidemics occur during the cold ENSO phase, a time when SF abundance shows its highest fluctuations. PMID:25275503

RainyDay: An Online, Open-Source Tool for Physically-based Rainfall and Flood Frequency Analysis

NASA Astrophysics Data System (ADS)

Wright, D.; Yu, G.; Holman, K. D.

2017-12-01

Flood frequency analysis in ungaged or changing watersheds typically requires rainfall intensity-duration-frequency (IDF) curves combined with hydrologic models. IDF curves only depict point-scale rainfall depth, while true rainstorms exhibit complex spatial and temporal structures. Floods result from these rainfall structures interacting with watershed features such as land cover, soils, and variable antecedent conditions as well as river channel processes. Thus, IDF curves are traditionally combined with a variety of "design storm" assumptions such as area reduction factors and idealized rainfall space-time distributions to translate rainfall depths into inputs that are suitable for flood hydrologic modeling. The impacts of such assumptions are relatively poorly understood. Meanwhile, modern precipitation estimates from gridded weather radar, grid-interpolated rain gages, satellites, and numerical weather models provide more realistic depictions of rainfall space-time structure. Usage of such datasets for rainfall and flood frequency analysis, however, are hindered by relatively short record lengths. We present RainyDay, an open-source stochastic storm transposition (SST) framework for generating large numbers of realistic rainfall "scenarios." SST "lengthens" the rainfall record by temporal resampling and geospatial transposition of observed storms to extract space-time information from regional gridded rainfall data. Relatively short (10-15 year) records of bias-corrected radar rainfall data are sufficient to estimate rainfall and flood events with much longer recurrence intervals including 100-year and 500-year events. We describe the SST methodology as implemented in RainyDay and compare rainfall IDF results from RainyDay to conventional estimates from NOAA Atlas 14. Then, we demonstrate some of the flood frequency analysis properties that are possible when RainyDay is integrated with a distributed hydrologic model, including robust estimation of flood hazards in a changing watershed. The U.S. Bureau of Reclamation is supporting the development of a web-based variant of RainyDay, a "beta" version of which is available at http://her.cee.wisc.edu/projects/rainyday/.

Precipitation Climatology over Mediterranean Basin from Ten Years of TRMM Measurements

NASA Technical Reports Server (NTRS)

Mehta, Amita V.; Yang, Song

2008-01-01

Climatological features of mesoscale rain activities over the Mediterranean region between 5 W-40 E and 28 N-48 N are examined using the Tropical Rainfall Measuring Mission (TRMM) 3B42 and 2A25 rain products. The 3B42 rainrates at 3-hourly, 0.25 deg x 0.25 deg spatial resolution for the last 10 years (January 1998 to July 2007) are used to form and analyze the 5-day mean and monthly mean climatology of rainfall. Results show considerable regional and seasonal differences of rainfall over the Mediterranean Region. The maximum rainfall (3-5 mm/day) occurs over the mountain regions of Europe, while the minimum rainfall is observed over North Africa (approximately 0.5 mm/day). The main rainy season over the Mediterranean Sea extends from October to March, with maximum rainfall occurring during November-December. Over the Mediterranean Sea, an average rainrate of approximately 1-2 mm/day is observed, but during the rainy season there is 20% larger rainfall over the western Mediterranean Sea than that over the eastern Mediterranean Sea. During the rainy season, mesoscale rain systems generally propagate from west to east and from north to south over the Mediterranean region, likely to be associated with Mediterranean cyclonic disturbances resulting from interactions among large-scale circulation, orography, and land-sea temperature contrast.

On the Predictability of Northeast Monsoon Rainfall over South Peninsular India in General Circulation Models

NASA Astrophysics Data System (ADS)

Nair, Archana; Acharya, Nachiketa; Singh, Ankita; Mohanty, U. C.; Panda, T. C.

2013-11-01

In this study the predictability of northeast monsoon (Oct-Nov-Dec) rainfall over peninsular India by eight general circulation model (GCM) outputs was analyzed. These GCM outputs (forecasts for the whole season issued in September) were compared with high-resolution observed gridded rainfall data obtained from the India Meteorological Department for the period 1982-2010. Rainfall, interannual variability (IAV), correlation coefficients, and index of agreement were examined for the outputs of eight GCMs and compared with observation. It was found that the models are able to reproduce rainfall and IAV to different extents. The predictive power of GCMs was also judged by determining the signal-to-noise ratio and the external error variance; it was noted that the predictive power of the models was usually very low. To examine dominant modes of interannual variability, empirical orthogonal function (EOF) analysis was also conducted. EOF analysis of the models revealed they were capable of representing the observed precipitation variability to some extent. The teleconnection between the sea surface temperature (SST) and northeast monsoon rainfall was also investigated and results suggest that during OND the SST over the equatorial Indian Ocean, the Bay of Bengal, the central Pacific Ocean (over Nino3 region), and the north and south Atlantic Ocean enhances northeast monsoon rainfall. This observed phenomenon is only predicted by the CCM3v6 model.

Thermodynamic ocean-atmosphere Coupling and the Predictability of Nordeste rainfall

NASA Astrophysics Data System (ADS)

Chang, P.; Saravanan, R.; Giannini, A.

2003-04-01

The interannual variability of rainfall in the northeastern region of Brazil, or Nordeste, is known to be very strongly correlated with sea surface temperature (SST) variability, of Atlantic and Pacific origin. For this reason the potential predictability of Nordeste rainfall is high. The current generation of state-of-the-art atmospheric models can replicate the observed rainfall variability with high skill when forced with the observed record of SST variability. The correlation between observed and modeled indices of Nordeste rainfall, in the AMIP-style integrations with two such models (NSIPP and CCM3) analyzed here, is of the order of 0.8, i.e. the models explain about 2/3 of the observed variability. Assuming that thermodynamic, ocean-atmosphere heat exchange plays the dominant role in tropical Atlantic SST variability on the seasonal to interannual time scale, we analyze its role in Nordeste rainfall predictability using an atmospheric general circulation model coupled to a slab ocean model. Predictability experiments initialized with observed December SST show that thermodynamic coupling plays a significant role in enhancing the persistence of SST anomalies, both in the tropical Pacific and in the tropical Atlantic. We show that thermodynamic coupling is sufficient to provide fairly accurate forecasts of tropical Atlantic SST in the boreal spring that are significantly better than the persistence forecasts. The consequences for the prediction of Nordeste rainfall are analyzed.

Plant and arthropod community sensitivity to rainfall manipulation but not nitrogen enrichment in a successional grassland ecosystem.

PubMed

Lee, Mark A; Manning, Pete; Walker, Catherine S; Power, Sally A

2014-12-01

Grasslands provide many ecosystem services including carbon storage, biodiversity preservation and livestock forage production. These ecosystem services will change in the future in response to multiple global environmental changes, including climate change and increased nitrogen inputs. We conducted an experimental study over 3 years in a mesotrophic grassland ecosystem in southern England. We aimed to expose plots to rainfall manipulation that simulated IPCC 4th Assessment projections for 2100 (+15% winter rainfall and -30% summer rainfall) or ambient climate, achieving +15% winter rainfall and -39% summer rainfall in rainfall-manipulated plots. Nitrogen (40 kg ha(-1) year(-1)) was also added to half of the experimental plots in factorial combination. Plant species composition and above ground biomass were not affected by rainfall in the first 2 years and the plant community did not respond to nitrogen enrichment throughout the experiment. In the third year, above-ground plant biomass declined in rainfall-manipulated plots, driven by a decline in the abundances of grass species characteristic of moist soils. Declining plant biomass was also associated with changes to arthropod communities, with lower abundances of plant-feeding Auchenorrhyncha and carnivorous Araneae indicating multi-trophic responses to rainfall manipulation. Plant and arthropod community composition and plant biomass responses to rainfall manipulation were not modified by nitrogen enrichment, which was not expected, but may have resulted from prior nitrogen saturation and/or phosphorus limitation. Overall, our study demonstrates that climate change may in future influence plant productivity and induce multi-trophic responses in grasslands.

Association between Childhood Diarrhoeal Incidence and Climatic Factors in Urban and Rural Settings in the Health District of Mbour, Senegal

PubMed Central

Thiam, Sokhna; Diène, Aminata N.; Sy, Ibrahima; Winkler, Mirko S.; Schindler, Christian; Ndione, Jacques A.; Faye, Ousmane; Vounatsou, Penelope; Utzinger, Jürg; Cissé, Guéladio

2017-01-01

We assessed the association between childhood diarrhoeal incidence and climatic factors in rural and urban settings in the health district of Mbour in western Senegal. We used monthly diarrhoeal case records among children under five years registered in 24 health facilities over a four-year period (2011–2014). Climatic data (i.e., daily temperature, night temperature and rainfall) for the same four-year period were obtained. We performed a negative binomial regression model to establish the relationship between monthly diarrhoeal incidence and climatic factors of the same and the previous month. There were two annual peaks in diarrhoeal incidence: one during the cold dry season and one during the rainy season. We observed a positive association between diarrhoeal incidence and high average temperature of 36 °C and above and high cumulative monthly rainfall at 57 mm and above. The association between diarrhoeal incidence and temperature was stronger in rural compared to urban settings, while higher rainfall was associated with higher diarrhoeal incidence in the urban settings. Concluding, this study identified significant health–climate interactions and calls for effective preventive measures in the health district of Mbour. Particular attention should be paid to urban settings where diarrhoea was most common in order to reduce the high incidence in the context of climatic variability, which is expected to increase in urban areas in the face of global warming. PMID:28895927

The effects of meteorological factors on airborne fungal spore concentration in two areas differing in urbanisation level

NASA Astrophysics Data System (ADS)

Oliveira, M.; Ribeiro, H.; Delgado, J. L.; Abreu, I.

2009-01-01

Although fungal spores are an ever-present component of the atmosphere throughout the year, their concentration oscillates widely. This work aims to establish correlations between fungal spore concentrations in Porto and Amares and meteorological data. The seasonal distribution of fungal spores was studied continuously (2005-2007) using volumetric spore traps. To determine the effect of meteorological factors (temperature, relative humidity and rainfall) on spore concentration, the Spearman rank correlation test was used. In both locations, the most abundant fungal spores were Cladosporium, Agaricus, Agrocybe, Alternaria and Aspergillus/Penicillium, the highest concentrations being found during summer and autumn. In the present study, with the exception of Coprinus and Pleospora, spore concentrations were higher in the rural area than in the urban location. Among the selected spore types, spring-autumn spores ( Coprinus, Didymella, Leptosphaeria and Pleospora) exhibited negative correlations with temperature and positive correlations both with relative humidity and rainfall level. On the contrary, late spring-early summer (Smuts) and summer spores ( Alternaria, Cladosporium, Epicoccum, Ganoderma, Stemphylium and Ustilago) exhibited positive correlations with temperature and negative correlations both with relative humidity and rainfall level. Rust, a frequent spore type during summer, had a positive correlation with temperature. Aspergillus/Penicillium, showed no correlation with the meteorological factors analysed. This knowledge can be useful for agriculture, allowing more efficient and reliable application of pesticides, and for human health, by improving the diagnosis and treatment of respiratory allergic disease.

Seasonal modeling of hand, foot, and mouth disease as a function of meteorological variations in Chongqing, China

NASA Astrophysics Data System (ADS)

Wang, Pin; Zhao, Han; You, Fangxin; Zhou, Hailong; Goggins, William B.

2017-08-01

Hand, foot, and mouth disease (HFMD) is an enterovirus-induced infectious disease, mainly affecting children under 5 years old. Outbreaks of HFMD in recent years indicate the disease interacts with both the weather and season. This study aimed to investigate the seasonal association between HFMD and weather variation in Chongqing, China. Generalized additive models and distributed lag non-linear models based on a maximum lag of 14 days, with negative binomial distribution assumed to account for overdispersion, were constructed to model the association between reporting HFMD cases from 2009 to 2014 and daily mean temperature, relative humidity, total rainfall and sun duration, adjusting for trend, season, and day of the week. The year-round temperature and relative humidity, rainfall in summer, and sun duration in winter were all significantly associated with HFMD. An inverted-U relationship was found between mean temperature and HFMD above 19 °C in summer, with a maximum morbidity at 27 °C, while the risk increased linearly with the temperature in winter. A hockey-stick association was found for relative humidity in summer with increasing risks over 60%. Heavy rainfall, relative to no rain, was found to be associated with reduced HFMD risk in summer and 2 h of sunshine could decrease the risk by 21% in winter. The present study showed meteorological variables were differentially associated with HFMD incidence in two seasons. Short-term weather variation surveillance and forecasting could be employed as an early indicator for potential HFMD outbreaks.

Impact of Climate on the incidence of Dengue Haemorrhagic fever in Semarang City

NASA Astrophysics Data System (ADS)

Khairunisa, Ummi; Endah Wahyuningsih, Nur; Suhartono; Hapsari

2018-05-01

Dengue Haemorrhagic Fever (DHF) is one of major health problems in Indonesia. DHF is a caused by the dengue virus and potentially deadly infection spread by some mosquitos. The mosquito Aedes aegypti is the main species that spreads this disease. The incidence rate of dengue haemorrhagic fever was still increased in 2011 to 2015 in Indonesia. Dengue viruses and their mosquito vectors are sensitive to their environment. Temperature, rainfall and humidity have well-define roles in the transmission cycle. Therefore changes in these conditions may contribute to increasing incidence. The aim of this study was to analyze the relationship between climate factors and the incidence rate of dengue hemorrhagic fever in Semarang City. The type of research was analytic with cross sectional study. The sample used is the climate data from Meteorology, Climatology and Geophysics Agency (BMKG) and the number of dengue cases from Health Office in Semarang City from 2011 to 2016. Data were analyzed using Pearson trials with α=0,05. Base on this study here air temperature and relative humidity were moderate correlation with negative direction on air temperature (p = 0,000 and r = -0, 429), weakly correlation with positive direction on rainfall (p = 0,014 and r = 0,288) and humidity (p=0,001 and r = 0,382) with dengue hemorrhagic fever incidence in Semarang City. The conclusions of this study there were correlation between climate (air temperature, rainfall, and relative humidity) and DHF in Semarang City in 2011-2016.

Atmospheric electricity/meteorology analysis

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard; Buechler, Dennis

1993-01-01

This activity focuses on Lightning Imaging Sensor (LIS)/Lightning Mapper Sensor (LMS) algorithm development and applied research. Specifically we are exploring the relationships between (1) global and regional lightning activity and rainfall, and (2) storm electrical development, physics, and the role of the environment. U.S. composite radar-rainfall maps and ground strike lightning maps are used to understand lightning-rainfall relationships at the regional scale. These observations are then compared to SSM/I brightness temperatures to simulate LIS/TRMM multi-sensor algorithm data sets. These data sets are supplied to the WETNET project archive. WSR88-D (NEXRAD) data are also used as it becomes available. The results of this study allow us to examine the information content from lightning imaging sensors in low-earth and geostationary orbits. Analysis of tropical and U.S. data sets continues. A neural network/sensor fusion algorithm is being refined for objectively associating lightning and rainfall with their parent storm systems. Total lightning data from interferometers are being used in conjunction with data from the national lightning network. A 6-year lightning/rainfall climatology has been assembled for LIS sampling studies.

Indian Monsoon Rainfall Variability During the Common Era: Implications on the Ancient Civilization

NASA Astrophysics Data System (ADS)

Pothuri, D.

2017-12-01

Indian monsoon rainfall variability was reconstructed during last two millennia by using the δ18Ow from a sediment core in the Krishna-Godavari Basin. Higher δ18Ow values during Dark Age Cold Period (DACP) (1550 to 1250 years BP) and Little Ice Age (LIA) (700 to 200 years BP) represent less Indian monsoon rainfall. Whereas during Medieval Warm Period (MWP) (1200 to 800 years BP) and major portion of Roman Warm Period (RWP) 2000 to 1550 years BP) document more rainfall in the Indian subcontinent as evident from lower δ18Ow values. A significant correlation exist between the Bay of Bengal (BoB) sea surface temperature (SST) and Indian monsoon proxy (i.e. δ18Ow), which suggests that; (i) the forcing mechanism of the Indian monsoon rainfall variability during last two millennia was controlled by the thermal contrast between the Indian Ocean and Asian Land Mass, and (ii) the evaporation processes in the BoB and associated SST are strongly coupled with the Indian Monsoon variability over the last two millennia.

Identifying hydrological pre-conditions and rainfall triggers of slope failures for 2014 storm events in the Ialomita Subcarpathians, Romania

NASA Astrophysics Data System (ADS)

Chitu, Zenaida; Bogaard, Thom; Busuioc, Aristita; Burcea, Sorin; Adler, Mary-Jeanne; Sandric, Ionut

2015-04-01

Like in many parts of the world, in Romania, landslides represent recurrent phenomena that produce numerous damages to infrastructure every few years. Various studies on landslide occurrence in the Curvature Subcarpathians reveal that rainfall represents the most important triggering factor for landslides. Depending on rainfall characteristics and environmental factors different types of landslides were recorded in the Ialomita Subcarpathians: slumps, earthflows and complex landslides. This area, located in the western part of Curvature Subcarpathians, is characterized by a very complex geology whose main features are represented by the nappes system, the post tectonic covers, the diapirism phenomena and vertical faults. This work aims to investigate hydrological pre-conditions and rainfall characteristics which triggered slope failures in 2014 in the Ialomita Subcarpathians, Romania. Hydrological pre-conditions were investigated by means of water balance analysis and low flow techniques, while spatial and temporal patterns of rainfalls were estimated using radar data and six rain gauges. Additionally, six soil moisture stations that are fitted with volumetric soil moisture sensors and temperature soil sensors were used to estimate the antecedent soil moisture conditions.

Morning-evening differences in global and regional oceanic precipitation as observed by the SSM/I

NASA Technical Reports Server (NTRS)

Petty, Grant W.; Katsaros, Kristina B.

1992-01-01

For the present preliminary analysis of oceanic rainfall statistics, global oceanic SSM/I data were simply scanned for pixels which exhibited a 37 GHz polarization difference (vertically polarized brightness temperatures minus horizontally polarized brightness temperatures) of less than 15 K. Such a low polarization difference over the open ocean is a completely unambiguous indication of moderate to intense precipitation. Co-located brightness temperatures from all seven channels of the SSM/I were saved for each pixel so identified. Bad scans and geographically mislocated block of data were objectively identified and removed from the resulting data base. We collected global oceanic rainfall data for two time periods, each one month in length. The first period (20 July-19 August 1987) coincides with the peak of the Northern Hemisphere summer. The second period (13 January-12 February 1988) coincides with the Northern Hemisphere winter.

Early warning method of Glacial Lake Outburst Floods based on temperature and rainfall

NASA Astrophysics Data System (ADS)

Liu, Jingjing; Su, Pengcheng; Cheng, Zunlan

2017-04-01

Glacial lake outburst floods (GLOFs) are serious disasters in glacial areas. At present, glaciers are retreating while glacial lake area and the outburst risk increases due to the global warming. Therefore, the research of early warning method of GLOFs is important to prevent and reduce the disasters. This paper provides an early warning method using the temperature and rainfall as indices. The daily growth rate of positive antecedent accumulative temperature and the antecedent thirty days accumulative precipitation are calculated for 21 events of GLOF before 2010, based on data from the 21 meteorological stations nearby. The result shows that all the events are above the curve, TV = -0.0193RDC + 3.0018, which can be taken as the early warning threshold curve. This has been verified by the GLOF events in the Ranzeaco glacial lake on 2013-07-05.

Assessing the impact of climate-change scenarios on landslide occurrence in Umbria Region, Italy

NASA Astrophysics Data System (ADS)

Ciabatta, L.; Camici, S.; Brocca, L.; Ponziani, F.; Stelluti, M.; Berni, N.; Moramarco, T.

2016-10-01

Landslides are frequent and widespread geomorphological phenomena causing loss of human life and damage to property. The main tool for assessing landslide risk relies on rainfall thresholds and thus, many countries established early warning systems aimed to landslide hazard assessment. The Umbria Region Civil Protection Centre developed an operational early warning system for landslide risk assessment, named PRESSCA, based on the soil saturation conditions to identify rainfall thresholds. These thresholds, currently used by the Civil Protection operators for the day-by-day landslide hazard assessment, provided satisfactory results with more than 86% of the landslides events correctly identified during the period 1990-2013. In this study, the PRESSCA system was employed for the assessment of climate change impact on landslide hazard in Central Italy. The outputs of five different Global Circulation Models (GCMs) were downscaled and weather generators were used for obtaining hourly rainfall and temperature time series from daily GCMs projection. Then, PRESSCA system was employed to estimate the number of landslide occurrence per year. By comparing results obtained for three different periods (1990-2013 (baseline), 2040-2069 and 2070-2099), for the Umbria territory a general increase in events occurrence was expected (up to more than 40%) in the future period, mainly during the winter season. The results also revealed that the effect of climate change on landslides was not straightforward to identify and the close interaction between rainfall magnitude/intensity, temperature and soil moisture should be analysed in depth. Overall, soil moisture was projected to decrease throughout the year but during the wet season the variations with respect to the present period were very small. Specifically, it was found that during the warm-dry season, due to the strong decrease of soil moisture, even for a sensible increase in rainfall intensity, the landslide occurrence was unchanged. Conversely, during the cold-wet season, the number of landslide events increased considerably if a positive variation in rainfall amount, more significant than rainfall intensity, was coupled with small negative variations in soil moisture.

Using Rainfall and Temperature Data in the Evaluation of National Malaria Control Programs in Africa.

PubMed

Thomson, Madeleine C; Ukawuba, Israel; Hershey, Christine L; Bennett, Adam; Ceccato, Pietro; Lyon, Bradfield; Dinku, Tufa

2017-09-01

Since 2010, the Roll Back Malaria (RBM) Partnership, including National Malaria Control Programs, donor agencies (e.g., President's Malaria Initiative and Global Fund), and other stakeholders have been evaluating the impact of scaling up malaria control interventions on all-cause under-five mortality in several countries in sub-Saharan Africa. The evaluation framework assesses whether the deployed interventions have had an impact on malaria morbidity and mortality and requires consideration of potential nonintervention influencers of transmission, such as drought/floods or higher temperatures. Herein, we assess the likely effect of climate on the assessment of the impact malaria interventions in 10 priority countries/regions in eastern, western, and southern Africa for the President's Malaria Initiative. We used newly available quality controlled Enhanced National Climate Services rainfall and temperature products as well as global climate products to investigate likely impacts of climate on malaria evaluations and test the assumption that changing the baseline period can significantly impact on the influence of climate in the assessment of interventions. Based on current baseline periods used in national malaria impact assessments, we identify three countries/regions where current evaluations may overestimate the impact of interventions (Tanzania, Zanzibar, Uganda) and three countries where current malaria evaluations may underestimate the impact of interventions (Mali, Senegal and Ethiopia). In four countries (Rwanda, Malawi, Mozambique, and Angola) there was no strong difference in climate suitability for malaria in the pre- and post-intervention period. In part, this may be due to data quality and analysis issues.

Analysis of hydrologic variation under climate change environment in southern Taiwan

NASA Astrophysics Data System (ADS)

Chen, Yung-Chau; Chen, Yu-Chin; Chen, Wen-Fu

2014-05-01

Impact and adaptation is an important issue in response to climate change. We need to know the affections of climate change on hydrologic characteristics before estimating the impacts and making adaptation strategies of concerned area. The wet and dry seasons of southern Taiwan are significant. In addition, the amount of average annual rainfall is about 2,100mm in southern Taiwan. Most of rainfalls happen in wet season and are caused by cyclones (typhoons) or thunderstorms in wet season. It implies that both quantity and intensity of rainfall are large in wet season, while they are small in dry season. Corresponding to the phenomena, the possibility of flood in wet season and draught in dry season is high. This means significant hydrologic variations may cause disasters. The purpose of this study is to analyze hydrologic variation due to recent climate changes in southern Taiwan, and provide decision makers some information to understand possible impacts and make adaptation strategies. Before typhoon Morakot hit Taiwan, southern Taiwan was suffering from aridity. As usual, people were expecting the rainfall accompanied with typhoons will resolve the drought in this area. However, it fell down huge amount of water within a short period of time and the rain became a big disaster in this area. The rainfall is an over 200-year event, a record breaker. The data used in this research is based on the records of Taiwan Central Weather Bureau at Chiayi, Tainan, Kaohsiung, and Hengchun station, respectively. The trends of temperature, amount of rainfall, and number of rainy days are examined. Both Mann-Kendall trend test and linear regression method are chosen as the means to do trend examination.The results show that annual mean temperatures at Chiayi, Tainan, Kaohsiung, and Hengchun have raised 0.5~0.9°C during past decades under the impact of global warming. The amount of annual rainfall does not appear statistically significant trend. However, the number of annual rainy day is reduced by15%. It suggests that rainfall intensity is increased and the mean length of drought period is increased as well, generally. That means possibility of flood and drought is becoming larger in future. Decision makers should pay more attentions about it and proceed adaptation strategies plans.

Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy)

USGS Publications Warehouse

Napolitano, E.; Fusco, F; Baum, Rex L.; Godt, Jonathan W.; De Vita, P.

2016-01-01

Mountainous areas surrounding the Campanian Plain and the Somma-Vesuvius volcano (southern Italy) are among the most risky areas of Italy due to the repeated occurrence of rainfallinduced debris flows along ash-fall pyroclastic soil-mantled slopes. In this geomorphological framework, rainfall patterns, hydrological processes taking place within multi-layered ash-fall pyroclastic deposits and soil antecedent moisture status are the principal factors to be taken into account to assess triggering rainfall conditions and the related hazard. This paper presents the outcomes of an experimental study based on integrated analyses consisting of the reconstruction of physical models of landslides, in situ hydrological monitoring, and hydrological and slope stability modeling, carried out on four representative source areas of debris flows that occurred in May 1998 in the Sarno Mountain Range. The hydrological monitoring was carried out during 2011 using nests of tensiometers and Watermark pressure head sensors and also through a rainfall and air temperature recording station. Time series of measured pressure head were used to calibrate a hydrological numerical model of the pyroclastic soil mantle for 2011, which was re-run for a 12-year period beginning in 2000, given the availability of rainfall and air temperature monitoring data. Such an approach allowed us to reconstruct the regime of pressure head at a daily time scale for a long period, which is representative of about 11 hydrologic years with different meteorological conditions. Based on this simulated time series, average winter and summer hydrological conditions were chosen to carry out hydrological and stability modeling of sample slopes and to identify Intensity- Duration rainfall thresholds by a deterministic approach. Among principal results, the opposing winter and summer antecedent pressure head (soil moisture) conditions were found to exert a significant control on intensity and duration of rainfall triggering events. Going from winter to summer conditions requires a strong increase of intensity and/or duration to induce landslides. The results identify an approach to account for different hazard conditions related to seasonality of hydrological processes inside the ash-fall pyroclastic soil mantle. Moreover, they highlight another important factor of uncertainty that potentially affects rainfall thresholds triggering shallow landslides reconstructed by empirical approaches.

Tropical Cyclones Feed More Heavy Rain in a Warmer Climate

NASA Technical Reports Server (NTRS)

Lau, K.-M.; Zhou, Y. P.; Wu, H.-T.

2007-01-01

The possible linkage of tropical cyclones (TC) to global warming is a hotly debated scientific topic, with immense societal impacts. Most of the debate has been focused on the issue of uncertainty in the use of non-research quality data for long-term trend analyses, especially with regard to TC intensity provided by TC forecasting centers. On the other hand, it is well known that TCs are associated with heavy rain during the processes of genesis and intensification, and that there are growing evidences that rainfall characteristics (not total rainfall) are most likely to be affected by global warming. Yet, satellite rainfall data have not been exploited in any recent studies of linkage between tropical cyclones (TC) and global warming. This is mostly due to the large uncertainties associated with detection of long-term trend in satellite rainfall estimates over the ocean. This problem, as we demonstrate in this paper, can be alleviated by examining rainfall distribution, rather than rainfall total. This paper is the first to use research-quality, satellite-derived rainfall from TRMM and GPCP over the tropical oceans to estimate shift in rainfall distribution during the TC season, and its relationships with TCs, and sea surface temperature (SST) in the two major ocean basins, the northern Atlantic and the northern Pacific for 1979-2005. From the rainfall distribution, we derive the TC contributions to rainfall in various extreme rainfall categories as a function to time. Our results show a definitive trend indicating that TCs are contributing increasingly to heavier rain events, i.e., intense TC's are more frequent in the last 27 years. The TC contribution to top 5% heavy rain has nearly doubled in the last two decades in the North Atlantic, and has increased by about 10% in the North Pacific. The different rate of increase in TC contribution to heavy rain may be related to the different rates of different rate of expansion of the warm pool (SST >2S0 C) area in the two oceans.

Projected Changes in Seasonal Mean Temperature and Rainfall (2011-2040) in Cagayan Valley, Philippines

NASA Astrophysics Data System (ADS)

Basconcillo, J. Q.; Lucero, A. J. R.; Solis, A. S.; Kanamaru, H.; Sandoval, R. S.; Bautista, E. U.

2014-12-01

Among Filipinos, a meal is most often considered incomplete without rice. There is a high regard for rice in the entire archipelago that in 2012, the country's rice production was accounted to more than 18 million tons with an equivalent harvested area of 4.7 million hectares. This means that from the 5.4 million hectares of arable land in the Philippines, 11 percent are found and being utilized for rice production in Cagayan Valley (CV). In the same year, more than 13 percent of the country's total annual rice production was produced in CV. Rice production also provides employment to 844,000 persons (out of 1.4 million persons) which suggest that occupation and livelihood in Cagayan Valley are strongly anchored in rice production. These figures outline the imaginable vulnerability of rice production in CV amidst varying issues such as land conversion, urbanization, increase in population, retention of farming households, and climate change. While all these issues are of equal importance, this paper is directed towards the understanding the projected changes in seasonal rainfall and mean temperature (2011-2040). It is envisioned by this study that a successful climate change adaptation starts with the provision of climate projections hence this paper's objective to investigate on the changes in climate patterns and extreme events. Projected changes are zonally limited to the Provinces of Cagayan, Isabela, Nueva Vizcaya, and Quirino based on the statistical downscaling of three global climate models (BCM2, CNCM3, and MPEH5) and two emission scenarios (A1B and A2). With the idea that rainfall and temperature varies with topography, the AURELHY technique was utilized in interpolating climate projections. Results obtained from the statistical downscaling showed that there will be significant climate changes from 2011-2040 in terms of rainfall and mean temperature. There are also indications of increasing frequency of extreme 24-hour rainfall and number of dry days (especially in Tuguegarao City). This study was forged in a partnership of PAGASA and FAO AMICAF. Further efforts to improve climate change adaptations in CV are directed towards provision of climate projections as input to crop and water resources modeling, market modeling, hunger and poverty reduction, and policy formulation.

Signature of present and projected climate change at an urban scale: The case of Addis Ababa

NASA Astrophysics Data System (ADS)

Arsiso, Bisrat Kifle; Mengistu Tsidu, Gizaw; Stoffberg, Gerrit Hendrik

2018-06-01

Understanding climate change and variability at an urban scale is essential for water resource management, land use planning, development of adaption plans, mitigation of air and water pollution. However, there are serious challenges to meet these goals due to unavailability of observed and/or simulated high resolution spatial and temporal climate data. The statistical downscaling of general circulation climate model, for instance, is usually driven by sparse observational data hindering the use of downscaled data to investigate urban scale climate variability and change in the past. Recently, these challenges are partly resolved by concerted international effort to produce global and high spatial resolution climate data. In this study, the 1 km2 high resolution NIMR-HadGEM2-AO simulations for future projections under Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios and gridded observations provided by Worldclim data center are used to assess changes in rainfall, minimum and maximum temperature expected under the two scenarios over Addis Ababa city. The gridded 1 km2 observational data set for the base period (1950-2000) is compared to observation from a meteorological station in the city in order to assess its quality for use as a reference (baseline) data. The comparison revealed that the data set has a very good quality. The rainfall anomalies under RCPs scenarios are wet in the 2030s (2020-2039), 2050s (2040-2069) and 2080s (2070-2099). Both minimum and maximum temperature anomalies under RCPs are successively getting warmer during these periods. Thus, the projected changes under RCPs scenarios show a general increase in rainfall and temperatures with strong variabilities in rainfall during rainy season implying level of difficulty in water resource use and management as well as land use planning and management.

Effect of meteorological variables on Plasmodium vivax and Plasmodium falciparum malaria in outbreak prone districts of Rajasthan, India.

PubMed

Lingala, Mercy A L

Malaria is a public health problem caused by Plasmodium parasite and transmitted by anopheline mosquitoes. Arid and semi-arid regions of western India are prone to malaria outbreaks. Malaria outbreak prone districts viz. Bikaner, Barmer and Jodhpur were selected to study the effect of meteorological variables on Plasmodium vivax and Plasmodium falciparum malaria outbreaks for the period of 2009-2012. The data of monthly malaria cases and meteorological variables was analysed using SPSS 20v. Spearman correlation analysis was conducted to examine the strength of the relationship between meteorological variables, P. vivax and P. falciparum malaria cases. Pearson's correlation analysis was carried out among the meteorological variables to observe the independent effect of each independent variable on the outcome. Results indicate that malaria outbreaks have occurred in Bikaner and Barmer due to continuous rains for more than two months. Rainfall has shown to be an important predictor of malaria outbreaks in Rajasthan. P. vivax is more significantly correlated with rainfall, minimum temperature (P<0.01) and less significantly with relative humidity (P<0.05); whereas P. falciparum is significantly correlated with rainfall, relative humidity (P<0.01) and less significantly with temperature (P<0.05). The determination of the lag period for P. vivax is relative humidity and for P. falciparum is temperature. The lag period between malaria cases and rainfall is shorter for P. vivax than P. falciparum. In conclusion, the knowledge generated is not only useful to take prompt malaria control interventions but also helpful to develop better forecasting model in outbreak prone regions. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

Effect of Climate Factors on the Childhood Pneumonia in Papua New Guinea: A Time-Series Analysis.

PubMed

Kim, Jinseob; Kim, Jong-Hun; Cheong, Hae-Kwan; Kim, Ho; Honda, Yasushi; Ha, Mina; Hashizume, Masahiro; Kolam, Joel; Inape, Kasis

2016-02-15

This study aimed to assess the association between climate factors and the incidence of childhood pneumonia in Papua New Guinea quantitatively and to evaluate the variability of the effect size according to their geographic properties. The pneumonia incidence in children under five-year and meteorological factors were obtained from six areas, including monthly rainfall and the monthly average daily maximum temperatures during the period from 1997 to 2006 from national health surveillance data. A generalized linear model was applied to measure the effect size of local and regional climate factor. The pooled risk of pneumonia in children per every 10 mm increase of rainfall was 0.24% (95% confidence interval: -0.01%-0.50%), and risk per every 1 °C increase of the monthly mean of the maximum daily temperatures was 4.88% (95% CI: 1.57-8.30). Southern oscillation index and dipole mode index showed an overall negative effect on childhood pneumonia incidence, -0.57% and -4.30%, respectively, and the risk of pneumonia was higher in the dry season than in the rainy season (pooled effect: 12.08%). There was a variability in the relationship between climate factors and pneumonia which is assumed to reflect distribution of the determinants of and vulnerability to pneumonia in the community.

Spatio-temporal distribution of dengue fever under scenarios of climate change in the southern Taiwan

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung

2014-05-01

Dengue fever has been recognized as the most important widespread vector-borne infectious disease in recent decades. Over 40% of the world's population is risk from dengue and about 50-100 million people are infected world wide annually. Previous studies have found that dengue fever is highly correlated with climate covariates. Thus, the potential effects of global climate change on dengue fever are crucial to epidemic concern, in particular, the transmission of the disease. This present study investigated the nonlinearity of time-delayed impact of climate on spatio-temporal variations of dengue fever in the southern Taiwan during 1998 to 2011. A distributed lag nonlinear model (DLNM) is used to assess the nonlinear lagged effects of meteorology. The statistically significant meteorological factors are considered, including weekly minimum temperature and maximum 24-hour rainfall. The relative risk and the distribution of dengue fever then predict under various climate change scenarios. The result shows that the relative risk is similar for different scenarios. In addition, the impact of rainfall on the incidence risk is higher than temperature. Moreover, the incidence risk is associated to spatially population distribution. The results can be served as practical reference for environmental regulators for the epidemic prevention under climate change scenarios.

Convective Systems Over the South China Sea: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Shie, C.-L.; Johnson, D.; Simpson, J.; Braun, S.; Johnson, R.; Ciesielski, P. E.; Starr, David OC. (Technical Monitor)

2002-01-01

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, ships, wind profilers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convective storms and air pattern changes associated with monsoons over the South China Sea region. SCSMEX also provided rainfall estimates which allows for comparisons with those obtained from the Tropical Rainfall Measuring Mission (TRMM), a low earth orbit satellite designed to measure rainfall from space. The Goddard Cumulus Ensemble (GCE) model (with 1-km grid size) is used to understand and quantify the precipitation processes associated with the summer monsoon over the South China Sea. This is the first (loud-resolving model used to simulate precipitation processes in this particular region. The GCE-model results captured many of the observed precipitation characteristics because it used a fine grid size. For example, the temporal variation of the simulated rainfall compares quite well to the sounding-estimated rainfall variation. The time and domain-averaged temperature (heating/cooling) and water vapor (drying/ moistening) budgets are in good agreement with observations. The GCE-model-simulated rainfall amount also agrees well with TRMM rainfall data. The results show there is more evaporation from the ocean surface prior to the onset of the monsoon than after the on-et of monsoon when rainfall increases. Forcing due to net radiation (solar heating minus longwave cooling) is responsible for about 25% of the precipitation in SCSMEX The transfer of heat from the ocean into the atmosphere does not contribute significantly to the rainfall in SCSMEX. Model sensitivity tests indicated that total rain production is reduced 17-18% in runs neglecting the ice phase. The SCSMEX results are compared to other GCE-model-simulated weather systems that developed during other field campaigns (i.e., west Pacific warm pool region, eastern Atlantic region and central USA). Large-scale forcing vie temperature and water vapor tendency, is the major energy source for net condensation in the tropical cases. The effects of large-scale cooling exceed that of large-scale moistening in the west pacific warm pool region and eastern Atlantic region. For SCSMEX, however, the effects of large-scale moistening predominate. Net radiation and sensible and latent hc,it fluxes play a much more important role in the central USA.

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.

Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

NASA Astrophysics Data System (ADS)

Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

2016-12-01

Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong LST and Emissivity anomaly over the lake in comparison with surrounding lands. These anomalies should explain rainfall underestimations tendency over this lake. LST and Emissivity of lake Poopó are closest to surrounding land and the slight observed rainfall overestimation appears to be related to the very arid context of the region.

Identification of tipping elements of the Indian Summer Monsoon using climate network approach

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Surovyatkina, Elena; Kurths, Jurgen

2015-04-01

Spatial and temporal variability of the rainfall is a vital question for more than one billion of people inhabiting the Indian subcontinent. Indian Summer Monsoon (ISM) rainfall is crucial for India's economy, social welfare, and environment and large efforts are being put into predicting the Indian Summer Monsoon. For predictability of the ISM, it is crucial to identify tipping elements - regions over the Indian subcontinent which play a key role in the spatial organization of the Indian monsoon system. Here, we use climate network approach for identification of such tipping elements of the ISM. First, we build climate networks of the extreme rainfall, surface air temperature and pressure over the Indian subcontinent for pre-monsoon, monsoon and post-monsoon seasons. We construct network of extreme rainfall event using observational satellite data from 1998 to 2012 from the Tropical Rainfall Measuring Mission (TRMM 3B42V7) and reanalysis gridded daily rainfall data for a time period of 57 years (1951-2007) (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE). For the network of surface air temperature and pressure fields, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). Second, we filter out data by coarse-graining the network through network measures, and identify tipping regions of the ISM. Finally, we compare obtained results of the network analysis with surface wind fields and show that occurrence of the tipping elements is mostly caused by monsoonal wind circulation, migration of the Intertropical Convergence Zone (ITCZ) and Westerlies. We conclude that climate network approach enables to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to identify tipping regions of the ISM. Obtained tipping elements deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Drought in West Africa: How CHIRPS and Reference Evapotranspiration can be used for Index Insurance in a Non-Stationary Setting

NASA Astrophysics Data System (ADS)

Blakeley, S. L.; Husak, G. J.; Harrison, L.; Funk, C. C.; Osgood, D. E.; Peterson, P.

2017-12-01

Index insurance is increasingly used as a safety net and productivity tool in order to improve the resilience of small-holder farmers in developing countries. In West Africa, there are already index insurance projects in many countries, and various non-governmental organizations are eager to expand implementation of this risk management tool. Often, index insurance payouts rely on rainfall to determine drought years, but designation of years based on precipitation variations is particularly complex in places like West Africa where precipitation is subject to much natural variability across timescales [Giannini 2003, among others]. Furthermore, farmers must also rely on other weather factors for good crop yields, such as the availability of moisture for their plants to absorb and maximum daily temperatures staying within an acceptable range for the crops. In this presentation, the payouts of an index based on rainfall (as measured by the Climate Hazards Group Infrared Precipitation with Stations {CHIRPS} dataset) is compared to the payouts of an index using reference evapotranspiration data (using the ASCE's Penmen-Monteith formula and MERRA-2 drivers). The West African rainfall index exhibits a fair amount of long-term variability, reflective of the Atlantic Multidecadal Oscillation, but the reference evapotranspiration index shows different variability, through changes in radiative forcing and temperatures. Therefore, the use of rainfall for an index is appropriate for capturing rainfall deficits, but reference evapotranspiration may also be an appropriate addition to an index or as a stand-alone index for capturing crop stress. In summary, the results point to farmer input as an invaluable source of knowledge in determining the most appropriate dataset as an index for crop insurance. Alessandra Giannini, R Saravanan, and P Chang. Oceanic forcing of Sahel rainfall on interannual to interdecadal time scales. Science, 302(5647):1027-1030, 2003.

Vegetation controls on weathering intensity during the last deglacial transition in southeast Africa

USGS Publications Warehouse

Ivory, Sarah J.; McGlue, Michael M.; Ellis, Geoffrey S.; Lézine, Anne-Marie; Cohen, Andrew S.; Vincens, Annie

2015-01-01

Tropical climate is rapidly changing, but the effects of these changes on the geosphere are unknown, despite a likelihood of climatically-induced changes on weathering and erosion. The lack of long, continuous paleo-records prevents an examination of terrestrial responses to climate change with sufficient detail to answer questions about how systems behaved in the past and may alter in the future. We use high-resolution records of pollen, clay mineralogy, and particle size from a drill core from Lake Malawi, southeast Africa, to examine atmosphere-biosphere-geosphere interactions during the last deglaciation (~18–9 ka), a period of dramatic temperature and hydrologic changes. The results demonstrate that climatic controls on Lake Malawi vegetation are critically important to weathering processes and erosion patterns during the deglaciation. At 18 ka, afromontane forests dominated but were progressively replaced by tropical seasonal forest, as summer rainfall increased. Despite indication of decreased rainfall, drought-intolerant forest persisted through the Younger Dryas (YD) resulting from a shorter dry season. Following the YD, an intensified summer monsoon and increased rainfall seasonality were coeval with forest decline and expansion of drought-tolerant miombo woodland. Clay minerals closely track the vegetation record, with high ratios of kaolinite to smectite (K/S) indicating heavy leaching when forest predominates, despite variable rainfall. In the early Holocene, when rainfall and temperature increased (effective moisture remained low), open woodlands expansion resulted in decreased K/S, suggesting a reduction in chemical weathering intensity. Terrigenous sediment mass accumulation rates also increased, suggesting critical linkages among open vegetation and erosion during intervals of enhanced summer rainfall. This study shows a strong, direct influence of vegetation composition on weathering intensity in the tropics. As climate change will likely impact this interplay between the biosphere and geosphere, tropical landscape change could lead to deleterious effects on soil and water quality in regions with little infrastructure for mitigation.

Vegetation Controls on Weathering Intensity during the Last Deglacial Transition in Southeast Africa

PubMed Central

Ivory, Sarah J.; McGlue, Michael M.; Ellis, Geoffrey S.; Lézine, Anne-Marie; Cohen, Andrew S.; Vincens, Annie

2014-01-01

Tropical climate is rapidly changing, but the effects of these changes on the geosphere are unknown, despite a likelihood of climatically-induced changes on weathering and erosion. The lack of long, continuous paleo-records prevents an examination of terrestrial responses to climate change with sufficient detail to answer questions about how systems behaved in the past and may alter in the future. We use high-resolution records of pollen, clay mineralogy, and particle size from a drill core from Lake Malawi, southeast Africa, to examine atmosphere-biosphere-geosphere interactions during the last deglaciation (∼18–9 ka), a period of dramatic temperature and hydrologic changes. The results demonstrate that climatic controls on Lake Malawi vegetation are critically important to weathering processes and erosion patterns during the deglaciation. At 18 ka, afromontane forests dominated but were progressively replaced by tropical seasonal forest, as summer rainfall increased. Despite indication of decreased rainfall, drought-intolerant forest persisted through the Younger Dryas (YD) resulting from a shorter dry season. Following the YD, an intensified summer monsoon and increased rainfall seasonality were coeval with forest decline and expansion of drought-tolerant miombo woodland. Clay minerals closely track the vegetation record, with high ratios of kaolinite to smectite (K/S) indicating heavy leaching when forest predominates, despite variable rainfall. In the early Holocene, when rainfall and temperature increased (effective moisture remained low), open woodlands expansion resulted in decreased K/S, suggesting a reduction in chemical weathering intensity. Terrigenous sediment mass accumulation rates also increased, suggesting critical linkages among open vegetation and erosion during intervals of enhanced summer rainfall. This study shows a strong, direct influence of vegetation composition on weathering intensity in the tropics. As climate change will likely impact this interplay between the biosphere and geosphere, tropical landscape change could lead to deleterious effects on soil and water quality in regions with little infrastructure for mitigation. PMID:25406090

Vegetation controls on weathering intensity during the last deglacial transition in southeast Africa.

PubMed

Ivory, Sarah J; McGlue, Michael M; Ellis, Geoffrey S; Lézine, Anne-Marie; Cohen, Andrew S; Vincens, Annie

2014-01-01

Tropical climate is rapidly changing, but the effects of these changes on the geosphere are unknown, despite a likelihood of climatically-induced changes on weathering and erosion. The lack of long, continuous paleo-records prevents an examination of terrestrial responses to climate change with sufficient detail to answer questions about how systems behaved in the past and may alter in the future. We use high-resolution records of pollen, clay mineralogy, and particle size from a drill core from Lake Malawi, southeast Africa, to examine atmosphere-biosphere-geosphere interactions during the last deglaciation (∼ 18-9 ka), a period of dramatic temperature and hydrologic changes. The results demonstrate that climatic controls on Lake Malawi vegetation are critically important to weathering processes and erosion patterns during the deglaciation. At 18 ka, afromontane forests dominated but were progressively replaced by tropical seasonal forest, as summer rainfall increased. Despite indication of decreased rainfall, drought-intolerant forest persisted through the Younger Dryas (YD) resulting from a shorter dry season. Following the YD, an intensified summer monsoon and increased rainfall seasonality were coeval with forest decline and expansion of drought-tolerant miombo woodland. Clay minerals closely track the vegetation record, with high ratios of kaolinite to smectite (K/S) indicating heavy leaching when forest predominates, despite variable rainfall. In the early Holocene, when rainfall and temperature increased (effective moisture remained low), open woodlands expansion resulted in decreased K/S, suggesting a reduction in chemical weathering intensity. Terrigenous sediment mass accumulation rates also increased, suggesting critical linkages among open vegetation and erosion during intervals of enhanced summer rainfall. This study shows a strong, direct influence of vegetation composition on weathering intensity in the tropics. As climate change will likely impact this interplay between the biosphere and geosphere, tropical landscape change could lead to deleterious effects on soil and water quality in regions with little infrastructure for mitigation.

Rainfall Effects on the Kuroshio Current East of Taiwan

NASA Astrophysics Data System (ADS)

Hsu, Po-Chun; Lin, Chen-Chih; Ho, Chung-Ru

2017-04-01

Changes of sea surface salinity (SSS) in the open oceans are related to precipitation and evaporation. SSS has been an indicator of water cycle. It may be related to the global change. The Kuroshio Current, a western boundary current originating from the North Equatorial Current, transfers warm and higher salinity to higher latitudes. It flows northward along the east coasts of Luzon Island and Taiwan Island to Japan. In this study, effects of heavy rainfall on the Kuroshio surface salinity east of Taiwan are investigated. Sea surface salinity (SSS) data taken by conductivity temperature depth (CTD) sensor on R/V Ocean Researcher I cruises, conductivity sensor on eight glider cruises, and Aquarius satellite data are used in this study. The rain rate data derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are also employed. A glider is a kind of autonomous underwater vehicle, which uses small changes in its buoyancy in conjunction with wings to convert vertical motion to horizontal in the underwater without requiring input from an operator. It can take sensors to measure salinity, temperature, and pressure. The TRMM/TMI data from remote sensing system are daily and are mapped to 0.25-degree grid. The results show a good correlation between the rain rate and SSS with a correlation coefficient of 0.86. The rainfall causes SSS of the Kuroshio surface water drops 0.176 PSU per 1 mm/hr rain rate.

A test-tube model for rainfall

NASA Astrophysics Data System (ADS)

Wilkinson, Michael

2014-05-01

If the temperature of a cell containing two partially miscible liquids is changed very slowly, so that the miscibility is decreased, microscopic droplets nucleate, grow and migrate to the interface due to their buoyancy. The system may show an approximately periodic variation of the turbidity of the mixture, as the mean droplet size fluctuates. These precipitation events are analogous to rainfall. This paper considers a theoretical model for these experiments. After nucleation the initial growth is by Ostwald ripening, followed by a finite-time runaway growth of droplet sizes due to larger droplets sweeping up smaller ones. The model predicts that the period \\Delta t and the temperature sweep rate ξ are related by \\Delta t\\sim C \\xi^{-3/7} , and is in good agreement with experiments. The coefficient C has a power-law divergence approaching the critical point of the miscibility transition: C\\sim (T-T_{\\text{c}})^{-\\eta} , and the critical exponent η is determined. It is argued that while the mechanism does not provide a quantitative description of terrestrial rainfall, it may be a faithful model for precipitation on other planets.

Long-term Increases in Flower Production by Growth Forms in Response to Anthropogenic Change in a Tropical Forest

NASA Astrophysics Data System (ADS)

Pau, S.; Wright, S. J.

2016-12-01

There is mounting evidence that anthropogenic global change is altering the ecology of tropical forests. A limited number of studies have focused on long-term trends in tropical reproductive activity, yet differences in reproductive activity should have consequences for demography and ultimately forest carbon, water, and energy balance. Here we analyze a 28-year record of tropical flower production in response to anthropogenic climate change. We show that a multi-decadal increase in flower production is most strongly driven by rising atmospheric CO2, which had approximately 8x the effect of the Multivariate ENSO Index and approximately 13x the effect of rainfall or solar radiation. Interannual peaks in flower production were associated with greater solar radiation and low rainfall during El Niño years. Observed changes in solar radiation explained flower production better than rainfall (models including solar radiation accounted for 94% of cumulative AICc weight compared to 87% for rainfall). All growth forms (lianas, canopy trees, midstory trees, and shrubs) produced more flowers with increasing CO2 except for understory treelets. The increase in flower production was matched by a lengthening of flowering duration for canopy trees and midstory trees; duration was also longer for understory treelets. Given that anthropogenic CO2 emissions will continue to climb over the next century, the long-term increase in flower production may persist unless offset by increasing cloudiness in the tropics, or until rising CO2 and/or warming temperatures associated with the greenhouse effect pass critical thresholds for plant reproduction.

Moisture status during a strong El Niño explains a tropical montane cloud forest's upper limit.

PubMed

Crausbay, Shelley D; Frazier, Abby G; Giambelluca, Thomas W; Longman, Ryan J; Hotchkiss, Sara C

2014-05-01

Growing evidence suggests short-duration climate events may drive community structure and composition more directly than long-term climate means, particularly at ecotones where taxa are close to their physiological limits. Here we use an empirical habitat model to evaluate the role of microclimate during a strong El Niño in structuring a tropical montane cloud forest's upper limit and composition in Hawai'i. We interpolate climate surfaces, derived from a high-density network of climate stations, to permanent vegetation plots. Climatic predictor variables include (1) total rainfall, (2) mean relative humidity, and (3) mean temperature representing non-El Niño periods and a strong El Niño drought. Habitat models explained species composition within the cloud forest with non-El Niño rainfall; however, the ecotone at the cloud forest's upper limit was modeled with relative humidity during a strong El Niño drought and secondarily with non-El Niño rainfall. This forest ecotone may be particularly responsive to strong, short-duration climate variability because taxa here, particularly the isohydric dominant Metrosideros polymorpha, are near their physiological limits. Overall, this study demonstrates moisture's overarching influence on a tropical montane ecosystem, and suggests that short-term climate events affecting moisture status are particularly relevant at tropical ecotones. This study further suggests that predicting the consequences of climate change here, and perhaps in other tropical montane settings, will rely on the skill and certainty around future climate models of regional rainfall, relative humidity, and El Niño.

Rain Characteristics and Large-Scale Environments of Precipitation Objects with Extreme Rain Volumes from TRMM Observations

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Lau, William K M.; Liu, Chuntao

2013-01-01

This study adopts a "precipitation object" approach by using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) and National Centers for Environmental Prediction (NCEP) reanalysis data to study rainfall structure and environmental factors associated with extreme heavy rain events. Characteristics of instantaneous extreme volumetric PFs are examined and compared to those of intermediate and small systems. It is found that instantaneous PFs exhibit a much wider scale range compared to the daily gridded precipitation accumulation range. The top 1% of the rainiest PFs contribute over 55% of total rainfall and have 2 orders of rain volume magnitude greater than those of the median PFs. We find a threshold near the top 10% beyond which the PFs grow exponentially into larger, deeper, and colder rain systems. NCEP reanalyses show that midlevel relative humidity and total precipitable water increase steadily with increasingly larger PFs, along with a rapid increase of 500 hPa upward vertical velocity beyond the top 10%. This provides the necessary moisture convergence to amplify and sustain the extreme events. The rapid increase in vertical motion is associated with the release of convective available potential energy (CAPE) in mature systems, as is evident in the increase in CAPE of PFs up to 10% and the subsequent dropoff. The study illustrates distinct stages in the development of an extreme rainfall event including: (1) a systematic buildup in large-scale temperature and moisture, (2) a rapid change in rain structure, (3) explosive growth of the PF size, and (4) a release of CAPE before the demise of the event.

Challenges in predicting and simulating summer rainfall in the eastern China

NASA Astrophysics Data System (ADS)

Liang, Ping; Hu, Zeng-Zhen; Liu, Yunyun; Yuan, Xing; Li, Xiaofan; Jiang, Xingwen

2018-05-01

To demonstrate the challenge of summer rainfall prediction and simulation in the eastern China, in this work, we examine the skill of the state-of-the-art climate models, evaluate the impact of sea surface temperature (SST) on forecast skill and estimate the predictability by using perfect model approach. The challenge is further demonstrated by assessing the ability of various reanalyses in capturing the observed summer rainfall variability in the eastern China and by examining the biases in reanalyses and in a climate model. Summer rainfall forecasts (hindcasts) initiated in May from eight seasonal forecast systems have low forecast skill with linear correlation of - 0.3 to 0.5 with observations. The low forecast skill is consistent with the low perfect model score ( 0.1-0.3) of atmospheric model forced by observed SST, due to the fact that external forcing (SST) may play a secondary role in the summer rainfall variation in the eastern China. This is a common feature for the climate variation over the middle and high latitude lands, where the internal dynamical processes dominate the rainfall variation in the eastern China and lead to low predictability, and external forcing (such as SST) plays a secondary role and is associated with predictable fraction. Even the reanalysis rainfall has some remarkable disagreements with the observation. Statistically, more than 20% of the observed variance is not captured by the mean of six reanalyses. Among the reanalyses, JRA55 stands out as the most reliable one. In addition, the reanalyses and climate model have pronounced biases in simulating the mean rainfall. These defaults mean an additional challenge in predicting the summer rainfall variability in the eastern China that has low predictability in nature.

Interannual variability and predictability over the Arabian Penuinsula Winter monsoon region

NASA Astrophysics Data System (ADS)

Adnan Abid, Muhammad; Kucharski, Fred; Almazroui, Mansour; Kang, In-Sik

2016-04-01

Interannual winter rainfall variability and its predictability are analysed over the Arabian Peninsula region by using observed and hindcast datasets from the state-of-the-art European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal prediction System 4 for the period 1981-2010. An Arabian winter monsoon index (AWMI) is defined to highlight the Arabian Peninsula as the most representative region for the Northern Hemispheric winter dominating the summer rainfall. The observations show that the rainfall variability is relatively large over the northeast of the Arabian Peninsula. The correlation coefficient between the Nino3.4 index and rainfall in this region is 0.33, suggesting potentially some modest predictability, and indicating that El Nino increases and La Nina decreases the rainfall. Regression analysis shows that upper-level cyclonic circulation anomalies that are forced by El Nino Southern Oscillation (ENSO) are responsible for the winter rainfall anomalies over the Arabian region. The stronger (weaker) mean transient-eddy activity related to the upper-level trough induced by the warm (cold) sea-surface temperatures during El Nino (La Nina) tends to increase (decrease) the rainfall in the region. The model hindcast dataset reproduces the ENSO-rainfall connection. The seasonal mean predictability of the northeast Arabian rainfall index is 0.35. It is shown that the noise variance is larger than the signal over the Arabian Peninsula region, which tends to limit the prediction skill. The potential predictability is generally increased in ENSO years and is, in particular, larger during La Nina compared to El Nino years in the region. Furthermore, central Pacific ENSO events and ENSO events with weak signals in the Indian Ocean tend to increase predictability over the Arabian region.

Interdecadal change of the controlling mechanisms for East Asian early summer rainfall variation around the mid-1990s

NASA Astrophysics Data System (ADS)

Yim, So-Young; Wang, Bin; Kwon, MinHo

2014-03-01

East Asian (EA) summer monsoon shows considerable differences in the mean state and principal modes of interannual variation between early summer (May-June, MJ) and late summer (July-August, JA). The present study focuses on the early summer (MJ) precipitation variability. We find that the interannual variation of the MJ precipitation and the processes controlling the variation have been changed abruptly around the mid-1990s. The rainfall anomaly represented by the leading empirical orthogonal function has changed from a dipole-like pattern in pre-95 epoch (1979-1994) to a tripole-like pattern in post-95 epoch (1995-2010); the prevailing period of the corresponding principal component has also changed from 3-5 to 2-3 years. These changes are concurrent with the changes of the corresponding El Nino-Southern Oscillation (ENSO) evolutions. During the pre-95 epoch, the MJ EA rainfall anomaly is coupled to a slow decay of canonical ENSO events signified by an eastern Pacific warming, which induces a dipole rainfall feature over EA. On the other hand, during the post-95 epoch the anomalous MJ EA rainfall is significantly linked to a rapid decay of a central Pacific warming and a distinct tripolar sea surface temperature (SST) in North Atlantic. The central Pacific warming-induced Philippine Sea anticyclone induces an increased rainfall in southern China and decreased rainfall in central eastern China. The North Atlantic Oscillation-related tripolar North Atlantic SST anomaly induces a wave train that is responsible for the increase northern EA rainfall. Those two impacts form the tripole-like rainfall pattern over EA. Understanding such changes is important for improving seasonal to decadal predictions and long-term climate change in EA.

Latitudinal variation in summer monsoon rainfall over Western Ghat of India and its association with global sea surface temperatures.

PubMed

Revadekar, J V; Varikoden, Hamza; Murumkar, P K; Ahmed, S A

2018-02-01

The Western Ghats (WG) of India are basically north-south oriented mountains having narrow zonal width with a steep rising western face. The summer monsoon winds during June to September passing over the Arabian Sea are obstructed by the WG and thus orographically uplift to produce moderate-to-heavy precipitation over the region. However, it is seen that characteristic features of rainfall distribution during the season vary from north to south. Also its correlation with all-India summer monsoon rainfall increases from south to north. In the present study, an attempt is also made to examine long-term as well as short-term trends and variability in summer monsoon rainfall over different subdivisions of WG using monthly rainfall data for the period 1871-2014. Konkan & Goa and Coastal Karnataka show increase in rainfall from 1871 to 2014 in all individual summer monsoon months. Short-term trend analysis based on 31-year sliding window indicates that the trends are not monotonous, but has epochal behavior. In recent epoch, magnitudes of negative trends are consistently decreasing and have changed its sign to positive during 1985-2014. It has been observed that Indian Ocean Dipole (IOD) plays a dominant positive role in rainfall over entire WG in all summer monsoon months, whereas role of Nino regions are asymmetric over WG rainfall. Indian summer monsoon is known for its negative relationship with Nino SST. Negative correlations are also seen for WG rainfall with Nino regions but only during onset and withdrawal phase. During peak monsoon months July and August subdivisions of WG mostly show positive correlation with Nino SST. Copyright © 2017 Elsevier B.V. All rights reserved.

Stable isotope ratios in rainfall and water vapour at Bangalore, Southern India during the monsoon period of 2013

NASA Astrophysics Data System (ADS)

Peethambaran, Rahul; Ghosh, Prosenjit

2015-04-01

Rainwater and water vapour were collected during monsoon rainfall from Bangalore station to identifying the signature of moisture sources. Moisture responsible for the rainfall originates from Arabian Sea and Bay of Bengal and advected to the station together with vapour generated from the local . Total no of samples includes 72 for water vapour and 81 for rainwater respectively. The mean difference between water vapour and rainwater was found to be -13.27±2.5 ‰ for δ18O, -100±9 ‰ for δD, which was calculated from monthly mean values of water vapour and rainwater. The most enriched samples of rainwater and water vapour were found during the pre monsoon months which correspond to temperature maximum at the study location. Lighter isotopic ratios were recorded in samples collected during the starting of monsoon showers which goes to further depletion in δ18O during the period of post monsoon. This was mainly due to the change in the prevailing wind direction from southwest to northeast. Local Meteoric Water Line (LMWL) generated for rainwater (d = 7.49 δ 18O + 5.2555, R² = 0.93) equation suggesting enrichment due to evaporation. Local Vapour Line (LVL) (d = 7.5248 δ 18O + 6.6534,R² = 0.8957) indicates the dominance of vapor from local source. The time series of d-xcess of rainwater and water vapor reveals large variability, coinciding with the presence of transported and local sources. It was observed that rainwater and water vapor exhibits higher values indicating re-evaporation from the region. Repetition of this feature demonstrated pattern of moisture recycling in the atmosphere and the contribution of continental evaporation and transpiration. The sensitivity of isotopes to the sudden change in wind direction was documented by an abrupt variations in the isotope values. Such changes in wind patterns were mostly associated with the prevalence of low pressure depression systems during the monsoon periods. Detailed analysis on role of wind patterns and air parcel trajectories, atmospheric parameters such as rainfall, temperature and relative humidity and quantitative estimation of local source moisture source contributions will be discussed at the time of presentation.

Rainfall and cave water isotopic relationships in two South-France sites

NASA Astrophysics Data System (ADS)

Genty, D.; Labuhn, I.; Hoffmann, G.; Danis, P. A.; Mestre, O.; Bourges, F.; Wainer, K.; Massault, M.; Van Exter, S.; Régnier, E.; Orengo, Ph.; Falourd, S.; Minster, B.

2014-04-01

This article presents isotopic measurements (δ18O and δD) of precipitation and cave drip water from two sites in southern France in order to investigate the link between rainfall and seepage water, and to characterize regional rainfall isotopic variability. These data, which are among the longest series in France, come from two rainfall stations in south-west France (Le Mas 1996-2012, and Villars 1998-2012; typically under Atlantic influence), and from one station in the south-east (Orgnac 2000-2012; under both Mediterranean and Atlantic influence). Rainfall isotopic composition is compared to drip water collected under stalactites from the same sites: Villars Cave (four drip stations 1999-2012) in the south-west, and Chauvet Cave (two drip stations 2000-2012) in the south-east, near Orgnac. The study of these isotopic data sets allows the following conclusions to be drawn about the rainfall/drip water relationships and about rainfall variability: (1) the cave drip water isotopic composition does not show any significant changes since the beginning of measurements; in order to explain its isotopic signature it is necessary to integrate weighted rainfall δ18O of all months during several years, which demonstrates that, even at shallow depths (10-50 m), cave drip water is a mixture of rain water integrated over relatively long periods, which give an apparent time residence from several months to up to several years. These results have important consequences on the interpretation of proxies like speleothem fluid inclusions and tree-ring cellulose isotopic composition, which are used for paleoclimatic studies; (2) in the Villars Cave, where drip stations at two different depths were studied, lower δ18O values were observed in the lower galleries, which might be due to winter season overflows during infiltration and/or to older rain water with a different isotopic composition that reaches the lower galleries after years; (3) local precipitation is characterized by local meteoric water lines, LMWL, with δ18O/δD slopes close to 7 in both areas, and correlations between air temperature and precipitation δ18O are low at both monthly and annual scales, even with temperature weighted by the amount of precipitation; (4) the mesoscale climate model REMOiso, equipped with a water isotope module, allows the direct comparison of modeled and observed long term water isotope records. The model slightly overestimates rainfall δ18O at the respective sampling stations. However, it simulates very well not only the seasonal rainfall isotopic signal but also some intra-seasonal patterns such as a typical double-peak δ18O pattern in winter time.

A Monte-Carlo Bayesian framework for urban rainfall error modelling

NASA Astrophysics Data System (ADS)

Ochoa Rodriguez, Susana; Wang, Li-Pen; Willems, Patrick; Onof, Christian

2016-04-01

Rainfall estimates of the highest possible accuracy and resolution are required for urban hydrological applications, given the small size and fast response which characterise urban catchments. While significant progress has been made in recent years towards meeting rainfall input requirements for urban hydrology -including increasing use of high spatial resolution radar rainfall estimates in combination with point rain gauge records- rainfall estimates will never be perfect and the true rainfall field is, by definition, unknown [1]. Quantifying the residual errors in rainfall estimates is crucial in order to understand their reliability, as well as the impact that their uncertainty may have in subsequent runoff estimates. The quantification of errors in rainfall estimates has been an active topic of research for decades. However, existing rainfall error models have several shortcomings, including the fact that they are limited to describing errors associated to a single data source (i.e. errors associated to rain gauge measurements or radar QPEs alone) and to a single representative error source (e.g. radar-rain gauge differences, spatial temporal resolution). Moreover, rainfall error models have been mostly developed for and tested at large scales. Studies at urban scales are mostly limited to analyses of propagation of errors in rain gauge records-only through urban drainage models and to tests of model sensitivity to uncertainty arising from unmeasured rainfall variability. Only few radar rainfall error models -originally developed for large scales- have been tested at urban scales [2] and have been shown to fail to well capture small-scale storm dynamics, including storm peaks, which are of utmost important for urban runoff simulations. In this work a Monte-Carlo Bayesian framework for rainfall error modelling at urban scales is introduced, which explicitly accounts for relevant errors (arising from insufficient accuracy and/or resolution) in multiple data sources (in this case radar and rain gauge estimates typically available at present), while at the same time enabling dynamic combination of these data sources (thus not only quantifying uncertainty, but also reducing it). This model generates an ensemble of merged rainfall estimates, which can then be used as input to urban drainage models in order to examine how uncertainties in rainfall estimates propagate to urban runoff estimates. The proposed model is tested using as case study a detailed rainfall and flow dataset, and a carefully verified urban drainage model of a small (~9 km2) pilot catchment in North-East London. The model has shown to well characterise residual errors in rainfall data at urban scales (which remain after the merging), leading to improved runoff estimates. In fact, the majority of measured flow peaks are bounded within the uncertainty area produced by the runoff ensembles generated with the ensemble rainfall inputs. REFERENCES: [1] Ciach, G. J. & Krajewski, W. F. (1999). On the estimation of radar rainfall error variance. Advances in Water Resources, 22 (6), 585-595. [2] Rico-Ramirez, M. A., Liguori, S. & Schellart, A. N. A. (2015). Quantifying radar-rainfall uncertainties in urban drainage flow modelling. Journal of Hydrology, 528, 17-28.

Divergent trajectories in tropical rainforest carbon-climate relationships: results from a new tropical forest carbon inventory database

NASA Astrophysics Data System (ADS)

Taylor, P.; Wieder, W.; Townsend, A.; Asner, G. P.; Cleveland, C.; Loarie, S.

2010-12-01

Intact tropical rainforests play a disproportionate role in the terrestrial carbon (C) cycle because they exchange more CO2 with the atmosphere than any other biome. As with any ecosystem, climate controls rates of C uptake and storage; however, the specific nature of climate-carbon relationships in the tropics remains poorly understood and oft-debated. Consequently, there are major uncertainties in how human-driven climate change may alter tropical C storage. One way to investigate climate - forest C interactions is via meta-analyses that examine shifts in forest C dynamics along climatic gradients. Past such analyses for the role of precipitation suggest tropical aboveground net primary production (ANPP) peaks near 2500 mm/yr, and then sharply declines in wetter regions. However, the downturn in ANPP is driven by a bias in early databases toward montane forests, which may exhibit temperature-driven biogeochemical feedbacks not present in wet lowland forests. To address this possibility, we assembled a tropical forest carbon dynamics database that includes nearly 900 different sites. We found substantial divergence in montane versus lowland forest ANPP responses to shifts in rainfall. As previous analyses imply, montane forest ANPP shows a distinct “hump-shaped” pattern, with a downturn in wetter sites. However, in contrast to prevailing assumptions, we find that lowland forest ANPP and biomass remain steady or increase with increasing rainfall. The data suggest that temperature plays a key role in determining the shape of rainfall - forest C interactions by regulating plant-soil nutrient feedbacks that underlie trends in ANPP. In montane systems, lower temperatures under wet conditions allow the development of organic horizons and the persistence of low redox conditions that reduce fertility, but in lowland systems, higher temperatures prevent organic matter accumulation, and high precipitation appears to drive rapid exchanges of nutrients between litter and soil. Furthermore, in lowland forests, we find that ANPP-rainfall relationships stratify by soil order, with the highest ANPP values occurring on nutrient-rich inceptisols, and the lowest values on nutrient poor oxisols and spodosols. Our findings have important implications for tropical forest C cycling. The data for lowland systems suggest a revision in our understanding of basic climate - forest C relations, and the possibility that the wettest of lowland forests - zones that are often subject to lower rates of deforestation and degradation - may be global hotspots for C uptake and storage. In addition, our data strongly suggest the importance of nutrient availability to determining rates of C exchange and storage in the tropics, and their response to climate, and hence the need for coupled carbon-climate models that can explicitly consider multiple biogeochemical cycles.

Measuring dynamic infiltration rates during rainfall of fluctuating intensity: an approach using affine Horton equations.

NASA Astrophysics Data System (ADS)

Dunkerley, David

2017-04-01

It is important to develop methods for determining infiltrability and infiltration rates under conditions of fluctuating rainfall intensity, since rainfall intensity rarely remains constant. During rain of fluctuating intensity, ponding deepens and dissipates, and the drivers of soil infiltration, including sorptivity, fluctuate in value. This has been explored on dryland soils in the field, using small plots and rainfall simulation, involving repeated changes in intensity as well as short and long hiatuses in rainfall. The field area was the Fowlers Gap Arid Zone Research Station, in western NSW, Australia. The field experiments used multiple 60 minute design rainfall events that all had the same total depth and average rainfall intensity, but which included intensity bursts at various positions within the event. These were based on the character of local rainfall events in the field area. Infiltration was found from plot runoff rates measured every 2 minutes, and rainfall intensities that were adjusted by computer-controlled pumps at 1 second intervals. Data were analysed by fitting a family of affine Horton equations, all having the same final infiltrability (about 6-7 mm/h) but having initial infiltrabilities and exponential decay constants that were permitted to recover during periods of very low intensity rain, or rainfall hiatuses. Results show that the terms in the Horton equation, f0, fc, and Kf, can all be estimated from field data of the kind collected. This is a considerable advance over 'steady-state' rainfall simulation methods, which typically only allow the estimation of the final infiltrability fc. This may rarely be reached owing to the occurrence of short rainfall events, or to changing intensity under natural rainfall, that prohibits the establishment of steady-state infiltration and runoff. Importantly, this method allows a focus on the recovery of infiltrability during periods of reduced rainfall intensity. Recovery of infiltrability is shown to proceed at rates of up to 1 mm/h per minute of hiatus time, or by 20 mm/h during a 20 minute period of low rainfall intensity.

Exploring the relationship between malaria, rainfall intermittency, and spatial variation in rainfall seasonality

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Wimberly, M. C.; Henebry, G. M.; Senay, G. B.

2014-12-01

Malaria is a major public health problem throughout tropical regions of the world. Successful prevention and treatment of malaria requires an understanding of the environmental factors that affect the life cycle of both the malaria pathogens, protozoan parasites, and its vectors, anopheline mosquitos. Because the egg, larval, and pupal stages of mosquito development occur in aquatic habitats, information about the spatial and temporal distribution of rainfall is critical for modeling malaria risk. Potential sources of hydrological data include satellite-derived rainfall estimates (TRMM and GPM), evapotranspiration derived from a simplified surface energy balance, and estimates of soil moisture and fractional water cover from passive microwave imagery. Previous studies have found links between malaria cases and total monthly or weekly rainfall in areas where both are highly seasonal. However it is far from clear that monthly or weekly summaries are the best metrics to use to explain malaria outbreaks. It is possible that particular temporal or spatial patterns of rainfall result in better mosquito habitat and thus higher malaria risk. We used malaria case data from the Amhara region of Ethiopia and satellite-derived rainfall estimates to explore the relationship between malaria outbreaks and rainfall with the goal of identifying the most useful rainfall metrics for modeling malaria occurrence. First, we explored spatial variation in the seasonal patterns of both rainfall and malaria cases in Amhara. Second, we assessed the relative importance of different metrics of rainfall intermittency, including alternation of wet and dry spells, the strength of intensity fluctuations, and spatial variability in these measures, in determining the length and severity of malaria outbreaks. We also explored the sensitivity of our results to the choice of method for describing rainfall intermittency and the spatial and temporal scale at which metrics were calculated. Results demonstrate that information about the seasonality and intermittency of rainfall has the potential to improve our understanding of malaria epidemiology and improve our ability to forecast malaria outbreaks.

High temporal resolution of extreme rainfall rate variability and the acoustic classification of rainfall

NASA Astrophysics Data System (ADS)

Nystuen, Jeffrey A.; Amitai, Eyal

2003-04-01

The underwater sound generated by raindrop splashes on a water surface is loud and unique allowing detection, classification and quantification of rainfall. One of the advantages of the acoustic measurement is that the listening area, an effective catchment area, is proportional to the depth of the hydrophone and can be orders of magnitude greater than other in situ rain gauges. This feature allows high temporal resolution of the rainfall measurement. A series of rain events with extremely high rainfall rates, over 100 mm/hr, is examined acoustically. Rapid onset and cessation of rainfall intensity are detected within the convective cells of these storms with maximum 5-s resolution values exceeding 1000 mm/hr. The probability distribution functions (pdf) for rainfall rate occurrence and water volume using the longer temporal resolutions typical of other instruments do not include these extreme values. The variance of sound intensity within different acoustic frequency bands can be used as an aid to classify rainfall type. Objective acoustic classification algorithms are proposed. Within each rainfall classification the relationship between sound intensity and rainfall rate is nearly linear. The reflectivity factor, Z, also has a linear relationship with rainfall rate, R, for each rainfall classification.

Quality-control of an hourly rainfall dataset and climatology of extremes for the UK.

PubMed

Blenkinsop, Stephen; Lewis, Elizabeth; Chan, Steven C; Fowler, Hayley J

2017-02-01

Sub-daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non-operation of gauges. Given the prospect of an intensification of short-duration rainfall in a warming climate, the identification of such errors is essential if sub-daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near-complete hourly records for 1992-2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n-largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north-south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub-daily rainfall, with convection dominating during summer. The resulting quality-controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality-control procedures for sub-daily data, the validation of the new generation of very high-resolution climate models and improved understanding of the drivers of extreme rainfall.

Using rainfall radar data to improve interpolated maps of dose rate in the Netherlands.

PubMed

Hiemstra, Paul H; Pebesma, Edzer J; Heuvelink, Gerard B M; Twenhöfel, Chris J W

2010-12-01

The radiation monitoring network in the Netherlands is designed to detect and track increased radiation levels, dose rate more specifically, in 10-minute intervals. The network consists of 153 monitoring stations. Washout of radon progeny by rainfall is the most important cause of natural variations in dose rate. The increase in dose rate at a given time is a function of the amount of progeny decaying, which in turn is a balance between deposition of progeny by rainfall and radioactive decay. The increase in progeny is closely related to average rainfall intensity over the last 2.5h. We included decay of progeny by using weighted averaged rainfall intensity, where the weight decreases back in time. The decrease in weight is related to the half-life of radon progeny. In this paper we show for a rainstorm on the 20th of July 2007 that weighted averaged rainfall intensity estimated from rainfall radar images, collected every 5min, performs much better as a predictor of increases in dose rate than using the non-averaged rainfall intensity. In addition, we show through cross-validation that including weighted averaged rainfall intensity in an interpolated map using universal kriging (UK) does not necessarily lead to a more accurate map. This might be attributed to the high density of monitoring stations in comparison to the spatial extent of a typical rain event. Reducing the network density improved the accuracy of the map when universal kriging was used instead of ordinary kriging (no trend). Consequently, in a less dense network the positive influence of including a trend is likely to increase. Furthermore, we suspect that UK better reproduces the sharp boundaries present in rainfall maps, but that the lack of short-distance monitoring station pairs prevents cross-validation from revealing this effect. Copyright © 2010 Elsevier B.V. All rights reserved.

Quality‐control of an hourly rainfall dataset and climatology of extremes for the UK

PubMed Central

Lewis, Elizabeth; Chan, Steven C.; Fowler, Hayley J.

2016-01-01

ABSTRACT Sub‐daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non‐operation of gauges. Given the prospect of an intensification of short‐duration rainfall in a warming climate, the identification of such errors is essential if sub‐daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near‐complete hourly records for 1992–2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n‐largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north–south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub‐daily rainfall, with convection dominating during summer. The resulting quality‐controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality‐control procedures for sub‐daily data, the validation of the new generation of very high‐resolution climate models and improved understanding of the drivers of extreme rainfall. PMID:28239235

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

PubMed

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

2011-01-17

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

Dynamic size responses to climate change: prevailing effects of rising temperature drive long-term body size increases in a semi-arid passerine.

PubMed

Gardner, Janet L; Amano, Tatsuya; Mackey, Brendan G; Sutherland, William J; Clayton, Mark; Peters, Anne

2014-07-01

Changes in animal body size have been widely reported as a correlate of contemporary climate change. Body size affects metabolism and fitness, so changing size has implications for resilience, yet the climatic factors that drive size variation remain poorly understood. We test the role of mean and extreme temperature, rainfall, and remotely sensed primary productivity (NDVI) as drivers of body size in a sedentary, semi-arid Australian passerine, Ptilotula (Lichenostomus)penicillatus, over 23 years. To distinguish effects due to differential growth from changes in population composition, we analysed first-year birds and adults separately and considered climatic variation at three temporal scales (current, previous, and preceding 5 years). The strongest effects related to temperature: in both age classes, larger size was associated with warmer mean temperatures in the previous year, contrary to Bergmann's Rule. Moreover, adults were larger in warmer breeding seasons, while first years was larger after heat waves; these effects are more likely to be mediated through size-dependent mortality, highlighting the role of body size in determining vulnerability to extinction. In addition to temperature, larger adult size was associated with lower primary productivity, which may reflect a trade-off between vegetative growth and nectar production, on which adults rely. Finally, lower rainfall was associated with decreasing size in first year and adults, most likely related to decreased food availability. Overall,body size increased over 23 years, strongly in first-year birds (2.7%) compared with adults (1%), with size outcomes a balance between competing drivers. As rainfall declined over time and productivity remained fairly stable, the temporal increase in body size appears largely driven by rising mean temperature and temperature extremes. Body size responses to environmental change are thus complex and dynamic, driven by effects on growth as well as mortality.

A 1000-Year Carbon Isotope Rainfall Proxy Record from South African Baobab Trees (Adansonia digitata L.)

PubMed Central

2015-01-01

A proxy rainfall record for northeastern South Africa based on carbon isotope analysis of four baobab (Adansonia digitata L.) trees shows centennial and decadal scale variability over the last 1,000 years. The record is in good agreement with a 200-year tree ring record from Zimbabwe, and it indicates the existence of a rainfall dipole between the summer and winter rainfall areas of South Africa. The wettest period was c. AD 1075 in the Medieval Warm Period, and the driest periods were c. AD 1635, c. AD 1695 and c. AD1805 during the Little Ice Age. Decadal-scale variability suggests that the rainfall forcing mechanisms are a complex interaction between proximal and distal factors. Periods of higher rainfall are significantly associated with lower sea-surface temperatures in the Agulhas Current core region and a negative Dipole Moment Index in the Indian Ocean. The correlation between rainfall and the El Niño/Southern Oscillation Index is non-static. Wetter conditions are associated with predominantly El Niño conditions over most of the record, but since about AD 1970 this relationship inverted and wet conditions are currently associated with la Nina conditions. The effect of both proximal and distal oceanic influences are insufficient to explain the rainfall regime shift between the Medieval Warm Period and the Little Ice Age, and the evidence suggests that this was the result of a northward shift of the subtropical westerlies rather than a southward shift of the Intertropical Convergence Zone. PMID:25970402

A 1000-Year Carbon Isotope Rainfall Proxy Record from South African Baobab Trees (Adansonia digitata L.).

PubMed

Woodborne, Stephan; Hall, Grant; Robertson, Iain; Patrut, Adrian; Rouault, Mathieu; Loader, Neil J; Hofmeyr, Michele

2015-01-01

A proxy rainfall record for northeastern South Africa based on carbon isotope analysis of four baobab (Adansonia digitata L.) trees shows centennial and decadal scale variability over the last 1,000 years. The record is in good agreement with a 200-year tree ring record from Zimbabwe, and it indicates the existence of a rainfall dipole between the summer and winter rainfall areas of South Africa. The wettest period was c. AD 1075 in the Medieval Warm Period, and the driest periods were c. AD 1635, c. AD 1695 and c. AD1805 during the Little Ice Age. Decadal-scale variability suggests that the rainfall forcing mechanisms are a complex interaction between proximal and distal factors. Periods of higher rainfall are significantly associated with lower sea-surface temperatures in the Agulhas Current core region and a negative Dipole Moment Index in the Indian Ocean. The correlation between rainfall and the El Niño/Southern Oscillation Index is non-static. Wetter conditions are associated with predominantly El Niño conditions over most of the record, but since about AD 1970 this relationship inverted and wet conditions are currently associated with la Nina conditions. The effect of both proximal and distal oceanic influences are insufficient to explain the rainfall regime shift between the Medieval Warm Period and the Little Ice Age, and the evidence suggests that this was the result of a northward shift of the subtropical westerlies rather than a southward shift of the Intertropical Convergence Zone.

Monsoon climate response in Indian teak (Tectona grandis L.f.) along a transect from coast to inland

NASA Astrophysics Data System (ADS)

Sengupta, Saikat; Borgaonkar, Hemant; Joy, Reji Mariya; Ram, Somaru

2017-11-01

Indian monsoon (June-September) and post monsoon (October-November) rainfall show a distinct trend from coast to inland primarily due to moisture availability. However, the response of this synoptic-scale variation of rainfall amount to annual ring growth of Indian teak has not been studied systematically yet. The study is important as (1) ring width of Indian teak is considered as a reliable proxy for studying monsoon climate variability in multi-centennial time scale and (2) observed meteorological data show systematic changes in rainfall variation from coast to inland since last three decades. Towards this, we present here tree-ring width data from two locations—Thatibanda (1747-1979) and Nagzira (1728-2000) and use similar published data from two other locations—Allapalli (1866-1897) and Edugurapalli (1827-2000). The locations fall along a southeast northwest transect from south east Indian coast to inland. Monthly mean data from nearest observatories show an increasing trend in monsoon rainfall and a pronounced decreasing trend in post monsoon rainfall towards inland. Ring width data show moderately positive response to monsoon rainfall and negative response to summer (March-May) temperature for all stations suggesting moisture deficit in hot summer and intense precipitation in monsoon affect ring growth pattern in different ways. Ring width indices also exhibit significantly positive response with post monsoon rainfall at coastal location. The response gradually reduces towards inland. This preliminary study, thus, suggests that Indian teak has a potential to capture signals of the synoptic variation of post monsoon rainfall from coast to inland.

Observed changes in the characteristics of Active and Break Spells in the Indian Summer Monsoon

NASA Astrophysics Data System (ADS)

Singh, D.; Tsiang, M.; Rajaratnam, B.; Diffenbaugh, N. S.

2013-12-01

South Asia is home to about 24% of the world's population and is one of the world's most disaster prone regions. The majority of the people in this region depend on agriculture for their livelihood. Substantial variability in the South Asian Summer Monsoon occurs on an intraseasonal timescale (30-60 day) during which it fluctuates between spells of heavy (active spells) and low rainfall (breaks or weak spells). Considering the potentially severe implications of such rainfall variations, we quantify historical changes in the active and break spell characteristics in an effort to understand how these events are likely to respond to future anthropogenic forcings using the 1degx1deg gridded rainfall dataset. We find a decreasing trend in peak season rainfall since 1951 and a statistically significant shift in the rainfall distribution, suggesting greater extremes. Consequently, our results suggest an intensification of the active spells and more frequent occurrence of break spells at the 95% significance level. To understand the cause of these changes, we explore the environmental parameters in the North Indian Ocean and the Western Pacific that influence the occurrence of such events over the core monsoon region. We use the NCEP/NCAR Reanalysis 1 (1948-present) to do a composite analysis for two periods - 1951-1980 and 1981-2011. First, we examine the energetics of the baroclinic instabilities that initiate cyclonic depressions in the northern Bay of Bengal and the net moisture flux into the region. Further, sea surface temperatures are known to influence the characteristics of active and break spells. Therefore, next, we study sea surface temperature patterns in the Bay of Bengal and the equatorial western Pacific preceding breaks. We also examine the persistence of breaks through the diabatic heating anomalies over this region.

Passive microwave remote sensing of rainfall with SSM/I: Algorithm development and implementation

NASA Technical Reports Server (NTRS)

Ferriday, James G.; Avery, Susan K.

1994-01-01

A physically based algorithm sensitive to emission and scattering is used to estimate rainfall using the Special Sensor Microwave/Imager (SSM/I). The algorithm is derived from radiative transfer calculations through an atmospheric cloud model specifying vertical distributions of ice and liquid hydrometeors as a function of rain rate. The algorithm is structured in two parts: SSM/I brightness temperatures are screened to detect rainfall and are then used in rain-rate calculation. The screening process distinguishes between nonraining background conditions and emission and scattering associated with hydrometeors. Thermometric temperature and polarization thresholds determined from the radiative transfer calculations are used to detect rain, whereas the rain-rate calculation is based on a linear function fit to a linear combination of channels. Separate calculations for ocean and land account for different background conditions. The rain-rate calculation is constructed to respond to both emission and scattering, reduce extraneous atmospheric and surface effects, and to correct for beam filling. The resulting SSM/I rain-rate estimates are compared to three precipitation radars as well as to a dynamically simulated rainfall event. Global estimates from the SSM/I algorithm are also compared to continental and shipboard measurements over a 4-month period. The algorithm is found to accurately describe both localized instantaneous rainfall events and global monthly patterns over both land and ovean. Over land the 4-month mean difference between SSM/I and the Global Precipitation Climatology Center continental rain gauge database is less than 10%. Over the ocean, the mean difference between SSM/I and the Legates and Willmott global shipboard rain gauge climatology is less than 20%.